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Association of ADIPOQ rs1501299 with long-COVID syndrome: a single-center cross-sectional study Background Long-COVID syndrome is a public health issue, affecting millions of individuals worldwide. However, the pathophysiological mechanisms underlying the syndrome’s sequelae are still under...

3D Virtual Reality Performance Metrics as a Future Fatigue Biomarker in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) Background Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating disorder, characterized by symptoms such as post-exertional malaise...

Some posts have been moved to: A thread of no importance. Post something completely inconsequential.

What exactly are you basing T/A coding for valine on? Edit: You previously said the opposite for A and G. Why has that changed?

Yes, it looks comparable. The Post-exertional malaise topic (capitalized above) has a large correlation, but who knows what terms this encompasses. The specific term "post exertional malaise" is lower, but still high. Honestly, the idea about the correlation of ME/CFS searches with British...

Thanks! I should have done a quick search because just seeing the search results for "west virginia unhealthy" makes it very clear this probably is actually related to their health. I thought it might be an issue with Google Trends, but I guess instead this provides more support about Trends...

Something weird seems to be going on with West Virginia (WV). I keep seeing WV listed as the number one ranked state by search interest, or at least highly ranked, for various diseases. To examine this more systematically, I downloaded the Google Trends state scores for the 28 common conditions...

I tested the above suggestions, alongside ME/CFS, "tired", "always tired", and "fatigue" as well, for English, Scottish, and Irish ancestry. I sorted by Pearson, but also tested Spearman to see if large outliers are masking an association (which seems to be the case for Mississippi being an...

Relatively low correlations of Scottish or English ancestry with these four search terms: Note that the data for "type 1 narcolepsy" and "type 2 narcolepsy" might not be very reliable, because there looks to be very little search volume for these, and unlike most searches, states only have...

The correlation of English ancestry with early onset arthritis in Murph's Australia census analysis, and the many diseases highly correlated to ME/CFS in my USA Google Trends analysis made me wonder if places with British people have higher rates of many diseases, whether through genetic or...

An imaging flow cytometry method to study platelet-monocyte aggregates using Long COVID as a model Background Long COVID is characterised by persistent systemic inflammation and endothelial dysfunction, with increasing evidence implicating thromboinflammatory mechanisms. Platelet-monocyte...

I managed to do this, using gtrendsR, as suggested by Murph. I decided to have an AI code basically the whole script, and I am pleasantly surprised by how well it works. Essentially, the script is testing how well search interest in "chronic fatigue syndrome" correlates to search interest for...

Yeah, mine has always said "Disability". In a video about Trends, they seem to imply that any word under the term other than "Search term" means a Topic. Interesting that your R2 is higher. Just to clarify, the trends page you're using says "CFS/ME" and not "Myalgic encephalomyelitis/chronic...

That's funny. I had to look it up: - https://en.wikipedia.org/wiki/Irn-Bru

A hypothesis connecting dysgeusia due to defects in ATP-P2X3 signaling and fatigue in myalgic encephalomyelitis/chronic fatigue syndrome: lessons learned from long-COVID Srinivasan, Mythily; Joseph, Paule Valery Abstract Myalgic encephalomyelitis (ME)/chronic fatigue syndrome (CFS) is a...

I came back to this. I found out that the 210 "Metro" divisions for the US in Google Trends aren't just arbitrary shapes. They match up with Nielsen Designated Market Area (DMA) boundaries. (These DMAs are "a proprietary geography defined by Nielsen. They are non-overlapping geographic regions...

I've been using the Google Trends results for the ME/CFS Topic. Since Topics are more of a black box in terms of what search terms they contain, I wanted to check how the specific search term "ME/CFS" as well as other terms, correlate to ancestry. This whole thing started with English ancestry...

Just to check how well a Google Trends search for the ME/CFS "Topic" (which should be a combination of related terms, including other languages) compares to the data just for the specific term "ME/CFS", here is the data for both: R^2 = 0.52. That's basically only as good as British ancestry...

I just did some testing and the function works (most of the time - sometimes it seems to just hang.) I was getting worried about the R function getting different data than what I saw in the browser even though I was looking at both at the same time. Then I realized that my browser wasn't going...

Nice, I'll take a look. Python has (had) pytrends, another unofficial API, but it stopped working/being maintained a couple years ago, based on GitHub issues. This note from the maintainer of pytrends is a bit worrying: If Google gives fake data if downloading with a bot, it might affect the...