AneRBC dataset: a benchmark dataset for computer-aided anemia diagnosis using RBC images.

Visual analysis of peripheral blood smear slides using medical image analysis is required to diagnose red blood cell (RBC) morphological deformities caused by anemia. The absence of a complete anaemic RBC dataset has hindered the training and testing of deep convolutional neural networks (CNNs) for computer-aided analysis of RBC morphology. We introduce a benchmark RBC image dataset named Anemic RBC (AneRBC) to overcome this problem.

Effects of ALA-PDT on the murine footpad model of Fonsecaea monophora infection and its related mechanisms in vivo.

Background: 5-aminolevulinic acid photodynamic therapy (ALA-PDT) has received growing attention for treating chromoblastomycosis (CBM) and has shown efficacy in a handful of clinical case reports. However, there is insufficient information regarding the effects of ALA-PDT on Fonsecaea monophora in mouse infection model and the related mechanisms. This study investigated these issues in vivo.

Cerebrovascular damage caused by the gut microbe/host co-metabolite -cresol sulfate is prevented by blockade of the EGF receptor.

The gut microbiota-brain axis has been associated with the pathogenesis of numerous disorders, but the mechanism(s) underlying these links are generally poorly understood. Accumulating evidence indicates the involvement of gut microbe-derived metabolites. Circulating levels of the gut microbe/host co-metabolite -cresol sulfate (pCS) correlate with cerebrovascular event risk in individuals with chronic kidney disease (CKD), but whether this relationship is mechanistic is unclear.

Evaluation of the Neuroprotective Effect of Total Glycosides of and Investigation of Novel Brain-Targeting Natural MAO-B Inhibitors.

In this study, we investigated the role of total glycosides of (TC) in MPTP-induced neuronal injury. Further, we screened potential inhibitory components of monoamine oxidase B (MAO-B). The study results indicate that TC may improve movement disorders and apoptosis of dopamine (DA) neurons by inhibiting MAO-B activity while reducing the number of glial cells, adjusting the metabolism level of monoamine neurotransmitters, and lowering inflammation and oxidative stress levels.

Antileishmanial potential of thiourea-based derivatives: design, synthesis and biological activity.

Leishmaniasis is a neglected tropical disease caused by protozoan parasites and transmitted to humans by the sandfly vector. Currently, the disease has limited therapeutic alternatives. Thiourea derivatives were designed, synthesized, and screened for antileishmanial activity.

Coated cysteamine and choline chloride could be potential feed additives to mitigate the harmful effects of fatty liver hemorrhagic syndrome in laying hens caused by high-energy low-protein diet.

The research aimed to examine the impact of coated cysteamine (CS) and choline chloride (CC) on relieving the pathological effects of fatty liver hemorrhagic syndrome (FLHS) in laying hens. FLHS was induced by a high-energy low-protein (HELP) diet. Ninety laying hens were equally divided into 5 treatments with 6 replicates per treatment (3 hens/replicate).

Peripheral intravenous catheter-induced phlebitis in a tertiary hospital of Karachi: a cohort study.

Purpose: This study aimed to determine the incidence of peripheral intravenous catheter (PIVC)-induced phlebitis and its predictors among adult patients hospitalized at Dow University Hospital, Karachi, Pakistan.

Methods: A sample of 258 adult patients admitted in the selected wards and planned for peripheral intravenous catheter insertion were recruited through consecutive sampling during March to May 2019. Daily follow-ups were performed to observe signs of phlebitis using a validated tool.

Dietary supplementation of protease and organic acid in poultry by-product meal-based diet in broilers.

Objective: This study investigated the impact of supplementation of protease and organic acid on growth performance and other biological parameters in broilers fed poultry byproduct meal (PBM) based diet.

Methods: Five hundred 1-day-old broiler chicks (Ross 308) were distributed into five treatments with 5 replicates, each pen having 20 birds, and fed each group one of five isocaloric and isonitrogenous diets in two phases: stater phase (1 to 21 days) metabolizable energy (ME) 3000 kcal/kg; crude protein (CP) 22%, and a finisher phase (22 to 35 days) ME 3,200 kcal/kg; CP 19.5%.

A Cutaneous Phaeohyphomycosis Case Caused by in Southern China.

is a coelomycetous fungus species that was recently identified. We present a case of an elderly farmer with chronic skin lesions of the opisthenar caused by .

Gender and its association with cardiac defects in down syndrome population at Children Hospital & Institute of Child Health, Lahore, Pakistan.

Objective: The objective of this study was to determine the frequency of different congenital cardiac defects co-existing in karyotypically proved Down syndrome population. It also highlighted the association between gender and pattern of congenital cardiac defects and gender as a risk factor.

Methods: A cross sectional comparative study was done in the Department of Genetics, Children Hospital Lahore in the year 2017.

Patient Safety Culture: A Healthcare Provider's Prospect.

Introduction And Objective: Safe care is a challenge around the globe, especially in developing countries. In resource-limited settings achieving patient safety is an additional complexity. Patient safety is now considered a significant public health concern worldwide.

Coated cysteamine, a potential feed additive for ruminants - An updated review.

For sustainable development, better performance, and less gas pollution during rumen fermentation, there is a need to find a green and safe feed additive for ruminants. Cysteamine (CS) is a biological compound naturally produced in mammalian cells. It is widely used as a growth promoter in ruminants because of its ability to control hormone secretions.

Frequency of dysnatremia in patients admitted with COVID-19 infection and its prognostic implication.

Objective: We aimed to investigate the frequency of dysnatremia among patients admitted with COVID-19 infection and its association with inpatient mortality.

Methods: This retrospective longitudinal study was conducted for 12 weeks. Serum sodium levels were recorded at admission, during the hospital stay, and within 48 hours of discharge or death.

Evidence of a causal and modifiable relationship between kidney function and circulating trimethylamine N-oxide.

The host-microbiota co-metabolite trimethylamine N-oxide (TMAO) is linked to increased cardiovascular risk but how its circulating levels are regulated remains unclear. We applied "explainable" machine learning, univariate, multivariate and mediation analyses of fasting plasma TMAO concentration and a multitude of phenotypes in 1,741 adult Europeans of the MetaCardis study. Here we show that next to age, kidney function is the primary variable predicting circulating TMAO, with microbiota composition and diet playing minor, albeit significant, roles.

Asynchronous Federated Learning for Improved Cardiovascular Disease Prediction Using Artificial Intelligence.

Healthcare professionals consider predicting heart disease an essential task and deep learning has proven to be a promising approach for achieving this goal. This research paper introduces a novel method called the asynchronous federated deep learning approach for cardiac prediction (AFLCP), which combines a heart disease dataset and deep neural networks (DNNs) with an asynchronous learning technique. The proposed approach employs a method for asynchronously updating the parameters of DNNs and incorporates a temporally weighted aggregation technique to enhance the accuracy and convergence of the central model.

Privacy-Aware Collaborative Learning for Skin Cancer Prediction.

Cancer, including the highly dangerous melanoma, is marked by uncontrolled cell growth and the possibility of spreading to other parts of the body. However, the conventional approach to machine learning relies on centralized training data, posing challenges for data privacy in healthcare systems driven by artificial intelligence. The collection of data from diverse sensors leads to increased computing costs, while privacy restrictions make it challenging to employ traditional machine learning methods.

Breast Cancer Classification through Meta-Learning Ensemble Technique Using Convolution Neural Networks.

This study aims to develop an efficient and accurate breast cancer classification model using meta-learning approaches and multiple convolutional neural networks. This Breast Ultrasound Images (BUSI) dataset contains various types of breast lesions. The goal is to classify these lesions as benign or malignant, which is crucial for the early detection and treatment of breast cancer.

Community centred co-design methodology for designing and implementing socio-behavioural interventions to counter COVID-19 related misinformation among marginalized population living in the squatter settlements of Karachi, Pakistan: a methodology paper.

Background: Misinformation regarding COVID-19 pandemic and vaccination is damaging COVID-19 vaccine trust and acceptance in Low- and Middle-Income Countries (LMIC). Identification of misinformation and designing locally acceptable solutions are needed to improve COVID-19 vaccine acceptance. This study aimed to utilize community-led co-design methodology to evaluate misinformation regarding COVID-19 and develop contextual interventions to address misinformation in a marginalized peri urban slum communities of Landhi town Karachi, Pakistan.

Federated Machine Learning for Skin Lesion Diagnosis: An Asynchronous and Weighted Approach.

The accurate and timely diagnosis of skin cancer is crucial as it can be a life-threatening disease. However, the implementation of traditional machine learning algorithms in healthcare settings is faced with significant challenges due to data privacy concerns. To tackle this issue, we propose a privacy-aware machine learning approach for skin cancer detection that utilizes asynchronous federated learning and convolutional neural networks (CNNs).

Predicting the effects of rare genetic variants on oncogenic signaling pathways: A computational analysis of HRAS protein function.

The HRAS gene plays a crucial role in regulating essential cellular processes for life, and this gene's misregulation is linked to the development of various types of cancers. Nonsynonymous single nucleotide polymorphisms (nsSNPs) within the coding region of HRAS can cause detrimental mutations that disrupt wild-type protein function. In the current investigation, we have employed methodologies to anticipate the consequences of infrequent genetic variations on the functional properties of the HRAS protein.

An overview of biofeedback techniques in mechanical low back pain: effects on sensory integration of balance.

Low back pain is a common musculoskeletal disorder involving the lumbar spine. It affects almost 80% of the world's population and is associated with functional limitations. The reported global prevalence ranges from15-30%.