[Detection of Adulteration in Milk Powder with Starch Near Infrared].

Three China trademarks of milk powder called Mengniu, Yili, Wandashan were taken as testing samples. Each of them mixed varied amount of starch in different gradient, which were consisted of 32 adulterated milk powder samples mixed with starch, was taken as standard samples for constructing predicted model. To those 32 samples, the reflecting spectrum characteristics in middle wave of near infrared spectrum with Near Infrared Spectrum Analyzer (Micro NIR 1700) produced by JDSU Ltd. USA were collected for five repeats in five different days. The time span was nearly two months. Firstly, we build the model used the reflecting spectrum characteristics of those samples with biomimetic pattern recognition (BPR) arithmetic to do the qualitative analysis. The analysis included the reliability of testing result and stability of the model. When we took ninety percent as the evaluation threshold of testing result of CAR (Correct Acceptance Rate) and CRR (Correct Rejection Rate), the lowest starch content of adulterate milk powder in all tested samples which the tested result were bigger than that abovementioned threshold was designated CAR threshold (CAR-T) and CRR threshold (CRR-T). CAR means the correct rate of accepting a sample which is belong to itself, CRR means correct rate of refusing to accept a sample which is not belong to itself. The results were shown that, when we constructed a model based on the near infrared spectrum data from each of three China trademark milk powders, respectively, if we constructed a model with infrared spectrum data tested in a same day, both the CAR-T and CRR-T of adulterate starch content of a sample can reach 0.1% in predicting the remainder infrared spectrum data tested within a same day. The three China trademarks of milk powder had the same result. In addition, when we ignored the trademarks, put the spectrum data of adulterate milk powder samples mixed with the same content of starch of three China trademarks milk powder together to construct a model, the CAR-T of mixed starch content of a sample may reach 0.1%, the CRR-T can reach 1%, if the model construction and predicting were performed with near infrared spectrum data tested in a same day. However, the CAR-T can just stably reach up to 5% and the CRR-T have the same result, if the model construction and predicting were crossly performed with mixed near infrared spectrum data tested in different days. Furthermore, the correct recognizing threshold mixed starch of a sample can stably reach up to 1% and the CAR-T can reach 5%, if the model construction was based on near infrared spectrum data combined the previous four days to predict the output of the another day. On the other hand, we also engaged quantitative analysis to the starch content in milk power with two kinds of arithmetic (PLSR, LS-SVR). In contrast with the testing outputs, the reliability of both the CAR-T and CRR-T in qualitative analysis was further validated.

A novel UPLC/MS/MS method for rapid determination of metapristone in rat plasma, a new cancer metastasis chemopreventive agent derived from mifepristone (RU486).

Mifepristone (RU486) is a chemical abortifacient used by hundreds of millions of women world-wide. It has recently been used in clinical trials for psychotic depression and cancer chemotherapy. Metapristone is the most predominant biological active metabolite of mifepristone, and being developed as a novel cancer metastasis chemopreventive agent based on its unique pharmacological properties. In this study, a novel rapid and sensitive method using UPLC/MS/MS was developed and validated for quantitative analysis of metapristone in plasma, which used less plasma volume and was demonstrated to be more simple and low-cost than the published methods. Metapristone in plasma was recovered by liquid-liquid extraction using 1 mL of ethyl acetate and chromatographic separation was carried on a C18 column at 35 °C, with a gradient mobile phase consisting of methanol and water containing 0.1% (v/v) formic acid at a flow rate of 0.3 mL/min. The mass spectrometric detection was carried out using a triple-quadrupole system via positive electrospray ionization. Multiple reaction monitoring was used for quantitation of m/z transitions from 416.3 to 119.9 for metapristone and from 313.1 to 109 for levonorgestrel (internal standard). Good linearity (r²> 0.9926) was achieved over a concentration range from 7.1 to 2840 ng/mL with a lower limit of quantification of 7.1 ng/mL for metapristone. The intra- and inter-day variations of the assay were 2.4-10.0% relative standard deviation with an accuracy of -5.6 to 8.6% relative error. This newly developed method was successfully applied to a pharmacokinetic study that revealed, for the first time, that there was a significant difference in pharmacokinetic profile between genders.

[Reason analysis of inadaptability and its correction research on the authenticity identification model of West Lake Longjing tea based on LVF micro-NIR spectrometer].

In the present paper, the micro-NIR spectrometer with the splitter of linear variable filter was used to develop the recognition models of the West Lake Longjing tea and the ordinary flat tea of the year 2012 and 2013. The NIR spectral data of different years and different storage times were decomposed by PCA algorithm. The PLS-DA models were developed by the representative samples selected by the mathematical characteristics of PCA-scores' distribution in order to analyze the reason for the inadaptability of the models according to mathematical principles and find out the solution for its correction. Being examined by the external validation set, the adaptability of the authenticity identification model was enhanced effectively. The result of this research indicated that, for the West Lake Longjing tea and the ordinary flat tea, the correct recognition rate of the model developed by all different-year samples' NIR spectral data would be enhanced effectively. The model developed by the NIR spectral data of different storage time samples indicated that the physicochemical properties of the ordinary flat tea have changed remarkably after cryopreservation for 3 months, while the physicochemical properties of the West Lake Longjing tea are relatively stable. The model adaptabilities for different years and different storage times were studied according to the mathematical perspective of the principal component characteristics of spectral data. After the authenticity identification model of West Lake Longjing tea was developed, the prediction accuracy was enhanced effectively. This research would provide reference for not only the application of NIR spectroscopy in quality grading and safety of agricultural products, but also the enhancement of the prediction accuracy of the NIR grading models for agricultural products.

[The study of AutoFlow role in volume controlled ventilation].

OBJECTIVE: To evaluate the efficacy and safety of automatic variable flow rate (AutoFlow) for volume control ventilation through monitoring the number of ventilator alarm. METHODS: Forty-eight adult patients receiving the Drager Evita 4 ventilator with an expectation of more than 2 days duration were divided into two groups by randomly digital methods, each n=24. The patients in control group were received routinely mode with synchronized intermittent mandatory ventilation (SIMV), and the others in observation group were given SIMV and assist with AutoFlow. The midazolam and fentanyl was given to retain the Ramsay score 2-3 by continuous micro-pump. The ventilator alarm, blood gas analysis and respiratory function were recorded. RESULTS: There were no significant differences in respiratory rate (RR), tidal volume (VT), positive end-expiratory pressure (PEEP), fraction of inspired oxygen (FiO2), pH, arterial partial pressure of carbon dioxide (PaCO2), arterial partial pressure of oxygen (PaO2), oxygenation index (PaO2/FiO2), as well as sedative dose and time between two groups within 5 days of mechanical ventilation. Duration of mechanical ventilation in all patients was 164 days (3756 hours), and 78 days (1812 hours) in control group, 86 days (1944 hours) in observation group. The duration of mechanical ventilation in observation group was longer than that in control group [3 (1-15) days vs. 2 (1-28) days, P>0.05]. A total of 23 843 alarms were recorded, approximately 6 times/h, and 17 386 alarms in control group, averagely 9.6 times/h, 6457 alarms in the observation group, averagely 3.3 times/h. The number of ventilator alarm in observation group was less than that in control group (P<0.01). The number of airway pressure alarm in observation group was less than that in the control group [122 (8-1068) vs. 565 (13-1898), P<0.01]. There was no significant difference in sequential organ failure assessment (SOFA) score within 5 days between the two sets of mechanical ventilation. In the observation group ventilator-associated pneumonia (VAP) was occurred in 4 cases, and no pneumothorax happened, while in the control group there were 8 cases and 2 cases respectively. The mortality rate in intensive care unit (ICU) in observation group was lower than that in control group, but there was no statistical difference (25.0% vs. 37.5%, P>0.05). CONCLUSIONS: AutoFlow is confirmed be safe for volume control ventilation mode, and could significantly reduce the alarm of ventilator.

[Fast determination of the proportion of metalaxyl-M enantiomers by UV spectroscopy].

In the present study, beta-cyclodextrin(betaCD) was used as chiral selector to detect the proportion of chiral isomers of metalaxyl. The proportion of metalaxyl enantiomers can be detected by ultraviolet (UV)spectroscopy since the interaction between the R, S isomer of metalaxyl with beta-CD is different. The quantitative models were established by partial least squares regression (PLS) and the robust of models was evaluated by independent validation samples. The determination coefficient R2 of calibration set in the quantitative model was 0.999 0. The standard error of calibration set (SEC) and the relative standard deviation (RSD) of the model was respectively 0.006 7 and 0.89%; The correlation coefficient r of estimated value and specified value of the 6 independent validation samples was 0.998 5. The standard error of prediction (SEP) and RSD was respectively 0.008 9 and 1.17%. This method is rapid and easy to operate in practical applications.