Proteomic Difference Analysis of Whole Blood and Bloodstains / 法医学杂志

OBJECTIVES@#To study the changes of protein levels in peripheral blood after it dried.@*METHODS@#The proteins from whole blood and bloodstains were detected by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and normalized by the label-free quantification (LFQ) method. The differential proteins were analyzed by using R 4.2.1 software, limma and edgeR package. The analysis of biological function, signaling pathway and subcellular localization for the differential proteins was then performed.@*RESULTS@#A total of 623 and 596 proteins were detected in whole blood and bloodstains, respectively, of which 31 were statistically significant in the quantitative results, including 10 up-regulated and 21 down-regulated proteins in bloodstains.@*CONCLUSIONS@#The protein abundances in whole blood and bloodstains are highly correlated, and the variation of protein abundances may be related to the changes of endogenous and structural proteins in cells. The application of proteomics technology can assist the screening and identification of protein biomarkers, thereby introducing new biomarkers for forensic research.

~1H-qNMR quantification of total ginsenosides in Shenmai Injection / 中国中药杂志

A content determination method based on ~1H-qNMR was developed for the determination of total ginsenosides in Shenmai Injection. The parameters were optimized with CD_3OD as the solvent, dimethyl terephthalate as the internal standard, the peak at δ 8.11 as the internal standard peak, and the peaks at δ 1.68 and δ 0.79 as quantitative peaks of total ginsenosides. The developed ~1H-qNMR-based method was validated methodologically. The results showed that the method could achieve accurate measurement of total ginsenosides in Shenmai Injection in the range of 0.167 6-3.091 1 mmol·L~(-1). The developed ~1H-qNMR-based method for total ginsenosides is simple in operation, short in analysis time, strong in specificity, independent of accompanying standard curve, and small in sample volume, which can serve as a reliable mean for the quality control of Shenmai Injection. This study is expected to provide new ideas for the development of quantification methods of total ginsenosides.

Application of navigator IDEAL-IQ in liver fat quantification:a comparative study with MRS / 实用放射学杂志

Objective To quantitatively assess the liver fat content by Nav IDEAL-IQ and compare with conventional breath-hold IDEAL-IQ and magnetic resonance spectroscopy (MRS).Methods Twenty volunteers,twenty fatty liver patients and twenty patients with other liver diseases were enrolled in this study.IDEAL-IQ,Nav IDEAL-IQ and MRS imaging were performed and fat fraction (FF) were measured respectively.The results were compared by t-test to explore whether there were differences between these groups. Spearman correlation analysis was also used to test the correlation.Results No significant differences in the FF measured by IDEAL-IQ,Nav IDEAL-IQ and MRS in normal volunteers [(4.09±0.82)%,(3.94±0.83)%,(3.92±0.85)%],fatty liver [(15.5±6.1)%,(11.8±6.5)%,(1 2 .4 ± 7 .2 )% ] and other liver lesions patients [(4.20±0.84)%,(4.00±0.94)%,(3.97±0.96)%]were found between these groups (P>0.05). There was a significant positive correlation between Nav IDEAL-IQ and MRS,and the correlation coefficients of these groups were 0.959,0.786 and 0.945,respectively.Conclusion The results of Nav IDEAL-IQ of fat quantification are consistent with MRS results and it increases the success rate of fat quantitative testing.In a word,it is a noninvasive,convenient and accurate way to measure fat fraction.

Trial of Objective Diagnosis of Blood Deficiency Using a Skin Moisture Meter / 日本東洋医学雑誌

[Purpose] In Kampo medicine, blood deficiency is considered to cause systemic symptoms such as insomnia and dizziness, in addition to skin-related symptoms such as xeroderma. Diagnosis of blood deficiency does not appear to be definitive since it is based on subjective judgment. To resolve this problem, we have attempted to establish an objective method for diagnosing blood deficiency by measuring skin moisture.[Methods] Using a skin moisture meter, we measured the skin moisture (at the neck, forearm, and abdomen) of 80 women during their first examination at our clinic. The patients were also classified according to their blood deficiency scores.[Results] A statistically significant difference was observed between patients with blood deficiency and those without blood deficiency with regard to the skin moisture at the neck and forearm. The coefficient of correlation between the skin moisture of the neck and the blood deficiency score was -0.41.The results of statistical analysis performed using a type1quantification method revealed high values even for some conditions not associated with the skin, such as hypomenorrhea and excessive strain of the abdominal muscles, in addition to high values for skin-associated conditions. And in pre-post-treatment comparisons, improvements in blood deficiency scores generally matched transitions in keratinous moisture.[Discussion] Due to the absence of a high correlation between skin moisture and the blood deficiency score, it is unlikely that skin moisture can be used instead of the blood deficiency score as a parameter for the accurate diagnosis of blood deficiency.[Conclusion] Although skin moisture levels may be an indicator of blood deficiency, further studies are required before this parameter can be applied in clinical diagnosis.

Characteristics of health lifestyle patterns by the quantification method / 예방의학회지

The purpose of this study was to investigate the relation between health behavior patterns and demographic, socio-economic characteristics, health status, health information in Korea. The quantification method through canonical correlation analysis was conducted to the data from Korea National Health Survey in 1995, which consisted of 5,805 persons. The health lifestyle patterns were quantified as good diet lifestyle, passive lifestyle to the negative direction and drinker lifestyle, smoker lifestyle, hedonic lifestyle and fitness lifestyle to the positive direction. The covariate were related to health lifestyle patterns in the order of sex, age, marital status, occupation, health information, economic status, level of physical labour, health status. Characteristics of male, age below 50, married, blue colored worker, no health information, low in economic status, heavy level of physical labour, and poor in health status were positively related to drinker lifestyle, smoker lifestyle, hedonic lifestyle, fitness lifestyle sequentially.