Microplastics as an Emerging Potential Threat: Toxicity, Life Cycle Assessment, and Management.

The pervasiveness of microplastics (MPs) in terrestrial and aquatic ecosystems has become a significant environmental concern in recent years. Because of their slow rate of disposal, MPs are ubiquitous in the environment. As a consequence of indiscriminate use, landfill deposits, and inadequate recycling methods, MP production and environmental accumulation are expanding at an alarming rate, resulting in a range of economic, social, and environmental repercussions.

Evaluation of Selected Folk Herbs on the Fertility of Sprague Dawley Male Rats: Biochemical, Histological, and Molecular Investigations.

Scientists have shown great interest in traditional plant extracts, particularly (LS), (OM), (FH), and (ES), which are frequ ently used to improve health. Recently, attention has been directed toward their influence on spermatogenesis and male fertility. Hence, the objective of this study was to explore their impact on male rats' fertility.

Housing Environmental Enrichment, Lifestyles, and Public Health Indicators of Neurogenesis in Humans: A Pilot Study.

Background: In response to the rising mental health concerns and cognitive decline associated with the human brain's neurogenesis, which continues until the tenth decade of life but declines with age and is suppressed by poor environments, this pilot study investigates how physical environments may influence public health proxy measures of neurogenesis in humans. This pilot study focuses on the residential environment where people spend most of their time and age in place, exploring the dependency of depression, anxiety, and cognitive impairment variations on spatial and lifestyle variables.

Methods: A total of 142 healthy adults in England completed a survey consisting of PHQ-8, GAD-7, and CFI questionnaires and other questions developed to capture the variance in spatial and lifestyle factors such as time spent at home, house type layout complexity, spaciousness, physical activity, routine and spatial novelty, and perceived loneliness.

Textbook outcome in liver surgery for intrahepatic cholangiocarcinoma: defining predictors of an optimal postoperative course using machine learning.

Background: We sought to define textbook outcome in liver surgery (TOLS) for intrahepatic cholangiocarcinoma (ICC) by considering the implications of perioperative outcomes on overall survival (OS).

Methods: Using a multi-institutional database, TOLS for ICC was defined by employing novel machine learning (ML) models to identify perioperative factors most strongly predictive of OS ≥ 12 months. Subsequently, clinicopathologic factors associated with achieving TOLS were investigated.

Machine learning based prediction model for bile leak following hepatectomy for liver cancer.

Objective: We sought to develop a machine learning (ML) preoperative model to predict bile leak following hepatectomy for primary and secondary liver cancer.

Methods: An eXtreme Gradient Boosting (XGBoost) model was developed to predict post-hepatectomy bile leak using data from the ACS-NSQIP database. The model was externally validated using data from hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) multi-institutional databases.