Traditional Chinese Medicine (TCM), as a treasure of the Chinese nation, plays a significant role in maintaining public health. In 2019, the Central Committee of the Communist Party of China and the State Council proposed for the first time the establishment of a TCM registration and evaluation evidence system that integrates TCM theory, "personal experience" and clinical trials (referred to as the "Three-in-One" System) to promote the inheritance and innovation of TCM. Subsequently, the National Medical Products Administration issued several guiding principles to advance the improvement and implementation of this system. Owing to the complexity of its implementation, there are still differing understandings within the TCM industry regarding the positioning of the "Three-in-One" Registration and Evaluation Evidence System, as well as the connotation and value orientation of the "personal experience." To address this, Academician WANG Qi, President of the TCM Association, China International Exchange and Promotion Association for Medical and Healthcare and TCM master, led a group of academicians, TCM masters, TCM pharmacology experts and clinical TCM experts to convene a "Seminar on Promoting the Implementation of the ′Three-in-One′ Registration and Evaluation Evidence System for Chinese Medicinals." Through extensive discussions, an expert consensus was formed, clarifying the different roles of the TCM theory, "personal experience" and clinical trials within the system. It was further emphasized that the "personal experience" is the core of this system, and its data should be derived from clinical practice scenarios. In the future, the improvement of this system will require collaborative efforts across multiple fields to promote the high-quality development of the Chinese medicinal industry.

Objective:To understand the current situation and influencing factors of functional constipation among elderly people in nursing homes, and construct a risk prediction model.Methods:Conveniently select 542 elderly people from 8 nursing homes in Tangshan urban area from July to November 2023 as the research subjects, use binary logistic regression analysis to construct a risk prediction model, and conduct internal validation of the model.Results:Among the 542 elderly people who were included in the study, there were 250 males and 292 females with an average age of 78.00 (70.00, 86.00) years. The incidence of functional constipation among elderly people in nursing homes was 54.06%(293/542). The predictive model includes six predictive factors: age, Barthel index, water intake, daily vegetable intake, insomnia, and perianal disease. The model AUC was 0.885 (95% CI 0.858-0.913), the Youden index was 0.628, the best critical value was 0.585, sensitivity was 0.819, specificity was 0.809. The Hosmer-Lemeshow test χ2=6.38, P=0.605. The internal validation results of the Bootstrap method showed that the AUC of the model was 0.876, the calibration curve was close to the standard line, and the Brier score was 0.135. The DCA results showed that the threshold was 0.1-0.9, and the model had good clinical net benefits. Conclusions:The incidence of functional constipation in elderly care institutions is relatively high. The functional constipation risk prediction model constructed in this study has good predictive efficacy and applicability, which can provide reference for nursing home staff.

As the incidence of autism rises annually,its unknown pathogenesis makes it challenging to treat the varied repetitive and stereotyped behaviors that characterize its core symptoms.The striatum is an important brain region for the control of locomotor behaviors,featuring a unique mosaic structure,complex neural origin,and finely regulated developmental process that is highly susceptible to genetic and environmental influences.Both clinical and basic studies have indicated that abnormal development of the striatal nuclei may contribute to the pathogenesis of these repetitive stereotyped behaviors in autism.Clinical imaging data have primarily identified gross anatomical variations in the stratum(e.g.,its general outline),but lack the resolution necessary to detect the cellular and subcellular alterations within the region.By introducing the abnormalities in the spatiotemporal development of the striatum and their links to the characteristic behaviors of autism,this review aims to advance our understanding of the role of the striatum in autism pathogenesis and to inform future animal studies and clinical research.

Objective To achieve non-invasive and precise prediction of mean arterial pressure(MAP)based on a fully convolutional neural network(FCNN).Methods A high-precision blood pressure data acquisition system compliant with international metrological standards was used in conjunction with the'gold standard'auscultation method to collect blood pressure and pulse waveform data from patients.True MAP values were derived via Gaussian fitting of pulse waveform data,constructing a traceable dataset.The FCNN was applied to this dataset to develop a novel MAP prediction method.Additionally,the predictive accuracy of the FCNN was compared with linear regression and conventional empirical formulas.Results The mean squared errors(MSE)for MAP prediction using the FCNN,linear regression,and empirical formulas were 19.76,21.40,and 30.97,respectively.The coefficients of determination(R2)were 0.90,0.89,and 0.84,and the prediction accuracies were 0.90,0.89,and 0.85,respectively.Conclusions By using systolic blood pressure,diastolic blood pressure,age,and arm circumference as input parameters,the FCNN-based MAP prediction method significantly reduces the bias of empirical formulas.This approach not only improves the accuracy of hemodynamic boundary condition acquisition but also contributes to refining the metrological traceability system of non-invasive blood pressure measurement.

Objective To achieve non-invasive and precise prediction of mean arterial pressure(MAP)based on a fully convolutional neural network(FCNN).Methods A high-precision blood pressure data acquisition system compliant with international metrological standards was used in conjunction with the'gold standard'auscultation method to collect blood pressure and pulse waveform data from patients.True MAP values were derived via Gaussian fitting of pulse waveform data,constructing a traceable dataset.The FCNN was applied to this dataset to develop a novel MAP prediction method.Additionally,the predictive accuracy of the FCNN was compared with linear regression and conventional empirical formulas.Results The mean squared errors(MSE)for MAP prediction using the FCNN,linear regression,and empirical formulas were 19.76,21.40,and 30.97,respectively.The coefficients of determination(R2)were 0.90,0.89,and 0.84,and the prediction accuracies were 0.90,0.89,and 0.85,respectively.Conclusions By using systolic blood pressure,diastolic blood pressure,age,and arm circumference as input parameters,the FCNN-based MAP prediction method significantly reduces the bias of empirical formulas.This approach not only improves the accuracy of hemodynamic boundary condition acquisition but also contributes to refining the metrological traceability system of non-invasive blood pressure measurement.

Objective:To understand the current situation and influencing factors of functional constipation among elderly people in nursing homes, and construct a risk prediction model.Methods:Conveniently select 542 elderly people from 8 nursing homes in Tangshan urban area from July to November 2023 as the research subjects, use binary logistic regression analysis to construct a risk prediction model, and conduct internal validation of the model.Results:Among the 542 elderly people who were included in the study, there were 250 males and 292 females with an average age of 78.00 (70.00, 86.00) years. The incidence of functional constipation among elderly people in nursing homes was 54.06%(293/542). The predictive model includes six predictive factors: age, Barthel index, water intake, daily vegetable intake, insomnia, and perianal disease. The model AUC was 0.885 (95% CI 0.858-0.913), the Youden index was 0.628, the best critical value was 0.585, sensitivity was 0.819, specificity was 0.809. The Hosmer-Lemeshow test χ2=6.38, P=0.605. The internal validation results of the Bootstrap method showed that the AUC of the model was 0.876, the calibration curve was close to the standard line, and the Brier score was 0.135. The DCA results showed that the threshold was 0.1-0.9, and the model had good clinical net benefits. Conclusions:The incidence of functional constipation in elderly care institutions is relatively high. The functional constipation risk prediction model constructed in this study has good predictive efficacy and applicability, which can provide reference for nursing home staff.

As the incidence of autism rises annually,its unknown pathogenesis makes it challenging to treat the varied repetitive and stereotyped behaviors that characterize its core symptoms.The striatum is an important brain region for the control of locomotor behaviors,featuring a unique mosaic structure,complex neural origin,and finely regulated developmental process that is highly susceptible to genetic and environmental influences.Both clinical and basic studies have indicated that abnormal development of the striatal nuclei may contribute to the pathogenesis of these repetitive stereotyped behaviors in autism.Clinical imaging data have primarily identified gross anatomical variations in the stratum(e.g.,its general outline),but lack the resolution necessary to detect the cellular and subcellular alterations within the region.By introducing the abnormalities in the spatiotemporal development of the striatum and their links to the characteristic behaviors of autism,this review aims to advance our understanding of the role of the striatum in autism pathogenesis and to inform future animal studies and clinical research.

Objective:To retrospectively analyze the molecular epidemiological features and genetic recombination of coxsackievirus A4 (CVA4) strains isolated in Jiangsu from 2015 to 2022.Methods:Throat or anal swab samples were collected from patients with herpangina or hand, foot and mouth disease (HFMD). Real-time PCR was used to detect CVA4. A comprehensive and systematic phylogenetic analysis was conducted based on 72 whole genomes and 99 VP1 sequences of CVA4 strains. Several bioinformatics software including DNAStar, MEGA7.0 and Similarity plots3.5.1 was used for analysis of homology, genetic recombination and amino acid variation sites.Results:Four genotypes (A, B, C and D) and five sub-genotypes (C1-C5) of CVA4 were identified based on the VP1 nucleotide sequences. C2 was the predominant sub-genotype causing HFMD. The Jiangsu strains showed high homology with the CVA4 prototype in the P1 region, and higher identity with other strains of enterovirus group A (EV-A) in the P2 and P3 regions. Genetic recombination analysis revealed that the Jiangsu strains had three genetic recombination patterns with other EV-A epidemic strains in the P2, P3 and 3′-UTR regions. These recombination patterns took place during the sustained and widespread circulation of CVA4 in people and increased the transmissibility of CVA4.Conclusions:This study analyzes the phylogenetic and molecular features of 28 whole genomes of Jiangsu CVA4 strains, which helps to better understand the genomic diversity of CVA4. By analyzing the genetic recombination and amino acid mutations in the VP1 region, this study elucidates the evolution and transmission of CVA4, which is conducive to the control and prevention of CVA4 infection.

Objective:To explore the application of COVID-19-specific IgG antibody in identifying epidemic Omicron BA.5 strain infection.Method:Omicron BF.7/BA.5 naturally infected population, healthy population vaccinated with the COVID-19 vaccine, and Omicron BF.7/BA.5 breakthrough cases were enrolled into this study. The serum WT-S-IgG and BA.5-S-IgG were detected by indirect ELISA, and the serum-specific IgG antibody levels of different populations were compared. The application value of the two antibody titers and the ratio of the two antibodies in identifying Omicron BA.5 epidemic strain infection were explored by the ROC curve, aiming to provide technical support for pathogen diagnosis.Results:The antibody titers of WT-S-IgG and BA.5-S-IgG in the breakthrough cases were higher than those in the naturally infected population and the healthy population ( P<0.05). The area under the curve (AUC) of WT-S-IgG and BA.5-S-IgG in identifying epidemic Omicron BA.5 strain infection was 0.947 and 0.961, respectively. The AUC of BA.5-S-IgG and WT-S-IgG antibody titer ratio was 0.873. When the antibody titer ratio was 0.855, the sensitivity and specificity were 80.00% and 90.00%, respectively. According to the interval since the last infection, the AUC of the ratio of BA.5-S-IgG to WT-S-IgG antibody titer to identify the infection of epidemic strains less than 30 days and more than 30 days was 0.887 and 0.863, respectively, and the sensitivity and specificity were both above 80%. Conclusion:Both BA.5-S-IgG and WT-S-IgG, as well as the combination of these two antibodies, are of high value in the identification of epidemic strains.

Objective:To explore the application of COVID-19-specific IgG antibody in identifying epidemic Omicron BA.5 strain infection.Method:Omicron BF.7/BA.5 naturally infected population, healthy population vaccinated with the COVID-19 vaccine, and Omicron BF.7/BA.5 breakthrough cases were enrolled into this study. The serum WT-S-IgG and BA.5-S-IgG were detected by indirect ELISA, and the serum-specific IgG antibody levels of different populations were compared. The application value of the two antibody titers and the ratio of the two antibodies in identifying Omicron BA.5 epidemic strain infection were explored by the ROC curve, aiming to provide technical support for pathogen diagnosis.Results:The antibody titers of WT-S-IgG and BA.5-S-IgG in the breakthrough cases were higher than those in the naturally infected population and the healthy population ( P<0.05). The area under the curve (AUC) of WT-S-IgG and BA.5-S-IgG in identifying epidemic Omicron BA.5 strain infection was 0.947 and 0.961, respectively. The AUC of BA.5-S-IgG and WT-S-IgG antibody titer ratio was 0.873. When the antibody titer ratio was 0.855, the sensitivity and specificity were 80.00% and 90.00%, respectively. According to the interval since the last infection, the AUC of the ratio of BA.5-S-IgG to WT-S-IgG antibody titer to identify the infection of epidemic strains less than 30 days and more than 30 days was 0.887 and 0.863, respectively, and the sensitivity and specificity were both above 80%. Conclusion:Both BA.5-S-IgG and WT-S-IgG, as well as the combination of these two antibodies, are of high value in the identification of epidemic strains.