Objective:To investigate the clinical phenotype and genetic characteristics of infantile epileptic spasm syndrome caused by BRWD3 gene mutation. Methods:Clinical data of a child with BRWD3 related infantile epileptic spasm syndrome who was admitted to Department of Pediatric Neurology of Linyi People′s Hospital on August 2, 2019 were collected and followed up, whole exome sequencing technology and Sanger sequencing were applied to verify the child and his parents, and the pathogenicity of mutation site was analyzed. The studies till June 2023 were searched with keywords of " BRWD3" in both English and Chinese databases of China National Knowledge Infrastructure, Wanfang, Online Mendelian Inheritance in Man, and PubMed. The clinical phenotype and genetic characteristics of patients with BRWD3 related epilepsy were summarized. Results:The patient was a 4 years and 4 months old boy, with a clinical phenotype including severe global development delay, focal seizures (the onset age was 4 months), epileptic spasm (the onset age was 6 months), autism, megacephaly, high forehead as well as hypsarrhythmia. The whole exome sequencing results showed a de novo and frameshift variation c.4318_4319del(p.Q1441Efs*20)(NM_153252) in the BRWD3 gene, and the variation was interpreted as pathogenic (PVS1+PS2+PM2) according to the American College of Medical Genetics and Genomics variant classification criteria and guidelines. A total of 7 English literature articles were retrieved reporting 16 cases of BRWD3 gene related epilepsy in children (including 1 case of infantile epileptic spasm syndrome), and there has been no report in China yet. Totally there were 17 cases of BRWD3 gene related epilepsy including this case. All the cases showed X chromosome dominant inheritance, of whom 15 cases showed minor variations, including 7 missense variations, 3 frameshift variations, 3 splicing variations, 2 nonsense variations, and the remaining 2 cases showed large segment deletions. A total of 15 different variants were found. The phenotypes of the 17 patients mainly included epileptic seizures (17/17), intellectual disability (10/17), motor development disorder (7/17), speech impairment (9/17), megacephaly (8/17), facial malformation (8/17), autism (4/17) and hypotonia (4/17). The common seizure types were found to be focal seizures, occasionally epileptic spasm seizures and tonic seizures. Conclusions:BRWD3 gene variation related epilepsy is an X chromosome dominant genetic disease with a wide clinical phenotype spectrum. BRWD3 gene mutation c.4318_4319del(p.Q1441Efs *20) could cause infantile epileptic spasm syndrome, manifested as severe global developmental delay, epileptic spasm, focal seizures, autism, craniofacial malformation and hypsarrhythmia. This research enriches BRWD3 gene mutation spectrum.

Objective To observe the value of ultrasound radiomics for distinguishing early and middle-late stage endometrial cancer(EC).Methods A total of 294 women with EC were retrospectively enrolled,including 196 in early stage and 98 in middle-late stage.The patients were randomly divided into training set(n=206)and validation set(n=88)at the ratio of 7∶3.Clinical data were compared between different stages,and a clinical model was constructed.Radiomics features were extracted and screened based on ultrasound data,and radiomics models were constructed with logistic regression(LR),random forest(RF),support vector machine(SVM),Gaussian naive Bayes(GNB)and extreme gradient boosting(XGBoost),respectively.Finally,a clinical-radiomics model was constructed.The value of each model for distinguishing early and middle-late stages EC was observed.Results Significant differences of age of consultation,menstrual disorders,abdominal pain and proportion of menopause were found between patients with early and middle-late stage EC(all P＜0.05).Among these 5 radiomics models,RF model had the highest area under the curve(AUC)for distinguishing early and middle-late stage EC.Pairwise comparison of clinical model,RF radiomics model and clinical-RF radiomics model showed that significant differences of AUC were found between each 2 models(all P＜0.05),and clinical-RF radiomics model had the highest AUC.Conclusion Ultrasound radiomics based on RF were helpful for distinguishing early and middle-late stage EC,and better diagnostic efficacy could be obtained through combining with clinical data.

Objective To train influenza clinical syndrome data using machine learning methods;To obtain an influenza syndrome differentiation model.Methods The medical records of influenza patients who visited the fever clinic of China-Japan Friendship Hospital from December 2019 to March 2022 were collected.The data set system was used for data processing,and the data generated by different data processing processes were stored separately for training.The study selected logistic regression,decision tree,naive Bayes,support vector machine,multi-layer perceptron,lightGBM and random forest as alternative models,and optimized the hyperparameters through Optuna.Models were trained separately in each data set,and the model prediction performance was evaluated,with the macro-F1 score as the core.Results Totally 1 011 training samples were collected,including 453 cases of wind-heat syndrome,152 cases of superficial wind-cold syndrome,and 406 cases of superficial cold and internal heat syndrome;8 data sets were obtained for training,containing 80 copies of data.After training,the macro-F1 scores of logistic regression,decision tree,naive Bayes,support vector machine,multi-layer perceptron lightGBM and random forest model were 0.783 0,0.774 2,0.731 5,0.782 4,0.716 7,0.793 8 and 0.815 3,respectively.Weighted samples could significantly improve the average model performance,while PCA would reduce the average model performance.The prediction performance of the logistic regression model was the best in the single method models,and the random forest model was the best in the integrated method models.Conclusion In the case of a small sample size,it is more appropriate to use logistic regression,decision tree,support vector machine and lightGBM for the TCM influenza syndrome differentiation model.As the sample size increases,logistic regression,support vector machine,lightGBM and random forest may be more suitable.Different data processing methods will affect model performance.Collecting information on the typical degree of syndrome types is beneficial to improving model performance.

Objective:To investigate the Correlation between ADC combined with serum C-reactive protein (CRP) and delayed encephalopathy after carbon monoxide poisoning (DEACMP), It provides scientific basis for early prediction of DEACMP.Methods:According to the design principle of case-control study, the data of acute carbon monoxide poisoning (ACOP) patients admitted to Shandong Provincial Hospital from December 2017 to December 2021 were retrospectively selected. Among them, patients with DEACMP were selected as the case group, without DEACMP were used as the control group. Univariate and multivariate analyses were performed on the two groups. Receiver operating characteristic curve (ROC) was used to evaluate the diagnostic efficacy of ADC combined with CRP as a combined predictor for disease.Results:A total of 89 patients with ACOP were included, including 33 patients with DEACMP and 56 patients without DEACMP. There were no significant differences in gender, age, smoking, drinking, and underlying diseases (hypertension, coronary heart disease) between groups ( P>0.05). Logistic regression analysis showed that white blood cell count (WBC) ( OR=1.64, 95% CI: 1.19-2.26, P=0.003), CRP ( OR=1.22, 95% CI: 1.03-1.45, P=0.019) and ADC value of central semiovale white matter ( OR=0.99, 95% CI: 0.98-1.00, P=0.010) were associated with DEACMP in patients with ACOP. The ROC curve results showed that the area under the ROC of ADC combined with CRP in the center of semiovale was 0.765 (95% CI: 0.656-0.845), the specificity was 87.9%, the sensitivity was 23.2%, and the cut-off value was 3.5°. Conclusions:WBC, CRP and ADC value of central semiovale are independent factors for DEACMP. ADC value of central semiovale combined with CRP has more clinical value in the early diagnosis of DEACMP. For ACOP patients with DEACMP triggering factors, the diagnosis and treatment awareness of early screening of brain magnetic resonance imaging should be strengthened to avoid DEACMP.

OBJECTIVE To compare efficacy and safety of continuous pump versus intermittent infusion of amphotericin B in the treatment of invasive fungal infection， and to provide evidence-based reference for clinical treatment. METHODS Retrieved from PubMed， the Cochrane Library， Web of Science， Embase， Wanfang， CNKI， CBM and VIP database， randomized controlled trial （RCT） and cohort study about 24 h continuous pump （trial group） versus intermittent infusion （control group） of amphotericin B were collected from the inception to Jan. 2023. After literature screening and data extraction， the quality of RCT was evaluated with modified Jadad scale， and the quality of cohort study was evaluated with Newcastle-Ottawa scale. Meta-analysis and sensitivity analysis were performed by using RevMan 5.4 software. RESULTS A total of 7 literature were included， involving 1 RCT and 6 cohort studies with a total of 767 patients. The results of meta-analysis showed that the clinical effective rate [RR＝1.44， 95%CI （1.13，1.83）， P＝0.003] of trial group was significantly higher than that of control group， and all-cause mortality rate [RR＝0.37， 95%CI（0.19，0.72），P＝0.003] and the incidence rate of infusion reaction [RR＝0.28，95%CI（0.18，0.43）， P＜0.000 01] were significantly lower than control group； there was no statistical significance in the incidence rate of renal impairment between 2 groups [RR＝0.71，95%CI（0.45，1.11），P＝0.13] . The sensitivity analysis results showed that the results obtained in this study were robust. CONCLUSIONS The efficacy and safety of 24 h continuous pump of amphotericin B are better than those of intermittent infusion in the treatment of invasive fungal infection.

Lotus medicinal herbs have the effects of resolving blood stasis and stopping bleeding， invigorating the spleen and benefiting the kidneys， restoring coordination between heart and kidney， and tranquilizing the fetus. Lotus root， lotus leaf， lotus seed， Lotus plumule， Shilianzi（Nelumbo nucifera Gaertn） and other lotus herbs are used to treat various female reproductive system diseases. For example， lotus leaf tip with modified Youshi Pangxing Shuangtu Decoction （伍尤氏胖型双土汤）， lotus root section with modified Youshi Shouxing Shuangteng Decoction （尤氏瘦型双藤汤） were used for polycystic ovary syndrome； Youshi Yangchao Formula （尤氏养巢方） （containing lotus seed）， Gengnian Formula （更年方） （containing lotus plumule） for ovarian reserve dysfunction； Lotus seed - Shihu （Dendrobium nobile） as the herb-pair， lotus stamen with ginseng flowers and Sanqi Flower for thin endometrium； Shilianzi（Nelumbo nucifera Gaertn）， lotus leaf tip， lotus stamen， lotus seed， lotus room， lotus root section can be used for premature abortion， and we summarized the characteristics of clinical medication， compounding experience， drug dosage and precautions of each lotus drug in different diseases.

Trace amines(TAs)are metabolically related to catecholamine and associated with cancer and neuro-logical disorders.Comprehensive measurement of TAs is essential for understanding pathological pro-cesses and providing proper drug intervention.However,the trace amounts and chemical instability of TAs challenge quantification.Here,diisopropyl phosphite coupled with chip two-dimensional(2D)liquid chromatography tandem triple-quadrupole mass spectrometry(LC-QQQ/MS)was developed to simul-taneously determine TAs and associated metabolites.The results showed that the sensitivities of TAs increased up to 5520 times compared with those using nonderivatized LC-QQQ/MS.This sensitive method was utilized to investigate their alterations in hepatoma cells after treatment with sorafenib.The significantly altered TAs and associated metabolites suggested that phenylalanine and tyrosine metabolic pathways were related to sorafenib treatment in Hep3B cells.This sensitive method has great potential to elucidate the mechanism and diagnose diseases considering that an increasing number of physiological functions of TAs have been discovered in recent decades.

Objective:To develop a deep learning model which can automatically and accurately detect osteoporotic vertebral compression fractures (OVCF) based on artificial intelligence.Methods:MRI images of 500 patients diagnosed with OVCF at The First People＇s Hospital of Guangzhou from January 2019 to October 2021 were collected retrospectively. There were 396 males and 204 females, with an age of (74.5±6.0) years. The T value of bone mineral density was -2.9±0.8. The fracture segments were L1 in 128 cases, L2 in 113 cases, L3 in 109 cases, L4 in 115 cases, and L5 in 108 cases. The multimodal layered converged network was used to train, test, and verify the robustness and generalization ability of a deep learning model based on MRI images of OVCF. The grad-cam was applied to visualize the results. The diagnostic value of the model for OVCF was assessed by comparing the diagnoses between the artificial intelligence model and 2 senior spinal surgeons on the MRI images of 30 OVCF patients randomized from the 500 ones.Results:Of the precise auxiliary diagnosis model for OVCF based on MRI images, the diagnostic accuracy was 96.7%, the sensitivity 93.5%, the specificity 88.9%, the positive predictive value 100.0%, and the negative predictive value 86.6%, all significantly higher than those of the 2 senior spinal surgeons (70.0%, 72.7%, 28.6%, 82.1%, and 28.6%) ( P<0.05). Conclusion:The present study has successfully established a deep learning model which can automatically and accurately diagnose OVCF based on MRI images, showing a high diagnostic efficiency than human spinal surgeons.

OBJECTIVE To systematically evaluate the adverse effects of drug-resistant tuberculosis （DR-TB） drugs on pregnant women and fetuses ，so as to provide evidence-based reference for clinical medication. METHODS PubMed，Cochrane Library，Embase，CBM，CNKI，Wanfang database and VIP were searched by computer to collect randomized controlled trials （RCTs），cohort studies ，case-control studies ，case series and case reports about pregnant women exposed to DR-TB drugs. The retrieval time limit was from the establishment of each database to August 20，2021. After selecting the literature and extracting the data，the bias risk assessment tool recommended by 6.2 version of Cochrane system evaluator manual was used to evaluate the quality of the included RCTs ；Newcastle-Ottawa scale was used to evaluate the quality of the included cohort studies and case-control studies ；IHE scale issued by the Canadian Institute of Health Economics （IHE）was used to evaluate the quality of the included case series and case reports. RevMan 5.1 software was used for Meta-analysis of non-comparative binary data. RESULTS A total of 13 literature were included ，including 7 case series and 6 case reports ，involving 203 patients and 204 newborns；among them，there were 6 literature about non-comparative binary data. The results of meta-analysis showed that after exposure to DR-TB drugs，no newborn had birth defects ；the mortality of pregnant women was 0.09[95％CI（0.06，0.15），P＜0.000 01]；the neonatal mortality was 0.02[95％CI（0，0.06），P＜0.000 01]；the incidence of preterm birth was 0.14[95％CI（0.03，0.43），P＝0.02]；the incidence of infants with low birth weight was 0.17[95％CI（0.04，0.51），P＝0.06]；the incidence of growth retardation was 0.15[95％CI（0.09，0.22），P＜0.000 01]；the incidence of stillbirth was 0.05[95％CI（0.02，0.09），P＜0.000 01]；the incidence of abortion was 0.08[95％CI（0.05，0.14），P＜0.000 01]. CONCLUSIONS Pregnant women exposed to DR-TB drugs can cause pregnant women ’s death and abortion ，neonatal death ，premature birth ，infants with low birth weight ，growth retardation and stillbirth，but there is no neonatal birth defect ；these adverse outcomes may be related to the history of DR-TB.

BACKGROUNDS: At present, there is no consensus on the induction methods in term pregnancy with borderline oligohydramnios. This study aimed to compare the effectiveness and pregnancy outcomes of labor induction with dinoprostone or single-balloon catheter (SBC) in term nulliparous women with borderline oligohydramnios. METHODS: We conducted a retrospective cohort study from January 2016 to November 2018. During the study period, a total of 244 cases were enrolled. Of these, 103 cases were selected for induction using dinoprostone and 141 cases were selected for induction with SBC. The pregnancy outcomes between the two groups were compared. Primary outcomes were successful vaginal delivery rates. Secondary outcomes were maternal and neonatal adverse events. Multivariate logistic regression was used to assess the risk factors for vaginal delivery failure in the two groups. RESULTS: The successful vaginal delivery rates were similar between the dinoprostone group and the SBC group (64.1% [66/103] vs. 59.6%, [84/141] P = 0.475), even after adjustment for potential confounding factors (adjusted odds ratio [aOR]: 1.07, 95% confidence interval [CI]: 0.57-2.00, P = 0.835). The incidence of intra-amniotic infection was lower in the dinoprostone group than in the SBC group (1.9% [2/103] vs. 7.8%, [11/141] P < 0.001), but the presence of non-reassuring fetal heart rate was higher in the dinoprostone group than in the SBC group (12.6% [13/103] vs. 0.7%, [1/141] P < 0.001). Multivariate logistic regression showed that nuchal cord was a risk factor for vaginal delivery failure after induction with dinoprostone (aOR: 6.71, 95% CI: 1.96-22.95). There were three factors related to vaginal delivery failure after induction with SBC, namely gestational age (aOR: 1.51, 95% CI: 1.07-2.14), body mass index (BMI) >30 kg/m2 (aOR: 2.98, 95% CI: 1.10-8.02), and fetal weight >3500 g (aOR: 2.49, 95% CI: 1.12-5.50). CONCLUSIONS Term nulliparous women with borderline oligohydramnios have similar successful vaginal delivery rates after induction with dinoprostone or SBC, with their advantages and disadvantages. In women with nuchal cord, the risk of vaginal delivery failure is increased if dinoprostone is used in the induction of labor. BMI >30 kg/m2, large gestational age, and estimated fetal weight >3500 g are risk factors for vaginal delivery failure after induction with SBC.
Administration, Intravaginal ; Catheters ; Dinoprostone/therapeutic use* ; Female ; Fetal Weight ; Humans ; Infant, Newborn ; Labor, Induced/methods* ; Nuchal Cord ; Oligohydramnios ; Oxytocics ; Pregnancy ; Pregnancy Outcome ; Retrospective Studies