Objectives: To create a novel preoperative prediction model based on a deep learning algorithm to predict neoplasm T staging and grading in patients with upper tract urothelial carcinoma (UTUC). Methods: We performed a retrospective cohort study of patients diagnosed with UTUC between 2001 and 2012 at our institution. Five deep learning algorithms (CGRU, BiGRU, CNN-BiGRU, CBiLSTM, and CNN-BiLSTM) were used to develop a preoperative prediction model for neoplasm T staging and grading. The Matthews correlation coefficient (MMC) and the receiver-operating characteristic curve with the area under the curve (AUC) were used to evaluate the performance of each prediction model. Results: The clinical data of a total of 884 patients with pathologically confirmed UTUC were collected. The T-staging prediction model based on CNN-BiGRU achieved the best performance, and the MMC and AUC were 0.598 (0.592–0.604) and 0.760 (0.755–0.765), respectively. The grading prediction model [1973 World Health Organization (WHO) grading system] based on CNN-BiGRU achieved the best performance, and the MMC and AUC were 0.612 (0.609–0.615) and 0.804 (0.801–0.807), respectively. The grading prediction model [2004 WHO grading system] based on BiGRU achieved the best performance, and the MMC and AUC were 0.621 (0.616–0.626) and 0.824 (0.819–0.829), respectively. Conclusions: We developed an accurate UTUC preoperative prediction model to predict neoplasm T staging and grading based on deep learning algorithms, which will help urologists to make appropriate treatment decisions in the early stage.

Dielectric elastomer actuators (DEAs) are attracting much attention as candidates for next-generation flexible actuation. Among various DE matrices, polyacrylate rubber (AR) is especially promising owing to their intrinsically high dielectric constant (ε_r) and good mechanical performance. In particular, its mechanical behavior is close to that of porcine bladder tissue, making it a potentially good material for soft biomedical actuators for artificial bladder constructs. To achieve high actuated strain, which requires high ε_r, high breakdown strength, and low elastic modulus, an AR DE composite filled with silane-functionalized TiO₂ was fabricated, exhibiting good electromechanical performance enabled by strengthened interfacial polarization. To improve compatibility between TiO₂ and AR matrix, TiO₂ was preferentially modified with a silane coupling agent (CA) that features a double bond as its functional group, which can be introduced on TiO₂ surface and participate in vulcanization with AR, thereby forming co-crosslinking bridges that strengthen interfacial bonding, improve filler dispersion, and increase interfacial polarizability within the matrix. As a result, at relatively low filler loadings, the composite exhibits a significantly increased ε_r, while maintaining low modulus, low dielectric loss and high elasticity. The 10 CA@TiO₂/AR composite exhibits a maximal actuated strain of 7.9% at 31.9 kV/mm without pre-stretch, which is 1.48 times that of pure AR and 1.32 times that of the 10 TiO₂/AR composite.

Background: Robot-assisted kidney transplantation (RAKT) has currently become an effective alternative to open kidney transplantation (OKT), which has long been considered the gold standard for kidney transplant surgery. This study aimed to summarize our initial experience with RAKT and explore its safety and feasibility. Materials and methods: Ten cases of RAKT, including 8 cases of deceased-donor kidney transplantation and 2 cases of living-donor kidney transplantation, were performed at our center from March 2023 to November 2023. Perioperative clinical data and follow-up results of patients were collected and statistically analyzed. Results: All RAKT surgeries were performed successfully with no complications. The average operative time was 297.90 ± 65.59 minutes, and the median estimated blood loss was 100 mL. The average serum creatinine level decreased from 918.14 ± 166.63 μmol/L preoperatively to 109.89 ± 29.89 μmol/L at discharge. The postoperative outcomes of RAKT from both deceased and living donors were satisfactory during the follow-up period. Conclusions: Robot-assisted kidney transplantation is an effective alternative to OKT and is suitable for both deceased- and living-donor kidney transplantations. The short-term postoperative follow-up results were satisfactory, and the postoperative complications were acceptable. Robot-assisted kidney transplantation appears to be a safe and feasible procedure for transplantation teams skilled in OKT and robot-assisted surgery. This study is an exploratory research providing preliminary experience, and future large-sample controlled studies are needed to further verify its safety.

Three-dimensional (3D) printing and tissue engineering offer patient-specific strategies for auricular reconstruction, but bibliometric structure alone cannot establish technical maturity or clinical value. We combined bibliometric mapping of English-language Articles and Reviews in the Web of Science Core Collection (2014–2025) with a translational evidence map. The locked corpus comprised 169 publications (143 Articles and 26 Reviews) and 4291 citations at the 12 June 2026 snapshot. Annual output, countries, institutions, authors, journals, highly cited records, author-keyword co-occurrence, and temporal terminology were analyzed. Citation-age sensitivity used citations per publication-year (CPY), year-normalized scores, and within-year percentiles. Record-level coding evaluated technical routes, materials, cell systems, construct scale, evidence stage, scientific endpoints, reporting completeness, and barriers. Among Articles, 40 (28.0%) were in vitro only, 41 (28.7%) reached small-animal testing, four (2.8%) reached large-animal testing, and nine (6.3%) reported human evidence; only one was comparative clinical research. Chondrogenesis or extracellular-matrix outcomes were reported in 84 Articles (58.7%), whereas vascularization, clinical/aesthetic outcomes, and long-term safety/adverse events were each reported in ≤6.3%. The field is expanding internationally but remains predominantly preclinical; progress requires standardized reporting, native-cartilage comparators, long-term shape and safety assessment, and larger-animal and comparative clinical validation.