The Role of Lipids in Atherosclerosis: Focus on Molecular Biology Mechanisms and Therapeutic Approaches.

Atherosclerosis is a complex vascular disease characterized by the buildup of lipids, inflammatory cells and fibrous components in arterial walls leading to plaque formation and potential thrombotic events like myocardial infarction and strokes. Recently, there has been research on the roles of various types of lipids such as low-density lipoprotein (LDL) cholesterol, oxidized LDL (oxLDL) cholesterol and small dense LDL (sdLDL) in the onset and progression of atherosclerosis. These lipoproteins contribute to dysfunction and inflammation processes that play a role in the development and instability of plaques.

Rare/Common Variants Are Associated with Inhaled Corticosteroid Response among Children with Asthma.

Inhaled corticosteroids (ICS) are efficacious in the treatment of asthma, which affects more than 300 million people in the world. While genome-wide association studies have identified genes involved in differential treatment responses to ICS in asthma, few studies have evaluated the effects of combined rare and common variants on ICS response among children with asthma. Among children with asthma treated with ICS with whole exome sequencing (WES) data in the PrecisionLink Biobank (91 White and 20 Black children), we examined the effect and contribution of rare and common variants with hospitalizations or emergency department visits.

Consensus Gene Network Analysis Identifies the Key Similarities and Differences in Endothelial and Epithelial Cell Dynamics after Infection.

Endothelial and epithelial cells are morphologically different and play a critical role in host defense during infection. Both cells respond to infection by activating various signaling pathways and gene expression patterns. Their interactions with these pathogens can have beneficial and detrimental effects, and a better understanding of these interactions can help guide the development of new therapies for infection.

Outcomes of COVID-19 patients with acute kidney injury and longitudinal analysis of laboratory markers during the hospital stay: A multi-center retrospective cohort experience from Pakistan.

The frequency of acute kidney injury (AKI) in COVID-19 patients can be varied and related to worse outcomes in the disease population. AKI is common among hospitalized patients with COVID-19, particularly the ones needing critical care. This study was conducted in order to determine the outcomes of hospitalized patients with prolonged hospital stays who suffered from COVID-19 associated AKI.

Features derived from blood pressure and intracranial pressure predict elevated intracranial pressure events in critically ill children.

Clinicians frequently observe hemodynamic changes preceding elevated intracranial pressure events. We employed a machine learning approach to identify novel and differentially expressed features associated with elevated intracranial pressure events in children with severe brain injuries. Statistical features from physiologic data streams were derived from non-overlapping 30-min analysis windows prior to 21 elevated intracranial pressure events; 200 records without elevated intracranial pressure events were used as controls.

Coexpression network analysis of human candida infection reveals key modules and hub genes responsible for host-pathogen interactions.

Invasive fungal infections are a significant reason for morbidity and mortality among organ transplant recipients. Therefore, it is critical to investigate the host and candida niches to understand the epidemiology of fungal infections in transplantation. is an opportunistic fungal pathogen that causes fatal invasive mucosal infections, particularly in solid organ transplant patients.

Split Dosage Weekly Regimen of Oral Methotrexate is Associated With Improved Side Effect Profile in Rheumatoid Arthritis Patients: A Quasi-Experimental Study.

Background And Objectives: Methotrexate (MTX) is globally used by physicians to treat patients with Rheumatoid Arthritis (RA). Previously conducted researches indicate prevalent side effects associated with conventional once-weekly dosage amongst a population sample of patients consuming MTX. The objectives of our study were to find out whether there is a difference between the two studied regimens in efficacy and adverse effects of methotrexate.

Molecular identification of two entomopathogenic fungus Clonostachys rosea strains and their efficacy against two aphid species in Iraq.

Background: The green peach aphid, Myzus persicae Sulzer, and the bean aphid, Aphis fabae Scopoli (both Hemiptera: Aphididae), are serious pests of greenhouse vegetable crops in Iraq and other regions of the globe. In this study, two morphological identical isolates (AA80 and AA82) of the entomopathogenic fungus Clonostachys rosea Schroers (Hypocreales: Bionectriaceae) from Iraq were isolated and characterized with phylogenetic analysis based on the internal transcribed spacer (ITS) region. The efficacy of C.

Prediction of low Apgar score at five minutes following labor induction intervention in vaginal deliveries: machine learning approach for imbalanced data at a tertiary hospital in North Tanzania.

Background: Prediction of low Apgar score for vaginal deliveries following labor induction intervention is critical for improving neonatal health outcomes. We set out to investigate important attributes and train popular machine learning (ML) algorithms to correctly classify neonates with a low Apgar scores from an imbalanced learning perspective.

Methods: We analyzed 7716 induced vaginal deliveries from the electronic birth registry of the Kilimanjaro Christian Medical Centre (KCMC).

Characteristics of Asymptomatic Bacteriuria in Patients with Chronic Kidney Disease: A Tertiary Care Hospital Experience from a Developing Country.

Asymptomatic bacteriuria (ASB) is the isolation of bacteria in a urine sample from individuals who do not have any symptoms of a urinary tract infection (UTI). The outcomes of ASB in chronic kidney disease (CKD) patients are poorly understood in Pakistan. This study aimed to determine the characteristics of ASB and antibiotic susceptibility pattern among patients with CKD.

A CROSS-SECTIONAL SCREENING SURVEY ON THE SEROPREVALENCE OF HEPATITIS B AND HEPATITIS C AMONGST THE GENERAL POPULATION OF RURAL DISTRICTS OF SINDH, PAKISTAN.

Background: Viral hepatitis is a global phenomenon, with the disease burden varying on a daily basis. Amongst chronic infections, hepatitis B virus and hepatitis C virus (HCV) are egregiously linked to severe health-related complications, with a worldwide prevalence of 248 million and 71 million respectively. Amongst the developing world, a hand full of countries are exhibiting a gross decline in chronic viral infection prevalence, like Bangladesh.

Integrative Analyses of Circulating Small RNAs and Kidney Graft Transcriptome in Transplant Glomerulopathy.

Transplant glomerulopathy develops through multiple mechanisms, including donor-specific antibodies, T cells and innate immunity. This study investigates circulating small RNA profiles in serum samples of kidney transplant recipients with biopsy-proven transplant glomerulopathy. Among total small RNA population, miRNAs were the most abundant species in the serum of kidney transplant patients.

Characteristics of Asymptomatic Bacteriuria in Diabetes Mellitus Patients: A Retrospective Observational Study.

Background and objective The term asymptomatic bacteriuria (ASB) refers to the isolation of bacteria in a urine specimen of individuals without any symptoms of urinary tract infection (UTI). Diabetes mellitus (DM) is a disease involving multiple organ systems, characterized by its chronicity and hence endless complications including ASB. This study aimed to determine the characteristics of ASB and antibiotic susceptibility patterns among patients with diabetes.

Machine Learning Identifies Complicated Sepsis Course and Subsequent Mortality Based on 20 Genes in Peripheral Blood Immune Cells at 24 H Post-ICU Admission.

A complicated clinical course for critically ill patients admitted to the intensive care unit (ICU) usually includes multiorgan dysfunction and subsequent death. Owing to the heterogeneity, complexity, and unpredictability of the disease progression, ICU patient care is challenging. Identifying the predictors of complicated courses and subsequent mortality at the early stages of the disease and recognizing the trajectory of the disease from the vast array of longitudinal quantitative clinical data is difficult.

HeMA: A hierarchically enriched machine learning approach for managing false alarms in real time: A sepsis prediction case study.

Early detection of sepsis can be life-saving. Machine learning models have shown great promise in early sepsis prediction when applied to patient physiological data in real-time. However, these existing models often under-perform in terms of positive predictive value, an important metric in clinical settings.

Role of Biochemical Markers in Invasive Ventilation of Coronavirus Disease 2019 Patients: Multinomial Regression and Survival Analysis.

Background and objectives Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the pathogen responsible for the coronavirus disease 2019 (COVID-19) pandemic. The disease mainly affects the respiratory system of the patient, in particular, the lungs, which leads to patients presenting with acute respiratory distress syndrome and acute respiratory failure, with 5-15% of patients requiring observation in the intensive care unit (ICU) with respiratory support in the form of ventilation. This study was aimed at identifying the role of biochemical markers in the risk stratification of invasive and non-invasive ventilation of hospitalized COVID-19 patients.

Temporal Differential Expression of Physiomarkers Predicts Sepsis in Critically Ill Adults.

Background: Sepsis is a life-threatening condition with high mortality rates. Early detection and treatment are critical to improving outcomes. Our primary objective was to develop artificial intelligence capable of predicting sepsis earlier using a minimal set of streaming physiological data in real time.

Poor Prognostic Biochemical Markers Predicting Fatalities Caused by COVID-19: A Retrospective Observational Study From a Developing Country.

Background and objectives Infections with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are rapidly spreading, posing a serious threat to the health of people worldwide, resulting in the World Health Organization officially declaring it a pandemic. There are several biochemical markers linked with predicting the severity of coronavirus disease. This study aims to identify the most effective predictive biomarker such as C-reactive protein (CRP), ferritin, lactate dehydrogenase (LDH), procalcitonin (PCT), and D-dimer, among others, in predicting the clinical outcome of the disease.

Correction: Clinical Profiles, Characteristics, and Outcomes of the First 100 Admitted COVID-19 Patients in Pakistan: A Single-Center Retrospective Study in a Tertiary Care Hospital of Karachi.

[This corrects the article DOI: 10.7759/cureus.8712.