Periodontitis is a globally prevalent inflammatory oral disease, affecting approximately 50% of the population worldwide and imposing a substantial burden on patients′ health and quality of life. Early and accurate diagnosis is critical for preventing disease progression; however, conventional diagnostic approaches often rely on subjective clinical assessments, which only primarily evaluate the cumulative state of the disease, thus limiting their ability to achieve precise early detection. In recent years, the rapid advancement of artificial intelligence (AI) in medical diagnostics has demonstrated significant promise, particularly through the integration of multimodal data to enable more comprehensive information capture and analysis. Multimodal data fusion, which combines diverse inputs such as imaging, clinical parameters, and biomarkers, offers transformative potential for AI-powered periodontitis diagnostics. This innovative approach aims to overcome the limitations of traditional methods, significantly enhancing diagnostic accuracy and predictive capabilities. This manuscript reviews the primary diagnostic techniques for periodontitis, explores recent advances in AI applications within this domain, and emphasizes the potential of multimodal data in facilitating precision diagnosis. Furthermore, it provides new insights and supports for personalized treatment strategies.

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.

Periodontitis is a globally prevalent inflammatory oral disease, affecting approximately 50% of the population worldwide and imposing a substantial burden on patients′ health and quality of life. Early and accurate diagnosis is critical for preventing disease progression; however, conventional diagnostic approaches often rely on subjective clinical assessments, which only primarily evaluate the cumulative state of the disease, thus limiting their ability to achieve precise early detection. In recent years, the rapid advancement of artificial intelligence (AI) in medical diagnostics has demonstrated significant promise, particularly through the integration of multimodal data to enable more comprehensive information capture and analysis. Multimodal data fusion, which combines diverse inputs such as imaging, clinical parameters, and biomarkers, offers transformative potential for AI-powered periodontitis diagnostics. This innovative approach aims to overcome the limitations of traditional methods, significantly enhancing diagnostic accuracy and predictive capabilities. This manuscript reviews the primary diagnostic techniques for periodontitis, explores recent advances in AI applications within this domain, and emphasizes the potential of multimodal data in facilitating precision diagnosis. Furthermore, it provides new insights and supports for personalized treatment strategies.

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.

AIM:This study aimed to observe the analgesic effects of Hegu acupoint catgut embedding in a rat model of labor and investigate its influence on biomarkers such as calcitonin gene-related peptide(CGRP)signals at the Hegu acupoint.METHODS:Thirty-six pregnant rats were randomly divided into three groups:control group,Hegu acu-puncture group,and Hegu catgut embedding group.Pain threshold changes were assessed using the tail immersion test and paw withdrawal thermal latency at four time points:pre-induction,before the onset of labor,at the onset of labor,and at the mid-stage of labor.Tissue samples from the Hegu acupoint were collected at the mid-stage of labor to detect the ex-pression of CGRP,substance P(SP),and mast cells using immunofluorescence.The concentrations of ATP and ade-nosine were measured using ELISA.RESULTS:Before labor induction,there was no significant difference in tail immer-sion test and paw withdrawal thermal latency among the three groups(P>0.05).Before the onset of labor,both the acu-puncture and catgut embedding groups exhibited significantly higher tail-flick times and paw withdrawal latencies com-pared to the control group(P<0.05).At labor initiation and mid-labor,the catgut embedding group had significantly higher tail-flick times and paw withdrawal latencies compared to both the control and acupuncture groups(P<0.05).During mid-labor,the expression of CGRP,SP,mast cells,ATP,and adenosine concentrations in the catgut embedding group was significantly higher than that in the control and acupuncture groups(P<0.05),with co-expression of CGRP,SP,and mast cells observed.CONCLUSION:Hegu acupoint catgut embedding effectively alleviates labor pain,and its mechanism may involve increased local expression of CGRP and SP,promoting mast cell degranulation,and increasing ATP release and its conversion to adenosine.

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 explore the effects of status epilepticus(SE)on neuronal processes and synapses in the cerebral cortex and hippocampus of young mice.Methods:The young mice of SE model was established by intraperito-neal injection of lithium chloride and pilocarpine.Morris water maze test was used to detect the behavioral changes in the mice.Immunofluorescence staining was used to observe the morphological changes of axons,dendrites and synaptic connections of neurons in the cerebral cortex and hippocampus of mice,and the ultrastructural changes of synapses of pyramidal neurons in the mouse hippocampus were observed with transmission electron microscopy.Results:The sei-zure rate of grade IV and above in mice was 80％,and the mortality rate was 25％.The escape latency of SE mice was prolonged(P＜0.05),the trajectory of exploring the platform was significantly longer and more complicated,and the time spent in the target quadrant and the number of crossing the platform were significantly reduced(P＜0.05).Posi-tive expression of axonal neurofilament marker protein SMI312 and microtubule-associated protein 2(MAP2)were found in the cerebral cortex and hippocampus of both groups,and the axonal neurofilaments and neuronal dendrites in the SE group were of different lengths and arranged densely and scatteredly.The positive expression of synaptophysin(SYP)and the number of positive spots increased significantly in in the hippocampus of SE group(P＜0.01).The number of synaptic vesicles in the SE group increased significantly,and the postsynaptic density(PSD)thickness decreased significantly(P＜0.01).Conclusion:SE might lead to acute injury of synapses in the cerebral cortex and hippocampal area of young mice,induce synaptic vesicle circulation disorders,and then cause widespread destruction and disorder of the axon and dendrite networks,the reactive or compensatory reconstruction of synaptic.

Background: Pyroptosis is involved in the occurrence of acute pancreatitis, but its role in remote organ injury remains unclear. Aims: To investigate the role and mechanism of NLRP3 inflammasome-dependent pyroptosis in acute pancreatitis- related lung injury. Methods: Thirty-two male Sprague-Dawley rats were randomly divided into four groups: control group, severe acute pancreatitis (SAP) group, Z-WEHD-FMK (caspase-1 inhibitor) group and disulfiram (GSDMD inhibitor) group. Experimental SAP was constructed by using 5% sodium taurocholate in the latter 3 groups. Serum levels of amylase, lipase, procalcitonin, and the myeloperoxidase (MPO) activity were determined; the severity of pancreatic and lung injuries was assessed by histopathology and lung wet/dry weight ratio; serum levels of pyroptosis-related inflammatory cytokines and the expressions of proteins involved in pyroptosis pathway in lung tissue were measured by ELISA method and immunohisto- chemistry and Western blotting, respectively. Results: Compared with the control group, the serum biochemical indices, MPO activity, and interleukin (IL)-1β, IL-18 levels in SAP group were significantly increased with aggravated pancreatic and lung tissue injuries; meanwhile, the expressions of NLRP3, caspase-1 and GSDMD in lung tissue were significantly up- regulated (all P<0.05). Pretreatment with caspase-1 or GSDMD inhibitors reduced the severity of pancreatic and lung tissue injuries, improved the serum biochemical indices and MPO activity, and ameliorated the increased pyroptosis - related inflammatory cytokines and pyroptosis pathway - related proteins (all P<0.05). Conclusions: NLRP3/caspase - 1/GSDMD pathway mediated pyroptosis plays an important role in acute pancreatitis-related lung injury, and inhibition of pyroptosis pathways might be a new direction for its treatment.