Mr. W. Dale Malleck to Mr. James Meredith (1 October 1962)

https://egrove.olemiss.edu/mercorr_pro/1298/thumbnail.jp

Which feedback mechanisms dominate in the high-pressure environment of the Central Molecular Zone?

Supernovae (SNe) dominate the energy and momentum budget of stellar feedback, but the efficiency with which they couple to the interstellar medium (ISM) depends strongly on how effectively early, pre-SN feedback clears dense gas from star-forming regions. There are observational constraints on the magnitudes and timescales of early stellar feedback in low ISM pressure environments, yet no such constraints exist for more cosmologically typical high ISM pressure environments. In this paper, we determine the mechanisms dominating the expansion of HII regions as a function of size-scale and evolutionary time within the high-pressure (P/k_\rm{B}~$10^{7-8}$K cm$^{-3}$) environment in the inner 100pc of the Milky Way. We calculate the thermal pressure from the warm ionised (P_\rm{HII}; 10$^{4}$K) gas, direct radiation pressure (P_\rm{dir}), and dust processed radiation pressure (P_\rm{IR}). We find that (1) P_\rm{dir} dominates the expansion on small scales and at early times (0.01-0.1pc; $0.1$pc; $>1$Myr); (3) during the first ~1Myr of growth, but not thereafter, either $P_{\rm IR}$ or stellar wind pressure likely make a comparable contribution. Despite the high confining pressure of the environment, natal star-forming gas is efficiently cleared to radii of several pc within ~2Myr, i.e. before the first SNe explode. This `pre-processing' means that subsequent SNe will explode into low density gas, so their energy and momentum will efficiently couple to the ISM. We find the HII regions expand to a radius of 3pc, at which point they have internal pressures equal with the surrounding external pressure. A comparison with HII regions in lower pressure environments shows that the maximum size of all HII regions is set by pressure equilibrium with the ambient ISM

Metabolic clusters of breast cancer in relation to gene- and protein expression subtypes

Background: The heterogeneous biology of breast cancer leads to high diversity in prognosis and response to treatment, even for patients with similar clinical diagnosis, histology, and stage of disease. Identifying mechanisms contributing to this heterogeneity may reveal new cancer targets or clinically relevant subgroups for treatment stratification. In this study, we have merged metabolite, protein, and gene expression data from breast cancer patients to examine the heterogeneity at a molecular level.Methods: The study included primary tumor samples from 228 non-treated breast cancer patients. High-resolution magic-angle spinning magnetic resonance spectroscopy (HR MAS MRS) was performed to extract the tumors metabolic profiles further used for hierarchical cluster analysis resulting in three significantly different metabolic clusters (Mc1, Mc2, and Mc3). The clusters were further combined with gene and protein expression data.Results: Our result revealed distinct differences in the metabolic profile of the three metabolic clusters. Among the most interesting differences, Mc1 had the highest levels of glycerophosphocholine (GPC) and phosphocholine (PCho), Mc2 had the highest levels of glucose, and Mc3 had the highest levels of lactate and alanine. Integrated pathway analysis of metabolite and gene expression data uncovered differences in glycolysis/gluconeogenesis and glycerophospholipid metabolism between the clusters. All three clusters had significant differences in the distribution of protein subtypes classified by the expression of breast cancer-related proteins. Genes related to collagens and extracellular matrix were downregulated in Mc1 and consequently upregulated in Mc2 and Mc3, underpinning the differences in protein subtypes within the metabolic clusters. Genetic subtypes were evenly distributed among the three metabolic clusters and could therefore contribute to additional explanation of breast cancer heterogeneity.Conclusions: Three naturally occurring metabolic clusters of breast cancer were detected among primary tumors from non-treated breast cancer patients. The clusters expressed differences in breast cancer-related protein as well as genes related to extracellular matrix and metabolic pathways known to be aberrant in cancer. Analyses of metabolic activity combined with gene and protein expression provide new information about the heterogeneity of breast tumors and, importantly, the metabolic differences infer that the clusters may be susceptible to different metabolically targeted drugs

Cholesterol and the risk of grade-specific prostate cancer incidence: evidence from two large prospective cohort studies with up to 37 years' follow up

<b>Background</b> High cholesterol may be a modifiable risk factor for prostate cancer but results have been inconsistent and subject to potential "reverse causality" where undetected disease modifies cholesterol prior to diagnosis.<p></p> <b>Methods</b> We conducted a prospective cohort study of 12,926 men who were enrolled in the Midspan studies between 1970 and 1976 and followed up to 31st December 2007. We used Cox-Proportional Hazards Models to evaluate the association between baseline plasma cholesterol and Gleason grade-specific prostate cancer incidence. We excluded cancers detected within at least 5 years of cholesterol assay.<p></p> <b>Results</b> 650 men developed prostate cancer in up to 37 years' follow-up. Baseline plasma cholesterol was positively associated with hazard of high grade (Gleason score[greater than or equal to]8) prostate cancer incidence (n=119). The association was greatest among men in the 4th highest quintile for cholesterol, 6.1 to <6.69 mmol/l, Hazard Ratio 2.28, 95% CI 1.27 to 4.10, compared with the baseline of <5.05 mmol/l. This association remained significant after adjustment for body mass index, smoking and socioeconomic status.<p></p> <b>Conclusions</b> Men with higher cholesterol are at greater risk of developing high-grade prostate cancer but not overall risk of prostate cancer. Interventions to minimise metabolic risk factors may have a role in reducing incidence of aggressive prostate cancer

The stellar and sub-stellar IMF of simple and composite populations

The current knowledge on the stellar IMF is documented. It appears to become top-heavy when the star-formation rate density surpasses about 0.1Msun/(yr pc^3) on a pc scale and it may become increasingly bottom-heavy with increasing metallicity and in increasingly massive early-type galaxies. It declines quite steeply below about 0.07Msun with brown dwarfs (BDs) and very low mass stars having their own IMF. The most massive star of mass mmax formed in an embedded cluster with stellar mass Mecl correlates strongly with Mecl being a result of gravitation-driven but resource-limited growth and fragmentation induced starvation. There is no convincing evidence whatsoever that massive stars do form in isolation. Various methods of discretising a stellar population are introduced: optimal sampling leads to a mass distribution that perfectly represents the exact form of the desired IMF and the mmax-to-Mecl relation, while random sampling results in statistical variations of the shape of the IMF. The observed mmax-to-Mecl correlation and the small spread of IMF power-law indices together suggest that optimally sampling the IMF may be the more realistic description of star formation than random sampling from a universal IMF with a constant upper mass limit. Composite populations on galaxy scales, which are formed from many pc scale star formation events, need to be described by the integrated galactic IMF. This IGIMF varies systematically from top-light to top-heavy in dependence of galaxy type and star formation rate, with dramatic implications for theories of galaxy formation and evolution.Comment: 167 pages, 37 figures, 3 tables, published in Stellar Systems and Galactic Structure, Vol.5, Springer. This revised version is consistent with the published version and includes additional references and minor additions to the text as well as a recomputed Table 1. ISBN 978-90-481-8817-

Amyloid-Associated Nucleic Acid Hybridisation

Nucleic acids promote amyloid formation in diseases including Alzheimer's and Creutzfeldt-Jakob disease. However, it remains unclear whether the close interactions between amyloid and nucleic acid allow nucleic acid secondary structure to play a role in modulating amyloid structure and function. Here we have used a simplified system of short basic peptides with alternating hydrophobic and hydrophilic amino acid residues to study nucleic acid - amyloid interactions. Employing biophysical techniques including X-ray fibre diffraction, circular dichroism spectroscopy and electron microscopy we show that the polymerized charges of nucleic acids concentrate and enhance the formation of amyloid from short basic peptides, many of which would not otherwise form fibres. In turn, the amyloid component binds nucleic acids and promotes their hybridisation at concentrations below their solution Kd, as shown by time-resolved FRET studies. The self-reinforcing interactions between peptides and nucleic acids lead to the formation of amyloid nucleic acid (ANA) fibres whose properties are distinct from their component polymers. In addition to their importance in disease and potential in engineering, ANA fibres formed from prebiotically-produced peptides and nucleic acids may have played a role in early evolution, constituting the first entities subject to Darwinian evolution

Molecular gas kinematics within the central 250 pc of the Milky Way

Using spectral-line observations of HNCO, N2H+, and HNC, we investigate the kinematics of dense gas in the central ~250 pc of the Galaxy. We present SCOUSE (Semi-automated multi-COmponent Universal Spectral-line fitting Engine), a line fitting algorithm designed to analyse large volumes of spectral-line data efficiently and systematically. Unlike techniques which do not account for complex line profiles, SCOUSE accurately describes the {l, b, v_LSR} distribution of CMZ gas, which is asymmetric about Sgr A* in both position and velocity. Velocity dispersions range from 2.6 km/s28. The gas is distributed throughout several "streams", with projected lengths ~100-250 pc. We link the streams to individual clouds and sub-regions, including Sgr C, the 20 and 50 km/s clouds, the dust ridge, and Sgr B2. Shell-like emission features can be explained by the projection of independent molecular clouds in Sgr C and the newly identified conical profile of Sgr B2 in {l ,b, v_LSR} space. These features have previously invoked supernova-driven shells and cloud-cloud collisions as explanations. We instead caution against structure identification in velocity-integrated emission maps. Three geometries describing the 3-D structure of the CMZ are investigated: i) two spiral arms; ii) a closed elliptical orbit; iii) an open stream. While two spiral arms and an open stream qualitatively reproduce the gas distribution, the most recent parameterisation of the closed elliptical orbit does not. Finally, we discuss how proper motion measurements of masers can distinguish between these geometries, and suggest that this effort should be focused on the 20 km/s and 50 km/s clouds and Sgr C

Large-scale genome-wide association studies and meta-analyses of longitudinal change in adult lung function.

BACKGROUND: Genome-wide association studies (GWAS) have identified numerous loci influencing cross-sectional lung function, but less is known about genes influencing longitudinal change in lung function. METHODS: We performed GWAS of the rate of change in forced expiratory volume in the first second (FEV1) in 14 longitudinal, population-based cohort studies comprising 27,249 adults of European ancestry using linear mixed effects model and combined cohort-specific results using fixed effect meta-analysis to identify novel genetic loci associated with longitudinal change in lung function. Gene expression analyses were subsequently performed for identified genetic loci. As a secondary aim, we estimated the mean rate of decline in FEV1 by smoking pattern, irrespective of genotypes, across these 14 studies using meta-analysis. RESULTS: The overall meta-analysis produced suggestive evidence for association at the novel IL16/STARD5/TMC3 locus on chromosome 15 (P  =  5.71 × 10(-7)). In addition, meta-analysis using the five cohorts with ≥3 FEV1 measurements per participant identified the novel ME3 locus on chromosome 11 (P  =  2.18 × 10(-8)) at genome-wide significance. Neither locus was associated with FEV1 decline in two additional cohort studies. We confirmed gene expression of IL16, STARD5, and ME3 in multiple lung tissues. Publicly available microarray data confirmed differential expression of all three genes in lung samples from COPD patients compared with controls. Irrespective of genotypes, the combined estimate for FEV1 decline was 26.9, 29.2 and 35.7 mL/year in never, former, and persistent smokers, respectively. CONCLUSIONS: In this large-scale GWAS, we identified two novel genetic loci in association with the rate of change in FEV1 that harbor candidate genes with biologically plausible functional links to lung function