Objective To explore a deep learning-based automatic bone age estimation model for elbow joint X-ray images of Chinese Han adolescents and children and evaluate its performance.Methods A total of 943(517 males and 426 females)elbow joint frontal view X-ray images of Chinese Han ado-lescents and children aged 6.00 to<16.00 years were collected from East,South,Central and North-west China.Three experimental schemes were adopted for bone age estimation.Scheme 1:Directly in-put preprocessed images into the regression model;Scheme 2:Train a segmentation network using"key elbow joint bone annotations"as labels,then input segmented images into the regression model;Scheme 3:Train a segmentation network using"full elbow joint bone annotations"as labels,then in-put segmented images into the regression model.For segmentation,the optimal model was selected from U-Net,UNet++and TransUNet.For regression,VGG16,VGG19,InceptionV2,InceptionV3,ResNet34,ResNet50,ResNet101 and DenseNet121 models were selected for bone age estimation.The dataset was randomly split into 80%(754 samples)for training and validation for model fitting and hyperparameter tuning,and 20%(189 samples)as an internal test set to test the performance of the trained model.An additional 104 elbow joint X-ray images from the same demographic and age group were col-lected and used as an external test set.Model performance was evaluated by comparing the mean ab-solute error(MAE),root mean square error(RMSE),accuracies within±0.7 years(P±0.7 years)and±1.0 years(P±1.0 years)between the estimated age and the actual age,and by drawing radar charts,scat-ter plots,and heatmaps.Results When segmented with Scheme 3,the UNet++model achieved good segmentation performance with a segmentation loss of 0.000 4 and an accuracy of 93.8%at a learning rate of 0.000 1.In the internal test set,the DenseNet121 model with Scheme 3 yielded the best results with MAE,P±0.7 years and P±1.0 years being 0.83 years,70.03%,and 84.30%,respectively.In the external test set,the DenseNet121 model with Scheme 3 also performed best,with an average MAE of 0.89 years and an average RMSE of 1.00 years.Conclusion When performing automatic bone age estima-tion using elbow joint X-ray images in Chinese Han adolescents and children,it is recommended to use the UNet++model for segmentation.The DenseNet121 model with Scheme 3 achieves optimal per-formance.Using segmentation networks,especially that trained with annotation areas encompassing the full elbow joint including the distal humerus,proximal radius,and proximal ulna,can improve the ac-curacy of bone age estimation based on elbow joint X-ray images.

Objective To explore a deep learning network model suitable for bone age estimation using shoulder joint X-ray images in Chinese Han adolescents.Methods A retrospective collection of 1 286 shoulder joint X-ray images of Chinese Han adolescents aged 12.0 to<18.0 years(708 males and 578 females)was conducted.Using random sampling,approximately 80%of the samples(1 032 cases)were selected as the training and validation sets for model learning,selection and optimization,and the other 20%samples(254 cases)were used as the test set to evaluate the model's generalization ability.The original single-channel shoulder joint X-ray images and dual-channel inputs combining original images with segmentation labels(manually annotated shoulder joint regions multiplied pixel-by-pixel with original images,followed by segmentation via the U-Net++network to retain only key shoulder joint region information)were respectively input into four network models,namely VGG16,ResNet18,ResNet50 and DenseNet121 for bone age estimation.Additionally,manual bone age estimation was con-ducted on the test set data,and the results were compared with the four network models.The mean absolute error(MAE),root mean square error(RMSE),coefficient of determination(R2),and Pear-son correlation coefficient(PCC)were used as main evaluation indicators.Results In the test set,the bone age estimation results of the four models with dual-channel input of shoulder joint X-ray images outperformed those with single-channel input in all four evaluation indicators.Among them,DenseNet121 with dual-channel input achieved best results with MAE of 0.54 years,RMSE of 0.82 years,R2 of 0.76,and PCC(r)of 0.88.Manual estimation yielded an MAE of 0.82 years,ranking second only to dual-channel DenseNet121.Conclusion The DenseNet121 model with dual-channel input combined with original images and segmentation labels is superior to manual evaluation results,and can effectively estimate the bone age of Chinese Han adolescents.

BACKGROUND: Growing evidence suggests that long non-coding RNAs (lncRNAs) exert pivotal roles in fostering chemoresistance across diverse tumors. Nevertheless, the precise involvement of lncRNAs in modulating chemoresistance within the context of gallbladder cancer (GBC) remains obscure. This study aimed to uncover how lncRNAs regulate chemoresistance in gallbladder cancer, offering potential targets to overcome drug resistance. METHODS: To elucidate the relationship between gemcitabine sensitivity and small nucleolar RNA host gene 1 ( SNHG1 ) expression, we utilized publicly available GBC databases, GBC tissues from Renji Hospital collected between January 2017 and December 2019, as well as GBC cell lines. The assessment of SNHG1, miR-23b-3p, and phosphatase and tensin homolog (PTEN) expression was performed using in situ  hybridization, quantitative real-time polymerase chain reaction, and western blotting. The cell counting kit-8 (CCK-8) assay was used to quantify the cell viability. Furthermore, a GBC xenograft model was employed to evaluate the impact of SNHG1 on the therapeutic efficacy of gemcitabine. Receiver operating characteristic (ROC) curve analyses were executed to assess the specificity and sensitivity of SNHG1. RESULTS: Our analyses revealed an inverse correlation between the lncRNA SNHG1 and gemcitabine resistance across genomics of drug sensitivity in cancer (GDSC) and Gene Expression Omnibus (GEO) datasets, GBC cell lines, and patients. Gain-of-function investigations underscored that SNHG1 heightened the gemcitabine sensitivity of GBC cells in both in vitro and in vivo  settings. Mechanistic explorations illuminated that SNHG1 could activate PTEN -a commonly suppressed tumor suppressor gene in cancers-thereby curbing the development of gemcitabine resistance in GBC cells. Notably, microRNA (miRNA) target prediction algorithms unveiled the presence of miR-23b-3p binding sites within SNHG1 and the 3'-untranslated region (UTR) of PTEN . Moreover, SNHG1 acted as a sponge for miR-23b-3p, competitively binding to the 3'-UTR of PTEN , thereby amplifying PTEN expression and heightening the susceptibility of GBC cells to gemcitabine. CONCLUSION The SNHG1/miR-23b-3p/PTEN axis emerges as a pivotal regulator of gemcitabine sensitivity in GBC cells, holding potential as a promising therapeutic target for managing GBC patients.
Humans ; Deoxycytidine/pharmacology* ; PTEN Phosphohydrolase/genetics* ; Gemcitabine ; RNA, Long Noncoding/metabolism* ; MicroRNAs/genetics* ; Gallbladder Neoplasms/genetics* ; Cell Line, Tumor ; Animals ; Mice ; Drug Resistance, Neoplasm/genetics* ; Mice, Nude ; Antimetabolites, Antineoplastic ; Gene Expression Regulation, Neoplastic

Based on the pharmacokinetics theory, this study investigated the pharmacokinetic characteristics of albiflorin, paeoniflorin, wogonoside, and wogonin in normal and febrile rats and summarized absorption and elimination rules of Dayuanyin in them to provide reference for further development and clinical application of Dayuanyin. Blood samples were taken from the fundus venous plexus of normal and model rats after intragastric administration of Dayuanyin at different time points. The concentration of each substance in blood was determined by ultra performance liquid chromatography-triple quadrupole mass spectrometry(UPLC-MS/MS) technique at different time points. DAS 2.0, a piece of pharmacokinetics software, was used to calculate the pharmacokinetic parameters of each component. The results show that the 4 components had good linear relationship in their respective ranges, and the results of methodological investigation met the requirements. The pharmacokinetic parameters of C_(max), T_(max), t_(1/2), AUC_(0-t), AUC_(0-∞), and MRT_(0-t) were calculated by the DAS 2.0 non-compartmental model. Compared with those in the normal group, C_(max) and AUC_(0-t) of the 4 components in the model group were significantly increased. There were significant differences in the pharmacokinetic characteristics between the normal and model groups, suggesting that the absorption and elimination of Dayuanyin may be affected by the changes of internal environment of the body in different physiological states.
Animals ; Rats ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Rats, Sprague-Dawley ; Fever/metabolism* ; Tandem Mass Spectrometry ; Chromatography, High Pressure Liquid ; Glucosides/pharmacokinetics* ; Monoterpenes

This study identified blood-entering components of Anshen Dropping Pills and explored their anti-insomnia effects and mechanisms. The main blood-entering components of Anshen Dropping Pills were detected and identified by UPLC-Q-TOF-MS/MS. The rationality of the formula was assessed by using enrichment analysis based on the relationship between drugs and symptoms, and core targets of its active components were selected as the the potential anti-insomnia targets of Anshen Dropping Pills through network pharmacology analysis. Furthermore, protein-protein interaction(PPI) network, Gene Ontology(GO) enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analysis were performed on the core targets. An active component-core target network for Anshen Dropping Pills was constructed. Finally, the effects of low-, medium-, and high-dose groups of Anshen Dropping Pills on sleep episodes, sleep duration, and sleep latency in mice were measured by supraliminal and subliminal pentobarbital sodium experiments. Moreover, total scores of the Pittsburgh sleep quality index(PSQI) scale was used to evaluate the changes before and after the treatment with Anshen Dropping Pills in a clinical study. The enrichment analysis based on the relationship between drugs and symptoms verified the rationality of the Anshen Dropping Pills formula, and nine blood-entering components of Anshen Dropping Pills were identified by UPLC-Q-TOF-MS/MS. The network proximity revealed a significant correlation between eight components and insomnia, including magnoflorine, liquiritin, spinosin, quercitrin, jujuboside A, ginsenoside Rb_3, glycyrrhizic acid, and glycyrrhetinic acid. Network pharmacology analysis indicated that the major anti-insomnia pathways of Anshen Dropping Pills involved substance and energy metabolism, neuroprotection, immune system regulation, and endocrine regulation. Seven core genes related to insomnia were identified: APOE, ALB, BDNF, PPARG, INS, TP53, and TNF. In summary, Anshen Dropping Pills could increase sleep episodes, prolong sleep duration, and reduce sleep latency in mice. Clinical study results demonstrated that Anshen Dropping Pills could decrease total scores of PSQI scale. This study reveals the pharmacodynamic basis and potential multi-component, multi-target, and multi-pathway effects of Anshen Dropping Pills, suggesting that its anti-insomnia mechanisms may be associated with the regulation of insomnia-related signaling pathways. These findings offer a theoretical foundation for the clinical application of Anshen Dropping Pills.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Tandem Mass Spectrometry/methods* ; Sleep Initiation and Maintenance Disorders/metabolism* ; Mice ; Network Pharmacology ; Male ; Chromatography, High Pressure Liquid ; Humans ; Protein Interaction Maps/drug effects* ; Sleep/drug effects* ; Female ; Adult

Coronary heart disease is a cardiovascular disease that affects coronary arteries. It presents high incidence and high mortality worldwide, bringing a serious threat to human health and quality of life. Salviae Miltiorrhizae Radix et Rhizoma derived from Salvia miltiorrhiza is widely used in the treatment of cardiovascular diseases, such as coronary heart disease. Salvianolic acid B is an active component in Salviae Miltiorrhizae Radix et Rhizoma extracts, and studies have shown that it has anti-inflammatory, antioxidant, apoptosis-and autophagy-regulating, anti-fibrosis, and metabolism-modulating effects. This article reviews the research progress regarding the therapeutic effect of salvianolic acid B on coronary heart disease in the recent decade. It elaborates on the role and mechanism of salvianolic acid B in treating coronary heart disease from multiple perspectives, such as the inhibition of thrombosis, improvement of blood circulation, reduction of myocardial cell injury, and inhibition of cardiac remodeling. This article provides a theoretical basis for the application of Chinese medicinal materials and TCM prescriptions containing salvianolic acid B in the treatment of coronary heart disease.
Humans ; Benzofurans/administration & dosage* ; Coronary Disease/genetics* ; Drugs, Chinese Herbal/administration & dosage* ; Salvia miltiorrhiza/chemistry* ; Animals ; Depsides

This study investigates the genetic diversity and evolutionary relationships of different Artemisia argyi germplasm resources to provide a basis for germplasm identification, variety selection, and resource protection. A total of 192 germplasm resources of A. argyi were studied, and EST-based simple sequence repeat(EST-SSR) primers were designed based on transcriptomic data of A. argyi. Polymerase chain reaction(PCR) amplification was performed on these resources, followed by fluorescence capillary electrophoresis to detect genetic diversity and construct DNA fingerprints. From 197 pairs of primers designed, 28 pairs with polymorphic and clear bands were selected. A total of 278 alleles were detected, with an average of 9.900 0 alleles per primer pair and an average effective number of alleles of 1.407 2. The Shannon's diversity index(I) for the A. argyi germplasm resources ranged from 0.148 1 to 0.418 0, with an average of 0.255 7. The polymorphism information content(PIC) ranged from 0.454 5 to 0.878 0, with an average of 0.766 9, showing high polymorphism. Cluster analysis divided the A. argyi germplasm resources into three major groups: Group Ⅰ contained 136 germplasm samples, Group Ⅱ contained 45, and Group Ⅲ contained 11. Principal component analysis also divided the resources into three groups, which was generally consistent with the clustering results. Mantel test results showed that the genetic variation in A. argyi populations was to some extent influenced by geographic distance, but the effect was minimal. Structure analysis showed that 190 germplasm materials had Q≥ 0.6, indicating that these germplasm materials had a relatively homogeneous genetic origin. Furthermore, 8 core primer pairs were selected from the 28 designed primers, which could distinguish various germplasm types. Using these 8 core primers, DNA fingerprints for the 192 A. argyi germplasm resources were successfully constructed. EST-SSR molecular markers can be used to study the genetic diversity and phylogenetic relationships of A. argyi, providing theoretical support for the identification and molecular-assisted breeding of A. argyi germplasm resources.
Artemisia/classification* ; Microsatellite Repeats ; Genetic Variation ; Expressed Sequence Tags ; DNA Fingerprinting ; Phylogeny ; Polymorphism, Genetic ; DNA, Plant/genetics* ; Genetic Markers

Medical institutions, with their clinical practice foundation and abundant human use experience data, have become important carriers for the inheritance and innovation of traditional Chinese medicine(TCM) and the "cradles" of the preparation of new TCM. To effectively promote the transformation of new TCM originating from the TCM clinical practice in medical institutions and establish an effective evaluation index system for the transformation of new TCM conforming to the characteristics of TCM, consensus experts adopted the literature research, questionnaire survey, Delphi method, etc. By focusing on the policy and technical evaluation of new TCM originating from the TCM clinical practice in medical institutions, a comprehensive evaluation from the dimensions of drug safety, efficacy, feasibility, and characteristic advantages was conducted, thus forming a comprehensive evaluation system with four primary indicators and 37 secondary indicators. The expert consensus reached aims to encourage medical institutions at all levels to continuously improve the high-quality research and development and transformation of new TCM originating from the TCM clinical practice in medical institutions and targeted at clinical needs, so as to provide a decision-making basis for the preparation, selection, cultivation, and transformation of new TCM for medical institutions, improve the development efficiency of new TCM, and precisely respond to the public medication needs.
Medicine, Chinese Traditional/standards* ; Humans ; Consensus ; Drugs, Chinese Herbal/therapeutic use* ; Surveys and Questionnaires

Based on the ultra performance liquid chromatography-quadrupole Exactive Orbitrap mass spectrometry(UPLC-Q-Exactive Orbitrap-MS) technology, combined with related literature, databases, and reference material information, this study qualitatively analyzed the components of Dayuanyin in the tissue of rats after gavage and employed molecular docking technology to predict the rationality of the mechanism behind the antipyretic effect of the in vivo components in Dayuanyin. A total of 21, 26, 20, 21, 14, and 31 prototype components and 3, 16, 3, 7, 5, and 24 metabolites were identified from the heart, liver, spleen, lung, kidney, and hypothalamus of the rats, respectively, and the binding ability of key components and targets was further verified by molecular docking. The results showed that all components had good binding ability with targets. The established UPLC-Q-Exactive Orbitrap-MS could effectively and quickly identify the Dayuanyin components distributed in tissue and preliminarily identify their metabolites. Many components were identified in the hypothalamus, which suggested that the components delivered to the brain should be focused on in the study on Dayuanyin in the treatment of febrile diseases. The molecular docking technology was used to predict the rationality of the mechanism behind its antipyretic effect, which lays the foundation for the clarification of the material basis and action mechanism of Dayuanyin, the development of new preparations, and the prediction of quality markers.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Rats ; Molecular Docking Simulation ; Male ; Antipyretics/metabolism* ; Rats, Sprague-Dawley ; Tissue Distribution ; Mass Spectrometry ; Chromatography, High Pressure Liquid ; Hypothalamus/metabolism*

Sishen Pills and its separated prescriptions are classic prescriptions of traditional Chinese medicine to treat intestinal diseases. In this study, a high-performance liquid chromatography-electrospray ionization tandem mass spectrometry(HPLC-ESI-MS/MS) technology was used to identify the components of Sishen Pills, Ershen Pills, and Wuweizi Powder. The positive and negative ion sources of electrospray ionization were simultaneously collected by mass spectrometry. A total of 11 effective components were detected in Sishen Pills, with four effective components detected in Ershen Pills and eight effective components detected in Wuweizi Powder, respectively. To explore the effects of Sishen Pills and its separated prescriptions on the human intestinal flora, an in vitro anaerobic fermentation model was established, and the human intestinal flora was incubated with Sishen Pills, Ershen Pills, and Wuweizi Powder in vitro. The 16S rDNA sequencing technology was used to analyze the changes in the intestinal flora. The results showed that compared with the control group, Sishen Pills, and its separated prescriptions could decrease the intestinal flora abundance and increase the Shannon index after fermentation. The abundance of Bifidobacterium was significantly increased in the Sishen Pills and Ershen Pills groups. However, the abundance of Lactobacillus, Weissella, and Pediococcus was significantly increased in the Wuweizi Powder group. After fermentation for 12 h, the pH of the fermentation solution of three kinds of liquids with feces gradually decreased and was lower than that of the control group. The decreasing amplitude in the Wuweizi Powder group was the most obvious. The single-bacteria fermentation experiments further confirmed that Sishen Pills and Wuweizi Powder had inhibitory effects on Escherichia coli, Staphylococcus aureus, and Enterococcus faecalis, and the antibacterial activity of Wuweizi Powder was stronger than that of Sishen Pills. Both Sishen Pills and Ershen Pills could promote the growth of Lactobacillus brevis, and Ershen Pills could promote the growth of Bifidobacterium adolescentis. This study provided a more sufficient theoretical basis for the clinical application of Sishen Pills and its separated prescriptions.
Humans ; Gastrointestinal Microbiome/drug effects* ; Drugs, Chinese Herbal/chemistry* ; Fermentation/drug effects* ; Bacteria/drug effects* ; Chromatography, High Pressure Liquid ; Tandem Mass Spectrometry ; Intestines/microbiology*