Research news from Bhupesh Prusty

As I recall, they did deep immune profiling of patient and HC blood. They then ran a Machine Learning classification algorithm on the samples. The algorithm separated into LC vs non-LC. This had 94% correlation with the patient's self-reported diagnosis (i.e included in study with or without active symptomatology).

UMAP is Uniform Manifold Approximation and Projection for Dimension Reduction. See UMAP Dimensionality Reduction — An Incredibly Robust Machine Learning Algorithm.

 

Yes, I struggle with this and that's not even getting into the detail of ML algorithms. I guess there are two questions: is it valid to say that the two subgroups are so clearly different that this has to indicate an abnormal state (a "perfect model"); and whether this process is guided or unguided. Ie can you ask the machine the following?

Here is group of patient samples; each has "a bunch" of observational data.
Can you, the machine — with no knowledge of what any of these observations might mean — separate these samples into two or more sub-groups.
Let's say the machine reports back "there are two sub-groups in the samples you gave me", extremely widely divergent as defined by some valid distance-between-data mathematical construct.
The machine calls them 'Subgroup A' and 'Subgroup B'
You then do statistics referring back to your participants, which basically shows A = LC and B = HC per your/the patients' self reports (with maybe one or two incorrect).
You can then summarise the statistics as having 94% concordance between unguided machine classification and patient self-report.

That wouldn't be circular I think.

The alternative, that would be circular, would be guided classification: where you say here is 80% or 90% of our data-set; I'm telling you this subgroup is 'LC' and the other subgroup is 'HC'; can you make a classifier algorithm? We will then check this against the remaining 10 or 20% of our data-set to make sure it sticks.

I don't know anywhere near enough about ML to understand what they've done. There may be IT experts or scientists familiar with the techniques on the forum who could explain this better or further.

 

Prusty's talk at the Invest in ME conference 2023 is titled:
Herpesvirus reactivation as a trigger for mitochondrial dysfunction in ME/CFS

http://www.investinme.org/IIMEC15.shtml#about

 

https://www.tlcsessions.net/episodes/episode-54-dr-bhupesh-prusty-molecular-virologist

 

Here's an interview with Bupesh Prusty summarising his findings/thoughts so far.
Episode 54: Dr Bhupesh Prusty – Molecular Virologist
(Via TLC Sessions - Living with Long Covid.)
I hope you will find it illuminating. I think he's probably onto something fundamental to our disease. Let's hope so.

The interview with Prusty starts 8 minutes in. (It's general chit chat until then.)

https://www.tlcsessions.net/episodes/episode-54-dr-bhupesh-prusty-molecular-virologist

 

Ha ha. You beat me to it ... by 3 minutes!!

 

Interesting.

Ron Davis- something in the blood

Bhupesh-something missing in the blood

 

And.....

Dr Les Simpson- something different about the blood......diminished red blood cell deformability.....
In the 90s.

 

For anyone that can’t listen to the podcast, this bit is from 40 minutes in:

“We found that there is something which is normally there in every human being. In the patients, it starts to deplete inside the body. And it’s like a balance. You tilt toward one side, you start developing mild, tilt more, become moderate patient, you tilt completely, you completely lose it, become severe. Its the switch. It’s really amazing. The number of ME/CFS patients we have tested so far … The severe patients, they just completely lost this biomarker…”

 

Thank you for sharing this! Too tired to go in and listen right now, but very interested in these updates on his research. It really would be amazing to have an identified biomarker. Though don't want to get my hopes up too much!

 

Be very interesting if there is a genetic predisposition for this switch given that ME seems to run in some families .
It could give Decide ME something to validate .

 

Looking forward to reading the paper. It'd be great if they really have found something.

 

This is the first time I've felt genuine hope in two years. I hope prusty is really onto something here. I feel like if he was bullshitting at this point his reputation would be trashed?

Edit: By Bullshitting I mean exaggerating somehow, I'm not meaning to suggest prusty is lying.

And I am doing my best to temper my hopes with a healthy dose of realism.

 

This could just be a downstream effect, the lower the activity (i.e healthy, mild, moderate, severe) the lower the levels of many "biomarkers". It may just be a pointer to how inactive patients are.
Until he tells us what it is we have no way of knowing. I would temper optimism until then.

 

Indeed. I go back to my original thoughts which are that he should say nothing until he can say all of it. As John says it could simply be an illustration of lack of activity. Getting hopes up when you cant give all the info is cruel and irresponsible IMHO no matter how well meant.

 

https://twitter.com/user/status/1646795634517614593

 

To be fair, he might have to publish some findings before getting ethical approval for further tests on inactive controls (tetraplegics? teenagers?), but the showmanship is definitely irksome.

 

Bhupesh says this new work is relevant to the 2020 paper that something in serum causes mitochondrial disfunction. This latest model shows what the thing in serum is.

He says: Take the thing and put it in cell and it causes disfunction in healthy cells, changing metabolism and source of energy and causing endothelial cell mito disfunction.

I thought it was a lack of the thing, not the thing itself that caused disfunction?

He also says that Robert Phair said his 2020 paper was “Nobel prize worthy”. The same paper that people with science backgrounds on this board thought was incoherent and really more of a hypothesis paper than a paper that proved anything.

I dunno.. I am skeptical about scientists who seem to court attention.