Identification of enhanced cytokine generation following sepsis. Dream of magic bullet for mortality prediction and therapeutic evaluation.

BACKGROUND AND THE PURPOSE OF THE STUDY: sepsis is one of the most widespread and lethal disease in Intensive Care Units (ICU). Based on pathophisyology of sepsis, it seems that routine laboratory tests combined with analysis of pro-inflammatory cytokines plasma levels, help clinicians to have more information about disease progress and its correct management. METHODS: This was a prospective observational study to determine the predictive role of Tumor Necrosis Factor alpha (TNF-α), Interleukin (IL)-1ß and IL-6 as three main pro-inflammatory cytokines and Acute Physiology and Chronic Health Evaluation (APACHE II) and Sequential Organ Failure Assessment (SOFA) as two scoring systems in mortality of critically ill patients with severe sepsis. Fifty and five patients with criteria of severe sepsis were included in this study. An exclusion criterion was post Cardiopulmonary Resuscitation (CPR) status. Cytokines (TNF-α, IL-1ß and IL-6) were assayed in the first, third and seventh days in blood of patients. RESULTS AND MAJOR CONCLUSION: Among three measured cytokines, sequential levels of TNF-α and IL-6 showed significant differences between survivors and nonsurvivors. IL-6 had a good correlation with outcome and scoring systems during the period of this study. The areas under the receiver operating characteristic (AUROC) curve indicated that APACHE II (0.858, 0.848, 0.861) and IL-6 (0.797, 0.799, 0.899) had discriminative power in prediction of mortality during sequental measured days. Multiple logestic regression analysis identified that evaluation of APACHE II and TNF-α in the first day and APACHE II and IL-6 in the third and seventh days of severe septic patients are independent outcome predictors. Results of this study suggest that IL-6 and APACHE II are useful cytokine and scoring systems respectively in prediction of mortality and clinical evaluation of severe septic patients.

Simultaneous spectrophotometric determination of paracetamol, phenylephrine and chlropheniramine in pharmaceuticals using chemometric approaches.

BACKGROUND AND THE PURPOSE OF THE STUDY: The linear multivariate calibration models such as principal components regression (PCR) and partial least squares regressions (PLS1 and PLS2) due to the mathematical simplicity and physical or chemical interpretability are sufficient and generally preferred method for analysis of multicomponent drugs. In this study, simultaneous determination of paracetamol, phenylephrine and chlorpheniramine in pharmaceuticals using chemometric methods and UV spectrophotometry is reported as a simple alternative technique. MATERIAL AND METHODS: Principal components regression (PCR) and partial least squares regressions (PLS1 and PLS2) were used for chemometric analyses of data obtained from the spectra of paracetamol, phenylephrine and chlorpheniramine between wavelengths of 200 to 400 nm at several concentrations within their linear ranges. The analytical performance of these chemometric methods were characterized by relative prediction errors and recoveries (%) and compared with each other. RESULTS: PCR, PLS1 and PLS2 were successfully applied to a tablet formulation, with no interference from excipients as indicated by the recovery. However, the PLS1 shows better results due to its flexibility and mathematical principals. CONCLUSION: The proposed methods are simple and rapid requiring no separation step, and can be easily used as an alternative in the quality control of drugs.

Assessment of endogenous androgen levels in meat, liver and testis of Iranian native cross-breed male sheep and bull by gas chromatography-mass spectrometry.

Androgenic steroids always exist in different animal tissues at trace level, with significant numbers of interfering compounds, which makes their determination difficult. To solve some of the problems in quantification of the natural steroids in those tissues, a new GC-MS method was developed in this study. By using a surrogate analyte approach, which was developed in the authors' previous studies, and extensive sample preparation procedure, which successfully eliminates many of the interfering compounds and resulting in a cleaner extract, accuracy, precision, sensitivity and selectivity of the method for the determination of steroids in complex matrices such as meat, liver and testis were improved. By aid of this method, the levels of androgens in different tissues of Iranian native cross-breed bulls and male sheep were determined. According to the results obtained in the present study, although the androgenic profile (contents and ratios of precursors and metabolites to the main hormones) is similar between the same tissues of both animals, the total androgenic content of each tissue is higher in the bull than the same tissue in male sheep. In addition, in both animals higher amount of androgens were found in liver in comparison with meat and testis.

Simultaneous spectrophotometric determination of paracetamol, ibuprofen and caffeine in pharmaceuticals by chemometric methods.

In this study, the simultaneous determination of paracetamol, ibuprofen and caffeine in pharmaceuticals by chemometric approaches using UV spectrophotometry has been reported as a simple alternative to using separate models for each component. Spectra of paracetamol, ibuprofen and caffeine were recorded at several concentrations within their linear ranges and were used to compute the calibration mixture between wavelengths 200 and 400 nm at an interval of 1 nm in methanol:0.1 HCl (3:1). Partial least squares regression (PLS), genetic algorithm coupled with PLS (GA-PLS), and principal component-artificial neural network (PC-ANN) were used for chemometric analysis of data and the parameters of the chemometric procedures were optimized. The analytical performances of these chemometric methods were characterized by relative prediction errors and recoveries (%) and were compared with each other. The GA-PLS shows superiority over other applied multivariate methods due to the wavelength selection in PLS calibration using a genetic algorithm without loss of prediction capacity. Although the components show an important degree of spectral overlap, they have been determined simultaneously and rapidly requiring no separation step. These three methods were successfully applied to pharmaceutical formulation, capsule, with no interference from excipients as indicated by the recovery study results. The proposed methods are simple and rapid and can be easily used in the quality control of drugs as alternative analysis tools.

Performance comparison of neural network training algorithms in modeling of bimodal drug delivery.

The major aim of this study was to model the effect of two causal factors, i.e. coating weight gain and amount of pectin-chitosan in the coating solution on the in vitro release profile of theophylline for bimodal drug delivery. Artificial neural network (ANN) as a multilayer perceptron feedforward network was incorporated for developing a predictive model of the formulations. Five different training algorithms belonging to three classes: gradient descent, quasi-Newton (Levenberg-Marquardt, LM) and genetic algorithm (GA) were used to train ANN containing a single hidden layer of four nodes. The next objective of the current study was to compare the performance of aforementioned algorithms with regard to predicting ability. The ANNs were trained with those algorithms using the available experimental data as the training set. The divergence of the RMSE between the output and target values of test set was monitored and used as a criterion to stop training. Two versions of gradient descent backpropagation algorithms, i.e. incremental backpropagation (IBP) and batch backpropagation (BBP) outperformed the others. No significant differences were found between the predictive abilities of IBP and BBP, although, the convergence speed of BBP is three- to four-fold higher than IBP. Although, both gradient descent backpropagation and LM methodologies gave comparable results for the data modeling, training of ANNs with genetic algorithm was erratic. The precision of predictive ability was measured for each training algorithm and their performances were in the order of: IBP, BBP>LM>QP (quick propagation)>GA. According to BBP-ANN implementation, an increase in coating levels and a decrease in the amount of pectin-chitosan generally retarded the drug release. Moreover, the latter causal factor namely the amount of pectin-chitosan played slightly more dominant role in determination of the dissolution profiles.

Two matrix metalloproteinases inhibitors from Ferula persica var. persica.

Matrix metalloproteinases (MMPs) play a role in several physiologic and pathologic events. There is some evidence indicating the involvement of MMPs in tumor invasion and inflammatory diseases. Here we studied the chloroform extract of Ferula persica var. persica. The influence of these extracts vs. a reference drug, diclofenac sodium, on MMP production by the fibrosarcoma cell line was investigated using an in vitro cytotoxicity assay, sodium dodecyl sulfate-polyacrylamide, and gelatin zymography. The total extract of the roots was found to exhibit a selective inhibitory effect on tumor cell invasion. The bioactivity-guided fractionation of this extract led to the isolation of two compounds. These compounds showed highest MMP inhibitory effect at minimal toxic dose levels. Using conventional spectroscopy methods, the active fractions were identified as t-butyl 3-[(1-methylthiopropyl)dithio]-2-propenyl malonate (persicasulphide B) and umbelliprenin, previously isolated from F. persica var. latisecta. Since inhibition of MMP activity has been employed in modality therapy in diseases such as cancer, this compound might be promising in the preparation of anti-MMP therapeutic derivatives.

The development of cross-tolerance between morphine and nicotine in mice.

In the present study, cross-tolerance between nicotine and morphine in mice has been investigated. Mice were treated subcutaneously with three doses of morphine (12.5, 25 and 50 mg/kg) once daily, for 3 days in order to produce tolerance to morphine and nicotine antinociception. Tolerance only developed in the high dose group. On the 4th day, the antinociceptive effect of three test doses of morphine (3, 6 and 9 mg/kg) or nicotine (0.01, 0.05 and 0.1 mg/kg) were assessed. Tolerance to the responses of both drugs were observed. Intraperitoneal administration of nicotine (2 mg/kg) three times a day for a period of 12 days, also induced tolerance to the antinociceptive effects of both morphine and nicotine. When animals were tested on the 13th day, the antinociceptive responses of morphine or nicotine were reduced. Another group of animals was treated with low doses of morphine daily (12.5 or 25 mg/kg) plus nicotine (2 mg/kg) three times daily for 3 days. In this group of animals, the antinociception to either morphine or nicotine was tested. Combination of both drugs caused an increase in tolerance to either drug. It is concluded that there is cross-tolerance between the two drugs.