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PubMed2026

Single-cell transcriptomics reveals heterogeneous stress responses and Mg2+-mediated survival mechanisms in Lactobacillus delbrueckii subsp. bulgaricus during freeze-drying and storage.

Maintaining the viability of lactic acid bacteria during dehydration and subsequent storage remains a significant challenge. Here, we employed single-cell RNA sequencing to reveal the heterogeneous stress responses of Lactobacillus delbrueckii subsp. bulgaricus, identifying seven distinct transcriptional clusters across the liquid culture, freeze-drying, and storage phases. The dominant clusters in the freeze-drying and storage were not completely consistent, showing significant functional differentiation. Genomic stability may be important for survival during freeze-drying and storage, while intracellular energy homeostasis appears important for viability during storage. The magnesium transporter mgtB was highly expressed in clusters tolerant to freeze-drying and storage, suggesting a critical role for Mg2+ homeostasis. Further experimental validation confirmed that Mg2+ treatment significantly bolstered stress resistance, increasing immediate post-freeze-drying survival by over 2-fold (up to 92.90%) and post-storage survival by over 5-fold (up to 5.98%). Proteomic data indicated that Mg2+ supplementation correlated with the maintenance of several biological functions potentially relevant to bacterial survival during freeze-drying and storage, including DNA repair, translation, and central carbon metabolism. These findings provide a map of microbial stress resistance through population heterogeneity and offer a potential strategy that may be adapted for enhancing the stability of other industrial lactic acid bacteria products.

Freeze Drying↗

PubMed2026

Comparative analyses of olfactory receptor repertoires in Schizothorax fish based on the chromosome-level genomes: Implications for regulatory roles of dietary differentiation and ploidy variation.

The olfactory receptor (OR) genes constitute the molecular basis of fish olfaction, mediating survival behaviors and environmental adaptation while coevolving with habitat-driven evolution. Schizothorax, a cyprinid genus endemic to the Qinghai-Tibetan Plateau, exhibits remarkable dietary divergence and ploidy variation in response to plateau environmental changes, which presumably facilitates the adaptive evolution of OR genes. However, the evolutionary patterns of OR genes associated with trophic divergence and ploidy variation in this genus remain unclear. In this study, three species were selected: the herbivorous diploid S. macropogon, the carnivorous diploid S. lantsangensis, and the herbivorous tetraploid S. curvilabiatus. S. macropogon possessed 142 OR genes (92.25% functional), primarily located on chromosomes 14 and 24, with the fewest sequence clusters. Such compact gene repertoire and highly overlapping chromosomal clusters indicated specialization for a herbivorous olfactory niche. S. lantsangensis contained 127 OR genes (93.70% functional), concentrated on chromosomes 4 and 5, with fewer sequence clusters and a scattered distribution, reflecting evolution of OR genes under carnivorous feeding habits. The herbivorous tetraploid S. curvilabiatus exhibited striking features: 316 OR genes (94.30% functional), the most subfamilies, unique ε and κ OR subfamilies, and species-specific motifs. These characteristics revealed that ploidy, rather than herbivory, dominated OR gene evolution. In conclusion, dietary differentiation and ploidy variation together drove olfactory adaptive evolution in Schizothorax, providing new insights into vertebrate OR gene ecological adaptation.

Animals↗

PubMed2026

RPLP0 drives diffuse large B-cell lymphoma cell proliferation through reactive oxygen species-dependent AKT/mTOR activation and inhibition of stress-induced autophagy.

Diffuse large B-cell lymphoma (DLBCL) is a common, aggressive subtype of non-Hodgkin lymphoma with poor outcomes. Identifying the primary molecular causes of DLBCL remains key. The present study examined the function of ribosomal protein lateral stalk subunit P0 (RPLP0) in DLBCL pathogenesis. The Cancer Genome Atlas-DLBCL and GSE12453 datasets overlapping differentially expressed genes were identified. Hub genes were identified via protein-protein interaction network analysis. DLBCL cells were subjected to functional tests following RPLP0 overexpression or knockdown. Reverse transcription-quantitative PCR, western blotting, flow cytometry, transmission electron microscopy, colony formation assay and biochemical analysis were among the tests performed. N-acetylcysteine (NAC), rapamycin (RAPA) and 3-MA were among the medication therapies. In the DLBCL datasets, six ribosome-associated genes were differentially expressed. RPLP0 knockdown inhibited the proliferation of DLBCL cells and caused G2-phase arrest, without impacting apoptosis. Thioredoxin, heat shock protein family A member 1A and heat shock protein family B member 1 expression was downregulated by RPLP0 knockdown, which also increased the NAD+/NADH ratio, promoted reactive oxygen species (ROS) accumulation and caused mitochondrial membrane potential depolarization. Meanwhile, 3-MA reversed the effects of RPLP0 knockdown, which encouraged LC3-II accumulation, autophagy-related gene 5 (ATG5) overexpression and an increase in autophagic vesicles. Autophagy-related indicators were decreased, and AKT/mTOR phosphorylation was increased by RPLP0 overexpression, which RAPA inhibited. NAC therapy preserved the viability of RPLP0-silenced cells, restored p-AKT/p-mTOR levels and restored normal LC3 and ATG5 expression. These findings suggest that RPLP0 regulates stress-induced autophagy through ROS-dependent AKT/mTOR signaling and may represent a potential therapeutic target for DLBCL.

AKT/mTOR signaling pathway↗

PubMed2026

Quality assessment, prognostic factors, and biomarkers for brain tumor analysis: a comprehensive systematic review.

The brain tumors possess different causative factors and properties, making their diagnosis and treatment difficult. Growth of these cancers usually leads to compression of the adjacent nerves and obstruction of the flow of cerebrospinal fluid, thus leading to increase in intracranial pressure. This affects the working of brain in many ways; thus, the difficulty involved in its treatment. With the improvements in technology in neuroimaging, including Diffusion Tensor Imaging (DTI), Positron Emission Tomography (PET), and multiparametric Magnetic Resonance Imaging (mpMRI), the diagnosis process has become easy. The effectiveness of any form of therapy in such patients depends primarily on their prognosis. While it is a common practice that physicians determine the prognosis of the disease by considering the age of the patient, histological grade of the tumor, and resection status, now this method has become more comprehensive by adding molecular signature and genetic analyses to the list of criteria. Next-generation sequencing (NGS) allows a reliable molecular classification. It increases the level of risk stratification, facilitating the application of therapies tailored to individual patients. Thus, molecular oncology has greatly changed our views on brain tumors' pathology and prognosis while neoadjuvant treatments aim at increasing the survival rate. On the other hand, radiogenomics is a field of study that combines non-invasive imaging phenotypes and genomic information in order to find unique molecular signatures of tumors without collecting samples from tumors. Molecular biomarkers are absolutely essential in the diagnosis of cancer, treatment monitoring, and recurrence of cancer. Advances in liquid biopsy technology, particularly the methods for circulating tumor DNA (ctDNA) and Extracellular Vesicle (EV) based analysis, have enabled the possibility of non-invasive monitoring of the progression of the tumors over time. This review highlights key studies and important scientific works about imaging technologies, biomarkers, and prognostic factors of malignant brain tumors.

Humans↗

PubMed2025

Systematic Review of Symptoms of Catatonia in Autism Spectrum Disorder.

Catatonia is a complex neuropsychiatric syndrome characterized by disturbances in mood, motor function, behavior and speech. It is increasingly recognized in individuals with autism spectrum disorder (ASD), although its identification remains challenging due to the overlapping clinical features of the two conditions. Shared characteristics, such as echophenomena, mannerisms, social indifference and repetitive behaviors can obscure accurate diagnosis. Although reports suggest a significant prevalence of catatonia among individuals with ASD, the condition remains poorly understood and frequently under recognized, leading to substantial diagnostic and treatment challenges. A systematic review was conducted to characterize the symptoms of catatonia in individuals with ASD. The literature search included peer-reviewed journal articles published in English from 1980 onward, focusing on studies examining co-occurring catatonia and ASD. A qualitative framework analysis was implemented to evaluate 45 peer-reviewed studies, with findings interpreted in relation to, and extending beyond, the diagnostic criteria for catatonia outlined in the International Classification of Diseases, 11th revision (ICD-11). The objective was to identify symptom patterns extending beyond current diagnostic frameworks and to support improved clinical recognition and diagnostic precision in ASD populations. The review identified six primary symptom clusters associated with catatonia in individuals with ASD: (1) psychomotor activity, (2) speech disturbances, (3) changes in behavior/skills/functions, (4) mental health symptoms, (5) physiological symptoms, and (6) symptoms related to arousal and awareness. Notably, several symptoms observed within these clusters are not currently included in the ICD-11 diagnostic criteria for catatonia. These additional symptoms include tics, motor compliance, incoherent speech, self-injury, impaired cognition, and appetite changes, suggesting a broader clinical presentation of catatonia in ASD populations than is presently captured in existing diagnostic frameworks. The findings of this review highlight the significance of enhancing clinicians' awareness and understanding of how catatonia manifests in individuals with ASD. Most notably, six symptom clusters, psychomotor changes, speech disturbances, behavioral and functional regression, affective and psychiatric symptoms, physiological symptoms, and arousal/awareness disturbances, were observed. Several symptoms identified in this review are not included in the current diagnostic criteria, and their recognition may facilitate in earlier identification and timely intervention, potentially preventing the severe consequences of untreated catatonia in this population.

Humans↗

PubMed2026

Analysis of end-stage renal disease mediated by cuproptosis-related genes.

OBJECTIVE: The complex pathophysiological mechanism of end-stage renal disease (ESRD) has not been fully understood. Cuproptosis is a newly discovered type of programmed cell death. Therefore, this study attempts to clarify the relationship between cuproptosis-related genes (CRGs) and the phenotype of ESRD. MATERIALS AND METHODS: The National Center for Biological Information Gene Expression Omnibus database was applied to obtain the GSE37171 dataset comprising whole-genome microarray analysis of peripheral blood samples. A 3 : 1 case-control design was employed with 75 ESRD patients and 20 healthy controls who were frequency-matched for age, sex, and ethnicity. Based on differentially expressed genes (DEGs) and genes related to cuproptosis, CRGs were identified. Thereafter, we explored two different subpopulations based on the cuproptosis gene and analyzed their expression and immune infiltration. Genes specific to the CRG cluster were identified through the weighted gene co-expression network analysis algorithm, and the best prediction model was determined and verified by four machine learning methods. RESULTS: The study identified 14 differentially expressed CRGs, among which ATP7B, SLC31A1, LIAS, LIPT1, DLD, MTF1, CDKN2A, DBT, and DLST had relatively high expression levels in the ESRD samples. Compared with the control group, expression levels of FDX1, DLAT, PDHA1, PDHB, and GLS were significantly lower in the ESRD group, and CRGs played a key role in the regulation of immune infiltration in ESRD. Two cuproptosis-related molecular clusters were identified in the ESRD samples. Cluster2 was more correlated with the immune infiltration of ESRD. By analyzing the intersection points between CRG cluster and key genes of ESRD, a total of 888 specific DEGs were identified. Functional differences related to specific DEGs were further explored using gene set variation analysis. Five significant genes (SMC5, USP47, USP53, AGA, and DMXL1) were identified by the support vector machine model as key predictors for ESRD disease risk, achieving an area under the curve (AUC) of 1.00 in internal validation. However, external validation in independent cohorts is required prior to clinical application. Individual gene analysis showed an AUC > 0.81 in discriminating ESRD patients from healthy controls, and the expression of all 5 genes in ESRD patients was significantly lower than in the control group. CONCLUSION: This study clarified the relationship between CRGs and the phenotype of ESRD, analyzed their specific roles in the immune microenvironment, and obtained a predictive model, providing new insights for the study of its potential therapeutic targets.

Humans↗

PubMed2026

Functional neuroimaging subtypes of obsessive-compulsive disorder: A systematic review and meta-analysis.

Obsessive-compulsive disorder (OCD) exhibits substantial clinical heterogeneity that may reflect underlying neurobiological diversity. Neuroimaging-based subtyping may advance precision psychiatry by identifying biologically distinct subgroups with differential treatment responses. This study systematically synthesized evidence from functional neuroimaging subtyping studies in OCD to identify reproducible neurobiological subtypes, characterize their clinical profiles, and establish a consensus-based classification framework. We reviewed 40 original studies employing machine learning, clustering, normative modeling, or classification approaches, encompassing approximately 8,150 patients. Consensus clustering identified three reproducible neurobiological subtypes. The Limbic-Hyperactive subtype, comprising approximately 40% of patients, exhibited amygdala and insula hyperconnectivity, elevated anxiety levels, predominant contamination and washing symptoms, and favorable response to cognitive-behavioral therapy. The Fronto-Striatal-Hypoconnected subtype, comprising approximately 35% of patients, demonstrated reduced orbitofrontal-striatal connectivity, cognitive inflexibility, predominant checking and ordering symptoms, and a favorable response to selective serotonin reuptake inhibitors. The Global-Disrupted subtype, comprising approximately 25% of patients, exhibited widespread connectivity disruption, greater symptom severity, and poor treatment response. Support vector machine classification achieved 81.5% accuracy for subtype assignment, though classification of OCD versus healthy controls showed limited generalizability in multisite settings (AUC 0.567-0.673). These findings support a neuroimaging-based framework for personalized treatment selection but require prospective validation.

Humans↗

PubMed2026

From prediction to mechanism: Explainable AI uncovers plasma and CSF proteomic signatures of Alzheimer's disease.

Alzheimer's disease (AD) plasma and cerebrospinal fluid (CSF) proteomics can distinguish AD from cognitively normal controls, but the generalizability of machine learning performance and the recurrence of biological signals across datasets require cautious interpretation. We developed an explainable artificial intelligence framework spanning two fluids and four ADNI proteomic datasets, covering 2082 modality specific samples, all analysed internally within ADNI. Phase 1 analysed plasma using a 119 analyte NULISA and targeted UPENN panel (n = 727; 216 CE, 511 controls). Phase 2 extended the analysis to CSF using SOMAscan7k, TMT-MS and targeted SET2, with Elecsys Aβ42, Aβ40, total tau and p-tau181 as anchor biomarkers. Only SOMAscan was subject-independent relative to Phase 1 plasma; TMT-MS and SET2 overlapped with Phase 1 for 96.0% and 97.7% of subjects and therefore are not independent replication cohorts. Under subject-level splits with fold internal preprocessing, we compared Elastic Net, Explainable Boosting Machines and gradient boosted trees with SHAP-based explanations. Among the candidate pipelines, we selected the pipeline with the highest held-out test ROC AUC for each platform; the selected values were 0.927 in plasma and 0.954-0.973 across the three CSF datasets. Because the same held out test performance was used for pipeline selection and headline reporting, these are optimistically selected single-holdout estimates, not unbiased estimates of generalizable or clinical performance. Explanations identified five recurring biological axes within ADNI: cholinergic (ACHE), tau/14-3-3 (YWHAG, YWHAZ, YWHAB, YWHAE), neuro-axonal (NEFL, NEFH), microglial/complement (CHIT1, SMOC1, CHI3L1, C7, CFH) and synaptic (NPTXR, NPTX2, DLG4, SYT5, VSNL1, ELAVL2). CSF analyses showed synaptic vesicle-cycle enrichment (q = 2 × 10-6), and CSF YWHAG correlated strongly with total tau (ρ = 0.87). Cross-fluid directional concordance was modest overall (54-57%) but increased to 73-80% among mapped analyte/protein rows reaching q < 0.05 in CSF. These findings provide hypothesis-generating, internally supported evidence within ADNI. Independent external cohorts with locked pipelines are required to evaluate generalizable performance and biological reproducibility; the overlapping TMT-MS and SET2 analyses should not be interpreted as independent replication.

Alzheimer Disease↗

PubMed2026

Genome-wide identification and expression profiling of CSP and OBP genes in Stictocephala bisonia reveals candidate genes potentially associated with insecticide response.

Stictocephala bisonia is an important invasive agricultural pest. Due to the frequent application of insecticides in its habitat, this species is under intense selection pressure. Chemosensory proteins (CSPs) and odorant-binding proteins (OBPs) are known to play key roles in insecticide resistance, but their specific functions in S. bisonia remain unclear. In this study, we identified a total of 22 SbisCSPs and 16 SbisOBPs based on the S. bisonia genome. To screen for candidate genes potentially linked to insecticide resistance, we adopted a multi-criteria screening strategy that integrated phylogenetic analysis, molecular docking with three insecticides, and tissue-specific expression profiling. Phylogenetic analysis identified several SbisCSPs and SbisOBPs clustering with genes known to be involved in insecticide resistance, serving as an initial evolutionary filter. Molecular docking results indicated that λ-Cyhalothrin exhibited the strong predicted binding affinity with most of SbisCSPs and SbisOBPs. Subsequent qPCR validation of seven prioritized candidates revealed distinct expression patterns: SbisCSP22 was highly expressed in adults and demonstrated strong binding affinity to all three insecticides tested, suggesting a potential role in mediating multi-insecticide response. Conversely, SbisCSP17 was significantly upregulated in larvae, clustered with genes known to mediate imidacloprid resistance, and exhibited strong binding affinity to imidacloprid. Given its larval-specific expression and the soil-dwelling behavior of larvae, we hypothesize that SbisCSP17 is a key candidate gene for larvae coping with soil-treated insecticides.

Animals↗

PubMed2026

Depression and amyloid-β across CSF, PET, and plasma biomarkers: a systematic review and meta-analysis.

Alzheimer's disease is increasingly defined by biomarker evidence of amyloid-β and tau pathology, sharpening questions about whether late-life depression contributes to, or instead reflects, this pathology. We conducted a systematic review and meta-analysis of studies published between 2000 and 2025 that compared amyloid-β biomarkers in adults with and without depression, with depression defined by validated clinical diagnoses or symptom rating scales. Twenty-four studies were included, spanning three biomarker sources: cerebrospinal fluid, positron emission tomography imaging, and plasma. Across all sources, the pooled difference in amyloid-β burden between depressed and non-depressed individuals was small and clustered near zero, indicating only a weak, statistically non-significant tendency toward higher amyloid in depression. When the three sources were examined separately, each yielded a similar near-null result, although between-study heterogeneity was considerable for cerebrospinal fluid and plasma and moderate for imaging. Importantly, a prespecified subgroup analysis showed that imaging results diverged by quantification method: studies using the simpler standardized uptake value ratio clustered around zero, whereas the smaller group of studies using kinetic distribution volume ratio modelling showed a significant positive association, suggesting that methodological choices critically influence the observed relationship. Taken together, these findings indicate that depression is not consistently accompanied by greater amyloid-β burden across widely used biomarker platforms. The distribution volume ratio signal nonetheless raises the possibility of subtle associations that cruder methods may obscure, and suggests that depression may shape Alzheimer's disease trajectories more by modifying the clinical impact of amyloid than by altering its amount.

Humans↗

PubMed2026

Comparative safety and operative efficiency of surgical approaches for open reduction and internal fixation of mandibular condylar fractures: a systematic review and network meta-analysis.

BACKGROUND: The optimal surgical approach for mandibular condyle fractures remains controversial, particularly regarding the trade-off between facial nerve safety and surgical efficiency. METHODS: Our systematic review and frequentist NMA analyzed studies evaluating open reduction and internal fixation (ORIF) for mandibular condyle fractures. The primary safety outcome was transient or persistent (≥6 months) facial nerve weakness. The efficiency outcome was operative exposure time. Surgical approaches were categorized, and random-effects NMAs estimated odds ratios (ORs) and mean differences (MDs). Treatments were ranked using P-scores, and clustered rankings explored safety-efficiency relationships. RESULTS: Overall, 121 studies (n = 6659 patients) were included. For facial nerve safety, endoscope-assisted (EA), preauricular transmasseteric anteroparotid (PATMA), and high submandibular (HSMA) approaches ranked highest, while the retromandibular transparotid (RMTA) approach carried a higher risk. Analyses restricted to persistent weakness yielded consistent results. For exposure time, submandibular (SM), HSMA, and retromandibular transmasseteric anteroparotid (RMTMA) approaches were most efficient. Clustered ranking analysis identified HSMA and RMTMA as achieving the best overall balance between safety and efficiency. Subgroup analyses confirmed the overall hierarchy, though evidence for high-level and intracapsular fractures remains limited. CONCLUSIONS: HSMA and RMTMA offer an optimal compromise between safety and efficiency for extracapsular condylar fractures, while EA may minimize nerve injury risk where technical expertise allows. High-quality comparative trials - particularly for intracapsular fractures - are warranted.

Humans↗

PubMed2026

Integrated assessment of biocontrol potential and genome analysis of endophytic Bacillus velezensis MGL-B1 against mango stem-end rot.

Mango stem-end rot is a globally significant postharvest disease that severely threatens the mango industry, primarily caused by Botryosphaeria dothidea. However, information on biocontrol agents targeting this pathogen in mango remains limited. In this study, we isolated and identified a strain of Bacillus velezensis MGL-B1 from mango leaf tissues for the first time, which exhibited broad-spectrum antifungal activity. Both in vitro and in vivo assays demonstrated that MGL-B1 effectively inhibited the growth of B. dothidea, with an in vivo biocontrol efficacy reaching 83.72 ± 5.10%, comparable to that of the commonly used chemical fungicide thiabendazole. Further mechanistic analysis revealed that MGL-B1 acts by directly disrupting the integrity of the pathogen's mycelial cell membrane. In addition, its released volatile organic compounds (VOCs) also displayed significant antifungal activity, with components such as 2-nonanone, 2-nonanol, and phenylethyl alcohol being confirmed to exert antifungal effects in in vitro fumigation assays. qPCR analysis showed that MGL-B1 treatment significantly upregulated the transcriptional levels of genes involved in plant-pathogen interaction, phenylpropanoid biosynthesis, and antioxidant defense pathways in mango fruits, with upregulation folds of 16.32, 37.19, and 75.93, respectively; meanwhile, the expression of browning-related genes such as polyphenol oxidase (PPO) was markedly suppressed. Whole-genome sequencing further revealed 14 biosynthetic gene clusters for antimicrobial compounds, including five unknown gene clusters. Collectively, B. velezensis MGL-B1 represents a promising biocandidate strain with multiple antifungal mechanisms and excellent control efficacy, providing a valuable resource for green and sustainable management of mango diseases.

Mangifera↗

PubMed2026

Integration of single-cell transcriptomics and genomic mutation analysis identifies an immunotherapy-resistant tumor subcluster and validates ARNTL2 as a malignant driver in lung adenocarcinoma.

BACKGROUND: Immunotherapy resistance in lung adenocarcinoma (LUAD) remains a critical clinical challenge, and the mechanisms underlying resistance-associated intratumoral heterogeneity are poorly characterized. METHODS: We performed single-cell RNA sequencing of LUAD patients receiving neoadjuvant immunotherapy (responders vs. non-responders), integrating inferCNV, GSVA, and differential expression analyses. Cluster-specific genes were validated across seven independent cohorts (TCGA-LUAD, GSE13213, GSE26939, GSE29016, GSE30219, GSE31210, GSE42127). A multi-algorithm machine learning framework was used to construct a prognostic model, and the immune microenvironment was characterized using TCIA scoring, seven infiltration algorithms, and ESTIMATE. ARNTL2 function was assessed by CCK-8 and Transwell assays in A549 and H1299 cells. RESULTS: Non-responders showed significant enrichment of epithelial cells, depletion of cytotoxic T/NK cells, and elevated copy number variation burden versus responders (p < 0.0001). A resistance-enriched malignant subcluster (Cluster 2) exhibited hyperproliferative and metabolic reprogramming signatures with upregulated KRT17, S100A2, and CST6, which showed tumor-specific overexpression, adverse prognostic value, and genomic amplification across cohorts. CoxBoost combined with survivalSVM achieved optimal predictive performance (C-index = 0.686), yielding robust risk stratification (HR: 2.54-10.51, all p < 0.05). Low-risk patients showed greater immune infiltration and higher TCIA immunophenoscores. ARNTL2 was an independent prognostic factor (HR: 2.07-4.64) strongly correlated with risk score (r = 0.69), and its knockdown suppressed proliferation and invasion in both LUAD cell lines (all p < 0.05). CONCLUSION: This study identifies a resistance-associated malignant subcluster in LUAD, constructs a validated CoxBoost + survivalSVM prognostic model with robust immune stratification, and establishes ARNTL2 as a core oncogenic driver and therapeutic target.

ARNTL2↗

PubMed2026

Comparative phylogenomics and transcriptional regulatory networks of AQPs, HSPs, and LEA proteins in salt-stressed Portulaca oleracea.

Soil salinization severely threatens global food security, necessitating systematic investigations of halophytes like Portulaca oleracea to decode the molecular mechanisms of environmental resilience. Utilizing an integrated framework of deep learning-based genome annotation (58,817 predicted genes; 96.5% BUSCO completeness), multi-tissue RNA-Seq, phylogenomics, and gene regulatory network (GRN) inference, the synergistic orchestration of 78 aquaporins (AQPs), 525 heat shock proteins (HSPs), and 119 late embryogenesis abundant (LEA) proteins was elucidated. The active transcriptome, encompassing 39,065 expressed loci, revealed a systemic growth-defense trade-off. Tissues displayed distinct adaptive mechanisms: leaves modulated intracellular water balance via specialized AQPs, whereas adult roots maintained proteostasis through robust HSP20/HSP70 induction. Phylogenomic clustering across 154 species demonstrated that salinity tolerance constitutes an evolutionary mosaic, identifying 81 halophyte-exclusive orthogroups and 1129 species-specific clusters. Comparative topology across six independent GRNs (4.2M-5.3 M edges) unmasked a highly modular transcriptional reprogramming strategy governed by a core apparatus of 22 stress-exclusive regulators, with functional enrichment heavily prioritizing protein dimerization and chromatin remodeling. Theoretically, the distinct convergence of Trihelix transcription factors with guard cell differentiation pathways offers a candidate transcriptomic framework to explain the plant's characteristic C4-CAM photosynthetic plasticity under severe osmotic pressure. Practically, these evolutionary blueprints and specific master switches transcend single-gene transgenic limitations. Utilizing these root-sustained and stress-inducible targets under localized promoters provides a naturally optimized, network-level precision engineering roadmap to transfer robust, compartmentalized halotolerance to sensitive glycophytic crops.

Gene Regulatory Networks↗

PubMed2026

Acceptability of alcohol-based hand rub during neonatal care in rural Ugandan households: a qualitative study nested within the BabyGel trial.

BACKGROUND: Poor access to water, sanitation and hygiene exacerbates the spread of infections among newborns. The BabyGel cluster randomised trial assessed the effectiveness of a community-level alcohol-based hand rub with a training component in reducing infection or death rates among newborns in Uganda. OBJECTIVE: Nested in the BabyGel trial, this study investigated the acceptability of the BabyGel intervention among mothers and household members in Eastern Uganda, using the Theoretical Framework of Acceptability. METHODS: In 2022, we conducted individual semistructured interviews with mothers, and group interviews with mothers and other household members, all recruited from intervention-arm clusters. Thematic analysis combined inductive and deductive coding, structured by the framework's seven constructs: affective attitude, burden, ethicality, intervention coherence, opportunity costs, perceived effectiveness and self-efficacy. RESULTS: Twenty mothers and 14 household members participated in 10 individual and 10 small group interviews. Participants found the intervention generally acceptable, appreciating its convenience and perceived protection against infection. Many described hand hygiene changes that persisted beyond the intervention period. However, concerns related to its harmful effects, spiritual beliefs and social tensions with visitors occasionally influenced its use. CONCLUSION: Alcohol-based hand rub combined with a training component was generally well accepted, driven by perceived health and practical benefits, although concerns related to safety, belief systems and social dynamics remained. Because data collection coincided with the COVID-19 pandemic, a period of heightened hygiene awareness, the acceptability observed could differ in nonpandemic periods. Culturally adapted education, community engagement and reinforcement of correct use may enhance acceptability and sustainability in similar settings.

Humans↗

PubMed2026

Dissociable neural mechanisms of cognitive enhancement through transcranial stimulation and behavioral training.

BACKGROUND: Transcranial direct current stimulation (tDCS) and adaptive working memory (WM) training are promising cognitive enhancement approaches; however, their neural mechanisms and potential synergies remain poorly understood. OBJECTIVE: We directly compared how tDCS and WM training modulate neural oscillations during WM performance and examined whether combining both interventions produces additive effects. METHODS: We randomized 112 healthy adults into four groups: control (sham tDCS + non-adaptive 1-back), tDCS-only (active tDCS + non-adaptive 1-back), training-only (sham tDCS + adaptive n-back training), or combined (active tDCS + adaptive training). Participants underwent five daily intervention sessions. We recorded high-density EEG during transfer n-back tasks at baseline, post-intervention, and one-week follow-up. RESULTS: All active interventions improved WM performance relative to the control group, with the combined group showing the largest gains (n-back accuracy: +15.6% vs. + 10.1% tDCS-only, +9.7% training-only, +0.7% control; all p < 0.001). Critically, tDCS selectively increased gamma-band (30-50 Hz) power in the frontal and parietal regions (cluster p = 0.018, d > 1.0), whereas WM training enhanced frontal theta-band (4-8 Hz) power and theta-gamma phase-amplitude coupling (both cluster p < 0.012, d > 0.85). The combined group exhibited both neural signatures. Brain-behavior correlations revealed dissociable relationships: gamma increases predicted n-back accuracy improvements (r = 0.61, p < 0.001), whereas theta enhancements correlated with operation span gains (r = 0.58, p = 0.002). CONCLUSIONS: tDCS and WM training enhance cognition through distinct yet complementary neural mechanisms: tDCS via gamma-mediated cortical excitability and WM training via theta-mediated cognitive control. These findings provide neurophysiological evidence for multimodal enhancement strategies that target parallel pathways within WM networks.

Humans↗

PubMed2026

Phenotypic and transcriptomic characterization of biallelic RNU2-2 developmental and epileptic encephalopathy.

OBJECTIVE: A significant proportion of individuals with suspected genetic developmental and epileptic encephalopathies (DEEs) remain unsolved following whole genome sequencing (WGS). Here we describe biallelic RNU2-2 variants causing a recently reported, severe, recessive DEE. METHODS: We screened individuals who have received WGS analyses at the Genomic Medicine Centre Karolinska for Rare Diseases for biallelic RNU2-2 variants. Deep phenotyping was performed through reviewing entire medical histories and phenotypic traits were transcribed to their corresponding Human Phenotype Ontology (HPO) term. HPO terms were used to generate pairwise phenotypic similarity scores and assess for significantly shared phenotype enrichment in the RNU2-2 sub-cohort. RNA sequencing analyses were performed in fibroblast and blood tissues to compare splicing events between RNU2-2 individuals and two independent control groups. RESULTS: We identified 14 individuals from nine families with 12 ultra-rare biallelic RNU2-2 variants clustering in the conserved 5' domains. Genotype data from 13 of 14 individuals has been reported previously as part of a larger cohort. All individuals presented with a highly concordant, severe DEE, characterized by severe to profound intellectual disability, inability to walk or communicate, hyperkinesia, and refractory seizures. Infantile spasms and tonic seizures were the predominant seizure types and a Lennox-Gastaut syndrome-like phenotype was common. These individuals had a significantly similar phenotypic signature when compared with 703 individuals with complex pediatric epilepsies (two-sided Monte Carlo permutation test, p = .005). RNA sequencing analyses showed aberrant splicing, with the most pronounced effects in fibroblast tissues in mutually exclusive exon and alternate 3' splice-site events, which were not detectable in blood. SIGNIFICANCE: We present deep phenotyping data and transcriptomic analyses that provide support for rare, 5' clustering biallelic RNU2-2 variants causing this novel, severe DEE. We propose an RNA sequencing methodology on fibroblast tissue for future validation of RNU2-2 variants.

autosomal recessive disease↗

PubMed2026

Precision targeting of teacher burnout using network-informed ecological momentary interventions.

Teacher well-being affects classroom functioning and workforce stability, yet generic digital programs rarely use person-specific affect dynamics to select support. This cluster-randomised trial evaluated whether micro-interventions selected from high expected influence (EI) nodes in teachers' contemporaneous affect networks produced larger changes in burnout-related EI and everyday happiness than content-matched random allocation. The objectives were to estimate allocation effects on changes in estimated network summaries and happiness, evaluate network change as a statistical mediator, examine personality moderation, and benchmark simpler allocation rules. A two-arm cluster randomised platform trial was conducted in 84 public schools across four urban districts in H Province. After a 14 day baseline of ecological momentary assessment (EMA), person specific partial correlation networks were estimated for happiness, exhaustion, detachment, efficacy and rumination. An optimisation engine prioritised three brief micro-intervention types per teacher according to baseline EI, while the active control received the same library without network information. EMA continued for 8 weeks; Bayesian multilevel models, permutation-based mediation, and benchmarking analyses were applied. EI-based targeting produced larger reductions in the composite EI-change index than active control (mean difference 0.11, 95% credible interval 0.08 to 0.14) and higher week 7 EMA happiness (4.4 points on a 0 to 100 scale, 95% credible interval 2.7 to 6.0), with a positive arm by week slope difference of 0.62 points per week (95% credible interval 0.39 to 0.85). Model-based mediation estimates were consistent with approximately one half of the happiness difference being statistically associated with change in the composite EI-change index (average conditional mediation estimate 3.5 points, 95% credible interval 2.0 to 5.2). Benchmarking showed smaller gains under severity, threshold, or group-level centrality rules. Effects were stronger among teachers higher in conscientiousness. The findings indicate that integrating EMA, network modelling, and EI-driven optimisation yields measurable gains beyond content-matched exposure, providing a proof of concept for district-scale precision mental health that requires prospective implementation testing. Replication in additional regions, expanded node sets, and longer follow up are warranted to assess durability and generalisability.

Female↗