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.

Clinical practice guidelines represent the best recommendations for patient care. They are developed through systematically reviewing currently available clinical evidence and weighing the relative benefits and risks of various interventions. However, clinical practice guidelines have to go through a long translation cycle from development and revision to clinical promotion and application, facing problems such as scattered distribution, high duplication rate, and low actual utilization. At present, the clinical practice guideline information platform can directly or indirectly solve the problems related to the lengthy revision cycles, decentralized dissemination and limited application of clinical practice guidelines. Therefore, this paper systematically examines different types of clinical practice guideline information platforms and investigates their corresponding challenges and emerging trends in platform design, data integration, and practical implementation, with the aim of clarifying the current status of this field and providing valuable reference for future research on clinical practice guideline information platforms.

ObjectiveTo investigate the preventive effect and mechanism of Dendrobium officinale （DO） on non-alcoholic fatty liver disease （NAFLD） by network pharmacology and animal experiments. MethodsDO components in blood after administration were identified and analyzed using ultra-performance liquid chromatography-quadrupole-electrostatic field orbitrap high-resolution mass spectrometry （UPLC-QE-HF-MS/MS）. Network pharmacology and molecular docking methods were employed to obtain active ingredients and potential targets of DO for NAFLD control. High-fat feeds were used to replicate the NAFLD rat model. Biochemical kits were used for detecting the expression levels of blood lipids， hepatic lipids， and liver functions of rats. Hematoxylin-eosin （HE） staining and oil red O staining were employed to observe pathological changes in rat liver， and real-time fluorescence quantitative PCR （Real-time PCR） assay was performed to validate potential targets obtained from the network pharmacology analysis. ResultsA total of 13 DO components were identified in blood， including berberine， dihydrosanguinarine， and oxypeucedanin. A total of 14 potential targets were screened through network pharmacology， including Forkhead box protein O1 （FoxO1）， epidermal growth factor receptor （EGFR）， and insulin-like growth factor 1 （IGF-1R）， involving pathways such as the advanced glycation end product （AGE）/receptor for AGE （RAGE） signaling pathway， blood lipids and atherosclerosis， insulin resistance， and FoxO signaling. The results of animal experiments showed that the NAFLD rat model was successfully replicated. After the preventive treatment with DO for NAFLD rats， the indexes of blood lipids， hepatic lipids， and liver function were normalized； lipid deposition and lesions in the liver were significantly improved； the expression level of FoxO1 mRNA in the liver was significantly reduced （P<0.05）， and the mRNA expression levels of phosphatidylinositide 3-kinases （PI3K）， protein kinase B （Akt）， EGFR， and IGF-1R were significantly increased （P<0.05）. ConclusionDO has a preventive effect on NAFLD rats， and the mechanism of action may be related to the modulation of IGF1R and EGFR targets and activation of the PI3K/Akt/FoxO1 signaling pathway.

ObjectiveIn the realm of forensic science, dust is a valuable type of trace evidence with immense potential for intricate investigations. With the development of DNA sequencing technologies, there is a heightened interest among researchers in unraveling the complex tapestry of microbial communities found within dust samples. Furthermore, striking disparities in the microbial community composition have been noted among dust samples from diverse geographical regions, heralding new possibilities for geographical inference based on microbial DNA analysis. The pivotal role of microbial community data from dust in geographical inference is significant, underscoring its critical importance within the field of forensic science. This study aims to delve deeply into the nuances of fungal community composition across the urban landscapes of Beijing, Fuzhou, Kunming, and Urumqi in China. It evaluates the accuracy of biogeographic inference facilitated by the internal transcribed spacer 2 (ITS2) fungal sequencing while concurrently laying a robust foundation for the operational integration of environmental DNA into geographical inference mechanisms. MethodsITS2 region of the fungal genomes was amplified using universal primers known as 5.8S-Fun/ITS4-Fun, and the resulting DNA fragments were sequenced on the Illumina MiSeq FGx platform. Non-metric multidimensional scaling analysis (NMDS) was employed to visually represent the differences between samples, while analysis of similarities (ANOSIM) and permutational multivariate analysis of variance (PERMANOVA) were utilized to statistically evaluate the dissimilarities in community composition across samples. Furthermore, using Linear Discriminant Analysis Effect Size (LEfSe) analysis to identify and filter out species that exhibit significant differences between various cities. In addition, we leveraged SourceTracker to predict the geographic origins of the dust samples. ResultsAmong the four cities of Beijing, Fuzhou, Kunming and Urumqi, Beijing has the highest species richness. The results of species annotation showed that there were significant differences in the species composition and relative abundance of fungal communities in the four cities. NMDS analysis revealed distinct clustering patterns of samples based on their biogeographic origins in multidimensional space. Samples from the same city exhibited clear clustering, while samples from different cities showed separation along the first axis. The results from ANOSIM and PERMANOVA confirmed the significant differences in fungal community composition between the four cities, with the most pronounced distinctions observed between Fuzhou and Urumqi. Notably, the biogeographic origins of all known dust samples were successfully predicted. ConclusionSignificant differences are observed in the fungal species composition and relative abundance among the cities of Beijing, Fuzhou, Kunming, and Urumqi. Employing fungal ITS2 sequencing on dust samples from these urban areas enables accurate inference of biogeographical locations. The high feasibility of utilizing fungal community data in dust for biogeographical inferences holds particular promise in the field of forensic science.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

Hepatic encephalopathy （HE） is a common complication of severe liver disease in the end stage， and it is urgently needed to improve the rate of effective treatment and clarify the pathogenesis of HE. The liver is a crucial hub for immune regulation， and disruption of immune homeostasis is a key factor in the pathological mechanisms of HE. As the main metabolites of intestinal flora， short-chain fatty acids （SCFAs） play a vital role in the biological processes of both innate and adaptive immunity and can regulate the proliferation and differentiation of immune cells maintain the homeostasis of intestinal microenvironment and the integrity of barrier function. Studies have shown that SCFAs participate in bidirectional and dynamic interactions with the liver-gut-brain axis through immunomodulatory pathways， thereby playing an important role in the diagnosis， treatment， and prognostic evaluation of HE. Starting from the immunoregulatory effect of SCFAs， this article summarizes and analyzes the crosstalk relationship between SCFAs and the liver-gut-brain axis and the significance of SCFAs in the diagnosis and treatment of HE， in order to provide new ideas for optimizing clinical prevention and treatment strategies.

OBJECTIVE: To explore the mechanism of electroacupuncture (EA) in promoting recovery of the facial function with the involvement of autophagy, glial cell line-derived neurotrophic factor (GDNF), and phosphatidylinositol-3-kinase (PI3K)/mammalian target of rapamycin (mTOR) signaling pathway. METHODS: Seventy-two male Sprague-Dawley rats were randomly allocated into the control, sham-operated, facial nerve injury (FNI), EA, EA+3-methyladenine (3-MA), and EA+GDNF antagonist groups using a random number table, with 12 rats in each group. An FNI rat model was established with facial nerve crushing method. EA intervention was conducted at Dicang (ST 4), Jiache (ST 6), Yifeng (SJ 17), and Hegu (LI 4) acupoints for 2 weeks. The Simone's 10-Point Scale was utilized to monitor the recovery of facial function. The histopathological evaluation of facial nerves was performed using hematoxylin-eosin (HE) staining. The levels of Beclin-1, light chain 3 (LC3), and P62 were detected by immunohistochemistry (IHC), immunofluorescence, and reverse transcription-polymerase chain reaction, respectively. Additionally, IHC was also used to detect the levels of GDNF, Rai, PI3K, and mTOR. RESULTS: The facial functional scores were significantly increased in the EA group than the FNI group (P<0.05 or P<0.01). HE staining showed nerve axons and myelin sheaths, which were destroyed immediately after the injury, were recovered with EA treatment. The expressions of Beclin-1 and LC3 were significantly elevated and the expression of P62 was markedly reduced in FNI rats (P<0.01); however, EA treatment reversed these abnormal changes (P<0.01). Meanwhile, EA stimulation significantly increased the levels of GDNF, Rai, PI3K, and mTOR (P<0.01). After exogenous administration with autophagy inhibitor 3-MA or GDNF antagonist, the repair effect of EA on facial function was attenuated (P<0.05 or P<0.01). CONCLUSIONS EA could promote the recovery of facial function and repair the facial nerve damages in a rat model of FNI. EA may exert this neuroreparative effect through mediating the release of GDNF, activating the PI3K/mTOR signaling pathway, and further regulating the autophagy of facial nerves.
Rats ; Male ; Animals ; Rats, Sprague-Dawley ; Electroacupuncture ; Phosphatidylinositol 3-Kinase/metabolism* ; Facial Nerve Injuries/therapy* ; Phosphatidylinositol 3-Kinases/metabolism* ; Beclin-1 ; Glial Cell Line-Derived Neurotrophic Factor ; Signal Transduction ; TOR Serine-Threonine Kinases/metabolism* ; Autophagy ; Mammals/metabolism*

Qualitative analysis of the ingredients absorbed into blood and their metabolites of Xihuang pill (XHP) were conducted using high-performance liquid chromatography quadrupole time-of-flight mass spectrometry (HPLC-Q-TOF-MS/MS) technology. Network pharmacology was used to explore the potential anticancer mechanisms of the ingredients against glioma, and their specific mechanisms were validated through molecular docking and experimental verification. SD rats were intragastrically administered with XHP, and rat serum samples were collected. Ingredients absorbed into blood and their metabolites were identified based on the retention time of chromatographic peaks, accurate molecular mass, characteristic fragment ions, and comparisons with reference substances and literature data. PharmMapper and SwissTarget Prediction databases were used to obtain the targets of the XHP-medicated serum, while GeneCards, OMIM, PharmGKB, TTD, and DrugBank databases were used to obtain glioma disease targets. The "component-target" network relationship diagram was constructed using Cytoscape 3.9.1 software. The protein-protein interaction (PPI) network diagram was constructed using the STRING database, and the targets were analyzed using GO and KEGG analyses. Molecular docking was used to verify the binding ability of core targets with their corresponding compounds in XHP-medicated serum. The potential mechanism of the anti-glioma effect of 11-keto-β-boswellic acid (KBA), a representative component of XHP-medicated serum, was verified using CCK-8 and Western blot assays. A total of 40 compounds were identified in the XHP-medicated serum, including 28 prototype components and 12 metabolites. The network pharmacology results showed that elemonic acid, 3-acetyl-β-boswellic acid, KBA, α-boswellic acid, and other 5 compounds might be the active ingredients of XHP-medicated serum in the treatment of glioma. Glutathione reductase (GSR), glucose-6-phosphate dehydrogenase (G6PD), ATP-citrate lyase (ACLY), aldo-keto reductase family 1 member B1 (AKR1B1) and glutaredoxin (GLRX) were identified as key targets, involving pathways such as glutathione metabolism and the pentose phosphate pathway. Further cell experiments showed that KBA significantly inhibited the proliferation of T98G cells with an IC₅₀ of 30.96 μmol·L^-1, and KBA (30 μmol·L^-1) significantly downregulated the protein expression levels of GSR in T98G cells. In summary, XHP-medicated serum may exert its anti-glioma effect by regulating GSR and G6PD-targeted pathways involved in glutathione metabolism. These results provide valuable evidence for further investigating the mechanism of XHP in treating glioma. The animal welfare and experimental procedures were approved by the Ethical Committee of Laboratory Animals at Nanjing University of Chinese Medicine (approval No. ACU221001).

Objective To investigate the clinical efficacy of modified Fuzheng Yiliu Decoction(composed of Astragali Radix,Codonopsis Radix,Ligustri Lucidi Fructus,Hedyotis Diffusae Herba,Moutan Cortex,Visci Herba,etc.)combined with XELOX regimen(Oxaliplatin plus Capecitabine)for the treatment of postoperative patients with advanced gastric cancer of qi and yin deficiency type.Methods A total of 80 postoperative patients with advanced gastric cancer of qi and yin deficiency type were randomly divided into the Chinese medicine group and the control group,with 40 cases in each group.Both groups received chemotherapy with XELOX regimen,while the Chinese medicine group was given modified Fuzheng Yiliu Decoction.Three weeks constituted a course of treatment,the medication of Chinese medicine decoction lasted for two weeks or more in each course of treatment,and a total of 8 courses of treatment were performed.The incidence of adverse reactions during chemotherapy was monitored and changes in serum tumor markers of serum carcinoembryonic antigen(CEA),carbohydrate antigen 199(CA199)and alpha-fetoprotein(AFP)were observed in the two groups before and after treatment.Moreover,the patients'quality of life was assessed by the scores of Karnofsky's Performance Status(KPS)and World Health Organization Quality of Life Measurement Scale(WHOQOL-100).Long-term follow-up was carried out for the evaluation of the prognostic indicators such as overall survival and one-year and 2-year overall survival rates.Results(1)Patients in the two groups were all followed up,and the median follow-up time was 27 months(95%CI:23.59-27.86).(2)After treatment,the levels of serum CEA and AFP in the Chinese medicine group were significantly lower than those before treatment(P＜0.05 or P＜0.01),while serum CA199 tended to decrease compared with those before treatment,but the difference was not statistically significant(P＞0.05);in the control group,the levels of serum CEA,CA199,and AFP were not significantly decreased after treatment(P＞0.05).The intergroup comparison showed that the decrease of serum CEA,CA199 and AFP levels in the Chinese medicine group was significantly superior to that in the control group(P＜0.05 or P＜0.01).(3)The adverse reactions during chemotherapy in the two groups mainly involved bone marrow suppression,gastrointestinal reactions and liver function abnormalities,etc.The incidences of all adverse reactions in the Chinese medicine group tended to be lower than those in the control group,but the differences were not statistically significant(P＞0.05).(4)After treatment,the KPS scores of patients in both groups were improved compared with those before treatment(P＜0.01),and the improvement in the Chinese medicine group was significantly superior to that in the control group(P＜0.01).(5)After treatment,the scores of the four dimensions of WHOQOL-100 such as health status,mobility,life feelings,and other activities of daily life in the Chinese medicine group were significantly improved compared with the pre-treatment(P＜0.05),whereas there was no significant improvement in the control group(P＞0.05).The intergroup comparison showed that the improvement of the scores of each dimension of the WHOQOL-100 in the Chinese medicine group was significantly superior to that in the control group(P＜0.05 or P＜0.01).(6)The median survival in the Chinese medicine group was 29.0 months(95%CI:25.95-31.70)and that in the control group was 22.0 months(95%CI:19.67-25.58),indicating that the median survival was significantly prolonged in Chinese medicine group(P＜0.01).The one-year and 2-year postoperative survival rates were 97.5%and 77.5%in the Chinese medicine group and 92.5%and 47.5%in the control group,respectively.The intergroup comparison showed that the one-year and 2-year postoperative survival rates in the Chinese medicine group were higher than those in the control group(P＜0.01).Conclusion Modified Fuzheng Yiliu Decoction can effectively alleviate the adverse reactions during adjuvant chemotherapy for postoperative patients with advanced gastric cancer of qi and yin deficiency type,improve the quality of life of patients,and prolong the survival time of patients.

With the development of digital technology,computer-aided design and manufacturing(CAD/CAM)combined with 3D printing technology is increasingly used in clinical and teaching applications in dentistry.In clinical dentistry,3D printing technology has been widely used in oral and maxillofacial surgery,orthodontics and implantation.Traditional oral laboratory teaching usually uses extracted teeth,resin teeth or various dental models,while 3D printing of oral models can achieve standardized,mass-produced and close-to-real clinical application,which better meets the needs of clinical pre-practice teaching.This article reviews the latest educa-tional applications of 3D printing of dental models in teaching of oral restoration,dental pulp-cavity,oral and maxillofacial surgery,and summarizes the selection of different printing processes and printing materials,aiming to apply the research strategy of 3D printing technology in pre-clinical teaching in dentistry.Finally,the article explores the trends and urgent problems that need to be solved in the development of 3D printed dental models.