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Good point! I suppose I'm hoping the word 'presumed' would do a lot of the heavy lifting and no one would notice.

Just for curiosity and in light of the fact DecodeME is not picking up so many long covid derived ME/CFS patients to our current knowledge. In the last update I remember I think DecodeME had far fewer than 1000 ME from long covid patients signed up so I'm wondering whether maybe there isn't...

I wonder how many people have both long covid and an ME/CFS diagnosis. My doctor was reluctant to diagnose me with CFS because it's an 'unhappy' diagnosis, so I might guess if someone has long covid they'd probably get diagnosed with long covid rather than ME or both - all conjecture obviously...

Quite selective inclusion criteria but no requirement for matching CCC or IOM criteria (unless that's built into the NINDS repository). Per2 is a transcription factor whose expression levels oscillate over a roughly 24 hour cycle and who regulates circadian rhythm related activity as I...

I think that might be to do with the number of groups. It looks like the number of LDs you get is 1-number of groups. Since they're looking at 4 groups in figures F and G there's presumably 3 LDs and they're only plotting two of them. The total of all three would be 100% I believe

I do think there could be some utility in this method in finding out which features are most responsible for separating the groups. Each of the features will have a loading value for each LD (or PC) which basically represent that feature's contribution to that LD. So imagine if you saw for...

I get values of 53% for LD1 and 47% for LD2 for proportion of separation respectively. My understanding is that it's not right to interpret these values as explaining the variation in the data overall, but as the proportion each LD is responsible for separating the different groups in this...

I've modelled this in R here using data with no signal and only random noise. In this paper they have about 1000 features (readings for 1000 different wavelengths) over 1000s of cells - so its dimensionality is high. I've generated a dataset for 1000 'samples' each with 1000 'features.' The...

Thanks for the breakdown @Hutan ! The problem with supervised machine learning of any kind - where you first tell the algorithm what the groups are (ME, MS, Controls) and then tell it to separate them as best as possible - is that if you have a large enough amount of 'features' for each sample...

I remember seeing this before and not being convinced so looking again to try and remind myself why. First thing is the wave forms of the different cohorts have been translated up or down in figures A and B to aid visibility. I thought this was a bit misleading as it makes it look like they are...

Oh and also Fluge and Mella are beginning pilot studies using the CD38 monoclonal Daratumumab - which additionally targets plasma cells (which rituximab does not). They reported some preliminary data on this at the Charite conference but far too early to make any conclusions. Still knowing the...

Agree that the things have been worth looking forward to are Prusty's biomarker, NIH intramural study and decode ME. Prusty's paper isn't out yet afaik but agree that what we know has underwhelmed. Agreeing also that Hanson lab is doing solid seeming work and that they had an interesting urine...

Too long, didn't read: Using some python libraries I have a set up which can track eye movements using a webcam. It does ok at detecting large eye movements but struggles with smaller ones which might be more important. I am not sure the data quality will be high enough to be useful at this...

Yeah I think that's true and it also depends on the type of video game. There are some that require high reaction times and some that require a lot of 'organisation,' reading bits of text and balancing numbers and puzzle solving. Generally speaking I've found video games a relaxing activity but...

I want to try and test some different measures of cognitive exertion and want to document some thoughts here that I might update later (or more likely leave blank as available energy dictates). This will be a bit of a ramble. Commercial options for Eye Tracking There was some discussion...

Just checking to see if they see these genes in Ahmed & Grimson 2022's single cell RNA seq paper where they find some monocyte abnormalities in ME/CFS and then validate with RNA seq of bulk sorted monocytes. monocyte chemokine related expression from scRNA-seq: bulk RNA-seq of monocytes...

That's brilliant thankyou. You're right that if you scroll back far enough you can see @ahandvanish did retweet. There's no straight forward way to search for retweets by text of the embedded tweet that I could find so I missed that.

I was just speaking to my british friend with long covid who is very integrated into the online community. I was surprised to find out they had never heard of DecodeME but are happy to share it. I did a twitter search of some long covid accounts with large numbers of followers and found none of...

In light of the other thread on actimetry I was just thinking again about the discussion i think in this thread about how to measure different kinds of exertion. One suggestion in this thread (EDIT: not in this thread but in a similar discussion in the past) for cognitive exertion was some kind...

For sure there's no stopping a disingenuous interpretation of the results. Obviously there will be a correlation between inactivity and fatigue and it should be blindingly obvious that you're doing less because you're tired and not the other way around - but as we've seen it's possible to spin...