Objective To propose a multiple regression-variational auto-encoders(MR-VAE)model to realize precise and non-invasive prediction of intra-abdominal pressure(IAP)in critically ill patients.Methods At first,a dataset was constructed by retrospectively analysing baseline characteristics and clinical indicators of 100 critically ill patients admitted to the Intensive Care Unit of Daping Hospital of Army Medical University between 30 August 2019 and 30 March 2021.Then,a MR-VAE prediction model was developed by integrating a feedforward neural network for supervised regression onto a variational autoencoder(VAE)framework and incorporating multiple regression strategies to mitigate feature interference.Finally,the MR-VAE model had its performance evaluated by its comparison with five classical models including support vector machines(SVM),convolutional neural networks(CNN),Scikit-learn integrated model(SIM),multi-layer perceptron(MLP)and K-nearest neighbors(KNN),and its prediction accuracy verified by testing the data of 10 randomly selected patients.Results The MR-VAE model behaved the best when compared with the five classical models,with a mean squared error(MSE)of 0.207,a root mean square error(RMSE)of 0.454,a mean absolute error(MAE)of 0.361,a median absolute deviation(MAD)of 0.243,an explained variance score(EVS)of 0.814 and a R2of 0.823,which also outperformed the five models in fitting performance,convergence and final loss.In random sample testing,the MR-VAE model exhibited high consistency between predicted and actual values.Conclusion The MR-VAE model proposed can accurately predict IAP,which has great potential in reducing the repeated measurements of IAP in critically ill patients and providing new ideas for the early diagnosis and treatment of IAH.

OBJECTIVE: To investigate the effect of zedoarondiol on neovascularization of atherosclerotic (AS) plaque by exosomes experiment. METHODS: ApoE^-/- mice were fed with high-fat diet to establish AS model and treated with high- and low-dose (10, 5 mg/kg daily) of zedoarondiol, respectively. After 14 weeks, the expressions of anti-angiogenic protein thrombospondin 1 (THBS-1) and its receptor CD36 in plaques, as well as platelet activation rate and exosome-derived miR-let-7a were detected. Then, zedoarondiol was used to intervene in platelets in vitro, and miR-let-7a was detected in platelet-derived exosomes (Pexo). Finally, human umbilical vein endothelial cells (HUVECs) were transfected with miR-let-7a mimics and treated with Pexo to observe the effect of miR-let-7a in Pexo on tube formation. RESULTS: Animal experiments showed that after treating with zedoarondiol, the neovascularization density in plaques of AS mice was significantly reduced, THBS-1 and CD36 increased, the platelet activation rate was markedly reduced, and the miR-let-7a level in Pexo was reduced (P<0.01). In vitro experiments, the platelet activation rate and miR-let-7a levels in Pexo were significantly reduced after zedoarondiol's intervention. Cell experiments showed that after Pexo's intervention, the tube length increased, and the transfection of miR-let-7a minics further increased the tube length of cells, while reducing the expressions of THBS-1 and CD36. CONCLUSION Zedoarondiol has the effect of inhibiting neovascularization within plaque in AS mice, and its mechanism may be potentially related to inhibiting platelet activation and reducing the Pexo-derived miRNA-let-7a level.
Animals ; MicroRNAs/genetics* ; Exosomes/drug effects* ; Plaque, Atherosclerotic/genetics* ; Neovascularization, Pathologic/genetics* ; Human Umbilical Vein Endothelial Cells/metabolism* ; Humans ; Blood Platelets/drug effects* ; Apolipoproteins E/deficiency* ; Thrombospondin 1/metabolism* ; CD36 Antigens/metabolism* ; Platelet Activation/drug effects* ; Male ; Mice ; Mice, Inbred C57BL

OBJECTIVE: To explore the functional roles and underlying mechanisms of neferine in the context of angiotensin II (Ang II)-induced hypertension and vascular dysfunction. METHODS: Male mice were infused with Ang II to induce hypertension and randomly divided into treatment groups receiving neferine or a control vehicle based on baseline blood pressure using a random number table method. The hypertensive mouse model was constructed by infusing Ang II via a micro-osmotic pump (500 ng/kg per minute), and neferine (0.1, 1, or 10 mg/kg), valsartan (10 mg/kg), or double distilled water was administered intragastrically once daily for 6 weeks. A non-invasive blood pressure system, ultrasound, and hematoxylin and eosin staining were performed to assess blood pressure and vascular changes. RNA sequencing and network pharmacology were employed to identify differentially expressed transcripts (DETs) and pathways. Vascular ring tension assay was used to test vascular function. A7R5 cells were incubated with neferine for 24 h and then treated with Ang II to record the real-time Ca²⁺ concentration by confocal microscope. Immunohistochemistry (IHC) and Western blot were used to evaluate vasorelaxation, calcium, and the extracellular signal-regulated kinase (ERK)1/2 pathway. RESULTS: Neferine treatment effectively mitigated the elevation in blood pressure, pulse wave velocity, aortic thickening in the abdominal aorta of Ang II-infused mice (P<0.05). RNA sequencing and network pharmacology analysis identified 355 DETs that were significantly reversed by neferine treatment, along with 25 potential target genes, which were further enriched in multiple pathways and biological processes, such as ERK1 and ERK2 cascade regulation, calcium pathway, and vascular smooth muscle contraction. Further investigation revealed that neferine treatment enhanced vasorelaxation and reduced Ca²⁺-dependent contraction of abdominal aortic rings, independent of endothelium function (P<0.05). The underlying mechanisms were mediated, at least in part, via suppression of receptor-operated channels, store-operated channels, or voltage-operated calcium channels. Neferine pre-treatment demonstrated a reduction in intracellular Ca²⁺ release in Ang II stimulated A7R5 cells. IHC staining and Western blot confirmed that neferine treatment effectively attenuated the upregulation of p-ERK1/2 both in vivo and in vitro, which was similar with treatment of ERK1/2 inhibitor PD98059 (P<0.05). CONCLUSIONS Neferine remarkably alleviates Ang II-induced elevation of blood pressure, vascular dysfunction, and pathological changes in the abdominal aorta. This beneficial effect is mediated by the modulation of multiple pathways, including calcium and ERK1/2 pathways.
Animals ; Angiotensin II ; Male ; Benzylisoquinolines/therapeutic use* ; Network Pharmacology ; Blood Pressure/drug effects* ; Sequence Analysis, RNA ; Mice ; Hypertension/chemically induced* ; Mice, Inbred C57BL ; Calcium/metabolism*

Objective To investigate the effects of Chaihuang Qingyi Huoxue Granules on multiple organ damage induced by caerulein combined with lipopolysaccharide in mice with severe acute pancreatitis(SAP).Methods Twenty-four C57BL/6J mice were randomly divided into three groups:control(n=8),SAP(n=8)and Chaihuang Qingyi Huoxue Granules(CHQY group,n=8).Mice in SAP and CHQY groups were intraperitoneally injected with caerulein(50 μg/kg)at hourly intervals for 7 consecutive times,followed by an immediate intraperitoneal injection of lipopolysaccharide(10 mg/kg).Mice in control group received an equal volume of normal saline.After the successful establishment of the model,CHQY group mice were administered Chaihuang Qingyi Huoxue Granules[3.185 g/(kg·d)]via gavage,while control and SAP group mice received an equal volume of normal saline.Twenty-four hours post-modeling,mice were anesthetized,and serum was collected and separated for analysis of the activities of amylase(AMY),lipase(LPS),aspartate transaminase(AST),alanine transaminase(ALT)and the contents of creatinine(CREA)and urea(UREA)using an automatic biochemical analyzer.Serum levels of interleukin(IL)-1β,IL-6,IL-8,IL-18,and tumor necrosis factor-α(TNF-α)were measured by ELISA.Tissue samples from pancreas,lung,liver,kidney,and small intestine were collected for histopathological examination using hematoxylin-eosin(HE)staining and scored.The expression of nuclear factor-κB p65(NF-κB p65)was detected in all tissues by immunohistochemistry.Results Compared with control group,the activities of AMY,LPS,AST and ALT,and the contents of CREA,UREA,IL-1β,IL-6,IL-8,IL-18,and TNF-α were increased(P<0.05).Pathological injuries in the pancreas,lung,liver,kidney,and small intestine was significant,with increased pathological scores and a higher proportion of NF-κB p65 positive cells(P<0.05).Compared with SAP group,the activities of AMY,LPS,AST,ALT,and the contents of CREA,UREA,IL-1β,IL-6,IL-8,IL-18,and TNF-α in the serum of CHQY group were decreased(P<0.05).Pathological injuries in the pancreas,lung,liver,kidney and small intestine were reduced,with lower pathological scores and a decreased proportion of NF-κB p65 positive cells(P<0.05).Conclusion Chaihuang Qingyi Huoxue Granules have a certain therapeutic effect on SAP model mice,which may be related to reducing inflammation response and improving multiple organ damage such as the pancreas,lung,liver,kidney and small intestine.

Objective: To explore the causal link of cumulative ecological risk and future orientation with health risk behaviors among higher vocational college students, so as to provide reference for reducing and preventing health risk behaviors among higher vocational college students. Methods: A longitudinal follow up study was conducted on 612 students using convenience sampling from 2 vocational colleges in Hunan Province. The Cumulative Ecological Risk Scale, Future Orientation Scale, and Health Risk Behavior Scale were used during three follow up visits (T1: September 2022, T2: June 2023, T3: March 2024), and a cross lagged panel model was constructed to examine the longitudinal causal relationship of cumulative ecological risk, future orientation and health risk behaviors. Analysis of longitudinal intermediary effect between variables by Bootstrap. Results: The cumulative ecological risk scores of T1, T2 and T3 among higher vocational college students were (2.94±1.44,2.99±1.63,3.02±1.54), future orientation scores (40.49±4.71,41.51±5.72,41.06±4.35) and health risk behavior scores (3.73±2.01,3.49±2.00,3.23±2.00). The results of repeated measures ANOVA showed that the future orientation score of T2 was higher than that of T1, and the main effect of measurement time was statistically significant ( F=5.09，P＜0.01,η 2=0.02). The health risk behavior score of T1 was higher than that of T2, and the health risk behavior score of T2 was higher than that of T3, and the main effect of measurement time was statistically significant ( F=10.12，P＜0.01,η 2=0.03).The cross lagged model showed good adaptability, with χ 2/df =7.20 ( P <0.01), relative fitting indicators GFI=0.98, CFI=0.99, TLI=0.96, IFI=0.99, NFI =0.99, and absolute fitting indicator RMSEA =0.06. Among them, the T1, T2 cumulative ecological risk showed negatively predictive effects on T2, T3 future orientation ( β =-0.24, -0.47 ), and T1, T2 cumulative ecological risk positively predicted T2, T3 health risk behavior ( β =0.20, 0.24), while T1, T2 future orientation negatively predicted T2, T3 health risk behavior ( β =-0.25, -0.18) ( P ＜0.01). Bootstrap test analysis found that T2 future orientation had a longitudinal mediating effect ( β=0.04, P ＜0.01) on the T1 cumulative ecological risk and T3 health risk behavior. Conclusions The accumulation of ecological risk among higher vocational college students can positively predict health risk behaviors, while future orientation can negatively predict healthrisk behaviors. Moreover, future orientation plays a longitudinal mediating role between accumulated ecological risks and health risk behaviors.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Purpose To explore the clinical and pathological characteristics of primary benign,borderline,and malignant cardiac tumors in children.Methods 15 cases of primary cardiac tumors in children were collected,and their clinical manifestations,pathological morphology,and immunophenotypes were analyzed.Relevant literature was also reviewed.Results The age of 15 patients ranged from 0.3 to 12 years old,with an average age of about 5 years and a median age of 2 years.9 cases were males and 6 cases were females.4 cases were found to have heart masses during physical examination,3 cases were treated for symptoms of cerebral infarction,1 case was treated for limb weak-ness,1 case was treated for systemic edema,1 case was treated for accelerated heartbeat,1 case was treated for cough,1 case was treated for pneumonia,1 case was treated for abdominal pain,1 case was treated for vomiting,and 1 case was treated for fever and shortness of breath.Echocardiography showed 8 cases occurring in the left heart system(6 in the left atrium and 2 in the left ventricle),4 cases occurring in the right heart system(2 in the right atrium and 2 in the right ventricle),2 cases occurring in the pericardium,and 1 case occurring in the interventricular septum.Ac-cording to pathological diagnosis,13 cases were benign tumors(8 cases of mucinous tumors,4 cases of rhabdomyo-mas,and 1 case of fibroma),1 case was a malignant tumor(embryonal rhabdomyosarcoma),and 1 case was a border-line tumor(NTRK rearranged spindle cell tumor).Conclusion Primary cardiac tumors in children are relatively rare,and borderline and malignant tumors are even rarer.The types of common tumors are different from those in a-dults,and they are prone to misdiagnosis due to non-specific clinical symptoms.For specific cardiac tumors,it is rec-ommended to conduct genetic testing when necessary based on clinical manifestations to further investigate the possibili-ty of related syndromes.

Objective To propose a multiple regression-variational auto-encoders(MR-VAE)model to realize precise and non-invasive prediction of intra-abdominal pressure(IAP)in critically ill patients.Methods At first,a dataset was constructed by retrospectively analysing baseline characteristics and clinical indicators of 100 critically ill patients admitted to the Intensive Care Unit of Daping Hospital of Army Medical University between 30 August 2019 and 30 March 2021.Then,a MR-VAE prediction model was developed by integrating a feedforward neural network for supervised regression onto a variational autoencoder(VAE)framework and incorporating multiple regression strategies to mitigate feature interference.Finally,the MR-VAE model had its performance evaluated by its comparison with five classical models including support vector machines(SVM),convolutional neural networks(CNN),Scikit-learn integrated model(SIM),multi-layer perceptron(MLP)and K-nearest neighbors(KNN),and its prediction accuracy verified by testing the data of 10 randomly selected patients.Results The MR-VAE model behaved the best when compared with the five classical models,with a mean squared error(MSE)of 0.207,a root mean square error(RMSE)of 0.454,a mean absolute error(MAE)of 0.361,a median absolute deviation(MAD)of 0.243,an explained variance score(EVS)of 0.814 and a R2of 0.823,which also outperformed the five models in fitting performance,convergence and final loss.In random sample testing,the MR-VAE model exhibited high consistency between predicted and actual values.Conclusion The MR-VAE model proposed can accurately predict IAP,which has great potential in reducing the repeated measurements of IAP in critically ill patients and providing new ideas for the early diagnosis and treatment of IAH.