Effect of shear wave elastography in predicting pathological responses to neoadjuvant chemotherapy in patients with breast cancer / 中华超声影像学杂志

Objective:To investigate the clinical value of shear wave elastography (SWE) in predicting pathological responses to neoadjuvant chemotherapy in breast cancer.Methods:According to the postoperative pathological responses, 56 patients who received neoadjuvant chemotherapy followed by surgical excision in the Fujian Cancer Hospital from August 2019 to September 2020 were divided into responders and non-responders. The relative change rates of tumor maximum diameter(ΔD2, ΔD4) and SWE stiffness (ΔEmax2, ΔEmax4, ΔEmean2, ΔEmean4) were assessed before NAC and after different NAC cycles (t2, t4). Clinical information, including age, T, N stages, ER, PR, HER2, Ki67, and molecular subtype were also considered as the variables. The independent influencing factors of pathological responses after neoadjuvant chemotherapy were obtained by logistic regression analysis and diagnostic test was carried out.Results:There were 23 cases as responders (41.0%, 23/56), and 33 cases as non-responders (58.9%, 33/56). Results of multivariate analysis showed ΔEmax4 and HER2 index were independent influencing factors of pathological responses ( OR=1.11, P<0.001; OR=31.81, P=0.002). Area under curve of the ΔEmax4 (AUC: 0.869, 95% CI: 0.746-0.941) was higher than that of HER2 (AUC: 0.690, 95% CI: 0.545-0.834). The combination of ΔEmax4 and HER2 gave the best prediction of pathological responses (AUC 0.930, 95% CI: 0.829-0.981). the sensitivity, specificity, diagnostic accuracy, postive predictive value, and negative predictive value were 78.26%, 96.97%, 75.23%, 94.73%, and 86.49%, respectively. Conclusions:ΔEmax4 and HER2 are independent predictors of pathological responses after neoadjuvant chemotherapy for breast cancer. Combined ΔEmax4 and HER2 can improve the predictive diagnostic efficacy of pathological responses to chemotherapy for breast cancer.

Non-destructive monitoring of netted muskmelon quality based on its external phenotype using Random Forest.

The internal phenotypes of netted muskmelon (Cucumis melo L. var. eticulates Naud.) are always associated with its external phenotypes. In this study, the parameters of external phenotypic traits were extracted from muskmelon images captured by machine vision, and the internal phenotypes of interest to us were measured. Pearson analysis showed that most external phenotypic traits were highly correlated with these internal phenotypes in muskmelon fruit. In this study, we used the random forest algorithm to predict muskmelon fruit internal phenotypes based on the significantly associated external parameters. Carotenoids, sucrose, and total soluble solid (TSS) were the three most accurately monitored internal phenotypes with prediction R-squared (R2) values of 0.947 (root-mean-square error (RMSE) = 0.019 mg/100 g), 0.918 (RMSE = 3.233 mg/g), and 0.916 (RMSE = 1.089%), respectively. Further, a simplified model was constructed and validated based on the top 10 external phenotypic parameters associated with each internal phenotype, and these parameters were filtered with the varImp function from the random forest package. The top 10 external phenotypic parameters correlated with each internal phenotype used in the simplified model were not identical. The results showed that the simplified models also accurately monitored the melon internal phenotypes, despite that the predicted R2 values decreased 0.3% to 7.9% compared with the original models. This study improved the efficiency and accuracy of real-time fruit quality monitoring for greenhouse muskmelon.

Abundance and diversity of nitrogen-fixing bacteria in rhizosphere and bulk paddy soil under different duration of organic management.

Denaturing gradient gel electrophoresis (DGGE) and quantitative real-time PCR (qPCR) approaches were used to assess respectively the molecular diversity and quantity of the nifH gene sequences in rhizosphere and bulk paddy soil under conventional management and different duration of organic management (2, 3, 5, 9 years). The phylogenetic distribution of clones based on nifH gene sequence showed that taxonomic groups were consisted of Alphaproteobacteria (27.6%), Betaproteobacteria (24.1%) and Gammaproteobacteria (48.3%). Members of the order Rhizobiales and Pseudomonadales were prevalent among the dominant diazotrophs. When the quantity of the nifH gene sequences was determined by qPCR, 2.27 × 10(5) to 1.14 × 10(6) copies/g of soil were detected. Except for 2 years organically managed soil, nifH gene copy numbers in organic soil, both rhizosphere and bulk, were significantly higher than in CM soil. Moreover, nifH gene copy numbers in the organic rhizosphere soil (3, 5, 9 years) were significantly higher than in bulk soil. The abundance and diversity of nitrogen-fixing bacteria tended to increase with duration of organic management but the highest number of nifH gene copies was observed in the rhizosphere and bulk soil of 5 years organic management. In addition, analysis of variance and canonical correspondence analysis (CCA) showed that C/N, C and N were important factors influencing the abundance and community structure of nitrogen-fixing bacterial.