Objective To investigate the metabolism characteristics and the potetial biomarker candidates of osteonecro?sis of the femoral head (ONFH) using metabolomic technology. Methods The femoral head specimens from 23 ONFH patients (25 necrotic femoral heads) and 18 normal femoral heads from femoral neck fracture patients were collected for histopathological examination to confirm the diagnosis of all samples. All the metabolites of bone trabecula were extracted for ultra-high perfor?mance liquid chromatography-MS/MS analyzed. The measured variables was pretreat, and PCA (principal component analysis), PLS?DA (partial least squares?discriminant analysis) and OPLS?DA (orthogonal?partial least squares?discriminant analysis) models were employed to confirm the difference between these two groups after UPLC?MS/MS (ultra?high performance liquid chromatogra?phy?mass spectrometry/mass spectrometry) analysis. At last, the differential variables were screened out by PLS?DA and variate analysis (Kruskal?Wallis H test). The changed metabolites were confirmed by MS and MS/MS aligned in HMDB (human metabolo?mic database) and Massbank. The changed metabolites with the most obviously changed peak abundance, D?arginine, L?proline and L?glutamine, were picked out as the potential diagnostic biomarkers. After binary logistic regression analysis, the combined biomarkers candidates were further analyzed by receiver operating characteristic (ROC) curve to evaluate the significance of the combined biomarkers. Results Significant distinction of metabolites expression mode can be seen in PCA, PLS?DA and OPLS?DA models scoring plots between ONFH and control groups. Twelve changed metabolites in ONFH bone trabeculas were con?firmed by multi?variate statistical analysis and variate statistical analysis. Compared with the femoral neck fracture patients, the in?creased metabolites included D?arginine, L?proline, L?glutamine, creatine, uracil, uridine, LysoPC(20∶4(5Z, 8Z, 11Z, 14Z)), Ly?soPC(16∶0), PC(20∶1(11Z)/18∶3(6Z, 9Z, 12Z)) and PE(P?16∶0e/0∶0). The decreased metabolites were reticulataxanthin and β?cryptoxanthin. According to the change fold of peak abundance and variable weight projection in PLS?DA, the most obviously dif? ferential metabolites were picked out as the biomarker candidates of ONFH. The potential biomarkers candidates were identified as D?arginine, L?proline and L?glutamine. The area under the curve of D?arginine, L?proline and L?glutamine ROC were 0.873, 0.712 and 0.862. The area under the curve of ROC was 0.946 after combining D?arginine, L?proline, L?glutamine using binary lo?gistic regression analysis. Conclusion PCA, PLS?DA and OPLS?DA models were used to find out the differential variables in the metabolites of bone trabeculas in ONFH and femoral neck fracture patients. Twelve metabolites were identified by MS/MS, and 3 obviously changed metabolites, D?arginine, L?proline, L?glutamine, were indicated as biomarker candidates. These 3 obviously changed metabolites showed a good diagnostic significance.

OBJECTIVE: To investigate the association between transforming growth factor beta1(TGF-beta1)-800G>A polymorphism and cerebral infarction (CI). METHODS: The genotypes of 247 patients with atherosclerotic cerebral infarction and 167 sex- and age-matched healthy controls were detected by PCR-RFLP, and the frequency distribution of alleles calculated. RESULTS: TGF-beta1-800G>A polymorphism was found in Han population in Hunan Province, China. The distribution of -800G>A genotypes was consistent with Hardy-Weinberg balance in the CI and healthy control group. There was no significant difference between genotypes and allele frequency of TGF-beta1-800G>A in the CI and control group (P>0.05). Logistic regression analysis suggested that no genotypes could increase or reduce the risk of CI onset (P>0.05). CONCLUSION TGF-beta1-800G>A polymorphism is not associated with CI in Han population in Hunan Province.
Case-Control Studies ; Cerebral Infarction ; genetics ; China ; ethnology ; Female ; Gene Frequency ; Genotype ; Humans ; Male ; Polymorphism, Genetic ; genetics ; Polymorphism, Single Nucleotide ; Transforming Growth Factor beta1 ; genetics

OBJECTIVETo develop a new method to rapidly determine and identify Guizhi Fuling capsule by portable acousto-optic tunable filter-near infrared spectroscopy.

METHODThe qualitative model was set up using principal component analysis. The correlation models between the NIR spectra and the reference values of five major constituents were obtained with partial least squares method.

RESULTThe identifying model accurately identified Guizhi Fuling capsule, and quantitative analytical models could precisely predicted the content of ellagic acid, baicalin, benzoylpaenoniflorin, cinnamaldehyde, and paeonol. The correlation coefficients of the calibration models were 0.924 2, 0.938 4, 0.924 2, 0.933 6, 0.934 7, the validation set coefficients of the calibration were 0.924 2, 0.938 4, 0.924 2, 0.933 6, 0.934 7, and the RMSEP were 1.138%, 3.014%, 0.751%, 0.625%, 3.455%, 1.363%, respectively. The results of external validation showed no significant difference between the predictive and the determining values by t-test.

CONCLUSIONThe method is accurate, rapid and non-destructive, and can be used for determining and identifying Guizhi Fuling capsule.

Acetophenones ; analysis ; Acrolein ; analogs & derivatives ; analysis ; Calibration ; Capsules ; chemistry ; Drug Evaluation ; methods ; Drugs, Chinese Herbal ; analysis ; Ellagic Acid ; analysis ; Flavonoids ; analysis ; Least-Squares Analysis ; Models, Chemical ; Principal Component Analysis ; methods ; Spectroscopy, Near-Infrared ; methods

Purpose To evaluate the diagnostic value of high-frequency ultrasonography (HFUS) in the diagnosis of rheumatoid arthritis (RA) Achilles tendinopathy.Materials and Methods The Achilles tendon HFUS findings in 67 cases including a total of 93 feet were analyzed retrospectively,among which,11 cases including 22 feet were set as healthy control group (group A),36 cases including 40 feet as RA Achilles tendon group (group B) and 20 cases including 31 feet as non RA Achilles tendon group (group C).HFUS was used to observe the gray-scale imaging (GSI) and power Doppler imaging (PDI) features of the Achilles tendon:① the positive rate of Achilles tendon GSI abnormality.② The thickness and width of the starting point,mid point and ending point of Achilles tendon.③ The detection rate of retrocalcaneal bursal effusion.④ The detection rate of blood flow signal in the internal Achilles tendon.⑤ The level of blood flow signal.The data of each group were compared and analyzed.Restlts ① The positive rate of Achilles tendon GSI abnormality:there was no significant difference between group A and group B (x2=0.064,P＞0.05).Compared with group A and group B,group C had higher rate of abnormalities (x2=31.601 and 39.256,P＜0.05).② The thickness and width of Achilles tendon:the thickness of each point increased in group C than that in group A and group B (P＜0.05),and there was no significant difference in width between groups (P＞0.05).③ The detection rate of retrocalcaneal bursal effusion:negative in group A.The detection rate of group B (55％) was higher than that of group C (19.4％),the difference was statistically significant (P＜0.05).④ The detection rate of blood flow signal in the Achilles tendon:negative in group A.The detection rate of group B (97.5％) was higher than that of group C (45.2％),the difference was statistically significant (P＜0.05).⑤ The level of blood flow signal:level Ⅰ signal detection rate in group B (7.5％) was lower than that in group C (35.5％),while level Ⅱ signal detection rate in group B (35.0％) was higher than that of group C (9.7％),the differences were statistically significant (P＜0.05).Level Ⅲ signal was detected in only group B (45.0％) while not detected in group C.In addition,aspiration biopsy was performed on 3 patients of whom the fat pad of Achilles tendon was involved by level Ⅲ blood flow signal in PDI,and the pathological findings were consistent with ultrasonic manifestations.Conclusion HFUS is of great value in the diagnosis of RA Achilles tendinopathy and it can also be used to distinguish from non-RA Achilles tendinopathy.Moreover,it helps to achieve early diagnosis and early treatment in clinic to avoid Achilles tendon rupture and other bad progresses.