Arrhythmias, Cardiac ; pathology ; physiopathology ; Humans ; Purkinje Fibers

Since haemoplasmodium is not detected for screening in blood donor,morbidity of transfusion-associated malaria increased rapidly in China recently and became an important problem of public health.It is necessary to emphasize donor screening for malaria.Hematology analyzer with MAPSS is recommended to screen malaria.Flow cytometry and immunochromatography test(ICT)can also screen malaria effectively.For the suspicious samples with haemoplasmodium,it is necessary to be reexamined by standard microscopic examination or polymerase chain reaction(PCR).

OBJECTIVE:To determinate the dissolution of Compound Flavone capsules by HPLC.METHODS:Nova-Pak C18(250mm? 4.0mm,5? m) column was used with column at room temperature.The mobile phase consisted of methanol-0.4% H3PO4(50:50) at a flow rate of 1.0mL? min-1.The detective wavelength was 360nm.The dissolution of the Compound Flavone capsules was determined by basket stirring technique with 0.1mol? L-1 hydrochloric acid as dissolvent at a speed of 100r? min-1.RESULTS:The cumulative dissolution rate of Compound Flavone capsules was above 80% at 30 minutes.The linear range of Quercetin was 0.065 84～ 0.658 4?g(r=0.999 9).The average recovery was 99.35%,RSD=0.92%(n=6).CONCLUSION:The method is simple,accurate and reproducible,and suitable for the guality control of Compound Flavone capsules.

Objective To investigate the incidence of candidal colonization and to analyze its risk factors in patients with connective tissue diseases (CTDs). Methods Throat swabs, midstream urine and anal swabs from 153 patients with CTDs and 63 healthy volunteers were collected for fungus culture. The logistic regression was completed via the software package SPSS 11.0. Results The incidence rate of candidal colonization was higher in the patients than that in the healthy controls (35.29% vs 7.59%). Of all the isolated fungus strains, the proportion of Candida albicans was the highest. The logistic regression analysis revealed that decrease of blood erythrocytes, increase of urine protein, decrease of complements such as CH50, C3 and C4 in serum, high daily dosage of corticosteroids and broad-spectrum antibiotic administration all significantly increased the risk of candidal colonization (all P 0.05). Conclusions The incidence rate of candidal colonization in patients with CTDs is higher than that in healthy controls. Avoiding the risk factors will help to decrease the incidence of candidal colonization in CTDs.

Gas Chromatography-Mass Spectrometry ; methods ; Humans ; Trichloroacetic Acid ; urine

Adolescent ; Adult ; Aged ; Child ; Female ; Foreign Bodies ; diagnostic imaging ; Head ; Humans ; Male ; Middle Aged ; Neck ; Tomography, Spiral Computed ; Tomography, X-Ray Computed ; Young Adult

Animals ; Chronic Disease ; Heart Failure ; drug therapy ; Humans ; Hydroxymethylglutaryl-CoA Reductase Inhibitors ; adverse effects ; therapeutic use

Adult ; Bone Neoplasms ; diagnosis ; surgery ; Cervical Vertebrae ; Humans ; Male ; Osteochondroma ; diagnosis ; surgery

Humans ; Leukemia, Lymphocytic, Chronic, B-Cell ; Societies, Medical ; United States

Objective By surface-enhanced laser desorption / ionization time-of-flight mass spectrometry(SELDI-TOF-MS), the serum pmteomic fingerprints related with the changing of malignant tumor patients' serum glucose after chemotherapy was selected and constructed as an predictive model. Methods By SELDI-TOF-MS, the serum of 182 malignant tumor patients who had received chemotherapy were tested, and the pmteomic fingerprints were received. After 2 years follow-up, all the patients were divided into 3 groups: the euglycemia group(136 people), the carbohydrate tolerance abnormality group(27 people), and the diabetes mellitus group (19 people). The proteomic fingerprints were analyzed by Biomarker Wizard Software and the idio-proteomic fingerprint of protective models were constructed by BPS (biomarker pattern software). Results The diagnosis model composed with 2 proteins (M/Z values were 5298 and 9608) could classify the carbohydrate tolerance abnormality group, and the diabetes mellitus group correctly. In the test model, the sensitivity and specificity were 81.48 %(22/27) and 100.00 %(17/17) respectively, the accuracy was 88.64 % (39/44). The diagnosis model composed with 3 proteins (M/Z values were 10324, 2761 and 4084) could classify the diabetes mellitus group and the euglycemia group correctly. In the test model, the sensitivity and specificity were 62.35 %(53/85) and 88.24 %(15/17) respectively, the accuracy was 66.67 %(68/102). The diagnosis model composed with 6 proteins (M/Z values were 5895,6010,6099,3930,5430 and 2495) could classify the diabetes mellitus group and the the carbohydrate tolerance abnormality group correctly. In the test model, the sensitivity and specificity were 77.65 %(66/85) and 96.30 %(26/27) respectively, the accuracy was 82.14 %(92/112). Conclusion SELDI-TOF-MS could be utilized to analyze protein profiling in screening serum glucose changing-related biomarkers and developing diagnostic and predictive patterns, and the developed patterns may be used to predict the changing of serum glucose after chemotherapy in malignant tumor patients.