FDA：长效β受体激动剂需限制使用

适当使用时,LABAs利大于弊,可继续用于治疗哮喘。FDA建议仅用于哮喘控制药物如吸入性皮质激素不能有效缓解病情的患者。     

A fast and effective method of quantifying myocardial perfusion by magnetic resonance imaging

The quantification of global myocardial blood flow (MBF) by measuring coronary sinus flow by magnetic resonance (MRI) was demonstrated to be very well correlated with positron emission tomography (PET). We proposed a new method for the quantification of regional myocardial perfusion with MRI by the integration of MBF and first pass technique. The aim of this study was to validate this new method for quantification of regional perfusion by comparing it with 13NH13-PET in swine models of myocardial infarction and in humans in resting and hyperemic conditions. MRI and 13NH3-PET was performed in 2 healthy swine, 11 swine models of myocardial infarction (5 reperfused, 6 non reperfused) and in 12 humans at rest and during hyperemia. MBF was estimated by MRI through the quantification of coronary sinus flow and left ventricular (LV) mass. The upslope of signal intensity (SI-upslope) of each myocardial segment was obtained by the first pass gadolinium technique. Regional SI-upslope was indexed by the upslope of the entire left ventricular myocardium (global upslope). Regional myocardial perfusion was estimated as the product of MBF and SI-upslope/global upslope. Regional perfusion was also estimated by 13NH3-PET. A close agreement of the MRI and PET techniques for measurement of regional myocardial perfusion was found in all myocardial segments by Bland–Altman analysis (mean difference 5.1 %; limits of agreement, ?37.2–27.5 %). With the integration of the first pass technique and the measurement of global MBF by coronary sinus flow/LV mass, MRI allows direct quantification of regional myocardial perfusion.     

How the signal-to-noise ratio influences hyperpolarized 13C dynamic MRS data fitting and parameter estimation

MRS of hyperpolarized (13) C-labeled compounds represents a promising technique for in vivo metabolic studies. However, robust quantification and metabolic modeling are still important areas of investigation. In particular, time and spatial resolution constraints may lead to the analysis of MRS signals with low signal-to-noise ratio (SNR). The relationship between SNR and the precision of quantitative analysis for the evaluation of the in vivo kinetic behavior of metabolites is unknown. In this article, this topic is addressed by Monte Carlo simulations, covering the problem of MRS signal model parameter estimation, with strong emphasis on the peak amplitude and kinetic model parameters. The results of Monte Carlo simulation were confirmed by in vivo experiments on medium-sized animals injected with hyperpolarized [1-(13) C]pyruvate. The results of this study may be useful for the establishment of experimental planning and for the optimization of kinetic model estimation as a function of the SNR value.     

HIV-1 B-subtype capsid protein: a characterization of amino acid’s conservation and its significant association with integrase signatures

The HIV-1 pre-integration phase and the subsequent integration of viral genome to the host of nuclear chromosomes are not well analyzed so far. Many studies are discussing the question of pre- and post-nuclear viral entry which is to support the assumption that HIV-1 integrase (IN) is maintained in the volume of intact conical structure’s capsids through HIV entry. The aim of the current study is to identify the prevalence of capsid’s (CA) signatures among drug-naïve and antiretroviral (ARV)-treated patients in a cohort of 827 HIV-1 B-subtype-infected individuals, and subsequently the relationship between IN and CA amino acid’s changes was evaluated. These analyses suggest a conceivable co-evolution of IN–CA sequences, especially in relation to steps of nuclear viral entry. The frequency of mutations was calculated, and statistically has been compared between treatment-naïve and ARV-treated patients. The binomial correlation coefficient was used to assess covariation among CA and IN mutations; then, the average linkage hierarchical agglomerative clustering was performed. The results show a detailed conservation of HIV-1 CA protein both in drug-naïve and in ARV-treated patients. Moreover, the specific CA substitutions are significantly associated with different IN signatures at the amino acid level and the topology of the dendrogram has revealed the existence of two strong sub-clusters associated with hypothetical different mutational pathways. The in vitro and in vivo studies are necessary to exclude the hypothetical statistical false positive results and in order to confirm that some CA amino acid signatures are going to establish specific and precise implication in the HIV life cycle.     

Biomarkers of periodontal inflammation in the Australian adult population

Background:  Several inflammatory biomarkers are implicated in the pathogenesis of periodontitis including interleukin-1β (IL-1β) and C-reactive protein (CRP). This study investigated the presence of these factors in gingival crevicular fluid (GCF) and their relationship to clinical and social determinants of periodontitis in the Australian population.
Methods:  Equal numbers of periodontitis cases and non-cases were sampled during oral epidemiologic examination in the National Survey of Adult Oral Health. GCF was sampled from four sites where probing pocket depth (PPD) and recession were recorded. From these, IL-1β and CRP were quantified by ELISA and the log amount of GCF IL-1β (pg) per person and the proportion of adults with detectable CRP was computed.
Results:  Periodontitis cases (n = 511) had significantly higher levels of IL-1β and CRP than non-cases (n = 562). PPD, clinical attachment loss, plaque and gingivitis indices were positively associated with elevated levels of both biomarkers. Levels of both were positively associated with age, low socio-economic position and non-Australian birth.
Conclusions:  The presence of IL-1β and CRP in GCF are associated with periodontal disease parameters within the Australian population. The levels of both biomarkers are influenced by age, education and eligibility for public dental care.