1. When a system is very simple, we explain its actions in terms of its properties and external forces acting on it.
2. When it's a medium complexity system, we tend to explain its actions in terms of its design, putting ourselves in the designer's shoes.
3. When it's a complex enough goal-seeking system, we begin to empathise with the system itself, thinking why "it chose" a course of action.
I remember how impressed I was with this classification and how much sense it made in terms of how we're able to understand the world and predict what will happen next.
From this angle, much of modern computer software is clearly in category 3, and it just makes things easier for us to think of it as having a mind of its own.
Quoting from wikipedia "For the simplest vehicles, the motion of the vehicle is directly controlled by some sensors (for example photo cells). Yet the resulting behaviour may appear complex or even intelligent."
When you try to describe a complex or subtle thing concisely, you might find it hard. Even if the system is neither animal nor human, you too might notice yourself reaching for "character with motivations" to describe it.
> Covid-19 is like a burglar who slips in your unlocked second-floor window and starts to ransack your house.
https://www.cs.utexas.edu/users/EWD/transcriptions/EWD10xx/E...
"It is probably more illuminating to go a little bit further back, to the Middle Ages. One of its characteristics was that "reasoning by analogy" was rampant; another characteristic was almost total intellectual stagnation, and we now see why the two go together. A reason for mentioning this is to point out that, by developing a keen ear for unwarranted analogies, one can detect a lot of medieval thinking today."
https://www.cs.utexas.edu/users/EWD/transcriptions/EWD08xx/E...
And the ever-popular
https://www.cs.utexas.edu/users/EWD/transcriptions/EWD12xx/E...
"When we returned from the interview, some more legal professionals had arrived and there was a lively discussion going on. For me the exposure was a cultural shock, instructive, but also rather disorienting. Of course I knew that lawyers are not scientists, yet the atmosphere of a trade school took me by surprise. Of course I knew that lawyers mainly deal with national law, yet I was unprepared for the prevailing parochialism. (Now I come to think of it, the system of common law, based —as it is— on custom and precedent, could very well strengthen this phenomenon.) but the most disorienting thing was that I found myself suddenly submerged in a verbal tradition that was totally foreign to me! They were on the average very verbose —some even repetitive—, they had a tendency to "reason" by analogy and more than once I felt that speakers cared more about the potential influence of their words than about what they actually said. (Are these common professional deformations of the trial lawyer?) I spoke for ten minutes, that is, I tried to do so: after several hours of exposure I no longer knew how to address this crowd."
Why do you believe that?
Theories are attempts to explain the mechanism of something based on the observed data. Given data on patient symptoms and known drugs (ACE inhibitors in this case) and their effects, a computer could easily produce a theory that the disease acted like ACE inhibitors. It'd still take a human to write the program to generate these theories, but a computer could do it.
You might phrase a title that way if you believe that we trust computers more than we trust scientists. Is that true? I don't think so. But if it is, how horrifying.
We evolved in kinship groups. The most important phenomena to understand were your fellow humans, followed by animals.
The human brain has a highly-optimised "Character with motivations taking actions" parser.
"A person used a supercomputer to analyse Covid-19" conveys no more knowledge than "A supercomputer analyzed Covid-19".
One thing that I think strongly suggests that this hypothesis is wrong is that there is no strong relation between ACE-inhibitors and Covid mortality. Indeed, most of the studies that I've seen suggest that ACE-inhibitors have a somewhat protective effect whereas ARBs actually seem to have a minor detrimental effect [1]. So for the article to claim that covid behaves pharmacologically like ACE-inhibitors seems wrong at face value.
(I know this because I have the PubPeer extension installed which puts a big red warning by it.)
Perhaps you can clear up something for me. We've all heard how obesity and hypertension are risk factors for covid morbidity. But I could never get a clarification regarding treated vs. untreated hypertension.
AFAIK, many obese people take ACE inhibitors to treat hypertension. If we divide obese people into three groups: (a) untreated, (b) treated with ACE inhibitors, and (c) treated with other medications, how do their covid moribity rates compare?
This article does a great job outlining the current state of the knowledge on the subject of Covid/hypertension as well as some clinical trials that should be posting results early next year [1].
I haven't seen any studies that try and tease apart all of the complex relationships amongst various comorbidities, but I think we have seen pretty conclusively that obesity is a very significant risk factor.
[1]https://www.acc.org/latest-in-cardiology/articles/2020/07/06...
> ACE2 counters the activity of the related angiotensin-converting enzyme (ACE) by reducing the amount of angiotensin-II and increasing Ang(1-7)
The cell/tissue tropism of SARS-CoV-2 must logically have some effect on the function of the renin–angiotensin system (RAS). What is frustrating is that these questions remain unanswered.
[1] https://en.wikipedia.org/wiki/Angiotensin-converting_enzyme_...
[2] https://en.wikipedia.org/wiki/Pulmonary_alveolus#Type_II_cel...
The article is fluff.
98% of all bioinformatics is done on "supercomputers" or 'high performance computing environments" saying the researchers used supercomputers to analyze the expression data is like saying someone used a shovel to dig a hole.
"Put simply, medics found that severely ill flu patients nursed outdoors recovered better than those treated indoors. A combination of fresh air and sunlight seems to have prevented deaths among patients; and infections among medical staff.[1] There is scientific support for this. Research shows that outdoor air is a natural disinfectant. Fresh air can kill the flu virus and other harmful germs. Equally, sunlight is germicidal and there is now evidence it can kill the flu virus."
[1]: https://medium.com/@ra.hobday/coronavirus-and-the-sun-a-less...
I read that vitamin D and observed benefits for those who have vitamin D is a correlation. Meaning that taking vitamin D supplements might not be as helpful as getting sunlight (a natural way to get vitamin D)
Very very interesting theories as it also helped during the 1918 flu.
Lay people use the two interchangeably.
In at least two of the thesaurus I have at hand hypothesis is synonymous is theory.
"Here, we perform a new analysis on gene expression data from cells in bronchoalveolar lavage fluid (BALF) from COVID-19 patients that were used to sequence the virus. Comparison with BALF from controls identifies a critical imbalance in RAS represented by decreased expression of ACE in combination with increases in ACE2, renin, angiotensin, key RAS receptors, kinogen and many kallikrein enzymes that activate it, and both bradykinin receptors. This very atypical pattern of the RAS is predicted to elevate bradykinin levels in multiple tissues and systems that will likely cause increases in vascular dilation, vascular permeability and hypotension."
FTFY. They didn't measure patients. They modeled genomic interactions to make some predictions about biochemical effects on patients. Then they noted that some of those predicted effects correlate with symptoms of Covid patients. They went further and shotgunned a list of treatments which are known to affect the same biochemical processes. The farther along the path of inference, the weaker the conclusions get, but it sounds like a promising arrow for research to me.
> why they couldn't just measure bradykinine levels directly? Is that too hard?
Don't need nearly as much permission or human resources to run computer simulations on offline data as you do to take measurements of patients in the hospital.
It is. To measure gene expression, you isolate total mRNA and sequence it. This tells you the expression of all genes simultaneously. The protocol is fairly standard, cheap, and quick. That doesn't tell you anything about bradykinine, though, because there is no mRNA that codes for it.
In contrast, no such protocol exists for proteins. Sequencing a single protein is comparatively difficult, and no high throughput device exists that sequences lots of proteins, let alone quantifies their abundance. The traditional lab methods like PAGE gels are slow and labor intensive.
Hard to question that.
Really hoping this is better by the next few months or my Seattle winter will be even more pill popping to maintain basic human functionality....
If this info has been out since 5 months I'd expect several trials already that target the bradykinin storm.
It supposedly acts on the RAS and down regulates ace2
[1]: https://journals.physiology.org/doi/full/10.1152/ajpregu.000...
https://elifesciences.org/articles/59177
Excerpts from the abstract:
Bradykinin is a potent part of the vasopressor system that induces
hypotension and vasodilation and is degraded by ACE and enhanced by
the angiotensin1-9 produced by ACE2.
This very atypical pattern of the RAS is predicted to elevate
bradykinin levels in multiple tissues and systems that will likely
cause increases in vascular dilation, vascular permeability and
hypotension.
I could find only the article below on IBM's news section (they created this super computer). Speaking about the results of the 2 day analysis, Jeremy Smith, Governor’s Chair at the University of Tennessee, director of the UT/ORNL Center for Molecular Biophysics, and principal researcher in the study: “Our results don’t mean that we have found a cure or treatment for COVID-19. We are very hopeful, though, that our computational findings will both inform future studies and provide a framework that experimentalists will use to further investigate these compounds. Only then will we know whether any of them exhibit the characteristics needed to mitigate this virus.”
https://newsroom.ibm.com/US-Dept-of-Energy-Brings-the-Worlds...