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Objective To develop a machine learning prediction model for histologic chorioamnionitis (HCA) in patients with preterm premature rupture of membranes (PPROM) after delivery. Methods A total of 512 pregnant women who were diagnosed with PPROM at 28~36+6 weeks in our hospital were enrolled in this study. After 31 clinical items consisting of general information, maternal history, laboratory data, and imaging parameters were collected for each subject, they were randomly divided into a training set (n=358) and a testing set (n=154) in a ratio of 7:3. Least absolute shrinkage and selection operator (LASSO) algorithm was used to identify independent predictors in the training set. Based on these factors (reproductive tract infection, ultrasound fetal weight, gestational age at PPROM, maximum body temperature before antibiotics, number of previous uterine operations, and interval between rupture of membranes and antibiotic use), 6 machine learning models, including support vector machine (SVM), logistic regression (LR), multilayer perceptron (MLP), random forest (RF), extreme gradient boosting (XGB) and decision tree (DT) were developed. Area under the curve (AUCs) value was used to compare the prediction efficiency of the built models. Then prediction efficiency and clinical applicability of optimal model were evaluated to calculate the importance of risk factors. Results Among 6 machine learning algorithms, the SVM model performed best with an accuracy of 0.862, sensitivity of 0.840, and specificity of 0.750 in the testing set. The predicted values derived from the model were highly consistent with the actual situations in discrimination of calibration curve and decision curve analysis. SHapley Additive exPlanations (SHAP) plot prioritized the predictive weights of 6 risk factors, and reproductive tract infection was of most significant importance. Conclusion An SVM prediction model of HCA occurrence in PPROM patients is successfully constructed. Its excellent predictive ability contributes to guiding clinical treatment, improving adverse pregnancy outcomes, and promoting maternal and infant health.

Objective: To study the pharmacokinetics and bioequivalence of asparaginase loaded in hyaluronic acid-graft-poly(ethylene glycol)/ sulfobutylether-β-cyclodextrin nanocapsules (AHSP) in SD rats., Methods: The morphology of AHSP was observed under the transmission electron microscope and the particle size and zeta potential were measured. AHSP and free asparaginase were intravenously injected in rats, and the plasma asparaginase activity was measured at different time points after the injections. The pharmacokinetic parameters were calculated using the software DAS 2.1.1 to assess the bioequivalence of AHSP and free asparaginase., Results: AHSP had an average particle size of 413.80∓10.97 nm with a zeta potential of -20.37∓2.38 mV. The AUC(0-48 h) of AHSP and free asparaginase was 137.34∓1.82 U/mL and 46.38 ∓1.98 U/mL, and their AUC(0-∞) was 164.66∓6.88 U/mL and 51.44∓3.01 U/mL with half-lives of 4.62∓0.60 h and 1.86∓0.38 h, respectively. Compared with free AN, AHSP exhibited increased AUC(0-48 h), AUC(0-∞), and half-life by 2.24, 2.55 and 2.32 folds, respectively. The 90% confidential intervals of AUC(0-48 h), AUC(0-∞) and Cmax of the tested formulation were 75.0%-76.5%, 74.3%-76.1%, and 95.1%-96.7%, respectively., Conclusion: AHSP can improve the bioavailability and extend the biological half-life of asparaginase in rats, and AHSP and free asparaginase are not bioequivalent.

Objective: To study the effects on the survival rates and DNA damage of benzo[a]pyrene or lead alone or in combination in rat neurons in vivo., Methods: Primary cultures of rat cerebellar neurons were prepared from 8-day-old pups, 10 groups cultures in each experiments were used, (1) control group, (2) vehicle group (Equal volume of DMSO + S9-mix), (3) low dose lead group (PbAc 5 micromol/L), (4) high dose lead group (PbAc 50 micromol/L), (5) low dose BaP group (BaP 5 micromol/L+ S9-mix), (6) high dose BaP group (BaP 50 micromol/L + S9-mix), (7) low dose lead + low dose BaP group, (8) low dose lead + high dose BaP group, (9) high dose lead + low dose BaP group, (10) high dose lead + high dose BaP group. After 90 min administration, the neurons were collected by the method of trypsin digestion, the survival rates were detected by the method of Tapian-blue dying, Detect cracks on the DNA straps by the method of SCGE., Results: (1) The survival rates of all the administrated groups were significantly lower than that of control groups (P < 0.05, P < 0.01). (2) In the high-dose BaP group (group 6), groups combine administrated with BaP and lead, one or two of them at high dose (groups 8, 9, 10), the DNA damage were more serious than that of control groups (P < 0.01)., Conclusion: (1) Both BaP and lead with some vivo neurotoxicity, the effects of two toxicants can do concord. (2) Neuron DNA damage may be one of the mechanisms by which BaP result in toxicity on the cultured neurons.