Carbon-13 and silicon-29 NMR spectra of some [tris(trimethylsilyl)methyl]-substituted silanes and related compounds

Fourier Transform 13C and 29Si NMR spectra are reported for series of [tris-(trimethylsilyl)methyl] dimethylsilanes, [tris(trimethylsilyl)methyl] diphenylsilanes, and for related compounds. Analysis of chemical shift values indicates that such information can be useful in determining the structure in these highly hindered, but structurally similar compounds. In particular, the carbon and silicon atoms of the trimethylsilyl groups absorb in a narrow shift range, while other carbon and silicon atoms more characteristically reflect the substitution patterns in these compounds.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/23894/1/0000133.pd

Identification of Key Processes that Control Tumor Necrosis Factor Availability in a Tuberculosis Granuloma

Tuberculosis (TB) granulomas are organized collections of immune cells comprised of macrophages, lymphocytes and other cells that form in the lung as a result of immune response to Mycobacterium tuberculosis (Mtb) infection. Formation and maintenance of granulomas are essential for control of Mtb infection and are regulated in part by a pro-inflammatory cytokine, tumor necrosis factor-α (TNF). To characterize mechanisms that control TNF availability within a TB granuloma, we developed a multi-scale two compartment partial differential equation model that describes a granuloma as a collection of immune cells forming concentric layers and includes TNF/TNF receptor binding and trafficking processes. We used the results of sensitivity analysis as a tool to identify experiments to measure critical model parameters in an artificial experimental model of a TB granuloma induced in the lungs of mice following injection of mycobacterial antigen-coated beads. Using our model, we then demonstrated that the organization of immune cells within a TB granuloma as well as TNF/TNF receptor binding and intracellular trafficking are two important factors that control TNF availability and may spatially coordinate TNF-induced immunological functions within a granuloma. Further, we showed that the neutralization power of TNF-neutralizing drugs depends on their TNF binding characteristics, including TNF binding kinetics, ability to bind to membrane-bound TNF and TNF binding stoichiometry. To further elucidate the role of TNF in the process of granuloma development, our modeling and experimental findings on TNF-associated molecular scale aspects of the granuloma can be incorporated into larger scale models describing the immune response to TB infection. Ultimately, these modeling and experimental results can help identify new strategies for TB disease control/therapy

Scholarship on Gender and Sport in Sex Roles and Beyond

In this paper we critically review how research on girls or women and sport has developed over the last 35 years. We use a post-positivist lens to explore the content of the papers published in Sex Roles in the area of women, gender and sport and examine the shifts in how gender and sport have been conceptualized in these accounts. In order to initiate a broader dialogue about the scholarly analysis of gender and sport, we subsequently explore ideas inspired by feminist theorizing that have dominated/guided related research in other outlets over this time period but have received relatively little attention in papers published in Sex Roles. We conclude by briefly making suggestions for further research in this area

MOBAS: identification of disease-associated protein subnetworks using modularity-based scoring

Network-based analyses are commonly used as powerful tools to interpret the findings of genome-wide association studies (GWAS) in a functional context. In particular, identification of disease-associated functional modules, i.e., highly connected protein-protein interaction (PPI) subnetworks with high aggregate disease association, are shown to be promising in uncovering the functional relationships among genes and proteins associated with diseases. An important issue in this regard is the scoring of subnetworks by integrating two quantities: disease association of individual gene products and network connectivity among proteins. Current scoring schemes either disregard the level of connectivity and focus on the aggregate disease association of connected proteins or use a linear combination of these two quantities. However, such scoring schemes may produce arbitrarily large subnetworks which are often not statistically significant or require tuning of parameters that are used to weigh the contributions of network connectivity and disease association. Here, we propose a parameter-free scoring scheme that aims to score subnetworks by assessing the disease association of interactions between pairs of gene products. We also incorporate the statistical significance of network connectivity and disease association into the scoring function. We test the proposed scoring scheme on a GWAS dataset for two complex diseases type II diabetes (T2D) and psoriasis (PS). Our results suggest that subnetworks identified by commonly used methods may fail tests of statistical significance after correction for multiple hypothesis testing. In contrast, the proposed scoring scheme yields highly significant subnetworks, which contain biologically relevant proteins that cannot be identified by analysis of genome-wide association data alone. We also show that the proposed scoring scheme identifies subnetworks that are reproducible across different cohorts, and it can robustly recover relevant subnetworks at lower sampling rates

May Measurement Month 2018: a pragmatic global screening campaign to raise awareness of blood pressure by the International Society of Hypertension

Aims Raised blood pressure (BP) is the biggest contributor to mortality and disease burden worldwide and fewer than half of those with hypertension are aware of it. May Measurement Month (MMM) is a global campaign set up in 2017, to raise awareness of high BP and as a pragmatic solution to a lack of formal screening worldwide. The 2018 campaign was expanded, aiming to include more participants and countries. Methods and results Eighty-nine countries participated in MMM 2018. Volunteers (≥18 years) were recruited through opportunistic sampling at a variety of screening sites. Each participant had three BP measurements and completed a questionnaire on demographic, lifestyle, and environmental factors. Hypertension was defined as a systolic BP ≥140 mmHg or diastolic BP ≥90 mmHg, or taking antihypertensive medication. In total, 74.9% of screenees provided three BP readings. Multiple imputation using chained equations was used to impute missing readings. 1 504 963 individuals (mean age 45.3 years; 52.4% female) were screened. After multiple imputation, 502 079 (33.4%) individuals had hypertension, of whom 59.5% were aware of their diagnosis and 55.3% were taking antihypertensive medication. Of those on medication, 60.0% were controlled and of all hypertensives, 33.2% were controlled. We detected 224 285 individuals with untreated hypertension and 111 214 individuals with inadequately treated (systolic BP ≥ 140 mmHg or diastolic BP ≥ 90 mmHg) hypertension. Conclusion May Measurement Month expanded significantly compared with 2017, including more participants in more countries. The campaign identified over 335 000 adults with untreated or inadequately treated hypertension. In the absence of systematic screening programmes, MMM was effective at raising awareness at least among these individuals at risk