Selective syntheses of leuconolam, leuconoxine, and mersicarpine alkaloids from a common intermediate through regiocontrolled cyclizations by Staudinger reactions

Selective syntheses of leuconolam, leuconoxine, and mersicarpine alkaloids bearing distinctive core structures were achieved through Staudinger reactions using a common intermediate. In the key cyclization step, water functioned like a switch to control which core structure to produce. The chemistry allowed for selective syntheses of the group of alkaloids from a simple intermediate through straightforward chemical operations

Predicting peritoneal carcinomatosis of gastric cancer: A simple model to exempt low-risk patients from unnecessary staging laparoscopy

BackgroundPeritoneal carcinomatosis (PC) of gastric cancer indicates a poor outcome and is mainly diagnosed by staging laparoscopy (SL). This study was designed to develop a risk stratification model based on the number of risk factors to exempt low-risk patients from unnecessary SL.MethodsThis was a retrospective cohort study based on a single institution between January 2015 and December 2019. SL is indicated for patients of advanced locoregional stage, and clinicopathologic characteristics of 535 consecutive patients were included. PC-associated variables were identified by logistic regression analysis. A risk stratification model based on the number of risk factors was constructed, and we defined its predictive value with a receiver operating characteristic (ROC) curve and negative predictive value.ResultsIn total, 15.9% of included patients were found to have PC during SL. Borrmann type IV, elevated CA125, and tumour diameter ≥5 cm were independent risk factors of PC. These three factors combined with cT4 were selected as predictive factors, and the number of predictive variables was significantly related to the possibility of PC (2.0%, 12.8%, 20.0%, 54.2%, and 100%, respectively). When the cutoff value is more than one predictive factor, the negative predictive value is 98.0%, with an area under the curve of 0.780. This model could exempt 29.8% of unnecessary SL compared to the indication of the current NCCN guideline.ConclusionsWe constructed a simple model to predict the probability of PC using the number of predictive factors. It is recommended that patients without any of these factors should be exempt from SL

Monitoring of a Nearshore Small Dolphin Species Using Passive Acoustic Platforms and Supervised Machine Learning Techniques

Passive acoustic monitoring (PAM) is increasingly being adopted as a non-invasive method for the assessment of ocean ecological dynamics. PAM is an important sampling approach for acquiring critical information about marine mammals, especially in areas where data are lacking and where evaluations of threats for vulnerable populations are required. The Indo-Pacific humpback dolphin (IPHD, Sousa chinensis) is a coastal species which inhabits tropical and warm-temperate waters from the eastern Indian Ocean throughout Southeast Asia to central China. A new population of this species was recently discovered in waters southwest of Hainan Island, China. An array of passive acoustic platforms was deployed at depths of 10–20 m (the preferred habitat of humpback dolphins), across sites covering more than 100 km of coastline. In this study, we explored whether the acoustic data recorded by the array could be used to classify IPHD echolocation clicks, with the aim of investigating the spatiotemporal patterns of distribution and acoustic behavior of this species. A number of supervised machine learning algorithms were trained to automatically classify echolocation clicks from the different types of short-broadband pulses recorded. The best performance was reported by a cubic support vector machine (Cubic SVM), which was applied to 19,215 5-min recordings (∼4.2 TB), collected over a period of 75 days at six locations. Subsequently, using spectrogram visualization and audio listening, human operators confirmed the presence of clicks within the selected files. Additionally, other dolphin vocalizations (including whistles, buzzes, and burst pulses) and different sound sources (soniferous fishes, snapping shrimps, human activities) were also reported. The detection range of IPHD clicks was estimated using a transmission loss (TL) model and the performance of the trained classifier was compared with data synchronously collected by an acoustic data logger (A-tag). This study demonstrates that the distribution and habitat use of a coastal and resident dolphin species can be monitored over a large spatiotemporal scale, using an array of passive acoustic platforms and a data analysis protocol that includes both machine learning techniques and spectrogram inspection

Roles of structural plasticity in chaperone HdeA activity are revealed by 19 F NMR

Multiple conformations of acid chaperone HdeA and their roles in activity

Safety and effects of a home-based Tai Chi exercise rehabilitation program in patients with chronic heart failure: study protocol for a randomized controlled trial

IntroductionChronic heart failure (CHF), as the final stage of the progression of many cardiovascular disorders, is one of the main causes of hospitalization and death in the elderly and has a substantial impact on patients' quality of life (QOL). Exercise-based cardiac rehabilitation (CR) has been shown to considerably enhance QOL and prognosis. Given the barriers to center-based CR faced by most developing countries in the form of expensive instruments, the development of home-based CR is necessary. Tai Chi, as an instrument-free exercise, has been shown to be successful in treating elderly CHF individuals. Fu Yang, as one of the academic concept of Traditional Chinese Medicine (TCM), believes that the fundamental pathogenesis of CHF is the gradual decline of Yang, and emphasizes the restoration of Yang physiological function in the treatment process. Therefore, we develope a home-based Tai Chi exercise rehabilitation program called Fu Yang Tai Chi (FYTC) for elderly CHF patients by combining the Fu Yang Theory of TCM with the CR theory. The objective of this study is to evaluate the effectiveness, acceptability, and safety of the program.Methods and analysisWe suggest conducting a parallel randomized controlled clinical trial with open label. Eighty CHF elderly participants will be randomly assigned in a 1:1 ratio to the FYTC rehabilitation program group or the moderate-intensity aerobic walking control group. Eligible participants will engage in either three sessions weekly of FYTC or walking exercise for 12 weeks. The primary outcome is the relative change in 6 min walk distance (6MWD). The secondary outcomes are the plasma levels of N-terminal pro-B-type natriuretic peptide (NT-proBNP), QOL, left ventricular ejection fraction (LVEF), left ventricular end-diastolic diameter (LVEDd), self-rating anxiety scale (SAS) and depression scale (SDS), exercise skills, and noninvasive hemodynamic monitoring. Throughout the trial, adverse events will be recorded for safety evaluation. Researchers who are blinded to the treatment allocation will analyze the data.Ethics and disseminationThis research was authorized by the Guang'anmen Hospital Ethics Committee of the Chinese Academy of Medical Sciences (2022-141-KY). Our findings will be shared online and in academic conferences as well as in peer-reviewed journals. Trial registration numberChiCTR2200063511

Air Quality and Residents’ Health in China: An Empirical Analysis Based on Spatial Simultaneous Equations

Large-scale air pollution has an impact on the health and travel of residents in China. First, this article uses the gravity model and finds that China’s air quality presents a typical spatial correlation network. The network structure has changed from complex to simple, indicating that China’s air quality is gradually improving. Second, this paper uses spatial simultaneous equations to study the effect of air quality on residents’ health. The results show that an increase in the air quality index of local and surrounding provinces will have a significant impact on the health of residents. The absolute and relative air quality affects the lives of residents. The decline in the health of residents from the previous period will prompt the government to adopt various pollution reduction policies, which will improve air quality in the current period. Based on the empirical research conclusions, this article makes policy recommendations

Air Quality and Residents’ Health in China: An Empirical Analysis Based on Spatial Simultaneous Equations

Large-scale air pollution has an impact on the health and travel of residents in China. First, this article uses the gravity model and finds that China’s air quality presents a typical spatial correlation network. The network structure has changed from complex to simple, indicating that China’s air quality is gradually improving. Second, this paper uses spatial simultaneous equations to study the effect of air quality on residents’ health. The results show that an increase in the air quality index of local and surrounding provinces will have a significant impact on the health of residents. The absolute and relative air quality affects the lives of residents. The decline in the health of residents from the previous period will prompt the government to adopt various pollution reduction policies, which will improve air quality in the current period. Based on the empirical research conclusions, this article makes policy recommendations

IBM Stock Forecast Using LSTM, GRU, Attention and Transformer Models

In the stock market, the change of stock price has always been the most concerned thing of shareholders. However, due to the uncertainty of the stock market, it is also very difficult to predict the trend of stock price. In this paper, first, we collected IBM\u27s stock price data from January 2, 1962 to August 21, 2017, and then we calculated the middle price of the stock. Next, we present four model approach to stock prediction. The method used in our study is known as LSTM, LSTM+GRU, Attention, and Transformer. We carried out several sets of experiments to test the validity of the analysis. The test results show that the LSTM and GRU model superposition method is more effective than other methods in predicting the stock price trend of IBM