Does candidate race influence simulated patient ratings in standardised assessments of clinical practice? A single-blinded randomised study in UK medical schools.

Objectives: Standardisation of medical examinations involves minimising assessor stereotyping and bias for a fair process. This study aimed to determine whether being a non-white candidate affected scoring by simulated patients, compared with a white candidate, at three different performance grades in the same history-taking station.

Design: Single-blinded, video-based, randomised study.

Transgenic tomato strategies targeting whitefly eggs from apoplastic or ovary-directed proteins.

Background: Transgenic plants expressing proteins that target the eggs of the ubiquitous plant pest Bemisia tabaci (whitefly) could be an effective insecticide strategy. Two approaches for protein delivery are assessed using the mCherry reporter gene in transgenic tomato plants, while accommodating autofluorescence in both the plant, phloem-feeding whitefly and pedicle-attached eggs.

Results: Both transgenic strategies were segregated to homozygous genotype using digital PCR.

An Innovative Approach to Navigating Microaggressions in Medical Education Settings.

Problem: Microaggressions negatively affect the experiences of medical students, especially those from minoritized groups, indicating the need for heightened awareness and open dialogue. The increasing recognition of the potential harm caused by such behaviors has led to a call for educational strategies that enable medical students to identify and address microaggressions effectively. This report details an innovative approach designed to navigate the complexities of microaggressions within medical education settings.

Blood smear imagery dataset for malaria parasite detection: A case of Tanzania.

Malaria is a major public health issue in many regions of Africa, including Tanzania. The Tanzania Malaria National Strategic Plan (2021-2025) emphasizes on high-quality testing services availability, high coverage of timely diagnosis of malaria, and availability of innovative diagnostic systems for effective detection, treatment and control of malaria. This would be achieved by employing state of the art technologies like Machine learning.