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(1) Background: Group A Streptococcal (GAS) pharyngitis is common, resulting in numerous ambulatory visits. Accurate diagnosis is challenging. This study evaluated the clinical utility, cost, and performance of a nucleic acid amplification test (NAAT) for GAS detection, comparing it to a rapid antigen detection test (RADT) and throat culture. Additionally, we assessed the diagnostic stewardship related to these testing methods to ensure appropriate antibiotic use in clinical practice. Methods: Between November 2022 and February 2023, 82 throat swabs were analyzed, with McIsaac clinical scores calculated for each. The Abbott ID NOW STREP A 2 NAAT and Sekisui Diagnostics' OSOM® STREP A RADT were performed, followed by bacterial culture. Diagnostic performance was compared using culture as the gold standard. Results: Of the 82 samples, 28 (34.14%) tested positive for pathogenic germs, primarily Streptococcus pyogenes (92.85%). RADTs showed a sensitivity of 80.76% and a specificity of 100%, while NAATs demonstrated a sensitivity of 100% and specificity of 96.42%. Cost analysis indicated the need for reimbursement adjustments to optimize NAAT's economic benefits. Clinical data indicated that symptoms alone were insufficient for reliable diagnosis. Conclusions: This study confirmed the superior sensitivity of Abbott's Strep A2 NAAT over RADT. Given the Belgian guidelines against routine antibiotic treatment for pharyngitis and considering local treatment recommendations and cost, implementing NAAT for GAS detection in Belgian laboratories is less beneficial. However, the role of NAAT in supporting antimicrobial stewardship by ensuring appropriate antibiotic use remains significant. [ABSTRACT FROM AUTHOR]

Dementia is primarily caused by neurodegenerative diseases like Alzheimer's disease (AD). It affects millions worldwide, making detection and monitoring crucial. This study focuses on the detection of dementia from speech transcripts of controls and dementia groups. We propose encoding in-text pauses and filler words (e.g., "uh" and "um") in text-based language models and thoroughly evaluating their impact on performance (e.g., accuracy). Additionally, we suggest using contrastive learning to improve performance in a multi-task framework. Our results demonstrate the effectiveness of our approaches in enhancing the model's performance, achieving 87% accuracy and an 86% f1-score. Compared to the state of the art, our approach has similar performance despite having significantly fewer parameters. This highlights the importance of pause and filler word encoding on the detection of dementia. [ABSTRACT FROM AUTHOR]

Sleep staging has a very important role in diagnosing patients with sleep disorders. In general, this task is very time-consuming for physicians to perform. Deep learning shows great potential to automate this process and remove physician bias from decision making. In this study, we aim to identify recent trends on performance improvement and the causes for these trends. Recent papers on sleep stage classification and interpretability are investigated to explore different modeling and data manipulation techniques, their efficiency, and recent advances. We identify an improvement in performance up to 12% on standard datasets over the last 5 years. The improvements in performance do not appear to be necessarily correlated to the size of the models, but instead seem to be caused by incorporating new architectural components, such as the use of transformers and contrastive learning. [ABSTRACT FROM AUTHOR]

In the current investigation, molecular dynamics (MD) and Grand Canonical Monte Carlo (GCMC) simulation as remarkable and competent approaches have been employed for understanding structural and transport properties of MMMs in the realm of gas separation. The two commonly used polymers i.e. polysulfone (Psf) and polydimethylsiloxane (PDMS) as well as zinc oxide (ZnO) nanoparticle (NP) were used to carefully examine the transport properties of three light gasses (CO2, N2 and CH4) through simple Psf, Psf/PDMS composite loaded by different amounts of ZnO NP. Also, the fractional free volume (FFV), X-ray diffraction (XRD), glass transition temperature (Tg), and Equilibrium density were calculated to scrutinize the structural characterizations of the membranes. Moreover, the effect of feed pressure (4–16 bar) on gas separation performance of simulated MMMs was investigated. Results obtained in different experiments showed a clear improvement in the performance of simulated membranes by adding PDMS to PSf matrix. The selectivity of studied MMMs was in the range from 50.91 to 63.05 at pressures varying from 4 to 16 bar for the CO2/N2 gas pair, whereas the corresponding value for CO2/CH4 system was found to be in the range 27.27–46.24. For 6 wt% ZnO in 80%PSf + 20%PDMS membrane, high permeabilities of 78.02, 2.86 and 1.33 barrers were observed for CO2, CH4 and N2 gases, respectively. The 90%PSf + 10%PDMS membrane with 2% ZnO had a highest CO2/N2 selectivity value of 63.05 and its CO2 permeability at 8 bar was 57 barrer. [ABSTRACT FROM AUTHOR]

The effect of humic acid (HA) on the nutritional value and quality of wheat grain and flour has rarely been studied. A field experiment to determine the effect of fertigation of HA and Azotobacter chroococcum UT1 (AZ) on nutrient elements (P, K, Zn, Fe, Mn and Cu), dry gluten, protein and essential amino acids of two wheat cultivars (Chamran and Kouhdasht), comparing four treatments (control, HA, AZ and HA × AZ) using randomized complete block design with four replicates was conducted at the research station of Chardavol in Iran. The 2 years data during 2019 and 2020 indicated that the fertigation of HA and its interaction with AZ (HA × AZ) improved the nutrient elements, dry gluten and protein concentration of wheat grain and flour in both wheat cultivars in comparison with the control treatment. Inoculation of AZ reduced dry gluten of flour in the Kouhdasht cultivar by 6.34%. The application of HA × AZ also significantly enhanced the concentration of essential amino acids of wheat grain and flour in both wheat cultivars by 7.24–11.6%. In similar treatments, the concentration of nutrient elements, dry gluten, protein and essential amino acids of the Chamran cultivar were higher than those in Kouhdasht cultivar. Therefore, it can be concluded that the combined application of HA and AZ can be a suitable recommendation for improving wheat quality. [ABSTRACT FROM AUTHOR]