Biology Direct

Sicyoidochytrium minutum DNA virus (SmDNAV) was isolated several years ago from a protist host of family Thraustochytriaceae of the class Labyrinthulomycetes. This virus shared little similarity to other viruses in gene content and protein sequences, albeit seemingly belonging to the phylum Nucleocytoviricota. By extensive searches in genomic and metagenomic sequence databases, we identified numerous long contigs related to the SmDNAV genome and analyzed proteins shared by these putative viruses. Phylogenetic analyses place these viruses within the class Megaviricetes, outside of all established orders, and as a sister group to the clade combining families Mamonoviridae and Manesviridae. Homologs of SmDNAV proteins were found in association (either integrated or co-sequenced) with other Labyrinthulomycetes and Rhodophyta protists from diverse marine and freshwater environments. Consequently, we propose SmDNAV as the prototype member of a new order, provisionally named Ariadnavirales, within class Megaviricetes, phylum Nucleocytoviricota. Members of Ariadnavirales have lost most of the genes encoding components of the replication and transcription systems that are otherwise conserved in nucleocytoviricots, suggestive of transition to genome replication and expression dependent on the host nucleus.

Developmental regression is a severe but poorly understood complication of several neurodevelopmental disorders. In Kleefstra syndrome (KLEFS1), caused by EHMT1 haploinsufficiency, regression often emerges during adolescence or early adulthood and is frequently preceded by marked sleep disturbance. Experimental work implicating EHMT1/G9a in metabolic regulation and stress responses raises the possibility that impaired metabolic resilience contributes to this vulnerability. Here, we aimed to investigate whether altered glucose metabolism is a feature of KLEFS1 and whether it relates to clinical variability, including regression. Through [18F]FDG-PET/CT, individuals with KLEFS1 who had experienced regression (n=4) exhibited a hypometabolic brain profile, whereas one individual who had not experienced regression showed globally elevated metabolic activity. In parallel, G9a mutant flies exhibited increased baseline metabolic rate and neuronal ATP levels together with sleep fragmentation resembling the clinical phenotype. Providing flies with oxidative stress to model KLEFS1 regression further exacerbated sleep disruption and was associated with a reduction in metabolic output. Importantly, adult high sugar feeding in flies prevented oxidative stress-induced worsening of sleep and maintained metabolic stability under challenge. Together, these findings suggest that regression in KLEFS1 and associated sleep disturbances are linked to underlying metabolic vulnerability and impaired maintenance of energy homeostasis under stress.

Organosulfur compounds are the predominant sulfur source in terrestrial environments, requiring bacteria to use enzymes for their assimilation. Most described organosulfur-assimilating enzymes require oxygen, and enzymes that function under anoxic conditions remain poorly understood. Recently, methylthio-alkane reductase (Mar), a nitrogenase-like enzyme that reduces the volatile organic sulfur compounds (VOSCs) methylthio ethanol (MT-EtOH), dimethyl sulfide (DMS), and ethyl methyl sulfide (EMS) under anoxic conditions, was identified in the purple nonsulfur bacterium Rhodospirillum rubrum. However, another purple nonsulfur bacterium, Rhodopseudomonas palustris, has three loci of nitrogen fixation-like (NFL) genes with high sequence similarity to Mar, suggesting additional Mar-like enzymes with distinct roles. Here, we tested whether these NFL genes are required for VOSC assimilation in R. palustris. RNA-seq analysis revealed that all three NFL loci are upregulated under sulfur limitation, supporting a role in sulfur assimilation. Only disruption of the NFL genes encoded by RPA2634-37, renamed marBHDK1, caused fitness defects with EMS, DMS, and dimethylsulfoniopropionate (DMSP) as sulfur sources, indicating a functional Mar enzyme. The NFL genes RPA2347-48 and RPA2353-54, renamed marKD2 and marHB2, were required for activity with MT-EtOH or ethanethiol but not DMS, EMS, or DMSP. No activity was observed for the third locus, RPA2363-64, renamed nflDK. Overall, two Mar homologs in R. palustris are capable of VOSC reduction, one specialized for simple VOSCs and the other preferring a substrate with an additional functional group.

Viral infections have long been proposed as environmental contributors to neurodegenerative diseases, including Parkinson's disease (PD), yet the molecular mechanisms linking infection and neurodegeneration are not well defined. Neuroinflammation and disruption of central nervous system (CNS) homeostasis have emerged as potential mediators. In this study, we used severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, as a model pathogen to investigate convergent molecular pathways between viral infection and PD. Single-nucleus RNA sequencing (snRNA-seq) was performed on post-mortem striatal tissue from 14 individuals stratified into four groups: COVID-19 only (COVID-19), PD only (PD), comorbid PD with COVID-19 (PD/COVID-19), and controls (Control). The PD/COVID-19 group exhibited an expanded astrocytic population and a pronounced interferon-associated molecular signature characterized by increased expression of canonical interferon-stimulated genes, including IFI44L (average log2FC= 3.9; adjusted p=2.3 x 10-373), IFI44 (average log2FC=2.9; adjusted p=8.0 x 10-266), ISG15 (average log2FC=3.1; adjusted p=1.2 x 10-197), and RSAD2 (average log2FC= 3.5; adjusted p=8.6 x 10-111). Pathway analyses demonstrated activation of innate immune and antiviral signaling pathways, particularly within microglia and astrocytes, including interferon signaling, pattern-recognition receptor pathways, and complement-associated responses. In parallel, genes involved in lipid metabolism, cholesterol homeostasis, synaptic maintenance, and neuronal signaling were reduced across disease groups. Proteomic analyses independently confirmed enrichment of antiviral and interferon-associated pathways and identified convergent suppression of sterol, cholesterol, and lipid metabolic processes. Our findings identify a convergent molecular signature linking PD and COVID-19, pronounced in comorbid individuals and characterized by interferon-driven innate immune activation, glial inflammatory responses, and dysregulation of lipid metabolic homeostasis. Collectively, the data support a model in which severe viral infection amplifies biological pathways already implicated in PD pathogenesis.

High-protein diets increase hepatic sulfur amino acid metabolism, but the underlying transcriptional mechanisms remain unclear. This study investigated whether Kruppel-like factor 15 (KLF15) directly regulates cystathionine {gamma}-lyase (CTH), a key enzyme linking methionine transsulfuration to hydrogen sulfide (H2S) and taurine production. Promoter-reporter assays, electrophoretic mobility shift assays, and chromatin immunoprecipitation identified two functional KLF15-binding elements, designated 1-1 and 2-2, within the proximal Cth promoter. Mutation of either element attenuated KLF15-dependent promoter activation, whereas mutation of both largely abolished it. In vivo luciferase imaging further demonstrated that these elements were required for the hepatic transcriptional response to a high-protein diet. KLF15 loss of function reduced high-protein-diet-induced Cth expression and altered the hepatic sulfur amino acid profile. Methionine, cystathionine, and cystine accumulated, whereas taurine production and the high-protein-diet-induced increase in hepatic H2S were attenuated. Gene expression analyses further indicated that KLF15 selectively regulates components of methionine, taurine, and H2S metabolism rather than controlling the entire sulfur metabolic program. Collectively, these findings establish the high-protein diet-KLF15-CTH axis as a physiologically relevant transcriptional pathway that amplifies hepatic sulfur amino acid disposal and directs sulfur toward H2S and taurine production.

The QxxR motif is evolutionarily conserved within DEAD-box RNA helicases, including Drosophila Me31B and human DDX6, which post-transcriptionally regulate gene expression during animal development. A pathogenic H372R substitution (QxHR to QxRR) in the QxxR motif of human DDX6 has been associated with various developmental defects, but how this motif contributes to DDX6-family protein function remains unclear. Here, we used Drosophila Me31B as an in vivo model to investigate the QxxR motifs developmental role. We generated a Drosophila strain carrying the corresponding H333R missense mutation in Me31B and characterized its effects on female fertility, embryonic viability, germline development, and Me31B-associated molecular pathways. The me31BH333R mutation reduced female fertility in a gene dose-dependent manner, with homozygous mutant females being sterile. Embryos from the mutant females also exhibited primordial germ cell defects. Despite these developmental phenotypes, the me31BH333R mutation did not significantly alter Me31B protein abundance, global ovarian transcriptome or proteome profiles, or representative germ plasm mRNA and protein localization. In contrast, bait-normalized IP-MS analysis revealed altered enrichment of selected Me31B-associated proteins, including increased association of known Me31B interactors Trailer hitch (Tral) and Ypsilon Schachtel (Yps). These findings establish Me31BH333R as an in vivo model for investigating the conserved QxxR motif and suggest that disruption of this motif compromises development not through broad changes in gene expression, but potentially through altered composition or regulation of Me31B-containing ribonucleoprotein complexes.

Background: Cardiometabolic diseases frequently involve concurrent cardiovascular and hepatic dysfunction, yet the conserved molecular mechanisms underlying these systemic responses remain poorly defined. Objectives: To identify conserved molecular responses across complementary manifestations of cardiometabolic stress and determine whether integrated multi-organ analyses reveal therapeutically actionable targets for heart failure. Methods: Cardiac functional phenotyping, hepatic injury profiling, and bulk RNA sequencing were performed across three complementary mouse models representing distinct manifestations of cardiometabolic stress: high-fat diet plus L-NAME (HFD+LN)-induced heart failure with preserved ejection fraction (HFpEF; cardiovascular disease), Western diet (WD)-induced obesity (systemic metabolic stress), and choline-deficient, L-amino acid-defined, high-fat diet (CDAHFD)-induced steatotic liver disease (hepatic metabolic stress). Comparative transcriptomic analyses distinguished organ-specific responses from conserved molecular signatures. Results: Each model produced distinct systemic, hepatic, and cardiac phenotypes accompanied by divergent transcriptional responses within individual organs. Cross-model and cross-organ integration identified a limited set of conserved molecular responses to cardiometabolic stress, with Serpine1, encoding plasminogen activator inhibitor-1 (PAI-1), emerging as a highly conserved candidate that exhibited preferential induction in the heart. Pharmacologic inhibition of PAI-1 significantly improved cardiac function and attenuated adverse remodeling in established HFpEF, whereas hepatic pathology was comparatively less affected, indicating differential organ-specific dependence on this pathway. Conclusions: Integrated analyses across complementary manifestations of cardiometabolic stress identified conserved molecular signatures that transcend individual disease models and organs. These findings establish a comparative framework for discovering cardiovascular therapeutic targets and identify PAI-1 as a promising mediator of cardiac remodeling in cardiometabolic disease.

Background: The condition of a patient with acute stroke often changes within hours of ICU admission. Prognostic work here targets fixed endpoints predicted from admission data, and trajectory phenotyping assigns one label per patient. We used longitudinal ICU data to identify interpretable dynamic clinical states, characterize transitions between them, and relate the current state to later events. Methods: Retrospective cohort study of 6368 adults with acute stroke in MIMIC IV v3.1. The first 72 h were divided into twelve 6-hour windows, and a hidden Markov model was fitted to 21 neurological, physiological and organ support variables. State number was chosen against criteria fixed before fitting: statistical fit, restart stability, state occupancy and clinical interpretability. Generalized estimating equations related the current state to new mechanical ventilation and vasopressor use within 12 h, and to ICU death within 72 h. Eleven sensitivity analyses assessed the robustness of the state solution. Results: Four states were selected: neurologically preserved-low support, neurological impairment low support, impairment renal dysfunction and impairment-respiratory support (63.3%, 7.8%, 11.8% and 17.1% of windows). Within 72 h, 40.3% of patients changed state at least once, and transitions ran in both directions rather than along a single severity gradient. States were identified without outcome data, yet ICU mortality by last state ranged from 2.9% to 43.9%. Adjusted for age, sex, subtype and Charlson index, the current state remained associated with organ-support escalation and death. State prevalence differed by at most 1.1 percentage points between training and test sets, and 10 of 11 sensitivity analyses gave a stable four-state solution (ARI 0.754 0.955). Conclusions: The early ICU course of acute stroke can be represented as movement among a small number of clinically interpretable states. The representation was reproducible in a held out set and across admission eras, but requires validation in an independent database before any clinical use.

Background: Polymorphisms in the N-acetyltransferase 2 (NAT2) gene explain much of the interindividual variation in isoniazid (INH) metabolism and determine risk of toxicities. However, there is limited evidence to guide INH dose adjustment according to the NAT2 acetylator profile in weekly rifapentine-INH tuberculosis preventive therapy (TPT). Methods: In a prospective, multicenter, within-subject PK trial (NCT05413551), adults initiating 3HP in Brazil were assigned genotype-guided INH doses (slow: 5 mg/kg <=300 mg; intermediate: 15 mg/kg <=900 mg; rapid: 25 mg/kg <=1,500 mg) alongside a standard 900 mg flat dose on an alternate occasion. AUC0-24 and C24 were estimated from serial blood samples; a two-compartment Michaelis-Menten population PK model characterized NAT2 effects on clearance. Results: Among 228 participants, 47.4% (108/228) were intermediate, 43.4% (99/228) slow, and 9.2% (21/228) rapid acetylators. Genotype-guided dosing reduced AUC0-24 variability approximately two-fold versus standard dosing (CV 58.8% vs 76.8%) and increased exposure uniformity (median AUC0-24 27.2 [IQR 18.8-41.3] vs 43.2 [27.3-71.0] mg h/L). Among slow acetylators, C24 >0.15 ug/mL decreased from 27/42 (64%) with standard dosing to 1/42 (2%) with genotype-guided dosing (P<0.0001). In 104 participants with intensive PK sampling, rapid acetylators receiving guided doses had AUC0-24 similar to standard-dose intermediate acetylators (42.8 vs 39.5 mg h/L; P=.63). Monte Carlo simulations supported doses of 600, 900, and 1,200 mg for slow, intermediate, and rapid acetylators, respectively. Conclusions: NAT2-guided isoniazid dosing reduced variation in drug levels, averting very low and high AUC and C24. These findings inform genotype-stratified dosing of INH for TPT, which might reduce toxicities and improve outcomes.

Introduction: Risk of recurrent opioid use during buprenorphine-naloxone (bup-nx) treatment is dynamic and remains elevated after initiation, with vulnerability shaped in part by treatment intensity and gaps between visits, yet routine outpatient care relies on episodic encounters and retrospective data. This mismatch can delay recognition of emerging instability and limit timely treatment adjustments. This paper reports the development and specification of an intervention strategy to address this mismatch. Methods: We used a structured, multi-phase design process to specify and configure a measurement-based care (MBC) strategy for bup-nx treatment (Bup-MBC) in outpatient addiction clinics through three phases: (1) a systematic review of patient-reported outcome measures (PROMs) for substance use treatment; (2) a qualitative needs assessment using the Theoretical Domains Framework and COM-B (Capability, Opportunity, Motivation-Behavior) model to identify gaps in risk monitoring, agency, and trust; and (3) iterative co-design with multidisciplinary clinicians to refine workflow fit and trust-preserving use of data. Patients informed item and feedback content during the needs assessment but did not participate in the co-design cycles. Results: Bup-MBC integrates (1) brief between-visit PROMs (e.g., withdrawal, craving, adherence); (2) immediate non-punitive patient feedback; (3) clinician-facing summaries and non-directive prompts in the electronic health record (EHR); and (4) an opt-in between-visit outreach pathway with predefined safety triggers, all configured within existing EHR and patient portal infrastructure. It targets patient and clinician capability to recognize changes in risk, opportunity for action through structured monitoring and visit preparation, and trust and agency through non-punitive communication, without adding substantial burden. The full measure set, severity bands, and question-to-action map are provided as supplementary material. Key trade-offs included prioritizing single-item measures for feasibility, balancing opt-in outreach with safety overrides, and assuming routine clinician use of summaries. Conclusion: This development study specifies an EHR-integrated MBC strategy for outpatient bup-nx treatment. As single-center design work with co-design limited to clinicians and delivery contingent on portal or text-message access, its outputs are hypotheses about mechanism and fit rather than demonstrated effects. Feasibility studies are needed to evaluate uptake, acceptability, workflow fit, and effects on treatment.

Introduction Continuous Glucose Monitoring (CGM) is considered standard care in high-income countries. There is, however, limited published evidence on CGM use in low- and middle-income countries. The purpose of this study was to assess the usability, acceptability, and feasibility of CGM use among people living with type 1 diabetes (T1D) and caregivers in a low-resource setting. Research Design and Methods This prospective study conducted at the Kenyatta National Hospital purposively enrolled persons aged 4-25 years who had been on management for T1D for at least six months, and caregivers of those under 18 years. Fourty youth living with T1D used CGM for three months in place of self monitoring of blood glucose (SMBG). The System Usability Scale (SUS), a Theoretical Framework of Acceptability-based questionnaire, the Diabetes Distress Scale (DDS), the Glucose Monitoring Satisfaction Survey (GMSS), and a feasibility survey were administered. Outcomes were summarized descriptively, including means, medians, and frequencies using R statistical software. Results The median SUS score was 98.8 (IQR 92.5-100.0). Acceptability was high, and the median total GMSS score improved from 3.73 to 4.73. Among adolescents and adults, the median overall DDS score reduced from 1.54 to 1.36, with reductions in scores in all domains, except for hypoglycemia distress which increased, and physician distress which remained low. Among caregivers, the median overall DDS score declined from 2.05 (moderate distress) to 1.90 (low distress), with modest reductions in teen management and parent-teen relationship distress and a slight increase in personal distress. Median CGM active wear time was 89%. Conclusion This study comprehensively evaluated CGM across usability, acceptability, and feasibility outcomes, with the findings supporting the integration of CGM into routine diabetes management in low-resource settings. The short follow-up period, however, may not capture changing perceptions or long-term adherence.

Background: Pressure ulcers often develop complex three-dimensional morphologies that extend beyond the visible wound surface. Subsurface extensions such as tunneling and undermining create hidden cavities that complicate clinical assessment and wound management. Despite their clinical relevance, the prevalence and spatial characteristics of these subsurface wound morphologies have not been well characterized at scale. Methods: We performed a registry-based analysis using data from the LIFT-OFF Pressure Ulcer Registry, which captures longitudinal clinical documentation of pressure ulcers treated in routine care. The registry included approximately 18,000 patients with 32,000 documented pressure ulcers. Spatial characteristics of tunneling and undermining were analyzed using measurements recorded during routine wound assessments, including tract length, direction, and circumferential extent. Directional and circumferential distributions of subsurface defects were examined to characterize wound geometry. Results: Tunneling was present in 764 of 14,700 full-thickness pressure ulcers (5.2%), whereas undermining occurred in 2,293 wounds (15.6%). Tunneling tracts were typically short and exhibited directional clustering relative to the wound bed. In contrast, undermining demonstrated broader circumferential distributions and frequently involved larger subsurface separations beneath the wound margin. Both morphologies demonstrated distinct spatial patterns across anatomical locations and wound stages. Conclusion: Tunneling and undermining are common subsurface features of pressure ulcers and exhibit distinct spatial geometries. Whereas tunneling manifests as directional tract-like extensions, undermining more frequently produces circumferential tissue separation beneath wound margins. Improved characterization of subsurface wound architecture may enhance assessment of wound complexity and provide information not captured by surface measurements alone. Future studies should evaluate whether these features contribute to wound severity assessment, prognosis, and risk stratification.

Predicting disease risk from prior diagnoses is fundamental to clinical decision-making, particularly during health emergencies such as the COVID-19 pandemic, when individuals with long-term conditions may be disproportionately vulnerable to adverse outcomes. Despite intense interest in developing models to predict disease risk from prior diagnoses (1-3), most prediction models do not estimate effects of each prior diagnosis on disease risk conditional on other diagnoses, limiting interpretability and clinical utility. We developed the Comorbidity Risk Score (CRS), trained on 13 million individuals (age 40-69) from linked electronic health record (EHR) datasets of the entire population of England, to predict COVID-19 hospitalisation and 87 other disease outcomes. CRS was trained at close to saturated sample size and precisely estimated the effects of 212 prior diagnoses on the 88 disease outcomes, conditional on all other prior diagnoses. Correlations of CRS effect sizes across outcomes (e.g. 0.76 for myocardial infarction vs. hyperlipidaemia) matched the corresponding genetic correlations (e.g. 0.79 for myocardial infarction vs. hyperlipidaemia), confirming that comorbidity architectures capture disease aetiology. On average, CRS identified 5% of the population with 3.4-fold higher disease risk, including myocardial infarction (4.4-fold), lung cancer (6.5-fold), and COVID-19 hospitalisation (6.3-fold). Using prior diagnoses alone, CRS outperformed state-of-the-art clinical COVID-19 models (4). Furthermore, CRS (N=13 million) substantially outperformed state-of-the-art AI (1) (N=0.5 million) and linear (3) (N=0.5 million) models in predicting disease risk, suggesting that training sample size outweighs model complexity. CRS attained near-perfect transferability across self-reported ethnicities (e.g., Black vs. White: AUROC ratio = 97.3%). Finally, CRS distinguished independently predictive comorbidities from indirect associations, e.g., lipid metabolism disorder was a strong predictor of myocardial infarction risk but not ischaemic stroke, after conditioning on other prior diagnoses. In conclusion, CRS provides a comprehensive resource for understanding the impact of comorbidities on COVID-19 and other future diseases, revealing disease aetiology while enabling powerful prediction of disease risk.

The distribution of fat-soluble compounds (including antioxidants) in follicular fluid (FF) remains sparsely documented in relation to in vitro fertilization (IVF) outcomes and existing studies have reported diverging associations. This study aimed to describe plasma and FF concentrations of fat-soluble micronutrients in women undergoing IVF and to analyze their adjusted associations with ovarian function, embryo development and pregnancy outcomes. In 2021-2022, plasma and FF samples were collected from 82 women (first IVF cycle) at oocyte puncture, along with lifestyle data covering the three preceding months. Eleven compounds (two tocopherols, three xanthophylls, five carotenes and retinol) were quantified. All compounds were detected in both compartments (lowest in FF) except phytoene, undetectable in FF. Plasma and FF -tocopherol concentrations were positively associated with plasma estradiol levels before oocyte puncture (both p<0.01) while FF -carotene and lycopene were inversely associated with plasma progesterone concentrations (p=0.01 and 0.02, respectively). Plasma phytofluene and phytoene were positively associated with mature oocyte rate (p=0.03 and p=0.01, respectively), while FF retinol was negatively associated (p=0.03). Carotenes, tocopherols and retinol were inversely associated with later IVF outcomes: fertilization rate (p<0.001 for plasma g-tocopherol, 0.02 for FF retinol), top-quality embryo (p=0.02 for plasma phytofluene), biochemical pregnancy at day 7 post-embryo transfer (p=0.05 for plasma -tocopherol, 0.02 for plasma -carotene), clinical pregnancy (p=0.03 for plasma -tocopherol, 0.01 for plasma phytoene) and live birth (p=0.04 for plasma -tocopherol, 0.02 for plasma phytoene). Plasma and FF g-tocopherol were positively associated with embryo fragmentation (both p<0.05). Finally, among xanthophylls, only plasma {beta}-cryptoxanthin was positively associated with plasma progesterone concentrations (p=0.02). Our findings of heterogeneous associations between tocopherols, carotenes, retinol and IVF outcomes across the stages of IVF suggest a beneficial effect limited to early outcomes and support a complex and context-dependent role of these compounds in female reproduction. This manuscript has been submitted to PlosOne on August 19, 2026.

Abstract: Objective: Post-traumatic epilepsy (PTE) is a common sequela of traumatic brain injury (TBI). Research indicates that individuals with PTE tend to experience greater cognitive difficulties compared to those with TBI alone. However, it is plausible that a distinct cognitive profile exists that distinguishes between TBI cases with and without PTE. We aimed to identify longitudinal changes in cognitive measures among TBI patients to better assess the changes associated with developing PTE. Setting: Outpatient. Participants: Prospective subjects who had suffered TBI within 6 months post-injury (TBI-6M, n=32), retrospective subjects with pre-existing PTE diagnoses (PTE, n=20), and healthy control subjects (HC, n=41). Design: We examined cognitive performance for TBI patients within 6 months post-injury, then again within 12 months (TBI-12M, n=26), and within 18-months (TBI-18M, n=25), and compared this with cognitive performance among HC and PTE. Main Measures: Cognitive tests administered yielded 15 test components for analysis. We utilized linear mixed effects modeling to examine cohort-level differences cognitive function. Results: 11/15 tests showed a significant performance deficit in the PTE subjects compared to HC. TBI-6M was not significantly different from the PTE subjects; with time, 9/15 tests showed some degree of recovery in TBI subjects. Tests for information processing speed/working memory and executive function showed strong recovery (TBI-6M vs. TBI-18M, SDMT written: p<0.0001, SDMT oral and COWAT: p<0.001). Tests for visual attention/working memory also showed a smaller but significant recovery (TBI-18M vs. PTE, p<0.05). By contrast, tests for verbal memory [HVLT-R Delayed Recall] showed chronic impairment in TBI (TBI-18M vs HC, p<0.0001). TBI subjects generally trend towards recovery in cognitive performance post-TBI. Conclusions: Information processing speed/working memory are strong indicators for TBI recovery, while auditory learning/memory shows chronic impairment. The stagnation of recovery in cognitive domains typically characterized by robust recovery may correlate with an elevated risk of developing PTE.

Importance: Patients are increasingly learning Alzheimers disease (AD) genetic and biomarker results through electronic health portals. Evaluation of alternative scalable delivery models for return of AD risk information is needed to best support patient understanding and psychological well-being. Objective: To determine whether a patient-centered digital platform is comparable to clinician-mediated telehealth sessions for returning APOE and plasma pTau-217 results on outcomes of knowledge and psychological well-being. Design: The Evaluation of Self-Mediated Alternatives for Risk Testing Education and Return of Results (eSMARTER) study was a noninferiority trial of a patient-centered digital platform compared to clinician-mediated disclosure of APOE genotype and optional pTau-217 disclosure. Setting: Decentralized, fully remote trial enrolled participants in the contiguous United States (U.S.) between October 2024 and February 2025, with follow-up completed in November 2025. Participants: Eligible participants were aged 60-80 and had previously undergone APOE genotyping (without disclosure) via the GeneMatch program, passed psychological screening, had internet access, and were English-speaking. Interventions: Participants were randomized, 2:1, to the eSMARTER digital platform or clinician-mediated disclosure of APOE genotype. Following the 6-month post-APOE assessment, participants were offered optional pTau-217 disclosure via the same randomized modality. Main Outcomes and Measures: Primary outcomes at 1-7 days following APOE disclosure included changes in anxiety, disease-specific distress, and AD-related knowledge within a priori non-inferiority margins. Results: 674 persons (mean [SD] age 68 [4.7] years; 451 [67%] female; mean [SD] telephone MoCA=19 [2]) were eligible and provided demographic information. 651 participants were randomized to clinician-mediated (n=216) or digital disclosure (n=435) and completed APOE disclosure (66 [10%] APOE4 homozygotes, 377 [58%] heterozygotes, 208 [32%] non-carriers). 604 participants completed the study; 500 completed optional pTau-217 disclosure. Baseline characteristics were balanced across groups. At 1-7 days following APOE disclosure, scores on AD-related knowledge, PROMIS Anxiety, and disease-specific distress measures met non-inferiority. Conclusions and Relevance: Disclosure of APOE genotype by the eSMARTER digital platform is non-inferior to clinician-mediated telehealth disclosure. No significant between group differences were found following disclosure of pTau-217 results. Together, these results suggest that this digital platform may provide an evidence-based scalable approach for returning AD genetic and biomarker results.

Next-generation sequencing (NGS) for the detection of somatic variants has become the method of choice in a variety of molecular oncology fields and in the clinic. Its use ranges from sequencing entire tumor genomes and transcriptomes to targeted clinical diagnostic gene panels. The NYU Langone Genome PACT (Profiling of Actionable Cancer Targets, LG-PACT) assay is a qualitative in vitro diagnostic test that uses targeted next generation sequencing (NGS) of formalin-fixed paraffin-embedded (FFPE) tumor tissue matched with normal specimens from patients to detect gene alterations in a targeted panel covering 606 genes and the TERT promoter. Indications for testing are cancer (solid tumors and hematological malignancies) where a mutational profile from multiple genes would be informative for disease stratification, prognosis, or treatment options including targeted therapies and eligibility for clinical trials. The test is intended to provide information on somatic mutations including point mutations, small insertions/deletions (indels), and copy number aberrations for diagnostic and treatment decisions. LG-PACT is a United States Food and Drug Administration (FDA) cleared diagnostic test (510K: K202304). The clinical interpretation of sequencing data of molecular tumor markers from NGS encompasses automated variant calling tools with human interpretation. This final mostly manual review of data step is intensive, involving highly trained scientists, encompassing literature review, interpretation and clinical tier classification by pathologists, who then provide a complete molecular diagnostic report to the treating oncologists. We provide analysis of 1339 clinical genomic profiles from 31 different cancers and their subtypes, comprising of central nervous system (CNS) 792 (59%) cases (incl. meningioma, glioma and glioblastoma), with 267 (20%) cases predominantly of lung, pancreatic and colorectal and 280 of others (21%). Here, we present the technical challenges of validating an NGS oncological diagnostic targeted assay for clinical grade accuracy and sensitivity for patient care. We show how copy number alterations provide a more comprehensive description of the tumors genomic profile. We then outline the utility of targeted panel sequencing based on certified pathologist selection of reportable variants for our current patient cohort. Where analysis of variant detection has led to 49.4% (661/1339) of our clinical tumor samples containing mutations in known therapy targeted genes, 35.6% (477/1339) with mutation detected in other genes, and 15% (201/1339) cases being negative.

Study Objective Little is known about where in hospital care for multiple long-term conditions (MLTC) is delivered. We aimed to describe pathways of care (ward transfers) and outcomes for people admitted to hospital for unscheduled care by MLTC status and other key sociodemographic characteristics. Design and setting Analysis of routinely-collected electronic health records from a large acute UK hospital. Participants Adult unscheduled care admissions from 1st July 2018 to 30th June 2019. The presence of two or more of 59 long-term conditions was ascertained using ICD-10 codes from previous hospital discharges. Main outcome measures Markov state transition probabilities were derived for ward moves and compared for MLTC vs no MLTC, age, sex, ethnicity and neighbourhood deprivation. Outcomes (length of stay, death, readmission, move from definitive ward) and time spent in emergency and assessment departments were compared between subgroups. Results A total of 33,252 adults, mean age 56.0 (SD 21.9) years were analysed; 14,834 (42.4%) had MLTC. People with MLTC were more likely to die in hospital (4.2 vs 1.9%, p<0.001), transfer to internal medicine wards or older peoples medicine wards, were less likely to transfer to surgical wards, had longer median length of stay (1.83 vs 0.69 days, p<0.001), stayed longer in acute medical units (15.5 vs 9.6 hours, p<0.001), and were more likely to move from their definitive ward (18.2 vs 16.4%, p=0.002). Conclusion Unscheduled hospital care pathways are complex and differ for people with MLTC, who have worse outcomes and may be less likely to receive optimal care.

Improvements in data availability, sharing, and integration, together with the development of explainable artificial intelligence (XAI) techniques, are advancing precision medicine for pediatric cancer by facilitating diagnosis, biomarker discovery, and drug development. Data sharing commons and initiatives like the Childhood Cancer Data Initiative (CCDI) provide access to pediatric-specific genomic and clinical data cohorts and improve data availability for pediatric cancer research. Based on CCDI, a scalable AI platform, Graph Artificial Intelligence for Pediatric Oncology (GAIPO), integrates various data modalities from bulk and single-cell omics data to clinical information. Such multi-modal data facilitates the training and development of advanced XAI models for pediatric cancers. We then developed an end-to-end multi-modality framework, PCGS, for pediatric cancer by incorporating omics-specific representation learning via GNN models with cross-attention fusion and multi-objective learning for downstream tasks such as classification, clustering, and survival analysis. This framework outperforms previous supervised multi-omics integration baseline approaches based on glioma and Wilms tumor cohorts and enables GNN model explainability via Shapley value-based feature attribution approaches to explain the contributions of gene-level features across various biomedical tasks, including classification and survival. Given specific background samples (e.g., age groups, sex, grades) as baselines, this explainable GNN model estimates and ranks the importance scores for input features from each omics modality. It identifies background-specific key features for biomarker discovery, risk group identification, and survival analysis in glioma and Wilms tumor, with potential applicability to other pediatric cancers.

Purpose: Lung cancer screening (LCS) with low-dose computed tomography (LDCT) reduces lung cancer mortality, yet screening participation remains low. We evaluated whether a brief informational video nudge delivered immediately before a scheduled clinical encounter increased LCS ordering and baseline LCS completion. Patients and Methods: We conducted a randomized feasibility trial within Kaiser Permanente Colorado from March through October 2025. LCS-eligible patients with an upcoming primary care or pulmonology appointment were assigned to intervention or usual care based on birth month. Intervention patients were split into two group, a group who received the LCS informational video nudge via text message within 24 hours of an eligible appointment; and second group who received the text plus a QR code video link during appointment rooming. Outcomes included LCS orders, baseline LCS-LDCT completion, and video engagement. Multivariable logistic regression was used to evaluate factors associated with LCS ordering. Results: Among 1,093 patients, 549 were assigned to intervention and 544 to usual care. Intervention patients were more likely to receive an LCS order within 1 day of their appointment (22.6% vs 16.4%; p=.010) and any time during follow-up (32.6% vs 24.1%; p=.002). Baseline LCS-LDCT completion was 51% higher in the intervention group, although the difference was not statistically significant (8.6% vs 5.7%; p=.078). Among the intervention group, 93 individuals (17%) viewed the video, generating 114 total views, and viewers watched an average of 79% of the video. Most views (82.5%) occurred through text-message delivery rather than QR codes. Conclusion: A brief, low-burden LCS informational video delivered immediately before a clinical encounter and integrated into existing workflows significantly increased LCS ordering and was associated with higher screening completion. Timely, scalable digital nudges may provide an effective strategy for improving LCS participation. Based on the observed effectiveness, feasibility, and efficiency of the intervention, KPCO incorporated the behavioral nudge into standard clinical care in February 2026.