Continuous manufacturing, as an innovative pharmaceutical production model, offers advantages such as high production efficiency and ease of control compared to traditional batch production, aligning with the future trend of drug production moving toward greater efficiency and intelligence. However, the development of continuous manufacturing technology in wet granulation has been slow. On one hand, this is closely related to its high technical complexity, substantial equipment investment costs, and stringent process control requirements. On the other hand, the long-term use of the traditional batch production model has created strong path dependence, and the lack of mature standardized processes further increases the difficulty of technological transformation. To promote the deep integration of wet granulation technology with continuous manufacturing, this review systematically outlines the current application of wet granulation in continuous manufacturing. It focuses on the development of key technologies such as online detection, process modeling, and process scale-up, with the aim of providing a reference for process innovation and application in wet granulation.
Drug Compounding/instrumentation* ; Technology, Pharmaceutical/methods* ; Drugs, Chinese Herbal/chemistry* ; Models, Theoretical

Hepatic fibrosis is a key pathological process in the development of chronic liver disease to cirrhosis, and its core mechanism involves the activation of hepatic stellate cells(HSC) and abnormal deposition of extracellular matrix(ECM). Although existing treatments, such as antiviral drugs, can delay disease progression, they have the problem of single therapeutic targets and cannot reverse fibrosis. Accordingly, multidimensional intervention strategies are urgently needed. Recent studies have shown that circadian rhythm disorders aggravate hepatic fibrosis by regulating metabolism, immunity, and inflammation. Traditional Chinese medicine(TCM) plays a unique role in restoring the circadian clock via multi-target and holistic regulation. This paper establishes a three-dimensional network by systematically integrating biological clock, metabolism, and immunity for the first time to elucidate the scientific connotation of the theory of time-concerned treatment of TCM, and proposes a new strategy for the development of time-targeted compound prescriptions, providing innovative ideas for the treatment of hepatic fibrosis.
Humans ; Liver Cirrhosis/metabolism* ; Drugs, Chinese Herbal/therapeutic use* ; Circadian Rhythm/drug effects* ; Animals ; Medicine, Chinese Traditional ; Hepatic Stellate Cells/drug effects*

OBJECTIVE: To examine the effectiveness of Chinese medicine (CM) Lianhua Qingwen Granule (LHQW) and Jingyin Gubiao Prescription (JYGB) in asymptomatic or mild patients with Omicron infection in the shelter hospital. METHODS: This single-center retrospective cohort study was conducted in the largest shelter hospital in Shanghai, China, from April 10, 2022 to May 30, 2022. A total of 56,244 asymptomatic and mild Omicron cases were included and divided into 4 groups, i.e., non-administration group (23,702 cases), LHQW group (11,576 cases), JYGB group (12,112 cases), and dual combination of LHQW and JYGB group (8,854 cases). The length of stay (LOS) in the hospital was used to assess the effectiveness of LHQW and JYGB treatment on Omicron infection. RESULTS: Patients aged 41-60 years, with nadir threshold cycle (C_T) value of N gene <25, or those fully vaccinated preferred to receive CM therapy. Before or after propensity score matching (PSM), the multiple linear regression showed that LHQW and JYGB treatment were independent influence factors of LOS (both P<0.001). After PSM, there were significant differences in LOS between the LHQW/JYGB combination and the other groups (P<0.01). The results of factorial design ANOVA proved that the LHQW/JYGB combination therapy synergistically shortened LOS (P=0.032). CONCLUSIONS Patients with a nadir C_T value <25 were more likely to accept CM. The LHQW/JYGB combination therapy could shorten the LOS of Omicron-infected individuals in an isolated environment.
Humans ; Drugs, Chinese Herbal/therapeutic use* ; Male ; Female ; Middle Aged ; Adult ; China/epidemiology* ; Hospitalization ; COVID-19 Drug Treatment ; COVID-19/epidemiology* ; SARS-CoV-2 ; Retrospective Studies ; Treatment Outcome ; Length of Stay ; Young Adult ; Aged

[This corrects the article DOI: 10.1016/j.apsb.2022.05.019.].

Breast cancer is the most common cancer in women and one of the deadliest cancers worldwide.According to the distribution of tumor tissue,breast cancer can be divided into invasive and non-invasive forms.The cancer cells in invasive breast cancer pass through the breast and through the immune system or systemic circulation to different parts of the body,forming metastatic breast cancer.Drug resistance and distant metastasis are the main causes of death from breast cancer.Research on breast cancer has attracted extensive attention from researchers.In vitro construction of tumor models by tissue engineering methods is a common tool for studying cancer mechanisms and anticancer drug screening.The tumor microenvironment consists of cancer cells and various types of stromal cells,including fibroblasts,endothelial cells,mesenchymal cells,and immune cells embedded in the extracellular matrix.The extracellular matrix contains fibrin proteins(such as types Ⅰ,Ⅱ,Ⅲ,Ⅳ,Ⅵ,and Ⅹcollagen and elastin)and glycoproteins(such as proteoglycan,laminin,and fibronectin),which are involved in cell signaling and binding of growth factors.The current traditional two-dimensional(2D)tumor models are limited by the growth environment and often cannot accurately reproduce the heterogeneity and complexity of tumor tissues in vivo.Therefore,in recent years,research on three-dimensional(3D)tumor models has gradually increased,especially 3D bioprinting models with high precision and repeatability.Compared with a 2D model,the 3D environment can better simulate the complex extracellular matrix components and structures in the tumor microenvironment.Three-dimensional models are often used as a bridge between 2D cellular level experiments and animal experiments.Acellular matrix,gelatin,sodium alginate,and other natural materials are widely used in the construction of tumor models because of their excellent biocompatibility and non-immune rejection.Here,we review various natural scaffold materials and construction methods involved in 3D tissue-engineered tumor models,as a reference for research in the field of breast cancer.

In this work,an electrochemical sensor for detection of Rhodamine B(RhB)was constructed by modifying molecularly imprinted polymer(MIP)and carboxylated multi-walled carbon nanotubes(f-MWCNTs)onto the surface of glassy carbon electrode(GCE).The MIP/f-MWCNT/GCE electrochemical sensor demonstrated outstanding performance in detection of RhB due to the excellent conductivity of f-MWCNT and synergistic selectivity of MIP.Under optimal experimental conditions,the sensor had a wide linear response range(0.01?30 nmol/L,30?500 nmol/L),with limit of detection of 0.01 nmol/L.In addition,the sensor exhibited excellent recognition ability to RhB in the presence of other structurally similar compounds(e.g.,Rhodamine 6G,methylene blue,and methyl orange),and common metal ions(K+,Ca2+,Mg2+and Fe3+).Furthermore,the sensor exhibited good stability and reproducibility.Additionally,the electrochemical sensor exhibited good practical adaptability when analyzing RhB in real samples,with recoveries ranging from 99.8%?105.6%for tap water and 99.2%?105.0%for river water samples.

Malocclusion,identified by the World Health Organization(WHO)as one of three major oral diseases,profoundly impacts the dental-maxillofacial functions,facial esthetics,and long-term development of～260 million children in China.Beyond its physical manifestations,malocclusion also significantly influences the psycho-social well-being of these children.Timely intervention in malocclusion can foster an environment conducive to dental-maxillofacial development and substantially decrease the incidence of malocclusion or reduce the severity and complexity of malocclusion in the permanent dentition,by mitigating the negative impact of abnormal environmental influences on the growth.Early orthodontic treatment encompasses accurate identification and treatment of dental and maxillofacial morphological and functional abnormalities during various stages of dental-maxillofacial development,ranging from fetal stages to the early permanent dentition phase.From an economic and societal standpoint,the urgency for effective early orthodontic treatments for malocclusions in childhood cannot be overstated,underlining its profound practical and social importance.This consensus paper discusses the characteristics and the detrimental effects of malocclusion in children,emphasizing critical need for early treatment.It elaborates on corresponding core principles and fundamental approaches in early orthodontics,proposing comprehensive guidance for preventive and interceptive orthodontic treatment,serving as a reference for clinicians engaged in early orthodontic treatment.

Objective To explore the correlation between sleep status and traditional Chinese medicine(TCM)constitution types of sub-healthy population in Lingnan area.Methods From May 2022 to May 2023,an investigation was carried out in a sub-healthy population of 688 persons who lived in Shenzhen for more than 5 years,had no serious cardiovascular disease and were confirmed by the sub-health rating scale.The questionnaire survey of Pittsburgh Sleep Quality Index(PSQI)scale and the TCM constitution classification rating scale was conducted,and multiple linear regression analysis was performed to explore the correlation between the sleep status and TCM constitution types.Results(1)A total of 688 questionnaires were released,of which 19 were lost to follow-up,and 669 were responded.After weeding out the 29 invalid questionnaires,640 valid questionnaires were finally included for the analysis.(2)According to the PSQI score,the population was divided into excellent sleep group(total PSQI score＜8)of 350 cases and poor sleep group(total PSQI score≥8)of 290 cases.The item scores of time for falling asleep,sleep time and sleep disorder as well as the total PSQI score of the excellent sleep group were significantly lower than those of the poor sleep group(P＜0.05 or P＜0.01).(3)The persons with excellent sleep usually had the balanced constitution(86.86%),while the persons with poor sleep often had the biased constitution(79.64%).The top three biased constitution types in the persons with poor sleep were damp-heat constitution(15.52%),phlegm-damp constitution(13.79%)and qi-stagnation constitution(13.10%).(4)Multiple linear regression analysis showed that the time for falling asleep was positively correlated with phlegm-damp constitution and qi-stagnation constitution(P＜0.01),and was negatively correlated with balanced constitution(P＜0.05);the sleep efficiency was positively correlated with damp-heat constitution and inherited special constitution(P＜0.05 or P＜0.01),and was negatively correlated with balanced constitution(P＜0.05);sleep disorder was positively correlated with qi-stagnation constitution and yin-deficiency constitution(P＜0.01);hypnotic drugs were positively correlated with yin-deficiency constitution(P＜0.01);daytime dysfunction was positively correlated with phlegm-damp constitution(P＜0.05).Conclusion The sleep status of sub-healthy population in Lingnan area has a certain correlation with TCM constitution types.Damp-heat constitution,phlegm-damp constitution,qi-stagnation constitution,yin-deficiency constitution,balanced constitution and inherited special constitution are the six constitution types that affect sleep status.It is of great significance to guide the sub-healthy population to achieve the purpose of prevention before illness by improving their constitution after the identification of TCM constitution types.

Objective To analyze the atrioventricular synchronization rate after implantation of Micra AV leadless pacemaker,and the impact of postoperative programming optimization on atrioventricular synchronization rate.Methods A prospective cohort study was conducted to select patients with complete atrioventricular block who underwent Micra AV leadless pacemaker implantation at Beijing Anzhen Hospital from August 2022 to June 2023.Programming optimization were performed at 1 week,1 month,and 3 months postoperatively,and atrioventricular synchronization rate,electrical parameters,and echocardiography were recorded.Results A total of 68 patients with complete atrioventricular block implanted with Micra AV were selected,with an average age of(68.2±9.7)years,including 47 males(69.1％).All patients were successfully implanted with Micra AV,and there were no serious postoperative complications;The average threshold,sense,and impedance parameters were stable during 1 week,1 month,and 3 months after the procedure;There was no significant difference in the EF value of postoperative echocardiography(P=0.162);The average atrioventricular synchronization rates at 1 week,1 month,and 3 months postoperatively were(75.2％vs.83.8％vs.91.6％,P=0.001).Conclusions As an mechanical atrial sensing,Micra AV requires personalized adjustment of relevant parameters;Postoperative follow-up programming optimization plays an important role in the atrioventricular synchronization and comfort level in patients with complete atrioventricular block after implantation of Micra AV leadless pacemaker.

Objective To construct a machine learning prediction model for postoperative liver injury in patients with non-liver surgery based on preoperative and intraoperative medication indicators.Methods A case-control study was conducted on 315 patients with liver injury after non-liver surgery selected from the databases developed by 3 large general hospitals from January 2014 to September 2022.With the positive/negative ratio of 1 ∶3,928 cases in corresponding period with non-liver surgery and without liver injury were randomly matched as negative control cases.These 1243 patients were randomly divided into the modeling group(n=869)and the validation group(n=374)in a ratio of 7∶3 using the R language setting code.Preoperative clinical indicators(basic information,medical history,relevant scale score,surgical information and results of laboratory tests)and intraoperative medication were used to construct the prediction model for liver injury after non-liver surgery based on 4 machine learning algorithms,k-nearest neighbor(KNN),support vector machine linear(SVM),logic regression(LR)and extreme gradient boosting(XGBoost).In the validation group,receiver operating characteristic(ROC)curve,precision-recall curve(P-R),decision curve analysis(DCA)curve,Kappa value,sensitivity,specificity,Brier score,and F1 score were applied to evaluate the efficacy of model.Results The model established by 4 machine learning algorithms to predict postoperative liver injury after non-liver surgery was optimal using the XGBoost algorithm.The area under the receiver operating characteristic curve(AUROC)was 0.916(95%CI:0.883～0.949),area under the precision-recall curve(AUPRC)was 0.841,Brier score was 0.097,and sensitivity and specificity was 78.95%and 87.10%,respectively.Conclusion The postoperative liver injury prediction model for non-liver surgery based on the XGBoost algorithm has effective prediction for the occurrence of postoperative liver injury.