A novel (-)-(2S)-7,4'-dihydroxyflavanone compound for treating age-related diabetes mellitus through immunoinformatics-guided activation of CISD3.

The iron-sulfur domain (CISD) proteins of CDGSH are classified into three classes: CISD1, CISD2, and CISD3. During premature ageing, mutations that affect these proteins, namely their binding sites, could result in reduced protein production and an inability to preserve cellular integrity. Consequently, this leads to the development of conditions such as diabetes.

Immunoinformatic-based drug design utilizing hesperetin to target CISD2 activation for liver aging in humans.

The CISD protein family, consisting of CISD1, CISD2, and CISD3, encodes proteins that feature CDGSH iron-sulfur domains crucial for cellular functions and share a common 2Fe-2S domain. CISD2, which is pivotal in cells, regulates intracellular calcium levels, maintains the endoplasmic reticulum and mitochondrial function, and is associated with longevity and overall health, with exercise stimulating CISD2 production. However, CISD2 expression decreases with age, impacting age-related processes.

A Hybrid Multimodal Emotion Recognition Framework for UX Evaluation Using Generalized Mixture Functions.

Multimodal emotion recognition has gained much traction in the field of affective computing, human-computer interaction (HCI), artificial intelligence (AI), and user experience (UX). There is growing demand to automate analysis of user emotion towards HCI, AI, and UX evaluation applications for providing affective services. Emotions are increasingly being used, obtained through the videos, audio, text or physiological signals.

National survey of intraoperative mitomycin C use during trabeculectomy surgery in the UK.

Purpose: Mitomycin C is a routinely used antimetabolite which effectively limits the scarring process. Conventionally, the intra-operative technique of MMC delivery during trabeculectomy is the direct application of the soaked sponges. The aim of this study is to evaluate the current practice of delivering MMC during trabeculectomy and to see the practices related to a retained MMC swab during trabeculectomy in the UK.

On computing critical factors based healthy behavior index for behavior assessment.

Objective: Ubiquitous computing has supported personalized health through a vast variety of wellness and healthcare self-quantification applications over the last decade. These applications provide insights for daily life activities but unable to portray the comprehensive impact of personal habits on human health. Therefore, in order to facilitate the individuals, we have correlated the lifestyle habits in an appropriate proportion to determine the overall impact of influenced behavior on the well-being of humans.

SemImput: Bridging Semantic Imputation with Deep Learning for Complex Human Activity Recognition.

The recognition of activities of daily living (ADL) in smart environments is a well-known and an important research area, which presents the real-time state of humans in pervasive computing. The process of recognizing human activities generally involves deploying a set of obtrusive and unobtrusive sensors, pre-processing the raw data, and building classification models using machine learning (ML) algorithms. Integrating data from multiple sensors is a challenging task due to dynamic nature of data sources.

iCBLS: An interactive case-based learning system for medical education.

Medical students should be able to actively apply clinical reasoning skills to further their interpretative, diagnostic, and treatment skills in a non-obtrusive and scalable way. Case-Based Learning (CBL) approach has been receiving attention in medical education as it is a student-centered teaching methodology that exposes students to real-world scenarios that need to be solved using their reasoning skills and existing theoretical knowledge. In this paper, we propose an interactive CBL System, called iCBLS, which supports the development of collaborative clinical reasoning skills for medical students in an online environment.

mlCAF: Multi-Level Cross-Domain Semantic Context Fusioning for Behavior Identification.

The emerging research on automatic identification of user's contexts from the cross-domain environment in ubiquitous and pervasive computing systems has proved to be successful. Monitoring the diversified user's contexts and behaviors can help in controlling lifestyle associated to chronic diseases using context-aware applications. However, availability of cross-domain heterogeneous contexts provides a challenging opportunity for their fusion to obtain abstract information for further analysis.

Ontology-Based High-Level Context Inference for Human Behavior Identification.

Recent years have witnessed a huge progress in the automatic identification of individual primitives of human behavior, such as activities or locations. However, the complex nature of human behavior demands more abstract contextual information for its analysis. This work presents an ontology-based method that combines low-level primitives of behavior, namely activity, locations and emotions, unprecedented to date, to intelligently derive more meaningful high-level context information.

Soluble transferrin receptors in malaria.

Objective: To determine the concentration of soluble transferrin receptors (sTfR) in patients with malaria.

Study Design: Cross-sectional, analytical study.

Place And Duration Of Study: Baqai Institute of Haematology, Baqai Medical University, Karachi, from December 2009 to April 2010.