Effect of Early Normobaric Hyperoxia on Blast-Induced Traumatic Brain Injury in Rats

Neurochemical Research - Blast-induced traumatic brain injury (bTBI) is a leading cause of disability and mortality in soldiers during the conflicts in Iraq and Afghanistan. Although substantial...     

9-Phenanthrol,a TRPM4 Inhibitor,Protects Isolated Rat Hearts from Ischemia–Reperfusion Injury

Despite efforts to elucidate its pathophysiology, ischemia–reperfusion injury lacks an effective preventative intervention. Because transient receptor potential cation channel subfamily M member 4 (TRPM4) is functionally expressed by many cell types in the cardiovascular system and is involved in the pathogenesis of various cardiovascular diseases, we decided to assess its suitability as a target of therapy. Thus, the aim of this study was to examine the possible cardioprotective effect of 9-phenanthrol, a specific inhibitor of TRPM4. Isolated Langendorff-perfused rat hearts were pretreated with Krebs–Henseleit (K–H) solution (control), 9-phenanthrol, or 5-hydroxydecanoate (5-HD, a blocker of the ATP-sensitive potassium channel) and then subjected to global ischemia followed by reperfusion with the K–H solution. To evaluate the extent of heart damage, lactate dehydrogenase (LDH) activity in the effluent solution was measured, and the size of infarcted area of the heart was measured by 2,3,5-triphenyltetrazolium chloride staining. In controls, cardiac contractility decreased, and LDH activity and the infarcted area size increased. In contrast, in hearts pretreated with 9-phenanthrol, contractile function recovered dramatically, and the infarcted area size significantly decreased. The cardioprotective effects of 9-phenanthrol was not completely blocked by 5-HD. These findings show that 9-phenanthrol exerts a cardioprotective effect against ischemia in the isolated rat heart and suggest that its mechanism of action is largely independent of ATP-sensitive potassium channels.     

Capillary gas chromatographic determination of 1,4-butanediol and gamma-hydroxybutyrate in human plasma and urine

This article describes two methods for the determination of 1,4-butanediol and gamma-hydroxybutyrate in human plasma and urine using capillary gas chromatography. For 1,4-butanediol, plasma or urine samples (500 microl) were extracted by protein precipitation whereas for gamma-hydroxybutyrate, plasma or urine samples (500 microl) were extracted and derivatised with BF3-butanol. The compounds were separated on a Supelcowax-10 column and detection was achieved using a flame ionization detector. The methods are linear over the specific ranges investigated, accurate (with a percentage of the nominal concentration <109.8%) and showed intra-day and inter-day precision within the ranges of 5.0-12.0 and 7.0-10.1%, respectively. No interferences were observed in plasma and urine from hospitalized patients.     

Comparison of Linear,Nonlinear and Semiparametric Mixed‐effects Models for Estimating HIV Dynamic Parameters

The potency of antiretroviral agents in AIDS clinical trials can be assessed on the basis of an early viral response such as viral decay rate or change in viral load (number of copies of HIV RNA) of the plasma. Linear, parametric nonlinear, and semiparametric nonlinear mixed‐effects models have been proposed to estimate viral decay rates in viral dynamic models. However, before applying these models to clinical data, a critical question that remains to be addressed is whether these models produce coherent estimates of viral decay rates, and if not, which model is appropriate and should be used in practice. In this paper, we applied these models to data from an AIDS clinical trial of potent antiviral treatments and found significant incongruity in the estimated rates of reduction in viral load. Simulation studies indicated that reliable estimates of viral decay rate were obtained by using the parametric and semiparametric nonlinear mixed‐effects models. Our analysis also indicated that the decay rates estimated by using linear mixed‐effects models should be interpreted differently from those estimated by using nonlinear mixed‐effects models. The semiparametric nonlinear mixed‐effects model is preferred to other models because arbitrary data truncation is not needed. Based on real data analysis and simulation studies, we provide guidelines for estimating viral decay rates from clinical data. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Quantifying the Early Immune Response and Adaptive Immune Response Kinetics in Mice Infected with Influenza A Virus

Seasonal and pandemic influenza A virus (IAV) continues to be a public health threat. However, we lack a detailed and quantitative understanding of the immune response kinetics to IAV infection and which biological parameters most strongly influence infection outcomes. To address these issues, we use modeling approaches combined with experimental data to quantitatively investigate the innate and adaptive immune responses to primary IAV infection. Mathematical models were developed to describe the dynamic interactions between target (epithelial) cells, influenza virus, cytotoxic T lymphocytes (CTLs), and virus-specific IgG and IgM. IAV and immune kinetic parameters were estimated by fitting models to a large data set obtained from primary H3N2 IAV infection of 340 mice. Prior to a detectable virus-specific immune response (before day 5), the estimated half-life of infected epithelial cells is ∼1.2 days, and the half-life of free infectious IAV is ∼4 h. During the adaptive immune response (after day 5), the average half-life of infected epithelial cells is ∼0.5 days, and the average half-life of free infectious virus is ∼1.8 min. During the adaptive phase, model fitting confirms that CD8⁺ CTLs are crucial for limiting infected cells, while virus-specific IgM regulates free IAV levels. This may imply that CD4 T cells and class-switched IgG antibodies are more relevant for generating IAV-specific memory and preventing future infection via a more rapid secondary immune response. Also, simulation studies were performed to understand the relative contributions of biological parameters to IAV clearance. This study provides a basis to better understand and predict influenza virus immunity.Current strategies for preventing or decreasing the severity of influenza infection focus on increasing virus-neutralizing antibody titers through vaccination, as experience indicates that this is the best way to prevent morbidity and mortality. Influenza A virus (IAV) undergoes mutations of the genes encoding the hemagglutinin (HA) and neuraminidase (NA) proteins that the neutralizing antibodies are directed against. When the variation is low (antigenic drift), prior vaccination often confers substantial heterologous immunity against a new seasonal IAV strain. In contrast, major genetic changes (antigenic shift) can result in pandemic IAV strains, since for novel strains, the humoral immune response is a primary response, and heterologous immunity is lacking. The emergence of such pandemic strains and the fact that young children are more vulnerable to influenza diseases highlight the need to better understand which viral and immune parameters determine the outcome of infection with viruses novel to the individual.Conventional experimental methods to measure influenza virus immunity have been limited to animal models and studies of adult human peripheral blood leukocytes. The advantages of using animal models include the ability to intensively sample multiple tissues and to utilize genetic and other interventions, such as blocking or depleting antibodies, to dissect the contribution of individual arms of the immune system. However, it is easy to question the relevance of these experiments to humans because of the many important biological differences between human and murine immune systems (29). In both the animal and human systems, we are limited to measuring those parameters and variables for which assays are available, most of them being ex vivo. Parameters such as cell-to-cell spread of the virus in vivo, trafficking of immune cells to the lung, and the in vivo interactions in an intact immune system are much more difficult or impossible to measure with contemporary techniques, particularly in humans. Computational approaches have the potential to offset some of these limitations and provide additional insight into the kinetics of the IAV infection and the associated immune response.Animal models of influenza virus infection in which different arms of the immune system have been suppressed suggest that some components of the adaptive immune system are required for complete viral clearance, often termed a sterilizing immune response. For example, abrogation of the CD4 T-cell response by cytotoxic antibody therapy or through knockout of major histocompatibility complex (MHC) class II slightly delays viral clearance but has little overall effect on the ability to control the infection (21, 54, 55). Elimination of the CD8 T-cell response typically results in delayed viral clearance (12, 20, 47), although animals with intact CD4 T-cell and B-cell compartments are able to control the infection in the absence of CD8 T cells. Presumably, this occurs through antibody-mediated mechanisms (54). Most animals depleted of both CD8 T cells and B cells are not able to clear the virus, which results in death (14, 32, 53). CD4⁺ T cells certainly contribute to the control of IAV infection, although cytotoxic CD4 T cells are not frequently observed unless cultured in vitro (8, 22, 45). Thus, it is generally accepted that CD8 T cells and/or antibodies are sufficient for timely and complete IAV clearance. Studies that strictly separate the relative roles of CD8 T cells and virus-specific antibodies are less satisfying. Animals depleted of both CD4 and CD8 T cells generally do not control the infection, despite substantial production of anti-IAV IgM antibodies (4, 23, 33, 34). However, adoptive transfer of IAV-specific IgM or IgG antibodies is protective (40, 51), suggesting that the timing and magnitude of the antibody response, i.e., the affinity, avidity, and antibody isotype, are important protective factors.While murine gene knockout or lymphocyte depletion studies are highly informative, they also have a number of limitations. Most importantly, the near-complete ablation of one component of the adaptive immune system often causes profound and unpredictable effects on many other immune components. Although the reported experimental measurements are highly quantitative, they often focus only on a limited number of time points or measurements and do not capture the complexity of the altered, or intact, immune response. In contrast, high-frequency experimental sampling, coupled with mathematical modeling techniques and new statistical approaches, can give insights into the complex biology of IAV infection and test the assumptions inherent in the model. We have learned from other systems, particularly HIV (19, 35, 37, 38, 56), that quantitative analysis of the biology can reveal important factors that are not intuitively obvious. For example, our current estimates for the rates of HIV production and the life span of productively infected cells in vivo were obtained via mathematical modeling (35).Mathematical models have long been used to investigate viral dynamics and immune responses to viral infections, including influenza A virus (3, 5, 7, 15, 16, 31, 36, 48). We recently described a complex differential equation model to simulate and predict the adaptive immune response to IAV infection (24). This model involves 15 equations and 48 parameters, and because of its complexity, many of the parameter values that could not be directly measured were unidentifiable. Thus, it is difficult to estimate all model parameters by fitting experimental data directly to this complex model, although the model can be used to perform simulation predictions (25). This issue can, however, be addressed by reducing the model into smaller submodels with smaller but identifiable sets of parameters, which can be estimated from experimental data. In this paper, we describe such an approach which focuses on IAV infection and the immune response solely within the lung.In the present report, we have fitted a model of primary murine influenza virus infection to data. In naïve subjects, our data suggested that there is no adaptive immune response (e.g., IAV-specific CD8⁺ T cells or antibodies) detectable in the spleen, lymph nodes, or lung until approximately 5 days after infection; therefore, we have divided the analysis into the following two phases: the initial preadaptive (innate) phase and the later adaptive phase. We use direct experimental data from infection of mice with the H3N2 influenza virus A/X31 strain (2, 24) to obtain key kinetic parameters. The model fitting has revealed that the duration of the infection depends on a small set of immune components, and even large fluctuations in other arms of the immune system or IAV behavior have surprisingly little impact on the outcome of the infection.     

MARS Approach for Global Sensitivity Analysis of Differential Equation Models with Applications to Dynamics of Influenza Infection

Differential equation models are widely used for the study of natural phenomena in many fields. The study usually involves unknown factors such as initial conditions and/or parameters. It is important to investigate the impact of unknown factors (parameters and initial conditions) on model outputs in order to better understand the system the model represents. Apportioning the uncertainty (variation) of output variables of a model according to the input factors is referred to as sensitivity analysis. In this paper, we focus on the global sensitivity analysis of ordinary differential equation (ODE) models over a time period using the multivariate adaptive regression spline (MARS) as a meta model based on the concept of the variance of conditional expectation (VCE). We suggest to evaluate the VCE analytically using the MARS model structure of univariate tensor-product functions which is more computationally efficient. Our simulation studies show that the MARS model approach performs very well and helps to significantly reduce the computational cost. We present an application example of sensitivity analysis of ODE models for influenza infection to further illustrate the usefulness of the proposed method.     

Characterization of N-terminal amino group–heme ligation emerging upon guanidine hydrochloric acid induced unfolding of <Emphasis Type="Italic">Hydrogenobacter thermophilus</Emphasis> ferricytochrome <Emphasis Type="Italic">c</Emphasis><Subscript>552</Subscript>

Nonnative heme coordination structures emerging upon guanidine hydrochloric acid (GdnHCl) induced unfolding of Hydrogenobacter thermophilus ferricytochrome c ₅₅₂ were characterized by means of paramagnetic NMR. The heme coordination structure possessing the N-terminal amino group of the peptide chain in place of axial Met (His–N_term form) was determined in the presence of GdnHCl concentrations in excess of 1.5 M at neutral pH. The stability of the His–N_term form at pH 7.0 was found to be comparable with that of the bis-His form which has been recognized as a major nonnative heme coordination structure in cytochrome c folding/unfolding. Consequently, in addition to the bis-His form, the His–N_term form is a substantial intermediate which affects the pathway and kinetics of the folding/unfolding of cytochromes c, of which the N-terminal amino groups are not acetylated. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

(3,3-Difluoro-pyrrolidin-1-yl)-[(2S,4S)-(4-(4-pyrimidin-2-yl-piperazin-1-yl)-pyrrolidin-2-yl]-methanone: A potent,selective, orally active dipeptidyl peptidase IV inhibitor

A series of 4-substituted proline amides was synthesized and evaluated as inhibitors of dipeptidyl pepdidase IV for the treatment of type 2 diabetes. (3,3-Difluoro-pyrrolidin-1-yl)-[(2S,4S)-(4-(4-pyrimidin-2-yl-piperazin-1-yl)-pyrrolidin-2-yl]-methanone (5) emerged as a potent (IC₅₀ = 13 nM) and selective compound, with high oral bioavailability in preclinical species and low plasma protein binding. Compound 5, PF-00734200, was selected for development as a potential new treatment for type 2 diabetes.     

AngⅡ通过激活Notch1/Sox2通路对肝星状细胞LX2的活化和增殖的作用

目的探讨AngⅡ通过靶向调控Notch1/Sox2肝星状细胞LX2细胞的增殖。 方法通过CCK8检测AngⅡ对肝星状细胞增殖能力的影响,通过羟脯氨酸酸法检测AngⅡ对肝星状细胞胶原合成能力的影响,并通过脂质体转染siRNA-Notch1构建Notch1低表达细胞模型,通过CCK8检测敲低Notch1对AngⅡ诱导的肝星状细胞LX2增殖的影响,通过Western Blot检测敲低Notch1对AngⅡ诱导的肝星状细胞LX2蛋白表达的影响。所有的检测结果都进行生物学重复。采用方差分析和t检验进行统计学分析。 结果CCK8结果显示,AngⅡ（5、10、20、40、80 nmol/L）预处理A450值分别为0.67±0.06、0.88±0.07、0.98±0.07、1.08±0.07、1.23±0.07,较对照组0.57±0.05上升,差异具有统计学意义（F = 45.76,P < 0.01）,羟脯氨酸检查结果显示,AngⅡ（10、20、40 nmol/L）预处理组羟脯氨酸浓度分别为（2.60±0.20）、（3.47±0.25）、（4.17±0.21）mg/L,羟脯氨酸浓度较对照组（1.90±0.10）mg/L上升,差异具有统计学意义（F = 75.18,P < 0.01）。Western Blot结果显示,AngⅡ10、20、40 nmol/L组Notch1蛋白表达水平分别为0.20±0.02、0.54±0.04、0.82±0.03,与正常对照组0.11±0.02发生升高,差异具有统计学意义（F = 400.50,P < 0.01）。Notch1干扰后,CCK8结果显示,siRNA-Notch1+AngⅡ组（10、20、40 nmol/L）A450值分别为0.53±0.06、0.83±0.03、1.03±0.03,与siRNA-NC+ AngⅡ对照组0.97±0.06,1.43±0.06,1.73±0.06比较发生降低（P < 0.01）。进一步Western Blot结果显示,Notch1敲低组（AngⅡ+ siRNA-Notch1）Notch1、HES1和Sox2蛋白表达水平分别为1.47±0.12、0.77±0.06和0.50±0.10,分别与AngⅡ对照组2.83±0.15、2.20±0.10和1.17±0.06比较,差异具有统计学意义（P < 0.01）。 结论AngⅡ通过激活Notch1/Sox2信号促进肝星状细胞LX2增殖。