Evaluation of key aroma compounds and protein secondary structure in the roasted Tan mutton during the traditional charcoal process.

The traditional charcoal technique was used to determine the changes in the key aroma compounds of Tan mutton during the roasting process. The results showed that the samples at the different roasting time were distinguished using GC-MS in combination with PLS-DA. A total of 26 volatile compounds were identified, among which 14 compounds, including (E)-2-octenal, 1-heptanol, hexanal, 1-hexanol, heptanal, 1-octen-3-ol, 1-pentanol, (E)-2-nonenal, octanal, 2-undecenal, nonanal, pentanal, 2-pentylfuran and 2-methypyrazine, were confirmed as key aroma compounds through the odor activity values (OAV) and aroma recombination experiments. The OAV and contribution rate of the 14 key aroma compounds were maintained at high levels, and nonanal had the highest OAV (322.34) and contribution rate (27.74%) in the samples after roasting for 10 min. The content of α-helix significantly decreased (P < 0.05), while the ß-sheet content significantly increased (P < 0.05) during the roasting process. The content of random coils significantly increased in the samples roasted for 0-8 min (P < 0.05), and then no obvious change was observed. At the same time, ß-turn content had no obvious change. Correlation analysis showed that the 14 key aroma compounds were all positively correlated with the content of α-helix and negatively correlated with the contents of ß-sheet and random coil, and also positively correlated with the content of ß-turn, except hexanal and 2-methypyrazine. The results are helpful to promoting the industrialization of roasted Tan mutton.

Water distribution and key aroma compounds in the process of beef roasting.

The key aroma compounds and water distribution of the beef at different roasting times (0, 3, 6, 9, 12, 15, and 18 min) were identified and analyzed. The results showed that the L * value increased considerably before peaking and then decreased. On average, a * values decreased significantly first and then kept stable, while b * values increased first and then decreased. A total of 47 odorants were identified in all samples, including 14 alcohols, 18 aldehydes, 6 ketones, 1 ester, 3 acids, 4 heterocyclic compounds, and 1 other compound. Among them, 11 key aroma compounds were selected and aldehydes and alcohols predominantly contributed to the key aroma compounds. The fluidity of the water in the beef during the roasting process was decreased, and the water with a high degree of freedom migrated to the water with a low degree of freedom. The correlation analysis showed that water content and L * were negatively correlated with key aroma compounds of the samples, while M 21 was positively correlated with key aroma compounds.

The diagnostic and prognostic value of interleukin-10 in cerebrospinal fluid for central nervous system lymphoma: a meta-analysis.

Central nervous system lymphoma (CNSL) presents diagnostic and prognostic challenges. The aim of this meta-analysis was to evaluate the diagnostic and prognostic value of interleukin (IL)-10 in cerebrospinal fluid (CSF) for CNSL comprehensively. PubMed and Cochrane Library databases were searched through September 2016. Four studies with 212 CNSL patients and 262 control patients were included. The pooled sensitivity and specificity of CSF IL-10 for diagnosing CNSL were 81% (95% CI: 66-91%) and 97% (95% CI: 83-100%), respectively. The summary receiver operating characteristic (SROC) curve indicated that the area under the curve was 0.95 (0.93-0.97). The ROC curve based on extracted individual data showed that the optimal cutoff value was 6.88 pg/ml. Moreover, elevated CSF IL-10 was found to be associated with shorter progression-free survival (hazard ratio: 2.89, 95% CI: 1.13-7.41, p = .027). In conclusion, our meta-analysis showed that CSF IL-10 is an effective diagnostic and prognostic biomarker for CNSL.

[Study on Multi-Bands Recognition for Varieties of Mutton by Using Hyperspectral Technologies].

This paper focused on the research on identifying and classifying for mutton varieties of Tan-han hybrid sheep,Yanchi Tan-sheep and small-tailed sheep in Ningxia by using visible/ near-infrared (400~1 000 nm). Near infrared (900~1 700 nm) hyperspectral technologies, baseline and SG convolution smoothing spectra pretreatment methods were applied respectively according to the characteristics of different spectrum bands; the characteristic wavelengths were extracted by using successive projection algorithm (SPA);then combined with linear discriminant analysis (LDA) and radial basis kernel function of support vector machine (RBFSVM) model were applied to identify the different mutton varieties under characteristic wavelengths and full-wave bands. Results showed that there were good effects for mutton varieties identification in different hyperspectral bands, among which Baseline-Fullwave-RBFSVM and the same models under 12 characteristic wavelengths obtained accuracy of 100% and 98.75% in 400~1 000 nm respectively, and Baseline-Fullwave-RBFSVM and the same models under 7 characteristic wavelengths obtained accuracy of 96.25% and 87.80% in 900~1 700 nm respectively.The identification accuracy of RBFSVM nonlinear classification was higher than the LDA linear discriminant result, meanwhile the identification accuracy in 400~1 000 nm bands was better than in 1 000~1 700 nm bands, which explained that the differences of color and texture were more significant than the component contents among the 3 varieties mutton. Combined hyperspectral technologies with RBFSVM models can obtain a better recognition effect of mutton varieties.