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Community-driven advances in computational mass spectrometry: The perspective of EuBIC-MS members.

Advances in data acquisition, artificial intelligence, and integrative bioinformatics are driving the rapid evolution of computational mass spectrometry, and in turn, transforming modern proteomics, metabolomics, and lipidomics. These developments have greatly increased the scale and complexity of mass spectrometry data, underscoring the importance of evolving accurate, transparent, efficient and reproducible data processing workflows. Addressing these challenges requires collaborative innovation that brings together expertise in software engineering, statistics, and biology. The European Bioinformatics Community for Mass Spectrometry (EuBIC-MS), an initiative of the European Proteomics Association (EuPA), fosters a culture of open, community-driven development through its biennial Developers Meetings and Winter Schools. This commentary summarizes the scientific background and outcomes of the EuBIC-MS Developers Meeting 2025, which took place in Novacella, Italy. Three keynote presentations highlighted major frontiers in the field: deep proteome and phosphoproteome profiling, text mining for protein-protein interaction extraction, and scalable proteomics for AI-driven drug discovery. Seven community-selected hackathons addressed emerging challenges such as single-cell proteomics data analysis, FAIR metadata extraction, deep learning frameworks, R-Python interoperability, and DIA validation. Together, these efforts demonstrate the potential for scientific and technical innovation to arise from open collaboration, and highlight how community-driven initiatives can accelerate progress in computational mass spectrometry. SIGNIFICANCE: Modern proteomics increasingly depends on computational advances to translate complex, high-dimensional data into biological knowledge. The EuBIC-MS Developers Meeting 2025 exemplifies how community-driven collaboration can directly accelerate this process by bringing together experts from bioinformatics, statistics, and experimental proteomics to co-develop open, interoperable, and reproducible analytical tools. By fostering shared software frameworks, transparent benchmarking, and collaborative problem solving, the EuBIC-MS community helps ensure that technological innovation translates into reliable biological insights. This collaborative model strengthens the foundation for quantitative, system-level understanding of proteomes and establishes a sustainable path for integrating artificial intelligence and next-generation data acquisition into routine biological discovery. This commentary shows some current highlights in the field of computational mass spectrometry and community-based approaches undertaken during the most recent Developers Meeting to solve these challenges. The approaches discussed and initiated during the meeting - ranging from deep proteome profiling and phosphosite mapping to text mining, single-cell data analysis, and FAIR metadata extraction - address key bottlenecks that currently limit the biological interpretability and comparability of proteomics data.

Mass Spectrometry

Integrated electronic nose, GC-MS, and metagenomic analyses reveal volatile flavor and microbial community differences in heap-fermented grains of Jiangxiangxing Baijiu across different fermentation degrees.

The fermentation degree of heap-fermented grains in Jiangxiangxing Baijiu production is a critical factor influencing base Baijiu quality. However, conventional assessment methods largely rely on empirical experience and therefore suffer from limited objectivity and accuracy. In this study, integrated volatile profiling and metagenomic approaches were employed to investigate volatile characteristics and microbial functional potential differentiation in fermented grains with different fermentation degrees (under-fermented, normally fermented, and over-fermented). Significant differences in physicochemical properties were observed among fermentation degrees, particularly in acidity and reducing sugar content. Electronic nose analysis revealed distinct sensor response patterns among different fermentation degrees, indicating differences in overall volatile odor fingerprint patterns. A total of 81 volatile compounds were identified by HS-SPME-GC-MS, with aldehydes, ketones, and pyrazines showing pronounced variations among fermentation degrees, and acetaldehyde exhibiting strong discriminatory potential. LEfSe analysis identified 18 microbial taxa as potential biomarkers associated with different fermentation degrees, including Pichia kudriavzevii, Lentibacillus daiqui, and Acetobacter pasteurianus. Correlation analysis revealed significant positive associations between acetaldehyde levels and Acetobacter abundance. Furthermore, KEGG, CAZy, and eggNOG analyses revealed differentiated functional potentials among fermentation degrees, providing insights into the potential metabolic basis associated with flavor differentiation. Overall, these findings highlight that fermentation degree differentiation is closely associated with coordinated changes in physicochemical conditions, microbial communities, and functional potentials, providing ecological insights into flavor differentiation and theoretical support for objective fermentation degree evaluation and quality control of Jiangxiangxing Baijiu production.

Fermentation

Evaluation of pilocarpine effects on sweat proteome.

BACKGROUND: Sweat is increasingly recognized as a valuable, non-invasive biofluid for biomarker discovery, yet its composition depends on the stimulation method. This study aimed to determine how pharmacological induction with pilocarpine compares to physiologically induced sweat through exercise in shaping the sweat proteome. RESULTS: We analyzed thermoregulatory sweat from exercise, pilocarpine-induced sweat, and combined pilocarpine plus exercise sweat. Total protein concentrations were similar across conditions, but pilocarpine markedly increased proteomic diversity, with combined pilocarpine plus exercise sweat showing the highest number of identifications. The core sweat proteome remained stable, while pilocarpine selectively enriched low-abundance proteins involved in vesicular trafficking, cytoskeletal remodelling, and metabolism. Proteins linked to the canonical M3-Gq-PLC-Ca2+ pathway, including AQP5, CALML5, and CLIC1, were consistently enriched, confirming cholinergic activation. Pilocarpine-induced sweat also contained plasma-derived and immune-related proteins, reflecting enhanced secretion and reduced ductal reabsorption. CONCLUSIONS: Exercise yields a physiologically relevant but less complex proteome, pilocarpine-induced sweat produces a pharmacologically enriched yet biased profile, and combined pilocarpine plus exercise sweat maximizes protein detection at the expense of interpretability. These findings highlight the critical impact of stimulation paradigm on sweat proteomics and provide a reference framework for biomarker research. SIGNIFICANCE: This study employed LC-MS/MS to systematically characterize eccrine sweat and delineate how stimulation paradigms-exercise, pilocarpine, and their combination-shape its proteomic landscape. By demonstrating that pharmacological induction profoundly alters protein diversity and composition compared to physiologically induced sweat, these findings establish a critical benchmark for sweat-based biomarker research and highlight the need for paradigm-aware sampling strategies in clinical and translational contexts. Nonetheless, several methodological constraints warrant consideration: the limited sample size (five individuals per group), the exclusive inclusion of women under combined oral contraceptive treatment (21 active pills followed by 7 pill-free days), which restricts extrapolation to naturally cycling women, and the focus on healthy young adults (18-25 years), limiting generalizability to older or clinically heterogeneous populations. Despite these limitations, this work provides a foundational framework for optimizing sweat collection protocols and advancing precision approaches in non-invasive diagnostics.

Pilocarpine

On-filter fractionation by empFASP improves identification of membrane peptides in proteomic experiments.

Membrane proteins remain among the most analytically challenging targets in bottom-up proteomics due to their limited solubility and low abundance of protease-accessible sites within transmembrane domains. In addition, hydrophobic peptides are frequently lost during detergent removal and the on-filter processing steps. Here, we present empFASP, a straightforward on-filter-fractionation-based modification of the enhanced filter-aided sample preparation (eFASP) workflow that enhances recovery of membrane-embedded peptides otherwise lost during digestion and cleanup. The method combines controlled on-filter inversion with sequential ethyl acetate extraction at defined pH values, enabling recovery of peptide material retained on the filter and redistributed into detergent micelles. Compared with SP3 and SP4 in HEK293T lysates, empFASP increased unique hydrophobic peptide identifications by up to 48% and increased the proportion of detected transmembrane peptides. Application to mouse mitochondrial membranes and phosphatidylethanolamine-deficient and PE-containing Escherichia coli membranes showed that the additional fractions of empFASP contribute complementary recovery of hydrophobic and membrane-associated peptides, with the strongest gains observed at the peptide level. Because empFASP requires no specialized reagents or instrumentation, it can be readily implemented in standard proteomics workflows to improve coverage of membrane-embedded regions. SIGNIFICANCE: The empFASP (enhanced membrane peptide) workflow offers a practical solution to one of the persistent limitations in membrane proteomics-the underrepresentation of hydrophobic and transmembrane peptides in standard digests. By integrating simple pH-controlled extractions into an on-filter format, empFASP recovers peptides otherwise lost through adsorption or detergent micelle retention, substantially improving coverage of the membrane proteome. This method expands the analytical reach of bottom-up proteomics without requiring specialized instrumentation, making it immediately applicable for studies of membrane topology, protein-lipid interactions, and the structural consequences of altered membrane composition.

Proteomics

Metabolomic differences in the Ophiura sarsii complex from the Yellow Sea Cold Water Mass and Bering Sea Cold Pool.

Metabolomics provides a functional readout of cellular physiology and can reveal metabolite-level differences associated with environmental and evolutionary contexts. Here, we used GC-MS- and LC-MS-based metabolomics to characterize metabolic profiles of the Ophiura sarsii complex from the Yellow Sea Cold Water Mass (YSCWM) and the Bering Sea Cold Pool (BSCP). This metabolomics analysis identified 398 LC-MS/MS and 87 GC-MS/MS differential metabolites (DEMs). Marked metabolic differences were observed between the two taxa, involving antioxidant-related metabolites, central carbon-related intermediates, osmolyte-associated compounds, and membrane lipid components. O. sarsii vadicola from the YSCWM showed higher levels of glutathione, glucose, citric acid, D-ribulose 5-phosphate, and unsaturated lipid-related metabolites, indicating differences in antioxidant-related and energy-associated metabolic profiles. By contrast, O. sarsii from the BSCP was characterized by higher levels of sugar alcohols, particularly myo-inositol, together with differences in membrane lipid-associated metabolites. These results provide metabolomics-based evidence for metabolite-level physiological differences between two members of the O. sarsii complex sampled from the Yellow Sea Cold Water Mass and the Bering Sea Cold Pool, while the relative contributions of lineage divergence and site-specific environmental variation remain to be tested experimentally.

Metabolomics

Quantitative N-glycoproteomic analysis reveals glycosylation signatures of plasma immunoglobulin G in sepsis.

INTRODUCTION: Sepsis is a life-threatening condition resulting from organ dysfunction due to a dysregulated immune response to infection. Immunoglobulin G (IgG) plays a role in modulating immune responses. However, the precise IgG subclass-specific N-glycosylation profiles in patients with sepsis remain poorly characterized. METHODS: This study aimed to define the site-specific N-glycosylation signatures of plasma IgG subclasses in sepsis patients with different prognoses using quantitative glycoproteomics. By employing our established GlycoQuant strategy, we quantified the intact N-glycopeptides (IGPs) of IgG subclasses in 40 healthy controls and 40 sepsis patients with a clear prognosis. RESULTS: We identified 12 IGPs with altered abundances between patients with sepsis and healthy controls. After Benjamini-Hochberg (BH) correction of the 31 outcome-stratified IGP comparisons, IGP24 and IGP25 remained significant and met the prespecified fold-change criterion. Global BH correction across 124 IGP-clinical parameter correlations retained positive associations of IGP19, IGP22, and IGP23 with procalcitonin (PCT). In exploratory outcome-stratified ROC analyses, candidates were selected using the original unadjusted P-value and fold-change screen; five IGPs were evaluated, with IGP25 and IGP24 yielding the highest individual AUCs. Collectively, our findings underscore the potential of IgG subclass-specific glycosylation profiling as a novel translational approach for clinical applications in sepsis management. SIGNIFICANCE: Sepsis remains a leading cause of global mortality, with patient outcomes heavily dependent on timely diagnosis and accurate prognosis. The dysregulated host immune response, particularly involving immunoglobulins, is central to its pathophysiology. This study provides a significant advance in the field of clinical glycoproteomics by applying a quantitative, site-specific strategy to delineate the plasma IgG subclass N-glycosylation landscape in sepsis. We report, for the first time, a panel of subclass-specific intact IgG N-glycopeptides (IGPs) that are significantly altered in sepsis patients compared to healthy controls. The identified IGPs not only demonstrate diagnostic and prognostic potential but also show a significant correlation with procalcitonin, a key clinical severity index. These findings bridge a critical knowledge gap by moving beyond bulk IgG glycosylation analysis to subclass-resolved profiling, offering novel molecular insights into sepsis immunopathology. The identified glycosylation signatures hold substantial translational promise as a foundation for developing innovative, glycan-based biomarker panels to improve the precision management of this heterogeneous and life-threatening syndrome.

Humans

Sex- and age-specific associations of VEGFA polymorphisms with multiple sclerosis susceptibility.

AIM: To evaluate six VEGFA polymorphisms (rs1570360, rs699947, rs3025033, rs2146323, rs1413711 and rs833061) and serum VEGFA concentrations in 270 Lithuanian patients with multiple sclerosis (MS) and 270 matched healthy controls. METHODS: Genotyping was performed using real-time PCR, and serum VEGFA levels were measured by enzyme-linked immunosorbent assay. Statistical analyses were conducted using IBM SPSS version 31.0. RESULTS: Nominal differences in VEGFA genotype and allele distributions were observed in sex- and age-stratified analyses. Among females, the rs1413711 C allele was more frequent (p = 0.005), whereas the rs833061 C allele was less frequent (p = 0.006), in MS patients than controls. In participants aged >38 years, the rs1413711 C allele was also more frequent in MS cases (57.5% vs. 46.0%, p = 0.008). Logistic regression identified nominal associations, particularly for rs1413711, rs699947 and rs833061, but none remained significant after correction for multiple testing. Serum VEGFA levels were higher in MS patients than controls (p = 0.004). Nominal genotype-related differences in serum VEGFA levels and haplotype associations with reduced MS odds were also observed, but did not remain significant after multiple-testing correction. No consistent associations were found between VEGFA variants and clinical parameters. CONCLUSION: VEGFA genetic variation and elevated serum VEGFA may be associated with MS, but the genetic findings require confirmation in larger independent cohorts.

Humans

First insights into the role of evolutionary history in shaping venom composition of Vipera ammodytes.

Understanding intraspecific venom variation requires distinguishing the contributions of neutral population history from natural selection. This study aims to determine whether venom variation in Vipera ammodytes species complex is structured across eight phylogenetic groups. Despite a complex evolutionary history, venom composition did not differ among phylogenetic groups within the analytical framework used, suggesting that shared ancestry alone does not explain venom variation. Whether local adaptation to environmental conditions explains the observed variation remains an open question for future studies.

Animals

Ultra-high-frequency ECG quantifies residual electrical dyssynchrony during left bundle branch area pacing in patients with wide QRS: a paired within-patient study.

BACKGROUND: Left bundle branch area pacing (LBBAP) may restore a more physiological pattern of ventricular activation in patients with conduction delay; however, QRS narrowing alone may incompletely characterize electrical resynchronization. Ultra-high-frequency ECG (UHF-ECG) provides quantitative markers of ventricular activation timing and dyssynchrony. OBJECTIVE: To quantify paired OFF-to-ON changes in conventional ECG and UHF-ECG metrics during LBBAP in patients with baseline wide QRS and to assess the relationship between paced R-wave peak time (RWPT) and residual UHF-ECG dyssynchrony. METHODS: In this prospective single-center paired study, 21 patients with bradycardia and baseline wide QRS underwent standard ECG and UHF-ECG assessment during intrinsic rhythm (pacing OFF) and during LBBAP (pacing ON). Endpoints included QRS duration, signed VED16, absolute VED16 (|VED16|), mean ventricular delay (meanVD), and a clinically interpretable distance-to-normal metric defined as dist&#xa0;=&#xa0;max(|VED16|-20, 0). Paired changes were summarized as medians with bootstrap 95% confidence intervals and tested using the Wilcoxon signed-rank test. Associations between paced RWPT and residual dyssynchrony during pacing were evaluated using Pearson and Spearman correlation coefficients. RESULTS: LBBAP significantly narrowed QRS duration from 136.8 [130.2-153.6] ms during intrinsic rhythm to 116.0 [107.8-125.6] ms during pacing (median &#x394; -21.0&#xa0;ms; 95% CI -33.9 to -18.6; p&#xa0;<&#xa0;0.001). Signed VED16 did not change significantly (median &#x394; 0.4&#xa0;ms; p&#xa0;=&#xa0;1.000), consistent with the mixed conduction-phenotype composition of the cohort. In contrast, severity-oriented UHF-ECG endpoints improved: |VED16| decreased numerically (median &#x394; -5.2&#xa0;ms; p&#xa0;=&#xa0;0.070), whereas dist decreased significantly (median &#x394; -0.7&#xa0;ms; 95% CI -14.4 to 0.0; p&#xa0;=&#xa0;0.015). The proportion of patients within the normal dyssynchrony band (|VED16|&#xa0;&#x2264;&#xa0;20&#xa0;ms) increased from 7/21 (33.3%) to 12/21 (57.1%). Median paced RWPT was 66.6 [58.6-74.6] ms, and shorter RWPT correlated with lower residual |VED16| during pacing (Pearson r&#xa0;=&#xa0;-0.45, p&#xa0;=&#xa0;0.038). CONCLUSIONS: In patients with baseline wide QRS, LBBAP produces marked QRS narrowing, whereas UHF-ECG provides complementary quantification of residual electrical dyssynchrony. Severity-oriented UHF-ECG endpoints, particularly a distance-to-normal metric, may offer an interpretable mechanistic framework beyond conventional ECG alone. Shorter paced RWPT was associated with lower residual dyssynchrony during pacing, supporting physiological coherence between procedural and high-resolution electrocardiographic markers.

Humans

Development and validation of a liquid chromatography-tandem mass spectrometry method for the quantification of twenty-five steroids in equine serum.

Steroids are potential biomarkers for monitoring equine pregnancy. However, immunoassays currently used for their quantification suffer from cross-reactivity and limited specificity, thus requiring more accurate methods. This study reports the development and validation of a robust liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for simultaneous quantification of 25 steroids covering the main biosynthetic pathways of progestogens, corticosteroids, androgens, and estrogens. Steroids were extracted by protein precipitation followed by evaporation, derivatization, and reconstitution before LC-MS/MS analysis. A surrogate matrix was used for calibration and validation to avoid endogenous interference. Validation was performed according to and partly adapted from Clinical and Laboratory Standards Institute guidelines (CLSI), including linearity, trueness, precision, limits of detection and quantification, measurement uncertainty, recovery, matrix effects, carryover, selectivity, and stability. Calibration curves were fitted using the best-performing weighted linear or quadratic regression model, yielding excellent linearity (R2&#xa0;>&#xa0;0.990), trueness between -9.0% and 2.3%, and intra- and inter-day precision <6.3%. Lower limits of quantification ranged from 2.07 to 2250&#xa0;pg/mL depending on physiological analytes concentration. Extraction recovery averaged 24.3-114.9%, matrix effects were acceptable, and accuracy ranged from 94.4% to 98.9%. No carryover or interferences were detected. Measurement uncertainty remained <15%. This study presents the first LC-MS/MS method partially validated per CLSI criteria for the quantification of 24 steroids in equine serum. The method offers a sensitive and specific alternative to immunoassays and provides a robust tool for equine steroid profiling with potential applications in pregnancy monitoring, placentitis diagnosis, and fetal sex determination.

Animals

Mapping the immune-genetic architecture of Epstein-Barr virus-related phenotypes and multiple sclerosis through a single-cell genetic framework for target prioritization and pharmacologic hypothesis generation.

BACKGROUND: Multiple sclerosis (MS) is a severe neuroinflammatory disease causing substantial long-term disability. Strong epidemiologic evidence links Epstein-Barr virus (EBV) exposure with MS risk, but genetic evidence for immune target prioritization in EBV-related phenotypes remains limited. METHODS: We integrated single-cell cis-eQTL data from 14 immune cell types with GWASs of an EBV-related clinical phenotype and MS using a single-cell Mendelian randomization framework with colocalization analyses. Candidate eGenes were evaluated in independent cohorts. For multi-SNP instruments, we performed heterogeneity, pleiotropy, MR-Egger, weighted median, mode-based, and MR-PRESSO sensitivity analyses. We also conducted phenome-wide association analyses and queried DrugBank to annotate candidate compounds targeting prioritized genes. RESULTS: We prioritized 43 immune-cell-specific candidate eGenes with convergent genetic support, including 6 for the EBV-related phenotype and 37 for MS. SERPINB1 in NK cells was associated with increased risk of the EBV-related phenotype, whereas HLA-G was associated with decreased risk. For MS, APOM and MSH5 showed protective associations, while AHI1 showed cell-type-dependent, bidirectional associations across immune lineages. Colocalization and independent cohort evaluation supported these findings. Among FDR-significant multi-SNP associations, MR-Egger intercept tests did not indicate directional pleiotropy, although a small subset showed heterogeneity or MR-PRESSO signals. Phenome-wide analyses identified no significant adverse phenotypic associations among evaluable genes at the prespecified threshold. DrugBank annotation nominated sodium nitroprusside, fasudil, artenimol, and choline as hypothesis-generating compounds for experimental follow-up. CONCLUSIONS: This study provides a single-cell genetic framework for prioritizing immune-cell-specific candidate targets for EBV-related phenotypes and MS, and nominates genetically supported targets and pharmacologic hypotheses for experimental investigation.

Humans

Comprehensive study on pesticide residues and mycotoxins in freeze-dried strawberries and raspberries.

Freeze-dried fruit has gained popularity because it preserves the flavour and nutritional value of fresh fruit while providing extended shelf life. Despite this, there are concerns regarding its chemical safety. This study evaluated 58 freeze-dried fruit products from the Czech retail market, focusing on potential contamination. Pesticide residues and mycotoxins were determined using LC-MS/MS and GC-MS/MS. Overall, 111 pesticide residues (or their metabolites) and 3 mycotoxins were quantified. After applying processing factors, 12 pesticide residues exceeded EU maximum residue limits. Prohibited substances, including carbofuran, omethoate, and haloxyfop, were detected. Tenuazonic acid was found in 71% of samples, while alternariol and tentoxin were detected less frequently. More than half (54%) of strawberry samples contained 10 or more pesticide residues, indicating potential cumulative exposure concerns, particularly for children with lower body weight. These findings highlight the need for continued monitoring of freeze-dried fruits and further assessment of dietary exposure.

Pesticide Residues

Nimodipine in animal models of demyelination relevant to multiple sclerosis: a systematic review.

BACKGROUND: Multiple sclerosis (MS) is the most common inflammatory neurodegenerative disease in which axonal injury, neuronal death, and demyelination occur. Treatment for MS relapses remains limited, which alleviates acute loss of function but has no impact on long-term disability. This study aimed to perform a systematic review of the effects of nimodipine on experimental demyelination models, including experimental autoimmune encephalomyelitis (EAE) and Cuprizone models in rodents. METHODS: This study was conducted following the PRISMA statement. A systematic search was performed in PubMed, Scopus, the Cochrane Library, and Google Scholar. The primary outcome was EAE clinical disease severity (peak clinical score and/or cumulative disease burden). Secondary outcomes included relapse activity (when reported), histological myelin outcomes, oligodendrocyte lineage markers, neuroaxonal injury markers, and inflammatory readouts. Risk of bias was assessed using the SYRCLE tool. RESULTS: Out of 4660 results, 5 studies were included in the systematic review (four EAE studies and one cuprizone model). Nimodipine was administered using heterogeneous regimens (oral, intravenous, intraperitoneal, subcutaneous, or osmotic pump delivery; 1-30&#xa0;mg/kg/day). The included studies reported the variable effects of nimodipine on relapse-related outcomes, myelination, inflammatory processes, and neuroprotection in the EAE model of MS. Across EAE studies, nimodipine generally reduced clinical disease severity or cumulative burden, although relapse-related outcomes were inconsistent. CONCLUSIONS: Preclinical evidence suggests that nimodipine may attenuate disease severity and demyelination and may promote repair-related processes in rodent models relevant to MS. However, to evaluate the clinical applicability of nimodipine in MS patients, well-powered, transparently reported preclinical replication and early-phase clinical studies are required before clinical translation.

Animals

Normoalbuminuric and albuminuric diabetic kidney disease exhibit divergent renal proteomic characteristics: implications for management.

BACKGROUND: The pathogenesis of diabetic kidney disease (DKD) is complex. Normoalbuminuric diabetic kidney disease (NADKD) is a special subtype of DKD that often progresses insidiously without detectable albuminuria, posing diagnostic and therapeutic challenges. Its pathogenesis remains unclear. Proteomic analysis of renal tissues may offer insights into its pathogenesis and identify biomarkers. METHODS: Clinicopathological data from 295 biopsy-proven DKD patients were collected and classified into normoalbuminuric (UACR&#xa0;<&#xa0;30&#xa0;mg/g, n&#xa0;=&#xa0;25), microalbuminuric (UACR 30-300&#xa0;mg/g, n&#xa0;=&#xa0;26), and macroalbuminuric (UACR&#xa0;>&#xa0;300&#xa0;mg/g, n&#xa0;=&#xa0;244) groups. Laser microdissection combined with mass spectrometry (LMD/MS) was used to analyze glomerular and proximal tubule proteomics in 5 patients per DKD subgroup and 5 control subjects. Associations with clinical features were examined. RESULTS: Glomerular proteomic analysis revealed that oxidative stress and metabolic pathways (UQCRC1) were upregulated in NADKD group, whereas the complement and coagulation cascades (C3, C5, C6, C9, CFH, CFHR1) were significantly upregulated in the microalbuminuric and macroalbuminuric DKD groups. The proximal tubule proteomics analysis showed that oxidative phosphorylation-related proteins (SDHA, CYCS, UQCRQ) were upregulated in NADKD, and collagen I related proteins (COL1A1, COL1A2) were significantly upregulated. CONCLUSION: Oxidative stress and mitochondrial dysfunction are involved in the progression of NADKD, lesions predominantly located in the tubulointerstitium. The complement pathway participates in the pathogenesis and progression of albuminuric DKD (ADKD). These divergent molecular profiles suggest that NADKD and ADKD may reflect different pathophysiological mechanisms and have important implications for therapeutic strategies in diabetes management.

Humans

Distinct molecular responses to acute cold exposure revealed by comparative transcriptomic and metabolomic profiling in the bay scallop Argopecten irradians.

Acute cold stress can elicit distinct molecular responses even when bay scallop populations show similar phenotypic outcomes. We compared a seventh-generation fast-growing bay scallop line (BS) with a commercial control population (CC) during a 72-h acute cold exposure at -1&#xa0;&#xb1;&#xa0;0.3&#xa0;&#xb0;C. RNA-seq was used as the discovery layer, representative BS cold-responsive genes were evaluated by qRT-PCR, and paired LC-MS profiles provided a comparative metabolic layer. At baseline, 138 genes differed between BS and CC; after cold exposure, 134 of these baseline differences disappeared and 61 of 65 cold-state differences newly emerged. BS showed a larger transcriptomic response magnitude than CC, with 1129 cold-responsive genes compared with 28 genes in CC, and this ordering remained robust across multiple sensitivity analyses. Survival after 72&#xa0;h was identical in BS and CC (83/90, 92.2% in each population). Biochemical responses were time-dependent and marker-specific: CAT, LZM, T-SOD and T-AOC showed population-by-time interactions, whereas GSH-Px and MDA did not, and the 72-h differences were not consistently favourable to BS. Metabolomic cold effects were strongly concordant between populations, and no feature showed a significant population-by-cold interaction. Features putatively assigned to arachidonic acid metabolism were enriched, but this provider-annotated pathway signal remains exploratory because authentic-standard confirmation was not performed. These findings indicate population-specific differences in molecular responsiveness but do not establish superior cold tolerance in BS.

Animals

Effects of aerosol aging on composition and light-absorbance of nitrogen-containing organic compounds: Evidences from ultra-high-resolution mass spectrometry analysis.

Nitrogen-containing organic compounds (NOCs) are key components of particulate matter (PM), but their compositional evolution and light-absorbing properties during atmospheric aging remain poorly understood. In this study, ultra-high-performance liquid chromatography coupled with Orbitrap mass spectrometry was used to semi-quantitatively analyze 59 PM1 samples collected in Shanghai. NOCs accounted for 31 % and 64 % of the detected species in negative (ESI-) and positive (ESI+) ionization modes, respectively. Atmospheric aging significantly reduced the molecular diversity of polar organics, with both the number and mass concentration percentages of CHON- compounds showing significant negative correlations with aging degree. Van Krevelen analysis demonstrated a decrease in the number of carboxylic-rich alicyclic molecules and their CHON- contributions during the aging process (from 37.7 % in fresh samples to 21.2 % in aged samples). CHN+ compounds, a major NOCs group in ESI+ mode, also decreased with aging. Correlation analyses involving the Bep/(Bep+Bap) ratio, relative humidity, and mass absorption efficiency at 365 nm revealed a decline in light absorption capacity with aging, suggesting aqueous-phase oxidation as a dominant aging mechanism. CHON- and CHN+ compounds were identified as the principal light-absorbing constituents in PM1. This work provides new insights into the aging-induced transformations of NOCs in urban PM1, and their changing role in light absorption, highlighting the need for further investigation of the aging mechanisms of NOCs.

Aerosols

Prevalence of Slowly Expanding Lesions in Patients With Multiple Sclerosis: A Systematic Review and Meta-Analysis.

BACKGROUND AND OBJECTIVES: Chronic active lesions (CALs) reflect chronic inflammation in multiple sclerosis (MS). Slowly expanding lesions (SELs) are CALs identified on conventional MRI by linear, concentric expansion over time, while paramagnetic rim lesions (PRLs) are CALs characterized by a paramagnetic rim on susceptibility-sensitive MRI. However, the prevalence of SELs and their overlap with PRLs remain unclear. The aims of this study were to (1) estimate the proportion of SELs among all T2 lesions and the proportion of patients with at least 1 SEL and (2) assess the proportion of SELs overlapping with PRLs. METHODS: We systematically searched PubMed, Scopus, Web of Science, and Embase on February 1, 2026, for studies evaluating SELs in MS. At least 2 authors independently assessed study eligibility. Primary outcomes were the pooled proportion of SELs among T2 lesions and the proportion of patients with at least 1 SEL. We estimated mean per-patient volumes of SELs and total T2 lesions and the proportion of SELs overlapping with PRLs. Random-effects generalized linear mixed-effects models and inverse-variance methods were used, with between-study heterogeneity assessed using &#x3c4;2 and I2 and robustness using sensitivity analyses. Univariable meta-regression explored heterogeneity. PROSPERO: CRD42024603778. RESULTS: Of 5,980 records, 20 studies comprising 4,786 patients with MS were included (mean age: 43.6 &#xb1; 6.3 years; 63.7% female). Sample sizes varied by outcome. SELs accounted for 14% (95% CI 10-21) of all T2 lesions, and 78% (67-85) of patients had at least 1 SEL. After sensitivity analysis, per-patient mean volumes were 1.42 mL (0.79-2.06) for SELs and 10.6 mL (8.53-12.67) for total T2 lesions. In total, 11% (6-20) of SELs overlapped with PRLs. In subgroup analyses, proportions of SELs were similar in relapsing-remitting and progressive MS (15%), but the proportion of patients with at least 1 SEL was higher in progressive MS. Between-study heterogeneity was high across analyses with no significant sources identified. DISCUSSION: Although SELs represent a minority of T2 lesions, most patients have at least 1 SEL and a subset overlaps with PRLs, suggesting a partial correspondence between these 2 imaging markers of chronic inflammatory activity. Limitations include possible publication bias, high unexplained heterogeneity, differences in SEL identification methods, and differences in MRI time point number/timing.

Humans

Furanic compounds in different coffee extraction systems: Analysis of the main influencing factors and correlation with acrylamide.

This study investigates how different coffee types representative of distinct roast profiles and brewing methods jointly affect the occurrence of furanic compounds and acrylamide in brewed coffee. Coffees were prepared using eight extraction methods (AeroPress, Clever, Chemex, French Press, Moka, Pure Brew, Turkish and V60). Five furanic compounds (furfural, furfuryl acetate, 5-methylfurfural, furfuryl alcohol and 5-hydroxymethylfurfural) were quantified in coffee powders and brews by HS-SPME-GC-MS, while acrylamide was determined by UHPLC-MS/MS. Moka and Turkish brews consistently exhibited the highest concentrations of furanic compounds, whereas paper-filtered pour-over methods (V60 and Chemex) showed the lowest levels. Pearson correlation analysis revealed coffee-dependent relationships between furanic compounds, acrylamide and extraction parameters with the strongest associations observed in dark-roasted coffee, reflecting advanced Maillard reaction chemistry. Overall, these results demonstrate that contaminant levels arise from the combined effects of intrinsic coffee chemistry and brewing mechanics and support targeted mitigation strategies: such as roast selection and brewing method optimization.

Acrylamide