Search Results (2,585)

Quinoa (Chenopodium quinoa), a stress-tolerant pseudocereal ideal for studying abiotic stress responses, was used to systematically identify optimal reference genes for qPCR normalization under gradient stresses: low temperatures (LT group: −2 °C to −10 °C), heat (HT group: 39° C to 45 °C), and drought (DR group: 7 to 13 days). Through multi-algorithm evaluation (GeNorm, NormFinder, BestKeeper, the ΔCt method, and RefFinder) of eleven candidates, condition-specific optimal genes were established as ACT16 (Actin), SAL92 (IT4 phosphatase-associated protein), SSU32 (Ssu72-like family protein), and TSB05 (Tryptophan synthase beta-subunit 2) for the LT group; ACT16 and NRP13 (Asparagine-rich protein) for the HT group; and ACT16, SKP27 (S-phase kinase), and NRP13 for the DR group, with ACT16, NRP13, WLIM96 (LIM domain-containing protein), SSU32, SKP27, SAL92, and UBC22 (ubiquitin-conjugating enzyme E2) demonstrating cross-stress stability (global group). DHDPS96 (dihydrodipicolinate synthase) and EF03 (translation elongation factor) showed minimal stability. Validation using stress-responsive markers—COR72 (LT), HSP44 (HT), COR413-PM (LT), and DREB12 (DR)—confirmed reliability; COR72 and COR413-PM exhibited oscillatory cold response patterns, HSP44 peaked at 43 °C before declining, and DREB12 showed progressive drought-induced upregulation. Crucially, normalization with unstable genes (DHDPS96 and EF03) distorted expression profiles. This work provides validated reference standards for quinoa transcriptomics under abiotic stresses. Full article

Transcription factors play crucial roles in regulating gene expression, and any dysregulation in their levels could be involved in cancer progression. The role of androgen receptors (AR) and zinc finger (ZNF) proteins in tumors, like prostate cancer (PC), remains poorly understood. Moreover, due to the multifaceted transcriptional behavior of ARs and ZNFs, their biological role in cancer progression may also depend on the interplay with micro-RNAs (miRNAs). Based on The Cancer Genome Atlas (TCGA) database, we analyzed the expression levels of zinc finger transcripts and ARs in PC. Specifically, exploring their involvement in cancer progression and regulation by miRNAs. The analysis relied on several tools to create a multivariate combination of the original biomarkers to improve their diagnostic efficacy. Multidimensional Scaling (MDS) identified two new dimensions that were entered into a regression analysis to determine the best predictors of overall survival (OS) and disease-free interval (DFI). A combination of both dimensions predicted almost 50% (R² = 0.46) of the original variance of OS. Kaplan–Meier survival analysis also confirmed the significance of these two dimensions regarding the clinical output. This study showed preliminary evidence that several transcription factor expression levels belonging to the zinc family and related miRNAs can effectively predict patients’ overall PC survivability. Full article

Hereditary ataxias are a highly heterogenous group of diseases characterized by loss of coordination. In this study, we investigated a family of random-bred dogs, in which two siblings were affected by a slowly progressive ataxia. They presented with clinical signs of progressive cerebellar ataxia, hypermetria, and absent menace response. The MRI revealed generalized brain atrophy, reduced cortical demarcation, hypoplastic corpus callosum, and cerebellar folia thinning, highly suggestive of a neurodegenerative disorder. We sequenced the genomes of the two affected dogs and their unaffected parents. Filtering for protein-changing variants that had homozygous alternate genotypes in the affected dogs, heterozygous genotypes in the parents, and homozygous reference genotypes in 1576 control genomes yielded a single missense variant in the RAB24 gene, XM_038534663.1:c.239G>T or XP_038390591.1:p.(Gly80Val). Genotypes at this variant showed the expected co-segregation with the ataxia phenotype in the investigated family. The predicted amino acid affects the conserved RabF4 motif. Glycine-80 resides at the protein surface and the introduction of a hydrophobic isopropyl side chain of the mutant valine might impede solvent accessibility. Another missense variant in RAB24, p.Glu38Pro, was previously reported to cause a clinically similar form of cerebellar ataxia in Gordon Setters and Old English Sheepdogs. Taken together, the available data suggest that RAB24:p.Gly80Val represents the causal variant in the studied dogs. To the best of our knowledge, this is only the second report of a potentially pathogenic RAB24 variant in any species and further supports that RAB24 should be considered a candidate gene in human ataxia patients with unclear molecular etiology. Full article

This study measured eight key phenotypic traits across 259 fresh maize inbred lines, including plant height and spike length. A total of 82 single nucleotide polymorphisms (SNPs) significantly associated with these phenotypes were identified by applying a mixed linear model to calculate the best linear unbiased prediction (BLUP) values and integrating genome-wide genotypic data through genome-wide association analysis (GWAS). A further analysis of significant SNPs contributed to the identification of 63 candidate genes with functional annotations. Notably, 11 major candidate genes were identified from multi-trait association loci, all of which exhibited highly significant P-values (<0.0001) and explained between 7.21% and 12.78% of phenotypic variation. These 11 genes, located on chromosomes 1, 3, 4, 5, 6, and 9, were functionally involved in signaling, metabolic regulation, structural maintenance, and stress response, and are likely to play crucial roles in the growth and physiological processes of fresh maize inbred lines. The functional genes identified in this study have significant implications for the development of molecular markers, the optimization of breeding strategies, and the enhancement of quality in fresh maize. Full article

Background/Objectives: Genetic polymorphisms in the BRCA2 gene have been implicated in breast cancer susceptibility. While numerous studies have investigated this polymorphism, its precise role in breast cancer development remains unclear. Furthermore, to the best of our knowledge, no related studies have been conducted in Azerbaijan. The aim of this study was to determine the distribution of the BRCA2 Met1915Thr polymorphism (rs4987117) in the Azerbaijani population and to evaluate its potential association with breast cancer risk. Methods: A total of 144 breast cancer patients and 152 healthy controls were recruited from the Oncology Clinic of Azerbaijan Medical University between 2021 and 2024. The Met1915Thr polymorphism was genotyped using PCR-RFLP and visualized on a 2% agarose gel. Results: A statistically significant association with increased breast cancer susceptibility was observed for the heterozygous Met/Thr genotype (OR = 1.83, 95%CI = 1.08–3.11, p = 0.02), the Thr allele (OR = 1.57, 95%CI = 1.12–2.20, p = 0.008), and under the dominant inheritance model (OR = 1.83, 95%CI = 1.15–2.90, p = 0.01). Notably, this association was more evident among individuals aged over 58 years, in whom the Met/Thr genotype conferred a significantly elevated risk (OR = 2.35, 95%CI = 1.17–4.73, p = 0.02). Conclusions: The BRCA2 Met1915Thr polymorphism is associated with an increased risk of breast cancer in the Azerbaijani population. These findings suggest a potential role of this polymorphism in breast cancer susceptibility and highlight the need for further studies in larger cohorts to validate these associations. Full article

This study analyzed the heavy metal tolerance and chromium reduction and the potential of plant growth to promote Rhizobium sp. OS-1. By genetic makeup, the Rhizobium strain is nitrogen-fixing and phosphate-solubilizing in metal-contaminated agricultural soil. Among the Rhizobium group, bacterial strain OS-1 showed a significant tolerance to heavy metals, particularly chromium (900 µg/mL), zinc (700 µg/mL), and copper. In the initial investigation, the bacteria strains were morphologically short-rod, Gram-negative, appeared as light pink colonies on media plates, and were biochemically positive for catalase reaction and the ability to ferment glucose, sucrose, and mannitol. Further, bacterial genomic DNA was isolated and amplified with the 16SrRNA gene and sequencing; the obtained 16S rRNA sequence achieved accession no. HE663761.1 from the NCBI GenBank, and it was confirmed that the strain belongs to the Rhizobium genus by phylogenetic analysis. The strain’s performance was best for high hexavalent chromium [Cr(VI)] reduction at 7–8 pH and a temperature of 30 °C, resulting in a total decrease in 96 h. Additionally, the adsorption isotherm Freundlich and Langmuir models fit best for this study, revealing a large biosorption capacity, with Cr(VI) having the highest affinity. Further bacterial chromium reduction was confirmed by an enzymatic test of nitro reductase and chromate reductase activity in bacterial extract. Further, from the metal biosorption study, an Artificial Neural Network (ANN) model was built to assess the metal reduction capability, considering the variables of pH, temperature, incubation duration, and initial metal concentration. The model attained an excellent expected accuracy (R² > 0.90). With these features, this bacterial strain is excellent for bioremediation and use for industrial purposes and agricultural sustainability in metal-contaminated agricultural fields. Full article

Asia minor bluegrass (Polypogon fugax), a widespread Poaceae weed, exhibits broad tolerance to abiotic stresses. Validated reference genes (RGs) for reliable RT-qPCR normalization in this ecologically and agriculturally significant species remain unidentified. This study identified eight candidate RGs using transcriptome data from seedling tissues. We assessed the expression stability of these eight RGs across various abiotic stresses and developmental stages using Delta Ct, BestKeeper, geNorm, and NormFinder algorithms. A comprehensive stability ranking was generated using RefFinder, with validation performed using the target genes COR413 and P5CS. Results identified EIF4A and TUB as the optimal RG combination for normalizing gene expression during heat stress, cold stress, and growth stages. EIF4A and ACT were most stable under drought stress, EIF4A and 28S under salt stress, and EIF4A and EF-1 under cadmium (Cd) stress. Furthermore, EIF4A and UBQ demonstrated optimal stability under herbicide stress. Additionally, application of validated RGs revealed higher acetyl-CoA carboxylase gene (ACCase) expression in one herbicide-resistant population, suggesting target-site gene overexpression contributes to resistance. This work presents the first systematic evaluation of RGs in P. fugax. The identified stable RGs provide essential tools for future gene expression studies on growth and abiotic stress responses in this species, facilitating deeper insights into the molecular basis of its weediness and adaptability. Full article

Porcine endogenous retroviruses (PERVs) are integrated into the genome of all pigs. As they can be released as infectious virus particles capable of infecting human cells in vitro, they pose a potential risk for xenotransplantation involving pig cells or organs. To assess whether pigs produce infectious human-tropic viruses, infection assays with human cells are required. There are three main types of assays. First is the incubation of human target cells with gamma-irradiated pig cells. This method ensures that viral transmission is assessed in the absence of replicating pig cells. However, gamma irradiation may alter gene expression in pig cells, potentially affecting the results. Second is the co-culture in a double-chamber system in which pig and human cells are separated by a porous membrane, preventing direct cell-to-cell contact. While this method allows for the detection of infection by free virus particles, it does not account for infection via cell-to-cell transmission, which is a common mode of retroviral infection. And third is the co-culture of pig cells with human cells expressing a resistance gene. The resistance gene allows selective elimination of pig cells upon the addition of a selection medium. This assay enables both free virus and cell-to-cell transmission as well as complete removal of pig cells, which may not be fully achieved in the first type of assay. The third assay best simulates the conditions of in vivo xenotransplantation. However, in all cases the selection of donor and recipient cells is crucial to the experimental outcome. Results only indicate whether a specific pig cell type releases PERVs and whether a specific human cell type is susceptible to infection. A negative infection result does not necessarily reflect the in vivo situation, in which a transplanted organ consists of multiple pig cell types interacting with a diverse range of human cells within a living organism. Knowledge of these limitations is important for authorities regulating clinical applications for xenotransplantation. Full article

Background/Objectives: The resistance mutations EGFR^{L858R/T790M/C797S} in epidermal growth factor receptor (EGFR) are key factors in the reduced efficacy of Osimertinib. Predicting the inhibitory effects of Osimertinib derivatives against these mutations is crucial for the development of more effective inhibitors. This study aims to predict the inhibitory effects of Osimertinib derivatives against EGFR^{L858R/T790M/C797S} mutations. Methods: Six models were established using heuristic method (HM), random forest (RF), gene expression programming (GEP), gradient boosting decision tree (GBDT), polynomial kernel function support vector machine (SVM), and mixed kernel function SVM (MIX-SVM). The descriptors for these models were selected by the heuristic method or XGBoost. Comprehensive learning particle swarm optimizer was adopted to optimize hyperparameters. Additionally, the internal and external validation were performed by leave-one-out cross-validation ($Q_{LOO}^2$), 5-fold cross validation ($Q_{5-fold}^2$) and concordance correlation coefficient (CCC), $Q_{F1}^2$, and $Q_{F2}^2$. The properties of novel EGFR inhibitors were explored through molecular docking analysis. Results: The model established by MIX-SVM whose kernel function is a convex combination of three regular kernel functions is best: $R^2$ and RMSE for training set and test set are 0.9445, 0.1659 and 0.9490, 0.1814, respectively; $Q_{LOO}^2$, $Q_{5-fold}^2$, CCC, $Q_{F1}^2$, and $Q_{F2}^2$ are 0.9107, 0.8621, 0.9835, 0.9689, and 0.9680. Based on these results, the IC₅₀ values of 162 newly designed compounds were predicted using the HM model, and the top four candidates with the most favorable physicochemical properties were subsequently validated through PEA. Conclusions: The MIX-SVM method will provide useful guidance for the design and screening of novel EGFR^{L858R/T790M/C797S} inhibitors. Full article

Accurate gene expression quantification using reverse transcription quantitative PCR (RT-qPCR) requires stable reference genes (RGs) for reliable normalization. However, few studies have systematically identified RGs suitable for simultaneous high salt, alkaline, and high-temperature conditions. This study addresses this gap by evaluating the stability of eight candidate RGs in the anaerobic halophilic alkalithermophile Natranaerobius thermophilus JW/NM-WN-LF^T under combined salt, alkali, and thermal stresses. The stability of these candidate RGs was assessed using five statistical algorithms: Delta CT, geNorm, NormFinder, BestKeeper, and RefFinder. Results indicated that recA exhibited the highest expression stability across all tested conditions and proved adequate as a single RG for normalization in both RT-qPCR and droplet digital PCR (ddPCR) assays. Furthermore, recA alone or combined with other RGs (sigA, rsmH) effectively normalized the expression of seven stress-response genes (proX, opuAC, mnhE, nhaC, trkH, ducA, and pimT). This work represents the first systematic validation of RGs under polyextreme stress conditions, providing essential guidelines for future gene expression studies in extreme environments and aiding research on microbial adaptation mechanisms in halophilic, alkaliphilic, and thermophilic microorganisms. Full article

Background/Objectives: Ovarian cancer (OC) remains one of the most lethal malignancies of the female reproductive system. Glucose oxidase (GOx) has emerged as a potential therapeutic agent in cancer treatment by inducing tumor starvation through glucose depletion. Nonetheless, its clinical application is constrained due to its systemic toxicity, immunogenicity, poor in vivo stability, and short half-life. These challenges can be addressed through nanotechnology; in particular, biogenic mesoporous silica nanoparticles (MSNs) offer promise as drug delivery systems (DDSs) that enhance therapeutic efficacy while minimizing side effects. Methods: Biogenic MSNs were extracted from the Equisetum myriochaetum plant via acid digestion, functionalized with 3-aminopropiltrietoxysilane (APTES) and glutaraldehyde (GTA), and loaded with GOx. The free and immobilized MSNs were characterized using FTIR, DLS, XRD, SEM/EDX, and BET techniques. A colorimetric approach was employed to quantify the enzymatic activity of both the free and immobilized GOx. The MTT assay was employed to assess the viability of SKOV3 cells. The obtained IC₅₀ concentration of the nanoformulation was administered to SKOV3 cells to analyze the expression of cancer-related genes using RT-qPCR. Results: IC₅₀ values of 60.77 ng/mL and 111.6 µg/mL were ascertained for the free and immobilized GOx, respectively. Moreover, a significant downregulation of the oncogene β-catenin (CTNNB1) was detected after 24 h with the nanoformulation. Conclusions: Our findings indicate that GOx-loaded biogenic MSNs may serve as a potential therapeutic agent for ovarian cancer. This is, to the best of our knowledge, the first report exploring the effect of GOx-loaded biogenic MSNs on SKOV3 cells. Full article

Gleason score (GS) is one of the best predictors of prostate cancer (PCa) aggressiveness; however, its biological features need to be elucidated. This study aimed to explore the biological characteristics of localized/locally advanced PCa stratified using in silico GS analysis. Biological features were analyzed using gene set variation analysis and the xCell algorithm with mRNA expression in two independent public databases: The Cancer Genome Atlas (TCGA) (n = 493; radical prostatectomy cohort) and GSE116918 (n = 248; radiation therapy cohort). GS levels were positively correlated with the activity levels of cell proliferation-related gene sets, including E2F targets, the G2M checkpoint, the mitotic spindle, and MYC targets v1 and v2 in both cohorts. Furthermore, GS levels were positively associated with the activity levels of immune-related gene sets and infiltrating fractions of immune cells, including CD4+ memory T cells, dendritic cells, M1 macrophages, and Th2 cells, in both cohorts. Notably, GS levels were positively associated with the score levels of homologous recombination defects, intratumor heterogeneity, fraction genome alteration, neoantigens, and mutation rates in the TCGA cohort. In conclusion, PCa with high GS levels was associated with cancer cell proliferation, immune cell infiltration, and high mutation rates, which may reflect worse clinical outcomes. Full article

This paper conducts a literature review on the role of natural killer cells in haploidentical hematopoietic stem cell transplantation. Theoretical concepts related to KIR genes are introduced regarding their structure, nomenclature, genetic organization, polymorphism, and inheritance pattern, types of KIR proteins and receptors, HLA ligands for KIR receptors, and the definition of different NK alloreactivity prediction models for the donor of haploidentical hematopoietic stem cell transplantation and the recipient. These models include the following and consider incompatibility: ligand–ligand, receptor–ligand, gene–gene, and KIR haplotype models or the KIR-B donor group. These models consider the presence or absence of specific ligands or receptors and/or KIR genes in the donor and recipient to predict alloreactivity. Determining the best model for predicting KIR alloreactivity and its significance in donor selection algorithms for haploidentical transplantation is still under investigation. Full article

The current work focused on the molecular selection of Oreochromis niloticus with improved growth performance through marker-trait associations between SNPs within the growth hormone gene (GH) and growth performance. A total of 155 fish of the same age were collected from three locations (Lake Brullus (B), the River Nile at El-Qanater El-Khairia (Q), and Lake Nasser (A)). The selected individual progenies were evaluated through gene expression analysis for growth, inflammatory, nervous, and immune-related genes. A total of nine SNPs and three InDels were significantly associated with morphometric characteristics. The phenotypic variance (R²) of the detected SNPs ranged between 2.6% and 36%. The best populations were A and Q, as they recorded the best growth performance and harboured the highest number of SNPs and InDels, in addition to a significant increase in body weight and length. Furthermore, their progenies documented the most promising gene expression patterns of all tested genes. The current research highlights the importance of molecular selection and the potential use of population-specific SNPs in tilapia breeding programs. Full article

Chemical modifications are the standard for small interfering RNAs (siRNAs) in therapeutic applications, but predicting their off-target effects remains a significant challenge. Current approaches often rely on sequence-based encodings, which fail to fully capture the structural and protein–RNA interaction details critical for off-target prediction. In this study, we developed a framework to generate reproducible structure-based chemical features, incorporating both molecular fingerprints and computationally derived siRNA–hAgo2 complex structures. Using an RNA-Seq off-target study, we generated over 30,000 siRNA–gene data points and systematically compared nine distinct types of feature representation strategies. Among the datasets, the highest predictive performance was achieved by Dataset 3, which used extended connectivity fingerprints (ECFPs) to encode siRNA and mRNA features. An energy-minimized dataset (7R), representing siRNA–hAgo2 structural alignments, was the second-best performer, underscoring the value of incorporating reproducible structural information into feature engineering. Our findings demonstrate that combining detailed structural representations with sequence-based features enables the generation of robust, reproducible chemical features for machine learning models, offering a promising path forward for off-target prediction and siRNA therapeutic design that can be seamlessly extended to include any modification, such as clinically relevant 2′-F or 2′-OMe. Full article