Journal of Proteomics

Water availability is critical for plants and their microbial communities, including pathogens. The plant pathogen Phytophthora cinnamomi persists in soils with fluctuating moisture, yet cellular responses to water limitation remain poorly understood in Phytophthora and oomycetes more broadly. Although we recently characterized the proteomic response of P. cinnamomi to NaCl-induced osmotic and ionic stress, its response to PEG-mediated water limitation remains poorly understood, leaving a critical gap in our understanding of drought-relevant stress adaptation. Here, we quantified mycelial growth and profiled time-resolved proteome dynamics of P. cinnamomi during polyethylene glycol (PEG-3350)-treatment, simulating moderate water limiting conditions. Treatment with 5% PEG-3350 enhanced radial mycelial growth relative to controls, with no early growth inhibition observed. Label-free proteomics identified 1,097 protein groups, with 880 proteins shared between conditions and an asymmetric abundance profile dominated by decreasing protein abundance over time. Only a small subset of proteins increased, mainly enzymes involved in redox buffering (e.g., thioredoxin and glutaredoxin-like proteins) and mitochondrial/metabolic regulation (e.g., alternative oxidase) and mitochondrial/metabolic regulation. Hierarchical clustering revealed a potential three-phase temporal program: early translational and regulatory remodeling (1-6 HPT), sustained metabolic adjustment (6-12 HPT), and delayed engagement of redox and proteostasis functions (12-24 HPT). Network analysis demonstrated that redox-associated function was integrated throughout this adaptation, with individual clusters further specialized by cofactor preference (NADP- versus NAD-dependent enzymes) and distinct metabolic roles (malate dehydrogenase, CoA-ligase activity). This coordinated, multi-phase reorganization sustained mycelial growth despite moderate osmotic stress, indicating that P. cinnamomi employs active proteomic adaptation rather than passive stress tolerance. These findings reveal the cellular mechanisms underlying drought persistence in this invasive pathogen and suggest molecular targets for disease management under water-limited conditions.

Plant cold acclimation emerges from coordinated adjustments in photosynthesis, primary metabolism, and intracellular carbon allocation. Yet, the regulatory role of subcellular metabolite compartmentation in natural variation of cold acclimation remains insufficiently understood. Here, we investigated four Arabidopsis thaliana accessions grown either individually or in bulk to determine how growth configuration and genotype shape the metabolism of sugars and organic acids during cold exposure. Using non-aqueous fractionation, we quantified plastidial, cytosolic, and vacuolar sugar pools alongside whole-cell carbohydrates, organic acids, enzyme activities, photosynthetic parameters, and stress markers. A neural-network classifier revealed that subcellular sugar distribution together with sugar amounts and organic acids provided the strongest discriminatory power among accessions, surpassing photosynthetic traits and enzyme activities. Our findings demonstrate that natural variation in cold acclimation is strongly determined by genotype-specific subcellular metabolite architectures, and that the cultivation strategy modulates these intracellular signatures. We conclude that subcellular compartmentation of metabolites represents a cellular control layer for natural variation of cold acclimation and resilience in Arabidopsis thaliana.

All living organisms rely on the movement of ions across cell membranes as the fundamental physical basis of their internal energy and signaling, and plants are no exception. Plants perceive, integrate, and respond to environmental stimuli through electrical signals, classified as action, variation, and system potentials, that are coupled with calcium waves, reactive oxygen species, and hydraulic and hormonal changes to coordinate whole-organism responses despite the absence of a nervous system. Yet most studies characterize these signals using a single feature, such as amplitude or spike duration, in a single tissue, an approach that cannot establish how such signals correspond to the underlying ionic activity, mobility, and structural complexity of the signaling environment, or how this correspondence varies across organs. Here, we correlate plant bioelectrical signals with potential ionic energy flow using a multi-domain framework, combining discrete spike events, continuous waveform properties, spectral composition, and signal complexity applied to leaf, stem, and root recordings from tomato (Solanum lycopersicum) exposed to different stimulus. Electrical activity with increased stimulus strength, likely reflecting increased ionic flow, with the root showing the largest response. This suggests plant electrical signaling works as a distributed, ion-based information system, useful for stress monitoring and bio-inspired sensor design.

Background: Acute phase response is an early immunometabolic response to brain injuries, primarily coordinated by the liver via the activation of acute phase proteins. These immune responses can be both beneficial, promoting tissue repair, and detrimental, exacerbating neurological deficits, if not properly controlled. Despite the central role of the liver in immunometabolism, how hepatic metabolism dynamically adapts to traumatic brain injury remains under explored, primarily due to limited liver-specific modalities that can assess metabolic pathways in vivo. 13C MRI utilizing hyperpolarized 13C-pyruvate can assess key regulatory enzyme activities in hepatic metabolism. Methods: Rats with controlled cortical impact were studied in vivo using hyperpolarized [1-13C]pyruvate and [2-13C]pyruvate under fed and fasted conditions 3-4 days after injury. Hyperpolarized 13C products, including [13C]bicarbonate from [1-13C]pyruvate and [5-13C]glutamate, [1-13C]acetyl-L-carnitine, and [2-13C]phosphoenolpyruvate from [2-13C]pyruvate, were evaluated to assess mitochondrial and gluconeogenic metabolism. In parallel, liver tissues were collected following [U-13C3]pyruvate injection for NMR isotopomer analysis of phosphoenolpyruvate, glucose, and glutamate. Results: While no metabolic differences were detected under fed condition, [13C]bicarbonate and [2-13C]phosphoenolpyruvate increased after brain injury under fasted condition, indicating an upregulation of the hepatic gluconeogenic pathway after injury. 13C NMR of liver tissue extracts from injured rats showed an elevated [2,3-13C2]glutamate-to-[4,5-13C2]glutamate ratio and increased 13C-labeling in phosphoenolpyruvate than controls, confirming enhanced hepatic gluconeogenic pathway. Conclusion: This study demonstrates that hepatic acute phase response to brain injuries can be monitored in vivo by hyperpolarized pyruvate, which may be further utilized for longitudinal immunometabolic evaluation of the liver during pathogenesis and therapeutic interventions.

Simultaneous quantification of monoglycosphingolipid stereoisomers is required to monitor changes in defective enzymatic pathways linked to diseases such as Gaucher Disease, Parkinson's Disease, and Krabbe Disease. Resolution of beta-glucosyl and beta-galactosyl epimers cannot be achieved by standard liquid chromatography, electrospray ionization, tandem mass spectrometry (LC-ESI-MS/MS). Separation becomes possible when field asymmetric ion mobility spectrometry (FAIMS), also known as differential mobility mass spectrometry (DMS), is added as an orthogonal separation technique to LC. FAIMS/DMS separates epimeric ion clusters in a high versus low electric field (separation voltage, SV) then redirects the target epimeric ions to the mass spectrometer through the application of a direct current (compensation voltage, CoV). Resolving SVs and CoVs must be manually determined for each lipid. Manual derivation is a labour-intensive process that requires pure synthetic standards, limiting the number of stereoisomers a user can include in an assay. To address this problem, we introduce here intelligent DMS (iDMS). iDMS is an in silico supervised neural network model that learns the ion mobility relationships between SV and CoV and the monoglycosphingolipid structural features of sugar headgroup, N-acyl chain length, and N-acyl degree of unsaturation. iDMS predicts the SV and CoV combinations capable of resolving any stereoisomer pair from a training dataset of composed of measured signal intensities across a range of SVs and CoVs of 12 lipids. This machine learning alternative to manual DMS optimization promises to accelerate the deployment of multiple-reaction-monitoring mode (MRM) RPLC-ESI-DMS-MS/MS assays for the routine and rapid quantification of biologically relevant monoglycosphingolipid stereoisomers.

Parallelization of data acquisition substantially increases the throughput of mass spectrometry-based proteomics. However, parallelization also increases the density of mass spectra and consequently the overlap between ions, frustrating their analysis. To improve sequence identification and quantification from such spectra, we developed an open-source software for Joint Modeling of mass spectra (JMod). JMod models overlapping peaks as linear superpositions of their components in both MS1 and MS2 space, which permits multiplexed DIA with smaller mass offsets to increase the multiplexing capacity and thus proteomics throughput for a given plexDIA tag. This enables 9-plexDIA using 2 Da offset PSMtags, increasing throughput 9-fold while preserving quantitative accuracy and coverage depth. Furthermore, we use JMod to deconvolve simultaneous labeling by mass tags and heavy amino acids, thus increasing the throughput of metabolic pulse experiments measuring protein synthesis and degradation rates in single cells from mouse liver. By supporting enhanced decoding of highly multiplexed DIA spectra, JMod provides an open and flexible software that increases the throughput of sensitive proteomics.

Objective White smoke inhalation injury (WSI) causes severe acute lung damage with no specific therapy currently available. Sphingolipid metabolism is implicated in pulmonary inflammation, but its transcriptional regulatory landscape in WSI remains unexplored. This study aimed to identify key sphingolipid metabolism related genes and evaluate their regulatory roles and therapeutic potential in WSI. Methods We established a rat model of WSI and performed integrated bulk RNA sequencing, weighted gene coexpression network analysis (WGCNA), and single-cell RNA sequencing (scRNAseq) to screen for differentially expressed sphingolipid metabolism-related genes (DESRGs). Protein-protein interaction (PPI) network with four centrality algorithms was used to prioritize hub genes. In silico gene knockout and molecular docking were conducted to assess regulatory functions and identify potential drug candidates. Results We identified 22 DESRGs that were predominantly enriched in DNA replication and cell cycle pathways rather than canonical sphingolipid metabolic processes. PPI consensus prioritized three hub genes--Top2a, Ttk, and Ccna2--with Top2a exhibiting the highest expression in epithelial cells and significant downregulation after smoke exposure. ScRNAseq revealed immune cell infiltration and epithelial differentiation trajectories. Virtual knockout showed that Top2a depletion affected the largest transcriptomic fraction (~0.4%) and was enriched in lysosome biogenesis, innate immunity, phagocytosis, and lipid catabolism. Molecular docking identified thalidomide as a high affinity ligand for Top2a (Vina score: -8.5 kcal/mol). Conclusion Our multiomics integrative framework identifies Top2a as a central regulatory hub linking sphingolipid associated inflammation to epithelial responses in WSI, and nominates thalidomide as a potential drug repurposing candidate. These findings provide prioritized targets for future translational investigation.

Intertidal mudflats are low hydrodynamic energy environments hosting microphytobenthic communities that experience strong spatiotemporal variability in light regimes, including changes in spectral quality and light intensity that can lead to cellular photooxidative stress. To cope with these fluctuations, autotrophs exhibit diverse and highly plastic adaptations that are often species-dependent and shaped by their ecological niches. This study investigates photophysiological responses and metabolic remodeling in a diatom assemblage originating from a natural winter microphytobenthic biofilm under contrasting red and blue light intensities. To this end, photosynthetic parameters were monitored alongside changes in lipophilic metabolites, including untargeted lipids and lipophilic pigments. While few metabolites showed temporal remodeling, rapid and contrasting changes were observed within 30 minutes in response to both spectral quality and light intensity. Red light treatments induced broader remodeling of lipophilic metabolites than blue light, whereas blue light appeared to have a greater impact on photosynthetic parameters. Moreover, red light induced xanthophyll-cycle responses comparable to those observed under blue light at equivalent incident intensity. We discuss these metabolic responses in relation to diatom photoadaptive strategies, placing these findings within the intertidal environmental framework. This work further underlines the importance of understanding rapid metabolic plasticity in coping with light fluctuations, providing new insights into the photoregulatory strategies of natural microphytobenthic communities.

Background: Multiple sclerosis (MS) is a chronic neurodegenerative disorder in which inflammatory demyelinating lesions affect the brain, optic nerve and spinal cord. MS lesion formation is accompanied by profound changes to blood vessels, including the density of PDGFR{beta}+ mural cells, historically identified as pericytes. Intriguingly, in recent years, single-cell and lineage tracing studies have shown that the PDGFR{beta}+ cell population is heterogeneous, comprising both pericytes and perivascular fibroblasts. Yet, due to their overlapping expression profiles, the spatial distribution of these cell populations in MS lesions remains poorly understood. Methods: We employed multiplex immunohistochemistry for endothelial cells (CD31), basement membrane (laminin), fibroblasts (PDGFR{beta}, COL1A1, SMA), pericytes (PDGFR{beta}, SLC6A12) and immune cells (CD45, CD68) to characterize the spatial localization of fibroblasts and pericytes in MS lesions, and how this relates to perivascular space enlargement and immune cell presence. Results: We analysed 17633 individual vessels across 5 control white matter, 5 normal-appearing white matter, 4 active and 4 chronic active MS lesions. By carefully delineating endothelium and perivascular compartments, we find that perivascular space area but not number of vessels is increased in MS lesions. Through mining of publicly available sequencing datasets, we confirm COL1A1 and SLC6A12 as fibroblast and pericyte markers, respectively, in the human brain. COL1A1+ and SLCA12+ vessels were largely distinct of one another. Unsupervised clustering of the expression profile of PDGFR{beta}, COL1A1 and SLC6A12 in individual vessels distinguished three partially overlapping vessel clusters. Of these, the fibroblast-associated vessel type (COL1A1 high, SLC6A12 low) was increased in chronic active lesion rim and center. Importantly, fibroblast-associated vessels were related to increased perivascular space enlargement and more accumulation of immune cells. Conclusion: We identify distinct fibroblast- and pericyte-associated vascular phenotypes in human white matter. Notably, fibroblast-associated vessels are increased in chronic active lesions, where they are related to immune cell cuffs. These findings provide a spatial link between perivascular fibroblasts and chronic inflammation in MS.

Conventional univariate reference intervals (UniRIs) are widely used to identify abnormal biomarker values, but they evaluate each biomarker independently and do not account for coordinated deviations between biomarkers. We developed and evaluated a joint reference region (JRR) framework for plasma proteomics data using the Olink proteomics dataset generated by the UK Biobank Pharma Proteomics Project, covering approximately 3,000 plasma proteins. JRRs were estimated for selected protein pairs in a healthy reference subset, while UniRIs were estimated separately for individual proteins using the nonparametric method. Both approaches were then evaluated in ICD-defined disease subsets. Biomarker discovery revealed sparse and heterogeneous disease--protein associations, with some proteins recurring across multiple phenotypes and others showing more disease-specific patterns. The added value of JRRs varied across diseases and protein pairs. Across evaluated protein pairs, 56.5\% showed higher sensitivity under the JRR framework than the UniRI of the first protein, and 47.3\% showed higher sensitivity than the UniRI of the second protein. At the disease level, the median proportion of protein pairs with improved JRR sensitivity was 0.57. JRRs were most informative when univariate detection was limited but a subset of diseased observations was flagged only by the joint region. These findings suggest that JRRs provide a complementary approach to UniRIs by capturing abnormal joint biomarker configurations in high-dimensional proteomics data.

Metabolic dysfunction-associated steatotic liver disease (MASLD), the leading cause of chronic liver pathologies worldwide, represents a growing clinical burden. Its diagnosis remains reliant on liver biopsy that limits early detection and the ability to capture molecular changes across disease progression. A systematic understanding of stage-dependent gene expression changes is essential to identify biomarkers and effectively characterize disease mechanisms. Therefore recent studies provided databases for searching genes as well as prediction of multi-gene signatures for disease progression. However, there is still a need for interactive and comprehensive meta-analysis of datasets of MASLD patients with available histological metadata. Herein, we performed a meta-analysis of RNA-seq datasets using NAFLD Activity Score (NAS; n = 897) and fibrosis stage (n = 856) upon conducting pairwise comparisons across histological stages and identified differentially expressed genes associated with disease progression. Most importantly, we provide our findings via a dedicated web server, the MASLD-META NETWORK (https://masld.scilicium.com), enabling users to interactively explore meta-analysis results across diverse network modalities. In addition, we characterized gene expression dynamics across increasing disease stages to identify consistent progression-associated pathways using Louvain clustering. Network-based parameters such as centrality in combination with meta-analysis scores further highlighted central genes and pathways implicated in disease mechanisms. Accordingly, MASLD-META NETWORK enabled an integrative reassessment of recently published gene signatures, identifying COL1A1, COL3A1, THBS2, FBLN5, and PDGFA as the most central genes, and SULF2, MMP14, IL32, GPNMB, and COL3A1 as candidate markers of earlier transcriptional alterations. Network analysis of MASLD associated biological modules further identified LAMA2 and LAMA3 as previously unrecognized central candidate targets.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by progressive dysfunction and loss of upper and lower motor neurons. Although motor neuron degeneration ultimately drives paralysis, neuronal dysfunction may precede cell death by a prolonged interval, suggesting that vulnerable neurons engage stress-adaptive programs that permit survival despite impaired function. Cellular senescence represents one such persistent stress response and has increasingly been implicated in neurodegenerative disease, including disorders associated with TDP-43 pathology. Here, we investigated whether senescence-associated molecular states are present in vulnerable motor neurons in ALS and whether they differ according to anatomical region and phosphorylated TDP-43 (pTDP-43) pathology. Postmortem primary motor cortex, cervical spinal cord, and lumbar spinal cord were obtained from the Department of Veterans Affairs Biorepository Brain Bank from individuals with ALS classified as pTDP-43-positive or pTDP-43-negative, together with non-ALS controls. Targeted bulk transcriptomic profiling was combined with GeoMx Digital Spatial Profiling of individual motor neurons to characterize disease-, region-, and pathology-associated molecular phenotypes while preserving anatomical context. Across ALS cases, we identified alterations in pathways related to cell-cycle regulation, RNA processing, mitochondrial function, proteostasis, inflammation, and synaptic signaling. These signatures varied by anatomical region and pTDP-43 status, indicating substantial heterogeneity in the molecular response to ALS pathology. Despite these differences, both ALS groups exhibited convergent proteomic and transcriptomic features associated with cellular senescence. These findings identify senescence-associated molecular states within vulnerable neuronal populations in ALS and support a model in which persistent stress adaptation may permit neuronal survival while contributing to progressive cellular dysfunction. This spatially resolved analysis links neuronal phenotype to anatomical and pathological context and supports further evaluation of senescence-associated pathways as therapeutic vulnerabilities in ALS.

Orthodontic tooth movement relies on a tightly regulated pro-inflammatory and pro resorptive mechanoresponse of local periodontal ligament fibroblasts (PdLFs). Dysregulation is linked to complications such as root resorption and tooth loss. Hyperlipidemic conditions promote excessive PdL mechanoresponses, with growth differentiation factor 15 (GDF15) acting as potential regulator. This study examined the contribution of the inflammasome/pyroptosis pathway as underlying mechanism for dysregulated mechanoresponses. Human PdLFs were treated with palmitic acid (PA) or oleic acid (OA) for six days before 24 hours of compressive loading. PA increased CASP1, CASP4, and CASP3 activity, secretion of IL-1{beta}, IL-18, and HMGB1, and LDH release. Pharmacological blockade and siRNA-mediated knockdown of inflammasome- and pyroptosis-related targets revealed that NLRP3, CASP1, CASP4, and GSDMD partially contributed to monocyte and osteoclast overactivation. Silencing PA-increased GDF15, partially normalized the phenotype, at least in part by inflammasome/pyroptosis regulation. GDF15 acted through extracellular, and a nuclear signaling route, each accounting partially to this phenotype. Together, GDF15 partially regulates the PA-induced, pyroptosis-associated overactivated mechanoresponse alongside pyroptosis-independent mechanisms suggesting it as an interesting target for potential clinical interventions.

Introduction: Polyendocrine metabolic ovarian syndrome (PMOS), formerly known as polycystic ovary syndrome (PCOS), is a common endocrine disorder affecting women of reproductive age. Besides reproductive and metabolic disturbances, PMOS negatively impacts psychological well-being and quality of life. Despite available treatment options, there remains a need for safe and effective therapies that improve both clinical symptoms and fertility outcomes. Aim: To compare the efficacy of VAMHA and MYRHA tablet combination therapy with standard non-hormonal therapy in restoring regular menstruation. Secondary objectives included assessment of ovulation, menstrual symptoms, polycystic ovarian morphology, hormonal and metabolic parameters, anthropometric measures, and skin manifestations. Study Design: Open-label, randomized, multicentre, prospective comparative clinical study. Methods: Seventy-one women with PMOS were randomized to Group A (n=37) or Group B (n=34). Group A received VAMHA and MYRHA tablets (2 tablets each), while Group B received Metformin 500 mg plus Myoinositol 600 mg (1 tablet), twice daily for 180 days. Data were recorded in Case Report Forms. Statistical Analysis: Continuous variables were summarized using mean and standard deviation, while categorical variables were expressed as frequencies and percentages. Appropriate statistical tests, including Chi-square, were used. A p-value [&le;]0.05 was considered significant. Results: Significantly more participants in Group A achieved regular menstrual cycles than Group B (31 vs. 22; p<0.05). Ovulation occurred in 16 participants in Group A compared with 6 in Group B (p<0.05). Both groups showed significant improvement in menstrual irregularity and related symptoms. Significant reductions in Anti-Mullerian Hormone (AMH), fasting insulin, and body mass index (BMI) were observed in both groups (p<0.05). Resolution of polycystic ovarian morphology occurred in 13 participants (38.23%) in Group A and 10 (33.33%) in Group B. Both treatments were well tolerated with no major safety concerns. Conclusions: VAMHA and MYRHA combination therapy was superior to standard non-hormonal therapy in improving menstrual regularity and ovulation. It also produced favourable metabolic, hormonal, and ultrasonographic outcomes, suggesting its potential as a safe and effective option for comprehensive PMOS management and fertility enhancement.

Abstract Objective: Glaucoma is a chronic disorder that impairs ocular health and may exacerbate ocular surface disease leading to tear film instability, dry eye symptoms and decreased quality of life. This study compared changes in tear quantity among glaucoma subjects living with and without diabetes mellitus, attending an eye clinic in Nigeria. Methods: A comparative cross sectional research design was used. 157 subjects which comprised 74 glaucoma subjects living with diabetes mellitus and 83 glaucoma subjects living without diabetes mellitus participated in the study. Tear quantity assessment included the Schirmer I test and tear meniscus height (TMH) measurement. Descriptive statistics, independent samples t-test and Chi-square test were used to examine the data at 0.05 level of significance. Results: Glaucoma subjects living with diabetes mellitus showed substantially decreased tear production (11.4 +/- 6.8 mm) compared with glaucoma subjects living without diabetes mellitus (19.6 +/- 9.6 mm; p < 0.001). Tear meniscus height in glaucoma subjects living with diabetes mellitus (0.8 +/- 0.3 mm) was significantly greater than in subjects living without diabetes mellitus (0.7 +/- 0.3 mm; p = 0.034). Conclusion: Diabetes mellitus dramatically deteriorates the ocular surface function in glaucoma subjects by decreasing tear production, altering the tear meniscus height and increasing the severity of ocular surface symptoms. Routine glaucoma care, especially in patients with diabetes mellitus, should include a full ocular surface evaluation including Schirmer I test, TBUT, TMH, and OSDI assessment to allow early detection and management of ocular surface disease, better treatment adherence, and improved visual outcomes. Keywords: Glaucoma, Diabetes Mellitus, Tear production, Tear Meniscus Height, Ocular Surface Disease.

Background & Aims: Fatigue is a central symptom of chronic liver disease (CLD), substantially impacting health-related quality of life (HRQoL). This study aimed to further understand CLD symptomatology, including fatigue, and its impact on HRQoL from a patient perspective. Methods: Abbott Global Assessment of Patients unmet needs (aGAP) was a multinational, cross-sectional survey in adults with compensated CLD in China, India and Mexico, conducted between July and November 2024. Adult participants who self-reported that they had physician-diagnosed CLD and were experiencing fatigue completed a quantitative survey to assess symptom burden and included three HRQoL patient-reported outcome (PRO) questionnaires (Patient-Reported Outcomes Measurement Information System [PROMIS]-29+2, Work Productivity and Activity Impairment - Specific Health Problem version 2.0 [WPAI: SHP], Multidimensional Fatigue Inventory [MFI]). Results: Overall, 505 participants (China: 200; Mexico: 105; India: 200) completed the study. Participants reported that their CLD-related fatigue sometimes, often or always affected their self-esteem/confidence (45.1%) and ability to maintain or acquire new employment (38.6%). Most participants reported moderate (51.3%) or serious (26.9%) fatigue, with 33.5% experiencing fatigue every day or almost every day. Many participants felt their social life was negatively impacted by their fatigue (47.3%) and that there were related financial difficulties (53.9%). Use of validated PRO tools demonstrated severe fatigue (MFI: overall mean [SD] 13.9 [3.4] general fatigue and 13.4 [3.6] physical fatigue) as well as substantial levels of work and activity impairment (WPAI: SHP overall mean [SD] 53.0 [26.4]) and high levels of anxiety, pain interference, depression and sleep interference (PROMIS T-scores [&ge;]54). Conclusions: Fatigue has a substantial impact on HRQoL among adults with CLD across several countries, highlighting a global unmet need for targeted interventions to effectively identify and manage the condition.

Importance: Evidence on GLP-1/GIP therapies is largely derived from trials enrolling selected populations or medical records that miss utilization outside healthcare channels. No nationally representative cohort has characterized real-world uptake, indications, and access. Objective: To characterize GLP-1/GIP prevalence, indication, clinical profile, and access. Design: Prospective cohort study with three GLP-1/GIP surveillance waves (March 2024, December 2024, October 2025). Setting: The Understanding America Study, an address-based, nationally representative panel of approximately 15,000 US adults aged 18+ years initiated in 2014. Participants: UAS participants responding to at least one surveillance wave (n=9150). Exposures: GLP-1/GIP use status (never vs any use, comprising current and former use), self-reported primary indication (diabetes, weight loss, or other), and access pathway (traditional vs non-traditional). Main Outcomes and Measures: Survey-weighted prevalence of GLP-1/GIP use, overall and by indication and access pathway; sociodemographic, cardiometabolic, treatment, and access characteristics; and smartwatch-derived resting heart rate, heart rate variability, maximum activity heart rate, step count, and sleep duration and variability. Results: Among n=9150 adults (1274 with any use; 60.9% female; median age 53 years), weighted prevalence increased 46%, from 8.2% (March 2024) to 12.0% (October 2025) representing 32 million. Weight-loss indications grew, reaching nearly half of use (4.1% to 5.6%); diabetes-indicated use was stable (5.3% to 5.4%). Users carried high cardiometabolic burden (obesity, 68.2%; diabetes, 53.6%) but diverged by indication: diabetes-indicated users were older (median, 59 vs 49 years), whereas weight-loss-indicated users were more often female (69.9% vs 51.3%) and healthier. One in three users (~9 million) had non-traditional access, especially in weight-loss-indicated users, of whom 33% had no conventional prescription; 41% used compounding, online, or foreign pharmacies; and, 43% lacked coverage. Non-traditional users were five times as likely to report an unlisted, likely compounded formulation (19.8% vs 4.1%). All p<0.05. Conclusions and Relevance: Real-world GLP-1/GIP use has grown rapidly and diversified substantially in indication, access, and population profile. One in 3 users obtained treatment through nontraditional channels largely invisible to claims data, raising long-term safety, efficacy, and coverage questions. GLIMMER provides a public, nationally representative longitudinal evidence base for future payer and provider decisions.

Background. Videolaryngoscopy still requires adjuncts or hyperangulated rescue in a clinically important minority, and bedside screening discriminates modestly. Point-of-care ultrasound (POCUS) of the anterior airway is a promising alternative, but existing prediction models are opaque or assume a pre-specified functional form. We developed and internally validated a parsimonious, fully disclosed POCUS risk equation whose form is recovered from data and whose structural properties are machine-checked by formal proof - to our knowledge the first formally verified clinical risk predictor - following TRIPOD+AI 2024. Methods. In a prospective single-centre, single-operator cohort of 259 adults undergoing elective videolaryngoscopy (no-Easy airway 68/259, 26.3%), Sequentially Thresholded Least Squares with bootstrap stability selection (B=300) screened a 71-term library of nine POCUS features and retained a seven-term logistic equation; a two-term bootstrap-stable model was pre-specified as robustness analysis. Internal validation used 5x10 repeated cross-validation plus temporal and device hold-outs, with pre-specified overfitting and optimism assessments. Five behavioural properties of the deployed equation were machine-checked in Lean 4. Results. Two interactions met the |c|/sigma_c>2 stability criterion: skin-to-epiglottis x skin-to-hyoid-bone distance and tongue volume x sagittal tongue area. The seven-term equation reached a 5x10 cross-validated C-statistic of 0.966 (optimism-corrected 0.968) and held across temporal and device hold-outs (0.94-0.97). Calibration-in-the-large matched prevalence, with cross-validated slope 0.90 attenuating to 0.625 out-of-time; standard recalibration restored 0.92 without loss of discrimination. The pre-specified two-term robustness model reproduced this performance (C-statistic 0.964-0.968; events-per-parameter 34; shrinkage 0.99), confirming the result is not an artefact of the screening stage. Net benefit over a clinical baseline was positive across 10-50% thresholds. All five Lean 4 theorems compiled without sorry. Conclusions. A sparse, formally verified POCUS equation predicts difficult videolaryngoscopy with high internally validated discrimination and quantified, modest overfitting. Because the equation was developed in a single-operator cohort and its inputs are operator-dependent, external validation requires prior harmonisation of the measurement protocol and operator credentialing.

Muscle architecture shapes muscle function and changes with age, growth, training and disease, yet quantifying three-dimensional (3D) muscle architecture in vivo remains challenging. We introduce a hybrid fascicle tractography approach for freehand 3D ultrasound data that accurately reconstructs 3D muscle fascicles with respect to an objective, anatomically relevant coordinate system defined by the muscle's central aponeurosis. The hybrid approach combines Hessian-based fascicle detection with wavelet-based refinement to generate volumetric fascicle orientations. In a synthetic dataset with known ground truth, fascicle orientations and lengths were estimated with errors of [&le;]2{degrees} and ~1.5%, respectively. In vivo, the approach detected physiologically plausible fascicle lengthening in the human tibialis anterior following a passive plantar flexion rotation, whereas diffusion tensor imaging of the same muscle did not. The proposed method enables anatomically relevant, objective and non-invasive quantification of 3D muscle architecture in vivo, providing a practical framework for applications in clinical and applied muscle physiology.

Background: Prostate cancer enzalutamide treatment is approved at a standard dose of 160 mg daily. Concerns for real-world patients -- older and more fragile than those enrolled in clinical trials -- have prompted consideration of initiating treatment with lower doses, but the long-term efficacy of this approach remains unknown. We evaluate the long-term survival and longevity in patients treated with standard versus upfront low-dose enzalutamide. Methods: Retrospective analysis of 151 patients treated with enzalutamide (102 receiving 160 mg; 49 receiving [&le;]80 mg) between 2014--2021 at the Centre Hospitalier Universitaire de Martinique, with complete follow-up through end of life (98.7% completeness of follow-up). Primary outcomes were overall survival (OS), progression-free survival (PFS), and longevity (attained age). Results: Doses [&le;]80 mg were associated with longer median OS (36.3 vs. 20.7 months), improved restricted mean OS (difference of 0.7 years, p=0.05), and enhanced longevity (median 82.5 vs. 78.3 years, p=0.004). PSA response rate at 12 weeks was higher with lower-dose (71.4% vs. 48.8%, p=0.016). In multivariable models adjusted for prognostic factors, [&le;]40 mg compared with 160 mg was non-inferior regarding OS (HR=0.61, 95% CI 0.36--1.06), superior regarding PFS (HR=0.59, 95% CI 0.35--0.99), and superior regarding longevity (HR=0.48, 95% CI 0.28--0.84). Bone metastasis, poor performance status, PSA response, time to PSA nadir, and disease duration were independent predictors of outcomes. A post-hoc analysis revealed a strong association between dose and physician-prescribing profiles, ranging from "endorse-lowest-dose" to "never-deviate-from-full-dose". Conclusions: Lower doses of enzalutamide were non-inferior to full-dose. Dose-adapted strategies warrant further investigation.