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Aims To investigate the capability, properties, and molecular mechanism of inulin fermentation by lactic acid bacteria (LAB) from Sichuan pickle. Methods and results A total of 79 LAB strains were purified from 30 aged Sichuan pickle brine samples, and only 21 Lactiplantibacillus plantarum strains (26.58%, 21/79) derived from 15 samples grew well through utilizing inulin as a carbon source. The fermentation tests through using long-chain inulin (lc-inulin) as a carbon source showed that only 6 L. plantarum strains grew well, while other 15 strains could only utilize short-chain oligofructose (FOS), and thin-layer chromatography analysis evidenced a strain specificity of inulin consumption patterns. Lactiplantibacillus plantarum YT041 is a vigorous inulin fermenter, and whole genome sequencing data revealed that sacPTS1 and fosRABCDXE operons might be associated with the fermentation of FOS and lc-inulin, respectively. Conclusions The phenotype of inulin consumption is commonly present in LAB from Sichuan pickle, which is strain-specific and largely depends on their specific ecological niche and degree of polymerization. [ABSTRACT FROM AUTHOR]

To investigate the prediction value of a radiomics model based on apparent diffusion coefficient (ADC) maps for pelvic lymph node metastasis (PLNM) in patients with stage IB–IIA cervical squamous cell carcinoma (CSCC). A total of 153 stage IB–IIA CSCC patients who underwent preoperative MRI including DWI from January 2015 to October 2017 were retrospectively studied and divided into a training cohort (n = 102) and a validation cohort (n = 51). Radiomics features were extracted from the ADC maps. The one-way ANOVA method, Mann-Whitney U test and Pearson's correlation analysis were used for selecting radiomics features. Logistic regression analyses were used to develop the model. ROC analyses were used to evaluate the prediction performance of the model. Clinical stage, tumor diameter, and MR-reported lymph node (LN) status were significantly associated with LN status (p < 0.05 for both the training and validation cohorts). The radiomics model, which incorporated clinical stage, MR-reported LN status, and grey-level non-uniformity, showed good predictive performance in the training group (AUC 0.864; 95% CI, 0.782 – 0.924) and the validation group (AUC 0.870; 95% CI, 0.747 – 0.948). The performance of the radiomics model was significantly better than that of each predictive factor alone. The presented radiomics model, a non-invasive preoperative prediction tool, has the potential to have more predictive efficacy than clinical and radiological factors for differentiating between metastatic and non-metastatic lymph nodes. A radiomics model derived from the ADC maps of primary lesions demonstrated good performance for predicting PLNM in stage IB-IIA CSCC patients and may help to improve clinical decision-making. [ABSTRACT FROM AUTHOR]