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Objectives: To explore whether radiomics-based machine learning (ML) models could outperform conventional diagnostic methods at identifying vulnerable lesions on coronary computed tomographic angiography (CCTA). Methods: In this retrospective study, 36 heart transplant recipients with coronary heart disease (CAD) and end-stage heart failure were included. Pathological cross-section samples of 350 plaques were collected and coregistered to patients' preoperative CCTA images. A total of 1184 radiomic features were extracted from CCTA images. Through feature selection and stratified fivefold cross-validation, we derived eight radiomics-based ML models for lesion vulnerability prediction. An independent set of 196 plaques from another 8 CAD patients who underwent heart transplants was collected to validate radiomics-based ML models' diagnostic accuracy against conventional CCTA feature-based diagnosis (presence of at least 2 high-risk plaque features). The performance of the prediction models was assessed by the area under the receiver operating characteristic curve (AUC) with 95% confidence intervals (CI). Results: The training group used to develop radiomics-based ML models contained 200/350 (57.1%) vulnerable plaques and the external validation group was composed of 67.3% (132/196) vulnerable plaques. The radiomics-based ML model based on eight radiomic features showed excellent cross-validation diagnostic accuracy (AUC: 0.900 ± 0.033). In the validation group, diagnosis based on conventional CCTA features demonstrated moderate performance (AUC: 0.656 [95% CI: 0.593 –0.718]), while the radiomics-based ML model showed higher diagnostic ability (0.782 [95% CI: 0.710 –0.846]). Conclusions: Radiomics-based ML models showed better diagnostic ability than the conventional CCTA features at assessing coronary plaque vulnerability. Key Points: • CCTA has great potential in the diagnosis of vulnerable coronary artery lesions. • Radiomics model built through CCTA could discriminate coronary vulnerable lesions in good diagnostic ability. • Radiomics model could improve the ability of vulnerability diagnosis against traditional CCTA method, sensitivity especially. [ABSTRACT FROM AUTHOR]

This study investigated the causal effect of retirement on the labor supply. We used male workers in China as an example and selected work hours as a measure of labor supply. The study employed two methods, namely fuzzy regression discontinuity and two-stage least squares, to analyze the impact of retirement on the work hours of the older adults based on data from the China Health and Retirement Longitudinal Study in 2015. Results show that retirement did not significantly reduce the labor supply. However, its impact on the supply of different types of labor was inconsistent. We also found that retired old adults tended to allocate more work hours to self-employment. Policy implications are as following. There's room for increasing retirement age, but it may not be as effective as expected in increasing the level of labor supply. If a delay retirement policy is to be implemented, we should pay attention to the side effects on the normal replacement of labor in the job market and maintaining a reasonable turnover rate by implementing a flexible retirement system. Moreover, establishing a good job market environment for older adults as well as a mechanism and system for retired older adults with high human capital accumulation to return to the labor market are also recommended to increase the productivity level of the labor force. [ABSTRACT FROM AUTHOR]

Abstract: The potential harm of heavy metals is a primary concern in application of sludge to the agricultural land. A pot experiment was conducted to evaluate the effect of two sludges on fractionation of Zn and Cu in soil and their phytotoxicity to pakchoi. The loamy soil was mixed with 0%, 20%, 40%, 60% and 80% (by weight) of digested sewage sludge (SS) and composted sludge (SC). The additions of the both sludges caused a significant raise in all fractions, resulting in that exchangeable (EXCH) and organic matter (OM) became predominance for Zn and organic bound Cu occupied the largest portion. There was more available amount for Zn and Cu in SS treatments than SC treatments. During the pot experiment, the concentration of Zn in EXCH, carbonate (CAR) and OM and Cu in EXCH and OM fractions decreased in all treatments, so their bioavailability reduced. Germination rate and plant biomass decreased when the addition rate was high and the best yield appeared in 20% mixtures at the harvest of pakchoi. The two sludges increased tissue contents of Zn and Cu especially in the SS treatments. Zn in pakchoi was not only in relationship to ΔEXCH and ΔCAR forms but also in ΔOM forms in the sludge-soil mixtures. Tissue content of Cu in pakchoi grown on SC-soils could not be predicted by ΔEXCH. These correlation rates between Zn and Cu accumulation in pakchoi and variation of different fractions increased with time, which might indicate that sludges represented stronger impacts on the plant in long-term land application. [Copyright &y& Elsevier]