The graphene-based affinity cryo-EM grid for the endogenous protein structure determination.

Following recent advancements in cryo-electron microscopy (cryo-EM) instrumentation and software algorithms, the next bottleneck in achieving high-resolution cryo-EM structures arises from sample preparation. To overcome this, we developed a graphene-based affinity cryo-EM grid, the Graffendor (GFD) grid, to target low-abundance endogenous protein complexes. To maintain grid quality and consistency within a single batch of 36 grids, we established a one-step crosslinking batch-production method using genetically modified ALFA nanobody as affinity probe (GFD-A grid).

Satisfactory Evaluation of Call Service Using AI After Ureteral Stent Insertion: Randomized Controlled Trial.

Background: Ureteral stents, such as double-J stents, have become indispensable in urologic procedures but are associated with complications like hematuria and pain. While the advancement of artificial intelligence (AI) technology has led to its increasing application in the health sector, AI has not been used to provide information on potential complications and to facilitate subsequent measures in the event of such complications.

Objective: This study aimed to assess the effectiveness of an AI-based prediction tool in providing patients with information about potential complications from ureteroscopy and ureteric stent placement and indicating the need for early additional therapy.