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Single nucleus multiomics reveals an early inflammatory response to high-fat diet in mouse islets.

In periods of sustained hyper-nutrition, pancreatic β-cells undergo functional compensation through transcriptional upregulation of gene programs driving insulin secretion. This adaptation is essential for maintaining systemic glucose homeostasis and metabolic health. Using single nuclei multiomics, we have mapped the early transcriptional adaptive mechanisms in murine islets of Langerhans exposed to high-fat diet (HFD) for 1 and 3 wk. We show that β-cells exhibit the largest transcriptional response to HFD, characterized by early activation of pro-inflammatory eRegulons and down-regulation of β-cell identity genes, particularly in a distinct subset of β-cells. These observations extend to humans, where the prevalence of an β-cells with a high inflammatory signature is increased in diabetes. Collectively, these observations point to cellular crosstalk through pro-inflammatory signaling as a central and early driver of β-cell dysfunction that limits the compensatory capacity of β-cells, which is closely linked to the development of diabetes.

Animals

Pathogenic Variants in HEPACAM Alter Protein Localization and Interactome in Astrocytes of the Developing Mouse Cortex.

Megalencephalic leukoencephalopathy with subcortical cysts (MLC) is a rare leukodystrophy characterized by early-onset macrocephaly, white matter edema, seizures, and motor and cognitive decline. Approximately 25% of MLC patients carry HEPACAM pathogenic variants, many of which are dominant missense variants causing remitting MLC Type 2b. HEPACAM encodes hepatic and glial cell adhesion molecule (hepaCAM), also known as GlialCAM, an astrocyte-enriched transmembrane protein with important roles in astrocyte territory establishment, gap junction coupling, branching organization, synaptic function, and development of the gliovascular unit. The molecular mechanisms through which pathogenic variants in HEPACAM alter hepaCAM protein function in vivo and facilitate MLC pathogenesis during brain development remain largely unknown. Here, we used new viral tools and proximity-based proteomics to examine how three different dominant pathogenic variants alter hepaCAM subcellular localization and protein interactome in astrocytes of the developing mouse cortex. We found dramatic changes in hepaCAM distribution throughout the astrocyte, which were common to all mutants tested. We also observed significant changes in protein interactome between wild type and mutant hepaCAM, including decreased association with previously described hepaCAM-interacting proteins Connexin 43 and CLC-2. Moreover, we identified the epilepsy-associate potassium channel KCNQ2 as a novel hepaCAM interaction partner and found reduced association between KCNQ2 and pathogenic variants. Collectively, our data provide new insights into hepaCAM protein function in astrocytes during brain development, reveal altered protein dynamics of pathogenic variants, and provide a new resource to explore the molecular underpinnings of MLC pathogenesis.

Animals

Cannabis and cannabinoids for the treatment of mental and substance use disorders and symptoms: A systematic review and meta-analysis of experimental and observational studies.

BACKGROUND: Interest in cannabinoids for mental and substance use disorders is increasing. We examined experimental and observational evidence for treating these disorders and their symptoms. METHODS: Systematic review and meta-analysis (PROSPERO CRD42023467536). We searched CENTRAL, MEDLINE, Embase and PsycINFO to May 2025 for studies of cannabinoids in adults (≥18 years) with ADHD, anxiety, depression, PTSD, psychosis or Tourette syndrome, or alcohol, cannabis, opioid or tobacco use disorders. Two reviewers screened, extracted and assessed quality using a risk-of-bias tool and GRADE. RESULTS: We included 82 experimental and 118 observational studies. In RCTs, cannabinoids reduced anxiety symptoms (SMD=-0.40; 95% CI: -0.57, -0.23; I²=90%) and, in one small trial, PTSD symptoms (SMD=-2.60; 95% CI: -4.58, -0.62; n=20), with trivial-to-no effect on depression (SMD=-0.20; 95% CI: -0.43, 0.04; I²=91.6%), ADHD, psychosis and Tourette syndrome. Much anxiety and depression evidence came from symptoms measured as secondary outcomes in other primary conditions. Cannabinoids worsened cannabis use disorder severity in one RCT (SMD=2.35; 95% CI: 1.49, 3.21), with no effect on craving or withdrawal; evidence for alcohol, opioid and tobacco use disorders was very limited. Observational studies suggested improvements but had high risk of bias. The only significant safety finding was increased withdrawals due to adverse events with THC (OR=2.78; 95% CI: 1.66, 4.65). Certainty was predominantly very low. DISCUSSION: The evidence base shows very low certainty, high heterogeneity and methodological limitations, and is insufficient to support cannabinoids as first-line treatment. Signals for anxiety and PTSD are limited by indirectness and low certainty; no benefit was evident for depression; THC-related safety signals warrant careful consideration.

Humans

Effectiveness of different anaesthetic techniques, agents and adjunctive interventions in handling pain during dental treatment of MIH-affected teeth: a systematic review.

BACKGROUND: Molar incisor hypomineralisation (MIH) is frequently associated with hypersensitivity, dental anxiety and reduced efficacy of local anaesthesia, complicating pain control during dental treatment in children. AIM: To evaluate, based exclusively on randomised controlled trials (RCTs), the effectiveness of different local anaesthetic techniques, agents and adjunctive interventions in reducing pain during dental treatment of MIH-affected teeth in children. METHODS: A systematic review was conducted following PRISMA 2020 guidelines and registered in PROSPERO (CRD420251150485). MEDLINE, Cochrane Central, ScienceDirect, SCOPUS, EBSCO, and LILACS were searched up to September 2025. Eligible studies were RCTs involving children and adolescents (6 - 18 years-of-age) with MIH, assessing pain outcomes during dental procedures. Risk of bias was assessed using the Cochrane RoB 2 tool, and certainty of evidence was evaluated using the GRADE approach. RESULTS: Eight RCTs were included. Low-certainty evidence suggested that intraosseous anaesthesia and 4% articaine may reduce intra-operative pain compared with conventional techniques or 2% lidocaine. Adjunctive cryotherapy and pre-emptive ibuprofen showed potential benefits, but evidence was of very low certainty and limited to single trials. Findings for photobiomodulation were inconsistent across studies. Most trials were judged to be at high risk of bias, primarily due to lack of blinding and reliance on subjective pain outcomes. CONCLUSION: Current evidence supporting specific pain management strategies for MIH-affected teeth is limited and of low certainty. Whilst 4% articaine and intraosseous anaesthesia appear promising, well-designed, adequately powered RCTs with standardised pain outcomes are required to inform robust clinical recommendations.

Local anaesthesia

Meta-PseU: A meta-classifier for robust prediction of RNA pseudouridine modification sites from long sequences.

BACKGROUND AND OBJECTIVES: Pseudouridine (Ψ) represents one of the most abundant and conserved RNA modifications. Ψ provides an additional hydrogen-bond donor that enhances RNA structural stability and modulates translation. It participates in diverse biological processes, including RNA-protein interactions, splicing, translational control, and stress responses. Aberrant pseudouridylation is implicated in cancer, neurodegenerative disorders, and autoimmune diseases. Despite its biological importance, experimental identification of Ψ sites remains time-consuming and costly, limiting the feasibility of transcriptome-wide profiling. Computational approaches have therefore become essential complements to experimental techniques. However, state-of-the-art machine-learning and deep-learning predictors often suffer from limited generalizability due to small training datasets. To overcome these issues, we aim at constructing new long-sequence datasets and developing a novel Ψ site predictor. METHODS: New long-sequence datasets were constructed as benchmarks for RNA Ψ-site prediction. The Ψ modification sites in RMBase 3.0 were mapped to the reference genomes across three species of human, mouse, and yeast, and the RNA sequences with a length of 201 were generated by extending the upstream and downstream from the mapped, central sites. To eliminate sequence redundancy, the sequences were clustered using CD-HIT with a 70% sequence identity threshold. We developed Meta-PseU, a logistic regression-based meta-classifier that considered 118 machine learning and deep learning classifiers. The datasets and programs are freely accessible at https://github.com/kuratahiroyuki/MetaPseU. RESULTS: By optimizing model configuration, we proposed the Meta-PseU model stacking 32 machine learning and deep learning classifiers out of 118 classifiers. Meta-PseU substantially improved model generalizability, overcoming a key limitation of existing approaches. It greatly outperformed state-of-the-art predictors and achieved increasing accuracy with increasing sequence length. CONCLUSIONS: Long-sequence datasets were newly constructed as benchmarks for RNA Ψ-site prediction. Meta-PseU offers a new framework for robust Ψ-site identification by using long sequences.

Pseudouridine

Molecular adaptation of caspase genes to salinity stress in the tropical sea cucumber Stichopus monotuberculatus: A comparative analysis across echinoderms.

Apoptosis is an essential physiological process that plays a critical role in development and tissue homeostasis. Caspases, as central regulators of apoptosis, are crucial in controlling inflammation and cell death. In this study, we investigated the caspase gene family in Stichopus monotuberculatus to explore their potential roles in salinity stress adaptation. Five caspase genes were identified from the genome of S. monotuberculatus, including Smcaspase3, Smcaspase6, Smcaspase8a, Smcaspase8b, and Smcaspase8c. Phylogenetic analysis revealed that these Smcaspase genes clustered into distinct caspase subfamilies and showed high conservation with homologs from other echinoderms and representative vertebrates. Conserved motif and gene structure analyses showed relatively similar structural patterns within each clade, whereas divergence was observed among different subfamilies. Promoter analysis identified numerous cis-acting elements related to gene regulation, immune response, and growth and development. Expression profiling under salinity stress showed that Smcaspase8a was significantly upregulated, particularly under prolonged stress, whereas the other genes exhibited limited transcriptional responses. Our findings highlight caspase function in salinity stress and provide the foundation of molecular salinity adaptation mechanisms in S. monotuberculatus.

Animals

De-escalation of radiotherapy in HPV-negative non-nasopharyngeal head and neck squamous cell carcinoma: a systematic review.

BACKGROUND: Definitive and postoperative radiotherapy are central components of treatment for head and neck squamous cell carcinoma (HNSCC) but are associated with significant toxicities that can impair long-term function and quality of life. De-escalation strategies, aiming to reduce treatment-related morbidity while maintaining tumor control, have attracted increasing interest. However, most research has focused on HPV-positive oropharyngeal carcinoma. Systematic evidence for HPV-negative disease remains limited. METHODS: PubMed and EMBASE were searched for prospective studies investigating radio(chemo)therapy de-escalation in HPV-negative, HPV-unspecified, or mixed non-nasopharyngeal HNSCC populations. CLINICALTRIALS: gov was searched for ongoing prospective trials. Data extraction and verification were performed independently by three investigators. RESULTS: Screening of 3156 records identified 14 published prospective studies, 10 in the definitive and four in the postoperative setting. Strategies included reduction or omission of elective nodal volumes, dose reduction, and combined approaches. Additionally, 23 ongoing prospective trials were identified. Across studies, elective nodal failure rates were consistently low (0-4.6%), with most recurrences occurring within high-dose volumes rather than de-escalated elective regions. Randomized evidence for elective nodal dose reduction is mixed: two trials maintained regional control and reduced acute toxicity, whereas another was stopped for futility. CONCLUSION: Available evidence on de-escalation in HPV-negative HNSCC is limited, derived primarily from small, heterogeneous phase II studies with mixed HPV populations. Although data are promising in selected settings, notably for elective nodal control, the randomized evidence for elective nodal dose reduction is conflicting, and further adequately designed prospective randomized trials are required.

Humans

Changes in heroin-related ambulance attendances following the introduction of a medically supervised injecting room in Victoria, Australia.

BACKGROUND: Injecting drug use contributes significantly to morbidity, mortality and broader social harms globally. Supervised Injecting Facilities (SIFs) are harm reduction interventions that reduce overdose risk and facilitate access to health services for marginalised individuals. While international evidence supports the effectiveness of SIFs, Australian population-level surveillance data quantifying their impact on emergency medical service utilisation remain limited. METHODS: Using data from the National Ambulance Surveillance System, we conducted a retrospective, interrupted time series analysis of heroin-related ambulance attendances within the local catchment of the Medically Supervised Injecting Room (MSIR) between January 2015 and December 2023. Supplementary analysis included comparisons with central Melbourne suburbs and the broader state of Victoria. Key intervention timepoints, including the opening of the MSIR on 30 June 2018, expansion of its operating hours in July 2019, and the COVID-19 pandemic from April 2020 to October 2021, were examined to assess changes in heroin-related attendances over time. Segmented regression models were used to assess changes in heroin-related ambulance attendance trends over time. RESULTS: At the time the MSIR opened, the model-predicted heroin-related ambulance attendance rate within the MSIR catchment was 123 per 100,000 population per month, equivalent to approximately 48 heroin-related ambulance attendances per month. Prior to implementation, the attendance rate was increasing by an estimated 0.74 per 100,000 population per month. Following the opening of the MSIR, the previously increasing trajectory reversed, with ambulance attendance rates declining by approximately 2.3 per 100,000 population per month relative to the pre-intervention trend. By the end of the study period (December 2023), the predicted monthly heroin-related ambulance attendance rate had declined to 36 per 100,000 population (approximately 14 attendances per month), representing an overall reduction of 70.7% from the time of MSIR implementation. These reductions persisted throughout the COVID-19 lockdown period and were sustained after restrictions lifted. Supplementary analysis showed no comparable reductions in the central Melbourne region or the remainder of Victoria. CONCLUSIONS: The introduction of the MSIR in Richmond was associated with a sustained reduction in heroin-related ambulance attendances within its catchment area. These findings provide strong population-level evidence that SIFs reduce acute heroin-related harms requiring emergency ambulance response, reinforcing their role as an effective harm reduction strategy within the Australian context.

Humans

Selective monitoring of trace-level catechin and myricetin in herbal and aqueous matrices using magnetic MIP-DSPME: Optimization via design of experiments.

A novel dispersive solid-phase microextraction approach utilizing a magnetic molecularly imprinted polymer (MMIP) integrated with HPLC-UV detection was developed for the concurrent quantification of catechin and myricetin in herbal extracts and aqueous samples. The sorbent was engineered as a core-shell nanocomposite, consisting of a selective polymer layer deposited onto Fe3O4@SiO2-APTMS magnetic nanoparticles. Dual-template imprinting using catechin and myricetin generated complementary binding cavities within the polymer framework. Experimental variables influencing extraction were systematically screened and subsequently optimized. A Plackett-Burman design was first applied to identify the most influential factors, with pH and sorption time identified as the dominant variables. These parameters were subsequently fine-tuned using a central composite design, and the optimization process was completed in only 30 experimental runs. The sorption characteristics of the imprinted sorbent (MMIP) were compared with those of its non-imprinted counterpart (MNIP). The MMIP demonstrated markedly higher maximum binding capacities (Qmax), reaching 119.3 mg g-1 for myricetin and 112.1 mg g-1 for catechin, whereas the corresponding values for the MNIP were 32.55 and 32.08 mg g-1, respectively. Moreover, the affinity constants (KL = 0.760-0.950 L mg-1) were approximately 2.3-fold higher for the MMIP, confirming its stronger and more selective interactions with the target analytes. The selectivity coefficients for the targeted flavonoids relative to structurally related compounds, including ferulic acid, p-coumaric acid, melatonin, and curcumin, exceeded 3.5 for the MMIP, whereas the corresponding values for the MNIP were close to 1.1, demonstrating the high molecular recognition capability of the imprinted sorbent. Method validation demonstrated limits of detection (LODs) of 0.33-0.59 ng mL-1 and limits of quantification (LOQs) of 1.10-1.96 ng mL-1, and excellent linearity over the concentration range of 5.0-5500 ng mL-1 (R2 > 0.998). The method achieved recoveries of 93.96% to 105.69% with RSDs below 5.5%, while the preconcentration factors ranged from 209 to 229. Furthermore, the sorbent retained more than 95% of its extraction efficiency after four consecutive reuse cycles and more than 80% after six cycles, demonstrating excellent stability and reusability. The proposed method was successfully applied to the analysis of six medicinal plant extracts and water samples, showing negligible matrix interference and superior sensitivity, selectivity, and operational simplicity compared with conventional solid-phase extraction methods.

Flavonoids

Getting to the Core of the Matter-Assessing the Role of Replication in Metabarcoding-Based sedaDNA.

Replication is central to most experimental and sampling designs, increasing inferential power and capturing fine-scale data heterogeneity. However, its importance remains poorly evaluated in some ecological and evolutionary settings. This is the case of metabarcoding studies using DNA recovered from sedimentary archives, in which biological signals integrate ecological information through depositional and burial processes, yet are commonly inferred from a single sediment core per site. Here, we evaluated the effect of different types of replication using sedimentary DNA metabarcoding data from two genetic markers (mitochondrial COI and nuclear 18S) using a nested sampling design. The design included three intertidal sites, three spatially separated sediment cores per site (biological replicates), two sediment horizons per core, and eight PCR (technical) replicates per sediment sample. Variance partitioning showed that site identity and sediment age group together explained > 70% of the variation in beta diversity, indicating that among-site spatial and stratigraphic differences were the dominant drivers of community composition. PERMANOVA likewise identified non-significant effects of biological replication. Among PCR replicates from the same sediment sample, richness varied substantially, whereas Shannon diversity was more consistent. Despite this variability, differences in community composition among technical replicates remained smaller than those associated with biological replication or site identity, indicating a limited influence on broader ecological patterns. Community composition was highly similar among replicate cores within sites, consistent with stratigraphic coherence. These results indicate limited within-site heterogeneity and suggest that, under stratigraphically coherent conditions, increasing biological replication may provide little additional information, whereas enhancing technical replication and stratigraphic resolution can improve ecological inference from sedimentary DNA metabarcoding datasets.

DNA Barcoding, Taxonomic

CAR-T Cell Therapy: Manufacturing Platforms and Clinical Consequences.

Chimeric antigen receptor (CAR) T-cell therapy has transformed hematological cancer care, yet variability in efficacy, durability, and safety cannot be explained solely by antigen selection or patient factors. We propose that manufacturing platforms are active biological determinants of outcome. Viral vectors, used in all licensed products, provide stable genomic integration and durable expression but are limited by cost, cargo capacity, and centralized production. Nonviral strategies, including transposons, CRISPR knock-ins, and messenger RNA delivery, enable faster, less-expensive manufacturing with larger payloads, while introducing distinct safety and persistence profiles. This review presents a three-layer mechanistic framework that reframes manufacturing as biology: integration biology determines genomic risk and transgene stability; clonal fitness shapes persistence, dominance, and exhaustion; and epigenomic imprinting, influenced by gene transfer method, cytokines, and culture stress, preconfigures functional trajectories. Clinical observations link platform choice to immune recovery, where prolonged B-cell aplasia and delayed T-cell reconstitution contribute to infection-related nonrelapse mortality, and hematopoietic reserve at apheresis emerges as a practical predictor. Finally, manufacturing is positioned as the key to democratizing cell therapy. Decentralized, nonviral production aligned with regulatory standards may enable equitable access and transition CAR-T therapy from innovation to sustainable global care.

Humans

Deciphering CD8+ T cell exhaustion in human cancers through single-cell and spatial transcriptomics.

Exhausted CD8+ T cells (Tex) within the tumor microenvironment (TME) represents a critical barrier limiting anti-tumor immune responses. Tex cells are characterized by upregulated inhibitory immune checkpoint receptors, reduced cytotoxicity, and functional heterogeneity. Their genomic features and regulatory networks remain poorly defined, and only a minority of patients respond to immune checkpoint blockade (ICB) therapy. Single-cell RNA sequencing (scRNA-seq), through high-resolution transcriptomic profiling, has revealed diverse Tex subpopulations, identified subpopulation-specific marker genes and regulatory pathways. Spatial transcriptomics has further mapped the spatial distribution of Tex and their interaction networks with immune cells, tumor cells, and stromal cells, elucidating the impact of spatial heterogeneity on Tex functionality. Current studies indicate that the exhausted state of Tex is dynamic and modifiable, with functional differences among subpopulations closely associated with tumor progression and therapeutic response. However, the genomic characteristics, epigenetic regulation, and spatial interaction mechanisms of Tex require further exploration. This review summarizes recent advances in high-resolution omics technologies for precisely dissecting Tex heterogeneity, functional features, and interactions with other cells. It emphasizes the central value of optimizing Tex-targeted tumor immunotherapy strategies, providing theoretical foundations and directional guidance for developing more effective anti-tumor immunotherapies.

Humans

Comparative in silico analysis of Apis mellifera immune responses to Varroa destructor and Tropilaelaps mercedesae: Common and mite-specific molecular signatures.

Parasitic mites Varroa destructor and Tropilaelaps mercedesae represent major threats to global honey bee (Apis mellifera) health and productivity, yet comparative molecular insights into host responses remain limited. To address this, we systematically compiled published studies (2015-2025) reporting genes associated with honey bee interactions with V. destructor (11 studies, 87 genes), T. mercedesae (4 studies, 35 genes), and hygienic behavior (6 studies, 44 genes). Gene identifiers were harmonized to the Amel_HAv3.1 genome assembly, yielding three non-redundant sets: 64 Varroa-associated, 34 Tropilaelaps-associated, and 44 hygienic behavior-associated genes. Venn analysis identified 10 overlapping genes (including A0A088A8D5, A0A088ADL8, ABAE_APIME, Def1, Def2, Gapdh, HYTA_APIME, Imd, LOC726783, and Vg), suggesting conserved defense mechanisms, while 41 and 24 genes were uniquely associated with Varroa and Tropilaelaps, respectively. Enrichment analyses revealed Varroa-responsive genes were enriched in immune processes, chitin catabolism, and signaling pathways (Toll/Imd, MAPK, Wnt). Tropilaelaps-associated genes were enriched for antibacterial defense and stress response, with Toll/Imd signaling as the sole significantly enriched pathway. Overlapping genes reinforced core innate immunity activation. Protein-protein interaction network centrality analysis identified key hub genes: Def1, HYTA_APIME, ABAE_APIME, PPO, Imd, PGRP-LC, Vg for Varroa; and ACPH1_APIME, MRJP1, Vg, LOC726783 for Tropilaelaps. Results demonstrate that, despite differences in mite biology, honey bees show a conserved immune response against both parasites, centered on antibacterial defense, humoral immunity, and activation of the Toll/Imd pathway. Although limited by the in-silico nature and research asymmetries reflecting Tropilaelaps' emergence, this curated resource establishes a comprehensive framework for elucidating shared and distinct molecular defense mechanisms. Ultimately, this approach prioritizes diagnostic markers and candidate genes for functional validation and breeding strategies to enhance colony resilience against mite‑driven disease globally.

Animals

Clinical outcomes of Epstein-Barr virus infection/reactivation following CAR-T cell therapy: A systematic review.

BACKGROUND: Epstein-Barr virus (EBV) infection or reactivation is an emerging but underrecognized complication following chimeric antigen receptor T-cell (CAR-T) therapy and is likely associated with treatment-induced immune dysregulation. Data regarding its clinical impact remain limited. OBJECTIVE: To evaluate the reported occurrence, clinical manifestations, and outcomes of EBV infection or reactivation in adults undergoing CAR-T therapy. METHODS: A systematic review was conducted in accordance with the PRISMA 2020 guidelines. PubMed, Embase, and Cochrane CENTRAL were searched from inception to March 2025 for studies reporting EBV infection or reactivation after CAR-T therapy in adults. Due to limited and heterogeneous data, results were synthesized descriptively. RESULTS: Five studies comprising 80 patients were included (median age, 55 years; 52.6% male among patients with reported sex data [10/19]). Across the included studies, 11 EBV infection/reactivation events were identified among 80 described CAR-T recipients, representing 13.8% of the reported sample rather than a true incidence estimate. Among events with usable individualized timing data, the median interval from CAR-T infusion to EBV detection/reactivation was 9.8 months (approximate range, 1-44 months). Because EBV surveillance strategies and definitions were inconsistently reported across studies, this proportion should not be interpreted as a true incidence estimate. Four patients (36.4%) developed EBV-associated disease, including three cases of EBV-related lymphoproliferative disorder and one case of EBV-associated diffuse large B-cell lymphoma. Among seven patients with reported post-CAR-T treatment response, four achieved Complete Remission/ Continuous Complete Remission; treatment response should be interpreted separately from final survival status. Confirmed EBV-related mortality occurred in 2/11 patients with reported EBV infection/reactivation and in 2/4 patients with EBV-associated disease; all-cause mortality could not be reliably estimated because patient-level vital status could not be fully attributed to the EBV-reactivated subgroup. Reported toxicities predominantly consisted of low-grade cytokine-release syndrome; however, toxicity data were limited. CONCLUSION: Although infrequently reported, EBV infection or reactivation after CAR-T therapy may be associated with substantial morbidity and mortality among affected patients. However, the available evidence is limited by the small sample size, heterogeneous study designs, and inconsistent EBV surveillance practices.

Humans

Portable metagenomics for preventive surveillance and outbreak control in livestock and poultry: Pathogen detection, resistome profiling, and antimicrobial stewardship.

Conventional diagnostics for livestock and poultry outbreaks commonly rely on culture or targeted PCR panels, which may be too slow or too narrow to guide early control decisions. Portable metagenomics, particularly real-time nanopore sequencing, offers a route to broad pathogen detection, antimicrobial-resistance gene profiling, and outbreak investigation within an integrated workflow. This implementation-focused review evaluates how near-point-of-care metagenomics may support preventive veterinary medicine through earlier detection, surveillance, cohorting, biosecurity decisions, and antimicrobial stewardship. We synthesize sample-to-answer workflows for enteric and respiratory disease in food-producing animals, including sampling, nucleic-acid extraction, host depletion or target enrichment, library preparation, sequencing, bioinformatics, quality control, and interpretation. Applications in calf diarrhea, bovine respiratory disease, poultry outbreaks, mastitis, and resistome monitoring are considered alongside the central limitation that detection alone does not establish causation. Pathogen and resistance-gene signals must therefore be interpreted with clinical signs, lesions, epidemiology, controls, and confirmatory testing. We also propose a minimum reporting checklist, intended as a practical framework rather than a validated consensus standard. Portable metagenomics is not a replacement for conventional diagnostics, but appropriately validated workflows can reduce uncertainty during time-sensitive outbreaks and support more judicious antimicrobial use.

Animals

Messaging Strategies for Tobacco Prevention and Cessation Among People with Depression: A Scoping Review.

INTRODUCTION: Depression is strongly associated with higher tobacco use and lower quit rate; few communication campaigns have been designed with these mental health factors in mind. This scoping review compiles existing research on tobacco prevention and cessation messaging involving people with depression to identify gaps and opportunities for future message development. METHODS: Sources included PubMed, PsycINFO, Scopus, Academic Search Premier, and ProQuest Central (November - December 2024). The 55 studies included examined tobacco prevention or cessation messages and measured depression, depressive symptoms, or mental health as a primary outcome or analytic covariate. Study characteristics, target population, delivery format, message content, theoretical frameworks, outcomes, and gaps were extracted. RESULTS: RCTs made up half (51%) of the included studies, and most (78%) were conducted in the U.S. Nearly half (46%) required participants to have a mental health condition. Interventions most often used interactive (65.5%) or text-based (47.3%) communication and focused on tobacco cessation (89%) rather than vaping (9%). Common outcomes included feasibility or acceptability (37.7%) and point prevalence abstinence (37.7%). Mental health-specific messages showed mixed effectiveness. CONCLUSIONS: Despite progress in integrating mental health into tobacco messaging, targeted interventions for people with depression remain limited. Few studies tested long-term outcomes or used biochemical verification; many relied on untargeted generalized messaging.

Journal Article

Assessing the effects of non-invasive transcranial electrical stimulation (tACS and tDCS) on electrophysiological sleep parameters - a systematic review.

Transcranial electrical stimulation (tES), including transcranial direct current stimulation (tDCS) and transcranial alternating current stimulation (tACS), is considered a safe method to modulate cortical activity and endogenous brain oscillations. Given the therapeutic potential of tES across various clinical conditions and the central role of sleep in restoration and memory consolidation, numerous studies have investigated its effects on sleep and sleep-related parameters, yielding inconsistent results. This systematic review provides an up-to-date synthesis of 51 studies assessing the impact of tES on objectively measured electrophysiological sleep outcomes in both healthy individuals and clinical populations. The reviewed studies demonstrate heterogeneous effects, reflecting substantial variability in study designs. Nonetheless, consistent trends emerge, including reduced NREM1 and increases in total sleep time, NREM2, and NREM3 following tES. Moreover, slow-oscillatory tES increased slow-wave power during sleep. Here we show that tES, particularly slow-oscillatory tES, may positively influence sleep architecture and continuity by modulating endogenous brain oscillations. However, due to heterogeneous stimulation protocols, inconsistent findings, the limited number of significant effects and substantial risk of bias the current evidence remains inconclusive. Well-designed, large-scale trials targeting specific sleep outcomes are needed to clarify the therapeutic potential of tES.

Humans

Beyond predictive performance: A systematic review and critical methodological appraisal of AI/ML and conventional modelling strategies in breast, colorectal, and pancreatic Cancer.

BACKGROUND: Predictive modelling for cancer risk, treatment-related complications, and survival is central to precision oncology. Conventional logistic regression (LR) and Cox proportional hazards (CoxPH) regression remain widely used but are limited when modelling nonlinear interactions, high-dimensional imaging features, and multimodal clinical-metabolic predictors. Artificial intelligence (AI) and machine learning (ML) methods offer expanded capability through automated feature extraction, ensemble learning, and flexible survival modelling, but the evidence on when AI/ML adds value over conventional models across cancer sites and predictive tasks remains fragmented. OBJECTIVE: To systematically evaluate the methodological performance, validation strategies, and translational limitations of AI/ML models compared with conventional statistical models in published predictive-modelling studies for breast, colorectal, or pancreatic cancer. METHODS: PubMed, Scopus, and Web of Science were searched for studies published between January 2019 and March 2025. Two reviewers independently conducted title-and-abstract screening, full-text eligibility assessment, and PROBAST risk-of-bias assessment. Sixty-five studies (n = 907,567 participants) were narratively synthesised by cancer site, predictive task, model family, comparator, validation strategy, predictor modality, and calibration or explainability reporting. RESULTS: The 65 studies comprised breast cancer (n = 35), colorectal cancer (n = 21), and pancreatic cancer (n = 9). AI/ML superiority over LR and CoxPH was task- and data-dependent. CNN- and U-Net-based models predominated in imaging and body-composition tasks, tree-based ensembles consistently outperformed LR for tabular perioperative complication prediction, and CoxPH remained competitive, and in the largest pancreatic risk study, superior to XGBoost (C-index 0.802 vs 0.723) in well-structured datasets. PROBAST analysis-domain risk was moderate in 54 of 65 studies (83%), driven by limited external validation, sparse calibration reporting (11/65), and few decision-curve analyses (7/65). CONCLUSION: AI/ML adds the most methodological value in imaging-derived feature extraction and nonlinear perioperative prediction, while conventional regression remains preferable in large, structured datasets with linear predictors. Clinical translation requires standardised body-composition definitions, external validation, calibration assessment, decision-curve analysis, and explainability, in line with TRIPOD+AI and CLAIM standards.

Humans