BACKGROUND: Menopausal disorders include obscure symptomatology that greatly reduce work productivity among female workers. Quantifying the impact of menopause-related symptoms on work productivity is very difficult because no such guidelines exist to date. We aimed to develop a scale of overall health status for working women in the perimenopausal period. METHODS: In September, 2021, we conducted an Internet web survey which included 3,645 female workers aged 45-56 years in perimenopausal period. We asked the participants to answer 76 items relevant to menopausal symptomatology, that were created for this study and performed exploratory and confirmatory factor analyses for the scale development. Cronbach's alpha, receiver operating characteristic analysis, and logistic regression analysis were used to verify the developed scale. RESULTS: Approximately 85% participants did not have menstruation or disrupted cycles. Explanatory factor analysis using the maximum likelihood method and Promax rotation identified 21 items with a four-factor structure: psychological symptoms (8 items, α = 0.96); physiological symptoms (6 items, alpha = 0.87); sleep difficulty (4 items, alpha = 0.92); human relationship (3 items, alpha = 0.92). Confirmatory factor analyses found excellent model fit for the four-factor model (RMSR = 0.079; TLI = 0.929; CFI = 0.938). Criterion and concurrent validity were confirmed with high correlation coefficients between each of the four factors, previously validated menopausal symptom questionnaire, and Copenhagen Burnout Inventory scales, respectively (all ps < 0.0001). The developed scale was able to predict absenteeism with 78% sensitivity, 58% specificity, and an AUC of 0.727 (95%CI: 0.696-0.757). Higher scores of each factor as well as total score of the scale were more likely to be associated with work absence experience due to menopause-related symptoms even after adjusting for Copenhagen Burnout Inventory subscales (all ps < 0.0001). CONCLUSION We found that the developed scale has high validity and reliability and could be a significant indicator of absenteeism for working women in perimenopausal period.
Humans ; Female ; Perimenopause ; Reproducibility of Results ; Menopause/psychology* ; Workplace ; Surveys and Questionnaires ; Psychometrics

BACKGROUND: This study aimed to develop a comprehensive instrument for evaluating and ranking clinical practice guidelines, named Scientific, Transparent and Applicable Rankings tool (STAR), and test its reliability, validity, and usability. METHODS: This study set up a multidisciplinary working group including guideline methodologists, statisticians, journal editors, clinicians, and other experts. Scoping review, Delphi methods, and hierarchical analysis were used to develop the STAR tool. We evaluated the instrument's intrinsic and interrater reliability, content and criterion validity, and usability. RESULTS: STAR contained 39 items grouped into 11 domains. The mean intrinsic reliability of the domains, indicated by Cronbach's α coefficient, was 0.588 (95% confidence interval [CI]: 0.414, 0.762). Interrater reliability as assessed with Cohen's kappa coefficient was 0.774 (95% CI: 0.740, 0.807) for methodological evaluators and 0.618 (95% CI: 0.587, 0.648) for clinical evaluators. The overall content validity index was 0.905. Pearson's r correlation for criterion validity was 0.885 (95% CI: 0.804, 0.932). The mean usability score of the items was 4.6 and the median time spent to evaluate each guideline was 20 min. CONCLUSION The instrument performed well in terms of reliability, validity, and efficiency, and can be used for comprehensively evaluating and ranking guidelines.
Reproducibility of Results ; Surveys and Questionnaires ; Practice Guidelines as Topic ; Humans

OBJECTIVES: This study aims to predict the risk of deep caries exposure in radiographic images based on the convolutional neural network model, compare the prediction results of the network model with those of senior dentists, evaluate the performance of the model for teaching and training stomatological students and young dentists, and assist dentists to clarify treatment plans and conduct good doctor-patient communication before surgery. METHODS: A total of 206 cases of pulpitis caused by deep caries were selected from the Department of Stomatological Hospital of Tianjin Medical University from 2019 to 2022. According to the inclusion and exclusion criteria, 104 cases of pulpitis were exposed during the decaying preparation period and 102 cases of pulpitis were not exposed. The 206 radiographic images collected were randomly divided into three groups according to the proportion: 126 radiographic images in the training set, 40 radiographic images in the validation set, and 40 radiographic images in the test set. Three convolutional neural networks, visual geometry group network (VGG), residual network (ResNet), and dense convolutional network (DenseNet) were selected to analyze the rules of the radiographic images in the training set. The radiographic images of the validation set were used to adjust the super parameters of the network. Finally, 40 radiographic images of the test set were used to evaluate the performance of the three network models. A senior dentist specializing in dental pulp was selected to predict whether the deep caries of 40 radiographic images in the test set were exposed. The gold standard is whether the pulp is exposed after decaying the prepared hole during the clinical operation. The prediction effect of the three network models (VGG, ResNet, and DenseNet) and the senior dentist on the pulp exposure of 40 radiographic images in the test set were compared using receiver operating characteristic (ROC) curve, area under the ROC curve (AUC), accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F1 score to select the best network model. RESULTS: The best network model was DenseNet model, with AUC of 0.97. The AUC values of the ResNet model, VGG model, and the senior dentist were 0.89, 0.78, and 0.87, respectively. Accuracy was not statistically different between the senior dentist (0.850) and the DenseNet model (0.850)(P>0.05). Kappa consistency test showed moderate reliability (Kappa=0.6>0.4, P<0.05). CONCLUSIONS Among the three convolutional neural network models, the DenseNet model has the best predictive effect on whether deep caries are exposed in imaging. The predictive effect of this model is equivalent to the level of senior dentists specializing in dental pulp.
Humans ; Deep Learning ; Neural Networks, Computer ; Pulpitis/diagnostic imaging* ; Reproducibility of Results ; ROC Curve ; Random Allocation

The present study aims to explore the genetic diversity of germplasm resources of Chrysanthemum×morifolium (hereinafter, C.×morifolium) at the molecular level and to establish a fingerprint database of C.×morifolium varieties. We employed 12 pairs of primers with high levels of polymorphism, clear bands, and high degrees of reproducibility to analyze the SSR molecular markers and genetic diversity of 91 C.×morifolium materials and 14 chrysanthemum- related materials. With regard to constructing the fingerprints of the tested materials, we chose 9 pairs of core primers. The findings revealed that 12 primer pairs detected 104 alleles in 105 samples, ranging from 2 to 26. The average number of observed alleles (N_a) per site was 9.25. The average number of effective alleles (N_e) per site was 2.745 6, with its range being 1.276 0 to 4.742 5. Shannon genetic diversity index (I) values ranged between 0.513 3 and 2.239 9 (M=1.209 0). Nei's gene diversity index (H) ranged between 0.216 3 and 0.789 1 (M=0.578 0). The observed heterozygosity (H_o) ranged between 0.223 3 and 0.895 2 (M=0.557 5). The expected heterozygosity (H_e) ranged between 0.217 4 and 0.793 3 (M=0.580 8). The polymorphism information content (PIC) ranged between 0.211 5 and 0.774 0 (M=0.532 9). The genetic similarity (GS) ranged between 0.228 5 and 1.000 0 (M=0.608 3). Cluster analysis revealed that when the genetic distance (GD) equals to 0.30, the tested materials can be classified into 2 groups. When the GD equals to 0.27, the first group can be divided into 6 subgroups; accordingly, 105 tested materials can be divided into 7 subgroups. The cophenetic correlation test was carried out based on the cluster analysis, and the corresponding results showed that the cluster map correlated with the genetic similarity coefficient (r=0.952 73). According to the results of Structure population analysis, we obtained the optimal population number, with the true number of populations (K) being 3 and the population being divided concerning Q≥0.5. Three subgroups, i.e., Q1, Q2 and Q3, included 34, 33 and 28 germplasms, respectively, and the remaining 10 germplasms were identified as the mixed population. During the experiment, 9 pairs of core primers were screened among the total of 12 for a complete differentiation regarding 105 tested materials, and the fingerprints of 91 C.×morifolium materials and 14 chrysanthemum-related materials were further constructed. Overall, there were significant genetic differences and rich genetic diversity among C.×morifolium materials, which would shed light on the garden application and variety selection fields of C.×morifolium. The fingerprint database of 105 C.×morifolium varieties and chrysanthemum-related species may provide technical support for future research regarding the identification and screening system of C.×morifolium varieties.
Genetic Variation ; Chrysanthemum/genetics* ; Reproducibility of Results ; Microsatellite Repeats/genetics* ; Polymorphism, Genetic ; Biomarkers ; Phylogeny

Objective To investigate the influencing factors and establish a model predicting the performance of needle visualization in fine-needle aspiration (FNA) of thyroid nodules. Methods This study prospectively included 175 patients who underwent FNA of thyroid nodules in the Department of Ultrasound in China-Japan Friendship Hospital and compared the display of the needle tips in the examination of 199 thyroid nodules before and after the application of needle visualization.We recorded the location,the positional relationship with thyroid capsule,ultrasonic characteristics,and the distribution of the soft tissue strip structure at the puncture site of the nodules with unclear needle tips display before using needle visualization.Furthermore,according to the thyroid imaging reporting and data system proposed by the American College of Radiology,we graded the risk of the nodules.Lasso-Logistic regression was employed to screen out the factors influencing the performance of needle visualization and establish a nomogram for prediction. Results The needle tips were not clearly displayed in the examination of 135 (67.8%) and 53 (26.6%) nodules before and after the application of needle visualization,respectively,which showed a significant difference (P<0.001).Based on the positional relationship between the nodule and capsule,anteroposterior/transverse diameter (A/T) ratio,blood supply,and the distribution of subcutaneous strip structure at the puncture site,a nomogram was established to predict the probability of unclear display of the needle tips after application of needle visualization.The C-index of the prediction model was 0.75 (95%CI=0.67-0.84) and the area under the receiver operating characteristic curve was 0.72.The calibration curve confirmed the appreciable reliability of the prediction model,with the C-index of 0.70 in internal validation. Conclusions Needle visualization can improve the display of the needle tip in ultrasound-guided FNA of thyroid nodules.The nomogram established based on ultrasound features such as the positional relationship between the nodule and capsule,A/T ratio,blood supply,and the distribution of subcutaneous strip structure at the puncture site can predict whether needle visualization is suitable for the examination of nodules.
Humans ; Thyroid Nodule/diagnostic imaging* ; Biopsy, Fine-Needle/methods* ; Reproducibility of Results ; Ultrasonography ; Retrospective Studies ; Thyroid Neoplasms

Tanshinones are one of the main effective components of Salvia miltiorrhiza, which play important roles in the treatment of cardiovascular diseases. Microbial heterogony production of tanshinones can provide a large number of raw materials for the production of traditional Chinese medicine(TCM) preparations containing S. miltiorrhiza, reduce the extraction cost, and relieve the pressure of clinical medication. The biosynthetic pathway of tanshinones contains multiple P450 enzymes, and the catalytic element with high efficiency is the basis of microbial production of tanshinones. In this study, the protein modification of CYP76AK1, a key P450-C20 hydroxylase in tanshinone pathway, was researched. The protein modeling methods SWISS-MODEL, Robetta, and AlphaFold2 were used, and the protein model was analyzed to obtain the reliable protein structure. The semi-rational design of mutant protein was carried out by molecular docking and homologous alignment. The key amino acid sites affecting the oxidation activity of CYP76AK1 were identified by molecular docking. The function of the obtained mutations was studied with yeast expression system, and the CYP76AK1 mutations with continuous oxidation function to 11-hydroxysugiol were obtained. Four key amino acid sites that affected the oxidation acti-vity were analyzed, and the reliability of three protein modeling methods was analyzed according to the mutation results. The effective protein modification sites of CYP76AK1 were reported for the first time in this study, which provides a catalytic element for different oxidation activities at C20 site for the study of the synthetic biology of tanshinones and lays a foundation for the analysis of the conti-nuous oxidation mechanism of P450-C20 modification.
Oxidoreductases ; Biosynthetic Pathways ; Molecular Docking Simulation ; Reproducibility of Results ; Salvia miltiorrhiza/chemistry* ; Amino Acids/metabolism* ; Plant Roots/genetics*

Focusing on the development and quality improvement strategy of the traditional Chinese medicine(TCM) industry, the scientific and technological innovation of the new engineering of TCM should be paid attention to solve the "stuck neck" dilemma. Under the background of the ecological and industrial revolution of the scientific and technological innovation system, the super-scale information interaction and multi-dimensional integration will inevitably lead to profound changes in the manufacturing mode of TCM. Manufacturing measurement of TCM is formed on the basis of the reliability engineering theory of process control of TCM production. It is the development extension of system theory and system science ideas and a cross-fertilization discipline that combines theory with practice and adheres to the "four-oriented" re-epistemology improvement of the TCM discipline. In response to the problems of complex raw material sources, coarse process technology, unclear material basis, and poor applicability of equipment and technology in the manufacture of TCM, the transformation research mode of "aiming at the integration of pharmaceutical industry-developing intelligent production line-enabling industrial transformation" has been developed. This paper proposed the four key engineering technical problems, i.e., the identification of critical quality attributes(CQA) in the manufacture of TCM, the quality by design(QbD) and product development of the manufacturing process of TCM, the quality transfer principle and multivariate process capability index of TCM manufacturing, and the development of measurement technology and equipment of the manufacturing measurement of TCM, to achieve the systematization of quality control indicators, real-time process control, digitalization of manufacturing process, transparency of quality transfer, and intelligent whole-process control. In this paper, the new concepts, new theories, and new technologies provide a reference for the industrialization of TCM.
Medicine, Chinese Traditional ; Reproducibility of Results ; Commerce ; Drug Industry ; Quality Control

The pharmaceutical manufacturing model is gradually changing from intermittent manufacturing to continuous manufacturing and intelligent manufacturing. This paper briefly reviewed the supervision and research progress in continuous pharmaceutical manufacturing in China and abroad and described the definition and advantages of continuous pharmaceutical manufacturing. The continuous manufacturing of traditional Chinese medicine(TCM) at the current stage was summarized in the following three terms: the enhancement of the continuity of intermittent manufacturing operations, the integration of continuous equipment to improve physical continuity between units, and the application of advanced process control strategies to improve process continuity. To achieve continuous manufacturing of TCM, the corresponding key technologies, such as material property characterization, process modeling and simulation, process analysis technology, and system integration, were analyzed from the process and equipment, respectively. It was proposed that the continuous manufacturing equipment system should have the characteristics of high speed, high response, and high reliability, "three high(H~3)" for short. Considering the characteristics and current situation of TCM manufacturing, based on the two dimensions of product quality control and production efficiency, a maturity assessment model for continuous manufacturing of TCM, consisting of operation continuity, equipment continuity, process continuity, and quality control continuity, was proposed to provide references for the application of continuous manufacturing technology for TCM. The implementation of continuous manufacturing or the application of key continuous manufacturing technologies in TCM can help to systematically integrate advanced pharmaceutical technology elements and promote the uniformity of TCM quality and the improvement of production efficiency.
Medicine, Chinese Traditional ; Reproducibility of Results ; China ; Quality Control ; Pharmaceutical Preparations

In the new stage for intelligent manufacturing of traditional Chinese medicine(TCM) from pilot demonstration to in-depth application and comprehensive promotion, how to raise the degree of intelligence for the process quality control system has become the bottleneck of the development of TCM production process control technology. This article has sorted out 226 TCM intelligent manufacturing projects that have been approved by the national and provincial governments since the implementation of the "Made in China 2025" plan and 145 related pharmaceutical enterprises. Then, the patents applied by these pharmaceutical enterprises were thoroughly retrieved, and 135 patents in terms of intelligent quality control technology in the production process were found. The technical details about intelligent quality control at both the unit levels such as cultivation, processing of crude herbs, preparation pretreatment, pharmaceutical preparations, and the production workshop level were reviewed from three aspects, i.e., intelligent quality sensing, intelligent process cognition, and intelligent process control. The results showed that intelligent quality control technologies have been preliminarily applied to the whole process of TCM production. The intelligence control of the extraction and concentration processes and the intelligent sensing of critical quality attributes are currently the focus of pharmaceutical enterprises. However, there is a lack of process cognitive patent technology for the TCM manufacturing process, which fails to meet the requirements of closed-loop integration of intelligent sensing and intelligent control technologies. It is suggested that in the future, with the help of artificial intelligence and machine learning methods, the process cognitive bottleneck of TCM production can be overcome, and the holistic quality formation mechanisms of TCM products can be elucidated. Moreover, key technologies for system integration and intelligent equipment are expected to be innovated and accelerated to enhance the quality uniformity and manufacturing reliability of TCM.
Artificial Intelligence ; Medicine, Chinese Traditional ; Reproducibility of Results ; Quality Control ; Intelligence ; Pharmaceutical Preparations

UPLC-Q-Exactive-MS/MS and network pharmacology were employed to preliminarily study the active components and mechanism of Jinwugutong Capsules in the treatment of osteoporosis. Firstly, UPLC-Q-Exactive-MS/MS was employed to characterize the chemical components of Jinwugutong Capsules, and network pharmacology was employed to establish the "drug-component-target-pathway-disease" network. The key targets and main active components were thus obtained. Secondly, AutoDock was used for the molecular docking between the main active components and key targets. Finally, the animal model of osteoporosis was established, and the effect of Jinwugutong Capsules on the expression of key targets including RAC-alpha serine/threonine-protein kinase(AKT1), albumin(ALB), and tumor necrosis factor-alpha(TNF-α) was determined by enzyme-linked immunosorbent assay(ELISA). A total of 59 chemical components were identified from Jinwugutong Capsules, among which coryfolin, 8-prenylnaringenin, demethoxycurcumin, isobavachin, and genistein may be the main active components of Jinwugutong Capsules in treating osteoporosis. The topological analysis of the protein-protein interaction(PPI) network revealed 10 core targets such as AKT1, ALB, catenin beta 1(CTNNB1), TNF, and epidermal growth factor receptor(EGFR). The Kyoto Encyclopedia of Genes and Genomes(KEGG) enrichment showed that Jinwugutong Capsules mainly exerted the therapeutic effect by regulating the phosphatidylinositol 3-kinase(PI3K)/protein kinase B(AKT) signaling pathway, neuroactive ligand-receptor interaction, mitogen-activated protein kinase(MAPK) signaling pathway, Rap1 signaling pathway and so on. Molecular docking showed that the main active components of Jinwugutong Capsules well bound to the key targets. ELISA results showed that Jinwugutong Capsules down-regulated the protein levels of AKT1 and TNF-α and up-regulated the protein level of ALB, which preliminarily verified the reliability of network pharmacology. This study indicates that Jinwugutong Capsules may play a role in the treatment of osteoporosis through multiple components, targets, and pathways, which can provide reference for the further research.
Animals ; Tumor Necrosis Factor-alpha/genetics* ; Network Pharmacology ; Capsules ; Molecular Docking Simulation ; Phosphatidylinositol 3-Kinases ; Reproducibility of Results ; Tandem Mass Spectrometry