Search Results (349)

Background/Objectives: Dysbiosis of the vaginal microbiota, particularly the loss of Lactobacillus spp. dominance, is linked to female infertility. While community state types (CSTs) I–III and V have been studied extensively, CST IV remains underexplored. The aim of this prospective study was to compare vaginal microbiota composition—specifically CST IVA and IVB—between fertile and infertile women. Methods: Vaginal samples were collected from 22 women (15 infertile, 7 fertile) using cervical brushes and analyzed via 16S rRNA gene sequencing. DNA was extracted, and V3–V4 regions were sequenced using the Illumina MiSeq platform. Taxonomic classification was performed with QIIME 2 and the Greengenes database. Differences in microbial composition were assessed using the Wilcoxon rank-sum test (p < 0.05) in SPSS v21.0. Results: Infertile women showed lower relative abundances of Lactobacillus spp. (31.54% vs. 42.32%) and Oscillospira spp. relative to fertile women. CST IV was more frequent in the infertile group (29.75% vs. 21.61%). Within CST IV, CST IVA accounted for a higher proportion in infertile women (7.0% vs. 0.94%), with Prevotella spp. representing 95.18% of CST IVA in infertile subjects, as opposed to the figure of 69.77% in fertile counterparts. No clear differences in CST IVB were observed between groups. Conclusions: Increased prevalence of Prevotella spp. in CST IVA may contribute to an unfavorable vaginal environment in infertile women, potentially affecting sperm viability. The presence of Oscillospira spp. in fertile women suggests it is associated with a healthy vaginal microbiota profile. Full article

The Zebra Optimization Algorithm (ZOA) is a metaheuristic algorithm inspired by the collective behavior of zebras in the wild. Like many other swarm intelligence algorithms, the ZOA faces several limitations, including slow convergence, susceptibility to local optima, and an imbalance between exploration and exploitation. To address these challenges, this paper proposes an improved version of the ZOA, termed the Multi-strategy Improved Zebra Optimization Algorithm (MIZOA). First, a multi-population search strategy is introduced to replace the traditional single population structure, dividing the population into multiple subpopulations to enhance diversity and improve global convergence. Second, the mutation operation of genetic algorithm (GA) is integrated with the Metropolis criterion to boost exploration capability in the early stages while maintaining strong exploitation performance in the later stages. Third, a novel selective aggregation strategy is proposed, incorporating the hunting behavior of the Coati Optimization Algorithm (COA) and Lévy flight to further enhance global exploration and convergence accuracy during the defense phase. Experimental evaluations are conducted on 23 benchmark functions, comparing the MIZOA with eight existing swarm intelligence algorithms. The performance is assessed using non-parametric statistical tests, including the Wilcoxon rank-sum test and the Friedman test. The results demonstrate that the MIZOA achieves superior global convergence accuracy and optimization performance, confirming its robustness and effectiveness. The MIZOA was evaluated on real-world engineering problems against seven algorithms to validate its practical performance. Furthermore, when applied to path planning tasks for Automated Guided Vehicles (AGVs), the MIZOA consistently identifies paths closer to the global optimum in both simple and complex environments, thereby further validating the effectiveness of the proposed improvements. Full article

Optimal Power Flow (OPF) problems are essential in power system planning, but their nonlinear and large-scale nature makes them difficult to solve with traditional optimization methods. Metaheuristic algorithms have become increasingly popular for solving OPF problems due to their ability to handle complex search spaces and multiple objectives. The Jellyfish Search Optimizer (JSO) is a metaheuristic algorithm that performs well for solving various optimization problems. However, it suffers from low exploration and an imbalance between exploration and exploitation. Therefore, this study introduces an improved JSO called Conscious Neighborhood-based JSO (CNJSO) to address these shortcomings. The proposed CNJSO suggests a new movement strategy named Best archive and Non-neighborhood-based Global Search (BNGS) to enhance the exploration ability. In addition, CNJSO adapts the concept of conscious neighborhood and the Wandering Around Search (WAS) strategy. The proposed CNJSO facilitates exploration of the search space and strikes a suitable balance between exploration and exploitation. The performance of CNJSO was evaluated on CEC 2018 benchmark functions, and the results were compared with those of ten state-of-the-art metaheuristic algorithms. In addition, the results were statistically validated using the Wilcoxon rank-sum and Friedman tests. Additionally, the effectiveness of CNJSO was assessed through the resolution of OPF problems. The experimental and statistical results confirm that the proposed CNJSO algorithm is competitive and superior to the compared algorithms. Full article

Objective: Neurosurgical interventions for medically refractory hypertonia (MRH) benefit both patients and their caregivers. Concurrent severe rotatory scoliosis and fusion constructs can make traditional microsurgical rhizotomy and navigated radiofrequency ablation (RFA) peripheral rhizotomy technically infeasible. We report the first case series of lumbosacral endoscopic ventral–dorsal rhizotomy (eVDR) in patients with MRH, and highlight this novel, minimally invasive, safe, and effective technique. Material and Methods: We retrospectively reviewed our single institution series of four patients with advanced hypertonia, gross motor function classification scale (GMFCS) 5, and severe rotatory scoliosis who underwent an eVDR using a flexible endoscope. We report demographics, operative characteristics, and outcomes. Results: Four patients underwent bilateral L1-S1 eVDR. Two patients had spastic quadriplegia and two had mixed spastic and dystonic hypertonia. Mean operative time was 225 ± 11 min and mean estimated blood loss (EBL) was 28.8 ± 26.2 mLs. Average length of stay was 2.75 days (range = 1–5 days), and average follow-up was 5.75 months (range = 3–9 months). All patients had significant decrease in bilateral lower extremity modified Ashworth Scale (mAS) scores (median decrease = 3, interquartile range [IQR] = 1; Wilcoxon rank-sum test z = −2.3, p = 0.02). The median decrease in Barry–Albright Dystonia Scale (BADS) scores for both patients with dystonia was 8 (IQR = 0). Two patients had minor perioperative events; none required additional surgery. All parents reported improvement in caregiving metrics. Conclusions: eVDR offers a safe and effective approach for tone reduction in patients with MRH and severe rotatory scoliosis and/or fusion hardware, which disallows traditional approaches. Full article

Objectives: To investigate the feasibility of contrast-enhanced mammography-guided biopsy (CEM-Bx) to diagnose cancer via targeting the associated enhancements in the patients with extensive suspicious microcalcifications. Methods: All the women with extensive suspicious microcalcifications were mammographically screened. Contrast-enhanced mammography was first examined, followed by CEM-Bx if there was any relevant enhancement; otherwise, patients without enhancement were submitted to conventional mammography-guided biopsy (MG-Bx). We recorded and analyzed the histological results, morphologies and distributions of the microcalcifications. The outcomes were also compared to those patients (control group) who did not assess with CEM and received MG-Bx only by the Wilcoxon rank-sum test. Results: Between November 2021 and November 2023, a total of 61 participants participated in the test. A total of 26 women underwent CEM-Bx, and 35 underwent MG-Bx. In total, 19 of the 26 CEM-Bx were diagnosed as cancer, and none by MG-Bx. The cancer diagnostic rates (CDRs) identified by CEM-Bx were 81.8% for regional microcalcifications and 66.7% for segmental or diffuse distributions. The CDR of the test group was higher than the control group, 31.4% to 20%, respectively. Otherwise, the CDR of CEM-Bx was significantly higher than MG-Bx in the control group (73.08% to 20%, p-valve < 0.01). Conclusions: CEM-Bx was a safe and feasible procedure. With identification of the enhanced target, CEM-Bx faithfully performed among the extensive distributed suspicious microcalcifications. Although CEM-Bx improves CDR, larger prospective trials with surgical validation of all lesions are needed before widespread adoption. Full article

Unmanned Aerial Vehicles (UAVs) have become increasingly valuable for accident scene reconstruction and forensic surveying due to their flexibility and ability to capture high-resolution imagery. This study investigates the impact of flight altitude, camera angle, and image overlap on the spatial accuracy of 3D models generated from UAV imagery. A total of 27 flight configurations were conducted using a DJI Phantom 4 Pro V2, combining three altitudes (30 m, 45 m, 60 m), three camera angles (90°, 75°, 60°), and three overlap levels (60%, 70%, 80%). The resulting 3D models were assessed by comparing measured linear distances between ground control points with known reference distances. The Root Mean Square Error (RMSE) was used to quantify model accuracy. The results indicated that lower flight altitudes, nadir or moderately oblique camera angles, and higher image overlaps consistently yielded the most accurate reconstructions. A Wilcoxon rank-sum test confirmed that the differences in accuracy across parameter settings were statistically significant. These findings highlight the critical role of flight configuration in achieving centimeter-level accuracy, as evidenced by RMSE values ranging from 1.7 to 7.6 cm, and provide practical recommendations for optimizing UAV missions in forensic and engineering applications. Full article

The Planet Optimization Algorithm (POA) is a meta-heuristic inspired by celestial mechanics, drawing on Newtonian gravitational principles to simulate planetary dynamics in optimization search spaces. While the POA demonstrates a strong performance in continuous domains, we propose an Improved Binary Planet Optimization Algorithm (IBPOA) tailored to the classical 0-1 knapsack problem (0-1 KP). Building upon the POA, the IBPOA introduces a novel improved transfer function (ITF) and a greedy repair operator (GRO). Unlike general binarization methods, the ITF integrates theoretical foundations from branch-and-bound (B&B) and reduction algorithms, reducing the search space while guaranteeing optimal solutions. This improvement is strengthened further through the incorporation of the GRO, which significantly improves the searching capability. Extensive computational experiments on large-scale instances demonstrate the IBPOA’s effectiveness for the 0-1 KP, showing a superior performance in its convergence rate, population diversity, and exploration–exploitation balance. The results from 30 independent runs confirm that the IBPOA consistently obtains the optimal solutions across all 15 benchmark instances, spanning three categories. Wilcoxon’s rank-sum tests against seven state-of-the-art algorithms reveal that the IBPOA significantly outperforms all competitors $(p<0.05)$, though it is occasionally matched in its solution quality by the binary reptile search algorithm (BinRSA). Crucially, the IBPOA achieves solutions 4.16 times faster than the BinRSA on average, establishing an optimal balance between solution quality and computational efficiency. Full article

Reflective practice is vital for bridging theory and professional application in undergraduate public health education, yet its use in non-Western contexts is underexamined. This mixed-methods study evaluated the Minor in Public Health at the Saw Swee Hock School of Public Health, National University of Singapore, using a convergent parallel design. Using a longitudinal student survey (baseline upon entry: n = 289; graduation upon completion: n = 78) and cross-sectional stakeholder survey (n = 17), quantitative analysis included chi-square tests for competency changes and Wilcoxon rank-sum tests for group comparisons. Thematic analysis of open-ended responses highlighted strengths in systems thinking, analytical skills, and interdisciplinary integration, but also gaps in practical experience, specialised knowledge, and professional communication. Students reported significant improvements in 10 of 13 competencies from baseline to graduation and rated their attainment higher than stakeholders across all competencies. Those who achieved all competencies also gave significantly more positive ratings of the programme in the domains of teaching and learning, and in engagement, assessment, and feedback. These findings underscore the role of reflective practice in aligning education with workforce needs and offer a scalable approach for curriculum development. The study provides actionable insights for educators to design responsive and reflective curricula that support the preparation of competent public health professionals in diverse global contexts. Full article

Incorporating frequency constraints into the optimum design of large-scale truss dome structures is crucial for maintaining seismic resilience, as the natural frequencies must remain within specified ranges. In this work, seven metaheuristic algorithms—including three variants of the Fitness–Distance–Balance-based Adaptive Guided Differential Evolution (FDB-AGDE), the Cheetah Optimizer (CO), the Bonobo Optimizer (BO), the Flood Algorithm (FLA), and the Lung Performance Optimization (LPO) are applied to solve high-dimensional truss sizing problems under strict frequency limitations. Their convergence characteristics and solution quality are systematically compared across multiple dome configurations. Besides traditional measures of computational efficiency and final weight minimization, a suite of statistical analyses is conducted: the Wilcoxon rank-sum test to assess pairwise performance significance, the Friedman test to establish overall rank ordering, and Cohen’s test to quantify effect sizes. The results reveal that LPO, BO, CO, and the first variant of FDB-AGDE consistently produce lighter feasible designs with lower variability, whereas FLA and other variants of FDB-AGDE exhibit heavier structures or higher dispersion. The findings underscore the value of robust, well-tuned metaheuristics and rigorous statistical evaluation in structural optimization, offering clear guidance for seismic-focused designers seeking both lightweight solutions and reliable performance across repeated runs. Full article

To address the issues of low convergence accuracy, poor population diversity, and susceptibility to local optima in the Red-billed Blue Magpie Optimization Algorithm (RBMO), this study proposes a multi-strategy improved Red-billed Blue Magpie Optimization Algorithm (SWRBMO). First, an adaptive T-distribution-based sinh–cosh search strategy is used to enhance global exploration and speed up convergence. Second, a neighborhood-guided reinforcement strategy helps the algorithm avoid local optima. Third, a crossover strategy is also introduced to improve convergence accuracy. SWRBMO is evaluated on 15 benchmark functions selected from the CEC2005 test suite, with ablation studies on 12 of them, and further validated on the CEC2019 and CEC2021 test suites. Across all test sets, its convergence behavior and statistical significance are analyzed using the Wilcoxon rank-sum test. Comparative experiments on CEC2019 and CEC2021 demonstrate that SWRBMO achieves faster convergence and higher accuracy than RBMO and other competitive algorithms. Finally, four engineering design problems further confirm its practicality, where SWRBMO outperforms other methods by up to 99%, 38.4%, 2.4%, and nearly 100% in the respective cases, highlighting its strong potential for real-world engineering applications. Full article

Kala-azar is associated with case-fatality rates as high as 10% in certain regions. Early identification of mortality biomarkers can significantly reduce this risk. This study, strengthened by a relatively high number of kala-azar-related deaths, aimed to identify serum cytokines as predictive biomarkers of fatal kala-azar. We compared 48 deceased patients with kala-azar to 42 survivors. The concentrations of IL-1β, IL-6, IL-8, IL-10, IL-12, and tumor necrosis factor-α (TNF-α) were measured by flow cytometry. Cytokine levels were compared between groups using the Wilcoxon rank-sum test. Receiver operating characteristic (ROC) analysis, coupled with Youden’s index, defined the optimal diagnostic threshold. Upon admission, IL-8 concentrations were substantially higher in deceased kala-azar patients (median 76.5 pg/mL [IQR 35.2–242.4 pg/mL]) than in survivors (median 26.4 pg/mL [IQR 15.1–47.7 pg/mL]; p < 0.0001). ROC analysis identified 49.3 pg/mL as the optimal cutoff. When rounded to the clinically convenient value of 50 pg/mL, IL-8 predicted a fatal outcome with an area under the curve of 0.75, sensitivity of 70.8%, and specificity of 76.2%. In contrast, IL-1β, IL-6, IL-10, IL-12, and TNF-α showed no significant prognostic utility. Our findings suggest that IL-8 levels equal to or greater than 50 pg/mL are a reliable predictor of fatal kala-azar. Full article

Background/Objectives: We aim to identify predictors of response to ICIs in patients with advanced solid tumors that exhibiting a TMB ≥ 10 mut/Mb. Methods: Patients treated with ICIs alone at Northwestern University between 1 January 2015 and 31 December 2020 were identified. Progression-free survival (PFS) and overall survival (OS) were calculated using the Kaplan–Meier method, and groups were compared using the log-rank test. Wilcoxon rank sum tests, chi-squared tests, and Fisher’s exact tests were used for univariable analyses evaluating the impact of clinical and genetic variables on response, with significance defined as p < 0.05. Results: A total of 117 patients were classified as ICI-sensitive (n = 88) or non-ICI-sensitive (n = 29). Among evaluable patients (n = 105), the overall response rate was 34% with 14% achieving a complete response. Median PFS and OS were 8.05 months and 26.8 months, respectively. Higher PFS rates were significantly linked to the ICI-sensitive tumor group (p = 0.009), absence of liver metastasis (p = 0.015), and no prior systemic treatment (p = 0.001) in both cohorts. In non-ICI-sensitive patients, a TMB of ≥15 mut/Mb correlated with improved outcomes (p = 0.012). Mutations in the MYC pathway (p = 0.03) and the MLL2 gene (p = 0.014) were associated with poorer responses, while mutations in the TERT gene were linked to better responses (p = 0.031). Conclusions: Patients without liver metastasis, mutations in TERT, and TMB ≥ 15 mut/Mb are associated with superior response, while mutations in the MYC pathway and MLL2 are associated with worse responses. Full article

The growing demand for health-promoting and eco-friendly foods has driven interest in biofunctional dairy products. Goat milk yogurt, though nutritionally beneficial, faces sensory challenges, while antioxidant-rich spent coffee grounds (SCGs), a coffee by-product, offer sustainable enhancement potential. This study assessed the consumer acceptance of goat milk yogurt enriched with 2% and 3% SCG extract. A total of 137 untrained consumers evaluated six sensory attributes—appearance, aroma, taste, texture, coffee–yogurt balance, and aftertaste—on a five-point hedonic scale. Due to non-normal data, Wilcoxon rank-sum tests and Spearman correlations were applied. No significant differences emerged between formulations (p > 0.05). Taste, aftertaste, and aroma were strongly correlated (r > 0.65). All attributes significantly predicted purchase intent (p < 0.01), with taste as the strongest driver (OR = 2.24). Consumers aged 26–35, usually presenting health or environmental concerns, showed greater acceptance. The addition of SCG extract did not compromise sensory quality, supporting its viability as a sustainable functional ingredient. These findings present high acceptance of a newly developed eco-friendly and nutritionally beneficial product, responding to consumers’ current qualitative demands related to the food they consume. Full article

Background: Type 2 diabetes mellitus (T2DM) increases sepsis risk due to immune dysfunction and chronic inflammation. Antidiabetic medications, while primarily used for glycemic control, may modulate sepsis susceptibility through immune and inflammatory pathways. This study investigates the association between antidiabetic medication use and sepsis risk in T2DM patients. Methods: A longitudinal cohort study was conducted using clinical registry data from 5009 T2DM patients at the University Hospital, Debrecen, Hungary (2016–2020). Sepsis cases were identified via ICD-10 code A41, and antidiabetic medication use was categorized using ATC codes. Baseline comorbidities and laboratory parameters were extracted. Chi-square and Wilcoxon rank–sum tests assessed associations between sepsis and categorical/numerical variables, respectively. Time-adjusted multivariate logistic regression evaluated predictors of sepsis risk, with odds ratios (ORs) and 95% confidence intervals (CIs) reported. Results: Age, hypertension, ischemic heart disease, nephropathy, elevated blood glucose, C-reactive protein, and creatinine also independently increased sepsis risk. Insulin use was associated with a 2.6-fold increased sepsis risk (OR = 2.6, 95% CI: 2.09–3.34, p < 0.001), while SGLT2 inhibitors (OR = 0.56, 95% CI: 0.34–0.91, p = 0.02) and GLP-1 receptor agonists (OR = 0.39, 95% CI: 0.19–0.79, p = 0.009) were protective. Conclusions: Insulin-treated patients may require closer infection monitoring, while SGLT2 inhibitors and GLP-1 RAs could be prioritized in high-risk individuals. These findings highlight the potential to inform risk stratification and guide personalized antidiabetic therapy to reduce sepsis risk in T2DM. Full article

Background/Objectives: While elevated Lp(a) levels are associated with incident heart failure development, the role of Lp(a) in established heart failure with reduced ejection fraction (HFrEF) versus heart failure with preserved ejection fraction (HFpEF) remains unexplored. Methods: We conducted a retrospective analysis of 387 heart failure patients from our institutional database (January 2018–June 2024). Patients were categorized as HFrEF (n = 201) or HFpEF (n = 186) using ICD-10 codes. Categorical variables were compared between heart failure types using the Chi-square test or Fisher’s Exact test, and continuous variables were compared using the two-sample t-test or Wilcoxon rank-sum test, as appropriate. Logistic regression was utilized to assess heart failure type as a function of Lp(a) levels, adjusting for covariates. Spearman correlation assessed relationships between Lp(a) and pro-BNP levels. Results: Despite significant demographic and clinical differences between HFrEF and HFpEF patients, Lp(a) concentrations showed no significant variation between groups. Median Lp(a) levels were 60.9 nmol/dL (IQR: 21.9–136.7) in HFrEF versus 45.0 nmol/dL (IQR: 20.1–109.9) in HFpEF (p = 0.19). After adjusting for demographic and clinical covariates, Lp(a) showed no association with heart failure subtype (OR: 1.001, 95% CI: 0.99–1.004; p = 0.59). Conclusions: Lp(a) levels do not differ significantly between HFrEF and HFpEF phenotypes, suggesting possible shared pathophysiological mechanisms rather than phenotype-specific biomarker properties. These preliminary findings may support unified screening and treatment strategies for elevated Lp(a) across heart failure, pending confirmation in larger studies. Full article