IntroductionThe pathogenesis of post-acute sequelae of SARS-CoV-2 infection (PASC) remains poorly understood, and no effective treatment has been established...
seen from United States
seen from Singapore

seen from United States
seen from United States
seen from China

seen from TĂĽrkiye

seen from TĂĽrkiye
seen from Japan

seen from TĂĽrkiye
seen from United States

seen from United States
seen from China
seen from United States

seen from Russia
seen from Taiwan

seen from Taiwan

seen from Canada
seen from United States
seen from United States
seen from China
IntroductionThe pathogenesis of post-acute sequelae of SARS-CoV-2 infection (PASC) remains poorly understood, and no effective treatment has been established...

Anya is live and ready to show you everything. Watch her strip, dance, and perform exclusive shows just for you. Interact in real-time and make your fantasies come true.
Free to watch • No registration required • HD streaming
Purpose Unrefreshing and non-restorative sleep is a hallmark complaint in people with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). However, little is known about their habitual sleep and night-to-night fluctuations under real-life conditions. This study aimed to characterize sleep, and the intraindividual variability (IIV) of sleep in people living with ME/CFS compared with matched controls. Methods In this case-control study, 38 ME/CFS and 38 controls wore a wrist accelerometer continuously for 7 days and completed concurrent sleep diaries, the Pittsburgh Sleep Quality Index (PSQI), and Epworth Sleepiness Scale (ESS). Within the ME/CFS group, participants were also stratified by symptom severity using the Bell Disability Scale. Sleep IIV was quantified using the coefficient of variation, the root mean square of successive differences, and the Bayesian variability model, respectively. Results Compared with controls, individuals with ME/CFS spent significantly more time in bed and exhibited poorer sleep efficiency (SE) (all p
Based on the study provided, here is a summary of sleep efficiency (SE) in individuals with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS):
Key Findings on Sleep Efficiency:
Overall Reduction: Patients with ME/CFS exhibit significantly poorer sleep efficiency compared to healthy controls. They experience a nearly doubled sleep onset latency (taking much longer to fall asleep) and increased wakefulness after sleep onset (frequent waking during the night).
The "Time in Bed" Dissociation: Despite spending nearly an extra hour in bed, the actual total sleep time of ME/CFS patients does not differ from healthy individuals. This demonstrates that prolonged sleep opportunity does not translate into restorative sleep due to their compromised sleep efficiency.
High Night-to-Night Fluctuation: A hallmark finding of this study is that sleep efficiency in ME/CFS is highly unstable and shows pronounced intraindividual variability from one night to the next. Patients frequently alternate between low- and relatively high-efficiency nights.
Preserved Bedtime Schedules: Interestingly, this high instability in sleep continuity occurs despite patients maintaining relatively regular and stable bedtimes, which is often an adaptive pacing strategy to manage their illness.
Clinical Implications
Because sleep efficiency fluctuates so dramatically from night to night, a single- or two-night laboratory sleep assessment (such as standard polysomnography) can easily misrepresent a patient's typical sleep patterns. The study underscores the necessity of extended, multi-night ambulatory monitoring (e.g., using wrist accelerometry and sleep diaries) to truly capture the burden of sleep disturbances in ME/CFS.
Emerging evidence suggests that fatigue caused by accumulated stress may serve as a prodromal symptom of psychiatric disorders, and gut microbiome dysbiosis has been reported in many such conditions. However, little is known about microbial and metabolic signatures associated with fatigue in otherwise healthy individuals. This study aimed to investigate associations between fatigue, the gut microbiome, and fecal metabolites in healthy Japanese adults. We identified characteristic microbial and metabolic differences specific to fatigued healthy individuals. Taxonomic analysis revealed a reduction in potentially beneficial bacteria and an enrichment of Escherichia coli in their gut microbiome. Functional profiling demonstrated enrichment of KEGG orthologs related to oxidative stress and depletion of energy-producing pathways. Correspondingly, key energy metabolites such as citrate were decreased. Notably, some fatigue-associated bacterial alterations overlapped with findings from external datasets on psychiatric disorders and myalgic encephalomyelitis/chronic fatigue syndrome, suggesting associative overlap in gut microbial alterations. These findings suggest associations between host fatigue and gut microbiome alterations involving oxidative stress and impaired energy metabolism. The consistent overlap of fatigue-associated microbial changes with those observed in psychiatric disorders highlights the potential relevance of gut microbial signatures in fatigue-related biological states. This study provides a foundation for future studies on gut microbial and metabolic pathways.
Publish High-Quality Research in an International Peer-Reviewed Journal  Are you looking for a reputable journal to publish your latest sci
Science Journal
Ready to publish your research work in Science Journal? Innovare Academic Sciences can help! We provide different types of services – journal publication, journal subscription, book publication, conference proceedings & abstracts, and many more. For more information, you can visit our website https://innovareacademics.in/ or call us at +919165136558
Objective Long COVID (LC) refers to the long-term symptoms occurring after SARS-CoV-2 infection and resolution of the initial disease prodrome. While LC is incr...
Conclusions
In summary, this study identified persistent cerebral hypometabolism in LC patients, especially those with fatigue with PEM, up to two years post-infection. These results suggest that 18F-FDG PET-CT could be a valuable tool for diagnosing and managing LC. Further research is essential to confirm these findings and improve treatment strategies for patients with LC.

Anya is live and ready to show you everything. Watch her strip, dance, and perform exclusive shows just for you. Interact in real-time and make your fantasies come true.
Free to watch • No registration required • HD streaming
Plate VII. Molar teeth and skulls of Reithrodontomys (North American harvest mice). North American Fauna No. 36. 1914.
Internet Archive
AI Summary:
This preprint proposes that tiny particles released by gut microbes, called gut microbiota–derived extracellular vesicles (GMEVs), are a key mechanistic bridge between Long COVID–related gut dysbiosis, leaky gut, systemic inflammation, and neuroinflammation, especially in people with neurological Long COVID symptoms.​
Big-picture findings:
People with Long COVID show persistent, symptom-linked changes in their gut microbiome for at least 12 months, especially those with neurological symptoms such as memory issues and brain fog.​
Transferring stool from women with neurological Long COVID into germ-free mice causes leaky gut, neurobehavioral changes, and activation of astrocytes and microglia in the brain, while stool from Long COVID patients without neurological symptoms does not.
Isolated GMEVs from Long COVID patients trigger inflammation in intestinal epithelial cells, weaken barrier function, activate macrophages, and strongly activate human iPSC-derived microglia in vitro.
Chronic oral dosing of mice with Long COVID–derived GMEVs reshapes their gut microbiota, induces intestinal and systemic inflammation, alters behavior, and activates glial cells in specific brain regions.
The authors propose a “vesicle-centered” gut–brain axis model where microbial vesicles help sustain immune and neuroimmune activation in a post-viral state, highlighting BAFF signaling and other inflammatory programs as potential downstream effectors and therapeutic targets.
AI summary:
Key findings: long COVID
COVID‑19 was linked to a broad spectrum of comorbidities beyond the lungs, including circulatory, nervous, musculoskeletal, digestive, endocrine/metabolic, mental/behavioral, ocular, and oncologic conditions.​
People with substantial pre‑existing multimorbidity—especially cardiovascular disease, diabetes, kidney disease, COPD, and neuropsychiatric disorders—were more likely both to get COVID‑19 and to develop post‑COVID (long COVID) sequelae.​
Key findings: long flu
Influenza showed a similarly broad, system‑spanning pattern of associations, again involving circulatory, neurological, musculoskeletal, digestive, metabolic, mental/behavioral, ocular, respiratory, autoimmune, and cancer endpoints.​
Pre‑existing cardiovascular disease, chronic respiratory disease, type 2 diabetes, and inflammatory disorders strongly predisposed people to clinically significant influenza, indicating infection risk clusters in those with high baseline chronic disease burden.​
Long‑term sequelae and “long flu”
After influenza, there was a durable increase in new‑onset multi‑organ disease, with some risks remaining elevated for up to 5–15 years, defining a clear “long flu” phenotype.​
The most persistent signals were cardiovascular (thromboembolism, major adverse cardiovascular events such as heart failure, atrial fibrillation, myocardial infarction, stroke) and neurological/psychiatric (migraine, dementia/Alzheimer’s, depression), plus metabolic and renal outcomes like new‑onset type 2 diabetes and chronic kidney disease.​
The authors argue that influenza should be seen as a systemic event embedded in a chronic disease continuum, not just an isolated respiratory illness.​
Interpretation and implications
Both infections behave as systemic “stress tests” that unmask and accelerate chronic disease, especially in people with existing cardiometabolic and inflammatory conditions.​
The paper calls for recognizing long flu as a distinct post‑acute infection syndrome, intensifying prevention (particularly vaccination) and risk‑stratified long‑term surveillance, and developing multi‑organ follow‑up strategies analogous to those for long COVID.​