Objective To investigate the efficacy of an interpretable integrated learning model combining clinical indicators,CT image features and radiomics features for the differential diagnosis of lung squamous cell carcinoma and adenocarcinoma,so as to provide references for clincal treatment decisions.Methods A retrospective analysis was conducted on clinical and imaging data from 220 patients(231 lesions)with primary non-small cell lung cancer at Jiangjin Central Hospital of Chongqing(Center 1)and 83 patients(84 lesions)at Chongqing General Hospital(Center 2).In Center 1,the squamous cell carcinoma group consisted of 60 patients(60 lesions),while the adenocarcinoma group included 160 patients(171 lesions).In Center 2,the squamous cell carcinoma group comprised 18 patients(18 lesions),and the adenocarcinoma group involved 65 patients(66 lesions).The patients were categorized into squamous cell carcinoma and adenocarcinoma groups based on pathological findings.Center 1 was randomly partitioned into a training set and a validation set at a 7∶3 ratio,while Center 2 served as the independent test set.Firstly,a deep learning model,VB-Net,was used to automatically segment the tumor region on the lung window image;secondly,the SMOTE(synthetic minority oversampling technique)method was used to balance the categories in the training set and standardize the extracted features with Z-scores;thirdly,the least absolute shrinkage and selection operator(LASSO)were used to select the optimal radiomics features and calculate the radiomics score(Radscore),and univariate and multivariate logistic regression was used to screen clinical indicators and independent clinical factors for differentiating lung squamous cell carcinoma and adenocarcinoma in CT image features;finally,three ensemble learning algorithms(AdaBoost,Bagging decision tree and XGBoost)were used to combine independent clinical factors and Radscore to construct the model.The receiver operating characteristic(ROC)curve was used to evaluate the diagnostic performance of the models.SHAP technique was used to analyze the feature contribution and model decision-making process.Results Among the evaluated ensemble models,AdaBoost and Bagging decision trees demonstrated overfitting tendencies.In contrast,the XGBoost model showed the best performance,achieving AUC values of 0.939,0.887 and 0.853 in the training,validation and independent test sets,respectively.SHAP indicated that Radscore was the most important feature affecting the performance of the model.The decision diagram enabled the visualization of the diagnostic process of the model.Conclusion The interpretable integrated learning model based on clinical indicators,CT image and radiomics features is expected to non-invasively diagnose lung squamous cell carcinoma and adenocarcinoma before treatment and assist clinicians make treatment decisions as early as possible.[Chinese Medical Equipment Journal,2025,46(7):12-20]

AIM To explore the clinical effects of Huayu Ditan Linao Decoction combined with Suhexiang Pills on elderly patients with cerebral hemorrhage in convalescent stage.METHODS One hundred and ten patients were randomly assigned into control group(55 cases)for 1-month intervention of both conventional treatment and rehabilitation training,and observation group(55 cases)for 1-month intervention of Huayu Ditan Linao Decoction,Suhexiang Pills,conventional treatment and rehabilitation training.The changes in clinical effects,TCM syndrome score,NIHSS score,FMA score,BI index,cerebrovascular function indices(dynamic resistance,average flow velocity,peripheral resistance,average flow rate),serum inflammatory indices(IL-6,hs-CPR,TNF-α)and serum oxidative stress indices(SOD,MDA)were detected.RESULTS The observation group demonstrated higher total effective rate than the control group(P＜0.05).After the treatment,the two groups displayed decreased TCM syndrome score,NIHSS score,dynamic resistance,peripheral resistance,serum inflammatory indices,MDA(P＜0.05),and increased FMA score,BI index,average flow velocity,average flow rate,SOD(P＜0.05),especially for the observation group(P＜0.05).CONCLUSION For the elderly patients with cerebral hemorrhage in convalescent stage,Huayu Ditan Linao Decoction combined with Suhexiang Pills can enhance clinical effects,improve limb functions and nerve functions,regulate serum inflammatory and oxidative stress indice,and promote prognosis.

AIM To explore the clinical effects of Huayu Ditan Linao Decoction combined with Suhexiang Pills on elderly patients with cerebral hemorrhage in convalescent stage.METHODS One hundred and ten patients were randomly assigned into control group(55 cases)for 1-month intervention of both conventional treatment and rehabilitation training,and observation group(55 cases)for 1-month intervention of Huayu Ditan Linao Decoction,Suhexiang Pills,conventional treatment and rehabilitation training.The changes in clinical effects,TCM syndrome score,NIHSS score,FMA score,BI index,cerebrovascular function indices(dynamic resistance,average flow velocity,peripheral resistance,average flow rate),serum inflammatory indices(IL-6,hs-CPR,TNF-α)and serum oxidative stress indices(SOD,MDA)were detected.RESULTS The observation group demonstrated higher total effective rate than the control group(P＜0.05).After the treatment,the two groups displayed decreased TCM syndrome score,NIHSS score,dynamic resistance,peripheral resistance,serum inflammatory indices,MDA(P＜0.05),and increased FMA score,BI index,average flow velocity,average flow rate,SOD(P＜0.05),especially for the observation group(P＜0.05).CONCLUSION For the elderly patients with cerebral hemorrhage in convalescent stage,Huayu Ditan Linao Decoction combined with Suhexiang Pills can enhance clinical effects,improve limb functions and nerve functions,regulate serum inflammatory and oxidative stress indice,and promote prognosis.

Objective To investigate the efficacy of an interpretable integrated learning model combining clinical indicators,CT image features and radiomics features for the differential diagnosis of lung squamous cell carcinoma and adenocarcinoma,so as to provide references for clincal treatment decisions.Methods A retrospective analysis was conducted on clinical and imaging data from 220 patients(231 lesions)with primary non-small cell lung cancer at Jiangjin Central Hospital of Chongqing(Center 1)and 83 patients(84 lesions)at Chongqing General Hospital(Center 2).In Center 1,the squamous cell carcinoma group consisted of 60 patients(60 lesions),while the adenocarcinoma group included 160 patients(171 lesions).In Center 2,the squamous cell carcinoma group comprised 18 patients(18 lesions),and the adenocarcinoma group involved 65 patients(66 lesions).The patients were categorized into squamous cell carcinoma and adenocarcinoma groups based on pathological findings.Center 1 was randomly partitioned into a training set and a validation set at a 7∶3 ratio,while Center 2 served as the independent test set.Firstly,a deep learning model,VB-Net,was used to automatically segment the tumor region on the lung window image;secondly,the SMOTE(synthetic minority oversampling technique)method was used to balance the categories in the training set and standardize the extracted features with Z-scores;thirdly,the least absolute shrinkage and selection operator(LASSO)were used to select the optimal radiomics features and calculate the radiomics score(Radscore),and univariate and multivariate logistic regression was used to screen clinical indicators and independent clinical factors for differentiating lung squamous cell carcinoma and adenocarcinoma in CT image features;finally,three ensemble learning algorithms(AdaBoost,Bagging decision tree and XGBoost)were used to combine independent clinical factors and Radscore to construct the model.The receiver operating characteristic(ROC)curve was used to evaluate the diagnostic performance of the models.SHAP technique was used to analyze the feature contribution and model decision-making process.Results Among the evaluated ensemble models,AdaBoost and Bagging decision trees demonstrated overfitting tendencies.In contrast,the XGBoost model showed the best performance,achieving AUC values of 0.939,0.887 and 0.853 in the training,validation and independent test sets,respectively.SHAP indicated that Radscore was the most important feature affecting the performance of the model.The decision diagram enabled the visualization of the diagnostic process of the model.Conclusion The interpretable integrated learning model based on clinical indicators,CT image and radiomics features is expected to non-invasively diagnose lung squamous cell carcinoma and adenocarcinoma before treatment and assist clinicians make treatment decisions as early as possible.[Chinese Medical Equipment Journal,2025,46(7):12-20]

Bacterial biofilms gave rise to persistent infections and multi-organ failure, thereby posing a serious threat to human health. Biofilms were formed by cross-linking of hydrophobic extracellular polymeric substances (EPS), such as proteins, polysaccharides, and eDNA, which were synthesized by bacteria themselves after adhesion and colonization on biological surfaces. They had the characteristics of dense structure, high adhesiveness and low drug permeability, and had been found in many human organs or tissues, such as the brain, heart, liver, spleen, lungs, kidneys, gastrointestinal tract, and skeleton. By releasing pro-inflammatory bacterial metabolites including endotoxins, exotoxins and interleukin, biofilms stimulated the body’s immune system to secrete inflammatory factors. These factors triggered local inflammation and chronic infections. Those were the key reason for the failure of traditional clinical drug therapy for infectious diseases.In order to cope with the increasingly severe drug-resistant infections, it was urgent to develop new therapeutic strategies for bacterial-biofilm eradication and anti-bacterial infections. Based on the nanoscale structure and biocompatible activity, nanobiomaterials had the advantages of specific targeting, intelligent delivery, high drug loading and low toxicity, which could realize efficient intervention and precise treatment of drug-resistant bacterial biofilms. This paper highlighted multiple strategies of biofilms eradication based on nanobiomaterials. For example, nanobiomaterials combined with EPS degrading enzymes could be used for targeted hydrolysis of bacterial biofilms, and effectively increased the drug enrichment within biofilms. By loading quorum sensing inhibitors, nanotechnology was also an effective strategy for eradicating bacterial biofilms and recovering the infectious symptoms. Nanobiomaterials could intervene the bacterial metabolism and break the bacterial survival homeostasis by blocking the uptake of nutrients. Moreover, energy-driven micro-nano robotics had shown excellent performance in active delivery and biofilm eradication. Micro-nano robots could penetrate physiological barriers by exogenous or endogenous driving modes such as by biological or chemical methods, ultrasound, and magnetic field, and deliver drugs to the infection sites accurately. Achieving this using conventional drugs was difficult. Overall, the paper described the biological properties and drug-resistant molecular mechanisms of bacterial biofilms, and highlighted therapeutic strategies from different perspectives by nanobiomaterials, such as dispersing bacterial mature biofilms, blocking quorum sensing, inhibiting bacterial metabolism, and energy driving penetration. In addition, we presented the key challenges still faced by nanobiomaterials in combating bacterial biofilm infections. Firstly, the dense structure of EPS caused biofilms spatial heterogeneity and metabolic heterogeneity, which created exacting requirements for the design, construction and preparation process of nanobiomaterials. Secondly, biofilm disruption carried the risk of spread and infection the pathogenic bacteria, which might lead to other infections. Finally, we emphasized the role of nanobiomaterials in the development trends and translational prospects in biofilm treatment.

Objective To investigate the attributable risk(AR)of Acinetobacter baumannii(AB)infection in criti-cally ill patients.Methods A multicenter retrospective cohort study was conducted among adult patients in inten-sive care unit(ICU).Patients with AB isolated from sterile body fluid and confirmed with AB infection in each cen-ter were selected as the infected group.According to the matching criteria that patients should be from the same pe-riod,in the same ICU,as well as with similar APACHE Ⅱ score(±5 points)and primary diagnosis,patients who did not infect with AB were selected as the non-infected group in a 1:2 ratio.The AR was calculated.Results The in-hospital mortality of patients with AB infection in sterile body fluid was 33.3％,and that of non-infected group was 23.1％,with no statistically significant difference between the two groups(P=0.069).The AR was 10.2％(95％CI:-2.3％-22.8％).There is no statistically significant difference in mortality between non-infected pa-tients and infected patients from whose blood,cerebrospinal fluid and other specimen sources AB were isolated(P＞0.05).After infected with AB,critically ill patients with the major diagnosis of pulmonary infection had the high-est AR.There was no statistically significant difference in mortality between patients in the infected and non-infec-ted groups(P＞0.05),or between other diagnostic classifications.Conclusion The prognosis of AB infection in critically ill patients is highly overestimated,but active healthcare-associated infection control for AB in the ICU should still be carried out.

Objective:To provide reference for hospital drug selection and clinical rational drug selection,through evaluating the nutritional value of six commonly used balanced compound amino acid injection (BCAA) in clinical practice,including 18AA (250 mL:12.5 g),18AA-I (250 mL:17.5 g),18AA-Ⅱ(250 mL:21.25 g),18AA-IV (250 mL:8.7 g),18AA-V (250 mL:8.06 g),and 18AA-V-SF (250 mL:8.06 g). Methods:Based on the whole egg protein model,the nutritional value of six varieties of BCAA from two aspects were evaluated,including the first limiting amino acid chemical score (CS),value of essential amino acid (EAA) and the comprehensive quality of total EAA (both essential amino acid index and closeness to standard protein). Results:The first limiting amino acid CS value from high to low was 18AA-Ⅱ>18AA>18AA-V=18AA-V-SF>18AA-I=18AA-Ⅳ. Total EAA comprehensive quality:the essential amino acid index from high to low was 18AA-Ⅱ>18AA>18AA-I>18AA-Ⅳ>18AA-V=18AA-V-SF. The closeness to whole egg protein from high to low was 18AA-Ⅱ=18AA=18AA-I>18AA-Ⅳ>18AA-V=18AA-V-SF. Ultimately,the nutritional value of the 6 varieties of BCAA decreased from high to low:18AA-Ⅱ>18AA>18AA-I>18AA-Ⅳ>18AA-V=18AA-V-SF. Conclusions:Among the six varieties of BCAA,18AA-Ⅱ has the highest nutritional value and the highest amino acid content in the same liquid volume,making it the preferred drug for patients with normal liver and kidney function.

Objective To discuss the value of the apparent diffusion coefficient(ADC)in the prediction of therapeutic effect of neoadjuvant concurrent chemoradiotherapy(nCRT)in rectal cancer.Methods The clinical data of 52 patients with pathologi-cally diagnosed rectal cancer who underwent neoadjuvant chemoradiotherapy(nCRT)and received pelvic MR1 examinations before and 8 weeks after nCRT at the 900th Hospital of Joint Logistics Support Force from January 2019 to February 2023 were analyzed retrospectively.The ADC values before and after nCRT were obtained,and ΔADC and ΔADC％were calculated.The 52 patients were divided into a sensitive group(n=40)and a non-sensitive group(n=12)based on the tumor regression grade(TRG).The ADC values before nCRT,ΔADC and ΔADC％of the above two groups were compared by Mann-Whitney U test.The ADC values after nCRT of the two groups were compared by independent samples t-test.Spearman's rank correlation coefficient was used to evaluate the correlation of ΔADC and ΔADC％with TRG.The baseline data of the two groups were compared by independent samples t-test,Mann-Whitney U test and chi-square test.Binary Logistic regression was used to analyze the factors predicting efficacy.ROC was drawn to assess the ability of ΔADC in predicting nCRT efficacy,and determine optimal cut-off value.Results There was no statistical difference between the sensitive group and the non-sensitive group with regard to ADCs before and after nCRT(P＞0.05).There were statistical differences between the above two groups with regard to ΔADC and ΔADC％(P＜0.05).ΔADC and ΔADC％showed negative correlation with TRG(r=-0.378,-0.368,P＜0.05).Univariate analysis showed that there were statistically significant differences in tumor diameter between the two groups(P＜0.05).Multivariate analysis showed that ΔADC was an independent predictor of the efficacy.ROC curve analysis showed the optimal cut-off value of ΔADC was 236.600×10-6 mm2/s.Conclusion The ADC values before and after nCRT have limited predictive significance for assessing the efficacy of nCRT,whereas ΔADC can predict nCRT efficacy effectively and provide references for subsequent clinical treatment.[Chinese Medical Equipment Journal,2024,45(12):61-66]

Objective To discuss the value of the apparent diffusion coefficient(ADC)in the prediction of therapeutic effect of neoadjuvant concurrent chemoradiotherapy(nCRT)in rectal cancer.Methods The clinical data of 52 patients with pathologi-cally diagnosed rectal cancer who underwent neoadjuvant chemoradiotherapy(nCRT)and received pelvic MR1 examinations before and 8 weeks after nCRT at the 900th Hospital of Joint Logistics Support Force from January 2019 to February 2023 were analyzed retrospectively.The ADC values before and after nCRT were obtained,and ΔADC and ΔADC％were calculated.The 52 patients were divided into a sensitive group(n=40)and a non-sensitive group(n=12)based on the tumor regression grade(TRG).The ADC values before nCRT,ΔADC and ΔADC％of the above two groups were compared by Mann-Whitney U test.The ADC values after nCRT of the two groups were compared by independent samples t-test.Spearman's rank correlation coefficient was used to evaluate the correlation of ΔADC and ΔADC％with TRG.The baseline data of the two groups were compared by independent samples t-test,Mann-Whitney U test and chi-square test.Binary Logistic regression was used to analyze the factors predicting efficacy.ROC was drawn to assess the ability of ΔADC in predicting nCRT efficacy,and determine optimal cut-off value.Results There was no statistical difference between the sensitive group and the non-sensitive group with regard to ADCs before and after nCRT(P＞0.05).There were statistical differences between the above two groups with regard to ΔADC and ΔADC％(P＜0.05).ΔADC and ΔADC％showed negative correlation with TRG(r=-0.378,-0.368,P＜0.05).Univariate analysis showed that there were statistically significant differences in tumor diameter between the two groups(P＜0.05).Multivariate analysis showed that ΔADC was an independent predictor of the efficacy.ROC curve analysis showed the optimal cut-off value of ΔADC was 236.600×10-6 mm2/s.Conclusion The ADC values before and after nCRT have limited predictive significance for assessing the efficacy of nCRT,whereas ΔADC can predict nCRT efficacy effectively and provide references for subsequent clinical treatment.[Chinese Medical Equipment Journal,2024,45(12):61-66]

OBJECTIVE: To investigate the mechanism by which Chinese medicine Shengmai Yin (SMY) reverses epithelial-mesenchymal transition (EMT) through lipocalin-2 (LCN2) in nasopharyngeal carcinoma (NPC) cells CNE-2R. METHODS: Morphological changes in EMT in CNE-2R cells were observed under a microscope, and the expressions of EMT markers were detected using quantitative real-time PCR (RT-qPCR) and Western blot assays. Through the Gene Expression Omnibus dataset and text mining, LCN2 was found to be highly related to radiation resistance and EMT in NPC. The expressions of LCN2 and EMT markers following SMY treatment (50 and 100 µ g/mL) were detected by RT-qPCR and Western blot assays in vitro. Cell proliferation, migration, and invasion abilities were measured using colony formation, wound healing, and transwell invasion assays, respectively. The inhibitory effect of SMY in vivo was determined by observing a zebrafish xenograft model with a fluorescent label. RESULTS: The CNE-2R cells showed EMT transition and high expression of LCN2, and the use of SMY (5, 10 and 20 µ g/mL) reduced the expression of LCN2 and reversed the EMT in the CNE-2R cells. Compared to that of the CNE-2R group, the proliferation, migration, and invasion abilities of SMY high-concentration group were weakened (P<0.05). Moreover, SMY mediated tumor growth and metastasis in a dose-dependent manner in a zebrafish xenograft model, which was consistent with the in vitro results. CONCLUSIONS SMY can reverse the EMT process of CNE-2R cells, which may be related to its inhibition of LCN2 expression. Therefore, LCN2 may be a potential diagnostic marker and therapeutic target in patients with NPC.
Animals ; Humans ; Nasopharyngeal Carcinoma/genetics* ; Epithelial-Mesenchymal Transition ; Zebrafish ; Cell Proliferation ; Cell Line, Tumor ; Nasopharyngeal Neoplasms/radiotherapy* ; Cell Movement ; Gene Expression Regulation, Neoplastic