Search Results (10,671)

To determine the association between FGFR4 (rs351855 and rs7708357) gene variants, serum levels, and immunohistochemical markers (Ki-67 and p53) in pituitary adenoma (PA), a case-control study was conducted involving 300 subjects divided into two groups: the control group (n = 200) and a group of PA (n = 100). The genotyping of FGFR4 rs351855 and rs7708357 was carried out using the real-time polymerase chain reaction (RT-PCR) method. The serum FGFR4 levels were measured using the ELISA method. Immunohistochemical analysis (Ki-67 and p53) was conducted. Statistical analysis of the data was performed using IBM SPSS Statistics 30.0 software. There were no statistically significant differences after analyzing the genotypes and alleles of FGFR4 rs351855 and rs7708357 in patients with PA and control groups (all p > 0.05). After evaluating the distribution of genotypes and alleles of FGFR4 rs351855 and rs7708357 in micro/macro, invasiveness, activity, and recurrence of PA and the control groups, the analysis showed no statistically significant differences between the groups (p > 0.05). Similarly, no significant differences in FGFR4 levels were observed between PA patients and control group (median (IQR): 3642.41 (1755.08) pg/mL vs. 3126.24 (1334.15) pg/mL, p = 0.121). Immunohistochemistry for Ki-67 revealed a labeling index (LI) of <1% in 25.5% of patients with PA, an LI of 1% in 10.9%, and an LI of >1% in 63.6% of patients. Further analyses showed no statistically significant associations with tumor size, invasiveness, activity, or recurrence. Immunohistochemistry for p53 revealed that macroadenomas had a significantly higher p53 H-score compared to microadenomas (median (IQR): 30.33 (28.68) vs. 18.34 (17.65), p = 0.005). Additionally, a moderate, statistically significant positive correlation between the Ki-67 LI and the p53 expression was found (Spearman’s ρ = 0.443, p = 0.003, n = 43). FGFR4 variants and serum protein levels were not significantly associated with PA risk or tumor features. Conversely, immunohistochemical markers Ki-67 and p53 were more informative, with higher p53 expression in macroadenomas and a moderate positive correlation between Ki-67 and p53, highlighting their potential relevance in tumor growth assessment. Full article

Background: Amyotrophic lateral sclerosis is a systemic, complex, multifactorial, and fatal neurodegenerative disease with various factors involved in its etiology. This study aimed to understand the effects of SNPs in the MTHFR, MTR, SLC19A1, and VAPB genes on protein functionality and structure and their influence on ALS susceptibility. Methods: The dbSNP and ClinVar databases were used for SNP data annotation, while UniProt and PDB provided protein sequences. We performed functional and structural predictions of SNPs using PolyPhen-2 and SNAP2. We modeled mutant proteins using AlphaFold 2 and visualized them in PyMOL to compare native and mutant forms. Results: Our results identified SNP rs74315431 as pathogenic, inducing structural and functional changes and exhibiting visible alterations in the three-dimensional structure. Although predicted as non-pathogenic, SNPs rs1801131, rs1805087, and rs1051266 caused protein structural alterations, a finding confirmed by three-dimensional visualization. SNP rs1801133 diverged from the others, being predicted as pathogenic but without causing changes in protein structure or function. Conclusions: Our study found a strong correlation between SNAP2-predicted alterations and those predicted by AlphaFold 2, whereas PolyPhen-2 results did not directly correlate with three-dimensional structure changes. Full article

Rainwater harvesting for sustainable agriculture (RWHSA) offers a viable and eco-friendly strategy to alleviate water scarcity in semi-arid regions, particularly for agricultural use. This study aims to identify optimal sites for implementing RWH systems in northern Iraq to enhance water availability and promote sustainable farming practices. An integrated geospatial approach was adopted, combining Remote Sensing (RS), Geographic Information Systems (GIS), and Multi-Criteria Decision Analysis (MCDA). Key thematic layers, including soil type, land use/land cover, slope, and drainage density were processed in a GIS environment to model runoff potential. The Soil Conservation Service Curve Number (SCS-CN) method was used to estimate surface runoff. Criteria were weighted using the Analytical Hierarchy Process (AHP), enabling a structured and consistent evaluation of site suitability. The resulting suitability map classifies the region into four categories: very high suitability (10.2%), high (26.6%), moderate (40.4%), and low (22.8%). The integration of RS, GIS, AHP, and MCDA proved effective for strategic RWH site selection, supporting cost-efficient, sustainable, and data-driven agricultural planning in water-stressed environments. Full article

Cucumber, a high-yielding crop commonly grown in facility environments, is particularly susceptible to nitrogen (N) deficiency due to its rapid growth and high nutrient demand. This study used cucumber as its experimental subject and established a spectral dataset of leaves under four nutritional conditions, normal supply, nitrogen deficiency, phosphorus deficiency, and potassium deficiency, aiming to develop an efficient and robust method for quantifying N in cucumber leaves using Raman spectroscopy (RS). Spectral data were preprocessed using three baseline correction methods—BaselineWavelet (BW), Iteratively Improve the Moving Average (IIMA), and Iterative Polynomial Fitting (IPF)—and key spectral variables were selected using 4-Dimensional Feature Extraction (4DFE) and Competitive Adaptive Reweighted Sampling (CARS). These selected features were then used to develop a N content prediction model based on Partial Least Squares Regression (PLSR). The results indicated that baseline correction significantly enhanced model performance, with three methods outperforming unprocessed spectra. A further analysis showed that the combination of IPF, 4DFE, and CARS achieved optimal PLSR model performance, achieving determination coefficients (R²) of 0.947 and 0.847 for the calibration and prediction sets, respectively. The corresponding root mean square errors (RMSEC and RMSEP) were 0.250 and 0.368, while the residual predictive deviation (RPDC and RPDP) values reached 4.335 and 2.555. These findings confirm the feasibility of integrating RS with advanced data processing for rapid, non-destructive nitrogen assessment in cucumber leaves, offering a valuable tool for nutrient monitoring in precision agriculture. Full article

Background/Objectives: The increased risk of developing tendinopathies in athlete populations has led to investigations of several genes associated with tendon properties, suggesting that some individuals have a greater genetic predisposition for developing tendinopathies. The main purpose of this study was to investigate how the functional polymorphisms within the COL5A1, COL27A1 and TNC genes impact the risk of developing tendinopathies in high-level Croatian athletes. Methods: For this case–control genetic study, we recruited 63 high-level athletes with a diagnosis of tendinopathies and 92 healthy asymptomatic individuals as controls. All individuals were genotyped for three single-nucleotide polymorphisms (SNPs) within the COL5A1, COL27A1 and TNC genes using the pyrosequencing method. Results: TNC rs2104772 TT (p = 0.0089) and the T-T-T haplotype (p = 0.0234), constructed from rs12722, rs946053 and rs2104772, were significantly overrepresented in cases versus controls, implicating a predisposition for tendinopathies. COL27A1 rs946053 GG (p = 0.0118) and the G-A-C haplotype (p = 0.0424), constructed from rs12722, rs946053 and rs2104772, were significantly overrepresented in controls, implicating a protective role. Conclusions: These results further support associations between functional polymorphisms within the COL27A1 and TNC genes and the risk of tendinopathies in high-level athletes. Further research is needed to replicate these results in various populations and larger cohorts. Full article

Background/Objectives: Schizophrenia exhibits symptoms linked to the hippocampus and parahippocampal gyrus. This includes the entorhinal cortex (ERC) and perirhinal cortex (PRC) as anterior parts, along with the posterior segment known as the parahippocampal cortex (PHC). However, recent research has detailed atlases based on cytoarchitectural characteristics and the hippocampus divided into four subregions: cornu ammonis (CA), dentate gyrus (DG), subiculum (SUB), and hippocampal–amygdaloid transition (HATA). This study aimed to explore the functional connectivity (FC) changes between these hippocampal subregions and the parahippocampal gyrus structures (ERC, PRC, and PHC) as well as between hippocampal subregions and various functional brain networks in schizophrenia. Methods: In total, 50 individuals with schizophrenia and 50 matched healthy subjects were examined using resting state functional magnetic resonance imaging (rs-fMRI). Results: The results showed alterations characterized by increases and decreases in the strength of the positive connectivity between the parahippocampal gyrus structures and the four hippocampal subregions when comparing patients with schizophrenia with healthy subjects. Alterations were observed among the hippocampal subregions and functional brain networks, as well as the formation of new connections and absence of connections. Conclusions: There is strong evidence that the different subregions of the hippocampus have unique functions and their connectivity with the parahippocampal cortices and brain networks are affected by schizophrenia. Full article

Background/Objectives: While intravenous thrombolysis (IVT) is the standard treatment for acute ischemic stroke (AIS) within 4.5 h of symptom onset, many patients present beyond this time window. Recent trials suggest that IVT may be both effective and safe in selected patients treated after the standard time window. Methods: We searched MEDLINE, Scopus, and ClinicalTrials.gov for randomized-controlled clinical trials (RCTs) and individual patient-data meta-analyses (IPDMs) of RCTs comparing IVT plus best medical treatment (BMT) to BMT alone in AIS patients who were last-known-well more than 4.5 h earlier. The primary efficacy outcome was a 90-day excellent functional outcome [modified Rankin Scale (mRS)-scores of 0–1]. Secondary efficacy outcomes included good functional outcome (mRS-scores 0–2) and reduced disability (≥1-point reduction across all mRS-strata). The primary safety outcome was symptomatic intracranial hemorrhage (sICH); secondary safety outcomes were any ICH and 3-month all-cause mortality. Subgroup analyses were performed stratified by different thrombolytics, time-windows, imaging modalities, and affected circulation. Results: Nine studies were included, comprising 1660 patients in the IVT-group and 1626 patients in the control-group. IVT significantly improved excellent functional outcome (RR = 1.24; 95%CI:1.14–1.34; I² = 0%) and good functional outcome (RR = 1.18; 95%CI:1.05–1.33; I² = 70%). IVT was associated with increased odds of reduced disability (common OR = 1.3; 95%CI:1.15–1.46; I² = 0%) and increased risk of sICH (RR = 2.75; 95%CI:1.49–5.05; I² = 0%). The rates of any ICH and all-cause mortality were similar between the two groups. No significant subgroup differences were documented. Conclusions: IVT in the extended time window improved functional outcomes without increasing mortality, despite a higher rate of sICH. Full article

Background/Objectives: Direct oral anticoagulants (DOACs) are now the guideline-recommended alternative to vitamin K antagonists (VKAs) for long-term anticoagulation in patients with non-valvular atrial fibrillation. However, accurately assessing their impact on ischemic stroke outcomes remains challenging, primarily due to uncertainty regarding anticoagulation status at the time of hospital admission. This preliminary study addresses this gap by using point-of-care testing (POCT) to confirm DOAC activity at bedside, allowing for a more accurate comparison of 90-day functional outcomes between anticoagulated and non-anticoagulated stroke patients. Methods: We conducted a retrospective cohort study of 786 ischemic stroke patients admitted to the University of Pécs between February 2023 and February 2025. Active DOAC therapy was confirmed using the ClotPro^® viscoelastic testing platform, with ecarin Clotting Time (ECT) employed for thrombin inhibitors and Russell’s Viper Venom (RVV) assays for factor Xa inhibitors. Patients were categorized as non-anticoagulated (n = 767) or DOAC-treated with confirmed activity (n = 19). Mahalanobis distance-based matching was applied to account for confounding variables including age, sex, pre-stroke modified Rankin Scale (mRS), and National Institutes of Health Stroke Scale (NIHSS) scores at admission and 72 h post-stroke. The primary outcome was the change in mRS from baseline to 90 days. Statistical analysis included ordinary least squares (OLS) regression and principal component analysis (PCA). Results: After matching, 90-day functional outcomes were comparable between groups (mean mRS-shift: 2.00 in DOAC-treated vs. 1.78 in non-anticoagulated; p = 0.745). OLS regression showed no significant association between DOAC status and recovery (p = 0.599). In contrast, NIHSS score at 72 h (p = 0.004) and age (p = 0.015) were significant predictors of outcome. PCA supported these findings, identifying stroke severity as the primary driver of outcome. Conclusions: This preliminary analysis suggests that ischemic stroke patients with confirmed active DOAC therapy at admission may achieve 90-day functional outcomes comparable to those of non-anticoagulated patients. The integration of bedside POCT enhances the reliability of anticoagulation assessment and underscores its clinical value for real-time management in acute stroke care. Larger prospective studies are needed to validate these findings and to further refine treatment strategies. Full article

Background: The Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) was a 3-year, multicenter, randomized controlled trial to test the effects of the MIND diet on cognitive decline in 604 individuals at risk for Alzheimer’s dementia. Here, we describe the genotyping, imputation, and quality control (QC) procedures for the genetic data of trial participants. Methods: DNA was extracted from either whole blood or serum, and genotyping was performed using the Infinium Global Diversity Array. Established sample and SNP QC procedures were applied to the genotyping data, followed by imputation using the 1000 Genomes Phase 3 v5 reference panel. Results: Significant study-site, specimen type, and batch effects were observed. A total of 494 individuals of inferred European ancestry and 58 individuals of inferred African ancestry were included in the final imputed dataset. Evaluation of the imputed APOE genotype against gold-standard sequencing data showed high concordance (98.2%). We replicated several known genetic associations identified from previous genome-wide association studies, including SNPs previously linked to adiponectin (rs16861209, p = 1.5 × 10⁻⁵), alpha-linolenic acid (rs174547, p = 1.3 × 10⁻⁷), and alpha-tocopherol (rs964184, p = 0.003). Conclusions: This dataset represents the first genetic resource derived from a dietary intervention trial focused on cognitive outcomes. It enables investigation of genetic contributions to variability in cognitive response to the MIND diet and supports integrative analyses with other omics data types to elucidate the biological mechanisms underlying cognitive decline. These efforts may ultimately inform precision nutrition strategies to promote cognitive health. Full article

The modified Rankin Scale (mRS) is a widely used outcome measure for assessing disability in stroke care; however, its administration is often affected by subjectivity and variability, leading to poor inter-rater reliability and inconsistent scoring. Originally designed for hospital discharge evaluations, the mRS has evolved into an outcome tool for disability assessment and clinical decision-making. Inconsistencies persist due to a lack of standardization and cognitive biases during its use. This paper presents design principles for creating a standardized clinical assessment tool (CAT) for the mRS, grounded in human–computer interaction (HCI) and cognitive engineering principles. Design principles were informed in part by an anonymous online survey conducted with clinicians across Canada to gain insights into current administration practices, opinions, and challenges of the mRS. The proposed design principles aim to reduce cognitive load, improve inter-rater reliability, and streamline the administration process of the mRS. By focusing on usability and standardization, the design principles seek to enhance scoring consistency and improve the overall reliability of clinical outcomes in stroke care and research. Developing a standardized CAT for the mRS represents a significant step toward improving the accuracy and consistency of stroke disability assessments. Future work will focus on real-world validation with healthcare stakeholders and exploring self-completed mRS assessments to further refine the tool. Full article

Recurrent pregnancy loss (RPL) is defined as the occurrence of two or more pregnancy losses before 20 weeks of gestation. RPL is a common medical condition among reproductive-age women, with approximately 23 million cases reported annually worldwide. Up to 5% of pregnant women may experience two or more consecutive pregnancy losses. Previous studies have investigated risk factors for RPL, including maternal age, uterine pathology, genetic anomalies, infectious agents, endocrine disorders, thrombophilia, and immune dysfunction. However, RPL is a disease caused by a complex interaction of genetic factors, environmental factors (e.g., diet, lifestyle, and stress), epigenetic factors, and the immune system. In addition, due to the lack of research on genetics research related to RPL, the etiology remains unclear in up to 50% of cases. Platelets play a critical role in pregnancy maintenance. This study examined the associations of platelet receptor and ligand gene variants, including integrin subunit beta 3 (ITGB3) rs2317676 A > G, rs3809865 A > T; fibrinogen gamma chain (FGG) rs1049636 T > C, rs2066865 T > C; glycoprotein 1b subunit alpha (GP1BA) rs2243093 T > C, rs6065 C > T; platelet endothelial cell adhesion molecule 1 (PECAM1) rs2812 C > T; and platelet endothelial aggregation receptor 1 (PEAR1) rs822442 C > A, rs12137505 G > A, with RPL prevalence. In total, 389 RPL patients and 375 healthy controls (all Korean women) were enrolled. Genotyping of each single nucleotide polymorphism was performed using polymerase chain reaction–restriction fragment length polymorphism and the TaqMan genotyping assay. All samples were collected with approval from the Institutional Review Board at Bundang CHA Medical Center. The ITGB3 rs3809865 A > T genotype was strongly associated with RPL prevalence (pregnancy loss [PL] ≥ 2: adjusted odds ratio [AOR] = 2.505, 95% confidence interval [CI] = 1.262–4.969, p = 0.009; PL ≥ 3: AOR = 3.255, 95% CI = 1.551–6.830, p = 0.002; PL ≥ 4: AOR = 3.613, 95% CI = 1.403–9.307, p = 0.008). The FGG rs1049636 T > C polymorphism was associated with a decreased risk in women who had three or more pregnancy losses (PL ≥ 3: AOR = 0.673, 95% CI = 0.460–0.987, p = 0.043; PL ≥ 4: AOR = 0.556, 95% CI = 0.310–0.997, p = 0.049). These findings indicate significant associations of the ITGB3 rs3809865 A > T and FGG rs1049636 T > C polymorphisms with RPL, suggesting that platelet function influences RPL in Korean women. Full article

Background: Genetic polymorphisms in the cyclooxygenase-2 (COX-2) gene may contribute to individual susceptibility to periodontal disease. A meta-analysis assessed the association between three COX-2 single-nucleotide polymorphisms (SNPs) namely, −765 G/C (rs20417), −1195 G/A (rs689466), and 8473 T/C (rs5275), and the risk of CP. Methods: Following the PRISMA 2020 guidelines, we conducted a comprehensive search of five electronic databases and additional sources. The eligible studies were observational (case–control or cohort) with genotypic data comparing individuals with periodontal disease and periodontally healthy controls. Methodological quality was assessed using the Newcastle–Ottawa Scale (NOS), and the certainty of evidence was evaluated via the GRADE framework. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated under dominant genetic models. Results: Seven studies (n = 1467 participants) met the inclusion criteria. No eligible studies evaluated the 8473 T/C SNP. The meta-analysis of the −765 G/C variant revealed a significant association with periodontal disease (OR = 1.61; 95% CI: 1.12–2.32, p = 0.03; I² = 0%). For the −1195 G/A variant, the pooled OR was 1.86 (95% CI: 1.00–3.43, p = 0.05; I² = 35%), suggesting a borderline significant association. The certainty of evidence was graded as moderate for −765 G/C and low for −1195 G/A. Conclusions: The COX-2 −765 G/C polymorphism is significantly associated with increased CP risk, while the −1195 G/A variant shows a potential, though less certain, link. Larger, high-quality studies using standardized classifications are needed to confirm these associations. Full article

The size of the gluteus medius muscle (GM) in swine significantly impacts both hindlimb conformation and carcass yield, while little is known about the genetic architecture of this trait. This study aims to estimate genetic parameters and identify candidate genes associated with this trait through a genome-wide association study (GWAS). A total of 439 commercial crossbred pigs, possessing both Landrace and Yorkshire ancestry, were genotyped using the Porcine 50K chip. The length and width of the GM were directly measured, and the area was then calculated from these values. The heritabilities were estimated by HIBLUP (V1.5.0) software, and the GWAS was conducted employing the BLINK model implemented in GAPIT3. The heritability estimates for the length, width, and area of the GM were 0.43, 0.40, and 0.46, respectively. The GWAS identified four genome-wide significant SNPs (rs81381267, rs697734475, rs81298447, and rs81458910) associated with the gluteus medius muscle area. The PDE4D gene was identified as a promising candidate gene potentially involved in the regulation of gluteus medius muscle development. Our analysis revealed moderate heritability estimates for gluteus medius muscle size traits. These findings enhance our understanding of the genetic architecture underlying porcine muscle development. Full article

Adversarial attacks in Natural Language Processing (NLP) present a critical challenge, particularly in sentiment analysis, where subtle input modifications can significantly alter model predictions. In search of more robust defenses against adversarial attacks on sentimental analysis, this research work introduces two novel defense mechanisms: the Lexicon-Based Random Substitute Model (LRSM) and the Word-Variant Voting Model (WVVM). LRSM employs randomized substitutions from a dataset-specific lexicon to generate diverse input variations, disrupting adversarial strategies by introducing unpredictability. Unlike traditional defenses requiring synonym dictionaries or precomputed semantic relationships, LRSM directly substitutes words with random lexicon alternatives, reducing overhead while maintaining robustness. Notably, LRSM not only neutralizes adversarial perturbations but occasionally surpasses the original accuracy by correcting inherent model misclassifications. Building on LRSM, WVVM integrates LRSM, Frequency-Guided Word Substitution (FGWS), and Synonym Random Substitution and Voting (RS&V) in an ensemble framework that adaptively combines their outputs. Logistic Regression (LR) emerged as the optimal ensemble configuration, leveraging its regularization parameters to balance the contributions of individual defenses. WVVM consistently outperformed standalone defenses, demonstrating superior restored accuracy and F1 scores across adversarial scenarios. The proposed defenses were evaluated on two well-known sentiment analysis benchmarks: the IMDB Sentiment Dataset and the Yelp Polarity Dataset. The IMDB dataset, comprising 50,000 labeled movie reviews, and the Yelp Polarity dataset, containing labeled business reviews, provided diverse linguistic challenges for assessing adversarial robustness. Both datasets were tested using 4000 adversarial examples generated by established attacks, including Probability Weighted Word Saliency, TextFooler, and BERT-based Adversarial Examples. WVVM and LRSM demonstrated superior performance in restoring accuracy and F1 scores across both datasets, with WVVM excelling through its ensemble learning framework. LRSM improved restored accuracy from 75.66% to 83.7% when compared to the second-best individual model, RS&V, while the Support Vector Classifier WVVM variation further improved restored accuracy to 93.17%. Logistic Regression WVVM achieved an F1 score of 86.26% compared to 76.80% for RS&V. These findings establish LRSM and WVVM as robust frameworks for defending against adversarial text attacks in sentiment analysis. Full article

Agriculture is the backbone of Punjab’s economy, and with much of India’s population dependent on agriculture, the requirement for accurate and timely monitoring of land has become even more crucial. Blending remote sensing with state-of-the-art machine learning algorithms enables the detailed classification of agricultural lands through thematic mapping, which is critical for crop monitoring, land management, and sustainable development. Here, a Hyper-tuned Deep Neural Network (Hy-DNN) model was created and used for land use and land cover (LULC) classification into four classes: agricultural land, vegetation, water bodies, and built-up areas. The technique made use of multispectral data from Sentinel-2 and Landsat-8, processed on the Google Earth Engine (GEE) platform. To measure classification performance, Hy-DNN was contrasted with traditional classifiers—Convolutional Neural Network (CNN), Random Forest (RF), Classification and Regression Tree (CART), Minimum Distance Classifier (MDC), and Naive Bayes (NB)—using performance metrics including producer’s and consumer’s accuracy, Kappa coefficient, and overall accuracy. Hy-DNN performed the best, with overall accuracy being 97.60% using Sentinel-2 and 91.10% using Landsat-8, outperforming all base models. These results further highlight the superiority of the optimised Hy-DNN in agricultural land mapping and its potential use in crop health monitoring, disease diagnosis, and strategic agricultural planning. Full article