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PubMed2026

AI-driven snapshot hyperspectral imaging for on-line sorting systems in food industry: From real-time sensing to intelligent decision-making.

High-throughput food sorting requires rapid, non-destructive detection of external defects, foreign materials, and internal quality attributes in heterogeneous food matrices. Conventional scanning hyperspectral imaging may suffer from motion-induced spatial-spectral mismatches, whereas snapshot hyperspectral imaging (S-HSI) captures spectral images within a single integration time. However, its advantage is limited by trade-offs in resolution, signal-to-noise ratio (SNR), reconstruction uncertainty, and calibration stability, which are further amplified by variable tissue structure, surface reflection, moisture, and fat distribution in foods. This review critically examines artificial intelligence (AI)-driven S-HSI for on-line food sorting within a sensing-representation-decision-execution framework. Compact architectures are compared according to their physical constraints, food-sorting suitability, and ability to support mapping between spectral responses and physicochemical quality attributes. AI strategies are reviewed for spectral reconstruction, image restoration, spatial-spectral representation, band selection, uncertainty-aware decision-making, and edge implementation. AI can partially compensate for snapshot-specific limitations, but current evidence remains largely limited to laboratory or prototype studies. Future work should link system performance to food safety and quality outcomes by reporting throughput, decision latency, calibration drift, missed-detection risk, false-rejection cost, and closed-loop sorting success.

Hyperspectral Imaging↗

PubMed2026

Disentangling oscillatory and aperiodic neural activity in autism: A spectral parameterization analysis of neurofeedback intervention.

BACKGROUND: Autism Spectrum Disorder (ASD) is characterized by atypical neural oscillations and heterogeneous alterations in excitation/inhibition (E/I) balance, the directionality of which varies across individuals, neural circuits, and developmental stages. While Alpha-band neurofeedback (NFB) is a promising intervention, its underlying neurophysiological mechanisms remain unclear, partly due to the conflation of periodic and aperiodic signals in traditional EEG analysis. METHODS: This randomized controlled trial recruited 40 children with ASD, assigned to either an experimental group (Alpha-training NFB) or a no-feedback group. Resting-state EEG and behavioral assessments (SRS, ABC) were collected pre- and post-intervention. We employed spectral parameterization to decompose neural activity into aperiodic (1/f slope, offset) and periodic (periodic alpha power, center frequency) components. RESULTS: NFB training yielded significant behavioral improvements in social cognition and relating skills. Physiologically, the experimental group exhibited a significant steepening of the aperiodic slope (increased exponent), reflecting a reduction in neural noise and potential optimization of inhibitory modulation. Furthermore, we observed enhanced periodic alpha power and an acceleration of the alpha center frequency (ACF), indicative of improved neural efficiency and maturation. These physiological shifts in frontal and occipital regions were significantly correlated with improvements in behavioral scores. CONCLUSION: Alpha-training NFB was associated with improvements in caregiver-rated behavioral scores and modulated spectral features of resting-state EEG in children with ASD. These findings validate the utility of spectral parameterization markers in evaluating neuromodulatory interventions.

Humans↗

PubMed2026

Introgression shapes the genomic conflict landscape of Malus, providing evidence for a reticulate backbone in a woody crop lineage.

Phylogenomic discordance is widespread across plants, but its evolutionary significance is often obscured when conflict is treated primarily as analytical noise rather than as evidence of underlying processes. In woody lineages in particular, incomplete lineage sorting, introgression, and genome duplication can interact over long timescales to produce complex genomic histories that are not adequately summarized by a strictly bifurcating tree. Here, we use Malus as a model woody genus to investigate how these processes structure conflict across a genus-scale, accession-based phylogenomic framework. Using broad taxon sampling, hundreds of nuclear loci, plastid genomes, and genome-wide SNP summaries, we reconstruct a robust nuclear backbone for sampled Malus lineages and evaluate where discordance is concentrated and which processes best explain it. Nuclear analyses resolve eight major clades, whereas conflict is non-random and localized to recurrent hotspots rather than evenly distributed across the tree. Cytonuclear discordance is similarly concentrated, especially around Clade H, represented by sampled accessions of M. tschonoskii, where localized plastid-nuclear disagreement is consistent with candidate plastid capture or organellar introgression. Multiple complementary analyses further indicate that the strongest conflict is not explained by ILS alone, but instead reflects lineage-structured introgression, while polyploid complexes represent additional localized sources of evolutionary complexity. Together, these results provide evidence for a reticulate genomic backbone in Malus and show how integrating nuclear, plastid, and genome-wide conflict analyses can help distinguish background discordance from process-specific signals in woody plant radiations. Several lineage-level reticulation hypotheses identified here should now be tested with broader population-level sampling and curated reference accessions.

Malus↗

PubMed2026

Physiological and molecular responses of coelomocytes to low- to mid-frequency acoustic exposure in the sea urchin Strongylocentrotus intermedius.

Underwater noise is a widespread environmental pollutant in marine ecosystems, yet the effects of low- to mid-frequency acoustic exposure on immune physiology and molecular responses in echinoderms remain unclear. In this study, the sea urchin Strongylocentrotus intermedius was exposed to continuous pure-tone acoustic stimulation at 80, 125, 250, 500, 750, and 1000 Hz for 3 h. Results showed that acoustic exposure significantly affected redox homeostasis, energy metabolism, and immune function in S. intermedius coelomocytes: the antioxidant system and glutathione redox balance were altered, as indicated by increased superoxide dismutase (SOD) and catalase (CAT) activities, elevated reduced glutathione (GSH) content, and a higher GSH/GSSG ratio; glycolysis-related enzyme activities were enhanced, with increased pyruvate kinase (PK) activity under 125-500 Hz exposure and elevated hexokinase (HK) activity at 250 Hz; and immune function was impaired, as shown by increased coelomocyte mortality, reduced phagocytic activity, and inhibited acid phosphatase (ACP) and alkaline phosphatase (AKP) activities, whereas respiratory burst activity showed no significant change. Among all treatments, 250 Hz induced the most pronounced physiological responses. Transcriptomic analysis of coelomocytes from the 250 Hz group identified 663 differentially expressed genes, including 537 upregulated and 126 downregulated genes, mainly enriched in pathways related to apoptosis, phagosome, lysosome, glutathione metabolism, arachidonic acid metabolism, and carbohydrate metabolism. These findings indicate that low- to mid-frequency acoustic exposure can act as a physiological and molecular stressor to S. intermedius coelomocytes by affecting redox homeostasis, enhancing energy metabolism, and suppressing immune effector processes, with 250 Hz showing the strongest effect under the present exposure conditions. This study provides experimental evidence for evaluating the potential biological effects of low- to mid-frequency acoustic exposure on benthic echinoderms.

Animals↗

PubMed2026

Role of omentin-1 in the global proteome of porcine pituitary cells: insights into proliferation- and apoptosis-related processes.

The anterior pituitary integrates endocrine regulation, cellular growth, and adaptive responses. Adipokines, secreted mainly by adipose tissue, act as hormonal signals linking metabolism, inflammation, appetite, and reproduction. They regulate hypothalamic-pituitary-ovarian axis by modulating hormone secretion and intracellular signaling. The presence of adipokine receptors in anterior pituitary suggests local metabolic-endocrine interactions. Omentin-1, predominantly expressed in visceral adipose tissue, participates in glucose metabolism and ovarian steroid regulation. Recent findings indicate that omentin-1 modulates tropic hormones, their receptors, and adipokine balance in anterior pituitary cells. We hypothesized that omentin-1 affects protein expression and signaling pathways involved in pituitary cell proliferation and apoptosis. This study examined its effects in anterior pituitary cells from Large White and Meishan pigs. Proteomic analysis identified 230 candidate differentially abundant proteins after omentin-1 treatment: 30 downregulated and 3 upregulated in Large White pigs, and 107 downregulated and 90 upregulated in Meishan pigs, associated with enriched 116 Gene Ontology terms. Key proteins were associated with cell cycle, DNA replication, gene expression, and posttranscriptional/posttranslational regulation. Responses differed between breeds. CDK5RAP2 and SIX1 were linked to proliferative control in Large White pigs, whereas AKT1S1 and RHOA were among the proteins associated with the broader proteomic response observed in Meishan pigs. Meishan pigs showed dynamic apoptotic protein regulation, including HTRA2, PARP2, and DFFA. Complementary in vitro experiments demonstrated that omentin-1 downregulated cyclins and caspase-3, upregulated BCL2, increased BCL2/BAX ratio, and modulated ERK1/2, AKT, AMPKα, and STAT3 phosphorylation. Together, these findings suggest that omentin-1 modulates proteomic networks and intracellular signaling associated with anterior pituitary cell function during the mid-luteal phase of the estrous cycle.

Animals↗

PubMed2026

A combined stimulus of acute fasting and exercise modulates hippocampal mitochondrial quality control in healthy mice.

BACKGROUND AND AIMS: Exercise and fasting are recognized for their ability to improve brain health and mitigate neurodegeneration. However, little is known about how these interventions acutely impact mitochondrial quality control mechanisms including mitophagy. METHODS: We examined the effects of a single bout of fasting and exercise (FEx) on hippocampal mitochondrial function and proteomic remodeling in male and female mice. To assess in vivo autophagy dynamics, we combined proteomics with chloroquine (CQ) inhibition of autophagic flux. Mice were assigned to sedentary (Sed), fasting (F), exercise (Ex), or combined FEx groups and received unilateral intrahippocampal injections of CQ or PBS following treatments. Four hours later, hippocampi were collected for analysis. RESULTS: LC3-II levels significantly increased in the FEx group only following CQ treatment, indicating enhanced autophagic flux. Proteomic profiling showed sedentary males failed to mount a robust response to FEx however females exhibited upregulation of proteins involved in the TCA cycle, glutathione metabolism, and oxidative phosphorylation, suggesting greater mitochondrial adaptability. Functional assays supported these findings, females showed increased complex IV activity post-FEx. The mitochondrial DNA / nuclear DNA ratio increased after FEx regardless of sex, and upstream regulator analysis predicted activation of mitochondrial biogenesis. CONCLUSIONS: Together, these data reveal sex-specific mitochondrial remodeling in response to acute fasting and exercise. Defining these normative responses is critical for understanding how mitochondrial adaptability shapes resilience or vulnerability to neurological challenges.

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

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

Desert-derived Ensifer sp. SA403 enhances potato salt tolerance by reshaping rhizosphere microbiome functions and host responses.

Soil salinization increasingly threatens global food security, and potato (Solanum tuberosum L.), a moderately salt-sensitive crop, is particularly vulnerable to saline soils. Plant growth-promoting rhizobacteria (PGPR) offer a promising strategy to improve crop performance, yet how PGPR interact with native microorganisms to enhance potato salt tolerance remains poorly understood. In this study, we identified a desert-derived PGPR strain, Ensifer sp. SA403, which substantially enhanced potato performance under high salinity across sterile, non-sterile and field conditions. Physiologically, inoculation with SA403 reduced shoot Na⁺ accumulation and increased the K⁺/Na⁺ ratio; notably, these effects were markedly stronger in non-sterile substrates than under sterile conditions, indicating that SA403-mediated ion homeostasis relies on cooperation with the resident microbiota rather than on the strain acting alone. Metagenomic profiling indicated that SA403 strain reshaped rhizosphere communities, significantly enriching beneficial taxa such as Priestia and Bradyrhizobium, and upregulated functional pathways involved in glutathione and sulfur metabolism. Furthermore, host transcriptomic analyses showed that SA403 modulated plant responses to salt stress, with differentially expressed genes enriched in jasmonic acid signaling, ethanolamine metabolism and amino-acid biosynthesis pathways. Field trials on saline soils confirmed that SA403 significantly increased seedling emergence and tuber weight. Together, our results demonstrate that SA403 functions as a biological mediator that optimizes rhizosphere microecology and coordinates ion balance and host signaling to enhance potato salt tolerance. These findings support the potential of SA403 as a robust PGPR-based tool for sustainable potato production on saline soils.

Rhizosphere↗

PubMed2026

Reducing state anxiety with alpha-frequency transcranial alternating current stimulation.

BACKGROUND: Anxiety reactivity to acute stress is a transdiagnostic vulnerability factor. We tested whether a single session of alpha-frequency transcranial alternating current stimulation (tACS) targeting the frontoparietal control network reduces stress-evoked state anxiety in healthy adults. METHODS: In a randomized, blinded, sham-controlled study, 42 participants (mean age 58.9 years) completed an acute stress task before and after stimulation. The task was an adapted moving-circles paradigm in which circle collisions triggered a brief aversive event (mild electric shock plus unpleasant noise and a white flash). Active stimulation consisted of 20 min of 10-Hz tACS (2.0 mA/channel; 30-s ramp up/down) delivered via electrodes at F3, P3, Cz, and T7 (0° phase at F3/P3; 180° at Cz/T7). Sham stimulation used the same montage and ramp periods but no sustained current. RESULTS: State anxiety showed a significant Time × Protocol interaction (F(1,35) = 4.22, p = .047): STAI-S decreased after active tACS (Δ = -3.16) but increased slightly after sham (Δ = +1.17). Perceived stress appraisal (SAAS) did not change. Resting-state alpha power at F3/P3 showed no reliable pre-post effects. During the task, left-frontal relative alpha differed by protocol and showed a trend toward larger increases following active tACS. Electrodermal and pupil indices changed across sessions in both groups, with no differential stimulation effects. CONCLUSIONS: A single alpha-tACS session produced a modest, selective reduction in stress-evoked state anxiety, supporting oscillatory neuromodulation as a scalable approach to dampen anxiety reactivity.

Humans↗

PubMed2026

Data-centric, robust, and explainable multimodal deep learning for clinical decision support: A systematic review.

PURPOSE: Multimodal deep learning is increasingly proposed for clinical decision support (CDS) under a "data-centric" framing that prioritizes label quality, missing-modality robustness, distribution shift, calibration, and explainability. Prior reviews have examined multimodal medical AI, CDS, and data-centric methods separately, but none address their intersection. We mapped the modalities, fusion strategies, and data-centric and explainability techniques used in this recent literature, quantified how often each is implemented rather than merely mentioned, assessed deployment-relevant evidence (external validation, clinical-outcome measurement, equity), and formally appraised study-level risk of bias. METHODS: Following the PRISMA 2020 statement (PROSPERO CRD420261427815; registered retrospectively), we screened 150 records and included primary, clinical, multimodal studies that applied machine or deep learning to a decision-support task and reported at least one quantitative result. Two reviewers screened and extracted data with consensus adjudication. Each study was coded against pre-specified operational definitions, separating implemented or empirically evaluated techniques from those only mentioned. Study-level risk of bias was assessed with PROBAST + AI. Synthesis was narrative. RESULTS: Thirty-one studies met inclusion; 30 (97%) were published between 2024 and 2026, with a median of three modalities (range 2-6), most commonly structured EHR (71%) and imaging (39%). Data-centric techniques were frequently reported (74-84% across label-noise, distribution-shift, calibration, missing-modality and class-imbalance handling; equity 61%). However, external validation was reported in only 4/31 studies (13%), a clinical or provider outcome in 3/31 (10%), and no study reported routine deployment. Overall risk of bias was high in 27/31 studies (87%), driven by the analysis domain. CONCLUSION: Within this recent, self-selected slice of the field, technical robustness and explainability techniques are widely reported but rarely validated out-of-distribution or against clinical outcomes, and the underlying evidence is at high risk of bias. Progress requires external multi-site validation, clinical-outcome measurement, formal bias appraisal, and adherence to AI reporting standards (e.g., TRIPOD + AI) before deployment can be justified.

Deep Learning↗

PubMed2026

A STORM-based protocol for nanoscale imaging and quantitative analysis of protein-associated and phospholipid-associated structures in natural rubber.

Stochastic Optical Reconstruction Microscopy (STORM) enables nanoscale mapping of molecular components beyond the diffraction limit; however, its reproducible implementation in hydrophobic polymer matrices remains challenging because fluorescence-labeling specificity, fluorophore photoswitching, three-dimensional localization, chromatic registration, and quantitative image analysis must be carefully controlled. This protocol presents a standardized experimental workflow for dual-color labeling, astigmatism-based three-dimensional STORM acquisition, and quantitative analysis of protein-associated and phospholipid-associated structures in natural rubber (NR). The workflow covers sample pretreatment, Cy5 NHS ester labeling of protein-associated primary amines, DiI labeling of phospholipid-rich domains, STORM imaging-buffer preparation, three-dimensional single-molecule localization, dual-channel registration, generation of standardized xy projections, aggregate-size analysis, and projected lateral spatial correlation assessment. Reproducibility is supported by defined acquisition and localization criteria, three independent sample preparations with at least five fields of view analyzed per condition, and unlabeled, single-color, dye-only matrix, and processing-associated Cy5 controls. Mean lateral localization precisions of 11.8 ± 2.3 nm for Cy5 and 13.5 ± 2.9 nm for DiI were obtained, while two-dimensional Fourier ring correlation analysis of the xy projections yielded effective lateral image resolutions of approximately 25 and 28 nm, respectively. Image-based particle segmentation and localization-coordinate-based density-based spatial clustering of applications with noise (DBSCAN) were applied to standardized xy projections as complementary quantitative approaches. Application of the protocol to untreated, centrifuged, and protease-treated NR samples demonstrated treatment-associated changes in the detected abundance and projected size distributions of protein- and phospholipid-associated aggregates, together with a non-monotonic change in their projected lateral spatial correlation. These observations describe alterations in nanoscale organization but do not, by themselves, establish stable protein-phospholipid complex formation. Unlike previous studies that primarily demonstrated the feasibility of STORM imaging in rubber materials, the principal contribution of this work is an end-to-end, step-by-step protocol incorporating defined controls, three-dimensional localization, image-quality metrics, chromatic-registration procedures, and complementary quantitative-analysis pipelines for non-expert users. The workflow may be adaptable to other hydrophobic polymers and soft-material systems after appropriate optimization and validation.

Rubber↗

PubMed2026

Multi-omics integrative analysis provides insight into potential molecular responses to sustained high water flow in common carp (Cyprinus carpio) cultured in recirculating aquaculture.

To investigate the potential molecular responses by which water flow intensity affects the growth of common carp (Cyprinus carpio) in a recirculating aquaculture system (RAS), a control group (CG, actual water velocity 0.3 cm/s) and three sustained flow treatment groups were established, including a low-flow group (LF, 1 body length per second, bl/s), a medium-flow group (MF, 2 bl/s), and a high-flow group (HF, 3 bl/s). After 12 weeks of culture in the RAS, growth performance was compared among groups under different flow intensities. The best-performing group and the control group were then selected for the determination of intestinal digestive enzyme activities, as well as transcriptomic and whole-genome bisulfite sequencing analyses of muscle tissue. The results showed that the specific growth rate and feed intake of the HF group were significantly higher than those of the other groups (P < 0.05), whereas no significant difference in feed conversion ratio was observed among groups. Compared with the CG group, lipase activity was significantly higher in the HF group (P < 0.05), while α-amylase and trypsin activities showed increasing trends without significant differences. RNA-seq identified a total of 273 differentially expressed genes, including 72 upregulated genes and 201 downregulated genes in the HF group relative to the CG group. These genes were mainly enriched in glycolysis, pyruvate metabolism, ATP metabolism, the pentose phosphate pathway, the insulin signaling pathway, the PPAR signaling pathway, and the adipocytokine signaling pathway, indicating that sustained high water flow induced a muscle transcriptional response characterized by remodeling of energy metabolism and substrate utilization. Whole-genome bisulfite sequencing analysis showed that DNA methylation in common carp muscle occurred predominantly in the CpG context. Differentially methylated regions between the HF and CG groups were mainly distributed in transcription-related regulatory regions, including promoters, CpG islands, and CpG island shores. In promoter regions, the number of hypermethylated regions in the HF group relative to the CG group was markedly higher than that of hypomethylated regions. Integrated analysis further identified two candidate genes showing both promoter differential methylation and differential expression, namely LOC109094644 and bcorl1, suggesting that adaptation to high water flow may involve IGF-related growth regulation and remodeling of upstream transcriptional programs. The qPCR results were consistent with the transcriptomic data. Taken together, within the tested range, a sustained water flow of 3 bl/s was more conducive to the growth of common carp in the RAS, which may be associated with enhanced lipid digestion and utilization, remodeling of the muscle energy metabolic network, changes in promoter methylation, and the coordinated regulation of key candidate genes. This study provides a theoretical basis for clarifying the exercise adaptation mechanism of common carp in recirculating aquaculture and for optimizing flow velocity parameters.

Animals↗

PubMed2026

Assessment of the safety and efficacy of sodium pentaborate pentahydrate in individuals with overweight and obesity: a randomized, double-blind, placebo-controlled, phase 1/2 dose-finding trial.

The present study aimed to examine the short-term safety and tolerability of sodium pentaborate pentahydrate (NaB) and to explore preliminary efficacy and dose selection as secondary objectives in individuals with overweight or obesity. In this randomized, double-blind, placebo-controlled, phase 1/2 trial, conducted from July 2024 to January 2025, 177 adults with overweight or obesity were randomized, of whom 116 completed the 12-week trial. Participants received placebo or NaB at doses of 200, 400, 600, 800, or 1,000 mg for 12 weeks, alongside a standardized diet and exercise programme. The primary safety objective was to investigate short-term safety and tolerability through adverse events, hypoglycaemic episodes, gastrointestinal adverse events, and changes in haematological and biochemical parameters. The primary exploratory efficacy outcome was percentage change in body weight from baseline to week 12. Secondary and exploratory efficacy outcomes included body weight, body mass index (BMI), waist and hip circumferences, waist-to-hip ratio, glycaemic markers, lipid parameters, and blood pressure. Baseline characteristics were broadly similar across groups (all p ≥ 0.05), and no major short-term safety signal was observed. Mean body weight decreased in the 400 mg (-2.6 kg), 600 mg (-1.2 kg), and 1,000 mg groups (-3.1 kg). Compared with placebo, the 1,000 mg dose resulted in the largest reductions in body weight (mean difference, -2.30 kg; p = 0.01) and BMI (mean difference, -0.85 kg/m2; p = 0.02). The 1,000 mg dose showed preliminary efficacy for reducing body weight and BMI over 12 weeks compared with placebo, with no major short-term safety signal and no clinically meaningful changes in renal, hepatic, or haematological markers. All reported adverse events were mild. These short-term findings are exploratory and require confirmation in future phase 3 trials with extended follow-up to investigate long-term safety and efficacy.

Humans↗

PubMed2026

Genome-wide scans reveal candidate genes associated with wing morph differentiation in Tetrix japonica.

Wing dimorphism is an important dispersal-related trait in insects, but its genomic basis remains poorly understood in pygmy grasshoppers. Here, we integrated genome-wide single-nucleotide polymorphism (SNP) analyses, population structure inference, selection scans, and functional annotation to investigate genomic differentiation between long- and short-winged Tetrix japonica. Principal component analysis (PCA), ADMIXTURE, and phylogenetic analyses revealed weak genome-wide separation between morphs, indicating differentiation on a largely shared genetic background. Genome-wide scans based on the fixation index (FST), nucleotide diversity ratios, and Tajima's D, using 50-kb non-overlapping windows and empirical top-5% outlier thresholds, identified multiple candidate regions across seven chromosomes. The broader long- and short-winged candidate sets spanned 9.35 Mb and 9.37 Mb and directly overlapped 82 and 77 genes, respectively. Candidate genes were associated with signaling/hormone regulation, membrane transport, metabolism, cytoskeletal organization, extracellular matrix structure, and development. Short-winged candidate genes were significantly enriched for ABC-type transporter activity and ATP hydrolysis activity. Because all individuals originated from a single laboratory-maintained population with weak genome-wide structure, these regions should be regarded as candidate loci from a screening-stage analysis that require validation in independent populations and by functional assays, rather than as confirmed targets of selection.

Animals↗

PubMed2026

Acetylcholine signaling regulates osmotic stress adaptation in the phytopathogen Dickeya solani.

Plants impose strong selective pressures that shape both the composition and functional potential of plant microbiomes. The adaptation of plant-associated bacteria to their hosts relies on an extensive repertoire of signal transduction systems that sense plant-derived molecules and dynamically adjust bacterial physiology and metabolism within the holobiont. These signals include key plant signaling compounds that regulate processes essential for plant-microbe interactions. Among them, acetylcholine is emerging as an important signaling molecule in both plants and bacteria. Here, we demonstrate that acetylcholine regulates the expression of the osmotic stress response betIBA gene cluster in the important phytopathogen Dickeya solani, where it plays an important role in osmoprotection. We show that the TetR-family transcriptional regulator associated with this pathway, BetIDs, recognizes acetylcholine as well as choline and trimethylamine. These three ligands differentially induce betIBA transcription in a manner that correlates with their binding affinities. Ligand binding does not affect BetIDs binding to the bet promoter or its oligomeric state. Instead, it induces pronounced changes in the secondary structure of BetIDs, with the magnitude of these conformational changes being ligand-dependent. We further show that quorum sensing modulates osmotic stress tolerance in D. solani by regulating the expression of the Bet pathway. The Bet system is required for the full virulence of D. solani, particularly in chemically complex plant tissues. Phylogenetic analyses reveal that the BetIBA system is widely distributed among plant-associated Pseudomonadota, collectively supporting its importance for bacterial survival and adaptation in plant-related environments.

Osmotic Pressure↗

PubMed2026

METTL14-mediated m6A modification of CCNE1 accelerates progression of myelodysplastic syndromes via MAPK-ERK and PI3K-AKT signaling pathways.

BACKGROUND: N6-methyladenosine (m6A) is the most common RNA modification and plays a key role in the initiation, progression, and relapse of multiple cancers, including hematologic malignancies. However, the role of m6A and m6A regulatory genes in myelodysplastic syndromes (MDS) remains unclear. This study aims to elucidate the function and molecular mechanism of methyltransferase METTL14 in MDS. METHODS: RT-qPCR was used to assess the expression of multiple m6A regulators, focusing on METTL14 in MDS patients and cell lines. METTL14 overexpressing and knockdown cell lines were established, and CCK-8, EdU, and flow cytometry assays were performed to explore the biological functions of METTL14.Dot blot, MeRIP-Seq, MeRIP-qPCR, RT-qPCR, and Western blot were employed to investigate the underlying molecular mechanism. RESULTS: Dysregulation of multiple m6A regulators was observed in MDS, among which METTL14 was upregulated. Elevated METTL14 expression increases MDS risk and adverse prognosis, emerging as a biomarker for poor prognosis. METTL14 promoted proliferation and cell-cycle progression of MDS cells while inhibiting apoptosis; corresponding changes were observed in cell cycle and apoptosis markers. METTL14 regulated cellular m6A levels. Downstream targets of METTL14 were enriched in cell cycle-related pathways, with CCNE1 identified as a critical target. Knockdown of METTL14, actinomycin D, or S-adenosylhomocysteine treatment reduced CCNE1 mRNA and protein levels. Furthermore, METTL14 activated MAPK-ERK and PI3K-AKT signaling via CCNE1 in an m6A-dependent manner, thereby promoting proliferative MDS cells' capacity. CONCLUSIONS: This study delineates a METTL14/m6A/CCNE1 signaling axis in MDS progression and suggests that METTL14-mediated m6A modification may be a potential therapeutic target for MDS.

Humans↗

PubMed2026

Translational reprogramming of TGF-β signaling via TRMT61A-mediated tRNA m1A drives prostatic fibrosis and hyperplasia.

Dysregulation of the epitranscriptomic landscape is closely linked to pathological proliferation, but its specific role in benign prostatic hyperplasia (BPH) remains unclear. Here, we identify the tRNA methyltransferase TRMT61A as a critical driver of BPH progression. We found that TRMT61A and global N1-methyladenosine (m1A) levels are aberrantly upregulated in human BPH tissues. Functionally, TRMT61A knockdown potently suppresses prostate cell proliferation and reduces stromal fibrosis, inducing G1 cell cycle arrest and reversing pathological remodeling both in vitro and in vivo. By integrating ribosome profiling (Ribo-seq) and tRNA-seq, we observed that TRMT61A drives translational reprogramming. TRMT61A preserves the stability of specific tRNA isoacceptors (e.g., tRNA-Leu-CAA), which is required for the efficient decoding of mRNAs containing m1A-dependent codons. Consequently, TRMT61A selectively promotes the translational elongation of the key receptor TGFβR1. This amplifies downstream TGF-β/SMAD signaling and drives epithelial-mesenchymal transition (EMT) without affecting mRNA transcription. In summary, our study reveals how TRMT61A drives BPH progression through TGFβR1 translation, highlighting the therapeutic potential of targeting epitranscriptomic pathways to reverse prostatic hyperplasia and fibrosis.

Male↗