Beta-blocker use and COPD mortality: a systematic review and meta-analysis

ABSTRACT: BACKGROUND: Despite the benefits of beta-blockers in patients with established or sub-clinical coronary artery disease, their use in patients with chronic obstructive pulmonary disease (COPD) has been controversial. Currently, no systematic review has examined the impact of beta-blockers on mortality in COPD. METHODS: We systematically searched electronic bibliographic databases including MEDLINE, EMBASE and Cochrane Library for clinical studies that examine the association between beta-blocker use and all cause mortality in patients with COPD. Risk ratios across studies were pooled using random effects models to estimate a pooled relative risk across studies. Publication bias was assessed using a funnel plot. RESULTS: Our search identified nine retrospective cohort studies that met the study inclusion criteria. The pooled relative risk of COPD related mortality secondary to beta-blocker use was 0.69 (95% CI: 0.62-0.78; I2=82%). CONCLUSION: The results of this review are consistent with a protective effect of beta-blockers with respect to all cause mortality. Due to the observational nature of the included studies, the possibility of confounding that may have affected these results cannot be excluded. The hypothesis that beta blocker therapy might be of benefit in COPD needs to be evaluated in randomised controlled trials.     

Hematopoietic stem cell subtypes expand differentially during development and display distinct lymphopoietic programs

Adult hematopoietic stem cells (HSCs) with serially transplantable activity comprise two subtypes. One shows a balanced output of mature lymphoid and myeloid cells; the other appears selectively lymphoid deficient. We now show that both of these HSC subtypes are present in the fetal liver (at a 1:10 ratio) with the rarer, lymphoid-deficient HSCs immediately gaining an increased representation in the fetal bone marrow, suggesting that the marrow niche plays a key role in regulating their ensuing preferential amplification. Clonal analysis of HSC expansion posttransplant showed that both subtypes display an extensive but variable self-renewal activity with occasional interconversion. Clonal analysis of their differentiation programs demonstrated functional and molecular as well as quantitative HSC subtype-specific differences in the lymphoid progenitors they generate but an indistinguishable production of multipotent and myeloid-restricted progenitors. These findings establish a level of heterogeneity in HSC differentiation and expansion control that may have relevance to stem cell populations in other hierarchically organized tissues.     

Response surface methodology in docking study of small molecule BACE-1 inhibitors

Computational evaluation of ligand-receptor binding via docking strategy is a well established approach in structure-based drug design. This technique has been applied frequently in developing molecules of biological interest. However, any procedure would require an optimization set up to be more efficient, economic and time-saving. Advantages of modern statistical optimization methods over conventional one-factor-at-a-time studies have been well revealed. The optimization by experimental design provides a combination of factor levels simultaneously satisfying the requirements considered for each of the responses and factors. In this study, response surface method was applied to optimize the prominent factors (number of genetic algorithm runs, population size, maximum number of evaluations, torsion degrees for ligand and number of rotatable bonds in ligand) in AutoDock4.2-based binding study of small molecule β-secretase inhibitors as anti-alzheimer agents. Results revealed that a number of rotatable bonds in ligand and maximum number of docking evaluations were determinant variables affecting docking outputs. The interference between torsion degrees for ligand and number of genetic algorithm runs for docking procedure was found to be the significant interaction term in our model. Optimized docking outputs exhibited a high correlation with experimental fluorescence resonance energy transfer-based IC(50)s for β-secretase inhibitors (R(2)?=?0.9133).     

Associations between interleukin-10 polymorphisms and susceptibility to juvenile idiopathic arthritis: a systematic review and meta-analysis

Background

Cytokine genes, including interleukin-10 (IL-10), are known to play important roles in the pathogenesis of juvenile idiopathic arthritis (JIA). This study aims to determine whether the IL-10 polymorphisms confer susceptibility to JIA.

Methods

A meta-analysis was performed on the associations between the IL-10-1082 G/A, -592 C/A, and -819 C/T polymorphisms and JIA. A total number of 7 studies involving 1,785 patients and 6,142 controls were considered in the meta-analysis.

Results

Meta-analysis of the IL-10-592 C/A and -819 C/T polymorphisms showed no association with JIA in the study participants, or in Caucasian or Middle Eastern participants. Meta-analysis of the IL-10-1082 A allele in all study participants, Caucasian and Middle Eastern, showed significant associations with RA (overall ORs were 1.17, 1.15, and 1.41, respectively). Meta-analysis of the AA versus GG genotype of the IL-10-1082 G/A polymorphism revealed significant associations with JIA (OR = 3.66, 95% CI = 1.44-9.29, P = 0.006) in participants from Middle Eastern countries. Additionally, meta-analysis of the GG versus AA+GA genotypes of the IL-10 -1082 G/A polymorphism revealed the GG genotype as the protective factor against JIA in the Middle Eastern subgroup (OR = 0.44, 95% CI = 0.20-0.94, P = 0,04). Moreover, meta-analysis of the IL-10 -1082 A allele in 4 studies on Hardy-Weinberg equilibrium showed a significant association with JIA (OR = 1.17, 95% CI = 1.07-1.28, P = 0.0009). No association was found between the IL-10 (-1082, -819, -592) ACC, ATA, and GCC haplotypes and JIA.

Conclusions

These results suggest that the IL-10-1082 G/A polymorphism confers susceptibility to JIA.

     

Toll-like receptors pathway in common variable immune deficiency (CVID) and X-linked agammaglobulinemia (XLA)

Common variable immunodeficiency (CVID) and X-linked agammaglobulinemia (XLA) are two major humoral immunodeficiencies, causing a high rate of early age mortality in children. In order to identifiy the possible factors involved in the pathogenesis of CVID and XLA, recent studies have focused on Toll-like receptors (TLRs) and demonstrate the defects in different TLR pathways in immune cells of CVID and XLA patients. Herein, we measured TLR-4 and TLR-9 RNA levels and consequently TNF-α and IFN-α production in peripheral blood mononuclear cells (PBMCs) of patients with CVID and XLA. Contrary to healthy individuals, TLR-9 expression was not significantly increased after ligand stimulation, whereas ligand-induced TLR-4 expression was not significantly different from that in healthy control PBMCs. Lipopolysaccharide (LPS)-stimulated TNF-α production was significantly reduced in patients compared to controls, whereas IFN-α production was increased in all groups after CpG stimulation without any significant inter-group difference. Our data suggest that defects in TLR-9 activated pathways may be a result of the decreased TLR-9 expression, although TLR-9 is not the only modulator of IFN-α production in these patients. On the other hand, impaired signaling in TLR-4 activated pathways which results in significant reduction in TNF-α production are not related to a defect in TLR-4 expression.     

Flow Cytometry Bioinformatics

Flow cytometry bioinformatics is the application of bioinformatics to flow cytometry data, which involves storing, retrieving, organizing, and analyzing flow cytometry data using extensive computational resources and tools. Flow cytometry bioinformatics requires extensive use of and contributes to the development of techniques from computational statistics and machine learning. Flow cytometry and related methods allow the quantification of multiple independent biomarkers on large numbers of single cells. The rapid growth in the multidimensionality and throughput of flow cytometry data, particularly in the 2000s, has led to the creation of a variety of computational analysis methods, data standards, and public databases for the sharing of results. Computational methods exist to assist in the preprocessing of flow cytometry data, identifying cell populations within it, matching those cell populations across samples, and performing diagnosis and discovery using the results of previous steps. For preprocessing, this includes compensating for spectral overlap, transforming data onto scales conducive to visualization and analysis, assessing data for quality, and normalizing data across samples and experiments. For population identification, tools are available to aid traditional manual identification of populations in two-dimensional scatter plots (gating), to use dimensionality reduction to aid gating, and to find populations automatically in higher dimensional space in a variety of ways. It is also possible to characterize data in more comprehensive ways, such as the density-guided binary space partitioning technique known as probability binning, or by combinatorial gating. Finally, diagnosis using flow cytometry data can be aided by supervised learning techniques, and discovery of new cell types of biological importance by high-throughput statistical methods, as part of pipelines incorporating all of the aforementioned methods. Open standards, data, and software are also key parts of flow cytometry bioinformatics. Data standards include the widely adopted Flow Cytometry Standard (FCS) defining how data from cytometers should be stored, but also several new standards under development by the International Society for Advancement of Cytometry (ISAC) to aid in storing more detailed information about experimental design and analytical steps. Open data is slowly growing with the opening of the CytoBank database in 2010 and FlowRepository in 2012, both of which allow users to freely distribute their data, and the latter of which has been recommended as the preferred repository for MIFlowCyt-compliant data by ISAC. Open software is most widely available in the form of a suite of Bioconductor packages, but is also available for web execution on the GenePattern platform.

This is a “Topic Page” article for PLOS Computational Biology.

     

Anisotropy profoundly alters stress fields within contractile cells and cell aggregates

Biomechanics and Modeling in Mechanobiology - Many biological phenomena such as cell proliferation and death are correlated with stress fields within cells. Stress fields are quantified using...     

Dysregulation of the immune response in coronavirus disease 2019

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can trigger a cytokine storm in the pulmonary tissue by releasing various types of mediators, leading to acute respiratory distress syndrome (ARDS). Increased neutrophil-to-lymphocyte ratio, as well as CD4+ T lymphopenia, is reported in cases with novel coronavirus disease (COVID-19), meanwhile, lymphopenia is a significant finding in the majority of COVID-19 cases with a severe phenotype. Moreover, excessive activation of monocyte/macrophage and cytokine storms are associated with the severity of the disease and the related complications in SARS-CoV-2 infection. Understanding the immune response dysregulation in COVID-19 is essential to develop more effective diagnostic, therapeutic, and prophylactic strategies in this pandemic.     

Clinical and therapeutic implications of BRAF mutation heterogeneity in metastatic melanoma

Heterogeneity of BRAF mutation in melanoma has been a controversial subject. Quantitative data on BRAF allele frequency (AF) are sparse, and the potential relationship with response to BRAF inhibitors (BRAFi) in patients with metastatic melanoma is unknown. We quantitatively measured BRAF AF in a cohort of treatment naïve metastatic melanoma samples by pyrosequencing and correlated with survival data in patients treated with BRAFi as part of their clinical care. Fifty‐two samples from 50 patients were analysed. BRAF V600E mutations were detected in 71.1% of samples followed by V600K (25%) and V600R (3.9%). There was a wide range of AF from 3.9% to 80.3% (median 41.3%). In 33 patients treated with BRAFi, there was no difference in overall or progression‐free survival when the patients were categorized into high or low AF groups. There was no correlation between AF and degree of response, and no difference in survival based on genotype.