ObjectiveTo observe the clinical efficacy of the Yiqi Yangyin Huoxue prescription （YYHP） in the treatment of cathartic colon （CC） and its effects on fecal short-chain fatty acids （SCFAs）， and to explore the correlations among CC severity indicators and between these indicators and patient history. MethodsAccording to the inclusion and exclusion criteria， 98 patients meeting the diagnostic criteria of both traditional Chinese and Western medicine for CC with the syndrome of Qi-Yin deficiency complicated by blood stasis were randomly assigned to an observation group and a control group. The observation group received YYHP granules， while the control group received lactulose. Both medications were administered twice daily， one sachet each time， half an hour after breakfast and dinner， with a treatment course of 8 weeks. The primary constipation symptom score， Patient Assessment of Constipation Quality of Life （PAC-QOL） score， and TCM syndrome score were assessed before and after treatment and at the 8^th week after the end of treatment. The overall clinical effective rate， as well as the efficacy attenuation index and degree， were evaluated. Fecal SCFA levels were measured using gas chromatography-mass spectrometry （GC-MS）. Spearman correlation analysis was performed to explore the correlations among CC severity indicators and between these indicators and patient history. ResultsThe overall clinical effective rate in the observation group （95.83%） was higher than that in the control group （78.72%） （P<0.05）. After treatment， the total scores for primary constipation symptoms， PAC-QOL， and TCM syndromes decreased in both groups （P<0.05）， with more significant reductions in the observation group （P<0.05）. The severity of all primary constipation symptoms was alleviated in both groups （P<0.05）. In terms of "excessive straining and difficult defecation"， "anal heaviness， incomplete evacuation， and bloating sensation"， "abdominal distension"， and "defecation frequency"， the observation group showed better efficacy than the control group （P<0.05）. Scores of the four PAC-QOL dimensions and the scores and severity of primary and secondary TCM symptoms were reduced in both groups （P<0.05）， with more significant reductions in the observation group （P<0.05）. After treatment， acetic acid， propionic acid， butyric acid， and total SCFAs in the observation group increased significantly （P<0.05）. The efficacy attenuation index and degree in the observation group were lower than those in the control group （P<0.05）. No severe adverse reactions occurred in either group， and there was no statistically significant difference in the incidence of adverse reactions between the two groups. Positive correlations of varying degrees were observed among the total scores of primary constipation symptoms， PAC-QOL， and TCM syndromes， as well as between these scores and the history of stimulant laxative use， disease duration， and age. ConclusionYYHP can effectively alleviate the primary constipation symptoms in CC patients， improve quality of life， and ameliorate TCM syndromes， with good safety. It also has the advantage of a lower rebound degree after drug withdrawal， and its mechanism may be related to increasing fecal SCFA levels. Long-term abuse of stimulant laxatives may aggravate the severity of CC and prolong the disease course.

ObjectiveTo conduct a theoretical study on the medical-rehabilitation integration. MethodsStarting from the background, objectives and content of the medical-rehabilitation integration, this study analyzed its innovative points from the dimensions of conceptual innovation, organizational innovation, model innovation and technological innovation. Results and ConclusionThe medical-rehabilitation integration is an innovation in medical services that takes conceptual innovation as the forerunner, organizational innovation as the foundation, model innovation as the carrier and technological innovation as the core.

Traditional Chinese medicine(TCM) decoction pieces are a core carrier for the inheritance and innovation of TCM, and their quality and safety are critical to public health and the sustainable development of the industry. Conventional quality control models, while having established a well-developed system through long-term practice, still face challenges such as relatively long inspection cycles, insufficient objectivity in characterizing complex traits, and urgent needs for improving the efficiency of integrating multidimensional quality information when confronted with the dual demands of large-scale production and precision quality control. With the rapid development of artificial intelligence, machine learning can deeply analyze multidimensional data of the morphology, spectroscopy, and chemical fingerprints of decoction pieces by constructing high-dimensional feature space analysis models, significantly improving the standardization level and decision-making efficiency of quality evaluation. This article reviews the research progress in the application of machine learning in the processing, production, and rapid quality evaluation of TCM decoction pieces. It further analyzes current challenges in technological implementation and proposes potential solutions, offering theoretical and technical references to advance the digital and intelligent transformation of the industry.
Machine Learning ; Drugs, Chinese Herbal/standards* ; Quality Control ; Medicine, Chinese Traditional/standards* ; Humans

OBJECTIVES: To investigate the clinical sub-phenotype (SP) of pediatric acute kidney injury (AKI) and their association with clinical outcomes. METHODS: General status and initial values of laboratory markers within 24 hours after admission to the pediatric intensive care unit (PICU) were recorded for children with AKI in the derivation cohort (n=650) and the validation cohort (n=177). In the derivation cohort, a least absolute shrinkage and selection operator (LASSO) regression analysis was used to identify death-related indicators, and a two-step cluster analysis was employed to obtain the clinical SP of AKI. A logistic regression analysis was used to develop a parsimonious classifier model with simplified metrics, and the area under the curve (AUC) was used to assess the value of this model. This model was then applied to the validation cohort and the combined derivation and validation cohort. The association between SPs and clinical outcomes was analyzed with all children with AKI as subjects. RESULTS: In the derivation cohort, two clinical SPs of AKI (SP1 and SP2) were identified by the two-step cluster analysis using the 20 variables screened by LASSO regression, namely SP_d1 group (n=536) and SP_d2 group (n=114). The simplified classifier model containing eight variables (P<0.05) had an AUC of 0.965 in identifying the two clinical SPs of AKI (P<0.001). The validation cohort was clustered into SP_v1 group (n=156) and SP_v2 group (n=21), and the combined derivation and validation cohort was clustered into SP1 group (n=694) and SP2 group (n=133). After adjustment for confounding factors, compared with the SP1 group, the SP2 group had significantly higher incidence rates of multiple organ dysfunction syndrome and death during the PICU stay (P<0.001), and SP2 was significantly associated with the risk of death within 28 days after admission to the PICU (P<0.001). CONCLUSIONS This study establishes a parsimonious classifier model and identifies two clinical SPs of AKI with different clinical features and outcomes.The SP2 group has more severe disease and worse clinical prognosis.
Humans ; Acute Kidney Injury/diagnosis* ; Prognosis ; Male ; Female ; Child ; Child, Preschool ; Phenotype ; Infant ; Logistic Models ; Adolescent

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

OBJECTIVES: With the accelerating aging of the population and the rising prevalence of chronic diseases, the number of patients with pressure injuries (PIs) has increased markedly, prolonging the period of disease-related care. Informal caregivers play a critical role in the daily care of patients with pressure injuries, and their care burden has become increasingly prominent. This study aims to investigate the current status and influencing factors of care burden among informal caregivers of patients with PIs, providing evidence for targeted intervention strategies. METHODS: A total of 170 informal caregivers of patients with PIs were selected by convenience sampling from the Third Xiangya Hospital of Central South University. General demographic and clinical data of both patients and caregivers were collected. The Zarit Caregiver Burden Inventory (ZBI), Knowledge-Attitude-Practice Scale for Informal Caregivers of Patients with PIs, General Self-Efficacy Scale (GSES), and Family Caregiver Task Inventory (FCTI) were used to assess caregiving burden, knowledge-attitude-practice level, self-efficacy, and caregiving ability, respectively. Pearson correlation analysis was conducted to evaluate relationships among ZBI, Knowledge-Attitude-Practice Scale for Informal Caregivers of Patients with PIs, GSES, and FCTI scores. Stepwise multiple linear regression analysis was used to identify factors influencing caregiving. RESULTS: Among the 170 patients with pressure injuries, the age was (65.52±15.88) years; 118 (69.41%) were male and 52 (30.59%) were female. The duration of PIs was less than 1 month in 108 (63.53%) cases and 1 to 6 months in 40 cases (23.53%). Stage II injuries were predominant (135 cases, 79.41%). A total of 193 pressure injury sites were recorded, most commonly located at the sacrococcygeal region (127 sites, 65.80%), followed by the head (3 sites, 1.55%), shoulder and back (9 sites, 4.66%), feet (24 sites, 12.44%), and other regions (30 sites, 15.55%). Informal caregivers were 48.82% aged 46 to 59 years, 54.71% female, 41.77% primarily spouses and 47.06% children of the patients, and 77.06% lived with the patients. Caregivers who received assistance from others or had higher family per-capita monthly income reported significantly lower caregiver burden scores than those without assistance or with lower income (all P<0.001). The total ZBI score was 50.89±14.95, indicating a moderate burden. The total scores of the Knowledge-Attitude-Practice Scale for Informal Caregivers, GSES, and FCTI were 50.61±7.22, 26.03±7.11, and 14.76±8.70, respectively. Pearson correlation analysis revealed that ZBI scores were correlated with scores on the Knowledge-Attitude-Practice Scale for Informal Caregivers of Patients with PIs (r=-0.543, P<0.001), GSES scores (r=-0.545, P<0.001), and FCTI scores (r=0.800, P<0.001). The scores on Knowledge-Attitude-Practice Scale for Informal Caregivers of patients with PIs were correlated with GSES scores (r=0.500, P<0.001) and FCTI scores (r=-0.461, P<0.001); GSES scores was negatively correlated with FCTI scores (r=-0.415, P<0.001). Stepwise multiple linear regression analysis showed that assistance availability, family per-capita monthly income, total scores on the Knowledge-Attitude-Practice Scale for Informal Caregivers of Patients with PIs, total GSES score, and total FCTI score were the main influencing factors of caregiver burden, jointly explaining 79.38% of its variance. CONCLUSIONS The main factors influencing the caregiving burden of informal caregivers of patients with PIs include the availability of assistance, family per-capita monthly income, total score on the Knowledge-Attitude-Practice Scale for Informal Caregivers of PI patients, total score on the GSES, and total score on the FCTI. Developing targeted intervention strategies addressing these factors may help alleviate the caregiving burden among informal caregivers of patients with PIs.
Humans ; Caregivers/psychology* ; Pressure Ulcer/nursing* ; Female ; Male ; Middle Aged ; Cost of Illness ; Adult ; Aged ; Surveys and Questionnaires ; Health Knowledge, Attitudes, Practice ; Self Efficacy ; Caregiver Burden ; China

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 protective effect of resveratrol on myocardial damage caused by sepsis in rats.Methods Forty SD rats were randomly divided into control group,model group,experimental group and combined group,with 10 rats in each group.Except the control group,the other rats were intraperitoneally injected with 20 mg·kg-1 lipopolysaccharide,while the control group was injected with the same amount of normal saline.Two hours before modeling,the experimental group and combinated group were given 50 mg·kg-1 resveratrol by gavage,and the control group and model group were given the same amount of normal saline by gavage.The combined group was injected with 10 nmol of micro RNA-155(miR-155)agomir through the tail vein,and the other group was injected with equal volume of normal saline through the tail vein.Left ventricular function parameters of rats were measured by echocardiography.The level of myocardial injury markers was detected by colorimetry.Quantitative reverse transcription polymerase chain reaction was used to detect the expression of miR-155.The expression of sirtuin 1(SIRT1)and related proteins of nuclear factor κB signaling pathway were detected by Western blot.Results The left ventricular ejection fraction of control group,model group and experimental group were(80.78±12.85)％,(55.92±7.86)％and(71.55±10.71)％,respectively;left ventricular fractional shortening were(34.08±5.75)％,(22.92±2.96)％,(28.72±4.25)％,respectively;left ventricular end disatolic diameter were(3.12±0.46),(6.34±0.69),(4.95±0.57)mm,respectively;the left ventricular end systolic diameter were(5.98±0.65),(7.24±0.80),(6.16±0.78)mm,respectively;the fractional shortening were(38.91±5.38)％,(22.67±3.53)％,(30.74±3.97)％,and the expression levels of creatine kinase-MB were(661.56±85.44),(1181.41±142.14),(915.02±105.19)U·L-1,respectively;the expressions levels of cardiac troponin Ⅰ were(148.17±28.48),(448.17±60.34)and(375.44±49.01)ng·mL-1,respectively.The expression of miR-155 in control group,model group,experimental group and combined group were 1.00±0.12,3.79±0.45,1.87±0.23 and 4.03±0.49,respectively;the protein relative expression levels of nuclear factor κB(NF-κB)were 1.00±0.08,5.04±0.59,2.73±0.35,5.58±0.63,respectively;the protein relative expression levels of inhibitor of NF-κB-β were 1.00±0.11,3.03±0.37,1.35±0.15 and 2.89±0.34,respectively;the protein relative expressions of inhibitor of NF-κB-α were 1.00±0.13,0.86±0.08,1.21±0.18,0.77±0.09,respectively;the protein relative expression levels of SIRT1 were 1.00±0.16,0.66±0.07,0.93±0.14,0.54±0.06,respectively.The above indicators of the model group were compared with the control group,the experimental group were compared with the model group,and the above indicators of the combined group were compared with the experimental group,and the differences were statistically significant(all P＜0.05).Conclusion Resveratrol can alleviate myocardial injury and improve cardiac function in sepsis rats,which may be achieved by down-regulating the expression of miR-155,up-regulating the level of SIRT1,and inhibiting the nuclear factor κB signaling pathway.

As a non-invasive imaging modality,cardiac magnetic resonance(CMR)enables a"one-stop"in vivo assessment of cardiac morphology,structure,functional status and histological features,plays an irreplaceable role in the diagnosis,prognosis and risk stratification of cardiovascular diseases.In 2024,CMR has made continuous progress towards precision medicine.Upgraded technologies such as tissue characterization imaging and myocardial strain analysis,are gradually transformed into standard clinical practice.Artificial intelligence and other new algorithms have improved the quality and efficiency of CMR.The application of CMR in non-ischemic heart disease,ischemic heart disease and other areas is highly valued in the new version of various guidelines,highlighting the importance of CMR in the clinical management of cardiovascular diseases.This article aims to systematically review representative achievements of CMR in 2024 from the perspectives of both technological innovation and clinical translation,providing the latest update in this field.