Comparative transcriptome analysis reveals a serotype-specific immune response in Nile tilapia () infected with .

is a major causative agent of streptococcosis in Nile tilapia () and understanding its etiology is important to ensure the sustainable development of global tilapia farming. Our research group recently observed contrasting disease patterns in animals infected with two different serotypes (Ib and III). To better understand the basis for these divergent responses, we analyzed the brain transcriptome of Nile tilapia following bacterial exposure.

Does oral hygiene prevents nosocomial infections in hospitalized patients? A systematic review and meta-analysis.

Background: This study aimed to evaluate the impact of oral hygiene (OH) with chlorhexidine (CHX) on the evolution of nosocomial infections (NI).

Material And Methods: Electronic searches were carried out in PubMed, Scopus, Cochrane Library, Web of Science, VHL, and Grey Literature databases. Randomized clinical trials were included.

Antimicrobial consumption and resistance in a tertiary care hospital in Brazil: a 7-year time series.

Introduction: Antimicrobial resistance (AMR) is a major public health challenge globally. This study aimed to analyze the antibacterial consumption (ATBc), and the incidence of multidrug-resistant organisms (MDRO), focusing on pathogens Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp. (ESKAPE group), in a Brazilian tertiary care hospital.

Evaluating ChatGPT-4 for the Interpretation of Images from Several Diagnostic Techniques in Gastroenterology.

Several artificial intelligence systems based on large language models (LLMs) have been commercially developed, with recent interest in integrating them for clinical questions. Recent versions now include image analysis capacity, but their performance in gastroenterology remains untested. This study assesses ChatGPT-4's performance in interpreting gastroenterology images.

Explainable AI in Digestive Healthcare and Gastrointestinal Endoscopy.

An important impediment to the incorporation of artificial intelligence-based tools into healthcare is their association with so-called black box medicine, a concept arising due to their complexity and the difficulties in understanding how they reach a decision. This situation may compromise the clinician's trust in these tools, should any errors occur, and the inability to explain how decisions are reached may affect their relationship with patients. Explainable AI (XAI) aims to overcome this limitation by facilitating a better understanding of how AI models reach their conclusions for users, thereby enhancing trust in the decisions reached.