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Objectives This study aims to build a machine learning (ML) model to predict the recurrence probability for postoperative non-lactating mastitis (NLM) by Random Forest (RF) and XGBoost algorithms. It can provide the ability to identify the risk of NLM recurrence and guidance in clinical treatment plan. Methods This study was conducted on inpatients who were admitted to the Mammary Department of Shuguang Hospital affiliated to Shanghai University of Traditional Chinese Medicine between July 2019 to December 2021. Inpatient data follow-up has been completed until December 2022. Ten features were selected in this study to build the ML model: age, body mass index (BMI), number of abortions, presence of inverted nipples, extent of breast mass, white blood cell count (WBC), neutrophil to lymphocyte ratio (NLR), albumin-globulin ratio (AGR) and triglyceride (TG) and presence of intraoperative discharge. We used two ML approaches (RF and XGBoost) to build models and predict the NLM recurrence risk of female patients. Totally 258 patients were randomly divided into a training set and a test set according to a 75%-25% proportion. The model performance was evaluated based on Accuracy, Precision, Recall, F1-score and AUC. The Shapley Additive Explanations (SHAP) method was used to interpret the model. Results There were 48 (18.6%) NLM patients who experienced recurrence during the follow-up period. Ten features were selected in this study to build the ML model. For the RF model, BMI is the most important influence factor and for the XGBoost model is intraoperative discharge. The results of tenfold cross-validation suggest that both the RF model and the XGBoost model have good predictive performance, but the XGBoost model has a better performance than the RF model in our study. The trends of SHAP values of all features in our models are consistent with the trends of these features’ clinical presentation. The inclusion of these ten features in the model is necessary to build practical prediction models for recurrence. Conclusions The results of tenfold cross-validation and SHAP values suggest that the models have predictive ability. The trend of SHAP value provides auxiliary validation in our models and makes it have more clinical significance.

Objective To describe a minimally invasive comprehensive treatment for granulomatous lobular mastitis (GLM) and compare its effect with the existing methods, particularly in terms of its recurrence rate and esthetic outcomes. Methods This retrospective study reviewed 69 GLM patients receiving the minimally invasive comprehensive treatment. Patients’ information, including age, clinical features, image characteristics, histopathological findings, mastitis history, treatment process, operative technique, recurrence, and esthetic effect, was evaluated. Results All patients were female with a median age of 32 (range 17–55) years. Hospital stays ranged from 2 to 34 days, with a median of 6 days. The shortest time for complete rehabilitation was 2 days and the longest time was 365 days, with a median of 30 days. After a median follow-up of 391 days (range 162–690), 7 patients (10.14%) relapsed. The average cosmetic score was 2.62 ± 0.57 points and was mainly related to the past treatment, especially the surgical history. Conclusion Minimally invasive comprehensive treatment is a new method for the treatment of GLM, ensuring a therapeutic effect while maintaining breast beauty.

The effect of intramammary inoculation of Lactobacillus perolens CRL 1724 on bovine udders at drying off was evaluated through histological examination of the canal and cistern tissues. The persistence of the strain in the udder 7 d post inoculation was also determined. Lb. perolens CRL 1724 was recovered from all mammary quarters and no clinical signs or teat damage were observed after inoculation of 106 cfu/ml. The udders showed a normal structural aspect and there were no modifications of the milk appearance. Lb. perolens CRL 1724 cells were evidenced on the surface of the epithelial cells of the cistern without causing any morphological modifications or cell alterations. Lb. perolens CRL 1724 produces a mild inflammatory reaction, characterized by recruitment of neutrophils to the epithelial zone and a slight hyperaemia into blood vessels. This preliminary study provides important information for further studies directed towards the inclusion of Lb. perolens CRL 1724 in the design of probiotic products for preventing bovine mastitis in non-lactating dairy cows.