Search Results (845)

Background: Epicardial adipose tissue (EAT) is a metabolically active visceral fat depot increasingly associated with the development and progression of coronary artery disease (CAD). Transthoracic echocardiography is the most widely used modality for EAT assessment; however, substantial heterogeneity exists regarding the timing of measurement within the cardiac cycle, with EAT thickness variably assessed during systole or diastole. Whether these measurements provide equivalent information for identifying obstructive CAD remains unclear. This systematic review and meta-analysis evaluated the association between echocardiographically measured EAT thickness and angiographically confirmed obstructive CAD, with specific focus on systolic versus diastolic assessments. Methods: PubMed, Scopus, and EMBASE were systematically searched through December 2025 for observational studies comparing EAT thickness in patients with and without obstructive CAD confirmed by invasive coronary angiography. Random-effects models were used to pool standardized mean differences (SMDs) for systolic and diastolic EAT thickness. Heterogeneity was assessed using the I² statistic, publication bias by funnel plots and Egger’s regression test, and robustness by meta-regression and leave-one-out sensitivity analyses. Results: Twenty-two studies including more than 6500 patients were analyzed. Both systolic and diastolic EAT thickness were significantly greater in patients with obstructive CAD than in non-CAD controls. Systolic EAT showed a large, pooled effect size (SMD 1.27; 95% CI 0.96–1.59; p < 0.001), while diastolic EAT demonstrated a similarly strong association (SMD 1.59; 95% CI 1.10–2.07; p < 0.001). Heterogeneity was substantial (I² > 90%), but the direction of effect was consistent across all studies. Meta-regression analyses indicated that demographic, clinical, metabolic, geographic, and methodological characteristics, including ultrasound software/vendor category and timing of EAT measurement, did not significantly moderate the association between EAT thickness and obstructive CAD. No significant publication bias was detected, and sensitivity analyses confirmed the robustness of the results. Conclusions: Echocardiographically measured EAT thickness is strongly and consistently associated with obstructive CAD, irrespective of whether measurements are obtained during systole or diastole. Although both approaches show robust discriminatory capacity at the population level, differences in effect magnitude suggest that they may not be fully interchangeable. Moreover, in the absence of standardized and broadly applicable cut-off values, the interpretation and clinical management of EAT measurements as individual risk predictors require further investigation. Full article

Background/Objectives: Type 2 diabetes mellitus (T2DM) significantly elevates the risk of coronary artery disease (CAD), particularly in Asian populations where both conditions are epidemic. While shared genetic factors contribute to this comorbidity, evidence from Asian cohorts remains fragmented, with limited focus on population-specific variants. This meta-analysis synthesizes evidence on genetic variants associated with CAD risk in Asian patients with T2DM. Methods: We systematically searched several databases according to the PRISMA statement and checklist. Pooled odds ratios (ORs) with corresponding 95% confidence intervals (CIs) were calculated using random-effects models, with heterogeneity assessed via I² and Cochran’s Q, and publication bias via funnel plots and Egger’s test. Results: In total, data on 11,268 subjects were reviewed, including 4668 cases and 6600 controls. Among 950 identified studies, 18 met eligibility criteria, and 14 studies provided sufficient data for the meta-analysis. The random-effects pooled estimate across all studied variants was not statistically significant (OR = 1.16 [95% CI: 0.68–2.00]; z = 0.56, p = 0.58). However, analysis of individual loci revealed gene-specific associations with CAD among this population: PCSK1 gene (OR = 2.12 [95% CI: 1.26–3.52]; p < 0.05; weight = 8.77%), GLP1R gene (OR = 2.25 [95% CI: 1.27–3.97]; p < 0.01; weight = 8.62%). ADIPOQ gene (OR = 8.00 [95% CI: 2.34–27.14]; p < 0.01; weight = 6.35%). Several genes were associated with an elevated risk of CAD: PCSK1 gene (OR = 2.12 [95% CI: 1.26–3.52]; p < 0.05; weight = 8.77%), GLP1R gene (OR = 2.25 [95% CI: 1.27–3.97]; p < 0.01; weight = 8.62%) and ADIPOQ gene (OR = 8.00 [95% CI: 2.34–27.14]; p < 0.01; weight = 6.35%). Several genes were associated with possible protective effects: ACE gene (OR = 0.41 [95% CI: 0.23–0.73]; p < 0.01; weight = 8.57%), Q192R gene (OR = 0.20 [95% CI: 0.08–0.52]; p < 0.001; weight = 7.41%). Heterogeneity was substantial (τ² = 0.78; I² = 81.95%; Q (13) = 64.67, p < 0.001). Conclusions: This first meta-analysis of genetic variants associated with CAD in Asian populations with T2DM identified specific locus-level associations implicating lipid metabolism, incretin signaling, and oxidative stress pathways. The lack of a significant pooled effect, alongside high heterogeneity, underscores the complexity and population-specific nature of this genetic architecture. These findings suggest that effective precision risk stratification may depend more on specific variants than on a broad polygenic signal, highlighting the need for further research in a larger, distinct sample size. Full article

Background: Differentiating bipolar disorder (BD) from unipolar major depressive disorder (MDD) at first episode is clinically consequential but challenging. Artificial intelligence/machine learning (AI/ML) may improve early diagnostic accuracy across imaging and non-imaging data sources. Methods: Following PRISMA 2020 and a pre-registered protocol on protocols.io, we searched PubMed, Scopus, Europe PMC, Semantic Scholar, OpenAlex, The Lens, medRxiv, ClinicalTrials.gov, and Web of Science (2014–8 October 2025). Eligible studies developed/evaluated supervised ML classifiers for BD vs. MDD at first episode and reported test-set discrimination. AUCs were meta-analyzed on the logit (GEN) scale using random effects (REML) with Hartung–Knapp adjustment and then back-transformed. Subgroup (imaging vs. non-imaging), leave-one-out (LOO), and quality sensitivity (excluding high risk of leakage) analyses were prespecified. Risk of bias used QUADAS-2 with PROBAST/AI considerations. Results: Of 158 records, 39 duplicates were removed and 119 records screened; 17 met qualitative criteria; and 6 had sufficient data for meta-analysis. The pooled random-effects AUC was 0.84 (95% CI 0.75–0.90), indicating above-chance discrimination, with substantial heterogeneity (I² = 86.5%). Results were robust to LOO, exclusion of two high-risk-of-leakage studies (pooled AUC 0.83, 95% CI 0.72–0.90), and restriction to higher-rigor validation (AUC 0.83, 95% CI 0.69–0.92). Non-imaging models showed higher point estimates than imaging models; however, subgroup comparisons were exploratory due to the small number of studies: pooled AUC ≈ 0.90–0.92 with I² = 0% vs. 0.79 with I² = 64%; test for subgroup difference Q = 7.27, df = 1, p = 0.007. Funnel plot inspection and Egger/Begg tests found that we could not reliably assess small-study effects/publication bias due to the small number of studies. Conclusions: AI/ML models provide good and robust discrimination of BD vs. MDD at first episode. Non-imaging approaches are promising due to higher point estimates in the available studies and practical scalability, but prospective evaluation is needed and conclusions about modality superiority remain tentative given the small number of non-imaging studies (k = 2). Full article

The increasing demand for rapid identification of bacteria capable of degrading environmentally relevant organic compounds highlights the need for scalable and selective analytical tools. Cupriavidus necator catabolizes several hydroxybenzoic acids, including 2-hydroxybenzoate (salicylate, 2-HBA), 4-hydroxybenzoate (4-HBA), and 3-hydroxybenzoate (3-HBA), funneling them into central aromatic catabolism via monooxygenation to 2,5-dihydroxybenzoate (gentisate, 2,5-dHBA) and 3,4-dihydroxybenzoate (protocatechuate, 3,4-dHBA) followed by the oxidative cleavage reaction, enabling complete conversion to tricarboxylic acid (TCA) cycle intermediates. To quantify how readily C. necator is able to activate catabolic genes in response to hydroxybenzoic acid, an extracellular ligand, we applied an approach centered on a transcription-factor (TF)-based biosensor that combines ligand-bound regulator activity with a fluorescent reporter. This approach allowed to evaluate the ligand sensitivity by determining gene activation threshold AC_min and half-maximal effective concentration EC₅₀. Amongst studied hydroxybenzoic acids, 2-HBA and 4-HBA sensors from C. necator showed very low thresholds 4.8 and 2.4 μM and EC₅₀ values of 19.91 and 13.06 μM, indicating high sensitivity to these compounds and implicating a scavenging characteristic of associated catabolism. This study shows that the TF-based-biosensor approach applied for mapping functional sensing ranges of hydroxybenzoates combined with the research and informatics of catabolism can advance our understanding of how gene expression regulation systems have evolved to respond differentially to the availability and concentration of carbon sources. Furthermore, it can inform metabolic engineering strategies in the prevention of premature pathway activation or in predicting competitive substrate hierarchies in complex mixed environments. Full article

Kaprekar’s routine, i.e., sorting the digits of an integer in ascending and descending order and subtracting the two, defines a finite deterministic map on the state space of fixed-length digit strings. While its attractors (such as 495 for $D=3$ and 6174 for $D=4$) are classical, the global information-theoretic structure of the induced dynamics and its dependence on the digit length D have received little attention. Here an exhaustive analysis is carried out for $D\in \{3,4,5,6\}$. For each D, all states are enumerated and the transition structure is computed numerically; attractors and convergence distances are obtained, and the induced distribution over attractors across iterations is used to construct “entropy funnels”. Despite the combinatorial growth of the state space, average distances remain small and entropy decays rapidly before entering a slow tail. Permutation symmetry is then exploited by grouping states into digit multisets and, in a further reduction, into low-dimensional digit-gap features. On this gap space, a first-order Markov approximation is empirically estimated by counting one-step transitions induced by the exhaustively enumerated deterministic map. From the resulting empirical transition matrix, drift fields and the stationary distribution are computed numerically. These quantities serve as descriptive summaries of the projected dynamics and are not derived in closed form. Full article

Neonicotinoids are synthetic nicotine-like compounds extensively used globally as insecticides for agricultural and urban purposes. Neonicotinoid-contaminated produce is a major public health concern worldwide. Limited epidemiological studies have shown an association of neonicotinoid exposure with abnormal semen analysis. This study aimed to elucidate the potential disruption of the androgen receptor (AR) by eight common neonicotinoids, including imidacloprid (IMI), acetamiprid, clothianidin, thiamethoxam, dinotefuran, thiacloprid (THI), nitenpyram, and nithiazine using docking and molecular dynamics (MD) simulation. The results showed good binding strength of all compounds (except THI) with AR, as indicated by high binding energy, high binding affinity, and number of bonding interactions. The results of MD simulation supported the conformational stability and structural dynamic behavior of the AR-IMI (receptor-neonicotinoid) complex upon binding. This was indicated by root mean square deviation showing stability of the complex; the root mean square fluctuation showing minimized residual fluctuations upon binding; the radius of gyration showing greater compactness of the protein structure; the solvent-accessible surface area showing no changes upon binding; and the Gibbs funnel energy of the landscape showing a stable conformation state with minimum energy and slight change in size and position of the sampled energy basin of the AR, with a stable equilibrium. Taken together, the structural dynamics results showed that neonicotinoids are bound stably in the same ligand-binding domain of the AR as the native ligand testosterone. This may perturb the natural binding of testosterone with the AR and potentially disrupt downstream signaling and biological pathways, leading to male reproductive dysfunction. Full article

Background/Objectives: The outcomes of biologics in severe eosinophilic asthma (SEA) in real-world settings are less known. We describe the SEA population, treatment patterns, and outcomes following benralizumab authorization in Romania. Methods: BREEZE was a retrospective chart review study with a pre–post design conducted in five Central Eastern European and Baltic countries, including Romania (July 2022–January 2023). Adult SEA patients receiving ≥1 benralizumab dose in routine care were enrolled with up to 56 weeks (W) follow-up after benralizumab initiation. Using a funnel approach, the number of patients decreased throughout the follow-up; changes from baseline were tested in patients with available data. Results: The Romanian cohort included 131 patients (mean age: 54.4 years at benralizumab initiation; 66% females). Half of patients (53%) received 8 benralizumab doses; only 3 discontinued treatment. At benralizumab initiation, 15% were on maintenance oral corticosteroids (mOCS, median dose: 12.5 mg/day prednisone-equivalent; 17/20 patients > 5 mg/day). At W48, 11.4% of 70 patients with available data continued using mOCS (median dose: 5 mg/day; 3/8 > 5 mg/day). The annualized exacerbation rate was 2.61 (95%CI: 2.28–2.98) at baseline, reducing by 89% at W16 and 90% at W48. Blood eosinophils decreased early from a median of 620 cells/μL (94/120 > 400 cells/μL) at baseline to 1 cell/μL at W16 (n = 36; p < 0.001). FEV₁ increased from 1.8 L at baseline to 2.06 L at W16 (n = 59; p < 0.001), 2.15 L at W24 (n = 51; p < 0.001), and 1.96 L at W48 (n = 31; p = 0.002). Most patients had poorly controlled asthma (103 with ACT < 16) at baseline; score increased >9 points at W16 (n = 81; p < 0.001), W24 (n = 80; p < 0.001), and W48 (n = 55; p = 0.002). Conclusions: Our national cohort contributes to the increasing evidence on the meaningful results of benralizumab in SEA patients treated in routine practice. Full article

The presented dataset contains spatial models of cones formed from lunar soil simulants. The cones were formed in a laboratory by allowing the soil to fall freely through a funnel. Then, the cones were measured using three methods: a high-precision handheld laser scanner (HLS), photogrammetry, and a low-cost LiDAR system integrated into an iPad Pro. The dataset consists of two groups. The first group contains raw measurement data, and the second group contains the geometry of the cones themselves, excluding their surroundings. This second group was prepared to support the calculation of the cones’ volume. All data are provided in standard 3D file format (.STL). The dataset enables direct comparison of resolution and geometric reconstruction performance across the three techniques and can be reused for benchmarking 3D processing workflows, segmentation algorithms, and shape reconstruction methods. It provides complete geometric information suitable for validating automated extraction procedures for parameters such as cone height, base diameter, and angle of repose, as well as for further research into planetary soil and granular material morphology. Full article

This study investigates the synergistic influence of recycled concrete aggregate (RCA) and recycled steel fibers (RSF) on the fresh and hardened performance of eco-efficient fiber-reinforced self-compacting concrete (SCC). Twelve C30/37.5 mixtures were produced using demolition waste as coarse RCA at replacement levels of 25, 50, 75, and 100% by mass, combined with RSF recovered from scrap tires at volume fractions of 0.25, 0.50, and 0.75%. Fresh properties were assessed in accordance with EFNARC guidelines using slump-flow (T500), V-funnel, L-box, and J-ring tests, while hardened performance was evaluated through compressive, splitting tensile, and flexural strengths at 28 days, together with density and ultrasonic pulse velocity (UPV). Increasing RCA and RSF contents reduced workability, reflected in lower slump-flow diameters and higher T500 and V-funnel times, although most mixtures maintained satisfactory self-compacting behaviour. Compressive strength decreased with RCA content and, to a lesser extent, with higher RSF, with a maximum reduction of about 39% at 100% RCA relative to the control mix, yet values remained structurally acceptable. In contrast, RSF markedly enhanced tensile and flexural responses: at 25% RCA, 0.75% RSF increased splitting tensile and flexural strengths by approximately 41% and 29%, respectively, compared with the corresponding fiber-free mix. RCA reduced density and UPV by about 10–14%, but these reductions were partially mitigated by RSF addition. Overall, the results demonstrate that SCC with moderate RCA (25–50%) and RSF (0.50–0.75%) can achieve a favourable balance between rheological performance and enhanced tensile and flexural behaviour, offering a viable composite solution for sustainable structural applications. Full article

Background: While immune checkpoint inhibitors (ICIs) have improved survival in mNSCLC, outcomes may be disparate by age, race, and sex. However, given the limited diversity of trial populations, data are limited. Methods: A systematic review and meta-analysis were conducted of phase III prospective trials of ICIs in mNSCLC initiated after 2015, identified from PubMed and ClinicalTrials.gov in September 2025. Trials that did not report overall survival by race, sex, or age distribution were excluded. Random-effects meta-analyses were used to pool ratios of hazard ratios (RHRs) for overall survival to assess treatment-by-subgroup interactions by sex (men vs. women), race (white vs. Asian), and age (<65 vs. ≥65). Random-effects meta-analyses of odds ratios (ORs) for death were also performed for each subgroup in the investigational treatment arm and across all patients. Heterogeneity across trials was evaluated by Cochran’s Q test and I² statistics. Publication bias was assessed by Egger’s tests and funnel plots. Results: A total of 21 trials comprising 10,950 patients were included in the meta-analysis. Women have a non-significantly smaller overall survival benefit with the investigational treatment than with control compared with men (RHR 0.91; p = 0.17). On investigational agents, white patients had higher odds of death (OR 1.76; p = 0.0496) compared to Asian patients. Similarly, white patients had higher odds of death across both treatment arms compared to Asian patients (OR 2.35; p < 0.001). No trials reported subgroup analysis for Black patients due to small sample sizes. Patients ≥65 years old have a non-significantly smaller overall survival benefit with investigational agents compared with control (RHR 0.92; p = 0.19). Discussion: This study did not identify significant differences in overall survival benefit on the investigational treatment across race, sex, or age subgroups. Still, it remains unclear whether women and patients ≥65 years old derive less survival benefit from ICIs than men and younger patients. Asian patients had significantly greater survival than white patients on investigational therapies and all therapies, while Black patients were underrepresented in trials. Our results highlight the need for more representative trial populations and standardized reporting of subgroup analysis to ensure equitable benefit and evaluation of ICIs in mNSCLC treatment. Our meta-analysis was limited by inconsistent data reporting across subgroups and by the lack of time-to-event survival data within subgroups. Full article

Background: Brain-derived neurotrophic factor (BDNF) is a key regulator of neuroplasticity, cognitive function, and mental health. Exercise is proposed as a non-pharmacological strategy to enhance BDNF; however, findings across neurological and non-neurological disorders remain inconsistent, and the influence of exercise type or dose-related parameters remains unclear. Objective: This meta-analysis evaluated the effects of exercise interventions on peripheral BDNF levels in individuals with neurological (e.g., multiple sclerosis, cognitive impairment, schizophrenia, depression) and non-neurological (e.g., obesity, type 2 diabetes, cancer) disorders, and examined whether outcomes varied by disease category, exercise modality, or dose. Methods: A systematic search of Web of Science, PubMed, ScienceDirect, Scopus, and Cochrane was conducted up to 1 October 2025. Eligible randomized controlled trials (RCTs) and the quality of evidence were assessed using the PEDro scale and the GRADE approach, respectively. Random-effects models were applied, with subgroup analyses (neurological vs. non-neurological; exercise type; duration and assay type), meta-regressions (duration, frequency, session length), and publication bias tests (funnel plot, Begg’s test, Egger’s regression, and trim-and-fill). Results: Nineteen RCTs, including 850 participants, were analyzed. According to low-quality evidence, exercise significantly increased peripheral BDNF (SMD = 1.03, 95% CI: [0.56–1.49, p < 0.0001). Effects did not differ significantly between neurological (SMD = 0.91, 95% CI: 0.31–1.50) and non-neurological (SMD = 1.23, 95% CI: 0.47–1.99) conditions (Q (1) = 0.44, p = 0.51). Subgroup analyses revealed significant improvements for resistance exercise (SMD = 1.57, 95% CI: 0.91–2.23), followed by aerobic (SMD = 1.44, 95% CI: 0.36–2.52) and combined exercise (SMD = 0.55, 95% CI: 0.21–0.89). Meta-regressions showed no moderating effects of duration (β = 0.0101, p = 0.834), weekly frequency (β = 0.1464, p = 0.648), minutes per session (β = −0.0124, p = 0.233) or total weekly minutes (β = 0.0005, p = 0.919) apart from age and baseline BDNF level factors (β = 0.0348, p = 0.020; β = −0.035, p = 0.0258). Publication bias tests indicated minimal publication bias, with adjusted effects remaining robust. Conclusions: Exercise interventions have been shown to increase peripheral BDNF significantly across diverse clinical populations. In particular, resistance and aerobic exercise protocols accounted for the exploratory component, whereas simple dose-related factors did not explain the variability. These findings are consistent with the biological plausibility of exercise-induced neuroplasticity and underscore the need for larger, pre-registered RCTs with harmonized biomarker protocols to strengthen clinical translation. However, the certainty of evidence is limited by small sample sizes and the frequent lack of blinding of participants and assessors across included trials. Full article

Objective: This study aimed to systematically evaluate the therapeutic effects of repetitive transcranial magnetic stimulation (rTMS) on gait, motor function, and balance in patients with Parkinson’s disease (PD) and identify optimal stimulation parameters for clinical application. Methods: This systematic review and meta-analysis of randomized controlled trials (CTs) was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. PubMed, EMBASE, Cochrane Central, Scopus, and Ovid-LWW were searched until December 2024 for RCTs evaluating the effects of rTMS on PD-related gait, balance, or motor outcomes. Nineteen studies (n = 547) met the inclusion criteria. Data on study characteristics, rTMS protocols (frequency, target area, pulses, session duration, number of sessions, and treatment duration), and outcome measures (freezing of gait questionnaire [FOG-Q], gait speed, Unified Parkinson’s Disease Rating Scale Part III [UPDRS-III], UPDRS total, and timed up and go [TUG] test) were extracted. Effect sizes (Hedges’ g) were pooled using inverse variance meta-analysis, heterogeneity was assessed using I², and publication bias was assessed using funnel plots and Egger’s regression. Results: rTMS produced significant improvements in gait freezing (FOG-Q: g = −0.74; 95% confidence interval [CI] [−1.05, −0.43]; p < 0.001), gait speed (g = 0.62; 95% CI [0.29, 0.95]; p < 0.001), and motor symptoms (UPDRS-III: g = −0.42; 95% CI [−0.70, −0.15]; p = 0.003). No significant effects were observed for UPDRS total (g = 0.18; p = 0.58) or balance (TUG, g = −0.29; p = 0.06). Egger’s test indicated publication bias for gait speed (p = 0.016); however, trim-and-fill imputed zero studies. Subgroup analyses indicated that high-frequency stimulation of the supplementary motor area (SMA) for ≥20 min over 10 sessions (total duration <2 weeks or ≥2 weeks) optimally improved gait speed, whereas low-frequency stimulation targeting M1 and SMA with >1000 pulses per session for 20 min over 10 sessions within <2 weeks most effectively improved the UPDRS-III scores. Conclusions: rTMS exerts moderate and significant benefits on gait and motor performance in PD, particularly when tailored protocols involving SMA or M1 stimulation are employed. High-frequency SMA protocols improve gait speed, whereas low-frequency M1/SMA protocols optimize motor symptom relief. These findings provide evidence-based guidance for rTMS implementation in PD rehabilitation. Full article

Background and Objectives: Physician burnout, commonly described as emotional exhaustion (EE), depersonalization (DP), and reduced personal accomplishment (PA), remains common. We assessed whether structured, individual-focused programs improve Maslach Burnout Inventory (MBI) subscale scores among physicians. Materials and Methods: Registration, Open Science Framework, doi: 10.17605/OSF.IO/UAZ6B (unfunded). PubMed (MEDLINE) was searched from 1 January 2009 to 9 December 2023 (last searched 9 December 2023) to conduct a meta-analysis. Eligible English language studies evaluated a physician-focused intervention intended to reduce burnout and reported MBI outcomes; eligible designs were randomized trials, crossover trials, prospective cohort studies, or single-group pre–post studies. Risk of bias was rated using the original Cochrane Risk of Bias by two reviewers with consensus resolution. For quantitative synthesis, we pooled mean differences (MD) using fixed-effect inverse-variance meta-analysis with 95% confidence intervals (CI); heterogeneity was summarized with I², and funnel plots were inspected qualitatively. Results: Of 2769 records, 17 studies met criteria for qualitative analysis, and 6 studies (n = 585 physicians; 273 intervention, 312 control) were pooled. Interventions included mindfulness curricula, professional coaching, or structured peer discussion groups. Compared with controls, interventions were associated with lower EE (MD −5.56; 95% CI, −6.68 to −4.44; I² = 42%), lower DP (MD −2.11; 95% CI, −2.64 to −1.58), and higher PA (MD 2.01; 95% CI, 1.41 to 2.60). Funnel plots suggested asymmetry for EE. Evidence was limited by few trials, frequent high or unclear risk of bias in at least one domain, and variable intervention formats, and one pooled study used a single-group pre–post design. Conclusions: Structured individual-focused programs were associated with small but statistically significant changes in MBI subscale scores in physicians, but confidence in magnitude and generalizability are limited by study quality and a small evidence base. These programs may be useful adjuncts to organizational approaches to burnout. Full article

Background/Objectives: Prostate cancer is the most frequent male malignancy. The incidence of disease varies among different ethnic groups. CYP3A polymorphisms are candidates for prostate cancer susceptibility studies. The aim of the present study is to investigate the ethnicity-related clinical impact of CYP3A4 variants on prostate cancer risk. Methods: A systematic literature search and meta-analysis were conducted according to PRISMA guidelines. A total of 10 eligible studies, including 3116 prostate cancer cases and 3008 healthy controls, were analyzed. We evaluated the association between the CYP3A4*1B (rs2740574, −392 A > G) variant and prostate cancer risk in European Caucasians. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using six genetic models. Data were analyzed using fixed and random-effects models based on the I2 value of heterogeneity magnitude. Funnel plots and Egger’s linear regression tests were used to assess publication bias. Results: CYP3A4*1B was associated with prostate cancer susceptibility in the allele (G vs. A: OR = 1.32, CI = 0.91–1.93), dominant (AG + GG vs. AA OR = 1.41, CI = 0.95–2.09), recessive (GG vs. AA + AG, OR = 1.82, CI = 1.26–2.63), homozygous (GG vs. AA, OR = 1.92, CI = 1.32–2.77), heterozygous model (AG vs. AA, OR = 1.31, CI = 0.89–1.93) and co-dominant model (AG vs. AA + GG; OR = 1.27, CI = 0.88–1.85). Significant heterogeneity characterized the allele, as well as the dominant model (I2 = 84.1%, I2 = 80.0%). Egger’s tests (p < 0.05) and funnel plots did not identify publication bias. Conclusions: The present meta-analysis indicates that the G allele and GG genotype might affect prostate cancer susceptibility in European Caucasians; however, the validity and reliability of the results need to be examined in future research. Full article

Background: Prostate cancer remains a leading cause of mortality in men, making early, accurate detection crucial for early intervention. While radiologists utilize the Prostate Imaging Reporting and Data System (PI-RADS) for the interpretation of MRI imaging, variations in expertise and inter-reader differences can affect diagnostic accuracy. Artificial intelligence (AI) has emerged as a promising tool for automated detection, with the potential to achieve diagnostic performance comparable to radiologists in identifying clinically significant prostate cancer (csPCa), streamline workflows, and reduce unnecessary biopsies. However, its real-world performance compared to expert radiologists remains a topic of ongoing debate. Purpose: This meta-analysis aims to evaluate whether AI can achieve diagnostic performance that is comparable to that of radiologists in MRI-based prostate cancer detection by comparing diagnostic accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC). Methods: Following PRISMA 2020 guidelines, we searched PubMed for studies directly comparing AI and radiologists in MRI-based detection of csPCa. Ten studies (20,423 patients) were included, and quality was assessed using QUADAS-2. Analyses included forest plots for diagnostic sensitivity and specificity, funnel plots of AUROC to assess publication bias, and paired AUROC difference plots to directly compare diagnostic accuracy. Results: Pooled sensitivity was 0.87 (95% CI: 0.81–0.94) for AI and 0.85 (95% CI: 0.77–0.94) for radiologists; pooled specificity was 0.61 (95% CI: 0.51–0.72) for AI and 0.63 (95% CI: 0.54–0.71) for radiologists. Funnel plots of AUROC against standard error showed no strong visual evidence of publication bias. Paired AUROC difference analysis demonstrated no significant performance difference between AI and radiologists, with a pooled difference of 0.018 (p = 0.378). Conclusions: AI systems demonstrated diagnostic performance comparable to radiologists for MRI-based detection of csPCa, with a nonsignificant and slightly higher pooled sensitivity and AUROC. Moreover, AI has the potential to improve workflow speed, uniformity across expertise levels, and hybrid AI-radiologist approaches to reduce unnecessary biopsies. Large-scale, prospective trials with standardized protocols are needed to assess AI’s effectiveness across diverse clinical settings. Full article