Call for Papers & Thematic Issues—Current Microwave Chemistry

With more than 25,000 “open-access, rapid-publication with fake revewers, predatory journals” that have been created, and continue to explode, since about 2012 — you can imagine the difficulty in trying to come up with a new name (and initials that have not already been used) for your newly planned journal. 😊😉

Why so many new journals? The best answer we can give is the example (about seven years ago) of a family of four living in a small flat in Turkey and in one year [offering “reasonable” “page charges” to post your manuscript (on any topic) online] — this “publisher-company” family had “accepted” and published enough papers to clear more than $1 million in profits — just working from laptops in their kitchen…!! (i.e., the best answer is … VERY L-U-C-R-A-T-I-V-E…!!)

So, … the names of new journals can be as similar as Journal of Biological and Immunological Chemistry (JBIC), International Journal of Immunological and Biological Chemistry (IJIBC), World Journal of Biological Immunology (WJBI), World Journal of Biological Immunology and Chemistry (WJBIC), Global Journal of Biological Immunological Chemistry (GJBIC), Journal of Molecular Biology and Chemical Immunology (JMBCI), Zelenskyy Journal of Biology and Immunology in Wartime (ZJBIW) … and … and … [you can catch my drift] — just as long as the title and initials differ from all 25,000 others.

Well, this week Professor Vasiliou received an email request [see below] to “publish his next paper (on any topic)” in the journal of Current Microwave Chemistry (CMC).

We checked and the journal name “Trends in Microwave and Toaster Oven Chemistry” (TMTOC) has already been taken. ☹ Therefore, as a follow-up we are considering the title of a novel journal, “Frontiers in Egg-Beaters, Potato-Peelers and the Kitchen Sink Chemistry” (FEBPPKSC). After checking carefully, the International Committee on Fake Predatory Journals (ICFPJ) has accepted this new journal name as “one not yet taken.” 😉😉😉


Comments continue to pour in — on the topic of the many thousands of predatory open-access (questionably peer-reviewed) journals that have (explodingly) proliferated during this past decade. ☹ Dr. Randolph describes his point of view from the clinical practice of medicine. Fred Guengerich describes his consulting with clients in court, and those judges and lawyers who sometimes rely on “peer-reviewed” publications. Olavi Pelkonen contrasts all these new and untested journals with the older (more reliable/trustworthy) established journals, while John Reichard confirms that the Case Rep Obstetr Gynecol Reprod (CROGR) journal is clearly an example of a predatory journal, compared with Compar Microwave Chem journal (which lies in the grey zone). ☹ 😊

From: Reichard, John
Sent: Saturday, January 21, 2023 4:20 PM
To: Nebert, Daniel
Subject: RE: Call for Papers & Thematic Issues—Current Microwave Chemistry

Dan, I certainly agree that “Case Rep Onstetr Gynecol Reprod (crogr)” is without a doubt a predatory journal. (Reproductive … what??) I wonder about the poor schmucks who are listed on the editorial board. I wonder if they know their names are listed, or if they get paid for “serving,” on the board. I’ve heard of a few instances when Editorial Board members had never even known they were listed for a particular predatory journal!

From: Olavi Pelkonen
Sent: Sunday, January 22, 2023 12:14 AM

Dan, I have not counted (the number I’ve received of) these suspicious requests to publish, because I delete them outright, but it must be >10 per day. Then there are publishers like Frontiers and MDPI (both having headquarters in Switzerland), which publish generally valuable material, but sometimes pretty poorly scientific or biased material (e.g., on endocrine disruptors) gets through and is published. One of the problems of these open-access journals is proliferation of articles that pass the limit of “the least amount of publishable information” and just add to the CV of the authors, which may of course be significant to them, because it will advance their careers in their own countries.
In essence, from the point of view of an individual researcher, the “old respectable” publishing houses and journals are the mainstream sources of useful information — even if they are usually painstakingly slow and methodical in their reviewing routines. ☹


From: Guengerich, Frederick P < Sent: Saturday, January 21, 2023 4:09 PM Dan, there is another issue that you may or may not be aware of. I have done some consulting work on legal cases, mostly patents (one tort), and journal articles get brought in, as “evidence”….. One measure of their reliability (to the judge & other laymen) is whether they are peer-reviewed. Some of these journals at least claim to be, so there is room for trickery here by nasty lawyers. The other side (i.e., me) has to explain why this is a bad journal and can’t be trusted — if possible. Also, the new eLife reviewing plan is really going to create a can of worms, if it catches on. Surely you have heard about this — essentially, this plan eliminates peer review. At least lawyers & judges understand that data (accepted for publication but has not yet been peer-reviewed) in bioRXve is not a real journal — the other side tried this trick in a case I was helping with. F. Peter Guengerich, Ph. D. From: Dave Sent: Saturday, January 21, 2023 3:59 PM Dan, As a practicing physician, I am on the receiving end of “scientific evidence” in journal publications. I have to pull and review articles pertaining to a unique clinical condition, and then assess the validity of the study and conclusions. Recently I had a case of non-Hodgkin lymphoma (NHL) of the parotid gland which the treating oncologist from a very prestigious western university med school declared “was likely work related,” due to a possible benzene exposure. I reviewed the article. First, any substantial benzene exposure was unprovable. Second, there are over 60 types of NHL. Third, the publication addressed only eight of the 64 types — and did not include the rare parotid-associated NHL. Fourth, the patient’s father died of parotid-associated NHL (strongly suggesting a heritable disorder). All “peer-reviewed” and published articles must be cautiously examined. What is in the abstract may not be supported by the actual data. Statistical significance remains important. Everyone wants to pull a fast one, but you know this much better than I do. David Randolph, MD From: Nebert, Daniel Sent: Saturday, January 21, 2023 3:19 PM John Reichard [below] points out that this appears to be a “legitimate” journal, but there are questions about how honest and straightforward their policies are. Doron Lancet [below] laments that “these emails are copious and annoying and these might seem humorous on the surfake, but we should be weeping, rather than doing nothing — because predatory journals are helping drag “high-quality” science into the sewer. I probably receive between 20 and 40 emails PER DAY (most of them in my junk email folder) — ranging in journal topics from mathematics, physics and astronomy to clinical medicine, nursing student education and social sciences. In fact, the latest one [see below] just arrived while I was working on this email response. Note that this CASE REP OBSTET GYNECOL REP (crogr) “invitation to submit a manuscript came on 19 Jan 2023, with a request to submit the paper “on or before 27 Jan 2023,” i.e., eight days(!!) to prepare a manuscript. [This very short turnaround time is one of the factors that determine a predatory journal from a normal scientific journal. Other factors include: [a] shady names of the email server used to send you the email; [b] incorrect usage of English grammar in the email; [c] describing your expertise (in email below, am I an expert in Case Reports in Obstetrics & Gynecology?); [d] check the email server, sometimes it’s simply “gmail” or “yahoo;” and [e] pleading “We are in shortfall by one paper before we can publish the next issue; please help us out…”]. ☹☹ DwN From: CASE REP OBSTET GYNECOL REP Sent: Thursday, January 19, 2023 5:31 PM To: Nebert, Daniel Subject: Issue your expertise work and research Dear Dr. Daniel W Nebert We would be extremely grateful if you would submit your article to Case Reports in Obstetrics, Gynecology & Reproductive. Note that "Eliminated Open Access Charge" will be assured if the article is submitted on or before 27th January 2023. Please submit your files to the mentioned email. Do contact us for further information. Thanks and Regards, Albert Petrov Editorial Assistant From: Doron Lancet Sent: Thursday, January 19, 2023 4:12 PM I laugh, but in fact I should weep. Can’t the Artificial Intelligent (AI) giants find a way to filter all these predatory journals out? ---Doron From: Reichard, John Sent: Thursday, January 19, 2023 11:10 AM Hi Dan: It’s a hokey name for sure, but I think Current Microwave Chemistry it is a proper journal, and I know this is a field of chemistry (e.g., The journal falls under the umbrella of Bentham Science publishing. Under the Guidelines for Authors link, the journal states: “PAGE CHARGES: No page charges will be levied to authors for the publication of their article. However, the authors may decide for some paid-for editorial services such as open access publication and/or a faster overall publication for their article(s). “ [ i.e., it’s like Frontier Airlines, you can pay for upgrades. 🙂 ] Also, this journal is not listed in the most recent list of predatory journals, although it is possible that predatory journal names change as fast as the spoof calls that I get on my cell phone. They also have pretty extensive misconduct and fabrication policies. Impact factor is 3rd quartile per “Web of Science” – not great — but not as bad as I would expect if it was a predatory journal. Speaking only for myself, I usually know where I’m going to publish when I start writing, or at least I do some investigation to check impact factors, etc. as I am writing. So, my question is who is actually responding to emails like the one you forwarded and just so happens to have a spare manuscript lying around to submit? What are the clear telltale signs of a predatory journal, aside from unreasonable publishing costs, short publishing history, and low impact factor? John John F. Reichard, From: Nebert, Daniel Sent: Wednesday, January 18, 2023 3:58 PM From: Vasiliou, Vasilis Sent: Tuesday, January 17, 2023 6:09 PM Subject: Fwd: Call for Papers & Thematic Issues---Current Microwave Chemistry 🤣🤣🤣🤣🤣🤣 Sent from my iPhone Begin forwarded message: From: Current Microwave Chemistry
Date: January 17, 2023 at 9:07:05 PM EST
Subject: Call for Papers & Thematic Issues—Current Microwave Chemistry

(Indexed in Emerging Source Citation Index by Clarivate-ESCI


This is a call for papers & thematic issues for the journal Current Microwave Chemistry (CMIC). The journal is an international peer-reviewed journal that publishes important contributions describing advances in the use of the microwave in the fields of chemistry, biology, medicine, biomedical science, and engineering.
Current Microwave Chemistry is indexed by Emerging Sources Citation Index (ESCI), Chemical Abstracts Service/SciFinder, ChemWeb, Google Scholar, J-Gate, CNKI Scholar, Suweco CZ, EBSCO and Ulrich’s Periodicals Directory.
Submission of an article or abstract may be undertaken through our online system or via email. All submitted manuscripts are peer-reviewed prior to a possible decision on acceptance for publication.
If you are interested in guest editing a thematic issue, then please submit your proposal by return email. Thematic issue proposals should contain title, aims and scope of the theme issue, with the list of contributors (with corresponding authors having preferable h-index 10 or above) and tentative manuscript titles.
Author’s/Guest Editors’ Benefits:

There are no Article Processing Charges.
Articles submitted by March 31st, 2023, will be published as Full Text, without any additional fee.
Quick processing and publication of the submitted papers. Articles will be published online within 40 days of final acceptance.
Guest Editors will receive an honorarium of US$600 per thematic issue organized by them.
Guest Editors will receive a free online access to the contents of the journal for the volume in which their thematic issue will publish.
The corresponding authors will receive a complimentary one-year online subscription to the journal’s volume in which their article is published.
30% discount on the single-issue cost to authors on the purchase of issue(s) in which their article is published.
Multiple issue copies at discounted rates.
In case of your interest in any capacity, please provide us your consent via return email, so that we may guide you further accordingly.
We look forward to receiving your interest in article or thematic issue publication.
Nuzhat Gul
Sr. Editorial Manager
Current Microwave Chemistry

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Machine learning and artificial intelligence in physiologically based pharmacokinetic (PBPK) modeling

Artificial Intelligence (AI) and Machine Learning (ML) are two rapidly advancing fields of research, which will clearly play important roles in gene-environment interactions (GxE), as well as almost every venue of scientific study. Hence, GEITP is introducing this topic here.

AI is a subset of computer science, which seeks to develop machines or computational approaches that can solve various cognitive tasks — at a level similar to (or even exceeding) human intelligence (and by far exceeding the intelligence of politicians).

ML (a subset of AI) applies mathematical or computational algorithms to perform complex tasks by automatically learning from past data or knowledge. Three main types of ML methods include: [a] supervised learning (train a model on known input and output data with the goal to predict new ‘outputs’ based on new ‘inputs’); [b] unsupervised learning (allow the trained model to cluster data in meaningful ways to identify intrinsic patterns or structures based on unknown input and output data relationships); and [c] reinforcement learning (a feedback-based learning approach used to learn optimal actions in an environment to receive the maximum reward).

A new class of ML, called deep learning, enables one to create more complex models with a logic structure similar to the human brain. The ML and deep-learning algorithms establish essential blocking of AI systems; These algorithms provide a data-driven approach to the evaluation of chemical/drug ADME (absorption, distribution, metabolism, and excretion) and toxicity properties.

Physiologically-based pharmacokinetic (PBPK) models are useful tools in drug development and risk assessment of environmental chemicals. PBPK model development requires the collection of species-specific physiological-, and chemical-specific ADME parameters; this can be very time-consuming and expensive. This raises a need to create computational models capable of predicting input parameter values for PBPK models (especially for new compounds). In this review [see attached], authors summarize an emerging paradigm for integrating PBPK modeling with AI- and ML-based computational methods. This paradigm includes three steps: [a] extract time-concentration PK data and/or ADME parameters from publicly available databases; [b] develop AI/ML-based approaches to predict ADME parameters; and [c] incorporate the AI/ML models into PBPK models to predict PK summary statistics (e.g., areas-under-the-curve and maximum plasma concentrations).

Other areas in which AI/ML methodology is starting to be used — are in the fields of population genomics and genome-wide association studies (GWAS). For example, much attention has been paid to the utility of polygenic risk scores (PRS) — which represent the genetic burden of a given trait; the long-term (highly optimistic) plan is to develop strategies for risk-based intervention through lifestyle modification, screening, and drug therapy. A PRS for a given trait is typically defined as “a weighted sum of a set of germline SNVs, in which the weight for each SNV corresponds to an estimate of the strength of association between the SNV and the trait.” But these topics will be covered in future email blogs. 😊


Toxicol Sci Jan 2023; 191: 1-14

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Fusion Breakthrough May Be Game-Changer for Energy

This is really a BIG deal.

Of course, the hydrogen bomb is an example of fusion energy — but it is not “controlled energy” ☹😉

Fusion Breakthrough May Be Game-Changer for Energy

Tuesday, 13 December 2022 11:22 AM EST

Department of Energy Secretary Jennifer Granholm announced a “major scientific breakthrough” Tuesday in the decades-long quest to harness fusion, the energy that powers the sun and stars.

Researchers at the Lawrence Livermore National Laboratory in California for the first time produced more energy in a controlled fusion reaction than was used to ignite it, something called net energy gain, the Energy Department said.

The achievement will pave the way for advancements in national defense and the future of clean power, Granholm and other officials said.

“This is a landmark achievement for the researchers and staff at the National Ignition Facility who have dedicated their careers to seeing fusion ignition become a reality, and this milestone will undoubtedly spark even more discovery,” Granholm said at a news conference in Washington. The fusion breakthrough “will go down in the history books,” she said.

White House science adviser Arati Prabhakar, appearing with Granholm, called the fusion ignition “a tremendous example of what perseverance really can achieve” and “an engineering marvel beyond belief.”

Proponents of fusion hope that it could one day produce nearly limitless, carbon-free energy, displacing fossil fuels and other traditional energy sources. Producing energy that powers homes and businesses from fusion is still decades away. But researchers said it was a significant step nonetheless.

“It’s almost like it’s a starting gun going off,” said Professor Dennis Whyte, director of the Plasma Science and Fusion Center at the Massachusetts Institute of Technology and a leader in fusion research. “We should be pushing towards making fusion energy systems available to tackle energy security.”

Net energy gain has been an elusive goal because fusion happens at such high temperatures and pressures that it is incredibly difficult to control.

Fusion works by pressing hydrogen atoms into each other with such force that they combine into helium, releasing enormous amounts of energy and heat. Unlike other nuclear reactions, it doesn’t create radioactive waste.

Billions of dollars and decades of work have gone into fusion research that has produced exhilarating results — for fractions of a second. Previously, researchers at the National Ignition Facility, the division of Lawrence Livermore where the success took place, used 192 lasers and temperatures multiple times hotter than the center of the sun to create an extremely brief fusion reaction.

The lasers focus an enormous amount of heat on a small metal can. The result is a superheated plasma environment where fusion may occur.

Riccardo Betti, a professor at the University of Rochester and expert in laser fusion, said an announcement that net energy had been gained in a fusion reaction would be significant. But he said there’s a long road ahead before the result generates sustainable electricity.

He likened the breakthrough to when humans first learned that refining oil into gasoline and igniting it could produce an explosion.

“You still don’t have the engine and you still don’t have the tires,” Betti said. “You can’t say that you have a car.”

The net energy gain achievement applied to the fusion reaction itself, not the total amount of power it took to operate the lasers and run the project. For fusion to be viable, it will need to produce significantly more power and for longer.

It is incredibly difficult to control the physics of stars. Whyte said it has been challenging to reach this point because the fuel has to be hotter than the center of the sun. The fuel does not want to stay hot — it wants to leak out and get cold. Containing it is an incredible challenge, he said.

Net energy gain isn’t a huge surprise from the California lab because of progress it had already made, according to Jeremy Chittenden, a professor at Imperial College in London specializing in plasma physics.

“That doesn’t take away from the fact that this is a significant milestone,” he said.

It takes enormous resources and effort to advance fusion research. One approach turns hydrogen into plasma, an electrically charged gas, which is then controlled by humongous magnets. This method is being explored in France in a collaboration among 35 countries called the International Thermonuclear Experimental Reactor as well as by researchers at the Massachusetts Institute of Technology and a private company.

Last year the teams working on those projects in two continents announced significant advancements in the vital magnets needed for their work

© Copyright 2022 The Associated Press. All rights reserved. This material may not be published, broadcast, rewritten or redistributed.

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HUGO Gene Nomenclatre Committee (HGNC) Autumn NewsLetter


We are excited to announce that we have expanded our REST API so that you can now query both HGNC and VGNC data! The REST web-service is a convenient and quick way of searching and fetching data from our database within a script/program. Users may request results as either XML or JSON making our data easier to parse. Previously this was only supported for HGNC data, but it’s now possible to search & fetch VGNC data using the same REST API. Just prefix the request type with vgnc/ and you will be searching and retrieving records within the VGNC sister site. Full details can be found at
HGNC track on UCSC Genome Browser

We are delighted by the new HUGO Gene Nomenclature track that has recently been added to the UCSC Genome Browser! This new track is fully searchable and shows the HGNC approved symbol and HGNC ID along with an associated RefSeq ID, as shown in the image below.

Clicking on the HGNC gene in the browser links through to a UCSC-hosted report page that includes previous and alias gene symbols and names, as well other associated information such gene IDs for associated resources like Ensembl and UniProt. Importantly, the UCSC have added a “thesaurus” to their resource which means that HGNC aliases and previous nomenclature can now be used to access the correct gene in the UCSC genome browser.
Update on genes with the ‘stable’ tag

As of 16 Nov 2022, we have 3027 gene symbols tagged as ‘stable’, an increase of 81 stable genes since our Summer newsletter. These include several genes named with the CD# (CD molecule) and SLC# (solute carrier) root symbols, such as: CD44, CD55, CD59, SLC1A4, SLC2A10 and SLC5A1

The stabilisation process includes a review of the gene symbol and name; in a relatively small number of cases the gene symbol may be updated before the stable tag is added. For example, HGNC:11075 was updated from SLC9A3R1 (SLC9A3 regulator 1) to NHERF1 (NHERF family PDZ scaffold protein 1) due in part to the much higher usage of the NHERF1 symbol by the community. A consultation was held with research groups to confirm support for the change. The paralogs HGNC:11076 and HGNC:19891 were likewise renamed from SLC9A3R2 and PDZD3 to NHERF2 and NHERF4, while the fourth member of the group has the approved symbol PDZK1, which is well published, so PDZK1 has been retained as the approved symbol and assigned the stable tag, while NHERF3 is a symbol alias for this gene. The new NHERF# root symbol groups together these four paralogs encoding scaffold proteins.
Updates to placeholder symbols

Within the last quarter we have been able to update the following placeholder symbols with more informative nomenclature:

FAM183A -> CFAP144, cilia and flagella associated protein 144
FAM102A -> EEIG1, estrogen-induced osteoclastogenesis regulator 1
FAM102B -> EEIG2, EEIG family member 2

Gene Symbols in the News

This quarter we have some stories about how immune-related gene variants have altered our own and our ancestors’ susceptibility to disease. A new study on skeletons from the period of the black death and afterwards has found that mutations in the ERAP2 gene had a protective effect against the plague but that the same mutations are associated with auto-immune diseases such as Crohn’s disease in people today. Variants in the TYK2 gene have been shown to be protective against severe COVID-19 but to also increase the risk of auto-immune disease, particularly lupus.

In other COVID-related news, researchers found that people with a particular allele of the HLA-DQB1 gene, HLA-DQB1*06, showed an increased antibody response to vaccination against the disease than the rest of the population. The allele has a 30-40% prevalence in the UK.

Recent work into the mechanisms that result in cachexia in cancer patients has shown that the muscles of such patients have increased levels of the UBR2-encoded protein and an associated loss of myosin heavy chain. Studies in mice have shown that existing drugs can be used to reduce the UBR2 increase, raising hopes that such drugs may be used as part of cancer care in the future.

Finally, a study has suggested that the ARHGAP11B gene, a human-specific duplication of the ARHGAP11A gene, has a key role in human neocortex development. Expression of ARHGAP11B in chimpanzee cerebral organoids resulted in an increase of neocortex progenitor cells.

Bruford EA, Braschi B, Haim-Vilmovsky L, Jones TEM, Seal RL, Tweedie S. The importance of being the HGNC. Hum Genomics. 2022 Nov 15;16(1):58. DOI: 10.1186/s40246-022-00432-w. PMID: 36380364

Dornburg A, Mallik R, Wang Z, Bernal MA, Thompson B, Bruford EA, Nebert DW, Vasiliou V, Yohe LR, Yoder JA, Townsend JP. Placing human gene families into their evolutionary context. Hum Genomics. 2022 Nov 11;16(1):56. DOI: 10.1186/s40246-022-00429-5 PMID: 36369063; PMCID: PMC965288

Seal RL, Braschi B, Gray K, Jones TEM, Tweedie S, Haim-Vilmovsky L, Bruford EA. the HGNC resources in 2023. Nucleic Acids Res. 2022 Oct 16:gkac888. DOI: 10.1093/nar/gkac888. PMID: 36243972

Seal RL, Denny P, Bruford EA, Gribkova AK, Landsman D, Marzluff WF, McAndrews M, Panchenko AR, Shaytan AK, Talbert PB. A standardized nomenclature for mammalian histone genes. Epigenetics Chromatin. 2022 Oct 1;15(1):34.DOI:10.1186/s13072-022-00467-2 PMID: 36180920 PMCID: PMC9526256

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mRNA 5’ terminal sequences drive 200-fold differences in expression through effects on synthesis, translation and decay

This publication — which has just appeared today — has little to do with gene-environment interactions, per se. Rather, it answers some very important questions that many of us have pondered, dating back 30-40 years (i.e., does the mRNA itself contain specific nucleotide sequences that in some cases regulate its degree of expression, rates of synthesis and/or degradation?). The answer to this question is a resounding YES: specific combinations (in the noncoding portion of the mRNA) can lead to as much as 200-fold differences in expression of the gene having this particular mRNA…!! 😊



mRNA regulatory sequences control gene expression at multiple levels — including translation

initiation, and mRNA decay. The 5’ terminal sequences of mRNAs have unique regulatory

potential because of their proximity to key post-transcriptional regulators. Here we have systematically

probed the function of 5’ terminal sequences in gene expression in human cells.

Using a library of reporter mRNAs initiating with all possible 7-mer sequences at their 5’

ends, we find an unexpected impact on transcription that underlies 200-fold differences in

mRNA expression. Library sequences that promote high levels of transcription mirrored

those found in native mRNAs and define two basic classes with similarities to classic Initiator

(Inr) and TCT core-promoter motifs. By comparing transcription, translation and decay

rates, we identify sequences that are optimized for both efficient transcription and growth-regulated

translation and stability — including variants of terminal oligopyrimidine (TOP)

motifs. We further show that 5’ sequences of endogenous mRNAs are enriched for multifunctional

TCT/TOP hybrid sequences. Together, our results reveal how 5’ sequences

define two general classes of mRNAs with distinct growth-responsive profiles of expression

across synthesis, translation, and decay.

Author summary

mRNAs are basic units of gene expression that are regulated throughout their life cycle,

including at steps of transcription, translation and decay. Key regulatory proteins for each

of these steps interact with the 5’ end of mRNAs. The adjacent 5’ sequence is therefore

uniquely positioned to encode regulatory motifs that influence their function. To profile

the function of terminal mRNA 5’ sequences, we developed a library of mRNAs with all

possible 7-nucleotide 5’ sequences. We identify unique motifs that are optimized for efficient

transcription, while other classes of sequences link mRNA translation and stability

to cellular growth signals. Overall, our results show how the terminal 5’ sequences of

mRNAs define distinct profiles of gene expression across the mRNA life cycle.

PLoS Genet Nov 2022; 18: e1010532

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FW: Flu, RSV, Covid

I finally picked up something important from church last Sunday: A VIRUS. ☹

I stood outside (with no earmuffs, or scarf, wind chill about 30 F) talking for 15+ min.

Tuesday = I had a little bit of stuffy nose and not feeling “normal”…

Wed night I slept poorly because of a lot of dry coughing.

Thurs night was a drippy nose, lots of sneezing. Sore throat minimal.

Fri midday at Sushi Ave restaurant, I began to realize I was not enjoying the flavor of the sashimi lunch meal and hot sake.

Fri afternoon I lay down at 3:30 pm for a moment, woke up at 5:20 pm.

Fri evening = sudden explosive bowel sympotoms.

Hmm. Little bit of muscle aches and pains, plus tired eyes… Respiratory symptoms and now GI tract symptoms.

In Sept I had my annual flu shot, followed 2 weeks later by my COVID bivalent booster.

Influenza? RSV? COVID? THE LOSS OF TASTE and SMELL — was the defining symptom.

Today: the home test kit tested strongly positive for COVID.

From: Lucia Nebert
Sent: Saturday, November 19, 2022 8:43 AM

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A saturated map of common genetic variants associated with human height

Thank you, Magnus, for sharing your recent review. Thank you, Ge, for providing us with your comments on this recently-published study.

For those not as “learned” in “missing heritability,” let me add a few thoughts. Genes responsible for phenotypic variation among individuals in any population can be classified as: [1] monogenic (Mendelian) traits, typically influenced by one or a few rare coding variants; [2] predominantly oligogenic traits that usually represent variability largely elicited by a small number of major genes; and [3] complex traits — produced mostly by innumerable small-effect variants (e.g., height, blood pressure, autism spectrum disorder).

Variance explained by single-nucleotide variants (SNVs) will be some subset of the total 100% of phenotypic variation. If 12,111 SNVs reflect 40% of variance explained, let’s pick an imaginary scenario. If 11 major SNVs were to each reflect 1% of variance explained, then the remaining 12,100 SNVs, combined, would reflect the remaining 29% of variance explained. I hope this makes the topic more clear 😊, rather than more muddled. ☹


From: Ge Zhang
Sent: Wednesday, November 9, 2022 3:35 PM

Dear Dr. Nebert,

I’ve been too busy to read the full article. I glanced at the abstract and the main results, and I can say that the sample size was astonishingly large (5.4 million) and the phenotypic variance explained (in Europeans, 40~45%) almost reached (saturated) the estimated SNV-based heritability. These are amazing achievements; however, they are also the results one would expect.

I think that this type of study (detecting small-effect variants, and improving variance explained by “dramatically” increasing sample size) — cannot be replicated with any other phenotypes — given the fact that height might be the “simplest” complex trait to study. This is because it is easy to measure, stable, “robust” (i.e., not sensitive to environmental factors in well-nourished populations), and also exhibits high heritability.

In studies of other complex traits, the benefit of sheer increases in sample size may not be that obvious — because the amount of heterogeneity added might offset the benefits of a large sample size. Below is a slide that I used in a recent lecture on the genetic architecture of complex traits. In studies of several other complex traits in which the genome-wide association studies (GWAS) of cohorts have sizes of more than one million — the variance explained reached only 5~16% of total phenotypic variation.

Best, Ge

Professor of Human Genetics, Cincinnati Children’s Hospital Research Center, Ohio

From: Magnus Ingelman-Sundberg
Sent: Sunday, November 6, 2022 2:14 PM

Hi Dan

Many thanks for these articles. I find this topic very exciting.

In fact, I just recently wrote a review for Trends in Pharmacol Sci (TiPS) that includes a lot of information about the missing heritability in “absorption-disposition-metabolism-excretion” (ADME) research. For anyone interested, the preprint is (attached, extreme right).

—Best, Magnus
From: Nebert, Daniel (nebertdw)
Sent: Friday, November 4, 2022 6:02 PM

This topic is central to gene-environment interactions. What is “Missing Heritability?” Ge Zhang and I have written about this topic several times — most recently in an invited review published in 2017 [see below].

A genome-wide association study (GWAS) is a research approach used to identify genomic variants that are statistically associated with a risk for a disease or a particular trait (e.g., type-2 diabetes, autism spectrum disorder, facial features, height, or response to a drug). The method involves screening entire genomes of many people, looking for genomic variants that occur more frequently in those with a specific disease or trait — compared to those without the disease or trait. Once such genomic variants are identified, they are typically used to search for nearby variants that contribute directly to the disease or trait (by which better therapy, or improved risk assessment, might be achieved).

Personalized medicine: Genetic risk prediction of drug response

Ge Zhang a, Daniel W. Nebert a,b,

a Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229-3039, United States

b Department of Environmental Health and Center for Environmental Genetics, University of Cincinnati School of Medicine, Cincinnati, OH 45267-0056, United States

Pharmacology & Therapeutics 175 (2017) 75–90
Genome-wide association studies (GWAS)

The earliest GWAS was probably published in 2002, in which an association between the LTA gene and myocardial infarction was determined by typing almost 93,000 gene-based SNP markers (Ozaki, et al., 2002). Another early GWAS –– typing more than 116,000 SNPs –– reported an association between the CFH gene and age-related macular degeneration (Klein, et al., 2005). More recently, easy-to-use DNA chips containing 1 million to 5 million SNPs have become readily available. The GWAS field has expanded exponentially; today, >24,000 SNP-trait associations have been reported in >2,500 studies []. These robust GWAS –– having P-values ranging from <10−8 to <10−400 –– underscore the value of using more stringent statistical significance levels when one is studying >1 million SNPs in large cohorts containing thousands, or even hundreds of thousands, of samples.

GWAS quickly became far more reliable for genotype-phenotype association tests –– when compared with studies involving one or several SNPs in small cohorts of several dozen or even several hundred individuals. These latter publications of (type-I and type-II error) artifacts have variously been called “the incidentalome” (Kohane, Masys, & Altman, 2006) and “the P <0.05 false-positive studies” (Nebert, Zhang, & Vesell, 2008). It should be recognized that multiple parameters (effect-size, allelic frequency, significance level, sample size) will all affect statistical power for any genotype-phenotype association study. Statistical power obviously improves with larger numbers of cases and controls. As any minor allele frequency (MAF) increases, fewer subjects are usually needed in the study group, and the level of detectable contribution by a genetic variant to a phenotype will be lower. If the MAF is low, greater numbers per group will be required, and the level of detectable contribution by a variant to a phenotype will be higher. However, one cannot always embrace the above statements. For example, when the contribution (effect-size) of the risk variant is measured by heritability, or variance explained, influence of the MAF on statistical power of an association study is not significant. Nevertheless, if effect-size is measured by odds ratio (OR) or genotypic relative risk (GRR), the influence of a MAF will be greater –– especially for MAFs <0.05. In addition to the MAF and prevalence of a disorder, the inheritance model (“additive,” “dominant,” or “recessive”) of a risk allele can also influence power of an association study. Virtually never do GWAS have sufficient statistical power to detect epistasis (gene × gene interactions; G×G) (Bhattacharjee, et al., 2010; Sackton & Hartl, 2016) or gene-environment (G×E) interactions (D. Thomas, 2010). Moreover, an additional underappreciated class of genetic interactions is intergenic compound heterozygosity, i.e. interactions between multiple rare variants contributing to a trait (Gibson, 2011). Such interactions encompass heterozygous combinations of multiple alleles. In a broad sense, if hundreds of mutations –– each having a frequency of <0.1% –– all contribute to the phenotype, then such an event could contribute substantially to individuals that are heterozygous at many of these loci. “Missing heritability”: real or imagined? Twenty years after launching the Human Genome Project in October 1990, initial GWAS findings became frustrating to those who wanted clear-cut explanations into the etiology of a complex disease (D. B. Goldstein, 2009). For most complex diseases, even multiple GWAS variants considered together (e.g., using polygenic risk score) typically explain too little variability in disease occurrence to be of much predictive value (Manolio, 2013; Wray, et al., 2013). However, more importantly, some GWAS data had identified potential novel therapeutic targets for treating a complex disease –– without knowing its precise etiology. Similarly, some GWAS data might uncover potential therapeutic targets for treating an environmental disease, by learning something about its mode-of-action without necessarily understanding its precise mechanism-of-action. Many GWAS often explain only a small proportion of heritability (defined as additive genetic variance). The absent proportion became known as “missing heritability” (Lander, 2011; Manolio, et al., 2009), leading to renewed awareness in the genetic architecture of human complex disease and traits (Gibson, 2011; Ge Zhang, 2015) –– a topic that had been extensively debated in the early 20th century. First, it was realized that heritability attributable to some common variants could be substantial. However, as GWAS cohort sizes continued to increase –– thereby identifying additional variants contributing smaller effects to the trait –– the “revealed heritability” continued to grow, albeit rarely reaching more than 20–25% for various diseases and traits (Lander, 2011). In addition, current GWAS may overlook many variants of lower frequency (MAFs 1–5%), because existing SNP-typing arrays often lack a more useful marker. Many complex disease-related alleles are probably included in this frequency class. Also, new genotyping arrays and imputation methods, based on the 1000 Genomes Project (Genomes Project, et al., 2012; Genomes Project, et al., 2015) or The Haplotype Reference Consortium (S. McCarthy, et al., 2016), are able to capture these less frequent variants. This topic is discussed in detail later. GWAS also miss many common small-effect variants –– due to limited sample-size and/or stringent statistical thresholds imposed to ensure reproducibility. Efforts seeking to infer contributions of loci that fall just short of statistical significance were then addressed (Park, et al., 2010; J. Yang, et al., 2010). Contributions of loci that fall even further short of statistical significance, likewise, will result in even smaller effect-sizes on phenotype. Although their individual contributions may be too small ever to detect by investigators designing feasible sample cohort sizes, these very-small-effect variants collectively will probably also explain a significant fraction of heritability (Gibson, 2010; Lander, 2011). Furthermore, rare variants of large-effect will sometimes contribute substantially to common diseases, although their roles are just recently being explored. Increases in our understanding of rare variants have now advanced –– via whole-exome sequencing (WES) (Bertier, Hetu, & Joly, 2016) and whole-genome sequencing (WGS); also called “next-generation” sequencing (NGS) (Haimovich, Muir, & Isaacs, 2015; Pinto, Ariani, Bianciardi, Daga, & Renieri, 2016). Whether rare variants will lead to discovery of a substantial number of new genes –– is a question that perhaps can be answered by systematic WES or WGS. Given the background rate of rare variants, many thousands of samples will be required to achieve statistical significance. Correspondingly, how to quantify total heritability due to rare variants remains unclear. Although the inferred effect-sizes are larger, overall contribution to heritability may be small because of their low frequencies (Gibson, 2011; Ge Zhang, 2015). Lastly, some “missing heritability” might be purely an illusion (Lander, 2011) because heritability is estimated from epidemiological data by applying principles for inferring additive genetic effects. These approximations may be overestimated –– due to methods that are not effective at excluding nonlinear contributions of G×G interactions, G×E interactions, or epistasis –– which are likely to be important. This brings us — 5 years later — to this recently published article and editorial [see attached]. Since 2007, “height” has often been studied as a convenient polygenic multifactorial trait; increasing the cohort size has shown that the amount of heritability (“variance explained”) is greater, albeit not nearly close to 100%. Some have suggested that a GWAS that includes all adult humans on earth would still be insufficient to reach 100% of “variance explained”…!! Until now, the largest GWAS published for adult height had reported 3,290 independent associations in 712 loci, using a cohort size of 700,000 individuals (Yengo et al., 2018). Adult height (highly heritable and easily measured) has provided a larger number of common genetic associations than any other human phenotype. In addition, a large collection of genes has been implicated in disorders of skeletal growth, and these are enriched in loci mapped by GWAS of height in the normal range; these features thus make height an attractive model trait for assessing the role of common genetic variation in defining the genetic and biological architecture of polygenic human phenotypes. As available sample sizes continue to increase for GWAS of common variants — it becomes important to consider how much more heritability can be uncovered. Moreover, because most GWAS continue to be performed largely in populations of European ancestry, it is necessary to address these questions of “completeness” in the context of multiple ancestries. Finally, some have proposed that, when sample sizes become sufficiently large, effectively every gene and genomic region will be implicated by GWAS, rather than certain subsets of genes and biological pathways being specified. In the attached article just published, using data from a GWAS of 5.4 million individuals of diverse ancestries, authors show that 12,111 independent single-nucleotide variants (SNVs) that are significantly associated with height account for nearly all of the common SNV-based heritability; these SNvs are clustered within 7,209 non-overlapping genomic segments with a mean size of ~90 kilobases (kb), covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. This combined analysis of 281 GWAS not only found 12,111 common DNA variants associated with a person’s height — but also shows that larger studies will not yield more variants in populations of European ancestry. Authors have therefore demonstrated that it is possible to achieve saturation for complex traits (however, cohort size might have to be in the millions to do so…!!). Ancestrally, ethnically, globally and socio-economically diverse samples are now necessary to reap the full benefits of GWAS. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries. 😊😊😊 DwN Nature 27 Oct 2022; 610: 704-712 & editorial pp 631-632 COMMENT: Thank you, Magnus, for sharing your recent review. Thank you, Ge, for providing us with your comments on this recently-published study. For those not as “learned” in “missing heritability,” let me add a few thoughts. Genes responsible for phenotypic variation among individuals in any population can be classified as: [1] monogenic (Mendelian) traits, typically influenced by one or a few rare coding variants; [2] predominantly oligogenic traits that usually represent variability largely elicited by a small number of major genes; and [3] complex traits — produced mostly by innumerable small-effect variants (e.g., height, blood pressure, autism spectrum disorder). Variance explained by single-nucleotide variants (SNVs) will be some subset of the total 100% of phenotypic variation. If 12,111 SNVs reflect 40% of variance explained, let’s pick an imaginary scenario. If 11 major SNVs were to each reflect 1% of variance explained, then the remaining 12,100 SNVs, combined, would reflect the remaining 29% of variance explained. I hope this makes the topic more clear 😊, rather than more muddled. ☹ DwN

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Prostaglandin production selectively in brain endothelial cells is both necessary and sufficient for eliciting fever

This topic is a straightforward gene-environment interactions study. First, the environmental signal is a bacterial or viral infection; the response is the release of cytokines by specific types of immune cells (at the site of the infection). These cytokines then become an endogenous signal that leads to the response of fever. Since the cytokine molecules are too large to cross the blood-brain barrier, they bind to a receptor on blood-vessel endothelial cells located on the brain outer surface; the receptor then transmits a signal to specific fever-producing cells inside the brain.

Using genetically-modified mice that lack specific genes encoding for prostaglandin production in the brain endothelial cells, and then injecting substances present in cell walls of certain bacteria that typically produce a fever reaction — authors found that these genetically-modified mice did not show any fever reaction after that injection.

Authors then used a different genetically-modified mouse model in which the only cells in the body that are able to produce prostaglandin E2 are the brain surface endothelial cells. Injecting substances present in cell walls of certain bacteria that typically produce a fever reaction — the scientists found that these genetically-modified mice now DID exhibit a normal fever reaction after that injection. Authors thus concluded that it is the endothelial cell on the blood vessels of the brain’s surface (and not any other cell type located in liver or kidney or elsewhere in the body) that is necessary and sufficient to cause a fever reaction. 😊


Which brain cells are needed for fever

26 October 2022

Anders Törneholm

Researchers at Linköping University have identified in mice the cells in the blood vessels of the brain that are necessary for a fever reaction. The results have been published in PNAS, and answer a long-standing question as to which organs are involved in producing fever.

Man sitting by microscope.

“Our results answer a question that has been asked for several decades. There has not previously been any evidence that only the endothelial cells in the brain are needed to start a fever reaction. We have now filled this gap in our knowledge,” says Anders Blomqvist.

“Everyone gets fevers, occasionally. If we understand the mechanisms behind fever, we can also understand how new drugs and treatments can work,” says Anders Blomqvist, professor emeritus at the Department of Biomedical and Clinical Sciences, Linköping University.

Fever is the body’s response to infection or inflammation, and a defense mechanism against, for example, viruses and bacteria. When affected by infection or inflammation, the body releases molecules known as cytokines into the blood circulation. These molecules are too large to pass through the blood-brain barrier, a network of tiny blood vessels that protects the brain from harmful substances. But fever is just a symptom, which becomes manifest after the brain has itself released signals. So how does the brain detect that the body is affected by an inflammation or infection?

The explanation can be found in receptors located on the outer surface of the blood-brain barrier that detect the cytokines. These receptors pass the signal on to cells on the inner surface of the blood-vessel walls in the blood-brain barrier, known as endothelial cells. They then start to produce the hormone-like molecule prostaglandin E2, which in turn activates receptors in the hypothalamus, which acts as the body’s thermostat. A fever reaction has been initiated. It has, however, been unclear until now whether this is the only mechanism behind fever.
Filled a gap

It has previously been believed that prostaglandin must be produced also in certain cells of such organs as the liver and lungs in order to start a fever reaction. But the researchers at Linköping University (~200 km southwest of Stockholm) have now shown that this is not the case. In a study on mice published in Proceedings of the National Academy of Sciences, PNAS, Anders Blomqvist and his colleagues show that the endothelial cells of the brain are the only ones required for a fever reaction to be produced.

“Our results answer a question that has been asked for several decades. There has not previously been any evidence that only the endothelial cells in the brain are needed to start a fever reaction. We have now filled this gap in our knowledge,” says Anders Blomqvist.

The researchers have worked with gene-modified mice in which they have removed certain genes that code for prostaglandin production in the brain endothelial cells. The mice were subsequently injected with substances that are present in the cell walls of certain bacteria, producing in this way fever. The gene-modified mice did not show any fever reaction after the injection.
Stress raises temperature

This allowed the researchers to conclude that these endothelial cells are necessary to elicit fever, but did not show whether they are sufficient. For this reason, the researchers conducted tests on another gene-modified mouse model in which the only cells that could produce prostaglandin E2 were the brain endothelial cells. These mice exhibited a fever reaction, which confirms that the brain endothelial cells are, indeed, sufficient.

These experiments have been made possible using advanced techniques for managing and examining experimental animals. By surgically inserting an intravenous catheter and recording body temperature using telemetry, both the injections and the measurements can be made without causing stress for the animal, which means that the fever reaction can be observed more accurately.

“The general public has long believed that the body temperature of small animals is higher than that of humans and other large mammals, around 40 degrees F. But the measurements have been erroneous, because the animals became stressed during the process. The techniques we have used show that the mice have the same temperature as humans,” said Anders Blomqvist.

The article: Prostaglandin production selectively in brain endothelial cells is both necessary and sufficient for eliciting fever, Kiseko Shionoya, Anna Eskilsson, Anders Blomqvist, Proc Natl Acad Sci USA Vol. 119 No. 43, published online on 17 Oct 2022. DOI: 10.1073/pnas.2122562119

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Geneticist who unmasked lives of ancient humans wins the 2022 Nobel Prize in Physiology or Medicine


I, also, was too young to appreciate McClintock’s sentinel papers (in 1958 and 1960). Barbara retired from her position at Carnegie Institution in 1967, but then she worked as scientist emerita (working in her own lab, with grad students and postdocs) at Cold Spring Harbor (Long Island, NY), for another two decades after 1967 — receiving many awards and recognitions (including the National Medal of Science in 1970, the first woman ever to receive this award) — at least until 1993, a year after her death at age 90.

Interestingly, she wrote a letter to Oliver Nelson (a maize geneticist colleague) in 1973 — in reference to her decision 20 years earlier to “stop publishing detailed accounts of her work on controlling elements”: “Over the years I have found that it is difficult, if not impossible, to bring to consciousness of another person the nature of his tacit assumptions when, by some special experiences, I have been made aware of them. This became painfully evident to me in my attempts during the 1950s to convince geneticists that the action of genes had to be, and was, controlled. It is now equally painful to recognize the fixity of assumptions that many persons hold on the nature of controlling elements in maize and the manners of their operation. One must await the right time for conceptual change.”

When I attended (annual) mouse genetics meetings (at Bar Harbor, ME) between 1973 and 1983, I recall Professor McClintock giving talks there more than once. Ken Paigen, Director of Jackson Laboratory, had invited her; during this time period, Ken also visited her lab for a day or longer and I remember him saying “She’s discovered something very important and fundamental to genetics, but I cannot comprehend how her genetic-crossover experiments in maize — led her, ultimately, to her startling conclusions..!! ” 😊


From: John J Stegeman
Sent: Saturday, October 15, 2022 6:03 PM

Excellent examples, Dan..!! Two of these three, and Pääbo — all caught my attention immediately (I was too young at the time of McClintock’s first papers). All three awardees were/are “too cool” to be ignored. I remember clearly where I was, when I was first reading Prusiner’s paper. I met him once at an Academy function at Woods Hole.

John Stegeman, PhD

Senior Scientist, Woods Hole Oceanographic Institute, MA

From: Nebert, Daniel (nebertdw)
Sent: Saturday, October 15, 2022 6:50 PM
Subject: Geneticist who unmasked lives of ancient humans wins the 2022 Nobel Prize in Physiology or Medicine


This year’s prize is a GREAT example of what a Nobel Prize can be (or should be) — or what it has been, at least a few times over past decades [i.e., someone with a CRAZY idea that goes against the grain, he/she is convinced that they know they are correct, and they continue fighting the ~95 or 99% “consensus thinking” (or “groupthink”) who are certain he/she is wrong (or crazy). And then, after several, or many years, it turns out that the consensus groupthink was wrong — all along] … !!

Off the top of my head, three particularly outstanding examples come to mind.

[1] Barbara McClintock published her first paper on “jumping genes” in maize (genetic studies in corn; Bloomington, Indiana) in 1958 and her classic article in Proc Natl Acad Sci USA in 1960 — but she was regarded mostly as a “weirdo” and often laughed at, at scientific meetings. By the mid-1960s, steps leading from DNA transcription into mRNA, and translation of the messenger RNA into the amino acid sequences that make proteins, became well established (i.e., the genetic code was finally broken). Genes were no longer abstract concepts, but rather discrete molecular entities that could be manipulated in a test tube.

Mobile genetic elephants were then discovered in bacteriophages (viruses that infect bacteria) Soon, mobile elements were also discovered in bacteria, and eventually in the fruit fly Drosophila. The consensus scientific community gradually recognized that these “transposons” were real, and they were not just peculiar to maize, but were in fact widespread across species. McClintock was awarded the 1983 Nobel Prize for Medicine or Physiology — 35 years after her first published report of “transposition of genetic units”…!!

[2] “Mad cow disease,” and the human equivalent Creutzfeldt-Jakob disease — in the 1970s were degenerative brain diseases of unknown cause. After ~10 years of experiments, neurologist Stanley Prusiner reported in 1982 that these diseases were caused by a virus-like protein which he named “prion” (derived from “protein” and “infectious”). Almost every scientist laughed, because “viruses were well known ‘always’ to be made of DNA or RNA.” Prusiner persisted, however, because he was convinced the consensus groupthink was wrong, and that he was right. He proved to be correct and was awarded the 1997 Nobel Prize for Medicine or Physiology for his novel discovery. Prions are now realized to have effects in tissues other than brain and, in fact, are found even in lower organisms such as yeast…!!

[3] For decades, peptic ulcer was believed by consensus groupthink to be caused by “mental stress and excess stomach acid.” Following many years of experiments, physicians Barry Marshall and Robin Warren reported in 1985 that peptic ulcer was caused by a bacterium, Heliobacter pylori…!! This finding forever changed the field of ulcer research: instead of treating ulcers with antacid medications and/or surgery, antibiotics could now kill the bacteria and cure the disease…!! Twenty years later, Marshall and Warren were awarded the 2005 Nobel Prize for Medicine or Physiology for this breakthrough.

Moral of the Story: If you know what you’ve found something very real, and you’re convinced that the consensus groupthink does NOT appreciate your breakthrough findings — stick to your guns, and (hopefully) “everything will eventually come out in the wash” and you will be eventually credited for that breakthrough. 😊


From: Olavi Pelkonen Sent: Sunday, October 9, 2022 11:24 PM


Thanks very much for the information! I also have followed Pääbo’s papers. I remember the first time that I met him—somewhere in the late 1980’s in Uppsala or Umeå at a symposium. At that time, almost everyone in the audience (including myself) were pretty convinced that extracting readable ancient DNA from fossilized bones would be impossible, because of DNA degradation, combined with contamination of other biological materials in the dirt or mud—as well as any other problem of long exposures and processes occurring over many millennia.

It is good to know that all of us were completely wrong!


Olavi Pelkonen, PhD

eProfessor of Pharmacology

University of Oulu

From: Nebert, Daniel (nebertdw)
Sent: Saturday, October 8, 2022 5:16 PM

Because these GEITP pages have been sharing many of Svante Pääbo’s exciting breakthrough publications — over the past 14 years — we believe it is only appropriate to report on his winning the 2022 Nobel in Physiology or Medicine this past week. 😊 This [below] is a recent summary in the latest issue of Nature.

Geneticist who unmasked lives of ancient humans wins the 2022 Nobel Prize in Physiology or Medicine
Svante Pääbo has made stunning discoveries about human evolution using ancient DNA — and his work helped to spawn the competitive field of palaeogenomics.

Neanderthal researcher Svante Pääbo, recipient of 2022 Medicine nobel prize.
Svante Pääbo has been awarded a Nobel prize for discoveries about the genomes of extinct hominins and human evolution.
The 2022 Nobel Prize in Physiology or Medicine has been awarded for pioneering studies of human evolution that harnessed precious snippets of DNA found in fossils that are tens of thousands of years old.

The work of Svante Pääbo, a geneticist at the Max Planck Institute for Evolutionary Anthropology (MPI-EVA) in Leipzig, Germany, led to the sequencing of the Neanderthal genome and the discovery of a new group of hominins called the Denisovans, and also spawned the fiercely competitive field of palaeogenomics.

By tracing how genes flowed between ancient hominin populations, researchers have been able to trace these groups’ migrations, as well as the origins of some aspects of modern human physiology, including features of the immune system and mechanisms of adaptation to life at high altitudes.

Pääbo’s Nobel win “is an extraordinary recognition of this field maturing and of what he did in putting together everything that needed to be done to accomplish this miracle, which is getting ancient DNA from human remains”, says David Reich, a population geneticist at Harvard Medical School in Boston, Massachusetts, who worked closely with Pääbo on the Neanderthal genome sequence.

At a press conference following the announcement, Pääbo said that he was still digesting the news, and didn’t initially believe he had won the Nobel when he got the call from Stockholm. He “at first thought it was an elaborate prank developed by people in my group”.

Chris Stringer, a palaeoanthropologist at the Natural History Museum in London, says that Pääbo’s work — including recovery of the oldest ancient human DNA on record, 430,000-year-old sequences from Spain1 — has revolutionized our understanding of the past. “It’s central to human evolutionary studies now,” Stringer says, adding that the Nobel win is “great news”.
Damaged DNA

Pääbo had to develop ways of analysing DNA that had been damaged by thousands of years of exposure to the elements, and contaminated with sequences from microorganisms and modern humans. He and his collaborators then put these techniques to work sequencing the Neanderthal genome, which was published in 20102. This genetic analysis led to the finding that Neanderthals and Homo sapiens interbred, and that 1–4% of the genome of modern humans of European or Asian descent can be traced back to the Neanderthals.

Pääbo’s techniques were also used to identify the origins of a 40,000-year-old finger bone found in a southern Siberian cave in 2008. DNA isolated from the bone indicated that it was from neither Neanderthals nor Homo sapiens, but came from an individual belonging to a new group of hominins3. The group was named the Denisovans, after the cave in which the bone was found. Ancient humans living in Asia interbred with this group, too, and Denisovan DNA can be found in the genomes of billions of people alive today.

During the early years of ancient DNA research — led by Pääbo and other scientists in the 1980s and 1990s — the field was plagued by concerns over contamination from modern human DNA (Pääbo has admitted that DNA he recovered early on from Egyptian mummy remains was probably his own). But, thanks to methods developed in Pääbo’s laboratory, as well as the advent of new sequencing technologies, contamination is no longer the ‘boogeyman’ it once was.

“When I started, we weren’t even sure you could work with ancient human DNA,” says Pontus Skoglund, a palaeogeneticst at the Francis Crick Institute in London. “But now, and I think led by Svante’s department, we have an approach where contamination is really not a major issue anymore.”
Health implications

Pääbo’s work teasing out DNA from Neanderthals, Denisovans and other hominins also has important implications for modern medicine. Although the proportion of the human genome comprised of archaic DNA is small, this material seems to punch above its weight, making an important contribution to the risks of diseases ranging from schizophrenia4 to severe COVID-195. And people living on the Tibetan Plateau can thank Denisovans for gene variants linked to high-altitude adaptation6.

“The fact that a good fraction of the people running around in the world today have DNA from archaic humans like Neanderthals is of important consequence to who we are,” says Reich. “So I think that knowing that and trying to understand the implications of that for health is something that will be with us for the rest of our time as a species.”

With genomes from multiple Neanderthals and Denisovans available, it is now possible to identify uniquely human genes, says Johannes Krause, a palaeogeneticist at MPI-EVA. In September, researchers showed that a gene variant found in humans, but not in Neanderthals or Denisovans, is linked to greater neuronal growth in lab-grown brain organoids7. “We’ve never come so close to understanding what makes humans humans,” Krause says.

Researchers describe Pääbo as intense and driven, but also collegial and generous. His department at the Max Planck Institute for Evolutionary Anthropology has produced a generation of palaeogeneticists who are pushing the field ever further.

Viviane Slon, a palaeogeneticist at Tel Aviv University in Israel who did her PhD under Pääbo’s supervision, says her former mentor has an “uncanny” ability to see the larger picture while remaining laser-focused on details. When Slon was working on remains that turned out to be a first-generation Denisovan–Neanderthal hybrid, the sequence of maternally inherited mitochondrial DNA matched that of a Neanderthal. But, when publishing those results, Pääbo urged Slon to reserve judgment until they had sequenced nuclear DNA inherited from both parents. “He wouldn’t let me write that it’s a Neanderthal because we didn’t know that, and in fact it turned out to be a mixed offspring,” Slon says.

Reich says that working with Pääbo and the team he organized to sequence and analyse the first Neanderthal genome was inspirational. “It was the best consortium ever,” Reich says. “He recognized how special and unique this type of data they were producing was.” This eventually inspired Reich to set up his own ancient DNA laboratory.

Pääbo’s influence on ancient DNA work has been such that it’s hard to imagine where the field would be without him. “He’s the godfather of the field,” says Skoglund.

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What We Know about Long COVID So Far

This syndrome is getting to be just a little bit creepy — especially for those of us who are under 50 (–as well as those over 50 who sometimes feel like we’re still younger than 50). 😉
What We Know about Long COVID So Far

Maggie Fox

September 27, 2022

Editor’s note: Find the latest long COVID news and guidance in Medscape’s Long COVID Resource Center.

Long COVID: The name says it all. It’s an illness that, for many people, has not yet stopped.

Eric Roach became ill with COVID-19 in November 2020, and he’s still sick. “I have brain fog, memory loss,” says the 67-year-old Navy veteran from Spearfish, SD. “The fatigue has just been insane.”

Long COVID, more formally known as post-acute sequelae of COVID (PASC), is the lay term to describe when people start to recover, or seem to recover, from a bout of COVID-19 but then continue to suffer from symptoms. For some, it’s gone on for 2 years or longer. While the governments of the U.S. and several other countries formally recognize the existence of long COVID, the National Institutes of Health (NIH) has yet to formally define it. There’s no approved treatment, and the causes are not understood.

Here’s what is known: Long COVID is a post-viral condition affecting a large percentage of people who become infected with the coronavirus. It can be utterly debilitating or mildly annoying, and it is affecting enough people to cause concern for employers, health insurers, and governments.

First, the Many Symptoms

According to the CDC, long COVID symptoms may include:

Tiredness or fatigue that interferes with daily life
Symptoms that get worse after physical or mental effort (also known as “post-exertional malaise”)
Difficulty breathing or shortness of breath
Chest pain
Fast-beating or pounding heart (heart palpitations)
Difficulty thinking or concentrating (sometimes referred to as “brain fog”)
Sleep problems
Dizziness when standing
Pins-and-needles feelings
Change in smell or taste
Depression or anxiety
Stomach pain
Joint or muscle pain
Changes in menstrual cycles

“People with post-COVID conditions may develop or continue to have symptoms that are hard to explain and manage,” the CDC says on its website. “Clinical evaluations and results of routine blood tests, chest x-rays, and electrocardiograms may be normal. The symptoms are similar to those reported by people with ME/CFS (myalgic encephalomyelitis/chronic fatigue syndrome) and other poorly understood chronic illnesses that may occur after other infections.”

Doctors may not fully appreciate the subtle nature of some of the symptoms.

“People with these unexplained symptoms may be misunderstood by their health care providers, which can result in a long time for them to get a diagnosis and receive appropriate care or treatment,” the CDC says.

Health professionals should recognize that long COVID can be disabling,the U.S. Department of Health and Human Services says. “Long COVID can substantially limit a major life activity,” HHS says in civil rights guidance. One possible example: “A person with long COVID who has lung damage that causes shortness of breath, fatigue, and related effects is substantially limited in respiratory function, among other major life activities,” HHS says.

How Many People Are Affected?

This has been difficult to judge because not everyone who has had COVID-19 gets tested for it and there are no formal diagnostic criteria yet for long COVID. The CDC estimates that 19% of patients in the U.S. who have ever had COVID-19 have long COVID symptoms.

Some estimates go higher. A University of Oxford study in September 2021 found more than a third of patients had symptoms of long COVID between 3 months and 6 months after a COVID-19 diagnosis. As many as 55% of COVID-19 patients in one Chinese study had one or more lingering symptoms 2 years later, Lixue Huang, MD, of the China-Japan Friendship Hospital in Beijing, and colleagues reported in the journal Lancet Respiratory Medicine in May.

According to the CDC, age is a factor. “Older adults are less likely to have long COVID than younger adults. Nearly three times as many adults ages 50-59 currently have long COVID than those age 80 and older,” the CDC says. Women and racial and ethnic minorities are more likely to be affected.

Many people are experiencing neurological effects, such as the so-called brain fog, according to Ziyad Al-Aly, MD, of the Washington University School of Medicine and the VA St. Louis Health Care System, writing in the journal Nature Medicine in September. They estimated that 6.6 million Americans have brain impairments associated with COVID infection.

“Some of the neurologic disorders reported here are serious chronic conditions that will impact some people for a lifetime,” they wrote. “Given the colossal scale of the pandemic, and even though the absolute numbers reported in this work are small, these may translate into a large number of affected individuals around the world — and this will likely contribute to a rise in the burden of neurologic diseases.”


It’s not clear what the underlying causes are, but most research points to a combination of factors. Suspects include ongoing inflammation, tiny blood clots, and reactivation of what are known as latent viruses, or those that linger quietly in your body without causing damage. In May, Brent Palmer, PhD, of the University of Colorado School of Medicine, and colleagues found people with long COVID had persistent activation of immune cells known as T-cells that were specific for SARS-CoV-2, the virus that causes COVID-19.

COVID-19 itself can damage organs, and long COVID might be caused by ongoing damage. In August, Alexandros Rovas, MD, of University Hospital Munster in Germany, and colleagues found patients with long COVID had evidence of damage to their capillaries. “Whether, to what extent, and when the observed damage might be reversible remains unclear,” they wrote in the journal Angiogenesis.

People with long COVID have immune responses to other viruses, such as Epstein-Barr — evidence that COVID-19 might reactivate latent viruses. “Our data suggest the involvement of persistent antigen, reactivation of latent herpesviruses, and chronic inflammation,” immunobiologist Akiko Iwasaki, PhD, of the Yale University School of Medicine, and colleagues wrote in a study posted in August that had not yet been peer-reviewed for publication.

This might be causing an autoimmune response. “The infection may cause the immune system to start making autoantibodies that attack a person’s own organs and tissues,” the NIH says.

There could be other factors. A study by Harvard researchers found that people who felt stressed, depressed, or lonely before catching COVID-19 were more likely to develop long COVID afterward. “Distress was more strongly associated with developing long COVID than physical health risk factors such as obesity, asthma, and hypertension,” Siwen Wang, MD, a research fellow with Harvard University’sT.H. Chan School of Public Health, said in a statement. Plus, nearly 44% of those in the study developed COVID-19 infections after having been assessed for stress, Wang and colleagues reported in the journal JAMA Psychiatry.

Vaccine Protection

There’s evidence that vaccination protects against long COVID, both by preventing infection in the first place, but also even for people who have breakthrough infections.

A meta-analysis covering studies involving 17 million people found evidence vaccination might reduce the severity of COVID-19 or might help the body clear any lingering virus after an infection.

“Overall, vaccination was associated with reduced risks or odds of long COVID, with preliminary evidence suggesting that

two doses are more effective than one dose,” Cesar Fernandez de las Penas, PhD, of King Juan Carlos University in Madrid, Spain, and colleagues wrote.

A team in Milan, Italy, found unvaccinated people in their study were nearly three times as likely to have serious symptoms for longer than 4 weeks compared to vaccinated volunteers. Writing in July in The Journal of the American Medical Association, Elena Azzolini, MD, PhD, an assistant professor atthe Humanitas Research Hospital, said the team found two or three doses of vaccine reduced the risk of hospitalization from COVID to 16% or 17% compared to 42% for the unvaccinated.


With no diagnostic criteria and no understanding of the causes, it’s hard for doctors to determine treatments.

Most experts dealing with long COVID, even those at the specialty centers that have been set up at hospitals and health systems in the U.S.,recommend that patients start with their primary care doctor before moving on to specialists.

“The mainstay of management is supportive, holistic care, symptom control, and detection of treatable complications,” Trish Greenhalgh, MD, professor of primary care health sciences at the University of Oxford, and colleagues wrote in the journal The BMJ in September. “Patients with long COVID greatly value input from their primary care clinician. Generalist clinicians can help patients considerably by hearing the patient’s story and validating their experience … (and) making the diagnosis of long COVID (which does not have to be by exclusion) and excluding alternative diagnoses.”

Evidence is building that long COVID closely resembles other post-viral conditions — something that can provide clues for treatment. For example, several studies indicate that exercise doesn’t help most patients.

But there are approaches that can work. Treatments may include pulmonary rehabilitation; autonomic conditioning therapy, which includes breathing therapy; and cognitive rehabilitation to relieve brain fog. Doctors are also trying the antidepressant amitriptyline to help with sleep disturbances and headaches; the antiseizure medication gabapentin to help pain, numbness, and other neurological symptoms; and drugs to relieve low blood pressure in patients experiencing postural orthostatic tachycardia syndrome (POTS).

The NIH is sponsoring studies that have recruited just over 8,200 adults. And more than two dozen researchers from Harvard; Stanford; the University of California, San Francisco; the J. Craig Venter Institute; Johns Hopkins University; the University of Pennsylvania; Mount Sinai Hospitals; Cardiff University; and Yale announced in September they were forming the Long COVID Research Initiative to speed up studies.

The group, with funding from private enterprise, plans to conduct tissue biopsy, imaging studies, and autopsies and will search for potential biomarkers in the blood of patients.


CDC: “Long COVID or Post-COVID Conditions.”

CDC National Center for Health Statistics: “Nearly One in Five American Adults Who Have Had COVID-19 Still Have ‘Long COVID.'”

National Institutes of Health: “Long COVID,” “Long COVID symptoms linked to inflammation.”

PLoS Medicine: “Incidence, co-occurrence, and evolution of long-COVID features: A 6-month retrospective cohort study of 273,618 survivors of COVID-19.”

The Lancet Respiratory Medicine: “Health outcomes in people 2 years after surviving hospitalisation with COVID-19: a longitudinal cohort study.”

Angiogenesis: “Persistent capillary rarefication in long COVID syndrome.”

PLoS Pathogens: “SARS-CoV-2-specific T cells associate with inflammation and reduced lung function in pulmonary post-acute sequalae of SARS-CoV-2.”

Lancet eClinical Medicine: “Impact of COVID-19 vaccination on the risk of developing long-COVID and on existing long-COVID symptoms: A systematic review.”

JAMA Psychiatry: “Associations of Depression, Anxiety, Worry, Perceived Stress, and Loneliness Prior to Infection With Risk of Post–COVID-19 Conditions.”

U.S. Department of Health and Human Services: “Guidance on ‘Long COVID’ as a Disability Under the ADA, Section 504, and Section 1557.”

Long COVID Research Initiative:”Introducing LCRI.”

Nature Medicine: “Long-term Neurologic Outcomes of COVID-19.”

The BMJ: “Long COVID—an update for primary care.”

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