Search Results (3,256)

Background: Environmental enrichment is a promising strategy to improve the welfare of dairy goats and sheep. However, studies in this field remain scattered, and its effects on productivity are unclear. Objectives: To evaluate the effects of environmental enrichment on behavioral, physiological, and productive parameters in dairy goats and sheep. Data sources: Scopus and Web of Science were searched for studies published from 2010 to 2025. Study eligibility criteria: Experimental or observational peer-reviewed studies comparing enriched vs. non-enriched housing in dairy goats or sheep, reporting on welfare or productivity outcomes. Methods: This review followed PRISMA 2020 guidelines and the PICO framework. Two independent reviewers screened and extracted data. Risk of bias was assessed with the SYRCLE tool. Results: Thirteen studies were included, mostly with goats. Physical, sensory, and social enrichments showed benefits for behavior (e.g., activity, fewer stereotypies) and stress physiology. However, results varied by social rank, enrichment type, and physiological stage. Only three studies assessed productive parameters (weight gain in kids/lambs); none evaluated milk yield or quality. Limitations: Most studies had small samples and short durations. No meta-analysis was conducted due to heterogeneity. Conclusions: Environmental enrichment can benefit the welfare of dairy goats and sheep. However, evidence on productivity is scarce. Long-term studies are needed to evaluate its cost-effectiveness and potential impacts on milk yield and reproductive performance. Full article

In the digital era, understanding the intention to use generative AI is critical, as it enhances productivity, transforms workflows, and enables humans to focus on higher-value tasks. Drawing upon the unified theory of acceptance and use of technology (UTAUT) and the technology threat avoidance theory (TTAT), this research integrates perceived AI literacy into the AI acceptance–avoidance framework as a central variable. This study gathered 583 valid survey responses from China and validated its model using a dual-phase, combined method that integrates structural equation modeling and artificial neural networks. Research findings indicate that the model explains 51.6% of the variance in generative AI usage intention. Except for social influence, all variables within the extended framework significantly impact the usage intention, with perceived AI literacy being the strongest predictor (β = 0.33, p < 0.001). Additionally, perceived AI literacy mitigates the adverse effect of perceived threats on the intention to use AI. Practical implications suggest that enterprises adopt a tiered strategy, as follows: maximize perceived benefits by integrating AI skills into reward systems and providing task-automation training; minimize perceived costs through dedicated technical support and transparent risk mitigation plans; and cultivate AI literacy via progressive learning paths, advancing from data analysis to innovation. Full article

Construction and demolition waste (C&D waste) contains various types of substances, which require different processing methods to maximize benefits and minimize harm to realize the goal of the circular economy. Therefore, it is urgent to promote the on-site sorting of C&D waste and explore the determinants of managers’ waste sorting intention. Based on a comprehensive literature review of C&D waste management, seven determinants are identified to explore how antecedent factors influence waste sorting intention by symmetric and asymmetric techniques. Firstly, the partial least squares structural equation modeling (PLS-SEM) was adopted to analyze the data collected from 489 managers to assess the net impact of each determinant on their intentions. Then, the fuzzy-set qualitative comparative analysis (fsQCA) provided another perspective by determining the configurations of the causal conditions that lead to higher or lower levels of intention. The PLS-SEM results reveal that all determinants show a significant positive relationship with the intention except for the perceived risks, which are negatively correlated with managers’ attitudes and intentions regarding C&D waste sorting. Moreover, top management support and subjective norms from other project participants and the public exhibit a huge impact, while the influence of perceived behavioral control (PBC) and policies is moderate. Meanwhile, fsQCA provides a complementary analysis of the complex causality that PLS-SEM fails to capture. That is, fsQCA identified six and five configurations resulting in high and low levels of intention to sort the C&D waste, respectively, and highlighted the crucial role of core conditions. The results provide theoretical and practical insights regarding proper C&D waste management and enhancing sustainable development. Full article

We introduce a novel portfolio optimization framework—Distributionally Robust Multivariate Stochastic Cone Order (DR-MSCO)—which integrates partial orders on random vectors with Wasserstein-metric ambiguity sets and adaptive cone structures to model multivariate investor preferences under distributional uncertainty. Grounded in measure theory and convex analysis, DR-MSCO employs data-driven cone selection calibrated to market regimes, along with coherent tail-risk operators that generalize Conditional Value-at-Risk to the multivariate setting. We derive a tractable second-order cone programming reformulation and demonstrate statistical consistency under empirical ambiguity sets. Empirically, we apply DR-MSCO to 23 Borsa Istanbul equities from 2021–2024, using a rolling estimation window and realistic transaction costs. Compared to classical mean–variance and standard distributionally robust benchmarks, DR-MSCO achieves higher overall and crisis-period Sharpe ratios (2.18 vs. 2.09 full sample; 0.95 vs. 0.69 during crises), reduces maximum drawdown by 10%, and yields endogenous diversification without exogenous constraints. Our results underscore the practical benefits of combining multivariate preference modeling with distributional robustness, offering institutional investors a tractable tool for resilient portfolio construction in volatile emerging markets. Full article

Background: The importance of lymph node dissection (LND) at the time of radical cystectomy for urothelial carcinoma (UC) is widely accepted despite known risks. The therapeutic benefits of LND for variant subtype bladder cancer (VBC), a heterogenous and distinct set of diseases, are not well established. We aim to characterize the impact of LND on overall survival across VBC subtypes. Methods: The National Cancer Database was queried for all cases of variant subtype bladder cancer managed with radical cystectomy between 2004 and 2020, using the International Classification of Disease-O-3 morphological codes. The cases were stratified by receipt of individual variant subtypes. The primary outcome was overall survival associated with pathologic nodal status and receipt of nodal dissection. A Kaplan–Meier analysis and Cox proportional hazards analysis were used for survival analyses. Results: A total of 30,911 patients with VBC that were managed with radical cystectomy were included in our analysis. The pNx rates ranged from 33.1% in the micropapillary subtype, 42.2% in the sarcomatoid subtype, 68.4% in the squamous subtype, 48.9% in the adenocarcinoma subtype, and 56.2% in the neuroendocrine subtype. The median OS was higher in those that received a nodal dissection across subtypes but was statistically significant only for the squamous (71.0 [68.0 vs. 74.0] vs. 37.2 [33.6 vs. 40.9] months p < 0.001) and adenocarcinoma (45.9 [32.9 vs. 59.0] vs. 37.9 [28.6 vs. 47.1] months p = 0.037) subtypes. Using Cox proportional hazards regression, LN dissection was associated with improved OS for the squamous (0.50 (0.44–0.58) p < 0.001) and adenocarcinoma (0.65 [0.45–0.93) p = 0.030) subtypes. Conclusions: The role of LND across VBC subtypes is not clearly defined and warrants further investigation to develop a more risk-adaptive approach. We demonstrate heterogeneity with respect to the OS benefit associated with LND at the time of surgery. Among certain VBC subtypes, LND may not offer a significant therapeutic benefit, while LND in squamous and adenocarcinoma VBCs is correlated with improved survival. Full article

Sarcopenia is a progressive age-related musculoskeletal disorder characterized by loss of muscle mass, strength, and physical performance, contributing to functional decline and increased risk of disability. Emerging evidence suggests that vitamin D (Vit D) plays a pivotal role in skeletal muscle physiology beyond its classical functions in bone metabolism. This review aims to critically analyze the relationship between serum Vit D levels and sarcopenia in older adults, focusing on pathophysiological mechanisms, diagnostic criteria, clinical evidence, and preventive strategies. An integrative narrative review of observational studies, randomized controlled trials, and meta-analyses published in the last decade was conducted. The analysis incorporated international diagnostic criteria for sarcopenia (EWGSOP2, AWGS, FNIH, IWGS), current guidelines for Vit D sufficiency, and molecular mechanisms related to Vit D receptor (VDR) signaling in muscle tissue. Low serum 25-hydroxyvitamin D levels are consistently associated with decreased muscle strength, reduced physical performance, and increased prevalence of sarcopenia. Although interventional trials using Vit D supplementation report variable results, benefits are more evident in individuals with baseline deficiency and when combined with protein intake and resistance training. Mechanistically, Vit D influences muscle health via genomic and non-genomic pathways, regulating calcium homeostasis, mitochondrial function, oxidative stress, and inflammatory signaling. Vit D deficiency represents a modifiable risk factor for sarcopenia and functional impairment in older adults. While current evidence supports its role in muscular health, future high-quality trials are needed to establish optimal serum thresholds and dosing strategies for prevention and treatment. An individualized, multimodal approach involving supplementation, exercise, and nutritional optimization appears most promising. Full article

Purpose: Predicting colorectal cancer liver metastasis (CRLM) is essential for prognostic assessment. This study aims to develop and validate an interpretable multimodal machine learning framework based on multiparametric MRI for predicting CRLM, and to enhance the clinical interpretability of the model through SHapley Additive exPlanations (SHAP) analysis and deep learning visualization. Methods: This multicenter retrospective study included 463 patients with pathologically confirmed colorectal cancer from two institutions, divided into training (n = 256), internal testing (n = 111), and external validation (n = 96) sets. Radiomics features were extracted from manually segmented regions on axial T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI). Deep learning features were obtained from a pretrained ResNet101 network using the same MRI inputs. A least absolute shrinkage and selection operator (LASSO) logistic regression classifier was developed for clinical, radiomics, deep learning, and combined models. Model performance was evaluated by AUC, sensitivity, specificity, and F1-score. SHAP was used to assess feature contributions, and Grad-CAM was applied to visualize deep feature attention. Results: The combined model integrating features across the three modalities achieved the highest performance across all datasets, with AUCs of 0.889 (training), 0.838 (internal test), and 0.822 (external validation), outperforming single-modality models. Decision curve analysis (DCA) revealed enhanced clinical net benefit from the integrated model, while calibration curves confirmed its good predictive consistency. SHAP analysis revealed that radiomic features related to T2WI texture (e.g., LargeDependenceLowGrayLevelEmphasis) and clinical biomarkers (e.g., CA19-9) were among the most predictive for CRLM. Grad-CAM visualizations confirmed that the deep learning model focused on tumor regions consistent with radiological interpretation. Conclusions: This study presents a robust and interpretable multiparametric MRI-based model for noninvasively predicting liver metastasis in colorectal cancer patients. By integrating handcrafted radiomics and deep learning features, and enhancing transparency through SHAP and Grad-CAM, the model provides both high predictive performance and clinically meaningful explanations. These findings highlight its potential value as a decision-support tool for individualized risk assessment and treatment planning in the management of colorectal cancer. Full article

Background/Objectives: Acne vulgaris is a widespread, chronic inflammatory skin condition that significantly impacts patients’ quality of life. Although oral isotretinoin remains the most effective treatment, recent evidence suggests that H₁-antihistamines such as desloratadine and levocetirizine may enhance acne therapy. This study assesses whether combining H₁-antihistamines to isotretinoin enhances treatment efficacy in acne vulgaris compared to isotretinoin alone. Methods: Our analysis included 10 randomized controlled trials involving 675 patients collectively, predominantly from Asia and the Middle East. Data were extracted by two independent reviewers, with discrepancies resolved by a third. Risk of bias was assessed using the Cochrane RoB 2 tool. Analyses were performed using RevMan 5.4 with random-effects models, and heterogeneity was evaluated via I² and Q tests. Sensitivity analyses were conducted to assess result robustness. Results: Combination therapy with isotretinoin and desloratadine showed a significantly greater reduction in GAGS (Global Acne Grading Scale) score by week 12 (p < 0.00001; MD 2.68, 95% CI 1.60 to 3.75; I² = 0%) while earlier timepoints showed non-significant or borderline results. For inflammatory lesions, significant improvements with desloratadine emerged at weeks 4, 8, and 12 after excluding an influential outlier, with low heterogeneity and consistent direction of effect. Non-inflammatory lesions did not differ significantly at weeks 4 or 8. At week 12, a significant reduction was seen in the desloratadine subgroup (OR 2.61, p = 0.003, I² = 11%) and in overall pooled analysis (OR 2.77, p < 0.0001, I² = 2%). Among side effects, acne flare-ups, pruritus, and cheilitis were significantly reduced in the desloratadine group, as well as in pooled analysis. Xerosis did not consistently differ between groups. Overall, desloratadine improved tolerability and reduced mucocutaneous adverse events more than levocetirizine. Conclusions: Current evidence suggests that combining oral antihistamines with isotretinoin may offer therapeutic benefits in acne management, particularly in enhancing tolerability and potentially improving clinical outcomes, as reflected by significant reductions in GAGS scores and mucocutaneous adverse effects such as cheilitis, pruritus, and acne flare-ups. Full article

Background and Objectives: Patients with hip fractures have a high mortality rate, highlighting the need for a reliable prognostic tool. Although the prognostic nutritional index (PNI) is a well-established predictor in patients with cancer, its utility has not been thoroughly investigated in patients with hip fractures. Therefore, this study aims to evaluate the association between PNI and mortality in patients undergoing hip fracture surgery. Materials and Methods: A retrospective review was conducted on all patients aged ≥65 years who underwent surgery for hip fracture between January 2014 and February 2018. Quartile stratification was chosen because no universally accepted clinical cut-off exists for PNI; this approach enables comparison of equally sized groups and exploration of potential non-linear risk patterns. The primary endpoints were 1-year and overall mortality in older adults undergoing hip fracture surgery. Multivariable Cox proportional-hazards models adjusted for age, sex, ASA class and comorbidities. Results: A total of 815 patients were analyzed. One-year and overall mortality rates were highest in the Q1 group (26.6%, 14.2%, 6.9%, 6.4% [p < 0.001] and 56.7%, 36.3%, 27.0%, 15.2% [p < 0.001], respectively). In Cox regression analysis, a lower preoperative PNI was significantly associated with an increased risk of overall mortality (Q1: HR 3.25, 95% confidence interval [CI] 2.11–5.01, p < 0.001; Q2: HR 1.85, 95% CI 1.19–2.86, p = 0.006; Q3: HR 1.52, 95% CI 0.97–2.38, p = 0.065; Q4 as reference), indicating a stepwise, dose–response increase in mortality risk as PNI decreases. Conclusions: The findings demonstrate that a lower preoperative PNI is significantly associated with higher 1-year and overall mortality in older adults undergoing hip fracture surgery. Although further prospective validation is needed, preoperative PNI may help predict mortality in frail patients undergoing hip fracture surgery and identify those who could benefit from nutritional assessment and optimization before surgery. Full article

Background/Objectives: Infants with high-output enterostomies often require prolonged parenteral nutrition (PN), increasing risks of infections, liver dysfunction, and impaired growth. Mucous fistula refeeding (MFR) is proposed to enhance intestinal adaptation, weight gain, and distal bowel maturation. This systematic review and meta-analysis assessed its effectiveness, safety, and technical aspects. Methods: Following PRISMA guidelines, studies reporting MFR-related outcomes were included without data or language restrictions. Data sources included PubMed, EMBASE, CINAHL, Scopus, Web of Science, Cochrane Library, and UpToDate. Bias risk was assessed using the Joanna Briggs Institute Critical Appraisal Checklist. Meta-analysis employed random- and fixed-effects models, with outcomes reported as odds ratios (ORs) and 95% confidence interval (CI). Primary outcomes assessed were weight gain, PN duration, and complications and statistical comparisons were made between MFR and non-MFR groups. Results: Seventeen studies involving 631 infants were included; 482 received MFR and 149 did not. MFR started at 31 postoperative days and lasted for 50 days on average, using varied reinfusion methods, catheter types, and fixation strategies. MFR significantly improved weight gain (4.7 vs. 24.2 g/day, p < 0.05) and reduced PN duration (60.3 vs. 95 days, p < 0.05). Hospital and NICU stays were also shorter (160 vs. 263 days, p < 0.05; 122 vs. 200 days, p < 0.05). Cholestasis risk was lower (OR 0.151, 95% CI 0.071–0.319, p < 0.0001), while effects on bilirubin levels were inconsistent. Complications included sepsis (3.5%), intestinal perforation (0.83%), hemorrhage (0.62%), with one MFR-related death (0.22%). Conclusions: Despite MFR benefits neonatal care, its practices remain heterogeneous. Standardized protocols are required to ensure MFR safety and efficacy. Full article

Background: Acute myeloid leukemia (AML) is a common and aggressive adults hematological malignancies. This study explored megakaryocyte–erythroid progenitors (MEPs) signature genes and constructed a prognostic model. Methods: Uniform manifold approximation and projection (UMAP) identified distinct cell types, with differential analysis between AML-MEP and normal MEP groups. Univariate and the least absolute shrinkage and selection operator (LASSO) Cox regression selected biomarkers to build a risk model and nomogram for 1-, 3-, and 5-year survival prediction. Results: Ten differentially expressed genes (DEGs) related to overall survival (OS), six (AHSP, MYB, VCL, PIM1, CDK6, as well as SNHG3) were retained post-LASSO. The model exhibited excellent efficiency (the area under the curve values: 0.788, 0.77, and 0.847). Pseudotime analysis of UMAP-defined subpopulations revealed that MYB and CDK6 exert stage-specific regulatory effects during MEP differentiation, with MYB involved in early commitment and CDK6 in terminal maturation. Finally, although VCL, PIM1, CDK6, and SNHG3 showed significant associations with AML survival and prognosis, they failed to exhibit pathological differential expression in quantitative real-time polymerase chain reaction (qRT-PCR) experimental validations. In contrast, the downregulation of AHSP and upregulation of MYB in AML samples were consistently validated by both qRT-PCR and Western blotting, showing the consistency between the transcriptional level changes and protein expression of these two genes (p < 0.05). Conclusions: In summary, the integration of single-cell/transcriptome analysis with targeted expression validation using clinical samples reveals that the combined AHSP-MYB signature effectively identifies high-risk MEP-AML patients, who may benefit from early intensive therapy or targeted interventions. Full article

Background: BDE-47, a pervasive environmental pollutant detected in >90% of human serum samples, is increasingly linked to metabolic disorders. This study investigates the specific impact of BDE-47 exposure on the gut microbiota in prediabetic mice and evaluates the efficacy of therapeutic interventions in mitigating these effects. Objectives: To determine whether BDE-47 exposure induces diabetogenic dysbiosis in prediabetic mice and to assess whether dietary interventions, such as grape exosomes and an antioxidant cocktail, can restore a healthy microbiota composition and mitigate diabetes risk. Methods: In this study, a prediabetic mouse model was established in 54 male SPF-grade C57BL/6J mice through a combination of high-sugar and high-fat diet feeding with streptozotocin injection. Oral glucose tolerance tests (OGTT) were conducted on day 7 and day 21 post-modeling to assess the establishment of the model. The criteria for successful model induction were defined as fasting blood glucose levels below 7.8 mmol/L and 2 h postprandial glucose levels between 7.8 and 11.1 mmol/L. Following confirmation of model success, a 3 × 3 factorial design was applied to allocate the experimental animals into groups based on two independent factors: BDE-47 exposure and exosome intervention. The BDE-47 exposure factor consisted of three dose levels—none, high-dose, and medium-dose—while the exosome intervention factor included three modalities—none, Antioxidant Nutrients Intervention, and Grape Exosomes Intervention. Fresh fecal samples were collected from mice two days prior to sacrifice. Cecal contents and segments of the small intestine were collected and transferred into 1.5 mL cryotubes. All sequences were clustered into operational taxonomic units (OTUs) based on defined similarity thresholds. To compare means across multiple groups, a two-way analysis of variance (ANOVA) was employed. The significance level was predefined at α = 0.05, and p-values < 0.05 were considered statistically significant. Bar charts and line graphs were generated using GraphPad Prism version 9.0 software, while statistical analyses were performed using SPSS version 20.0 software. Results: The results of 16S rDNA sequencing analysis of the microbiome showed that there was no difference in the α diversity of the intestinal microbiota in each group of mice (p > 0.05), but there was a difference in the Beta diversity (p < 0.05). At the gate level, the abundances of Proteobacteria, Campylobacterota, Desulfobacterota, and Fusobacteriota in the medium-dose BDE-7 group were higher than those in the model control group (p < 0.05). The abundance of Patellar bacteria was lower than that of the model control group (p < 0.05). The abundances of Proteobacteria and Campylobacterota in the high-dose BDE-7 group were higher than those in the model control group (p < 0.05). The abundance of Planctomycetota and Patescibacteria was lower than that of the model control group (p < 0.05), while the abundance of Campylobacterota in the grape exosome group was higher than that of the model control group (p < 0.05). The abundance of Patescibacteria was lower than that of the model control group (p < 0.05), while the abundance of Firmicutes and Fusobacteriota in the antioxidant nutrient group was higher than that of the model control group (p < 0.05). However, the abundance of Verrucomicrobiota and Patescibacteria was lower than that of the model control group (p < 0.05). At the genus level, the abundances of Bacteroides and unclassified Lachnospiraceae in the high-dose BDE-7 group were higher than those in the model control group (p < 0.05). The abundance of Lachnospiraceae NK4A136_group and Lactobacillus was lower than that of the model control group (p < 0.05). The abundance of Veillonella and Helicobacter in the medium-dose BDE-7 group was higher than that in the model control group (p < 0.05), while the abundance of Lactobacillus was lower (p < 0.05). The abundance of genera such as Lentilactobacillus and Faecalibacterium in the grape exosome group was higher than that in the model control group (p < 0.05). The abundance of Alloprevotella and Bacteroides was lower than that of the model control group (p < 0.05). In the antioxidant nutrient group, the abundance of Lachnospiraceae and Hydrogenophaga was higher than that in the model control group (p < 0.05). However, the abundance of Akkermansia and Coriobacteriaceae UCG-002 was significantly lower than that of the model control group (p < 0.05). Conclusions: BDE-47 induces diabetogenic dysbiosis in prediabetic mice, which is reversible by dietary interventions. These findings suggest that microbiota-targeted strategies may effectively mitigate the diabetes risk associated with environmental pollutant exposure. Future studies should further explore the mechanisms underlying these microbiota changes and the long-term health benefits of such interventions. Full article

Rapid urbanization and escalating disaster risks necessitate resilient urban governance systems. Smart city initiatives that leverage digital technologies—such as the internet of things (IoT), big data analytics, and artificial intelligence (AI)—demonstrate transformative potential in enhancing emergency management capabilities. However, empirical evidence regarding their causal impact and underlying mechanisms remains limited, particularly in developing economies. Drawing on panel data from 275 Chinese prefecture-level cities over the period 2006–2021 and using China’s smart city pilot policy as a quasi-natural experiment, this study applies a multi-period difference-in-differences (DID) approach to rigorously assess the effects of smart city construction on emergency management capabilities. Results reveal that smart city construction produced a statistically significant improvement in emergency management capabilities, which remained robust after conducting multiple sensitivity checks and controlling for potential confounding policies. The benefits exhibit notable heterogeneity: emergency management capability improvements are most pronounced in central China and in cities at the extremes of population size—megacities (>10 million residents) and small cities (<1 million residents)—while effects remain marginal in medium-sized and eastern cities. Crucially, mechanism analysis reveals that digital technology application fully mediates 86.7% of the total effect, whereas factor allocation efficiency exerts only a direct, non-mediating influence. These findings suggest that smart cities primarily enhance emergency management capabilities through digital enablers, with effectiveness contingent upon regional infrastructure development and urban scale. Policy priorities should therefore emphasize investments in digital infrastructure, interagency data integration, and targeted capacity-building strategies tailored to central and western regions as well as smaller cities. Full article

Background and Objectives: Cancer patients are particularly susceptible to infections caused by multidrug-resistant Gram-negative bacteria (MDR GNB) due to chemotherapy- or radiation therapy-induced immunosuppression. Colistin is often prescribed as a last-resort agent for MDR GNB infection, but its clinical benefit in oncology patients remains unclear. This study aims to evaluate the mortality risk associated with colistin versus non-colistin regimens in cancer patient with MDR GNB infections, stratified by resistance profiles, infection sites, and concomitant medication use. Materials and Methods: A retrospective cohort study was conducted in adult cancer patients with MDR GNB infections that are resistant to at least three antibiotic classes and identified from at least two anatomical sites at a tertiary care hospital in Korea. Propensity score-matched in a 1:3 ratio either to the colistin group or non-colistin group and multivariate Cox hazard regression analyses were used to evaluate mortality in cancer patients with MDR GNB infections, primarily Acinetobacter baumannii, Klebsiella pneumoniae, and Pseudomonas aeruginosa. Results: A total of 85 patients (29 patients in the colistin and 56 patients in the non-colistin group) were included in the analysis. Overall, colistin use did not show a statistically significant mortality benefit compared to non-colistin regimens (hazard ratio (HR) 0.93, 95% CI 0.47–1.87). However, the subgroup analysis revealed that colistin had a potential association with significantly lower mortality in pneumonia patients with aminoglycoside-resistant infections (HR 0.04, 95% CI 0.002–0.69). Concomitant use of antipsychotics and benzodiazepines in selected resistance profiles also correlated with improved outcomes. In contrast, a potential association was found between concomitant macrolide use and increased mortality in patients with fluoroquinolone- or penicillin-resistant profiles. Conclusions: Colistin may offer survival benefits in selected high-risk cancer patients with MDR GNB pneumonia. Treatment outcomes are influenced by resistance profiles, infection sites, and concomitant medications, indicating the significant importance of individualized antimicrobial therapy and antimicrobial stewardship in oncology patients. Full article

Background/Objectives: Sodium-glucose cotransporter-2 inhibitors (SGLT2i) have revolutionized heart failure (HF) therapies and are an essential component of guideline-directed medical therapy (GDMT); however, their significance in arrhythmia prevention is still uncertain. This meta-analysis evaluates the benefits of SGLT2i on arrhythmias in HF. Methods: A comprehensive examination was performed with PubMed, ScienceDirect, PLOS One, Cochrane, Google Scholar, and ClinicalTrials.gov from January 2014 to March 2025, complying with PRISMA guidelines. Randomized controlled trials (RCTs) comparing SGLT2i with placebo were incorporated. Primary results included ventricular arrhythmias (VA), sudden cardiac death (SCD), atrial arrhythmias, and conduction disorders. Subgroup analyses investigated the effects on arrhythmias in HF with reduced ejection fraction (HFrEF) and preserved ejection fraction (HFpEF). Results: A total of 11 RCTs involving 23,701 patients, 11,848 on SGLT2i (mean age: 68.26 ± 10 yrs, 53.5% males) and 11,853 on placebo (mean age: 67.91 ± 10 yrs, 53% males), were analyzed with a mean follow-up of 2.71 yrs. No significant differences were reported between SGLT2i and placebo for VA [relative risk (RR): 1.02, 95% confidence interval (CI): 0.83–1.25], I² =0%), atrial arrhythmias (RR: 0.92 [CI: 0.67–1.27], I² = 65.3%), or conduction disorders (RR:1.22 [CI: 0.86–1.73], I² = 10.4%). Notably, significant reductions in risk of SCD (RR: 0.68 [CI: 0.49–0.93], I² = 0%) and in the risk of atrial arrhythmias in HFrEF (RR: 0.66 [CI: 0.49–0.89], I² = 10.3%) were witnessed, although no such reduction was seen in HFpEF (RR: 1.14 [CI: 0.94–1.40], I² = 33.8%). Conclusions: SGLT2i do not reduce overall arrhythmia or conduction disorder risk in HF but significantly reduce the risk of SCD and atrial arrhythmias in HFrEF patients. These results highlight potential arrhythmia prevention benefits in HFrEF, warranting further targeted studies. Full article