Objective: To observe the changes of circulating fractalkine and its receptor CX3CR1 level in patients with chronic congestive heart failure (CHF).
Methods: Our work included 2 group, CHF group, n=55 patients and Control group, n=25 healthy subjects. Plasma level of soluble fractalkine (sFKN) was measured by ELISA, CX3CR1 in peripheral blood mononuclear cell was examined by lfow cytometry method. The relationship between sFKN and NT-proBNP was studied.
Results: Compared with Control group, CHF group had increased sFKN level, P=0.004, and the patients with NYHY III, IV were more than NYHY II, and CHF group also had the higher CX3CR1 expression (14.7 ± 8.1), P<0.05. The CX3CR1 level increased accordingly with NYHY classiifcation, as the patients with NYHY II, CX3CR1 was at (25.1 ± 12.4), P=0.03 compare with Control group;with NYHY III, CX3CR1 was at (37.3 ± 11.0) , P=0.04 compared with NYHY II;with NYHY IV, CX3CR1 was at (41.7 ± 11.1), P=0.009 compared with NYHY II. The circulating sFKN level was positively related to pro-BNP level (r=0.364, P<0.01).
Conclusion: The circulating FKN l and its receptor CX3CR1 might be involved in pathogenesis of immune-inlfammatory pathogenesis in CHF patients.

Objective To investigate whether timing of image acquisition influenced infarct size estimation using delayed CeMRI,and the association of left ventricular ejection fraction between magnetic resol3anee imaging and left ventrieulography Was also studied.Method From Junary 2005 to April 2006,27 first,onset AMI patients [23 male,mean age(54.3±10.5)years]were enrolledinthistudr.Allpatients receivedleft ventrictdographyas well as coronary angiography.The average checking time was(13.2±5.2)clays after the onset of AMI.MR imaging was performed with a 1.5-T magnet(SIMENS).After breath-hold eine images were acquired,patients re.ceived afI intravenous bolus of 0.05 mmol/kg Gd-DTPA at a rate of 5 ml/8.A first-pass perfusion scan was ac.qllired.Then a second bolus of 0.15 mmoVkg Gd-DTPA was give.at a rate of 2 mE/Is.After the hyperenhancement localized,the typical short axis slice with hyperenhancement WaS chosen to repeat imaging for IlleasuriIin.farct size every5minutesfrom5minutes after secondinjection ofcontrast until 20minutes.Results Twexty-seren patients showed hyperenhancement at the delayed CeMRI and hypoenhancement at the first pass enhancement(FPE).The average infarct size estimated by CeMRI WaS(17.9士9.8)%of LV nlass.Myocardial enhancement at a repesentative short-axis slice WIllS(7.2±6.2)%of LV Imss at 5 minutes,(8.5±7.4)%at 10 minutes,(7.3±6.3)%at 15 minutes and(6.9-t-6.4)%at 20 minutes respectively.There WltlS significant difference be-tween lmfninmes and 20-minutes enhancement size(P<0.05).Correlations of EF obtained by cineventriculo-grapIIy and MR irr,lg were significant(r=0.867,P<0.01).There were also correlations between infarction size and pe.k CK(r:O.819,P

Angelica dahurica,as a medicinal and edible traditional Chinese medicine,is widely used in clinical practice.It is mainly cultivated in Henan,Hebei,Sichuang and Zhejiang provinces.At present,the study found that the main chemical components of this plant contained coumarins,volatile oil,polysaccharides,alkaloids,and amino acids and other components.It has anti-inflammatory,analgesic,anti-oxidant,anti-tumor,whitening effect and other pharmacological activities.In this paper,the chemical composition,pharmacological action of Angelica dahurica were summarized.Based on the core concepts of quality markers,the quality markers of Angelica dahurica were predicted and analyzed from the aspects of plant relativity and chemical component specificity,traditional medicinal properties,traditional efficacy,measurability of chemical components,Sulfur Fumigated,so as to provide reference for establishment and development of quality evaluation system of Angelica dahurica.

Objective:To analyze the frequency and alteration of circulating dendritic cells (DCs) and subtypes in patients with ST‐elevated acute myocardial infarction(AMI) .Methods:A total of 17 patients with ST‐elevated AMI(AMI group) and 14 pa‐tients with stable angina pectoris(SAP) as SAP group and 15 people with normal coronary angiogram with matched age and gender(control group) were enrolled .The absolute number and percentage in peripheral blood mononuclear cells of circulating DCs ,myeloid dendritic cell(mDC) and plasmacytoid dendritic cell(pDC) in the three groups were detected using the 3‐colure staining flow cytometry .The levels of interleukin‐6(IL‐6) and tumor necrosis factor‐α(TNF‐α) were detected with enzyme‐linked immunosorbent assay .In the AMI group ,these indexes were measured on the 7th day after the attack .Results:The per‐centage of circulating DCs in peripheral blood mononuclear cells and the absolute number of DCs ,the percentage of circulating mDC and pDC in peripheral blood mononuclear cells and the absolute numbers of mDC and pDC and mDC/pDC ratio in the AM I group on the day of attack(<24 h) were significantly lower than those in the control group and the SAP group(P<0 .01 or 0 .05) .In the AMI group ,on the 7th day after the attack , the percentages of DCs ,mDC and pDC in peripheral blood mononuclear cells and the absolute numbers of DCs ,mDC and pDC and mDC/pDC ratio were higher than those on the day of attack (P<0 .01 or 0 .05) .The level of IL‐6 and TNF‐αin the AMI group on the day of attack were significantly higher than those in the control group and SAP group(P<0 .05) ,and the level of IL‐6 decreased on the 7th day after the attack in the AMI group (P<0 .05) .But there was no significant difference in the percentage of DCs ,mDC and pDC in peripheral blood mononu‐clear cells and the absolute numbers and mDC/pDC ratio between the control group and the SAP group(P>0 .05) .Conclu‐sions:Circulating mDC and pDC are significantly reduced in patients on the day of attack of AM I ,and it can increase to nearly normal on the 7th day after attack .It indicates that the possibility of DCs recruits into coronary plaques and improve the forma‐tion of unstable plaque .

Objective:To establish a disease risk prediction model for the newborn screening system of inherited metabolic diseases by artificial intelligence technology.Methods:This was a retrospectively study. Newborn screening data ( n=5 907 547) from February 2010 to May 2019 from 31 hospitals in China and verified data ( n=3 028) from 34 hospitals of the same period were collected to establish the artificial intelligence model for the prediction of inherited metabolic diseases in neonates. The validity of the artificial intelligence disease risk prediction model was verified by 360 814 newborns ' screening data from January 2018 to September 2018 through a single-blind experiment. The effectiveness of the artificial intelligence disease risk prediction model was verified by comparing the detection rate of clinically confirmed cases, the positive rate of initial screening and the positive predictive value between the clinicians and the artificial intelligence prediction model of inherited metabolic diseases. Results:A total of 3 665 697 newborns ' screening data were collected including 3 019 cases ' positive data to establish the 16 artificial intelligence models for 32 inherited metabolic diseases. The single-blind experiment ( n=360 814) showed that 45 clinically diagnosed infants were detected by both artificial intelligence model and clinicians. A total of 2 684 cases were positive in tandem mass spectrometry screening and 1 694 cases were with high risk in artificial intelligence prediction model of inherited metabolic diseases, with the positive rates of tandem 0.74% (2 684/360 814)and 0.46% (1 694/360 814), respectively. Compared to clinicians, the positive rate of newborns was reduced by 36.89% (990/2 684) after the application of the artificial intelligence model, and the positive predictive values of clinicians and artificial intelligence prediction model of inherited metabolic diseases were 1.68% (45/2 684) and 2.66% (45/1 694) respectively. Conclusion:An accurate, fast, and the lower false positive rate auxiliary diagnosis system for neonatal inherited metabolic diseases by artificial intelligence technology has been established, which may have an important clinical value.