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BackgroundWith the increasing use of radiomics in cancer diagnosis and treatment, it has been applied by some researchers to the preoperative risk assessment of endometrial cancer (EC) patients. However, comprehensive and systematic evidence is needed to assess its clinical value. Therefore, this study aims to investigate the application value of radiomics in the diagnosis and treatment of EC.MethodsPubmed, Cochrane, Embase, and Web of Science databases were retrieved up to March 2023. Preoperative risk assessment of EC included high-grade EC, lymph node metastasis, deep myometrial invasion status, and lymphovascular space invasion status. The quality of the included studies was appraised utilizing the RQS scale.ResultsA total of 33 primary studies were included in our systematic review, with an average RQS score of 7 (range: 5–12). ML models based on radiomics for the diagnosis of malignant lesions predominantly employed logistic regression. In the validation set, the pooled c-index of the ML models based on radiomics and clinical features for the preoperative diagnosis of endometrial malignancy, high-grade tumors, lymph node metastasis, lymphovascular space invasion, and deep myometrial invasion was 0.900 (95%CI: 0.871–0.929), 0.901 (95%CI: 0.877–0.926), 0.906 (95%CI: 0.882–0.929), 0.795 (95%CI: 0.693–0.897), and 0.819 (95%CI: 0.705–0.933), respectively.ConclusionsRadiomics shows excellent accuracy in detecting endometrial malignancies and in identifying preoperative risk. However, the methodological diversity of radiomics results in significant heterogeneity among studies. Therefore, future research should establish guidelines for radiomics studies based on different imaging sources.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=364320 identifier CRD42022364320.

Deforestation poses a global threat to biodiversity and its capacity to deliver ecosystem services. Yet, the impacts of deforestation on soil biodiversity and its associated ecosystem services remain virtually unknown. We generated a global dataset including 696 paired-site observations to investigate how native forest conversion to other land uses affects soil properties, biodiversity, and functions associated with the delivery of multiple ecosystem services. The conversion of native forests to plantations, grasslands, and croplands resulted in higher bacterial diversity and more homogeneous fungal communities dominated by pathogens and with a lower abundance of symbionts. Such conversions also resulted in significant reductions in carbon storage, nutrient cycling, and soil functional rates related to organic matter decomposition. Responses of the microbial community to deforestation, including bacterial and fungal diversity and fungal guilds, were predominantly regulated by changes in soil pH and total phosphorus. Moreover, we found that soil fungal diversity and functioning in warmer and wetter native forests is especially vulnerable to deforestation. Our work highlights that the loss of native forests to managed ecosystems poses a major global threat to the biodiversity and functioning of soils and their capacity to deliver ecosystem services. [ABSTRACT FROM AUTHOR]

The aging degree of rice has a direct influence on its eating quality, and the requirements for the aging degree of rice during processing vary according to the form of final products. In order to determine the correlation indexes and threshold intervals of rice suitable for the processing of cooked rice and rice noodles and to establish a rapid method to identify the eating quality of cooked rice and rice noodles, this study measured the biochemical and gelatinization properties of rice with different aging degrees stored under accelerated conditions and evaluated the eating quality attributes of cooked rice and rice noodles made from aged rice. The data obtained were analyzed by principal component analysis (PCA), cluster analysis (CA) and stepwise regression (SR). The aging degree of rice was detected using acid-base indicators and L*, a* and b* were recorded. Finally, the color was restored by image processing software to develop a colorimetric card for rapidly identifying the eating quality of cooked rice and rice noodles based on rice grain quality. The results showed that the regression equation between the comprehensive score of cooked rice (Y) and its fatty acid content (X) was Y = 7.729 − 0.236X. Based on Y, the quality of cooked rice could be divided into excellent (Y ≥ 2.361), medium (− 1.039 ≤ Y 37 mg/100 g, respectively. The regression equation between the comprehensive score (Y) and fatty acid content (X) of rice noodles was Y = − 17.030 + 1.021X − 0.015X2. Likewise, the quality of rice noodles could be divided into 3 grades: excellent (Y ≥ 0.244), medium (− 1.589 ≤ Y 45 mg/100 g, respectively. The colorimetric card based on fatty acid content allows direct identification of the suitability of rice for the processing of cooked rice and rice noodles, which will providing a basis and guidance for the processing of rice grains.