In the context of Pharma 4.0, the design tools that support the pharmaceutical Quality by Design(QbD) are iterating fast toward intelligent or smart design. The conventional development methods for traditional Chinese medicine(TCM) preparations have the limitations such as over dependence on experience, low dimensions for the designed experiment parameters, poor compatibility between the process and equipment, and high trial-and-error cost during process scale-up. Therefore, this paper innovatively proposed the intelligent co-design involving material, process, and equipment for manufacturing high-quality TCM preparations, and introduced the design philosophy, targets, tools, and applications with TCM oral solid dosage(OSD) as an example. In terms of design philosophy, the pharmaceutical design tetrahedron composed of critical material attributes, critical process parameters, critical equipment attributes, and critical quality attributes was developed. The design targets were put forward based on the product performance classification system. The design tools involve a design platform that contains several modules, such a as the iTCM material database, the processing route classification system, the system modeling and simulation, and reliability-based optimization. The roles of different modules in obtaining essential and universal design knowledge of the key common manufacturing units were introduced. At last, the applications of the co-design methodology involving material, process, and equipment in the high shear wet granulation process development and the improvement of the dissolving or dispersion capability of TCM formula granules are illustrated. The research on advanced pharmaceutical design theory and methodology will help enhance the efficiency and reliability of drug development, improve the product quality, and promote the innovation of high-end TCM products across the industry.
Medicine, Chinese Traditional ; Reproducibility of Results ; Quality Control ; Computer Simulation ; Commerce ; Pharmaceutical Preparations ; Drugs, Chinese Herbal

This study aimed to explore key quality control factors that affected the prognosis of intensive care unit (ICU) patients in Chinese mainland over six years (2015-2020). The data for this study were from 31 provincial and municipal hospitals (3425 hospital ICUs) and included 2 110 685 ICU patients, for a total of 27 607 376 ICU hospitalization days. We found that 15 initially established quality control indicators were good predictors of patient prognosis, including percentage of ICU patients out of all inpatients (%), percentage of ICU bed occupancy of total inpatient bed occupancy (%), percentage of all ICU inpatients with an APACHE II score ⩾15 (%), three-hour (surviving sepsis campaign) SSC bundle compliance (%), six-hour SSC bundle compliance (%), rate of microbe detection before antibiotics (%), percentage of drug deep venous thrombosis (DVT) prophylaxis (%), percentage of unplanned endotracheal extubations (%), percentage of patients reintubated within 48 hours (%), unplanned transfers to the ICU (%), 48-h ICU readmission rate (%), ventilator associated pneumonia (VAP) (per 1000 ventilator days), catheter related blood stream infection (CRBSI) (per 1000 catheter days), catheter-associated urinary tract infections (CAUTI) (per 1000 catheter days), in-hospital mortality (%). When exploratory factor analysis was applied, the 15 indicators were divided into 6 core elements that varied in weight regarding quality evaluation: nosocomial infection management (21.35%), compliance with the Surviving Sepsis Campaign guidelines (17.97%), ICU resources (17.46%), airway management (15.53%), prevention of deep-vein thrombosis (14.07%), and severity of patient condition (13.61%). Based on the different weights of the core elements associated with the 15 indicators, we developed an integrated quality scoring system defined as F score=21.35%xnosocomial infection management + 17.97%xcompliance with SSC guidelines + 17.46%×ICU resources + 15.53%×airway management + 14.07%×DVT prevention + 13.61%×severity of patient condition. This evidence-based quality scoring system will help in assessing the key elements of quality management and establish a foundation for further optimization of the quality control indicator system.
Humans ; China/epidemiology* ; Cross Infection/epidemiology* ; Intensive Care Units/statistics & numerical data* ; Quality Control ; Quality Indicators, Health Care/statistics & numerical data* ; Sepsis/therapy* ; East Asian People/statistics & numerical data*

Humans ; Gemcitabine ; Neoplasms

Objective To assess the psychological status of staff at the centers for disease control and prevention(CDC) in Sichuan during the outbreak of coronavirus disease 2019(COVID-19) and explore the influencing factors. Methods The staff at Sichuan provincial,municipal,and county(district)-level CDC were selected by convenience sampling.Their basic information,work status,training status,work difficulties,and support from the work group were collected from the self-filled questionnaires online.The Generalized Anxiety Disorder Scale and the 9-question Patient Health Questionnaire were respectively employed to measure the anxiety and depression of the staff.The stepwise Logistic regression was carried out to analyze the influencing factors of anxiety and depression in CDC staff. Results Among the 653 staff,58.35% and 50.06% presented anxiety and depression,respectively.The regression results showed that age(OR=0.95,95%CI=0.92-0.97) and mental support from the work group(OR=0.61,95%CI=0.45-0.82) were the protective factors while physical fatigue(OR=1.82,95%CI=1.20-2.74),work pressure(OR=1.61,95%CI=1.21-2.12),and insufficient protective equipment(OR=1.92,95%CI=1.06-3.49) were the risk factors for depression of CDC staff.Age(OR=0.97,95%CI=0.94-0.99),length of sleep per day(OR=0.74,95%CI=0.56-0.96),and participation in technical training(OR=0.33,95%CI=0.12-0.95) were the protective factors while mental fatigue(OR=1.68,95%CI=1.18-2.41),work pressure(OR=2.94,95%CI=2.08-4.17),and unclear incentive system for overtime(OR=1.99,95%CI=1.23-3.23) were the risk factors for the anxiety of CDC staff. Conclusion The anxiety and depression status of CDC staff during the COVID-19 outbreak were worrying,which were mainly affected by age,sleep,supply of protective equipment,incentive system,fatigue,and work pressure.
Anxiety/epidemiology* ; COVID-19 ; Centers for Disease Control and Prevention, U.S. ; China/epidemiology* ; Cross-Sectional Studies ; Disease Outbreaks ; Humans ; SARS-CoV-2 ; Surveys and Questionnaires ; United States

Three sesquiterpenoids were isolated and purified from the 95% ethanol extract of Atractylodis Macrocephalae Rhizoma by column chromatography on silica gel, Sephadex LH-20, ODS, and high-performance liquid chromatography(HPLC). Their chemical structures were identified on the basis of spectroscopic analysis and physiochemical properties as(7Z)-8β,13-diacetoxy-eudesma-4(15),7(11)-diene(1), 7-oxo-7,8-secoeudesma-4(15),11-dien-8-oic acid(2), and guai-10(14)-en-11-ol(3). Compounds 1 and 2 are new compounds and compound 3 was obtained from Compositae family for the first time. Compounds 1, 2, and 3 showed weak inhibitory activities against sterol regulatory element-binding proteins(SREBPs).
Atractylodes/chemistry* ; Drugs, Chinese Herbal/chemistry* ; Rhizome/chemistry* ; Sesquiterpenes, Eudesmane/pharmacology* ; Sterol Regulatory Element Binding Proteins/antagonists & inhibitors*

The use of the big data analytics technology to collect, summarize and analyze medical big data is effective to precisely mine and explore the underlying information, which greatly facilitates medical science research and clinical practices. Currently, the medical big data analytics technology mainly includes artificial intelligence, databases and programming languages, which have been widely employed in medical imaging, disease risk prediction, disease control, healthcare management, follow-up, and drug and therapy development. This review summarizes the currently available medical big data analytics technologies and their applications, with aims to facilitate the related studies.

During the coronavirus disease (COVID-19) epidemic, there have been concerns about the impact of vaccines on people's fertility, including the fertility of those who are currently preparing for pregnancy and those who might become pregnant in future. However, there is still a lack of research on the effect of the COVID-19 vaccine on male fertility, and it is not surprising that couples and donors have concerns regarding vaccination. In this study, a retrospective cohort study was conducted to examine semen quality before and after receipt of the inactivated COVID-19 vaccine. There were no statistically significant changes in semen parameters (volume, sperm concentration, progressive motility, and total progressive motile count) after two doses of vaccine (all P > 0.05). In summary, our study updates the most recent studies on the effects of the COVID-19 vaccine on male fertility, and the information from this study could be used to guide fertility recommendations for assisted reproductive technology (ART) patients and donors.
COVID-19 ; COVID-19 Vaccines ; Female ; Humans ; Male ; Pregnancy ; Retrospective Studies ; Semen ; Semen Analysis ; Sperm Count ; Sperm Motility ; Spermatozoa ; Vaccination ; Vaccines, Inactivated

Objective: To analyze the association of fasting plasma glucose (FPG) with mild cognitive impairment (MCI) in the Chinese middle-aged and elderly population from four provinces. Methods: Data were drawn from the baseline data of the Community-based Cohort Study on Nervous System Disease 2018-2019. We selected 3 272 subjects aged 55 and above with completed information on demographics, lifestyle, disease history, cognitive test, psychological assessment, and bio-chemistries measurement, and who were capable of performing basic activities of daily living but without Alzheimer's disease during recruitment. A multivariate logistic regression model was employed to analyze the association between FPG and MCI. Results: Median level of FPG in the study population was 5.5 mmol/L. The prevalence of MCI was 24.8%, and those in groups of the FPG quintile were 19.4%, 22.2%, 29.2%, 26.6%, and 26.1%, respectively, which significantly increased the trend (P=0.002). After adjustment of confounders, multivariate logistic regression analysis found that the MCI risk of subjects in the Q₃,Q₄ and Q₅ groups was 1.641 (95%CI: 1.226-2.131), 1.373 (95%CI: 1.036-1.825), 1.402 (95%CI: 1.054-1.871) times as high as that in the Q₁ group, respectively. Conclusion: High FPG level might serve as a risk factor for MCI in the middle-aged and elderly population, suggesting the importance of monitoring and controlling plasma glucose even without diabetes.
Middle Aged ; Humans ; Aged ; Fasting ; Blood Glucose ; Activities of Daily Living ; Cohort Studies ; Cognitive Dysfunction/epidemiology* ; China/epidemiology*

Objective: To investigate the incidence and trend of short-term outcomes among preterm infants born <34 weeks' gestation. Methods: A secondary analysis of data from the standardized database established by a multicenter cluster-randomized controlled study "reduction of infection in neonatal intensive care units (NICU) using the evidence-based practice for improving quality (REIN-EPIQ) study". This study was conducted in 25 tertiary NICU. A total of 27 192 infants with gestational age <34 weeks at birth and admitted to NICU within the first 7 days of life from May 2015 to April 2018 were enrolled. Infants with severe congenital malformation were excluded. Descriptive analyses were used to describe the mortality and major morbidities of preterm infants by gestational age groups and different admission year groups. Cochran-Armitage test and Jonckheere-Terpstra test were used to analyze the trend of incidences of mortality and morbidities in 3 study-years. Multiple Logistic regression model was constructed to analyze the differences of outcomes in 3 study-years adjusting for confounders. Results: A total of 27 192 preterm infants were enrolled with gestational age of (31.3±2.0) weeks at birth and weight of (1 617±415) g at birth. Overall, 9.5% (2 594/27 192) of infants were discharged against medical advice, and the overall mortality rate was 10.7% (2 907/27 192). Mortality for infants who received complete care was 4.7% (1 147/24 598), and mortality or any major morbidity was 26.2% (6 452/24 598). The incidences of moderate to severe bronchopulmonary dysplasia, sepsis, severe intraventricular hemorrhage or periventricular leukomalacia, proven necrotizing enterocolitis, and severe retinopathy of prematurity were 16.0% (4 342/27 192), 11.9% (3 225/27 192), 6.8% (1 641/24 206), 3.6% (939/25 762) and 1.5% (214/13 868), respectively. There was a decreasing of the overall mortality (P<0.001) during the 3 years. Also, the incidences for sepsis and severe retinopathy of prematurity both decreased (both P<0.001). However, there were no significant differences in the major morbidity in preterm infants who received complete care during the 3-year study period (P=0.230). After adjusting for confounders, infants admitted during the third study year showed significantly lower risk of overall mortality (adjust OR=0.62, 95%CI 0.55-0.69, P<0.001), mortality or major morbidity, moderate to severe bronchopulmonary dysplasia, sepsis and severe retinopathy of prematurity, compared to those admitted in the first study year (all P<0.05). Conclusions: From 2015 to 2018, the mortality and major morbidities among preterm infants in Chinese NICU decreased, but there is still space for further efforts. Further targeted quality improvement is needed to improve the overall outcome of preterm infants.
Bronchopulmonary Dysplasia/epidemiology* ; Gestational Age ; Humans ; Infant ; Infant Mortality/trends* ; Infant, Newborn ; Infant, Premature ; Infant, Premature, Diseases/epidemiology* ; Patient Discharge ; Retinopathy of Prematurity/epidemiology* ; Sepsis/epidemiology*

Objective:To analyze the molecular epidemiological characteristics of the Corona virus disease 2019 (COVID-19) cases in Shijiazhuang, which can reveal the origin of the outbreak and provide a scientific basis for COVID-19 prevention and control.Methods:From January 2 to January 8, 2021, a total of 404 samples from 170 COVID-19 cases were collected from the Shijiazhuang Fifth Hospital. The consensus sequence of 2019 novel Coronavirus(2019-nCoV) was obtained through multiplex polymerase chain reaction-based sequencing. The sequences of 170 COVID-19 cases were analyzed by the PANGOLIN, and the data were statistically analyzed by T-test.Results:Among the 404 COVID-19 samples, a total of 356 samples obtained high quality genome sequences (>95%,100×sequencing depth). The whole genome sequences of 170 COVID-19 cases were obtained by eliminating repeated samples. All 170 sequences were recognized as lineage B1.1 using PANGOLIN. The number of single nucleotide polymorphism arrange from 18-22 and most of the single nucleotide polymorphism were synonymous variants. All of 170 genomes could be classified into 48 sub-groups and most of the genomes were classified into 2 sub-groups (66 and 31, respectively).Conclusions:All cases in this study are likely originated from one imported case. The viruses have spread in the community for a long time and have mutated during the community transmission.