Next-generation diabetes diagnosis and personalized diet-activity management: A hybrid ensemble paradigm.

Diabetes, a chronic metabolic condition characterised by persistently high blood sugar levels, necessitates early detection to mitigate its risks. Inadequate dietary choices can contribute to various health complications, emphasising the importance of personalised nutrition interventions. However, real-time selection of diets tailored to individual nutritional needs is challenging because of the intricate nature of foods and the abundance of dietary sources.

Investigating Seidel energies and thermodynamic properties of benzenoid hydrocarbons through regression models.

In this article, we present the concept of extended Seidel energy by employing a generalized extended matrix to study various molecular properties, including the Kovats retention index, boiling point, enthalpy of formation, entropy, acentric factor, and octanol-water partition coefficient. Our research broadens the scope of energy matrices in graph theory, with a particular emphasis on Sombor energy, reduced Sombor energy, average Sombor energy, Banhatti Sombor energy and reduced Banhatti Sombor energy. We examined the correlation of these graph-based energy descriptors with the thermodynamic properties of Benzenoid hydrocarbons (BHC), uncovering strong relationships between these indices and different molecular attributes.

m5c-iEnsem: 5-methylcytosine sites identification through ensemble models.

Motivation: 5-Methylcytosine (m5c), a modified cytosine base, arises from adding a methyl group at the 5th carbon position. This modification is a prevalent form of post-transcriptional modification (PTM) found in various types of RNA. Traditional laboratory techniques often fail to provide rapid and accurate identification of m5c sites.

Toward Efficient Hydrogen Generation Using Nickel-Molybdenum Catalyst and Its Environmental Sustainability.

In this study, a catalyst with Ni-Mo combination was synthesized using the electric heating/reductive tempering method. Nickel (II) nitrate hexahydrate and ammonium molybdate were combined in a ratio of 1.1 in this approach.

Smart Vision Transparency: Efficient Ocular Disease Prediction Model Using Explainable Artificial Intelligence.

The early prediction of ocular disease is certainly an obligatory concern in the domain of ophthalmic medicine. Although modern scientific discoveries have shown the potential to treat eye diseases by using artificial intelligence (AI) and machine learning, explainable AI remains a crucial challenge confronting this area of research. Although some traditional methods put in significant effort, they cannot accurately predict the proper ocular diseases.

Comparative Efficacy of Magnesium and Potassium Towards Cholesterol and Quality of Life in Patients With Type 2 Diabetes Mellitus: A Randomised Single-Blinded Controlled Clinical Trial.

Unlabelled: Previous studies exploring the relationship between dietary potassium and magnesium intake and the risk of type 2 diabetes mellitus (T2DM) have yielded inconsistent results.

Objective: The present study was designed to compare the effect of magnesium, potassium and both (potassium and magnesium combined) on cholesterol levels and quality of life (QoL) among patients with T2DM.

Methods: A randomised controlled trial (single blinded) was conducted at The University of Lahore and Lahore Medical Research Center (LMRC).

Ligand modelling of phytocompounds for cell wall synthesis enzyme in .

Aquaculture faces challenges from , causing Motile Aeromonas Septicaemia, particularly affecting (Rohu) in Pakistan. This study explores potential herbal antibacterials targeting , molecular docking of (ajwain) phytocompounds against pathogen. The cell wall synthesis ligase, D-alanine-D-alanine ligase (PDB ID 6ll9) was processed in BIOVIA Discovery Studio and docked with 13 antibacterial phytocompounds found after QSAR analysis of .

How to get green with agricultural footprint: A global analysis of carbon emissions, environmental taxes, and agrochemical use.

The agriculture sector, being highly vulnerable to climate change, plays a pivotal role in achieving green and sustainable economies. As the 2030 Agenda emphasizes the integrated development of environmental, social, and economic dimensions, it is crucial to understand how agricultural practices affect sustainability. This study investigates the environmental impact of the agricultural sector on the green economy by examining key environmental factors, such as agricultural energy emissions, environmental taxes, irrigated water use efficiency, fertilizer use, and pesticide application.

Political Economy of Maternal Child Malnutrition: Experiences about Water, Food, and Nutrition Policies in Pakistan.

This study examined access to water, food, and nutrition programs among marginalized communities in Southern Punjab, Pakistan, and their effects on nutrition. Both qualitative and quantitative data were used in this study. We held two focus group discussions (one with 10 males and one with 10 females) and conducted in-depth interviews with 15 key stakeholders, including 20 mothers and 10 healthcare providers.

-Mediated Biosynthesis of MnO Nanoparticles: Structural, Electrochemical, and Biological Investigations.

MnO nanoparticles (NPs) find diverse applications in the fields of medicine, biomedicine, biosensors, water treatment and purification, electronics, electrochemistry, and photoelectronics. The production of MnO NPs was reported earlier through various physical, chemical, and green routes, but no studies have still been performed on their biosynthesis from . We synthesized manganese oxide NPs, i.

A gene selection algorithm for microarray cancer classification using an improved particle swarm optimization.

Gene selection is an essential step for the classification of microarray cancer data. Gene expression cancer data (deoxyribonucleic acid microarray] facilitates in computing the robust and concurrent expression of various genes. Particle swarm optimization (PSO) requires simple operators and less number of parameters for tuning the model in gene selection.

Multidisciplinary cancer disease classification using adaptive FL in healthcare industry 5.0.

Emerging Industry 5.0 designs promote artificial intelligence services and data-driven applications across multiple places with varying ownership that need special data protection and privacy considerations to prevent the disclosure of private information to outsiders. Due to this, federated learning offers a method for improving machine-learning models without accessing the train data at a single manufacturing facility.

"An obedient wife never says "no" to her virtual god." High fertility conceptions and barriers to contraceptive use among mothers of Southern Pakistan: a qualitative study.

Issue: Biomedical approaches want to change locals' behaviors without understanding the sociocultural rationales and contextualizing the cultural and structural backdrop of women's agency.

Objectives: This study explored the perceptions and practices of rural mothers about fertility and reproductive health and further examine the lack of preference for contraception and birth spacing in Southern Pakistan.

Methodology: Using purposive sampling we recruited 15 healthcare providers and 20 mothers from Southern Punjab.

m5c-iDeep: 5-Methylcytosine sites identification through deep learning.

5-Methylcytosine (m5c) is a modified cytosine base which is formed as the result of addition of methyl group added at position 5 of carbon. This modification is one of the most common PTM that used to occur in almost all types of RNA. The conventional laboratory methods do not provide quick reliable identification of m5c sites.

A study of time-fractional model for atmospheric internal waves with Caputo-Fabrizio derivative.

The internal atmospheric waves are gravity waves and occur in the inner part of the fluid system. In this study, a time-fractional model for internal atmospheric waves is investigated with the Caputo-Fabrizio time-fractional differential operator. The analytical solution of the considered model is retrieved by the Elzaki Adomian decomposition method.

Methanolic extracts of litchi (Litchi chinensis Sonn.): A novel approach of targeting glucose-6-phosphate dehydrogenase for liver cancer therapy.

Cancer metabolism has emerged as a potential target for innovative therapeutic approaches in the treatment of cancer. Cancer metabolism has received much attention, particularly in relation to glucose metabolism. It has been observed that human malignancies have high levels of glucose-6-phosphate dehydrogenase (G6PD) activity which is an important enzyme of glucose metabolism.

Association among Household Wealth, Maternal Employment, and Undernutrition in Children under Three Years of Age in Pakistan.

Background: There is an abundance of studies explaining the separate impact of female employment and household wealth status in reducing malnutrition. However, our study has unraveled the combined impact of maternal employment and household wealth on undernutrition among children under three in Pakistan.

Methods: Using a sample of 1093 children under three years of age from the Pakistan Demographic and Health Survey 2017-2018, a binary logistic model was employed to gauge factors influencing the children's undernutrition.

Synthesis, antibacterial, antibiofilm, and docking studies of chalcones against multidrug resistance pathogens.

The escalating threat of drug-resistant microbes underscores the urgent need for novel antimicrobial agents. In response, considerable research effort has been directed towards developing innovative frameworks and strategies to address this challenge. Chalcones, known for their broad-spectrum biological activities, have emerged as promising candidates for combating drug resistance.

Correction to "Ion-Exchange Resin/Carrageenan-Copper-Based Nanocomposite: Artificial Neural Network, Advanced Thermodynamic Profiling, and Anticoagulant Studies".

[This corrects the article DOI: 10.1021/acsomega.4c01540.

Corn leaf disease: insightful diagnosis using VGG16 empowered by explainable AI.

The agricultural sector is pivotal to food security and economic stability worldwide. Corn holds particular significance in the global food industry, especially in developing countries where agriculture is a cornerstone of the economy. However, corn crops are vulnerable to various diseases that can significantly reduce yields.

Culinary Comfort: Understanding the Connection between Food and Well-Being.

This study investigated the complex interaction between individuals' culinary tastes, at-home dining habits, and their broader impact on general well-being and relationships dynamics. An all-encompassing tool for assessing the impact of dietary choices on emotions related to coziness, social interaction, and general wellness, the multidimensional Culinary Comfort and Connection Index (CCCI) focuses on traditional home-cooked meals, in particular. We used an online-based survey to validate the CCCI.

Prospective Roles of Extremophilic Fungi in Climate Change Mitigation Strategies.

Climate change and the resultant environmental deterioration signify one of the most challenging problems facing humankind in the 21st century. The origins of climate change are multifaceted and rooted in anthropogenic activities, resulting in increasing greenhouse gases in the environment and leading to global warming and weather drifts. Extremophilic fungi, characterized by their exceptional properties to survive extreme habitats, harbor great potential in mitigating climate change effects.