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.

Objective To analyze the differences in distribution of traditional Chinese medicine (TCM) syndrome elements and salivary microbiota between the individuals with pulmonary nodules and those without, and to explore the potential correlation between the distribution of TCM syndrome elements and salivary microbiota in patients with pulmonary nodules. Methods We retrospectively recruited 173 patients with pulmonary nodules (PN) and 40 healthy controls (HC). The four diagnostic information was collected from all participants, and syndrome differentiation method was used to analyze the distribution of TCM syndrome elements in both groups. Saliva samples were obtained from the subjects for 16S rRNA high-throughput sequencing to obtain differential microbiota and to explore the correlation between TCM syndrome elements and salivary microbiota in the evolution of the pulmonary nodule disease. Results The study found that in the PN group, the primary TCM syndrome elements related to disease location were the lung and liver, and the primary TCM syndrome elements related to disease nature were yin deficiency and phlegm. In the HC group, the primary TCM syndrome elements related to disease location were the lung and spleen, and the primary TCM syndrome elements related to disease nature were dampness and qi deficiency. There were differences between the two groups in the distribution of TCM syndrome elements related to disease location (lung, liver, kidney, exterior, heart) and disease nature (yin deficiency, phlegm, qi stagnation, qi deficiency, dampness, blood deficiency, heat, blood stasis) (P<0.05). The species abundance of the salivary microbiota was higher in the PN group than that in the HC group (P<0.05), and there was significant difference in community composition between the two groups (P<0.05). Correlation analysis using multiple methods, including Mantel test network heatmap analysis and Spearman correlation analysis and so on, the results showed that in the PN group, Prevotella and Porphyromonas were positively correlated with disease location in the lung, and Porphyromonas and Granulicatella were positively correlated with disease nature in yin deficiency (P<0.05). Conclusion The study concludes that there are notable differences in the distribution of TCM syndrome elements and the species abundance and composition of salivary microbiota between the patients with pulmonary nodules and the healthy individuals. The distinct external syndrome manifestations in patients with pulmonary nodules, compared to healthy individuals, may be a cascade event triggered by changes in the salivary microbiota. The dual correlation of Porphyromonas with both disease location and nature suggests that changes in its abundance may serve as an objective indicator for the improvement of symptoms in patients with yin deficiency-type pulmonary nodules.

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.

Objective To analyze the trend of global cellulitis disease burden from 1990 to 2019, and to provide a theoretical basis for the prevention and control of cellulitis disease. Methods The Global Burden of Disease 2021 (GBD2021) data were collected, and data on the incidence, mortality, and disability-adjusted life year (DALY) of cellulitis were analyzed for each country worldwide. The estimated annual percentage change (EAPC) and age-standardized rate (ASR) were used to estimate the trend change of cellulitis from 1990 to 2021. Results The global burden of cellulitis increased significantly in 2021, with 55.96 million cases, 28.9 million deaths and 876.1 million DALYs, respectively. Incidence and mortality rates were generally higher in males than in females. The incidence and DALYs were higher in high SDI regions, with the highest burden observed in South Asia. In contrast, East Asia exhibited the lowest burden and demonstrated a declining trend. There were significant differences between countries, with India having the highest prevalence, the United States having the highest incidence, and Bahrain having the fastest growing rate.In 2021, China had the lowest age-standardised incidence of cellulitis in the world and the fastest declining age-standardised incidence and age-standardised DALYs. Conclusion The global disease burden of cellulitis is increasing from 1990-2021, and cellulitis remains an an important global public health problem. Targeted preventive meausres should be taken in areas with different economical levels. Men, middle-aged and elderly people, and newborns are the key groups in need of attention and health education.

Hydrogen sulfide,as a third gas signal molecule and neurotransmitter,can play a neuroprotective role by anti-oxidative stress,anti-inflammatory response,metabolic inhibition and other mechanisms.It is of great significance for the occurrence and development of neurodegenerative diseases including Alzheimer's disease(AD)and Parkinson's disease(PD)mediated by neuroinflammation.This article reviews the research progress of hydrogen sulfide and neuroinflammation and its mediated neurodegenerative diseases,so as to provide new ideas for the treatment of neurodegenerative diseases.

Objective To observe the impact of cold circulation liquid temperature on ablation focus morphology of microwave ablation(MWA)for in vitro porcine liver tissue.Methods Twenty in vitro fresh porcine liver blocks were randomly divided into ice water circulation group(group A)and normal temperature circulation group(group B),respectively.Ten target ablations in each subgroups in group A and group B,i.e.A1 and B1(50 W,1 min),A2 and B2(50 W,5 min),A3 and B3(60 W,1 min),A4 and B4(60 W,5 min),A5 and B5(70 W,1 min)as well as A6 and B6(70 W,5 min)subgroups were performed using different ablation power(50,60,70 W)and ablation time(1,5 min),respectively.Then the morphology indexes of ablation foci,including longitudinal diameter(LD),transverse diameter(TD),roundness index(RI)and volume(V)were compared between subgroups in group A and B,also among subgroups within group A and B.Results Under the same ablation power and time,LD of ablation foci in subgroups of group A were all smaller than those of group B(all P＜0.05).Significant differences of RI of ablation foci were found between A1 and B1,A2 and B2,A4 and B4,A5 and B5 as well as A6 and B6 subgroups(all P＜0.05),but not between A3 and B3 subgroups(P＞0.05).However,the main effect of cold circulation liquid temperature on ablation focus TD(F=1.125)nor V(F=3.332)was not significant(both P≥0.05).Under the same cold circulation liquid temperature,significant differences of the morphology indexes of ablation foci were detected between A1 and A2,A3 and A4 as well as A5 and A6 subgroups,also between corresponding subgroups in group B(all P＜0.05).Conclusion During MWA for in vitro porcine liver tissue under constant ablation power and time,taken ice water as the cold circulation liquid was benefit to ablation focus shaped spherically.With the extension of ablation time,the larger the ablation focus,the higher the RI.

Objective:To explore the clinical manifestations,pathological features,immunophenotype,as well as diagnosis,treatment and prognosis of patients with CD4-CD56+blastic plasmacytoid dendritic cell neoplasm(BPDCN),in order to further understand the rare disease.Methods:The clinical data,laboratory examinations and treatment regimens of two patients with CD4-CD56+BPDCN in the First Affiliated Hospital of Wannan Medical College were retrospectively analyzed.Results:The two patients were both elderly males with tumor involved in skin,bone marrow,lymph nodes,etc.Immunohistochemical results of skin lesions showed that both CD56 and CD123 were positive,while CD4,CD34,TdT,CD3,CD20,MPO and EBER were negative.Flow cytometry of bone marrow demonstrated that CD56,CD123,and CD304 were all positive,while specific immune markers of myeloid and lymphoid were negative.Two patients were initially very sensitive to acute lymphoblastic leukemia or lymphomatoid chemotherapy regimens,but prone to rapid relapse.The overall survival of both patients was 36 months and 4 months,respectively.Conclusion:CD4-CD56+BPDCN is very rare and easily misdiagnosed as other hematological tumors with poor prognosis.Acute lymphoblastic leukemia or lymphomatoid therapy should be used first to improve the poor prognosis.

Objective:To investigate the role of levofloxacin combined with recombinant human granulocyte colony-stimulating factor(G-CSF)or only G-CSF supportive therapy in preventing infection in autologous hematopoietic stem cell transplantation(ASCT),and to analyze the length of hospital stay,hospitalization cost and post-transplant survival of the patients.Methods:A retrospective analysis was performed in the patients with hematological malignancies who accepted ASCT at our hospital from January 2012 to July 2022,the febrile neutropenia,the incidence of bacterial infection and the use rate of intravenous antibiotics in the levofloxacin+G-CSF group and only G-CSF support group during ASCT were observed.The length of hospital stay,total cost during hospitalization and survival after 90 days of transplantation between the two groups were compared.Results:A total of 102 cases were included in this study,including 57 cases of multiple myeloma,36 cases of acute leukaemia,7 cases of lymphoma,3 cases of myelodysplastic syndrome,1 case of light chain amyloidosis,and 1 case of POEMS syndrome.47 patients received levofloxacin+G-CSF antibacterial prophylaxis,and 55 patients received G-CSF supportive therapy.In the levofloxacin+G-CSF group,40 cases(85.11％)developed febrile neutropenia,and 13 cases(27.66％)were confirmed as bacterial infection.In the G-CSF group,44 cases(80.00％)developed febrile neutropenia,and 16 cases(29.09％)were bacterial infection.There was no statistically significant difference in the incidence of febrile neutropenia and bacterial infection between the two groups(x2=0.46,P=0.50;x2=0.03,P=0.87).The use rate of intravenous antibiotics in the levofloxacin+G-CSF group was 85.11％(40/47),which was not statistically different from 85.45％(47/55)in the G-CSF group(X2=0.04,P=0.84).The detection rates of levofloxacin-resistant bacteria in the levofloxacin+G-CSF group and G-CSF group were 8.57％(3/35)and 21.43％(6/28),respectively,with no statistical difference(x2=0.65,P＞0.05).The median length and median cost of hospitalization in the levofloxacin+G-CSF group and G-CSF group were 25 d vs 22 d and 78 216.24 yuan vs 80 724.38 yuan,with no statistically significant differences(t=3.00,P=0.09;t=0.94,P=0.09).Within 90 days after transplantation,two cases(4.26％)died in the levofloxacin+G-CSF group and one case(1.82％)died in the G-CSF group,with no statistically significant difference between the two groups(x2=0.53,P=0.47).Conclusion:Application of levofloxacin+G-CSF showed no significant benefit compared to G-CSF support for the prevention of bacterial infections during ASCT.

Objective:To evaluate the clinical characteristics and risk factors of infections occurring during hospitalization in patients with multiple myeloma (MM) treated with new generation therapies (including immuno-modulatory drugs,proteasome inhibitors and monoclonal antibodies).Methods:The clinical data were collected from 155 patients with multiple myeloma who were treated in Shanxi Bethune Hospital from March,2017 to March,2022 and were retrospectively analyzed.For this study,the following therapies were considered to be new generation therapies:lenalidomide,pomadomide,bortezomib,ixazomib,daratumumab. The clinical characteristics and risk factors of infection were analyzed.Results:A total of 155 patients were included in this study.The median follow-up time was 20 months.Of 155 patients with MM,242 infection episodes were identified.Among the 242 infections,the incidence of clinically defined infection (CDI)was the highest (186,76.86％),followed by microbiologically defined infection (MDI)in 50 cases (20.66％),and fever at unknown focus (FUF)in 6 cases (2.48％).35 cases (14.46％)of bacteria,10 cases (4.13％)of viruses,and 5 cases (2. 07％)of fungi were clearly infected.The most common site of infection was the lower respiratory tract in 90 cases (37.19％),the upper respiratory tract in 83 cases (34.30％),and the digestive tract in 27 cases (11.16％).All-cause mortality was 8.39％(13/155).In univariate analysis,there was a higher correlation between ISS stage Ⅲ,the number of treatment lines ≥2,frail and infected patients with multiple myeloma.In multivariate analysis,ISS stage Ⅲ(OR=2.96,95％CI:1.19-7.40,P=0.02),the number of treatment lines ≥2 (OR=2.91,95％CI:1.13-7.51,P=0.03)and frail (OR=3.58,95％CI:1.44-8.89,P=0. 01)were risk factors for infection in patients with multiple myeloma in the era of new drugs.Conclusion:Patients with multiple myeloma treated with new agents are prone to bacterial infection during hospitalization.ISS stage Ⅲ,lines of therapy(≥2)and frail were associated with high risk for infection.

Objective To observe the expression changes of micro RNA-23a(miR-23a)and apoptotic protease-activating factor-1(APAF-1)in endometrial carcinoma tissues and analyze its clinical significance.Methods 123 specimens of endometrial carcinoma in our hospital from May 2018 to May 2020 were selected as endometrial carcinoma group,and the para cancerous tissue was selected as the normal group.Expression of miR-23a and APAF-1 were examined in endometrial tissues;the relationship between miR-23a and APAF-1 and the clinicopathology of patients and the correlation between the two were analyzed;Kaplan-Meier method was used to analyze the survival of patients with endometrial cancer.Results Compared with the normal group,the expression level of miR-23a in endometrial carcinoma group was significantly increased,the expressions of APAF-1 mRNA and protein decreased significantly(P<0.05);miR-23a and APAF-1 were significantly correlated with clinical stage,histological differentiation and myometrial invasion(P<0.05);Pearson analysis showed that miR-23a was nega-tively correlated with APAF-1(P<0.05);Kaplan-Meier curves showed that PFS and OS were significantly higher in the miR-23a low-expression group as well as the APAF-1-positive expression group than in the miR-23a high-expression group and the APAF-1-negative expression group(P<0.05).Conclusion The expression level of miR-23a is increased and APAF-1 expression is decreased in endometrial carcinoma,both of which correlate with endometrial cancer progression and patient prognosis,are expected to be biomarkers for clinical assessment of disease progression and prognosis in early-stage patients.