Maternal Sepsis and associated factors: A multi-central study from two tertiary care hospitals of South Punjab, Pakistan.

Objective: To determine the risk factors and outcomes of maternal sepsis.

Methods: This case-control study was performed at the departments of Obstetrics & Gynecology, Nishtar Hospital, Multan, and Ghazi Khan Hospital, Dera Ghazi Khan, Pakistan, from June 2023 to May 2024. Cases were comprised of females aged 18-45 years diagnosed with maternal sepsis, and admitted during the study period.

Advances in physiological and clinical relevance of hiPSC-derived brain models for precision medicine pipelines.

Precision, or personalized, medicine aims to stratify patients based on variable pathogenic signatures to optimize the effectiveness of disease prevention and treatment. This approach is favorable in the context of brain disorders, which are often heterogeneous in their pathophysiological features, patterns of disease progression and treatment response, resulting in limited therapeutic standard-of-care. Here we highlight the transformative role that human induced pluripotent stem cell (hiPSC)-derived neural models are poised to play in advancing precision medicine for brain disorders, particularly emerging innovations that improve the relevance of hiPSC models to human physiology.

Efficacy and Safety of Total Body Irradiation Versus Chemotherapy Conditioning for Hematopoietic Stem Cell Transplant in Adult Acute Lymphoblastic Leukemia: A Systematic Review and Meta-Analysis.

Hematopoietic stem cell transplantation (HSCT) is a potentially curative option for adults with acute lymphoblastic leukemia (ALL) who have achieved remission. This systematic review and meta-analysis compare the efficacy of total body irradiation (TBI) versus chemotherapy (CHT) based regimens for conditioning in adult ALL patients being prepared for HSCT. A comprehensive literature search was conducted in MEDLINE, Embase, the Cochrane Library, and relevant trial registries from their inception to August 2024.

The intersection of finTech adoption, HR competency potential, service innovation, and firm growth in the banking sectors using Entropy and TOPSIS.

The adoption of Financial Technology (FinTech), along with the enhancement of Human Resource (HR) competencies, service innovation, and firm growth, plays a crucial role in the development of the banking sector. Despite their importance, obtaining reliable results is often challenging due to the complex, high-dimensional correlations among various features that affect the industry. To address this issue, this research introduces a hybrid Multi-Criteria Decision-Making (MCDM) model that integrates the Entropy-Weighted Method (EWM) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS).

Blockchain-enabled digital twin system for brain stroke prediction.

A digital twin is a virtual model of a real-world system that updates in real-time. In healthcare, digital twins are gaining popularity for monitoring activities like diet, physical activity, and sleep. However, their application in predicting serious conditions such as heart attacks, brain strokes and cancers remains under investigation, with current research showing limited accuracy in such predictions.