Search Results (1,335)

Hepatocellular carcinoma (HCC) is the most prevalent subtype of liver cancer with an increasing incidence worldwide. Single nucleotide polymorphisms (SNPs) may influence disease risk and serve as predictive markers. This study aimed to evaluate the association of PNPLA3 (rs738409 and rs2294918), GCKR (rs780094), MBOAT7 (rs641738), NCAN (rs2228603), and TM6SF2 (rs58542926) SNPs with the risk of developing HCC in a Mexican population. A case-control study was conducted in unrelated Mexican individuals. Cases were 173 adults with biopsy-confirmed HCC and 346 were healthy controls. Genotyping was performed using TaqMan allelic discrimination assay. Logistic regression was applied to evaluate associations under codominant, dominant, and recessive inheritance models. p-values were corrected using the Bonferroni test (pC). Haplotype and gene–gene interaction were also analyzed. The GG homozygous of rs738409 and rs2294918 of PNPLA3, TT, and TC genotypes of GCKR, as well as the TT genotype of MBOAT7, were associated with a significant increased risk to HCC under different inheritance models (~Two folds in all cases). The genotypes of NCAN and TM6SF2 did not show differences. The haplotype G-G of rs738409 and rs2294918 of PNPLA3 was associated with an increased risk of HCC [OR (95% CI) = 2.2 (1.7–2.9)]. There was a significant gene–gene interaction between PNPLA3 (rs738409), GCKR (rs780094), and MBOAT7 (rs641738) (Cross-validation consistency (CVC): 10/10; Testing accuracy = 0.6084). This study demonstrates for the first time that PNPLA3 (rs738409 and rs2294918), GCKR (rs780094), and MBOAT7 (rs641738) are associated with an increased risk of developing HCC from multiple etiologies in Mexican patients. Full article

(1) Background: Chronic myeloid leukemia (CML) is a myeloproliferative disorder driven by the BCR::ABL oncoprotein. During the chronic phase, Philadelphia chromosome-positive hematopoietic stem cells generate proliferative myeloid cells with various stages of maturation. Despite this expansion, leukemic stem cells (LSCs) retain self-renewal capacity via asymmetric cell divisions, sustaining the stem cell pool. Quiescent LSCs are known to be resistant to tyrosine kinase inhibitors (TKIs), potentially through BCR::ABL-independent signaling pathways. We hypothesize that dysregulation of genes governing asymmetric division in LSCs contributes to disease progression, and that their expression pattern may serve as a prognostic marker during the chronic phase of CML. (2) Methods: Genes related to asymmetric cell division in the context of hematopoietic stem cells were extracted from the PubMed database with the keyword “asymmetric hematopoietic stem cell”. The collected relative gene set was tested on two independent bulk transcriptome cohorts and the results were confirmed by single-cell RNA sequencing. (3) Results: The expression of genes involved in asymmetric hematopoietic stem cell division was found to discriminate disease phases during CML progression in the two independent transcriptome cohorts. Concordance between cohorts was observed on asymmetric molecules downregulated during blast crisis (BC) as compared to the chronic phase (CP). This downregulation during the BC phase was confirmed at single-cell level for SELL, CD63, NUMB, HK2, and LAMP2 genes. Single-cell analysis during the CP found that CD63 is associated with a poor prognosis phenotype, with the opposite prediction revealed by HK2 and NUMB expression. The single-cell trajectory reconstitution analysis in CP samples showed CD63 regulation highlighting a trajectory cluster implicating HSPB1, PIM2, ANXA5, LAMTOR1, CFL1, CD52, RAD52, MEIS1, and PDIA3, known to be implicated in hematopoietic malignancies. (4) Conclusion: Regulation of CD63, a tetraspanin involved in the asymmetric division of hematopoietic stem cells, was found to be associated with poor prognosis during CML progression and could be a potential new therapeutic target. Full article

Background and Objectives: Galectin-3 (Gal-3), a pro-inflammatory cytokine, has been implicated in atherosclerosis and adverse cardiovascular outcomes. While its role in coronary artery disease (CAD) is increasingly recognized, its association with systemic atherosclerosis remains underexplored. Objective: To investigate serum Gal-3 levels in patients with CAD and evaluate correlations between CAD severity and extra-coronary atherosclerotic involvement (carotid, femoral, and radial territories). Materials and Methods: We prospectively enrolled 56 patients with CAD undergoing coronary angiography (42.8% with acute-ACS; 57.2% with chronic coronary syndromes-CCS). Gal-3 levels were measured within 24 h of admission. Atherosclerosis severity was assessed angiographically and through vascular ultrasound of the carotid, femoral, and radial arteries. Patients were stratified by median Gal-3 levels, and clinical follow-up was performed at 1 and 3 months. Results: Gal-3 levels were significantly higher in CAD vs. controls (20.7 vs. 10.1 ng/mL; p < 0.00001) and in ACS vs. CCS (22.18. vs. 17.93 ng/mL; p = 0.019). Gal-3 correlated positively with culprit lesion diameter stenosis (DS) (R = 0.30; p = 0.023) and maximum severity of additional treated lesions (R = 0.62; p = 0.006). Gal-3 also correlated positively with carotid plaque thickness (R = 0.32; p = 0.016), while patients with Gal-3 levels above the median showed increased median values for femoral plaque thickness (32.4 vs. 26.45 mm, p = 0.046). No correlation was found with radial artery calcification. Gal-3 showed moderate discrimination for ACS (AUC = 0.685; cut-off 20.18 ng/mL). On multivariate analysis age, DS, and ACS presentation were independent predictors of Gal-3 above 19.07 ng/mL. Conclusions: Gal-3 levels are elevated in ACS and correlate with atherosclerotic burden, particularly in coronary, carotid, and femoral territories. These findings support Gal-3 as a potential marker of lesion severity and systemic vascular involvement, highlighting its possible role in risk stratification and the monitoring of atherosclerotic disease progression. This study provides integrated insights into the impact of Gal-3 across multiple vascular beds by assessing them concurrently within the same patient cohort. Full article

Inflammatory biomarkers, including high-sensitivity C-reactive protein (hsCRP), serum amyloid A (SAA), and interleukin-6 (IL-6), have been associated with an increased risk of future cardiovascular events. While they provide valuable prognostic information, these associations do not necessarily imply a direct causal role. The combined prognostic utility of these markers, however, remains insufficiently studied. We analysed 3300 well-characterised participants of the Ludwigshafen Risk and Cardiovascular Health (LURIC) study, all of whom underwent coronary angiography. Participants were stratified based on their serum concentrations of hsCRP, SAA, and IL-6. Associations between biomarker combinations and mortality were assessed using multivariate Cox regression and ROC analysis. Individuals with elevated hsCRP and SAA or IL-6 showed higher prevalence rates of coronary artery disease, heart failure, and adverse metabolic traits. These “both high” groups had lower estimated glomerular filtration rate, higher NT-proBNP, and increased HbA1c. Combined elevations of hsCRP and SAA were significantly associated with higher all-cause and cardiovascular mortality in partially adjusted models. However, these associations weakened after adjusting for IL-6. IL-6 alone demonstrated the highest predictive power (AUC: 0.638) and improved risk discrimination when included in multi-marker models. The co-elevation of hsCRP, SAA, and IL-6 identifies a high-risk phenotype characterised by greater cardiometabolic burden and increased mortality. IL-6 may reflect upstream inflammatory activity and could serve as a therapeutic target. Multi-marker inflammatory profiling holds promise for refining cardiovascular risk prediction and advancing personalised prevention strategies. Full article

Rye regeneration in anther cultures is problematic and affected by albino plants. DNA methylation changes linked to Cu²⁺ ions in the induction medium affect reprogramming microspores from gametophytic to sporophytic path. Alternations in S-adenosyl-L-methionine (SAM), glutathione (GSH), or β-glucans and changes in DNA methylation in regenerants obtained under different in vitro culture conditions suggest a crucial role of biochemical pathways. Thus, understanding epigenetic and biochemical changes arising from the action of Cu²⁺ and Zn²⁺ that participate in enzymatic complexes may stimulate progress in rye doubled haploid plant regeneration. The Methylation-Sensitive Amplified Fragment Length Polymorphism approach was implemented to identify markers related to DNA methylation and sequence changes following the quantification of variation types, including symmetric and asymmetric sequence contexts. Reverse-Phase High-Pressure Liquid Chromatography (RP-HPLC) connected with mass spectrometry was utilized to determine SAM, GSH, and glutathione disulfide, as well as phytohormones, and RP-HPLC with a fluorescence detector to study polyamines changes originating in rye regenerants due to Cu²⁺ or Zn²⁺ presence in the induction medium. Multivariate and regression analysis revealed that regenerants derived from two lines treated with Cu²⁺ and those treated with Zn²⁺ formed distinct groups based on DNA sequence and methylation markers. Zn²⁺ treated and control samples formed separate groups. Also, Cu²⁺ discriminated between controls and treated samples, but the separation was less apparent. Principal coordinate analysis explained 85% of the total variance based on sequence variation and 69% of the variance based on DNA methylation changes. Significant differences in DNA methylation characteristics were confirmed, with demethylation in the CG context explaining up to 89% of the variance across genotypes. Biochemical profiles also demonstrated differences between controls and treated samples. The changes had different effects on green and albino plant regeneration efficiency, with cadaverine (Cad) and SAM affecting regeneration parameters the most. Analyses of the enzymes depend on the Cu²⁺ or Zn²⁺ ions and are implemented in the synthesis of Cad, or SAM, which showed that some of them could be candidates for genome editing. Alternatively, manipulating SAM, GSH, and Cad may improve green plant regeneration efficiency in rye. Full article

Background: The Malnutrition Screening Tool (MST) is commonly used to identify malnutrition risk; however it has demonstrated poor sensitivity to detect malnutrition in inpatients with chronic kidney disease (CKD) and kidney replacement therapy (KRT) populations. Gastrointestinal symptoms, such as poor appetite, may better detect malnutrition. The accuracy of MST or other nutrition-related parameters to detect malnutrition in ambulatory patients with CKD stages 4–5 without KRT has not been evaluated. Methods: A single site retrospective audit of outpatient records from May 2020 to March 2025 was conducted. Patients with eGFR < 25 mL/min/1.73 m² without KRT who had both MST and a 7-point Subjective Global Assessment (SGA) within 7 days were included. Sensitivity, specificity, and ROC-AUC analyses compared nutritional parameters against SGA-defined malnutrition. Nutritional parameters tested included MST, hand grip strength, upper gastrointestinal symptom burden, poor appetite and a combination of some of these parameters. Results: Among 231 patients (68.8% male, median age 69 years, median eGFR 15), 29.9% were at risk of malnutrition (MST ≥ 2) and 33.8% malnourished (SGA ≤ 5). All potential screening tools had AUC ranging from 0.604 to 0.710, implying a poor-to-moderate discriminator ability to detect malnutrition. Combining HGS ≤ 29.5 kg or MST ≥2 demonstrated high sensitivity (95.5%) and negative predictive value (93.3%), but low specificity (33.3%) for detecting malnutrition, indicating this approach is effective for ruling out malnutrition but may over-identify at-risk individuals. Conclusions: MST and other tested tools showed limited overall accuracy to identify malnutrition. Using combined nutritional markers of HGS or MST score was the most sensitive tool for detecting malnutrition in this advanced CKD without KRT population. Full article

The Ichubamba Yasepan wetlands, in the Andean páramos of Ecuador, suffer heavy metal contamination due to anthropogenic activities and volcanic ash from Sangay, impacting biodiversity and ecosystem services. This quasi-experimental study evaluated the bioaccumulation and tolerance of metals in high Andean species through stratified random sampling and linear transects in two altitudinal ranges. Concentrations of Cr, Pb, Hg, As, and Fe in water and the tissues of eight dominant plant species were analyzed using atomic absorption spectrophotometry, calculating bioaccumulation indices (BAIs) and applying principal component analysis (PCA), clustering, and linear discriminant analysis (LDA). Twenty-five species from 14 families were identified, predominantly Poaceae and Cyperaceae, with Calamagrostis intermedia as the most relevant (IVI = 12.74). The water exceeded regulatory limits for As, Cr, Fe, and Pb, indicating severe contamination. Carex bonplandii showed a high BAI for Cr (47.8), Taraxacum officinale and Plantago australis for Pb, and Lachemilla orbiculata for Hg, while Fe was widely accumulated. The LDA highlighted differences based on As and Pb, suggesting physiological adaptations. Pollution threatens biodiversity and human health, but C. bonplandii and L. orbiculata have phytoremediation potential. Full article

Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) are rare tumors with different clinical and biological characteristics. Ki-67 staining and mitotic counts are the most commonly used prognostic markers, but these methods are time-consuming and lack reproducibility, highlighting the need for innovative approaches that improve histological evaluation and prognosis. In our previous study, we observed that the microRNA (miRNA) expression profile of GEP-NENs correlates with the three grades of GEP-NENs. This study aimed to characterize a group of miRNAs that discriminate well-differentiated GEP-NENs grading 1 (G1) and grading (G2). Fifty formalin-fixed and paraffin-embedded tissue specimens from well-differentiated GEP-NENs G1 and G2 tissues were used for this study. The expression levels of 21 miRNAs were examined using qRT-PCR, while FGFR2 and FGF1 protein expression were evaluated through immunohistochemistry (IHC). We identified four miRNAs (hsa-miR-133, hsa-miR-150-5p, hsa-miR-143-3p and hsa-miR-378a-3p) that are downregulated in G2 GEP-NENs compared to G1. Bioinformatic analysis revealed that these miRNAs play a key role in modulating the FGF/FGFR signaling pathway. Consistent with this observation, we found that fibroblast growth factor receptor 2 (FGFR2) expression is markedly higher in G2 NENs patients, whereas its expression remains low in G1 NENs. Our findings highlight the potential use of miRNAs to confirm the histological evaluation of GEP-NENs by employing them as biomarkers for improving histological evaluation and tumor classification. Full article

Background: Gastric cancer (GC) is a malignant tumor of the gastrointestinal tract, characterized by high mortality rates and responsible for about one million new cases each year globally. Surgery is the main treatment, but achieving radical resection remains a relevant intraoperative challenge. Fluorescence-guided surgery offers clinicians greater capabilities for real-time detection of tumor nodules and visualization of tumor margins. In this field, the main challenge remains the development of fluorescent dyes that can selectively target tumor tissues. Methods: we examined the expression of the most suitable GC markers, including carcinoembryonic antigen cell adhesion molecule-5 (CEACAM5) and Claudin-4 (CLDN4), in GC cell lines. To further evaluate their expression, we performed immunohistochemistry (IHC) on tumor and healthy tissue samples from 30 GC patients who underwent partial gastrectomy at the Digestive System Surgery Unit, AOU Careggi, Florence. Additionally, we validated anti-CEACAM5 expression on patient-derived organoids. Furthermore, we developed a fluorescent molecule targeting CEACAM5 on the surface of GC cells and assessed its binding properties on patient tissue slices and fragments. Results: in this work, we first identified CEACAM5 as an optimal GC biomarker, and then we developed a fluorescent antibody specific for CEACAM5. We also evaluated its binding specificity for GC cell lines and patient-derived tumor tissue, achieving an optimal ability to discriminate tumor tissue from healthy mucosa. Conclusions: Overall, our results support the development of our fluorescent antibody as a promising tumor-specific imaging agent that, after further in vivo validation, could improve the accuracy of complete tumor resection. Full article

Background and Objectives: Accurate noninvasive differentiation between hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) remains a clinical challenge. This study aimed to assess the dignostic performance of apparent diffusion coefficient (ADC) values from diffusion-weighted MRI in distinguishing between HCC and ICC, with histological confirmation as the gold standard. Materials and Methods: A retrospective analysis was performed on 61 patients (41 HCC, 20 ICC) who underwent liver MRI and percutaneous biopsy between 2019 and 2024. ADC values were measured from diffusion-weighted sequences (b-values of 0, 500, and 1000 s/mm²), and regions of interest were placed over solid tumor areas. Statistical analyses included t-tests, one-way ANOVA, and ROC curve analysis. Results: Mean ADC values did not differ significantly between HCC (1.09 ± 0.19 × 10⁻³ mm²/s) and ICC (1.08 ± 0.11 × 10⁻³ mm²/s). ROC analysis showed poor discriminative ability (AUC = 0.520; p = 0.806). In HCC, ADC values decreased with lower differentiation grades (p = 0.008, η² = 0.224). No significant trend was observed in ICC (p = 0.410, η² = 0.100). Immunohistochemical markers such as CK-7, Glypican 3, and TTF-1 showed significant diagnostic value between tumor subtypes. Conclusions: ADC values have limited utility for distinguishing HCC from ICC but may aid in HCC grading. Immunohistochemistry remains essential for accurate diagnosis, especially in poorly differentiated tumors. Further studies with larger cohorts are recommended to improve noninvasive diagnostic protocols. Full article

Background and Objectives: Despite significant advances in surgical techniques and perioperative care, major adverse cardiovascular events (MACE) remain a leading cause of postoperative morbidity and mortality in patients undergoing coronary artery bypass grafting and/or aortic valve replacement. Accurate preoperative risk stratification is essential yet often limited by models that overlook atrial mechanics and underutilized biomarkers. Materials and Methods: This study aimed to develop an interpretable machine learning model for predicting perioperative MACE by integrating clinical, biochemical, and echocardiographic features, with a particular focus on novel physiological markers. A retrospective cohort of 131 patients was analyzed. An Extreme Gradient Boosting (XGBoost) classifier was trained on a comprehensive feature set, and SHapley Additive exPlanations (SHAPs) were used to quantify each variable’s contribution to model predictions. Results: In a stratified 80:20 train–test split, the model initially achieved an AUC of 1.00. Acknowledging the potential for overfitting in small datasets, additional validation was performed using 10 independent random splits and 5-fold cross-validation. These analyses yielded an average AUC of 0.846 ± 0.092 and an F1-score of 0.807 ± 0.096, supporting the model’s stability and generalizability. The most influential predictors included total atrial conduction time, mitral and tricuspid annular orifice areas, and high-density lipoprotein (HDL) cholesterol. These variables, spanning electrophysiological, structural, and metabolic domains, significantly enhanced discriminative performance, even in patients with preserved left ventricular function. The model’s transparency provides clinically intuitive insights into individual risk profiles, emphasizing the significance of non-traditional parameters in perioperative assessments. Conclusions: This study demonstrates the feasibility and potential clinical value of combining advanced echocardiographic, biochemical, and machine learning tools for individualized cardiovascular risk prediction. While promising, these findings require prospective validation in larger, multicenter cohorts before being integrated into routine clinical decision-making. Full article

Resistance to the fumigant phosphine (PH₃) was studied for 28 populations of Rhyzopertha dominica from eight states of the USA and four provinces of Canada, as well as for 34 populations of Tribolium castaneum from twelve states of the USA and four provinces of Canada, using both a discriminating dose bioassay and molecular marker analysis. We used a molecular marker analysis for a point mutation in the gene that encodes dihydrolipoamide dehydrogenase and facilitates the “strong resistance” phenotype in both species. Our results showed that PH₃ resistance was correlated with higher frequencies of the strong resistance R allele in both species (R² = 0.59 in R. dominica and R² = 0.79 in T. castaneum). We also found that recessive R allele frequency did not correlate well with the geographic distribution of the resistant populations of these two species (R² = 0.21 in R. dominica and R² = 0.15 in T. castaneum). Therefore, populations of both species with higher R allele frequencies had higher resistance levels to PH₃. Our results showed that the geographic distribution of PH₃ resistance in both species varied and was not related geographically, but this supports the idea that the adaptive evolution of PH₃ resistance in these species is caused by selection pressure for their resistance genes. Full article

Background: Autoimmune liver diseases (ALDs) are a diverse group of chronic inflammatory disorders. Individuals with a history of one autoimmune disease (AD) are at a substantially increased risk of developing additional autoimmune conditions. Polyautoimmunity has increasingly been recognized as a factor associated with a more complex disease course and poorer long-term outcomes. Methods: This retrospective, cross-sectional observational study reviewed medical records of patients diagnosed with ALDs who had been admitted to the gastroenterology clinic. Results: A total of 457 patients with ALDs were included. Polyautoimmunity was present in 194 patients (42.5%), and multiple autoimmune syndrome (MAS) was diagnosed in 26 of these patients (5.7%). Serological comparisons revealed that antinuclear antibody (ANA) positivity was significantly more common in the polyautoimmunity group. Only 22.2% of the patients with polyautoimmunity were ANA-negative, compared with 52.9% in those without. An ROC curve analysis was conducted to assess the predictive value of clinical and laboratory variables for polyautoimmunity. Among all the tested parameters, ANA positivity (>+2) had the strongest predictive value (AUC: 0.724). A disease duration longer than 6.5 years followed, with a moderate discriminative capacity (AUC: 0.677). Additionally, lower albumin levels (<3.0 g/dL) and elevated erythrocyte sedimentation rates (ESRs) (>29.5 mm/h) were significantly associated with polyautoimmunity. Conclusions: In our cohort, 42.5% of patients had at least one additional autoimmune disorder, highlighting the need for a systemic and comprehensive approach to patient care. Simple and accessible markers—such as ANA titers, disease duration, albumin levels, and ESRs—may help to identify patients at greater risk. Full article

Stropharia rugosoannulata, an ecologically valuable and economically important edible mushroom, faces challenges in strain-level identification and breeding due to limited genomic resources and the lack of high-resolution molecular markers. In this study, we generated high-quality genomic data for 105 S. rugosoannulata strains and identified over 2.7 million SNPs, unveiling substantial genetic diversity within the species. Using core gene-associated multiple nucleotide polymorphism (cgMNP) markers, we developed an efficient and transferable framework for strain discrimination. The analysis revealed pronounced genetic differentiation among cultivars, clustering them into two distinct phylogenetic groups. Nucleotide diversity (π) across 83 core genes varied significantly, highlighting both highly conserved loci under purifying selection and highly variable loci potentially associated with adaptive evolution. Phylogenetic analysis of the most variable gene, Phosphatidate cytidylyltransferase mitochondrial, identified 865 SNPs, enabling precise differentiation of all 85 cultivars. Our findings underscore the utility of cgMNP markers in addressing challenges posed by horizontal gene transfer and phylogenetic noise, demonstrating their robustness in cross-species applications. By providing insights into genetic diversity, evolutionary dynamics, and marker utility, this study establishes a foundation for advancing breeding programs, conservation strategies, and functional genomics in S. rugosoannulata. Furthermore, the adaptability of cgMNP markers offers a universal tool for high-resolution strain identification across diverse fungal taxa, contributing to broader fungal phylogenomics and applied mycology. Full article

Background/Objectives: The oral cavity represents a convenient route of administration for drugs that exhibit significant hepatic first-pass extraction. In this study, the mucosal permeation properties of selected active pharmaceutical ingredients (APIs) incorporated into oral cavity drug products that are approved by the U.S. Food and Drug Administration were quantified using the human-derived sublingual HO-1-u-1 and buccal EpiOral™ in vitro tissue models. Methods: Epithelial barrier properties were monitored using propranolol and Lucifer Yellow as prototypic transcellular and paracellular markers. APIs were dissolved in artificial saliva, pH 6.7, and transepithelial flux from the apical to the basolateral compartment was quantified using HPLC. Results: Apparent permeability coefficients (Papp) calculated for these APIs in the sublingual HO-1-u-1 tissue model varied from Papp = 2.72 ± 0.06 × 10⁻⁵ cm/s for asenapine to Papp = 6.21 ± 2.60 × 10⁻⁵ cm/s for naloxone. In contrast, the buccal EpiOral™ tissue model demonstrated greater discrimination power in terms of permeation properties for the same APIs, with values ranging from Papp = 3.31 ± 0.83 × 10⁻⁷ cm/s for acyclovir to Papp = 2.56 ± 0.68 × 10⁻⁵ cm/s for sufentanil. The tissue-associated dose fraction recovered at the end of the transport experiment was significantly increased in the buccal EpiOral™ tissue model, reaching up to 8.5% for sufentanil. Conclusions: Experimental permeation data collected for selected APIs in FDA-approved oral cavity products will serve as a training set to aid the development of predictive computational models for improving algorithms that describe drug absorption from the oral cavity. Following a robust in vitro–in vivo correlation analysis, it is expected that such innovative in silico modeling strategies will the accelerate development of generic oral cavity products by facilitating the utility of model-integrated evidence to support decision making in generic drug development and regulatory approval. Full article