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.

p53 is required for radiation-induced apoptosis in mouse thymocytes

Abstract: The p53 tumour suppressor gene is the most widely mutated gene in human tumorigenesis. p53 encodes a transcriptional activator whose targets may include genes that regulate genomic stability, the cellular response to DNA damage, and cell-cycle progression. Introduction of wild-type p53 into cell lines that have lost endogenous p53 function can cause growth arrest or induce a process of cell death known as apoptosis. During normal development, self-reactive thymocytes undergo negative selection by apoptosis, which can also be induced in immature thymocytes by other stimuli, including exposure to glucocorticoids and ionizing radiation. Although normal negative selection involves signalling through the T-cell receptor, the induction of apoptosis by other stimuli is poorly understood. We have investigated the requirement for p53 during apoptosis in mouse thymocytes. We report here that immature thymocytes lacking p53 die normally when exposed to compounds that may mimic T-cell receptor engagement and to glucocorticoids but are resistant to the lethal effects of ionizing radiation. These results demonstrate that p53 is required for radiation-induced cell death in the thymus but is not necessary for all forms of apoptosis.

The theory of planned behaviour: reactions and reflections

Abstract: The seven articles in this issue, and the accompanying meta-analysis in Health Psychology Review [McEachan, R.R.C., Conner, M., Taylor, N., & Lawton, R.J. (2011). Prospective prediction of health-related behaviors with the theory of planned behavior: A meta-analysis. Health Psychology Review, 5, 97–144], illustrate the wide application of the theory of planned behaviour [Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179–211] in the health domain. In this editorial, Ajzen reflects on some of the issues raised by the different authors. Among the topics addressed are the nature of intentions and the limits of predictive validity; rationality, affect and emotions; past behaviour and habit; the prototype/willingness model; and the role of such background factors as the big five personality traits and social comparison tendency.

Corporate Social Responsibility and Firm Financial Performance

Abstract: Using Fortune magazine's ratings of corporate reputations, we analyzed the relationships between perceptions of firms’ corporate social responsibility and measures of their financial performance. Results show that a firm's prior performance, assessed by both stock-market returns and accounting-based measures, is more closely related to corporate social responsibility than is subsequent performance. Results also show that measures of risk are more closely associated with social responsibility than previous studies have suggested.

A language modeling approach to information retrieval

Abstract: In today's world, there is no shortage of information. However, for a specific information need, only a small subset of all of the available information will be useful. The field of information retrieval (IR) is the study of methods to provide users with that small subset of information relevant to their needs and to do so in a timely fashion. Information sources can take many forms, but this thesis will focus on text based information systems and investigate problems germane to the retrieval of written natural language documents. Central to these problems is the notion of "topic." In other words, what are documents about? However, topics depend on the semantics of documents and retrieval systems are not endowed with knowledge of the semantics of natural language. The approach taken in this thesis will be to make use of probabilistic language models to investigate text based information retrieval and related problems. One such problem is the prediction of topic shifts in text, the topic segmentation problem. It will be shown that probabilistic methods can be used to predict topic changes in the context of the task of new event detection. Two complementary sets of features are studied individually and then combined into a single language model. The language modeling approach allows this problem to be approached in a principled way without complex semantic modeling. Next, the problem of document retrieval in response to a user query will be investigated. Models of document indexing and document retrieval have been extensively studied over the past three decades. The integration of these two classes of models has been the goal of several researchers but it is a very difficult problem. Much of the reason for this is that the indexing component requires inferences as to the semantics of documents. Instead, an approach to retrieval based on probabilistic language modeling will be presented. Models are estimated for each document individually. The approach to modeling is non-parametric and integrates the entire retrieval process into a single model. One advantage of this approach is that collection statistics, which are used heuristically for the assignment of concept probabilities in other probabilistic models, are used directly in the estimation of language model probabilities in this approach. The language modeling approach has been implemented and tested empirically and performs very well on standard test collections and query sets. In order to improve retrieval effectiveness, IR systems use additional techniques such as relevance feedback, unsupervised query expansion and structured queries. These and other techniques are discussed in terms of the language modeling approach and empirical results are given for several of the techniques developed. These results provide further proof of concept for the use of language models for retrieval tasks.

Alzheimer-type neuropathology in transgenic mice overexpressing V717F beta-amyloid precursor protein.

Abstract: Alzheimer's disease (AD) is the most common cause of progressive intellectual failure in aged humans. AD brains contain numerous amyloid plaques surrounded by dystrophic neurites, and show profound synaptic loss, neurofibrillary tangle formation and gliosis. The amyloid plaques are composed of amyloid beta-peptide (A beta), a 40-42-amino-acid fragment of the beta-amyloid precursor protein (APP). A primary pathogenic role for APP/A beta is suggested by missense mutations in APP that are tightly linked to autosomal dominant forms of AD. A major obstacle to elucidating and treating AD has been the lack of an animal model. Animals transgenic for APP have previously failed to show extensive AD-type neuropathology, but we now report the production of transgenic mice that express high levels of human mutant APP (with valine at residue 717 substituted by phenylalanine) and which progressively develop many of the pathological hallmarks of AD, including numerous extracellular thioflavin S-positive A beta deposits, neuritic plaques, synaptic loss, astrocytosis and microgliosis. These mice support a primary role for APP/A beta in the genesis of AD and could provide a preclinical model for testing therapeutic drugs.