Multilayer Choline Phosphate Molecule Modified Surface with Enhanced Cell Adhesion but Resistance to Protein Adsorption

Choline phosphate (CP), which is a new zwitterionic molecule, and has the reverse order of phosphate choline (PC) and could bind to the cell membrane though the unique CP–PC interaction. Here we modified a glass surface with multilayer CP molecules using surface-initiated atom-transfer radical polymerization (SI-ATRP) and the ring-opening method. Polymeric brushes of (di­methyl­amino)­ethyl meth­acrylate (DMAEMA) were synthesized by SI-ATRP from the glass surface. Then the grafted PDMAEMA brushes were used to introduce CP groups to fabricate the multilayer CP molecule modified surface. The protein adsorption experiment and cell culture test were used to evaluate the biocompatibility of the modified surfaces by using human umbilical veinendothelial cells (HUVECs). The protein adsorption results demonstrated that the multilayer CP molecule decorated surface could prevent the adsorption of fibrinogen and serum protein. The adhesion and proliferation of cells were improved significantly on the multilayer CP molecule modified surface. Therefore, the biocompatibility of the material surface could be improved by the modified multilayer CP molecule, which exhibits great potential for biomedical applications, e.g., scaffolds in tissue engineering

Microwave-Assisted Rapid Synthesis of γ‑Cyclodextrin Metal–Organic Frameworks for Size Control and Efficient Drug Loading

The micron and nanometer-sized γ-cyclodextrin metal–organic frameworks (γ-CD-MOFs) were successfully synthesized using the microwave technique for the first time for rapid and facile synthesis. Polyethylene glycol 20000 (PEG 20000) was used as surfactant to control the size and morphology of γ-CD-MOFs. The as-synthesized γ-CD-MOFs were characterized using various techniques, including X-ray powder diffraction (PXRD), scanning electron microscopy (SEM), thermogravimetric analysis (TGA), and N₂ adsorption. The increment in the reaction time and MeOH ratio dramatically damaged the crystalline integrity of γ-CD-MOFs. Fenbufen was selected as a model drug to evaluate the loading characteristics of γ-CD-MOF crystals. As a result, the nanometer sized γ-CD-MOFs (100–300 nm) showed rapid and higher adsorption (196 mg g^–1) of Fenbufen in EtOH when compared with the micron crystals. The adsorption parameters fitted well to a pseudo-second-order kinetic model and chemisorption of Fenbufen was further supported by molecular docking illustrations. In summary, the controlled synthesis of γ-CD-MOFs was successfully achieved by microwave assisted method and resultant crystals were further evaluated for potential drug delivery applications

Data_Sheet_1_Re-tear after arthroscopic rotator cuff repair can be predicted using deep learning algorithm.xlsx

The application of artificial intelligence technology in the medical field has become increasingly prevalent, yet there remains significant room for exploration in its deep implementation. Within the field of orthopedics, which integrates closely with AI due to its extensive data requirements, rotator cuff injuries are a commonly encountered condition in joint motion. One of the most severe complications following rotator cuff repair surgery is the recurrence of tears, which has a significant impact on both patients and healthcare professionals. To address this issue, we utilized the innovative EV-GCN algorithm to train a predictive model. We collected medical records of 1,631 patients who underwent rotator cuff repair surgery at a single center over a span of 5 years. In the end, our model successfully predicted postoperative re-tear before the surgery using 62 preoperative variables with an accuracy of 96.93%, and achieved an accuracy of 79.55% on an independent external dataset of 518 cases from other centers. This model outperforms human doctors in predicting outcomes with high accuracy. Through this methodology and research, our aim is to utilize preoperative prediction models to assist in making informed medical decisions during and after surgery, leading to improved treatment effectiveness. This research method and strategy can be applied to other medical fields, and the research findings can assist in making healthcare decisions.</p