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PubMed2026

Investigation of ACE gene polymorphism and serum ACE activity in relation to alopecia areata among Iraqi patients.

BACKGROUND: Alopecia areata (AA) is a multifactorial disorder with immune dysregulation and genetic susceptibility, affecting 0.5-2% globally. OBJECTIVE: This study investigated angiotensin converting enzyme (ACE) gene insertion /deletion (I/D) polymorphism and serum ACE activity in Iraqi AA patients and their association with inflammatory cytokines (interleukin [IL]-17) and nutritional markers to understand disease progression. METHODS: This case-control study included 50 AA patients (Male and Female) and 35 healthy controls. ACE gene polymorphism (rs1799752) was analyzed using real-time polymerase chain reaction (qPCR) with high-resolution melting (HRM) analysis. Serum IL-17 levels were determined by enzyme-linked immunosorbent assay (ELISA), and biochemical markers were measured using an automated analyzer. RESULTS: ACE gene polymorphism (rs1799752) showed non-significant genotype distribution between patient and control groups (p > 0.05), though a trend toward DD genotype enrichment was observed in patients. Serum ACE levels were significantly higher in patients versus controls (p < 0.0001) with high diagnostic performance. ACE correlated positively with IL-17 (P < 0.0001) and negatively with vitamin D3 and zinc (P < 0.0001). Female patients had significantly higher ACE levels than males (P < 0.01). CONCLUSIONS: ACE emerges as an immunometabolic hub in AA pathogenesis, integrating inflammation with nutritional deficits, suggesting its potential as a biomarker and therapeutic target.

Humans↗

PubMed2026

Effects of Photobiomodulation Therapy in Lateral Luxation of Anterior Permanent Teeth: A Randomized, Double-Blind Clinical Trial.

BACKGROUND: Among the traumatic dental injuries (TDIs), lateral luxation may present poor prognosis due to frequent root resorption and consequent tooth loss. Photobiomodulation therapy (PBMT) modulates cellular activities (proliferation, differentiation, growth factor secretion) and may improve outcomes. OBJECTIVE: This randomized, double-blind, placebo-controlled trial evaluated PBMT (660 vs. 808 nm) for post-operative pain and pulp sensitivity recovery in lateral luxation of permanent anterior teeth. METHODS: Initially, 41 patients were included, with a total of 63 teeth traumatized by lateral luxation and were allocated to G1 (n = 21): Splinting + sham PBM (placebo), G2 (n = 21): Splinting + 808 nm infrared PBM and G3 (n = 21): Splinting + 660 nm red PBM. Four weekly sessions (3 J/point, 3 points) were administered. Pain (by numeric rating scale) and pulp sensitivity (by cold test) were assessed weekly. Pain was analyzed using the Kruskal-Wallis test, followed by multiple comparisons using Dunn's method with Bonferroni correction, and pulp sensitivity by a logistic regression model (p < 0.05). RESULTS: Three participants (total of 5 teeth) were excluded due to loss to follow-up. Fifty-eight teeth were analyzed (G1 = 21, G2 = 17, G3 = 20). Pain: All groups showed a significant reduction in pain over time (p < 0.001). Both G2 and G3 demonstrated a significantly greater reduction in pain compared to G1 (p < 0.001 and p = 0.026, respectively). No significant difference in pain reduction was observed between G2 and G3. Pulp sensitivity: G2 showed a significant improvement over time (p < 0.001), despite starting from a more unfavorable baseline. In contrast, no significant change in pulp sensitivity was observed for G1 or G3 between the initial and final assessments. CONCLUSION: Within the limitations of this clinical study, all intervention groups were effective in reducing pain in lateral luxation of permanent anterior teeth, with superior results for laser groups compared to the placebo. However, only the 808 nm laser irradiation protocol demonstrated a significant improvement in pulp sensitivity, suggesting it may offer a more complete therapeutic response.

Humans↗

PubMed2026

Examining early-phase symptom trajectories in interpersonal psychotherapy versus antidepressant medication for adults with depression: A dynamic time warp network analysis.

BACKGROUND: Depression is characterized by substantial symptom heterogeneity, which is often concealed when examining total severity scores. Analyzing symptom-level change can improve our understanding of treatment effects and recovery processes. This study, therefore, examined dynamic symptom networks during early-phase interpersonal psychotherapy (IPT) and selective serotonin reuptake inhibitor (SSRI) antidepressant treatment, assessing patterns of symptom change across as well as differences between treatments. METHODS: Using weekly item-level Hamilton Depression Rating Scale (HAM-D) data from a randomized clinical trial comparing IPT and SSRIs for adults with depression, this preregistered study examined symptom trajectories in the first six weeks of treatment with Dynamic Time Warping (DTW). RESULTS: Depressive symptom trajectories and DTW-based symptom networks were largely similar for IPT and SSRI. In both conditions, changes in somatic symptoms of anxiety and middle insomnia tended to precede improvements in depressed mood. CONCLUSIONS: Early symptom change may occur outside the core affective domain, underscoring the importance of monitoring symptoms broadly. Symptom-level patterns may reflect patients' stage of recovery and provide clinically relevant information beyond total severity scores. The absence of differences in improvement patterns between IPT and SSRI suggest few indications for treatment selection based on baseline symptom profiles. Future research should replicate and extend these findings to subsequent treatment phases using more frequent assessments and a broader range of interventions.

Humans↗

PubMed2026

Stage-specific ROMO1 in rheumatoid arthritis: predictive immune insights into the MIF pathway and HLA-DR/IL2RA axis via integrated GWAS, transcriptomic, single-cell, and spatial profiling.

Emerging evidence links reactive oxygen species modulator 1 (ROMO1), a key mitochondrial ROS regulator, to rheumatoid arthritis (RA) pathogenesis. However, its exact mechanism remains elusive given the conflicting evidence about its specific function. We used a four-level integrative framework combining multi-omics data and literature‑supported mechanistic inference. At the genetic level, Mendelian randomization (MR) was performed to explore potential causal relationships between ROMO1, IL2RA, HLA-DR, MIF, and RA risk, followed by differential expression analysis and machine learning-based feature selection to identify key mROS genes. The temporal expression dynamics of ROMO1 were assessed in RA progression. At the cellular and tissue levels, we integrated single-cell RNA sequencing and spatial transcriptomics to map cell-type-specific expression and synovial localization of ROMO1-related immune cells and pathways. Finally, our multi-omics findings were contextualized with literature-supported mechanistic inference. (1) MR results were consistent with a potential protective effect of ROMO1 on RA (OR = 0.52) and its potential regulation of risk factors IL2RA (OR = 0.46) and HLA-DR (OR = 0.40). Conversely, IL2RA (OR = 1.42), HLA-DR (OR = 1.88), and MIF (OR = 1.17) were positively associated with RA risk. Additionally, ROMO1 was identified as a top candidate diagnostic predictor with stage-specific dynamics: downregulated in the early but upregulated in the late/remission stages. (2) Single-cell RNA sequencing showed ROMO1's cell-specific expression in CD14+ HLA-DR+ CD74+ monocytes and CD4+ IL2RA+ T cells. Cell communication analysis further suggested that these cells may participate in MIF pathway regulation. Spatial transcriptomics subsequently identified that ROMO1-related cells localized to synovial pathological regions, with MIF pathway changes correlated with RA progression. (3) Finally, literature-supported mechanistic inference suggests that ROMO1 may modulate mROS levels to promote anti-inflammatory M2 macrophage polarization, which could theoretically contribute to reduced systemic inflammation and the alleviation of multi-organ decline in RA. This integrated multi-omics investigation, supported by literature-based mechanistic inference, suggests ROMO1 as a stage-dependent biomarker candidate and potential immune regulator in RA.

Humans↗

PubMed2026

Evolutionary characterization and expression profiling of ACC and FASN genes in Chinese mitten crab Eriocheir sinensis.

Acetyl-CoA carboxylase (ACC) and fatty acid synthase (FASN) are rate-limiting enzymes in the fatty acid biosynthetic pathway, yet their evolutionary relationships, sequence features, and expression profiles remain poorly understood in crustaceans, particularly in the economically important Chinese mitten crab (Eriocheir sinensis). Here, we identified and systematically analyzed ACC and FASN genes in E. sinensis using comparative genomic analyses across 43 species. ACC was highly conserved as a single-copy gene in invertebrates, in contrast to the multiple paralogs observed in vertebrates. Similarly, FASN was generally maintained as a single-copy gene across most taxa but exhibited lineage-specific expansion in certain insect groups. Phylogenetic and structural analysis revealed strong conservation of both genes within crustaceans, supported by multiple conserved motifs and canonical functional domains. Expression profiling showed predominant expression in the hepatopancreas and midgut, suggesting their potential involvement in crustacean lipid metabolism. During the molting cycle, ACC and FASN exhibited higher expression levels during stages C and D, suggesting an increased capacity for fatty acid biosynthesis before molting. In addition, dietary lipid levels experiment revealed that ACC and FASN expression responded dynamically to dietary lipid availability, with increased expression at moderate lipid levels but reduced expression under excessive lipid supplementation, indicating a possible adaptive transcriptional response to lipid status. Collectively, this study provides insights into the evolutionary conservation and expression dynamics of ACC and FASN and improves our understanding of lipid metabolic adaptation in crustaceans.

Animals↗

PubMed2026

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↗

PubMed2026

Sexual selection purges mutation load, but not overall genetic diversity, decreasing vulnerability to extinction.

Theory suggests sexual selection will enhance population viability by purging deleterious alleles. However, direct genomic evidence for this fundamental idea is scarce and contradictory. We combined long-term experimental evolution with whole-genome resequencing to directly test how sexual selection affects mutation load, genomic divergence, and extinction risk in small populations (maximum Ne = 40) of Tribolium castaneum. After 156 generations, populations evolving under strong sexual selection carried substantially fewer deleterious alleles than populations under weak sexual selection, based on both individual-level estimates of missense and nonsense variants and population-level Rxy analyses, indicating more efficient purging of deleterious alleles. In contrast, nucleotide diversity and runs of homozygosity were similar across treatments, indicating that purging acted most strongly on deleterious variation, and that reduced mutation load in these small populations under strong sexual selection was not explained by demographic effects. Importantly, population-level mutation load estimates best explained extinction risk under inbreeding, directly linking sexual selection to purging and population viability. Genome scans of high and low sexual selection populations revealed peaks of divergence, which included genes involved in courtship, sex discrimination, and seminal fluid proteins. Our results provide direct genomic evidence that sexual selection can reduce mutation load without eroding standing genetic diversity and thus adaptive potential, while driving adaptive divergence in reproductive traits. This beneficial purging may help explain the widespread prevalence of sexual reproduction in nature despite inherent costs and have important ramifications as to how we manage populations of conservation concern.

Animals↗

PubMed2026

Phylogenomics and female reproductive morphology reframe the classification of the Halymeniales (Rhodophyta).

The red algal order Halymeniales (Rhodophyta) exhibits remarkable morphological and taxonomic diversity but its higher-level relationships remain poorly resolved. Here, we present a comprehensive phylogenomic analysis based on newly generated plastid (170 protein-coding genes), mitochondrial (23 genes), and complete nuclear ribosomal cistron sequences from 56 taxa, complemented with an expanded rbcL dataset encompassing 334 sequences. Our results provide a robust phylogenomic framework for the Halymeniales, offering a taxonomic backbone for future systematic studies. The analyses consistently recover six early-diverging lineages (Acrodiscus, Isabbottia, Norrissia, Pachymenia, Zymurgia, and Tsengia) and two strongly supported larger clades (Halymenia s.l. and Grateloupia s.l.). While most small and recently described genera are monophyletic, several traditional genera (e.g., Halymenia, Cryptonemia, Grateloupia) are poly- or paraphyletic, requiring considerable taxonomic revision. At the family level, the data indicate that reinstatement of the Grateloupiaceae sensu Kim et al. (2021) would entail a revised circumscription of the Halymeniaceae and the recognition of at least five small families to accommodate the early-diverging lineages. Although such a revised classification would result in monophyletic families, it is not supported by morpho-anatomical characters. Instead, we propose a more stable two-family system, recognizing a broadly circumscribed Halymeniaceae that is sister to the Tsengiaceae. Female reproductive characters, particularly the structure of carpogonial and auxiliary cell ampullae, support this two-family system and further characterize many genus-level clades, although substantial convergence across lineages exists.

Phylogeny↗

PubMed2026

ATF4-histone 2-hydroxyisobutyrylation feedback loop drives sepsis-induced inflammation.

BACKGROUND AND PURPOSE: The role and mechanisms of lysine 2-hydroxyisobutyrylation (Khib) in the acute inflammatory phase of sepsis remain unclear. We investigated the function and underlying mechanisms of histone H4 lysine 5 2-hydroxyisobutyrylation (H4K5-hib) in sepsis-induced inflammation in vivo and in vitro. EXPERIMENTAL APPROACH: Acute sepsis was induced by caecal ligation and puncture (CLP) in mice, and inflammatory responses were modelled in lipopolysaccharide (LPS)-stimulated macrophages. CUT&Tag-seq was used to identify genomic targets associated with H4K5-hib and activating transcription factor 4 (ATF4). Immunofluorescence, Western blotting, qPCR, dual-luciferase assays, and ELISA were performed to investigate the underlying mechanisms. KEY RESULTS: H4K5-hib levels were increased in macrophages during the acute inflammatory phase of sepsis. LPS stimulation enhanced H4K5-hib enrichment at the ATF4 promoter, thereby promoting ATF4 transcription. Inhibition of EP300-mediated 2-hydroxyisobutyrylation or mutation of H4K5 abolished ATF4 activation. Increased H4K5-hib activated the ATF4/NLRP3 signalling axis, promoting inflammasome assembly and amplifying inflammatory responses. ATF4 directly bound to the EP300 promoter and enhanced its transcription, forming a positive feedback loop that further increased H4K5-hib levels. In CLP-induced sepsis, pharmacological inhibition of EP300 or ATF4 reduced H4K5-hib levels and suppressed NLRP3 inflammasome activation. CONCLUSION AND IMPLICATIONS: These findings reveal a previously unrecognized epigenetic mechanism underlying sepsis-induced inflammation and identify the EP300/ATF4/H4K5-hib positive feedback loop as a potential therapeutic target for sepsis.

Animals↗

PubMed2026

Investing in Canada's nursing workforce: a comprehensive review to inform policy innovations and directions.

BACKGROUND: Health systems worldwide face persistent health workers challenges including nursing shortages, workforce strain, and inequities. In Canada, these challenges have prompted renewed national and provincial reforms to strengthen recruitment, retention, leadership, and sustainability. This paper compares nursing workforce policy directions across Canada, and international jurisdictions to inform policy and planning. METHODS: A cross-country comparative analysis of policies building on a comprehensive national funded review that included an umbrella review of 69 systematic reviews, a comparative policy review of nursing workforce strategies in five jurisdictions, and validation through national horizon-scanning and policy dialogues (n >100). Evidence was analyzed across system, organizational, and individual levels. RESULTS: At the system level, international jurisdictions demonstrate comprehensive, legislated approaches integrating data, governance, and multi-year funding have advanced key nursing strategies. In Canada, the advances show the importance of strategies to have national and provincial/territorial alignment emphasizing leadership, flexibility, and inclusion as key levers. Organizational and individual-level reforms such as mentorship, leadership development, and wellness initiatives are expanding but remain variably evaluated. Experts identified national workforce data strategies and policy integration with embedded evaluation as key enablers to inform scalability and sustainability of implemented strategies. CONCLUSIONS: Canada's nursing workforce reforms are advancing toward coordinated, equity-driven, and evidence-informed strategies. Continued investment in evaluation, leadership, and national integrated data systems along with integrating nursing workforce planning within broader intersectoral planning will consolidate these gains and position Canada as an international leader in sustainable nursing workforce policy.

Canada↗

PubMed2026

A 20-Y Analysis of Motorcycle Trauma After Helmet Law Repeal.

INTRODUCTION: After Arkansas repealed its universal motorcycle helmet law in 1997, helmet use decreased and motorcycle-related injuries and fatalities increased. Long-term clinical and population-level impacts of this policy change remain incompletely characterized. This study integrates statewide crash and fatality data with trauma center data to evaluate trends in helmet use, injury severity, and mortality at scene and hospitalization. METHODS: We retrospectively reviewed motorcycle-related admissions and emergency department deaths at the state's only adult level I trauma center from 2004 to 2023 across three periods: 2004-2006, 2013-2015, and 2021-2023. Demographics, helmet use, injury severity, and outcomes were assessed. Logistic regression evaluated associations between helmet use, severe head injury (Abbreviated Injury Scale ≥3), and inhospital mortality. Fatality data were obtained from the National Highway Traffic Safety Administration, and crash-level data (2015-2023) were obtained from the State Department of Transportation. RESULTS: Among 1104 trauma admissions, annual admissions nearly tripled over time, with nonhelmeted riders representing 64%-72%. Helmet use was independently associated with lower odds of severe head injury (odds ratio 0.48, P < 0.001). Nonhelmeted riders had higher on-scene fatality risk (relative risk 1.21). Severe head injuries increased and were strong predictors of inhospital mortality. Population-adjusted motorcycle fatality rates rose from 2.34 to 3.18 per 100,000 residents by 2021-2023. CONCLUSIONS: Motorcycle fatalities and severe head injuries increased during the postrepeal period and were associated with helmet nonuse and severe head trauma. Clinical and statewide data show consistent associations among helmet nonuse, severe head injury, and prehospital and in-hospital mortality, highlighting helmet use as a target for injury prevention policy.

Acute brain injury↗

PubMed2026

Comparative profiling of microbial community structure, enzyme potential, metabolic features, and volatile composition in craft and Jiafan Huangjiu processes.

Craft Huangjiu and Jiafan Huangjiu represent two distinct industrial Huangjiu product outcomes with contrasting volatile profiles. This study compared craft Huangjiu (L70) and Jiafan Huangjiu (L79) to characterize their physicochemical, microbial, gene-level functional, metabolic, and volatile features. Because L70 involved mid-fermentation addition of finished Huangjiu, this comparison was not intended to isolate the sole effect of fermentation interruption versus continued fermentation. L79 showed more extensive carbon and nitrogen utilization, with lower residual substrates and higher ethanol and acetic acid contents than L70, whereas L70 retained a less complete fermentation state. At the volatile level, GC-MS and volatile metabolomics consistently showed an ester-enriched profile in L79 and a more alcohol-dominant profile in L70. FlavorDB-based putative annotation and threshold-based OAV analysis further indicated distinct database-assigned descriptor distributions and potential odor-active compounds, with more OAV > 1 ester-related compounds in L79. Metagenomic analysis showed that L70 was dominated by Lactobacillus acetotolerans, whereas L79 contained higher relative abundances of Saccharomyces cerevisiae, Aspergillus oryzae, Aspergillus flavus, and Fructilactobacillus fructivorans. Metagenomic functional annotation showed higher representation of hydrolysis-related CAZy genes and ester-related enzyme annotations in L79. KEGG-based pathway mapping further indicated greater gene-level potential for ethanol-, acetate-, and acetyl-CoA-related metabolism in L79. Accordingly, the L70 profile should be interpreted as the integrated final-product outcome of process intervention, exogenous input, and subsequent fermentation. The findings provide a comparative basis for future flavor regulation and process optimization in Huangjiu and other fermented alcoholic beverages.

Volatile Organic Compounds↗

PubMed2025

The effects of haptonomy and virtual reality, anxiety, prenatal attachment and acceptance of pregnancy in unplanned pregnancy.

AIM: Unplanned pregnancies are an important public health problem that negatively affects the health of women and babies. This study aimed to determine the effects of haptonomy and virtual reality on anxiety, prenatal attachment and acceptance of pregnancy in unplanned pregnancies. Haptonomy, a touch-based bonding technique, and virtual reality, an immersive fetal visualisation tool, were used as interventions. METHODS: The sample of this randomised controlled study consisted of 217 pregnant women (haptonomy: 73, virtual reality: 72 and control: 72) who applied to the Obstetrics and Gynaecology outpatient clinics of a public hospital in eastern Turkey between July 2020 and April 2021. For both experimental groups, four interviews were conducted with the pregnant women between the 24thand32nd gestational weeks at intervals of 7-10 days. Data were collected on pregnancy-related anxiety, prenatal attachment and pregnancy acceptance. Group differences were analysed using appropriate statistical comparisons. RESULTS: Pregnancy-related anxiety was lower, and acceptance of pregnancy was higher in the experimental groups compared to the control group (p < .001). Prenatal attachment level was higher in the haptonomy and virtual reality groups compared to the control group (p < .001). Notably, prenatal attachment scores were significantly higher in the haptonomy group compared to the virtual reality group (p < .001). CONCLUSION: In unplanned pregnancies, imagining the baby through haptonomy and imagining the baby through virtual reality are techniques that reduce the level of anxiety related to pregnancy and increase the level of prenatal attachment and acceptance of pregnancy. Especially haptonomy showed a higher effect on prenatal attachment.

Humans↗

PubMed2026

ReMeDy: A Flexible Statistical Framework for Region-Based Detection of DNA Methylation Dysregulation.

Region-based epigenome-wide association studies have demonstrated improved statistical power and biological interpretability compared with probe-wise analyses of DNA methylation data. However, most existing region-based methods characterize methylation dysregulation primarily through changes in mean methylation levels associated with a phenotype of interest. Substantial evidence indicates that phenotype-associated methylation alterations may also manifest through changes in methylation variability or through joint shifts in mean and variability. Despite this, no existing statistical framework jointly models mean-variance methylation changes in a region-based manner. We propose ReMeDy, a flexible statistical framework that uses a hierarchical likelihood approach within a generalized linear model setting to identify differentially methylated regions, variably methylated regions, and regions exhibiting joint differential and variable methylation at a genome-wide scale. Unlike existing models, ReMeDy operates directly on biologically defined co-methylated regions, allowing it to naturally capture spatial correlation inherent in DNA methylation array data, while avoiding reliance on heuristic, user-defined tuning parameters such as smoothing spans and kernel bandwidths that can substantially influence results and introduce subjectivity. Through extensive simulation studies and comprehensive benchmarking against popular models, we demonstrate that ReMeDy maintains false discovery and Type-I error rates at nominal levels while achieving consistently higher statistical power across a wide range of realistic scenarios. Application to population-level DNA methylation data further shows that ReMeDy identifies biologically meaningful regions and pathways implicated in complex human diseases that are not captured by conventional mean-based analyses alone. ReMeDy is implemented as an open-source R package and is freely available at https://github.com/SChatLab/ReMeDy.

DNA Methylation↗

PubMed2026

Applications of quantum AI in brain disorder diagnosis: A systematic review.

BACKGROUND AND OBJECTIVE: Brain disorder diagnosis and prediction remain challenging because neuroimaging, electrophysiological, behavioral, and multimodal data are high-dimensional, noisy, heterogeneous, and limited by small clinical cohorts. This systematic review synthesised applications of quantum artificial intelligence (QAI) for brain disorder diagnosis, prediction, detection, and monitoring. METHODS: Following PRISMA guidelines, studies published from 2016 to 13 January 2026 were retrieved from Scopus, Web of Science, and IEEE Xplore. After screening, 36 studies met the eligibility criteria and were qualitatively analysed according to disorder category, data modality, QAI method, implementation setting, validation strategy, and performance. RESULTS: At the broader disease-group level, neurodegenerative disorders were the most frequently investigated, followed by mental health and psychiatric disorders. At the individual level, Parkinson's disease and schizophrenia were the leading applications, followed by depression, anxiety, Alzheimer's disease, and stress-related tasks. MRI-based modalities were the most frequently used data source, followed by multimodal data and EEG. Methodologically, primary QAI approaches were dominated by quantum neural and QDL architectures, followed by quantum-inspired optimization or feature-selection methods and quantum-kernel/conventional QML classifiers. Qiskit/IBM Quantum and PennyLane were the most frequently reported quantum software frameworks. However, most studies relied on simulators, classical quantum-inspired implementations, or unclear implementation settings, with limited real-hardware evaluation. CONCLUSIONS: QAI shows emerging potential for brain disorder analysis, particularly through hybrid quantum-classical learning, quantum neural architectures, quantum-kernel methods, and quantum-inspired optimization. Nevertheless, current evidence remains preliminary and requires larger datasets, subject-level and external validation, fair classical benchmarking, noise-resilient circuits, real quantum hardware evaluation, explainability, and clinical validation.

Humans↗

PubMed2026

Routine methods misidentify Serratia spp.: Limitations of MALDI-TOF MS revealed by whole-genome sequencing.

Accurate species-level identification within the genus Serratia remains challenging due to extensive phenotypic overlap and high genomic relatedness among closely related and recently described taxa. This study presents an evaluation of routine and genome-based identification approaches applied to clinical Serratia isolates, integrating phenotypic assays, MALDI-TOF MS (Bruker Daltonics), 16S rRNA gene sequencing, and Whole-Genome Sequencing (WGS). A total of 103 isolates collected from a teaching hospital were analyzed. WGS was performed on a subset of isolates. Conventional biochemical methods classified all isolates as Serratia marcescens, whereas MALDI-TOF MS identified 60.1% as S. marcescens, 11.6% as S. ureilytica, and 28.1% just at the genus level. Peak analysis from MALDI-TOF MS revealed specific peaks associated with S. marcescens and S. ureilytica, but limited discriminatory power. WGS of six isolates initially identified as S. ureilytica by MALDI-TOF MS revealed reclassification as Serratia sarumanii (n = 5) and Serratia montpellierensis (n = 1), supported by Average Nucleotide Identity (ANI), Average Amino Acid Identity (AAI), and Digital DNA-DNA Hybridization (dDDH) thresholds. In contrast, 16S rRNA analysis showed limited species-level resolution. Phylogenomic and SNP-based analyses confirmed these classifications with strong support. Overall, this study underscores the critical role of high-resolution genomic approaches for precise species identification and highlights the need for continuous expansion and curation of MALDI-TOF MS reference databases to support reliable clinical diagnostics and epidemiological surveillance of emerging Serratia species.

Spectrometry, Mass, Matrix-Assisted Laser Desorpti↗

PubMed2026

Antiadalimumab Antibodies in Patients With Inflammatory Ocular Diseases: Incidence and Clinical Outcomes.

PURPOSE: To determine the incidence, effect on adalimumab drug levels, and clinical consequences of antiadalimumab antibody formation, and to assess potential risk factors. DESIGN: Retrospective clinical cohort study. PARTICIPANTS: One hundred twenty-eight patients treated with adalimumab who underwent antiadalimumab antibody monitoring. METHODS: Beginning October 2023, regularly scheduled antiadalimumab antibody and adalimumab level testing was begun. Using staggered entry analysis, anchored observation to treatment initiation, incidence was calculated. Time-updated models evaluated risk factors for antiadalimumab antibody formation. MAIN OUTCOME: Incidence of antiadalimumab antibodies. RESULTS: Antiadalimumab antibodies developed in 37 of 128 patients for a rate of 0.077 per person-year (PY) (95% confidence interval [CI] 0.055/PY, 0.104/PY). Median serum adalimumab concentrations were significantly lower in antiadalimumab antibody-positive blood samples (2.6 µg/mL; interquartile range 0.8, 7.0) than in antibody-negative samples (10.2 µg/mL; interquartile range 6.9, 15.1), P < .00001. In time-updated analyses, there was a suggestion that concomitant immunosuppression was associated with a reduced risk of antiadalimumab antibodies (odds ratio [OR] 0.64; 95% CI 0.37, 1.10; P = .10) and weekly adalimumab dosing was associated with a reduced risk (OR 0.62; 95% CI 0.42, 0.91; P = .01). Antiadalimumab antibodies were associated with active ocular inflammation (OR 3.68; 95% CI 1.99, 6.82; P < .00001). CONCLUSIONS: Antiadalimumab antibodies occur commonly among patients treated with long-term adalimumab, with a cumulative incidence of nearly 50% by 8 years of therapy. Antibody formation was associated with lower serum adalimumab levels and active ocular inflammation.

Humans↗

PubMed2026

PaNDA: Efficient Optimization of Phylogenetic Diversity in Networks.

Phylogenetic diversity (PD) plays an important role in biodiversity, conservation, and evolutionary studies by measuring the diversity of a set of taxa based on their phylogenetic relationships. In phylogenetic trees, a subset of k taxa with maximum PD can be found by a simple and efficient greedy algorithm. However, this algorithmic tractability is lost when considering phylogenetic networks, which incorporate reticulate evolutionary events such as hybridization and horizontal gene transfer. To address this challenge, we introduce PaNDA (Phylogenetic Network Diversity Algorithms), the first software package and interactive graphical user-interface for exploring, visualizing, and maximizing diversity in phylogenetic networks. PaNDA includes a novel algorithm to find a subset of k taxa with maximum diversity, running in polynomial time for networks of bounded scanwidth, a measure of tree-likeness of a network that grows slower than the well-known level measure. This algorithm considers the variant of PD on networks in which the branch lengths of all paths from the root to the selected taxa contribute towards their diversity. We demonstrate the scalability of this algorithm on simulated networks, successfully analyzing level-15 networks with up to 200 taxa in seconds. We also provide a proof-of-concept analysis using a phylogenetic network on Xiphophorus species, illustrating how the tool can support diversity studies based on real genomic data. The software is easily installable and freely available at https://github.com/nholtgrefe/panda. Additionally, we extend the definition of PD to semi-directed phylogenetic networks, which are mixed graphs increasingly used in phylogenetic analysis to model uncertainty of the root location. We prove that finding a subset of k taxa with maximum diversity remains NP-hard on semi-directed networks, but do present a polynomial-time algorithm for networks with bounded level.

network↗