Safety reporting in trials on glaucoma interventions registered in ClinicalTrials.gov and corresponding publications.

Accurate, comprehensive, and consistent reporting of adverse events is of great importance for treatment decisions in clinical practice and patient safety. Aiming to evaluate the completeness and transparency of reported adverse events we conducted a retrospective analysis of completed clinical trials on glaucoma interventions registered in ClinicalTrials.gov from September 27, 2009, and updated and with results on or before November 1, 2023, as well as in corresponding journal publications.

Impact of Simultaneous Nutrient Priming and Biopriming on Soybean Seed Quality and Health.

In soybean production, numerous strategies are utilized to enhance seed quality and mitigate the effects of biotic and abiotic stressors. Zn-based nutrient priming has been shown to be effective for field crops, and biopriming is a strategy that is becoming increasingly important for sustainable agriculture. On the other hand, there is a lack of information about the effect of comprehensive nutrient priming and biopriming techniques on soybean seed quality and viability and seed health.

Assessment of Various Nanoprimings for Boosting Pea Germination and Early Growth in Both Optimal and Drought-Stressed Environments.

One of the main climate change-related variables limiting agricultural productivity that ultimately leads to food insecurity appears to be drought. With the use of a recently discovered nanopriming technology, seeds can endure various abiotic challenges. To improve seed quality and initial growth of 8-day-old field pea seedlings (cv.

Tackling the Antimicrobial Resistance "Pandemic" with Machine Learning Tools: A Summary of Available Evidence.

Antimicrobial resistance is recognised as one of the top threats healthcare is bound to face in the future. There have been various attempts to preserve the efficacy of existing antimicrobials, develop new and efficient antimicrobials, manage infections with multi-drug resistant strains, and improve patient outcomes, resulting in a growing mass of routinely available data, including electronic health records and microbiological information that can be employed to develop individualised antimicrobial stewardship. Machine learning methods have been developed to predict antimicrobial resistance from whole-genome sequencing data, forecast medication susceptibility, recognise epidemic patterns for surveillance purposes, or propose new antibacterial treatments and accelerate scientific discovery.

First Report of Collar and Root Rot of Lettuce Caused by in Serbia.

In March 2021, unusual plant stuning, collar, and wet root rot of lettuce ( L.) during the rosette stage was observed in two commercial fields in Serbia (44°58'N, 20°32'E; 44°45'N, 20°43'E). Disease incidence in the fields (≈ 0.