الملخص
Objective:To research optimum compatibility components ratio for the anti-influenza virus effect of different compatibility of Menthae Haplocalycis Herba-Schizonepetae Herba. Method:The 228 SPF grade ICR rats of half male and half female were randomly divided into 19 groups, with 12 rats in each group. In each group, the ratio of flavonoids and volatile oil was determined. ICR rats were anesthetized with ether and infected with influenza A virus A/PR/8/34 (H1N1) with A 10-fold lethal dose(LD50)50 μL nasal drip infection. Than the blank control group was treated with the same amount of normal saline nasal drip control, and the rats were given the drug by gavage on the day after virus infection, the blank group and model group were given the same amount of distilled water, and the positive control group were given Oseltamivirphosphate and compound Jinyinhua granules by gavage, and once a day for 7 days. Different compatibility of volatile oil and flavonoids in Menthae Haplocalycis Herba and Schizonepetae Herba are applied to rats infected with influenza A/PR8/34 (H1N1) virus to study the pharmacodynamic screening by lung index of influenza-infected mice and histopathological examination. And antiviral effects as well as the expression of interleukin-6(IL-6), interleukin-1β(IL-1β), tumor necrosis factor-α (TNF-α) is studied. Result:Lung infection injury was prepared by infecting mice with influenza A virus A/ pr8/34(H1N1). Lung mass increased at the end of the experiment in the model group, and lung index was compared with that in the blank group(P<0.01). And the experimental lung weight of oseltamivirphosphate group, compound Jinyinhua granules group, volatile oil 1-volatile oil 2 group, volatile oil 1 group and volatile oil 2 group were compared with that of the model group (P<0.05). Lung index of Oseltamivirphosphate group and volatile oil group was compared with that of model group (P<0.01).Lung index of compound Jinyinhua granules group, volatile oil 1-volatile oil 2 group, volatile oil 2-flavonoids 2 group, volatile oil 1-volatile oil 2-flavonoids 1 group, volatile oil 1-volatile oil 2-flavonoids 2 group, volatile oil 1-volatile oil 2-flavonoids 2 group, volatile oil 1-volatile oil 2-flavonoids 2 group and volatile oil 2 group were compared with the model group (P<0.05). And antiviral effect as well as the expression of IL-6, IL-1β, TNF-α is studied. The expression levels of IL-6, IL-1β, TNF-α in volatile oil 1-flavonoids 1 group, volatile oil 1-flavonoids 2 group, volatile oil 1-volatile oil 2 group, volatile oil 1-volatile oil 2-flavonoids 1 group, volatile oil 1-volatile oil 2-flavonoids 2 group, volatile oil 2 groups, flavonoids 2 groups were decreased, compared with the model group (P<0.01). Conclusion:It is found that different combinations have better biological effects and good antiviral effects. This study explores the synergies compatibility rule and mechanism of action on Menthae Haplocalycis Herba and Schizonepetae Herba pairs, which will not only develop the theory of Chinese medicine compatibility but also contribute to laying a foundation for the innovation of the influenza virus drug development.
الملخص
Objective To analyze the differences among electrical damage, burns and abrasions in pig skin using Fourier transform infrared microspectroscopy (FTIR-MSP) combined with machine learning algorithm, to construct three kinds of skin injury determination models and select characteristic markers of electric injuries, in order to provide a new method for skin electric mark identification. Methods Models of electrical damage, burns and abrasions in pig skin were established. Morphological changes of different injuries were examined using traditional HE staining. The FTIR-MSP was used to detect the epidermal cell spectrum. Principal component method and partial least squares method were used to analyze the injury classification. Linear discriminant and support vector machine were used to construct the classification model, and factor loading was used to select the characteristic markers. Results Compared with the control group, the epidermal cells of the electrical damage group, burn group and abrasion group showed polarization, which was more obvious in the electrical damage group and burn group. Different types of damage was distinguished by principal component and partial least squares method. Linear discriminant and support vector machine models could effectively diagnose different damages. The absorption peaks at 2 923 cm-1, 2 854 cm-1, 1 623 cm-1, and 1 535 cm-1 showed significant differences in different injury groups. The peak intensity of electrical injury's 2 923 cm-1 absorption peak was the highest. Conclusion FTIR-MSP combined with machine learning algorithm provides a new technique to diagnose skin electrical damage and identification electrocution.
الموضوعات
Animals , Algorithms , Fourier Analysis , Least-Squares Analysis , Machine Learning , Swineالملخص
Objective To infer postmortem interval (PMI) based on spectral changes of the dorsal skin of rats within 15 days postmortem using Fourier transform infrared (FTIR) spectroscopy. Methods The rats were sacrificed by cervical dislocation after anesthesia, and then placed at 25 ℃ and relative humidity of 50%. The FTIR spectral data collected from the dorsal skin at PMI points were modeled with machine learning technique. Results There was no significant difference of absorption peak location among all the PMI groups but their peak intensities changed as a function of PMIs. The model for PMI estimation was constructed using partial least squares (PLS) regression, reaching a R2 of 0.92 and a root mean square error (RMSE) of 1.30 d. As shown in variable importance for projection (VIP), four spectral bands including 1 760-1 700 cm-1, 1 660-1 640 cm-1, 1 580-1 540 cm-1 and 1 460-1 420 cm-1 were determined as important contributions to model prediction. Conclusion Application of the FTIR technique to detect postmortem spectral changes of the rat skin provides a novel proposal for PMI estimation.
الموضوعات
Animals , Rats , Autopsy , Postmortem Changes , Spectroscopy, Fourier Transform Infraredالملخص
Objective To analyse the relationship between Fourier transform infrared (FTIR) spectrum ofrat's spleen tissue and postmortem interval (PMI) for PMI estimation using FTIR spectroscopy combinedwith data mining method. Methods Rats were sacrificed by cervical dislocation, and the cadavers were placed at 20 ℃. The FTIR spectrum data of rats' spleen tissues were taken and measured at different time points. After pretreatment, the data was analysed by data mining method. Results The absorption peak intensity of rat's spleen tissue spectrum changed with the PMI, while the absorption peak position was unchanged. The results of principal component analysis (PCA) showed that the cumulative contribution rate of the first three principal components was 96%. There was an obvious clustering tendency for the spectrum sample at each time point. The methods of partial least squares discriminant analysis (PLS- DA) and support vector machine classification (SVMC) effectively divided the spectrum samples with different PMI into four categories (0-24 h, 48-72 h, 96-120 h and 144-168 h). The determination coefficient (R2) of the PMI estimation model established by PLS regression analysis was 0.96, and the root mean square error of calibration (RMSEC) and root mean square error of cross validation (RMSECV) were 9.90 h and 11.39 h respectively. In prediction set, the R2 was 0.97, and the root mean square error of prediction (RMSEP) was 10.49 h. Conclusion The FTIR spectrum of the rat's spleen tissue can be effectively analyzed qualitatively and quantitatively by the combination of FTIR spectroscopy and data mining method, and the classification and PLS regression models can be established for PMI estimation.
الملخص
Objective To explore infrared spectrum characteristics of different voltages induced electrical injuries on swine skin by using Fourier transform infrared-microspectroscopy (FTIR-MSP) combined with machine learning algorithms, thus to provide a reference to the identification of electrical skin injuries caused by different voltages.Methods Electrical skin injury model was established on swines.The skin was exposed to 110 V, 220 V and 380 V electric shock for 30 s and then samples were took, with normal skin tissues around the injuries as the control.Combined with the results of continuous section HE staining, the FTIR-MSP spectral data of the corresponding skin tissues were acquired.With the combination of machine learning algorithms such as principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA), different spectral bands were selected (full band 4 000-1 000 cm-1and sub-bands 4 000-3 600 cm-1, 3 600-2 800 cm-1, 2 800-1 800 cm-1, and 1 800-1 000 cm-1), and various pretreatment methods were used such as orthogonal signal correction (OSC), standard normal variables (SNV), multivariate scatter correction (MSC), normalization, and smoothing.Thus, the model was optimized, and the classification effects were compared.Results Compared with simple spectrum analysis, PCA seemed to be better at distinguishing electrical shock groups from the control, but was not able to distinguish different voltages induced groups.PLS-DA based on the 3 600-2 800 cm-1band was used to identify the different voltages induced skin injuries.The OSC could further optimize the robustness of the 3 600-2 800 cm-1band model.Conclusion It is feasible to identify electrical skin injuries caused by different voltages by using FTIR-MSP technique along with machine learning algorithms.
الملخص
OBJECTIVES@#To analyse the Fourier transform infrared (FTIR) spectral data of renal tissue at different temperatures in rats after death, and to explore the effects of temperature on the FTIR spectral characteristics of renal tissue.@*METHODS@#The rats were sacrificed by cervical dislocation and placed at 4 ℃, 20 ℃ and 30 ℃. The FTIR spectral data of renal tissue were collected at different time points and analysed by data mining method.@*RESULTS@#The principal component analysis (PCA) results showed that there were significant trends of clustering in the samples of partial time point at 4 ℃, 20 ℃ and 30 ℃. Partial least square (PLS) regression models were established with the spectral data at three temperature groups. The performance of PLS regression models in 20 ℃ and 30 ℃ groups were more superior than that in 4 ℃ group, and the stability of the model in 20 ℃ group was better than that in 30 ℃ group.@*CONCLUSIONS@#There are differences in the FTIR spectral characteristics of renal tissue of rats after death at different temperatures. Temperature has a major impact on the performance of FTIR spectral PLS regression model. Therefore, in order to improve the accuracy of postmortem interval estimation, the effects of temperature on the model should be considered in the related study by spectral method.
الموضوعات
Animals , Rats , Autopsy , Death , Postmortem Changes , Spectroscopy, Fourier Transform Infrared/methods , Temperatureالملخص
As a keratinized material, nail recently has attracting researchers' attention in the pharmaceuticals analysis. There are comparatively limited studies concerning nail's xenobiotic determination and its mechanism. This article reported the development of a sensitive, specific and reproducible LC-MS/MS method, which could be as a foundation of other studies on drug determination in nail. It can also be regarded as the first report on organic drug in mainland China. Sixteen nail samples from volunteers, who were ingested clozapine for more than nine months, are confirmed positive after being analyzed by the method. It is found that contents of clozapine in the patients' nails are above the nanogram level. Besides, a comparative study of clozapine concentration in nails and hair was made, with a result that there exists a correlation between the two materials in terms of clozapine concentration.
الموضوعات
Adult , Female , Humans , Male , Middle Aged , Antipsychotic Agents , Pharmacokinetics , China , Chromatography, Liquid , Methods , Clozapine , Pharmacokinetics , Hair , Chemistry , Nails , Chemistry , Psychotic Disorders , Metabolism , Tandem Mass Spectrometry , Methodsالملخص
OBJECTIVE@#To investigate the feasibility of the new method of combining freeze grinding with ultrasonic technique for the pretreatment of the nail for toxicological and pharmaceutical analysis and to compare the advantages and disadvantages of this method with other traditional methods.@*METHODS@#Five pretreatment methods were examined. Scanning electron microscope (SEM) was used to observe the microstructural changes of the nail.@*RESULTS@#The microscopic structure of nail totally destroyed after alkali treatment. The hierarchy mode of the internal structure became obvious and tight after acid hydrolysis, which became indistinct after methanol infiltration. The structure of nail broke to pieces after ultrasonic technique. After freeze grinding combined ultrasonic technique, the particle structure kept original shape, and its size was one hundred times smaller than which after manual way.@*CONCLUSION@#The freeze grinding combined ultrasonic technique can improve the release efficiency, and ensure the stability of the toxicant or drug during the pretreatment process. It is appropriate for toxicological and pharmaceutical analysis in the nail.
الموضوعات
Humans , Forensic Pathology , Freeze Drying/methods , Microscopy, Electron, Scanning , Nails/chemistry , Particle Size , Ultrasonicsالملخص
A sensitive LC-MS/MS method to determine cocaine and its major metabolite benzoylecgonine in guinea pig' s hair has been established. About 20 mg of decontaminated hair sample was hydrolyzed with 0. 1 mol x L(-1) HCl at 50 degrees C overnight, in the presence of cocaine-d3 and benzoylecgonine-d8 used as internal standards, and then extracted with dichlormethane. The analysis was performed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Positive electrospray ionization (ESI +) and multiple reactions monitoring (MRM) mode were used. The limit of detection (LOD) for cocaine and benzoylecgonine was 1 pg x mg(-1). The calibration curves of extracted standards were linear over the range from 5 pg x mg(-1) to 250 pg x mg(-1) (r2 > or = 0.9997). The method was validated and applied to the analysis of guinea pig's hair after a single dose administration of cocaine hydrochloride. Cocaine and benzoylecgonine were not only detected, but also quantified in guinea pigs hair.
الموضوعات
Animals , Chromatography, High Pressure Liquid , Cocaine , Metabolism , Guinea Pigs , Hair , Chemistry , Metabolism , Spectrometry, Mass, Electrospray Ionization , Tandem Mass Spectrometryالملخص
OBJECTIVE@#To establish a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the simultaneous analysis of cocaine (COC) and its metabolite benzoylecgonine(BZE) in urine samples.@*METHODS@#A single dose of COC (10 mg/kg) was injected intraperitoneally into guinea pigs and urine samples were collected for 7 days. The urine samples were extracted by auto solid phase extraction (SPE), separated by the Allure PFP propyl column with a mobile phase consisting of methanol and 20 mmol/L ammonium acetate buffer [0.1% formic acid (80:20, V/V)], and then analyzed by LC-MS/MS. Multiple reaction monitoring (MRM) mode was used to analyze COC (m/z 304.2-->182.3, m/z 304.2-->150.1) and BZE (m/z 290.2-->168.3, m/z 290.2-->105.0).@*RESULTS@#COC and BZE showed a fairly good linearity over the range of 2.0-100 ng/mL (r=0.9995). The detection limit was 0.5 ng/mL. The recovery rate was greater than 90% and the deviation of intra- and inter-day precision was less than 6%. BZE was the major target detected in urine samples, and its detection window was longer than COC.@*CONCLUSION@#This newly developed method shows high sensitivity and selectivity, and is suitable for the simultaneous analysis of cocaine and benzoylecgonine in urine samples.