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PubMed2026

Clinical Efficacy and Learning Curve of Far-Lateral Approach (FLA) in Uni-Portal Non-Coaxial Spinal Endoscopic Surgery (UNSES) in the Treatment of Lumbar Degenerative Diseases: A Prospective Study.

BACKGROUND: Uniportal non-coaxial spinal endoscopic surgery (UNSES) via far-lateral approach (FLA) is an innovative minimally invasive procedure for lumbar degenerative diseases, particularly far-lateral disc herniation and foraminal stenosis. However, complex lateral lumbar anatomy and strict endoscope-instrument coordination create a distinct learning curve that may compromise early surgical efficiency and safety. This study aimed to evaluate the efficacy and safety, quantify the learning curve, and to provide clinical guidance for the standardized promotion and application of this technology. METHODS: A total of 40 consecutive patients with lumbar degenerative diseases who underwent UNSES via FLA by a single surgeon between January 2025 and December 2025 were included. All data were analyzed using SPSS 26.0 statistical software (IBM, USA). Primary outcomes included operation time, blood loss, fluoroscopy frequency, and intraoperative complication rate. Secondary outcomes were VAS, ODI, and modified Macnab criteria at 1, 3, and 6 months postoperatively. The learning curve and the inflection point of the learning curve was determined using cumulative sum (CUSUM) analysis. The differences in clinical indicators between early and proficient stage were compared. RESULT: Operation time, blood loss, and fluoroscopy times decreased significantly with case accumulation (p < 0.05). CUSUM identified an inflection point at the 16th case, after which operation time stabilized at (55.3 ± 8.6) min, much shorter than the early phase (89.5 ± 10.3) min (p < 0.001). Before the 16th case, the curve was in an upward trend; after the 16th case, the curve tended to be flat, indicating the proficiency stage. Postoperative VAS and ODI improved significantly than those before surgery at each follow-up time (p < 0.05). There was no significant difference in postoperative VAS score and ODI between the two groups at each follow-up time point (p > 0.05). The total complication rate was 12.5% (5/40), were cured by conservative treatment. The total excellent-good rate was 90.0% (36/40). L5/S1 and Bertolotti's syndrome were independent factors affecting the learning curve. CONCLUSION: UNSES via FLA is a safe and effective minimally invasive technique for treating complex lumbar degenerative diseases. It has a certain learning curve, and the inflection point is about the 16th case. After mastering the key techniques such as anatomical positioning, endoscopic manipulation and hemostasis, the surgeon can gradually reach the proficiency stage, with significantly improved surgical efficiency and clinical efficacy, and controllable complications. This study provides a theoretical basis for the clinical training and technology promotion of UNSES via FLA.

Humans↗

PubMed2026

Sulfonic Ion-Exchange Resins as Versatile Tools for the Oxidative Degradation of Chemical and Biological Hazardous Agents.

Commercial sulfonic styrene-divinylbenzene ion-exchange resins are activated with aqueous H2O2 to generate metal-free decontamination systems that combine strong Brønsted acidity with immobilized oxidizing capability. Among five tested materials, Amberlyst 15 dry showed the best performance in terms of oxidant immobilization capacity and promoting the oxidative degradation of the sulfur mustard simulant (2-chloroethyl)ethyl sulfide, CEES, and the organophosphorus pesticide malathion under very mild conditions. Control experiments with K2CO3-exchanged resin demonstrate that efficient decontamination requires the synergy between surface acidity and peroxide functionality. The activated resins also display rapid biocidal activity, strongly reducing viable Escherichia coli and Staphylococcus aureus and completely suppressing the infectivity of HSV-1 and SARS-CoV-2 within min. These findings identify peroxide-activated sulfonic resins as simple, sustainable, regenerable, and versatile tools for efficient combined hazardous chemical and biological decontamination.

Oxidation-Reduction↗

PubMed2026

Family-Wise Error Rate Control in Clinical Trials With Overlapping Populations.

We consider clinical trials with multiple, overlapping patient populations that test multiple treatment policies specifically tailored to these populations. Such designs may lead to multiplicity issues, as false statements will affect several populations. For type I error control, often the family-wise error rate (FWER) is controlled, which is the probability to reject at least one true null hypothesis. If the joint distribution of the test statistics is known, the FWER level can be exhausted by determining critical values or adjusted-levels. The adjustment is typically done under the common ANOVA assumptions. However, the performed tests are then only valid under the rather strong assumption of homogeneous null effects, that is, when the null hypothesis applies to all subpopulations and their intersections. We show that under cancelling null effects, when heterogeneous effects cancel out in some or all subpopulations, this procedure does not provide FWER control. We also suggest different alternatives and compare them in terms of FWER control and their power.

Humans↗

PubMed2026

Genome-wide identification and expression profiling of CSP and OBP genes in Stictocephala bisonia reveals candidate genes potentially associated with insecticide response.

Stictocephala bisonia is an important invasive agricultural pest. Due to the frequent application of insecticides in its habitat, this species is under intense selection pressure. Chemosensory proteins (CSPs) and odorant-binding proteins (OBPs) are known to play key roles in insecticide resistance, but their specific functions in S. bisonia remain unclear. In this study, we identified a total of 22 SbisCSPs and 16 SbisOBPs based on the S. bisonia genome. To screen for candidate genes potentially linked to insecticide resistance, we adopted a multi-criteria screening strategy that integrated phylogenetic analysis, molecular docking with three insecticides, and tissue-specific expression profiling. Phylogenetic analysis identified several SbisCSPs and SbisOBPs clustering with genes known to be involved in insecticide resistance, serving as an initial evolutionary filter. Molecular docking results indicated that λ-Cyhalothrin exhibited the strong predicted binding affinity with most of SbisCSPs and SbisOBPs. Subsequent qPCR validation of seven prioritized candidates revealed distinct expression patterns: SbisCSP22 was highly expressed in adults and demonstrated strong binding affinity to all three insecticides tested, suggesting a potential role in mediating multi-insecticide response. Conversely, SbisCSP17 was significantly upregulated in larvae, clustered with genes known to mediate imidacloprid resistance, and exhibited strong binding affinity to imidacloprid. Given its larval-specific expression and the soil-dwelling behavior of larvae, we hypothesize that SbisCSP17 is a key candidate gene for larvae coping with soil-treated insecticides.

Animals↗

PubMed2026

Modelling peak microbial pollution events caused by combined sewer overflows in a source-to-sea system.

Predicting peak microbial pollution events in downstream coastal bathing waters caused by combined sewer overflows (CSOs) is essential for protecting public health. In urban areas, wastewater effluents, CSOs, and surface runoff can contribute to elevated microorganism loads to downstream waters. These pressures are likely to be intensified by growing population density and more frequent heavy rainfalls due to climate change. This study developed a process-based model to simulate Escherichia coli (E. coli) emissions, transport, and fate from the initial sources to coastal beaches. A three-year retrospective simulation (2017-2019) shows that E. coli concentrations in CSO discharges varied widely across the catchment (4.6 - 7.3 (log10 CFU 100 ml-1)). 99th percentile E. coli concentrations (4.0 (log10 CFU 100 ml-1)) at the inland water outlet were dominated by local CSO emissions, whereas 90th percentile E. coli concentrations (3.6 (log10 CFU 100 ml-1)) reflected cumulative upstream contributions from both CSO and effluent emissions. With the simulation accuracy of 89%, the model reliably reproduced the E. coli dynamics on the downstream beach and showed strong performance in representing peak concentrations based on Complementary Cumulative Distribution Function (CCDF) analysis. The process-based model enables quantitative tracking of source contributions and identification of pollution hotspots, providing support for mitigation measures. The study lays down a source-to-sea modelling framework for representing pollution transport across the aquatic continuum and provides a transferable tool for microbial pollution forecasting and climate adaptation planning.

Climate projection↗

PubMed2026

Development and validation of a comprehensive prognostic model for 28-day ICU mortality in non-traumatic subarachnoid hemorrhage: an analysis based on the MIMIC-IV database.

BACKGROUND: Due to the complex pathophysiology of non-traumatic subarachnoid hemorrhage (SAH), accurate risk prediction remains a challenge. Our aim is to develop and validate a comprehensive prognostic model that integrates demographic characteristics, vital signs, laboratory parameters, and more, to provide clinical decision-making support in real-world practice. METHODS: We conducted a retrospective cohort study of 785 Non-traumatic subarachnoid hemorrhage patients. The cohort was randomly divided into a training set (n = 549) and a validation set (n = 236). Feature selection was performed using LASSO regression, followed by backward stepwise Cox regression for optimization. A nomogram was constructed based on independent predictive factors, and model performance was assessed using discrimination, calibration, and decision curve analysis. To prevent immortal-time bias, all predictors were anchored to a fixed early (first-24-hour) measurement window, treatment variables were modelled as binary indicators rather than cumulative exposures, and a five-model sensitivity analysis with baseline-severity adjustment was performed. RESULTS: The development of our model followed a systematic approach: first, 15 potential predictive factors were selected via LASSO regression, which were then refined to 12 independent predictors using backward stepwise Cox regression. The final predictive factors included: Ventilation, AHT, Nimodipine 60 mg, Age, SAPS.II, Input amount, Calcium total, Platelet count, White blood cells, Anion gap, pH, and Chloride. The integrated model demonstrated excellent predictive ability for 7-day, 14-day, and 21-day mortality in both the training set (AUC: 0.972, 0.934, 0.898) and the validation set (AUC: 0.968, 0.948, 0.911). Calibration curves and decision curve analysis confirmed the model's reliability and clinical utility across different time points. We constructed a nomogram for individualized risk prediction. Univariate Kaplan-Meier survival analysis demonstrated significant stratification of survival outcomes by each predictor, while restricted cubic spline analysis revealed non-linear relationships between continuous variables and mortality risk. Random survival forest analysis identified the top three predictive factors (Nimodipine 60 mg, Ventilation, AHT) and compared them with our full 12-variable model, confirming superior performance of the integrated model at all time points. At the 28-day primary endpoint, the model achieved a time-dependent AUC of 0.898 (training) and 0.904 (validation); after restricting predictors to the early baseline window, the leakage-controlled model retained good discrimination (validation C-index 0.803). CONCLUSIONS: Our ICU 28-day mortality prognosis model demonstrated robust performance in predicting ICU 28-day mortality in non-traumatic subarachnoid hemorrhage. The model, through the nomogram, provides individualized risk assessment, aiding clinical decision-making and patient stratification.

Humans↗

PubMed2026

Loneliness and Personality: Noise- and Bias-Free True Correlations Between Loneliness and the Big Five Personality Domains.

OBJECTIVE: While loneliness is intertwined with many mental and physical health problems, its origins are not yet well understood. We sought to better understand its link to personality in a large national cohort. METHODS: Combining self- and informant ratings in multiple samples, we conducted the largest study to date to examine loneliness' true correlations (rtrues) with the Big Five personality traits, free of single-method biases and transient and random errors. RESULTS: Across three samples (Estonian-speaking, N = 20,893; Russian-speaking, N = 762; English-speaking, N = 599), we found a strong relationship between loneliness and Neuroticism (rtrue = 0.60-0.70). Loneliness also had robust but much weaker associations with Extraversion (rtrue = -0.20 to -0.30), and only weak associations (rtrue = 0.10 to -0.20) with Agreeableness, Conscientiousness, and Openness. Collectively, the Big Five accounted for over 50% of loneliness variance. In a subsample, the associations were only slightly smaller longitudinally over approximately 10 years. CONCLUSION: Overall, feeling lonely is more closely related to Neuroticism than previously understood, and the association endures over time.

Humans↗

PubMed2026

Applications of quantum AI in brain disorder diagnosis: A systematic review.

BACKGROUND AND OBJECTIVE: Brain disorder diagnosis and prediction remain challenging because neuroimaging, electrophysiological, behavioral, and multimodal data are high-dimensional, noisy, heterogeneous, and limited by small clinical cohorts. This systematic review synthesised applications of quantum artificial intelligence (QAI) for brain disorder diagnosis, prediction, detection, and monitoring. METHODS: Following PRISMA guidelines, studies published from 2016 to 13 January 2026 were retrieved from Scopus, Web of Science, and IEEE Xplore. After screening, 36 studies met the eligibility criteria and were qualitatively analysed according to disorder category, data modality, QAI method, implementation setting, validation strategy, and performance. RESULTS: At the broader disease-group level, neurodegenerative disorders were the most frequently investigated, followed by mental health and psychiatric disorders. At the individual level, Parkinson's disease and schizophrenia were the leading applications, followed by depression, anxiety, Alzheimer's disease, and stress-related tasks. MRI-based modalities were the most frequently used data source, followed by multimodal data and EEG. Methodologically, primary QAI approaches were dominated by quantum neural and QDL architectures, followed by quantum-inspired optimization or feature-selection methods and quantum-kernel/conventional QML classifiers. Qiskit/IBM Quantum and PennyLane were the most frequently reported quantum software frameworks. However, most studies relied on simulators, classical quantum-inspired implementations, or unclear implementation settings, with limited real-hardware evaluation. CONCLUSIONS: QAI shows emerging potential for brain disorder analysis, particularly through hybrid quantum-classical learning, quantum neural architectures, quantum-kernel methods, and quantum-inspired optimization. Nevertheless, current evidence remains preliminary and requires larger datasets, subject-level and external validation, fair classical benchmarking, noise-resilient circuits, real quantum hardware evaluation, explainability, and clinical validation.

Humans↗

PubMed2026

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↗

PubMed2026

Prevalence and risk factors of red blood cell alloimmunization among sickle cell disease patients in resource-limited countries: A systematic review and meta-analysis.

BACKGROUND: Sickle cell disease (SCD) is an inherited hemoglobinopathy characterized by hemoglobin S production, in which homozygous individuals (HbSS) develop a broad range of acute and chronic complications. While disease-modifying and curative therapies are increasingly available in high-income settings, red blood cell (RBC) transfusion remains the mainstay of treatment in resource-limited countries and is associated with high rates of alloimmunization. This systematic review and meta-analysis aimed to estimate the prevalence of alloimmunization and identify associated risk factors among patients with SCD living in resource-limited settings. METHODS: Africa Journals Online (AJOL), Embase, PubMed, Scopus, and Web of Science were searched for original studies published from inception to December 15, 2025. Only studies conducted in low- and lower-middle-income countries (LMICs) were included. Eligible studies evaluated the prevalence of alloimmunization in patients with SCD receiving RBC transfusions. A random-effects meta-analysis of proportions was performed to pool quantitative data, while qualitative findings were systematically summarized in tabular form. Statistical heterogeneity was assessed using the I² statistic and further explored using Baujat plots, leave-one-out analyses, and meta-regression. RESULTS: Our analysis included 27 studies conducted in Africa (n = 23) and Asia (n = 4), predominantly from lower-middle-income countries (n = 19) and mainly employing a cross-sectional design (n = 20), comprising 3128 previously transfused patients with SCD. The pooled prevalence of RBC alloimmunization was 8.76% (95% CI: 6.71-11.37%; I² = 75%). Higher alloimmunization rates were observed in West and North Africa, particularly in Côte d'Ivoire, Egypt, and Nigeria, whereas lower rates were reported in Asia and East Africa. The most frequently identified antibodies belonged to the Rh blood group system (n = 153), followed by the Kell system (n = 65). CONCLUSION: In resource-limited settings, RBC alloimmunization is a frequent and clinically significant complication in patients with SCD, contributing to increased morbidity and potential mortality. Targeted and economically viable antigen matching may reduce alloimmunization rates and improve transfusion safety in LMICs.

Humans↗

PubMed2026

In Situ Hybridization and RT-PCR Detection of Nervous Necrosis Virus in Fourfinger Threadfin, Eleutheronema tetradactylum, in Taiwan.

Between April and July 2020, suspected outbreaks of nervous necrosis virus (NNV) infection were observed in fourfinger threadfin (Eleutheronema tetradactylum) fingerling hatcheries in Pingtung County, southern Taiwan. Affected fish exhibited spiral swimming behaviour and abdominal distension, resulting in mortality rates between 50% and 100%. Histopathological examination showed severe vacuolation in the brain and ocular tissues, with large oval and/or irregular basophilic cytoplasmic inclusion bodies in the brain. Phylogenetic analysis of the viral replicase (RNA1) and capsid protein (RNA2) genes revealed high nucleotide sequence identities among the isolates in this study, with sequence similarity rates of 96.9%-99% for RNA1 and 98.2%-99.0% for RNA2 compared to RGNNV reference strains available in the NCBI GenBank database. This is the first detection of betanodavirus in fourfinger threadfin in Taiwan, using RT-PCR and ISH. A positive correlation between elevated water temperatures and disease severity indicates the need for year-round surveillance and genomic analysis to clarify the epidemiology of FTNNV. The data suggest that infected eggs may facilitate the vertical transmission of Betanodavirus. Crucially, utilising virus-free broodstock, alongside routine health screening and environmental control, is essential for mitigating NNV risks in fourfinger threadfin aquaculture.

Animals↗

PubMed2026

Assessing the Frequency of VEXAS-Related Canonical UBA1 Mutations in Myelodysplastic Syndrome Patients.

OBJECTIVES: Somatic mutations in the UBA1 gene cause VEXAS syndrome, which presents with inflammatory and hematological symptoms. Case studies show a strong overlap between VEXAS and myelodysplastic syndrome (MDS). Recognizing VEXAS is important for differential diagnosis in patients with both inflammation and MDS, as accurate identification guides treatment. The study focuses on determining how often canonical UBA1 mutations linked to VEXAS occur in MDS patients. METHODS: Patients diagnosed with MDS were enrolled in the study, and genomic DNA was isolated from bone marrow FFPE samples. Molecular analysis was performed using a specifically designed ARMS-PCR approach. Additionally, protein-protein interaction (PPI) studies combined with bioinformatic analyses were carried out to explore potential links between UBA1 and pyroptosis. RESULTS: Among the 149 MDS patients analyzed, none exhibited high-Variant Allele Frequency (VAF) the canonical UBA1 point mutations linked to VEXAS syndrome. PPI analysis revealed a possible association between UBA1 and the NLRP3 inflammasome component. CONCLUSIONS: Expanding the sample size and using targeted NGS or ddPCR would improve mutation detection sensitivity and could reveal UBA1 canonical and non-canonical variants and more accurately estimate the frequency of VEXAS-related mutations in the MDS population.

Humans↗

PubMed2026

Behind the Curtain of Care. Nurses' Experiences Providing Care to Consumers With Alcohol and Other Drug Issues: A Qualitative Scoping Review.

AIM: To scope and synthesise qualitative literature relating to nurses' experiences of providing care to consumers with alcohol and other drug issues and explore how meaning is constructed in practice. DESIGN: Scoping review. METHODS: A scoping review was conducted following Arksey and O'Malley's framework. Findings were analysed using thematic analysis. DATA SOURCES: Systematic searches were conducted between September and November 2025 across Medline, Emcare, CINAHL and Google Scholar, using controlled vocabulary and keywords relevant to nurses' experiences of providing care to consumers with alcohol and other drug issues. RESULTS: Twenty-four studies from 12 countries were included. Seven themes were identified: emotional aspects of care, education, training and skills in practice, the spectrum of stigma, ethical issues in professional practice, navigating pain management, limited support, and how meaning is constructed in practice. CONCLUSION: Nurses' experiences of providing care to consumers with alcohol and other drug issues are shaped by multiple intersecting factors influencing care delivery and professional practice. Further research is needed to examine how workplace culture, language and interpersonal interactions influence healthcare experiences, and inform education, service development and support needs. REPORTING METHOD: Reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

alcohol and other drugs↗

PubMed2026

Tripled-Stranded Antisense Oligonucleotide for Biomarker-Activated Suppression of Essential Genes.

Conditional activation of antisense oligonucleotides (ASOs) is a promising strategy for selective suppression of cancer cells without affecting normal cells. In this study, we developed a tripled-stranded ASO (tsASO) that is rendered inactive through complexation with two additional oligonucleotides. The key innovation is the use of partial overlap between the parent ASO and the biomarker sequence, combined with toehold-mediated strand displacement, enabling precise conditional activation. The tsASO effectively triggered RNase H-mediated degradation of DYNC1I2 and DARS1 RNAs exclusively in the presence of the ERBB2 sequence. In cell-free systems, the tsASO demonstrated high cleavage efficiency (up to 81%), comparable to the parent ASO efficiency, with minimal background activity in the absence of the biomarker sequence, validating the concept at the molecular level. However, in cells using lipid-based transfection, the tsASO exhibited nonspecific cytotoxicity that did not correlate with biomarker presence or target gene expression. Detailed analysis showed no clear support for known sequence-driven toxicity mechanisms (CpG/TLR9, G-quadruplexes) in the nonimmune cell lines, suggesting that the primary limitation is intracellular delivery rather than the tsASO design. Future work should focus on optimizing delivery platforms to achieve controlled cellular uptake and biomarker-dependent release, unlocking the therapeutic potential of this conditional gene silencing approach.

Oligonucleotides, Antisense↗

PubMed2026

Influenza as a Less Commonly Recognized Cause of Hemophagocytic Lymphohistiocytosis: A Systematic Review of Case Reports and Case Series.

Hemophagocytic lymphohistiocytosis (HLH) is a life-threatening hyper-inflammatory condition that can be triggered by viral infections. However, influenza is not commonly recognized as a cause of HLH, and there is no comprehensive synthesis of influenza-associated HLH in the literature to guide clinicians. We conducted a systematic search of Pubmed and Embase to identify case reports and case series on influenza-associated HLH, and included 29 articles involving 47 patients. Their age ranged from 2 months to 72 years. 67% were males. Influenza A accounted for 91.3% of the cases, predominantly H1N1 (90.2%). All patients had fever, 60% had anemia, 69.7% had thrombocytopenia, 46.6% had leukopenia, 61.3% had splenomegaly, 71.4% had hypertriglyceridemia, and 94.7% had elevated ferritin levels. 97.6% had hemophagocytosis on biopsy. Antiviral therapy was administered in 89.5% of patients. HLH-directed therapy included corticosteroids (77%), intravenous immunoglobulin (36%), and etoposide (23.1%). Intensive care was required in 95.2% of cases. Overall survival was 53.2%. Survival rate was 50% among patients who received either antiviral therapy alone or HLH-directed therapy alone, compared with 65.4% among those who received both. Further studies are necessary to establish standardized diagnostic and therapeutic protocols for influenza-associated HLH.

Humans↗

PubMed2026

Context matters: coordinated transcriptional regulation and root plasticity under multinutrient conditions.

Plants often encounter simultaneous imbalances in multiple nutrients, but the regulatory logic coordinating their responses remains poorly understood. We aimed to uncover shared transcriptional programs and regulatory nodes underpinning multinutrient adaptation in Arabidopsis thaliana roots. We analyzed publicly available RNA-seq datasets spanning 15 nutrient and beneficial element conditions using differential expression, co-expression network (WGCNA), and gene regulatory network analysis. Selected transcription factors (TFs) were validated via root phenotyping, suberin staining, and ionomic profiling under two-nutrient stress conditions. We identified a core set of 2050 genes responsive to multiple nutrient treatments, enriched for suberin biosynthesis, and structured into modular co-expression clusters. Eight prioritized candidate TFs (ARR10, GBF3, HHO5, NAC32, NF-YA3, NF-YB2, SARD1, and WRKY33) were shown to modulate root system architecture under specific nutrient combinations. WRKY33 and NF-YB2, in particular, regulated nutrient-responsive suberin deposition and ionomic plasticity. These findings reveal suberin remodeling as a shared downstream process in multinutrient responses and suggest that plasticity is not a fixed trait but a modular, polygenic, and context-dependent outcome. Repurposed TFs with pleiotropic functions coordinate structural and physiological traits, providing regulatory entry points for improving nutrient resilience.

Plant Roots↗

PubMed2026

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/m²; 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↗

PubMed2026

The cold case of state transition 7 (stt7) mutants of Chlamydomonas reinhardtii, solved by whole-genome sequencing.

The process of State Transitions (ST) corresponds to an STT7 kinase-driven redistribution of the transmembrane LHCII antenna proteins between Photosystem II (PSII) and Photosystem I (PSI), which results from changes in their phosphorylation state. For the past two decades, two LHCII-kinase mutants, stt7-1 and stt7-9, have been instrumental in the study of STs in Chlamydomonas reinhardtii, the former being a null mutant for the kinase but quasi-sterile in crosses, while the latter, although fertile, has a leaky phenotype. Using long-read sequencing, this study further characterized the genetic lesions of the stt7 mutant strains through whole-genome reconstruction and de novo chromosome assembly. In addition, two new stt7 null mutants were generated, one derived by crosses from the original stt7-1 and one obtained by Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-associated protein 9 (Cas9) technology. This work provides a comprehensive genomic characterization of the original stt7-1 null mutant, revealing extensive chromosomal rearrangements and high levels of aneuploidy, associated with increased cell size and meiotic dysfunction. Reassessment of their physiology and genetic backgrounds highlights the need for caution in interpreting genetic information. We thus produced more reliable null mutants for the LHCII-kinase, amenable to genetic crosses for the study of STs in a variety of genetic backgrounds.

Chlamydomonas reinhardtii↗

Results for “real&#x2010;world evidence”

Results for “real‐world evidence”