Objective:To investigate the magnetic resonance imaging (MRI) features of pediatric and adolescent mediastinal T-lymphoblastic lymphoma (T-LBL) and to evaluate their predictive value for early treatment response.Methods:A retrospective, multicenter case series study was conducted on 49 pediatric and adolescent patients diagnosed with mediastinal T-LBL between September 2020 and May 2024 at the Fifth Affiliated Hospital of Zhengzhou University, Beijing Gaobo Boren Hospital, and Henan Cancer Hospital.All patients underwent chest MRI, including conventional MRI sequences and diffusion-weighted imaging.Tumor imaging characteristics were analyzed, and quantitative parameters such as minimum apparent diffusion coefficient (ADCmin), maximum ADC (ADCmax), and mean ADC (ADCmean) were measured.Treatment response was evaluated 15 days post-treatment.The patients were divided into a response group (complete or partial response, 26 cases) and a non-response group (progressive disease or minor response, 23 cases).The relationship between MRI features and treatment response was analyzed.The intraclass correlation coefficient was used to assess inter-reader agreement, and independent sample t-tests and chi-square tests were employed to compare differences between groups.Receiver operating characteristic (ROC) curve analysis was conducted to evaluate the predictive performance of imaging parameters. Results:Significant differences were observed between the response and non-response groups in ADC values [ADCmin (0.80±0.41)×10 -3 mm 2/s vs.(1.23±0.70)×10 -3 mm 2/s, ADCmax (1.14±0.48)×10 -3 mm 2/s vs.(1.92±0.77)×10 -3 mm 2/s, ADCmean (0.98±0.42)×10 -3 mm 2/s vs.(1.56±0.74)×10 -3 mm 2/s] and the maximum tumor diameter was [(11.92±3.61) cm vs.(8.17±2.46) cm] (all P<0.05).ROC curve analysis showed that ADCmax had the highest predictive efficiency for treatment response, with an area under the curve (AUC) of 0.853 (95% CI: 0.790-0.910), sensitivity of 92.3%, and specificity of 65.2%.The AUC for the maximum tumor diameter was 0.814, demonstrating its excellent predictive performance. Conclusions:MRI features, particularly ADC values and the maximum tumor diameter, can effectively predict treatment response in pediatric and adolescent mediastinal T-LBL.

The knowledge and experience of medical practitioners in the diagnosis and treatment of diseases throughout history are mostly reflected in the description and analysis of relevant clinical events.The diagnosis and treatment thinking and cognitive reasoning process among the knowledge has dynamic and complex characteristics in time and space.However,the current exploration of ancient doctors' diagnosis and treatment experience of diseases and syndromes is mainly focuses on the academic evolution of the entire historical time line,and lacks the exploration of the concept of time and its medical relevance in ancient books.It mainly focuses on entity knowledge,and lacks the presentation of temporal dynamic cognitive logic.Moreover,the research primarily focuses on the study of specific terms in ancient Chinese medicine books,without fully covering ancient medical events.To address this issue,this research proposes to construct the evolution model of diagnosis and treatment experience based on time-series dynamic perspective:according to the time series of diagnosis and treatment events,it covers the time system module,the"coming disease"module,the"already sick"module,and the"after sick"module,which involves the dynamic risk assessment of disease occurrence by ancient medical practitioners,the grasp of the dynamic evolution of the already sick state and the treatment plan,and the dynamic health plan for the after sick state.

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.

ObjectiveTo elucidate the chemical composition of Danshenyin and its blood components in rats after oral administration. MethodsUltra performance liquid chromatography-quadrupole-time-of-flight tandem mass spectrometry（UPLC-Q-TOF-MS/MS） coupled with PeakView 1.2 software was used to systematically characterize and identify the components of Danshenyin aqueous extract and its migratory components in rat blood after oral administration based on the retention time， quasi-molecular ion peaks， secondary fragmentation ions， and literature reports， and a preliminary compounds identification of Salviae Miltiorrhizae Radix et Rhizoma aqueous extract， the co-decoction of Santali Albi Lignum and Amomi Fructus was carried out to attribute the chemical constituents of the aqueous extract of Danshenyin. ResultsA total of 73 compounds， including 21 phenolic acids， 23 diterpenes， 6 flavonoids， 7 organic acids， 3 volatile oils and 13 others， were identified from the aqueous extract of Danshenyin. And 36 prototypes and 15 metabolites were identified in rat plasma， the major metabolic pathways included reduction， hydration， hydroxylation， demethylation， methylation， sulfation and others， these metabolites were mainly derived from tanshinones and salvianolic acids. ConclusionThe main blood components of the aqueous extract of Danshenyin are salvianolic acids and tanshinones， which may be the material basis of the efficacy. This study can provide reference for pharmacological research， quality control， and clinical application of Danshenyin.

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.

The knowledge and experience of medical practitioners in the diagnosis and treatment of diseases throughout history are mostly reflected in the description and analysis of relevant clinical events.The diagnosis and treatment thinking and cognitive reasoning process among the knowledge has dynamic and complex characteristics in time and space.However,the current exploration of ancient doctors' diagnosis and treatment experience of diseases and syndromes is mainly focuses on the academic evolution of the entire historical time line,and lacks the exploration of the concept of time and its medical relevance in ancient books.It mainly focuses on entity knowledge,and lacks the presentation of temporal dynamic cognitive logic.Moreover,the research primarily focuses on the study of specific terms in ancient Chinese medicine books,without fully covering ancient medical events.To address this issue,this research proposes to construct the evolution model of diagnosis and treatment experience based on time-series dynamic perspective:according to the time series of diagnosis and treatment events,it covers the time system module,the"coming disease"module,the"already sick"module,and the"after sick"module,which involves the dynamic risk assessment of disease occurrence by ancient medical practitioners,the grasp of the dynamic evolution of the already sick state and the treatment plan,and the dynamic health plan for the after sick state.

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.

Japanese encephalitis virus(JEV)usually evades the inhibitory effect of the innate immunity factor type Ⅰ interferon(Ⅰ-IFN)when it infects human cells and tissues.The virus then causes a series of serious symptoms,such as spasticity,neurodegenerative lesions,neuroinflammation,and even death.Generally,JEV escapes innate immunity by inhibiting IFN-α/β production and the interferon Janus kinase-signal transducer and activator of transcription signaling pathway.Because of this special immune escape mechanism,various mouse infection models have been constructed for the study of the pathogenesis of and therapeutic regimens for JEV infections.In this review,based on an exposition of the IFN immune escape mechanism of JEV,we systematically introduce the concept of JEV-infected mouse models and analyze the characteristics of these models and the degree to which they simulate human symptoms.The intention is to develop various new JEV-infected mouse models based on potential new research targets and provide novel ideas for animal models for JEV research.

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.

Japanese encephalitis virus(JEV)usually evades the inhibitory effect of the innate immunity factor type Ⅰ interferon(Ⅰ-IFN)when it infects human cells and tissues.The virus then causes a series of serious symptoms,such as spasticity,neurodegenerative lesions,neuroinflammation,and even death.Generally,JEV escapes innate immunity by inhibiting IFN-α/β production and the interferon Janus kinase-signal transducer and activator of transcription signaling pathway.Because of this special immune escape mechanism,various mouse infection models have been constructed for the study of the pathogenesis of and therapeutic regimens for JEV infections.In this review,based on an exposition of the IFN immune escape mechanism of JEV,we systematically introduce the concept of JEV-infected mouse models and analyze the characteristics of these models and the degree to which they simulate human symptoms.The intention is to develop various new JEV-infected mouse models based on potential new research targets and provide novel ideas for animal models for JEV research.