ObjectiveTo analyze the changes in the degree of coordination of China's major epidemic prevention and control efforts before and after the outbreak of the Corona Virus Disease 2019 (COVID-19), so as to explore the impact of epidemic prevention and control measures on coordination dynamics. MethodsA total of 3 864 policy documents related to epidemic prevention and control from January 2000 to December 2020 across 31 provinces (autonomous regions, and municipalities) in China were systematically collected. Contents specific to collaborative and cooperative efforts were extracted, and the extent of interdepartmental coordination were quantified to assess the effectiveness of epidemic prevention and control efforts. Wilcoxon signed-rank test was adopted to statistically analyze the differences between the indicators before and after the epidemic. ResultsThe average overall coordination level for major epidemic prevention and control in 31 provinces (autonomous regions, and municipalities) increased from 43.06% to 97.62%, and the average coordination levels in the eastern, central, and western China soared from 42.29%, 37.50%, and 47.46%, to 98.81%, 96.20%, and 97.46%, respectively, with statistically significant differences (all P<0.05). In terms of department categorization, coordination levels in the professional departments and the key support departments peaked at 100.00%, while other support departments rose to 95.43%, with an increase of 77.15%, 181.85%, and 139.89%, respectively, exhibiting noteworthy statistically significant differences (all P<0.001). ConclusionThe scope of coordination departments of China’s major epidemic prevention and control exists a remarkable surge following the COVID-19 outbreak, notable heightened coordination is particularly observed among the key support departments. Future endeavors should prioritize the roles played by diverse departments in epidemic prevention and control, enhancing both the clarity of departmental responsibilities and the effectiveness of interdepartmental coordination.

ObjectiveTo systematically evaluate the public health governance capacity of 40 cities in Jiangsu, Zhejiang, and Anhui Provinces, providing a scientific evaluation basis for building a "Healthy Yangtze River Delta". MethodsA comprehensive collection of policy documents, public information reports, and research literature related to public health governance capacity in Jiangsu, Zhejiang, and Anhui Provinces was conducted, totaling 6 920 policy documents, 1 720 information reports, and 1 200 literature pieces. Based on the evaluation standards for an appropriate public health system established by the research team, the basic status of public health governance capacity was assessed to identify the strengths and weaknesses of the 40 cities. ResultsIn 2022, the public health governance capacity score for the 40 cities in Jiangsu, Zhejiang, and Anhui Provinces was (562.5±38.0) points. In terms of specific areas, the emergency response field received the highest score of (791.4±49.7) points, while the chronic disease prevention and control field received the lowest score of (368.2±29.6) points. The Jiangsu-Zhejiang-Anhui region has largely achieved the strategic priority of health, gradually improved public health legal regulations, and established a basic organizational framework with a solid foundation for information and data infrastructure. However, challenges still need to be addressed, such as unstable government funding for public health, unclear departmental responsibilities, and barriers to information interoperability. ConclusionThe public health governance capacity of the 40 cities in Jiangsu, Zhejiang, and Anhui Province has been at a moderate level, but disparities have still existed across regions and fields. In the future, while continuing to deepen existing advantages, it is essential to accurately identify the causes of problems, establish a long-term and stable investment mechanism, enhance information connectivity mechanisms, further clarify departmental responsibilities, and promote the achievement of the "Healthy Yangtze River Delta" goal.

Objective To construct a "disease-syndrome combination" mathematical representation model for pulmonary nodules based on oral microbiome data, utilizing a multimodal data algorithm framework centered on dynamic systems theory. Furthermore, to compare predictive models under various algorithmic frameworks and validate the efficacy of the optimal model in predicting the presence of pulmonary nodules. Methods A total of 213 subjects were prospectively enrolled from July 2022 to March 2023 at the Hospital of Chengdu University of Traditional Chinese Medicine, Sichuan Cancer Hospital, and the Chengdu Integrated Traditional Chinese and Western Medicine Hospital. This cohort included 173 patients with pulmonary nodules and 40 healthy subjects. A novel multimodal data algorithm framework centered on dynamic systems theory, termed VAEGANTF (Variational Auto Encoder-Generative Adversarial Network-Transformer), was proposed. Subsequently, based on a multi-dimensional integrated dataset of “clinical features-syndrome elements-microorganisms”, all subjects were divided into training (70%) and testing (30%) sets for model construction and efficacy testing, respectively. Using pulmonary nodules as dependent variables, and combining candidate markers such as clinical features, lesion location, disease nature, and microbial genera, the independent variables were screened based on variable importance ranking after identifying and addressing multicollinearity. Missing values were then imputed, and data were standardized. Eight machine learning algorithms were then employed to construct pulmonary nodule risk prediction models: random forest, least absolute shrinkage and selection operator (LASSO) regression, support vector machine, multilayer perceptron, eXtreme Gradient Boosting (XGBoost), VAE-ViT (Vision Transformer), GAN-ViT, and VAEGANTF. K-fold cross-validation was used for model parameter tuning and optimization. The efficacy of the eight predictive models was evaluated using confusion matrices and receiver operating characteristic (ROC) curves, and the optimal model was selected. Finally, goodness-of-fit testing and decision curve analysis (DCA) were performed to evaluate the optimal model. Results There were no statistically significant differences between the two groups in demographic characteristics such as age and sex. The 213 subjects were randomly divided into training and testing sets (7 : 3), and prediction models were constructed using the eight machine learning algorithms. After excluding potential problems such as multicollinearity, a total of 301 clinical feature information, syndrome elements, and microbial genera markers were included for model construction. The area under the curve (AUC) values of the random forest, LASSO regression, support vector machine, multilayer perceptron, and VAE-ViT models did not reach 0.85, indicating poor efficacy. The AUC values of the XGBoost, GAN-ViT, and VAEGANTF models all reached above 0.85, with the VAEGANTF model exhibiting the highest AUC value (AUC=0.923). Goodness-of-fit testing indicated good calibration ability of the VAEGANTF model, and decision curve analysis showed a high degree of clinical benefit. The nomogram results showed that age, sex, heart, lung, Qixu, blood stasis, dampness, Porphyromonas genus, Granulicatella genus, Neisseria genus, Haemophilus genus, and Actinobacillus genus could be used as predictors. Conclusion The “disease-syndrome combination” risk prediction model for pulmonary nodules based on the VAEGANTF algorithm framework, which incorporates multi-dimensional data features of “clinical features-syndrome elements-microorganisms”, demonstrates better performance compared to other machine learning algorithms and has certain reference value for early non-invasive diagnosis of pulmonary nodules.

Under the background of carbon peaking and carbon neutrality goals, the Ministry of Ecology and Environment, together with 15 national ministries and commissions, has formulated the Implementation Plan on Establishing a Carbon Footprint Management System, and it is urgent for traditional Chinese medicine(TCM) pharmaceutical enterprises to carry out research on carbon footprint accounting methods of related products. Based on the life cycle assessment(LCA) theory, taking mulberry leaf extract produced by a certain enterprise as an example, this study analyzed the carbon footprint of TCM extracts during the life cycle. The results show that for every 1 kg of product produced, the carbon emissions from the stages of raw material acquisition, transportation, and extract production are-20.569, 1.205, and 173.577 kgCO_2eq(CO_2 equivalent), respectively. The carbon footprint of the product is 154.213 kgCO_2eq·kg~(-1). In addition, the carbon emission is the highest in the production stage, in which the consumption of ethanol solvents makes the greatest contribution to the carbon footprint, accounting for 25.71%, more than one-fourth of the total carbon footprint. The second contribution was from the treatment process of TCM residues, accounting for 19.67%, closely followed by wastewater treatment(17.71%), the consumption of hot steam(17.43%), and drinking water(16.90%). The consumption of electric power and packaging materials has a smaller carbon emission of 2.58%. In particular, the carbon emission caused by the consumption of packaging materials is only 0.04%, which is negligible. The results of the study are expected to provide a reference for TCM enterprises to carry out research on the carbon footprint of products, offer ideas for collaborative innovation in reducing pollution and carbon emissions throughout the entire industry chain of TCM, and develop new quality productivity of modern TCM industry based on green and low-carbon manufacturing.
Morus/chemistry* ; Plant Leaves/chemistry* ; Carbon Footprint ; Drugs, Chinese Herbal/chemistry* ; Plant Extracts/analysis* ; Medicine, Chinese Traditional

A high performance liquid chromatography-tandem mass spectrometry(HPLC-MS/MS) method was established for simultaneous determination of seven characteristic components from the active fraction of Alpiniae Officinarum Rhizoma in rat plasma, including galangin, kaempferol, kaempferide, pinocembrin, 1,7-diphenyl-4-en-3-heptanone, 5-hydroxy-7-(4-hydroxy-3-methoxyphenyl)-1-phenyl-3-heptanone(DHPA), and 7-(4-hydroxy-3-methoxyphenyl)-1-phenyl-4-en-3-heptanone(DPHB). The new developed HPLC-MS/MS method was applied to study the pharmacokinetics of the 7 characteristic components in rats with Helicobacter pylori gastritis. A Waters Sunfire C_(18) column(2.1 mm×150 mm, 3.5 μm) was used. The acetonitrile-aqueous solution(containing 0.1% formic acid) was adopted as the mobile phase for gradient elution. Seven components and internal standard(chlorogenic acid) were separated within 12 min. Mass spectrometric detection was performed in multiple reaction monitoring(MRM) mode using electrospray ionization(ESI) source with fast switching between positive and negative ions. The method was verified by specificity, linearity, precision, accuracy, recovery, matrix effect, and stability and met the requirements of pharmacokinetic study on the 7 components in rat plasma. Pharmacokinetic results showed that the average peak time(T_(max)) of the 7 components was 0.31-2.19 h, their elimination half-life(t_(1/2)) was 5.26-16.65 h, and the average residence time(MRT) was 6.29-31.03 h after the oral administration of the active fraction of Alpiniae Officinarum Rhizoma to rats with H. pylori gastritis. The plasma exposure levels of galangin and DHPA were higher than those of the other components. The concentration-time curves of four detected flavonoids showed obvious double peaks. This study elucidated the pharmacokinetic characteristics of 7 characteristic components from the active fraction of Alpiniae Officinarum Rhizoma in rats with H. pylori gastritis, providing a scientific basis for the identification of the pharmacodynamic substances of Alpiniae Officinarum Rhizoma for treatment of H. pylori gastritis and the clinical application of Alpiniae Officinarum Rhizoma in the prevention and treatment of H. pylori gastritis.
Animals ; Rats ; Chromatography, High Pressure Liquid/methods* ; Tandem Mass Spectrometry/methods* ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Helicobacter pylori/drug effects* ; Alpinia/chemistry* ; Rats, Sprague-Dawley ; Gastritis/metabolism* ; Helicobacter Infections/metabolism* ; Flavonoids/blood* ; Rhizome/chemistry* ; Liquid Chromatography-Mass Spectrometry

Aromatic immunity in traditional Chinese medicine(TCM) is the medical knowledge accumulated in the process of people's struggling with diseases. It plays an important role in plague prevention, disease treatment, health preservation, and rehabilitation, and has profound TCM basic theoretical support and abundant modern scientific evidence. With the in-depth promotion of the Healthy China initiative and the succession of health needs in the post-COVID-19 era, how to practice the health concept of aromatic immunity in TCM and develop its health service resources with high quality has become an important proposition to be discussed urgently. This paper summarizes the cognitive process, puts forward the basic concept, discusses the scientific connotation and clinical application value, and looks forward to the future development trend of aromatic immunity in TCM, aiming to provide guidance for the development of great health products and promote the application of aromatic immunity in TCM in serving people's health.
Medicine, Chinese Traditional/methods* ; Humans ; COVID-19/immunology* ; China ; Drugs, Chinese Herbal/therapeutic use* ; SARS-CoV-2

The chemical composition of Paeoniae Radix Alba(PRA) is complex, with primary secondary metabolites including monoterpenoids, tannins, triterpenoids, and flavonoids. In previous studies on the material basis of PRA, it was found that, in addition to the widely studied characteristic monoterpene glycosides, tannic acid components also play an important role in the efficacy of PRA. However, their pharmacological effects have not been thoroughly investigated. This paper reviews the tannic acid components in PRA, including pentagaloyl glucose(PGG), tetragaloyl glucose(TGG), trigaloyl glucose(TriGG), and gallic acid, along with their structures, properties, and characteristics to provide a detailed discussion of their pharmacological activities and related mechanisms, aiming to offer a theoretical basis for the material basis research and clinical application of PRA.
Paeonia/chemistry* ; Tannins/chemistry* ; Humans ; Drugs, Chinese Herbal/chemistry* ; Animals ; Plant Extracts

Primary ciliary dyskinesia (PCD) is a clinically rare, genetically and phenotypically heterogeneous condition characterized by chronic respiratory tract infections, male infertility, tympanitis, and laterality abnormalities. PCD is typically resulted from variants in genes encoding assembly or structural proteins that are indispensable for the movement of motile cilia. Here, we identified a novel nonsense mutation, c.466G>T, in cilia- and flagella-associated protein 300 ( CFAP300 ) resulting in a stop codon (p.Glu156*) through whole-exome sequencing (WES). The proband had a PCD phenotype with laterality defects and immotile sperm flagella displaying a combined loss of the inner dynein arm (IDA) and outer dynein arm (ODA). Bioinformatic programs predicted that the mutation is deleterious. Successful pregnancy was achieved through intracytoplasmic sperm injection (ICSI). Our results expand the spectrum of CFAP300 variants in PCD and provide reproductive guidance for infertile couples suffering from PCD caused by them.
Adult ; Female ; Humans ; Male ; Pregnancy ; China ; Ciliary Motility Disorders/genetics* ; Codon, Nonsense ; East Asian People/genetics* ; Exome Sequencing ; Homozygote ; Infertility, Male/genetics* ; Kartagener Syndrome/genetics* ; Pedigree ; Sperm Injections, Intracytoplasmic ; Cytoskeletal Proteins/genetics*

Nonobstructive azoospermia (NOA), one of the most severe types of male infertility, etiology often remains unclear in most cases. Therefore, this study aimed to detect four biallelic detrimental variants (0.5%) in the minichromosome maintenance domain containing 2 ( MCMDC2 ) genes in 768 NOA patients by whole-exome sequencing (WES). Hematoxylin and eosin (H&E) demonstrated that MCMDC2 deleterious variants caused meiotic arrest in three patients (c.1360G>T, c.1956G>T, and c.685C>T) and hypospermatogenesis in one patient (c.94G>T), as further confirmed through immunofluorescence (IF) staining. The single-cell RNA sequencing data indicated that MCMDC2 was substantially expressed during spermatogenesis. The variants were confirmed as deleterious and responsible for patient infertility through bioinformatics and in vitro experimental analyses. The results revealed four MCMDC2 variants related to NOA, which contributes to the current perception of the function of MCMDC2 in male fertility and presents new perspectives on the genetic etiology of NOA.
Humans ; Male ; Azoospermia/genetics* ; Meiosis/genetics* ; Spermatogenesis/genetics* ; Adult ; Exome Sequencing ; Microtubule-Associated Proteins/genetics* ; Alleles ; Infertility, Male/genetics*

OBJECTIVES: To investigate the molecular epidemiology of children with phenylketonuria (PKU) in Gansu, China, providing foundational data for intervention strategies. METHODS: A retrospective analysis was conducted on 1 159 PKU families who attended Gansu Provincial Maternity and Child Care Hospital from January 2012 to December 2024. Sanger sequencing, multiplex ligation-dependent probe amplification, whole exome sequencing, and deep intronic variant analysis were used to analyze the PAH gene. RESULTS: For the 1 159 children with PKU, 2 295 variants were identified in 2 318 alleles, resulting in a detection rate of 99.01%. The detection rates were 100% (914/914) in 457 classic PKU families, 99.45% (907/912) in 456 mild PKU families, and 96.34% (474/492) in 246 mild hyperphenylalaninemia families. The 2 295 variants detected comprised 208 distinct mutation types, among which c.728G>A (14.95%, 343/2 295) had the highest frequency, followed by c.611A>G (4.88%, 112/2 295) and c.721C>T (4.79%, 110/2 295). The cumulative frequency of the top 23 hotspot variants reached 70.28% (1 613/2 295), and most variant alleles were detected in exon 7 (29.19%, 670/2 295). CONCLUSIONS Deep intronic variant analysis of the PAH gene can improve the genetic diagnostic rate of PKU. The development of targeted detection kits for PAH hotspot variants may enable precision screening programs and enhance preventive strategies for PKU.
Humans ; Phenylketonurias/epidemiology* ; Female ; Male ; Retrospective Studies ; Phenylalanine Hydroxylase/genetics* ; Mutation ; Child, Preschool ; China/epidemiology* ; Child ; Infant