By now many of my readers are aware of our article in Oncotarget dismantling the Achs et al “hit piece for hire”. This is a paper that tried, but failed, to dismiss the DNA contamination story. It was fast tracked through Nature despite the below conflicts being presented to the authors prepublication but never being addressed in final form. Our manuscript did not emphasize the conflicts as it was easy to hang them with their own data. However, the conflicts deserve their own scrutiny now that their methods have been dismantled and shown to consistently make errors that point in one “safe and effective” direction.

I don’t use the terms “hit piece for hire” lightly.

They were paid 350,000 Euros to perform this work.

There is more detail on this here.

When the Achs preprint published, we posted comments on the Nature PrePrint server that alerted the Journal to technical issues. We also quickly published a preprint alerting the public of the fact that these authors worked at an Institute funded by an mRNA vaccine company known as Sensible Biotech. There is no way these conflicts do not qualify as disclosable material in a paper attempting to pacify the publics concerns over DNA contamination in mRNA vaccines.

The conflicts deserves a thorough review. You see, the communicating author on the Achs paper is the Director of Institute at the Slovakian Academy of Sciences.

She is also the signature on the collaboration agreement with the vaccine company so there is no way she is not aware of this overt conflict that was raised in preprint commentary but buried in final publication. She is both the communicating author on the paper that declared no conflicts and the person who signed the deal with the vaccine company.

The 5lovakian Academy of 5cience would like to plead the 5th on this matter.

The receipts for these conflicts are below.

Annual Reports from SAS.

https://www.sav.sk/?lang=en&doc=ins-org-ins&institute_no=198&action=annual

/https://crz.gov.sk/data/att/3004740.pdf

Other conflicts recorded below. Note- X is now shadow banning these links so I have had to directly link to some of the documents but Miroslav should be credited for finding most of these. That credit isn’t obvious on my X acount as all of these links were hidden after I posted them… and after I challenged Elon Musk on his exuberance for the recent Science by Press Release of the Moderna “Cancer Vaccine”.

• https://crz.gov.sk/data/att/5241423.pdf?fbclid=IwY2xjawTvfcxwZG9mBWV4dG4DYWVtAjEwAGJyaWQRMllWYVBkWVc0M2JNSVZmSlpzcnRjBmFwcF9pZBAyMjIwMzkxNzg4MjAwODkyAAEeNijqeIW4tUVhXmgDawOvJTR3ZmzcEXYOv0oWZouLieFqvdMpL6u44zYWqYU_aem_-N2HzHUlVjI1b8Y6yxckig

• https://bmc.sav.sk/wp-content/uploads/2025-10-28_Vyhlasenie_Obchodnej_verejnej_sutaze_Prenajom-BTL-A3-A4N.pdf?utm_source=chatgpt.com

• /https://crz.gov.sk/data/att/6634874.pdf

• https://cms.minzp.sk/files/uradna-tabula/gmo/ppz163.ziadost.pdf

Now that you get a sense of the “hit piece for hire” types of 5cientists we are dealing with, lets take a closer examination of their own data.

I must thank for this nugget as it was something I looked at briefly before we published in Oncotarget but got distracted by all the other technical issues that required addressing.

It deserves much more attention.

Let’s first explore their own Illumina Sequencing Data in Figure 12. These are DNA sequencing coverage plots. If you are going to use qPCR to measure the DNA of a single 100bp location in the plasmid and then extrapolate the concentration of that one target to represent the entire 7,824 bp plasmid, you must rest on the assumption that the 100bp region you are looking at is a fair proxy for the whole 7,824bp plasmid.

So their DNA sequencing coverage plots answer this question. Is the KAN region showing the same depth of coverage as the Spike region and if not showing equivalent depth of coverage, WHY NOT?

What does this do to your estimations of the amount of DNA in the shots if the 100bp region you chose to measure doesn’t represent the whole plasmid? If KAN is a lower DNA concentration than Spike, then your extrapolation can be off by orders of magnitude!

You’ll notice they didn’t bother to annotate the plasmid map on the X axis of these charts as that might lead you to question if their qPCR primers used for DNA quantification were placed in the region they get little DNA sequencing from.

Turns out they were.

Their 63bp KAN amplicon that reported the highest level of DNA happens to fall in these regions with no sequence coverage.

Oops.

When they target spike they resort to 233bp amplicons. This hides the problem (See below).

Thats an overt slight of hand. They are measuring the regions in Red with qPCR and then using those low readings to extrapolate the rest of the plasmid DNA when their own sequencing data demonstrates that is a fabrication. There is at least 10X-100X more DNA in the spike region according to their own DNA sequencing data. Where have we heard that number before?

Below is a more honest way to present this data, where the plasmid is annotated so you can find the Spike gene and the KAN gene and ask yourself if the KAN region is a fair place to put the qPCR primers? Note the LOG scale coverage on the Y axis and that the Red and the Orange samples (Moderna lots 400012A and 200106A) have far lower sequence coverage in the KAN region. We explain why this occurs in our JIMs paper.

RNA/DNA hybrids are resistant to DNaseI treatment. After making modRNA from DNA, you have a molecule that is half RNA and half DNA and DNaseI doesn’t recognize this as a digestable template so it properly digests the KAN region and doesn’t digest the spike region.

This is why the TGA, Moderna and Pfizer are using qPCR assays in the plasmid backbone near KAN to monitor the DNA. They know this. We know they know this as Pfizer has a RT-qPCR assay for spike disclosed with the EMA to prove the spike RNA is there but they refuse to use that to quantitate the DNA. This would be a simple change in the polymerase to make those primer quantitate only DNA. They instead went and designed a new assay in KAN to give them the number they needed and avoided at all costs monitoring Spike as they would get 10-100X higher number and fail.

This isn’t only something we quantitated in our JIMs paper but it is also published by BioNtech themselves!

Lenk R, Kleindienst W, Szabó GT, Baiersdörfer M, Boros G, Keller JM, Mahiny AJ, Vlatkovic I. Understanding the impact of in vitro transcription byproducts and contaminants. Front Mol Biosci. 2024; 11:1426129. https://doi.org/10.3389/fmolb.2024.1426129. [PubMed].

Let’s layer in the 3rd sample 000058A into this data…. Yup.. even more KAN suppression. But note.. Its not in all lots from Moderna which underscores the variability in their manufacturing.

From Lenk et al (BioNtech). 100 fold suppression of DNA digestion of RNA/DNA hybrids like spike.

Exactly what is observed in Achs own data.

So how badly could this be gamed?

We scanned the Plasmid backbone for 100bp windows to look for the lowest coverage regions in KAN vs the highest regions in Spike and a 168X-465X underestimate could be achieved using Achs own data with qPCR methods targeting 100bp amplicons. We also repeated this with 50bp and 300bp virtual PCR primers with the known read distributions of their sequencing data (See appendix data).

This is why we place extreme caution on using a single amplicon to monitor this DNA. Its too easy to cheat the number. Qubit on the other hand, does NOT use primers and hence measures all DNA as long as you use lots of RNase A to remove the confounding cross talk from RNA.

This qPCR variance between plasmid backbone and spike is not a one off finding. It is highly reproduced through the prior literature Achs had access to but left unaddressed.

Speicher et al noted 6CT differences between spike and the plasmid backbone (See Red and Blue bars for Moderna). Note, not all lots show this artifact which begs the question of manufacturing consistency.

Sonia Pekova reported it as well and also found lot to lot variance in this artifact.

Andrew Recknagel presented this in the South Carolina Senate.

And McKernan et al published it in JIMS (albeit after Achs published).

What does Ach’s chalk this up to?

Mysterious DNA degradation?

“Likely due to residual DNA degradation”.

The old DNA self decaying canard is an incoherent excuse when your sample prep for sequencing used 95C for 10 minutes prior to sequencing. This is known to fragment DNA. There are no vial storage conditions that could eclipse this level of damage induced by Achs themselves and there is no mechanism that could explain KAN specific destruction over spike from heat alone.

They even hint at this being from expired vials.. No citations provided for such targeted self decaying DNA.

What is particularly troubling about this is that Lenk et al was published by BioNtech a year before Achs and with a title that makes you wonder how in the hell did they miss this paper when Sutton et al and RNA/DNA hybrids are spelled out in Speicher et al… The very paper Achs critiques but clearly hasn’t read.

Speicher et al calls this out.

So there you have it. They are an arm of the vaccine industry and if you call out their conflicts, they hide them. Our papers demonstrate that all of the techniques they used were designed to come to one under measurement conclusion. Give it a read. Its a pretty overt white washing.

Their own data dismantles their conclusions! And Nature played along.

I’m actually shocked that a director of the 5lovakian Academy of 5cience is directly involved in both signing the Research Agreement with a mRNA vaccine manufacturing company and declaring she has NO conflicts of interest as the communicating author of a paper regarding the safety of those vaccines. They were paid to do this work. The conflict was raised during their preprint process and they still concealed it in their final publication in Nature.

That is not an accidental omission. Its overt and its a clear case of scientific misconduct steering the entire institute. Its goal was to mislead regulators of mandated liability-free injections. Pretty dark behavior.

This thread has mostly focused on one type of error in DNA measurement related to RNA/DNA hybrids.

But there is another independent form of error glanced over in the Achs paper that we discuss in the Oncotarget paper. Due to its independence it can error stack and further widen the error bars.

This is related to the distance of the qPCR primers. covered this in her piece and its further explored in the thread below.

When you are working with fragmented DNA from these vaccines, primers that are 60bp apart will give you 16-32 fold higher quantitation of DNA than primers that are 300bp apart.

We confirmed this on Pfizer vaccine lots that were selected to NOT have this RNA/DNA hybrid issue so we could independently measure it.

In the process we also developed a novel qPCR chemistry known as LIDAR which enables small amplicon quantitation and multi channel High Resolution Melt analysis (mcHRM) to confirm your qPCR is on target.

We also took the Achs reads and asked how 50bp vs 300bp amplicons would skew the detection in KAN vs Spike. The variance induced with primer placement biased can be measured with their own reads and can resort in 5X - 615X measurement variance in their lots (analysis by Claude Science). These numbers resonate with much of our work and actually validate Speicher et al as opposed to contradict it.

On a final note, some of our critiques during the preprint process were in fact addressed suggesting they did read them. The preprint was burdened with a-lot of anti-vax and misinformation pejoratives which displayed the bias in the authors personal beliefs about these products.

They even went on a transparency and misinformation soapbox while hiding their own conflicts.

Since our reputations were placed into question I feel its important to defend our technical literacy and contributions to this field.

We may not have 350,000 Euros supporting our work but we do have deep domain experience with these tools. I was aware of the Capillary Electrophoresis (CE) scam in the Achs paper because I optimized one of the largest CE labs ever constructed at MIT for the Human Genome Project. Electrokinetic injection bias is what sunk the Molecular Dynamics MegaBACE and left the ABI3700 to take the market. This was a Billion dollar failure.

I was aware of their DNA purification biases because I’m one of the inventors on the patent of the very chemistry Achs tried to hood wink their audience with (SPRI). I was also aware of the fragmentation bias in next generation sequencers because I was an author and an inventor on the Ion Torrent platform and the SOLiD sequencing platform that both share these biases.

And I was aware of the qPCR games they played as I have also invented novel qPCR chemistries seen above (LIDAR). We don’t need 350,000 Euros to measure DNA. We eat and breath these technologies everyday and have a track record of inventing the very tools they are fumbling with in their attempt to refute the existence of this DNA contamination.

Please give the LIDAR substack a read. It is a real game changer for qPCR and helps to confirm these data with both SYBR Green qPCR and a novel detection method that provides more information than Taqman based qPCR.

Appendix

The details of this analysis can be found on this Claude Science (Opus 5)/ChatGPT generated and human reviewed website.

https://spikevax-residual-dna-dc4wku6ktrnvrkdwgccnrk.streamlit.app/

We have a new paper out dissecting the systematic errors in Achs et al. Like clockwork, the PubSmear mob has been activated and announced their intentions to find problems even before they have finished reading the work. 5cience ^TM in motion.

This isn’t new. Many of the PubSmears have announced that I am on their future target list.

What is interesting is that if our paper is pointing out flaws in Ach’s, you’d think a research integrity clan would want to read it and understand the work but their knee jerk reaction is to find flaws in our citations before they have even read the paper?

Odd bunch.

What should trigger any “Research Integrity” alarms is that the Ach’s paper makes multiple errors and all errors point in the same under measurement direction.

Some of these errors are irrefutable as we dug up the specifications of the instruments they used and the manufacturers claim the instruments are not fit to measure what Ach’s is claiming. This blows apart their entire section on Capillary Electrophoresis (CE).

Likewise their methods for Illumina sequencing are all mangled and provide no information on the fragmentation of the DNA.

The qPCR is equally a mess. The whole paper is a methodological trainwreck and all errors point in the “Safe and Effective” direction.

To add insult to injury, they didnt disclose their funding from Sensible Biotech (mRNA vax company). You would think a conflict like this would be at the top of PubSmears concern list but instead they are here to march in and defend it!

They also defended surgisphere and proximal origins so we shouldn’t get our hopes up. They are known to work hand and hand with RetractionWatch who facilitated Dr. Marschalek violated his confidential with the journal Autoimmunity and publish his confidential peer review of the Speicher paper.

Of course he only leaked his review and not our arguments which traversed his in the eyes of the editors.

In the process of this the leak, the geniuses at RetractionWatch forgot to scrub the metadata of the PDF file from Marschalek this exposing him as the leak and the violator of the NDA with Autoimmunity.

RetractionWatch didn’t contest this ethical breach and actually facilitated, albeit in a low wattage that exposed their source.

Ironically, RetractionWatch posted a whole article trying to Whitewash their failure to get ahead of the breach and in doing lied in their headline claiming Dr. Marschalek rejected the paper.

No such thing happened and the editors of Autoimmunity came forward claiming Dr. Marschalek never rejected the paper and just asked for edits which were delivered.

This admission didn’t convince RetractionWatch to retract their own fabricated story.

RetractionWatch for thee but not for me!

Many of the Achs errors were documented on their preprint server but were ignored for their final publication suggesting the authors are aware of the criticisms but had no answer for them and thus chose not to address them.

This is particularly odd behavior from Nature. Ach’s is a critique of our work and I highlighted their overt errors with my signature on them. This was in some dark corner of the internet but on Nature’s own preprint server back in October of last year. You would think an editor would pay most attention to the criticisms being advanced by the author Ach’s is targeting? Instead this preprint was fast tracked through Nature and their hidden conflicts of interest and errors ignored.

Our Oncotarget manuscript was submitted nearly 8 months ago. Since then we have further measured the amplicon size bias with SYBR Green and LIDAR.

There is a dense read on that problem in the below substack but the TL/DR is that the amplicon size alone can create a 16-32 fold under measurement of the DNA. This error is unique and independent of the 100 fold RNA/DNA hybrid problem we published on earlier (Journal of Independent Medicine) and thus can stack to offer a 1600-3200 fold error in measuring the DNA. Without knowledge of the methods the regulators use to qPCR this DNA, any assurances of it being under 10ng/ul is pure regulatory charade.

distilled this dense read on her article here:

MD REPORTS

What if we’ve been measuring DNA contamination the wrong way?

For several years, concerns over excessive DNA contamination in Covid-19 mRNA vaccines have been investigated almost entirely by independent scientists…

Read more

23 days ago · 76 likes · 21 comments · Maryanne Demasi, PhD

Stay tuned.. We have a new qPCR method called LIDAR that will further dissect this problem.

This work occurred at lightning speed thanks to Claude code.

Last week we were held up waiting for new LIDAR probers to be synthesized, it was midsummer and half the lab was on holiday. We found ourselves sequencing some Psilocybe genomes we promised for a colleague in this summer doldrum.

Fungi are never straight forward genome projects. Psilocybe cubensis is known for making spores that survive the 40-60 meter, 4 stomach, pH 2-3, cattle digestive tract and still sprout on dung after this 5 day corrosive journey. So getting enough DNA from the chitin and melanin rich spores is no easy feat. We can usually do this with bead beating protocols but the DNA is heavily fragmented and only usable for Illumina sequencing. We put 117 of these genomes public at https://psilocydia.net/ and these have become a public resource for the field to analyze the genetic diversity in the US spore samples being sold on line but also a tool to dissect the actual origin of this magic mushroom.

To get DNA for long read sequencers like PacBio or ONT sequencing, -80 freezers, mortar and pestle come into play. Long reads are required to build a reference grade fungal genome and this is particularly important when you are sequencing a suspected novel species. Simply mapping Illumina reads back to a Psilocybe cubensis reference genome can be misleading if the reads actually map to the target genome with only 87% identity. Once the suspected genome is diverged enough, reference guided analysis will miss all the novel content in the new species. So long reads are really required for de novo sequencing ancestral genomes that could predate the Penis Envy Psilocybe cubensis reference genome.

We applied Oxford Nanopore sequencing to a new Psilocybe species (P.natalensis) that may be one of the missing links for Psilocybe cubensis diaspora out of Africa. Unlike P. cubensis, which has specialized on herbivore (now largely cattle) dung and grows readily on grain in cultivation, P. natalensis occupies a broader niche typical of the African cubensis-relatives: dung-associated and woodland/grassland, not wood-decaying. Its lineage diverged from P. cubensis deep in the past (Bradshaw et al. 2026 estimate ~1.5 million years ago for the cubensis/ochraceocentrata split, 95% HPD ~0.71–2.55 Mya): far earlier than cattle domestication (~10,000 years ago), so any shared coprophily reflects an ancient association with native herbivores rather than domesticated cattle.

Psilocybe cubensis (“Cubes”) , suggests origins in Cuba but this is a contested origin story and is unlikely to be the entire history.

This is a subtle but important detail as the McTaggart et al. sequenced many Psilocybe cubensis (2023) and P.subaeruginosa (2024) in Australia. In the 2023 study, they compared Australian P.cubes to U.S. based P.cubes in Psilocydia.net and hypothesized the cubes to have diverged with cattle introduction to Australia.

They published this in Cell/Press Current Biology

However other work from McTaggart finds differences in the P.Subs that mirror pacific northwest wood lovers (P.cyanescens and P.azurescens). A Claude.ai summary of the diaspora below-

The short version: subs is the native, and the Northern Hemisphere is the invasion

The key paper is McTaggart AR, Scarlett K, Slot JC, Barlow C, … James TY (2024), “Wood-loving magic mushrooms from Australia are saprotrophic invaders in the Northern Hemisphere,” Fungal Systematics and Evolution 14:209–217, doi:10.3114/fuse.2024.14.14. Its central finding: Australasia is the centre of origin of these wood-degrading magic mushrooms. The psilocybin loci show high allelic diversity and evidence of balancing selection, and geographically separated populations remain fully sexually compatible despite minimal gene flow since they diverged from a shared ancestor.

They reached that conclusion by studying P. subaeruginosa over its distribution in Australia based on genomic analyses of isolates to investigate population structure and species boundaries, examine allelic diversity at psilocybin loci, and test its centre of origin. The sample was Australian subs plus a couple of Northern-Hemisphere outgroups — Australian populations of Psilocybe subaeruginosa (n = 86), and P. azurescens (n = 2) and P. cyanescens (n = 1) from the Northern Hemisphere.

Very recently, Bradshaw et al published another African ancestor and tried to clarify some taxonomic confusion that occurred from sequencing targeted regions of the genomes (ITS, EF1alpha, RPB1, RPB2). Illumina whole genome sequencing was performed to better cement these taxonomic interpretations.

“We report the discovery of the cryptic species Psilocybe ochraceocentrata, the closest wild relative of P. cubensis from sub-Saharan Africa.” -Bradshaw et al.

Four of Five P.natalensis samples were mentioned in this study as having been misclassified as P.ochraceocentrata.

In order to contribute to this question, we whole genome sequenced P.natalensis we obtained through a spore provider in Massachusetts. This was performed on Oxford Nanopore last weekend.

We had a blow out 17Gb MinION run which turned into a great reference genome (Flye assembler) and aligned these contigs to Penvy (gold standard reference genome for P.cubensis we published many years ago). Claude code brewed up a great comparative genome browser to show the side by side similarities.

It does genetically appear to be a different species at 4 loci compared to P.cubensis and P.ochraceocentrata although species differentiation could be strengthened with more samples and mating loci compatibility.

A very important limitation. We sequenced a single commercial P. natalensis spore syringe (Mass Mycology, batch A072403). Barcoding this one genome at four loci places it concordantly within the P. natalensis complex and ~5.5% from P. ochraceocentrata, so this vial is a genuine natalensis-complex organism rather than the mislabeled ochraceocentrata common in the trade (Bradshaw et al.). As a single specimen, this speaks to the identity of this batch, not to population-level or species-wide variation.

Why do we care? P.subaeruginosa in Australia (P.Subs) are known as “wood lovers” or grow on decaying wood (but not exclusively) and under these conditions appear to occasionally express a compound (yet to be identified) that causes wood lovers paralysis. During a Psilocybin experience with P.subs, you can experience acute but reversible paralysis. Not fun if you happen to be swimming at the time but also a potential great drug for anesthesia.

Below is the Psilocybin gene cluster that is responsible for synthesizing these tryptamines.

One of the most interesting hypothesis for where WLP (Wood Lovers Paralysis) may derive is from the Simon Beck and Caine Barlow paper. Bufotenidine (from poisonous Toads) is one OH group different than Psilocin and its possible that some mutations in the Psilocybin synthesis cluster is adding that OH group to a different part of the ring in Psilocin. This is a rational structural speculation at this point with limited and potential contradictory analytical chemistry for this hypothesis.

From Claude.ai Opus 4.8

The Wood Lovers Paralysis question — where the evidence stands

Wood Lovers Paralysis (WLP) is a rare, reversible weakness/paralysis reported after eating certain wood-inhabiting Psilocybe. It clusters in two regions with endemic wood-loving species: Australia / New Zealand (P. subaeruginosa — the source of a DNA-confirmed clinical case series from Victoria; Silvester et al. 2026) and the Pacific Northwest USA (P. azurescens, P. cyanescens), where the phenomenon was first noted (Stamets, 1996) and later shaped Oregon’s regulatory exclusion of lignicolous species. It is consistently associated with wood-growing species and not with dung- or grass-associated ones. Paralysis after magic mushrooms was first described in 1973 for the wood-inhabiting P. subcaerulipes; the colloquial term is more recent (Dörner et al. 2022). Notably, there are no reports of WLP from South Africa or involving P. natalensis — though this reflects reporting patterns (WLP surveillance is concentrated in Australia/NZ and the US), not proven absence. No causative compound has been identified. The leading idea, on structural grounds, is that the quaternary trimethylammonium tryptamine aeruginascin — or its dephosphorylated congener 4-OH-TMT — might behave like the paralytic quaternary alkaloid bufotenidine, to which it is structurally analogous (the aeruginascin/bufotenidine analogy is the basis of the hypothesis, e.g. Beck & Barlow).

Two findings keep this hypothetical, not established — and both come from analytical chemistry:

• The chemistry is not wood-lover-specific. In the Hoffmeister lab’s LC-MS survey, aeruginascin was detected in P. mexicana and P. cyanescens, and — consistent with earlier work — also in the dung-inhabiting, non-paralytic P. cubensis. The paper notes explicitly that no WLP report pertains to P. cubensis (Dörner et al. 2022). So the presence of aeruginascin alone does not track with the paralysis.

• The putative active metabolite is not found in the mushroom. In the same survey the dephosphorylated congener 4-OH-TMT was not detected in any of the species examined (Dörner et al. 2022) — it is a hypothesized in-body conversion product, not a measured fungal metabolite. And where 4-OH-TMT has been synthesized and receptor-profiled, its pharmacology does not cleanly reproduce bufotenidine’s (Chadeayne et al. 2020).

As of this writing, the WLP causative agent remains unidentified, and aeruginascin is a leading candidate on structural grounds that analytical chemistry has not confirmed. This is where comparative genomics can contribute, not resolve: a reference-grade psilocybin cluster from a non-wood-loving African relative (this study) is a baseline against which the biosynthetic gene complement of the wood-loving P. subaeruginosa clade (McTaggart et al. 2024) can be compared, asking whether any enzyme difference could plausibly redirect tryptamine chemistry. Notably, McTaggart et al. (2024) report that the psiH hydroxylase is duplicated to up to three copies in wood-degrading Psilocybe versus a single copy in P. cubensis — but they caution in the same work that there is no evidence linking the psilocybin pathway to wood lover's paralysis, and that Dörner et al. (2022) suggest the symptoms are likely not tryptamine-related at all. It does not, by itself, identify a toxin. We make no claim that P. natalensis causes or relates to WLP.

Bufotenidine is a known paralytic agent from Bufo gargarizans and Bufo melanosticus. Other Bufo alvarius (poisonous Toad now called Incilius alvarius and also known for 5-MeO-DMT).

As a safety measure any Psilocybe mushrooms that grow on wood are suspect of this synthesis pathway until proven otherwise but there are no reports of WLP from South Africa.

To better understand this, its very important we align the genomes of these species (Cubes, Subs and ancestral Psilocybe) and look for structural differences in the synthesis pathways that may inform on genetic variants that could drive altered tryptamine synthesis.

Once again, Claude has come to rescue and helped us align these genomes, predict the amino acid sequences and run them through Alpha fold and ESMfold so we can compare the structural differences in these proteins and display them easily. This is preliminary work.

The video at the top of this thread is the structural alignment of a few of these genes between P.nat and P.cube. This allows you to interpret all of the variants in these two genomes Psi cluster in the context of their impact of the 3D protein structure of each gene.

These data are only a week old so take them as an early draft but its very refreshing to load a genome on Friday and have this level of analysis available on the next Friday.

One of the interesting aspects of Oxford Nanopore sequencing is that it often delivers bacterial genomes assembled into a single contiguous circular genome.

As a result, the fungal microbiome came through on this 17Gb run. 60% of the reads were microbiome. Not uncommon as bacteria grow faster and are easier to lyse than fungal spores/mycelium so they can get enriched in the sequencing process. With over 100X P.nat coverage of a 46-50Mb genome, its not surprising to get many fully sequenced microbiome genomes.

This data was analyzed with only a partial snap shot of the data as it was still sequencing so it will improve as we analyze the complete 17Gb of sequence.

Credits

Stephen McLaughlin wrestled the ONT data with Claude.

Caleb McKernan, Brendan Kane, Kevin McKernan, Yvonne Helbert and Juliana Carvalho handled the DNA preps, Library Preps and ONT sequencing.

More resources on this topic:

OUR GENOME PORTAL FOR THIS DATA

Since the roll out of mRNA vaccines, there has been an active debate regarding the safety of residual DNA found in the vaccines and if prior FDA/WHO guidelines were crafted with LNP transfection in mind. Prior guidelines for injected vaccines that lack transfection reagents placed the limit at 10ng/dose of DNA over 200bp in size. But this guideline was based on long DNA and acknowledged that short DNA of the same weight contains orders of magnitude more copies of DNA and thus require LOWER limits.

This paragraph is from Keith Peden’s and Sheng-Fowler’s work from the FDA. The basis for the claim to safety rested on the injected DNA being naked and exposed to nucleases that would destroy <200bp fragments quickly. The half life of naked DNA in the blood is often cited as the basis for this degradation rate. It’s under 10 minutes and shorter DNA degrades faster.

However, this degradation rate does not apply to LNP protected DNA and with the DNA being short, it may not encode entire oncogenes but it still contains functional promoters, hypermutability elements, origins of replication and microORFs. Some DNA fragments sequenced with Oxford Nanopore contain the entire spike Open reading frame with a cryptic mammalian promoter (ColE1), suggesting full spike expression is hypothetically plausible from the transfected DNA given the Pfizer plasmids also contain nuclear localization signals in the SV40 Enhancer.

Given the plethora of data now published on spike persistence in patients with LongVax, you would think regulators would be very interested in this being a primary hypothesis for the source of continued spike detection in patients years after vaccination.

So exactly how much small DNA is in these shots? This has been a notoriously difficult question to answer as the regulators are using qPCR tools incapable of measuring it. Once the DNA is fragmented, qPCR with 200bp amplicon sizes fail to measure the majority of the product. Fluorometry has been suggested as an alternative but Georgiou et al has demonstrated that PicoGreen also suffers from 70% under reporting from DNaseI treated DNA. While the Fluorometry reports much more DNA than large amplicon qPCR, it still under reports the digested DNA.

McKernan et al has also demonstrated that the DNaseI used to fragment the plasmid DNA in the vaccines does not process RNA:DNA hybrids thus leaving 100 fold more spike DNA than Ori or plasmid DNA. This Spike/Ori qPCR delta CT has now been observed in many studies but surprisingly doesn’t exist in all lots demonstrating lot to lot heterogeneity in the spike DNA contamination. This variable has gone un-noticed by regulators as they are only using a single qPCR assay outside of the DNaseI protected spike region to assess the residual DNA load.

Why are they allowing a single qPCR assay to monitor this problem when C19 testing demands multiple qPCR assays to address the virus? This is a double standard they refuse to address.

What is known from a FOIA request from the TGA is that the regulators are using a Kanamycin Taqman assay which they refuse to disclose the details of. Taqman based qPCR suffers from its inability to target small DNA. This detection method requires a 3rd known sequence (a probe) to generate its signal and this 3rd sequence requires DNA of certain size (over 75bp) to afford detection. SYBR Green is often used in its place as it has no requirement for a 3rd sequence, however SYBR Green is a single color assay and forces one to sacrifice the spectral multiplexing offered by 5 color Taqman in order to obtain small amplification. Uniquely SYBR Green affords high resolution melt (HRM) capabilities that Taqman cannot provide.

Researchers downgrading to single color SYBR can still recapture some multiplexing capabilities if they design their target amplicons to have different melting temperatures in the HRM domain.

A quick review on HRM.

After qPCR, most thermal cyclers can ramp the temperature up from 50°C to 95°C and monitor the signal through this thermal ramp. When using intercalating dyes like SYBR Green which only fluoresce in the presence of DOUBLE stranded DNA, you will witness a drop in SYBR Green signal as the target amplicon reaches its melting temperature and becomes SINGLE stranded DNA. This is an important piece of information you can use to confirm what target actually amplified.

At CannMed 2026, we presented a novel qPCR technology known as LIDAR qPCR that unifies the tradeoffs between SYBR Green HRMs and Taqman while retaining the capacity to amplify small DNA in 5 colors with HRM capability.

https://rumble.com/v7bpsoi-lidar-qpcr-from-medicinal-genomics.html

We then applied these new tools to the detection of various pathogens and variable sized DNA targets in the mRNA vaccines.

To address this problem, we first engineered a novel qPCR detection method that does not use irreversible hydrolysis (FEN1 activity in Taqman polymerases) as a dequenching mechanism. Taqman cannot perform HRMs because it relies on the irreversible destruction of the probe to liberate a Quencher from a Fluorophore.

Once the Quenchers are cleaved from the dye, subsequent cooling and heating provides no additional information on the target DNA. SYBR Green on the other hand, has dyes that can melt from DNA and re-associate providing a reversible ON and OFF signal based on thermal conditions. Unfortunately, these intercalating dyes have a very broad excitation and emission spectra and consume the majority of the visible spectrum on qPCR instruments such that only 1 color can be used.

To obtain this capability with 5 color fluorescence, we engineered PCR primers that act as Probes or “Probers”. These engineered Probers have a Fluorophore-Quencher (F-Q) in close proximity in a single stranded primer but distanced from one another by 3.4 Angstroms per base once the ssDNA is forced into the helical pitch of double stranded DNA. Thus the formation of the helix longitudinally separates the Dye from the Quencher and this is a reversible 5 color signal similar to SYBR Green. Hence the term LIDAR or Longitudinal ID of Amplified Reporters.

These Probers can then be used on the 5’ end of PCR primers and consume zero internal DNA real-estate for amplification and thus capture small DNA just like SYBR Green.

This PCR reaction tailing is an important detail to zero in on as it is the cost driver of Taqman based qPCR. The synthesis of an internal custom dye labeled probe is usually about $300 where unlabeled primers are closer to $15. So every time you want to target a new organism with Taqman, you find yourself synthesizing another $300 probe.

By putting this reporter on a 5 prime tail of a primer, you can make that sequence whatever you want and the same for every organism you want to target. You simply need to synthesize an unlabeled bridge primer that unites your species specific primer to your LIDAR reporter. For instance, the sequence in yellow below is the LIDAR sequence for the Quasar705 LIDAR bridge primer and the black sequence is the ORI target. We can easily swap out these unlabeled bridge primers with different prober tails if we want to change colors for a given assay.

Below is the Cy5 Bridge primer for Spike. Note these are unlabeled bridge primer but the prober sequence with the LIDAR Fluorophore and quencher are same sequence as you see in their respective color, only with 2 modifications (Dye and Quencher).

Since the reporter target is on the bridge primer tails, they are universal. We can now make these reporters in bulk and not have to pay for a novel Taqman probe for every new assay. This is critical to cost reductions as bulk synthesis of labeled reporters scales. If you want 10X more synthesized, it usually only costs you 3X more.

5 Color LIDAR

Below is an example of a 5 color HRM using LIDAR probers. They maintain signal at low temperature (left) but as you raise the temperature and melt the strands from their targets, they go back to single stranded state and continue acting as quenchers.

Now that we have multi-channel (multiple colors) HRMs we can entertain targeting more than one region in the vaccine plasmid to address McKernan et al’s concerns over using a single KAN target as a proxy for DNA content after a complex and non-uniform DNaseI digestion.

Similarly, now that we also have HRMs, we can create a qPCR tiling of 50bp, 60bp, 70bp, 80bp, 90bp, 100bp, 150bp, 200bp, 250bp and 300bp target amplicons to measure the actual fragmentation rate in the DNaseI treated vaccine. How much more DNA is detected if your amplicons are 50bp vs 300bp?

Below is a depiction of this effect using SYBR Green. 60bp amplicons present a CT of 13 while 300bp amplicons deliver a CT of 17.5 in the Pfizer Vaccine.

This 4-5 CT difference in small versus large amplicons equates to a 16-32 fold (2^4, 2^5) variance that alone could account for the reason why the regulators can’t see this problem. They have never disclosed the size of the amplicon they are using and these methodological details remain redacted and confidential to this day. As you can see, use of a larger amplicon could easily tip the scales to a passing sample when it in fact has 32 fold more DNA than they claim.

Similar offsets are seen with LIDAR although the effect is more pronounced due to the subtleties of the photophysics.

SYBR Green stains DNA with a small-8bp footprint so the longer your DNA amplicon, the more SYBR Green it recruits. This overestimates the larger DNA compared to the smaller DNA. This is the exact photophysics effect described by Georgiou et al who measured a 70% loss in quantitation (with the intercalator PicoGreen) once you fragmented the DNA into smaller pieces with DNaseI.

LIDAR end labels the DNA with 1 dye molecule per amplicon and provides a more direct measurement of the quantification of DNA molecules. In this case we chose a Pfizer vial that did not show the 100 fold offset of Spike vs Ori DNA as we want both targets to be operating in the same dynamic range for these optimizations. This 100 fold spike-ori offset is discussed in Speicher et al and McKernan et al and is now known to be an artifact of DNaseI failure to digest DNA that is shielded by RNA (RNA:DNA hybrids). However, not all lots show this artifact which is in itself a manufacturing variance that should have created a halt on the vaccines.

When running these SYBR qPCR assays on the vaccine, you need to have a non fragmented synthetic control to compare them to. These are known as gBlocks from IDT.

Below is the SYBR Green HRM of the 50bp-300bp amplicons. The larger amplicons have higher melt temperatures as expected. These had to be run in independent qPCR wells as SYBR is single color and the Red/Blue coloring in the below charts is a pseudo-coloring to afford overlay and comparisons of spike and ori amplicons. HRMs provide added confidence that your PCR reaction is producing the expected amplicon.

LIDAR changes the multiplexing dimensionality. We can Run Spike assays in CY5 and Ori in Quasar to obtain both targets in a single well.

Below is the LIDAR HRM of the CY5 spike amplicon series.

You’ll notice the HRMs agree with SYBR for amplicons under 150bp. They depart due to a 70% GC knot at base 120 in the spike amplicons.

That artifact is actually very informative for LIDAR as we can get Left of Knot (LOK) and Right of Knot (ROK) melting temps for each amplicon if we label the LIDAR reactions from both ends with different colors. SYBR Green cannot do this. It will always report the average Tm of the molecule where LIDAR can show Left vs Right melting temps (Tms) for long amplicons and provide more sequence context information. Below is a LIDAR HRM using Quasar on the Ori amplicon set.

You will note the Quasar Prober is giving more concordant HRMs with SYBR than the Cy5 prober if you simply look at Full Width at Half maximum. This is a measurement of how ‘Fat’ the melt derivatives look for the longer amplicons.

When you chart the fragmentation size as measured with both SYBR Green and LIDAR you will notice SYBR slightly inflates the longer DNA compared to LIDAR. However, both assays demonstrate that the quantitation can vary by over an order of magnitude just by making your qPCR amplicons longer.

This plagued the Ach’s paper which attempted, but failed to debunk the Speicher paper due to several methodological biases in their assays including erratically sized qPCR amplicons.

The below chart shows the estimated DNA in the vaccine using differently sized amplicons with SYBR green vs LIDAR. You will notice LIDAR estimates more of the DNA to be smaller than SYBR due to this photophysics effect and SYBR inflates the quants for the larger amplicons due to multiple dyes being recruited to the larger amplicons and overcounting their numbers. This emphasizes that Taqman assays over 100bp will only capture 10% of the DNA compared to 50-60bp amplicons. Hence the Qubit vs Taqman debate is not about the RNA cross staining with PicoGreen. Speicher and McKernan et al both used RNaseA to remove RNA, yet this critique continues to circulate while the photophysics of the detection tools is actually one of the 16-32 fold mechanisms at play. The second mechanism at play was already published in the Journal of Independent Medicine. This second mechanism (RNA:DNA hybrids) has a larger impact (6CTs or 100 fold) and is also published by BioNtech scientists. DNaseI doesn’t process RNA shielded DNA and one can see a 100 fold more DNA in spike than in the KAN region.

We continued this exploration on amplicons arrays using synthetic DNA controls which are not fragmented like the vaccine. We looked at both 300bp synthetic controls and 400bp synthetic controls as there is some literature in the field that priming DNA on the termini of CT rich DNA can suffer poor hybridization when primed flush to the termini of the template. The 400bp synthetic DNA is designed to control for this artifact and we do indeed see slightly different results from a few of the terminal amplicons.

The gBlocks are contiguous synthetic DNA made by IDT. These have no fragmentation so every molecule in the reaction is full length. These are in Blue and Green. You will note, regardless of the size of the amplicons we get similar CTs although the amplitude of the signal can be altered by SYBR green as larger fragments provide more dye. The Red lines are the SYBR PCR of the vaccine and you can see a notable increase in CT as the amplicons get larger. The lighter Red lines are the smaller amplicons and the darker red lines represent the larger amplicons.

There are some subtle differences priming the spike amplicon gBlock termini due to some CT context at the termini of those fragments. This artifact is resolved when longer synthetic DNA is present and our primers are not trying to hybridize to termini without flanks. This is a very subtle detail in hybridization kinetics required for peer review but it is worth disclosing. There is a thermodynamic tax hybridizing to the flush end of some CT sequences that doesn’t occur if the DNA target has flanking sequence.

If you run these amplicon arrays using LIDAR with a Quasar tailed Forward primer for Ori you get a similar clustering of CTs for short amplicons with some delays for the longer amplicons on gBlocks. These larger amplicon CT delays mostly disappear on the 400bp gBlocks but are still delayed compared to SYBR Green versions of these assays (yellow curves on lower right chart). We believe this is due to the photophysics effects described earlier. A curious eye will see a later CT (14 SYBR vs 16 LIDAR) on the smaller amplicons. This delay is related to the 1:100 dilution of the Bridge primer in the LIDAR reactions and doesn’t impact the final quant as the standard curves are run with that same bridge primer dilution.

This bridge primer delay is the cost of using universal tails but can be mitigated if you link your species specific primer to the prober in synthesis but then you are back to the economics of Taqman probe synthesis.

This bridge primer delay is an artifact of unlabeled Bridge primer concentration and doesn’t impact final CT→DNA concentration assessments when the same bridge primers are used in your standard curves. Both reactions have a similar CT offset and the quant remains accurate. LIDAR can be run without bridge primers but you forfeit the use of universal reporters and are back to the same expense as Taqman where a F-Q probe or prober must be uniquely synthesized for every target.

At this point, most people question how sensitive is LIDAR next to Taqman? In our experience, LIDAR usually shows up 2CTs earlier than Taqman when probers are synthesized with a species specific 3’ end (No Bridge priming).

This is due to LIDAR labelling the 1st step of PCR while Taqman is a 2nd order proxy for amplification. Signal generation in Taqman is dependent on 3 steps.

First, a primer must extend. 2nd a Probe must hybridize to the primer synthesized DNA and this process is not 100% efficient. 3rd, Flap Endonuclease activity (5→3 exo) must engage and hydrolyze the probe and this is the slowest activity of the polymerase. So Taqman signal is actually the composite of Hybridization efficiency X FEN1 activity and several steps downstream of the priming event that generates signal in LIDAR.

To further explore LIDARs flexibility, we have amplified Pseudomonas with 5 different LIDAR probers and evaluated their HRMs. We note they all overlap with different colors and the different master-mixes can have a subtle impact on the HRM likely due to Mg2+ or salt differences. Some probers amplify more aggressively than others and their bridge primer concentrations need to be optimized to balance them all.

Repeated on 5 different organisms with altered ratios of bridge primers to normalize the different probers.

When you flip the probers onto their reverse primers and rerun these HRMs you get additional information.

A good way to think about LIDAR HRMs is that they are 2D HRMs where the amplicon provides 90% of the melt prediction and the Forward and Reverse orientation of the HRM is an additional 10% contribution to the HRM. Thus you can get additional sequence context information from LIDAR that is averaged into one HRM from SYBR green.

LIDAR is also a more direct readout of the process of PCR compared to Taqman.

When amplifying with CY5 (Pseudo) and FAM (Staph) Taqman probes, we observe amplification curves that plateau at 1750, and 4000 RFUs respectively.

With LIDAR the reaction plateaus around 6,000 with Quasar705 on Pseudomonas. This could be a result of the different Quantum yield of these dyes but in our experience this is common even with the same dye as most Taqman protocols call for using half as much probe as primer. Taqman probes have suboptimal F-Q distances that usually put the Quencher and the Dye 20-25 bases apart and this leads to partial quenching and high background when equimolar amounts of primer and probe are used so the general rule of thumb is 2X less probe than primer and you pay for it with lower signal amplification compared to when your primers are your reporters (as in LIDAR).

Below is a serial dilution of Pseudomonas amplification showing quantitative linearity with LIDAR and a slightly earlier CT call than Taqman.

Unlike Taqman, sharp HRMs are obtained after amplification, verifying the target amplified. You will note that the HRM amplitude is reflective of the end point PCR yield. This is another dimension of LIDAR that can be leveraged. More on that later.

In our experience, the comparison of LIDAR vs Taqman performance is a bake off that fails to leverage their combined strengths. The fact that Taqman dequenches differently than LIDAR can be further leveraged over using any one technique in isolation.

This gets into the combinatorics of using one or more colors to label a target. A simple deployment would assign 3-4 targets in each color where each target has unique HRMs. This enables 15-20X multiplexing.

But once you have orthogonally dequenched reporters (as you do when you combine LIDAR with Taqman), you can solve a long standing problem in the qPCR space known as the unordered pair problem.

Briefly, with Taqman alone, you cannot use expanded color combinations to encode more targets. What do I mean by that?

There has always been the temptation to use pairs of colors to encode targets. With 5 (N) colors you have (5X5)-N different 2 color combinations or N^2-N if you omit identical color combinations like Blue-Blue, Green-Green, Yellow-Yellow, Red-Red, and Orange-Orange. People omit the same color combinations as you get one signal from qPCR and you can’t discern Just Blue from Blue-Blue.

These color combinations have historically gone under-utilized as Taqman also fails to discern Yellow-Green targets from targets labeled Green-Yellow. It cannot order these pairs of colors so targets labeled Yellow-Green look the same as their reverse ordered Green-Yellow pair.

Once you have a signal that dequenches differently, you can order this unordered pair problem.

Note the color chart on the right. One set of colors is Taqman detected on the Y axis and another set is LIDAR detected in the X dimension. Only the LIDAR signal shows up in HRM.

So the differential dequenching of Taqman vs LIDAR can be used to solve the unordered pair problem by observing which signal shows up in HRM and which signal disappears. Now the Yellow-Green target has a unique signature compared to the Green-Yellow target and your color spectrum has expanded from 5 colors to 20 dual colors.

Combine this with targets that occupy different (3-4) HRM zones and you can get 20 targets to expand to 60-80 targets.

But there is still another dimension left under utilized. Signal amplitude is often used to plex different targets in the same color. Use half as much same color probe for one target and the amplitude ‘should be identifiable’ as a different target. We are not great fans of this type of multiplexing as various things can inhibit Taqman to blur those amplitude lines and as I mentioned earlier, Taqman is a 2nd order signal.

However, if one were planning on using the amplitude domain to multiplex, you’d be far less error prone doing so if your readout was not 3 steps removed from priming. Since LIDAR probers measure the 1st step in PCR amplification and not (primer extension) x (probe hyb efficiency) x (FEN1 activity) like Taqman, signal amplitude measurements are more direct and can be done on both forward and reverse primers with different dyes to confirm results.

Below is an example of such a concept. In this case we performed asymmetric PCR where one Forward primer is 10X lower in concentration than its Reverse.

We have 3 different targets all being amplified with a universal LIDAR tail. This is an important distinction as the most expensive part of Taqman is using species specific dual labeled (F-Q) probes. With LIDAR you can make these M13 tails so you make 1 universal prober for all assays and rely on a naked (unlabeled) tailed primer to create the bridge to the universal reporter. After 1-2 cycle of PCR, your E.coli specific amplicon now has your LIDAR tail incorporated and LIDAR can begin the labelling with a universal LIDAR prober. This dramatically reduces probe synthesis costs as all targets can be addressed with 5-10 perfectly engineered reporters (5 diff colored Forward Probers and 5 differently colored reverse probers) and all you have to do to address new organisms is change the bridge/tail primer that unites your target to a reporter sequence. Below, the Blue regions of the primer are Organisms specific. The Red and Green sequences are universal LIDAR prober sequences.

Using this tailed approach, we have E.coli, Staph and Salmonella bridge primers all amplifying with Quasar705. We have Pseudo-color coded the HRMs to show they are all distinguishable with unique HRM temps. You will also notice Blue and Green peaks that are half the amplitude of their other respective colors.

These are wells where the primer concentrations for the Forward strand were 10X lower than the Reverse strand so asymmetric PCR occurred and generated more Reverse strand than forward strand thus making the HRM amplitudes lower.

You’ll note the chart has “with and without probe” labeled. We used Taqman probes designed to hit different strands to confirm the Asymmetric PCR but these don’t show up in HRM. This could also be done with Dual LIDAR detection and is demonstrated in my CannMed 2026 talk.

In conclusion, we have reengineered qPCR to give us the best of both worlds. SYBR Green like HRMs with 5 colors + Forward and Reverse melting temperature dimensionality, while also reducing the DNA footprint required for amplifying small DNAs as seen in miRNA, Circulating Tumor DNA, vaccine QC, and ancient DNA applications. We have also removed the greatest cost barrier to Taqman (probe synthesis) by engineering universal tails for qPCR that give a more direct measurement of the kinetics of the amplification.

LIDAR used in combination with Taqman, greatly expands the color dimensionality by solving the unordered pair problem. This significantly expands the information content delivered from a qPCR reaction such that single target PCR becomes reckless corner cutting.

This added multiplex capability doesn’t need to trade off accuracy for speed. One can use these expanded codes to include more internal controls, more matrix controls and more amplicons per organisms to protect against PCR generated pseudo-epidemics. This can also be used to increase the number of targets one amplifies to assess DNaseI fragmented libraries while retaining quantitation of small DNAs.

These data demonstrate that amplicon size can alter DNA quantitation by 4-5 CTs and introduce a 16-32 fold variance in DNaseI treated vaccines. Because amplicon-size bias and region-specific digestion are independent effects — the former an intrinsic property of the detection chemistry, the latter a property of the template — they act orthogonally and compound rather than overlap. Combining this size effect with the ~6 CT differential digestion of Ori versus Spike regions reported by McKernan et al. , Speicher et al., and Fleming et al. therefore implies a combined variance approaching 10 CT (~1000-fold) between large amplicons targeting Ori and short amplicons targeting Spike.

Thus having the qPCR methods used by the regulators deemed as proprietary is simply a refusal to have any transparency or assurances of the actual metric in question. Claiming something is below 10ng/dose may be from a combinations of failing to look in spike where the DNaseI is 100 fold less active or using large amplicons that simply fail to PCR the majority of the DNA that is present. The fact that this DNA is small is of no assurance as its LNP protected, has nuclear targeting sequences, mammalian promoters and mammalian origins of replication and somatic hypermutability elements in the SV40 Enhancer. Its important to emphasize that the both Pfizer and Moderna vaccines have ColE1 oris. These are published to be mammalian cryptic promoters that can express genes downstream of them. For the regulators to call this DNA non-functional is an egregious error as it contains all the material required to express spike protein in mammalian cells and DNA is known to decay slower than RNA thus giving credence to this contaminant being the primary cause of persistent spike expression in patients with LongVax. The 10ng/dose does not apply to transfections of such content. Small DNA, once transfected is not benign. It is more prone to integrate as it has a higher molarity of Phosphates and hydroxyls than high molecular weight DNA and its known to trigger the cGAS-STING pathway.

Kwon et al has shown that chronic stimulation of cGAS-STING can lead to oncogenesis (cancer). Recent data from SEER shows an increase of such events since the vaccine program rolled out.

A few people at CannMed asked this question.

Since most Point of Care DNA testing tools use Bst polymerase or enzymes that do not have FEN1 activity (5→3 exo-), they cannot utilize multi-color taqman. Many of these tests remain single color and therefor lack internal controls when you need them most.

LAMP is one such method we have some experience with but have found it to be very sensitive to contamination from crude boil preps often used in the field. Likewise any agricultural foliar spray residues that might be left on the plant can inhibit crude field preps if the read out chemistry isnt robust.

This is largely the function of the type of read out chemistry used. One of the most popular read out chemistries is the use of pH sensitive dyes that change from Pink to Yellow as the LAMP reaction spits out H+ groups during the synthesis of nucleic “ACIDS”. So to make this pH sensitive colorimetric (not fluorescent) readout occur, they need to strip all the buffer out the reaction so the pH swings very easily during amplification.

So if you’re plant is in slightly acidic water or has just been sprayed by something acidic, that spills into your LAMP assay and creates False positives with that pH triggered colorimetric test.

And since you have only 1 color, you have to run Positive controls and Internal controls in their own wells. You really don’t have internal controls when they are external to your assay. Internal controls should always light up to prove your sample didn’t have Polymerase inhibitors (think terpenes) so putting them in other wells because your detection chemistry is single color exposes you to many false negatives.

The pictures at the top of this post are LIDAR reactions being illuminated with a portable P51 labs transilluminator. This only have a Blue LED so it will not excite all 5 colors but does handle FAM and SUN well enough to read it with the naked eye on an iPhone.

We have in fact run Bst polymerases with LIDAR in a simple 2 primer PCR like model at isothermal 65C against Aspergillus and it creates Ct curves. These cycles are just imaging times (like 30sec imaging cycles) and I didn’t spend much time optimizing any of these. The Bst 2.0 polymerase was dug out of a freezer and was 8 years old and expired but we did get melt curves although they were broader (more FWHM) than qPCR products.

I then tried to find unexpired Bst polymerase and all I had in the freezer was the NEB colorimetric kits which I threw LIDAR probers into so we had both colorimetric and fluorescent read outs in the same well. In this case the colorimetric dye may have risen the background in the FAM channel

The amp curves a little slower than what we get from 3 step cycling with LIDAR but they still amplify. The LIDAR probers behave wonderfully as LIDAR doesn’t require any 5→3 exo and Bst polymerase doesn’t have any but Bst being strand displacing is a little slower than qPCR that cycles. LAMP turbo charges the reaction to make up for this with very high primer concentrations and a concatemer amplification method that more than doubles every cycle. If you can get your head around the hall of mirrors LAMP amplification.. congrats.. Its very hard to conceptualize and to design primers for as it often requires 4-6 primers per target and has much higher primer dimer related false positives. Its hard (but not impossible) to use as a quantitative reaction as you dont have that nice perfect doubling of DNA every cycle and there are no cycles…. Just time at 60-65C and imaging every X number of seconds during the reaction but the reaction is usually done in 25 minutes.

A few considerations.

This reaction creates massive concatemers so HRMs are meaningless and cannot be plexed. While DUAL-LIDAR could be deployed (2 loop primers as probers), we don’t have orthogonal dequenching since Taqman can’t be run side by side with LIDAR. This limits the color combos to a 5 Choose 2 problem (10 color combos).

So LIDAR will likely enable 5-10 Color LAMP but it is not our primary focus as LAMP has FP and FN issues surrounding its complicated primer requirements (many primers and higher concentrations) and in our experience it is usually 5-10X less sensitive than qPCR. Highly multiplexed LAMP assays are hard to design as there are many more primer interactions you have to consider and everything has to work perfectly at one temperature. You don’t have as many knobs to turn to optimize around primer dimer artifacts like Touchdown PCR or different annealing temperatures than extension temperatures.

has a great write up on LIDAR. I’ve been traveling from Boston to Lake Tahoe and now up to Camp Nakamoto in NH so I’ve been limited to brief jargony write ups while half asleep at airports.

Hello everyone..

Ive been a busy bee lately and have had to put Substack down for a bit while we build.

The good news is that Im mostly out of my Fugue state with much to share.

I turned into an AI Vampire and began coding night and day with Claude code as have a few of our colleagues at Medicinal Genomics. My work has been mostly focused on inventing a new way to perform qPCR which I will be sharing shortly.

I know qPCR can be a dirty word to all of those people who were abused by sloppy implementations of it during COVID. Our method will fix this as we have devised a way to get much more information content out of a qPCR reaction.

The work below is where others at MGC dug in. We took our large cannabis genomics database and sicked Claude on it to give it a facelift and the video below will show you some of the new features.

A few I need highlight up front.

1)Alphafold3 protein predictions. We take the variants we find in the plant genes and feed them into Alphafold so it can render the 3D protein structure of the gene and paint your variants onto that 3D structure.

2)Microbiome analysis of any Whole Genome Shotgun cannabis sample.

3)Autoflower, Early Flower, Seed quality, Monoecy (hermaphroditism) and cannabinoid synthase genetics brought to you like a 23&Me report.

4)3 different ways to view the ever growing phylogenetic tree.

Stay tuned..

We have some developments on the PCR front that will change the way you think about Fluorescence and how we can use that to improve qPCR 10 fold. Most likely will be presenting this at CannMed if all the data rolls in as expected in the next week.

Thanks for sticking with the subscriptions through my hiatus.

And yes.. The ticks are everywhere up here and I recently got bit and had to go on Doxy for a while. More on that rabbit hole later

An excellent article from Dr. Charlotte Kuperwasser.

I will add that the litany of mRNA vaccine Nucleic Acid persistence papers are finding Spike nucleic acids in patients weeks (Castruita, Gonzalez, Roltgen, Krauson, Hanna) to 17 months (Ota) after Vaccination. has recent work that goes out 3 years. Many of these papers are using RT-qPCR to find this and they don’t always itemize if this qPCR assay is amplifying DNA or RNA as the technique amplifies both. To itemize if RT-qPCR is amplifying DNA, one simply uses an RNase and skips the 55C RT step in cycling or doesnt add the RT enzyme into the process. To amplify exclusively RNA, one needs to deploy a DNAse that removed RNA:DNA hybrids like DNaseI-XT. Most papers tracking this published before the DNA contamination was known and assumed the spike positivity in these assays was derived from the spike modRNA.

Given there is ample evidence of spike nucleic acid persistence and DNA is known to be more stable than RNA, why are the regulators content to NOT measure spike DNA in the vaccines? They are entirely content with measuring the one part of the plasmid that isn’t being found in patients!

Well, that is not entirely true. Some papers are finding the SV40 and Ori or Kan sequences and I’ve documented on this substack many great papers that have these sequences contaminating their patient data in the SRA archive. (Ryan et al, Chakraborty er al, Lee et al, Knabl et al). However, the plasmid sequences are never a smoking gun for the vaccine as they can have other potential sources.

Kitome contamination (plasmid sequences from the polymerases in the sequencing and PCR kits) to lab contamination as these sequences are NOT unique to the vaccine. Only spike sequence is a fingerprint for the vaccines but they will not monitor that as a byproduct in the manufacturing process as they have plausible deniability when people find SV40/Ori or Kan DNA in patients samples.

This is particularly unnerving when EMA documents disclose that Pfizer has a Spike RT-qPCR assay validated to prove the spike gene is inserted into the plasmid. They will never report the CT score from that assay. They instead expend extra effort validating a new qPCR assay in a region outside of spike to provide the regulators with the illusion of low levels of DNA and the presence of DNA they can always claim came from somewhere else.

I no longer believe this is ignorance.

A helpful soul send me the below manuscript. It is another Pfizer employee review paper about mRNA tricks of the trade. There was an interesting section in here that caught my eye as it resonated with a personal anecdote.

Having been in the genomics field for 30 years and having had several successful exits, I have come to know many of the CEOs in the biotech space. One of them privately shared that Pfizer was cutting corners to save money in the RNA purification arena for these shots. Instead of using gold standard commercial RNA purification kits, they starting home brewing new methods to save money during scale up. This comment didn’t surprise me. The world had never had to make this much RNA before and the gold standard kits would probably need to be run 1000s of times to make this much RNA but what frightened me about the comment, is that home brewing new RNA purification kits for injectables isn’t something that can be done at warp speed. There are too many contaminants you need to prove you dont’ capture and many of these contaminants have very similar molecular structures that make crude homebrew methods a bit of challenge to engineer in short order.

This manuscript will show you why. In this case there a mention of mRNA purification changes that were made to avoid using HPLC and acetonitrile. This is an odd comparison. Its a bit of a strawman argument. “We don’t want to use this toxic method that this not fit for purpose, so we invented this cellulose method instead”.

What is not shown is the real gold standard which would have been oligo-dT affinity chromatography. “This was Qiagen's territory (POROS oligo-dT resin), as well as Sartorius/BIA Separations (CIMmultus monoliths) and GE/Cytiva (Dynabeads)”(quote from Claude.ai).

This is the paper that points to the Kariko Cellulose methods

Ugur Sahin and Kariko’s paper on this new Cellulose method is below.

The damning aspect of this paper is that they knew this method would not resolve RNA:DNA hybrids as seen with their S9.6 mAb stain in Figure 1B. These would be guaranteed to co-elute with the ssRNA.

I asked Claude.ai and ChatGPT about this. Why are they comparing their new method to one that isn’t the real gold standard? Both gave consistent results but I have only shown Claude.ai output below.

Claude.ai - This is an excellent and underappreciated set of overlapping problems. Let me break this down systematically across the three issues you’re raising.

1. The Cellulose Method Explicitly Does Not Remove RNA:DNA Hybrids — By Design

The authors themselves state that dsDNA, DNA:RNA hybrid, and single-stranded RNA (ssRNA) that had none or a low density of 2′-hydroxyl residues did not bind to the cellulose. They frame this as a feature, not a bug — the selectivity mechanism requires the high 2’-OH density unique to dsRNA. Binding of double-stranded nucleic acids to cellulose in the 16% ethanol-containing buffer is a unique property of dsRNA, as RNA:DNA hybrid or double-stranded DNA (dsDNA) remain in the unbound fractions under these conditions.

The consequence is stark: any RNA:DNA hybrids formed between the IVT-generated mRNA and residual plasmid DNA template will co-elute directly with the “purified” ssRNA product. The cellulose step is structurally incapable of addressing this class of contamination.

2. The HPLC “Gold Standard” — What Does It Actually Do to RNA:DNA Hybrids?

The HPLC method referenced as the comparator is Karikó et al.’s 2011 IP-RP HPLC on a non-porous polystyrene-divinylbenzene (SDVB/RNASep) column. The seminal finding was that contaminants including dsRNA in nucleoside-modified IVT RNA are responsible for innate immune activation, and their removal by HPLC results in mRNA that does not induce IFNs.

However, the HPLC gold standard claim is essentially for dsRNA removal — not RNA:DNA hybrid removal. A few important mechanistic points:

• IP-RP HPLC can be performed under non-denaturing conditions (room temperature), partly denaturing, or fully denaturing conditions (60°C and higher; 75°C was shown to fully denature dsRNA into ssRNA). Under non-denaturing room-temperature conditions — which is how the cellulose paper runs its comparator HPLC — an RNA:DNA hybrid adopts an A/B intermediate helix geometry distinct from both ssRNA and dsRNA. Whether this intermediate conformation produces sufficient chromatographic resolution from the ssRNA mRNA on a polystyrene-DVB column has never been tested or validated in the IVT mRNA context.

• Under fully denaturing HPLC conditions (75°C), the RNA:DNA hybrid would be thermally melted, liberating the DNA strand as a separate species. That DNA would then need to be separated from the ssRNA by size — which is possible but depends on whether the residual template DNA fragments (which could be from the linearized plasmid, ~3–6 kb) fall outside the mRNA elution window.

• Critically, neither the 2011 Karikó paper nor this 2019 cellulose paper specifically tests HPLC performance against RNA:DNA hybrids. The HPLC validation is exclusively against J2 dot blot signal (dsRNA). The “gold standard” claim is entirely dsRNA-centric.

3. The Antibodies in Figure 1 — Minimum Detection Limits

J2 mAb (dsRNA-specific): J2 and K1 mAbs recognize continuous double-stranded structure of at least 40 bp in length, which is not found in any of the coding sequences or UTRs in the mRNAs analyzed. This is a critically underappreciated constraint. J2 is blind to dsRNA shorter than ~40 bp. This means:

• Short abortive IVT transcripts that form partial duplexes < 40 bp are invisible

• RNA hairpins or short secondary structures in the mRNA itself won’t register

• Short RNA:DNA hybrids from partial-length reverse transcription events won’t trigger J2

S9.6 mAb (RNA:DNA hybrid-specific): The minimum length of the hybrids should be more than 8 base-pair for S9.6 binding. The structural basis for this was elucidated by cryo-EM — the heavy chain inserts into the minor groove. A more precise structural study found the contact epitope even smaller: S9.6 binds to a 6-bp epitope on DNA-RNA hybrids with high affinity and specificity.

However, two important caveats:

First, the cross-reactivity problem. The S9.6 antibody is broadly used to detect RNA:DNA hybrids but has significant affinity for double-stranded RNA. The impact of this off-target RNA binding activity has not been thoroughly investigated. This means in a dot blot loaded with IVT mRNA — which contains abundant ssRNA with secondary structure hairpins — S9.6 signal is not exclusively reporting RNA:DNA hybrids. Any residual dsRNA present will bleed into the S9.6 channel.

Second, S9.6 exhibits robust selectivity in binding hybrids over double-stranded RNA and categorically rejects dsDNA, recognizing a compact epitope of two consecutive RNA nucleotides via their 2’-hydroxyl groups and six consecutive DNA nucleotides via backbone phosphate and deoxyribose groups. So in a clean system, specificity is good — but in a complex IVT mixture, the dsRNA off-target signal muddies interpretation.

For a dot blot assay specifically, the S9.6 lower detection boundary is ~6–8 bp duplex length, but practically at the mass loadings used (typically 100–200 ng of total RNA), short hybrid species (<15 bp) at low molar abundance in a large excess of ssRNA are unlikely to be resolved above background. The cellulose paper’s Figure 1B uses the S9.6 dot blot primarily to confirm RNA:DNA hybrids are present/absent in fractions — not to quantify them at low levels.

Summary Table of Blind Spots

The composite picture is that the entire validation framework of this paper — J2 dot blot for dsRNA purity confirmation, S9.6 as a secondary check — was never designed or validated for detecting short RNA:DNA hybrids at the levels likely to be present in IVT mRNA. When you carry this forward to the mRNA vaccine context, where your work has documented RNA:DNA hybrids that are protected from DNase digestion precisely because of hybrid formation, neither the cellulose purification step nor the HPLC gold standard would be expected to remove them, and neither antibody assay at dot-blot mass loadings would reliably detect them at low abundance against the background of a multi-kb ssRNA preparation.

>End Claude.ai

The best way to eliminate RNA:DNA hybrids is to use a DNase that actually digests them before these purification steps. Something BioNtech was also fully aware of in the Lenk et al paper as they note Sutton et al documented that DNaseI digests RNA:DNA hybrids with 100 fold less efficiency than dsDNA alone. Many other nucleases exist that solve this problem (DNaseI-XT being just one of them).

Instead of solving this problem, they designed a qPCR assay that would never find it. We describe this qPCR game in the Journal of Independent Medicine. To this day, news agencies, fact checkers and even the New York Times recent plagiarism of exclusive article on the ACIP meeting, claim this DNA contamination work has been debunked because regulators simply took the CT values from a single non-spike PCR amplicon from Pfizer and believed them. They never asked Pfizer why they wont report the CT values from the Spike qPCR assay they have listed in their EMA documents?

There is 100 fold more spike DNA in the shots than the non-spike DNA as the spike region has RNA:DNA hybrids that DNaseI cant digest. Pfizer knows this as Lenk et al is from Pfizer and published this 100 fold failure. These purification papers also underscore that they know this material survives their purification process. These authors are also part of BioNtech.

The only thing I can take from these disclosures is that Pfizer wants the RNA:DNA hybrids in the shots but they don’t want the regulators to know its there. Why would Pfizer want these additional inflammatory molecules in their shots? Do they not illicit the desired response without them? I will point you to substacks from and to answer that question as it brings into question immune tolerance and perhaps the chronic disease market they now profit from with vaccine injuries: a class of injury that has escaped having an ICD10 code to track until very recently. That is in fact a very clever business model. Profit from a large injury market you created while the health care system has no capacity to track it back to you.

Yes, many of the vaccine injured patients are being given drugs made by Pfizer. Eliquis is just one anti-coagulant that has seen sharp increases in sales since 2020.

Greetings substack audience.

I have been taking a bit of break from X and Substack to explore a new method for DNA sequencing. I have not retreated from this fight. I was in fact in DC last week to speak at the MAHA Institute and had the pleasure of meeting Wafik El-Deiry, Del Bigtree, , and Maria Gutschi in person. It was great to finally meet many I only know online.

However, I was not born to tear things down and live in a perpetual state of protest. I need to build. A perpetual screaming into the void destroys your ingenuity, erodes your soul, while hopelessness becomes a contagious nihilism. Additionally, I have found the medical freedom movement to enter the “eat each other” stage of divide and conquer and its becoming an unproductive time sink for me.

nailed it in this post.

One afternoon, someone asked me a question about lagging strand synthesis and this made me realize most of the patents I was awarded for SOLiD sequencing are now open source and after 20 years there are so many better ways to improve upon this method with new enzymes, better detection methods, and pretty much every proprietary reagent we relied on back then, now over the counter and available by multiple competitive vendors.

As I watched the 2026 AGBT presentations roll out I was struck at how the price declines in DNA sequencing came to screeching halt after the SOLiD Hitachi plant was taken out by the Tsunami in Japan. At this point Life Tech was forced to go all in on Ion Torrent with hopes of it giving Illumina a run for its money. It fit a niche and had its own remarkable achievements with brilliant people pushing it to the extremes but for a decade Illumina held a near monopoly and price declines didn’t materialize.

Now some of Illumina patents are also expiring and this has opened the door for 2 promising SOLiD/ILMN like competitors to enter the market. Element Bio and Ultima Genomics have come to market with their own cheaper versions of Sequencing by Synthesis and prices are beginning to fall again. Ultima Genomics looks like FISSEQ on beads deposited on circular wafers. Think sequencing on a 30 tray CD player.

Element did something very clever and instead of relying on a single fluorophore per base, created avidity tags that allow them to decorate 5-10 fluorophores per base and improve signal to noise.

While Oxford Nanopore and PacBio have made groundbreaking advancements on Long reads, 80% of the market doesn’t need these as they are working with fragmented DNA in FFPE or liquid biopsies. For most human genomics markets, high read count matters more than the long reads that dominate the smaller de novo sequencing market. The market seems to have settled on 2X150 base pair reads being sufficient for most applications and while several companies offer more expensive 2x300bp reads, they are rarely run as often the DNA is shorter than this or the improvements don’t justify the longer run times or sequencing costs.

Now the entire competitive race appears to have shifted back to accuracy. Q30 reads to Q40 reads are now the race.

As of this date no sequencer has matched the accuracy of SOLiD. This was largely due to its use of ligases that don’t incorporate a single base but 5 bases at time so very interesting error correction codes could be engineered into the dye read out strategy. SOLiD just suffered from Short reads (75bp)…. 20 Years ago.

If you are into Galois fields and Claude Shannon like error correction in DNA sequencing this is a good place to start but this unique system saw the the first next gen sequencing data that was capable of sensing 1 in a million polymerase errors. A 2x150 sequencer with SOLiD like accuracy would be the ideal combination today.

The new sequencing method we are exploring certainly shares many of these themes with SOLiD and may in fact turn out to be an excellent approach for Next Gen sequencers we’ve brought to market before but that is not our immediate focus.

There is a gap in the sequencing market that often leaves people overly trusting qPCR data. In many ways this plagued the COVID era as the Drosten PCR approach failed to perform this level of validation before sparking a public panic with false positive C19 PCR assays that had no internal controls and many errors in their primer sequences. I’m not a virus denier and I use qPCR everyday but qPCR can easily lead to over confidence in conclusions if you don’t sequence validate what you amplify and now we find ourselves in a world were a few shoddy qPCR asssays can lead to global lockdowns, culling of millions of animals and vaccines heavily contaminated with DNA as regulators never scrutinize the veracity of the qPCR results being produced by their sponsors.

For this reason, many people, including the inventor of PCR , Kary Mullis, prefer qPCR data be sequence validated before screaming “Pandemic”.

But this step often gets skipped as NextGen sequencers cost over $1000 to run. They certainly deliver an enormous amount of data for this $1000 but it is CostCo like batch economics. You achieve low cost by buying in bulk and dropping $1000 on every $10 PCR amplicon makes no sense. You need to barcode these samples and pool them with others PCR Products to multiplex them on these large volume sequencers to make any economic sense. This batching process ultimately delays turn around time as you wait for enough sample pools to make these expensive runs make economic sense.

Sanger sequencing often fills this niche. It’s a $billion a year market, still growing 3%/year but there are only ~50,000 Sanger instruments globally. They are $50-$150K per instrument and require weekly watering to prevent the Capillaries from drying out. As result they tend to be centralized in facilities and require shipment to these facilities to run single amplicons. Usually a 48 hour Turn Around Time and $10-$20/read after shipping is included.

Oxford Nanopore (ONT) looked like a nice solution to this application space with their $90 Flongles but even these need 10 amplicons barcoded to get the costs below $20/sample. Libraries need to be made and pooled to make the chip costs get close to Sanger sequencing. The library construction and barcoding costs bring in another ~$20 per sample and this becomes cost prohibitive unless you need deep sequencing data for each amplicon. Most dont need this level read depth to verify an amplicon.

Very recently they replaced the CEO of ONT and now the lower throughput/lower cost P2S platforms are being sunsetted due to the high support costs of the lower throughput markets.

Our solution to this market gap is a method than can run on the 500,000 -1M qPCR instruments already in the field post COVID and only require a small liquid handling robot to automate the methods.

The patent application has been filed but the exact details I will reserve for a later post when we have more data in hand. At the moment, we have several specialty reagents being synthesized to get this proof of concept nailed down.

We can see this being helpful in many markets where a sample is PCR positive but people want sequence confirmation of the amplicon to speciate it in an afternoon. Given the chemistry behaves on single amplicons, it is entirely congruent with running in massively parallel systems we have designed before only with longer readlengths and some of the error correction capabilities built in.

The NextGen market isn’t our immediate focus as we want something to address our current customer base using qPCR in the Cannabis, Food and Supplement testing space. The capacity to sequence a PCR amplicon in an afternoon without any additional equipment other than the qPCR instrument already in place and a liquid handler most labs already have, would certainly change our lab and very likely many others.

Stay tuned. As this develops, I’ll be certain to keep this audience apprised of the Journey.

Comes a time when the blind-man takes your hand, says "Don't you see?
Gotta make it somehow on the dreams you still believe.” Don’t give it up, you got an empty cup only love can fill. Only love can fill.

This paper appeared on BioRXiV on Jan 25 2026

Recall this is the preprint server funded by Zuck Bucks that refused to host our RNA:DNA hybrid paper that is now published and Peer Reviewed.

I’m going to bet this Moderna preprint will get hustled through one of the top Journals despite a glaring smoke grenade in the paper.

The parlor trick rests on the public not being very attentive to Avogadro’s number.

They of course can’t resist opening up their Introduction with how well validated these vaccines are based on the regulatory shortcuts, mandates and liability waivers they all leveraged.

They go on to proclaim that if Biodistribution for LNPs can be validated with one drug substance, they can be assumed safe for all drugs using LNPs! This “Bridging across products” language is code for, once established for one vaccine, we can swap out the payload for mRNA coding for hyper-toxic peptides and superimpose prior vaccine acceptance for future ones. The vaccine industry loves these types of illusions where one vaccine is tested against a different vaccine as placebos are “Unethical”.

If you want to follow where my head is going on this dangerous loop hole, Just ask any AI system what are the most toxic peptides ever cloned into plasmids? Most won’t answer you as you might be a bioterrorist but there are far more toxic peptides than spike that could be snuck into such an assumed safety “platform” argument. Shiga toxin, conotoxins, botox and many of the fungal peptides (Amaitins from the death cap mushroom) that cause imminent death. I’m not going to expand on this as Substack is showing signs of being compromised. has recently posted on her page being Age gated and ID required for her to log back into her account. This happened once she entered Australia and remains after her departure.

Gemini short circuits if you ask it about toxic peptides. A bit shortsighted given the popularity in OTC peptide therapies these days and how easy it is to find these far more dangerous peptides already cloned into plasmids in literature in PubMed

Their results section begins with a bold conclusion.

But this is the sentence that begins the Parlor Trick.

Just looking in the Serum is one parlor trick (they do mention other tissues in their tables but this should be further scrutinized)… but it gets worse.

Here they try to claim prior studies picking up spike protein 200-700 days are flawed and picking up C19 spike despite those papers addressing this? While they try to claim the life cycle of CD16+ monocytes is too short for this to occur, they do not address immuno-privileged stems cells that could be the transfected source of these cells. There tomes of other papers that also find persistence but they ignore all of these (Ota, Hanna, Roltgen, Krauson, Gonzalez, Castruita, Hulscher)

This is where the paper goes straight off the rails.

The most sensitive analytical methods for detecting RNA? Really?

0.00085ng/ml or per gram is horribly insensitive.

Check for yourself at the NEB ssRNA mass to mole converter. The mRNA is 4284 bases in length and at 0.00085 ng/ml being the lowest point on their standard curve sits at 3.728 X 10^5 molecules.

372,800 copies is their detection floor for RT-qPCR!

We’ll this is embarrassingly broken by the Moderna authors. Having made HIV detection kits while at Beckman Coulter… You need get to 50 copies/ml or you can’t get into the market. Maybe they should rename this bDNA assay of their as BrailleDNA assay?

Gemini review lines up with this.

I’m not an expert on the spike protein assays so take Gemini with a grain of salt here. Some slop could exist in this number depending on trimer state of spike and glycosylation status but this is likely to only change the number ~10 fold.

You’ll also note the paper has no RT-qPCR primers or PCR conditions! Just makes claims of sensitivity while trying to snow the readers with many leading zeros on a nanogram number.

0.00085 ng/ml looks really low right? Convert these nanograms to molecules and the emperor has no clothes.

Without any disclosed qPCR methods nor clarity on how they convert CT scores to mRNA molecules, the entire paper is a “Trust Me Bro, I’m from Moderna” advertisement dressed up as a real paper.

Of course, BioRXiV has no problem hosting this garbage as it fits their woke narrative. Papers with far more transparency and rigor get blackballed from the site.

You’ll note, our methods for detection of DNA in Moderna vaccines have CT scores, triplicate testing, 3 different targets, 3 different dilutions (27 qPCR tests per sample) Standard Curves present, transparent equations for conversion, orthogonal methods like Fluorometry and Oxford Nanopore Sequencing, nuclease controls….. etc all public while they claim it’s “not validated”. BioRXIV declined to host this paper on their preprint server.

Granted this Moderna advertisement is only a preprint but when the PrePrint servers start censoring submissions, peer review is grotesquely captured to manufacture a narrative.

This capture also exists with post publication mobs like Retraction Watch and PubSmear. This week we came to learn that the Arnold Foundation who funds these two Pharma hitsquads, have funders who are “Close Friends” of Jeffrey Epstein. Laura and John Arnold are listed in the contact map as “Close Friends”. I don’t know what to make of that connection?

This is straight from the DOJ website. I can’t vouch for the fidelity of this tie as people have found documents in there that looked modified like the SpaceX logo clearly photoshopped onto a victim, likely for political purposes.

But when you consider we have seen this same Peer review capture act before with the same people, the connections tin foil starts to fade.

You merely need to understand the history of Peer Review, Robert Maxwell and Pergamon Press.

Ghislaines father, Robert Maxwell, ran a scientific influencer control circuit much like Jeffrey. If you control Peer Review, you control policy. If you control policy, you can get liability free products mandated…. All with the illusion of safety and 95% pure squid ink when people start asking about accountability.

I was asked my thoughts about this preprint paper.

It should be known that I am biased. I’ve worked with these authors before and have deep respect for the risk they are taking doing this work and how hard it is to get it done.

I’m going to limit my comments to my speciality of DNA and RNA detection as I think we can learn a few things as a community on how to interpret data like this. I have not scrutinized the complete paper yet. I focused in on the questions people asked of me.

First thing everyone has to appreciate when looking at PCR of Spike in a human background is that Pfizer and Moderna codon optimized their Spike sequence and did so very recklessly.

If you take the Pfizer Spike sequence and BLAT it against the human genome you can find many regions in the vaccine that map 100% to the Human genome for short 20-47bp spans. This means primers that perfectly amplify vaccine vials, may cross react with human DNA and cause false positive PCR signals when human DNA is in the background. They may be clean in vaccine positive controls but produce unexpected bands once applied to human DNA looking for vaccine DNA.

This alone should scare the shit out you as there is something known as RNA interference that will process mRNA like this and down regulate the genes that have homology to this spike sequence. It requires about 20-22bp to trigger.

I have a whole thread on this mess here:

Some of these sequences are perfect hits to OMIM genes involved in Spermatogenic failure and we have evidence of that actually happening in the vaccinated.

OMIM genes are the genes best nailed down to be causative of disease.

To make matters worse, several of the hits in the BLAT table above are to genes expressed in testis.

The viral spike doesn’t have this homology. Its purely a product of Pfizer “codon optimization”.

Many of these studies looking at sperm motility/count obscure this signal by mixing Moderna and Pfizer patients but if you only look at Pfizer, which uniquely has this homology, you can find the problem in Gat et al.

So you need to take the primers used in any paper like this and run them through NCBI-primer BLAST against the Human genome and human transcripts.

It’s important to use the Primer-BLAST tool. If you just BLAST primers as single sequences, you will get lots of short hits to such a large genome but the only hits that matter are when both primers are in close proximity in the genome as PCR doesnt work across chromosomes and is usually limited to under 4kb. With perfect conditions, you get ~20kb to amplify with very specific enzymes and primer design.

Many people took the simple BLAST shortcut to attack the last paper that found this as these people have zero experience making PCR assays.

The NCBI-Primer BLAST takes into consideration the orientation and distance of each primer to give you a better sense if the amplicons are possible.

For example, here is one of Hulschers Spike assays. It can make a 102 bp amplicon on Human DNA if you allow for 3 mismatches in each primer. The 1224bp amplicon, Im less concerned about as their bands on the gel dont imply this is happening.

One limitation of the study is that they are not using qPCR which requires 3 primers to all be properly arranged and it gives you a quantitative framework. Primers that amplify at CT 35 in human are less convincing than primers that fire off at a CT of 25 (1000 fold more signal).

So when you have just bands on a gel, where the cycling conditions are not specified, you have to sanger sequence them to confirm. They did this for the Ori primers and they match Pfizer but there doesnt appear to be spike or SV40 Sanger confirmation.

Ori is its own worst enemy. This sequence contaminates nearly all PCR polymerase kits as the polymerases are usually expressed in E.coli with a plasmid that contains this Ori so its a well known Kitome contaminant. These kitome contaminants usually only light up after CT 30 but we dont have this information from the Hulscher paper.

They rightly don’t make bold claims about Ori amplification and acknowledge it could have different sources.

I think the most compelling figure in the paper is 6B.

When you see 6 amplicons all popping up in the tissue but not that negative control, it becomes harder to believe these are all off target as I cant find off target hits for S1 or S3 primers using NCBI-Primer BLAST tool.

The Ori, SV40 and S2 primers I can find some human primer hits, albeit with mismatches and which need further scrutiny as NCBIs human genome is often contaminated with these vector sequences which are from the sequencing vectors people use in sequencing projects. They are mislabelled as part of human cDNAs because those cDNAs were sequenced from plasmids which contained those sequences and they were not fully removed from the database. I have not done this level of forensics as Figure 6B looks to have all 6 amplifying, albeit at very different intensities but of the expected size seen in the positive controls. Given all of the other clinical data they have corroborating spike expression, this is likely real.

It would help if they better described their negative controls? Are they water or are they human DNA pre-pandemic? The methods section on the PCR conditions needs more detail. How many cycles etc…

You will likely see the typical critiques of the paper where some newb just BLASTs a single primer and gets human hits like this and declares “FRAUD”. US Mortality beclowned himself once like this before.

Ignore these attention seeking amateurs. They don’t understand the primers need to match on the 3’ ends and be pointed at each other <4kb apart for any amplification to actually occur. The paper they critiqued claimed to have sanger confirmed the amplicons such that these critiques were shallow gotcha’s. That paper was mysteriously taken down and was by no means perfect but the primer concerns raised were shallow single BLASTs like seen below. One 15bp homology or even two on different chromosomes are irrelevant. Not ideal but not fatal.

If the critique comes from the PubSmear mob..

Just remind them that their funders (Arnold Foundation) are Close Friends with Jeffrey Epstein and they should pack their bags. No one should trust them anymore.

You read that correctly. The Epstein docs are live and there is a contact map published that has John and Laura Arnold as “Close Friends” of the Epstein mob. And its is no surprise we can see emails inside that network planning for Pandemics to capitalize on them. I’ve seen many super hero vs villains films and none of the movies had villains this evil or bereft of ethics. Truth is stranger than fiction.

This is a case where you have to take on the totality of evidence. They have Spike protein detected years later and some evidence of mRNA and plasmid DNA in particular cells or tissues of interest. Also gene expression changes and multiple labs confirming this. Anyone datapoint you might be able to contest but all them together make a pretty compelling story. This is a preprint. Its likely to clarify some of these details in final publication but important to get out ASAP.

It would be very interesting to see if their RNA-Seq data supports the pathways we expect to be dysregulated by these contaminants (cGAS-STING, IL-10, RIG-1, TLR7/8/9) recently highlighted in substack on this.

Malone News

Universal Repeated mRNA Boosting Was (and is) Bad Policy

Universal Repeated mRNA Boosting Was (and is) Bad Policy…

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7 months ago · 125 likes · 28 comments · Dr. Robert W. Malone

If I were reviewing this, I’d suggest

1)Better describe the NTCs? Are these water or pre-pandemic human negatives. How do these primers behave on Corielle human pre-pandemic DNA controls like NA12878?

2)Better disclosure on PCR cycles, conditions etc.

3)Might want to use DNaseI-XT for your RT-PCR as DNaseI doesnt process the spike DNA very well (McKernan et al). Not critical for publication but maybe for future work.

4)Any Sanger data on Spike S1, S2, S3? Bands are dim but perhaps nested PCR can rescue these?

5)Perhaps supplement disclosure of the NCBI Primer-BLAST hits for the primers. I’ve run all 6 through and they don’t look as bad as what might occur when someone just single primer BLASTs these primers.

6)Don’t be afraid to self cite. The Kammerer et al paper is critical context for this. The SV40 cell passaging work adds to the credibility of this observation. PubSmear loves to critique on this axis but they are just wrong in this case.

Some of the parameters used in NCBI Primer-BLAST

Our paper on RNA:DNA hybrids is now peer reviewed.

This weekend I zipped out to Park City Utah to catch up with some friends and family and fortunately Jess already covered this topic so this will be brief.

Unacceptable Jessica

RNA:DNA Hybrids Survive Digestion in mRNA Vaccine Manufacturing

First things first…

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7 months ago · 156 likes · 35 comments · Jessica Rose

I thought I’d share a few of the low wattage responses to the paper. Note the Jab, Mask and Ukraine flag in Bio helping to virtue signal this persons “in-tribe”.

When they exhaust their Appeal to Authority arguments, they send in the real piconeurons to deliver additional Associative Fallacies.

When associate fallacies are expired, toss in some receipt-less ad-hominems to see if those stick.

I’m getting the sense, we’re down to the 3rd string bench members from team mutton.

We are 5 years into this and we have MDs who still rely on “Journal prestige” Appeals to Authority to spoon feed them the truth. They still have not learned their lesson from Proximal Origins (Nature), Surgisphere (Lancet), and Bangledesh mask studies (Science) that claimed effectiveness when the P values for the color of mask was more significant than for those who wore them. All “top tier” Journals with top tier fraud left spotless from the PubSmear mob,

Put aside the 3 logical fallacies, read the paper and decide for yourself. The failure for doctors like this to actually have an ounce of intellectual self reliance is what led to the COVID disaster. They are great at reciting what they are told to memorize but never once question the hierarchy they paid a 1/3rd of their life praying to.

One of the reasons for this Journal selection is that the editors are very familiar with the games being played by PubSmear and we wanted to demonstrate to the world how quickly the process would proceed if we were not faced with Gatekeeping from Journals that have Pharma funding.

Recall Speicher et al was desk rejected 5 times and there was nearly a 2 year gap from experiment to final appearance in Autoimmunity. It kills me to think of how many people were injected in this time frame having heard the DNA story was anti-vax fake news that wasn’t peer reviewed.

We started the experiments for the RNA:DNA hybrid paper on Veterans Day in November of 2025.

We submitted this to JIM over Thanksgiving and a few days later we got permission from JIM to put it on BioRXIV who proceeded to sit on it for 8 days only to censor it.

Ironically, we got our acceptance at JIM (with edits) on the same day, woke BioRxiv censored it.

This likely would have been published over Christmas if it were not for everyones Holiday travel schedule but here it is in mid January.

So when Science is not being reviewed by wing nut reviewers like the one you see below, It can proceed at a rapid pace.

And the reason you are seeing logical fallacies as the only retort is that the paper actually agrees with BioNtechs own paper on the topic (Lenk et al) and Moderna’s patent estate. To attack the conclusions of the paper will lead them to taking down their holy vaccine manufacturers work. That is correct. Lenk et al from BioNtech published that RNA:DNA hybrids reduce DNaseI activity 100 fold citing a paper from 1997 (Sutton et al). This is exactly what we see.

For some reason Taylor and Francis thought this person (Rolf) would make a great reviewer for the Speicher paper? They didn’t see issue with his DFG funding? They didn’t recognize that our paper directly critiqued his work and he should have recused himself from trying to bury a paper that highlights his own flaws through an anonymous curtain.

They didn’t recognize that Rolf exhibited the same backhanded behavior with Konig et al.

When he gets called out for a fair and open debate, he cheats and runs.

He’s not very IT savvy. In his review, he complained about not being able to unzip the VAERs file!

And when he tried to leak his Review of our paper to Retraction Watch, he only leaked his side of the argument and omitted our responses which traversed his critiques and satisfied the Journal. Unfortunately, for IT illiterate Rolf, he didn’t realize the author (him) of the ‘leaked anon review’ was recorded in the PDF metadata and he got exposed. So his violation of the Journals confidentiality agreement and COPE guidelines was now pinned on him.

This was reported to his university and I’m sure they are thrilled for him as they certainly don’t want to stop the flow of vax money into their institution.

He also managed to get Retraction Watch to publish a false headline. Retraction Watch claims he rejected the paper and in their own article (that leads with such a false title) it has a quote from the Journals Editor refuting this statement. Rolf approved the manuscript with edits and they have that on record. The curtains don’t match the rug. Their headline should be retracted as their own article refutes it.

More sober minds on the problem below.

https://www.francesoir.fr/videos-les-debriefings-videos-english/vaccines-cancer-and-academic-freedom-prof-wafik-el-deiry

A few observant readers may have felt relieved by the recent RNA:DNA hybrid paper we published as this shows the KAN gene and the plasmid vector must get degraded 100 fold more readily than spike and thus the SV40 DNA should also be 100 fold lower than Spike. This would be great news as we don’t want billions of copies of SV40 Promoters in every dose.

I’m sorry to be the bearer of bad news but that is not what our qPCR data is demonstrating and I think we have identified the mechanism

In all qPCR studies to date, the SV40 assays have the highest contaminating DNA content in the vaccines and these are NOT expected to have RNA:DNA hybrids so something else is protecting these region from DNaseI digestion.

The answer lies in a Dental Biofilm study.

I never thought I’d find Dental Biofilms beautiful but how can you resist!

What is fascinating about this study is that they quantitate how poorly DNaseI digests G4 DNA.

97% of it remains!

Keep in mind, the codon optimizations introduced many G4s into the spike sequences so those are protected by both RNA:DNA hybrids and G4s!

The authors go on to use micrococcal nuclease which is a bitch of an enzyme as it digests both single and double stranded RNA and DNA down to single nucleotides and doesnt heat kill.

They even try this in vivo

Surprisingly, they find chloroquine stimulates DNaseI to do a better Job! Are you so thankful for PubSmear burying the benefits of Chloroquine and its hydroxylated derivative!

If you haven’t connected the dots, Plug the SV40 promoter sequence into QGRS mapper.

>SV40 Promoter

CCTGAGGCGGAAAGAACCAGCTGTGGAATGTGTGTCAGTTAGGGTGTGGAAAGTCCCCAGGCTCCCCAGCAGGCAGAAGTATGCAAAGCATGCATCTCAATTAGTCAGCAACCAGGTGTGGAAAGTCCCCAGGCTCCCCAGCAGGCAGAAGTATGCAAAGCATGCATCTCAATTAGTCAGCAACCATAGTCCCGCCCCTAACTCCGCCCATCCCGCCCCTAACTCCGCCCAGTTCCGCCCATTCTCCGCCCCATGGCTGACTAATTTTTTTTATTTATGCAGAGGCCGAGGCCGCCTCGGCCTCTGAGCTATTCCAGAAGTAGTGAGGAGGCTTTTTTGGAGGCCTAGGCTTTTGCAAAGATCGATCAAGAGACAGGATGAGGATCGTTTCGC

It should look something like this…

And give you something like this…

That’s 5 very stable (above G-Score 10) G4s in the SV40 promoter!

Combine this with the fact that the SV40 promoter has a 72bp directed repeat that can hairpin on itself and we have a DNA knot that can’t be processed with DNaseI.

This explains why SV40 also Persists! Thank you Pfizer. You have a vaccine perfectly designed to not degrade the most dangerous parts of your plasmid.

You should hire a new Enzyme team. This is getting really embarrassing.

There has been ample drama on X over Anon accounts on both sides of any given scientific debate. This article attempts to address this in the context of verification and bias… with a few concepts from the cryptography field that can help address these problems. It will also explore a few examples where Anon publishing is a required feature of any society currently engaged in censorship and Orwellian activity related to the freedom of speech and freedom of inquiry.

Science is a not a conclusion, nor is it ever “settled”. Science is a verb which starts with falsifying a hypothesis. The seed of science is a question and attempting to falsify or confirm the question. Thus, when you see PubSmear attacking hypothesis papers (Hazan et al), under the banner of “Scientific Integrity” you have an anti-science mob masquerading as the saviors of science.

Currently, most Peer Review is single blinded. The authors are known and the reviewers Anon. However, reviewers are not random. They are selected by an Oracle or Journal editorial team as being experts in the field. While conflict of interest screening is performed, it’s often lackluster. In stark contrast to this, post publication review platforms like PubSmear are often non-experts in the field with zero conflict of interest screening. This asymmetry undermines progress in validating work.

Much of the consternation over PubSmear stems from multiple asymmetries of the attacks.

Authors spend an enormous amount of time and money getting their research published with their reputations on the table, methods disclosed, and conflicts revealed. Yet an Anon troll on PubSmear can slander the work with zero methods section, conflict review or reputational risk if proven to be sloppy or even fraudulent.

There are many examples of complaints from PubSmear being erroneous themselves. It has also become a platform to sell PubSmear software like ImageTwin to Journals. The CEO of this software company is known to frequently comment on papers on PubSmear to pump the validity of their tool. No False Positive or False Negative rate is published for this software and its not open source. Follow for a deeper dive on this. has documented much of the fallacious activity on the platform.

There are people in PubSmear known to have multiple aliases. When one alias begins to acquire a reputation for slop, they can launder their future complaints through a second, third and forth alias, thus enabling a Sybil attack on the work.

In any system that has high energy required for publication but little to no energy to retract, science that goes against the narrative or incumbent economic interests will not survive.

This is an information theory topic that relates to email and spam on the internet. To the extent email is free, spam can outnumber signal. Adam Back addressed this problem in his famous HashCash invention where some CPU time was required to hash an email. This is a hard to compute, but easy to verify algorithm.

Sending one email would cost 1 second of CPU to compute and a microsecond to verify…. but sending 100,000 emails would come at a cost. These principles are embedded into Bitcoins hashing functions and cited in Satoshi Nakamoto’s seminal work on Bitcoin.

What we have in PubSmear is the opposite of this. The cost to publish the paper is high and the cost to retract or eliminate this block of work is near-nothing.

This is one reason, most seasoned scientists do not place any faith in a single peer review process but instead look for independent replication from people with different financial conflicts before they consider a piece of work confirmed. They also know to ignore retractions if the editors have illogical reasons for doing such.

Naturally, PubSmear-like organizations attract commercial interests like a moth to a flame as they are ideal hitmen for hire to keep the narrative of smoking being safe, vaccines being glorious and ivermectin being horse dewormer. PubSmear defended Proximal Origins and Surgisphere while attacking generic drug use like HCQ/Didier Raoult, and IVM/Hazan, Kory, McCullough, Rose etc. Their members cheered on locking down your children and masking todlers and most viciously attack papers related to Covid Vaccine risks. Some members are notorious for using AI fabrications of admittedly erroneous reports to Journals to promote retraction. Others even use their mobs power as a vindictive threat against their perceived ‘Anti-vaxxer’ opponents.

This is one reason the moniker “Pick up a pipette or STFU” lands. The original work is always more work to pioneer but less cost to validate. Unless you are actively replicating the methods, your critiques are usually superficial with minimal skin in the game.

At the same time Anon authors have contributed greatly to the world but they are not allowed to publish in todays academic world. This is the paradox of the current publishing system. They will not allow anon submission but they will accept anon criticism. This is in a world where many journals are paradoxically experimenting with double blind review to avoid vendetta based reviews and academic chicanery.

You may be skeptical of Anon contributions to science but I merely need to point you to Satoshi Nakamoto and Bitcoin to prove the point. You may not be a bitcoiner, but you cannot deny the fact that it became a $2T asset in 15 years and outpaced the internet, Google, NVIDIA and Next Gen sequencing in terms of its growth rate. It has no CEO, no marketing budget and is entirely an organic project that spread virally from a single Whitepaper published by an Anon author on 10.31.2009.

In my mind, this might be the single most important invention for human flourishing and peace around the world. That is a longer discussion I will reserve for a future article, but it does beg the question that if our formal Scientific process for publishing can’t capture this then it is unfit to exist.

This asymmetry is against evolutionary principles.

DNA has a similar proof of work system as HashCash and Bitcoin. In order for you to replicate DNA, you must consume dATP. This isn’t some indirect energy consumption. The fuel of the cell (ATP) is literally written into the code of DNA and RNA (A in A,T,C,G is dATP). In other words, you need to consume energy to propagate information worth transmitting through time. Without this, genetic spam emerges and signal from noise has no selective force.

Hits Home

I experienced this myself back in 2016. I sequenced the genome of Psilocybe cubensis otherwise known as the magic mushroom. This fungi expresses Psilocybin, which has recently been given break through designation by the FDA for drug resistant depression.

It is also one of the most promising compounds for expanding cellular lifespan.

Despite this, the fruiting bodies of this were illegal at the time. Fortunately, spores and DNA were not illegal leaving a small loop hole to get this done in a legal grey zone.

At the time, my father was fighting prostate cancer. We had sequenced his tumors and found BRAF-K601E variants in the tumors. These called for AKT1 inhibitors. None existed. We could experiment with some small N number trials of new drugs or look outside the permission slipped drugs.

Fortunately Cannabinoids are potent AKT1 inhibitors and we soon found an Ethanol extraction of a 1:1 CBD:THC Jamaican Lion cultivar that his Tumors responded to. His PSA dropped from 150→6 in a few months and he began to recover.

This AKT1 pathway also plays a role in cannabinoids and C19

But I was exposed. The medical cannabis markets in Massachusetts at the time were poorly regulated. Aspergillus contamination and pesticide contamination were common in the dispensary system. I knew enough about the intricacies of that early market, that I couldn’t trust it. I had to grow this strain in my basement and perform all the ethanol extraction and QC myself.

Publishing the Psilocybe genome with my name on it, at that time, could get me a visit from the authorities and shut down my fathers access to a therapy that was working.

So I looked around for Journals that would take anon data.

Journals- Nope

NCBI- Nope

MAPS- Yes.. but they had no expertise to validate it so No.

PrePrint Servers- Nope

WikiLeaks- Yes.. but they had no expertise to validate it so No.

I turned to various Crypto related projects like IPFS, Alexandria.io and Open Bazaar.

Alexandria went under and I’m not certain it even circulates on Open Bazaar anymore as that site isn’t indexed by google so to the extent it exists there, no one can find it.

In 2019, my father required an new MRI compliant pacemaker for better tracking of the progress of his disease and to manage this surgery we decided to ween him off of cannabinoids for fear of Drug-Drug-Interactions (DDI) with conventional anesthesia.

By this time he had reduced his cannabis oil consumption to a maintenance dose which we were guessing at by judging what ever dose just made his quality of life the best. Use your body as the bioassay for proper dose as we were in uncharted territory.

He made it through the surgery but his nausea and cachexia came screaming back and the hospital had nothing in their repertoire to get it under control. Some angel-like nurses actually listened to us when we told them what actually works. They left the room and turned a blind eye while we gave him the Cannabinoid oils. He walked out of there 40 minutes later, only after the nurses took pictures of the vials we were using. By this time we had migrated to oils from Myriam’s Hope as they had CBG, CBGA, CBDA and CBA oils and we could mimmic the extract I made with commercial oils from QC vendors we trusted. After this weening and reapplication of cannabinoids he never quite felt the same.

At this point we began sequencing his blood stream to monitor circulating tumor DNA to track the BRAF K601E variant in the blood with Foundation Medicine and JHU.

I was familiar with this approach as we took the cover of Science Translational medicine with JHU back in 2010 pioneering the method. 8 years later it was commercial grade.

Throughout this effort, a ctDNA P53 mutation emerged and this put DFCI into high alert who encouraged more aggressive radiation and even experimental PD-L1 inhibitors.

Unfortunately for our father, the clinical trial accidentally injected an undiluted 10X concentration of the drug and his veins/arteries turned into napalm tubes. An absolute torture chamber he never quite recovered from. Soon after this thrombocytopenia set in and more and more desperate radiology was utilized until he eventually succumbed to the disease.

This was just before the C19 pandemic and we are thankful none of this occurred during the pandemic as he would have been left to die alone with this torture.

We were lucky in may regards. With stage 4 prostate and Mets to the bone, our father never needed a Morphine drip or a single opiate. He had 4 years of relatively good lifestyle with cannabinoids and may have lasted longer if we didn’t succumb to the escalating fear campaign over his P53 mutation. I wish we explored IVM, Fenben and other safer drugs before rushing into these experimental immuno therapies as the impact of cannabinoids on these drugs was unknown but we suspect not congruent based on the immuno-modulatory aspects of CBD.

Year Later

Nevertheless, after this episode I was determined to get the Psilocybe genome published properly and resequenced it with PacBio HiFi and Phase Genomics HiC to make a better reference genome and followed that up with 81 more genomes performed on Illumina.

Even in this exercise we faced gatekeeping. The reviewers of the 81 genomes paper had competing papers and behaved like woke children. They tossed sand in the gears of our paper while asking for very particular ITS sequences from us. During this prolonged review they published an ITS Psilocybe paper of their own while they suffocated our paper in the review process. They did not cite our paper in this new publication of theirs and they are on record in the open review asking for these very ITS sequences that could inform their paper.

The peer review process was interesting for this journal as they experimented with having the reviewers put their names on the review but authors were not allowed to contact the reviewers to harass or collude with them outside of the review process.

All of our protest over this academic malfeasance had to be laundered through the Editors who seemed exhausted by the drama. In an act of hilarious karma, a few years pass and the authors reach out to gain access to the sequencing data in the paper they rejected. This opened the door for me to tell them to GFY. They had access from the review and chose to reject the paper. If they believe its valuable, they should un-reject the paper. Otherwise the genome remained public on our website and they were free to download them but we would not be spoon feeding them any additional details.

We documented all of this nonsense below.

When you read through their protests of our paper in the now public reviews, their main critique is that we didn’t get the samples from the approved biobanks and thus the paper was invalid.

We got our samples from the vendors that are selling spores online thus these are the strains being used in the commercial Psilocybe market. The Museum specimens they demanded we use, only they had access to (due to being at an Institution) and no one in the market gives two shits about them as they are historical and not consumed in the market place.

Some of this occurred on the Cannabis genome as well back in 2011. In the US, we would have needed a DEA license and Cannabis from U.Miss to sequence its genome legally. We knew this permission slipping would take years, so instead we set up a BV in Holland and engineered a DNA purification system that could fit in our luggage. We purified the DNA in the Dylan Hotel, Amsterdam and sent that out for sequencing.

Knowing the journals would frown upon this, we just put the sequence public on an Amazon instance on 8.18.2011. We eventually put it all into NCBI.

This is where Institutional bias occurs and you simply need to ask any of the people recently excommunicated from their Institutions over C19 and vax insanity what this does to your publication and scientific career.

Suddenly journals start desk rejecting your work as the authors are not affiliated with an Institution that can slap their hand if they step out of line. Byram, Speicher, Jess Rose can all relate to this.

Consider how early was on the myocarditis story and how the Bik mob attacked this work and likely led thousands of more kids to myocarditis slaughter.

This leads us to this fiasco.

Author discovers a cervical cancer risk in HPV vaccines. Has credible threats of harm if he/she publishes with his/her name. To satisfy Journals demands of having a name and institution during submission, he makes one up.

Perhaps not the best plan but the paper turns out to be valid! It was nonetheless, retracted on the basis of his deception to get through the Journal filters.

The Journals will have none of this despite the cancer risk they are burying. This is the largest tell that they are not in the pursuit of truth but in the business of reinforcing the guardrails of their manufactured consent.

In conclusion

We need methods for Anon Science to emerge and perhaps a zero knowledge proof system that can confirm conflicts of interest without revealing them publicly. If the journals were wise they would embrace this. In any system like this we need an Oracle that can verify the conflicts and maintain the privacy in the process. Likewise, digital signatures can help Anon authors sign their work and build credibility over time and eliminate imposters attempting to hijack unearned reputation. This is something X is not very good at and platforms like Nostr that sign every post with user keys are far more credible for Anon content. There is no gatekeeping on Nostr. Anyone can publish. Your Institution is irrelevant but people can verify that the Anon account isn’t an imposter with a modified version of the data.

Everything else the Journals do, would be better done without them in the picture. All of the tools are available for Peer to Peer review and journal disintermediation when authors names are publicly known. The one place a 3rd party might play a role in the future is conflict checking anon work and resting their Oracles reputation on how well the work checks out later.

So the argument isn’t Anon good or Anon bad. It is about how do you build a credit system with conflict of interest inspection/veracity while avoiding sybil attacks when these aspects are needed for controversial science.

Immortalization of data on Bitcoin and Nostr is equally important as we are going to find people use AI to modify papers, circulate spoofed versions, and it will be unknown to the reader unless they have a hash of the file on an immortalized ledger.

Zero Knowledge Proof descriptions below.