Browse Articles

Exploring PKMYT1 as a potential marker for colorectal cancer progression through bioinformatics analyses and experimental validation

Experimental and simulation study of shielding features of polyester/HgO composites against photons using GEANT4 and MCNP codes

Unveiling the subsurface geological structure of the centre region, cameroon, with aeromagnetic data analysis

Assessment of off-road agricultural traction in situ using large scale machine learning and neurocomputing models

The antibacterial and photocatalytic properties of copper and tin doped titanium dioxide nanoparticles for the nano remediation of pesticide residues in soil

Effect of age-related hyperkyphosis on open and closed-loop postural control in older adults

Multireference diffusion Monte Carlo reaches 2D materials

Abstract Quantum confinement in 2D materials strongly enhances electronic correlation effects. Therefore, predicting the properties of these unique materials, with both a high level of accuracy and computational efficiency, without relying on adjustable parameters or functionals, remains an outstanding theoretical challenge. The majority of theoretical studies are based on the approximations of density functional theory (DFT). The reliability of DFT predictions are heavily dependent on the choice of an approximated exchange-correlation functional. Here, we estimate the magnitude of impact of correlation on the total energy for the quintessential 2D material, graphene, by performing and comparing state-of-the-art selected CI and quantum Monte Carlo extrapolated calculations for a single unit cell at the $$\Gamma$$ point. We demonstrate that Self-Healing Diffusion Monte Carlo (SHDMC) obtains a very compact, but high-quality wavefunction for this system that lacks the strong basis set dependence displayed by state of the art quantum chemistry methods. The SHDMC wavefunction is of higher quality compared to that obtained from sCI, in the same orbital basis, while being $$\sim$$  1000 times smaller in terms of determinant count compared to sCI. We also demonstrate that extrapolating SHDMC results to the infinite determinant limit compares extremely well with complete basis set extrapolated sCI. Our work paves the way for future validation of SHDMC applied to challenging 2D materials.

Identification of biomarkers associated with mitophagy in bladder cancer

Comprehensive hydrogeochemical characterization and seasonal water quality index analysis for sustainable groundwater management in Valliyur region, Southern Tamil Nadu, India

An optimized tissue sampling scheme guided by MRI features reveals intratumoral heterogeneity in glioblastoma

Clinical application value of erythroferrone (ERFE) and hepcidin in pregnant women with thalassemia and iron-deficiency anemia: a comprehensive study

Exploration of effective biomarkers and infiltrating immune cells in metastatic colorectal cancer based on bioinformatics analysis

Abstract Colorectal cancer (CRC) ranks as the third most prevalent malignancy globally and represents the second leading cause of cancer-related mortality worldwide. Metastatic colorectal cancer (mCRC) is clinically classified as an advanced-stage malignancy, characterized by therapeutic resistance and substantially diminished survival outcomes. The 5-year survival rate for mCRC is significantly lower than that for early-stage CRC. A multi-dimensional computational framework was implemented to dissect CRC transcriptomics. Gene expression profiles were systematically acquired from TCGA and GEO repositories. A series of data were then analyzed using ssGSEA algorithm, xCell algorithm, edgeR, limma, DAVID enrichment analysis, CytoHubba, ROC logistic regression and correlation analysis. Immune cell infiltration analysis revealed 7 tumor-infiltrating immune cell subtypes exhibiting significant abundance disparities between metastatic and non-metastatic colorectal cancer cohorts. Further integrative analysis identified 28 immune-related metastatic colorectal cancer differentially expressed genes (ICDEGs) in metastatic lesions. Through comprehensive analysis, 9 pivotal hub genes (AGTR1, CD86, CMKLR1, FGF1, FYN, IL10RA, INHBA, TNFSF13B, and VEGFC) were successfully identified. Notably, AGTR1, CD86, CMKLR1 and TNFSF13B genes have been rarely reported in mCRC. Furthermore, our correlation studies revealed significant inverse relationships between epithelial cells and three specific genes: TNFSF13B, CD86, and IL10RA. The identified 9 hub genes demonstrate significant potential as reliable diagnostic biomarkers for mCRC. Moreover, these molecular markers may contribute to disease pathogenesis through their dynamic interactions with tumor-infiltrating immune cells, suggesting a crucial role in the tumor microenvironment.

Prediction of personalized antiseizure medications response based on clinical signatures in epilepsy

Combined albumin and CEA improve prognostic prediction in resectable gastric cancer

Genomic location of stripe rust resistance in a hexaploid derivative of durum wheat Glossy Huguenot and development of closely linked markers

Abstract Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is a devastating fungal disease that affects wheat production in many regions of the world. The identification and characterisation of new sources of host plant resistance is required to enrich the existing gene pool. Durum wheat landrace Glossy Huguenot showed high level of resistance to stripe rust in the field. To utilise this resistance in wider wheat germplasm, we transferred it to common wheat cultivar Westonia. A backcross2F5 (BC2F5) line (WGH54) which showed high levels of all stage resistance against the then prevalent Pst pathotypes was crossed with the susceptible parent Avocet S (AvS) and F2:3 generation was raised. Monogenic segregation was observed among WGH54/AvS F2:3 families. Bulked segregant analysis using iSelect wheat 90 K Infinium SNP array mapped the stripe rust resistance on chromosome 2A. The gene was temporarily named as YRWGH54. Single nucleotide polymorphism (SNP) markers were used to refine the location of YRWGH54. Genotyping showed chromosomal rearrangements in this genomic region when compared with the Chinese Spring (CS) reference sequence. Stripe rust resistance gene YR32 was located on chromosome 2AL previously and markers linked with it were mapped in the same region as YRWGH54. Greenhouse tests with recent Pst pathotypes showed same virulence/avirulence specificity suggesting that YRWGH54 and YR32 may be the same. Closely linked KASP markers identified in this study will be useful for marker assisted pyramiding of YRWGH54 with other marker-tagged stripe rust resistance genes in future wheat cultivars to achieve durable control.

Gene expression data mining by hybrid biclustering with improved GA and BA

Importin-7 promotes tension-induced osteogenesis by regulating RUNX2 nuclear translocation during orthodontic tooth movement

Nitric oxide and arginine mitigate salt stress through physio-biochemical modulations and ions regulation in Brassica napus L.

Exploring trajectories of acute kidney injury in the intensive care unit: a population-based cohort study

Abstract Acute kidney injury (AKI) represents a complex disorder characterized by distinct subphenotypes with varied clinical presentations and prognoses. Categorizing these subphenotypes may facilitate standardization of research cohorts and optimization of therapeutic strategies. The endothelial activation and stress index (EASIX) quantifies thrombotic microangiopathy severity, a pathophysiological hallmark of AKI. Consequently, we utilized EASIX trajectory analysis to identify AKI subphenotypes. AKI patients were identified from the eICU Collaborative Research Database to develop a group-based trajectory model. EASIX scores recorded during the initial seven ICU days were utilized for trajectory modeling. Patients were stratified into distinct subgroups according to the best model. Variable selection was performed using LASSO regression, followed by multivariate Cox regression analyses to calculate hazard ratios (HRs) across the identified subgroups. An independent validation cohort comprised patients from the central ICU of West China Hospital (WCH). The study’s primary endpoints included all-cause in-ICU and in-hospital mortality across the identified subphenotypes. The final analysis included 317 patients from the eICU database and 58 patients from WCH. Based on the EASIX trajectories derived from the first seven ICU days, we identified two distinct subphenotypes: a “Stably High” (SH) group and a “Decreasing” (D) group. Compared to the D group, the SH group demonstrated significantly higher mortality risk, with an HR of 2.26 (95% CI 1.14–4.26, p = 0.018) for ICU mortality and 1.85 (95% CI 1.03–3.29, p = 0.038) for 30-day in-hospital mortality. These findings were replicated in the WCH validation cohort. This study identified and validated two distinct AKI subphenotypes through EASIX trajectory analysis, demonstrating significant heterogeneity in clinical characteristics, laboratory findings, comorbidities, and outcomes between these groups. Future research may focus on early subphenotype prediction, differential treatment responses, and molecular mechanisms driving inter-group variation.

Fabrication and analysis of nanoemulsion-based edible films loaded with vitamin D3 and Cordia myxa mucilage

Abstract This study developed a biodegradable nanoemulsion-based edible film containing encapsulated vitamin D3 and Cordia myxa (CM) mucilage to replace synthetic packaging. The mucilage showed strong antimicrobial activity against gram-positive bacteria, 67.4% antioxidant activity, and 218.2 µg/g flavonoid content. Nanoemulsions with various mucilage concentrations were characterized, and the best encapsulation efficiency (91.5%) was observed in the En1 sample. Films with encapsulated nanoemulsions demonstrated reduced water vapor permeability, lower solubility, improved thermal stability, and higher vitamin D3 retention over 14 days. FTIR analysis confirmed polysaccharides as the main component, supporting film biocompatibility. These findings suggest a promising, eco-friendly packaging solution using CM mucilage.