Objective To explore the recognition capabilities of electronic nose combined with machine learning in identifying the breath odor map of benign and malignant pulmonary nodules and Traditional Chinese Medicine (TCM) syndrome elements. Methods The study design was a single-center observational study. General data and four diagnostic information were collected from 108 patients with pulmonary nodules admitted to the Department of Cardiothoracic Surgery of Hospital of Chengdu University of TCM from April 2023 to March 2024. The patients' TCM disease location and nature distribution characteristics were analyzed using the syndrome differentiation method. The Cyranose 320 electronic nose was used to collect the odor profiles of oral exhalation, and five machine learning algorithms including random forest (RF), K-nearest neighbor (KNN), logistic regression (LR), support vector machine (SVM), and eXtreme gradient boosting (XGBoost) were employed to identify the exhaled breath profiles of benign and malignant pulmonary nodules and different TCM syndromes. Results (1) The common disease locations in pulmonary nodules were ranked in descending order as liver, lung, and kidney; the common disease natures were ranked in descending order as Yin deficiency, phlegm, dampness, Qi stagnation, and blood deficiency. (2) The electronic nose combined with the RF algorithm had the best efficacy in identifying the exhaled breath profiles of benign and malignant pulmonary nodules, with an AUC of 0.91, accuracy of 86.36%, specificity of 75.00%, and sensitivity of 92.85%. (3) The electronic nose combined with RF, LR, or XGBoost algorithms could effectively identify the different TCM disease locations and natures of pulmonary nodules, with classification accuracy, specificity, and sensitivity generally exceeding 80.00%.Conclusion Electronic nose combined with machine learning not only has the potential capabilities to differentiate the benign and malignant pulmonary nodules, but also provides new technologies and methods for the objective diagnosis of TCM syndromes in pulmonary nodules.

BACKGROUND:In recent years,with the rapid development of biomedicine,the study of brain aging and exosomes has attracted more and more attention,but there is no bibliometrics analysis in this field. OBJECTIVE:To objectively analyze domestic and foreign literature on brain aging and exosomes in the past 15 years,to summarize the research status,hot spots,and development trends in this field. METHODS:Using the core database of Web of Science as a search platform,we downloaded the literature on brain aging and exosomes published from the establishment of the database to December 28,2022,and analyzed the data from the aspects of country or region,institution,author,keywords,and co-cited literature using CiteSpace 6.1.R6 visualization software. RESULTS AND CONCLUSION:A total of 1 045 research articles were included,and the number of publications on brain aging and exosomes research both domestically and internationally was showing an increasing trend year by year.The United States ranked first with 429 papers,and China ranked second with 277 papers.Louisiana State University ranked first with 16 articles.Professor Lukiw Walter J from Louisiana State University in the United States was the author with the highest number of publications,and Professor Bartel DP from the Massachusetts Institute of Technology was the author with the most citations.The most prolific Journal was the International Journal of Molecular Sciences.Alzheimer's disease,microRNA,gene expression,extracellular vesicles,exosomes,oxidative stress,and biomarkers are the most relevant terms.According to the research on hot topics,biomarkers have become a new research hotspot.The above results indicate that the research on brain aging and exosomes has gradually increased in the past 15 years.The research direction has gradually shifted from the initial exploration of the expression of miRNAs in central nervous system diseases related to brain aging to the search for biomarkers that can identify and diagnose neurodegenerative diseases.The study of exocrine miRNAs to protect central nervous system from damage has emerged as promising therapeutic strategy.

ObjectiveTo unveil the mechanism of Jianpi Huogu prescription （JPHGP） in ameliorating the dyslipidemia of steroid-induced osteonecrosis of the femur head （SONFH） by oxylipidomics combined with transcriptomics. MethodsSixty SD rats were assigned into normal， model， low-， medium-， and high-dose （2.5， 5， 10 g·kg^-1， respectively） JPHGP， and Jiangushengwan （1.53 g·kg^-1） groups. Lipopolysaccharide was injected into the tail vein at a dose of 20 μg·kg^-1 on days 1 and 2， and methylprednisolone sodium succinate was injected at a dose of 40 mg·kg^-1 into the buttock muscle on days 3 to 5. The normal group received an equal volume of normal saline. Drug administration by gavage began 4 weeks after the last injection， and samples were taken after administration for 8 weeks. Hematoxylin-eosin staining was conducted to reveal the histopathological changes of the femoral head， and the number of adipocytes， the rate of empty bone lacunae， and the trabecular area were calculated. Micro-computed tomography was used for revealing the histological and histomorphometrical changes of the femoral head. Enzyme-linked immunosorbent assay was employed to measure the serum levels of triglyceride （TG）， total cholesterol （TC）， low-density lipoprotein （LDL）， high-density lipoprotein （HDL）， apolipoprotein A1 （ApoA1）， and apolipoprotein B （ApoB）. At the same time， the femoral head was collected for oxylipidomic and transcriptomic detection. The differential metabolites and differential genes were enriched and analyzed， and the target genes regulating lipid metabolism were predicted. The predicted target proteins were further verified by molecular docking， immunohistochemistry， and Western blot. ResultsCompared with the normal group， the model group showcased thinning of the femoral head， trabecular fracture， karyopyknosis， subchondral cystic degeneration， increases in the number of adipocytes and the rate of empty bone lacunae （P<0.01）， a reduction in the trabecular area （P<0.01）， decreases in BMD， Tb.Th， Tb.N， and BV/TV， and increases in Tb.Sp and BS/BV （P<0.01）. Compared with the model group， the JPHGP groups showed no obvious thinning of the femoral head or subchondroidal cystic degeneration. The high- and medium-dose JPHGP groups presented declines in the number of adipocytes and the rate of empty bone lacunae， an increase in the trabecular area （P<0.05， P<0.01）， rises in BMD， Tb.Th， Tb.N， and BV/TV， and decreases in Tb.Sp and BS/BV （P<0.05， P<0.01）. Compared with the normal group， the model group showcased raised serum levels of TG， TC， LDL， and ApoB and lowered serum levels of HDL and ApoA1 （P<0.01）. Compared with the model group， the JPHGP groups had lowered serum levels of TG， TC， LDL， and ApoB （P<0.05， P<0.01） and a risen serum level of ApoA1 （P<0.05， P<0.01）. Moreover， the serum level of HDL in the high-dose JPHGP group increased （P<0.01）. A total of 19 different metabolites of disease set and drug set were screened out by oxylipidomics of the femoral head， and 119 core genes with restored expression were detected by transcriptomics. The enriched pathways were mainly concentrated in inflammation， lipids， apoptosis， and osteoclast differentiation. Molecular docking， immunohistochemistry， and Western blot results showed that compared with the normal group， the model group displayed increased content of 5-lipoxygenase （5-LO） and peroxisome proliferator-activated receptor γ （PPARγ） in the femoral head （P<0.01）. Compared with the model group， medium- and high-dose JPHGP reduced the content of 5-LO and PPARγ （P<0.05， P<0.01）. ConclusionJPHGP can restore the levels of oxidized lipid metabolites by regulating the 5-LO-PPARγ axis to treat SONFH in rats. Relevant studies provide experimental evidence for the efficacy mechanism of JPHGP in the treatment of SONFH.

ObjectiveTo unveil the mechanism of Jianpi Huogu prescription （JPHGP） in ameliorating the dyslipidemia of steroid-induced osteonecrosis of the femur head （SONFH） by oxylipidomics combined with transcriptomics. MethodsSixty SD rats were assigned into normal， model， low-， medium-， and high-dose （2.5， 5， 10 g·kg^-1， respectively） JPHGP， and Jiangushengwan （1.53 g·kg^-1） groups. Lipopolysaccharide was injected into the tail vein at a dose of 20 μg·kg^-1 on days 1 and 2， and methylprednisolone sodium succinate was injected at a dose of 40 mg·kg^-1 into the buttock muscle on days 3 to 5. The normal group received an equal volume of normal saline. Drug administration by gavage began 4 weeks after the last injection， and samples were taken after administration for 8 weeks. Hematoxylin-eosin staining was conducted to reveal the histopathological changes of the femoral head， and the number of adipocytes， the rate of empty bone lacunae， and the trabecular area were calculated. Micro-computed tomography was used for revealing the histological and histomorphometrical changes of the femoral head. Enzyme-linked immunosorbent assay was employed to measure the serum levels of triglyceride （TG）， total cholesterol （TC）， low-density lipoprotein （LDL）， high-density lipoprotein （HDL）， apolipoprotein A1 （ApoA1）， and apolipoprotein B （ApoB）. At the same time， the femoral head was collected for oxylipidomic and transcriptomic detection. The differential metabolites and differential genes were enriched and analyzed， and the target genes regulating lipid metabolism were predicted. The predicted target proteins were further verified by molecular docking， immunohistochemistry， and Western blot. ResultsCompared with the normal group， the model group showcased thinning of the femoral head， trabecular fracture， karyopyknosis， subchondral cystic degeneration， increases in the number of adipocytes and the rate of empty bone lacunae （P<0.01）， a reduction in the trabecular area （P<0.01）， decreases in BMD， Tb.Th， Tb.N， and BV/TV， and increases in Tb.Sp and BS/BV （P<0.01）. Compared with the model group， the JPHGP groups showed no obvious thinning of the femoral head or subchondroidal cystic degeneration. The high- and medium-dose JPHGP groups presented declines in the number of adipocytes and the rate of empty bone lacunae， an increase in the trabecular area （P<0.05， P<0.01）， rises in BMD， Tb.Th， Tb.N， and BV/TV， and decreases in Tb.Sp and BS/BV （P<0.05， P<0.01）. Compared with the normal group， the model group showcased raised serum levels of TG， TC， LDL， and ApoB and lowered serum levels of HDL and ApoA1 （P<0.01）. Compared with the model group， the JPHGP groups had lowered serum levels of TG， TC， LDL， and ApoB （P<0.05， P<0.01） and a risen serum level of ApoA1 （P<0.05， P<0.01）. Moreover， the serum level of HDL in the high-dose JPHGP group increased （P<0.01）. A total of 19 different metabolites of disease set and drug set were screened out by oxylipidomics of the femoral head， and 119 core genes with restored expression were detected by transcriptomics. The enriched pathways were mainly concentrated in inflammation， lipids， apoptosis， and osteoclast differentiation. Molecular docking， immunohistochemistry， and Western blot results showed that compared with the normal group， the model group displayed increased content of 5-lipoxygenase （5-LO） and peroxisome proliferator-activated receptor γ （PPARγ） in the femoral head （P<0.01）. Compared with the model group， medium- and high-dose JPHGP reduced the content of 5-LO and PPARγ （P<0.05， P<0.01）. ConclusionJPHGP can restore the levels of oxidized lipid metabolites by regulating the 5-LO-PPARγ axis to treat SONFH in rats. Relevant studies provide experimental evidence for the efficacy mechanism of JPHGP in the treatment of SONFH.

Objective To analyze the distribution characteristics of the single nucleotide polymorphism (SNP) site rs76206423 in the promoter region of the interleukin-2 receptor (IL-2R) β gene among Han males in a high radiation background area (HBRA) in Yangjiang City. Methods A total of 48 male participants from Tangkou Town, Yangxi County, Yangjiang City (HBRA group), and 51 male participants from Hengpo Town, Enping City (control group) were selected as the research subjects using the random number table method. Peripheral venous blood samples of participants from both groups were collected, and genomic DNA was extracted. The genotyping and allele frequency distribution of the rs76206423 (A/G) site in the IL-2R β promoter region was detected among the participants in both groups using the SNP detection method. The difference of allele frequencies between population in HBRA group and five area of East Asia, South Asia, Africa, Europe, and the Americas published in the Human Genome Project database from National Center for Biotechnology Information were analyzed. Results The allele frequencies of rs76206423 of population in both groups conformed to Hardy-Weinberg equilibrium (P>0.05). In the HBRA group, the AA genotype was predominant (64.6%), while the AG genotype was the most common in the control group (51.0%), with a significant difference (P<0.05). Population in both groups showed a predominance of the variant allele A (78.1% and 72.5%, respectively), with no significant difference (P>0.05). The frequency of the G allele of rs76206423 in the population in HBRA group was higher than those in South Asian, African, European, and American populations (all P<0.01), but showed no significant difference compared with East Asian populations (P>0.05). Conclusion In the Han male population from the HBRA in Yangjiang City, the rs76206423 site in the IL-2R β gene promoter region is predominantly composed of the wild-type A allele and AA genotype, indicating genetic stability and a relatively high degree of variation at this locus.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

The immunomodulatory， repair， and regeneration-promoting functions of mesenchymal stem cells make them one of the potential treatment methods for liver diseases. At present， viral and non-viral delivery methods have been developed to genetically modify mesenchymal stem cells， and gene modification can promote the survival， homing， and cytokine secretion of mesenchymal stem cells， thereby enhancing the ability of mesenchymal stem cells to treat liver diseases. This article mainly summarizes the research advances in gene-modified mesenchymal stem cells in the treatment of liver diseases， in order to provide new insights and strategies for the clinical treatment of liver diseases.

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.