Synapse efficiency diverges due to synaptic pruning following over-growth

In the development of the brain, it is known that synapses are pruned following over-growth. This pruning following over-growth seems to be a universal phenomenon that occurs in almost all areas -- visual cortex, motor area, association area, and so on. It has been shown numerically that the synapse efficiency is increased by systematic deletion. We discuss the synapse efficiency to evaluate the effect of pruning following over-growth, and analytically show that the synapse efficiency diverges as O(log c) at the limit where connecting rate c is extremely small. Under a fixed synapse number criterion, the optimal connecting rate, which maximize memory performance, exists.Comment: 15 pages, 16 figure

Community Management of Endemic Scabies in Remote Aboriginal Communities of Northern Australia: Low Treatment Uptake and High Ongoing Acquisition

Like many impoverished areas around the world, Aboriginal communities in Australia experience an unacceptably high burden of scabies, skin infections, and secondary complications. Young children are most at risk. Our study investigated scabies in a remote setting with very high rates of skin disease, a high level of household overcrowding, and limited infrastructure for sanitation and preventive health measures. We assessed uptake of scabies treatment and scabies acquisition following provision of treatment by a community-based skin program. In a household where scabies was present, we found that treatment with topical permethrin cream of all close contacts can significantly reduce a susceptible individual's risk of infection. Our findings also demonstrate the challenges of achieving a high level of treatment participation, with limited permethrin use observed among household contacts. This suggests an urgent need for a more practical treatment option. International efforts to reduce childhood morbidity and mortality have demonstrated the efficacy of numerous child health interventions but have also highlighted the deficits in their delivery and implementation. Experiences like this, where the effectiveness of a coordinated local program delivering an efficacious intervention is hampered by poor treatment uptake and ongoing transmission, are an important and timely message for researchers, program managers, and policy-makers

A catalogue of structural and morphological measurements for DES Y1

We present a structural and morphological catalogue for 45 million objects selected from the first year data of the Dark Energy Survey (DES). Single Sersic fits and non-parametric ´ measurements are produced for g, r, and i filters. The parameters from the best-fitting Sersic ´ model (total magnitude, half-light radius, Sersic index, axis ratio, and position angle) are mea- ´ sured with GALFIT; the non-parametric coefficients (concentration, asymmetry, clumpiness, Gini, M20) are provided using the Zurich Estimator of Structural Types (ZEST+). To study the statistical uncertainties, we consider a sample of state-of-the-art image simulations with a realistic distribution in the input parameter space and then process and analyse them as we do with real data: this enables us to quantify the observational biases due to PSF blurring and magnitude effects and correct the measurements as a function of magnitude, galaxy size, Sersic ´ index (concentration for the analysis of the non-parametric measurements) and ellipticity. We present the largest structural catalogue to date: we find that accurate and complete measurements for all the structural parameters are typically obtained for galaxies with SEXTRACTOR MAG AUTO I ≤ 21. Indeed, the parameters in the filters i and r can be overall well recovered up to MAG AUTO ≤ 21.5, corresponding to a fitting completeness of ∼90 per cent below this threshold, for a total of 25 million galaxies. The combination of parametric and non-parametric structural measurements makes this catalogue an important instrument to explore and understand how galaxies form and evolve. The catalogue described in this paper will be publicly released alongside the DES collaboration Y1 cosmology data products at the following URL: https://des.ncsa.illinois.edu/releases

Candidate massive galaxies at z similar to 4 in the Dark Energy Survey

Using stellar population models, we predicted that the Dark Energy Survey (DES) – due to its special combination of area (5000 deg2) and depth (i = 24.3) – would be in the position to detect massive (1011 M) galaxies at z ∼ 4. We confront those theoretical calculations with the first ∼150 deg2 of DES data reaching nominal depth. From a catalogue containing ∼5 million sources, ∼26 000 were found to have observed-frame g − r versus r − i colours within the locus predicted for z ∼ 4 massive galaxies. We further removed contamination by stars and artefacts, obtaining 606 galaxies lining up by the model selection box. We obtained their photometric redshifts and physical properties by fitting model templates spanning a wide range of star formation histories, reddening and redshift. Key to constrain the models is the addition, to the optical DES bands g, r, i, z, and Y, of near-IR J, H, Ks data from the Vista Hemisphere Survey. We further applied several quality cuts to the fitting results, including goodness of fit and a unimodal redshift probability distribution. We finally select 233 candidates whose photometric redshift probability distribution function peaks around z ∼ 4, have high stellar masses [log (M∗/M) ∼ 11.7 for a Salpeter IMF] and ages around 0.1 Gyr, i.e. formation redshift around 5. These properties match those of the progenitors of the most massive galaxies in the local Universe. This is an ideal sample for spectroscopic followup to select the fraction of galaxies which are truly at high redshift. These initial results and those at the survey completion, which we shall push to higher redshifts, will set unprecedented constraints on galaxy formation, evolution, and the re-ionization epoch

Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer

Abstract: Stromal tumor-infiltrating lymphocytes (sTILs) are important prognostic and predictive biomarkers in triple-negative (TNBC) and HER2-positive breast cancer. Incorporating sTILs into clinical practice necessitates reproducible assessment. Previously developed standardized scoring guidelines have been widely embraced by the clinical and research communities. We evaluated sources of variability in sTIL assessment by pathologists in three previous sTIL ring studies. We identify common challenges and evaluate impact of discrepancies on outcome estimates in early TNBC using a newly-developed prognostic tool. Discordant sTIL assessment is driven by heterogeneity in lymphocyte distribution. Additional factors include: technical slide-related issues; scoring outside the tumor boundary; tumors with minimal assessable stroma; including lymphocytes associated with other structures; and including other inflammatory cells. Small variations in sTIL assessment modestly alter risk estimation in early TNBC but have the potential to affect treatment selection if cutpoints are employed. Scoring and averaging multiple areas, as well as use of reference images, improve consistency of sTIL evaluation. Moreover, to assist in avoiding the pitfalls identified in this analysis, we developed an educational resource available at www.tilsinbreastcancer.org/pitfalls

Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group

Funder: U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)Funder: National Center for Research Resources under award number 1 C06 RR12463-01, VA Merit Review Award IBX004121A from the United States Department of Veterans Affairs Biomedical Laboratory Research and Development Service, the DOD Prostate Cancer Idea Development Award (W81XWH-15-1-0558), the DOD Lung Cancer Investigator-Initiated Translational Research Award (W81XWH-18-1-0440), the DOD Peer Reviewed Cancer Research Program (W81XWH-16-1-0329), the Ohio Third Frontier Technology Validation Fund, the Wallace H. Coulter Foundation Program in the Department of Biomedical Engineering and the Clinical and Translational Science Award Program (CTSA) at Case Western Reserve University.Funder: Susan G Komen Foundation (CCR CCR18547966) and a Young Investigator Grant from the Breast Cancer Alliance.Funder: The Canadian Cancer SocietyFunder: Breast Cancer Research Foundation (BCRF), Grant No. 17-194Abstract: Assessment of tumor-infiltrating lymphocytes (TILs) is increasingly recognized as an integral part of the prognostic workflow in triple-negative (TNBC) and HER2-positive breast cancer, as well as many other solid tumors. This recognition has come about thanks to standardized visual reporting guidelines, which helped to reduce inter-reader variability. Now, there are ripe opportunities to employ computational methods that extract spatio-morphologic predictive features, enabling computer-aided diagnostics. We detail the benefits of computational TILs assessment, the readiness of TILs scoring for computational assessment, and outline considerations for overcoming key barriers to clinical translation in this arena. Specifically, we discuss: 1. ensuring computational workflows closely capture visual guidelines and standards; 2. challenges and thoughts standards for assessment of algorithms including training, preanalytical, analytical, and clinical validation; 3. perspectives on how to realize the potential of machine learning models and to overcome the perceptual and practical limits of visual scoring

Application of a risk-management framework for integration of stromal tumor-infiltrating lymphocytes in clinical trials

Funder: Breast Cancer Research Foundation (BCRF); doi: https://doi.org/10.13039/100001006Abstract: Stromal tumor-infiltrating lymphocytes (sTILs) are a potential predictive biomarker for immunotherapy response in metastatic triple-negative breast cancer (TNBC). To incorporate sTILs into clinical trials and diagnostics, reliable assessment is essential. In this review, we propose a new concept, namely the implementation of a risk-management framework that enables the use of sTILs as a stratification factor in clinical trials. We present the design of a biomarker risk-mitigation workflow that can be applied to any biomarker incorporation in clinical trials. We demonstrate the implementation of this concept using sTILs as an integral biomarker in a single-center phase II immunotherapy trial for metastatic TNBC (TONIC trial, NCT02499367), using this workflow to mitigate risks of suboptimal inclusion of sTILs in this specific trial. In this review, we demonstrate that a web-based scoring platform can mitigate potential risk factors when including sTILs in clinical trials, and we argue that this framework can be applied for any future biomarker-driven clinical trial setting

Measurement of the n_TOF beam profile with a micromegas detector

A Micromegas detector was used in the neutron Time-Of-Flight (n_TOF) facility at CERN to evaluate the spatial distribution of the neutron beam as a function of its kinetic energy. This was achieved over a large range of neutron energies by using two complementary processes: at low energy by capture of a neutron via the 6Li(n,[alpha])t reaction, and at high energy by elastic scattering of neutrons on gas nuclei (argon+isobutane or helium+isobutane). Data are compared to Monte Carlo simulations and an analytic function fitting the beam profile has been calculated with a sufficient precision to use in neutron capture experiments at the n_TOF facility.http://www.sciencedirect.com/science/article/B6TJM-4BRSWVV-3/1/01dd54d28c7a57560574f1adfbd8a2f