Incidence of postoperative cerebrospinal fluid leaks in endoscopic endonasal transsphenoidal surgery for pituitary adenomas without sellar floor reconstruction: A retrospective observational study from a low-middle-income country.

Objectives: To determine the incidence of postoperative cerebrospinal fluid (CSF) leaks after endoscopic endonasal transsphenoidal surgery (EETS) for pituitary adenomas without sellar floor reconstruction (SFR).

Methods: This retrospective observational study was conducted at Department of Neurosurgery, Punjab Institute of Neurosciences (PINS), Lahore, Pakistan from January, 2018 to December, 2022. It is a non-probability based consecutive case series.

Novel approach for Arabic fake news classification using embedding from large language features with CNN-LSTM ensemble model and explainable AI.

The widespread fake news challenges the management of low-quality information, making effective detection strategies necessary. This study addresses this critical issue by advancing fake news detection in Arabic and overcoming limitations in existing approaches. Deep learning models, Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM), EfficientNetB4, Inception, Xception, ResNet, ConvLSTM and a novel voting ensemble framework combining CNN and LSTM are employed for text classification.

Implications of the Gut Microbiome in Alzheimer's Disease: A Narrative Review.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder, with its prevalence doubling approximately every decade. It is a significant contributor to disability-adjusted life-years in individuals aged 50 and older, impacting a substantial portion of this population globally. The pathophysiology of AD is primarily explained by two hypotheses: the amyloid cascade hypothesis and the tau hypothesis.

TRI-POSE-Net: Adaptive 3D human pose estimation through selective kernel networks and self-supervision with trifocal tensors.

Accurate and flexible 3D pose estimation for virtual entities is a strenuous task in computer vision applications. Conventional methods struggle to capture realistic movements; thus, creative solutions that can handle the complexities of genuine avatar interactions in dynamic virtual environments are imperative. In order to tackle the problem of precise 3D pose estimation, this work introduces TRI-POSE-Net, a model intended for scenarios with limited supervision.

Case 331: Cardiac Sarcoidosis.

A 43-year-old male patient with no known past medical history presented to the emergency department with new-onset bitemporal headache, dizziness, and bilateral lower extremity weakness for 1 day. The patient denied chest pain, shortness of breath, cough, or recent exposure to sick individuals. He was not on any medications and denied alcohol or illicit drug use.

Early detection of autism spectrum disorder using explainable AI and optimized teaching strategies.

Autism spectrum disorder (ASD) is defined by the deficits of social relating, language, object use and understanding, intelligence and learning, and verbal and nonverbal communication. Most of the individuals with ASD have genetic conditions; however, early identification and intervention reduce the use of health services and other diagnostic procedures. The varied nature of ASD is widely acknowledged, with each affected individual displaying distinct traits.

BrainNet: an automated approach for brain stress prediction utilizing electrodermal activity signal with XLNet model.

Brain stress monitoring has emerged as a critical research area for understanding and managing stress and neurological health issues. This burgeoning field aims to provide accurate information and prediction about individuals' stress levels by analyzing behavioral data and physiological signals. To address this emerging problem, this research study proposes an innovative approach that uses an attention mechanism-based XLNet model (called BrainNet) for continuous stress monitoring and stress level prediction.

Data-centric automated approach to predict autism spectrum disorder based on selective features and explainable artificial intelligence.

Autism spectrum disorder (ASD) is a neurodevelopmental condition marked by notable challenges in cognitive function, understanding language, recognizing objects, interacting with others, and communicating effectively. Its origins are mainly genetic, and identifying it early and intervening promptly can reduce the necessity for extensive medical treatments and lengthy diagnostic procedures for those impacted by ASD. This research is designed with two types of experimentation for ASD analysis.

LesionNet: an automated approach for skin lesion classification using SIFT features with customized convolutional neural network.

Accurate detection of skin lesions through computer-aided diagnosis has emerged as a critical advancement in dermatology, addressing the inefficiencies and errors inherent in manual visual analysis. Despite the promise of automated diagnostic approaches, challenges such as image size variability, hair artifacts, color inconsistencies, ruler markers, low contrast, lesion dimension differences, and gel bubbles must be overcome. Researchers have made significant strides in binary classification problems, particularly in distinguishing melanocytic lesions from normal skin conditions.

Violet light transmission through eyeglasses and its effects on myopic children: A systematic review and meta-analysis.

Purpose: Myopia is a refractive error that impairs visual function and leads to visual blurring. This study aims to investigate the effect of violet light (VL) on controlling myopia, specifically in terms of axial length (AL), spherical equivalent refraction (SER), and visual acuity (VA).

Methods: A systematic review was conducted to compare VL and single-vision spectacles (SVSs) for treating childhood myopia.

Mutational analysis of cytoplasmic domain of integrin subunit alpha-1 and its association with periapical wound healing after surgical endodontic treatment.

Background: Numerous studies reported that the healing after surgical endodontic retreatment is influenced by multiple factors which include the genetic profile of the patient, epigenetics, and immune responses. The genes which are primarily responsible for the healing potential in different individuals are those which are involved in the regulation of the cytoskeleton and cellular adhesion which subsequently affects bone deposition and healing. Integrins are cell-surface molecules, possess a key role in the cytoskeleton and cellular adhesion.

Artificial intelligence-driven predictive framework for early detection of still birth.

Predictive modeling is becoming increasingly popular in the context of early disease detection. The use of machine learning approaches for predictive modeling can help early detection of diseases thereby enabling medical experts to appropriate medical treatments. Stillbirth prediction is a similar domain where artificial intelligence-based predictive modeling can alleviate this significant global health challenge.

Genome-wide association study reveals the genetic basis of amino acids contents variations in Peanut (Arachis hypogaea L.).

Peanut is a significant source of protein for human consumption. One of the primary objectives in peanut breeding is the development of new cultivars with enhanced nutritional values. To further this goal, a genome-wide association study (GWAS) was conducted to analyze seed amino acids contents in 390 diverse peanut accessions collected worldwide, mainly from China, India, and the United States, in 2017 and 2018.

An automated approach to predict diabetic patients using KNN imputation and effective data mining techniques.

Diabetes is thought to be the most common illness in underdeveloped nations. Early detection and competent medical care are crucial steps in reducing the effects of diabetes. Examining the signs associated with diabetes is one of the most effective ways to identify the condition.

Sustainable development goals and green human resource management: A comprehensive review of environmental performance.

Sustainable development goals and rising sustainability concerns push stakeholders and society to demand organizations adopt innovative practices that can contribute to business sustainability. This study aims to provide a systematic review through comprehensive bibliometric analysis of almost 1st quarter of the 21st century. The main focus is on how green human resource management practices promote and have a relationship with environmental performance, which is a significant part of sustainability.

Prevalence and associated factors of non-adherence to antihyperlipidemic medication: a nationwide cross sectional survey in Pakistan.

Hyperlipidemia significantly contributes to the risk of developing cardiovascular diseases. However, about half of the patients do not adhere to their antihyperlipidemic medications, leading to healthcare costs and premature mortality. This study's objective was to determine the prevalence and associated factors of non-adherence to antihyperlipidemic medications.

Successful bone marrow transplantation in a patient with Omenn syndrome, a rare variant of severe combined immunodeficiency syndrome: A case report.

Key Clinical Message: Bone marrow transplantation (BMT) saves lives in Omenn syndrome, a severe immunodeficiency disorder. Timely genetic diagnosis and matched donor BMT are crucial. Emphasis on newborn screening and multidisciplinary care improves outcomes for infants with inherited disorders.

Corrigendum: Characterization of a novel mitovirus infecting isolated from tea plants.

[This corrects the article DOI: 10.3389/fmicb.2021.

Case 331.

A 43-year-old male patient with no known past medical history presented to the emergency department with new-onset bitemporal headache, dizziness, and bilateral lower extremity weakness for 1 day. The patient denied chest pain, shortness of breath, cough, or recent exposure to sick individuals. He was not on any medications and denied alcohol or illicit drug use.

Genetic Analysis of Cotton Fiber Traits in Gossypium Hybrid Lines.

Cotton plays a crucial role in the progress of the textile industry and the betterment of human life by providing natural fibers. In our study, we explored the genetic determinants of cotton architecture and fiber yield and quality by crossbreeding Gossypium hirsutum and Gossypium barbadense, creating a recombinant inbred line (RIL) population. Utilizing SNP markers, we constructed an extensive genetic map encompassing 7,730 markers over 2,784.

Translation and psychometric properties of the Arabic version of the ageism scale for dental students (ASDS-Ar): A multi-institutional validation.

Background And Objective: Ageism represents an important barrier to high-quality healthcare for older adults. The present study sought to translate and validate the Arabic version of the Ageism Scale for Dental Students (ASDS-Arabic).

Materials And Methods: The 27-item ASDS tool was translated from English into Arabic following recommended cross-sectional forward and backward translation guidelines.