Dosing, Toxicity and Drug Concentrations for Ganciclovir/Valganciclovir in Preterm and Low Birthweight Infants Treated for Cytomegalovirus.

Background: There is a lack of data regarding suitable dosage when administering intravenous ganciclovir (GCV) or oral valganciclovir (valGCV) to preterm and low birthweight infants with cytomegalovirus (CMV) disease.

Methods: Data were collected for infants born before 32 weeks gestation and/or weighing less than 1.8 kg treated for CMV disease with GCV or valGCV between 2016 and 2023.

A content review of COVID-19-related apps used in Vietnam.

Introduction: Various digital applications (apps) have been developed as an aid to address the novel issues caused by the Coronavirus disease 2019 (COVID-19) pandemic. Vietnam has experienced a proliferation of apps for this purpose. This review aims to evaluate all Vietnamese COVID-19 apps, analyzing their features, functionality, advantages, disadvantages, and ethical issues to inform developers, communities, and governments on the most desirable features of COVID-19 apps and the user's opinions.

Color correction methods for underwater image enhancement: A systematic literature review.

Underwater vision is essential in numerous applications, such as marine resource surveying, autonomous navigation, objective detection, and target monitoring. However, raw underwater images often suffer from significant color deviations due to light attenuation, presenting challenges for practical use. This systematic literature review examines the latest advancements in color correction methods for underwater image enhancement.

In Vitro and In Silico Antidiabetic Efficacy of Solanum lasiocarpum Dunal Fruit Extract.

Exploring the possibility of familiar dietary sources as additional diabetes treatments is crucial, especially considering the financial difficulties related to diabetes mellitus. Using both in vitro and in silico techniques, this work aims to assess the antidiabetic benefits of extract from Solanum lasiocarpum Dunal. The evaluations encompass the ability to scavenge DPPH radicals, inhibition of α-amylase, α-glucosidase, inhibition of DPP-4, cytotoxicity, and glucose absorption kinetics.

Assessing the Accuracy of Fitness Smartwatch Data for Cardiovascular and Physical Activity Monitoring: A Validation Study in Digital Health.

This study aims to validate the accuracy of low-cost fitness smartwatches by comparing their data with gold-standard measurements for cardiovascular and physical activity parameters. The study enrolled 50 subjects, 26 undergoing validation testing for heart rate, blood oxygen saturation (SpO2), and sleep data against polysomnography (PSG). Additionally, 24 subjects participated in the 3-Minute Walk Test (3MWT) and Stairs Climbing (SC), with step counts validated against manual video calculations.

Gilteritinib versus salvage chemotherapy in predominantly Asian patients with relapsed/refractory FLT3-mutated acute myeloid leukemia: a regional analysis of COMMODORE in China, South-East Asia, and Russia.

The COMMODORE study demonstrated the efficacy and safety of gilteritinib versus salvage chemotherapy (SC) treatment in a predominantly Asian population with relapsed/refractory (R/R) FMS-like tyrosine kinase 3 (FLT3)-mutated() acute myeloid leukemia (AML); here we present an exploratory analysis of the study stratified by region (China, South-East Asia and Russia). COMMODORE was a Phase 3, open-label, randomized (1:1), multicenter trial. There were 151, 50, and 33 patients in the China, South-East Asia, and Russia cohorts, respectively.

Resveratrol: a potential alternative therapeutic agent for patients suffering from chronic obstructive pulmonary disease (COPD).

This review explores the therapeutic potential of resveratrol, focusing on its molecular and cellular effects on Chronic Obstructive Pulmonary Disease (COPD), bioavailability enhancement strategies, and development challenges for applications in food, pharmaceuticals, and postharvest sectors. Resveratrol protects lungs by activating SIRT1, reducing oxidative stress via ROS regulation through Nrf2-mediated antioxidant enzymes. It shows promise as an alternative to corticosteroids in COPD and cancer treatment.

Global Burden of Major Chronic Liver Diseases in 2021.

Background: This study utilised the Global Burden of Disease data (2010-2021) to analyse the rates and trends in point prevalence, annual incidence and years lived with disability (YLDs) for major chronic liver diseases, such as hepatitis B, hepatitis C, metabolic dysfunction-associated liver disease, cirrhosis and other chronic liver diseases.

Methods: Age-standardised rates per 100,000 population for prevalence, annual incidence and YLDs were compared across regions and countries, as well as the socio-demographic index (SDI). Trends were expressed as percentage changes (PC) and estimates were reported with uncertainty intervals (UI).

Aspiration to admission: Widening access to medical education: AMEE Guide No. 181.

SERIES INTRODUCTORY ABSTRACTWidening Access, Participation and SuccessThis AMEE guide series explores three interconnected strategies for widening access, participation, and success in medical education. The series emphasises the interdependence of these areas as essential to supporting students from entry to graduation. Each guide in the series addresses a specific phase of the student journey, from the first steps of widening access, through enhancing participation during their studies, to supporting their ultimate success.

Review of models for estimating 3D human pose using deep learning.

Human pose estimation (HPE) is designed to detect and localize various parts of the human body and represent them as a kinematic structure based on input data like images and videos. Three-dimensional (3D) HPE involves determining the positions of articulated joints in 3D space. Given its wide-ranging applications, HPE has become one of the fastest-growing areas in computer vision and artificial intelligence.

A secure healthcare data transmission based on synchronization of fractional order chaotic systems.

The transmission of healthcare data plays a vital role in cities worldwide, facilitating access to patient's health information across healthcare systems and contributing to the enhancement of care services. Ensuring secure healthcare transmission requires that the transmitted data be reliable. However, verifying this reliability can potentially compromise patient privacy.

GATI-RS model using Bi-LSTM and multi-head attention mechanism to enhance online shopping experience for the elderly with accurate click-through rate prediction.

With the rapid development of e-commerce and the increasing aging population, more elderly people are engaging in online shopping. However, challenges they face during this process are becoming more apparent. This article proposes a recommendation system based on click-through rate (CTR) prediction, aiming to enhance the online shopping experience for elderly users.

NOMA-MIMO in 5G network: a detailed survey on enhancing data rate.

Non-orthogonal multiple access (NOMA) is a technology that leverages user channel gains, offers higher spectral efficiency, improves user fairness, better cell-edge throughput, increased reliability, and low latency, making it a potential technology for the next generation of cellular networks. The application of NOMA in the power domain (NOMA-PD) with multiple-input multiple-output (MIMO) and other emerging technologies allows to achieve the demand for higher data rates in next-generation networks. This survey aims to funnel down NOMA MIMO resource allocation issues and different optimization problems that exist in the literature to enhance the data rate.

Atom Search Optimization: a comprehensive review of its variants, applications, and future directions.

The Atom Search Optimization (ASO) algorithm is a recent advancement in metaheuristic optimization inspired by principles of molecular dynamics. It mathematically models and simulates the natural behavior of atoms, with interactions governed by forces derived from the Lennard-Jones potential and constraint forces based on bond-length potentials. Since its inception in 2019, it has been successfully applied to various challenges across diverse fields in technology and science.

Blockchain technology and its impact on sustainable supply chain management in SMEs.

The COVID-19 pandemic has had a significant impact on small and medium-sized enterprises (SMEs), leading to disruptions in supply chains, financial losses, and closures. To overcome these challenges, organizations, including those in developing economies like Malaysia, are turning to blockchain technology as a solution to enhance traditional supply chain management frameworks. This study aims to identify the factors that influence the acceptance of blockchain technology among SMEs.

Impact of machine learning on dietary and exercise behaviors in type 2 diabetes self-management: a systematic literature review.

Self-awareness and self-management in diabetes are critical as they enhance patient well-being, decrease financial burden, and alleviate strain on healthcare systems by mitigating complications and promoting healthier life expectancy. Incomplete understanding persists regarding the synergistic effects of diet and exercise on diabetes management, as existing research often isolates these factors, creating a knowledge gap in comprehending their combined influence. Current diabetes research overlooks the interplay between diet and exercise in self-management.

An explainable multi-objective hybrid machine learning model for reducing heart failure mortality.

As the world grapples with pandemics and increasing stress levels among individuals, heart failure (HF) has emerged as a prominent cause of mortality on a global scale. The most effective approach to improving the chances of individuals' survival is to diagnose this condition at an early stage. Researchers widely utilize supervised feature selection techniques alongside conventional standalone machine learning (ML) algorithms to achieve the goal.

Novel cross-dimensional coarse-fine-grained complementary network for image-text matching.

The fundamental aspects of multimodal applications such as image-text matching, and cross-modal heterogeneity gap between images and texts have always been challenging and complex. Researchers strive to overcome the challenges by proposing numerous significant efforts directed toward narrowing the semantic gap between visual and textual modalities. However, existing methods are usually limited to computing the similarity between images (image regions) and text (text words), ignoring the semantic consistency between fine-grained matching of word regions and coarse-grained overall matching of image and text.

Unveiling personalized and gamification-based cybersecurity risks within financial institutions.

Gamification has emerged as a transformative e-business strategy, introducing innovative methods to engage customers and drive sales. This article explores the integration of game design principles into business contexts, termed "gamification," a subject of increasing interest among both scholars and industry professionals. The discussion systematically addresses key themes, like the role of gamification in marketing strategies, enhancing website functionality, and its application within the financial sector, including e-banking, drawing insights from academic and industry perspectives.

Leveraging a hybrid convolutional gated recursive diabetes prediction and severity grading model through a mobile app.

Diabetes mellitus is a common illness associated with high morbidity and mortality rates. Early detection of diabetes is essential to prevent long-term health complications. The existing machine learning model struggles with accuracy and reliability issues, as well as data imbalance, hindering the creation of a dependable diabetes prediction model.

Mesenchymal Stromal Cell-Derived Extracellular Vesicles in the Management of Atopic Dermatitis: A Scoping Review of Therapeutic Opportunities and Challenges.

Atopic dermatitis (AD) is a global concern marked by inflammation, skin barrier dysfunction, and immune dysregulation. Current treatments primarily address symptoms without offering a cure, underscoring the need for innovative therapeutic approaches. Mesenchymal stromal cell-derived extracellular vesicles (MSC-EVs) have attracted attention for their potential in immunomodulation and tissue repair, similar to their parent cells.

Translation and Validation of Rating-of-Fatigue Scale to be Used in Nonsurgical Endodontic Re-treatment.

Background: This study aimed to translate and validate the rating-of-fatigue (ROF) scale in the Kannada language.

Methods: This current study involved two steps, where forward translation, backward translation, cross-cultural adaptation, and test of a pre-final version of the ROF scale were conducted in the first step. Content validity, face validity, and construct validity of the ROF scale were performed in five stages.

Perianal fistulizing Crohn's disease: Mechanisms and treatment options focusing on cellular therapy.

Perianal fistulizing Crohn's disease (PFCD) is a common presentation of CD, which affects the patients' quality of life, including social and sexual function. The management of PFCD remains a critical challenge in inflammatory bowel disease, primarily due to limited understanding of the mechanisms involved in its pathogenesis, complicating medical treatment. Increased production of inflammatory cytokines such as tumor necrosis factor and interleukin-13 by infiltrating macrophages and other inflammatory cells stimulate the epithelial-to-mesenchymal transition, resulting in activation of myofibroblasts and elevation of matrix metalloproteinases, leading to fistula formation.

Eco-friendly pH monitoring in aquaculture: A comparative study of biomass waste extracts with different setup designs.

Maintaining optimal water quality is critical for the success of aquaculture operations, where pH monitoring plays a pivotal role. This study presents a novel approach for pH monitoring in aquaculture ponds by harnessing biomass-based indicators and smartphone-based colorimetric sensing using different setups designs. Three biomass indicators including red cabbage, mango leaf, and used coffee grounds extracts were tested.

YOLOv8-DEE: a high-precision model for printed circuit board defect detection.

Defects in printed circuit boards (PCBs) occurring during the production process of consumer electronic products can have a substantial impact on product quality, compromising both stability and reliability. Despite considerable efforts in PCB defect inspection, current detection models struggle with accuracy due to complex backgrounds and multi-scale characteristics of PCB defects. This article introduces a novel network, YOLOv8-DSC-EMA-EIoU (YOLOv8-DEE), to address these challenges by enhancing the YOLOv8-L model.