Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “structural features”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

440 recordsLinked to original sources
PubMed2026

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

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

Volatile Organic Compounds↗
PubMed2026

Metabolomic and structural signatures of pigmented and non-pigmented Himalayan rice landraces.

BACKGROUND: This study investigated the anti-oxidant properties, starch composition, pasting behavior, structural properties, textural properties and non-targeted metabolomic profiles of pigmented and non-pigmented rice landraces as potential next-generation functional food ingredients. RESULTS: Pigmented rice demonstrated 1.34 times more anti-oxidant activity as compared to non-pigmented rice. Pigmented landraces showcased superior nutritional and functional attributes, including higher total dietary fiber and starch content. Fourier-transform infrared (FTIR) analysis revealed distinct molecular signatures with enhanced peak transmittance, while X-ray diffraction (XRD) indicated greater crystallinity ranging from 36-44.3% in pigmented rice compared with 30-40% in non-pigmented rice, suggesting improved digestibility and processing versatility. Pigmented rice recorded less amylose content hence tended to possess increased adhesiveness values whereas non-pigmented rice revealed greater amylose content hence was coupled with greater hardness values. Field-emission scanning electron microscopy (FE-SEM) images revealed that pigmented rice had densely packed and polygonal starch granules whereas non-pigmented rice had loosely packed starch granules with intergranular voids. Untargeted gas chromatography-mass spectrometry (GC-MS) profiling identified 84 metabolites, including unique compounds such as 3,3-dimethylbutanol and ethanoic acid, along with shared metabolites such as sucrose and linoleic acid, highlighting notable biochemical diversity. Multivariate statistical analyses using principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway mapping further differentiated the metabolomic landscapes, with variable importance in the projection (VIP) scores identifying key bioactive contributors. CONCLUSION: Pigmented rice landraces exhibited significant functional and nutritional advantages, making them promising candidates for functional food development and nutritional improvement programs. These findings support their potential role in advancing sustainable and health-oriented food systems. © 2026 Society of Chemical Industry.

Oryza↗
PubMed2026

Age-dependent reorganization of behavioral and striatal function in Cntnap2 knockout mice.

Autism spectrum disorder (ASD) is characterized by persistent deficits in social communication and the presence of restricted and repetitive behaviors. While ASD has a neurodevelopmental origin, it remains a lifelong condition, yet little is known about how its behavioral and neural features evolve across adulthood. Here, we investigated behavioral, synaptic, and structural alterations across the transition from early to mature adulthood in Cntnap2 knockout mice, a widely used model of ASD. Using a longitudinal behavioral approach combined with electrophysiological recordings and morphological analysis, we show that KO mice exhibit increased stereotyped and repetitive behaviors and reduced exploratory activity at both ages. However, detailed analysis of behavioral patterns revealed age-dependent differences, with early adult KO mice displaying increased behavioral persistence that later evolved into distinct patterns of behavioral sequences. These behavioral changes were associated with alterations in inhibitory synaptic transmission in the dorsolateral striatum (DLS), including changes in spontaneous inhibitory postsynaptic current (sIPSC) frequency and temporal structure. In parallel, mature adult KO mice showed structural remodeling of spiny projection neurons, characterized by increased distal dendritic arborization and age-dependent organization of dendritic spines. Together, our findings demonstrate that ASD-related alterations are not static but evolve across adulthood, revealing a multi-level reorganization of behavioral, synaptic, and structural features. These results highlight the importance of considering adulthood stages in ASD and provide new insights into the dynamic nature of the condition.

Animals↗
PubMed2026

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↗
PubMed2026

SGLF-Net:Staged Global-to-Local Cross-Scale Fusion Network for Colonoscopic Polyp Segmentation.

Polyp segmentation in colonoscopy images plays a pivotal role in computer-aided medical diagnosis and the early prevention of colorectal cancer. However, existing methods often suffer from performance degradation when confronted with extreme polyp scale variation and polyp boundary ambiguity. To address these challenges, we propose the Staged Global-to-Local Cross-Scale Fusion Network (SGLF-Net), which adopts a novel staged global-to-local learning paradigm to progressively refine segmentation from coarse global semantics to fine-grained local details. Specifically, the Global Semantic Perception Stage integrates a Swin Transformer Encoder and a Dynamic Attentive Decoder (DAD) to construct comprehensive multi-scale contextual representations. The Local Detail Refinement Stage employs an Edge-aware Dynamic Attentive Decoder (E-DAD) to enhance structural fidelity and boundary precision through explicit edge-guided supervision. Furthermore, we introduce the Cross Spatial-Scale Feature Aggregation and Reconstitution (CSSAR) module, equipped with hybrid attention mechanisms, to facilitate efficient semantic structural interaction between the two cascaded stages. Extensive experiments on five public benchmark datasets demonstrate that SGLF-Net consistently outperforms state-of-the-art methods in both segmentation accuracy and boundary preservation.

Journal Article↗
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

Genome-wide characterization of heat shock protein genes reveals thermal stress-responsive candidates in Litopenaeus vannamei.

Heat shock proteins (HSPs) are conserved molecular chaperones involved in protein folding, refolding, aggregation prevention, and degradation of damaged proteins. However, the genomic organization and thermal responsiveness of HSP genes in the Pacific white shrimp (Litopenaeus vannamei) remain incompletely understood. Here, we performed a genome-wide analysis of the HSP gene family and examined its phylogenetic relationships, structural features, duplication patterns, sequence variation, interaction networks, and transcriptional responses to acute heat stress. A total of 34 HSP genes were identified and classified into the HSP90, HSP70, HSP40/DNAJ, HSP60, and small HSP families. Phylogenetic, motif, gene structure, synteny, and subcellular localization analyses revealed evolutionary conservation and structural diversification among family members. Three duplicated gene pairs were identified, comprising two segmental duplications and one tandem duplication. All pairs exhibited Ka/Ks ratios below 1, consistent with purifying selection of varying strength. Sequence analysis identified 295 nonsynonymous single-nucleotide polymorphisms, of which 12 were consistently predicted to be deleterious by multiple algorithms. Protein-protein interaction analysis indicated enrichment of protein-folding and cellular stress-response functions. RT-qPCR analysis showed significant induction of HSPA4, HSP90AA1, TRAP1, BiP, and DNAJA1 after 6, 12, and 24 h of exposure to 34 °C, whereas DNAJC3 was significantly induced only at 12 h. All six genes reached their highest transcript abundance at 12 h. These findings may provide a genomic framework for HSP genes in L. vannamei and identify candidate genes and variants associated with thermal stress responses.

Animals↗
PubMed2026

A mechanism-guided framework for prioritizing membrane-interaction anti-Vibrio peptides from peptidomics data.

A mechanism-guided framework for prioritizing membrane-interaction antimicrobial peptide candidates from proteomics-derived peptide mixtures is presented. The framework integrates conservative machine-learning-based antimicrobial peptide (AMP) screening with a literature-derived membrane-interaction plausibility (MAP) assessment and a data-driven membrane-interaction ranking function (AIPx), followed by structural visualization for interpretability. MAP encodes physicochemical characteristics commonly associated with peptide-membrane interaction and provides a graded plausibility assessment. Building upon this physicochemically interpretable framework, AIPx ranks peptides using feature weights calibrated from experimentally characterized anti-Vibrio peptides, where minimum inhibitory concentration (MIC) values are used as a coarse-grained ranking reference rather than a direct prediction target. In a peptidomics-based peptide fractionation study targeting Vibrio spp., AIPx exhibited a consistent relationship with experimentally observed antibacterial activity. Distributional analysis revealed that peptide fractions exhibiting high anti-Vibrio activity are characterized by enrichment of high-ranking peptides rather than by AMP abundance alone. By structuring AMP identification and prioritization as sequential stages, the MAP + AIPx framework enables interpretable and experimentally actionable candidate selection by reducing biologically implausible candidates. The framework facilitates species-oriented prioritization of AMP candidates, addressing a key challenge in antimicrobial peptide discovery where activity may depend on target-specific membrane characteristics. Moreover, the approach is extensible through species-specific calibration and supports interpretable, mechanism-informed prioritization in antimicrobial peptide discovery.

Proteomics↗
PubMed2026

Diagnosis, treatment and monitoring of pediatric Behçet's disease: Systematic literature review informing the ISSAID/PRES recommendations.

BACKGROUND: Pediatric-onset Behçet's disease (BD) accounts for up to 20% of cases and represents a distinct clinical entity characterized by evolving phenotypes and age-specific patterns of organ involvement. This systematic literature review synthesizes current evidence on pediatric BD, informing forthcoming recommendations by the International Society of Systemic Auto-Inflammatory Diseases (ISSAID) and the Pediatric Rheumatology European Society (PReS). METHODS: A systematic search was conducted according to PRISMA guidelines. Observational studies reporting clinical features, diagnostic criteria, management strategies, and outcomes in BD patients diagnosed before the age of 16 years were included. Proportional meta-analysis was performed to give pooled estimates for organ system involvement. RESULTS: Fifty-two studies, encompassing 2929 patients, met inclusion criteria. Sex distribution was balanced, with a 1:1 male-to-female ratio. The age of onset differed, with 1 year old being the lowest median age of onset and 2 years the lowest median age of diagnosis. The pooled random-effects estimate demonstrated that 50% of patients were HLA-B51 positive (95% CI, 0.5-0.6). Mucocutaneous manifestations were nearly universal (97.8%) and frequently represented the initial feature (80.9%). Musculoskeletal (36%), ocular (35%), neurological (17.9%), gastrointestinal (20%), vascular (15.4%) manifestations showed substantial variability in prevalence. Therapeutic approaches varied widely and were extrapolated from adult practice, with treatment guided by organ involvement and severity. CONCLUSIONS: Pediatric BD encompasses a heterogeneous spectrum of phenotypes requiring harmonized diagnostic frameworks, structured phenotypic stratification, and standardized monitoring to improve long-term outcomes. The relative burden and combination of organ manifestations varied across cohorts, reflecting both biological heterogeneity and differences in study design.

Humans↗
PubMed2026

Complexity in disguise: a systematic review of fractal analysis in psychiatric neuroimaging.

OBJECTIVES: Psychiatric diagnosis and fractal studies are complex processes that extend beyond clinical evaluation and require careful methodological considerations in neuroimaging. Over the years, fractals have helped reduce these complexities in research, but they still cannot grant clinical diagnoses. Thus, the main objective was a systematic review exploring the potential applications of fractal analysis in characterizing psychiatric conditions through neuroimaging techniques-including both functional and structural MRI. MATERIALS AND METHODS: A systematic literature review was conducted on PubMed, identifying thirty-nine original studies that met the inclusion criteria. Areas showing statistical significance (p&#x2009;<&#x2009;0.05) were reported. These studies were categorized according to DSM-V classification and examined for the description of psychiatric conditions through the fractal analysis. RESULTS: The review primarily focuses on young adults with psychiatric conditions compared to control groups. Schizophrenia and Autism Spectrum Disorder are major areas of investigation, and fractal dimension (FD) is the primary analysis method used to reflect brain patterns. Studies that calculated whole-brain FD may have underestimated local abnormalities due to the inclusion of a high percentage of tissue, potentially resulting in overlooked findings. Notably, abnormalities in the frontal cortex represent a common neurobiological feature across several psychiatric conditions. CONCLUSIONS: The findings from this systematic review shed light on the use of fractal analysis to quantify complex brain patterns in both psychiatric patients and healthy individuals. However, it is essential to recognize the need for further research to elucidate a fractal analysis protocol that allows for optimal extraction of psychiatric insights. KEY POINTS: Question Fractal analysis applied to structural and functional MRI help characterize brain alterations across psychiatric conditions. Findings This review shows consistent fractal patterns across multiple psychiatric disorders, especially in frontal regions. Despite heterogeneous methodologies, results highlight shared structural and functional abnormalities. Clinical relevance Fractal analysis may offer complementary characterization of subtle brain organization across psychiatric disorders. Its potential clinical utility-such as improving diagnostic characterization, earlier detection, among others-remains limited by the current absence of a standardized protocol.

Humans↗
PubMed2026

Regional genomic analysis of lineage distribution and transferable multidrug resistance among chicken-associated Salmonella Kentucky isolates in China.

Salmonella enterica serovar Kentucky is an important multidrug-resistant foodborne pathogen in the poultry meat supply chain. Although recent broader genomic studies have elucidated the population structure and epidemiological significance of major lineages in China (e.g., ST198 and ST314), the regional dynamics within local poultry supply chains remain insufficiently characterized. In this study, 31 chicken meat-derived isolates from Shanghai and 39 publicly available genomes from China were analyzed using antimicrobial susceptibility testing, whole-genome sequencing, phylogenetic analysis, conjugation experiments, and complete sequencing of representative plasmids. This enabled a systematic characterization of the molecular epidemiological features of the population and the mechanisms underlying resistance dissemination. Population genomic analysis revealed a lineage composition markedly different from the global epidemiological pattern: ST314 was the predominant sequence type among the Shanghai chicken-derived isolates (74.2%), whereas the internationally recognized high-risk clone ST198 accounted for only 25.8% of the local isolates. However, risk stratification analysis indicated that although ST198 was detected less frequently, it carried a significantly greater burden of acquired resistance genes and therefore represented a higher-risk resistant lineage. Functional and structural validation further elucidated the molecular basis of resistance dissemination within this high-risk lineage. Conjugation experiments confirmed the co-transfer of a multidrug resistance module carrying blaTEM-1 and blaCTX-M-267 to the recipient strain Escherichia coli J53. Complete plasmid analysis revealed that these two &#x3b2;-lactam resistance genes were co-localized on a 242-kb transferable plasmid flanked by Tn1331, Tn3, and multiple transposase-associated elements, thereby providing a structural basis for their horizontal transfer. This study provides important molecular epidemiological evidence for lineage-specific surveillance and risk-stratified control of resistant Salmonella in the poultry meat supply chain and further underscores the need for continuous monitoring of mobile genetic elements within a One Health framework.

Animals↗
PubMed2026

Active Site Assembly by SMG5 as a Mechanism for SMG6 Endonuclease Licencing in Nonsense-mediated mRNA Decay.

Nonsense-mediated mRNA decay (NMD) is a conserved eukaryotic surveillance pathway that eliminates transcripts containing premature termination codons (PTCs). Substantial progress has been made in defining the transcript features that mark aberrant translation termination for NMD activation, yet key mechanistic steps remain incompletely understood - including how recruitment of the central NMD factor UPF1 is coupled to the downstream effector phase in which targeted mRNAs are nucleolytically degraded. In metazoans, NMD employs an endonucleolytic route mediated by SMG6, a PIN-domain nuclease, alongside SMG5 and SMG7, which act downstream of PTC recognition. SMG5 has recently been proposed to licence SMG6 activity, yet the molecular basis of this licencing has remained elusive. Here, we combine AlphaFold structural predictions with biochemical assays to investigate interactions among human SMG5, SMG6, and SMG7. Structural models predict a high-confidence interface between SMG5 and SMG6 PIN domains that forms a composite active site: a conserved SMG5 aspartate (D893) complements the SMG6 acidic triad to reinstate the canonical tetrad required for PIN-domain catalysis. In vitro, SMG6 alone exhibits weak endonucleolytic activity, which is enhanced &#x223c;10-fold by the SMG5 PIN domain. Mutational analyses confirm that conserved residues from both proteins are essential for this composite configuration. Our findings reveal that the SMG5 PIN domain, previously considered catalytically inert, plays a critical role in activating SMG6 by completing its active site. This work provides mechanistic insight into the SMG5-dependent licencing step and uncovers a composite PIN nuclease architecture at the heart of the metazoan NMD effector phase.

Nonsense Mediated mRNA Decay↗
PubMed2026

Vestibular schwannoma associated normal pressure hydrocephalus: clinical features and shunt responsiveness compared with idiopathic NPH.

BACKGROUND: Vestibular schwannoma (VS) is commonly associated with obstructive hydrocephalus due to mass effect; however, a rarer communicating form resembling normal pressure hydrocephalus (NPH) has also been described, possibly related to impaired CSF absorption from elevated CSF protein. We aimed to characterize the clinical and imaging features of VS-associated NPH (VS-NPH) and compare them with those of an idiopathic NPH (iNPH) cohort. METHODS: We retrospectively analyzed 18 patients with VS-NPH identified between 2008 and 2024. For comparison, 41 iNPH patients were drawn from a prospective longitudinal study at our center. Variables included demographics, tumor size, VS treatment modality, CSF parameters, Radscale imaging features, and shunt responsiveness. RESULTS: VS-NPH patients had markedly higher CSF protein levels than patients with iNPH (median 100 vs. 51&#xa0;mg/dL, p&#xa0;<&#xa0;0.001). Radiological features largely overlapped; however, parasagittal sulcal narrowing was more frequent in VS-NPH (61&#xa0;% vs.13&#xa0;%, p&#xa0;=&#xa0;0.002). These differences remained significant in the sensitivity analysis excluding the two patients without gait impairment. VS-NPH patients were younger in the primary analysis (66.8 vs. 72.0&#xa0;years, p&#xa0;=&#xa0;0.03), while exploratory associations between larger tumor size and both earlier NPH symptom onset (r&#xa0;=&#xa0;-0.48, p&#xa0;=&#xa0;0.049) and smaller callosal angle (r&#xa0;=&#xa0;-0.49, p&#xa0;=&#xa0;0.048) attenuated to non-significant trends in the sensitivity analysis. Tumor size was&#xa0;<&#xa0;30&#xa0;mm in 89&#xa0;% of patients. Ventriculoperitoneal shunt (VPS) resulted in clinical improvement in both groups, although response rates were numerically lower in VS-NPH than in iNPH (63&#xa0;% vs.75&#xa0;%). CTT was positive in 9 of 11 VS-NPH patients who underwent testing, although improvement after shunting also occurred in patients with negative CTT results or without prior CTT. CONCLUSIONS: VS-NPH may represent a secondary subtype of NPH with distinct biochemical and subtle imaging features. Elevated CSF protein may contribute to altered CSF dynamics. These findings are exploratory and require confirmation in larger prospective studies.

Humans↗
PubMed2026

Lipid metabolism is a key central, systemic and gut microbial feature of the decline in rat hippocampal function during middle age.

Middle age is emerging as a turning point in brain ageing, prognostic of future cognitive health and amenable to intervention. Metabolic and proteomic differences during this period are not yet fully understood and may potentially influence functions of the hippocampus, a brain area that regulates memory and anxiety. While the gut microbiota is implicated in brain ageing, the relationship between the gut microbiota, the metabolic state, and hippocampal proteome in middle age has not been investigated. We hypothesise that peripheral metabolic or protein features are associated with hippocampal vulnerability in middle age. Therefore, young adult and middle-aged rats were assessed for behavioural, proteomic, metabolic, and gut microbiota differences. Proteomic profiling of the hippocampus revealed differential expression of proteins indicative of altered synaptic signalling. Concurrently, adult hippocampal neurogenesis was decreased in middle age. Hippocampal microglia exhibited a lipid rich, inflammatory phenotype in middle age which correlated with poorer memory performance. CSF and serum proteomic and metabolomic analyses identified dysregulated lipid-related pathways potentially contributing to hippocampal vulnerability in middle age. Furthermore, 16S rRNA sequencing revealed reduced abundance of bacteria involved in lipid metabolism regulation. However, faecal microbiota transfer from young to middle aged rats was not sufficient to robustly improve hippocampus-dependent spatial memory. Together, these findings highlight dysfunctional lipid metabolism as a key feature of middle age that may contribute to decline in hippocampal function. Given that the scope for intervention is limited during older age, targeting biomarkers involved in metabolic and lipid homeostasis may be pivotal for the development of pharmacological or lifestyle-based interventions during middle age which could ultimately delay future cognitive ageing.

Animals↗
PubMed2026

User Engagement and Feature Preferences in an AI-Powered mHealth Intervention for Diabetes Prevention: Secondary Analysis of a Randomized Controlled Trial.

BACKGROUND: Prediabetes is highly prevalent and increasing globally, yet lifestyle interventions remain underused. AI-driven mobile health (mHealth) tools can help scale diabetes prevention efforts, but the key factors driving their success are not well understood. OBJECTIVE: This post hoc secondary analysis of a randomized controlled trial (RCT) aimed to characterize the most valued features and the role of user engagement in outcomes of a fully automated mHealth intervention for diabetes prevention. METHODS: Data from 151 participants with prediabetes and overweight or obesity who were assigned to an AI-based diabetes prevention program (Sweetch) in a parent RCT (NCT05056376) were analyzed. Engagement (defined as the total number of days the app was used) was categorized into tertiles (low, medium, and high). Baseline characteristics were compared across engagement groups using ANOVA, Kruskal-Wallis, and chi-square tests, and regression models assessed the association between engagement and achievement of diabetes risk reduction outcomes (&#x2265;5% weight loss, &#x2265;4% weight loss with &#x2265;150 min/week of physical activity, or &#x2265;0.2 percentage point reduction in hemoglobin A1c [HbA1c] at 12 months). Perceived usefulness of intervention features was surveyed at 12 months. RESULTS: Median engagement was 98 (IQR 34-232) days. Older age (P<.001) and lower baseline BMI (P=.04) were significantly associated with higher engagement. Compared with low engagement, high engagement was associated with greater odds of achieving the composite diabetes risk reduction outcome (odds ratio [OR] 2.59, 95% CI 1.11-6.01; P=.03), &#x2265;5% weight loss (OR 3.31, 95% CI 1.16-9.42; P=.03), and &#x2265;0.2 percentage point reduction in HbA1c (OR 3.57, 95% CI 1.19-10.75; P=.02). Participants most frequently rated weight tracking, physical activity tracking, and the digital body weight scale as the features that were most helpful for achieving their health goals. CONCLUSIONS: Higher engagement with an AI-driven intervention requiring no human intervention was associated with improved diabetes risk reduction. Contrary to concerns about lower digital literacy, older adults engaged with the intervention more than younger adults. Features related to weight and physical activity tracking were most valued by patients in the program. TRIAL REGISTRATION: ClinicalTrials.gov NCT05056376; https://clinicaltrials.gov/study/NCT05056376.

Humans↗
PubMed2026

Investigating telomere length and hTERT-MNS16A VNTR polymorphism in Bipolar disorder: Insights into clinical features.

OBJECTIVE: To compare leukocyte telomere length (LTL; T/S ratio) and hTERT-MNS16A VNTR polymorphism between patients with bipolar disorder (BD) and healthy controls, and to examine their associations with clinical features in BD. METHODS: A total of 179 participants (100 BD patients, 79 healthy controls) were enrolled. Relative LTL was assessed by qPCR-based T/S ratio; hTERT-MNS16A VNTR genotyping by PCR and gel electrophoresis. Clinical variables including episode frequency, illness duration, age at onset, symptom severity scales, first episode polarity, and family history of mood disorder were evaluated. RESULTS: No significant differences were observed between BD patients and healthy controls in T/S ratio or hTERT-MNS16A VNTR genotype distributions (all p > 0.05). Within the BD group, S allele carriers (L/S or S/S) had significantly more depressive episodes than L/L homozygotes (1.45 &#xb1; 2.58 vs. 0.61 &#xb1; 1.52; p = .040). Significant inverse correlations were identified between T/S ratio and depressive episode count (&#x3c1; = -0.220, p = .028) and total mood episodes (&#x3c1; = -0.207, p = .039). Multivariable negative binomial regression revealed four independent predictors of depressive episode frequency: lower T/S ratio (p = 0.005), S allele carriage (L/S or S/S genotypes) (p = 0.001), first depressive episode polarity (p < 0.001), and family history of mood disorder (p = 0.035). CONCLUSION: Although LTL and hTERT-MNS16A VNTR genotype did not differ between BD patients and healthy controls, shorter telomere length and S allele carriage were independently associated with higher depressive episode frequency within the BD group, implicating telomere biology and hTERT genetic variation in the biological substrate of depressive illness burden.

Humans↗