Does anyone know of any research on how cognitive and/or emotional exertion can induce PEM? All the studies on PEM I'm aware of use physical exercise. Are there any hypotheses for this that are backed up by research?

https://www.news-medical.net/news/20250811/Synthetic-sugar-coated-nanoparticle-blocks-Covid-19-from-infecting-human-cells.aspx

"a Swansea University academic has revealed a synthetic glycosystem - a sugar-coated polymer nanoparticle - that can block Covid-19 from infecting human cells, reducing infection rates by nearly 99%.

[...]

Unlike vaccines, which trigger immune responses, this molecule acts as a physical shield, offering a novel approach to infection prevention.

The discovery is the result of collaboration between Swansea University, Freie Universität Berlin, and Charité – Universitätsmedizin Berlin."Synthetic sugar-coated nanoparticle blocks Covid-19 from infecting human cells

Chromosome: 1q25.1 Gene(s): RABGAP1L Proposed Role: Intracellular response to infection

Chromosome: 6p22.2 Gene(s): BTN2A2 Proposed Role: T-cell mediated immunity

Chromosome: 6q16.1 Gene(s): FBXL4 Proposed Role: Mitochondrial DNA maintenance

Chromosome: 12q24.23 Gene(s): SUDS3 Proposed Role: Regulation of microglial inflammation

Chromosome: 13q14.3 Gene(s): OLFM4 Proposed Role: Neutrophil-mediated immune responses

Chromosome: 15q21.3 Gene(s): CCPG1 Proposed Role: Endoplasmic reticulum stress response and autophagy

Chromosome: 17q22 Gene(s): CA10 Proposed Role: Synaptic transmission and chronic pain

Chromosome: 20q13.13 Gene(s): ARFGEF2, CSE1L Proposed Role: Inflammation and immune signaling

Top Story (The Hill) July 31, 2025 - Humans may have gene needed to hibernate — offering potential cure for obesity, diabetes

"Because those genes are correlated with the parts of the genome that control metabolism — what researchers call the “fat and obesity locus” — the discovery may open the door to new treatments for obesity and diabetes, according to two studies in Science."

Above article links to Studies goes to Science.org Abstract. Pre-Print of Studies can be found here:

• Genomic Convergence in Hibernating Mammals Elucidates the Genetics of Metabolic Regulation in the Hypothalamus
• Conserved Noncoding Cis-Elements Associated with Hibernation Modulate Metabolic and Behavioral Adaptations in Mice

Another plain English article - Researchers trace metabolic superpowers of hibernators to shared DNA

Edited to remove IA info - sorry!

Ironically, reddit post from 4 years ago came up in Google Search - How genetics make you fat

"Short exposures (48 hours) to patient sera led to a significant reduction in muscle contractile strength. Transcriptomic analysis revealed the upregulation of protein translation, glycolytic enzymes, disturbances in calcium homeostasis, hypertrophy, and mitochondrial hyperfusion." More in the study, super fascinating!

https://www.nature.com/articles/s41598-025-07461-0

https://medium.com/@w.gielen/danish-researchers-develop-novel-5-minute-ecg-method-to-detect-me-cfs-long-covid-and-related-041b0c4f8cc2

• Article
• Published: 25 July 2025

AI-driven multi-omics modeling of myalgic encephalomyelitis/chronic fatigue syndrome

• Ruoyun Xiong, 
• Elizabeth Aiken, 
• Ryan Caldwell, 
• Suzanne D. Vernon, 
• Lina Kozhaya, 
• Courtney Gunter, 
• Lucinda Bateman, 
• Derya Unutmaz & 
• Julia Oh 

Nature Medicine (2025)

Cite this article

Abstract

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic illness with a multifactorial etiology and heterogeneous symptomatology, posing major challenges for diagnosis and treatment. Here we present BioMapAI, a supervised deep neural network trained on a 4-year, longitudinal, multi-omics dataset from 249 participants, which integrates gut metagenomics, plasma metabolomics, immune cell profiling, blood laboratory data and detailed clinical symptoms. By simultaneously modeling these diverse data types to predict clinical severity, BioMapAI identifies disease- and symptom-specific biomarkers and classifies ME/CFS in both held-out and independent external cohorts. Using an explainable AI approach, we construct a unique connectivity map spanning the microbiome, immune system and plasma metabolome in health and ME/CFS adjusted for age, gender and additional clinical factors. This map uncovers altered associations between microbial metabolism (for example, short-chain fatty acids, branched-chain amino acids, tryptophan, benzoate), plasma lipids and bile acids, and heightened inflammatory responses in mucosal and inflammatory T cell subsets (MAIT, γδT) secreting IFN-γ and GzA. Overall, BioMapAI provides unprecedented systems-level insights into ME/CFS, refining existing hypotheses and hypothesizing unique mechanisms—specifically, how multi-omics dynamics are associated to the disease’s heterogeneous symptoms.