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PubMed2026

Emerging techniques of CRISPR/Cas system in antiviral therapy and diagnostics: Applications, limitations, and translational perspectives.

The CRISPR/Cas (clustered regularly interspaced short palindromic repeats) system is a versatile technology for developing antiviral medicines and editing viral genomes in both diagnostics and vaccine synthesis. Emerging insights into class 2 effectors, such as Cas9, Cas12, and Cas13, which target viral DNA and RNA, have revolutionized vaccines against viruses such as HIV, HPV, HBV, and EBV. Innovative diagnostic techniques such as SHERLOCK, DETECTR, and FELUDA have demonstrated system's diversity and accuracy in detecting the virus markers, supporting clinical decision-making, indicating adaptability and precision of CRISPR. This review critically evaluates CRISPR's role in RNA editing, emphasizing its importance for functional genomics and development of recombinant vaccines. Translational challenges are critically discussed, including off-target effects, delivery limitations, and ethical issues, for which unique approaches such as high-fidelity Cas variants, non-viral delivery systems, and bioethical frameworks are evaluated to address these limitations. This review also covers other social implications, such as accessibility and biosecurity risks, associated with CRISPR technologies Collectively, these advances underscore the transformative potential of CRISPR technologies in shaping next-generation antiviral diagnostics and therapeutics.

CRISPR-Cas Systems↗

PubMed2026

Proteomics in environmental pollution research: Advances, challenges, and future directions.

Environmental proteomics has emerged as a powerful approach for elucidating the molecular mechanisms underlying pollutant-induced biological effects. Although this field has developed rapidly, the systematic review of recent proteomics applications in environmental pollution research remains limited. This review explored the emerging roles of toxicoproteomics in biomarker discovery and mechanistic elucidation, as well as ecotoxicoproteomics in ecological risk assessment and bioremediation strategies. Here, we review the field, highlighting recent trends such as the integration of proteomics with genomics, transcriptomics, and metabolomics to provide a comprehensive view of biological responses to environmental stressors. We further discuss the growing application of artificial intelligence in improving proteomics data interpretation and accelerating biomarker discovery. In addition, recent technological advances in environmental proteomics are highlighted, including next-generation tissue microarray proteomics, nanoscale proteomics, single-cell proteomics, and spatial proteomics. Despite its potential, proteomics faces challenges, such as high operational costs, computational complexity in analysis, and technical limitations in low-abundance protein detection. We propose that the convergence of proteomics with artificial intelligence and multi-omics approaches offers promising solutions to these challenges, enhancing the practical application of proteomics in environmental monitoring and risk assessment.

Proteomics↗

PubMed2026

Targeted Nanoparticle Delivery CRISPR/Cas9: overcoming biological barriers, enhancing stability, and improving therapeutic precision.

Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) has emerged as a promising gene-editing platform for genetic disorders; however, its in vivo application remains limited by low delivery efficiency and biological barriers. Many CRISPR payloads fail to reach target sites due to extracellular degradation, immune clearance, and intracellular trafficking limitations. This review examines the interplay between biological barriers and nanoparticle engineering strategies for CRISPR/Cas9 delivery. A barrier-oriented engineering approach is proposed as a central framework, encompassing ligand-based surface modification for enhanced targeting and uptake, improved circulation stability via PEGylation and biomimetic coatings, and optimized payload release through endosomal escape strategies. Stimulus-responsive nanoparticle systems further enable spatiotemporal control over payload release. Nuclear targeting strategies, including optimization of nuclear localization signals (NLS) and exploitation of endogenous trafficking pathways, are highlighted as key factors for improving genome-level editing efficiency. Despite these advances, major challenges-including limited intracellular delivery efficiency, insufficient targeting precision, and safety concerns-continue to hinder clinical translation. Future directions highlight artificial intelligence-driven nanoparticle design, personalized delivery systems, and next-generation CRISPR platforms. Overall, an integrated, barrier-oriented engineering strategy is essential for advancing CRISPR/Cas9 delivery toward clinical applications, ultimately advancing global good health and well-being.

CRISPR/Cas9↗

PubMed2026

Machine learning vs. traditional methods for predicting postoperative cardiac complications after non-cardiac surgery: a systematic review and Bayesian network meta-analysis.

INTRODUCTION: Accurate prediction of peri-operative cardiac complications is critical to optimise pre-operative decision-making. Traditional risk prediction scores, such as the Revised Cardiac Risk Index, show only modest discrimination. Machine learning can model complex, non-linear relationships but their predictive performance compared with traditional scores remains unclear. METHODS: We performed a systematic review and Bayesian network meta-analysis. The primary outcome was postoperative adverse cardiac events following non-cardiac surgery. Prediction models were assessed relative to the Revised Cardiac Risk Index. As many studies evaluated multiple versions of each model type, the highest performing ('best version') and lowest performing ('worst version') results were analysed. Models were ranked using the surface under the cumulative ranking curve (SUCRA). RESULTS: Thirteen studies evaluating 54 models and 927,113 patients were included. Machine learning approaches generally outperformed traditional risk scores. Automated machine learning ranked highest (SUCRA 96.6) showed the greatest improvement in the best version analysis (mean difference (MD) 0.28 (95%CrI 0.16-0.40)) and remained superior in the sensitivity analysis (MD 0.30 (95%CrI 0.14-0.45)). Gradient boosting models showed superior performance over the Revised Cardiac Risk Index across analysis (best version: MD 0.20 (95%CrI 0.14-0.26), worst version: MD 0.18 (95%CrI 0.12-0.25), SUCRA 82.4). The Gupta Perioperative Risk for Myocardial Infarction or Cardiac Arrest score outperformed the Revised Cardiac Risk Index in the best version analysis (MD 0.16 (95%CrI 0.01-0.32)). Between-study heterogeneity was low. None of the included studies externally validated their machine learning models and only six were judged to be at low risk of bias. DISCUSSION: Most machine learning models showed better discrimination than traditional risk scores, with automated machine learning and gradient boosting models ranking highest. However, study quality, calibration reporting and absence of external validation limit immediate clinical adoption. Prospective, multicentre evaluation is required before integration of these models into peri-operative practice.

Humans↗

PubMed2026

[Analysis of clinical phenotypes and pathogenicity of a c.4476+5G>T variant of SCN1A gene in a Chinese pedigree affected with Genetic epilepsy with febrile seizures plus].

OBJECTIVE: To explore the pathogenicity and characteristics of a heterozygous splicing variant of SCN1A gene in a Chinese pedigree affected with Genetic epilepsy with febrile seizures plus (GEFS+). METHODS: A retrospective analysis was carried out on the clinical data and results of genetic testing of a GEFS+ pedigree consisting of 5 members who had visited the First Affiliated Hospital of Zhengzhou University on July 1, 2024. Pathogenicity of the splicing variant of the SCN1A gene was validated with a minigene splicing assay. This study was approved by the Medical Ethics Committee of the the First Affiliated Hospital of Zhengzhou University (Ethics No.: KS-2018-KY-36). RESULTS: The proband, a 24-year-old female, presented with FS in conjunct with focal seizures, and both of her younger brothers had Dravet syndrome. All of the three patients had carried a c.4476+5G>T variant of the SCN1A gene, which was unreported previously. Minigene experiment verified that the variant could cause loss of the first 7 bps of exon 24 and 138 bps from exon 23 of the SCN1A gene, resulting in alteration p.V1447_1495delfs*6 and affecting splicing. Based on the guidelines from American College of Medical Genetics and Genomics (ACMG), the variant was predicted as likely pathogenic (PVS1+PM2_Supporting). CONCLUSION: The c.4476+5G>T variant at an intronic site of the SCN1A gene probably underlay the pathogenesis of GEFS+ in this pedigree.

Adult↗

PubMed2026

Efficacy and Safety of iGlarLixi Versus IDegAsp by Baseline Age, Disease Duration and HbA1c in Chinese People With Type 2 Diabetes: Post Hoc Analyses of the Soli-D Study.

AIMS: To compare the efficacy and safety of insulin glargine 100 U/mL plus lixisenatide (iGlarLixi) with insulin degludec plus insulin aspart (IDegAsp) by baseline age, Type 2 diabetes (T2D) duration and glycated haemoglobin (HbA1c) in the Soli-D study. MATERIALS AND METHODS: In Soli-D, Chinese adults with T2D suboptimally controlled on oral antidiabetic drugs (OADs) were randomized to iGlarLixi or IDegAsp for 24 weeks. These post hoc analyses evaluated glycaemic efficacy, insulin dose, body weight and hypoglycaemia outcomes in subgroups defined by baseline age (< 65, ≥ 65 years), T2D duration (< 10, ≥ 10 years) and HbA1c (≥ 7% to ≤ 8% [≥ 53 to ≤ 64 mmol/mol], > 8% to ≤ 9% [> 64 to ≤ 75 mmol/mol], > 9% [> 75 mmol/mol]). RESULTS: Among 582 participants (iGlarLixi n = 291; IDegAsp n = 291), baseline age was < 65 years in 442 and ≥ 65 years in 140; T2D duration was < 10 years in 366 and ≥ 10 years in 216; and HbA1c was ≥ 7% to ≤ 8% in 205, > 8% to ≤ 9% in 209 and > 9% in 168. At Week 24, HbA1c reductions were greater with iGlarLixi versus IDegAsp, with no treatment-by-subgroup interactions for baseline age, T2D duration or HbA1c. Change in other glycaemic outcomes, insulin dose and body weight generally showed no interaction across subgroups. Total insulin daily doses during treatment and hypoglycaemia event rates were consistently lower with iGlarLixi versus IDegAsp in all subgroups. CONCLUSIONS: iGlarLixi provides improved glycaemic control at lower insulin doses with reduced risk of hypoglycaemia in Chinese adults with suboptimally controlled T2D on OADs, regardless of baseline age, disease duration or HbA1c.

Humans↗

PubMed2026

Three-Dimensional Fracture Mapping of the Terrible Triad of the Elbow: Morphological Characteristics and Clinical Implications.

BACKGROUND: The morphology of fractures in the terrible triad of the elbow (TTE) is complex, and precise management relies on a profound understanding of this morphology. This study aims to systematically analyze, for the first time, the distribution and morphological characteristics of TTE fracture lines using three-dimensional (3D) imaging technology. METHODS: Clinical data and thin-slice CT scans of 112 patients with TTE from January 2021 to December 2024 were retrospectively included. 3D fracture models were reconstructed using Mimics software. Virtual reduction and standardized alignment were performed using 3-matic software. Fracture lines were mapped onto standard ulnar and radial templates, and 3D fracture heat maps were generated using the E-3D software to demonstrate the high-frequency distribution zones of the fracture lines visually. Statistical analysis was performed using SPSS software (version 21.0, IBM Corp., Armonk, NY, USA). Continuous variables were compared using one-way analysis of variance (ANOVA), and categorical variables were compared using the chi-square test (χ2 test). A two-tailed p < 0.05 was considered statistically significant. RESULTS: The study revealed distinct patterns in the distribution of TTE fracture lines. In the coronoid process, the fracture "hot zone" presented as an annular high-density band extending from the lateral middle aspect to the tip. In the radial head, an oblique high-density band was observed in the anterolateral quadrant of the articular surface. The radial neck exhibited a circumferential high-density zone, which was most prominent in the anterolateral aspect. Statistical analysis indicated a significant correlation between age and fracture complexity; the proportion of Regan-Morrey type III coronoid fractures and Mason type III radial head fractures was significantly higher in elderly patients (> 60 years) (p < 0.05), suggesting that advanced age is a significant risk factor for complex fractures. CONCLUSION: This study is the first to visually reveal the Collaborative Distribution Patterns of TTE fracture lines using 3D fracture mapping technology. This model provides morphological evidence for understanding the injury mechanism of TTE and offers an anatomical framework that may assist surgeons in individualizing surgical approaches and fixation strategies.

Humans↗

PubMed2026

Associations of Illness Perception, Resignation Coping, and Social Support With Self-Regulatory Fatigue in Patients With Type 2 Diabetes: A Cross-Sectional Study.

AIMS: To examine the associations among illness perception, resignation coping, social support, and self-regulatory fatigue (SRF) in patients with Type 2 diabetes mellitus. The study specifically explores whether resignation coping and social support exhibit indirect associations with SRF in the context of illness perception. DESIGN: A cross-sectional study. METHODS: From November 2024 to October 2025, a convenience sample of 302 adult patients with T2DM was recruited from a tertiary general hospital in China. Participants completed validated instruments with established psychometric properties, namely the Brief Illness Perception Questionnaire, the Medical Coping Modes Questionnaire, the Perceived Social Support Scale, and the Self-Regulatory Fatigue Scale. Statistical analyses included Spearman correlation and serial mediation analysis using the PROCESS Macro (Model 6) with bias-corrected bootstrapping. RESULTS: SRF was positively correlated with negative illness perception (r = 0.579, p < 0.01) and resignation coping (r = 0.612, p < 0.01), and negatively correlated with social support (r = -0.598, p < 0.01). Serial mediation analysis revealed that illness perception was associated with SRF through indirect pathways involving resignation coping and social support. Resignation coping and social support mediated the association between illness perception and self-regulatory fatigue, both individually and sequentially. CONCLUSIONS: Negative illness perception correlates with higher SRF. This observed correlation is additionally linked to indirect pathways involving resignation coping and lower social support. Collectively, these findings highlight a pattern of interrelated cognitive (illness perception), behavioural (resignation coping), and resource (social support) factors that are associated with self-regulatory fatigue in this cross-sectional study. IMPLICATIONS FOR THE PROFESSION: The findings offer a clear, evidence-based framework for nursing practice. They highlight the potential value of integrated assessment and intervention that simultaneously addresses patients' illness beliefs, maladaptive coping strategies, and social support systems, which are associated with lower SRF and better diabetes self-management. REPORTING METHOD: This study adheres to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for cross-sectional studies. PATIENT OR PUBLIC CONTRIBUTION: Patients participated solely as research participants by providing survey data. They were not involved in the study design, implementation, data analysis, interpretation, or manuscript preparation. All patients provided written informed consent prior to questionnaire completion.

Humans↗

PubMed2026

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↗

PubMed2026

Synergistic transcriptional modules in Trichoderma asperellum enhance glutathione detoxification to counteract fungal pathogen toxins.

Trichoderma fungi are potent biocontrol agents. However, their defence mechanisms against pathogen-derived toxins remain poorly understood. We identified two synergistic transcription factor modules in T. asperellum that orchestrate the detoxification of cytotoxic secondary metabolites from the poplar blight pathogen Alternaria alternata. Overexpression of the central regulator TasMYB46 reduced disease lesion area by approximately 22% and was associated with decreased pathogen-induced reactive oxygen species (ROS) accumulation. Mechanistically, TasMYB46 directly activates the glutathione S-transferases TasGST61.1 and TasGST56.1 through distinct promoter binding sites (G-box/as-1/MBS), forming dedicated detoxification modules. Crucially, we identified urolithin C as the most abundant phytotoxin in A. alternata metabolites, which is efficiently detoxified through the TasMYB46-TasGST61.1 module. The transcription enhancer TasbHLH53.8 amplifies this system by binding to TasMYB46, boosting TasGST expression and enhancing glutathione-dependent detoxification capacity. This coordinated response elevates glutathione pools and antioxidant enzyme activities (GST/GPx), conferring increased oxidative stress resistance. This study reveals a novel defence mechanism in Trichoderma in which MYB-bHLH-GST modules enable biocontrol agents to neutralise pathogen-derived toxins. Given that Alternaria toxins threaten crops globally (tomatoes, potatoes, citrus), the discovered regulatory synergy represents a strategic advance in developing next-generation biocontrol solutions against toxin-producing plant pathogens.

Alternaria↗

PubMed2026

Ablative radiotherapy in castration-resistant prostate cancer.

OBJECTIVE: To prove the oncological benefit of ablative radiotherapy in patients with up to five metastases from castration-resistant prostate cancer (CRPC) a single-centre randomised trial was initiated. PATIENTS AND METHODS: This monocentric, randomised, phase II clinical trial enrolled patients with up to five prostate-specific membrane antigen-positive bone or lymph node metastases developing prostate-specific antigen (PSA) progression during androgen deprivation (ADT) or ADT and androgen-receptor targeted therapy. Participants were randomised (2:1) to receive metastasis-directed therapy (MDT) or observation (OBS) without changing systemic therapy. The primary endpoint was the proportion of patients having PSA progression within 1 year, with statistical analyses conducted using intention-to-treat principles. Here, results of a planned interim analysis of the primary endpoint are reported. RESULTS: A total of 30 patients (12 in the observation arm and 18 in the MDT arm) were enrolled, PSA progression within 1 year occurred in 44% of the MDT group vs 75% in the OBS group (P = 0.14, not significant). The median time to PSA progression was significantly longer in the MDT arm (12.4 months) compared to the OBS arm (2.9 months, P = 0.03). The pre-defined criteria to discontinue the study were not met. Limitations include the single-centre design and small sample size at interim analysis. CONCLUSION: This pre-planned interim analysis of the primary endpoint did not meet the discontinuation criteria of the study protocol, suggesting that MDT in oligometastatic CRPC may extend the time to PSA progression without immediate change of systemic therapy. The continuation of the study in a multicentre setting is planned (Institutional funding by the TU Dresden, ClinicalTrials.gov identifier: NCT04141709).

Humans↗

PubMed2026

The Role of Small Segmental Duplications in Generating Identical Isoforms Through Alternative Splicing Sites.

Alternative splicing plays a crucial role in expanding proteomic diversity but can also generate identical isoforms under certain conditions. While mutually exclusive splicing of tandem exons has occasionally been reported to produce identical isoforms, the extent to which other splicing events contribute to this phenomenon remains unclear. In this study, we demonstrate that alternative 5' and 3' splice site selection can also lead to the formation of identical isoforms, providing an additional type of splicing event for functional redundancy in transcriptomes. To address this, we analyzed reference genome annotations from 15 plant species, including Arabidopsis thaliana and wheat (Triticum aestivum), obtained from the RefSeq database. Identical isoforms were computationally defined as transcripts with distinct exon-intron structures but identical coding sequences. Our analysis reveals that the majority of alternative 5' and 3' fragments originate from small segmental duplications, suggesting that sequence repetition within gene regions facilitates the emergence of such splicing patterns. We also observed differences in the annotated 5' UTRs of some identical isoforms. However, since the alternative splicing sites themselves were not located within UTRs, these differences may reflect annotation uncertainty rather than genuine AS-derived variation. Given that UTR predictions in reference databases are not always precise, such observations should be interpreted cautiously. Expression analysis using an isoform-specific k-mer approach confirmed that identical isoforms can be differentially regulated. These findings suggest that, beyond expanding protein diversity, alternative splicing can also generate redundant isoforms that are differentially expressed at the RNA level, indicating potential regulatory roles. By elucidating the structural and regulatory factors contributing to the formation and retention of identical isoforms, our study provides new insights into the evolutionary and functional significance of alternative splicing in plants.

Alternative Splicing↗

PubMed2026

Chlorfenapyr-pyrethroid nets for pyrethroid-resistant malaria vectors: efficacy, resistance risks, and policy implications.

The Global Technical Strategy for Malaria 2016-2030 aims to reduce malaria incidence and mortality by 90%, yet widespread pyrethroid resistance among major malaria vectors in sub-Saharan Africa threatens this goal. Thus, the World Health Organization recommends chlorfenapyr-pyrethroid combination nets as a priority intervention where pyrethroid resistance undermines vector control. This systematic review synthesizes evidence on the performance, emerging resistance risks, and policy implications of these next-generation insecticide-treated nets. A structured search of literature from 2010 to 2024 across PubMed, Embase, WHO IRIS, and Google Scholar identified 31 eligible studies from 113 records. Evidence shows that chlorfenapyr-pyrethroid nets consistently outperform pyrethroid-only nets against resistant Anopheles populations, demonstrating a 1.8-fold increase in mosquito mortality (95% CI: 1.5-2.1). Community trials report 40-60% reductions in malaria infection incidence and entomological inoculation rates following deployment. However, early signs of chlorfenapyr resistance have emerged in Anopheles gambiae populations in Central Africa (RR: 2.4, p = 0.01), linked to CYP6P4 metabolic overexpression. A significant correlation was also observed between agricultural pesticide use and vector resistance patterns (r = 0.62, p < 0.05). Although chlorfenapyr-pyrethroid nets provide an important short-term tool for managing pyrethroid resistance, their long-term effectiveness depends on integrated resistance management. Rotational deployment with other insecticide classes, strengthened genetic and phenotypic surveillance, and a coordinated 'One Health' approach involving both public health and agriculture are essential to sustain gains and advance progress toward the 2030 malaria targets.

Pyrethrins↗

PubMed2026

Vitamin D Deficiency During Pregnancy Is Associated With Greater LDL-C Increase, Elevated β-Hydroxybutyrate and Altered Neonatal Metabolic Markers-A Secondary, Pooled Analysis of the Randomized, Controlled Vitamin D and Lifestyle for Gestational Diabetes Prevention Trial (DALI).

INTRODUCTION: Vitamin D (vitD) plays a role in metabolic regulation, including lipid metabolism and insulin sensitivity. During pregnancy, profound physiological changes in lipid handling and ketogenesis occur to support fetal development. However, the extent to which maternal vitamin D status influences these metabolic adaptations and fetal metabolic markers remains unclear. METHODS: In this secondary analysis, we examined lipid distribution throughout pregnancy-from before 20 weeks' gestation to delivery-in women with overweight or obesity, stratified by vitamin D status (deficiency, insufficiency, or sufficiency), assessing both maternal and cord blood. Main inclusion criteria were: age > =18 years, singleton pregnancy, < 20 weeks' gestation, BMI ≥ 29 kg/m2. Women with GDM < 20 weeks' gestation were excluded. In total, 962 pregnant women were divided into vitD deficient (< 30 nmol/L, n = 102), insufficient (30-50 nmol/L, n = 222) and sufficient (> 50 nmol/L, n = 638) groups. VitD levels and lipid concentrations were assessed at < 20, 24-28 and 35-37 weeks' gestation and in cord blood. RESULTS: Compared with vitD sufficient women, women with vitD deficiency had significantly larger increases in LDL-C throughout pregnancy and ß-OH-butyrate at 24-28 weeks' gestation, in adjusted analysis. VitD in cord blood was highest in offspring of mothers with vitD sufficiency. In cord blood, significantly higher ß-OH-butyrate was observed with vitD deficiency; lipid concentrations were similar between groups. CONCLUSIONS: Early vitamin D deficiency before 20 weeks of gestation was associated with altered metabolic trajectories during pregnancy, including greater increases in LDL cholesterol and ketone body concentrations in women with overweight or obesity, as well as higher cord blood ketone levels in their offspring. These findings suggest that early maternal vitamin D status may influence maternal and fetal metabolic adaptations, although causal relationships and clinical implications require further investigation. TRIAL REGISTRATION: Trial registered at ISRCTN registry (https://doi.org/10.1186/ISRCTN70595832) trial number ISRCTN70595832. Registration date 02/12/2011.

Humans↗

PubMed2026

Mul-PheG2P: decoupled learning and prediction-space fusion enables robust and interpretable multi-phenotype genomic prediction.

Genomic prediction of multiple phenotypes is crucial in modern plant breeding; however, existing methods struggle with negative transfer and lack interpretability, particularly across high-dimensional small-sample data and diverse species. To address this, we propose Mul-PheG2P, a novel paradigm based on decoupled learning and predictive space fusion. It employs a two-stage design: first training phenotype-specific encoders using genetic data, then decoupling phenotype-specific learning from cross-phenotype aggregation via an interpretable prediction layer. Mul-PheG2P outperforms existing methods across diverse crop datasets, including maize (Zea mays), wheat (Triticum aestivum), and tomato (Solanum lycopersicum). It provides a multi-scale interpretability chain: at the macro level, it quantifies phenotypic contributions via attention-based weighting; at the micro level, Integrated Gradients reveal the genetic basis of predictions. Notably, the model successfully identified the CCT (CONSTANS, CO-like, and TOC) motif regulating photoperiodism and the SQUAMOSA (SQUAMOSA promoter binding protein) promoter for inflorescence development, confirming its ability to capture functional biological mechanisms. These results highlight the high performance and interpretability of Mul-PheG2P, showcasing its value for low-cost, large-scale screening to advance precision breeding.

Phenotype↗

PubMed2026

Effects of GLP-1 Receptor Agonists and Dual GIP/GLP-1 Receptor Agonists on Inflammatory and Metabolic Biomarkers in Type 2 Diabetes: A Systematic Review and Meta-Analysis.

BACKGROUND: Glucagon-like peptide-1 receptor agonists (GLP-1RAs) and dual GIP/GLP-1 receptor agonists improve cardiovascular outcomes in type 2 diabetes mellitus (T2DM), but their effects on inflammatory and oxidative biomarkers are not fully defined. MATERIALS AND METHODS: We searched PubMed, Ovid MEDLINE, Scopus, Web of Science and the Cochrane Library from inception to 19 February 2026 for randomised controlled trials (RCTs) in adults with T2DM comparing a GLP-1RA or dual GIP/GLP-1 agonist with placebo or active therapy, and reporting C-reactive protein (CRP or high-sensitivity CRP [hs-CRP]), interleukin-6 (IL-6), tumour necrosis factor-α (TNF-α), monocyte chemoattractant protein-1 (MCP-1), malondialdehyde (MDA) or adiponectin. Random-effects meta-analyses were conducted using standardised mean differences (SMDs). RESULTS: Forty-one RCTs were included. GLP-1RAs significantly reduced CRP/hs-CRP (27 studies, 1991 participants; SMD -0.37, 95% CI -0.59 to -0.14) and MDA (3 studies, 272 participants; SMD -0.98, 95% CI -1.65 to -0.30), and increased adiponectin (16 studies, 1327 participants; SMD 0.30, 95% CI 0.13 to 0.46). Pooled effects on IL-6 (17 studies, 1068 participants; SMD -0.14, 95% CI -0.37 to 0.10), TNF-α (16 studies, 1164 participants; SMD -0.25, 95% CI -0.61 to 0.12) and MCP-1 (7 studies, 450 participants; SMD -0.27, 95% CI -0.58 to 0.03) were not statistically significant, although MCP-1 decreased in sensitivity analyses. Across biomarkers, heterogeneity was moderate to high. Two tirzepatide RCTs (562 participants) showed a significant reduction in IL-6 (SMD -0.28, 95% CI -0.47 to -0.09) and a non-significant trend towards lower CRP/hs-CRP. CONCLUSIONS: In adults with T2DM, incretin-based therapies consistently lower CRP/hs-CRP, reduce oxidative stress (MDA) and increase adiponectin, while effects on IL-6 and TNF-α are more variable. These data support a selective anti-inflammatory and metabolic regulatory profile of GLP-1-based therapy, but heterogeneity and limited data for some biomarkers warrant cautious interpretation and further mechanistic studies. TRIAL REGISTRATION: PROSPERO number: CRD420261321430.

Humans↗

PubMed2026

To Treat or Not to Treat: Navigating Early-Stage CLL in the Era of Targeted Therapy.

Chronic lymphocytic leukemia (CLL) is most frequently diagnosed at early, asymptomatic stages (Rai 0/Binet A), in which a watch-and-wait strategy remains the standard of care, based on historical trials demonstrating no overall survival benefit from early treatment. Over the past two decades, however, substantial advances in genomic profiling-including immunoglobulin heavy-chain variable region (IGHV) mutational status, TP53 disruption, recurrent gene mutations, and complex karyotype-have uncovered marked biological heterogeneity among early-stage patients and substantially improved prediction of disease progression. In parallel, targeted therapies such as Bruton tyrosine kinase (BTK) inhibitors and venetoclax-based combinations have transformed the management of symptomatic CLL, raising renewed interest in whether early intervention might favorably alter the natural history of biologically high-risk disease. In this review, we critically examine the evolution of prognostication in early-stage CLL, integrate contemporary molecular and clinical risk models, and summarize evidence from both historical chemotherapy-era studies and modern early-intervention trials. We discuss key unresolved controversies, including reliance on surrogate endpoints, the risks of overtreatment, and the persistent absence of an overall survival benefit across all early-treatment strategies. Finally, we outline future research priorities, including refined genomic stratification, minimal residual disease-driven (MRD)-driven approaches, and combination targeted therapies currently under investigation. Despite renewed interest in preemptive treatment, available evidence supports continued observation for asymptomatic patients outside clinical trials.

Humans↗

PubMed2026

Effects of Sacubitril Valsartan Combined With Vericiguat on NT-proBNP and CK-MB Levels in Patients With Chronic Heart Failure.

This study aims to probe the influence of sacubitril valsartan sodium tablets combined with vericiguat on N-terminal pro-B-type natriuretic peptide (NT-proBNP) and creatine kinase isoenzyme (CK-MB) levels in patients with chronic heart failure (CHF). One hundred and twenty CHF patients were enrolled and stratified into a control group (sacubitril valsartan sodium tablets) and a combination group (sacubitril valsartan sodium tablets + vericiguat). Outcome measures included New York Heart Association (NYHA) functional class shifts, echocardiographic indices, cardiac injury markers, 6-min walk distance (6MWD), endothelial function parameters, inflammatory mediator levels, and adverse clinical events. Following a 6-month treatment period, patients in the combination group exhibited superior functional improvement, as reflected by greater advancement in NYHA class. Echocardiographic evaluation revealed more favorable ventricular remodeling in this group, with reduced left ventricular end-diastolic and end-systolic diameters and an elevated ejection fraction. The combination group had a higher 6MWD. Biomarker analysis showed lower NT-proBNP and CK-MB levels in the combination group. Furthermore, improvements in endothelial function were noted, with decreased endothelin and elevated NO, NOS, and CGRP levels in the combination group. Markers of systemic inflammation, including CRP and IL-6, were also attenuated in the combination group. The incidence of adverse reactions and cardiovascular events did not differ significantly between the groups. Co-administration of sacubitril/valsartan and vericiguat enhances cardiac performance, optimizes vascular endothelial responsiveness, modulates heart failure-related biomarkers, and mitigates inflammatory activity in patients with CHF without increasing the risk of adverse events.

Humans↗

Results for “next&#x2010;generation sequencing”

Results for “next‐generation sequencing”