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.

Objective To explore the effectiveness of the OKR method in improving the efficiency of the whole process of critical value management,and to provide new ideas for the implementation of medical quality improvement in other medical insti-tutions.Methods A hospital in Tianjin was selected as the study object,which used the OKR method to reform the management of critical value since January 2024.The core goal of"improving the effectiveness of critical value management"was set,and the goal was broken down into quantitative key results such as"the rate of receiving the critical value system is over 95％"and"the rate of completing the standardised writing of medical records is up to 85％".Results After the reform,several quantitative key results,such as the completion rate of critical care medical record writing,the rate of standardised medical record writing,and the rate of overtime acceptance,were all better than before.Conclusion Through the OKR method to unify the whole hospital's strategic objectives,and the dynamic adjustment of the program based on data review,the hospital's critical value management efficiency has been significantly improved,effectively guaranteeing the safety of patients,and providing new perspectives and methods for the management of critical value in other medical institutions.

Objective:This study aims to investigate the expression of uridine diphosphate-glucose[]pyrophos-phorylase 2(UGP2)in breast cancer(BC)tissues and its oncogenic mechanism,assessing its potential value as a diag-nostic and prognostic biomarker for breast cancer.Methods:(1)Online database analysis was conducted to assess UGP2 mRNA and protein expression levels in breast cancer and explore their correlation with clinical characteristics.Im-munohistochemistry(IHC)was used to verify UGP2 expression in human breast cancer tumor tissues and evaluate its relationship with clinicopathological features.(2)Kaplan-Meier survival analysis and COX regression models were used to analyze the impact of UGP2 expression on breast cancer patient prognosis.(3)Bioinformatics methods were em-ployed to investigate the correlation between UGP2 and tumor immune cell infiltration,and to predict the biological func-tions and associated signaling pathways of UGP2 in breast cancer.Results:(1)The mRNA and protein expression levels of UGP2 were upregulated in breast cancer tissues(both P<0.05),and were negatively correlated with ER-positive and PR-positive status(OR<1,P<0.05),while positively correlated with Ki-67 levels and the triple-negative breast cancer(TNBC)subtype(OR>1,P<0.05).(2)Elevated expression levels of UGP2 were associated with poorer survival rates in breast cancer patients(both P<0.05)and were identified as an independent adverse prognostic factor for breast cancer(HR=1.40,P<0.05).(3)Functional analysis results suggested that UGP2 may promote tumor progression by regulating metabolism,hormone signaling,and the immune microenvironment.Additionally,UGP2 expression was negatively cor-related with NK cell activation status and positively correlated with the inhibitory state.Conclusion:UGP2 expression is elevated in breast cancer tissues and is closely associated with poor patient prognosis.It may promote cancer pro-gression through mechanisms such as metabolic reprogramming and immune suppression.UGP2 shows promise as a potential biomarker and therapeutic target in breast cancer,providing a basis for personalized treatment.

To investigate the anti-atherosclerotic effects of dietary hesperidin and naringin on ather-osclerosis in rabbits.Twenty-four adult healthy male New Zealand Large White rabbits were ran-domly assigned to four groups based on one factor:control(Con),model(Mod),hesperidin(HP),and naringenin(NG),each containing six rabbits and housed in solitary cages.During the experi-mental period,the control group received normal feed;the model group was fed high-fat for 30 d to establish the atherosclerosis,(AS)model and continued to be fed high-fat feed;the hesperidin and naringenin groups were fed high-fat for 30 d and then underwent AS modeling,and at a later stage,150 mg of hesperidin(or naringenin)was added to the diets at a rate of 1.5 mg per kg of di-et,respectively,for 30 d.Relative body quality,blood lipids,oxidation,and inflammatory factor lev-els were all assessed.At the end of the test period,the test rabbits were sacrificed to obtain the common carotid artery for histopathological section HE staining,Oil red O staining,and Sirius red staining in order to observe vascular tissue structure,lipid and inflammatory cell infiltration,and e-lastic plate and elastic fiber damage.The results indicated that the relative body quality of the mod-el,HP and NG groups increased rapidly,and the difference with the control group within the same period was highly significant(P＜0.01);The HP and NG interventions significantly decreased to-tal cholesterol(TC)and low-density lipoprotein cholesterol(LDL-C)levels(P＜0.01),while also leading to a significant increase in high-density lipoprotein cholesterol(HDL-C)levels(P＜0.01);MDA levels exhibited a significant decrease(P＜0.01),while SOD levels showed a notable in-crease(P＜0.01)following the HP and NG interventions;After HP and NG interventions,TNF-α and IL-1 were regressed(P＜0.01)and IL-10 was significantly elevated(P＜0.01);Compared with the control group,the model group showed approximately 41.8 and 2.5 fold thickening of the maximal endo-medial membrane,respectively,and the HP and NG interventions showed approxi-mately 13 and 15 fold thickening of the maximal endo-medial membrane,and both of the maximal medial membranes thickened by approximately 1.4 fold;Staining of pathological sections showed that HP and NG intervened to significantly reduce inflammatory cell infiltration,deposition of lipid components,slight thickening of the endothelium,and intact fibroblastic components.The results showed that the addition of HP and NG to diets could regulate blood lipids and exert anti-inflam-matory and antioxidant effects by inhibiting the expression of inflammatory factors and oxidizing factors,showing significant anti-AS effects,and the two effects were comparable.

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.

Objective To explore the effectiveness of the OKR method in improving the efficiency of the whole process of critical value management,and to provide new ideas for the implementation of medical quality improvement in other medical insti-tutions.Methods A hospital in Tianjin was selected as the study object,which used the OKR method to reform the management of critical value since January 2024.The core goal of"improving the effectiveness of critical value management"was set,and the goal was broken down into quantitative key results such as"the rate of receiving the critical value system is over 95％"and"the rate of completing the standardised writing of medical records is up to 85％".Results After the reform,several quantitative key results,such as the completion rate of critical care medical record writing,the rate of standardised medical record writing,and the rate of overtime acceptance,were all better than before.Conclusion Through the OKR method to unify the whole hospital's strategic objectives,and the dynamic adjustment of the program based on data review,the hospital's critical value management efficiency has been significantly improved,effectively guaranteeing the safety of patients,and providing new perspectives and methods for the management of critical value in other medical institutions.

To investigate the anti-atherosclerotic effects of dietary hesperidin and naringin on ather-osclerosis in rabbits.Twenty-four adult healthy male New Zealand Large White rabbits were ran-domly assigned to four groups based on one factor:control(Con),model(Mod),hesperidin(HP),and naringenin(NG),each containing six rabbits and housed in solitary cages.During the experi-mental period,the control group received normal feed;the model group was fed high-fat for 30 d to establish the atherosclerosis,(AS)model and continued to be fed high-fat feed;the hesperidin and naringenin groups were fed high-fat for 30 d and then underwent AS modeling,and at a later stage,150 mg of hesperidin(or naringenin)was added to the diets at a rate of 1.5 mg per kg of di-et,respectively,for 30 d.Relative body quality,blood lipids,oxidation,and inflammatory factor lev-els were all assessed.At the end of the test period,the test rabbits were sacrificed to obtain the common carotid artery for histopathological section HE staining,Oil red O staining,and Sirius red staining in order to observe vascular tissue structure,lipid and inflammatory cell infiltration,and e-lastic plate and elastic fiber damage.The results indicated that the relative body quality of the mod-el,HP and NG groups increased rapidly,and the difference with the control group within the same period was highly significant(P＜0.01);The HP and NG interventions significantly decreased to-tal cholesterol(TC)and low-density lipoprotein cholesterol(LDL-C)levels(P＜0.01),while also leading to a significant increase in high-density lipoprotein cholesterol(HDL-C)levels(P＜0.01);MDA levels exhibited a significant decrease(P＜0.01),while SOD levels showed a notable in-crease(P＜0.01)following the HP and NG interventions;After HP and NG interventions,TNF-α and IL-1 were regressed(P＜0.01)and IL-10 was significantly elevated(P＜0.01);Compared with the control group,the model group showed approximately 41.8 and 2.5 fold thickening of the maximal endo-medial membrane,respectively,and the HP and NG interventions showed approxi-mately 13 and 15 fold thickening of the maximal endo-medial membrane,and both of the maximal medial membranes thickened by approximately 1.4 fold;Staining of pathological sections showed that HP and NG intervened to significantly reduce inflammatory cell infiltration,deposition of lipid components,slight thickening of the endothelium,and intact fibroblastic components.The results showed that the addition of HP and NG to diets could regulate blood lipids and exert anti-inflam-matory and antioxidant effects by inhibiting the expression of inflammatory factors and oxidizing factors,showing significant anti-AS effects,and the two effects were comparable.

The pathological mechanisms and related physiological indicators of acute mountain sickness(AMS)were introduced,and the present situation of wearable devices applied in AMS auxiliary detection and diagnosis were reviewed.The challenges and future development directions of wearable devices applied in auxiliary detection and diagnosis were pointed out.[Chinese Medical Equipment Journal,2025,46(9):100-107]

Relevant China's literature on the application of brain-computer interface technology in the field of rehabilita-tion of stroke patients was retrieved in the China Knowledge Network database from its establishment to December 31,2024,and CiteSpace visual analysis software was used to analyze the selected literature in terms of trend of annual publica-tion number,author collaboration network,keyword co-occurrences and emergences and to generate a corresponding knowledge map.It's pointed out brain-computer interface technology showed significant application potential for motor function recovery and neurorehabilitation,which had the research hotspots of the cross technologies covering motor imagina-tion,rehabilitation training and virtual reality and the research frontiers of the fusion application of intelligent algorithms of deep learning and pattern recognition.The challenges and future development directions of the field were investigated,and references were provided for promoting the application of brain-computer interface technology to rehabilitation of sroke patients in China.[Chinese Medical Equipment Journal,2025,46(9):65-69]

The pathological mechanisms and related physiological indicators of acute mountain sickness(AMS)were introduced,and the present situation of wearable devices applied in AMS auxiliary detection and diagnosis were reviewed.The challenges and future development directions of wearable devices applied in auxiliary detection and diagnosis were pointed out.[Chinese Medical Equipment Journal,2025,46(9):100-107]