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The article presents a study on the first enantioselective oxidative tandem cyclizations under palladium catalysis using nitrogen atom-based nucleophiles and molecular oxygen as the sole oxidant in the U.S. Palladium-catalyzed tandem ring formation reactions are versatile and powerful tools to construct complex polycyclic products. The method used in this study provides a direct access to enantioenriched and structurally versatile indolines.

Background: Humans are constantly exposed to various volatile organic compounds (VOCs) because of their widespread sources and characteristic of easy evaporation. Existing evidence regarding the association between VOC exposure and osteoarthritis (OA) risk is limited., Purpose: This study aimed to investigate the associations between individual urinary VOC metabolites (VOCMs) and the VOCM mixture, representing internal exposure levels of VOCs, with prevalent OA risk and to explore the mediating effect of aging and oxidative stress (OS) in these associations., Methods: Data from the National Health and Nutrition Examination Surveys 2005-2020 were analyzed. Weighted generalized linear regression was employed to explore the associations between individual VOCMs and OA risk, as well as aging and OS biomarkers. A five-repeated ten-fold cross-validation elastic net model was used to identify critical VOCMs for the weight quantile sum (WQS) analysis, which was performed to explore the VOCM mixture and OA risk association. Parallel and serial mediation analyses were conducted to identify the potential mediators and mediation pathways., Results: This study included 6578 American adults aged ≥40 years, among whom 1052 (16.0 %) individuals reported prevalent OA. Urinary levels of N-acetyl-S-(benzyl)-L-cysteine, mandelic acid and phenylglyoxylic acid were positively associated with OA risk. Eleven VOCMs with nonzero coefficients were identified and included in the WQS analysis, and results revealed an average increase of 24.4 % in OA risk (OR = 1.244, 95 % CI: 1.041, 1.486) per one-quantile increment in the VOCM mixture. Two aging biomarkers, phenotypic age and biological age, parallelly mediated the association between the VOCM mixture and OA risk, with mediation effect proportions of 9.0 % and 16.4 %, respectively., Conclusions: Exposure to VOCs is associated with an increased OA risk in middle-to-old aged American adults. The mediating effect of aging contributes to the association between co-exposure to VOCs and OA risk. Further prospective studies are required to substantiate these findings., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Background and Objective: Clinical prognosis prediction plays an important role in clinical research and practice. The construction of prediction models based on electronic health record data has recently become a research focus. Due to the lack of external validation, prediction models based on single-center, hospital-specific datasets may not perform well with datasets from other medical institutions. Therefore, research investigating prognosis prediction model construction based on a collaborative analysis of multi-center electronic health record data could increase the number and coverage of patients used for model training, enrich patient prognostic features and ultimately improve the accuracy and generalization of prognosis prediction., Materials and Methods: A web service for individual prognosis prediction based on multi-center clinical data collaboration without patient-level data sharing (POPCORN) was proposed. POPCORN focuses on solving key issues in multi-center collaborative research based on electronic health record systems; these issues include the standardization of clinical data expression, the preservation of patient privacy during model training and the effect of case mix variance on the prediction model construction and application. POPCORN is based on a multivariable meta-analysis and a Bayesian framework and can construct suitable prediction models for multiple clinical scenarios that can effectively adapt to complex clinical application environments., Results: POPCORN was validated using a joint, multi-center collaborative research network between China and the United States with patients diagnosed with colorectal cancer. The performance of the models based on POPCORN was comparable to that of the standard prognosis prediction model; however, POPCORN did not expose raw patient data. The prediction models had similar AUC, but the BMA model had the lowest ECI across all prediction models, indicating that this model had better calibration performance than the other models, especially for patients in Chinese hospitals., Conclusions: The POPCORN system can build prediction models that perform well in complex clinical application scenarios and can provide effective decision support for individual patient prognostic predictions., (Copyright © 2018 Elsevier Inc. All rights reserved.)