The persistent high prevalence and poor survival outcomes of lung cancer underscore the urgent need for innovative therapeutic modalities. Here, we present a novel multifunctional delivery platform for the synergistic treatment of lung malignancies, combining in situ-triggerable photodynamic therapy (PDT) with radiotherapy. The new platform CLL was developed by loading a new reactive oxygen species (ROS)-triggerable photosensitizer, luminol-conjugated chlorin e6 (Ce6), into liposomes. CLL can be activated through the bioluminescence resonance energy transfer effect under oxidative stress, thereby producing singlet oxygen for targeted tumor treatment without external irradiation. In vitro studies showed significant cytotoxic effects of CLL in both 4T1 and A549 tumor cells. Furthermore, a PDT-radiopharmaceutical combination nanotherapy CLL-¹⁷⁷Lu was engineered by incorporating the radionuclide ¹⁷⁷Lu into CLL. CLL-¹⁷⁷Lu demonstrated synergistic antitumor effects in 4T1 and A549 tumor cells, as well as in mouse models of 4T1 breast cancer lung metastasis or A549 tumor xenografts. Mechanistically, CLL-¹⁷⁷Lu can induce singlet oxygen/ROS generation, enhance tumor cell apoptosis, and promote M1 macrophage-mediated immunotherapy. Preliminary assessments showed a favorable profile for CLL-¹⁷⁷Lu, highlighting its potential as a promising nanotherapy for cancer treatment. Additionally, CLL can serve as a versatile platform for delivering a range of therapies to achieve synergistic antitumor effects.

Objective:To discuss the expression and clinical significance of inositol polyphosphate-4-phosphatase type Ⅱ(INPP4B)gene in hepatocellular carcinoma(HCC)based on The Cancer Genome Atlas(TCGA)database and experimental verification with clinical samples.Methods:Based on data from 424 clinical samples in the TCGA database(including 374 HCC tissues and 50 paracarcinoma tissues),Kaplan-Meier method and Cox regression analysis were used to evaluate the relationship between INPP4B gene and the clinical characteristics and survival prognosis of the HCC patients.The correlations between INPP4B gene and the number of 24 types of immune cells,matrix,immune cell infiltration and tumor purity in tumor tissue,and the expression level of the high-frequency mutant gene tumor protein 53(TP53)in HCC were analyzed.The clinicopathological data and paraffin-embedded tissue sections of 60 HCC patients treated with surgical resection from December 2022 to December 2023 were collected.According to clinical diagnosis,they were divided into poorly differentiated group(HCC-L group),moderately differentiated group(HCC-M group)and well-differentiated group(HCC-H group),with 20 cases in each group;20 patients during the same period who underwent biopsy and were pathologically diagnosed as non-tumor were selected as normal group,and their clinicopathologic data and liver tissue paraffin sections were collected.HE staining was used to observe the pathomorphology of HCC tissue and normal liver tissue of the subjects in various groups;immunohistochemistry method was used to detect the expressions of Ki-67 and INPP4B proteins in the HCC tissue and normal liver tissue of the subjects in various groups.Results:The TCGA database analysis results showed that compared with normal tissue,the expression level of INPP4B mRNA in HCC tissue was significantly increased(P<0.01).Compared with INPP4B low expression group,the overall survival(OS)of the patients in INPP4B high expression group was significantly prolonged(P<0.05).The univariate Cox regression analysis results showed that tumor stage,pathological stage,tumor status and residual tumor had impacts on OS of the HCC patients(P<0.05).The univariate regression analysis results showed that the INPP4B prognostic risk model score ratio was HR=0.781,95％confidence interval(CI):0.552-1.105,P=0.168.The AUC value for the impact of INPP4B on OS of the HCC patients was 0.558,indicating that the INPP4B gene prognostic risk model had certain predictive value in survival prognosis.The INPP4B mRNA expression level was not correlated with TNM stage,stage,patient gender,age,race or body mass index(BMI)(P>0.05).In tumor tissue with high and low INPP4B expression,22 types of immune cells showed statistically significant differences(P<0.05);the INPP4B mRNA expression level was positively correlated with the number of 23 types of immune cells except T helper(Th)17 cells(r>0),among which all Th cells except natural killer(NK)CD56+cells were statistically significant(P<0.01);INPP4B was significantly correlated with matrix(r=0.475),immune cell infiltration(r=0.641)and tumor purity(r=0.599)in tumor tissue(P<0.01).INPP4B was correlated with TP53(r=0.287,P<0.01).The HE staining results showed that clear and complete lobular structure,neatly arranged cells and slight inflammatory cell infiltration were observed in liver tissue of the subjects in normal group;completely destroyed lobular structure,significant hepatocellular steatosis,massive inflammatory cell infiltration,and lesions such as ballooning degeneration and small cell hyperplasia in some cells were observed in HCC tissue of the patients in HCC-L,HCC-M and HCC-H groups,and the lower the HCC differentiation degree,the more severe the tissue destruction;The immunohistochemistry results showed that compared with normal group,the expression levels of Ki-67 protein in HCC tissue of the patients in HCC-L,HCC-M and HCC-H groups were significantly increased(P<0.01),and the lower the differentiation degree of the HCC patients,the higher the Ki-67 positive rate.Brownish-yellow granules evenly distributed in the cells and INPP4B protein was highly expressed in liver tissue of the subjects in normal group;compared with normal group,the expression levels of INPP4B protein in HCC tissue of the patients in HCC-L,HCC-M and HCC-H groups were significantly decreased(P<0.01),and the lower the differentiation degree of the HCC tissue,the lower the INPP4B positive rate.Conclusion:INPP4B is a protective factor for the prognosis of HCC patients;as a new tumor suppressor gene,INPP4B may become a potential target for new drug screening in HCC treatment.

Objective To investigate the predictive value of combined radiomic features derived from chest CT scans with clinical characteristics for epidermal growth factor receptor(EGFR)gene mutations in non-small cell lung cancer(NSCLC).Methods A multi-center case-control study was conducted on the clinical data and CT images of 1 070 NSCLC patients from the radiology departments of the 3 medical institutions between January 2013 and October 2023.The 719 NSCLC patients from the First Affiliated Hospital of Army Medical University were randomly divided into a training set and an internal validation set in a ratio of 7∶3;The 173 patients in the Eastern Theatre General Hospital and the 178 patients in Army Medical Centre of PLA were assigned into the external validation set 1 and 2,respectively.Least absolute shrinkage and selection operator(LASSO)regression was employed to identify the optimal radiomic features,which were subsequently used to construct a radiomics model.Univariate and multivariate logistic regression analyses were applied to identify clinical features associated with EGFR mutation,thereby developing a clinical model.The radiomic and clinical features were subsequently combined to develop a comprehensive model.All the 3 classification models were built using random forest(RF)machine learning.The area under curve(AUC),accuracy,sensitivity and specificity were utilized to evaluate the predictive performance of the models.Calibration curve was plotted to assess the goodness of fit of the comprehensive model,while decision curve analysis was performed to assess the clinical utility of the model.Results The AUC value of the radiomics model was 0.762 4(95%CI:0.692 4～0.825 1),0.745 4(95%CI:0.671 1～0.814 3),and 0.724 7(95%CI:0.639 7～0.801 6),respectively,in the internal validation set,external validation set 1,and external validation set 2;The AUC value of the clinical prediction model was 0.691 7(95%CI:0.627 9～0.757 6),0.652 5(95%CI:0.576 7～0.729 1),and 0.779 2(95%CI:0.712 5～0.847 3),respectively in the above sets in turn;The comprehensive model constructed based on clinical features and radiomic features showed the best predictive efficacy,with an AUC value of 0.818 0(95%CI:0.757 7～0.874 3),0.782 4(95%CI:0.703 1～0.848 2),and 0.796 6(95%CI:0.718 1～0.868 6),respectively in the above sets.Calibration curve analysis indicated that the comprehensive model had a good fit,while decision curve analysis revealed that the model provided a favorable net benefit.Conclusion Our comprehensive model constructed based on chest CT radiomic features and clinical characteristics shows superior predictive performance for EGFR gene mutations in NSCLC across multiple center datasets,which may be helpful for clinical decision-making for treatment strategies.

Objective To evaluate the predictive value of deep learning features from chest CT images combined with clinical and radiomics features for epidermal growth factor receptor(EGFR)mutations in non-small cell lung cancer(NSCLC).Methods This case-control study retrospectively analyzed clinical and imaging data of 1 070 NSCLC patients from radiology departments at three hospitals(January 2013 to October 2023).Patients were divided into:a training set(n=502)and internal validation set(n=217)via 7∶3 randomization of 719 cases from the First Affiliated Hospital of Army Medical University;external validation set 1(n=173)from General Hospital of Eastern Theater Command;external validation set 2(n=178)from Daping Hospital of Army Medical University.Deep learning features were extracted using a 2.5D convolutional neural network(CNN)with ResNet101 backbone,radiomics features were derived from CT images,and clinical risk factors were identified to construct models.An integrated model combined deep learning,clinical,and radiomics features.All four models were developed using random forest(RF)classifiers.Calibration curves assessed goodness-of-fit,and decision curve analysis(DCA)evaluated clinical utility.Results The deep learning model achieved AUCs of 0.833 7(95%CI:0.770 6～0.884 7),0.815 1(0.741 6～0.882 8),and 0.810 1(0.745 2～0.873 6)in the internal and two external validation sets,respectively.Clinical models yielded AUCs of 0.731 0(0.660 2～0.802 1),0.746 0(0.666 4～0.824 9),and 0.813 4(0.743 1～0.883 6);radiomics models showed AUCs of 0.762 4(0.692 4～0.825 1),0.745 4(0.671 1～0.814 3),and 0.724 7(0.639 7～0.801 6).The integrated model demonstrated optimal performance with AUCs of 0.905 5(0.857 0～0.945 4),0.832 7(0.763 3～0.896 4),and 0.889 0(0.834 4～0.934 3).DCA indicated significant net benefit for EGFR prediction at threshold probabilities of 0.15～0.85 using the integrated model.Conclusion Deep learning features from CT images effectively predict EGFR mutation status in NSCLC.The integrated model combining deep learning,clinical,and radiomics features further enhances predictive performance.

Objective The potential mechanism of hepatotoxicity induced by rhubarb was preliminarily explored by network pharmacology and verified by cell experiments.Methods Based on network pharmacology,component collection and target prediction are carried out through multiple databases.PPI network construction,GO enrichment analysis and KEGG pathway analysis were combined with software to systematically predict the mechanism of hepatotoxicity induced by rhubarb.The pathway information predicted by network pharmacology was verified by primary hepatocyte experiments and Western blot experiments.Results The results of network pharmacology showed that RH was the main component of hepatotoxicity induced by rhubarb.Seventeen core targets of hepatotoxicity induced by rhubarb were obtained.KEGG results suggested that DNA damage and apoptosis were one of the key mechanisms of hepatotoxicity induced by rhubarb.The results of primary hepatocytes and Western blot showed that RH could inhibit the viability of primary hepatocytes in a time-dose dependent manner.ABT and SFP can significantly reduce the toxicity of RH on primary liver cells in mice,and RFP can increase the toxicity of RH to mouse primary liver cells.Upregulation of γ-H2AX and PARP-1 protein in primary liver cells of mice after treatment with different concentrations of RH.Conclusion RH in rhubarb can significantly inhibit the viability of mouse primary hepatocytes,and its toxicity to mouse primary hepatocytes is mainly caused by the metabolic activation of RH by CYP 2C9.RH can activate PARP-1 protein,phosphorylate H2AX,induce DNA damage and apoptosis in mouse primary hepatocytes.

Objective This study aims to monitor the mRNA ratio of podocin to nephrin (PNR) in glomerular podocytes of early diabetic kidney disease (DKD) rat models. The feasibility of using PNR as an early diagnostic indicator for DKD was evaluated by comparing it with the urinary albumin-to-creatinine ratio (U-ACR). Additionally, the early intervention effects of valsartan and fosinopril sodium on DKD were compared. Methods The DKD rat model was established by caudal intravenous injection of streptozotocin (STZ) at a dosage of 60 mg/kg. The early changes in PNR and U-ACR were monitored and compared, followed by timely intervention with valsartan and fosinopril sodium. Hematoxylin and eosin staining (HE) was used to observe glomerular structure, while transmission electron microscopy examined the ultrastructure of glomerular podocytes. ResultsPNR reached the critical value(≥1) on day 9 after modeling, earlier than U-ACR, which reached the critical value(≥30 mg/g) on day 15. Intervention with valsartan and fosinopril sodium on day 9 after modeling significantly reduced U-ACR (P < 0.05), with low-dose valsartan showing better results than high-dose (P>0.05), while high-dose fosinopril sodium outperformed low-dose (P>0.05). Both low doses of valsartan and fosinopril sodium significantly reduced PNR (P<0.05), with no significant effect observed for high doses. The interventions with valsartan and fosinopril sodium improved and maintained glomerular structure and podocyte arrangement. ConclusionPNR changes earlier than U-ACR, indicating its potential as an early diagnostic marker for DKD in rats. Early intervention with valsartan and fosinopril sodium demonstrates a therapeutic effect on DKD in rats.

Objective:To investigate the levels of microRNA (miR) -106b-5p and miR-760 in the serum of early lung cancer patients, and the clinical value of the combination of them and low-dose spiral CT in the diagnosis of early lung cancer.Methods:Ninety early lung cancer patients (lung cancer group) who underwent treatment in Cangzhou People's Hospital of Hebei Province from January 2022 to March 2023 were collected as research subjects, meantime, 90 patients with benign pulmonary lesions (benign pulmonary nodules) diagnosed by pathology were selected as the control group. The levels of miR-106b-5p and miR-760 in the serum of two groups were compared, the results of low-dose spiral CT examination were analyzed; receiver operating characteristic curve was drawn to determine the optimal cut-off values of serum miR-106b-5p and miR-760; four grid table method was applied to analyze the diagnostic efficacy of serum miR-106b-5p, miR-760 combined with low-dose spiral CT for early lung cancer.Results:The level of miR-106b-5p in lung cancer group was higher than that in control group (1.39±0.31 vs. 1.04±0.30), serum miR-760 level was lower than that in control group (0.75±0.24 vs. 1.02±0.26), with statistically significant differences ( t=7.70, P<0.001; t=7.24, P<0.001). The area under curve (AUC) of miR-106b-5p, miR-760 and low-dose spiral CT in the diagnosis of early lung cancer was 0.83, 0.81 and 0.82, the accuracy was 76.67%, 77.22% and 81.67%, the sensitivity was 84.44%, 81.11% and 76.67%, and the specificity was 68.89%, 73.33% and 86.67%, respectively. The AUC, accuracy, sensitivity, and specificity of serum miR-106b-5p, miR-760 combined with low-dose spiral CT in diagnosing early lung cancer were 0.96, 90.00%, 94.44%, and 85.56%, respectively. The accuracy of the three combined diagnosis was higher than that of individual diagnosis of miR-106b-5p, miR-760 and low-dose spiral CT ( χ2=11.52, P=0.001; χ2=10.72, P=0.001; χ2=5.14, P=0.023), the sensitivity of the three combined diagnosis was higher than that of individual diagnosis of miR-106b-5p, miR-760 and low-dose spiral CT ( χ2=4.77, P=0.029; χ2=7.46, P=0.006; χ2=11.51, P=0.001), the specificity of the three combined diagnosis was higher than that of individual diagnosis of miR-106b-5p, miR-760 ( χ2=7.11, P=0.008; χ2=4.12, P=0.042) . Conclusion:The serum level of miR-106b-5p is significantly increased in early lung cancer patients, while the serum level of miR-760 is significantly reduced. The combination of miR-106b-5p, miR-760 and low-dose spiral CT has high diagnostic value for early lung cancer.

Objective:To explore the predictive value of the prognostic nutritional index (PNI) in concurrently infected patients with acute-on-chronic liver failure (ACLF).Methods:220 cases with ACLF diagnosed and treated at the First Affiliated Hospital of Xi'an Jiaotong University from January 2011 to December 2016 were selected. Patients were divided into an infection and non-infection group according to whether they had co-infections during the course of the disease. Clinical data differences were compared between the two groups of patients. Binary logistic regression analysis was used to screen out influencing factors related to co-infection. The receiver operating characteristic curve was used to evaluate the predictive value of PNI for ACLF co-infection. The measurement data between groups were compared using the independent sample t-test and the Mann-Whitney U rank sum test. The enumeration data were analyzed using the Fisher exact probability test or the Pearson χ2 test. The Pearson method was performed for correlation analysis. The independent risk factors for liver failure associated with co-infection were analyzed by multivariate logistic analysis. Results:There were statistically significant differences in ascites, hepatorenal syndrome, PNI score, and albumin between the infection and the non-infection group ( P ?

Objective:To evaluate the diagnostic accuracy of a noninvasive physiological parameter-based early sepsis screening model for elderly patients in comparison to the systemic inflammatory response syndrome(SIRS)and quick sequential organ failure assessment(qSOFA)scores.Methods:A retrospective study was conducted using data from the Medical Information Mart for Intensive Care Ⅳ(MIMIC-Ⅳ)database.The study focused on patients who were admitted to the intensive care unit(ICU)within 24 hours and were categorized into septic and non-septic groups based on the presence or absence of sepsis.Baseline data and patient outcomes were recorded.Additionally, the SIRS score and qSOFA scores within 24 hours of ICU admission were calculated.Physiological parameters that showed statistical significance in the univariate analysis included respiratory rate, heart rate, level of consciousness, body temperature, systolic blood pressure, and urine output.These parameters were then included in Logistic regression models.The specificity and sensitivity of the regression model for sepsis screening were calculated, and receiver operating characteristic(ROC)curves were plotted.The areas under the ROC curves(AUCs)of the screening model, SIRS, and qSOFA scoring systems were compared.Results:A total of 53 150 ICU hospitalization records were screened, and 23 681 patients with infection or suspected infection within 24 hours were included.Among them, 18 277 patients had sepsis.The 28-day mortality rate for septic patients was higher compared to non-septic patients(13.5% vs.5.1%, χ2=285.131, P<0.001).The baseline data within 24 hours showed significant differences between the two groups in terms of heart rate, respiratory rate, body temperature, state of consciousness, 24-hour urine output, and systolic blood pressure(all P<0.001).These variables were included in the regression equation: ∑β iX i=2.055+ 0.285(temperature: 0/1)+ 0.172(respiratory rate: 0/1)+ 0.073(heart rate: 0/1)+ 1.204(mental status: 0/1)-0.022(systolic blood pressure)+ 0.227(classification of urine output: 0/1/2), P=1/[1+ EXP(-∑β iX i)].The regression model diagnosed sepsis ROC area in young and middle-aged patients as 0.726(95% CI: 0.718 to 0.735), which was significantly higher than the SIRS score(0.585, 95% CI: 0.576 to 0.595)and the qSOFA score(0.676, 95% CI: 0.667 to 0.685)(both P<0.001).In elderly patients, the regression model diagnosed sepsis ROC area as 0.671(95% CI: 0.663 to 0.679), which was also significantly higher than the SIRS score(0.572, 95% CI: 0.563 to 0.580)and the qSOFA score(0.631, 95% CI: 0.623 to 0.639)(both P<0.001). Conclusions:The early sepsis diagnosis model, which utilizes noninvasive physiological parameters, has shown higher accuracy when compared to the SIRS and qSOFA scores.However, it is important to note that its accuracy is lower in elderly patients as compared to young and middle-aged patients.This indicates the necessity for further optimization of the model in order to improve its performance in diagnosing sepsis in the elderly.

Objective:To improve the standard and quality of clinical trials, the possible risks of Investigator-Initiated Clinical Trial(IIT) approvals based on drug supply and security were discussed and suggestions were put forward.Methods:According to the laws and regulations and literature review, concerning experimental drug supply and security during project negotiation, the risk points of IIT approvals were comprehensively analyzed and suggestions were put forward.Results:There are four main types of risks in assessing IIT approvals in terms of drug supply and security: drug entry and sales, drug promotion, discounts of observation fees, and concept confusion. Healthcare institutions should pay attention to and coordinate the IIT approvals.Conclusions:IIT is a supplement and extension of Industry Sponsored Trial(IST), which should be actively carried out by healthcare institutions while also paying attention to the security and risk prevention of drug supply, ensuring a standardized and orderly manner.