Search Results (8,123)

Infectious complications remain a principal determinant of late morbidity and mortality following major thermal injury, reflecting a convergence of barrier disruption, microbial adaptation, and host immune dysfunction. The post-burn environment creates a uniquely permissive niche for pathogen persistence, characterized by altered tissue perfusion, biofilm formation, and dynamic shifts in microbial ecology toward multidrug-resistant organisms. Concurrently, profound and evolving changes in host immunity and metabolism reshape both susceptibility to infection and response to therapy. This review integrates current evidence across pathophysiology, microbiology, diagnostics, and treatment, with a focus on challenges that limit effective infection control in burn patients. Particular attention is given to diagnostic uncertainty arising from overlap between sterile inflammation and true infection, the clinical implications of biofilm-associated tolerance, and the impact of burn-specific pharmacokinetic variability on antimicrobial efficacy. We further examine emerging diagnostic and therapeutic innovations, including host-response profiling, rapid molecular detection platforms, and next-generation anti-infective strategies targeting microbial virulence, biofilm structure, and host immune pathways. Despite substantial scientific advances, translation into clinical practice remains constrained by limited burn-specific trials, heterogeneous definitions, and systemic barriers to antimicrobial development. Collectively, these challenges underscore the need for integrated, precision-based approaches that combine early source control, individualized antimicrobial optimization, and advanced diagnostic frameworks. Future progress will depend on coordinated efforts to standardize definitions, generate high-quality multicenter data, and align innovation with clinical applicability across diverse healthcare settings. Full article

Background: Feline chronic gingivostomatitis (FCGS) is refractory stomatitis in cats. The cure rate of tooth extraction selected as a primary surgical treatment is insufficient. Methods: 52 FCGS-suspected cats, including 22 tooth-extracted and 30 unextracted cats, were studied. Commercially available antiviral and antibacterial agents were orally administered as initial treatment, followed by the antiviral agent solely as maintenance therapy. We examined the influence of prior tooth extraction on the therapeutic efficacy of these two drugs by analyzing changes in some physical signs and clinical laboratory biomarkers. Results: Mass spectrometric analysis revealed the active ingredients of antibacterial and antiviral were Moxifloxacin and Molnupiravir, respectively. All physical signs (weight, appetite, activity level, grooming behavior, ptyalism, erythema) showed statistically significant improvements with combined administration of these drugs. Numbers of white blood cells, neutrophils and monocytes, as well as circulating levels of total protein, albumin, globulin, and serum amyloid-A all statistically significantly decreased with their administration (p < 0.0001). Conclusions: No statistically significant differences were detected between two FCGS groups in the changes in any of the above physical signs or clinical biomarker levels, indicating combination therapy with antibacterial and antiviral agents leads to effective treatment of FCGS, regardless of whether prior tooth extraction was performed or not. Full article

This manuscript shows a clinical case of interest that was brought to the Teaching Veterinary Clinical Complex, College of Veterinary Science and Animal Husbandry, Jabalpur, Madhya Pradesh. Based on the clinical findings, infection with canine parvovirus type 2 (CPV-2) was a first-line diagnosis and later confirmed by a rapid antigen detection kit. Disease prognosis is influenced by viral virulence and host response, with early therapeutic intervention being critical for survival. The dog was given intensive supportive management including fluid therapy, antibiotics, antiemetics, antidiarrheals, antacids, and vitamin supplementation for six days. The dog became progressively better clinically, the gastrointestinal signs resolved completely, and the dog recovered fully. Full article

Histopathological evaluation of tissue sections remains the gold standard for the diagnosis, classification, and grading of breast cancer (BC). The widespread adoption of whole-slide imaging (WSI) has enabled the digitization of histological slides and facilitated the development of artificial intelligence (AI) approaches for computational pathology. In recent years, machine learning and deep learning (DL) algorithms have been increasingly investigated for the analysis of hematoxylin and eosin (H&E)-stained images, with potential applications in tumor detection, histological classification, prognostic stratification, and prediction of treatment response. This narrative review summarizes recent developments in AI-driven models applied to BC histopathology and discusses their potential role in supporting diagnostic and prognostic assessment. Several studies have demonstrated the promising performance of DL algorithms in tasks such as the detection of lymph node metastases, assessment of residual tumor after neoadjuvant therapy, and prediction of clinical outcomes from histopathological images. Emerging research has also explored the possibility of inferring molecular and biomarker information from histology images, although these approaches currently identify statistical associations rather than direct molecular measurements. Despite the rapid expansion of this research field, significant barriers remain before routine clinical implementation can be achieved. Key challenges include dataset bias, variability in staining and image acquisition, limited external validation across institutions, and the need for transparent and reproducible model development. In addition, the translation of AI-based systems into clinical practice requires compliance with regulatory frameworks governing software used for medical purposes, such as those established by the U.S. Food and Drug Administration. Overall, AI represents a promising research direction in computational pathology and may contribute to decision-support tools capable of assisting pathologists in the analysis of digital slides. Continued efforts toward methodological rigor, large multicenter datasets, and prospective validation studies will be essential to determine the future role of AI in BC histopathology. Full article

Objective: In metastatic colorectal cancer (mCRC), mucinous histology has been associated with poor clinical outcomes, particularly in the presence of peritoneal metastasis. However, it remains unclear whether mucinous histology exerts a context-dependent effect on treatment outcomes by modifying the efficacy of anti-vascular endothelial growth factor (VEGF)-based therapies independently of metastatic dissemination patterns and chemotherapy backbone. Methods: We retrospectively analyzed 250 patients with mCRC treated with bevacizumab-containing systemic therapy. Tumors were classified as mucinous (n = 52) or non-mucinous (n = 198). Progression-free survival (PFS) and overall survival (OS) were estimated using the Kaplan–Meier method and compared using the log-rank test. Cox proportional hazards regression models were applied for univariate and multivariate analyses. Predefined subgroup analyses were conducted according to peritoneal metastasis status and chemotherapy backbone (oxaliplatin- or irinotecan-based). A 6-month landmark analysis was performed to reduce early progression bias. Interaction analyses evaluated potential effect modification between histology, peritoneal metastasis, and chemotherapy backbone. Results: Mucinous tumors were more frequently right-sided and strongly associated with peritoneal metastasis. In the overall cohort, mucinous histology was associated with significantly longer median PFS compared with non-mucinous histology (22.9 vs. 11.9 months; p < 0.001). This benefit was driven by patients with peritoneal metastasis, in whom mucinous histology was associated with markedly prolonged PFS (23.9 vs. 8.7 months; p < 0.001). No significant PFS difference according to histology was observed in patients without peritoneal metastasis. On multivariate analysis, mucinous histology remained independently associated with improved PFS (HR 0.44; 95% CI 0.25–0.78; p = 0.005), an effect preserved in the landmark cohort (HR 0.39; 95% CI 0.26–0.59; p < 0.001). A significant interaction between mucinous histology and peritoneal metastasis was observed (p for interaction = 0.040), indicating that the prognostic impact of histology differed according to metastatic pattern. No significant PFS difference or interaction was detected according to chemotherapy backbone within the mucinous subgroup. Conclusions: Among bevacizumab-treated patients with mCRC, mucinous histology—particularly in the presence of peritoneal metastasis—is associated with a pronounced PFS advantage independent of chemotherapy backbone. These findings suggest that mucinous peritoneal mCRC represents a biologically and clinically distinct subgroup that may derive context-specific and disproportionate benefit from anti-VEGF-based strategies, warranting prospective validation. Full article

Introduction: Lung cancer remains the leading cause of cancer-related mortality among men in Poland. Prognosis is generally poor, largely due to late diagnosis at advanced stages and the aggressive biological nature of the disease. Aim: This study aimed to evaluate the effectiveness of various treatment modalities and determine their impact on overall survival in male patients diagnosed with small-cell (SCLC) and non-small-cell lung cancer (NSCLC). Methods: This retrospective cohort study analyzed 1431 men (mean age: 61.5 years) treated at the Katowice Oncology Center in Poland between 2002 and 2012. Overall survival was assessed using the Kaplan–Meier method and multivariable Cox proportional hazards regression. Evaluated prognostic factors included clinical stage, surgical intervention (partial or total lung resection), first-line treatment regimen, and the number of treatment cycles. Results: Survival probabilities declined progressively with advancing clinical stage for both SCLC and NSCLC. Patients who underwent surgical resection demonstrated significantly longer survival compared to non-surgically treated patients (p < 0.001). Furthermore, combined radiochemotherapy yielded superior therapeutic outcomes compared to chemotherapy alone. In the non-surgical NSCLC cohort, first-line treatment with platinum derivatives combined with gemcitabine resulted in the highest 1-year survival rate compared to other pharmacological schemes. Discussion: The high mortality observed within the first 12 months post diagnosis reflects the late-stage presentation common during the study period. The findings align with established oncological principles, confirming that surgical resection and multimodal therapies offer the greatest survival advantages for eligible patients. Conclusions: Survival rates for both SCLC and NSCLC are overwhelmingly dictated by early diagnosis and the feasibility of surgical resection. Improving long-term outcomes depends heavily on implementing effective lung cancer screening programs to detect the disease at operable stages and utilizing optimized combined treatment protocols. Full article

Extensive evidence now confirms Lipoprotein(a) [Lp(a)] as a causal, independent risk factor for atherosclerotic cardiovascular disease. Elevated Lp(a) levels are detected in approximately 20% of the global population, positioning it as a major contributor to residual cardiovascular risk. Circulating Lp(a) levels are determined predominantly by genetic factors, so they are largely unresponsive to lifestyle modifications or conventional lipid-lowering therapies. Therefore, multiple international guidelines now endorse a one-time, lifetime measurement of Lp(a), as lowering Lp(a) concentrations is expected to have a positive impact on the reduction of cardiovascular risk. Currently, the therapeutic landscape of Lp(a) lowering drugs is rapidly evolving. Some RNA-based therapies (antisense oligonucleotides (ASOs) and small interfering RNAs (siRNAs)) have been demonstrated to reduce plasma Lp(a) concentrations by up to 98% in early-phase clinical trials. The efficacy and safety of these compounds are currently being evaluated in large-scale cardiovascular outcome trials. The results of these studies will be critical in validating the “Lp(a) hypothesis”: specific reduction of Lp(a) levels can lead to a measurable decrease in cardiovascular events. The purpose of this narrative review is to examine and discuss the available evidence on the role of Lp(a) as a risk factor and pharmacological target to provide a practical tool for decision-making in clinical practice. Full article

Background/Objectives: Rapid and accurate electrocardiogram (ECG) interpretation is essential for timely recognition of ST-elevation myocardial infarction (STEMI) and initiation of reperfusion therapy in the emergency department (ED). We evaluated the diagnostic performance of a real-time artificial intelligence (AI) ECG interpretation system and its pragmatic impact when integrated into routine ED workflows. Methods: This prospective, single-center pragmatic observational study was conducted in a regional emergency medical center ED in Busan, Republic of Korea (1 January–31 December 2024). Consecutive adults (≥18 years) undergoing 12-lead ECG for cardiovascular-related symptoms were enrolled (N = 1524). A predefined alternating-day protocol allocated visits to physician-only interpretation days (physician-days, N = 763) or AI output disclosure days (AI-days, N = 761). Diagnostic performance for STEMI was assessed using paired ECG-level comparisons between physician-alone interpretation and AI output against a blinded expert-panel reference standard; clinical impact outcomes included reperfusion-related time metrics, hospital length of stay (LOS), and in-hospital mortality. Results: Against the expert reference standard, AI showed higher STEMI sensitivity than physician-alone interpretation (96.7% vs. 68.3%; McNemar p = 0.027), while specificity was lower (75.9% vs. 84.5%; p = 0.018). In pragmatic day-level comparisons, door-to-balloon time was shorter on AI-days (40.0 ± 19.81 vs. 47.34 ± 21.90 min; p = 0.001), and time to PCI was significantly reduced among patients with atypical presentations (42.3 ± 18.21 vs. 57.1 ± 20.11 min; p = 0.013). Among admitted patients, hospital LOS was shorter on AI-days (13 ± 9.21 vs. 17 ± 10.31 days; p = 0.010), whereas in-hospital mortality did not differ significantly between groups (17.0% vs. 16.77%; p = 0.191). Conclusions: Real-time AI-ECG integration in the ED was associated with improved STEMI detection sensitivity and shorter reperfusion-related time metrics, particularly in atypical presentations, and with reduced hospital LOS among admitted patients. Short-term mortality was comparable between groups. Further multicenter studies are warranted to confirm generalizability and to balance benefits against potential false-positive-related operational impacts. Full article

Background: Hepatitis B virus (HBV) reactivation in oncology patients receiving chemotherapy can cause severe hepatitis, including hepatic failure and death. Universal HBV screening before chemotherapy initiation can reduce HBV-related morbidity; however, screening practices vary widely, and guideline recommendations continue to evolve. Objective: The aim of this study was to evaluate the implementation of universal HBV screening in oncology patients and its effectiveness in identifying active infection, prior exposure, and individuals at risk for HBV reactivation. Methods: We implemented universal HBV screening at Rambam Health Care Campus in January 2018 for all patients initiating chemotherapy. This retrospective cohort study analyzed 1614 oncology patients who underwent chemotherapy between January 2018 and April 2024. Screening included testing for HBsAg, anti-HBc, and anti-HBs serology. HBV DNA testing was performed in patients with positive HBsAg and/or anti-HBc serology. Patients with known HBsAg positivity or those already receiving antiviral therapy were excluded. Results: Of the screened patients, 16 (1.0%) were HBsAg-positive, and 134 (8.3%) were HBsAg-negative/anti-HBc-positive. Detectable HBV DNA was identified in four patients (3%) within the latter group. One additional patient was classified as high risk for HBV reactivation based on the planned chemotherapy regimen. Overall, 21 patients met criteria for prophylactic antiviral therapy; however, prophylaxis was administered to only 17 patients. Notably, when applying the 2015 ASCO guidelines, only a single patient within the subgroup of HBsAg-negative, anti-HBc-positive, and HBV DNA-negative patients would have qualified for HBV serologic screening based on chemotherapy-related risk alone. Conclusions: Universal HBV screening prior to chemotherapy enables the identification of patients with active or prior HBV infection who would not have been detected using risk-based screening strategies alone. Our findings further support the implementation of universal HBV screening in oncology settings to prevent HBV reactivation and its potentially severe consequences. Full article

The integration of emerging technologies and real-world data is transforming the landscape of hematologic clinical trials. Artificial intelligence (AI) offers remarkable capabilities for predictive modeling, patient stratification, and adaptive trial design, while circulating tumor DNA (ctDNA) provides a minimally invasive biomarker for disease monitoring, the early detection of relapse, and treatment response assessment. Concurrently, real-world evidence (RWE) complements traditional clinical trial data by capturing treatment effectiveness, safety, and patient outcomes in broader, heterogeneous populations. This review examines the synergistic potential of AI, ctDNA, and RWE to optimize trial design and decision-making in hematologic malignancies. We discuss methodological innovations, including AI-driven patient selection, ctDNA-guided adaptive interventions, and the incorporation of RWE for external control arms and post-marketing surveillance. Key challenges, such as data standardization, regulatory considerations, and ethical implications, are also addressed. By integrating these advanced tools, clinical trials in hematology can achieve greater efficiency, precision, and translatability, ultimately accelerating the development of personalized therapies and improving patient outcomes. Full article

Background/Objectives: Gastric-type endocervical adenocarcinoma (G-EAC) is a rare, aggressive, and HPV-independent subtype of cervical cancer with a poor prognosis. Due to its rarity, existing literature is often limited by small sample sizes, which hinders the development of evidence-based clinical management strategies. This study aims to evaluate the clinicopathological features, prognostic factors, and responses to postoperative adjuvant therapy in a large cohort of G-EAC patients compared with those with usual endocervical adenocarcinoma (UEA). Methods: We conducted a nested case–control study within a prospectively maintained surgical cohort at a national referral center in China. The study population included 195 pathologically confirmed G-EAC cases and 765 UEA cases. Patients were followed longitudinally with comprehensive clinical and survival data collection. One-to-one propensity score matching (PSM) was performed to balance demographic, clinical, and treatment variables between the groups. Survival outcomes were compared using Kaplan–Meier analysis, and independent prognostic factors were identified via Cox regression. Results: G-EAC patients demonstrated significantly worse survival outcomes than matched UEA patients, with 3-year progression-free survival (PFS) of 66.1% vs. 79.8% (p = 0.014) and 3-year overall survival (OS) of 74.9% vs. 84.6% (p = 0.033). Parametrial involvement and pelvic lymph node metastasis were identified as independent risk factors for both recurrence and death (p < 0.05). Regarding adjuvant treatment, combined radiotherapy and chemotherapy significantly improved survival compared with single-modality treatments (PFS: 65.2% vs. 43.6%; OS: 74.3% vs. 54.5%; p < 0.05); however, G-EAC remained less responsive to these therapies than UEA. Conclusions: G-EAC exhibits more aggressive clinical behavior and poorer survival outcomes compared to UEA. While combined radiotherapy and chemotherapy offer survival benefits, outcomes remain suboptimal. These findings underscore the urgent need for early detection strategies and the development of more effective targeted therapies for this specific subtype. Full article

Actinobacillus pleuropneumoniae is a major swine pathogen that causes pleuropneumonia and leads to substantial economic losses due to mortality, impaired growth, and carcass condemnation. Nineteen serovars have been described, and their geographic distribution has been assessed using multiple typing approaches. High serovar diversity, together with limited cross-protective immunity, increases reliance on antimicrobial therapy for disease control. However, data on the genotypic diversity and antimicrobial susceptibility of A. pleuropneumoniae remain limited worldwide, and information on serovar distribution in Brazil is scarce. Here, we report serotyping, genotyping, and antimicrobial susceptibility profiling of A. pleuropneumoniae isolated from diseased pigs in Brazil. Eighty-five isolates from eight Brazilian states were analyzed; serovars 5 and 10 were the most prevalent (38.8% and 29.4%, respectively). Ceftiofur, spectinomycin, gentamicin, neomycin, tilmicosin, tulathromycin, and florfenicol showed good in vitro activity against the isolates. The highest resistance rates were observed for tylosin (98.8%), clindamycin (90.6%), chlortetracycline (67.1%), and oxytetracycline (67.1%), and multidrug resistance was detected in 55% of strains. SE-AFLP and PFGE revealed high genetic diversity, including among isolates of the same serovar, although a modest tendency to cluster by geographic origin and serovar was observed. Full article

Background: Comprehensive genomic profiling (CGP) is increasingly used in precision oncology to identify actionable genomic alterations and guide targeted therapies in solid tumors. However, the clinical implementation of CGP assays requires rigorous analytical validation to ensure accurate and reproducible detection of diverse genomic alterations across heterogeneous tumor samples. Despite rapid advancements in next-generation sequencing technologies, there remains a need for validated CGP platforms that demonstrate reliable performance and readiness for routine clinical use. Methods: This study evaluated the analytical and clinical performance of a CGP assay capable of detecting multiple genomic alteration types, including single nucleotide variants (SNVs), insertions/deletions (Indels), copy number variations (CNVs), gene fusions, and tumor mutational burden (TMB). Validation was conducted using patient-derived 117 FFPE tumor samples, external proficiency testing materials, and reference standards. Assay performance was assessed through comparison with orthogonal methods and through evaluation of reproducibility, limit of detection, and TMB concordance. Results: The assay demonstrated excellent analytical performance, achieving 100% sensitivity, specificity, and accuracy for variant detection across evaluated samples. Strong concordance was observed for TMB estimation (R² = 0.9925), with consistent classification of TMB-high cases. The assay showed robust inter- and intra-run reproducibility and reliable detection of low-frequency variants. Limit-of-detection (LOD) analysis confirmed accurate SNV detection at approximately 1% variant allele frequency and reliable RNA fusion detection at low input levels. Conclusions: The validated CGP assay provides accurate, reproducible, and comprehensive detection of clinically relevant genomic alterations in solid tumors. These results support its suitability for routine clinical deployment, enabling reliable genomic profiling to inform precision oncology treatment decisions. Full article

Background: Heart transplantation remains the definitive therapy for selected patients with end-stage heart failure, but outcomes are limited by acute rejection, chronic allograft injury, and cardiac allograft vasculopathy. Endomyocardial biopsy (EMB) remains the reference standard for rejection surveillance but is invasive and imperfectly captures diffuse myocardial injury. Cardiovascular magnetic resonance (CMR) offers noninvasive, multiparametric assessment of graft structure, function, tissue composition, and perfusion. We aimed to review current evidence supporting CMR in post-heart transplant surveillance and to evaluate the performance of serial CMR for acute cellular rejection in a prospective cohort. Methods: We performed a focused narrative review of the literature on CMR for detection of acute rejection, assessment of chronic allograft injury and prognosis, and evaluation of cardiac allograft vasculopathy and microvascular disease. In parallel, we conducted a prospective observational study of adult heart transplant recipients undergoing early post-transplant CMR (CMR1) and follow-up CMR (CMR2) with temporally matched EMB. Multiparametric CMR included cine imaging, native T1 and T2 mapping, extracellular volume fraction (ECV), and late gadolinium enhancement (LGE). Clinically significant acute cellular rejection was defined as ISHLT grade ≥ 2R. Results: Eighteen recipients were included (median 53 days to CMR1 and 192 days to CMR2). Baseline CMR parameters correlated with invasive hemodynamic and biomarkers. Two patients had biopsy-proven ≥2R rejection at follow-up. T2 values at CMR2 were significantly higher in rejection versus non-rejection patients (59.0 ± 1.4 ms vs. 51.1 ± 1.9 ms; p = 0.015), with greater LGE burden in rejection (p = 0.029). In longitudinal analyses, rejection was associated with divergent patterns of cardiac remodelling and tissue characterization, including increases in indexed ventricular volumes and T2 over time, whereas non-rejection patients demonstrated stable ventricular volumes and a decline in T2. Conclusions: Multiparametric CMR, anchored by T2 mapping, provides clinically meaningful, non-invasive information for acute rejection surveillance after heart transplantation and complements EMB within a personalized, risk-adapted follow-up framework. Establishing individualized baseline CMR phenotypes and monitoring longitudinal changes may support more personalized, less invasive graft surveillance strategies. Larger multicentre prospective studies are needed to define standardized implementation pathways. Full article