Background: Systemic inflammation plays a pivotal role in heart failure (HF) progression, yet no meta-analysis has synthesized prospective cohort data on interleukin-6 (IL-6), high-sensitivity C-reactive protein (hs-CRP), and neutrophil-to-lymphocyte ratio (NLR) as prognostic biomarkers. Objectives: To quantify the independent prognostic value of IL-6, hs-CRP, and NLR for mortality and HF-related outcomes across HF phenotypes. Methods: Following PRISMA and MOOSE guidelines, we searched PubMed, Embase, Scopus, Web of Science, and CENTRAL from January 2014 to October 2025 for prospective cohorts reporting adjusted hazard ratios (HRs). Random-effects meta-analysis pooled HRs; heterogeneity was assessed via I² statistic, with subgroup and sensitivity analyses for robustness. Quality was evaluated using Newcastle–Ottawa Scale (NOS) and GRADE. Results: Thirteen cohorts (n ≈ 19,000) were included. Elevated IL-6 (five studies) was associated with increased all-cause mortality and composite outcomes (low-moderate heterogeneity, I² < 35%). hs-CRP (five studies) showed similar prognostic strength, with trajectories amplifying risk. NLR (three studies) independently predicted adverse events with negligible heterogeneity. Associations persisted across HFrEF and HFpEF, acute/chronic settings, and geographic regions, independent of natriuretic peptides and comorbidities (NOS median 8/9; GRADE moderate-to-high). Conclusions: IL-6, hs-CRP, and NLR are robust, independent prognostic biomarkers in HF, supporting their integration into clinical risk stratification and inflammation-targeted therapies. PROSPERO: CRD420251207035.

With the onset of the COVID-19 pandemic, enormous efforts have been made to understand the genus SARS-CoV-2. Due to the high rate of global transmission, mutations in the viral genome were inevitable. A full understanding of the viral genome and its possible changes represents one of the crucial aspects of pandemic management. Structural protein S plays an important role in the pathogenicity of SARS-CoV-2, mutations occurring at this level leading to viral forms with increased affinity for ACE2 receptors, higher transmissibility and infectivity, resistance to neutralizing antibodies and immune escape, increasing the risk of infection and disease severity. Thus, five variants of concern are currently being discussed, Alpha, Beta, Gamma, Delta and Omicron. In the present review, a comprehensive summary of the following critical aspects regarding SARS-CoV-2 has been made: (i) the genomic characteristics of SARS-CoV-2; (ii) the pathological mechanism of transmission, penetration into the cell and action on specific receptors; (iii) mutations in the SARS-CoV-2 genome; and (iv) possible implications of mutations in diagnosis, treatment, and vaccination.

The first step in anthropological study is the positive identification of human remains, which can be a challenging undertaking when bones are broken. When bone pieces from different species are mixed together, it can be crucial to distinguish between them in forensic and archaeological contexts. For years, anthropology and archaeology have employed the histomorphological analysis of bones to evaluate species-specific variations. Based on variations in the dimensions and configuration of Haversian systems between the two groups, these techniques have been devised to distinguish between non-human and human bones. All of those techniques concentrate on a very particular kind of bone, zone, and segment. Histomorphometric techniques make the assumption that there are size, form, and quantity variations between non-humans and humans. The structural components of Haversian bones are significant enough to use discriminant function analysis to separate one from the other. This review proposes a comprehensive literature analysis of the various strategies or techniques available for distinguishing human from non-human bones to demonstrate that histomorphological analysis is the most effective method to be used in the case of inadequate or compromised samples.

This study aimed to evaluate the DSP method’s applicability to Romania’s contemporary population and to assess the accuracy and reliability of variables derived from CT images. A total of 80 pelvic CT scans were analyzed. Participants ranged from 22 to 93 years, with a mean age of 59.51 ± 22.7 years. All variables measured from the CT scans were analyzed using DSP software. The study found that sex estimation was possible in 71.25% of cases overall, with varying rates between males (57.50%) and females (85%). Despite encountering undetermined specimens comprising 42.5% males and 15% females, only one misclassification occurred. Regarding accuracy, the overall rate remained notably high at 98.24%. All female specimens that could be estimated were correctly classified (100% accuracy), while for males, the accuracy rate was 95.65%. Undetermined cases were noted to potentially impact the accuracy of sex classification, underscoring the critical role of precision in forensic contexts. In conclusion, the study highlights the importance of accuracy in forensic sex estimation. It emphasizes the confidence with which DSP software can be utilized, if not the only method, at least as a preliminary or adjuvantly accurate technique for sex estimation in forensic anthropology.

Background: SGLT2 inhibitors are key therapies in heart failure (HF), but their combined multidomain effects have not been analyzed together. Methods: We conducted a PROSPERO-registered (CRD420251235850) systematic review and meta-analysis of all randomized controlled trials (RCTs) comparing SGLT2i (dapagliflozin, empagliflozin, canagliflozin, sotagliflozin) with placebo in adults with HF, regardless of ejection fraction or diabetes status. We searched PubMed/MEDLINE, Embase, Cochrane CENTRAL, and Web of Science through 1 February 2025. Outcomes were grouped into four domains: (1) clinical events, (2) symptoms/health status (Kansas City Cardiomyopathy Questionnaire, KCCQ), (3) functional capacity (6 min walk distance, peak VO₂), and (4) cardiac remodeling/energetics (cardiac MRI, 31P-MRS). We used random-effects models with Hartung–Knapp adjustment and assessed heterogeneity by I² and prediction intervals. Results: Eleven RCTs with 23,812 patients (HFrEF, HFmrEF, HFpEF, and acute or recently decompensated HF) were included. SGLT2i lowered the risk of cardiovascular death or first HF hospitalization by 23% (HR 0.77, 95% CI 0.72–0.82; p < 0.0001; I² = 28%; prediction interval 0.68–0.87), with similar effects across ejection fraction, diabetes status, and presentation type. All-cause and cardiovascular mortality dropped by 12% (HR 0.88, 95% CI 0.81–0.96) and 14% (HR 0.86, 95% CI 0.78–0.95), respectively. SGLT2i improved KCCQ—Clinical Summary Score by 4.6 points (95% CI 3.4–5.8; p < 0.0001) and increased the odds of a ≥5-point improvement (OR 1.49, 95% CI 1.32–1.68; NNT = 12). Six-minute walk distance increased by 21.8 m (95% CI 9.4–34.2; p = 0.001), and mechanistic trials showed significant reverse remodeling (ΔLVEDV −19.8 mL, ΔLVEF +6.1%; both p < 0.001). No improvement was observed in myocardial PCr/ATP ratio. Safety was favorable, with no excess ketoacidosis or severe hypoglycemia. Conclusions: This multidomain synthesis demonstrates that SGLT2 inhibitors provide consistent, robust reductions in mortality and hospitalizations, while also delivering early, clinically meaningful improvements across multiple patient-centered domains. These results establish SGLT2i as a foundational component of contemporary HF management.

Background: Bloodstream infections (BSIs) complicate COVID-19 inpatients, increasing morbidity, mortality, and healthcare burden. This systematic review and meta-analysis evaluated prevalence, antimicrobial resistance (AMR), risk factors, and outcomes of BSIs in RT-PCR-confirmed COVID-19 cases. Methods: We searched PubMed, Google Scholar, ScienceDirect, and MDPI journals (January 2020–August 2025) following PRISMA 2020 guidelines. Twenty-two observational studies (~123,500 patients, ~602,000 blood cultures) were included: 10 prospective and 12 retrospective. Random-effects models estimated pooled prevalence, odds ratios (ORs), and mean differences, with subgroup analyses (ICU, non-ICU, pediatric) and meta-regression.Results: Pooled BSI prevalence was 8.2% (95% CI: 5.7–11.0; I² = 50%). Subgroup prevalence was higher in ICU (12.5%) than non-ICU (5.2%) populations. Pediatric cohorts (n = 3) showed a prevalence of 10.8%. Gram-negative pathogens predominated (61%), particularly Klebsiella pneumoniae (26%) and Acinetobacter baumannii (21%). AMR rates were 36% for MRSA and 31% for ESBL-producing Enterobacterales. Risk factors included mechanical ventilation (OR: 2.6), immunosuppression (OR: 2.3), and corticosteroid use (OR: 2.4). BSIs were associated with increased mortality (OR: 2.6), prolonged hospitalization (+6.8 days), and higher ICU admission (OR: 3.1).Conclusions: BSIs, largely driven by multidrug-resistant pathogens, substantially worsen COVID-19 outcomes. Variability in diagnostic criteria (CDC vs. ECDC) and reliance on retrospective designs are limitations, though moderate heterogeneity (I² = 50%) enhances generalizability across diverse populations. Strengthened infection prevention and antimicrobial stewardship are urgently required.