Detecting depression severity using weighted random forest and oxidative stress biomarkers.

This study employs machine learning to detect the severity of major depressive disorder (MDD) through binary and multiclass classifications. We compared models that used only biomarkers of oxidative stress with those that incorporate sociodemographic and health-related factors. Data collected from 830 participants, based on the Patient Health Questionnaire (PHQ-9) score, inform our analysis. In binary classification, the Random Forest (RF) classifier achieved the highest Area Under the Curve (AUC) of 0.84 when all features were included. In multiclass classification, the AUC improved from 0.84 with only oxidative stress biomarkers to 0.88 when all characteristics were included. To address data imbalance, weighted classifiers, and Synthetic Minority Over-sampling Technique (SMOTE) approaches were applied. Weighted random forest (WRF) improved multiclass classification, achieving an AUC of 0.91. Statistical tests, including the Friedman test and the Conover post-hoc test, confirmed significant differences between model performances, with WRF using all features outperforming others. Feature importance analysis shows that oxidative stress biomarkers, particularly GSH, are top ranked among all features. Clinicians can leverage the results of this study to improve their decision-making processes by incorporating oxidative stress biomarkers in addition to the standard criteria for depression diagnosis.

The Biological Activity of Natural Alkaloids against Herbivores, Cancerous Cells and Pathogens.

The growing incidence of microorganisms that resist antimicrobials is a constant concern for the scientific community, while the development of new antimicrobials from new chemical entities has become more and more expensive, time-consuming, and exacerbated by emerging drug-resistant strains. In this regard, many scientists are conducting research on plants aiming to discover possible antimicrobial compounds. The secondary metabolites contained in plants are a source of chemical entities having pharmacological activities and intended to be used for the treatment of different diseases. These chemical entities have the potential to be used as an effective antioxidant, antimutagenic, anticarcinogenic and antimicrobial agents. Among these pharmacologically active entities are the alkaloids which are classified into a number of classes, including pyrrolizidines, pyrrolidines, quinolizidines, indoles, tropanes, piperidines, purines, imidazoles, and isoquinolines. Alkaloids that have antioxidant properties are capable of preventing a variety of degenerative diseases through capturing free radicals, or through binding to catalysts involved indifferent oxidation processes occurring within the human body. Furthermore, these entities are capable of inhibiting the activity of bacteria, fungi, protozoan and etc. The unique properties of these secondary metabolites are the main reason for their utilization by the pharmaceutical companies for the treatment of different diseases. Generally, these alkaloids are extracted from plants, animals and fungi. Penicillin is the most famous natural drug discovery deriving from fungus. Similarly, marines have been used as a source for thousands of bioactive marine natural products. In this review, we cover the medical use of natural alkaloids isolated from a variety of plants and utilized by humans as antibacterial, antiviral, antifungal and anticancer agents. An example for such alkaloids is berberine, an isoquinoline alkaloid, found in roots and stem-bark of Berberis asculin P. Renault plant and used to kill a variety of microorganisms.

A study of deficiencies in teamwork skills among Jordan caregivers.

Purpose The purpose of this paper is to present the deficiencies in teamwork skills at Jordan hospitals as seen by team members. The study aims to identify training needs to improve teamwork-related soft skills of caregivers to enhance staff satisfaction and improve quality of care. Moreover, the paper provides a methodology to identify the training needs in any healthcare workplace by repeating the same questionnaire. Design/methodology/approach A self-administrated questionnaire was designed to study deficiencies in teamwork and team leadership at Jordan hospitals as seen by team members. Surveyed care providers included physicians, nursing and anesthesiologists operating in emergency departments, surgical operating rooms and intensive care units from various hospitals. Findings With a response rate of 78.8 percent, statistical analysis of collected data of opposing staff members revealed low levels of satisfaction (40.7-48 percent opposing), lack of awareness on the impact of teamwork on quality of care (15.6-22.1 percent opposing), low levels of involvement of top management (27.1-57.3 percent opposing), lack of training (52.5-69.8 percent opposing), lack of leadership skills (29.8-60 percent opposing), lack of communication (22.3-62.1 percent opposing), lack of employee involvement (37.6-50.8 percent opposing) and lack of collaboration among team members (28.6-50 percent opposing). Among the many, results illustrate the need for improving leadership skills of team leaders, improving communication and involving team members in decision making. Originality/value Several studies investigated relationships between teamwork skills and quality of care in many countries. To the authors' knowledge, no local study investigated the deficiencies of teamwork skills among Jordan caregivers and its impact on quality of care. The study provides the ground for management at Jordan hospitals and to healthcare academic departments to tailor training courses to improve teamwork skills of caregivers. Data of this study are collected from the society who is working in the field of healthcare. As the results of this are produced from a real data, it is expected that applying the recommendations will impact the society positively by enhancing the patients' satisfaction.