Search Results (1,397)

Antibiotic resistance remains one of the most formidable challenges to modern medicine, threatening to outpace therapeutic innovation and undermine decades of clinical progress. While resistance was once viewed narrowly as a clinical phenomenon, it is now understood as the outcome of complex ecological and molecular interactions that span soil, water, agriculture, animals, and humans. Environmental reservoirs act as silent incubators of resistance genes, with horizontal gene transfer and stress-induced mutagenesis fueling their evolution and dissemination. At the molecular level, advances in genomics, structural biology, and systems microbiology have revealed intricate networks involving plasmid-mediated resistance, efflux pump regulation, integron dynamics, and CRISPR-Cas interactions, providing new insights into the adaptability of pathogens. Simultaneously, the environmental dimensions of resistance, from wastewater treatment plants and aquaculture to airborne dissemination, highlight the urgency of adopting a One Health framework. Yet, alongside this growing threat, novel therapeutic avenues are emerging. Innovative β-lactamase inhibitors, bacteriophage-based therapies, engineered lysins, antimicrobial peptides, and CRISPR-driven antimicrobials are redefining what constitutes an “antibiotic” in the twenty-first century. Furthermore, artificial intelligence and machine learning now accelerate drug discovery and resistance prediction, raising the possibility of precision-guided antimicrobial stewardship. This review synthesizes molecular insights, environmental drivers, and therapeutic innovations to present a comprehensive landscape of antibiotic resistance. By bridging ecological microbiology, molecular biology, and translational medicine, it outlines a roadmap for surveillance, prevention, and drug development while emphasizing the need for integrative policies to safeguard global health. Full article

Aquaculture has rapidly become a vital sector for ensuring global food security by meeting the growing demand for animal protein. Bangladesh, one of the world’s leading aquaculture producers, recorded a production of 4.91 million MT in 2022–2023, largely driven by inland farming systems. Despite this remarkable growth, the sector is highly vulnerable to disease outbreaks, which are aggravated by different factors. Pathogens such as bacteria, viruses, fungi, and parasites cause significant losses, while conventional disease diagnosis in Bangladesh still depends mainly on visual assessment and basic laboratory techniques, limiting early detection. This narrative review highlights recent advances in diagnostics as molecular tools, immunodiagnostics, nanodiagnostics, machine learning, and next-generation sequencing (NGS) that are widely applied globally but remain limited in Bangladesh due to infrastructure gaps, lack of skilled manpower, and resource constraints. Current treatment strategies largely rely on antibiotics and aquaculture medicinal products (AMPs), often misused without proper diagnosis, contributing to antimicrobial resistance (AMR). Promising alternatives, including probiotics, immunostimulants, vaccines, and enhanced biosecurity, require greater adoption and farmer awareness. The near-term priorities for Bangladesh include standardized disease and AMR surveillance, prudent antibiotic stewardship, phased adoption of validated rapid diagnostics, and investment in diagnostic and human capacity. Policy-level actions, including a national aquatic animal health strategy, stricter antimicrobial regulation, strengthening diagnostic infrastructure in institution, are crucial to achieve sustainable disease management and ensure long-term resilience of aquaculture in Bangladesh. Full article

The Mycobacterium tuberculosis complex (MTBC) represents one of the most significant bacterial pathogen groups affecting both animals and humans worldwide. This review provides a comprehensive analysis of MTBC species distribution across different animal hosts and evaluates current laboratory diagnostic methodologies for pathogen detection and identification. The complex comprises seven primary species: Mycobacterium bovis, M. caprae, M. tuberculosis, M. microti, M. canettii, M. africanum, and M. pinnipedii, each exhibiting distinct host preferences, geographical distributions, and pathogenic characteristics. Despite sharing >99% genetic homology, these species demonstrate variable biochemical properties, morphological features, and pathogenicity profiles across mammalian species. Current diagnostic approaches encompass both traditional culture-based methods and advanced molecular techniques, including whole genome sequencing. This review emphasises the critical importance of rapid, accurate detection methods for effective tuberculosis surveillance and control programmes in veterinary and public health contexts. Full article

Background/Objectives: Fetal growth restriction (FGR) is a leading cause of perinatal morbidity and mortality. Accurate surveillance and timely delivery are critical to improving outcomes. This narrative review examines the role of computerized cardiotocography (cCTG) and short-term variation (STV) interpretation in the monitoring of FGR and its integration with Doppler velocimetry and the biophysical profile (BPP). Methods: A comprehensive literature search of PubMed, Scopus, and Web of Science was performed for studies published up to 2021 using combinations of terms related to FGR, CTG, STV, and Doppler surveillance. Eligible sources included original studies, systematic reviews, and international guidelines. Case reports, intrapartum-only monitoring, and studies involving major anomalies were excluded. Results: Reduced STV consistently correlates with fetal compromise, abnormal Doppler findings, and adverse perinatal outcomes. In early-onset FGR (<32 weeks), ductus venosus abnormalities often coincide with or precede STV reduction; combined use supports optimal timing of delivery. In late-onset FGR (≥32 weeks), STV changes are less pronounced and require integration with cerebroplacental ratio, variability indices, and trend-based interpretation. Longitudinal evaluation offers greater prognostic value than isolated measurements. However, heterogeneity in thresholds, fragmented outcome data, and system-specific definitions limit standardization and comparability across studies. Conclusions: cCTG provides an objective and adjunct to Doppler and BPP in the surveillance of FGR, a tool for obstetrician needs. Its greatest utility lies in serial, integrated assessment, supported by gestational age-specific reference ranges. Future advances should include standardized STV thresholds, large outcome-linked databases, and artificial intelligence-driven tools to refine decision-making and optimize delivery timing. Full article

Cyber-physical infrastructures such as hospitals and smart campuses face hybrid threats that target both digital and physical domains. Traditional security solutions separate surveillance from network monitoring, leaving blind spots when attackers combine these vectors. This paper introduces ARGUS, an autonomous robotic platform designed to close this gap by correlating cyber and physical anomalies in real time. ARGUS integrates computer vision for facial and weapon detection with intrusion detection systems (Snort, Suricata) for monitoring malicious network activity. Operating through an edge-first microservice architecture, it ensures low latency and resilience without reliance on cloud services. Our evaluation covered five scenarios—access control, unauthorized entry, weapon detection, port scanning, and denial-of-service attacks—with each repeated ten times under varied conditions such as low light, occlusion, and crowding. Results show face recognition accuracy of 92.7% (500 samples), weapon detection accuracy of 89.3% (450 samples), and intrusion detection latency below one second, with minimal false positives. Audio analysis of high-risk sounds further enhanced situational awareness. Beyond performance, ARGUS addresses GDPR and ISO 27001 compliance and anticipates adversarial robustness. By unifying cyber and physical detection, ARGUS advances beyond state-of-the-art patrol robots, delivering comprehensive situational awareness and a practical path toward resilient, ethical robotic security. Full article

A group of Spanish experts of different specialties participated in the ENFOCA2 project, promoted by the Spanish Oncology Genitourinary Group (SOGUG), which was designed to provide updated information on current and novel aspects contributing to the optimal care of prostate cancer (PCa) patients. In localized disease, it is important to implement strategic alliances with other institutions for improving adherence to active surveillance in low-risk groups and to explore genetic testing for a better indication of focal therapy. Local control of the disease should be maximized to prevent local failure and biochemical recurrence. In patients with locally advanced disease, with PSMA PET/CT-positive lesions in M0 staging on conventional imaging techniques, therapeutic decisions should be carefully evaluated due to insufficient evidence regarding the gold standard in this setting. In patients with metastatic castration-resistant PCa (mCRPC), assessment of BRCA somatic and germline mutations provides prognostic information and familial cancer risk and informs treatment decisions. Combinations of androgen receptor signaling inhibitor (ARSi) agents and poly-ADP ribose polymerase inhibitors (PARPi) are emerging alternatives for advanced PCa. The oldest segment of PCa patients (>70 years of age) may require geriatric assessment to evaluate physical and functional reserves, tailoring treatment to their individual characteristics and circumstances. The concept of a comprehensive multidisciplinary approach together with inter-center and/or inter-specialty therapeutic alliances should be implemented in the routine care of patients with PCa. Full article

Virus-associated hepatocellular carcinoma (HCC) remains a major global health burden despite effective antiviral therapies. Chronic infection with hepatitis B (HBV), hepatitis C (HCV), and hepatitis D (HDV) promotes malignant transformation through overlapping pathways of fibrosis, immune dysregulation, and microenvironmental remodeling. YKL-40, a glycoprotein secreted by hepatic stellate cells, hepatocytes under stress, macrophages, and endothelial cells, has emerged as a marker that reflects stromal activation rather than direct hepatocyte injury. Its expression is reinforced by profibrotic and angiogenic circuits, and circulating concentrations correlate with advanced fibrosis, residual risk after viral suppression, and oncologic outcomes. This review synthesizes current evidence on YKL-40 across HBV, HCV, and HDV cohorts, with emphasis on its role in bridging molecular mechanisms to clinical applications. We examine its utility in non-invasive fibrosis assessment, longitudinal monitoring after antiviral therapy, and prognostic modeling in HCC. Particular attention is given to its potential in the liver transplant pathway, where YKL-40 may refine eligibility beyond morphology, inform bridging therapy response, and predict post-transplant recurrence or graft fibrosis. Remaining challenges include its lack of disease specificity, assay variability, and limited multicenter validation. Future integration of YKL-40 into multimarker, algorithm-based frameworks could enable risk-adaptive strategies that align surveillance and transplant decisions with the evolving biology of virus-associated liver disease. Full article

Differentiated thyroid carcinoma (DTC) is the most common endocrine malignancy and typically has a favorable prognosis. However, a subset of patients experience aggressive disease, recurrence, or treatment resistance, underscoring the need for more precise diagnostic and therapeutic strategies. Advances in molecular profiling have improved the management of thyroid cancer by enabling risk-adapted treatment and targeted interventions. This narrative review offers a clinically focused synthesis of the current role of molecular diagnostics and personalized therapeutics in DTC. We examine key genetic alterations and their diagnostic, prognostic, and therapeutic implications, and discuss how molecular markers enhance traditional risk stratification systems, informing surgical decisions, radioactive iodine (RAI) use, and surveillance. The growing role of targeted therapies, such as tyrosine kinase inhibitors and agents against specific oncogenic drivers, is reviewed, particularly for RAI-refractory DTC. We also address real-world challenges in implementing precision medicine, including access, cost, and standardization. Future directions, such as liquid biopsy, artificial intelligence, and multi-omic integration, are explored as tools to achieve fully personalized care. This review aims to bridge the gap between molecular discovery and clinical application, offering practical insights for endocrinologists, surgeons, oncologists, and multidisciplinary teams managing DTC. Full article

A May 2025 symposium convened leading virology experts across Latin America and the Caribbean (LAC) to advance regional research and collaborative efforts. Sessions explored cutting-edge developments in arbovirology, pressing challenges in viral surveillance, and the complexities of vector biology. Integrated networking opportunities and hands-on workshops offered mentorship and training, focused on the next generation of virologists, and strengthened scientific communication within the region. The morning session included reports from the LAC Global Virus Network (GVN) Centers of Excellence. A roundtable dialogue tackled the present challenges faced in arbovirus research. The Abbott Pandemic Defense Coalition reported on its collaborative progress. Trainees from the University at Buffalo, the State University of New York, and the University of the West Indies Global Infectious Diseases Research Training program showcased their current research projects. A session concentrated on health landscapes and the capacity for viral vaccinations within the region. A mentoring workshop focused on immune evasion methodologies and obstacles associated with arboviruses. One Health perspectives on viral zoonotic diseases addressed developments in the surveillance of vector-borne viruses in the Caribbean. Studies of mosquitoes and ticks as vectors of viruses included discussion on the neurovirulence of arboviruses and symptoms occurring after viral infections. Pediatric infectious diseases were highlighted in their environmental health context. An additional mentoring workshop centered on viruses and the microbiome. The relationship between viruses and cancer was discussed in the South American context and included recent advancements in the field of vaccinology. The Jamaica Regional GVN meeting promoted collaboration, facilitated the exchange of knowledge, and advanced research efforts throughout the region. Full article

Methylphenidate (MPH) and its active enantiomer, dexmethylphenidate, are widely prescribed as first-line therapies for attention deficit hyperactivity disorder (ADHD), yet their increasing non-medical use highlights significant clinical and toxicological challenges. MPH blocks dopamine (DAT) and norepinephrine (NET) transporters, thereby elevating synaptic catecholamine levels. While this underpins therapeutic efficacy, prolonged or abusive exposure has been associated with mitochondrial impairment, disrupted bioenergetics, and excessive reactive oxygen species (ROS) production, which collectively contribute to neuronal stress and long-term neurotoxicity. Growing evidence suggests that the gut–brain axis may critically influence MPH outcomes: diet-induced shifts in microbiome composition appear to regulate oxidative stress, neuroinflammation, and drug metabolism, opening potential avenues for dietary or probiotic interventions. From a forensic perspective, the detection and monitoring of MPH misuse require advanced methodologies, including enantioselective LC–MS/MS and analysis of alternative matrices such as hair or oral fluids, which enable retrospective exposure assessment and improves abuse surveillance. Despite its established therapeutic profile, MPH remains a compound with a narrow balance between clinical benefit and toxicological risk. Future directions should prioritize longitudinal human studies, biomarker identification for abuse monitoring, and the development of mitochondria-targeted therapies to minimize adverse outcomes and enhance safety in long-term treatment. Full article

The intestinal mucus layer is a dynamic protective barrier that maintains gut homeostasis, supports immune defense, and regulates host–microbiota interactions. Rodent models have yielded valuable insights, but their intestinal structure and physiology differ from those of humans and pigs. By contrast, the omnivorous pig shares closer anatomical and immunological features with humans, making it a relevant large-animal model in translational studies. In this study, we established a histological workflow for porcine intestine by combining Carnoy’s fixation with Alcian Blue–Periodic Acid–Schiff and Mucicarmine staining. This enabled accurate visualization and quantification of goblet-cell density and mucus thickness across intestinal segments, with a particular focus on Peyer’s patches—key sites of immune surveillance. Both stains produced consistent results. We observed a clear proximal-to-distal gradient, from jejunum to colon, in mucus thickness: the colon displayed the thickest layer (~100 μm), whereas the follicle-associated epithelium over Peyer’s patches in the jejunum and ileum showed a markedly thinner layer (<12 μm) and fewer goblet cells. Immunofluorescence further revealed strong cytokeratin-18 expression in goblet cells, delineating their morphology and polarity. These findings demonstrate region-specific differences in mucus architecture and goblet-cell distribution that likely reflect specialized immune functions, advancing our understanding of the intestinal barrier and informing future strategies to support gut health and immunity. Full article

Background: Gastric cancer (GC) is the fifth most common malignancy worldwide. Early detection of precancerous conditions—atrophic gastritis (AG), intestinal metaplasia (IM), and dysplasia—is vital for surveillance. Objectives: To assess the accuracy of single high-quality endoscopy (HQE) in detecting advanced GPCs and to identify risk factors for AG, IM, and dysplasia. Methods: A retrospective review of 442 gastroscopies (2017–2022) at a single center. Endoscopic findings were compared with histology, including OLGA/OLGIM staging, dysplasia, and Helicobacter pylori (H. pylori) status. Results: The study population comprised 319 women (72.17%) and 123 men (27.83%), with a mean age of 59 years (SD: 12.53). AG, as defined by OLGA and OLGIM staging, was identified in 90 patients (20.36%) and 50 patients (11.31%), respectively. A total of 44 cases of de novo gastric dysplasia were observed, while HP infection was confirmed in 37 individuals (8.37%). We observed similar low sensitivity for detection of advanced OLGA (32.5%), OLGIM (40%), and dysplasia (19.7%) with relatively high specificity (~89%). Advanced AG and IM peaked at ages 51–53. Risk factors for advanced OLGIM included male sex (OR 2.26; p < 0.001) and presence of dysplasia (OR 2.09; p = 0.02). Dysplasia was positively associated with AG (OR 2.03; p < 0.001) and IM (OR 2.21; p < 0.001) but inversely associated with a family history of GC (OR 0.44; p < 0.001). Conclusions: A single HQE can help exclude advanced GPCs, but due to low sensitivity, gastric mapping biopsies remain crucial. Males are at increased risk of extensive IM. Family history of GC was linked to lower OLGA/OLGIM stages. Full article

Background/Objectives: Electronic fetal monitoring (EFM) has been used for intrapartum fetal surveillance for over 50 years. Despite numerous trials comparing EFM with standard fetal heart rate (FHR) auscultation, it remains contentious whether continuous monitoring with standard interpretation has reliably improved perinatal outcomes, specifically lower rates of perinatal morbidity and mortality. This review examines previous attempts to improve fetal monitoring and presents future directions for novel intrapartum fetal surveillance systems. Methods: We conducted a chronological review of EFM developments, including ancillary methods such as fetal ECG analysis, automated systems for FHR analysis, and artificial intelligence applications. We analyzed the evolution from visual interpretation to intelligent systems and evaluated the performance of various automated monitoring platforms. Results: Various ancillary methods developed to improve EFM accuracy for predicting fetal compromise have shown limited success. Only a limited number of studies demonstrated that adding fetal ECG analysis to visual FHR pattern interpretation resulted in better fetal outcomes. Automated systems for FHR analysis have not consistently enhanced intrapartum fetal surveillance. However, novel approaches such as the Fetal Reserve Index (FRI) show promise by incorporating clinical risk factors with traditional FHR patterns to provide higher-level risk assessment and prognosis. Conclusions: The shortcomings of visual interpretation of FHR patterns persist despite technological advances. Future intelligent intrapartum surveillance systems must combine conventional fetal monitoring with comprehensive risk assessment that incorporates maternal, fetal, and obstetric factors. The integration of artificial intelligence with contextualized metrics like the FRI represents the most promising direction for improving intrapartum fetal surveillance and clinical outcomes. Full article

This paper presents the final implemented design and performance evaluation of the ground-based C-band Cheia radar system, developed to enhance Romania’s contribution to the EU Space Surveillance and Tracking (EU SST) network. All data used for performance analysis are real-time, real-life measurements of true spatial test objects orbiting Earth. The radar is based on two decommissioned 32 m satellite communication antennas already present at the Cheia Satellite Communication Center, that were retrofitted for radar operation in a quasi-monostatic architecture. A Linear Frequency Modulated Continuous Wave (LFMCW) Radar design was implemented, using low transmitted power (2.5 kW) and advanced software-defined signal processing for detection and tracking of Low Earth Orbit (LEO) targets. System validation involved dry-run acceptance tests and calibration campaigns with known reference satellites. The radar demonstrated accurate measurements of range, Doppler velocity, and angular coordinates, with the capability to detect objects with radar cross-sections as low as 0.03 m² at slant ranges up to 1200 km. Tracking of medium and large Radar Cross Section (RCS) targets remained robust under both fair and adverse weather conditions. This work highlights the feasibility of re-purposing legacy satellite infrastructure for SST applications. The Cheia radar provides a cost-effective, EUSST-compliant performance solution using primarily commercial off-the-shelf components. The system strengthens the EU SST network while demonstrating the advantages of LFMCW radar architectures in electromagnetically congested environments. Full article

Background/Objectives: Escherichia coli is one of the leading causes of surgical site infections (SSIs) and poses a growing public health concern due to its increasing antimicrobial resistance. High rates of extended-spectrum beta-lactamase (ESBL) production among E. coli strains complicate treatment outcomes and emphasize the need for effective surveillance and control strategies. Methods: A total of 691 E. coli isolates from general surgery clinics (2020–2025) were identified using MALDI-TOF MS. Antibiotic susceptibility data and patient variables were cleaned, encoded, and used to predict resistance using the Random Forest, CatBoost, and Naive Bayes algorithms. SMOTE addressed class imbalance, and model performance was assessed through various validation methods. Results: Among the three machine learning models tested, Random Forest (RF) showed the best performance in predicting antibiotic resistance of E. coli, achieving median accuracy, precision, recall, and F1-scores of 0.90 and AUC values up to 0.99 for key antibiotics. CatBoost performed similarly but was less stable with imbalanced data, while Naive Bayes showed lower accuracy. Feature importance analysis highlighted strong inter-antibiotic resistance links, especially among β-lactams, and some influence of demographic factors. Conclusions: This study highlights the potential of simple, high-performing models using structured clinical data to predict antimicrobial resistance, especially in resource-limited clinical settings. By incorporating machine learning into antimicrobial resistance (AMR) surveillance systems, our goal is to support the advancement of rapid diagnostics and targeted antimicrobial stewardship approaches, which are essential in addressing the growing challenge of multidrug resistance. Full article