[Application of delayed replantation of degloving skin preserved at 4 in treatment of limb degloving injuries].

Objective: To investigate the effectiveness of delayed replantation of degloving skin preserved at 4℃ in treatment of limb degloving injuries.

Methods: Between October 2020 and October 2023, 12 patients with limb degloving injuries were admitted. All patients had severe associated injuries or poor wound conditions that prevented primary replantation.

Predicting transcriptional changes induced by molecules with MiTCP.

Studying the changes in cellular transcriptional profiles induced by small molecules can significantly advance our understanding of cellular state alterations and response mechanisms under chemical perturbations, which plays a crucial role in drug discovery and screening processes. Considering that experimental measurements need substantial time and cost, we developed a deep learning-based method called Molecule-induced Transcriptional Change Predictor (MiTCP) to predict changes in transcriptional profiles (CTPs) of 978 landmark genes induced by molecules. MiTCP utilizes graph neural network-based approaches to simultaneously model molecular structure representation and gene co-expression relationships, and integrates them for CTP prediction.

Enhancing drug solubility through competitive adsorption on silica nanosurfaces with ultrahigh silanol densities.

We develop a technology based on competitive adsorption between drug molecules and water, specifically designed to address the critical issue of poor drug solubility. By specially engineering silica nanosurfaces with ultrahigh densities of silanol, we significantly enhance their affinity for both drug molecules and water, with a notably greater increase in water affinity. Such surfaces can effectively adsorb a variety of drug molecules under dry conditions.

Hydrologic outputs generated over the Great Lakes with a calibrated version of the GEM-Hydro model.

This dataset contains outputs from a calibrated version of the GEM-Hydro model developed at Environment and Climate Change Canada (ECCC) and is available on the Federated Research Data Repository. The dataset covers the basins of the Laurentian Great Lakes and the Ottawa River and extends over the period 2001-2018. The data consist of all variables (hourly fluxes and state variables) related to the water balance of GEM-Hydro's land-surface scheme (including precipitation, surface and sub-surface runoff, drainage, evaporation, snow water equivalent, soil moisture…) and mean daily streamflow at 212 gauge locations.