University of Massachusetts Amherst

About: University of Massachusetts Amherst is a education organization based out in Amherst Center, Massachusetts, United States. It is known for research contribution in the topics: Population & Galaxy. The organization has 37274 authors who have published 83965 publications receiving 3834996 citations. The organization is also known as: UMass Amherst & Massachusetts State College.

Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes

Abstract: Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.

The Evolution of the Galaxy Rest-Frame Ultraviolet Luminosity Function Over the First Two Billion Years

Abstract: We present a robust measurement and analysis of the rest-frame ultraviolet (UV) luminosity function at z = 4 to 8. We use deep Hubble Space Telescope imaging over the CANDELS/GOODS fields, the Hubble Ultra Deep Field and the Hubble Frontier Field deep parallel observations near the Abell 2744 and MACS J0416.1- 2403 clusters. The combination of these surveys provides an effective volume of 0.6-1.2 ×10(exp 6) Mpc(exp 3) over this epoch, allowing us to perform a robust search for bright (M(sub UV) less than −21) and faint (M(sub UV) = −18) galaxies. We select galaxies using a well-tested photometric redshift technique with careful screening of contaminants, finding a sample of 7446 galaxies at 3.5 less than z less than 8.5, with more than 1000 galaxies at z of approximately 6 - 8. We measure both a stepwise luminosity function for galaxies in our redshift samples, as well as a Schechter function, using a Markov Chain Monte Carlo analysis to measure robust uncertainties. At the faint end our UV luminosity functions agree with previous studies, yet we find a higher abundance of UV-bright galaxies at z of greater than or equal to 6. Our bestfit value of the characteristic magnitude M* is consistent with −21 at z of greater than or equal to 5, different than that inferred based on previous trends at lower redshift. At z = 8, a single power-law provides an equally good fit to the UV luminosity function, while at z = 6 and 7, an exponential cutoff at the bright-end is moderately preferred. We compare our luminosity functions to semi-analytical models, and find that the lack of evolution in M* is consistent with models where the impact of dust attenuation on the bright-end of the luminosity function decreases at higher redshift, though a decreasing impact of feedback may also be possible. We measure the evolution of the cosmic star-formation rate (SFR) density by integrating our observed luminosity functions to M(sub UV) = −17, correcting for dust attenuation, and find that the SFR density declines proportionally to (1 + z)((exp −4.3)(+/-)(0.5)) at z greater than 4, consistent with observations at z greater than or equal to 9. Our observed luminosity functions are consistent with a reionization history that starts at redshift of approximately greater than 10, completes at z greater than 6, and reaches a midpoint (x(sub HII) = 0.5) at 6.7 less than z less than 9.4. Finally, using a constant cumulative number density selection and an empirically derived rising star-formation history, our observations predict that the abundance of bright z = 9 galaxies is likely higher than previous constraints, though consistent with recent estimates of bright z similar to 10 galaxies.

Evaluation of an inference network-based retrieval model

Abstract: Network representations have been used in information retrieval since at least the early 1960’s. Networks have been used to support diverse retrieval functions, including browsing [38], document clustering [7], spreading activation search [4], support for multiple search strategies [11], and representation of user knowledge [27] or document content [40]. Recent work suggests that significant improvements in retrieval performance will require techniques that, in some sense “understand” the content of documents and queries [9, 43] and can be used to infer probable relationships between documents and queries. In this view, information retrieval is an inference or evidential reasoning process in which we estimate the probability that a user’s information need, expressed as one or more queries, is met given a document as “evidence.” Network representations show promise as mechanisms for inferring these kinds of relationships [4, 12].

Infliximab improves signs and symptoms of psoriatic arthritis: results of the IMPACT 2 trial

Abstract: Objectives: To evaluate further in a phase III, double blind trial the efficacy of infliximab in patients with active psoriatic arthritis (PsA), as observed in the smaller IMPACT trial. Methods: 200 patients with active PsA unresponsive to previous treatment were randomised to infusions of infliximab 5 mg/kg or placebo at weeks 0, 2, 6, 14, and 22. Patients with inadequate response entered early escape at week 16. The primary measure of clinical response was ACR20. Other measures included Psoriatic Arthritis Response Criteria (PsARC), Psoriasis Area and Severity Index (PASI), and dactylitis and enthesopathy assessments. Results: At week 14, 58% of patients receiving infliximab and 11% of those receiving placebo achieved an ACR20 response and 77% of infliximab patients and 27% of placebo patients achieved PsARC (both p<0.001). Among the 85% of patients with at least 3% body surface area psoriasis involvement at baseline, 53/83 (64%) patients receiving infliximab had at least 75% improvement in PASI compared with 2/87 (2%) patients receiving placebo at week 14 (p<0.001). These therapeutic effects were maintained through the last evaluation (week 24). Fewer infliximab patients than placebo patients had dactylitis at week 14 (18% v 30%; p = 0.025) and week 24 (12% v 34%; p<0.001). Fewer infliximab patients (22%) than placebo patients (34%) had active enthesopathy at week 14 (p = 0.016); corresponding figures at week 24 were 20% and 37% (p = 0.002). Infliximab was generally well tolerated, with a similar incidence of adverse events in each group. Conclusions: Infliximab 5 mg/kg through 24 weeks significantly improved active PsA, including dactylitis and enthesopathy, and associated psoriasis.

Polymer‐Mediated Nanoparticle Assembly: Structural Control and Applications

Abstract: Nanoparticle-polymer composites are diverse and versatile functional materials, with applications ranging from electronic device fabrication to catalysis. This review focuses on the use of chemical design to control the structural attributes of polymer-mediated assembly of nanoparticles. We will illustrate the use of designed particles and polymers to create nanocomposites featuring interesting and pragmatic structures and properties. We will also describe applications of these engineered materials.