Does land use and landscape contribute to self-harm? A sustainability cities framework

Self-harm has become one of the leading causes of mortality in developed countries. The overall rate for suicide in Canada is 11.3 per 100,000 according to Statistics Canada in 2015. Between 2000 and 2007 the lowest rates of suicide in Canada were in Ontario, one of the most urbanized regions in Canada. However, the interaction between land use, landscape and self-harm has not been significantly studied for urban cores. It is thus of relevance to understand the impacts of land-use and landscape on suicidal behavior. This paper takes a spatial analytical approach to assess the occurrence of self-harm along one of the densest urban cores in the country: Toronto. Individual self-harm data was gathered by the National Ambulatory Care System (NACRS) and geocoded into census tract divisions. Toronto’s urban landscape is quantified at spatial level through the calculation of its land use at di erent levels: (i) land use type, (ii) sprawl metrics relating to (a) dispersion and (b) sprawl/mix incidence; (iii) fragmentation metrics of (a) urban fragmentation and (b) density and (iv) demographics of (a) income and (b) age. A stepwise regression is built to understand the most influential factors leading to self-harm from this selection generating an explanatory model.This research was supported by the Canadian Institutes of Health Research Strategic Team Grant in Applied Injury Research # TIR-103946 and the Ontario Neurotrauma Foundation grantinfo:eu-repo/semantics/publishedVersio

Extent of Fermi-surface reconstruction in the high-temperature superconductor HgBa2_2CuO4+δ_{4+\delta}

High magnetic fields have revealed a surprisingly small Fermi-surface in underdoped cuprates, possibly resulting from Fermi-surface reconstruction due to an order parameter that breaks translational symmetry of the crystal lattice. A crucial issue concerns the doping extent of this state and its relationship to the principal pseudogap and superconducting phases. We employ pulsed magnetic field measurements on the cuprate HgBa$_2$CuO$_{4+\delta}$ to identify signatures of Fermi surface reconstruction from a sign change of the Hall effect and a peak in the temperature-dependent planar resistivity. We trace the termination of Fermi-surface reconstruction to two hole concentrations where the superconducting upper critical fields are found to be enhanced. One of these points is associated with the pseudogap end-point near optimal doping. These results connect the Fermi-surface reconstruction to both superconductivity and the pseudogap phenomena.Comment: 5 pages. 3 Figures. PNAS (2020

Distinct amino acid compositional requirements for formation and maintenance of the [PSI+] prion in yeast

Multiple yeast prions have been identified that result from the structural conversion of proteins into a self-propagating amyloid form. Amyloid-based prion activity in yeast requires a series of discrete steps. First, the prion protein must form an amyloid nucleus that can recruit and structurally convert additional soluble proteins. Subsequently, maintenance of the prion during cell division requires fragmentation of these aggregates to create new heritable propagons. For the Saccharomyces cerevisiae prion protein Sup35, these different activities are encoded by different regions of the Sup35 prion domain. An N-terminal glutamine/asparagine-rich nucleation domain is required for nucleation and fiber growth, while an adjacent oligopeptide repeat domain is largely dispensable for prion nucleation and fiber growth but is required for chaperone-dependent prion maintenance. Although prion activity of glutamine/asparagine-rich proteins is predominantly determined by amino acid composition, the nucleation and oligopeptide repeat domains of Sup35 have distinct compositional requirements. Here, we quantitatively define these compositional requirements in vivo. We show that aromatic residues strongly promote both prion formation and chaperone-dependent prion maintenance. In contrast, nonaromatic hydrophobic residues strongly promote prion formation but inhibit prion propagation. These results provide insight into why some aggregation-prone proteins are unable to propagate as prions

Amino acid composition predicts prion activity

Many prion-forming proteins contain glutamine/asparagine (Q/N) rich domains, and there are conflicting opinions as to the role of primary sequence in their conversion to the prion form: is this phenomenon driven primarily by amino acid composition, or, as a recent computational analysis suggested, dependent on the presence of short sequence elements with high amyloid-forming potential. The argument for the importance of short sequence elements hinged on the relatively-high accuracy obtained using a method that utilizes a collection of length-six sequence elements with known amyloid-forming potential. We weigh in on this question and demonstrate that when those sequence elements are permuted, even higher accuracy is obtained; we also propose a novel multiple-instance machine learning method that uses sequence composition alone, and achieves better accuracy than all existing prion prediction approaches. While we expect there to be elements of primary sequence that affect the process, our experiments suggest that sequence composition alone is sufficient for predicting protein sequences that are likely to form prions. A web-server for the proposed method is available at http://faculty.pieas.edu.pk/fayyaz/prank.html, and the code for reproducing our experiments is available at http://doi.org/10.5281/zenodo.167136

Amino acid composition predicts prion activity

Many prion-forming proteins contain glutamine/asparagine (Q/N) rich domains, and there are conflicting opinions as to the role of primary sequence in their conversion to the prion form: is this phenomenon driven primarily by amino acid composition, or, as a recent computational analysis suggested, dependent on the presence of short sequence elements with high amyloid-forming potential. The argument for the importance of short sequence elements hinged on the relatively-high accuracy obtained using a method that utilizes a collection of length-six sequence elements with known amyloid-forming potential. We weigh in on this question and demonstrate that when those sequence elements are permuted, even higher accuracy is obtained; we also propose a novel multiple-instance machine learning method that uses sequence composition alone, and achieves better accuracy than all existing prion prediction approaches. While we expect there to be elements of primary sequence that affect the process, our experiments suggest that sequence composition alone is sufficient for predicting protein sequences that are likely to form prions. A web-server for the proposed method is available at http://faculty.pieas.edu.pk/fayyaz/prank.html, and the code for reproducing our experiments is available at http://doi.org/10.5281/zenodo.167136

Sloan Digital Sky Survey III Photometric Quasar Clustering: Probing the Initial Conditions of the Universe using the Largest Volume

The Sloan Digital Sky Survey has surveyed 14,555 square degrees of the sky, and delivered over a trillion pixels of imaging data. We present the large-scale clustering of 1.6 million quasars between z = 0.5 and z = 2.5 that have been classified from this imaging, representing the highest density of quasars ever studied for clustering measurements. This data set spans ~11,000 square degrees and probes a volume of 80(Gpc/h)^3. In principle, such a large volume and medium density of tracers should facilitate high-precision cosmological constraints. We measure the angular clustering of photometrically classified quasars using an optimal quadratic estimator in four redshift slices with an accuracy of ~25% over a bin width of l ~10 - 15 on scales corresponding to matter-radiation equality and larger (l ~ 2 - 30). Observational systematics can strongly bias clustering measurements on large scales, which can mimic cosmologically relevant signals such as deviations from Gaussianity in the spectrum of primordial perturbations. We account for systematics by employing a new method recently proposed by Agarwal et al. (2014) to the clustering of photometrically classified quasars. We carefully apply our methodology to mitigate known observational systematics and further remove angular bins that are contaminated by unknown systematics. Combining quasar data with the photometric luminous red galaxy (LRG) sample of Ross et al. (2011) and Ho et al. (2012), and marginalizing over all bias and shot noise-like parameters, we obtain a constraint on local primordial non-Gaussianity of fNL = -113+/-154 (1\sigma error). [Abridged]Comment: 35 pages, 15 figure

A Bibliometric Analysis of an International Research Ethics Trainee Program

We used bibliometric analysis to evaluate the citations associated with publications by trainees in the Fogarty International Center’s International Research Ethics Education and Curriculum Development program. Papers published between 2004 and 2008 were identified for analysis. The outcome measures were total citations, h-index, and i-10. A total of 328 manuscripts were identified, with a yearly average of 66 publications and 363 citations. The median number of citations per paper is 3 (IQR Q1–Q3:6). 12.6% (n = 53) of papers were cited over 10 times and the h-index is 22, indicating that 22 papers had been cited at least 22 times. The data indicate that trainees have been productive and contributed to the scholarly literature. Future studies to benchmark this performance with other bioethics education programs are required to make interpretation of citation analysis more meaningful

Cyclooxygenase-2 inhibition decreases primary and metastatic tumor burden in a murine model of orthotopic lung adenocarcinoma

AbstractObjectiveTo assess cyclooxygenase-2 inhibition on primary tumor and mediastinal metastases in a murine model of orthotopic lung adenocarcinoma.MethodsHuman lung adenocarcinoma cells (CRL5908, female nonsmoker with cyclooxygenase-2 expression by Western blot) were implanted under direct visualization through the parietal pleura in the upper lobe of the left lung (2 × 106 cells/animal) of SCID mice. Mice were randomly assigned to 2 groups, either untreated (n = 62) or celecoxib-treated (n = 60). Celecoxib, a selective cyclooxygenase-2 antagonist, was solubilized in the animals' drink (25 mg/kg per day). Mice were arbitrarily killed at 1, 2, 3, and 4 weeks. A blinded observer assessed primary tumor volume and metastatic disease grossly and histologically.ResultsGross metastatic lymph nodes were present at 3 weeks in none of 15 (0%) treated and 12 of 15 (80.0%) untreated animals (P < .0001). Mean primary tumor volumes at 3 weeks for treated mice were 7.9 ± 10.0 mm3 and for untreated mice were 533.1 ± 453.6 mm3 (mean ± SD, P < .0001). Gross metastatic lymph nodes were present at 4 weeks in 3 of 15 (20%) treated and 17 of 17 (100%) untreated animals (P < .0001). Mean primary tumor volumes at 4 weeks for treated mice were 37.1 ± 46.2 mm3 and for untreated mice were 809.6 ± 1226.4 mm3 (mean ± SD, P < .0001). Mean blood levels of celecoxib in treated mice were 236.8 ± 34.2 ng/mL (mean ± SD).ConclusionsCyclooxygenase-2 inhibition results in decreased primary and metastatic tumor burden in a murine model using human lung adenocarcinoma. Cyclooxygenase-2 inhibition has the potential to decrease tumor progression and metastases in patients with lung adenocarcinoma

The complex relationship between pediatric cardiac surgical case volumes and mortality rates in a national clinical database

ObjectiveWe sought to determine the association between pediatric cardiac surgical volume and mortality using sophisticated case-mix adjustment and a national clinical database.MethodsPatients 18 years of age or less who had a cardiac operation between 2002 and 2006 were identified in the Society of Thoracic Surgeons Congenital Heart Surgery Database (32,413 patients from 48 programs). Programs were grouped by yearly pediatric cardiac surgical volume (small, <150; medium, 150–249; large, 250–349; and very large, ≥350 cases per year). Logistic regression was used to adjust mortality rates for volume, surgical case mix (Aristotle Basic Complexity and Risk Adjustment for Congenital Heart Surgery, Version 1 categories), patient risk factors, and year of operation.ResultsWith adjustment for patient-level risk factors and surgical case mix, there was an inverse relationship between overall surgical volume as a continuous variable and mortality (P = .002). When the data were displayed graphically, there appeared to be an inflection point between 200 and 300 cases per year. When volume was analyzed as a categorical variable, the relationship was most apparent for difficult operations (Aristotle technical difficulty component score, >3.0), for which mortality decreased from 14.8% (60/406) at small programs to 8.4% (157/1858) at very large programs (P = .02). The same was true for the subgroup of patients who underwent Norwood procedures (36.5% [23/63] vs 16.9% [81/479], P < .0001). After risk adjustment, all groups performed similarly for low-difficulty operations. Conversely, for difficult procedures, small programs performed significantly worse. For Norwood procedures, very large programs outperformed all other groups.ConclusionThere was an inverse association between pediatric cardiac surgical volume and mortality that became increasingly important as case complexity increased. Although volume was not associated with mortality for low-complexity cases, lower-volume programs underperformed larger programs as case complexity increased