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Mechanisms linking the gut microbiota to colorectal cancer development and progression.

Colorectal cancer remains a leading cause of global cancer mortality, with a concerning rise in early-onset cases driven by complex interactions between environmental exposures, lifestyle factors, and host genetics. Mounting evidence indicates that gut microbiota dysbiosis critically modulates this oncogenic process, acting as an active participant rather than a passive bystander. This review systematically synthesizes the dichotomous roles of the intestinal microbiome in colorectal tumorigenesis through the conceptual framework of the driver-passenger model. We discuss how early initiating driver bacteria, such as Polyketide synthase-positive Escherichia coli and enterotoxigenic Bacteroides fragilis, compromise mucosal barriers, induce chronic mucosal inflammation, and inflict direct genomic instability. As the local tumor microenvironment undergoes profound metabolic remodeling, opportunistic passenger pathogens, notably Fusobacterium nucleatum, become enriched, further promoting cellular proliferation and facilitating tumor immune evasion. Conversely, protective commensals, exemplified by Clostridium butyricum and Streptococcus thermophilus, exert robust tumor-suppressive effects through multifaceted mechanisms. These beneficial microbes actively antagonize malignant progression by redirecting tumor metabolic fluxes toward oxidative stress, orchestrating deep epigenetic reprogramming, and degrading core oncoproteins to reverse chemoresistance. Transitioning from fundamental mechanisms to clinical application, we evaluate a comprehensive spectrum of microbiota-targeted interventions, encompassing non-invasive diagnostic biomarkers, fecal microbiota transplantation, engineered bacteria, phage therapy, and postbiotics. Finally, we critically address the formidable translational challenges associated with microbial heterogeneity, long-term safety, and regulatory standardization, aiming to provide a balanced perspective on integrating microbiome-based strategies into next-generation precision oncology for colorectal cancer.

Humans

Evolutionary architecture and lineage-specific diversification of Forkhead box transcription factors in Perna viridis.

The Forkhead box (Fox) transcription factors are evolutionarily conserved regulators of development, cell cycle, and apoptosis across metazoans. This study provides the first comprehensive genome-wide analysis of the Fox gene family in the Asian green mussel (Perna viridis). We identified 28 Fox genes distributed across 10 chromosomes. Comparative analysis reveals the absence of the FoxI, FoxQ1, FoxR and FoxS subfamily, consistent with other bivalves and indicative of lineage-specific gene loss during molluscan evolution. Notably, gene duplications in the FoxAB, FoxD, FoxH, FoxN1-4, FoxQ2 and FoxQD subfamilies may reflect functional diversification associated with environmental adaptation. Exon-intron structural variability, including intron loss in several paralogues, suggests structural diversification and potential regulatory variation. Phylogenetic reconstruction confirmed the monophyly of core Fox classes while highlighting divergent expansion patterns in lophotrochozoans. Selection analyses showed strong purifying selection across duplicated Fox paralogs, supporting functional conservation after lineage-specific expansion. Gene Ontology enrichment linked Fox genes to stress response, apoptosis, and transcriptional regulation. By integrating phylogenetic, structural, and transcriptomic analyses, this study provides a genomic framework for understanding Fox gene organisation, evolution, and tissue-associated expression patterns in Perna viridis and establishes a comparative resource for future functional studies in bivalves.

Animals

Decoding tumor immune microenvironment heterogeneity by single-cell and spatial multi-omics: From immunotherapy resistance to translational biomarkers.

Immune checkpoint blockade has transformed cancer therapy, yet primary and acquired resistance remain major clinical challenges. Increasing evidence indicates that immunotherapy resistance cannot be fully explained by tumor-intrinsic alterations or conventional biomarkers such as PD-L1 expression, tumor mutational burden, or microsatellite instability. Instead, therapeutic response is shaped by the tumor immune microenvironment (TIME) as a heterogeneous, spatially organized, and dynamically evolving ecosystem. Single-cell omics has revealed diverse immune and stromal cell states, including progenitor and terminally exhausted T cells, suppressive myeloid programs, B-cell/TLS-associated immune-reactive states, and CAF-mediated exclusion phenotypes. Spatial transcriptomics, spatial proteomics, and imaging-based approaches further demonstrate that these cell states assemble into distinct immune niches, including immune-inflamed, T-cell-excluded, myeloid-suppressive, metabolic/hypoxic, and TLS-associated niches. These spatial ecosystems determine whether antitumor immune cells can access malignant cells, receive antigen-presenting support, or become restrained by stromal, vascular, metabolic, and myeloid barriers. In this review, we summarize how single-cell and spatial multi-omics redefine TIME heterogeneity in immunotherapy resistance, highlight ligand-receptor communication networks linking cell states to spatial immune dysfunction, and discuss emerging translational biomarkers for patient stratification. We further propose that future immunotherapy biomarkers should evolve from static single-marker assays toward longitudinal, spatially resolved, and interpretable multi-omics models that guide precision combination immunotherapy.

Humans

Ancient DNA and Human Physiology.

Ancient DNA (aDNA) enables the reconstruction of chronologically sampled genomes from ancient humans, animals, plants, pathogens, and microorganisms, as well as environmental DNA, providing a record of biological changes through time. Improvements in short and degraded DNA extraction methods and low-cost sequencing now enable the generation of broad, cross-regional datasets that expand evolutionary analyses from past population demography to biological mechanisms. By tracking temporal shifts of allele frequencies, integrating functional genomics resources (e.g., gene expression, chromatin structure variation), modeling population demography to separate selection from genetic drift, and aligning genetic changes with archaeological, cultural, and climatic data, aDNA has the potential to link sequence variation to physiological function within their temporal and environmental contexts. In this review, we summarize illustrative case studies from aDNA research spanning complex traits, dietary adaptations, and responses to pathogens and other environmental changes, showing how human biology has evolved under multiple selective pressures through time. These dated signals help triage experimental work and expose mechanisms that are rare or absent in living cohorts. Although some challenges remain, such as geographic and temporal sampling disparities, limitations in data resolution and variant detection, and genotype-phenotype uncertainties, rapid methodological progress and stronger ethical frameworks are expanding what can be inferred, making aDNA a promising tool for refining physiological pathways, their timing, and their drivers.

Humans

LitCTL1: A novel C-type lectin involved in the mucosal and cellular immunity of the common periwinkle Littorinalittorea.

C-type lectins (CTLs) are vital pattern-recognition receptors (PRRs) that mediate innate immune responses in mollusks, yet their characterization in Caenogastropoda, the largest gastropod group, remains limited. This study characterizes LitCTL1, a novel secreted single-domain C-type lectin from the common periwinkle, Littorina littorea. The 199-amino acid polypeptide contains a conserved carbohydrate recognition domain with canonical QPD and WND motifs and is predicted to form a homodimer. Uniquely, LitCTL1 was localized in both circulating hemocytes and mucus-secreting epithelial cells of the foot, mantle, and hypobranchial gland - the first report of such dual localization for a molluscan lectin, linking systemic and mucosal defense. Expression analysis revealed that LitCTL1 is constitutively expressed in hemocytes. Functional assays with recombinant LitCTL1 demonstrated its role as a potent opsonin with hemagglutinating activity, significantly enhancing hemocyte spreading and the phagocytosis of zymosan. Genomic analysis reveals that LitCTL1 belongs to a rapidly diversifying, genus-specific expansion distinct from conserved perlucin-like lineages. These results identify LitCTL1 as a key effector molecule in both systemic and mucosal innate immunity, likely reflecting an evolutionary adaptation to the microbial challenges of the intertidal environment.

Animals

Distinct cell morphotypes of Aureobasidium melanogenum ZN exhibit differential functional profiles in promoting maize growth.

Black yeast-like fungi of the genus Aureobasidium exhibit morphological plasticity, but whether distinct cellular states within the same genetic background are associated with different plant growth-promoting functions remains unclear. Here, yeast-like cells (YL), swollen cells (SC), and chlamydospores (CH) of Aureobasidium melanogenum ZN were characterized. YL was associated mainly with siderophore production and laccase activity, SC with extracellular polysaccharide accumulation, and CH with phosphate mobilization and higher ammonia and IAA production. Whole-genome and comparative genomic analyses revealed a shared repertoire related to nutrient acquisition, auxin-associated metabolism, extracellular oxidation, and carbohydrate remodeling, with expansions in nutrient- and cell-surface-related gene families. Transcriptomic and metabolomic analyses showed distinct deployment of these capacities, with CH exhibiting broad reprogramming of tryptophan-associated, nitrogen, phosphate, central-carbon, and amino-acid metabolism. In maize, CH at the optimal inoculation concentration of 105 CFU·mL-1 produced the strongest growth promotion, increasing plant height, dry biomass, root length, root surface area, and root volume by 58.6%, 365.1%, 191.0%, 194.3%, and 222.4%, respectively. Consistent with this pronounced growth phenotype, maize root transcriptomics showed coordinated CH-induced responses involving root development, nutrient transport, redox regulation, and root-interface remodeling. Root-zone tracking showed greater short-term stability and persistence of CH. These findings identify cellular state as an important functional dimension of Aureobasidium-plant interactions and provide a basis for developing fungal inoculants with defined beneficial cellular states.

Zea mays

Multimodal intervention benefits: Responder analysis of J-MINT PRIME Kanagawa trial.

INTRODUCTION: The J-MINT PRIME Kanagawa trial was an 18-month multimodal intervention (incorporating exercise, nutrition, and metabolic management) for dementia prevention. Because the primary analysis showed no significant benefits, we performed an exploratory responder analysis to identify responsive subpopulations. METHODS: We analyzed the Full Analysis Set comprising 188 participants. Classification and regression tree (CART) analysis, applied to the intervention arm, identified baseline predictors of cognitive improvement. These rules were then applied to the entire cohort to evaluate treatment effects on the Mini-Mental State Examination (MMSE) using fully adjusted mixed-effects models for repeated measures (MMRM). RESULTS: CART identified a "Target Group" (N = 108) characterized by baseline profiles such as an MMSE score < 28 or specific metabolic ranges (e.g., LDL-C < 135 mg/dL). Within this target group, the intervention significantly preserved MMSE trajectories compared with the control group (group &#xd7; time interaction, P = 0.022). In contrast, the Non-Target Group (N = 80), consisting of high-functioning individuals (MMSE &#x2265; 28), exhibited no significant group &#xd7; time interaction. DISCUSSION: Multimodal interventions may effectively preserve global cognition in older adults with sub-threshold cognitive decline. Careful targeting of appropriate populations, while considering potential longitudinal measurement artifacts (e.g., practice effects), is essential. These findings provide a hypothesis-generating framework that warrants external validation in future prevention trials.

Humans

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

Efficient rDNA-mediated multi-copy integration of gene clusters in Aureobasidium melanogenum.

Aureobasidium melanogenum is a promising non-conventional yeast chassis for synthetic biology. However, techniques recombining large genetic fragments, such as gene clusters, are still unavailable, hindering further metabolic reprogramming in this chassis. To achieve multi-copy integration of genes, we employed highly repetitive ribosomal DNA (rDNA) sequences in A. melanogenum as homologous recombination sites for large genetic fragments. First, integration efficiency of three different regions of A. melanogenum rDNA were investigated: RNA polymerase I promoter region (rDNA1, 1.0&#x202f;kb), partial 26S rDNA region (rDNA2, 1.0&#x202f;kb), and RNA polymerase I terminator region (rDNA3, 1.0&#x202f;kb). Our findings revealed that the highest copy numbers and expression stability were observed for the short heterologous green fluorescent protein gene (gfp, 0.7&#x202f;kb) and the long native polyketide synthase gene (pks, 7.0&#x202f;kb) after rDNA1-mediated integration. Specifically, the copy numbers reached 7.0 and 8.0 for gfp and pks, respectively, and they remained stably expressed in the genome after 120-h subculturing. Furthermore, an 11.0&#x202f;kb gene cluster (comprising the native pks, phosphopantetheinyl transferase (npg1), and scytalone dehydratase genes (scd) responsible for melanin biosynthesis) was integrated at the rDNA1 site, resulting in stable recombination with 15.0 copies and an approximately 12-fold increase in melanin production. Overall, the convenience and efficiency of the proposed rDNA-mediated multi-copy insertion strategy will facilitate superior metabolic engineering of A. melanogenum chassis cells.

Multigene Family

Quantitative assessment of the fingerprint evidential value using machine learning.

Fingerprints as physical evidence have long supported criminal investigation and adjudication. In practice, however, fingerprint identification relies mainly on examiners' experience. Furthermore, expert opinions tend to be categorical, even though the opinions with the same conclusion could differ substantially in evidential strength. To quantitatively assess fingerprint evidential value, this study proposes a machine learning-based framework as an interpretable decision-support tool. A lightweight residual one-dimensional convolutional neural network was constructed, incorporating channel recalibration and a similarity-driven attention mechanism to learn adaptive contribution weights for different matched minutiae (minutiae for short). Controlled experiments revealed that the predicted evidential value increased with the number of minutiae and was significantly influenced by the quality of minutiae. With 10 minutiae, the mean predicted scores were 4.49, 7.00, and 9.09 for blurred, moderately blurred, and clear minutiae, respectively. Multiple regression analysis indicated that replacing a pair of blurred minutiae with a pair of clear minutiae increased the score by 0.492, whereas replacing it with a pair of moderately blurred minutiae increased the score by only 0.216. By mapping predicted scores to graded levels of evidential strength, the framework contributes to a paradigm shift from categorical expert opinions to graded ones, helping courts evaluate fingerprint evidence more scientifically.

Humans

Functional characterization of the MdFLZ2 gene in drought and salt stress tolerance in apple.

Drought and salt stress are significant environmental limitations that severely constrain plant growth and productivity, therefore, enhancing stress tolerance is a key goal in crop improvement. The plant-specific FCS-like zinc finger (FLZ) proteins have been identified as important regulators of stress adaptation. In this study, we conducted a genome-wide characterization of the FLZ gene family in apple and functionally characterized MdFLZ2. qRT-PCR analysis revealed that MdFLZ2 was differentially expressed across various tissues and transcriptionally induced by both drought and salt stress. Subcellular localization assays demonstrated that the MdFLZ2 protein is localized to both the nucleus and the cytoplasm. The overexpression of MdFLZ2 in apple calli, Arabidopsis and tomato conferred increased resistance to drought and salt stress. In addition, yeast two-hybrid (Y2H) assays confirmed that MdFLZ2 interacted with MdSnRK1.1, and similar interactions were also detected between other MdFLZ family members and MdSnRK1.1. Collectively, our findings suggest MdFLZ2 as a positive regulator of drought and salt tolerance and highlight its potential to serve as a genetic resource for abiotic stress improvement.

Malus

Plant cis-regulatory grammar: Decoding the multidimensional code of transcriptional regulation for programmable crop engineering.

Cis-regulatory elements (CREs) orchestrate the spatiotemporal precision of gene expression that underlies plant development, adaptation, and domestication. Decoding the cis-regulatory grammar of plant genomes remains a central challenge in modern biology, with profound implications for programmable crop engineering. Here, recent conceptual and technological advances are synthesized to reshape our understanding of plant CREs. This review first argues that CRE function is not only an intrinsic property of DNA sequence alone but also emerges from a multidimensional context, including chromatin accessibility, histone modifications, three-dimensional genome topology, and cell type-specific regulatory landscapes. Furthermore, the convergence of single-cell epigenomics, high-throughput functional assays, and CRISPR-based dissection has begun to unravel this contextual grammar, revealing the computational principles governing transcriptional regulation. Critically, we propose that artificial intelligence (AI) platforms are catalyzing an ongoing transition from descriptive discovery to predictive engineering, wherein these platforms outperform natural evolution in designing synthetic CREs. Finally, a roadmap is outlined toward a plant regulatory grammar foundation model, which will enable truly predictive engineering of gene expression when fine-tuned for specific tasks. Collectively, the integration of single-cell resolution maps, precise genome editing, AI-driven design, and regulatory-compliant delivery systems promises to transform our ability to reprogram plant gene regulation for next-generation agriculture, bridging the gap between foundational regulatory biology and tangible crop improvement.

artificial intelligence

Genomic history of the Caucasus: A systematic review and meta-analysis of ancient DNA studies.

The Caucasus region represents a unique natural laboratory for paleogenetic research due to its complex topography, long-standing role as a migratory corridor and glacial refugium, and exceptional preservation conditions for ancient DNA. This review synthesizes recent genome-wide studies to reconstruct the demographic history shaping the distinctive genetic landscape of modern Caucasus populations. The analysis reveals a deep pattern of continuity, isolation, and periodic admixture. Early genetic differentiation emerged in the Neolithic and Chalcolithic, forming distinct steppe and mountain population clusters. The Bronze Age was a pivotal period marked by large-scale gene flow from the Eurasian Steppe, particularly linked to the Yamnaya expansion, and interactions with Iranian and Anatolian-related groups. Despite these influences, many populations demonstrate remarkable genetic continuity from the Bronze Age to the present day. Significant knowledge gaps persist, particularly for the Paleolithic, Mesolithic, and Neolithic of the North Caucasus, as well as for the Late Medieval and Early Modern periods across the entire region. Addressing these gaps through targeted archaeogenomic studies is crucial for understanding the fine-scale processes that formed the hierarchical structure and high linguistic diversity of Caucasus populations, offering a powerful model for studying human adaptation, interaction, and language-genetics dynamics in a mountainous environment.

Humans

Efficacy of pharmacological and microbiota-based therapies in preclinical models of autism spectrum disorder: a systematic review.

BACKGROUND: Autism spectrum disorder (ASD) is a multifactorial neurodevelopmental condition in which pharmacological and microbiota-targeted interventions are emerging as promising therapeutic avenues. Animal models are the main tool to investigate etiology, molecular mechanisms and screening for pharmacological therapies. Methodological differences, outcome measure variability, incomplete reporting, biological confounders, and overgeneralization of the results made evaluating innovative pharmacological agents challenging. These limitations in the field highlight a need for systematic and standardized research to reliably assess and translate pharmacological interventions from ASD animal models to human clinical relevance. SUBJECTS: This systematic review synthesized efficacy evidence for pharmacological and microbiota-based therapies across established ASD animal models. RESULTS: We identified 52 recent (2010-2025) studies that reported key ASD behavioral outcomes after pharmacological or microbiota-focused treatments. Interventions were grouped into therapeutic classes - including oxytocinergic agents, E/I balance therapeutic targets, metabolic drugs, cannabinoids, purine-based interventions and emerging targets - alongside microbiota-directed strategies such as probiotics, prebiotics, and fecal microbiota transplantation. By integrating effect directions and robustness across models, we identified most potential drug candidates, evaluated the efficacy of novel strategies, and recognized critical translational gaps. The reviewed studies demonstrate that ASD-like behavioral deficits in preclinical models can be modulated through interventions targeting diverse biological systems, including neurotransmission, neuroinflammation, metabolism, and the gut-brain axis. CONCLUSIONS: These findings support the multifactorial nature of ASD pathophysiology which arises from a network of interacting systemic processes rather than a single molecular defect. It could explain the limited success of traditionally narrowly targeted interventions and suggest a paradigm shift into a more systemic approach.

Animals

Embedding cardiovascular risk assessment into routine BTK inhibitor management in chronic lymphocytic leukemia.

INTRODUCTION: Cardiovascular (CV) toxicities remain a major challenge during Bruton tyrosine kinase inhibitor (BTKi) therapy for chronic lymphocytic leukemia (CLL). Selecting the optimal BTKi based solely on a history of overt CV disease may underestimate underlying cardiovascular vulnerability. AREAS COVERED: We performed a targeted, non-systematic review of PubMed and MEDLINE to examine the association between baseline CV comorbidities and BTKi-related CV toxicities in CLL. Current evidence indicates that preferential use of BTKis with more favorable CV safety profiles, coupled with appropriate cardio-oncology surveillance, reduces the risk of CV adverse events in patients with pre-existing CV disease. In patients without established CV disease, the Systematic Coronary Risk Evaluation 2 (SCORE2) and SCORE2-Older Persons (SCORE2-OP) may help identify clinically meaningful latent CV risk, enabling early optimization of modifiable risk factors in line with the proactive cardiovascular management strategy endorsed by the 2026 European Hematology Association (EHA) CLL guidelines. EXPERT OPINION: A structured, risk-adapted approach integrating standardized CV risk assessment, early management of modifiable risk factors, individualized BTKi selection, and multidisciplinary cardio-oncology collaboration may improve the safety and tolerability of BTKi therapy in CLL. Pending prospective validation, SCORE2 and SCORE2-OP should complement, rather than replace, dedicated cardio-oncology evaluation.

Humans

ER proteostasis failure in HYOU1 deficiency alters B cells, neutrophils, and interferon signalling.

Hypoxia upregulated 1 (HYOU1) is a stress-inducible ER chaperone. We investigated 2 unrelated patients carrying biallelic HYOU1 variants and presenting with primary immunodeficiency. Patient 1, homozygous for p.Pro444His, displayed failure to thrive, hypoglycemia, B cell lymphopenia, and neutropenia. Patient 2, compound heterozygous for p.Arg262Gln and p.Pro757_Glu758insAla, exhibited recurrent infections, enteropathy, and hypogammaglobulinemia. In Patient 1, while HYOU1 transcription was preserved, the protein was severely reduced. Tunicamycin treatment of dermal fibroblasts showed a blunted unfolded protein response and defective induction of ER stress-responsive genes. Immunophenotyping showed near-absence of circulating B cells, and single-cell RNA sequencing of bone marrow identified an arrest at the pro-B cell stage. Neutrophils displayed hypogranulation and dysregulated IFN- and apoptosis-associated transcriptional signatures, unresponsive to G-CSF. HYOU1 deficiency hence results in ER stress-induced proteostasis failure that simultaneously impairs adaptive immunity through B cell developmental arrest and innate immunity through neutrophil dysfunction and IFN pathway imbalance. This work expands the spectrum of HYOU1 deficiency and further identifies ER proteostasis as a central determinant of immune homeostasis.

Journal Article

Digital Structured Education With Behavioral Nudge Tools for Adults With Type 2 Diabetes: Multicenter Randomized Controlled Trial.

BACKGROUND: Digital interventions offer scalable alternatives to traditional face-to-face diabetes education, but often face challenges related to inconsistent clinical effectiveness, and declining user engagement. However, whether a digital structured education program integrated with behavioral nudge tools can improve metabolic, behavioral, and psychological outcomes in adults with type 2 diabetes remains unclear. OBJECTIVE: This study aimed to evaluate the effectiveness of a digital structured education program integrated with behavioral nudge tools in improving metabolic, behavioral, and psychological outcomes among adults with type 2 diabetes. METHODS: This multicenter randomized controlled trial was conducted in the endocrinology departments of 4 hospitals in China. Adults with type 2 diabetes were randomly assigned to an intervention group receiving a digital structured education program integrated with behavioral nudge tools (n=146) or a control group receiving standard digital diabetes education (n=147). Assessments were conducted at baseline and 12-week follow-up. The primary outcome was hemoglobin A1c (HbA1c) at 12 weeks, adjusted for baseline HbA1c, and study center. Secondary outcomes included fasting blood glucose (FBG), weight, BMI, waist circumference, blood pressure, lipid profiles, self-management behaviors, self-efficacy, and habit strength. RESULTS: Among 293 participants (mean age 49.19, SD 10.02 y), 287 (97.9%) completed follow-up. At 12 weeks, the intervention group demonstrated significantly greater improvements than the control group in HbA1c (adjusted mean difference -0.38%, 95% CI -0.68% to -0.09%; P=.01), FBG (adjusted mean difference -0.75, 95% CI -1.27 to -0.44 mmol/L; P<.001), weight (adjusted mean difference -0.84, 95% CI -1.61 to -0.07 kg; P=.03), BMI (adjusted mean difference -0.38, 95% CI -0.65 to -0.11 kg/m&#xb2;; P=.01), systolic blood pressure (adjusted mean difference -2.71, 95% CI -4.62 to -0.79 mm Hg; P=.01), diastolic blood pressure (adjusted mean difference -2.92, 95% CI -4.47 to -1.37 mm Hg; P<.001), and total cholesterol (adjusted mean difference -0.27, 95% CI -0.48 to -0.05 mmol/L; P=.02). The intervention was also associated with significantly greater improvements in self-management behaviors, self-efficacy, and habit strength (all P<.05). CONCLUSIONS: Digital structured education integrated with behavioral nudge tools improved metabolic outcomes and strengthened psychological and behavioral determinants of self-management among adults with type 2 diabetes over a 12-week period. These findings suggest that a digital structured education program integrated with behavioral nudge tools may enhance diabetes self-management beyond standard digital diabetes education. Further studies with longer follow-up and real-world implementation are warranted to evaluate the sustainability, generalizability, and long-term clinical impact of this integrated intervention.

Humans

Longitudinal Neurocognitive Changes for Patients With Hematologic Malignancies Undergoing Hematopoietic Stem Cell Transplantation: A Systematic Review With Structured Narrative Synthesis.

OBJECTIVES: Neurocognitive changes in hematological malignancies (HM) and as a sequela of hematopoietic stem cell transplantation (HSCT) remain under-recognized. These changes may substantially affect patients' quality of life. Therefore, this review systematically evaluated longitudinal neurocognitive changes in patients with HM undergoing HSCT. METHODS: Following PRISMA guidelines, PubMed, Scopus, and CINAHL were searched on October 30, 2025. Longitudinal studies assessing neurocognitive changes in patients with HM undergoing HSCT, with or without healthy controls, were included. Risk of bias was assessed using an adapted National Institutes of Health quality assessment tool for before-after studies. Effect sizes with 95% confidence intervals were calculated to quantify changes in neurocognitive performance. RESULTS: Nine of 2012 studies met the inclusion criteria, with overall moderate study quality. Improvements may occur post-HSCT; however, allogeneic HSCT and myeloablative conditioning were main risk factors identified for persistent cognitive decline. In line with white matter damage, executive function and attention/processing speed impairments likely represent core deficits, which may affect other cognitive impairments. Post-HSCT changes depend on task characteristics, cognitive load, and conditioning intensity. CONCLUSIONS: Future research should emphasize regular neurocognitive assessment to guide cognitive rehabilitation, implement pre-transplant cognitive rehabilitation strategies to mitigate post-HSCT cognitive decline, and enhance treatment outcomes.

Humans