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 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 investigate the occurrence of frailty and its influencing factors in patients with lung cancer.Methods:Patients with lung cancer receiving treatment at Xiangya Hospital of Central South University were recruited between March 2022 and March 2023.The FRAIL scale was employed to categorize the patients into non-frailty, pre-frailty, and frailty groups.A comparison of their basic data, disease data, and relevant laboratory indicators before treatment was conducted to identify factors influencing frailty in lung cancer patients.Results:A total of 240 patients with lung cancer were analyzed in this study, comprising 46 patients(19.2%)in the non-frailty group, 121 patients(50.4%)in the pre-frailty group, and 73 patients(30.4%)in the frailty group.The average age of the frailty and pre-frailty groups was significantly higher than that of the non-frailty group( P<0.05).Additionally, the body mass index(BMI)of the frailty group was significantly lower compared to both the non-frailty and pre-frailty groups( P=0.005).The proportion of male patients in the frailty group was lower than that of female patients, while the proportion of pre-frailty patients was higher among females( P=0.017).Furthermore, the percentage of patients receiving family care was lower in both the frailty and pre-frailty groups compared to those without family care( P<0.001).Various blood markers such as white blood cells(WBC), neutrophils(NEUT), N terminal pro B type natriuretic peptide(NT-proBNP), carcinoembryonic antigen(CEA), neuron-specific enolase(NSE), neurophil to lymphocyte ratio(NLR), monocyte-lymphocyte ratio(MLR), and systemic inflammatory index(SII)were significantly elevated in the frailty group compared to the non-frailty group, whereas red blood cells(RBC), hemoglobin(Hb), hematocrit(HCT), lymphocytes(LYMPH), total protein(TP), albumin(Alb), total cholesterol(TC), high-density lipoprotein cholesterol(HDL-C), and low-desity lipoprotein cholesterol(LDL-C)were notably lower in the frailty group(all P<0.05).Similarly, NEUT, NLR, platelet to lymphocyte ratio(PLR), MLR, and SII were higher in the frailty group compared to the pre-frailty group, while RBC, Hb, HCT, LYMPH, TP, Alb, TC, HDL-C, and LDL-C were lower in the frailty group than the pre-frailty group( P<0.05).Moreover, NT-proBNP levels were higher in the pre-frailty group than in the non-frailty group, with all these differences being statistically significant(all P<0.05).The results of multifactorial Logistic regression analyses revealed several significant associations with frailty in lung cancer patients.Males had an increased risk of frailty( OR=2.80, P=0.033), while family care was linked to a decreased risk( OR=0.37, P=0.004).Additionally, advancing age was associated with a higher risk of frailty( OR=1.06, P=0.004).Furthermore, higher Alb levels were correlated with a reduced risk of frailty( OR=0.91, P=0.023), elevated LDL-C levels were associated with a lower risk( OR=0.59, P=0.027), and increased CEA levels were linked to a higher risk of frailty( OR=1.01, P=0.003)in lung cancer patients. Conclusions:In lung cancer patients, older age, male gender, and higher CEA levels were linked to a higher risk of frailty, whereas family care, higher Alb levels, and high LDL-C levels were associated with a lower risk of frailty.These findings imply the importance of intensifying frailty screening in lung cancer patients to identify and intervene in frailty risk early on.

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.

Objective To propose a human life signal separation and reconstruction method based on optimized variational mode decomposition(VMD)to improve the accuracy and timeliness of the life detection radar in extracting and separating human life signals such as heartbeat and respiration.Methods Firstly,the particle swarm optimization algorithm was used to optimize the parameters of VMD,and the human life signal was decomposed into a series of intrinsic mode functions(IMFs);secondly,the alignment entropy of each IMF was calculated,the noise was removed based on the alignment entropy threshold,and the remaining components were reconstructed to form human life signals;finally,the method proposed was compared with infinite impulse response(IIR)filtering,VMD and complete ensemble empirical mode decomposition with adaptive nosie(CEEMDAN)to verify its performance.Results Under different noise levels the proposed method outperformed IIR filtering,VMD and CEEMDAN in evaluation metrics of signal-to-noise ratio and root-mean-square error,and behaved better than CEEMDAN in terms of computational time-consumption.Conclusion The proposed method realizes rapid separation and reconstruction of vital signals such as heartbeat and respiration while effectively filtering out the noise,which has broad application prospects in the fields of non-contact vital signs detection of bum/scald patients,infectious disease patients and newborns and the search and rescue of buried casualties after a disaster.[Chinese Medical Equipment Journal,2024,45(3):9-15]

Objective To construct a big data sharing platform for clinical scientific research to solve the problems of clinical research in decentralized application systems and data sharing safety.Methods A clinical research information data usage management system was developed through the formulation of management methods in line with the actual situation of the institution,normalized standard data usage processes and a data usage service team.Then a clinical scientific research big data sharing platform including the components for sharing environment construction,research application integration,data desensitization and encryption and file management was established based on the existing hospital systems,the requirements of clinical research data usage management and the habits of clinical researchers.Results The platform realized the balance between open sharing of clinical research data and data security control,which improved the efficiency of clinical researchers while reducing data security risks during data transmission and data analysis.Conclusion The clinical scientific research big data sharing platform meets the needs of clinical scientific research application and data security management,and provides references for the co-construction-sharing of medical big data resources.[Chinese Medical Equipment Journal,2024,45(4):27-31]

Objective To retrospectively investigate the efficacy of pelvic floor muscle training(PFMT)using APP-based home device in the real-world scenario.Methods A retrospective survey was conducted among 171 000 Chinese female users over 18 years old who freely registered APP and performed PFMT using a domestic manufactured home device from Oct 1,2019 to Mar 31,2021.The Patient Global Impression of Improvement(PGI-I)questionnaires concerning pelvic floor general condition,sexual satisfaction and other three major symptoms related to pelvic floor muscle laxity such as stress urinary incontinence(SUI),pelvic organ prolapse(POP),and vaginal laxity(VL)were broadcast public online for users to self-assess the improvement.The vaginal muscle strength values prior and post training recorded by APP were also reported.All data were collected anonymously for further stratified analysis.Results A total of 984 valid questionnaires were collected by systematic sampling.The PGI-I scores of pelvic floor general condition(P=0.000 1),sexual satisfaction(P=0.009),SUI(P=0.000 1),POP(P=0.044)and VL(P=0.034)were statistically significant in users who reported to use the device for 3 months or more compared with those less than 3 months.In addition,the increase of vaginal muscle strength was related to the improvement of PGI-I scores in SUI and POP with statistical significance.There were no significant difference in subgroups such as age,education,parity,and delivery mode.Conclusion The subjective benefit of pelvic floor function-related symptoms and the improvement of vaginal muscle strength could be observed after PFMT for three months or more using APP-based home device in Chinese women in the real-world scenario.

The UV cross-linking immunoprecipitation (CLIP) technique was first established in 2003. Sequences of target RNAs and binding sites of specific RNA-binding proteins (RBPs) were identified within the entire transcriptome by UV cross-linking, immunoprecipitation, reverse transcription, and subsequent high-throughput sequencing. Over the last 20 years, CLIP has been continuously modified and improved. Advanced operability and accuracy have extended its application category. Currently, the widely used CLIP technologies include high-throughput sequencing with crosslinking-immunoprecipitation (HITS-CLIP), photoactivatable-ribonucleoside-enhanced CLIP (PAR-CLIP), individual nucleotide resolution CLIP (iCLIP), enhanced CLIP (eCLIP), infrared-CLIP (irCLIP), etc. HITS-CLIP combines high-throughput sequencing with UV cross-linking immunoprecipitation. The 254 nm UV cross-linking and RNAase digestion steps allow the technology to capture transient intracellular RBP-RNA interactions. However, there are limitations in the efficiency of UV cross-linking, with low resolution and high intrinsic background noise. For PAR-CLIP, photoactivatable ribonucleoside was incorporated into RNA molecules, and RBP cross-linked with RNA by 365 nm UV light to improve cross-linking efficiency and resolution. Cross-linking mediated single-base mutations provide more accurate binding site information and reduce interference from background sequences. Long-term alternative nucleotide incorporation, on the other hand, can be cytotoxic and may skew experimental results. iCLIP can identify RBP-RNA cross-linking sites at the single nucleotide level through cDNA circularization and subsequent re-linearization steps, but it has more experimental procedures, and partial cDNAs lost in the circularization step are inevitable. eCLIP discards the radioisotope labeling procedure and reduces RNA loss by ligating adaptors in two separate steps, greatly improving the library-building efficiency, and reducing bias associated with PCR amplification; however, the efficiency of immunoprecipitation cannot be visually assessed at the early stage of the experiment. The irCLIP technique replaces radioisotopes with infrared dyes and greatly reduces the initial number of cells required for the experiment; however, an infrared imaging scanner is essential for the irCLIP application. To address more particular scientific issues, derivative CLIP-related techniques such as PAPERCLIP, cTag-PAPERCLIP, hiCLIP, and tiCLIP have also been developed in recent years. In practice, the aforementioned CLIP approaches have their advantages and disadvantages. When deciding on a technical strategy, we should take into account our experimental objectives and conditions, such as whether we need to precisely define the RNA site for binding to RBP; whether we have the necessary experimental conditions for working with radioisotopes or performing infrared imaging; the amount of initial sample size, and so on. In addition, the CLIP technique has a relatively large number of procedures and can be divided into several successive experimental modules. We can try to combine modules from different mainstream CLIP technologies to meet our experimental requirements, which also gives us more opportunities to improve and refine them and to build more targeted derivative CLIP technologies according to our research objectives.

Objective The leptin receptor,encoded by the LEPR gene,is involved in tumorigenesis.A potential functional variant of LEPR,rs1137101(Gln223Arg),has been extensively investigated for its contribution to the risk of digestive system(DS)cancers,but results remain conflicting rather than conclusive.Here,we performed a case-control study and subsequent meta-analysis to examine the association between rs1137101 and DS cancer risk. Methods A total of 1,727 patients with cancer(gastric/liver/colorectal:460/480/787)and 800 healthy controls were recruited.Genotyping of rs1137101 was conducted using a polymerase chain reaction-restriction fragment length polymorphism(PCR-RFLP)assay and confirmed using Sanger sequencing.Twenty-four eligible studies were included in the meta-analysis. Results After Bonferroni correction,the case-control study revealed that rs1137101 was significantly associated with the risk of liver cancer in the Hubei Chinese population.The meta-analysis suggested that rs1137101 is significantly associated with the risk of overall DS,gastric,and liver cancer in the Chinese population. Conclusion The LEPR rs1137101 variant may be a genetic biomarker for susceptibility to DS cancers(especially liver and gastric cancer)in the Chinese population.