Chronic myeloid leukemia (CML) is a malignant hematologic disorder caused by abnormal proliferation of hematopoietic stem cells. In recent years, while the application of tyrosine kinase inhibitors (TKIs) has significantly improved the prognosis of CML patients through in-depth exploration of pathogenesis of CML and advancements in targeted therapies, some patients still face challenges including drug resistance, disease relapse, and failure to achieve treatment-free remission. Imunotherapy, as a complementary or alternative strategy, holds significant potential for overcoming these limitations, and has gradually emerged as a critical research focus in CML treatment. This review aims to summarize the current research status and latest advances in immunotherapy for CML.

Objective To reveal the scientific output and trends in pulmonary nodules/early-stage lung cancer prediction models. Methods Publications on predictive models of pulmonary nodules/early lung cancer between January 1, 2002 and June 3, 2023 were retrieved and extracted from CNKI, Wanfang, VIP and Web of Science database. CiteSpace 6.1.R3 and VOSviewer 1.6.18 were used to analyze the hotspots and theme trends. Results A marked increase in the number of publications related to pulmonary nodules/early-stage lung cancer prediction models was observed. A total of 12581 authors from 2711 institutions in 64 countries/regions published 2139 documents in 566 academic journals in English. A total of 282 articles from 1256 authors were published in 176 journals in Chinese. The Chinese and English journals which published the most pulmonary nodules/early-stage lung cancer prediction model-related papers were Journal of Clinical Radiology and Frontiers in Oncology, respectively. Chest was the most frequently cited journal. China and the United States were the leading countries in the field of pulmonary nodules/early-stage lung cancer prediction models. The institutions represented by Fudan University had significant academic influence in the field. Analysis of keywords revealed that multi-omics, nomogram, machine learning and artificial intelligence were the current focus of research. Conclusion Over the last two decades, research on risk-prediction models for pulmonary nodules/early-stage lung cancer has attracted increasing attention. Prognosis, machine learning, artificial intelligence, nomogram, and multi-omics technologies are both current hotspots and future trends in this field. In the future, in-depth explorations using different omics should increase the sensitivity and accuracy of pulmonary nodules/early-stage lung cancer prediction models. More high-quality future studies should be conducted to validate the efficacy and safety of pulmonary nodules/early-stage lung cancer prediction models further and reduce the global burden of lung cancer.

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 establish an HPLC method to determine the concentration of inositol nicotinate（IN） in rat skin, and study the pharmacokinetic characteristics of IN after transdermal administration of heparin sodium inositol nicotinate cream in rats. Methods HPLC method was used to establish a simple and rapid analytical method for the determination of IN concentration in the skin of rats at different time points after administration. The established method was used to study the pharmacokinetics of IN after transdermal administration of heparin sodium inositol nicotinate cream in rats, and the pharmacokinetic parameters were fitted with DAS software. Results The linearity of the analytical method was good in the concentration range of 0.25-20 μg/ml, the quantitative limit was 0.25 μg/ml, and the average recovery rate was 96.18%. The pharmacokinetic parameters of IN after transdermal administration of heparin sodium inositol nicotinate cream in rats were as follows: t_1/2 was （4.555±2.054） h, T_max was （6±0）h, C_max was （16.929±2.153）mg/L, AUC_0−t was （150.665±16.568） mg·h /L ,AUC_0−∞ was （161.074±23.917） mg·h /L, MRT_（0−t） was （9.044±0.618）h, MRT_{（0−∞）} was （10.444±1.91） h, CLz/F was （0.19±0.03） L/（h·kg）, and Vz/F was （1.19±0.437） L/（h·kg）. Conclusion IN could quickly penetrate the skin and accumulate in the skin for a long time, which was beneficial to the pharmacological action of drugs on the lesion site for a long time. The method is simple, rapid, specific and reproducible, which could be successfully applied to the pharmacokinetic study of IN after transdermal administration in rats.

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.

To investigate the existence of tick-borne pathogens infection of rodents at the border of China and the Demo-cratic People's Republic of Korea(DPRK).PCR was used to detect the spotted fever group rickettsiae(SFGR)ompA gene,Ehrlichia chaffeensis(Ec)and Anaplasma phagocytophilum(Ap)16S rRNA,Candidatus Neoehrlichia mikurensis(CNm)groEL gene,Bartonella(Ba)rpoB gene,and Francisella tularensis(Ft)fopA gene in rodents samples collected from Ji'an of Jilin province and Kuandian of Liaoning Province.The positivity rates of 132 wild rats spleen samples,SFGR,Ec,Ap,CNm,Ba,and Ft were 9.85％,12.88％,5.30％,3.79％,51.52％,and 6.06％,respectively,with statistical differences in in-fection rates(x2=149.236,P=0.000).The infection rate of Ba was the highest in wild rats in this area.There was no signifi-cant difference in the infection rate of SFGR,Ec,Ap,CNm,and Ft among different rats species,but there were significant differences in the infection rate of Ba(x2=13.36,P=0.010).The infection rate of Apodemus agrarius was the highest.A-mong 132 wild rats specimens,the coinfection rate of the two pathogens was 15.9％(21/132),with Ba as the main species(15/132),and two cases of coinfection with three pathogens were detected.The infection of six tick-borne pathogens is common in wild rats at the China/DPRK border.Co-infection of two or three pathogens indicates a risk of multiple tick-borne pathogens and mixed natural foci of multiple tick-borne infec-tious diseases.

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.

Heat stroke (HS), also known as severe sunstroke, is one of the most serious heat-related disorders, characterized by rapid onset, rapid progression, aggressive condition, and high morbidity and mortality. The occurrence and development of HS are closely related to pathophysiological processes such as inflammation, oxidative stress, cell death, and coagulation failure. With the gradual discovery of the pathogenic mechanisms of HS, some drugs or therapeutic approaches targeting its molecular regulatory pathways have shown clinical promise. This review intends to provide an overview of research advances in HS types, pathogenic mechanisms, preclinical and clinically relevant therapeutic strategies, as well as to highlight the potential clinical applications of HS-related biomarkers and therapeutic targets with a view to informing the clinical management of HS.

Objective:To evaluate the efficacy and safety of 308-nm excimer lamp and 308-nm excimer laser in the treatment of pediatric vitiligo.Methods:Clinical data were collected from children with stable vitiligo who received targeted phototherapy at the Department of Dermatology of Xijing Hospital from 2010 to 2015, and retrospectively analyzed. The patients were treated with either 308-nm excimer laser or 308-nm excimer lamp, and all were given topical drugs. The treatment lasted for at least 3 months, and follow-up for at least 6 months. The severity of vitiligo was assessed using the Vitiligo Area and Severity Index (VASI) score. The efficacy was evaluated after 3 months of treatment, and at least a 50% reduction in the VASI score (VASI50) was defined as "effectiveness". A logistic regression model was constructed using treatment efficacy as the dependent variable to screen factors related to the treatment outcome. The Wilcoxon signed-rank test was used to compare skewed data before and after treatment. Adverse reactions during treatment were recorded to evaluate the safety of targeted phototherapy.Results:A total of 194 children with stable vitiligo were included, comprising 103 males (53.1%) and 91 females (46.9%), with the age being 6 to 14 (10.2 ± 2.3) years. Among them, 138 (71.1%) received 308-nm excimer laser therapy, while 56 (28.9%) received 308-nm excimer lamp therapy. The VASI score ( M [ Q1, Q3]) was 0.12 (0.05, 0.40) at the baseline, significantly decreased to 0.06 (0.02, 0.19) after 3 months of treatment ( Z = 12.02, P < 0.001). After 3 months of treatment, 52 patients achieved VASI50, and 30 achieved VASI75, resulting in an overall response rate of 42.3% (82/194). Specifically, in the 308-nm excimer laser group, 38 patients achieved VASI50 and 26 achieved VASI75, with a response rate of 46.4% (64/138) ; in the 308-nm excimer lamp group, 14 patients achieved VASI50 and 4 achieved VASI75, yielding a response rate of 32.1% (18/56). Univariate logistic regression analysis indicated that lesions located on the head and neck or the trunk were more prone to repigmentation compared with those on the limbs ( OR = 3.56, 95% CI: 1.15 - 11.02, P = 0.027; OR = 6.58, 95% CI: 1.81 - 23.96, P = 0.004, respectively) ; additionally, facial lesions around the eyes were more prone to repigmentation compared with lesions on other facial areas ( OR = 4.58, 95% CI: 1.10 - 19.11, P = 0.037), and hair involvement in vitiligo lesions on the head and neck made repigmentation less likely to occur compared with lesions without hair involvement ( OR = 0.31, 95% CI: 0.13 - 0.75, P = 0.010). Multivariate logistic regression analysis revealed that the periorbital region was the most favorable site for repigmentation among facial areas ( OR = 5.37, 95% CI: 1.18 - 24.34, P = 0.029), and hair involvement in vitiligo lesions on the head and neck was an independent risk factor for phototherapy-induced repigmentation ( OR = 0.28, 95% CI: 0.08 - 0.96, P = 0.042). Among the 194 patients treated with targeted phototherapy for 3 months, 33 experienced short-term treatment-related adverse reactions, including erythema, blisters, desquamation, itching, and pain; most adverse reactions were mild, and no severe adverse reactions were observed. Conclusion:Targeted phototherapy using 308-nm excimer laser or 308-nm excimer lamp was safe and effective for the treatment of pediatric vitiligo.