Soybean ethylene response factors GmENS1 and GmENS2 promote nodule senescence.

The final phase in root nodule development is nodule senescence. The mechanism underlying the initiation of nodule senescence requires further elucidation. Here, we investigated the intrinsic signals governing soybean (Glycine max L. Merr.) nodule senescence, uncovering ethylene as a key signal in this intricate mechanism. Two AP2/ERF transcription factor genes, GmENS1 and GmENS2 (Ethylene-responsive transcription factors required for Nodule Senescence), exhibit heightened expression levels in both aged nodules and nodules treated with ethylene. Overexpression of either GmENS1 or GmENS2 accelerated senescence in soybean nodules, whereas the knockout or knockdown of both genes delayed senescence and enhanced nitrogenase activity. Furthermore, our findings indicated that GmENS1 and GmENS2 directly bind to the promoters of GmNAC039, GmNAC018, and GmNAC030, encoding three NAC transcription factors essential for activating soybean nodule senescence. Notably, the nodule senescence process mediated by GmENS1 or GmENS2 overexpression was suppressed in the soybean nac039/018/030 triple mutant compared with the wild-type control. These data indicate GmENS1 and GmENS2 as pivotal transcription factors mediating ethylene-induced nodule senescence through the direct activation of GmNAC039/GmNAC018/GmNAC030 expression in soybean.

The value of machine learning approaches in the diagnosis of early gastric cancer: a systematic review and meta-analysis.

BACKGROUND: The application of machine learning (ML) for identifying early gastric cancer (EGC) has drawn increasing attention. However, there lacks evidence-based support for its specific diagnostic performance. Hence, this systematic review and meta-analysis was implemented to assess the performance of image-based ML in EGC diagnosis. METHODS: We performed a comprehensive electronic search in PubMed, Embase, Cochrane Library, and Web of Science up to September 25, 2022. QUADAS-2 was selected to judge the risk of bias of included articles. We did the meta-analysis using a bivariant mixed-effect model. Sensitivity analysis and heterogeneity test were performed. RESULTS: Twenty-one articles were enrolled. The sensitivity (SEN), specificity (SPE), and SROC of ML-based models were 0.91 (95% CI: 0.87-0.94), 0.85 (95% CI: 0.81-0.89), and 0.94 (95% CI: 0.39-1.00) in the training set and 0.90 (95% CI: 0.86-0.93), 0.90 (95% CI: 0.86-0.92), and 0.96 (95% CI: 0.19-1.00) in the validation set. The SEN, SPE, and SROC of EGC diagnosis by non-specialist clinicians were 0.64 (95% CI: 0.56-0.71), 0.84 (95% CI: 0.77-0.89), and 0.80 (95% CI: 0.29-0.97), and those by specialist clinicians were 0.80 (95% CI: 0.74-0.85), 0.88 (95% CI: 0.85-0.91), and 0.91 (95% CI: 0.37-0.99). With the assistance of ML models, the SEN of non-specialist physicians in the diagnosis of EGC was significantly improved (0.76 vs 0.64). CONCLUSION: ML-based diagnostic models have greater performance in the identification of EGC. The diagnostic accuracy of non-specialist clinicians can be improved to the level of the specialists with the assistance of ML models. The results suggest that ML models can better assist less experienced clinicians in diagnosing EGC under endoscopy and have broad clinical application value.

The relationship between inflammatory cytokines and in-hospital complications of acute pancreatitis.

OBJECTIVE: Acute necrotic collection (ANC), acute peripancreatic fluid collection (APFC), pleural effusion, and ascites are common early complications of acute pancreatitis. This study aimed to investigate the relationship between 12 serum cytokines and the early complications and severity of acute pancreatitis (AP). METHODS: We retrospectively analyzed the clinical data of 307 patients with AP, and divided them into severe group and mild-to-moderate group according to the revised Atlanta classification. Propensity score matching was used to control for confounding factors. Binary logistic regression analysis was used to explore the relationship between cytokine levels and early complications of AP. RESULTS: Serum levels of interleukin (IL)-1ß, IL-5, IL-6, IL-8, IL-10, IL-17, and tumor necrosis factor-α were significantly higher in the severe acute pancreatitis (SAP) group than in the non-SAP group (p < .05). After adjusting for confounding factors, the upper quartiles of IL-6, IL-8, and IL-10 were associated with an increased risk of ANC compared with those in the lowest quartile (IL-6: quartile 3, odds ratio [OR] = 3.99, 95% confidence interval [CI] = 1.95-8.16; IL-8: quartile 4, OR = 2.47, 95% CI = 1.27-4.84; IL-10: quartile 2, OR = 2.22, 95% CI = 1.09-4.56). APFC was associated with high serum levels of IL-6 (quartile 3, OR = 1.32, 95% CI = 1.02-1.72), pleural effusions were associated with high serum levels of IL-1ß, IL-6, IL-8, and IL-10 (IL-1ß: quartile 4, OR = 2.36, 95% CI = 1.21-4.58; IL-6: quartile 3, OR = 4.67, 95% CI = 2.27-9.61; IL-8: quartile 3, OR = 2.95, 95% CI = 1.51-5.79; IL-10: quartile 4, OR = 3.20, 95% CI = 1.61-6.36), and high serum levels of IL-6 and IL-10 were associated with an increased risk of ascites (IL-6: quartile 3, OR = 3.01, 95% CI = 1.42-6.37; IL-10: quartile 3, OR = 2.57, 95% CI = 1.23-5.37). CONCLUSION: Serum cytokine levels, including IL-1ß, IL-6, IL-8, and IL-10 may be associated with the occurrence of early complications of AP. In daily clinical practice, IL-6 may be the most worthwhile cytokine to be detected.