Objective To investigate the expressions of interferon γ(IFNγ), interferon inducible protein-10(IP-10). chemokine receptor CXCR3 and their significance in infection-associated hemophagocytic syndrome(IAHPS). Methods Forty-three patients with IAHPS, 35 infection patients without HPS and 25 healthy controls were included in the study. The serum IFNγ and IP-10 levels were measured by enzyme linked immunosorbent assay(ELISA). The expression of CXCR3 on cell surface of CD_4~+ and CD_8~+ T cells in peripheral blood was determined by flow cytometry. SPSS 13.0 was used for data processing, and independent-sample t test was performed to compare the differences among the groups. Results The serum IFNγ and IP-10 levels in patients with IAHPS were( 608±135) pmol/L and(939±141) pmol/L respectively, which were significantly higher than those in without HPS group[(154±45) pmol/L and (385±119) pmol/L, t=4.97 and 4.02, P<0.05] and healthy controls[(56±18) pmol/L and (248±98) pmol/L, t=5.27 and 4.77, P<0.05]. The expressions of CXCR3 on CD_4~+ and CD_8~+ T cells in IAHPS group were (35±11)% and (23±8)% respectively, which were significantly higher than those in without HPS group[(24±7)% and (16±7)%, t=3.12 and 3.62, P<0.05] and healthy controls[(20±6)% and (12±5)%, t=4.46 and 4.93, P<0.05]. Conclusion The expressions of IFNγ, IP-10 and CXCR3 are increased significantly in patients with IAHPS, which may be related to the disease pathogenesis.

Objective By analysis of the key performance indexes of the clinical laboratory automation system, to clarify the advantage and optimize the comprehensive performance of the laboratory automation system.Methods Key performance indexes were Collected from January 2017 to April 2017 in biochemistry and immunoassay group of Clinical Laboratory of Shanghai Tong Ren Hospital.(1)The data were collected and compared by the before-and-after method,the starting time of the automation system and initial sample test were analyzed.(2)Key performance indexes were analyzed for the time of specimen registration,inspection,and reporting.(3)The specimen turnaround time(TAT)was analyzed based on two months operation of the laboratory automation system.In view of disadvantage of infectious assays, setting up priority sample absorption, then TAT performance was re-evaluated.(4)By the assessment of total serum dosage required in the automation system, the number of blood vacuum tubes were reduced reasonably.The pros and cons of laboratory automation system were analyzed and the potential improvement were proposed.Results (1)According to the sample peak shift forward,the system start time could move forward 30 minutes earlier.(2)With the adopting of railway logistics,the specimens were sent to the lab and the registration time was at 7:25 am,and the time required for specimen delivery was greatly reduced which made specimen test,report and audit time all moved forward accordingly.(3)Data has shown that specimen TAT declined dramatically based on the performance of the first two month operation of the automation system,biochemical items were shortened 2 h,and the immunoassay shortened 4 h,respectively.Moreover the trend keeps better gradually.With setting up priority absorption infectious tests,the TAT was improved greatly,TAT reduced the average by 40 min.(4)500 μl(including the sample in dead space of vacuum tube)were needed for all the 65 biochemical items included in the system, and 1 495 μl serum were used for the 28 immunoassay.As a result, a total of 2 000 μl serum will be enough for sample analysis by the system, which provided the feasibility to reduce 3 vacuum tubes averagely.Considering the current automation system does not include all the analysis items in our lab directory, a few tests remain to be performed on offline instruments respectively.The methodology for some infectious agents are different from previous method, therefore some test results may need a period of time for comprehensive clinical appreciation.Furthermore,due to the parallel connection of multiple instruments included in the system, more rigorous and frequent quality control becomes a necessity,which may rely on more strict quality control procedure to guarantee the quality.Conclusions The application of the automation system significantly enhanced the efficiency of clinical laboratory all round.In addition, by the quantitative indicators, it is possible to monitor the system operation performance real time, which may feedback and facilitate the improvement constantly,and result in auto confirmation the majority results,eventually.

Objective To explore the predictive value of serum uric acid on new-onset cholelithiasis.Methods The retrospective cohort study was conducted.The data of 97 469 subjects who participated health examination at the Kailuan General Hospital Affiliated to the North China University of Science and Technology,Kailuan Linxi Hospital,Kailuan Zhaogezhuang Hospital,Kailuan Tangjiazhuang Hospital,Kailuan Fan'gezhuang Hospital,Kailuan Lyujiatuo Hospital,Kailuan Jinggezhuang Hospital,Kailuan Linnancang Hospital,Kailuan Qianjiaying Hospital,Kailuan Majiagou Hospital and Kailuan Branch Hospital from June 2006 to December 2015 were collected.Epidemiological investigation,anthropometric parameters and biochemical indicators were collected.All the subjects were allocated into 4 groups according to squartiles of serum uric acid:24 140 with serum uric acid ＜232 μmol/L in the Q1 group,24 473 with 232 μmol/L≤ serum uric acid ＜282 μmol/L in the Q2 group,24 382 with 282 μmol/L≤ serum uric acid ＜338 μmol/L in the Q3 group and 24 474 with serum uric acid ≥ 338 μmol/L in the Q4 group.Observation indicators:(1) comparisons of clinical characteristics among the 4 groups;(2) incidence of cholelithiasis in the 4 groups;(3) effects of serum uric acid on the new-onset cholelithiasis:① the dose-response relationship between serum uric acid and the risk of cholelithiasis,② comparisons of the fitting degree of serum uric acid on the cholelithiasis model,③ effects of different serum uric acid levels on incidence of cholelithiasis after stratification by sex,④ serum uric acid of different gender on the boxplots,⑤ effects of different serum uric acid levels on the incidence of cholelithiasis after stratification by age.Measurement data with normal distribution were expressed as (x)±s,and comparisons among groups were analyzed using the one-way ANOVA.Measurement data with skewed distribution is expressed by M (Q),and comparisons among groups were analyzed using the nonparametric Krustal-willis test.Count data were represented by percentage,and comparisons among groups were analyzed using chi-square test.The incidences of cholethiasis in 4 groups of different serum uric acid were calculated by person-year incidence.Restrictive cubic spline regression was used to calculate the dose-response relation between the continuous variable and the risks of new-onset cholelithiasis and 95％ confidence interval (CI).COX regression model was used to analyze the hazard ratio (HR) and 95％ CI of different serum uric acid levels on new-onset cholelithiasis.Likelihood ratio test and akaike information criterion (AIC) were used to calculate the fitting degree of serum uric acid on new-onset cholelithiasis model.Boxplots were used to describe serum uric acid in different genders.Results (1) comparisons of clinical characteristics among the 4 groups:sex (male),age,body mass index (BMI),systolic pressure,diastolic pressure,fasting plasma glucose (FPG),total cholesterol (TC),triglyceride (TG),high sensitive C-reactive protein,diabetes,hypertension,smoking,drinking and physical exercise were 15 162,(50± 11) years,(24±3)kg/m2,(123±21)mmHg (1 mmHg=0.133 kPa),(82± 12)mmHg,(5.6±2.0) mmol/L,(4.8±1.2) mmol/L,1.14 mmol/L (range,0.81-1.63 mmol/L),0.70 mmol/L (range,0.23-2.23 mmol/L),2 537,9 415,4575,2380,2 649 in the Q1 group,19 079,(51±12) years,(25±3)kg/m2,(130±21)mmHg,(83±12) mmHg,(5.5 ± 1.7) mmol/L,(4.9 ± 1.2) mmol/L,1.20 mmol/L (range,0.86-1.76 mmol/L),0.71 mmol/L (range,0.28-1.98 mmol/L),2 287,10 124,6 918,3 649,3 288 in the Q2 group,21 132,(52±13)years,(25±3)kg/m2,(132±21)mmHg,(84±12)mmHg,(5.5±1.6)mmol/L,(5.0±1.2) mmol/L,1.29 mmol/L (range,0.91-1.94 mmol/L),0.80 mmol/L (range,0.30-2.06 mmol/L),2 027,10 755,8 259,4 730,3 958 in the Q3 group,22 651,(53± 14) years,(26± 3) kg/m2,(134± 21) mmHg,(85±12)mmHg,(5.4±1.5)mmol/L,(5.1±1.2)mmol/L,1.54 mmol/L (range,1.05-2.35 mmol/L),1.02 mmol/L (range,0.43-2.50 mmol/L),1 981,12 082,9 562,6 209,4 758 in the Q4 group,respectively,with statistically significant differences among the 4 groups (x2 =7 624.63,F=279.93,961.91,330.84,271.40,38.25,353.18,H =3 406.30,912.23,x2 =108.15,590.49,2567.07,2 209.21,760.15,P＜0.05).(2)Incidence of cholelithiasis in the 4 groups:97 469 participants were followed up for 592 922 person-year,4 270 participants had new-onset cholelithiasis,with a total person-year incidence of 7.20 thousand person / year.The person-year incidence were respectively 6.34 (971/153 205 * 1 000),6.91 (1 034/149 686 * 1 000),7.44 (1 090/146 549 * 1 000),8.19 (1 175/143 482 * 1 000) thousand person / year in Q1,Q2,Q3 and Q4 group.(3) Effects of serum uric acid on the new-onset cholelithiasis.① The dose-response relationship between serum uric acid and the risk of cholelithiasis:restricted cubic spline regression showed a linear relationship between continuous serum uric acid,logarithmic transformated serum uric acid and the risk of cholelithiasis (x2 =11.74,8.01,P＜0.05).② Comparisons of the fitting degree of serum uric acid on the cholelithiasis model:adjusted for sex,age,BMI,TC,TG,diabetes,hypertension,smoking,drinking and physical exercise,risks of new-onset cholelithiasis increased in Q3 and Q4 groups compared with Q1 group (HR=1.10,1.12,95％CI:1.01-1.20,1.03-1.23,P＜0.05).The-2Log L and AIC value of multivariate model,serum uric acid+multivariate model were 92 532.39,92 550.39 and 92 525.35,92 549.35,respectively,with a statistically significant difference (x2=7.04,P ＜ 0.05).③ Effects of different serum uric acid levels on incidence of cholelithiasis after stratification by sex:in female participants,adjusted for age,BMI,TC,TG,diabetes,hypertension,smoking,drinking and physical exercise,risk of new-onset cholelithiasis in Q1 group was not statistically significant different from that in Q2,Q3,Q4 group (HR=1.06,1.15,1.09,95％CI:0.88-1.28,0.93-1.34,0.91-1.31,P＞0.05).In male participants,adjusted for age,BMI,TC,TG,diabetes,hypertension,smoking,drinking and physical exercise,risks of new-onset cholelithiasis in Q2,Q3 and Q4 groups were increased compared with Q1 group (HR=1.17,1.24,1.30,95％CI:1.06-1.30,1.12-1.37,1.18-1.44,P＜0.05).④ Serum uric acid of different gender on the boxplots:in female participants,the level of serum uric acid was (249 ± 61) μmol/L,(235±50)μmol/L,(231±56) μmol/L,(250±66) μmol/L,(266±75) μmol/L,(281±81) μmol/L,(298±76) μmol/L,(379±86)μmol/L respectively in the group of 18-27 years old,28-37 years old,38-47 years old,48-57 years old,58-67 years old,68-77 years old,78-87 years old,88-97 years old after stratified by 10 years old.In male participants,the level of serum uric acid was respectively (310±76)μmol/L,(298 ±75) μmol/L,(298±74) μmol/L,(294±74) μmol/L,(302±78) μmol/L,(311 ±80) μmol/L,(322±80) μmol/Land (330±75)μmol/L after participants stratified by 10 years old.⑤ Effects of different serum uric acid levels on the incidence of cholelithiasis after stratification by age:in participants with age ≤ 60 years old,adjusted for sex,BMI,TC,TG,diabetes,hypertension,smoking,drinking and physical exercise,risk of new-onset cholelithiasis in the Q2 and Q3 groups were not increased compared with Q1 group (HR=1.05,1.10,95％CI:0.94-1.17,0.99-1.23,P＞0.05),however,risk of new-onset cholelithiasis was increased in the Q4 group (HR =1.15,95％CI:1.02-1.28,P＜0.05).In participants with age ＞ 60 years old,adjusted for sex,BMI,TC,TG,diabetes,hypertension,smoking,drinking and physical exercise,risk of new-onset cholelithiasis in the Q2 groups was not increased compared with Q1 group (HR=1.16,95％CI:0.99-1.36,P＞0.05),however,risks of new-onset cholelithiasis were increased in the Q3 and Q4 groups (HR =1.19,1.21,95％CI:1.02-1.40,1.04-1.41,P＜ 0.05).Conclusion Elevated serum uric acid is an independent risk factor for the new-onset cholelithiasis.