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Codonopsis pilosula (C. pilosula) is a renowned traditional Chinese medicine, and its geographical origin plays a crucial role in determining its quality. Therefore, advanced techniques are required to determine the geographical origin of C. pilosula. In this study, we collected a total of 210 samples of C. pilosula from seven prominent production areas in China. Four stable isotope ratios (δ 13C, δ 15N, δ 18O and δ 2H) and 42 elements were analyzed together for origin traceability and farming authentication purposes. Analysis of variance (ANOVA) and principal component analysis (PCA) were used to compare the stable isotope ratios and elements content, and statistically significant differences were found among C. pilosula samples from 7 geographical regions (p < 0.05). Linear discriminant analysis (LDA), k-nearest neighbor (KNN), random forest (RF), and support vector machine (SVM) were implemented to construct models for C. pilosula authentication. Among these models, the SVM model was suggested as the optimal option for identifying the origin of C. pilosula based on its superior discriminant accuracy rate (100%) and predictive accuracy rate (100%). Thus, this approach could serve as a crucial alternative method for ensuring authenticity and combatting issues of origin mislabeling and fraudulent activities associated with C. pilosula products. • δ 2H, δ 13C, δ 15N, and δ 18O in C. pilosula from 7 regions exhibited notable variations. • Combine stable isotopes with multi-elements to improve discrimination accuracy. • The SVM model was effective in discriminating C. pilosula samples from 7 regions. [ABSTRACT FROM AUTHOR]

Background: Wrist arthroscopy technology is a surgical technology invented in recent years and widely used in clinical treatment of various wrist diseases. This study uses the methods of bibliometrics and visual analysis to understand the global research status, research hotspots, and future development trends of wrist arthroscopy., Methods: The relevant literature of global publications on wrist arthroscopy from 2013 to 2023 was extracted from the Web of Science Core Collection database, and the annual output, cooperation, hot spots, research status, and development trend of this field were analyzed by using the bibliometric software (VOSviewers, CiteSpace, and the R package "Bibliometrix")., Results: A total of 635 articles were included, from 2013 to 2023, the number of publications related to wrist arthroscopy showed an overall upward trend, the USA, France, and China are the top 3 countries in terms of the number of publications, whereas Mayo Clinic is the institution with the highest number of publications, Ho PC holds a core position in this field, keyword analysis indicates that the research hotspots are the applications of wrist arthroscopy in triangular fibrocartilage complex injuries, scaphoid nonunion, and avascular necrosis of the lunate., Conclusion Subsections: Wrist arthroscopy has shown tremendous potential in treating various wrist diseases. However, there are still some challenges in its research domain. With continuous deep research, strengthened international collaboration, and ongoing technological advancements, wrist arthroscopy has the potential to become the standard treatment in hand surgery, offering more efficient and safer treatment options for patients worldwide., Competing Interests: The authors have no conflicts of interest to disclose., (Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.)

How will the dual structural effects, represented by industrial structure and energy structure, affect the future correlation between economic growth and CO 2 emissions? Taking Jilin Province as an example, this study explores the dynamic driving mechanism of dual structural effects on the correlation between economic growth and CO 2 emissions by innovatively building an integrated simulation model from 1995 to 2015 and setting different scenarios from 2016 to 2050. Correspondingly, the concept of marginal utility and the method of variance decomposition analysis are introduced to reveal the mechanism. The results show that the energy structure is different while the industrial structure tends to be similar when CO 2 emissions reach the peak under different scenarios. The slower the dual structure adjustment, the more significant the upward trend appears before the peak. The contribution of the dual structural effects to CO 2 emissions caused by unit GDP growth is basically the same in peak year. With the transformation of socio-economy, the positive driving effect of the industrial structure will gradually weaken, while the negative driving effect of the energy structure will gradually increase. The methods and results presented can provide insights into sensible trade-offs of CO 2 emissions and economic growth in different countries/regions during structural transitions.

Background: Current studies on the COVID-19 depicted a general incubation period distribution and did not examine whether the incubation period distribution varies across patients living in different geographical locations with varying environmental attributes. Profiling the incubation distributions geographically help to determine the appropriate quarantine duration for different regions., Methods: This retrospective study mainly applied big data analytics and methodology, using the publicly accessible clinical report for patients (n = 543) confirmed as infected in Shenzhen and Hefei, China. Based on 217 patients on whom the incubation period could be identified by the epidemiological method. Statistical and econometric methods were employed to investigate how the incubation distributions varied between infected cases reported in Shenzhen and Hefei., Results: The median incubation period of the COVID-19 for all the 217 infected patients was 8 days (95% CI 7 to 9), while median values were 9 days in Shenzhen and 4 days in Hefei. The incubation period probably has an inverse U-shaped association with the meteorological temperature. The warmer condition in the winter of Shenzhen, average environmental temperature between 10 °C to 15 °C, may decrease viral virulence and result in more extended incubation periods., Conclusion: Case studies of the COVID-19 outbreak in Shenzhen and Hefei indicated that the incubation period of COVID-19 had exhibited evident geographical disparities, although the pathological causality between meteorological conditions and incubation period deserves further investigation. Methodologies based on big data released by local public health authorities are applicable for identifying incubation period and relevant epidemiological research.

Introduction: Current studies estimated a general incubation period distribution of COVID-19 based on early-confirmed cases in Wuhan, and have not examined whether the incubation period distribution varies across population segments with different travel histories. We aimed to examine whether patients infected by community transmission had extended incubation periods than the early generation patients who had direct exposures to Wuhan., Methodology: Based on 4741 patient case reports from municipal centers of disease control by February 21, 2020, we calculated the incubation periods of 2555 patients with clear epidemiological survey information and illness development timeline. All patients were categorized into five groups by their travel histories. Incubation period distributions were modeled for each group by the method of the posterior Weibull distribution estimation., Results: Adults aged 30 to 59 years had the most substantial proportion of confirmed cases in China. The incubation period distribution varied slightly across patient groups with different travel histories. Patients who regularly lived in Wuhan and left to other locations before January 23, 2020 had the shortest posterior median value of 7.57 days for the incubation period, while the incubation periods for persons affected by local community transmission had the largest posterior median of incubation periods, 9.31 days., Conclusions: The median incubation period for all patients infected outside Wuhan was 9 days, a bit of more extended than the early estimated 5-day incubation period that was based on patients in Wuhan. Our findings may imply the decreases of virulence of the COVID-19 virus along with intergenerational transmission., Competing Interests: No Conflict of Interest is declared, (Copyright (c) 2020 Zuopeng Xiao, Xi Xie, Wenbo Guo, Zhiqiang Luo, Jianxiang Liao, Feiqiu Liang, Qingfeng Zhou, Te Zheng, Laiwei Han.)