Background: Circulating microRNAs are an emerging noninvasive tool for monitoring physiological adaptations to exercise. miR-146a is of special interest as it plays an important role in inflammatory regulation and immune-response feedback at the cellular level. Methods: Ten exercise-trained and 10 nonexercise controls were included for this study. The fold change of miR-146a expression was determined. High miR-146a expression (the sample median split [median = 1.029]) was considered the primary outcome. To prevent outcome leakage, the following factors were included as model predictors: age, body mass index, and exercise-training status. Results: miR-146a fold-change values ranged from 0.656 to 1.854, with an overall mean of 1.080 ± 0.288. The exercise-trained group showed a numerically higher mean expression than nonexercise controls (1.127 ± 0.211 vs. 1.033 ± 0.354), although this difference was not statistically significant (Welch P = 0.483; Mann–Whitney P = 0.224). High miR-146a expression was observed in 7/10 exercise-trained participants and 3/10 controls (Fisher exact P = 0.179), suggesting a directional but underpowered group trend. In leave-one-out cross-validation, k-nearest neighbors achieved 75% accuracy (area under the receiver operating characteristic curve [AUC] = 0.710), quadratic discriminant analysis with quadratic feature expansion achieved 75% accuracy with the highest AUC (0.790), and polynomial linear discriminant analysis achieved the highest balanced classification performance with 80% accuracy (AUC = 0.770, Brier = 0.200, sensitivity = 0.80, and specificity = 0.80). Conclusions: In this small exploratory cohort, optimized classification improved the miR-146a signal to a defensible moderate level. The 80% best-model accuracy should be retained r because it was obtained using nonleakage predictors and clean internal validation.
Background: Genetic alterations in thyroid-stimulating hormone receptor (TSHR) are associated with a spectrum of thyroid disorders which either result hypothyroidism or hyperthyroidism. Objective: The present study aimed to screen for mutations or genetic variants in the TSHR gene among individuals with hypothyroidism and hyperthyroidism from the Mongoloid ethnic population of Northeast India, a genetically distinct and underrepresented group. Methods: Thyroid function parameters, including thyroid-stimulating hormone, triiodothyronine, tetraiodothyronine, free triiodothyronine, and free thyroxine, were measured using a chemiluminescence immunoassay system. Individuals diagnosed with hypothyroidism were selected for molecular analysis. Genomic DNA was extracted from peripheral blood samples and subjected to polymerase chain reaction amplification targeting exons 7, 9, and 10 of the TSHR gene. Amplified products were analyzed using agarose gel electrophoresis and subsequently sequenced by Sanger sequencing. Sequence alignment and variant identification were performed using BioEdit and Basic Local Alignment Search Tool against the reference sequence (Gene ID: 7253; RefSeq: NC_000014.9). Results: Out of 900 individuals, 223 (24.69%) were hypothyroid and 11 (1.22%) were hyperthyroid. A higher prevalence of hypothyroidism was observed with 223 (24.69%) cases than hyperthyroidism with 11 (1.22%) cases. Sanger sequencing identified the TSHR exon 10 variant c.2181G>C (rs1991517) in 18 hypothyroid cases, resulting in an amino acid substitution p.Glu727Asp (E727D). Conclusion: The c.2181G>C (p.E727D) variant of the TSHR gene was identified in hypothyroid individuals from the Mongoloid population of Northeast India.
Background: Colon adenocarcinoma (COAD) is the most prevalent type of colorectal cancer, originating from glandular cells lining the colon. This study investigated the expression and functional relevance of inflammasome-associated genes (NOD-like receptor family pyrin domain containing 3 [NLRP3], caspase-1 [CASP1], interleukin-1 beta [IL-1 β], and interleukin-18 [IL-18]) in COAD and explored metformin as a repurposed inflammasome modulator. Methods: An integrative in silico approach was employed to analyze the expression, survival significance, and stage specific expression in COAD. Metformin was evaluated through target prediction, absorption, distribution, metabolism, excretion, and toxicity profiling, molecular docking, and 100 ns molecular dynamics (MD) simulations to assess its interaction with inflammasome-associated proteins. Results: Analysis revealed that all four genes are significantly upregulated in COAD. High expression of NLRP3 and IL-1 β strongly predicts poor overall survival and correlates with advanced disease stage, suggesting a pro-tumorigenic role for chronic inflammasome activation in established COAD. While CASP1 was upregulated, its expression level was not prognostic, indicating upstream NLRP3 activation and IL-1 β effector levels are rate-limiting. Metformin was identified as a promising inhibitor with an excellent safety profile. Molecular docking demonstrated strong binding affinities with Pro-caspase, NLRP3, and IL-1 β as key targets. Subsequent 100 ns MD simulations showed that while the IL-1 β-Metformin complex was moderately stable, the IL-18-Metformin complex exhibited greater stability and more persistent key interactions. Conclusions: In conclusion, these computational findings identify the NLRP3 inflammasome as a critical prognostic pathway in COAD and provide a strong mechanistic rationale for validating metformin as a therapeutic modulator of this axis.
Background: Pentraxin 3 (PTX3) is an anti-inflammatory biomarker associated with cardiac vascular regeneration. The study aimed to explore the importance of PTX3 as a diagnostic discriminator biomarker for hyperthyroidism and its relationship with cardiometabolic indices. Methods: The case-control study included 320 participants, divided equally into a hyperthyroidism group and a healthy control group. The data were distributed across models that included the first PTX3, the second metabolic indices, and the third cardiovascular indices. Results: PTX3 levels were significantly higher in patients with hyperthyroidism. Cardiometabolic indices, particularly those indicating insulin resistance, showed higher levels in the hyperthyroidism group. Analysis of the receiver operating characteristic curve revealed an area under the curve value of 0.906 (P < 0.001) for PTX3, confirming its diagnostic discriminator as a biomarker for hyperthyroidism, while the cardiometabolic indices did not show significant. Furthermore, PTX3 showed a positive correlation in forest plot analysis of crude and adjusted logistic regression models and Multidomain Restricted Cubic Spline logistic regression curves. The Pearson correlation coefficient showed that PTX3 has a significant negative association with Triglyceride–cholesterol–body weight index and Homeostatic Model Assessment of insulin sensitivity (HOMA-%S). Conversely, a significant positive association with Homeostatic model assessment for insulin resistance (HOMA-IR) and Triglyceride-glucose index. Conclusion: This study emphasizes the importance of monitoring PTX3 and serum cardiometabolic indices in patients with hyperthyroidism to aid prognostic evaluation and risk stratification. This study is also the first to suggest a potential predictive role for PTX3 in diagnosing hyperthyroidism, which requires validation in larger prospective studies.
Background: Cardiovascular stents have greatly improved the treatment of coronary and peripheral vascular disease. However, conventional stents still have limitations, particularly their standardized designs and limited ability to adapt to complex vascular anatomy and individual patient needs. Three-dimensional (3D) printing offers new possibilities for developing customized stents with greater control over their structure, materials, and therapeutic functions. Methods: This narrative review examined peer-reviewed studies identified through PubMed/MEDLINE, Scopus, and Web of Science, focusing mainly on research published between January 2019 and June 2026. The literature was qualitatively reviewed with particular attention to 3D-printing technologies, biomaterials, digital and patient-specific design, mechanical and biological performance, functional modifications, and challenges related to clinical translation. Of 45 identified records, 37 publications were included in the final synthesis. Results: Among the 37 included publications, 15 (40.5%) were in vitro studies, 8 (21.6%) were computational or virtual studies, 5 (13.5%) were animal studies, 3 (8.1%) were clinical or translational studies, and 6 (16.2%) were review or perspective articles. Current research shows that 3D printing can provide greater control over stent geometry, strut dimensions, lattice structure, porosity, and material distribution. Extrusion-based printing, photopolymerization, and metal additive manufacturing have been explored using polymeric, metallic, biodegradable, and composite materials. The integration of medical imaging, computer-aided design, and computational modeling also supports patient-specific stent development and mechanical optimization. However, most evidence remains preclinical, with important challenges involving mechanical durability, degradation control, hemocompatibility, manufacturing reproducibility, scalability, regulatory requirements, and limited long-term clinical evidence. Conclusion: 3D printing offers promising opportunities for developing more personalized and multifunctional cardiovascular stents. However, the technology remains at an emerging stage and has not yet demonstrated clear clinical superiority over established stent platforms. Further research is needed to improve materials and manufacturing processes and to establish long-term safety, efficacy, and clinical value through well-designed clinical studies.
