Treponema pallidum(Tp),a common sexually transmitted pathogen,can infect the fetus via pla-cental vertical transmission,leading to congenital syphilis(CS).This infection results in adverse pregnancy outcomes,such as stillbirth,miscarriage,preterm birth,and fetal growth restriction.However,the exact pathogenesis remains un-clear.Studies indicate that patients with early syphilis primarily exhibit pro-inflammatory immune responses.The Tp has been proven to induce dysfunction in various immune cells and abnormal expression of cytokines,potentially disrupting im-mune tolerance homeostasis and leading to adverse pregnancy outcomes.Grounded in the current understanding of CS and maternal-fetal immunology by scholars both domestically and internationally,this paper provides a comprehensive review of the potential mechanisms of Tp interacting with the cells of the maternal-fetal interface,ultimately leading to adverse pregnancy outcomes.It summarizes the pathogenesis characteristics,clinical manifestations,and maternal-fetal immune responses of CS.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.

Background/Aims: The histological characteristics and natural history of precirrhotic primary biliary cholangitis (PBC) with portal hypertension (PH) are unclear. Our aim was to clarify the prevalence, risk factors, and histological characteristics of precirrhotic PBC patients with PH. Methods: This retrospective study compared the clinical features, histological characteristics, and response to ursodeoxycholic acid (UDCA) between the PH and non-PH groups of precirrhotic PBC patients. Results: Out of 165 precirrhotic PBC patients, 40 (24.2%) also had PH. According to histological stage 1, 2 and 3 disease, 5.3% (1/19), 17.3% (17/98), and 45.8% (22/48) of patients also had PH, respectively. Precirrhotic PBC with PH was significantly positively correlated with bile duct loss, degree of cytokeratin 7 positivity, and degree of fibrosis in the portal area, but significantly negatively correlated with lymphoid follicular aggregation. Compared to the non-PH group, patients in the PH group showed a higher prevalence of obliterative portal venopathy, incomplete septal fibrosis, portal tract abnormalities and non-zonal sinusoidal dilatation (p<0.05). In addition, patients with PH were more likely to present with symptoms of jaundice, ascites, epigastric discomfort, a poorer response to UDCA, and more decompensation events (p<0.05). High alkaline phosphatase levels, low white blood cell counts, high Mayo scores, and high FIB-4 index values were risk factors for precirrhotic PBC with PH. Conclusions Approximately 24.2% of precirrhotic PBC patients have PH, which is histologically related to the injury of bile ducts. High alkaline phosphatase levels, low white blood cell counts, high Mayo scores, and high FIB-4 index values are associated with increased risk of precirrhotic PBC with PH.

Owing to the advancement in pharmaceutical technology, traditional Chinese medicine industry has seen rapid development. Preferring conventional manufacturing mode, pharmaceutical enterprises of traditional Chinese medicine have no effective process detection tools and process control methods. As a result, the quality of the final products mainly depends on testing and the quality is inconsistent in the same batch. Process analytical technology(PAT) for traditional Chinese medicine manufacturing, as one of the key advanced manufacturing techniques, can break through the bottleneck in quality control of medicine manufacturing, thus improving the production efficiency and product quality and reducing the material and energy consumption. It is applicable to the process control and real-time release of advanced manufacturing modes such as intelligent manufacturing and continuous manufacturing. This paper summarized the general idea of PAT for traditional Chinese medicine manufacturing. Through the analysis of the characteristics and status quo of the technology, we summed up the methodology for the continuous application and improvement of PAT during the whole life-cycle of traditional Chinese medicine. The five key procedures(process understanding, process detection, process modeling, process control, and continuous improvement) were summarized, and the application was reviewed. Finally, we proposed suggestions for the technical and regulatory challenges in implementing PAT in traditional Chinese medicine industry. This paper aims to provide a reference for development and application of PAT in advanced manufacturing, intelligent manufacturing, and continuous manufacturing of traditional Chinese medicine industry.
Medicine, Chinese Traditional ; Drugs, Chinese Herbal ; Technology, Pharmaceutical ; Drug Industry ; Quality Control

The application of new-generation information technologies such as big data, the internet of things(IoT), and cloud computing in the traditional Chinese medicine(TCM)manufacturing industry is gradually deepening, driving the intelligent transformation and upgrading of the TCM industry. At the current stage, there are challenges in understanding the extraction process and its mechanisms in TCM. Online detection technology faces difficulties in making breakthroughs, and data throughout the entire production process is scattered, lacking valuable mining and utilization, which significantly hinders the intelligent upgrading of the TCM industry. Applying data-driven technologies in the process of TCM extraction can enhance the understanding of the extraction process, achieve precise control, and effectively improve the quality of TCM products. This article analyzed the technological bottlenecks in the production process of TCM extraction, summarized commonly used data-driven algorithms in the research and production control of extraction processes, and reviewed the progress in the application of data-driven technologies in the following five aspects: mechanism analysis of the extraction process, process development and optimization, online detection, process control, and production management. This article is expected to provide references for optimizing the extraction process and intelligent production of TCM.
Medicine, Chinese Traditional ; Drugs, Chinese Herbal ; Quality Control ; Big Data ; Algorithms

Physical attributes of Chinese herbal extracts are determined by their chemical components, and the physical and chemical attributes jointly affect the preparation process performance and the final product quality. Therefore, in order to improve the quality control of Chinese herbal extracts, we should comprehensively study the batch-to-batch consistency of physical and chemical attributes as well as the correlations between them. This paper first explored the physical attributes affecting the preparation process performance of the compound Danshen extract and developed a method for characterizing the texture attributes. With such main chemical components as water, phenolic acids, saponins, and saccharides and texture, rheology, and other physical attributes taken into consideration, the batch-to-batch quality fluctuation of products from different production lines and time was analyzed by principal components analysis(PCA). Finally, the correlation and partial least squares(PLS) analysis was conducted, and the regression equation was established. The fitting result of the PLS model for dynamic viscosity was satisfying(R~2Y=0.857, Q~2=0.793), suggesting that the chemical components could be adjusted by the component transfer rate in the extraction process, the impurity removal rate in the alcohol precipitation process, and the water retention rate of the concentration process to meet the control of the extract dynamic viscosity. This study clarified the correlations between physical and chemical attributes of the compound Danshen extract and established a method for controlling its physical attributes based on process regulation, which would provide reference for improving the quality control of Chinese herbal extracts.
Drugs, Chinese Herbal/chemistry* ; Quality Control ; Salvia miltiorrhiza/chemistry* ; Water

OBJECTIVE: To investigate the method and clinical effect of modified Chevron osteotomy of the distal end of the first metatarsal in the treatment of moderate and severe hallux valgus. METHODS: From January 2015 to January 2019, 28 patients(30 feet) with moderate and severe hallux valgus were treated with modified Chevron osteotomy combined with lateral soft tissue release of the first metatarsophalangeal joint, including 2 males (2 feet) and 26 females (28 feet). The age ranged from 35 to 74 (57.3±9.3) years;10 feet on the left, 16 feet on the right, 2 cases on both sides(4 feet);the course of disease was 3 to 12 (9.32±3.89) years. The changes of hallux valgus angle(HVA), intermetatarsal angle(IMA) between the first and second metatarsals and distal metatarsal articular angle(DMAA) of the first metatarsal were measured and compared before and 6 months after operation. The American Orthopaedic Foot and Ankle Society(AOFAS) thumb joint scoring system was used to evaluate the curative effect. RESULTS: All 28 patients were followed up for 8 to 16 (11.28±3.42) months. The incision healed well in all patients, and there were no complications such as incision infection and metatarsal head necrosis. The healing time of osteotomy site was 6 to 10(7.12±1.34) weeks. Preoperative HVA, IMA, DMAA and AOFAS were (36.06±6.02) °, (21.78±4.16) °, (8.21±2.65) ° and (52.90±10.97) respectively, at six months after operation, they were (8.87±2.46) °, (11.66±2.84) °, (3.65±1.00) ° and (87.45±10.55) respectively, there was significant difference between preoperative and 6 months after operation(P<0.05). At 6 months after operation, AOFAS score was excellent in 20 feet, good in 7 feet and poor in 3 feet. Among the 3 patients with poor scores, 2 were excellent after revision, and 1 was significantly improved after using custom insoles. CONCLUSION Modified Chevron can effectively correct HVA, IMA and DMAA and improve functional recovery. The modified Chevron osteotomy increases the moving distance and the contact of the osteotomy surface. It can be fixed with multiple screws, has strong correction ability, and can exercise early. It is one of the optional methods for the treatment of moderate and severe hallux valgus.
Adult ; Aged ; Female ; Hallux Valgus/surgery* ; Humans ; Male ; Metatarsal Bones/surgery* ; Metatarsophalangeal Joint/surgery* ; Middle Aged ; Osteotomy ; Radiography ; Treatment Outcome

Objective: To construct the diagnostic model of superficial esophageal squamous cell carcinoma (ESCC) and precancerous lesions in endoscopic images based on the YOLOv5l model by using deep learning method of artificial intelligence to improve the diagnosis of early ESCC and precancerous lesions under endoscopy. Methods: 13, 009 endoscopic esophageal images of white light imaging (WLI), narrow band imaging (NBI) and lugol chromoendoscopy (LCE) were collected from June 2019 to July 2021 from 1, 126 patients at the Cancer Hospital, Chinese Academy of Medical Sciences, including low-grade intraepithelial neoplasia, high-grade intraepithelial neoplasia, ESCC limited to the mucosal layer, benign esophageal lesions and normal esophagus. By computerized random function method, the images were divided into a training set (11, 547 images from 1, 025 patients) and a validation set (1, 462 images from 101 patients). The YOLOv5l model was trained and constructed with the training set, and the model was validated with the validation set, while the validation set was diagnosed by two senior and two junior endoscopists, respectively, to compare the diagnostic results of YOLOv5l model and those of the endoscopists. Results: In the validation set, the accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of the YOLOv5l model in diagnosing early ESCC and precancerous lesions in the WLI, NBI and LCE modes were 96.9%, 87.9%, 98.3%, 88.8%, 98.1%, and 98.6%, 89.3%, 99.5%, 94.4%, 98.2%, and 93.0%, 77.5%, 98.0%, 92.6%, 93.1%, respectively. The accuracy in the NBI model was higher than that in the WLI model (P<0.05) and lower than that in the LCE model (P<0.05). The diagnostic accuracies of YOLOv5l model in the WLI, NBI and LCE modes for the early ESCC and precancerous lesions were similar to those of the 2 senior endoscopists (96.9%, 98.8%, 94.3%, and 97.5%, 99.6%, 91.9%, respectively; P>0.05), but significantly higher than those of the 2 junior endoscopists (84.7%, 92.9%, 81.6% and 88.3%, 91.9%, 81.2%, respectively; P<0.05). Conclusion: The constructed YOLOv5l model has high accuracy in diagnosing early ESCC and precancerous lesions in endoscopic WLI, NBI and LCE modes, which can assist junior endoscopists to improve diagnosis and reduce missed diagnoses.
Artificial Intelligence ; Endoscopy/methods* ; Esophageal Neoplasms/pathology* ; Esophageal Squamous Cell Carcinoma/diagnostic imaging* ; Humans ; Narrow Band Imaging ; Precancerous Conditions/diagnostic imaging* ; Sensitivity and Specificity

As intelligent production of traditional Chinese medicine （TCM） has been inevitable， informatization and automation of the production process have become the precondition for realizing intelligent manufacturing of TCM， of which the accumulation of critical material attribute and the critical quality attribute are the basis. The study of material properties is of great significance to achieve the quality control of the final product in the process， but there is a lack of systematic induction and summary of the research on the attribute of TCM pills. Therefore， the authors analyzed and summarized the attributes of raw materials， excipients and intermediates in the pill unit process according to the classification of powder properties， rheological properties and texture properties. What’s more， the impact of material attributes on the quality of the final product was summarized. Besides， this review summarized the attribute characterization techniques involved in the pill process and provided some suggestions for the characterization of product quality attributes. Finally， based on the concept of quality by design （QbD）， the authors proposed that the study of material attribute should be combined with process analytical technology （PAT）， and the focus of drug quality control should be moved forward to guide equipment upgrading， so as to realize intelligent continuous manufacturing of TCM pills.

The mixing process is one of the key operation units for solid preparation of traditional Chinese medicine. The physical properties such as particle size, density and viscosity of the mixture are key factors that need to be controlled, which will directly affect the performance of the preparation molding process and product quality. Subsequent dripping process performance and appearance qua-lity of dripping pills will be affected by dynamic viscosity of materials in the mixing process. Based on this, with mixing process of compound Danshen dripping pills as the object, a feedforward control method for the dripping pill mixing process was established based on the concept of quality by design(QbD). Firstly, critical quality attribute(CQA)-dynamic viscosity, critical material attributes(CMAs)-the moisture content of compound Danshen extract, average molecular weight of polyethylene glycol 6000 and critical process parameter(CPP)-mixing temperature were identified through the analysis of properties for multiple batches of the raw materials and excipients as well as technological mechanism. Then the Box-Behnken experimental design was used to establish the regression model among CMA, CPP and CMA(R■=0.972 0, RMSE =16.24) to obtain the design space. Finally, through the verification of three batches within the design space, the mixing process temperature was adjusted according to the properties of the raw materials and exci-pients to achieve accurate control of the dynamic viscosity attribute. The relative deviation between the actual dynamic viscosity value and the target value was less than 3.0 %. The feedforward control of the mixing process of compound Danshen dripping pills was rea-lized in this study, which can contribute to improving quality consistency of the mixing process intermediates, simultaneously provide a reference for the research on the process quality control of other Chinese medicine dripping pills.
Drugs, Chinese Herbal ; Medicine, Chinese Traditional ; Quality Control ; Research Design