These 'Beach Animals' were created by Theo Jansen as a fusion of art and engineering. The kinetic structures walk on their own and get all their energy from the
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https://t.co/hXlo8qgkD0
Look like that they got a classical case of PCR Cross-Contamination.
They had 2 fabricated samples (SRX9714436 and SRX9714921) on the same PCR run. Alongside with Lung07. They did not perform metagenomic sequencing on the “feces” and they did not get
A positive oral or anal swab from anywhere in their sampling. Feces came from anus and if these were positive the anal swabs must also be positive. Clearly it got there after the NA have been extracted and were from the very low-level degraded RNA which were mutagenized from
The Taq. https://t.co/yKXCgiT29w to see SRX9714921 and SRX9714436.
Human+Mouse in the positive SRA, human in both of them. Seeing human+mouse in identical proportions across 3 different sequencers (PRJNA573298, A22, SEX9714436) are pretty straight indication that the originals
Were already contaminated with Human and mouse from the very beginning, and that this contamination is due to dishonesty in the sample handling process which prescribe a spiking of samples in ACE2-HEK293T/A549, VERO E6 and Human lung xenograft mouse.
The “lineages” they claimed to have found aren’t mutational lineages at all—all the mutations they see on these sequences were unique to that specific sequence, and are the result of RNA degradation and from the Taq polymerase errors accumulated from the nested PCR process
Look like that they got a classical case of PCR Cross-Contamination.
They had 2 fabricated samples (SRX9714436 and SRX9714921) on the same PCR run. Alongside with Lung07. They did not perform metagenomic sequencing on the “feces” and they did not get
A positive oral or anal swab from anywhere in their sampling. Feces came from anus and if these were positive the anal swabs must also be positive. Clearly it got there after the NA have been extracted and were from the very low-level degraded RNA which were mutagenized from
The Taq. https://t.co/yKXCgiT29w to see SRX9714921 and SRX9714436.
Human+Mouse in the positive SRA, human in both of them. Seeing human+mouse in identical proportions across 3 different sequencers (PRJNA573298, A22, SEX9714436) are pretty straight indication that the originals
Were already contaminated with Human and mouse from the very beginning, and that this contamination is due to dishonesty in the sample handling process which prescribe a spiking of samples in ACE2-HEK293T/A549, VERO E6 and Human lung xenograft mouse.
The “lineages” they claimed to have found aren’t mutational lineages at all—all the mutations they see on these sequences were unique to that specific sequence, and are the result of RNA degradation and from the Taq polymerase errors accumulated from the nested PCR process
Hard agree. And if this is useful, let me share something that often gets omitted (not by @kakape).
Variants always emerge, & are not good or bad, but expected. The challenge is figuring out which variants are bad, and that can't be done with sequence alone.
You can't just look at a sequence and say, "Aha! A mutation in spike. This must be more transmissible or can evade antibody neutralization." Sure, we can use computational models to try and predict the functional consequence of a given mutation, but models are often wrong.
The virus acquires mutations randomly every time it replicates. Many mutations don't change the virus at all. Others may change it in a way that have no consequences for human transmission or disease. But you can't tell just looking at sequence alone.
In order to determine the functional impact of a mutation, you need to actually do experiments. You can look at some effects in cell culture, but to address questions relating to transmission or disease, you have to use animal models.
The reason people were concerned initially about B.1.1.7 is because of epidemiological evidence showing that it rapidly became dominant in one area. More rapidly that could be explained unless it had some kind of advantage that allowed it to outcompete other circulating variants.
Variants always emerge, & are not good or bad, but expected. The challenge is figuring out which variants are bad, and that can't be done with sequence alone.
Feels like the next thing we're going to need is a ranking system for how concerning "variants of concern\u201d actually are.
— Kai Kupferschmidt (@kakape) January 15, 2021
A lot of constellations of mutations are concerning, but people are lumping together variants with vastly different levels of evidence that we need to worry.
You can't just look at a sequence and say, "Aha! A mutation in spike. This must be more transmissible or can evade antibody neutralization." Sure, we can use computational models to try and predict the functional consequence of a given mutation, but models are often wrong.
The virus acquires mutations randomly every time it replicates. Many mutations don't change the virus at all. Others may change it in a way that have no consequences for human transmission or disease. But you can't tell just looking at sequence alone.
In order to determine the functional impact of a mutation, you need to actually do experiments. You can look at some effects in cell culture, but to address questions relating to transmission or disease, you have to use animal models.
The reason people were concerned initially about B.1.1.7 is because of epidemiological evidence showing that it rapidly became dominant in one area. More rapidly that could be explained unless it had some kind of advantage that allowed it to outcompete other circulating variants.
It was great to talk about reproducible workflows for @riotscienceclub @riotscience_wlv. You can watch the recording below, but if you don't want to listen to me talk for 40 minutes, I thought I would summarise my talk in a thread:
My inspiration was making open science accessible. I wanted to outline the mistakes I've made along the way so people would feel empowered to give it a go. Increased accountability is seen as a barrier to adopting open science practices as an ECR
It also comes across as all or nothing. You are either fully open science or your research won't get anywhere. However, that can be quite intimidating, so I wanted to emphasise this incremental approach to adapting your workflow
There are two sides to why you should work towards reproducibility. The first is communal. It's going to help the field if you or someone else can reproduce your whole pipeline.
There is also the selfish element of it's just going to help you do your work. If you can't remember what your work means after a lunch break, you're not going to remember months or years down the line
Thank you again @JamesEBartlett for a fantastic talk (with a really nice personal touch) on reproducible workflows!
— RIOT Science Club Wolverhampton (@riotscience_wlv) February 16, 2021
Thanks especially for the co-leads @IMLahart for co-hosting and @DrManiBhogal for nabbing James!
Slides: https://t.co/CNqxzOhch1
Video: https://t.co/YjHEHuRJlz
My inspiration was making open science accessible. I wanted to outline the mistakes I've made along the way so people would feel empowered to give it a go. Increased accountability is seen as a barrier to adopting open science practices as an ECR
It also comes across as all or nothing. You are either fully open science or your research won't get anywhere. However, that can be quite intimidating, so I wanted to emphasise this incremental approach to adapting your workflow
There are two sides to why you should work towards reproducibility. The first is communal. It's going to help the field if you or someone else can reproduce your whole pipeline.
There is also the selfish element of it's just going to help you do your work. If you can't remember what your work means after a lunch break, you're not going to remember months or years down the line
Why are lunch breaks important for #code?
— Dr Rebecca Hirst (@HirstRj) February 11, 2021
If you can't remember what your variable names refer to after lunch, you sure as hell won't remember in 3 months.
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1/ Here’s a list of conversational frameworks I’ve picked up that have been helpful.
Please add your own.
2/ The Magic Question: "What would need to be true for you
3/ On evaluating where someone’s head is at regarding a topic they are being wishy-washy about or delaying.
“Gun to the head—what would you decide now?”
“Fast forward 6 months after your sabbatical--how would you decide: what criteria is most important to you?”
4/ Other Q’s re: decisions:
“Putting aside a list of pros/cons, what’s the *one* reason you’re doing this?” “Why is that the most important reason?”
“What’s end-game here?”
“What does success look like in a world where you pick that path?”
5/ When listening, after empathizing, and wanting to help them make their own decisions without imposing your world view:
“What would the best version of yourself do”?
Please add your own.
2/ The Magic Question: "What would need to be true for you
1/\u201cWhat would need to be true for you to\u2026.X\u201d
— Erik Torenberg (@eriktorenberg) December 4, 2018
Why is this the most powerful question you can ask when attempting to reach an agreement with another human being or organization?
A thread, co-written by @deanmbrody: https://t.co/Yo6jHbSit9
3/ On evaluating where someone’s head is at regarding a topic they are being wishy-washy about or delaying.
“Gun to the head—what would you decide now?”
“Fast forward 6 months after your sabbatical--how would you decide: what criteria is most important to you?”
4/ Other Q’s re: decisions:
“Putting aside a list of pros/cons, what’s the *one* reason you’re doing this?” “Why is that the most important reason?”
“What’s end-game here?”
“What does success look like in a world where you pick that path?”
5/ When listening, after empathizing, and wanting to help them make their own decisions without imposing your world view:
“What would the best version of yourself do”?
