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Soybean leaves, by-products of soybeans, are functional food supplements for overall health, displaying nutritional superiority and various functionalities; they are widely used for both consumption and as functional materials. This study analyzed the physiological activity (efficacy) of 47 soybean leaves harvested in 2019 and 2020. Differences based on cultivation year (2 years), seed coat color (three varieties), and the interaction of soybean cultivation year × seed coat color were determined using analysis of variance (ANOVA). DPPH radical scavenging activity varied with seed coat color, while uncoupling protein-1 (UCP-1) and nitric oxide (NO) exhibited significant differences by cultivation year. Items that displayed greater increases in 2020 than in 2019 among the six measures of physiological activity (efficacy) were estrogen receptor alpha, UCP-1, and NO production inhibitory activity, whereas ABTS and DPPH radical scavenging activities as well as estrogen activity declined. ANOVA confirmed significant differences in DPPH radical scavenging activity according to seed coat color as well as in UCP-1 and NO production inhibitory activity by cultivation year. Annual comparisons in the correlations of efficacy with ABTS and DPPH radical scavenging activities exhibited strong correlations at 2 years, despite climatic variation, thus potentially being classifiable as analysis items with high cultivation stability. However, other efficacies displayed vast differences in correlation between years. Climate change may affect the added value of agricultural products by reducing the production of by-product soybean leaves and changing their bioactive properties, so various countermeasures are needed. This annual variation may largely be attributed to climatic variations owing to open field cultivation. Geomjeong Kong-5 (black color), B16 Neoljeokseoritae (black color), Sorok Kong (yellow color), and Gangwonyanggu-1994-3709 (green–black color) were selected as superior soybean leaf sources with minimal annual variation and high stability against cultivation environments. Further research is needed to ensure that the leaves of the soybean can be used as a sustainable resource for the agricultural industry. The data from this study can be used as a basis for breeding and cultivating soybean leaves while maintaining high efficacy, regardless of the instability of the growing environment due to climatic variations.

The functionality of soybeans is an important factor in the selection and utilization of excellent soybean cultivars, and isoflavones are representative functional substances in soybeans, which exhibit effects on antioxidants, estrogen activity, and cancer, and prevent cardiovascular diseases. This study analyzed ABTS, DPPH, estrogen, ER (ER) alpha, UCP-1, and NO inhibition activities in 48 types of soybean cultivars, as well as the relationship with 19 isolated types of individual isoflavone derivatives. Statistical analysis was conducted to find individual isoflavone derivatives affecting physiological activities, revealing the high correlation of three types of derivatives: genistein 7-O-(6″-O-acetyl)glucoside (6″-O-acetylgenistin), genistein 7-O-(2″-O-apiosyl)glucoside, and glycitein. Based on these results, 15 types of soybean cultivars were selected (one control type, seven yellow types, six black types, and one green type), which have both high physiological activities and a high content of individual isoflavone derivatives. In addition, these high correlations were further verified through a genome-wide association study (GWAS) to determine the association between activities, substances, and genetic characteristics. This study comprehensively describes the relationship between the specific physiological activities of soybean resources, individual isoflavone derivative substances, and SNPs, which will be utilized for in-depth research, such as selection of excellent soybean resources with specific physiological activities.

The aim of this study was to analyze the physiological activity of 48 soybean resources harvested in 2020 to identify the soybean resources’ relationships with individual isoflavone compounds and their genetic properties. These data will subsequently be compared with the research results on soybeans harvested in 2019. Initially, with respect to the physiological activity (6 types) and substances (19 types), this study evaluated the differences between the cultivation year (two years), seed coat color (three colors), and the interaction of the year and seed coat color of soybeans through ANOVA. Among the physiological activities, there were differences in the estrogen, estrogen receptor alpha, and UCP-1 (uncoupling protein-1) activities depending on the cultivation year. Moreover, there were differences in NO (nitric oxide), revealing differences in the ABTS (2, 2′-azino-bis-3ethylbenzo-thiazoline-6-sulfonic acid) and DPPH (2, 2-diphenyl-2-picrylhydrazyl) radical scavenging activities due to the seed coat color and the interaction of the year and seed coat color. Soybeans harvested in 2020 exhibited increased ABTS, DPPH, and NO inhibitory activities and reduced estrogen, estrogen receptor alpha, and UCP-1 activities compared to those harvested in 2019. According to the ANOVA results, eight of the nineteen individual derivatives illustrated yearly differences, while three derivatives displayed differences due to the seed coat color. Secondly, according to the relationship between the efficacy, derivative substances, and genetic properties, it was determined that genistein 7-O-(2″-O-apiosyl)glucoside (F5) is the individual isoflavone derivative that affected the six types of physiological activity, on which the genome-wide association study (GWAS) showed no significant differences for genetic properties. These results were inconsistent with the 2019 data, where three types of individual compounds, including F5, were proposed as substances that correlated with efficacy and there was a high correlation with genetic properties. Therefore, this study selected B17, B23, B15, B24, and Y7 as excellent varieties that are stable and highly functional in the cultivation environment, producing only small annual differences. The results of this study will be utilized as basic data for predicting soybean varieties and their cultivation, which have high environmental stability under climate variation and properly retain the functional substances and efficacy.

This study investigated the anti-obesity effects of yuja pomace extract fermented with lactic acid bacteria in rats with high-fat diet-induced obesity over a period of eight weeks. Epididymal fat cell size was significantly smaller, by about 33%, in the treatment groups given yuja pomace extract fermented with lactic acid bacteria compared to the CON group. Electron microscopic observation of hepatocyte microstructure showed that the number of lipid droplets was lower in hepatocytes, the number of mitochondria was higher, along with distinct cristae, and the rough endoplasmic reticula were well developed with stacks of cisternae and ribosomes. Thus, it is believed that yuja pomace extract fermented with lactic acid bacteria, by influencing body weight and lipid accumulation, is effective in the prevention and treatment of obesity.

Background： Total hip arthroplasty （THA） in developmental dysplasia of the hip （DDH） is more complex than the normal hip, with large replacement risks and many complications.Although nonosteotomy THA is convenient to perform, femoral osteotomy shortening can avoid blood vessel and nerve traction injuries.This study aimed to compare osteotomy THA with nonosteotomy to determine reasonable options for operative management of DDH.Methods： Data on 48 DDH patients who underwent THA were analyzed retrospectively.The patients were divided into two groups： Group A 29 cases （nonosteotomy）, and group B 19 cases （osteotomy）.Harris and Western Ontario and McMaster Universities Osteoarthritis Index （WOMAC） scores, limb length discrepancy （LLD）, radiological data on the hip, and claudication were evaluated.Data were analyzed by using paired-sample Student＆#39;s t-test, independent-sample Student＆#39;s t-test, and Pearson＆#39;s Chi-square test;the test level was α =0.05.Results： Postoperative Harris （90.7 ＆#177; 5.1） and WOMAC scores （88.0 ＆#177; 10.6） were significantly improved compared with preoperative Harris （44.8 ＆#177; 5.7） and WOMAC scores （42.0 ＆#177; 5.3） in group A （P 〈 0.05）.Postoperative Harris （90.4 ＆#177; 2.8） and WOMAC scores （88.2 ＆#177; 5.9） were significantly improved compared with preoperative Harris （44.4 ＆#177; 4.2） and WOMAC scores （43.2 ＆#177; 4.3） in group B （P 〈 0.05）.One case of dislocation occurred in group A;after closed reduction, dislocation did not recur.In group A, 2 patients developed cutaneous branch injury of the femoral nerve, which spontaneously recovered without treatment.Postoperative LLD 〉2 cm was seen in one case in group A and five cases in group B.Postoperative claudication showed no significant difference between the two groups （P 〉 0.05）.No patients developed infection;postoperative X-rays showed that the location of the prosthesis was satisfactory, and the surrounding bone was not dissolved.Conclusions： THA is effective and safe for DDH.For unilateral high dislocation DDH patients with limb lengthening ≤4 cm and good tissue conditions, THA without femoral osteotomy may be considered.

Splenic artery aneurysm, without obvious symptoms, is a direct threat to the patient＇s life, once it ruptures as hemorrhagic shock.Imaging examinations have been the main diagnostic methods of splenic artery aneurysm, including ultrasound, computed tomography （CT）, magnetic resonance imaging, and digital subtraction angiography （DSA）.Although various inspective methods have their own advantages and disadvantages, abdominal CT examination is the most comprehensively applied method in clinical settings.The representative images of splenic artery aneurysm from a relatively large number of patients examined by CT are presented in this study.

Through epithelial-mesenchymal transition (EMT), cancer cells acquire enhanced ability of migration and invasion, stem cell like characteristics and therapeutic resistance. Notch signaling regulates cell-cell connection, cell polarity and motility during organ development. Recent studies demonstrate that Notch signaling plays an important role in lung cancer initiation and cross-talks with several transcriptional factors to enhance EMT, contributing to the progression of non-small cell lung cancer (NSCLC). Correspondingly, blocking of Notch signaling inhibits NSCLC migration and tumor growth by reversing EMT. Clinical trials have showed promising effect in some cancer patients received treatment with Notch1 inhibitor. This review attempts to provide an overview of the Notch signal in NSCLC: its biological significance and therapeutic application.

Twitter presents a valuable and relevant social media platform to study the prevalence of information and sentiment on vaping that may be useful for public health surveillance. Machine learning classifiers that identify vaping-relevant tweets and characterize sentiments in them can underpin a Twitter-based vaping surveillance system. Compared with traditional machine learning classifiers that are reliant on annotations that are expensive to obtain, deep learning classifiers offer the advantage of requiring fewer annotated tweets by leveraging the large numbers of readily available unannotated tweets. This study aims to derive and evaluate traditional and deep learning classifiers that can identify tweets relevant to vaping, tweets of a commercial nature, and tweets with provape sentiments. We continuously collected tweets that matched vaping-related keywords over 2 months from August 2018 to October 2018. From this data set of tweets, a set of 4000 tweets was selected, and each tweet was manually annotated for relevance (vape relevant or not), commercial nature (commercial or not), and sentiment (provape or not). Using the annotated data, we derived traditional classifiers that included logistic regression, random forest, linear support vector machine, and multinomial naive Bayes. In addition, using the annotated data set and a larger unannotated data set of tweets, we derived deep learning classifiers that included a convolutional neural network (CNN), long short-term memory (LSTM) network, LSTM-CNN network, and bidirectional LSTM (BiLSTM) network. The unannotated tweet data were used to derive word vectors that deep learning classifiers can leverage to improve performance. LSTM-CNN performed the best with the highest area under the receiver operating characteristic curve (AUC) of 0.96 (95% CI 0.93-0.98) for relevance, all deep learning classifiers including LSTM-CNN performed better than the traditional classifiers with an AUC of 0.99 (95% CI 0.98-0.99) for distinguishing commercial from noncommercial tweets, and BiLSTM performed the best with an AUC of 0.83 (95% CI 0.78-0.89) for provape sentiment. Overall, LSTM-CNN performed the best across all 3 classification tasks. We derived and evaluated traditional machine learning and deep learning classifiers to identify vaping-related relevant, commercial, and provape tweets. Overall, deep learning classifiers such as LSTM-CNN had superior performance and had the added advantage of requiring no preprocessing. The performance of these classifiers supports the development of a vaping surveillance system.

Various studies have evaluated the significance of Notch1 expression in breast cancer, but the results have ever been disputed. By using 21 studies involving 3867 patients, this meta-analysis revealed that the expression of Notch1 was significantly higher in breast cancer than in normal tissues (OR=7.21; 95%CI, 4.7-11.07) and that higher Notch1 expression was associated with transition from ductal carcinoma in situ (DCIS) to invasive cancer (OR=3.75; 95% CI, 1.8-7.78). Higher Notch1 activity was observed in the basal subtype of breast cancer (OR=2.53; 95% CI, 1.18-5.43). Moreover, patients with Notch1 overexpression exhibited significantly worse overall and recurrence-free survival. Our meta-analysis suggests that Notch inhibitors may be useful in blocking the early progression of DCIS and that the outcomes of clinical trials for Notch1-targeting therapeutics could be improved by the molecular stratification of breast cancer patients.

Background The objective of this study was to evaluate the effect of platinum-based drugs on nuclear-factor erythroid2 like 2 (NRF2) signaling in non-small cell lung cancer cell lines with or without Kelch-like ECH-associated protein 1 (KEAP1) mutations and to determine the role of NRF2 and KEAP1 on platinum-based drug treatment. Methods We used real-time PCR to assess relative mRNA expression and used western blotting and immunofluorescence assays to assess protein expression. Small interfering RNA and shuttle plasmids were used to modulate the expression of NRF2, wild-type KEAP1, and mutant KEAP1. Drug sensitivity to platinum-based drugs was evaluated with Cell Count Kit-8. Results We found that platinum-based therapies modified the NRF2 signaling pathway differently in KEAP1-mutated non-small cell lung cancer (NSCLC) cell lines compared with wild-type KEAP1 cell lines. The reactive degree of NRF2 signaling also varies between nedaplatin and cisplatin. The modification of NRF2 or KEAP1 expression in NSCLC cell lines disrupted downstream gene expression and cell sensitivity to platinum-based drugs. Finally, gene expression data retrieved from The Cancer Genome Atlas (TCGA) consortium indicated that KEAP1 mutation significantly affects NRF2 signaling activity in patients with NSCLC. Conclusions Our findings suggest that NRF2 signaling plays an indispensable role in NSCLC cell sensitivity to platinum-based treatments and provides a rationale for using NRF2 as a specific biomarker for predicting which patients will be most likely to benefit from platinum-based treatment.