Under the background of rapid development of artificial intelligence(AI),this paper systematically proposes AI-based education(AIBE).It empowers the teaching process,learning process,research process,and teaching management with AI,and constructs an AI-based educational paradigm,including AI-based teaching(AIBT),AI-based learning(AIBL),AI-based re-search(AIBR),and AI-based management(AIBM).Taking the AI course of immunology teaching as an example,this paper deeply analyzes the practices and explorations of implementing AIBT,AIBL,AIBR and AIBM based on the AI course,so as to accelerate the promotion of the transformation of the fourth generation of medical education.

Objective To investigate the relationship between triple motif protein(TRIM)3,TRIM44 and clinicopathological parameters and prognosis in human papillomavirus(HPV)positive cervical cancer tissues.Methods The cancer tissues and adjacent normal cervical tissues(≥2 cm from the resection margin of the cancer)of 158 patients with HPV positive cervical cancer admitted to the hospital from February 2019 to Feb-ruary 2021 were selected,and the cancer tissues of 100 patients with HPV negative cervical cancer admitted to the hospital during the same period were selected.The positive expression rates of TRIM3 and TRIM44 in cancer tissues of HPV positive cervical cancer patients and their adjacent normal cervical tissues,and cancer tissues of HPV negative cervical cancer patients were detected and compared by immunohistochemistry.The relationship between the positive expression rate of TRIM3 and TRIM44 and the clinicopathological parame-ters of HPV positive cervical cancer patients was analyzed.The 3-year cumulative survival rate of patients with negative/positive TRIM3 expression and negative/positive TRIM44 expression were analyzed by Kaplan-Meier survival curve.The influencing factors of the prognosis of HPV positive cervical cancer patients were analyzed by COX regression model.Results Compared with adjacent normal cervical tissues and HPV nega-tive cervical cancer tissues,the positive expression rate of TRIM3 in HPV positive cervical cancer tissues was significantly decreased(P＜0.05),and the patients expression rate of TRIM44 was significantly increased(P＜0.05).Compared with the patients with FIGO stage Ⅰ A-Ⅰ B and no lymph node metastasis,the pa-tients with FIGO stage Ⅱ A and lymph node metastasis,the positive rate of TRIM3 expression decreased sig-nificantly(P＜0.05),while the positive rate of TRIM44 expression increased significantly(P＜0.05).A total of 3 patients were lost during the 3-year follow-up among 158 HPV positive cervical cancer patients,and 155 patients were finally followed up.Kplan-Meier survival curve showed that,the 3-year cumulative survival rate in TRIM3 negative expression group was significantly lower than that in TRIM3 positive expression group(P＜0.05).The 3-year cumulative survival rate in TRIM44 positive expression group was significantly lower than that in TRIM44 negative expression group(P＜0.05).COX regression analysis showed that lymph node metastasis,FIGO stage,negative expression of TRIM3 and positive expression of TRIM44 were risk factors for the prognosis of HPV positive cervical cancer patients(P＜0.05).Conclusion The expression of TRIM3 is low and the expression of TRIM44 is high in HPV positive cervical cancer tissues,which is relate to lymph node metastasis,FIGO stage and decrease 3-year cumulative survival rate.

OBJECTIVE: To investigate the inhibitory effect of Tanreqing Injection (TRQ) on the activation of nucleotide-binding oligomerization domain-like receptor pyrin domain containing 3 (NLRP3) inflammasome in macrophages infected with influenza A virus and the underlying mechanism based on mitophagy pathway. METHODS: The inflammatory model of murine macrophage J774A.1 induced by influenza A virus [strain A/Puerto Rico/8/1934 (H1N1), PR8] was constructed and treated by TRQ, while the mitochondria-targeted antioxidant Mito-TEMPO and autophagy specific inhibitor 3-methyladenine (3-MA) were used as controls to intensively study the anti-inflammatory mechanism of TRQ based on mitophagy-mitochondrial reactive oxygen species (mtROS)-NLRP3 inflammasome pathway. The levels of NLRP3, Caspase-1 p20, microtubule-associated protein 1 light chain 3 II (LC3II) and P62 proteins were measured by Western blot. The release of interleukin-1β (IL-1β) was tested by enzyme linked immunosorbent assay, the mtROS level was detected by flow cytometry, and the immunofluorescence and co-localization of LC3 and mitochondria were observed under confocal laser scanning microscopy. RESULTS: Similar to the effect of Mito-TEMPO and contrary to the results of 3-MA treatment, TRQ could significantly reduce the expressions of NLRP3, Caspase-1 p20, and autophagy adaptor P62, promote the expression of autophagy marker LC3II, enhance the mitochondrial fluorescence intensity, and inhibit the release of mtROS and IL-1β (all P<0.01). Moreover, LC3 was co-localized with mitochondria, confirming the type of mitophagy. CONCLUSION TRQ could reduce the level of mtROS by promoting mitophagy in macrophages infected with influenza A virus, thus inhibiting the activation of NLRP3 inflammasome and the release of IL-1β, and attenuating the inflammatory response.
Mitophagy/drug effects* ; NLR Family, Pyrin Domain-Containing 3 Protein/metabolism* ; Animals ; Macrophages/virology* ; Inflammasomes/drug effects* ; Drugs, Chinese Herbal/pharmacology* ; Mice ; Mitochondria/metabolism* ; Reactive Oxygen Species/metabolism* ; Influenza A virus/physiology* ; Interleukin-1beta/metabolism* ; Cell Line ; Injections

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

This study aims to systematically characterize the targeted effects of Quanduzhong Capsules on cartilage lesions in knee osteoarthritis by integrating spatial transcriptomics data mining and animal experiments validation, thereby elucidating the related molecular mechanisms. A knee osteoarthritis model was established using Sprague-Dawley(SD) rats, via a modified Hulth method. Hematoxylin and eosin(HE) staining was employed to detect knee osteoarthritis-associated pathological changes in knee cartilage. Candidate targets of Quanduzhong Capsules were collected from the HIT 2.0 database, followed by bioinformatics analysis of spatial transcriptomics datasets(GSE254844) from cartilage tissues in clinical knee osteoarthritis patients to identify spatially specific disease genes. Furthermore, a "formula candidate targets-spatially specific genes in cartilage lesions" interaction network was constructed to explore the effects and major mechanisms of Quanduzhong Capsules in distinct cartilage regions. Experimental validation was conducted through immunohistochemistry using animal-derived biospecimens. The results indicated that Quanduzhong Capsules effectively inhibited the degenerative changes in the cartilage of affected joints in rats, which was associated with the regulation of Quanduzhong Capsules on the thioredoxin-interacting protein(TXNIP)-NOD-like receptor family pyrin domain containing 3(NLRP3)-bone morphogenetic protein receptor type 2(BMPR2)-fibronectin 1(FN1)-matrix metallopeptidase 2(MMP2) signal axis in the articular cartilage surface and superficial zones, subsequently inhibiting cartilage matrix degradation leading to oxidative stress and inflammatory diffusion. In summary, this study clarifies the spatially specific targeted effects and protective mechanisms of Quanduzhong Capsules within pathological cartilage regions in knee osteoarthritis, providing theoretical and experimental support for the clinical application of this drug in the targeted therapy on the inflamed cartilage.
Animals ; Osteoarthritis, Knee/metabolism* ; Drugs, Chinese Herbal/administration & dosage* ; Rats, Sprague-Dawley ; Rats ; Male ; Humans ; Capsules ; Female ; Disease Models, Animal

Objective To investigate the value of procalcitonin-to-albumin ratio(PAR)for predicting 28-day mortality risk in elderly patients with sepsis for optimizing the diagnosis and treatment strategies.Methods The clinical data of 112 elderly patients diagnosed with sepsis in the intensive care unit were retrospectively reviewed and analyzed.Patients were assigned to survivors group or deaths group based on 28-day outcomes.Clinical characteristics and the results of laboratory tests were collected,including procalcitonin(PCT),albumin,and C-reactive protein(CRP).The normally distributed data were compared between groups using t-test.Mann-Whitney U test was adopted for comparing non-normally distributed data.Cox proportional hazards regression model was used to analyze the effects of multiple variables on survival time.Receiver operating characteristic(ROC)curve analysis was performed to determine the sensitivity and specificity of various variables in predicting mortality risk.Results Mechanical ventilation,APACHE Ⅱ scores,and length of hospital stay(all P＜0.05)were significantly different between survivors group and deaths group.Blood culture results showed that Gram-negative bacteria were predominant pathogen(75.9％),especially Escherichia coli(45.5％).Albumin level was significantly lower(P=0.026),while PCT,CRP,and PAR levels were significantly higher(P＜0.05)in the deaths group compared to those in the survivors group.Multivariate Cox regression analysis revealed that PAR was an independent predictor of 28-day mortality(HR=3.72,95％CI:1.98-4.42,P＜0.001).ROC curve analysis showed that the area under the curve(AUC)of PAR was 0.852 in predicting mortality,with a sensitivity of 81.25％and specificity of 87.82％.Conclusions PAR outperformed PCT or albumin alone in predicting 28-day mortality risk in elderly patient with sepsis.For every 0.1 increase in PAR,the risk of mortality increased by 272％.Early monitoring of PAR can assist clinicians in rapidly identifying high-risk patients and optimizing treatment strategies.

Objective To investigate the value of procalcitonin-to-albumin ratio(PAR)for predicting 28-day mortality risk in elderly patients with sepsis for optimizing the diagnosis and treatment strategies.Methods The clinical data of 112 elderly patients diagnosed with sepsis in the intensive care unit were retrospectively reviewed and analyzed.Patients were assigned to survivors group or deaths group based on 28-day outcomes.Clinical characteristics and the results of laboratory tests were collected,including procalcitonin(PCT),albumin,and C-reactive protein(CRP).The normally distributed data were compared between groups using t-test.Mann-Whitney U test was adopted for comparing non-normally distributed data.Cox proportional hazards regression model was used to analyze the effects of multiple variables on survival time.Receiver operating characteristic(ROC)curve analysis was performed to determine the sensitivity and specificity of various variables in predicting mortality risk.Results Mechanical ventilation,APACHE Ⅱ scores,and length of hospital stay(all P＜0.05)were significantly different between survivors group and deaths group.Blood culture results showed that Gram-negative bacteria were predominant pathogen(75.9％),especially Escherichia coli(45.5％).Albumin level was significantly lower(P=0.026),while PCT,CRP,and PAR levels were significantly higher(P＜0.05)in the deaths group compared to those in the survivors group.Multivariate Cox regression analysis revealed that PAR was an independent predictor of 28-day mortality(HR=3.72,95％CI:1.98-4.42,P＜0.001).ROC curve analysis showed that the area under the curve(AUC)of PAR was 0.852 in predicting mortality,with a sensitivity of 81.25％and specificity of 87.82％.Conclusions PAR outperformed PCT or albumin alone in predicting 28-day mortality risk in elderly patient with sepsis.For every 0.1 increase in PAR,the risk of mortality increased by 272％.Early monitoring of PAR can assist clinicians in rapidly identifying high-risk patients and optimizing treatment strategies.

Under the background of rapid development of artificial intelligence(AI),this paper systematically proposes AI-based education(AIBE).It empowers the teaching process,learning process,research process,and teaching management with AI,and constructs an AI-based educational paradigm,including AI-based teaching(AIBT),AI-based learning(AIBL),AI-based re-search(AIBR),and AI-based management(AIBM).Taking the AI course of immunology teaching as an example,this paper deeply analyzes the practices and explorations of implementing AIBT,AIBL,AIBR and AIBM based on the AI course,so as to accelerate the promotion of the transformation of the fourth generation of medical education.

Objective To investigate the correlation and predictive effect of serum CD4+/CD8+T lympho-cyte ratio combined with magnetic resonance angiography(MRA)on recurrence of cerebral infarction.Meth-ods A total of 153 patients with acute cerebral infarction admitted to the Zhenjiang First People's Hospital from January 2021 to February 2022 were selected.CD4+/CD8+T lymphocyte ratio of patients was deter-mined,vascular stenosis score and collateral circulation filling score were evaluated by MRA.The patients were followed up for 1 year,including 34 patients with recurrent cerebral infarction as recurrent cerebral in-farction group,107 patients without recurrent cerebral infarction as the non-recurrent cerebral infarction group,12 patients were excluded due to other causes of loss of follow-up,and the receiver operating character-istic(ROC)curve for using the indicators to predict the recurrent cerebral infarction was drawn.Results The CD4+/CD8+T lymphocyte ratio in recurrent cerebral infarction group was significantly higher than that in non-recurrent cerebral infarction group(P<0.05).Vascular stenosis score and collateral circulation filling score in recurrent cerebral infarction group were lower than those in non-recurrent cerebral infarction group(P<0.05).The recurrence of cerebral infarction was correlated with CD4+/CD8+T lymphocyte ratio,vascu-lar stenosis score and collateral circulation filling score(P<0.05).ROC curve analysis showed that the area under the curve(AUC)of CD4+/CD8+T lymphocyte ratio,vascular stenosis score,and collateral circulation filling score to predict recurrent cerebral infarction was 0.975,0.889,and 0.935,respectively,and the AUC of recurrent cerebral infarction was 0.994 when combined with the three factors.The AUC of cerebral infarction recurrence was significantly higher than that of each index alone.Conclusion Serum CD4+/CD8+T lympho-cyte ratio combined with MRA vascular stenosis score and collateral circulation filling score have high efficacy in the diagnosis of recurrent cerebral infarction,which have predictive value for recurrent cerebral infarction.