Knowledge, Attitude and Practices Towards Foot and Mouth Disease Among Farmers and Veterinary Practitioners in Selected Border Regions of Pakistan Adjoining to Afghanistan.

This study was conducted to look into the knowledge, attitudes and practices (KAP) of farmers, animal wholesalers and veterinary practitioners on foot and mouth disease (FMD) in the border area of Pakistan adjoining Afghanistan. Nearly half (41%) of the farmers understood the name of the disease or were aware of its incidence in their neighbourhood. The majority of farmers were able to identify the clinical signs (77.

Advancing the potential of nanoparticles for cancer detection and precision therapeutics.

Cancer poses a significant challenge with high death rate marked by heterogeneity, complexity, and resistance to available treatments, hence requiring creative approaches to improve early detection and precision medicines. Nanoparticles (NPs) exhibit distinctive physicochemical characteristics, including a high surface area-to-volume ratio, adjustable size and shape, and multifunctionality. This review paper critically explored the recent advancements in various NPs, such as graphene-based materials (to overcome cancer resistance and for diagnostic and therapeutics applications), metal organic frameworks (precised and targeted release of drug, e.

Diagnosis of cancer in the South and North of Nigeria: duration and causes of delay.

Introduction: Nigeria has a growing cancer burden, with late presentation and delayed diagnosis contributing to poor outcomes. We explored the durations and causes of the delay in the diagnosis of four common and treatable cancer types (breast, colorectum, head and neck, and uterine cervix) in Nigeria.

Methods: Retrospective study based on interviews with cancer patients following the Aarhus framework for designing and reporting such studies.

Vitamin C in Sepsis: Exploring Its Role in Modulating Inflammation and Oxidative Stress.

Background Despite improvements in medical treatment, sepsis remains a deadly illness with high fatality rates that is characterized by excessive inflammation and oxidative stress. Objective This study aimed to evaluate the impact of vitamin C supplementation on inflammatory response, oxidative stress, and clinical outcomes in sepsis patients. Methodology A prospective observational study was conducted over one year at Lady Reading Hospital, Peshawar, including 326 adult sepsis cases meeting the Sepsis-3 criteria.

Legendre based neural networks integrated with heuristic algorithms for the analysis of Lorenz chaotic model: an intelligent and comparative study.

The optimal control methods for managing Lorenz model are achieved using an innovative intelligent computing framework that integrates artificial neural networks with stochastic unsupervised learning-based optimizers, specifically Firefly (FA) and Archimedes algorithm (AOA). The hyper parameters (weights & biases) of unsupervised neural networks are refined through Legendre polynomials Artificial Neural Networks (LENN) optimized with global search techniques, including FA-AOA collectively referred to as LENN-FA-AOA. This design approach is employed to Lorenz model across three (3) different scenarios using various step sizes and input intervals.

Rhino-Orbital Mucormycosis in a Postpartum Diabetic Patient: An Atypical Presentation of Oral Ulcers and Facial Swelling.

Mucormycosis is a rare, life-threatening fungal infection primarily affecting immunocompromised individuals, particularly those with poorly controlled diabetes mellitus. This case report presents a 40-year-old female with a decade-long history of uncontrolled type 2 diabetes who developed progressively worsening oral ulcers, facial swelling, and vomiting, following a recent stillbirth. The patient exhibited extensive necrotic lesions involving the nose, oropharynx, and soft palate, leading to a high suspicion of invasive fungal infection.

Design of a novel noise resilient algorithm for fault detection in wind turbines on supervisory control and data acquisition system.

Wind turbine faults, including electrical, mechanical or aerodynamics-related, can potentially reduce operational efficiency, causing downtimes or, in some cases, leading to severe damage. Hence, timely detection of these operational anomalies is crucial for optimizing performance and reducing maintenance costs. The following study explores the application of Supervisory Control and Data Acquisition (SCADA) data for fault detection and diagnosing different operational states in wind turbines by focusing on environmental and operational factors which affect the performance.

Comparison Between the In-Hospital Outcomes of Patients Presented With Acute Anterior Wall ST-Segment Elevation Myocardial Infarction With and Without a Right Bundle Branch Block.

Background: Although a right bundle branch block (RBBB) complicates anterior wall ST-segment elevation myocardial infarction (AW-STEMI), its independent prognostic significance remains understudied.

Material And Method: This cross-sectional observational study was conducted at the Punjab Institute of Cardiology, Lahore, over a period of 18 months from January 2022 to June 2023. A total of 349 patients presenting with acute AW-STEMI were enrolled.

Health Care Professional Adherence to Breast Cancer Management Guidelines in Nigeria.

Importance: In Nigeria, 80% of breast cancer is diagnosed at an advanced stage, when clinical management is complex and necessitates multidisciplinary collaboration. The Nigerian Federal Ministry of Health promotes multidisciplinary tumor board (MDT) discussions and endorses the National Comprehensive Cancer Network Harmonized Guidelines for Sub-Saharan Africa (Harmonized Guidelines) to standardize breast cancer care, but the extent of their clinical utilization is not well understood.

Objective: To identify barriers to and facilitators of the standardization of breast cancer care in Nigeria as reflected by awareness and consultation of resource-adapted guidelines.

Meteorological drought and long-term trends and spatial variability of rainfall in the Niger River Basin, Nigeria.

In sub-Saharan Africa, rainfall is crucial for the livelihood of the population. This study aims to assess meteorological drought and long-term trends and spatial variability of rainfall in the Niger River Basin, Nigeria. This study employed the Bayesian estimator of abrupt change, seasonality, and trend (BEAST), Mann‒Kendall (MK), modified Mann‒Kendall (MMK) test, seasonal Mann‒Kendall (SMK) test, and innovative trend analysis (ITA) to analyze seasonal and annual rainfall trends in the Niger River Basin (NRB).

Context aware machine learning techniques for brain tumor classification and detection - A review.

Background: Machine learning has tremendous potential in acute medical care, particularly in the field of precise medical diagnosis, prediction, and classification of brain tumors. Malignant gliomas, due to their aggressive growth and dismal prognosis, stand out among various brain tumor types. Recent advancements in understanding the genetic abnormalities that underlie these tumors have shed light on their histo-pathological and biological characteristics, which support in better classification and prognosis.

Toxicity and Sublethal Effect of Chlorantraniliprole on Multiple Generations of L. (Diptera: Culicidae).

Due to the quick development of insecticide resistance, it is crucial to optimize management programs by understanding the sublethal effects of effective insecticides like chlorantraniliprole on L. populations. Using age-stage and two-sex life tables, we investigated the sublethal impacts of chlorantraniliprole on .

A systematic quantitative approach comprehensively defines domain-specific functional pathways linked to Schizosaccharomyces pombe heterochromatin regulation.

Heterochromatin plays a critical role in regulating gene expression and maintaining genome integrity. While structural and enzymatic components have been linked to heterochromatin establishment, a comprehensive view of the underlying pathways at diverse heterochromatin domains remains elusive. Here, we developed a systematic approach to identify factors involved in heterochromatin silencing at pericentromeres, subtelomeres and the silent mating type locus in Schizosaccharomyces pombe.

Development and Piloting of Implementation Strategies to Support Delivery of a Clinical Intervention for Postpartum Hemorrhage in Four sub-Saharan Africa Countries.

Introduction: Postpartum hemorrhage (PPH) remains the leading cause of maternal mortality. A new clinical intervention (E-MOTIVE) holds the potential to improve early PPH detection and management. We aimed to develop and pilot implementation strategies to support uptake of this intervention in Kenya, Nigeria, South Africa, and Tanzania.

Surface modification of graphene and fullerene with Sulfur (S), Selenium (Se), and Oxygen (O): DFT Simulation for enhanced zidovudine delivery in HIV treatment.

HIV is one of the most threatening health conditions with a highly increasing rate, affecting millions of people globally, and from its time of discovery until now, its potential cure cannot be explicitly defined. This challenge of having no/low effective drugs for the subjected virus has called for serious attention in the scientific world of virus disease therapeutics. Most of these drugs yields low effectiveness due to poor delivery; hence, there is a need for novel engineering methods for efficient delivery.

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.

Optimizing solar power efficiency in smart grids using hybrid machine learning models for accurate energy generation prediction.

The fourth energy revolution is characterized by the incorporation of renewable energy supplies into intelligent networks. As the world is shifting towards cleaner energy sources, there is a need for efficient and reliable methods to predict the output of renewable energy plants. Hybrid machine learning modified models are emerging as a promising solution for energy generation prediction.

Microwave seed priming and ascorbic acid assisted phytoextraction of heavy metals from surgical industry effluents through spinach.

The prevalence of inorganic pollutants in the environment, including heavy metals (HMs), necessitates a sustainable and cost-effective solution to mitigate their impacts on the environment and living organisms. The present research aimed to assess the phytoextraction capability of spinach (Spinach oleracea L.), under the combined effects of ascorbic acid (AA) and microwave (MW) irradiation amendments, cultivated using surgical processing wastewater.

Comprehensive Quality Analysis of Conventional and Novel Biomarkers in Diagnosing and Predicting Prognosis of Coronary Artery Disease, Acute Coronary Syndrome, and Heart Failure, a Comprehensive Literature Review.

Coronary artery disease (CAD), acute coronary syndrome (ACS), and heart failure (HF) are major global health issues with high morbidity and mortality rates. Biomarkers like cardiac troponins (cTn) and natriuretic peptides (NPs) are crucial tools in cardiology, but numerous new biomarkers have emerged, proving increasingly valuable in CAD/ACS. These biomarkers are classified based on their mechanisms, such as fibrosis, metabolism, inflammation, and congestion.

Realized heritability, inheritance, and mechanism of chlorfenapyr resistance in biocontrol agent, Chrysoperla carnea (Stephens) (Neuroptera: Chrysopidae): A step towards sustainable pest management.

A field population of Chrysoperla carnea was exposed for 17 generations to chlorfenapyr insecticide that resulted in 217-fold resistance compared to a susceptible strain. The overlapping of LC values in reciprocal crosses and their dominance values indicated that chlorfenapyr resistance was autosomal and incompletely dominant. The chi-square analysis of back-cross mortality confirmed the polygenic nature of chlorfenapyr resistance.

The Pathogenesis of Foot-and-Mouth Disease Virus Infection: How the Virus Escapes from Immune Recognition and Elimination.

Foot-and-mouth disease virus (FMDV) is a highly contagious and economically devastating pathogen that affects cloven-hoofed animals worldwide. FMDV infection causes vesicular lesions in the mouth, feet, and mammary glands, as well as severe systemic symptoms such as fever, salivation, and lameness. The pathogenesis of FMDV infection involves complex interactions between the virus and the host immune system, which determine the outcome of the disease.

Foot-and-mouth disease seroprevalence is higher in young female crossbred sheep and goats compared to their counterparts in the border area between Pakistan and Afghanistan.

Objective: Foot-and-mouth disease (FMD) is a highly contagious disease in ruminants that causes significant economic losses worldwide. However, the prevalence of FMD virus (FMDV) in small ruminants has been overlooked in Pakistan. This study aimed to determine the prevalence of FMD in sheep and goats in the border area between Pakistan and Afghanistan.