Difficulty in financing fracture care in south-western Nigeria: a prospective cohort study of predictors and recommendations for improvement.

Background: Bone fractures remain a significant global public health issue despite preventive measures, leading to substantial health and economic consequences. Effective treatment options are difficult to access in most sub-Saharan African countries, leading to reliance on unqualified practitioners and resulting in serious complications that worsen poverty. In Nigeria, the main challenge is the need for out-of-pocket payment for healthcare, which is the primary method of health financing.

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.

Impact of Malnutrition on Serum Levels of Pro-inflammatory Cytokines among Plasmodium falciparum Malaria Subjects in Nigeria.

Background: Understanding the impact of malnutrition on innate immune response in Plasmodium falciparum (Pf)-infected subjects is critical for malaria control.

Aims And Objectives: This study aims to investigate the nutritional status and innate immune response of Pf-infected subjects in Lagos, Nigeria.

Materials And Methods: A total of 1183 patients with a history of fever or axillary temperature ≥37°C were screened microscopically for Pf at Ijede General Hospital, Lagos, Nigeria.

Prevalence and Factors Associated With Awareness of Precision Medicine Among Individuals With Depression and Anxiety.

Objective: This study investigates the prevalence and determinants of awareness of precision medicine among a nationally representative sample of individuals with self-reported depression and anxiety in the United States."

Methods: Data were obtained from the Health Information National Trends Survey (HINTS) 5, Cycle 4, which is a study administered by the National Cancer Institute and is nationally representative. The survey, conducted between February and June 2020, targeted non-institutionalized, civilian US adults aged 18 years and older.

Reamed intramedullary nailing of diaphyseal multifragmentary femur fractures (AO/OTA 32-C) without fluoroscopy guidance: prospective analysis of methods and short-term outcomes in a low-resource setting.

Purpose: To describe the methods and outcomes of reamed intramedullary nailing (IMN) of diaphyseal multifragmentary femur (AO/OTA C2 and C3) fractures (DMFFs) in a low-resource setting without fluoroscopy and fracture table.

Methods: The prospective study involved 35 DMFFs among 318 femur fractures treated ≤ 3 weeks post-injury with SIGN nails. The fractures were fixed without fluoroscopy, fracture table and power reaming.

SS-DRPL: self-supervised deep representation pattern learning for voice-based Parkinson's disease detection.

Parkinson's disease (PD) is a globally significant health challenge, necessitating accurate and timely diagnostic methods to facilitate effective treatment and intervention. In recent years, self-supervised deep representation pattern learning (SS-DRPL) has emerged as a promising approach for extracting valuable representations from data, offering the potential to enhance the efficiency of voice-based PD detection. This research study focuses on investigating the utilization of SS-DRPL in conjunction with deep learning algorithms for voice-based PD classification.

TSSG-CNN: A Tuberculosis Semantic Segmentation-Guided Model for Detecting and Diagnosis Using the Adaptive Convolutional Neural Network.

Tuberculosis (TB) is an infectious disease caused by Mycobacterium. It primarily impacts the lungs but can also endanger other organs, such as the renal system, spine, and brain. When an infected individual sneezes, coughs, or speaks, the virus can spread through the air, which contributes to its high contagiousness.

A novel interpretable machine learning model approach for the prediction of TiO photocatalytic degradation of air contaminants.

Air contaminants lead to various environmental and health issues. Titanium dioxide (TiO) features the benefits of autogenous photocatalytic degradation of air contaminants. To evaluate its performance, laboratory experiments are commonly used to determine the kinetics of the photocatalytic-degradation rate, which is labor intensive, time-consuming, and costly.

Assessment of human health risk concerning edible plants contamination with toxic elements around functional and derelict mines.

Edible plants samples were analysed for non-carcinogenic and carcinogenic human health risks. The elements nickel (Ni), cadmium (Cd), arsenic (As), lead (Pb), chromium (Cr) and mercury (Hg) analysed using atomic absorption spectrophotometer (AAS). The recovery, limit of detection (LOD) and limit of quantification (LOQ) ranged from 75 to 89 %, 0.

HO-SsNF: heap optimizer-based self-systematized neural fuzzy approach for cervical cancer classification using pap smear images.

Cervical cancer is a significant concern for women, necessitating early detection and precise treatment. Conventional cytological methods often fall short in early diagnosis. The proposed innovative Heap Optimizer-based Self-Systematized Neural Fuzzy (HO-SsNF) method offers a viable solution.

Body image perception and social support as predictors of psychological distress among third trimester pregnant women in Nigeria.

Background: Body image perception and social support during pregnancy can impact the psychological distress levels experienced by pregnant women. As a result, the purpose of this study was to examine the relationship between various components of social support and body image perception on psychological distress levels among pregnant women in their third trimester in Nigeria.

Method: A cross-sectional study was conducted among 246 pregnant women who were in the third trimester and attending selected health care facilities in Ogbomoso, a semiurban city in Oyo State, Nigeria.

Workplace Productivity, Health and Wellbeing: Findings From a Cluster Randomised Controlled Trial of a Workplace Intervention to Reduce Sitting in Office Workers.

Objective: The aim of the study was to evaluate the feasibility and potential effects of a workplace intervention to reduce and break up sitting.

Methods: Office workers were randomized in clusters to intervention ( n = 22) or control ( n = 22). The intervention included a height-adjustable workstation, education, computer prompt software, and line manager support.

Ensuring Continuity of Care: Effective Strategies for the Post-hospitalization Transition of Psychiatric Patients in a Family Medicine Outpatient Clinic.

In healthcare, continuity of care is a crucial element, especially for patients in the field of psychiatry who have recently been discharged from a hospital. The shift from inpatient to outpatient care poses challenges for patients and healthcare providers, including openness to treatment, competing priorities, financial insecurity, concerns and dilemmas faced by patients regarding their post-hospitalization life after improvements in symptoms, lack of social support, poor patient-doctor relationships, lack of insight, and stigma associated with mental illness. Therefore, it is vital to employ effective strategies to ensure patients receive the required care and support during this transition.

Artificial intelligence framework for heart disease classification from audio signals.

As cardiovascular disorders are prevalent, there is a growing demand for reliable and precise diagnostic methods within this domain. Audio signal-based heart disease detection is a promising area of research that leverages sound signals generated by the heart to identify and diagnose cardiovascular disorders. Machine learning (ML) and deep learning (DL) techniques are pivotal in classifying and identifying heart disease from audio signals.

Retrograde intramedullary nailing with supplemental plate and lag screws allows early weight bearing following distal end-segment femur fractures (AO/OTA 33) in a low-resource setting.

Purpose: To underline the feasibility of achieving early weight bearing in patients with distal end-segment femur fractures (AO/OTA 33) treated with retrograde intramedullary nailing and supplemental plate or lag screws in the absence of C-arm.

Methods: 41 distal end-segment femur fractures (DFFs) included in the study were treated with SIGN nails with or without a side plate in a center that lacked intraoperative fluoroscopy and fracture table. A medial or lateral para-patellar incision was used for fracture reduction, nail insertion and side plate placement.

Evaluating deep learning variants for cyber-attacks detection and multi-class classification in IoT networks.

The Internet of Things (IoT), considered an intriguing technology with substantial potential for tackling many societal concerns, has been developing into a significant component of the future. The foundation of IoT is the capacity to manipulate and track material objects over the Internet. The IoT network infrastructure is more vulnerable to attackers/hackers as additional features are accessible online.

The growth of Ge and direct bandgap GeSn on GaAs (001) by molecular beam epitaxy.

Germanium tin (GeSn) is a tuneable narrow bandgap material, which has shown remarkable promise for the industry of near- and mid-infrared technologies for high efficiency photodetectors and laser devices. Its synthesis is challenged by the lattice mismatch between the GeSn alloy and the substrate on which it is grown, sensitively affecting its crystalline and optical qualities. In this article, we investigate the growth of Ge and GeSn on GaAs (001) substrates using two different buffer layers consisting of Ge/GaAs and Ge/AlAs molecular beam epitaxy.

Follow-up non-attendance after long-bone fractures in a low-resource setting: a prospective study of predictors and interventions to increase attendance rates.

Background: While the majority of traumatic injuries occur in low- and middle-income countries, the published literature comes chiefly from high-income countries due to poor follow-up. Clinical and radiographic post-surgical trauma follow-up is essential to high-quality research and objective monitoring for healing and/or complications. This study aimed to identify the predictors of follow-up non-attendance in a low-resource setting and investigate the extent to which interventional efforts based on mobile phone technology (MPT) and home visits improved the follow-up rates for fractures treated with SIGN nails.

Unveiling contextual influences of maternal satisfaction with labour care services in Nigeria: A qualitative inquiry.

Background: In light of the rising global effort to lower maternal mortality rates, it is crucial for low- and middle-income countries with poor maternal indices to investigate the problem of maternal satisfaction and the key elements that affect it. To this effect, this study explored the experiences of postnatal women in relation to labour services and investigated the factors that contribute to their overall satisfaction.

Aim: The study set out to explore factors influencing maternal satisfaction with labour care services in Ogbomoso, Oyo State, Nigeria.

Study of all-group-IV SiGeSn mid-IR lasers with dual wavelength emission.

Direct band gap GeSn alloys have recently emerged as promising lasing source materials for monolithic integration on Si substrate. In this work, optically pumped mid-infrared GeSn lasers were studied with the observation of dual-wavelength lasing at 2187 nm and 2460 nm. Two simultaneous lasing regions include a GeSn buffer layer (bulk) and a SiGeSn/GeSn multiple quantum well structure that were grown seamlessly using a chemical vapor deposition reactor.

Geochemical modeling and hydrochemical analysis for water quality determination around mine drainage areas.

Water sources in mining areas do not retain their natural quality due to the influence of mine drainage. Water quality test was through hydrochemical analysis, speciation modeling, and saturation indices. Water samples were analyzed for pH, conductivity, nitrate, phosphate, sulfate, chlorite, sodium, magnesium, calcium, turbidity, total hardness, lead, zinc, iron, copper, cadmium, manganese, nickel, and chromium.

A Cross-Sectional Study of the Trends in Cardiovascular Mortality Among African Americans With Hypertension.

Background and Objective In the United States, hypertension remains a significant cause of cardiovascular disease mortality and morbidity, affecting various racial and ethnic groups. High blood pressure is a common health concern, given its high frequency among all populations and racial groups in the United States; nevertheless, the condition remains untreated in most individuals. It affects a significant number of individuals in the African American community and contributes to a notable proportion of deaths.

Assessing the Relationship Between Health Information Technology Use and Self-Rated Health Among Adults with Chronic Low Back Pain in the United States.

Objective: To assess the use of health information technology (HIT) among adults with chronic low back pain (CLBP) in the United States and to evaluate the relationship between HIT use and self-rated health.

Methods: The independent variable was the use of the internet to (1) fill prescriptions, (2) communicate with a healthcare provider, (3) look up health information, and (4) schedule a medical appointment. Respondents rated their health in the last 12 months as worse, about the same, or better.