Objective To construct large medical model named by "Huaxi HongYi"and explore its application effectiveness in assisting medical record generation. Methods By the way of a full-chain medical large model construction paradigm of "data annotation - model training - scenario incubation", through strategies such as multimodal data fusion, domain adaptation training, and localization of hardware adaptation, "Huaxi HongYi" with 72 billion parameters was constructed. Combined with technologies such as speech recognition, knowledge graphs, and reinforcement learning, an application system for assisting in the generation of medical records was developed. Results Taking the assisted generation of discharge records as an example, in the pilot department, after using the application system, the average completion times of writing a medical records shortened (21 min vs. 5 min) with efficiency increased by 3.2 time, the accuracy rate of the model output reached 92.4%. Conclusion It is feasible for medical institutions to build independently controllable medical large models and incubate various applications based on these models, providing a reference pathway for artificial intelligence development in similar institutions.

ObjectiveThis study aims to develop and validate a novel multimodal predictive model， termed criss-cross network（CCNet）-directed graph neural network（DGNN）（CGN）， for accurate assessment of pulmonary nodule progression in high-risk individuals for lung cancer， by integrating longitudinal chest computed tomography（CT） imaging with both traditional Chinese and western clinical evaluation data. MethodsA cohort of 4 432 patients with pulmonary nodules was retrospectively analyzed. A twin CCNet was employed to extract spatiotemporal representations from paired sequential CT scans. Structured clinical assessment and imaging-derived features were encoded via a multilayer perceptron， and a similarity-based alignment strategy was adopted to harmonize multimodal imaging features across temporal dimensions. Subsequently， a DGNN was constructed to integrate heterogeneous features， where nodes represented modality-specific embeddings and edges denoted inter-modal information flow. Finally， model optimization was performed using a joint loss function combining cross-entropy and cosine similarity loss， facilitating robust classification of nodule progression status. ResultsThe proposed CGN model demonstrated superior predictive performance on the held-out test set， achieving an area under the receiver operating characteristic curve（AUC） of 0.830， accuracy of 0.843， sensitivity of 0.657， specificity of 0.712， Cohen's Kappa of 0.417， and F₁ score of 0.544. Compared with unimodal baselines， the CGN model yielded a 36%-48% relative improvement in AUC. Ablation studies revealed a 2%-22% increase in AUC when compared to simplified architectures lacking key components， substantiating the efficacy of the proposed multimodal fusion strategy and modular design. Incorporation of traditional Chinese medicine （TCM）-specific symptomatology led to an additional 5% improvement in AUC， underscoring the complementary value of integrating TCM and western clinical data. Through gradient-weighted activation mapping visualization analysis， it was found that the model's attention predominantly focused on nodule regions and effectively captured dynamic associations between clinical data and imaging-derived features. ConclusionThe CGN model， by synergistically combining cross-attention encoding with directed graph-based feature integration， enables effective alignment and fusion of heterogeneous multimodal data. The incorporation of both TCM and western clinical information facilitates complementary feature enrichment， thereby enhancing predictive accuracy for pulmonary nodule progression. This approach holds significant potential for supporting intelligent risk stratification and personalized surveillance strategies in lung cancer prevention.

A method for simultaneous determination of 21 kinds of Aconitum alkaloids(ATS)in biological specimens and infused liquor using ultra-performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS)was developed.The biological samples were pretreated with methanol-acetonitrile(1∶2,V/V)for protein precipitation,while infused liquors were diluted 100-fold with acetonitrile,followed by centrifugation,and filtration by a 0.22-μm membrane.Chromatographic separation was carried out on an EC-C18 column using gradient elution with the mixture of 10 mmol/L ammonium acetate and 0.2%formic acid as mobile phase A and acetonitrile as mobile phase B.With this method,all the analytes were separated within 9.5 min.The samples were detected in positive ESI mode with dynamic multiple reaction monitoring(MRM)and quantified via external standard calibration.The results showed that the concentrations of the analytes in the range of 2-1000 ng/mL had excellent linearity(R2>0.9992)with the peak area.The developed method was successfully used for detection of 21 kinds of aconitum alkaloids,with limits of detection of 0.5-2 ng/mL,quantification limits of 2-6 ng/mL,intra/inter-day precision≤6.0%,spiked recoveries of 89.4%-100.9%,extraction recoveries of 74.2%-104.4%,and matrix effects ranging from-11.1%to 9.2%in blood/urine.The method was applied to detection of 12 samples from 4 fatal aconite poisoning cases,and all 21 kinds of ATS with total alkaloid concentrations of 0.04-4.18 μg/mL in blood and 154.96-422.83 μg/mL in medicinal liquors were detected.Tissue distribution revealed that the order of concentrations from highest to lowest is as follows:urine(157.22 μg/mL)>gastric contents(51.37 μg/mL)>kidney(21.6 μg/g)>whole blood(4.18 μg/mL)>liver(0.03 μg/g).This method showed many advantages such as simple pretreatment,low detection limits,accurate quantification,broad analyte coverage,and superior anti-interference capability in complex matrices,proving ideal for forensic and toxicological analysis of aconitum alkaloids.

Objective To develop and evaluate a diagnostic model for autoimmune liver disease(AILD)using clinical indicators.Methods A total of 181 AILD patients(AILD group)diagnosed in the Department of Gastroenterology or Rheumatology and Immunology,the First Medical Center of Chinese PLA General Hospital,from June 2019 to February 2024,133 patients with hepatitis B virus cirrhosis(HBVC)(HBVC group),and 100 healthy individuals(HC group)were included in the study cohort for retrospective analysis.Clinical data,blood routine tests,and biochemical indicators were compared among the groups.Propensity score matching was used to balance the effects of factors such as gender and age.Multivariate logistic regression analysis was applied to identify characteristic indicators for AILD.Receiver operating characteristic(ROC)curves were used to evaluate the diagnostic efficacy of single and combined indicators,and the optimal diagnostic model for AILD was constructed.The Hosmer-Lemeshow test was performed to assess the model's goodness-of-fit,while ROC analysis was employed to evaluate the predictive validity.Additionally,an independent validation cohort,including 91 AILD patients(AILD validation group),82 HBVC patients(HBVC validation group),and 40 healthy individuals(HC validation group)who visited during the same period,was used to validate the diagnostic model.False-positive and false-negative rates were calculated to assess the diagnostic efficacy and clinical utility of the model.Results The age and the proportion of male patients in AILD and HBVC groups were higher than those in HC group,and the proportion of male patients in AILD group was higher than in HBVC group,the differences were statistically significant(P＜0.05).Prior to matching,compared with HC group,HBVC group and AILD group had significantly lower levels of hemoglobin(HB),red blood cell count(RBC),white blood cell count(WBC),platelet count(PLT),and albumin(ALB)(P＜0.05),but significantly higher levels of alanine aminotransferase(ALT),aspartate aminotransferase(AST),alkaline phosphatase(ALP),gamma-glutamyl transferase(GGT),total bilirubin(TBIL),and direct bilirubin(DBIL)(P＜0.05).Compared with HBVC group,AILD group had significantly higher levels of WBC,PLT,ALB,ALP,and GGT(P＜0.05 or P＜0.001)but significantly lower levels of TBIL and DBIL(P＜0.001).After maching,compared with HC group,AILD group still had significantly lower levels of HB,RBC,WBC,PLT,and ALB,but significantly higher levels of ALT,AST,ALP,GGT,TBIL,and DBIL(P＜0.05).Compared with HBVC group,AILD group had significantly higher levels of HB,RBC,WBC,PLT,ALB,ALT,ALP,and GGT,but significantly lower levels of DBIL(P＜0.05).ROC analysis results showed that AST,GGT,ALP,and DBIL had high predictive values for differentiating AILD from HC(AUC=0.843,0.804,0.802,0.773),while PLT,WBC,GGT,and ALP had high predictive values for differentiating AILD from HBVC(AUC=0.780,0.739,0.729,0.702).For distinguishing AILD from HC,the combined model of AST,ALP,and DBIL(Model e)had an AUC of 0.887,with a sensitivity of 82.2％,and a specificity of 94.7％.For distinguishing AILD from HBVC,the combined model of ALP,GGT,and PLT(Model D)had an AUC of 0.829,with a sensitivity of 78.5％and a specificity of 80.6％.Conclusions The combined diagnostic model based on AST,ALP,and DBIL can effectively differentiate healthy individuals without liver diseases from AILD patients,while the combined diagnostic model based on PLT,ALP,and GGT can effectively distinguish HBVC from AILD patients.

Objective To investigate the pharmacological mechanism through which total flavonoids extracted from Xiaobuxin-Tang(XBXT-2)affects neural network activities in the frontal cortex by focusing on the effects of XBXT-2 on the cortical field potentials in the frontal association cortex(FrA)in mice.Methods Cortical electrodes were implanted into the skull of C57BL/6J mice targeting the FrA.After a 7-day recovery period,the mice were administered XBXT-2 intragastrically at a dose of 100 mg/kg,and 1 hour later,local field potential(LFP)in the FrA were recorded for 30 minutes.Spectral analysis of the data was performed using Neuro Explorer software.Changes in the power spectral density of α,β,θ,γ,and δ frequency bands before and after drug administration were analyzed using GraphPad Prism 10.3.Phase-amplitude coupling of θ and γ oscillations was analyzed using Matlab 2021 software.Results It was found that the oral administration of XBXT-2 significantly suppressed high-frequency γ oscillations while simultaneously enhancing θ,β,α,and δ oscillations in FrA of mice compared to the control.Furthermore,XBXT-2 treatment markedly strengthened the phase-amplitude coupling between θ and γ oscillations.Conclusion XBXT-2 possibly affects emotional and cognitive functions by modulating neural network activity in FrA and enhancing θ-γ phase-amplitude coupling in mice.

Objective To investigate the effects of active respiratory circulation technique(ACBT)combined with resistance breathing training on pulmonary function and exercise capacity in patients with acute exacerbations of chronic obstructive pulmonary disease(AECOPD).Methods A total of 60 hospitalized AECOPD patients from the Geriatrics Department of a tertiary hospital in Kunming were selected as research subjects from January to May 2024.Patients were randomly divided into two groups,with 30 patients in each group.The control group received conventional pulmonary rehabilitation nursing,and the observation group received ACBT combined with resistance breathing training.Pulmonary function indicators,modified British Medical Council(mMRC)dyspnea scores,6-minute walk test(6MWT)distances,and the COPD Assessment Test(CAT)scores were collected 4 weeks after discharge to evaluate the intervention's effectiveness.Results After the intervention,the observation group showed significant improvements in lung function,mMRC scores,6M WT distances,and CAT scores compared to pre-intervention levels,and all were superior to the control group(P＜0.05).Conclusion ACBT combined with resistance breathing training can more effectively promote sputum clearance,reduce respiratory muscle fatigue,increase exercise endurance,and improve dyspnea severity and lung function in AECOPD patients.

The development of bone in human body and the maintenance of bone mass in adulthood are regulated by a variety of biological factors. Myocyte enhancer factor 2C (MEF2C), as one of the many factors regulating bone tissue development and balance, has been shown to play a key role in bone development and metabolism. However, there is limited systematic analysis on the effects of MEF2C on bone tissue. This article reviews the role of MEF2C in bone development and metabolism. During bone development, MEF2C promotes the development of neural crest cells (NC) into craniofacial cartilage and directly promotes cartilage hypertrophy. In terms of bone metabolism, MEF2C exhibits a differentiated regulatory model across different types of osteocytes, demonstrating both promoting and other potential regulatory effects on bone formation, with its stimulating effect on osteoclasts being determined. In view of the complex roles of MEF2C in bone tissue, this paper also discusses its effects on some bone diseases, providing valuable insights for the physiological study of bone tissue and strategies for the prevention of bone diseases.
Humans ; MEF2 Transcription Factors/physiology* ; Bone and Bones/metabolism* ; Animals ; Bone Development/physiology* ; Osteogenesis/physiology* ; Myogenic Regulatory Factors/physiology*

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

This study explores the therapeutic differences and mechanisms of salt-processed Phellodendri Chinensis Cortex in improving insulin resistance(IR) based on network pharmacology, molecular docking, and cellular experiments. The components and intersection targets of Phellodendri Chinensis Cortex in improving IR were collected from databases, and a "drug-component-target-disease" network and protein-protein interaction(PPI) network were constructed to screen core components and targets. A total of 29 active components and 240 intersection targets were identified, of which 13 were core targets. Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analyses were used to identify key signaling pathways, and molecular docking was performed to validate the binding activity between core components and targets. An IR model in HepG2 cells was induced using insulin combined with high glucose, and the effects of Phellodendri Chinensis Cortex before and after salt-processing on cell glucose consumption were evaluated. The expression of proteins related to the mitogen-activated protein kinase(MAPK) and phosphatidylinositol 3-kinase(PI3K)-protein kinase B(AKT) signaling pathways was detected by Western blot. The cellular experimental results showed that, compared with the model group, glucose consumption in the drug-treated groups was significantly increased(P<0.01), the phosphorylation level of extracellular regulated protein kinase(ERK) was decreased(P<0.05), the phosphorylation levels of PI3K and AKT were increased, and the expression of glucose transporter 4(GLUT4) was also upregulated(P<0.05). Furthermore, the effect of salt-processed Phellodendri Chinensis Cortex was better than that of raw Phellodendri Chinensis Cortex. The study demonstrates that Phellodendri Chinensis Cortex, both before and after salt-processing, improves IR by regulating the expression of related proteins in the MAPK and PI3K-AKT signaling pathways, with enhanced effects after salt-processing.
Humans ; Network Pharmacology ; Phellodendron/chemistry* ; Insulin Resistance ; Drugs, Chinese Herbal/chemistry* ; Hep G2 Cells ; Signal Transduction/drug effects* ; Molecular Docking Simulation ; Protein Interaction Maps/drug effects* ; Proto-Oncogene Proteins c-akt/genetics* ; Phosphatidylinositol 3-Kinases/genetics* ; Glucose/metabolism*

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