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Sunday, September 5, 2021

Va. GOP lt. gov. nominee says would support heartbeat abortion bill

 Virginia Republican lieutenant gubernatorial nominee Winsome Sears said on Friday that she would support heartbeat abortion legislation amid the fallout over a Texas law that bans abortion as early as six weeks into a pregnancy. 

"Well, I can tell you that would be me, that I would support [it]," Sears told Newsmax on Friday.

The comments come as Virginia Democrats have gone on the offensive on abortion, citing the recently passed Texas abortion law that would restrict abortion as early as the sixth week of pregnancy, when many women don’t know they’re pregnant.

Sears's campaign said in a statement to The Hill that the law passed in Texas would not pass in Virginia's General Assembly. 

"While Winsome personally supports protecting life and the most vulnerable, as a former legislator herself she also recognizes that Virginia is very different from Texas, and that legislation could never have the votes to pass the Virginia General Assembly," the campaign said. 
 
A spokesperson for Republican gubernatorial nominee Glenn Youngkin said the campaign agrees with the assessment from the Sears campaign, adding that "the Virginia legislature is very different than the Texas legislature." 
 
Republicans have hit back at Democrats on abortion, citing 2019 comments from Gov. Ralph Northam (D) in which he was asked about state legislation that would relax restrictions on third-trimester abortions.  Northam said that third-term abortions are rare and typically occur when an infant is severely deformed or unable to survive after birth. Virginia House Republicans ended up tabling the legislation.

Sears tied her opponent, state Del. Hala Ayala (D), to Northam’s comments.

“Here’s the thing,” Sears said. “When did it become the wrong thing for us to support the babies in the womb? And in fact, in Virginia, we’ve even gone further than that, where our current governor wanted to take us — and, by the way, my opponent wanted to take us — there, where the baby would be born, you would leave the baby on the table without any assistance or even keep it comfortable, and then wait for the mother to decide.”

Ayala touted the importance of electing a lieutenant governor in favor of abortion rights in a statement on Saturday, citing the lieutenant governor's tiebreaking role in the state Senate, which is currently split 20-20. 

"As Lieutenant Governor, I’ll never stop fighting to protect our fundamental rights," Ayala said. "Unfortunately, my opponent simply can’t say the same."

Youngkin has not said definitively whether he supports the Texas law but noted in comments this week that he would support abortion in cases of rape or incest, which differs from the Texas law. 

“My biggest concern when it comes to abortion in Virginia is my opponent’s extreme views where he actually advocates for taxpayer abortion that would actually be available all the way up through and including birth,” Youngkin said. 

"I'm pro-life. I've said it from the beginning of this campaign," he said. "I believe in exceptions in the case of rape, in the case of incest and in the case where the mother's life is in jeopardy." 

https://thehill.com/homenews/campaign/570859-virginia-gop-lieutenant-governor-nominee-says-she-would-support-heartbeat

Biden approval rating on COVID-19 down 10 points since late June: poll

 President Biden's approval rating for his handling of the coronavirus pandemic has dropped by 10 points since late June as the delta variant raises concerns and drives up cases nationwide.

In a new Washington Post/ABC News poll, 52 percent of respondents said they approve of the way Biden is handling the pandemic, which is down from the 62 percent of adults who gave him positive marks in late June.

The drop comes as the delta variant, which is more contagious than previous versions of COVID-19, is spreading rapidly throughout the U.S. and is now the dominant strain in the country.

Biden’s overall approval rating has also dropped since June, according to the new survey, falling from 50 percent to 44 percent.

Part of that decrease can be attributed to the situation in Afghanistan, pollsters noted.

Thirty percent of adults questioned said they approve of the president’s handling of the situation in Afghanistan, while 60 percent said they disapprove.

While a majority of those polled support Biden’s decision to withdrawal U.S. troops from Afghanistan and end America’s war, a large percentage of respondents disapprove of the way he handled the mission.

Twenty-six percent said they support the withdrawal and approve of Biden’s handling of the situation, while 52 percent said they support the withdrawal but disapprove of Biden’s handling.

Seventeen percent said they oppose the withdrawal overall.

The poll surveyed 1,006 adults between Aug. 29 and Sept. 1. The margin of error is plus or minus 3.5 percentage points.

https://thehill.com/homenews/administration/570886-biden-approval-rating-on-covid-19-down-10-points-since-late-june-poll

More Americans in new survey say they are at risk of getting sick from coronavirus

 More Americans now say they are at risk of getting sick from COVID-19 as the highly infectious delta variant spreads, according to a new poll.

The survey, conducted by The Washington Post and ABC News, found that 47 percent of adults said they have a high or moderate risk of getting sick from COVID-19, which was up from 29 percent who said the same in June.

When asked if they are worried about their perceived risk level, however, only 39 percent said they are very or somewhat concerned. Forty-five percent of respondents said they are not too worried or not at all worried.

More vaccinated and unvaccinated Americans in the new poll also rate their level of COVID-19 risk as high or moderate.

The percentage of vaccinated respondents who said their risk of getting sick from the virus was high or moderate jumped from 32 percent in June to 52 percent in the recent survey. For unvaccinated individuals, the percentage increased from 22 percent to 35 percent.

The increase in perceived risk level comes as the delta variant, which is more contagious than previous versions of the virus, spreads nationwide. It is now the dominant strain in the U.S.

The variant is driving up cases in the U.S., causing states across the country to see a summer surge.

The majority of recent hospitalizations and deaths, however, have mainly been among unvaccinated individuals, as inoculations have largely protected against serious illness.

The new Washington Post/ABC News poll also saw President Biden’s approval rating on his handling of the pandemic slip since last June, falling by 10 points to 52 percent.

The survey polled 1,006 adults between Aug. 29 and Sept. 1. The margin of error 3.5 percentage points.

https://thehill.com/policy/healthcare/570892-more-americans-in-new-survey-worried-about-getting-sick-from-coronavirus

Saturday, September 4, 2021

JAK Inhibitors: Can't Help It 'Bout the Shape I'm In

 BY DEREK LOWE

Messing around with cytokine signaling is a very large business indeed (because it's a very large area of cell biology as well). We've heard a lot about it during the pandemic, for example, with the too-vigorous immune response that gets many severely infected people into trouble. And that illustrates the balance in modulating such signaling: it's absolutely necessary for the immune pathways to function at all, so you certainly don't want to turn everything down too hard. But having these pathways roaring full blast for an extended period is bad news as well (thus the two-phase treatment with Covid patients - you don't want to start turning down cytokine signaling too early, nor do you want to wait too long if someone has progressed to the point where it's a problem).

Autoimmune conditions are a big reason that this is such a large market for the drug industry, of course: rheumatoid arthritis, psoraisis, and other conditions can indeed be improved if you just reach and in turn down an inappropriate or overactive immune response. There are a lot of ways to do this, which makes sense, considering the amount of biology involved. Autoimmune patients generally get methotrexate first, although the details of its effects on the immune system are complex and frankly not understood as thoroughly as you'd imagine for a drug that's been around since the Trumann administration. It can also be given with some of the newer agents, such as antibodies or fusion proteins that disrupt TNF-alpha signaling.

Those biologics are among the best-selling drugs in the world, and there have been many proposals to try to break into that market with small molecules rather than injected therapies. One class that's had massive amounts of work put into are the Janus kinase (JAK) inhibitors. I'm impressed that that Wikipedia link mentions that "JAK" originally stood for "Just Another Kinase" (it's true), but it turns out that they have two very similar phosphorylation domains (one regulatory, one acting on substrates), so retconning them with the two-faced Roman god worked out fine. (Not all of our benchtop nomenclature holds up so well. I wonder how many people who think about hERG assays realize that the acronym goes back to the Drosophila zanies and their mutant flies who looped around in ether vapors: the human Ether-a-Go-Go receptor. . .)

JAK (there are several subtypes) is a middleman in a lot of cytokine signaling, with the JAK-STAT pathway being a mighty bridge between extracellular signaling and downstream effects on gene transcription. And since we know an awful lot about making kinase inhibitors it was recognized early on as a promising drug target. Several of them have made it to market: Xeljanz (tolfacitinib), whose name is a leading candidate for the drug that sounds most like a planet in an old science fiction story and which hits both JAK1 and JAK3,  Olumiant (baricitinib, JAK1 and JAK2), Jyseleca (filgotinib, more JAK1 selective), Rinvoq (upadacitinib, more JAK1 selective), Jakafi (ruxolitinib, JAK1 and JAK2), and Inrebic (fedratinib, more JAK2 selective). Those first four are all approved as anti-inflammatories for autoimmune disease; the last two are used in myelofibrosis and some cancers. And those have shown good efficacy; they're the first oral drugs whose effects on rheumatoid arthritis can match those of the anti-TNF biologics. 

You'll note the various subtype selectivities mentioned, but those are, believe me, only a very rough guide. The differential selectivities of these compounds is a very knotty subject, especially in its implications for therapeutic efficacy and for incidence of side effects. That last part has been the subject of some news just recently. The FDA required Pfizer to do a post-approval study of Xeljanz to further characterize those effects versus the biologic therapies, and that one read out earlier this year. It wasn't reassuring: Xeljanz did not meet the non-inferiority endpoints for cardiovascular and oncology side effects. This was in an older population with known cardiovascular risk factors (and oncology risk factors such as smoking), but that's the real-world population for a lot of those RA prescriptions, of course. 

As the old Peter Green/Fleetwood Mac song had it, "Don't ask me what I think of you - I might not give the answer that you want me to". So it is with clinical trial data, and the question has been what the FDA would do with this information. Today they required warning labels on Xeljanz, Olumiant, and Rinvoq. Jyseleca isn't approved yet in the US, and Jakafi and Inrebic aren't approved for indications like RA at all. No one was particularly surprised at this for the first two, but Rinvoq (as mentioned above) is a more selective second-generation compound, and Abbvie (and its investors) weren't expecting it to be lumped in on the warning label requirement. As you'll see from that link, it looks like the entire JAK class is already slipping behind the biologics with physicians and insurors, and all this is going to run right into plans to extend their use to less severe autoimmune conditions like atopic dermatitis. It may still be that some JAK inhibitor types are cleaner than others, or show better efficacy in particular conditions that will raise their risk/benefit above the rest. But it's not going to easy to sort this out - if Abbvie or any other company would like to try to prove it, they're welcome to go for it in a controlled trial. And that's probably the only thing that would really convince everyone, but you're looking at several years of work and expense. If you enjoy making such calls, then a career as a pharma executive might be for you!

https://www.science.org/content/blog-post/jak-inhibitors-can-t-help-it-bout-shape-i-m

Keeping Up With the Coronavirus Variant Landscape

 BY DEREK LOWE

I'd like to recommend this excellent article by Olivia Goodhill at Stat for people wondering how you keep a vaccine up-to-date given the constant emergence of viral variants. It's an exclusive look at Pfizer's Pearl River site, which has that important but extremely demanding assignment, and it's a look at what really is the state of the art in commercial vaccine development. The usual warnings abou the complexity of human immunology apply, and how:

Studying Covid-19 has only emphasized how little we know. “A lot of times, when you’re working in this field, you’d look at the animal data and say this thing has a wimpy antibody response, let’s not go ahead with it,” said Roopchand. Data from the Phase 3 efficacy study of the Covid vaccine undermines that approach: Vaccinated participants have protections against the virus by day 12, at a time when there’s barely any antibody response. “That was the biggest surprise,” said Roopchand.

The good news is that these people (and many others around the world) are working frantically to characterize the viral mutations and the effectiveness of the current vaccines against them. That's basically an endless job right now. Millions upon millions of new coronavirus infections are happening, and each patient generates untold numbers of new viral particles, and each of the replications that generate each one of those is capable of throwing some new RNA variant into the mix. For any organism, fidelity in copying the genetic material is not so much an on-off switch as it is a dial marked "looser" and "tighter".

The amount that dial can turn and the levels it selects from are determined in a broad sense by evolutionary fitness. Many creatures (such as us!) have pretty extensive error-correcting machinery and are definitely on the "tighter" part of that rheostat dial. Viruses, though, replicate so quickly with such tight space constraints in their genomes (and are under such constant attack from their hosts) that a looser setting works out better for them in the long run. Even so, coronaviruses in general rather huge genomes already, perhaps the largest of the RNA viruses. A lot of that is devoted to proteins that affect the immune response of their hosts - which for SARS-CoV-2 now includes us, damn it all - and a lot of it codes for proteins involved in replication. Since viruses don't eat or mate, these are really where you'd expect the action to be anyway. The proteins that do the RNA synthesis and proofreading are nsp12 through nsp16, with nsp12 being the RNA polymerase itself and nsp14 being the proofreading enzyme. (See this overview of coronavirus biology for more). Those are the enzymes that have landed in the "good but not perfect" space, because a virus that went all the way up to nearly perfect fidelity could easily find itself boxed in as the environment around it changed, even if it were able to carry around all that high-quality enzymatic machinery at all. It works out better to throw the occasional mutation just to vary things up.

Bacteria are of course a lot larger and more complex than viruses, and as an aside, their "genetic fidelity" rheostat has a meta-rheostat of its own. Many bacteria switch over to more error-prone replication under stress, an adaptation that starts throwing Hail Mary passes in all directions. Obviously enough of these actually complete in the end zone for this strategy to have been handed down! Otherwise we'd never have heard of it again, naturally - we're seeing the descendents of the bacteria for which this last-ditch move paid off. Viruses don't have quite that level of control, though, so they end up at whatever single fidelity setting keeps the population going the best.

And as you'll see from that Stat article, that's more than enough to keep everyone working night and day. These mutations can potentially affect every job that a virus has on its list - how easily it enters human cells, how well it can evade host defenses along the way, how quickly it replicates, and more. It's important not to fall into teleological thinking when you look at these things: the only thing that counts is how well any given form of the virus does at making more virus. It doesn't have to necessarily change to become more deadly, for example, and in fact going too far along those lines actually will keepit from spreading as well as it could otherwise. Imagine a virus that drops people in their tracks, dead inside of a half hour, versus one that allow for days where a person can wander around spreading it. The second one has a real advantage in the Make More Virus competition, which is the only competition there is.

But evading a host's immune system could well have a side effect of making a viral infection worse, and the problem is that its more immediate effect is that it can Make More Virus. The same is obviously true for mutations that increase infectivity (which could happen via more effective binding to human cell membranes, or faster replication once that gets going, or any number of other things). We're already seeing the Delta variant showing up a clearly more infective, so the big questions are whether that could be ratcheted up even more, and whether that could also come along with increased evasion to the immune responses raised by either vaccination or prior infection with a slightly earlier coronavirus variant.

To a good approximation, the answer to those questions is that we have no idea (although it's not for lack of trying to figure them out). Over the last week or so, a lot of people have asked me about this preprint, which suggests that the current Delta variant may be a short distance away, mutationally, from one that could indeed do a better (well, worse for us) job of evading vaccine immunity. It's not at all a crank paper, and this is just the sort of question that has to be addressed - but the good news (from what I can see) is that this work is not as doomful as its title makes it seem. This Twitter thread goes into some of the reasons. A big one is that the cell line that's being used doesn't really recapitulate the cell-entry pathway used out here in the real world (it doesn't have the TMPRSS enzyme involved, to be specific). That's involved with the "furin cleavage site", which is a key part of SARS-CoV-2, and as Jeremy Kamil notes in that thread, viruses without the FCS can look very impressive when infecting things like Vero cells in vitro. But if you want to claim increased infectivity, you have to use a more realistic cell line, or (better yet) demonstrate in animal models.

He also says (correctly) that we truly have no idea what mutations will show up next, in what order, or on top of what existing variants. So it's not as meaningful as it sounds to say that "If you take Delta and add only X more changes you'll get a supervirus!" or whatever. The number of potential mutations in the coronavirus genome is beyond comprehension. There are 29,811 RNA residues in its sequence, and changing these produces a vast number of potential altered proteins. Amino acids can change, stop codons can show up, frameshifts can occur; it just goes on and on. Some of these are more likely than others, but even when we can go that far, their effects are almost entirely unpredictable. I would advise taking any "we're this close to a terrible variant" headines with a lot of sang-froid. I mean, we might be. Or we might not.

It's surely easier to get a handle on some protein surface region that we know to be important, rather than tackling the whole fitness landscape at once. This preprint does that by looking at computational modeling of all the amino acid residues at the Spike/RBD interface with human ACE2 (the protein binding event that that is the first step for viral entry). I'm not the greatest customer for this sort of approach - there are plenty of uncertainties in modeling protein-protein interactions - but the authors are especially looking for outliers, non-additive mutations that make a big change all by themselves. And they're not seeing much evidence for them, outside of the mutations we already have. The possibilities tend strongly to be incremental and additive, rather than Sudden New Landscape types, and they end by saying that ". . .the modest ensemble of mutations relative to the WT shown to reduce vaccine efficacy might constitute the majority of all possible escape mutationsSo I will allow myself to be cheered up a bit by that, and I very much hope that they're right. I'm happy to imagine the coronavirus running out of options, but I'm not quite ready to break out the party hats just yet. The Pfizer scientists interviewed in Goodhill's article seem to be pretty evenly divided on the question, and honestly, there aren't any people in the world who are in a position to say more.

https://www.science.org/content/blog-post/keeping-coronavirus-variant-landscape

'Mu' coronavirus variant predominant in Colombia: health official

 A new coronavirus variant known as "Mu," identified first in Colombia in January, is now the country's predominant strain and behind its deadliest pandemic wave yet, a health official said Thursday.

The variant was responsible for Colombia's deadly third infection wave between April and June,  Marcela Mercado told a local radio station.

During this period, with about 700 deaths per day, nearly two-thirds of tests from people who died came back positive for the Mu variant, she said.

"It is already in more than 43 countries and has shown high contagiousness," she added.

On Tuesday, the World Health Organization declared Mu, scientific name B.1.621, a "variant of interest."

It said the variant has mutations that indicate a risk of resistance to vaccines and further studies were needed to better understand it.

"The Mu variant has a constellation of mutations that indicate potential properties of immune escape," the agency said.

There is widespread concern over the emergence of new variants as infection rates tick up globally, with the highly transmissible Delta  taking hold, especially among the unvaccinated and in regions where anti-virus measures have been relaxed.

All viruses, including SARS-CoV-2, which causes COVID-19, mutate over time and most changes have little or no effect on the properties of the virus.

But certain mutations can alter how easily a virus spreads, the severity of the disease it causes, or its resistance to vaccines and drugs.

The WHO lists four coronavirus variants of concern, including Alpha, present in 193 countries, and Delta, in 170.

Colombia recently has counted around 100 COVID-19 deaths and 2,000 infections per day, on average.

Less than a third of Colombians have been vaccinated against the , which has claimed nearly 125,000 lives in the country to date.

https://medicalxpress.com/news/2021-09-mu-coronavirus-variant-predominant-colombia.html

Predicting possible Alzheimer’s with near 100 percent accuracy

 Researchers from Kaunas universities, Lithuania developed a deep learning-based method that can predict the possible onset of Alzheimer's disease from brain images with an accuracy of over 99 per cent. The method was developed while analysing functional MRI images obtained from 138 subjects and performed better in terms of accuracy, sensitivity and specificity than previously developed methods.

According to World Health Organisation, Alzheimer's disease is the most frequent cause of dementia, contributing to up to 70 per cent of dementia cases. Worldwide, approximately 24 million people are affected, and this number is expected to double every 20 years. Owing to societal ageing, the disease will become a costly public health burden in the years to come.

"Medical professionals all over the world attempt to raise awareness of an early Alzheimer's diagnosis, which provides the affected with a better chance of benefiting from treatment. This was one of the most important issues for choosing a topic for Modupe Odusami, a PhD student from Nigeria," says Rytis Maskeli?nas, a researcher at the Department of Multimedia Engineering, Faculty of Informatics, Kaunas University of Technology (KTU), Odusami's PhD supervisor.

Image processing delegated to the machine

One of the possible Alzheimer's first signs is mild cognitive impairment (MCI), which is the stage between the expected cognitive decline of normal ageing and dementia. Based on the previous research, functional magnetic resonance imaging (fMRI) can be used to identify the regions in the brain which can be associated with the onset of Alzheimer's disease, according to Maskeli?nas. The earliest stages of MCI often have almost no clear symptoms, but in quite a few cases can be detected by neuroimaging.

However, although theoretically possible, manual analysing of fMRI images attempting to identify the changes associated with Alzheimer's not only requires specific knowledge but is also time-consuming -- application of Deep learning and other AI methods can speed this up by a significant time margin. Finding MCI features does not necessarily mean the presence of illness, as it can also be a symptom of other related diseases, but it is more of an indicator and possible helper to steer toward an evaluation by a medical professional.

"Modern signal processing allows delegating the image processing to the machine, which can complete it faster and accurately enough. Of course, we don't dare to suggest that a medical professional should ever rely on any algorithm one-hundred-per cent. Think of a machine as a robot capable of doing the most tedious task of sorting the data and searching for features. In this scenario, after the computer algorithm selects potentially affected cases, the specialist can look into them more closely, and at the end, everybody benefits as the diagnosis and the treatment reaches the patient much faster," says Maskeli?nas, who supervised the team working on the model.

We need to make the most of data

The deep learning-based model was developed as a fruitful collaboration of leading Lithuanian researchers in the Artificial Intelligence sector, using a modification of well-known fine-tuned ResNet 18 (residual neural network) to classify functional MRI images obtained from 138 subjects. The images fell into six different categories: from healthy through the spectre of mild cognitive impairment (MCI) to Alzheimer's disease. In total, 51,443 and 27,310 images from The Alzheimer's Disease Neuroimaging Initiative fMRI dataset were selected for training and validation.

The model was able to effectively find the MCI features in the given dataset, achieving the best classification accuracy of 99.99%, 99.95%, and 99.95% for early MCI vs. AD, late MCI vs. AD, and MCI vs. early MCI, respectively.

"Although this was not the first attempt to diagnose the early onset of Alzheimer's from similar data, our main breakthrough is the accuracy of the algorithm. Obviously, such high numbers are not indicators of true real-life performance, but we're working with medical institutions to get more data," says Maskeli?nas.

According to him, the algorithm could be developed into software, which would analyse the collected data from vulnerable groups (those over 65, having a history of brain injury, high blood pressure, etc.) and notify the medical personnel about the anomalies related to the early onset of Alzheimer's.

"We need to make the most of data," says Maskeli?nas, "that's why our research group focuses on the European open science principle, so anyone can use our knowledge and develop it further. I believe that this principle contributes greatly to societal advancement."

The chief researcher, whose main area is focusing on the application of modern methods of artificial intelligence on signal processing and multimodal interfaces, says that the above-described model can be integrated into a more complex system, analysing several different parameters, for example, also monitoring eye movements' tracking, face reading, voice analysing, etc. Such technology could then be used for self-check and alert to seek professional advice if anything is causing concern.

"Technologies can make medicine more accessible and cheaper. Although they will never (or at least not soon) truly replace the medical professional, technologies can encourage seeking timely diagnosis and help," says Maskeli?nas.


Story Source:

Materials provided by Kaunas University of TechnologyNote: Content may be edited for style and length.


Journal Reference:

  1. Modupe Odusami, Rytis Maskeliūnas, Robertas Damaševičius, Tomas Krilavičius. Analysis of Features of Alzheimer’s Disease: Detection of Early Stage from Functional Brain Changes in Magnetic Resonance Images Using a Finetuned ResNet18 NetworkDiagnostics, 2021; 11 (6): 1071 DOI: 10.3390/diagnostics11061071