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In the last few years, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been the cause of a worldwide pandemic, highlighting the need for novel antiviral agents. The main protease (M) of SARS-CoV-2 was immediately identified as a crucial enzyme for viral replication and has been validated as a drug target. Here, we present the design and synthesis of peptidomimetic M covalent inhibitors characterized by quinoline-based P moieties.

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A Decade of Oocyte Cryopreservation: New Horizons in Patients Accessing Care.

J Womens Health (Larchmt)

January 2025

Reproductive Medicine Associates of NY, New York, NY, USA.

Utilization of fertility preservation treatments has increased since the American Society for Reproductive Medicine lifted the "experimental" label for oocyte cryopreservation in 2012. This study characterizes changes in insurance coverage, clinical outcomes, and live birth probabilities over a span of a decade (2012-2022) in patients who underwent planned oocyte cryopreservation. Retrospective analysis of planned oocyte cryopreservation cycles using vitrification from 2012 to 2022.

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Background: Childhood cancer is not a high priority in health care financing for many countries, including in Ghana. Delayed care seeking and treatment abandonment, often due to the financial burden of care seeking to families, are common reasons for a relatively low overall survival (OS) in low-and middle-income countries. In this study, we analyzed the cost-effectiveness of extending health insurance coverage to children with Burkitt lymphoma (BL) in Ghana.

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In the subauroral zone at the boundary of the auroral oval in the evening and night hours during geomagnetic disturbances, a narrow (about 1°-2°) and extended structure (several hours in longitude) is formed. It is known as a polarization jet (PJ) or the subauroral ion drift (SAID). The PJ/SAID is a fast westward ion drift and is one of the main signatures of a geomagnetic disturbance in the subauroral ionosphere at the altitudes of the F-layer, when the geomagnetic AE index reaches more than 500 nT.

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This study evaluates three Machine Learning (ML) models-Temporal Kolmogorov-Arnold Networks (TKAN), Long Short-Term Memory (LSTM), and Temporal Convolutional Networks (TCN)-focusing on their capabilities to improve prediction accuracy and efficiency in streamflow forecasting. We adopt a data-centric approach, utilizing large, validated datasets to train the models, and apply SHapley Additive exPlanations (SHAP) to enhance the interpretability and reliability of the ML models. The results show that TKAN outperforms LSTM but slightly lags behind TCN in streamflow forecasting.

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