Objective:To construct a machine learning model based on localization CT-based radiomics, dosiomics and clinical features for predicting radiotherapy response in non-small cell lung cancer (NSCLC) and validate its application value.Methods:A retrospective case series study was conducted. A total of 138 NSCLC patients who received radiotherapy at the Affiliated Hospital of Jining Medical University from January 2016 to December 2022 were selected. The efficacy was evaluated according to the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1, and the patients were stratified according to the objective remission (complete remission+partial remission). Random stratified sampling was used to divide the 138 patients into a training group (96 cases) and an internal validation group (42 cases) at a ratio of 7∶3. Additionally, 33 patients who received radiotherapy at Jining Cancer Hospital from January 2019 to December 2022 were included as the external validation group. Based on the pre-radiotherapy data of the radiotherapy planning system, PyRadiomics software package was used to extract 107 radiomics features and 107 dosiomics features for each patient. Pearson correlation analysis and LASSO regression analysis were used for dimensionality reduction screening; the final selected features were weighted and integrated to generate radiomics-dosiomics scores (RDS), which were then input into logistic regression (LR), support vector machine (SVM), extremely randomized forest (Extra Trees), K-nearest neighbor algorithm (KNN), lightweight gradient boosting machine (Light GBM), and multi-layer perceptron (MLP) machine learning algorithms to construct 6 radiomics-dosiomics models (RDM) for predicting the objective remission. RECIST 1.1 standard was used to evaluate objective remission as the gold standard, receiver operating characteristic (ROC) curve of 6 RDM for predicting objective remission was plotted, and the optimal algorithm for RDM was selected. Univariate and multivariate logistic regression were performed on demographic characteristics, hematological indicators and radiotherapy parameters of the training group to screen independent risk factors for NSCLC patients who received radiotherapy but did not achieve objective remission. These factors were input into the optimal machine learning algorithm to construct a clinical model (CM). Combined with features from RDS and CM, the clinical feature-radiomics-dosiomics combined model (CRDM) was established, and the nomogram of the model for predicting objective remission in NSCLC patients with radiotherapy was drawn. ROC curves were used to evaluate the efficacy of CM, RDM and CRDM in predicting the objective remission in NSCLC patients with radiotherapy in the training group, internal validation group and external validation group.Results:Four radiomics features (including grayscale variance, low grayscale long-range operation emphasis, low grayscale area emphasis, and small area low grayscale area emphasis, all of which were texture features) and 6 dosiomics features [including 1 first-order feature (robust mean absolute deviation), 4 texture features (grayscale non-uniformity, large area emphasis, large area high grayscale emphasis, contrast) and 1 shape feature (shortest axis length)] were selected. ROC curve analysis showed that the area under the curve (AUC) of the RDM constructed using SVM algorithm for judging the objective remission in the training group and the internal validation group was 0.907 (95% CI: 0.836-0.977) and 0.822 (95% CI: 0.685-0.959), which were higher than RDM constructed using other algorithms, and the sensitivity (96.2% and 91.7%), specificity (78.6% and 76.7%) and accuracy (83.3% and 81.0%) at the optimal cut-off values were all higher. Considering the stability and generalization ability of the model, SVM algorithm was ultimately used to construct RDM, CM and CRDM uniformly. Based on training group data, univariate and multivariate logistic regression analysis showed that elevated platelet-to-lymphocyte ratio (PLR) ( OR = 1.001, 95% CI: 1.000-1.003, P = 0.035) and increased target volume of radiotherapy plan ( OR = 1.001, 95% CI: 1.000-1.001, P = 0.008) were independent risk factors for failure to achieve objective remission. ROC curve analysis showed that in the training group and the internal validation group, the AUC of CRDM predicting objective remission were 0.914 (95% CI: 0.856-0.972) and 0.864 (95% CI: 0.754-0.974), respectively, which were better than CM [AUC were 0.735 (95% CI: 0.612-0.857) and 0.697 (95% CI: 0.507-0.888)] and RDM, respectively. In the external validation group, the AUC of CRDM, CM and RDM were 0.778 (95% CI: 0.500-1.000), 0.667 (95% CI: 0.434-0.899) and 0.741 (95% CI: 0.463-1.000), respectively. Conclusions:The CRDM constructed by combining radiomics, dosiomics and clinical features can comprehensively and accurately evaluate the radiotherapy response of NSCLC patients, and may have important clinical application value in achieving precision medicine and optimizing treatment strategies.

In the past decade, real-world data (RWD) research has undergone significant transformations due to data aggregation and processing technologies. However, there is still a lack of consensus regarding the scope of RWD applications and the value of real-world evidence (RWE). This study briefly outlined the origins of the concept of RWD study and its early research scope to promote further development in this area. We also reviewed the understanding of RWD applications and research models from the five perspectives of healthcare professionals, medical institutions, decision-making departments, cross-regional cooperation model, and the practice of the One-Health model. Finally, we systematically summarized the renewed understanding of the value of RWE while looking ahead to the challenges and future developments in this field.

Objective To investigate the protective effect of Gynostemma pentaphyllum on memory of individuals rapidly ascending to high altitudes.Methods Twenty-one healthy subjects were randomly divided into a G.pentaphyllum food group(n=12)and a control group(n=9).The first group consumed G.pentaphyllum food for seven consecutive days while the control group received placebos.Both groups ascended from the plains to an altitude of 3600 m.Memory function was assessed using the matching memory and sequential memory tests of a cognitive evaluation system on day 1 and day 7 on the plains,and at 24 and 48 h after ascending to the high altitude.Scores of acute mountain sickness symptoms were also recorded.Results After 24 h of stay at the high altitude,the score of headache of the G.pentaphyllum food group was significantly lower than that of the control group(P＜0.05).Cognitive test results showed that the matching memory accuracy and sequential memory accuracy of the control group at 24 and 48 h were significantly lower than those on the plains(P＜0.05).In contrast,the G.pentaphyllum food group performed significantly better than the control group in these metrics(P＜0.05).Conclusion Regular consumption of G.pentaphyllum food can effectively alleviate headache symptoms in individuals rapidly ascending to high altitudes and mitigate the decline in working memory,short-term memory,and memory spans caused by acute hypoxic exposure.

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection，characterized by high mortality rate.The pathological mechanisms of sepsis-induced organ failure are highly complex，including multiple processes such as abnormal immune responses，hemodynamic alterations，and severe endothelial dysfunction.Chromogranin A（Cg A），an acidic glycoprotein belonging to the granin family，serves as a precursor for various bioactive peptides，and is involved in diverse physiological processes，including inflammatory regulation，tissue repair，vascular function modulation，and glucose/lipid metabolism.Recent studies have revealed that Cg A and its derived peptides not only participate in the pathological progression of sepsis，but also exhibit significant correlations with the severity of organ injury. Consequently，Cg A has garnered attention for its potential role in the clinical diagnosis and prognostic evaluation of sepsis.This article provides a comprehensive review of the structure and functions of Cg A，as well as current research advances and clinical applications in sepsis.

Exosomes are a kind of nanovesicles with a wide range of chemical components，which are enriched in a variety of bioactive molecules，such as lipids，proteins，nucleic acids，etc. Exosomes carry biologically active molecules that transmit different messages between cells，and play a role in human physiological and pathological processes. Compared with synthetic carriers such as liposomes and nanoparticles，by virtue of their natural endogenous attributes and cell-specific targeting capabilities，exosomes have broad application prospects in the fields of early disease diagnosis marker screening and targeted therapy drug carriers. This article reviews the role of exosomes in common children's diseases and their research progress，providing new ideas for pediatric clinicians to explore disease diagnosis and treatment.

Objective To investigate the gene expression and regulatory mechanisms of mouse embryonic fibroblasts (MEFs) under inflammatory conditions, aiming to elucidate the role of MEFs in inflammatory responses and provide a foundation for discovering anti-inflammatory drugs that act by modulating MEF function. Methods MEFs cultured in vitro were divided into the following groups: lipopolysaccharides (LPS)-treated group, inflammatory conditioned medium (CM)-treated group, and control group, which were treated with LPS, CM, and equal volume solvent, respectively. Transcriptome sequencing was used to analyze the effects of two stimuli on gene expression profile of MEFs. Real time fluorescence quantitative PCR (RT-qPCR) was employed to verify the transcription levels of highly expressed genes of MEFs induced by CM. ELISA was performed to determine the concentrations of cytokines in cell supernatants. Finally, the regulatory effects of CM on the activation of signaling pathways in MEFs were analyzed by immunoblotting. Results Transcriptome analysis showed that both LPS and CM induced the transcription of a large number of genes in MEFs. Compared with LPS, CM potentiated the mRNA transcription of some acute phase proteins, inflammatory cytokines, chemokines, matrix metalloproteinases (MMP), prostaglandin synthetases, and colony-stimulating factors. The transcriptome analysis was verified by RT-qPCR. The results of ELISA showed that CM treatment significantly increased the secretion of interleukin 6 (IL-6), C-C motif chemokine ligand (CCL2), and C-X-C motif chemokine ligand (CXCL1) by MEFs compared with LPS. Mechanism study showed that both LPS and CM induced the phosphorylation of nuclear factor-κB p65 (NF-κB p65), p38 mitogen-activated protein kinase (p38 MAPK), extracellular regulated protein kinases 1/2 (ERK1/2), and TANK-binding kinase (TBK) in MEFs, and CM strongly stimulated the phosphorylation of signal transducer and activator of transcription 3 (STAT3) in MEFs. Conclusion Both LPS and CM can induce transcription and protein secretion of various inflammation-related genes in MEFs. CM can partly enhance LPS-induced activation of MEFs, and the mechanism may be related to the enhancement effect of CM on the activation STAT3 signaling pathway.
Animals ; Fibroblasts/immunology* ; Mice ; Lipopolysaccharides/pharmacology* ; Inflammation/metabolism* ; Signal Transduction/drug effects* ; Gene Expression Regulation/drug effects* ; Cytokines/genetics* ; Culture Media, Conditioned/pharmacology* ; Cells, Cultured

Objective:To explore the role and mechanism of Ras homolog gene family member E (RhoE) gene in myocardial fibrosis in diabetic cardiomyopathy.Methods:Wild-type SD rats were intraperitoneally injected with streptozotocin solution (STZ, 70 mg/kg) and an equal volume of sodium citrate solution to establish the type 1 diabetes mellitus (T1DM) group ( n=15) and the T1DM control group ( n=15), respectively. db/db spontaneous type 2 diabetes mellitus (T2DM) mice and wild-type C57BL/6J mice were conventionally housed for 8 weeks to establish the T2DM group ( n=5) and the T2DM control group ( n=5), respectively. Heterozygote SD rats with systemic knockout of the RhoE gene were intraperitoneally injected with STZ solution (70 mg/kg) and an equal volume of sodium citrate solution to establish the RhoE knockout T1DM group ( n=5) and the RhoE knockout control group ( n=5), respectively. Wild-type SD rats were injected with RhoE-overexpressing adeno-associated virus 9 through tail vein and intraperitoneally injected with STZ solution (70 mg/kg) to establish the RhoE overexpression T1DM group ( n=5), while wild-type SD rats injected with negative control virus through tail vein and intraperitoneally injected with an equal volume of sodium citrate solution served as the RhoE overexpression control group ( n=5). After successful modeling, all animals in each group were conventionally housed for an additional 6 or 8 weeks, which marked the experimental endpoint. At the experimental endpoint, echocardiography was performed to assess cardiac function of animals in each group, and left ventricular ejection fraction (LVEF) and the ratio of early to late diastolic transmitral flow velocity (E/A ratio) were analysed. Masson staining was used to detect collagen fiber deposition in myocardial tissue of animals in each group. Western blot analysis was conducted to detect the expression levels of RhoE gene, type Ⅰ collagen, type Ⅲ collagen, Smad2/3, and phosphorylated Smad2/3 protein in myocardial tissue of rats. Enzyme-linked immunosorbent assay was used to measure the levels of transforming growth factor-β1 (TGF-β1) in serum of rats. Results:Compared with their respective control groups, the expression of RhoE in the heart tissues of mice in the T2DM group and rats in the T1DM group was significantly downregulated, and the deposition of collagen fibers was more significant ( P<0.05), and LVEF and E/A ratio were lower (all P<0.05). Compared with the T1DM group, the phosphorylation level of Smad2/3、the levels of type Ⅰ collagen and type Ⅲ collagen in myocardial tissue and the level of TGF-β1 in serum were higher in the RhoE knockout T1DM group (all P<0.05). Additionally, rats in the RhoE overexpression T1DM group had higher LVEF and E/A ratios (both P<0.05) and less collagen fiber deposition ( P<0.05) compared with the T1DM group. Conclusions:Myocardial fibrosis induced by diabetes mellitus activates TGF-β1/Smads signaling pathway by inhibiting RhoE gene expression. Myocardial targeting overexpression of the RhoE mediated by adeno-associated virus 9 can alleviate myocardial fibrosis and improve cardiac function in rats with diabetic cardiomyopathy.

In the past decade, real-world data (RWD) research has undergone significant transformations due to data aggregation and processing technologies. However, there is still a lack of consensus regarding the scope of RWD applications and the value of real-world evidence (RWE). This study briefly outlined the origins of the concept of RWD study and its early research scope to promote further development in this area. We also reviewed the understanding of RWD applications and research models from the five perspectives of healthcare professionals, medical institutions, decision-making departments, cross-regional cooperation model, and the practice of the One-Health model. Finally, we systematically summarized the renewed understanding of the value of RWE while looking ahead to the challenges and future developments in this field.

Objective:To construct a machine learning model based on localization CT-based radiomics, dosiomics and clinical features for predicting radiotherapy response in non-small cell lung cancer (NSCLC) and validate its application value.Methods:A retrospective case series study was conducted. A total of 138 NSCLC patients who received radiotherapy at the Affiliated Hospital of Jining Medical University from January 2016 to December 2022 were selected. The efficacy was evaluated according to the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1, and the patients were stratified according to the objective remission (complete remission+partial remission). Random stratified sampling was used to divide the 138 patients into a training group (96 cases) and an internal validation group (42 cases) at a ratio of 7∶3. Additionally, 33 patients who received radiotherapy at Jining Cancer Hospital from January 2019 to December 2022 were included as the external validation group. Based on the pre-radiotherapy data of the radiotherapy planning system, PyRadiomics software package was used to extract 107 radiomics features and 107 dosiomics features for each patient. Pearson correlation analysis and LASSO regression analysis were used for dimensionality reduction screening; the final selected features were weighted and integrated to generate radiomics-dosiomics scores (RDS), which were then input into logistic regression (LR), support vector machine (SVM), extremely randomized forest (Extra Trees), K-nearest neighbor algorithm (KNN), lightweight gradient boosting machine (Light GBM), and multi-layer perceptron (MLP) machine learning algorithms to construct 6 radiomics-dosiomics models (RDM) for predicting the objective remission. RECIST 1.1 standard was used to evaluate objective remission as the gold standard, receiver operating characteristic (ROC) curve of 6 RDM for predicting objective remission was plotted, and the optimal algorithm for RDM was selected. Univariate and multivariate logistic regression were performed on demographic characteristics, hematological indicators and radiotherapy parameters of the training group to screen independent risk factors for NSCLC patients who received radiotherapy but did not achieve objective remission. These factors were input into the optimal machine learning algorithm to construct a clinical model (CM). Combined with features from RDS and CM, the clinical feature-radiomics-dosiomics combined model (CRDM) was established, and the nomogram of the model for predicting objective remission in NSCLC patients with radiotherapy was drawn. ROC curves were used to evaluate the efficacy of CM, RDM and CRDM in predicting the objective remission in NSCLC patients with radiotherapy in the training group, internal validation group and external validation group.Results:Four radiomics features (including grayscale variance, low grayscale long-range operation emphasis, low grayscale area emphasis, and small area low grayscale area emphasis, all of which were texture features) and 6 dosiomics features [including 1 first-order feature (robust mean absolute deviation), 4 texture features (grayscale non-uniformity, large area emphasis, large area high grayscale emphasis, contrast) and 1 shape feature (shortest axis length)] were selected. ROC curve analysis showed that the area under the curve (AUC) of the RDM constructed using SVM algorithm for judging the objective remission in the training group and the internal validation group was 0.907 (95% CI: 0.836-0.977) and 0.822 (95% CI: 0.685-0.959), which were higher than RDM constructed using other algorithms, and the sensitivity (96.2% and 91.7%), specificity (78.6% and 76.7%) and accuracy (83.3% and 81.0%) at the optimal cut-off values were all higher. Considering the stability and generalization ability of the model, SVM algorithm was ultimately used to construct RDM, CM and CRDM uniformly. Based on training group data, univariate and multivariate logistic regression analysis showed that elevated platelet-to-lymphocyte ratio (PLR) ( OR = 1.001, 95% CI: 1.000-1.003, P = 0.035) and increased target volume of radiotherapy plan ( OR = 1.001, 95% CI: 1.000-1.001, P = 0.008) were independent risk factors for failure to achieve objective remission. ROC curve analysis showed that in the training group and the internal validation group, the AUC of CRDM predicting objective remission were 0.914 (95% CI: 0.856-0.972) and 0.864 (95% CI: 0.754-0.974), respectively, which were better than CM [AUC were 0.735 (95% CI: 0.612-0.857) and 0.697 (95% CI: 0.507-0.888)] and RDM, respectively. In the external validation group, the AUC of CRDM, CM and RDM were 0.778 (95% CI: 0.500-1.000), 0.667 (95% CI: 0.434-0.899) and 0.741 (95% CI: 0.463-1.000), respectively. Conclusions:The CRDM constructed by combining radiomics, dosiomics and clinical features can comprehensively and accurately evaluate the radiotherapy response of NSCLC patients, and may have important clinical application value in achieving precision medicine and optimizing treatment strategies.

Objective:To explore the role and mechanism of Ras homolog gene family member E (RhoE) gene in myocardial fibrosis in diabetic cardiomyopathy.Methods:Wild-type SD rats were intraperitoneally injected with streptozotocin solution (STZ, 70 mg/kg) and an equal volume of sodium citrate solution to establish the type 1 diabetes mellitus (T1DM) group ( n=15) and the T1DM control group ( n=15), respectively. db/db spontaneous type 2 diabetes mellitus (T2DM) mice and wild-type C57BL/6J mice were conventionally housed for 8 weeks to establish the T2DM group ( n=5) and the T2DM control group ( n=5), respectively. Heterozygote SD rats with systemic knockout of the RhoE gene were intraperitoneally injected with STZ solution (70 mg/kg) and an equal volume of sodium citrate solution to establish the RhoE knockout T1DM group ( n=5) and the RhoE knockout control group ( n=5), respectively. Wild-type SD rats were injected with RhoE-overexpressing adeno-associated virus 9 through tail vein and intraperitoneally injected with STZ solution (70 mg/kg) to establish the RhoE overexpression T1DM group ( n=5), while wild-type SD rats injected with negative control virus through tail vein and intraperitoneally injected with an equal volume of sodium citrate solution served as the RhoE overexpression control group ( n=5). After successful modeling, all animals in each group were conventionally housed for an additional 6 or 8 weeks, which marked the experimental endpoint. At the experimental endpoint, echocardiography was performed to assess cardiac function of animals in each group, and left ventricular ejection fraction (LVEF) and the ratio of early to late diastolic transmitral flow velocity (E/A ratio) were analysed. Masson staining was used to detect collagen fiber deposition in myocardial tissue of animals in each group. Western blot analysis was conducted to detect the expression levels of RhoE gene, type Ⅰ collagen, type Ⅲ collagen, Smad2/3, and phosphorylated Smad2/3 protein in myocardial tissue of rats. Enzyme-linked immunosorbent assay was used to measure the levels of transforming growth factor-β1 (TGF-β1) in serum of rats. Results:Compared with their respective control groups, the expression of RhoE in the heart tissues of mice in the T2DM group and rats in the T1DM group was significantly downregulated, and the deposition of collagen fibers was more significant ( P<0.05), and LVEF and E/A ratio were lower (all P<0.05). Compared with the T1DM group, the phosphorylation level of Smad2/3、the levels of type Ⅰ collagen and type Ⅲ collagen in myocardial tissue and the level of TGF-β1 in serum were higher in the RhoE knockout T1DM group (all P<0.05). Additionally, rats in the RhoE overexpression T1DM group had higher LVEF and E/A ratios (both P<0.05) and less collagen fiber deposition ( P<0.05) compared with the T1DM group. Conclusions:Myocardial fibrosis induced by diabetes mellitus activates TGF-β1/Smads signaling pathway by inhibiting RhoE gene expression. Myocardial targeting overexpression of the RhoE mediated by adeno-associated virus 9 can alleviate myocardial fibrosis and improve cardiac function in rats with diabetic cardiomyopathy.