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.

This study selected 6 529 plant-based Chinese materia medica(PCMM) from Chinese Materia Medica as research subjects and applied a random permutation test to explore the overall correlation characteristics between nature and flavor, as well as the correlation characteristics after distinguishing different medicinal parts and harvest seasons. The results showed that the overall correlation characteristics between nature and flavor in PCMM were significantly associated in the following pairs: cold and bitter, cool and bitter, cool and astringent, cool and light, neutral and sweet, neutral and astringent, neutral and light, neutral and sour, hot and pungent, and warm and pungent. When analyzing the data by distinguishing medicinal parts and/or harvest seasons, new correlation patterns emerged, characterized by the disappearance of some significant correlations and the emergence of new ones. When analyzing by medicinal parts alone, significant correlations were found in the following cases: cold and light in leaves, cold and salty in barks, cool and sweet in fruits and seeds, neutral and pungent in whole herbs, neutral and salty in stems, and warm and salty in flowers. However, no significant correlations were found between cool and bitter in stems and other types of herbs, cool and astringent in fruits, seeds, flowers, and other types of herbs, cool and light in leaves, fruits, seeds, barks, flowers and other types of herbs, neutral and sweet in barks, neutral and astringent in whole herbs and stems, neutral and light in leaves, fruits, seeds, and flowers, neutral and sour in whole herbs, stems, barks, flowers, and other types of herbs, and hot and pungent in whole herbs, stems, flowers, and other types of herbs. When analyzing by harvest season alone, significant correlations were found in the following cases: cold and salty, and cool and sour in herbs harvested in winter, and neutral and salty in herbs harvested year-round. However, no significant correlation was found between cool and light in herbs harvested in winter. When considering both medicinal parts and harvest seasons, compared to the independent influence of medicinal parts, 14 new significant correlations emerged(e.g., the correlation between cool and bitter in stems harvested in spring), while 53 previously significant correlations disappeared(e.g., the correlation between cool and bitter in barks harvested in summer). Compared to the independent influence of harvest seasons, 11 new significant correlations appeared(e.g., the correlation between cold and light in barks harvested in autumn), while 50 previously significant correlations disappeared(e.g., the correlation between hot and pungent in leaves harvested in winter). This study is the first to reveal the influence of medicinal parts and harvest seasons on the correlation between nature and flavor in PCMM, which highlights that these two factors can interact and jointly affect nature-flavor correlations. Further research is needed to explore the underlying mechanisms. This study provides a deeper understanding of the inherent scientific connotations of herbal properties and offers a theoretical foundation for the cultivation and harvesting of PCMM.
Seasons ; Plants, Medicinal/growth & development* ; Drugs, Chinese Herbal/chemistry* ; Taste

Objective To investigate the clinical and pathological characteristics of adrenal cortical carcinoma(ACC),compare differences between hypercortisolism and non-functional ACC,and assess the diagnostic value of indicators such as Ki-67 index.Methods The clinical data of 57 ACC patients admitted to the First Medical Center of Chinese PLA General Hospital from January 2015 to March 2025 were retrospectively analyzed.According to the results of endocrine function assessment,47 of these patients were divided into hypercortisolism group(n=19)and non-functional group(n=28).The differences in clinical and pathological characteristics between the two groups were compared,and non-parametric tests and Spearman correlation analysis were used to explore the relationship between Ki-67 index and tumor stage as well as imaging features.Results Among the 57 patients,there were 20 males and 37 females,with a male-to-female ratio of 1:1.85.The age ranged from 16 to 76 years,and the age at diagnosis was(48.7±13.3)years.The tumor diameter was(10.53±4.14)cm.The tumors were located on the right side in 12 cases(21.1%),on the left side in 34 cases(59.6%),and bilaterally in 11 cases(19.3%).Among them,16 cases(28.1%)were complicated with glucose metabolism disorders,31 cases(54.3%)had hypertension,and 20 cases(35.1%)had hypokalemia.According to ENSAT staging,there were 0 cases in stage Ⅰ,15 cases(26.3%)in stage Ⅱ,24 cases(42.1%)in stage Ⅲ,and 18 cases(31.6%)in stage Ⅳ.Endocrine function assessment was completed in 47 of the 57 patients,including 28 cases(59.6%)of non-functional ACC and 19 cases(40.4%)of hypercortisolism(including 1 case of hypercortisolism combined with increased sex hormone secretion).Compared with non-functional group,hypercortisolism group had a significantly higher prevalence of hypertension(P=0.014),later ENSAT stage(P=0.010),and a higher proportion of hypervascularization(P=0.048).The median Ki-67 index was 20%(10%-40%),showing no significant correlation with either the maximum tumor diameter or SUVmax value,but it was related to ENSAT staging,with Ki-67 index in stageⅣ patients being significantly higher than that in stage Ⅱ(P=0.032).Immunohistochemistry results showed that the positive rate of Inhibin-α was 84.8%,and the positive rate of Melan-A was 40.9%.Conclusions ACC is a rare malignant endocrine tumor.ACC patients with hypercortisolism are more likely to be complicated with hypertension,have later staging,and more common hypervascular manifestations.Clinically,their endocrine function should be prioritized for assessment,and more active treatment strategies should be adopted.Diagnosis should be combined with imaging characteristics(such as hypervascularization)and immunohistochemical indicators(Ki-67,Inhibin-α,Melan-A).The significant increase in Ki-67 is in the advanced stage can serve as an important prognostic indicator to guide individualized treatment.

Aim To investigate the effect of dihydro-myricetin(DMY)on Ang Ⅱ-induced cardiac hypertro-phy in mice and the underlying mechanisms.Methods Fifty mice were randomly divided into control group,Ang Ⅱ group,Ang Ⅱ+catopril 12.0 mg·kg-1·d-1 group,AngⅡ+DMY 100 mg·kg-1·d-1 group,and Ang Ⅱ+DMY 200 mg·kg-1·d-1 group,with 10 mice in each group.The control mice were given saline by gavage,the drug intervention group was given DMY,and the positive drug group was given captopril;the mice in all groups except the control group were in-jected subcutaneously with Ang Ⅱ 1.0mg·kg-1·d-1.After four weeks,heart weight/body weight(HW/BW)and left ventricular weight/body weight(LVW/BW)ratios were calculated.The mRNA ex-pression of the fetal genes atrial natriuretic factor(ANF),brain natriuretic peptide(BNP),β-myosin heavy chain(β-MHC),adenosine triphosphate 5β-subunit(ATP 5β)and uncoupling protein 2(UCP2)were monitored,and the morphological changes of car-diac tissue were observed.Secondly,the creatine ki-nase isoenzyme(CK-MB),lactate dehydrogenase(LDH),free fatty acids(FFA)and lactic acid in ser-um were investigated.Lastly,the expression of AMP-activated proteinkinase(AMPK),peroxisome prolifer-ator-activated receptor alpha(PPAR-α)and T-cell nu-clear factor cytoplasmic 4(NFATc4)protein expres-sion were also detected.The Ang Ⅱ-induced H9C2 cardiomyocyte hypertrophy model was established and treated with the AMPK inhibitor compound C.The mRNA of ANF,BNP,β-MHC and the protein expres-sion of AMPK/PPAR-α were analyzed.Results DMY intervention significantly reduced HW/BW and LVW/BW in mice,fetal genes ANF,BNP,β-MHC and UCP2 mRNA expression decreased,whereas ATP 5 β mRNA increased,and the degree of hypertrophy of cardiomyocytes was alleviated.In addition,the serum levels of CK-MB,LDH,FFA and lactic acid were re-duced in DMY treated groups.Finally,DMY upregu-lated the protein expression of P-AMPK,AMPK and PPAR-α,and downregulated protein expression of NFATc4.In the Ang Ⅱ-induced cardiomyocyte hyper-trophy model,DMY pretreatment reduced the mRNA expression of fetal genes(ANF,BNP,β-MHC).However,when AMPK was inhibited by compound C,the expression of these fetal genes rebounded,accom-panied by decreased protein levels of AMPK and PPAR-α.Conclusions DMY can improve Ang Ⅱ-in-duced myocardial hypertrophy in mice by ameliorating disorders of glycolipid metabolism and increasing ener-gy supply to cardiomyocytes,and its mechanism is re-lated to the activation of the AMPK/PPAR-α pathway and the inhibition of NFATc4 expression.

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.

Aim To investigate the effect of dihydro-myricetin(DMY)on Ang Ⅱ-induced cardiac hypertro-phy in mice and the underlying mechanisms.Methods Fifty mice were randomly divided into control group,Ang Ⅱ group,Ang Ⅱ+catopril 12.0 mg·kg-1·d-1 group,AngⅡ+DMY 100 mg·kg-1·d-1 group,and Ang Ⅱ+DMY 200 mg·kg-1·d-1 group,with 10 mice in each group.The control mice were given saline by gavage,the drug intervention group was given DMY,and the positive drug group was given captopril;the mice in all groups except the control group were in-jected subcutaneously with Ang Ⅱ 1.0mg·kg-1·d-1.After four weeks,heart weight/body weight(HW/BW)and left ventricular weight/body weight(LVW/BW)ratios were calculated.The mRNA ex-pression of the fetal genes atrial natriuretic factor(ANF),brain natriuretic peptide(BNP),β-myosin heavy chain(β-MHC),adenosine triphosphate 5β-subunit(ATP 5β)and uncoupling protein 2(UCP2)were monitored,and the morphological changes of car-diac tissue were observed.Secondly,the creatine ki-nase isoenzyme(CK-MB),lactate dehydrogenase(LDH),free fatty acids(FFA)and lactic acid in ser-um were investigated.Lastly,the expression of AMP-activated proteinkinase(AMPK),peroxisome prolifer-ator-activated receptor alpha(PPAR-α)and T-cell nu-clear factor cytoplasmic 4(NFATc4)protein expres-sion were also detected.The Ang Ⅱ-induced H9C2 cardiomyocyte hypertrophy model was established and treated with the AMPK inhibitor compound C.The mRNA of ANF,BNP,β-MHC and the protein expres-sion of AMPK/PPAR-α were analyzed.Results DMY intervention significantly reduced HW/BW and LVW/BW in mice,fetal genes ANF,BNP,β-MHC and UCP2 mRNA expression decreased,whereas ATP 5 β mRNA increased,and the degree of hypertrophy of cardiomyocytes was alleviated.In addition,the serum levels of CK-MB,LDH,FFA and lactic acid were re-duced in DMY treated groups.Finally,DMY upregu-lated the protein expression of P-AMPK,AMPK and PPAR-α,and downregulated protein expression of NFATc4.In the Ang Ⅱ-induced cardiomyocyte hyper-trophy model,DMY pretreatment reduced the mRNA expression of fetal genes(ANF,BNP,β-MHC).However,when AMPK was inhibited by compound C,the expression of these fetal genes rebounded,accom-panied by decreased protein levels of AMPK and PPAR-α.Conclusions DMY can improve Ang Ⅱ-in-duced myocardial hypertrophy in mice by ameliorating disorders of glycolipid metabolism and increasing ener-gy supply to cardiomyocytes,and its mechanism is re-lated to the activation of the AMPK/PPAR-α pathway and the inhibition of NFATc4 expression.

Objective To investigate the incidence rate,clinical characteristics,and prognosis of neonatal stroke in Shenzhen,China.Methods Led by Shenzhen Children's Hospital,the Shenzhen Neonatal Data Collaboration Network organized 21 institutions to collect 36 cases of neonatal stroke from January 2020 to December 2022.The incidence,clinical characteristics,treatment,and prognosis of neonatal stroke in Shenzhen were analyzed.Results The incidence rate of neonatal stroke in 21 hospitals from 2020 to 2022 was 1/15 137,1/6 060,and 1/7 704,respectively.Ischemic stroke accounted for 75％(27/36);boys accounted for 64％(23/36).Among the 36 neonates,31(86％)had disease onset within 3 days after birth,and 19(53％)had convulsion as the initial presentation.Cerebral MRI showed that 22 neonates(61％)had left cerebral infarction and 13(36％)had basal ganglia infarction.Magnetic resonance angiography was performed for 12 neonates,among whom 9(75％)had involvement of the middle cerebral artery.Electroencephalography was performed for 29 neonates,with sharp waves in 21 neonates(72％)and seizures in 10 neonates(34％).Symptomatic/supportive treatment varied across different hospitals.Neonatal Behavioral Neurological Assessment was performed for 12 neonates(33％,12/36),with a mean score of(32±4)points.The prognosis of 27 neonates was followed up to around 12 months of age,with 44％(12/27)of the neonates having a good prognosis.Conclusions Ischemic stroke is the main type of neonatal stroke,often with convulsions as the initial presentation,involvement of the middle cerebral artery,sharp waves on electroencephalography,and a relatively low neurodevelopment score.Symptomatic/supportive treatment is the main treatment method,and some neonates tend to have a poor prognosis.

As artificial intelligence technology rapidly advances, its deployment within the medical sector presents substantial ethical challenges. Consequently, it becomes crucial to create a standardized, transparent, and secure framework for processing medical data. This includes setting the ethical boundaries for medical artificial intelligence and safeguarding both patient rights and data integrity. This consensus governs every facet of medical data handling through artificial intelligence, encompassing data gathering, processing, storage, transmission, utilization, and sharing. Its purpose is to ensure the management of medical data adheres to ethical standards and legal requirements, while safeguarding patient privacy and data security. Concurrently, the principles of compliance with the law, patient privacy respect, patient interest protection, and safety and reliability are underscored. Key issues such as informed consent, data usage, intellectual property protection, conflict of interest, and benefit sharing are examined in depth. The enactment of this expert consensus is intended to foster the profound integration and sustainable advancement of artificial intelligence within the medical domain, while simultaneously ensuring that artificial intelligence adheres strictly to the relevant ethical norms and legal frameworks during the processing of medical data.
Artificial Intelligence/legislation & jurisprudence* ; Humans ; Consensus ; Computer Security/standards* ; Confidentiality/ethics* ; Informed Consent/ethics*

Headache is a common clinical complication of ischemic stroke. As a precursor of stroke, headache occurs repeatedly in the convalescent period of ischemic stroke, leading to secondary stroke and seriously hindering patients' rehabilitation. Currently, it is believed that the pathogenesis of ischemic stroke-related headache is associated with the abnormal release of vasoactive substances, high platelet aggregation, and stimulation of intracranial pain-sensitive structures. The active ingredients in traditional Chinese medicines(TCM) with the effects of activating blood to resolve stasis and clearing heat to release exterior can protect brain tissue and relieve headache by reducing the release of inflammatory cytokines, alleviating antioxidant stress, inhibiting neuronal apoptosis and so on. This paper introduces the research progress in the potential mechanism and TCM treatment of ischemic stroke-related headache, aiming to provide reference for further research and drug development of this complication.
Humans ; Ischemic Stroke/drug therapy* ; Brain Ischemia/drug therapy* ; Medicine, Chinese Traditional ; Stroke/drug therapy* ; Headache/drug therapy* ; Drugs, Chinese Herbal/therapeutic use*