Search Results (419)

Cold stress severely limits legume productivity, threatening global food security, particularly in climate-vulnerable regions. This review synthesizes advances in understanding and enhancing cold tolerance in key legumes (chickpea, soybean, lentil, and cowpea), addressing three core questions: (1) molecular/physiological foundations of cold tolerance; (2) how emerging technologies accelerate stress dissection and breeding; and (3) integration strategies and deployment challenges. Legume cold tolerance involves conserved pathways (e.g., ICE-CBF-COR, Inducer of CBF Expression, C-repeat Binding Factor, Cold-Responsive genes) and species-specific mechanisms like soybean’s GmTCF1a-mediated pathway. Multi-omics have identified critical genes (e.g., CaDREB1E in chickpea, NFR5 in pea) underlying adaptive traits (membrane stabilization, osmolyte accumulation) that reduce yield losses by 30–50% in tolerant genotypes. Technologically, AI and high-throughput phenotyping achieve >95% accuracy in early cold detection (3–7 days pre-symptoms) via hyperspectral/thermal imaging; deep learning (e.g., CNN-LSTM hybrids) improves trait prediction by 23% over linear models. Genomic selection cuts breeding cycles by 30–50% (to 3–5 years) using GEBVs (Genomic estimated breeding values) from hundreds of thousands of SNPs (Single-nucleotide polymorphisms). Advanced sensors (LIG-based, LoRaWAN) enable real-time monitoring (±0.1 °C precision, <30 s response), supporting precision irrigation that saves 15–40% water while maintaining yields. Key barriers include multi-omics data standardization and cost constraints in resource-limited regions. Integrating molecular insights with AI-driven phenomics and multi-omics is revolutionizing cold-tolerance breeding, accelerating climate-resilient variety development, and offering a blueprint for sustainable agricultural adaptation. Full article

Background: Metabolic diseases, like type 2 diabetes mellitus and obesity, show a growing public health concern in Sri Lanka. Genetic predisposition and diet contribute to metabolic disease risk, but there are limited investigations into the impact of gene–diet interactions on metabolic disease risk in the Sri Lankan population. In this study, we examined whether a metabolic genetic risk score (GRS), constructed from 10 single nucleotide polymorphisms (SNPs), interacts with dietary factors to influence metabolic health indicators in Sri Lankan adults. Methods: This cross-sectional study included 105 generally healthy adults aged 25–50 years from the GOOD (Genetics of Obesity and Diabetes) study. Anthropometric, biochemical, and dietary data using food frequency questionnaires were collected using validated methods. Genotyping was performed using the KASP^® assay. The unweighted GRS was calculated by summing risk alleles across 10 SNPs in the TCF7L2, CAPN10, FTO KCNJ11, and MC4R genes. Gene–diet interaction analysis was conducted using regression models adjusted for confounders. Results: A statistically significant interaction was identified between the 10-SNP metabolic GRS and polyunsaturated fatty acid (PUFA) intake on waist circumference (P_{(interaction)} = 0.00009). Participants with a high GRS (≥6 risk alleles) and higher PUFA intake (≥3.1 g/day) exhibited significantly lower waist circumference (p = 0.047). Conclusions: This study provides novel insights to understand gene–diet interactions affecting metabolic traits in Sri Lankans. The findings suggest that higher PUFA intake may mitigate genetic susceptibility to central obesity, highlighting the importance of personalized dietary recommendations for metabolic disease prevention. Further studies in larger cohorts are warranted to confirm this finding. Full article

Background: Increased hip-flexion gait (HFgait) has been shown to promote increased aerobic demands by increasing peak swing-phase hip-flexion angles while walking at comfortable speeds. Biomechanically, HFgait produces a gait pattern similar to walking, while removing the flight phase from running and reducing tibial accelerations. We sought to identify knee joint contact forces between HFgait and common exercise modalities, including running, walking, and cycling, across intensity levels. Methods: Ten healthy participants completed two bouts (low and high intensity) of four different exercises: treadmill running, walking, HFgait, and cycling. Tibiofemoral joint compressive force (TCF) was estimated using a static optimization-based approach. Results: Peak TCF was greater in running compared to HFgait, walking, and cycling; greater in HFgait compared to cycling; and greater in walking compared to cycling. The integral of TCF (iTCF) was greater in running compared to cycling, greater in HFgait compared to running, walking, and cycling, and greater in walking compared to running and cycling. Conclusions: HFgait produced lower knee joint loading than running, comparable joint loading to walking, and greater joint loading than cycling. Thus, HFgait may serve as an exercise modality for populations where joint loading is of particular concern, while achieving aerobic demands similar to running or increased functional demands compared to stationary cycling. Full article

Acute lymphoblastic leukemia (ALL) represents the most common type of cancer in the pediatric population. The (1;19)(q23;p13) translocation is a primary chromosomal abnormality present in 3–12% of ALL cases. The current study aims to develop a label-free innovative nanodevice for the ultrasensitive diagnosis of the TCF3-PBX1 chimeric oncogene, featuring simplified operation and rapid analysis using minimal sample volumes, which positions it as a superior alternative for clinical diagnostics and early leukemia identification. The biosensor system was engineered on a nanostructured platform composed of polypyrrole (PPy) and a novel chemically functionalized hybrid nanocomposite of platinum nanospheres and titanium dioxide nanoparticles (TiO₂@Pt). Single-stranded oligonucleotide sequences were chemically immobilized on the nanoengineered transducer to enable biospecific detection. Cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), ultraviolet-visible spectroscopy (UV-Vis), and atomic force microscopy (AFM) were used to characterize each stage of the biotechnological device fabrication process. The analytical properties of the sensing tool were explored using recombinant plasmids containing the TCF3-PBX1 oncogenic sequence and clinical specimens from pediatric patients with B-cell ALL. After exposing the molecular monitoring system to the genetic target, significant variations were observed in the voltammetric oxidation current (∆I = 33.08% ± 0.28 to 124.91% ± 17.08) and in the resistance to charge transfer (ΔR_CT = 19.73% ± 0.96 to 83.51% ± 0.84). Data analysis revealed high reproducibility, with a relative standard deviation of 3.66%, a response range from 3.58 aM to 357.67 fM, a detection limit of 19.31 aM, and a limit of quantification of 64.39 aM. Therefore, a novel nanosensor for multiparametric electrochemical screening of the TCF3-PBX1 chimeric oncogene was described for the first time, potentially improving the quality of life for leukemic patients. Full article

Background/Objectives: The transcription factor 7-like 2 (TCF7L2) rs7903146 polymorphism has been strongly associated with type 2 diabetes mellitus (T2DM) in various populations; however, its impact on different ethnic groups is not fully understood. Given the distinct minor allele frequency in Chinese populations, this study aimed to analyze the association of rs7903146 with the risk of T2DM in a Han Chinese cohort and its relationship with relevant clinical parameters. Methods: We conducted a case–control study including 600 patients with type 2 diabetes mellitus (T2DM) and 511 sex-matched non-diabetic controls of Han Chinese descent. The TCF7L2 rs7903146 (C/T) polymorphism was genotyped using a TaqMan™ SNP assay. Clinical parameters, including body mass index (BMI), fasting plasma glucose, hemoglobin A1c, lipid profile, and high-sensitivity C-reactive protein (hs-CRP), were compared between genotypes. Logistic regression analyses were performed under a dominant genetic model (CT/TT vs. CC), adjusting for age, sex, systolic and diastolic blood pressure, BMI, and smoking status. Subgroup analyses were conducted by sex, BMI category, age at diagnosis, and family history of T2DM. Given the exploratory nature of this study and the low frequency of the TT genotype, no formal correction for multiple testing was applied. Results: Frequencies of the CT and TT genotypes were higher in the diabetic group (p = 0.045) and were significantly associated with an increased risk of T2DM under a dominant genetic model (adjusted OR = 2.24, p = 0.025). Individuals with CT/TT genotypes had elevated fasting glucose and hs-CRP levels; these genotypes were also linked to higher BMI in the female T2DM patients. The T allele frequency varied across ethnic groups, being lowest in East Asians and highest in Latin (Brazilian/mixed ancestry) populations. Mechanistically, the T allele may contribute to T2DM via altered TCF7L2 expression, impaired insulin secretion, inflammation, and metabolic dysregulation. Conclusions: The TCF7L2 rs7903146 T allele was associated with an increased risk of T2DM and higher fasting glucose and hs-CRP levels in this Han Chinese cohort. The CT/TT genotypes were also associated with higher BMI in the female T2DM patients. While the findings are consistent with the known effects of this variant in other populations, mechanistic hypotheses such as the involvement of inflammatory or metabolic pathways remain hypothetical and warrant further functional validation. Full article

This study examines the impact of overall Environmental, Social, and Governance (ESG) performance and its pillars on the default probability of Australian-listed firms. Using a panel dataset spanning 2014 to 2022 and applying the Generalized Method of Moments (GMM) regression, we find that firms with higher ESG scores exhibit a significantly lower likelihood of default. Disaggregating the ESG components reveals that the Environmental and Social pillars have a negative association with default risk, suggesting a risk-mitigating effect. In contrast, the Governance pillar demonstrates a positive relationship with default probability, which may reflect potential greenwashing behavior or an excessive focus on formal governance mechanisms at the expense of operational and financial performance. Furthermore, the analysis identifies trade credit financing (TCF) as a partial mediator in the ESG–default risk nexus, indicating that firms with stronger ESG profiles rely less on external short-term financing, thereby reducing their default risk. These findings provide valuable insights for corporate management, investors, regulators, and policymakers seeking to enhance financial resilience through sustainable practices. Full article

Background: Angiosarcomas (ASs) represent a heterogeneous and highly aggressive subset of tumors that respond poorly to systemic treatments and are associated with short progression-free survival (PFS) and overall survival (OS). The aim of this study was to develop and validate an immune-related prognostic model—termed the AS score—using data from two independent sarcoma cohorts. Methods: A prognostic model was developed using a previously characterized cohort of 25 angiosarcoma samples. Candidate genes were identified via the Maxstat algorithm (Maxstat v0.7-25 for R), combined with log-rank testing. The AS score was then computed by weighing normalized gene expression levels according to Cox regression coefficients. For external validation, transcriptomic data from TCGA Sarcoma cohort (n = 253) were analyzed. The Immunoscore—which reflects the tumor immune microenvironment—was inferred using the ESTIMATE package (v1.0.13) in R. All statistical analyses were performed in RStudio (v 4.0.3). Results: Four genes—IGF1R, MAP2K1, SERPINE1, and TCF12—were ultimately selected to construct the prognostic model. The resulting AS score enabled the classification of angiosarcoma cases into two prognostically distinct groups (p = 0.00012). Cases with high AS score values, which included both cutaneous and non-cutaneous forms, exhibited significantly poorer outcomes, whereas cases with low AS scores were predominantly cutaneous. A significant association was observed between the AS score and the Immunoscore (p = 0.025), with higher Immunoscore values found in high-AS score tumors. Validation using TCGA sarcoma cohort confirmed the prognostic value of both the AS score (p = 0.0066) and the Immunoscore (p = 0.0029), with a strong correlation between their continuous values (p = 2.9 × 10⁻⁸). Further survival analysis, integrating categorized scores into four groups, demonstrated robust prognostic significance (p = 0.00021). Notably, in tumors with a low Immunoscore, AS score stratification was not prognostic. In contrast, among cases with a high Immunoscore, the AS score effectively distinguished outcomes (p < 0.0001), identifying a subgroup with poor prognosis but potential sensitivity to immunotherapy. Conclusions: This combined classification using the AS score and Immunoscore has prognostic relevance in sarcoma, suggesting that angiosarcomas with an immunologically active microenvironment (high Immunoscore) and poor prognosis (high AS score) may be prime candidates for immunotherapy and this approach warrants prospective validation. Full article

Background: Glioblastoma (GBM) is one of the most challenging malignancies in all of neoplasms. These malignancies are associated with unfavorable clinical outcomes and significantly compromised patient wellbeing. The immunological landscape within the tumor microenvironment (TME) plays a critical role in determining GBM prognosis. By mining data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and correlating them with immune responses in the TME, genes associated with the immune microenvironment with potential prognostic value were obtained. Method: We selected GSE16011 as the training set. Gene expression profiles were substrates scored by both ESTIMATE and xCell, and immune cell subpopulations in GBM were analyzed by CIBERSORT. Gene expression profiles associated with low immune scores were performed by lasso regression, Cox analysis and random forest (RF) to identify a prognostic model for the multiple genes associated with immune infiltration in GBM. Then we constructed a nomogram to optimize the prognostic model using GSE7696 and TCGA-GBM as validation sets and evaluated these data for gene mutation and gene enrichment analysis. Result: The prognostic correlation between the six genes (MEOX2, PHYHIP, RBBP8, ST18, TCF12, and THRB) and GBM was finally found by lasso regression, Cox regression, and RF, and the online database obtained that all six genes were differentially expressed in GBM. Therefore, a prognostic correlation model was constructed based on the six genes. Kaplan–Meier (KM) survival analysis showed that this prognostic model had excellent prognostic ability. Conclusions: Prognostic models based on tumor microenvironment and immune score stratification and the construction of related genes have potential applications for prognostic analysis of GBM patients. Full article

B-lineage acute lymphoblastic leukemia (B-ALL) is classified into more than 20 molecular subtypes, and next-generation sequencing has facilitated the identification of these with high sensitivity. Bulk RNA-seq analysis of bone marrow was realized to identify molecular subtypes in Mexican pediatric patients with B-ALL. High hyperdiploidy (27.3%) was the most frequent molecular subtype, followed by DUX4 (13.6%), TCF3::PBX1 (9.1%), ETV6::RUNX1 (9.1%), Ph-like (9.1%), ETV6::RUNX1-like (9.1%), PAX5alt (4.5%), Ph (4.5%), KMT2A (4.5%), and ZNF384 (4.5%), with one patient presenting both the PAX5alt and low hypodiploidy subtypes (4.5%). The genes TYK2, SEMA6A, FLT3, NRAS, SETD2, JAK2, NT5C2, RAG1, and SPATS2L harbor deleterious missense variants across different B-ALL molecular subtypes. The Ph-like subtype exhibited mutations in STAT2, ADGRF1, TCF3, BCR, JAK2, and NRAS with overexpression of the CRLF2 gene. The DUX4 subtype showed mutually exclusive missense variants in the PDGRFA gene. Here, we have demonstrated the importance of using RNA-seq to facilitate the differential diagnosis of B-ALL with successful detection of gene fusions and mutations. This will aid both patient risk stratification and precision medicine. Full article

The flexible transparent conductive films (TCFs) of a ZnS/Cu/Ag/TiO₂ multilayered structure were deposited on a flexible PET substrate with high surface roughness using magnetic sputtering, and the effects of structural characteristics on the performance of the films were analyzed. The TCFs with TiO₂/Cu/Ag/TiO₂ and ZnS/Cu/Ag/ZnS symmetric structures were also prepared for comparison. The TCF samples were deposited using ZnS, TiO₂, Cu and Ag targets, and they were analyzed using scanning electronic microscopy, atomic force microscopy, grazing incidence X-ray diffraction, spectrophotometry and a four-probe tester. The TCFs exhibit generally uniform surface morphology, excellent light transmittance and electrical conductivity with optimized structure. The optimal values are 84.40%, 5.52 Ω/sq and 33.19 × 10⁻³ Ω⁻¹ for the transmittance, sheet resistance and figure of merit, respectively, in the visible spectrum. The satisfactory properties of the asymmetric multilayered TCF deposited on a rough-surface substrate should be mainly attributed to the optimized structure parameters and reasonable interfacial compatibilities. Full article

β-catenin is a key regulator of osteoblast differentiation, proliferation, and bone homeostasis. Through its interaction with transcription factors such as TCF/LEF, Runx2, and Osx, it coordinates gene expression essential for osteogenesis. The aim of this review is to demonstrate how β-catenin signaling is modulated by various physiological and pathological factors, including mechanical loading, oxidative stress, HIV-1 gp120, fluoride, implant topography, and microRNAs. These factors influence Wnt/β-catenin signaling through different mechanisms, often exerting opposing effects on osteoblast function. By integrating these modulators, we provide a comprehensive view of the dynamic regulation of β-catenin in bone biology. Understanding this complexity may provide insight into novel therapeutic strategies targeting β-catenin in bone regeneration, metabolic bone diseases, and pathologies such as HIV-associated bone loss or osteosarcoma. Full article

The monsoon is regarded as a key system influencing tropical cyclone (TC) activity over the Western North Pacific (WNP). However, the relationship between WNP TC frequency (TCF) and the monsoon across different timescales remains incompletely understood. This study explores the interannual-scale relationship between WNP TCF and the WNP summer monsoon over the period 1982–2020. We found that the interannual variation in basin-scale TCF is dominated by dynamic factors, particularly lower troposphere vorticity and middle troposphere ascending motion, which are driven by the WNP summer monsoon. Enhanced monsoonal precipitation over the WNP intensifies convective heating, which acts as a diabatic heat source and triggers a Rossby wave response to the west. This response generates anomalous lower troposphere cyclonic circulation and ascending motion in the main TC development region. In turn, the strengthened WNP summer monsoon circulation further amplifies precipitation, establishing positive feedback between atmospheric circulation and convection. This mechanism establishes dynamic conditions favorable for TC genesis, thereby dominating the basin-scale interannual variation in TCF. Full article

Colorectal cancer remains a leading malignancy. As the aberrant activation of Wnt/β-catenin signaling causes colorectal cancer, Wnt/β-catenin signaling inhibitors are potential candidates for colorectal cancer treatment. Our drug screening platform identified ursolic acid (UA), a triterpenoid with various biological activities, as a potential anticancer drug because it inhibits the T-cell factor (TCF)/β-catenin-mediated transcriptional activity. Here, we discovered that UA inhibited Wnt signaling by reducing the Wnt reporter activity and Wnt target gene expression, leading to a delay in cell cycle progression and the suppression of cell proliferation. Stepwise epistatic analyses suggested that UA functions on β-catenin protein stability in Wnt signaling. Further studies revealed that UA reduced β-catenin protein levels by Western blotting and immunofluorescent staining and induced autophagy by microtubule-associated protein 1 light chain 3 beta (LC3B) punctate staining. The cotreatment with UA and the autophagy inhibitors chloroquine and wortmannin recovered the β-catenin protein levels. Therefore, UA was confirmed to induce β-catenin degradation by the autophagy–lysosomal degradation system through inhibition in the phosphatidylinositol 3-kinase (PI3K)/Ak strain transforming (protein kinase B; AKT)/mammalian target of rapamycin (mTOR) signaling pathway. Our results not only highlight the potential of UA in Wnt-driven colorectal cancer therapy but also provide a workable Wnt signaling termination approach for the treatment of other Wnt-related diseases. Full article

The advancement of harvester technology increasingly relies on automated forest analysis within machine operational ranges. However, real-world testing remains costly and time-consuming. To address this, we introduced the Tree Classification Framework (TCF), a simulation platform for the cost-effective testing of harvester technologies. TCF accelerates technology development by simulating forest environments and machine operations, leveraging machine-learning and computer vision models. TCF has four components: Synthetic Forest Creation, which generates diverse virtual forests; Point Cloud Generation, which simulates LiDAR scanning; Stem Identification and Classification, which detects and characterises tree stems; and Experimental Evaluation, which assesses algorithm performance under varying conditions. We tested TCF across ten forest scenarios with different tree densities and morphologies, using two-point cloud generation methods: fixed points per stem and LiDAR scanning at three resolutions. Performance was evaluated against ground-truth data using quantitative metrics and heatmaps. TCF bridges the gap between simulation and real-world forestry, enhancing the harvester technology by improving efficiency, accuracy, and sustainability in automated tree assessment. This paper presents a framework built from affordable, standard components for stem identification and classification. TCF enables the systematic testing of classification algorithms against known ground truth under controlled, repeatable conditions. Through diverse evaluations, the framework demonstrates its utility by providing the necessary components, representations, and procedures for reliable stem classification. Full article

Background/Objectives: This study aimed to evaluate the relationship between sirtuin family members (SIRT1, SIRT3, and SIRT6) and Wnt/β-catenin pathways with inflammation during the rejection process following kidney transplantation, as well as to explore their potential roles as candidate biomarkers. Materials and Methods: Blood samples were collected from 35 kidney transplant rejection patients and 30 healthy controls. The gene expression levels of SIRT1, SIRT3, SIRT6, and Wnt/β-catenin pathway components were measured using real-time PCR, and miRNA and lncRNA expression levels were analyzed. Statistical analyses were performed using SPSS version 23. Results: Significant alterations in SIRT1, SIRT3, and SIRT6 expression levels were observed in rejection patients, suggesting their potential role in disease pathogenesis and as therapeutic biomarkers. Key altered genes included hsa-miR-34c-1, hsa-miR-122b-5b, MALAT1, HOTAIR, LINC00473, TUG, PVT1, SIRT1, SIRT3, SIRT6, WNT1, TCF-LEF, LRP, AXIN1, IL1B, IL6, and IFNB1, all showing significant changes. However, no significant differences were found for miRNAs such as hsa-miR-21-2, hsa-miR-155-5p, and hsa-miR-200b-3p. SIRT1 expression was significantly decreased in the cellular rejection group, with a more pronounced reduction in these patients. Significant differences in SIRT1 expression were observed with interstitial inflammation and glomerulitis. Increased inflammation severity correlated with decreased SIRT1 and increased TCF-LEF, TUG, and miR-21 levels, while tubulitis severity was associated with elevated TCF-LEF and miR-155 expression. Conclusions: Along with the activation of Wnt/β-catenin pathways and increased levels of certain miRNAs and long non-coding RNAs (lncRNAs) associated with TCF-LEF transcription factors, the observed decrease in SIRT1 expression may be related to the severity of inflammation and tubulitis. These findings suggest that SIRT1, Wnt/β-catenin pathways, and non-coding RNAs play a role in the rejection process following kidney transplantation and could be considered as potential biomarkers or therapeutic target candidates for future research. Full article