Objective:To construct a predictive model of ≥ grade 2 radiation esophagitis (RE) in patients with esophageal cancer during concurrent radiochemotherapy (CRT) based on machine learning (ML) algorithm.Methods:A retrospective analysis was conducted on the clinical data of 276 patients with esophageal cancer who had received CRT at Lu'an Hospital of Anhui Medical University from January 2018 to January 2023. The occurrence of RE was evaluated according to grading criteria of RE developed by American Radiation Therapy Oncology Group, with ≥ grade 2 RE as the outcome event. After screening variables through the least absolute shrinkage and selection operator (LASSO) regression, the dataset was re-established. The dataset was then divided into training set ( n=193) and testing set ( n=83) in a 7∶3 ratio and included in four ML models: random forest (RF) , decision tree (DT) , extreme gradient boosting (XGBoost) , and support vector machine (SVM) . In the models, data training and model optimization were conducted in the training set, and model performance was evaluated in the testing set using the receiver operator characteristic (ROC) curve. The area under the curve (AUC) , accuracy, precision, sensitivity, and F1 score were calculated to assess the model. SHAP analysis was used to explain the optimal model. Results:By the end of follow-up, 91 cases (32.97%) of esophageal cancer patients had experienced ≥ grade 2 RE during CRT. There were statistically significant differences in tumor lesion length ( Z=-5.53, P<0.001) , Karnofsky performance status (KPS) score ( χ2=5.92, P=0.015) , the Eastern Cooperative Oncology Group (ECOG) score ( χ2=4.01, P=0.045) , hypertension ( χ2=15.35, P<0.001) , diabetes ( χ2=13.06, P<0.001) , white blood cell count ( Z=-6.59, P<0.001) , neutrophil count ( Z=-6.72, P<0.001) , and radiotherapy dose ( χ2=9.81, P=0.002) between ≥ grade 2 RE occurrence group ( n=91) and no occurrence group ( n=185) . After LASSO regression screening, 7 characteristic variables were ultimately selected, which were tumor lesion length, ECOG score, KPS score, neutrophil count, hypertension, diabetes, and radiotherapy dose. ROC curve analysis showed that the XGBoost model had better predictive performance, with an AUC of 0.90, accuracy of 0.82, precision of 0.80, sensitivity of 0.73, and F1 score of 0.76. The AUC, accuracy, precision, sensitivity, and F1 score of RF model were 0.89, 0.78, 0.76, 0.48, and 0.59, respectively. The AUC, accuracy, precision, sensitivity, and F1 score of DT model were 0.72, 0.72, 0.44, 0.60, and 0.52, respectively. The AUC of SVM model was 0.74, with an accuracy of 0.82, precision of 0.52, sensitivity of 0.88, and F1 score of 0.65. The XGBoost model was explained using SHAP analysis, which indicated that the tumor lesion length, neutrophil count, hypertension, diabetes, and radiotherapy dose had a strong predictive ability for the occurrence of ≥ grade 2 RE during CRT in esophageal cancer patients. Conclusions:The model established based on the XGBoost method has good predictive performance for the occurrence of ≥ grade 2 RE in esophageal cancer patients during CRT. Meanwhile, combined with SHAP analysis, it can provide an intuitive understanding of the impact of important features in the model on the outcome.

The bacterial ATP-competitive GyrB/ParE subunits of type II topoisomerase are important anti-bacterial targets to treat super drug-resistant bacterial infections. Herein we discovered novel pyrrolamide-type GyrB/ParE inhibitors based on the structural modifications of the candidate AZD5099 that was withdrawn from the clinical trials due to safety liabilities such as mitochondrial toxicity. The hydroxyisopropyl pyridazine compound 28 had a significant inhibitory effect on Gyrase (GyrB, IC₅₀ = 49 nmol/L) and a modest inhibitory effect on Topo IV (ParE, IC₅₀ = 1.513 μmol/L) of Staphylococcus aureus. It also had significant antibacterial activities on susceptible and resistant Gram-positive bacteria with a minimum inhibitory concentration (MIC) of less than 0.03 μg/mL, which showed a time-dependent bactericidal effect and low frequencies of spontaneous resistance against S. aureus. Compound 28 had better protective effects than the positive control drugs such as DS-2969 ( 5) and AZD5099 ( 6) in mouse models of sepsis induced by methicillin-resistant Staphylococcus aureus (MRSA) infection. It also showed better bactericidal activities than clinically used vancomycin in the mouse thigh MRSA infection models. Moreover, compound 28 has much lower mitochondrial toxicity than AZD5099 ( 6) as well as excellent therapeutic indexes and pharmacokinetic properties. At present, compound 28 has been evaluated as a pre-clinical drug candidate for the treatment of drug-resistant Gram-positive bacterial infection. On the other hand, compound 28 also has good inhibitory activities against stubborn Gram-negative bacteria such as Escherichia coli (MIC = 1 μg/mL), which is comparable with the most potent pyrrolamide-type GyrB/ParE inhibitors reported recently. In addition, the structure-activity relationships of the compounds were also studied.

A sensitive and effective method for determination of 16 kinds of antibiotics, including tetracycline, sulfonamide, fluoroquinolone and macrolide, in livestock and poultry manure using solid phase extraction-ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was established.Aiming at the chemical properties and sample impurities of the target, the parameters such as mass spectrum conditions, types of extraction and ultrasonic power were optimized.Finally, the samples were extracted with 50% acetonitrile in phosphate buffer solution (pH =4) for three times, followed by ultrasonic steaming, centrifugal and rotary, dilution, and purified by SAX-HLB.After sample loading, the solid phase was washed with 10 mL of methanol-acetone (80∶20, V/V), evaporated to near dryness at 35℃, and then re-dissolved and vortex mixed in 1 mL of 0.1% formic acid∶methanol (1∶1, V/V).The extracts were analyzed with UPLC-MS/MS and calculated by external standard method based on the monitored product ion.The results indicated that the average spiked recoveries of tetracycline, sulfonamide, fluoroquinolone and macrolide in manure were 56.4%-94.6% with relative standard deviations (RSDs) of 2.6%-19.8%, the LODs (S/N=3) were 0.01-2.50 μg/kg, and the LOQs (S/N=10) were 0.05-7.90 μg/kg.The method was simple with high stability, high sensitivity and good reproducibility, and suitable for the simultaneously determination of many antibiotics in animal and poultry manure.