Miscellaneous Research Thread

Navigating Social Security disability benefits with Long COVID: A grounded theory study, 2026, Hair et al

Nicole Hair, Maushmi Patel, Ibitein Okeafor, Carly Urban, Nabil Natafgi

Background: Long COVID is an emerging public health challenge that impacts the health and financial security of millions. Individuals living with Long COVID may qualify for Social Security Administration (SSA) disability benefits; however, barriers limit access to these programs.

Methods: This qualitative study used Strauss and Corbin's grounded theory to examine how adults with Long COVID perceive and navigate SSA disability benefit programs, including factors shaping decisions to apply, delay, or discontinue applications. Data were collected through 17 interviews and 4 focus group discussions. Analysis was conducted using constant comparative methods until theoretical saturation was reached.

Population Studied: Participants included 35 US-based adults living with Long COVID, predominantly female (62.9%) and Black/African American (62.9%), representing 19 states. Eighteen participants reported applying to SSA programs; 15 had not applied, and two initiated but did not complete the application process.

Principal Findings: The central phenomenon, perceptions about SSA programs, reflects the conditions and processes shaping participants’ experiences.

Applicants described the process as complex and stressful, citing system-level biases, limited customer support, and insufficient information as key barriers. Uncertainty about eligibility, unclear procedures, long waiting times, and potential legal costs discouraged participation. Long COVID symptoms further compounded these challenges.

Applicants highlighted the importance of support from family, friends, providers, attorneys, advocates, and employers.

Conclusion: Administrative complexity and limited support within SSA disability programs present substantial barriers for individuals with Long COVID. Efforts to clarify eligibility criteria, streamline procedures, and strengthen support systems may improve access for individuals living with Long COVID.

Web | APHA 2026 Conference | Conference Abstract
 
Temporal Sequence of Onset: ME/CFS-like Fatigue and Functional Neurological Disorder (Gaber et al.)

Abstract said:

Background​

Fatigue is the most prevalent and one of the most disabling symptoms of Functional Neurological Disorder (FND), yet its causal relationship to the condition remains poorly understood. Emerging evidence suggests that chronic fatigue may precede rather than follow the onset of functional neurological symptoms. We hypothesised that a specific phenotype of chronic fatigue, resembling that seen in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS), may act as a precipitating factor in FND.

Methods​

We conducted a retrospective review of clinical records from 89 patients assessed through an integrated ME/CFS and FND community service in Wigan, UK, between March 2022 and March 2025. Complete data were available for 76 patients. Fatigue prevalence, phenotype, and its temporal relationship to the onset of FND symptoms were extracted and analysed descriptively.

Results​

Fatigue was reported by 62 of 76 patients (81.5%). In 39 patients (51% of the cohort), fatigue predated the onset of FND symptoms by months to years and exhibited features resembling ME/CFS, including post-exertional malaise, cognitive dysfunction, pain, and immune-like symptoms unrelieved by rest. In all 39, fatigue onset followed one or more stressful life events. A further 23 patients (30%) reported fatigue emerging concurrently with or following FND onset, also with post-exertional exacerbation. The remaining 14 patients (18.5%) without significant fatigue tended to present with isolated focal symptoms and minimal fluctuation, or with primary psychiatric or pain co-morbidities.

Conclusions​

These findings suggest that ME/CFS-like fatigue may play a previously underappreciated precipitating and perpetuating role in a substantial subgroup of FND patients. One possible interpretation is that persistent fatigue and post-exertional symptom exacerbation may constrain the brain’s capacity to process and integrate information, potentially contributing to the emergence or persistence of functional neurological symptoms. These observations are preliminary and require prospective validation, but they raise important questions about FND phenotypic heterogeneity and the appropriateness of exercise-based interventions in fatigue-predominant presentations.
Click to expand...
___

Link | PDF (Advances in Rehabilitation Science and Practice, October 2026, open access)
 
In other words, it ain't FND.

The whole concept is simply irrelevant, and hence highly counterproductive.

While this is actually a noteworthy finding (that does not support an FND diagnosis), so also is that they twist what should be a clear diagnosis of ME/CFS into one for a prodromal phase for FND.
 
EBV hijacks the metabolic function of CD73 to resist the antitumor function of NK cells, 2026, Duan et al.

Duan, Xiaobing; Hu, Jiali; Wan, Shuo; Luo, Qiong; Zhang, Yuncong; Feng, Guangyong; Luo, Miaoshan; Lin, Zhen; Yu, Pei; Jia, Hongyun; Li, Jinmei; Wang, Minhong; Wang, Zhongying; Chen, Mingxiao; Yang, Xinfeng; Lin, Meifang; Li, Siyu; Xiang, Tong; Zhou, Qiang; Zhang, Guihai

Abstract
CD73 is a metabolic immune checkpoint that regulates the homeostatic balance of adenosine levels in the tumor microenvironment (TME). However, the regulation of CD73 abnormal expression in Epstein-Barr virus (EBV)-associated malignancies remains unclear.

In this study, we demonstrate that CD73 is upregulated in EBV-associated malignancies and is negatively correlated with the anti-tumor activity of NK cells. Mechanistically, EBV latent protein LMP2A upregulates CD73 through the PI3K/AKT signaling pathway, and the metabolic product of CD73, adenosine, negatively regulates the anti-tumor function of NK cells through multiple signaling pathways.

Furthermore, targeted knockout of CD73, a small molecule inhibitor, or neutralizing antibody combined with the adoptive transfer of NK cells significantly improved the treatment efficacy for EBV-positive nasopharyngeal carcinoma (NPC). Importantly, we also found abnormal upregulation of CD73 in EBV-positive lymphoma, gastric cancer, and lung cancer.

In summary, our research identifies the mechanism of immune evasion of NK cell anti-tumor function in EBV-associated malignancies through the abnormal expression of CD73, and targeting CD73 combined with the adoptive transfer of NK cells may provide a new strategy for immunotherapy of EBV-related malignancies.

Web | DOI | PMC | PDF | npj Precision Oncology | Open Access
 
The role of the NLRP3 inflammasome in a CLN2 mouse model of neuroinflammation, 2026, Sánchez et al.
Sánchez, Kathryn E.; Elizalde, Samantha; Schwartz, Nancy B.; Domowicz, Miriam S.

Abstract
Neuronal ceroid lipofuscinoses, or Batten disease, comprises a group of inherited pediatric neurodegenerative disorders, and is characterized by the lysosomal accumulation of the fluorescent storage material lipofuscin.

The human classical late-infantile form of the disorder (CLN2) is caused by mutations in the CLN2 / Tripeptidyl peptidase 1 ( TPP1 ) gene. Comparable to human CLN2, a knockout of the Tpp1 gene ( Tpp1 -/- ) in the mouse leads to progressive vision loss, ataxia, motor atrophy, seizures, and premature death. While we previously showed using bulk RNA-seq analysis that reactive gliosis develops between 3 and 4 months in this animal model, the role of the inflammasome in CLN2 remains unexplored.

The inflammasome is a multiprotein complex formed through pattern recognition receptor engagement, which culminate in the cleavage and release of interleukin-1 beta. Here we report that while some inflammasome-associated genes are upregulated as early as 1-month in the Tpp1 -/- cerebellum, it is not until 3-months-old that all gene transcripts necessary for inflammasome assembly and function are upregulated, leading to IL1β release.

In Tpp1 -/- slice cultures, we demonstrated that MCC950, an inhibitor of inflammasome assembly, downregulates transcriptional expression of genes associated with reactive microglia and inflammasome function. Furthermore, prophylactic administration of MCC950 in drinking water of Tpp1 -/- animals for two months is sufficient to lower the expression of these same genes in the forebrain and cerebellum, suggesting that inflammasome inhibitors are promising therapeutics for CLN2 and neurodegeneration broadly. Graphical Abstract The role of the NLRP3 inflammasome in a CLN2 model of neuroinflammation.

The NLRP3 inflammasome is upregulated and assembled in Tpp1-/- microglia, leading to IL1β release. Treatment with an NLRP3 inflammasome inhibitor MCC950, in ex-vivo and in-vivo murine models of CLN2 neuroinflammation, results in the downregulation of inflammasome-associated genes.
Web | DOI | bioRxiv | Open Access
 
www.nature.com

Can GLP-1s heal the brain? Obesity drugs get a makeover for addiction and depression

Compounds inspired by the blockbuster weight-loss drugs are also being trialled for schizophrenia and Parkinson’s disease, among other conditions.
www.nature.com www.nature.com
Paywall

Can GLP-1s heal the brain? Obesity drugs get a makeover for addiction and depression​

Compounds inspired by the blockbuster weight-loss drugs are also being trialled for schizophrenia and Parkinson’s disease, among other conditions.
​

​

 
Fast and inexpensive visualization of genome collection at scale, 2026, Kotte et al.
Kotte, Sujatha; Tiwari, Naina; Vaddadi, Kavya; Saipradeep, Vangala Govindakrishnan; Joseph, Thomas; Rao, Aditya; Srinivasan, Rajgopal; Sivadasan, Naveen
Abstract

Background​

Investigating genetic progression and lineage using sequence data is a fundamental focus within the realm of viral genome research. Given the substantial increase in publicly accessible genome sequences, tools designed for extensive data analytics, particularly insightful visualizations play an important role in elucidating the spatio-temporal evolution as well as the diversity of viral lineages.

Existing genome data analysis methods frequently rely on multiple sequence alignment (MSA) and phylogeny computations, making integration of new sequences computationally expensive. Such methods are often metadata agnostic and typically utilize a global distance metric between candidate sequences.

We present BOVIZ, a fast and inexpensive method for rich visualization of large-scale genome collections. BOVIZ leverages variant-level features from candidate sequences and employs a novel Bag-Of-Variants (BOV) method that transforms high-dimensional variant feature vectors into a 2D-space, effectively capturing sequence (dis)similarities. BOVIZ circumvents the need for expensive MSA and phylogeny analyses, enabling efficient integration of novel sequences and faster visualization of large-scale sequences on a standard desktop.

Furthermore, BOVIZ supports a variety of filters, including metadata filters and selection of genomic regions of interest for effectively capturing localized similarities and dissimilarities on-the-fly. We perform extensive benchmarking of BOVIZ with state-of-the-art visualization methods using the SARS-CoV-2 viral genome dataset.

Results​

BOVIZ consistently outperformed these methods in capturing inter-sequence similarity and diversity, offering superior visualization of spatio-temporal and clade-level evolution. It is able to effectively distinguish SARS-CoV-2 lineages into distinct clusters, visualize the evolution of specific sublineages like Omicron and their variant patterns, as well as visualize potential sub-cluster within the SARS-CoV-2 Delta variant.

Conclusion​

BOVIZ is an effective visualization tool for genome surveillance, complementing resource-intensive deep analytics by providing key insights about the underlying genome landscape in a fast and scalable manner.
Web | DOI | PDF | BMC Bioinformatics | Open Access
 
Healthcare trajectories diverge years before Huntington disease is recorded in claims: a nationwide French matched cohort study (2026, Journal of Neurology, Neurosurgery & Psychiatry)
BACKGROUND
Huntington disease (HD) develops years before it is formally recorded, yet whether this generates measurable healthcare demand, and when, is unknown. We aimed to determine when trajectories of incident HD diverge from matched controls.

METHODS
Retrospective matched cohort study using the French National Health Data System. Adults with incident HD (2018 to 2024; ≥2 hospital visits or ≥1 long-term registration for nternational Classification of Diseases, 10th Revision (ICD-10) G10 or F02.2; no HD code in the prior 9 years) were each matched to five controls on sex, age and deprivation. Recurrent events were modelled from 9 years before to 7 years after the first HD record.

RESULTS
Among 2659 cases and 13 295 controls, divergence preceded the first record by 6 to 8 years. Antipsychotic use rose earliest (8 years prior, HR 1.54, 95% CI 1.31 to 1.80). From 6 years prior, neurology (HR 1.53, 95% CI 1.06 to 2.22), psychiatry (HR 1.25, 95% CI 1.04 to 1.47) and speech therapy (HR 2.16, 95% CI 1.46 to 3.19) diverged. Before the record, neurology consultations occurred in 50.8% of cases versus 10.0% of controls, psychiatry consultations in 33.9% vs 10.0% and speech therapy in 8.5% vs 0.6%. After the record, divergence widened: neurology peaked at 3 years (HR 5.44, 95% CI 3.94 to 7.54) and antipsychotic use at 5 years (HR 3.63, 95% CI 3.06 to 4.30), while physiotherapy emerged only afterwards (4 years, HR 3.10, 95% CI 2.89 to 3.33).

CONCLUSIONS
HD generates substantial care years before diagnostic coding. Neuropsychiatric and communicative demand precedes motor-related rehabilitative care by several years, defining a measurable window for earlier referral.
 
Yeah it's very clear that there are similar signals for a lot of illnesses. Here they seem especially inappropriate, but that's just common, I guess. It's something that makes poor recording of intermediate signals a real problem. There is likely more similar data out there in those cases that just never got recorded, or was misinterpreted.

People's lives don't change when they get a diagnosis of X. Those lives often change much earlier than that, diagnosis is just a step, one that apparently changes a focus on incorrect treatment approaches to the possibility of correct ones. There is a lot to learn here, and it's fortunate that AI is about to change everything, because it's not the kind of lessons that humans tend to do well at.
 
You must log in or register to reply here.
Back
Top Bottom