So this comment is going to revolve around the supposed loss of T cell epitopes (Figure 3B/3C). I have spent an egregious amount of time giving the benefit of the doubt to these researchers, but alas, I cannot see how they have proven their result.
Just to recap the experiment (with my concerns in parenthesis):
1.) Mice were "immunized" with a pool of either Wuhan or Omicron spike peptides (now does injecting peptides into a mouse's footpad denote sterilizing immunity or just cellular debris to be collected by macrophages).
2.) After 10 days lymph nodes near the area of injection were removed and prepared as single cell suspensions (there are lots of immune cells in lymph nodes - many of which can secrete INFy - many of which are not T cells - there is no indication that any effort was made to separate out CD4+ cells which bind to MHC-Class II which I suppose is the whole reason for using transgenic DRB1*04:01 mice - however, CD8+T cells are the main source of INFy in lymph nodes and they bind MHC Class I - if you want to make a point about DRB1*04:01 they maybe you should only use a lymphocyte that binds Class II MHC - specifically CD4+ cells - there are ways to separate immune cells - magnetic beads or flow cytometry are routinely used to accomplish this).
3.) These cell suspensions were incubated with Wuhan and Omicron spike peptides - activated lymphocytes will secrete INFy which will bind to the biotinylated anti-INFy antibodies bound to the ELISpot plate. Then they add a streptavidin(binds to biotin)-alkaline phosphatase conjugate. And finally a BCIP/NTB which turns a pretty blue/purple in the presence of alkaline phosphatase.
The results certainly do indicate that mice primed with Wuhan are certainly having a reaction to Wuhan peptides. And, mice primed with Omicron are certainly having a reaction to Omicron peptides. That right there is called a secondary immune response. You can't immunize with one set of peptides and then challenge with the same plus another set of peptides - of course the first immunization will have a stronger signal - it's had more time develop. It would be more interesting if they did a Wuhan peptide challenge and after some time an Omicron peptide challenge and after some more time run this assay (but maybe with just CD4+ T cells). If only Wuhan or only Omicron signals were seen then it could suggest imprinting.
Also interesting (which they do not mention) is the T547K peptide clearly has a response for all challenges although it is not listed as a likely candidate for a DRB1*04:01 restricted epitope (Table S9). And making a big deal over the "loss" of the Q493R... DRB1*04:01 restricted epitope when the computer modeling again predicted its loss (umm, maybe the 3 amino acid difference had something to do with that). There's a lot going on in the paper and just accepting their results is a bit ludicrous.
On a lighter note: I enjoy Cara Cara oranges and Honeycrisp apples!
I think this adds even further to the really suspicious addition of this study! The whole throwing in a priming study when referring to imprinting, when all the researchers likely did was lead to two priming with one confirmation is a pretty dangerous game to play with readers.
I saw the T547K mutation as well. You can see they once again chose a few epitopes to consider in their analysis.
Overall, I felt as if the T-cell study was very flawed, but it certainly is far more flawed than I initially assumed!
I'm probably one of those that downloaded this study, along with dozens and dozens of others I have also not read.
I only glanced at it, only thinking that this may actually be useful after we get to the worldwide recognition that the recipients of the "gene therapy" have damaged immune systems, politics be damned, and that this "(not a) vaccine" campaign will be viewed in the future as a bigger screw up than war, global warming, slavery, Communism, religious radicalism, centralized world government, or trans ideology.
First off, I think it's a generally good idea to download most studies because I have some feeling that eventually many of these studies will move from preprint to peer-reviewed status and at that point they'll be put behind a paywall.
We also have to make sure that we know the studies that we cite. I think there's a growing issue in which studies are picked that don't actually provide the information that people assume it to provide.
So we can't look at this study and say "this study says that vaxxed people's immune systems are shot" because that's not what the study is designed to show, nor can we extrapolate anything because of the lack of groups such as those who were naturally immunized.
I'm actually curious by your response Edwin. Was there something that led you to believe that this study would be an indication for the vaccines damaging the immune systems? Not asking antagonistically, but I'd like to hear your perspective.
Well, like a lot of folks I download stuff in case it becomes unavailable later. For instance that first Indian study identifying the GP120 insert, which of course was withdrawn later.
No, I didn't save this because it might be 'evidence' or anything like that, just that it might be relevant later when the medical system will hopefully admit the damage the "not a vaccines" have done and much more importantly, try to do something to help the victims of this fraudulent treatment. Who knows, in the closing stages of this cluster, what may be erased, toxified with disinformation, or denied to even exist. 6 months to 6+ years from now.
As a member of the health care system for 38 years ending in 2017 (retirement), my greatest hope is that we will eventually DO THE NEXT RIGHT THING AND HELP THESE PEOPLE.
We now have a "Death Care System" in which some folks are saying deny medical treatment to the 'pureblood' and there are even voices on the other side that blame the victims of the mRNA shots for their predicaments!
All of us, ALL OF US, have been victimized by this call it what you will.
I call it "Divide and Conquer."
Think of your children/grands, neighbors, community, schools, the grocery clerk, mailman, UPS delivery guy/gal, babysitter, mechanic, niece/nephew, Terminex guy, whatever, all these folks you interact with far more than the congressman/senator setting policy for ALL OF US!
We will need "all hands on deck" to have any chance of rescuing even a sliver of our past respect and admiration from the patients we serve. We have found we have precious few 'warriors' among the medical system, very few 'sheepdogs' and mostly a bunch of wussies with zero propensity to fight for the general patient welfare, relative to their Lexus car payment, or that new iPhone model they so crave.
Something went bad wrong decades ago with the attitude in health care.
Attitude-Behavior-Consequence.
And we are living with the consequences now!
What was it, well, for one thing, we started seeing ourselves as superior to those we served.
Too much Medicaid, Medicare, crappy insurance, 'fast food' care, oversight, metrics, administration squeezing every penny, administrators, accountants, Big Pharma, schemes, scams, lies, and fraud.
We "collectivized" it!
Sorry for the rant, but actual study analysis actually had little to nothing to do with it.
Thanks for your response Edwin. Those who have been in the trenches of our healthcare systems are likely to be the ones who can see a lot of what's going on. I'm much younger than you (put into perspective, I'm younger than you have been employed in the healthcare industry). For many of us who may have felt something was off it certainly came to fruition with COVID and was heavily amplified by these policies, only people like yourself likely saw things such as this coming years ago.
I suppose I was curious as to the application of the study in my response above (i.e. what would you take away from this study and use as a reference), but regardless having the information at your hands and learning for yourself how to discern the information is really one of the greatest tools you can have.
Empowering yourself by becoming knowledgeable is something that we should all strive for, and I suppose because of this I have grown more concerned that many people are falling into the trap of becoming emotionally driven rather than informed and knowledgeable.
And like I've told others, you shouldn't apologize for a rant! This isn't Twitter, and I much prefer people post their thoughts if it leads to discussion.
Thanks Kurt! I hope the information came across. I kept looking at it thinking I needed to add more variables and make it too complicated but I left it be.
I am nowhere near done reading/pondering ... but right off the bat I have some hesitation seeing that this paper is coming out of Imperial College London (notoriously bad modeling of the Covid outbreak). Of course, this could be purely coincidental and have absolutely no bearing on this paper. I just noticed it and thought I would make that comment.
Huh, I didn't look into that but I suppose I should have seen that and stopped right there!
Seriously though, if there was any indication that we should hesitate to make a "this is clearly showing the vaccines are bad!" type of response with respect to this study, it probably should be something such as this which indicates there's probably a heavy bias in favor of the vaccines to begin with.
RE “No Natural Immunity Cohort” it should once again be mentioned that the study shows an unvaxxed cohort of 18 in supplemental fig S1 (https://www.science.org/action/downloadSupplement?doi=10.1126%2Fscience.abq1841&file=science.abq1841_sm.pdf) but this group disappears after the week 71 reorganization which limits the flow to double-vaxxed. What should be shown here is three lines connecting Wuhan, Alpha, and uninfected double vaxxed Week 55 squares to the new more limited week 71 set. There’s no good reason why the authors didn’t draw the missing arrows here. By my reading, this suggests that the Alpha group were vaxxed before infection, but it could be the other way around. *edit: Actually it seems like recruitment was re-initiated at weeks 71, 83, and 94 so maybe these HCWs aren’t even in the original part of the study. But this still suggests they could simply have “re-recruited” either previous or new unvaxxed subjects.
Your caption for Figure 3 suggests a misread, though I am not sure if this carries through to your whole discussion of this part. 3B is Wuhan-peptide-pool primed mice, 3C is Omicron-pool-primed, both are then tested with both peptide pools, with the results shown per original/variant peptide type. So “The top figure takes transgenic mice primed by either Wuhan or Omicron peptide pools, then introduces individual epitopes from Wuhan spike to measure individual responses to each epitope” would be incorrect. Note that even the authors mess up their description here, at one point saying the Omicron-primed mice were n=7 when it was the Wuhan primed mice who were 7. A gigantic crazy mess, their work.
Ok, I think I see the problem with my caption. I think it's because I used "figure" to refer to both plots, yet I probably should have discerned whether I was referring to "plot" or "figure" so I'll try fixing that.
Edit: scratch that, the issue is that in-text information was correct, however I added the caption before publishing and I think I mixed up the wording there. You're right, it should read that the top is Wuhan-primed but exposed to epitopes from both spikes and the bottom is Omicron-primed given both epitopes.
I kind of thought it was an artifact of the writing process. One thing I like to do in general but especially when presenting confusing figures is annotate up the wazoo. So for this one I would insert the missing labels for B and C, add more accurate per-variant labels for each peptide (put "417K" over red and "417N" over black, etc.), and whatever else helps describe what the authors are actually showing. Feel free to steal this approach but please note that the Apple Orange color in Preview is officially "my brand."
Yes, so just to provide context I generally save the captions for last. I finished most of the written portion last night and put together the caption this morning, so I believe the gap and sleep made for that error, although I really should have caught it.
I definitely see you annotate a lot! I have considered it but then I get worried that I will end up covering up the figures, or maybe it'll cause more confusion. In reality, it's probably something I should really practice more rather than post everything in written form in the caption.
I have no idea what the Apple Orange color is... is there a feature I am unaware of?!
I use the default Preview app that comes with Mac OS. It's actually horrible. I used to use Sketchup a lot because it lets you place things with math; but it wasn't designed for 2D images and it shows. My license expired anyway.
Thanks for the comments Brian. To your first point I suppose I should have clarified that, from what I can tell, the authors may not mention of the unvaccinated cohort. They're not included anywhere in the actual analyses, and from that I made a remark that we may be entering into a climate in which researchers will not want to be caught dead including anyone who either wasn't vaccinated or naturally immunized, and so maybe they just threw out that whole cohort. I do wonder if maybe this group may have been one to have been "let go" due to mandates, but even then they would at least exist for that part of the study.
Your re-recruitment comment is interesting. There's a few points (Fig 1E, 1F) where the numbers between the cohorts are different. Most notably the delta group doubled, which I found a bit strange since that may at least affect the analysis. I kind of let that part go.
Thanks for pointing out the issue with the Figure 3 part. I bounced around this section a lot so I added/removed many things and so I think the end result led to that confusing wording. I'll try to change the language to make it more clear.
Maybe this would be improper of me to comment, but considering that I mentioned Dr. Malone's post I was wondering a few things that stood out to me in his analysis. I was actually going to include a few criticisms but this post already ran long.
One thing that you didn't mention was his last section (Prior infection differentially imprints Omicron T and B cell immunity). In it he includes a comment that 2 doses offered protection, yet 3 doses did not.
That didn't make sense to me, and I came to find out that he left out this part of the results:
"Two to three weeks after two vaccine doses there was a levelling up of S1 RBD B.1.1.529 (Omicron) binding antibody, such that infection-naïve, prior Wuhan Hu-1 and B.1.1.7 (Alpha) infected HCW made similar responses (Fig. 6, B and C)."
So in his remarks he took those the 2-3 week post 1 jab group then compared them to the 20-21 week post 2nd jab group, essentially adding an additional variable via time-lapse.
I'm not sure why this was done, and yet this completely changes the interpretations of those results. So I suppose I would like to hear your thoughts.
I would guess that he fell victim to relying primarily on the author's text to structure his review. So he pulls the quote about 2-3 weeks post D1, without looking at the figure to perform his own interpretation in a more wholistic way. He then extrapolates implications from the quote which would have been totally contradicted by a wholistic analysis. *edit: Maybe this is too generous. I didn't notice the first time how extra-botched this part of his post was.
Almost everything in that section / figure of the paper is a ridiculous mess. As with the first sections it's totally bewildering why they think there is anything to glean from the fact that anti-Omicron antibodies wane and then come back up after boosting with Wuhan spike. Like, duh. They are sort-of-matching antibodies, when there's more of them then sera sort-of-neutralizes, when there's fewer then sera doesn't, when the uninfected are first-dosed they won't have a lot, whereas the previously infected will have recall antibodies right off the bat, this is all obvious and uninteresting. But just by describing their own results in the most evasive terms possible the authors create a Rorschach test that the reader can use to see whatever you want to see.
The rest of fig 6 is the interesting bit where the Wuhan+vaxxed are flat at neutralization post-Omicron-wave-infection, as I noted in my comment to the previous post. But here things are really sabotaged by the small n of 6. Details about these subjects are in supplemental table S7. There's nothing to suggest they were actually Delta infected but it can't be ruled out (only recruitment date, not PCR+ date, is provided); also 2 were asymptomatic and the other 4 had fewer symptoms, and a predominance of "cough" which isn't quite as much of an Omicron signature. The authors should have taken the non-response against Omicron as prima-facie reason to question whether these were really Omicron infections rather than some huge brilliant discovery.
I suppose I do wish Dr. Malone was more careful in his analysis, mostly because his argument that this is an indication that the vaccines are causing imprinting wasn't substantiated (I think we should be a little leery when the article is trying to blame infection rather than the vaccine for causing imprinting), and also that many people may see the post but don't understand if/where the faults in the study are.
Honestly, I guess I'm rather tired of looking at the figures for this article. This really just makes me want to look back at other studies I've cited and see if I botched the analysis of their analyses.
I probably should have considered that this study should have done genomic sequencing to validate the variant, rather than assume due to the dominant variant. As to the small n, the small n can really just be an explanation for all of the strange data.
Do you guys ever write the folks who do these studies and ask them to explain their assumptions (or lack thereof), explanations (or lack thereof), etc.?
Honestly, I legitimately never thought to do such a thing. I suppose this type of academic interaction is one that I am unfamiliar with. I should actually consider providing some criticism.
My main reason for writing these types of posts is to provide some commentary/ a different perspective on the study and point out a few criticisms so that people may assess for themselves whether there are flaws, or whether the study is up to par.
Maybe it's the attorney in me 😂...wanting to get the facts right and set the record straight so to speak. You did such a beautiful, thorough analysis. I am (clearly) not in your field, but smart enough to see the discrepancies and holes in their analysis based on yours. I would be so curious to see what they said. Now, Brian wrote someone who didn't respond. However, 1) they at least know people are looking at this critically and 2) perhaps, if they read it, even though they may not want to admit it, they'll be more diligent on their next study.
I think what's interesting is that now with everything being released in a preprint form or open access it probably allows everyone to post and comment in any fashion. I wonder if the researchers/editors do some work to filter out the "unprofessionals" to choose who to respond to 🤷♂️
I wrote the contact on the Röltgen, et al. germinal center study pointing out my solution to the finding that had them so puzzled. No reply. But for this kind of "free peer review" commentary I think the more customary approach is to write the editor, like "here's the problem with the hot mess you published." Then that gets published in the letters journal and the study authors reply to that. That's the way it used to be but I don't know if that's gone away the last 20 years with the internet.
OTOH if it's preprint I usually post my critique in the comments at medrxiv.
I have it on backburner to lightbulb ways to be more engaged with the folks behind these studies, for now I don't really know what would work.
Thank you for your reply (I follow your Substack, too :) ). I just replied to MD's comment on this. I'm not in your field, so I don't know the best way to get to people. I just Google the heck out of people...LinkedIn, Spokeo, Intellius and look to find their cell phone numbers and email addresses 😂 and then contact them directly. I've always been successful. Thank you for all the work you do and for reaching out to tell them about their hot mess! 😤
I may have missed that, because I can only remember a giant table showing symptoms and minor demographic data. I may have to go back and check that out.
So this comment is going to revolve around the supposed loss of T cell epitopes (Figure 3B/3C). I have spent an egregious amount of time giving the benefit of the doubt to these researchers, but alas, I cannot see how they have proven their result.
Just to recap the experiment (with my concerns in parenthesis):
1.) Mice were "immunized" with a pool of either Wuhan or Omicron spike peptides (now does injecting peptides into a mouse's footpad denote sterilizing immunity or just cellular debris to be collected by macrophages).
2.) After 10 days lymph nodes near the area of injection were removed and prepared as single cell suspensions (there are lots of immune cells in lymph nodes - many of which can secrete INFy - many of which are not T cells - there is no indication that any effort was made to separate out CD4+ cells which bind to MHC-Class II which I suppose is the whole reason for using transgenic DRB1*04:01 mice - however, CD8+T cells are the main source of INFy in lymph nodes and they bind MHC Class I - if you want to make a point about DRB1*04:01 they maybe you should only use a lymphocyte that binds Class II MHC - specifically CD4+ cells - there are ways to separate immune cells - magnetic beads or flow cytometry are routinely used to accomplish this).
3.) These cell suspensions were incubated with Wuhan and Omicron spike peptides - activated lymphocytes will secrete INFy which will bind to the biotinylated anti-INFy antibodies bound to the ELISpot plate. Then they add a streptavidin(binds to biotin)-alkaline phosphatase conjugate. And finally a BCIP/NTB which turns a pretty blue/purple in the presence of alkaline phosphatase.
The results certainly do indicate that mice primed with Wuhan are certainly having a reaction to Wuhan peptides. And, mice primed with Omicron are certainly having a reaction to Omicron peptides. That right there is called a secondary immune response. You can't immunize with one set of peptides and then challenge with the same plus another set of peptides - of course the first immunization will have a stronger signal - it's had more time develop. It would be more interesting if they did a Wuhan peptide challenge and after some time an Omicron peptide challenge and after some more time run this assay (but maybe with just CD4+ T cells). If only Wuhan or only Omicron signals were seen then it could suggest imprinting.
Also interesting (which they do not mention) is the T547K peptide clearly has a response for all challenges although it is not listed as a likely candidate for a DRB1*04:01 restricted epitope (Table S9). And making a big deal over the "loss" of the Q493R... DRB1*04:01 restricted epitope when the computer modeling again predicted its loss (umm, maybe the 3 amino acid difference had something to do with that). There's a lot going on in the paper and just accepting their results is a bit ludicrous.
On a lighter note: I enjoy Cara Cara oranges and Honeycrisp apples!
Thanks so much Clarisse. You dived in even further and criticized the study even deeper. I suppose this is warranted:
https://www.youtube.com/watch?v=UcZzlPGnKdU
I think this adds even further to the really suspicious addition of this study! The whole throwing in a priming study when referring to imprinting, when all the researchers likely did was lead to two priming with one confirmation is a pretty dangerous game to play with readers.
I saw the T547K mutation as well. You can see they once again chose a few epitopes to consider in their analysis.
Overall, I felt as if the T-cell study was very flawed, but it certainly is far more flawed than I initially assumed!
I'm probably one of those that downloaded this study, along with dozens and dozens of others I have also not read.
I only glanced at it, only thinking that this may actually be useful after we get to the worldwide recognition that the recipients of the "gene therapy" have damaged immune systems, politics be damned, and that this "(not a) vaccine" campaign will be viewed in the future as a bigger screw up than war, global warming, slavery, Communism, religious radicalism, centralized world government, or trans ideology.
First off, I think it's a generally good idea to download most studies because I have some feeling that eventually many of these studies will move from preprint to peer-reviewed status and at that point they'll be put behind a paywall.
We also have to make sure that we know the studies that we cite. I think there's a growing issue in which studies are picked that don't actually provide the information that people assume it to provide.
So we can't look at this study and say "this study says that vaxxed people's immune systems are shot" because that's not what the study is designed to show, nor can we extrapolate anything because of the lack of groups such as those who were naturally immunized.
I'm actually curious by your response Edwin. Was there something that led you to believe that this study would be an indication for the vaccines damaging the immune systems? Not asking antagonistically, but I'd like to hear your perspective.
Well, like a lot of folks I download stuff in case it becomes unavailable later. For instance that first Indian study identifying the GP120 insert, which of course was withdrawn later.
No, I didn't save this because it might be 'evidence' or anything like that, just that it might be relevant later when the medical system will hopefully admit the damage the "not a vaccines" have done and much more importantly, try to do something to help the victims of this fraudulent treatment. Who knows, in the closing stages of this cluster, what may be erased, toxified with disinformation, or denied to even exist. 6 months to 6+ years from now.
As a member of the health care system for 38 years ending in 2017 (retirement), my greatest hope is that we will eventually DO THE NEXT RIGHT THING AND HELP THESE PEOPLE.
We now have a "Death Care System" in which some folks are saying deny medical treatment to the 'pureblood' and there are even voices on the other side that blame the victims of the mRNA shots for their predicaments!
All of us, ALL OF US, have been victimized by this call it what you will.
I call it "Divide and Conquer."
Think of your children/grands, neighbors, community, schools, the grocery clerk, mailman, UPS delivery guy/gal, babysitter, mechanic, niece/nephew, Terminex guy, whatever, all these folks you interact with far more than the congressman/senator setting policy for ALL OF US!
We will need "all hands on deck" to have any chance of rescuing even a sliver of our past respect and admiration from the patients we serve. We have found we have precious few 'warriors' among the medical system, very few 'sheepdogs' and mostly a bunch of wussies with zero propensity to fight for the general patient welfare, relative to their Lexus car payment, or that new iPhone model they so crave.
Something went bad wrong decades ago with the attitude in health care.
Attitude-Behavior-Consequence.
And we are living with the consequences now!
What was it, well, for one thing, we started seeing ourselves as superior to those we served.
Too much Medicaid, Medicare, crappy insurance, 'fast food' care, oversight, metrics, administration squeezing every penny, administrators, accountants, Big Pharma, schemes, scams, lies, and fraud.
We "collectivized" it!
Sorry for the rant, but actual study analysis actually had little to nothing to do with it.
Thanks for your response Edwin. Those who have been in the trenches of our healthcare systems are likely to be the ones who can see a lot of what's going on. I'm much younger than you (put into perspective, I'm younger than you have been employed in the healthcare industry). For many of us who may have felt something was off it certainly came to fruition with COVID and was heavily amplified by these policies, only people like yourself likely saw things such as this coming years ago.
I suppose I was curious as to the application of the study in my response above (i.e. what would you take away from this study and use as a reference), but regardless having the information at your hands and learning for yourself how to discern the information is really one of the greatest tools you can have.
Empowering yourself by becoming knowledgeable is something that we should all strive for, and I suppose because of this I have grown more concerned that many people are falling into the trap of becoming emotionally driven rather than informed and knowledgeable.
And like I've told others, you shouldn't apologize for a rant! This isn't Twitter, and I much prefer people post their thoughts if it leads to discussion.
Thanks for the “Organic Chemistry for Dummies” apples vs. oranges (sans controls) example.
Thanks Kurt! I hope the information came across. I kept looking at it thinking I needed to add more variables and make it too complicated but I left it be.
I am nowhere near done reading/pondering ... but right off the bat I have some hesitation seeing that this paper is coming out of Imperial College London (notoriously bad modeling of the Covid outbreak). Of course, this could be purely coincidental and have absolutely no bearing on this paper. I just noticed it and thought I would make that comment.
Huh, I didn't look into that but I suppose I should have seen that and stopped right there!
Seriously though, if there was any indication that we should hesitate to make a "this is clearly showing the vaccines are bad!" type of response with respect to this study, it probably should be something such as this which indicates there's probably a heavy bias in favor of the vaccines to begin with.
Exactly the kind of comment we need!
RE “No Natural Immunity Cohort” it should once again be mentioned that the study shows an unvaxxed cohort of 18 in supplemental fig S1 (https://www.science.org/action/downloadSupplement?doi=10.1126%2Fscience.abq1841&file=science.abq1841_sm.pdf) but this group disappears after the week 71 reorganization which limits the flow to double-vaxxed. What should be shown here is three lines connecting Wuhan, Alpha, and uninfected double vaxxed Week 55 squares to the new more limited week 71 set. There’s no good reason why the authors didn’t draw the missing arrows here. By my reading, this suggests that the Alpha group were vaxxed before infection, but it could be the other way around. *edit: Actually it seems like recruitment was re-initiated at weeks 71, 83, and 94 so maybe these HCWs aren’t even in the original part of the study. But this still suggests they could simply have “re-recruited” either previous or new unvaxxed subjects.
Your caption for Figure 3 suggests a misread, though I am not sure if this carries through to your whole discussion of this part. 3B is Wuhan-peptide-pool primed mice, 3C is Omicron-pool-primed, both are then tested with both peptide pools, with the results shown per original/variant peptide type. So “The top figure takes transgenic mice primed by either Wuhan or Omicron peptide pools, then introduces individual epitopes from Wuhan spike to measure individual responses to each epitope” would be incorrect. Note that even the authors mess up their description here, at one point saying the Omicron-primed mice were n=7 when it was the Wuhan primed mice who were 7. A gigantic crazy mess, their work.
Ok, I think I see the problem with my caption. I think it's because I used "figure" to refer to both plots, yet I probably should have discerned whether I was referring to "plot" or "figure" so I'll try fixing that.
Edit: scratch that, the issue is that in-text information was correct, however I added the caption before publishing and I think I mixed up the wording there. You're right, it should read that the top is Wuhan-primed but exposed to epitopes from both spikes and the bottom is Omicron-primed given both epitopes.
I kind of thought it was an artifact of the writing process. One thing I like to do in general but especially when presenting confusing figures is annotate up the wazoo. So for this one I would insert the missing labels for B and C, add more accurate per-variant labels for each peptide (put "417K" over red and "417N" over black, etc.), and whatever else helps describe what the authors are actually showing. Feel free to steal this approach but please note that the Apple Orange color in Preview is officially "my brand."
Yes, so just to provide context I generally save the captions for last. I finished most of the written portion last night and put together the caption this morning, so I believe the gap and sleep made for that error, although I really should have caught it.
I definitely see you annotate a lot! I have considered it but then I get worried that I will end up covering up the figures, or maybe it'll cause more confusion. In reality, it's probably something I should really practice more rather than post everything in written form in the caption.
I have no idea what the Apple Orange color is... is there a feature I am unaware of?!
It's this one https://unglossed.substack.com/p/the-hot-spot#footnote-6
I like it because it looks very mark-up-y (not part of the original figure) but it's not too neon.
Oh, ok yes! By the way is there something you use to mark it up in that way? Maybe I'm showing how tech unsavvy I am right now.
I use the default Preview app that comes with Mac OS. It's actually horrible. I used to use Sketchup a lot because it lets you place things with math; but it wasn't designed for 2D images and it shows. My license expired anyway.
Thanks for the comments Brian. To your first point I suppose I should have clarified that, from what I can tell, the authors may not mention of the unvaccinated cohort. They're not included anywhere in the actual analyses, and from that I made a remark that we may be entering into a climate in which researchers will not want to be caught dead including anyone who either wasn't vaccinated or naturally immunized, and so maybe they just threw out that whole cohort. I do wonder if maybe this group may have been one to have been "let go" due to mandates, but even then they would at least exist for that part of the study.
Your re-recruitment comment is interesting. There's a few points (Fig 1E, 1F) where the numbers between the cohorts are different. Most notably the delta group doubled, which I found a bit strange since that may at least affect the analysis. I kind of let that part go.
Thanks for pointing out the issue with the Figure 3 part. I bounced around this section a lot so I added/removed many things and so I think the end result led to that confusing wording. I'll try to change the language to make it more clear.
Maybe this would be improper of me to comment, but considering that I mentioned Dr. Malone's post I was wondering a few things that stood out to me in his analysis. I was actually going to include a few criticisms but this post already ran long.
One thing that you didn't mention was his last section (Prior infection differentially imprints Omicron T and B cell immunity). In it he includes a comment that 2 doses offered protection, yet 3 doses did not.
That didn't make sense to me, and I came to find out that he left out this part of the results:
"Two to three weeks after two vaccine doses there was a levelling up of S1 RBD B.1.1.529 (Omicron) binding antibody, such that infection-naïve, prior Wuhan Hu-1 and B.1.1.7 (Alpha) infected HCW made similar responses (Fig. 6, B and C)."
So in his remarks he took those the 2-3 week post 1 jab group then compared them to the 20-21 week post 2nd jab group, essentially adding an additional variable via time-lapse.
I'm not sure why this was done, and yet this completely changes the interpretations of those results. So I suppose I would like to hear your thoughts.
I would guess that he fell victim to relying primarily on the author's text to structure his review. So he pulls the quote about 2-3 weeks post D1, without looking at the figure to perform his own interpretation in a more wholistic way. He then extrapolates implications from the quote which would have been totally contradicted by a wholistic analysis. *edit: Maybe this is too generous. I didn't notice the first time how extra-botched this part of his post was.
Almost everything in that section / figure of the paper is a ridiculous mess. As with the first sections it's totally bewildering why they think there is anything to glean from the fact that anti-Omicron antibodies wane and then come back up after boosting with Wuhan spike. Like, duh. They are sort-of-matching antibodies, when there's more of them then sera sort-of-neutralizes, when there's fewer then sera doesn't, when the uninfected are first-dosed they won't have a lot, whereas the previously infected will have recall antibodies right off the bat, this is all obvious and uninteresting. But just by describing their own results in the most evasive terms possible the authors create a Rorschach test that the reader can use to see whatever you want to see.
The rest of fig 6 is the interesting bit where the Wuhan+vaxxed are flat at neutralization post-Omicron-wave-infection, as I noted in my comment to the previous post. But here things are really sabotaged by the small n of 6. Details about these subjects are in supplemental table S7. There's nothing to suggest they were actually Delta infected but it can't be ruled out (only recruitment date, not PCR+ date, is provided); also 2 were asymptomatic and the other 4 had fewer symptoms, and a predominance of "cough" which isn't quite as much of an Omicron signature. The authors should have taken the non-response against Omicron as prima-facie reason to question whether these were really Omicron infections rather than some huge brilliant discovery.
I suppose I do wish Dr. Malone was more careful in his analysis, mostly because his argument that this is an indication that the vaccines are causing imprinting wasn't substantiated (I think we should be a little leery when the article is trying to blame infection rather than the vaccine for causing imprinting), and also that many people may see the post but don't understand if/where the faults in the study are.
Honestly, I guess I'm rather tired of looking at the figures for this article. This really just makes me want to look back at other studies I've cited and see if I botched the analysis of their analyses.
I probably should have considered that this study should have done genomic sequencing to validate the variant, rather than assume due to the dominant variant. As to the small n, the small n can really just be an explanation for all of the strange data.
Do you guys ever write the folks who do these studies and ask them to explain their assumptions (or lack thereof), explanations (or lack thereof), etc.?
Honestly, I legitimately never thought to do such a thing. I suppose this type of academic interaction is one that I am unfamiliar with. I should actually consider providing some criticism.
My main reason for writing these types of posts is to provide some commentary/ a different perspective on the study and point out a few criticisms so that people may assess for themselves whether there are flaws, or whether the study is up to par.
Maybe it's the attorney in me 😂...wanting to get the facts right and set the record straight so to speak. You did such a beautiful, thorough analysis. I am (clearly) not in your field, but smart enough to see the discrepancies and holes in their analysis based on yours. I would be so curious to see what they said. Now, Brian wrote someone who didn't respond. However, 1) they at least know people are looking at this critically and 2) perhaps, if they read it, even though they may not want to admit it, they'll be more diligent on their next study.
I think what's interesting is that now with everything being released in a preprint form or open access it probably allows everyone to post and comment in any fashion. I wonder if the researchers/editors do some work to filter out the "unprofessionals" to choose who to respond to 🤷♂️
I wrote the contact on the Röltgen, et al. germinal center study pointing out my solution to the finding that had them so puzzled. No reply. But for this kind of "free peer review" commentary I think the more customary approach is to write the editor, like "here's the problem with the hot mess you published." Then that gets published in the letters journal and the study authors reply to that. That's the way it used to be but I don't know if that's gone away the last 20 years with the internet.
OTOH if it's preprint I usually post my critique in the comments at medrxiv.
I have it on backburner to lightbulb ways to be more engaged with the folks behind these studies, for now I don't really know what would work.
Thank you for your reply (I follow your Substack, too :) ). I just replied to MD's comment on this. I'm not in your field, so I don't know the best way to get to people. I just Google the heck out of people...LinkedIn, Spokeo, Intellius and look to find their cell phone numbers and email addresses 😂 and then contact them directly. I've always been successful. Thank you for all the work you do and for reaching out to tell them about their hot mess! 😤
I'm finally tackling this one for a post. It turns out there is a giant table in the supplemental materials with the actual raw data, amazing.
I may have missed that, because I can only remember a giant table showing symptoms and minor demographic data. I may have to go back and check that out.