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PubMed2026

Navigating Social Media: Balancing Connectivity With Media Literacy to Combat Misinformation and Protect Mental Well-Being.

BACKGROUND: The pervasive use of social media has created a complex digital ecosystem where high connectivity coexists with significant challenges, including the rapid spread of misinformation, particularly regarding mental health, and documented negative impacts on psychological well-being. Platform architectures designed for engagement maximization have been identified as central factors in both issues. OBJECTIVE: This paper critically analyzes the interconnected relationships between social media use, misinformation dissemination, and mental health impacts, with particular attention to psychiatric misinformation across diagnostic categories (e.g., depression, anxiety, ADHD). A primary objective is to evaluate the potential of advanced critical digital literacy frameworks to serve as protective mechanisms against these dual threats. METHODS: A systematic search was conducted following PRISMA 2020 guidelines across APA PsycInfo, PubMed, JSTOR, and Google Scholar for literature published between January 2018 and March 2026 (updated from the original 2023 search). The search yielded 2672 records. After removing 624 duplicates, 2048 records underwent title and abstract screening, with 1802 excluded. The remaining 246 full-text articles were assessed for eligibility, resulting in 86 studies included in the final qualitative synthesis. Inter-rater reliability was established (Cohen's κ = 0.82). Quality assessment was conducted using the Joanna Briggs Institute Checklist, AXIS, and CASP tools, with findings weighted by methodological quality. A thematic analysis was undertaken to synthesize findings. RESULTS: The analysis reveals that core architectural features of social media platforms, algorithmic curation and engagement-based metrics, simultaneously foster environments ripe for misinformation spread and contribute to psychological distress, including anxiety, depression, and harmful social comparison. Psychiatric misinformation specifically (e.g., inaccurate claims about treatment effectiveness, diagnostic criteria, and medication side effects) represents a growing concern, particularly on image- and video-based platforms. The findings indicate that conventional media literacy approaches focused solely on fact-checking are insufficient. Instead, a critical digital literacy framework encompassing algorithmic awareness, data literacy, and emotional awareness is essential for building user resilience, with evidence from high-quality systematic reviews supporting this approach. CONCLUSIONS: Navigating the complexities of modern social media requires an integrated approach combining "pedagogies of play" for experiential skill development with advocacy for structural change (e.g., algorithmic transparency, well being by design principles). This dual strategy empowers individual users to critically engage with digital content while advocating for ethical platform design, thereby safeguarding both mental well-being and democratic discourse. Implications for educators, mental health professionals (including competencies for addressing patient encounters with psychiatric misinformation), policymakers, and platform designers are discussed.

Humans↗

PubMed2026

Application of musculoskeletal ultrasound in postoperative rehabilitation assessment and monitoring after rotator cuff repair: A systematic review.

BACKGROUND: The development of rehabilitation protocols after rotator cuff repair has long lacked objective benchmarks. Traditional time‑based regimens are limited by considerable inter‑individual variability and an increased risk of re‑tear. Musculoskeletal ultrasound allows dynamic assessment of tendon healing and muscle morphology, yet evidence for directly linking its use to rehabilitation decisions remains scarce. OBJECTIVE: To systematically synthesize the evidence on the use of musculoskeletal ultrasound monitoring to inform rehabilitation decision‑making after rotator cuff repair. METHODS: Following the Preferred Reporting Items for Systematic Reviews and Meta‑Analyses (PRISMA) guidelines, we searched PubMed, China National Knowledge Infrastructure (CNKI), and Wanfang Data from January 2020 to April 2026. Original studies were included if they involved patients who had undergone rotator cuff repair, used musculoskeletal ultrasound (including gray‑scale ultrasound, elastography, etc.) to evaluate the rotator cuff tendons or shoulder muscles, and reported at least one parameter related to rehabilitation decision-making or functional outcomes. RESULTS: Eleven studies were included. Shear wave velocity (SWV), cross‑sectional area (CSA), and echo intensity (EI) were the most frequently reported ultrasound parameters. Available evidence indicated that SWV increased progressively after surgery, with an overall increase of approximately 22% to 25% from one week to 12 months postoperatively. This dynamic trajectory may serve as a reference baseline for judging rehabilitation progress. An abnormally elevated SWV in the early postoperative period was associated with an increased risk of re‑tear, suggesting that a more conservative rehabilitation strategy should be adopted. Tendon stiffness measured at 12 weeks after surgery independently predicted long‑term return to sport. Regarding muscle parameters, changes in CSA and EI were positively correlated with shoulder function scores, and the combination of these two parameters effectively identified patients with rehabilitation bottlenecks. CONCLUSION: Musculoskeletal ultrasound parameters are associated with the initiation of active movement, adjustment of exercise load, prediction of return‑to‑sport prognosis, and identification of retear risk. Among these, SWV shows particular promise as an objective monitoring parameter for supporting rehabilitation assessment after rotator cuff repair. Future randomized controlled trials are needed to determine whether ultrasound-informed assessment can improve rehabilitation outcomes compared with traditional time-based regimens, and to establish standardized measurement protocols and clinically applicable reference values. Key findings of this review are summarized in S1 File.

Humans↗

PubMed2026

Mapping antibody sequences and effector functions across spatial niches.

Antibodies are fundamental to human health but can also drive pathology. Each antibody has a molecular specificity, encoded by their clonally heritable B cell receptor (BCR). Recent advances in spatial transcriptomics coupled with repertoire sequencing have enabled capturing antibody-secreting cells (ASCs) and their clonal BCR within their tissue microenvironment. However, our understanding of antibody production niches remains limited. Furthermore, where antibodies are produced can be distinct from where antibodies exert their effector function. Here, we propose a conceptual spatial framework to distinguish between 'antibody production niches', defined by the ASC, BCR, and niche composition, versus 'antibody functional niches', composed of the antibody, antigen, and effector landscape. We then examine the possibilities and challenges to map and link antibody-encoding sequences and antibody effector functions using current and emerging technologies. Combined, we argue that integrating spatial sequence data with the antibody functional context is essential to decode the architecture of antibody-mediated immunity.

Humans↗

PubMed2026

Distinct functions of mammalian RAD51 paralogs in genome maintenance.

RAD51 paralogs (RAD51B, RAD51C, RAD51D, XRCC2, and XRCC3) are evolutionarily conserved essential proteins for cell survival and genome maintenance. RAD51 paralogs were originally identified to play a role in homologous recombination-mediated repair of DNA double-strand breaks (DSBs). However, investigations over the last decade have uncovered new roles of RAD51 paralogs beyond DSB repair in replication stress responses, including replication fork progression, fork stability, and its restart. Recent structural studies have not only uncovered the molecular architecture of previously known RAD51 paralog complexes but also identified novel paralog complex assemblies, providing mechanistic insights into their various genome-maintenance functions. Additionally, a role for RAD51 paralogs in resolving R-loops has been identified, and studies with cancer-associated variants suggest that RAD51 paralogs are potential determinants of cancer susceptibility and therapeutic responses. In the present review, we highlight the recently deciphered structures and novel functions of RAD51 paralog complexes and discuss the clinical and therapeutic implications.

Rad51 Recombinase↗

PubMed2026

Whole-Genome Deep Learning Predicts Chemotherapy Response in Colorectal Cancer.

Chemotherapy response in colorectal cancer (CRC) exhibits significant heterogeneity, with current clinical predictors failing to capture complex genomic determinants of resistance. We developed a hybrid deep learning framework integrating convolutional neural networks (CNNs) and bidirectional long short-term memory (BiLSTM) networks to analyze whole-genome somatic mutations, evolutionary conservation, chromatin accessibility, and 3D genome architecture in 2,546 TCGA patients. An attention mechanism identified predictive genomic regions. The model achieved an AUC of 0.92 (95% CI: 0.89-0.94) in cross-validation and 0.88 (95% CI: 0.85-0.91) in independent validation, outperforming clinical models (ΔAUC = +0.18, p < 0.001). Key predictors included non-coding variants in TP53, KRAS, and PIK3CA regulatory regions. Triple-positive patients (mutations in all 3 regions) had significantly worse progression-free survival (HR = 4.7, p < 0.001). Our framework enables accurate chemotherapy response prediction and reveals novel non-coding resistance mechanisms, advancing precision oncology in CRC.

Humans↗

PubMed2026

Control of foreign DNA: emerging roles of xenogeneic silencers.

Bacteria continuously acquire foreign DNA through horizontal gene transfer, yet its successful integration depends on regulatory mechanisms that balance genome protection with evolutionary innovation. Xenogeneic silencers are central to this process: they preferentially bind AT-rich DNA, a common feature of many horizontally acquired genetic elements, and repress its transcription. Recent studies, however, reveal a much broader regulatory repertoire. Beyond transcriptional repression, these proteins contribute to chromosome organization by forming higher-order nucleoprotein complexes and phase-separated condensates that shape bacterial nucleoid architecture. Furthermore, they play roles in regulating bacteriophage infection cycles, including mechanisms by which phages hijack host silencing activities for their own benefit. Their extensive regulatory reach, spanning virulence genes, biofilm formation, specialized metabolite production, and mobile genetic elements (MGEs), underscores their central role in connecting environmental signals, including fluctuations in the second messenger c-di-GMP, with gene expression, and genome organization. The diversification of xenogeneic silencers across bacterial chromosomes, plasmids, phages, and other MGEs highlights their evolutionary significance. Together, these recent findings position xenogeneic silencers as dynamic regulatory modules that shape the fate of foreign DNA across the horizontal gene transfer network.

Gene Transfer, Horizontal↗

PubMed2026

Strategies for mosaic variant calling in brain disorders.

The human brain is a genomic mosaic, where postzygotic mutations arising from embryogenesis to senescence drive diverse neurodevelopmental and neurodegenerative diseases. Because of numerous sequencing artifacts at ultralow variant allele frequencies (VAFs), detecting these variants remains a significant analytical challenge. This review focuses on single-nucleotide variants and small indels, summarizing current strategies for aligning sampling methods, including bulk, laser capture microdissection, and single-cell genomics, with the expected clonal architecture of the brain. It emphasizes that mosaic detection sensitivity is fundamentally constrained by sequencing depth, since even the most advanced algorithms cannot identify variants not physically represented in the sequencing library. The review further recommends the selection of variant calling algorithms based on validated VAF detection performance, matching tools like MuTect2 and MosaicForecast to their optimal performance ranges. Furthermore, we discuss how multitissue sampling, as emphasized by the SMaHT project, addresses the matched-control dilemma and supports accurate variant classification via cross-tissue VAF gradients. Integrating these established pipelines with multiomics modalities, including transcriptomic and epigenetic data, could advance the field toward a functional understanding of how the somatic genome impacts human brain health and disease.

Humans↗

PubMed2026

The present and future of nonviral delivery-based genome editing for hereditary hearing loss.

PURPOSE OF REVIEW: This review summarizes nonviral genome-editing delivery platforms for hereditary hearing loss, focusing on lipid nanoparticles (LNPs) and engineered virus-like particles (eVLPs), and discusses their advantages over adeno-associated virus-based delivery, as well as the barriers to clinical translation. RECENT FINDINGS: Recent advances have established LNPs as a clinically advanced nonviral platform, although challenges related to inner ear biodistribution, cell type specificity, endosomal escape, and immunogenicity remain to be addressed. In parallel, eVLPs have undergone substantial technical evolution, progressing from early low efficiency systems to advanced base editor- and prime editor-eVLP architectures that enhance cargo loading and editing efficiency. Extracellular vesicle-based genome editing has also emerged as an additional platform, although issues related to reproducibility, loading efficiency, and scalability remain major hurdles. SUMMARY: Nonviral genome editing platforms expand the therapeutic toolkit for hereditary hearing loss by enabling transient delivery of genome editors with potential safety advantages. Future efforts should focus on characterizing biodistribution and immunogenicity, refining cell type-specific tropism, and establishing scalable manufacturing processes to enable successful clinical translation.

Humans↗

PubMed2026

Machine learning-ready genomic biomarkers: ATF3 polymorphisms predict postoperative analgesic demand through AI-compatible phenotyping.

PURPOSE: To determine whether ATF3 polymorphisms can serve as genetic biomarkers for machine learning-based precision analgesia by establishing a genotype-phenotype association suitable for predictive modeling of postoperative opioid requirements. METHODS: In a prospective cohort of 167 adults undergoing abdominal surgery, ATF3 SNPs rs3122721 and rs3125293 were genotyped. A structured dataset architecture was developed to represent genetic profiles as input features for supervised learning models, enabling translational analysis of genotype‑dependent opioid consumption over 72 h. RESULTS: Patients with homozygous genotypes of the ATF3 SNPs had significantly higher opioid requirements than non‑carriers, despite reporting similar subjective pain scores. This consistent genotype‑dependent pattern provided a clinically relevant phenotype suitable for integration into predictive algorithms. CONCLUSION: ATF3 genotyping offers a promising biomarker for computationally informed precision analgesia. By linking genomic variability to clinically meaningful outcomes within a structured clinical and genomic framework, this approach supports the future development of risk-stratified clinical decision-support systems to optimize postoperative pain management.Trial registration ChiCTR1900021991, registered 30 April 2019. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1007/s13755-026-00480-9.

ATF3↗

PubMed2026

Insights into the regulation of the HOTAIR proximal promoter.

HOTAIR (HOX transcript antisense RNA) is a HOXC-cluster long intervening non-coding RNA (lincRNA) whose cancer relevance is tightly coupled to how its transcription is wired into hormone, hypoxia, inflammatory, and developmental signaling. HOTAIR is known to associate with cancer cell proliferation, motility, tumor invasion, and metastasis. The present mini-review focuses on the regulatory architecture and mechanistic complexity of HOTAIR transcriptional regulation, with emphasis on three organizing principles. First, we consider the impact of promoter choice between a canonical proximal promoter (P1), which supports the 2.2-2.4 kb transcript, and an alternative upstream promoter/TSS (P2), which contributes to context-dependent transcription initiation. Second, we examine the long-distance enhancer-promoter communication between HOTAIR distal enhancer and P1/P2. Third, we summarize the recent epigenetic and epi-transcriptomic mechanisms involved in HOTAIR transcript initiation and elongation. A combination of these events determines isoform-specific transcription to govern cell-type-, context-, and cancer specific modulation of HOTAIR expression that promotes tumor formation and cancer progression. Finally, the review proposes how large-scale RNA datasets, long-read sequencing, and isoform-specific studies can refine our understanding of this versatile lincRNA's regulation.

Humans↗

PubMed2026

Acetazolamide to prevent ventilatory drive withdrawal in REM sleep apnoea: a randomised controlled trial.

BACKGROUND: Obstructive sleep apnoea (OSA) pathogenesis during rapid-eye movement (REM) sleep has been linked to dips in ventilatory drive and downstream genioglossus hypotonia. The carbonic anhydrase inhibitor acetazolamide is known to increase ventilatory drive and improve OSA severity. Therefore, we tested the effect of acetazolamide on REM-predominant OSA severity (apnoea hypopnoea index (AHI) and hypoxic burden, co-primary outcomes) and underlying physiological mechanisms (ventilatory drive, ventilation and pharyngeal muscle activity). METHODS: 11 participants with REM-predominant OSA per baseline polysomnography (REM AHI/non-REM AHI≥2) were allocated to receiving acetazolamide 500 mg for three nights (first night at half dose) or placebo according to a randomised, crossover, double-blind design. Detailed physiological polysomnography with recording of diaphragm and genioglossus electromyography was conducted after each intervention, with a 1-week washout in between. RESULTS: As hypothesised, acetazolamide reduced AHI by 35.5% (95% CI 23.1% to 46.3%) and hypoxic burden by 35.9% (95% CI 21.1% to 48.4%) vs placebo (p<0.001), meeting the primary endpoint. Mechanistic analysis in REM revealed that, unexpectedly, acetazolamide did not mitigate dips in ventilatory drive versus placebo (first decile (+0.1 (-1.0 to 1.3) L/min, p=0.8). Rather, acetazolamide reduced collapsibility (increased ventilation at eupneic drive: +1.4 (1.2 to 1.8) L/min) and raised muscle responsiveness (ventilation vs drive slope: +32 (25 to 41) %ventilation/drive, p<0.001; genioglossus versus drive slope: +0.33 (0.13 to 0.54) %max/(L/min), p=0.001). CONCLUSIONS: Acetazolamide modestly improved REM OSA, with meaningful improvements in upper airway physiology, but failed to mitigate the dips in ventilatory drive responsible for REM OSA. TRIAL REGISTRATION NUMBER: NCT05589792.

Humans↗

PubMed2026

Comparative safety of lipid-lowering drugs alone or in combination: insights from a systematic review and network meta-analysis.

BACKGROUND AND AIMS: Although the safety profile of lipid-lowering therapies (LLTs) is known, there are no comprehensive comparative assessments. We aimed to compare the risk of muscle-related events, diabetes, liver dysfunction, and cognitive disorders among LLTs through a network meta-analysis. METHODS AND RESULTS: Databases were searched from inception to May 2025. Eligible studies included adult patients, using statins, ezetimibe, PCSK9 monoclonal antibodies (PCSK9mAbs), inclisiran, bempedoic acid, or their combinations as intervention, reporting the information about any of the selected adverse events, a total sample size of ≥200 subjects, and had ≥1 month of intervention. Pooled estimates were assessed by fixed effects model within a frequentist setting. Pooled relative risks (RR) and their 95% confidence interval were estimated. A total of 303,397 subjects from 153 RCTs were included. Bempedoic acid ranked the lowest risk of myalgia (vs PCSK9mAbs, RR 0.80 [0.69, 0.93]). PCSK9mAbs were associated with lower incidence of creatine kinase (CK) elevation, diabetes, and liver dysfunction comparing to statins (statins vs PCSK9mAbs, RR 1.44 [1.14, 1.81], RR 1.13 [1.05, 1.22], and RR 1.38 [1.17, 1.62], respectively). In terms of muscle-related events and cognitive disorders, no significant risk differences were found among treatments and their combinations. CONCLUSIONS: PCSK9mAbs appear to have a more favourable safety profile regarding the risk of CK elevation, diabetes, and liver dysfunction. Bempedoic acid seem to be a better choice for subjects with high risk of myalgia. This information can be valuable when selecting therapy for specific patient subgroups at higher risk of certain adverse events.

Humans↗

PubMed2026

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↗

PubMed2026

Cross-species variant-to-function analyses implicate MEIS1 in conferring sleep abnormalities and impaired cerebellar development.

Genome-wide association studies (GWAS) have identified numerous loci for insomnia, yet functional validation of effector genes remains limited because most risk variants lie in noncoding regions, and the true causal gene is not known. Here, we use prior human cell-based variant-to-gene mapping to nominate six insomnia effector genes and test them in zebrafish, a tractable diurnal vertebrate model well suited for sleep phenotyping. Our CRISPR-based behavioral screening identifies the MEIS1 ortholog, meis1b, as a regulator of sleep maintenance, with crispants displaying impaired nighttime-specific sleep maintenance and increased sleep latency. Comparative chromatin analyses reveal conserved regulatory architecture spanning the human insomnia-associated locus and selectively implicate meis1b, whereas the duplicated ohnolog meis1a was dispensable. Developmental profiling further shows that meis1b is expressed in cerebellar granule progenitors, paralleling human MEIS1 expression, and that its disruption impairs cerebellar development. Together, these findings establish zebrafish as an efficient vertebrate platform for functional interrogation of GWAS candidates and support an evolutionarily conserved cerebellar role for MEIS1 in sleep maintenance.

Animals↗

PubMed2026

Ramu stunt virus genome reveals previously unreported segments and nucleocapsid domain duplication in Mechlorovirus.

Ramu stunt virus (RmSV), a member of the genus Mechlorovirus within the family Phenuiviridae, was previously described as a six-segmented RNA virus infecting sugarcane. In this study, we re-examined type material and additional isolates using high-throughput sequencing and RT-PCR validation, revealing that RmSV possesses a nine-segmented genome, making it the largest reported in the Phenuiviridae. This expanded architecture includes duplicated RNA segments (RNA 2a and RNA 2b) encoding nucleocapsid-like proteins and two novel segments (RNA 7 and RNA 8). Comparative analysis showed that RNA 2a and 2b share about 84% amino acid identity, while RNA 5 encodes a third nucleocapsid homolog, indicating unprecedented domain redundancy. Structural modeling confirmed that all three nucleocapsid proteins maintain a conserved fold despite low sequence identity, with electrostatic mapping suggesting differential RNA-binding potential. Additionally, RNA 6 encodes a hypothetical protein structurally similar to the rice stripe virus disease-specific S-protein, implicating a role in symptom development. Transcript abundance analysis revealed RNA 6 as the most highly expressed segment across isolates. These findings revise the genomic composition of RmSV, highlight mechanisms of genome plasticity and adaptive evolution in plant-infecting bunyaviruses, and underscore practical implications for diagnostic assay design, resistance breeding, and biosecurity surveillance.

Genome, Viral↗

PubMed2026

Integrated multi-omics analyses identify an RAS-SLC11A2-associated molecular framework linking iron metabolism with PCOS-related cardiometabolic risk.

INTRODUCTION: PCOS is a common endocrine disorder with elevated cardiometabolic risk, yet the role of the renin-angiotensin system (RAS)-iron metabolism axis in this comorbidity remains unclear. We explored its underlying mechanisms and evaluated the therapeutic potential of gentiopicroside. METHODS: Integrated multi-omics analyses combining transcriptomics, single-cell RNA sequencing, Mendelian randomization, machine learning, molecular docking, and in vitro functional assays were performed to identify shared molecular pathways and therapeutic targets across PCOS, hypertension, NAFLD, and T2DM. RESULTS: SLC11A2 was consistently dysregulated in PCOS transcriptomic datasets, and associated with iron metabolism, inflammatory response and oxidative stress pathways. Genetic analyses validated RAS-related regulation in hypertension susceptibility and revealed shared genetic architecture between PCOS and cardiometabolic traits. Network and single-cell analyses characterized SLC11A2-associated molecular patterns in disease-relevant cell types; machine learning identified disease-classifying molecular signatures. Gentiopicroside alleviated inflammatory and oxidative stress phenotypes, including reduced IL-6 expression and reactive oxygen species accumulation. CONCLUSION: This study defines an RAS-SLC11A2 molecular framework linking iron metabolism dysregulation to PCOS-related cardiometabolic risk, elucidating the mechanisms connecting ovarian dysfunction, inflammation, oxidative stress and hypertension, and supports gentiopicroside as a promising therapeutic candidate.

Humans↗

PubMed2026

Efficacy and Safety of Bimagrumab in Adults With Obesity and Metabolic Dysfunction: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

AIMS: This study aims to systematically evaluate the efficacy of bimagrumab on body composition and glucose parameters in adults with obesity and metabolic dysfunction and its safety profile. METHODS: We searched MEDLINE, PubMed, Embase, and the Cochrane Library on April 20, 2026, for randomized controlled trials (RCTs) assessing bimagrumab treatment in adults with obesity, insulin resistance, or type 2 diabetes mellitus (T2DM). The risk of bias was assessed using the Cochrane Risk of Bias tool (RoB 2), and meta-analyses of efficacy and safety data were conducted using R software. The Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) system was used to assess the strength of evidence. The study was registered with PROSPERO (CRD420261377110). RESULTS: Of the 134 retrieved records, 4 RCTs (enrolling 268 participants) were included. The included population represented a broad spectrum of metabolic dysfunction, from obesity and nondiabetic insulin resistance to established T2DM. Compared with placebo, bimagrumab treatment significantly reduced total weight (mean difference [MD] -4.85 kg, 95% confidence interval [CI] -6.82 to -2.88), fat mass (-4.72 kg [-8.05 to -1.40]), and glycated haemoglobin (HbA1c) (-0.13% [-0.23 to -0.03]) and significantly increased total lean mass (1.66 kg [0.81 to 2.51]). However, bimagrumab led to an increase in low-density lipoprotein (LDL) concentrations of 0.47 mmol/L [0.03 to 0.91] and significantly increased incidences of discontinuation (risk ratio [RR] 5.75 [1.61 to 20.46]), muscle spasms (RR 10.44 [4.23 to 25.75]), and diarrhoea (RR 4.91 [2.38 to 10.11]). CONCLUSION: Bimagrumab effectively reversed adverse effects on body composition in obese individuals, resulting in significant fat reduction, increased skeletal muscle mass, and improved glycemic control, suggesting that bimagrumab is a promising new target for personalized metabolic therapy.

Humans↗

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↗