Infectious Disease

A narrative review focusing on randomized clinical trials of vitamin D supplementation for COVID-19 disease.

Current evidence is inconsistent on whether vitamin D supplementation can prevent COVID-19 infection or improve its clinical outcomes. To better understand and look into the issue, we went through the background knowledge of COVID-19 and vitamin D, searched in Pubmed [by using key words in the title containing "randomized clinical trial", "COVID-19", and "vitamin D (25-hydroxyvitamin D, or choleca...

Understanding the role of the gut microbiome in solid tumor responses to immune checkpoint inhibitors for personalized therapeutic strategies: a review.

Immunotherapy, especially immune checkpoint inhibitor (ICI) therapy, has yielded remarkable outcomes for some patients with solid cancers, but others do not respond to these treatments. Recent research has identified the gut microbiota as a key modulator of immune responses, suggesting that its composition is closely linked to responses to ICI therapy in cancer treatment. As a result, the gut micr...

Exploring the shared gene signatures and mechanism among three autoimmune diseases by bulk RNA sequencing integrated with single-cell RNA sequencing analysis.

BACKGROUND: Emerging evidence underscores the comorbidity mechanisms among autoimmune diseases (AIDs), with innovative technologies such as single-cel...

A hierarchy category of socially assistive robots' functions: Insights from older adults.

Socially assistive robots (SARs) are increasingly recognized for their potential in helping older adults age in place. Effectively meeting the diverse...

Artificial intelligence in antimicrobial stewardship: a systematic review and meta-analysis of predictive performance and diagnostic accuracy.

The increasing threat of antimicrobial resistance has prompted a need for more effective antimicrobial stewardship programs (AMS). Artificial intellig...

Interpretable machine learning for predicting sepsis risk in emergency triage patients.

The study aimed to develop and validate a sepsis prediction model using structured electronic medical records (sEMR) and machine learning (ML) methods...

Optimal selection of machine learning algorithms for ciprofloxacin prediction based on conventional water quality indicators.

The long-term presence of antibiotics in the aquatic environment will affect ecology and human health. Techniques for determining antibiotics are ofte...

Marine actinobacteria metabolites: unlocking new treatments for acne vulgaris.

Marine-derived actinobacteria isolated from sponge and soft coral were screened for antibacterial activity against acne-related bacteria, specifical...

Urine kidney injury molecule-1 predicts subclinical kidney disease among persons living with HIV initiating tenofovir disoproxil fumarate-based ART in Zambia.

INTRODUCTION: Antiretroviral therapy (ART) increases the life expectancy of persons living with HIV (PLWH), but not without potentially serious advers...

Biological activities of lichen extracts and UHPLC-ESI-QTOF-MS analysis of their secondary metabolites.

This research was designed to investigate the metabolite profiling, phenolics content, and the trypanocidal, nematicidal, antibacterial, antifungal, a...

Harnessing artificial intelligence in sepsis care: advances in early detection, personalized treatment, and real-time monitoring.

Sepsis remains a leading cause of morbidity and mortality worldwide due to its rapid progression and heterogeneous nature. This review explores the po...

Comparison between traditional logistic regression and machine learning for predicting mortality in adult sepsis patients.

BACKGROUND: Sepsis is a life-threatening disease associated with a high mortality rate, emphasizing the need for the exploration of novel models to pr...

Optimizing the production and efficacy of antimicrobial bioactive compounds from in combating multi-drug-resistant pathogens.

BACKGROUND: The rise of antibiotic-resistant pathogens has intensified the search for novel antimicrobial agents. This study aimed to isolate from lo...

Assessing fecal contamination from human and environmental sources using as an indicator in rural eastern Ethiopian households-a cross-sectional study from the EXCAM project.

INTRODUCTION: Enteric pathogens are a leading causes of diarrheal deaths in low-and middle-income countries. The Exposure Assessment of Infections in...

Trace detection of antibiotics in wastewater using tunable core-shell nanoparticles SERS substrate combined with machine learning algorithms.

Surface-enhanced Raman scattering (SERS) show great potential for rapid and highly sensitive detection of trace amounts of contamination from the envi...

High performance COVID-19 screening using machine learning.

Since the World Health Organization declared the Coronavirus Disease 2019 (COVID-19) pandemic as an international concern of public health emergency i...

Study of interaction in dual-species biofilm of Candida glabrata and Klebsiella pneumoniae co-isolated from peripheral venous catheter using Raman characterization mapping and machine learning algorithms.

Polymicrobial biofilm infections, especially associated with medical devices such as peripheral venous catheters, are challenging in clinical settings...

Ethical engagement with artificial intelligence in medical education.

The integration of large language models (LLMs) in medical education offers both opportunities and challenges. While these artificial intelligence (AI...

Managing emergency crises using secure information through educational awareness: COVID-19 case study.

Social networks are increasingly taking over daily life, creating a volume of unsecured data and making it very difficult to capture safe data, especi...

The role of artificial intelligence in pandemic responses: from epidemiological modeling to vaccine development.

Integrating Artificial Intelligence (AI) across numerous disciplines has transformed the worldwide landscape of pandemic response. This review investi...