Objective:To develop an artificial intelligence (AI)-based automatic scoring model for magnetic resonance imaging-detected extramural vascular invasion (AI-mrEMVI) and evaluate its performance and prognostic value in patients with rectal cancer.Methods:In this multicenter retrospective cohort study, a total of 2 501 rectal cancer patients from seven centers between November 2012 and December 2020 were included and divided into completely independent training ( n=1 830) and validation ( n=671) cohorts. A nnUNet-based AI-mrEMVI scoring model was constructed. Manual mrEMVI scores assigned by two radiologists served as the reference standard for accessing the accuracy of the AI-mrEMVI scoring. Kaplan-Meier survival analysis and Cox regression were used to evaluate the prognostic stratification ability of the AI-mrEMVI scores. The concordance index (C-index) was calculated to evaluate prognostic performance. Results:In the validation cohort, the manual mrEMVI scores were 0-2 in 425 patients (63.3%), 3 in 89 (13.4%), and 4 in 157 (23.4%). The AI-mrEMVI model identified 0-2 in 375 patients (55.9%), 3 in 95 (14.2%), and 4 in 201 (30.0%), with an overall accuracy of 81.1% (544/671, 95% CI 77.9%-84.0%). The 3-year disease-free survival (DFS) rates for patients with AI-mrEMVI scores of 0-2, 3, and 4 were 85.2%, 70.0%, and 58.2%, respectively, and the 5-year overall survival (OS) rates were 87.2%, 81.6%, and 62.6%, respectively (DFS: χ2=48.74, P<0.001; OS: χ2=30.04, P<0.001). Multivariable Cox regression showed that for DFS, AI-mrEMVI scores of 3 and 4 were associated with hazard ratios ( HR) of 1.75 (95% CI 1.11-2.77, P=0.016) and 2.65 (95% CI 1.86-3.78, P<0.001), respectively. For OS, an AI-mrEMVI score of 4 was associated with an HR of 2.56 (95% CI 1.62-4.03, P<0.001). The C-index values of the AI-mrEMVI scoring model for predicting DFS and OS were 0.647 (95% CI 0.608-0.686) and 0.650 (95% CI 0.598-0.702), respectively. Conclusion:The proposed AI-mrEMVI automatic scoring model demonstrated high diagnostic accuracy and performed favorably in predicting DFS and OS prognostic risk in patients with rectal cancer.

Organoids have become an important technological platform in cancer research,but simulating the primary tumor tissue structure and function still presents problems.The development of gene-editing technology,especially when combined with tumor organoids,provides a new approach for accurately and comprehensively simulating the in vivo characteristics of tumor models.Introducing specific gene mutations or correcting mutations in tumor organoids through gene-editing technology can allow detailed analysis of the mechanisms of tumor initiation and progression,as well as exploring potential therapeutic targets,accelerating the drug-screening process,and providing new insights for personalized cancer treatment.This article reviews the formation of tumor organoids and the technical aspects of gene-editing strategies,emphasizing their unique applications and prospects in tumor organoids.We also propose that accurately simulating the in vivo microenvironment,promoting the standardization and stability of organoid gene-editing technology,and optimizing the efficiency of gene editing can accelerate the application of organoids in precision medicine research.

Objective To systematically construct patient-derived tumor organoid(PDO)and patient-derived xenograft(PDX)models of prostate cancer(PCa),and to explore the inhibitory effect and mechanism of gambogic acid(GA)on PCa.Methods The PubChem,SwissTargetPrediction,SuperPred,SEA,GeneCards,OMIM,and STRING databases,and the Venny 2.1.0 online website,Cytoscape 3.8.2,and DAVID software were used to construct a protein-protein interaction network.Gene ontology(GO)and kyoto encyclopedia of genes and genomes(KEGG)enrichment analyses were carried out,and visualization processing was performed to identify the targets and pathways of GA acting on PCa.GA was applied to PDOs and PCa cells(22Rv1,PC3,and DU145)for 48 hours and its effects on cell viability were assessed by CellTiter-Glo and CCK-8 assays.Changes in gene and protein levels of the targets were analyzed by quantitative real-time polymerase chain reaction and Western Blot,respectively.The PDX model was treated with GA and the tumor volume and weight were measured.Changes in expression levels of the targets in tumor tissues were detected by immunohistochemistry.Results Network pharmacology identified signal transducer and activator of transcription 3(STAT3)as the core target of GA inhibiting PCa,related to the hypoxia-inducible factor(HIF)-1α signaling pathway.GA reduced the viability of cells and PDOs and significantly down-regulated HIF-1α,STAT3,and P-STAT3 protein levels.In vivo experiments,tumor volume and weight were significantly reduced in the GA group,and immunohistochemistry showed that STAT3 and HIF-1α expression levels were decreased.Conclusions The clinically representative PDO and PDX models,combined with cell lines,verified the prediction result of network pharmacology,confirming a significant killing effect of GA on PCa,possibly via a mechanism related to the STAT3/HIF-1α signaling pathway.

Objective To investigate the expression levels and diagnostic value of long non coding RNA(lncRNA)DNA damage inducible transcript 4 like protein 4 antisense RNA1(lncRNA DDIT4-AS1)and long chain non coding RNA(lncRNA)radial spoke head protein 9 homolog 4(RSPH9-4)in serum of patients with bacterial meningitis.Methods A total of 94 patients with meningitis in the Fifth Hospital of Deyang City from May 2022 to May 2024 were regarded as the bacterial meningitis group.According to the severity of damage to the central nervous system caused by bacterial meningitis,they were further separated into a general group(n=63)and a severe group(n=31).94 patients with suspected meningitis upon admission but excluded meningitis after examination were selected as the non bacterial meningitis group.A total of 94 patients diagnosed with bacterial meningitis in the Fifth Hospital of Deyang City from May 2022 to May 2024 were selected as the bacterial meningitis group 94 healthy volunteers who underwent physicalexamination were as the control group.Real-time fluorescence quantitative PCR(qRT-PCR)method was applied to detect the expression levels of lncRNA DDIT4-AS1 and lncRNA RSPH9-4 in serum samples of all personnel.Spearman analysis was applied to analyze the correlation between serum levels of lncRNA DDIT4-AS1 and lncRNA RSPH9-4 with the severity of bacterial meningitis.Multivariate Logistic analysis was applied to analyze the influencing factors of bacterial meningitis.Receiver operating characteristic(ROC)curve was plotted to analyze the diagnostic value of serum lncRNA DDIT4-AS1 and lncRNA RSPH9-4 levels for bacterial meningitis.Results Compared with the control group,the expression levels of serum lncRNA DDIT4-AS1(1.35±0.27,1.67±0.35 vs 1.01±0.18)and lncRNA RSPH9-4(1.30±0.25,1.56±0.32 vs 1.00±0.19)were increased in non bacterial meningitis group and bacterial meningitis group(t=10.159,16.259;9.263,14.589),compared with the non bacterial meningitis group,the expression levels of serum lncRNA DDIT4-AS1 and lncRNA RSPH9-4 in the bacterial meningitis group were increased(t=7.019,6.208),and the differences were statistically significant(all P<0.05),respectively.Compared with the general group,the expression levels of serum lncRNA DDIT4-AS1(1.88±0.38 vs 1.56±0.31)and lncRNA RSPH9-4(1.79±0.35 vs 1.45±0.28)were increased in the severe group,and the differences were statistically significant(t=4.361,5.088,all P＜0.05).Spearman correlation analysis results showed that serum levels of lncRNA DDIT4-AS1,lncRNA RSPH9-4 were positively correlated with the severity of bacterial meningitis(r=0.524,0.548,all P<0.05).The expression levels of PCT,LDH and CRP in patients with bacterial meningitis were higher than those in patients without bacterial meningitis,and the differences were statistically significant(t=7.459,4.234,8.565,all P<0.05).Multivariate Logistic analysis showed that PCT,LDH,CRP,lncRNA DDIT4-AS1 and lncRNA RSPH9-4 were influencing factors for bacterial meningitis(Wald χ2=4.768～12.035,all P＜0.05).The receiver operating characteristic(ROC)curve results showed that the combined diagnosis of serum lncRNA DDIT4-AS1 and lncRNA RSPH9-4 levels for bacterial meningitis had a significantly larger area under the curve(AUC)than the diagnosis of lncRNA DDIT4-AS1 and lncRNA RSPH9-4 alone,and the differences were statistically significant(Z=2.426,2.545,all P<0.05).Conclusion The expression levels of serum lncRNA DDIT4-AS1 and lncRNA RSPH9-4 are elevated in patients with bacterial meningitis,and the combination of the two has high diagnostic value for the disease.

Objective To systematically construct patient-derived tumor organoid(PDO)and patient-derived xenograft(PDX)models of prostate cancer(PCa),and to explore the inhibitory effect and mechanism of gambogic acid(GA)on PCa.Methods The PubChem,SwissTargetPrediction,SuperPred,SEA,GeneCards,OMIM,and STRING databases,and the Venny 2.1.0 online website,Cytoscape 3.8.2,and DAVID software were used to construct a protein-protein interaction network.Gene ontology(GO)and kyoto encyclopedia of genes and genomes(KEGG)enrichment analyses were carried out,and visualization processing was performed to identify the targets and pathways of GA acting on PCa.GA was applied to PDOs and PCa cells(22Rv1,PC3,and DU145)for 48 hours and its effects on cell viability were assessed by CellTiter-Glo and CCK-8 assays.Changes in gene and protein levels of the targets were analyzed by quantitative real-time polymerase chain reaction and Western Blot,respectively.The PDX model was treated with GA and the tumor volume and weight were measured.Changes in expression levels of the targets in tumor tissues were detected by immunohistochemistry.Results Network pharmacology identified signal transducer and activator of transcription 3(STAT3)as the core target of GA inhibiting PCa,related to the hypoxia-inducible factor(HIF)-1α signaling pathway.GA reduced the viability of cells and PDOs and significantly down-regulated HIF-1α,STAT3,and P-STAT3 protein levels.In vivo experiments,tumor volume and weight were significantly reduced in the GA group,and immunohistochemistry showed that STAT3 and HIF-1α expression levels were decreased.Conclusions The clinically representative PDO and PDX models,combined with cell lines,verified the prediction result of network pharmacology,confirming a significant killing effect of GA on PCa,possibly via a mechanism related to the STAT3/HIF-1α signaling pathway.

Organoids have become an important technological platform in cancer research,but simulating the primary tumor tissue structure and function still presents problems.The development of gene-editing technology,especially when combined with tumor organoids,provides a new approach for accurately and comprehensively simulating the in vivo characteristics of tumor models.Introducing specific gene mutations or correcting mutations in tumor organoids through gene-editing technology can allow detailed analysis of the mechanisms of tumor initiation and progression,as well as exploring potential therapeutic targets,accelerating the drug-screening process,and providing new insights for personalized cancer treatment.This article reviews the formation of tumor organoids and the technical aspects of gene-editing strategies,emphasizing their unique applications and prospects in tumor organoids.We also propose that accurately simulating the in vivo microenvironment,promoting the standardization and stability of organoid gene-editing technology,and optimizing the efficiency of gene editing can accelerate the application of organoids in precision medicine research.

Objective:To develop an artificial intelligence (AI)-based automatic scoring model for magnetic resonance imaging-detected extramural vascular invasion (AI-mrEMVI) and evaluate its performance and prognostic value in patients with rectal cancer.Methods:In this multicenter retrospective cohort study, a total of 2 501 rectal cancer patients from seven centers between November 2012 and December 2020 were included and divided into completely independent training ( n=1 830) and validation ( n=671) cohorts. A nnUNet-based AI-mrEMVI scoring model was constructed. Manual mrEMVI scores assigned by two radiologists served as the reference standard for accessing the accuracy of the AI-mrEMVI scoring. Kaplan-Meier survival analysis and Cox regression were used to evaluate the prognostic stratification ability of the AI-mrEMVI scores. The concordance index (C-index) was calculated to evaluate prognostic performance. Results:In the validation cohort, the manual mrEMVI scores were 0-2 in 425 patients (63.3%), 3 in 89 (13.4%), and 4 in 157 (23.4%). The AI-mrEMVI model identified 0-2 in 375 patients (55.9%), 3 in 95 (14.2%), and 4 in 201 (30.0%), with an overall accuracy of 81.1% (544/671, 95% CI 77.9%-84.0%). The 3-year disease-free survival (DFS) rates for patients with AI-mrEMVI scores of 0-2, 3, and 4 were 85.2%, 70.0%, and 58.2%, respectively, and the 5-year overall survival (OS) rates were 87.2%, 81.6%, and 62.6%, respectively (DFS: χ2=48.74, P<0.001; OS: χ2=30.04, P<0.001). Multivariable Cox regression showed that for DFS, AI-mrEMVI scores of 3 and 4 were associated with hazard ratios ( HR) of 1.75 (95% CI 1.11-2.77, P=0.016) and 2.65 (95% CI 1.86-3.78, P<0.001), respectively. For OS, an AI-mrEMVI score of 4 was associated with an HR of 2.56 (95% CI 1.62-4.03, P<0.001). The C-index values of the AI-mrEMVI scoring model for predicting DFS and OS were 0.647 (95% CI 0.608-0.686) and 0.650 (95% CI 0.598-0.702), respectively. Conclusion:The proposed AI-mrEMVI automatic scoring model demonstrated high diagnostic accuracy and performed favorably in predicting DFS and OS prognostic risk in patients with rectal cancer.

Objective To investigate the expression levels and diagnostic value of long non coding RNA(lncRNA)DNA damage inducible transcript 4 like protein 4 antisense RNA1(lncRNA DDIT4-AS1)and long chain non coding RNA(lncRNA)radial spoke head protein 9 homolog 4(RSPH9-4)in serum of patients with bacterial meningitis.Methods A total of 94 patients with meningitis in the Fifth Hospital of Deyang City from May 2022 to May 2024 were regarded as the bacterial meningitis group.According to the severity of damage to the central nervous system caused by bacterial meningitis,they were further separated into a general group(n=63)and a severe group(n=31).94 patients with suspected meningitis upon admission but excluded meningitis after examination were selected as the non bacterial meningitis group.A total of 94 patients diagnosed with bacterial meningitis in the Fifth Hospital of Deyang City from May 2022 to May 2024 were selected as the bacterial meningitis group 94 healthy volunteers who underwent physicalexamination were as the control group.Real-time fluorescence quantitative PCR(qRT-PCR)method was applied to detect the expression levels of lncRNA DDIT4-AS1 and lncRNA RSPH9-4 in serum samples of all personnel.Spearman analysis was applied to analyze the correlation between serum levels of lncRNA DDIT4-AS1 and lncRNA RSPH9-4 with the severity of bacterial meningitis.Multivariate Logistic analysis was applied to analyze the influencing factors of bacterial meningitis.Receiver operating characteristic(ROC)curve was plotted to analyze the diagnostic value of serum lncRNA DDIT4-AS1 and lncRNA RSPH9-4 levels for bacterial meningitis.Results Compared with the control group,the expression levels of serum lncRNA DDIT4-AS1(1.35±0.27,1.67±0.35 vs 1.01±0.18)and lncRNA RSPH9-4(1.30±0.25,1.56±0.32 vs 1.00±0.19)were increased in non bacterial meningitis group and bacterial meningitis group(t=10.159,16.259;9.263,14.589),compared with the non bacterial meningitis group,the expression levels of serum lncRNA DDIT4-AS1 and lncRNA RSPH9-4 in the bacterial meningitis group were increased(t=7.019,6.208),and the differences were statistically significant(all P<0.05),respectively.Compared with the general group,the expression levels of serum lncRNA DDIT4-AS1(1.88±0.38 vs 1.56±0.31)and lncRNA RSPH9-4(1.79±0.35 vs 1.45±0.28)were increased in the severe group,and the differences were statistically significant(t=4.361,5.088,all P＜0.05).Spearman correlation analysis results showed that serum levels of lncRNA DDIT4-AS1,lncRNA RSPH9-4 were positively correlated with the severity of bacterial meningitis(r=0.524,0.548,all P<0.05).The expression levels of PCT,LDH and CRP in patients with bacterial meningitis were higher than those in patients without bacterial meningitis,and the differences were statistically significant(t=7.459,4.234,8.565,all P<0.05).Multivariate Logistic analysis showed that PCT,LDH,CRP,lncRNA DDIT4-AS1 and lncRNA RSPH9-4 were influencing factors for bacterial meningitis(Wald χ2=4.768～12.035,all P＜0.05).The receiver operating characteristic(ROC)curve results showed that the combined diagnosis of serum lncRNA DDIT4-AS1 and lncRNA RSPH9-4 levels for bacterial meningitis had a significantly larger area under the curve(AUC)than the diagnosis of lncRNA DDIT4-AS1 and lncRNA RSPH9-4 alone,and the differences were statistically significant(Z=2.426,2.545,all P<0.05).Conclusion The expression levels of serum lncRNA DDIT4-AS1 and lncRNA RSPH9-4 are elevated in patients with bacterial meningitis,and the combination of the two has high diagnostic value for the disease.

Objective To construct a patient-derived pancreatic tumor organoid(PDO)and evaluate its effectiveness.Methods We collected fresh surgical specimens from pancreatic cancer patients for PDO culture and compared the pathological and genetic characteristics of the PDO model with those of primary tumors.The PDO model was used to evaluate the efficacy of clinical chemotherapy drugs,and the effectiveness of the model was assessed.Results A PDO model of pancreatic cancer was successfully established.Histomorphological analysis indicated that the PDO model maintained the basic pathological characteristics of the primary tumor.Whole-exon sequencing showed that both the organoids and original tumor tissue remained consistent in their gene mutation type and characteristics.Drug screening tests revealed that the PDO model had good sensitivity to gemcitabine and irinotecan.Conclusions A pancreatic cancer PDO was successfully constructed that reflected the histological and genetic characteristics of the original tumor.The model was shown to be effective for drug sensitivity experiments in vitro and is expected to have implications for precision medicine assays.

Objective:To construct a representative index system for evaluating pediatric orthopedic nursing quality, providing a basis for hospital pediatric orthopedic nursing quality assessment and monitoring.Methods:From April to July 2023, using the "structure-process-outcome" three-dimensional quality structure model as the theoretical framework, a literature review was conducted, and an item pool was formulated. Through two rounds of Delphi method expert consultations, the hierarchical analysis method was finally employed to determine the indicators and their weights at each level.Results:The effective recovery rates of the questionnaire of the two rounds of expert consultations were 100% (20/20), the authority coefficients of experts were 0.87 and 0.88, the coefficients of variation were 0.00 to 0.27 and 0.00 to 0.24. The Kendell harmony coefficients of the second and third indicators in the two rounds of inquiry were 0.140, 0.166 and 0.192, 0.161(all P<0.05). The final pediatric orthopedic nursing quality evaluation index system included 3 primary indicators, 21 secondary indicators and 83 tertiary indicators. Among the primary indicators, the weight of process quality was the highest at 0.493 4, followed by outcome quality at 0.310 8, and the lowest was structural quality at 0.195 8. In the secondary indicators, "assessment criteria of limb blood circulation" had the highest weight at 0.099 8. Conclusions:The constructed pediatric orthopedic nursing quality evaluation index system covers key aspects and is more operationally feasible. It provides better guidance for nursing interventions and quality control.