(THREAD CONTINUED)
As mentioned in the above videos human cloning has been confirmed and many of the elites you are now seeing are in fact clones or doubles standing in for themselves. The reason for these clones is because humanity has not yet awakened enough to handle knowing
More from Science
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.
If you are into cryptography or reverse engineering, you should love this.
Thread:
DNA consists of four different 'bases', A, C, G and T. These bases have specific meaning within our biology. Specifically, within the 'coding part' of a gene, a triplet of bases encodes for an amino acid
Most DNA is stored redundantly, in two connected strands. Wherever there is an A on one strand, you'll find a T on the other one. And similarly for C and G:
T G T C A G T
A C A G T C A
(note how the other strand is upside down - this matters!)
If you take all the DNA of an organism (both strands), you will find equal numbers of A's and T's, as well as equal numbers of C's and G's. This is true by definition.
This is called Chargaff's 1st parity rule.
https://t.co/jD4cMt0PJ0
Strangely enough, this rule also holds per strand! So even if you take away the redundancy, there are 99% equal numbers of A/T and C/G * on each strand *. And we don't really know why.
This is called Chargaff's 2nd parity rule.
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I've recently come across a disinformation around evidence relating to school closures and community transmission that's been platformed prominently. This arises from flawed understanding of the data that underlies this evidence, and the methodologies used in these studies. pic.twitter.com/VM7cVKghgj
— Deepti Gurdasani (@dgurdasani1) February 1, 2021
The paper does NOT evaluate the effect of school closures. Instead it conflates all ‘educational settings' into a single category, which includes universities.
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The paper primarily evaluates data from March and April 2020. The article is not particularly clear about this limitation, but the information can be found in the hefty supplementary material.
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The authors applied four different regression methods (some fancier than others) to the same data. The outcomes of the different regression models are correlated (enough to reach statistical significance), but they vary a lot. (heat map on the right below).
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The effect of individual interventions is extremely difficult to disentangle as the authors stress themselves. There is a very large number of interventions considered and the model was run on 49 countries and 26 US States (and not >200 countries).
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Here's how I'd measure the health of any tech company:
— Jeff Atwood (@codinghorror) October 25, 2018
How long, as measured from the inception of idea to the modified software arriving in the user's hands, does it take to roll out a *1 word copy change* in your primary product?
Hiring efficiency:
How long does it take, measured from initial expression of interest through offer of employment signed, for a typical candidate cold inbounding to the company?
What is the *theoretical minimum* for *any* candidate?
How long does it take, as a developer newly hired at the company:
* To get a fully credentialed machine issued to you
* To get a fully functional development environment on that machine which could push code to production immediately
* To solo ship one material quanta of work
How long does it take, from first idea floated to "It's on the Internet", to create a piece of marketing collateral.
(For bonus points: break down by ambitiousness / form factor.)
How many people have to say yes to do something which is clearly worth doing which costs $5,000 / $15,000 / $250,000 and has never been done before.