Orthopaedic patients' emergency department attendance behavior in relation to weather conditions: temperature, rain, day and time, and regional thursday effect.

Great variation was noticed in emergency department (ED) afflux in relation to daily weather conditions, including difficulties in arranging the correct number of orthopaedic on-calls on the floor. This study aimed to quantify the association between the number of patients referred to the orthopaedic team from the ED and weather conditions, particularly daily temperature and rain. Data were obtained from a large state research hospital's ED attendance. Weather information for the local area for the year was obtained from the regional meteorological office. Data were evaluated using descriptive statistics, with one-way analysis of variance for the relationship between the day of the week and patient numbers, the Pearson test for correlations between daily ED patient flow and daily temperature and the Spearman correlation test for correlations between daily patient flow and daily rain status. A positive and meaningful correlation existed between daily patient influx and daily temperature, along with a negative correlation between daily patient flow and daily rain. Throughout the year, significantly more patients were referred to the orthopaedic team on Thursdays than on any other day of the week. Patients tended to visit the ED more on warm days and days without rain. These results may help in organising daily, monthly or seasonal on-call orthopaedic team requirements despite the challenges. Incorporating climate forecasts into planning the on-call service might help alleviate the stress on the team.

Machine learning-assisted SERS approach enables the biochemical discrimination in Bcl-2 and Mcl-1 expressing yeast cells treated with ketoconazole and fluconazole antifungals.

Antifungal medications are important due to their potential application in cancer treatment either on their own or with traditional treatments. The mechanisms that prevent the effects of these medications and restrict their usage in cancer treatment are not completely understood. The evaluation and discrimination of the possible protective effects of the anti-apoptotic members of the Bcl-2 family of proteins, critical regulators of mitochondrial apoptosis, against antifungal drug-induced cell death has still scientific uncertainties that must be considered. Novel, simple, and reliable strategies are highly demanded to identify the biochemical signature of this phenomenon. However, the complex nature of cells poses challenges for the analysis of cellular biochemical changes or classification. In this study, for the first time, we investigated the probable protective activities of Bcl-2 and Mcl-1 proteins against cell damage induced by ketoconazole (KET) and fluconazole (FLU) antifungal drugs in a yeast model through surface-enhanced Raman spectroscopy (SERS) approach. The proposed SERS platform created robust Raman spectra with a high signal-to-noise ratio. The analysis of SERS spectral data via advanced unsupervised and supervised machine learning methods enabled unquestionable differentiation (100 %) in samples and biomolecular identification. Various SERS bands related to lipids and proteins observed in the analyses suggest that the expression of these anti-apoptotic proteins reduces oxidative biomolecule damage induced by the antifungals. Also, cell viability assay, Annexin V-FITC/PI double staining, and total oxidant and antioxidant status analyses were performed to support Raman measurements. We strongly believe that the proposed approach paves the way for the evaluation of various biochemical structures/changes in various cells.