Is More Always Better for Verbs? Semantic Richness Effects and Verb Meaning.
Ontology highlight
ABSTRACT:
SUBMITTER: Sidhu DM
PROVIDER: S-EPMC4885847 | biostudies-other | 2016
REPOSITORIES: biostudies-other
Publications
Is More Always Better for Verbs? Semantic Richness Effects and Verb Meaning.
Sidhu David M DM Heard Alison A Pexman Penny M PM
Frontiers in psychology 20160531
We examined how several semantic richness variables contribute to verb meaning, across a number of tasks. Because verbs can vary in tense, and the manner in which tense is coded (i.e., regularity), we also examined how these factors moderated the effects of semantic richness. In Experiment 1 we found that age of acquisition (AoA), valence, arousal and embodiment predicted faster response times in LDT. In Experiment 2 we examined a particular semantic richness variable, verb embodiment, and found ...[more]
Similar Datasets
Project description:ContextProstate cancer (PCa) remains one of the most diagnosed malignancies in the world, correlating with regions where men consume more of a so-called Western-style diet. As such, there is much interest in understanding the role of lifestyle and diet on the incidence and progression of PCa.ObjectiveTo provide a summary of published literature with regard to dietary macro- and micronutrients and PCa incidence and progression.Evidence acquisitionA literature search was completed using the PubMed database for all studies published on diet and PCa in June 2012 or earlier. Primary literature and meta-analyses were given preference over other review articles when possible.Evidence synthesisThe literature was reviewed on seven dietary components: carbohydrates, protein, fat and cholesterol, vegetables, vitamins and minerals, and phytochemicals. Current literature linking these nutrients to PCa is limited at best, but trends in the published data suggest consumption of carbohydrates, saturated and ω-6 fats, and certain vitamin supplements may promote PCa risk and progression. Conversely, consumption of many plant phytochemicals and ω-3 fatty acids seem to slow the risk and progression of the disease. All other nutrients seem to have no effect or data are inconclusive. A brief summary about the clinical implications of dietary interventions with respect to PCa prevention, treatment, and survivorship is provided.ConclusionsDue to the number and heterogeneity of published studies investigating diet and PCa, it is difficult to determine what nutrients make up the perfect diet for the primary and secondary prevention of PCa. Because diets are made of multiple macro- and micronutrients, further prospective studies are warranted, particularly those investigating the relationship between whole foods instead of a single nutritional component.
| S-EPMC3597758 | biostudies-literature
Project description:Background: Fidelity in simulation is an important design feature. Although it is typically seen as bipolar (i.e., "high" or "low"), fidelity is actually multidimensional. There are concerns that "low fidelity" might impede the immersion of learners during simulation training. "Locally built models" are characterized by decreased cost and reduced "structural" fidelity (how the simulator looks) while satisfying "functional" fidelity (what the simulator does). Objective: To 1) describe the use of a locally built chest tube model in building a mastery-based simulation curriculum and 2) describe evaluation of the model from learners in different stages and contexts. Methods: The model was built on the basis of key functional features of the assigned training task. A curriculum that combined progressive difficulty and opportunities for deliberate practice and mastery was developed. An analysis of the learner's survey responses was performed using SAS studio (SAS Software). Results: We describe the process of creating the chest tube model and a curriculum in which the model is used for increasing levels of difficulty to reach skill mastery. Learners at different stages and in different contexts, such as practicing physicians and trainees from developed and developing countries, evaluated the model similarly. We provide validity evidence for the content, response process, and relationship with other variables when using the model in the assessment of chest tube insertion skills. Conclusion: As demonstrated in our chest tube critical care medicine curriculum, the locally built models are simple to build and feasible to use. Contrary to current thinking that low-fidelity models might impede immersion in simulation training for experienced learners, the survey results show that different learners provide very similar evaluations after practicing with the model.
| S-EPMC8043267 | biostudies-literature
Project description:Animal-associated microbes are highly variable, contributing to a diverse set of symbiont-mediated phenotypes. Given that host and symbiont genotypes, and their interactions, can impact symbiont-based phenotypes across environments, there is potential for extensive variation in fitness outcomes. Pea aphids, Acyrthosiphon pisum, host a diverse assemblage of heritable facultative symbionts (HFS) with characterized roles in host defense. Protective phenotypes have been largely studied as single infections, but pea aphids often carry multiple HFS species, and particular combinations may be enriched or depleted compared to expectations based on chance. Here, we examined the consequences of single infection versus coinfection with two common HFS exhibiting variable enrichment, the antiparasitoid Hamiltonella defensa and the antipathogen Regiella insecticola, across three host genotypes and environments. As expected, single infections with either H. defensa or R. insecticola raised defenses against their respective targets. Single infections with protective H. defensa lowered aphid fitness in the absence of enemy challenge, while R. insecticola was comparatively benign. However, as a coinfection, R. insecticola ameliorated H. defensa infection costs. Coinfected aphids continued to receive antiparasitoid protection from H. defensa, but protection was weakened by R. insecticola in two clones. Notably, H. defensa eliminated survival benefits conferred after pathogen exposure by coinfecting R. insecticola Since pathogen sporulation was suppressed by R. insecticola in coinfected aphids, the poor performance likely stemmed from H. defensa-imposed costs rather than weakened defenses. Our results reveal a complex set of coinfection outcomes which may partially explain natural infection patterns and suggest that symbiont-based phenotypes may not be easily predicted based solely on infection status.IMPORTANCE The hyperdiverse arthropods often harbor maternally transmitted bacteria that protect against natural enemies. In many species, low-diversity communities of heritable symbionts are common, providing opportunities for cooperation and conflict among symbionts, which can impact the defensive services rendered. Using the pea aphid, a model for defensive symbiosis, we show that coinfections with two common defensive symbionts, the antipathogen Regiella and the antiparasite Hamiltonella, produce outcomes that are highly variable compared to single infections, which consistently protect against designated enemies. Compared to single infections, coinfections often reduced defensive services during enemy challenge yet improved aphid fitness in the absence of enemies. Thus, infection with multiple symbionts does not necessarily create generalist aphids with "Swiss army knife" defenses against numerous enemies. Instead, particular combinations of symbionts may be favored for a variety of reasons, including their abilities to lessen the costs of other defensive symbionts when enemies are not present.
| S-EPMC7028961 | biostudies-literature
Project description:Metaproteomics is a powerful tool to characterize the structure of microbial communities and the physiology, metabolism and interactions of the species in these communities. Metaproteomics seeks to identify and quantify proteins from microbial communities on a large scale using gel electrophoresis or advanced liquid chromatography (LC) combined with high-resolution, accurate-mass mass spectrometry. To achieve extensive coverage of a metaproteome using shotgun proteomics, the sample complexity has to be decreased, for which a main approach is the on-line separation of peptides using one or more LC dimensions. The aim of this study is to test different 1D- and 2D-LC methods, also in comparison with the standard GeLC (pre-separation of proteins via gel electrophoresis) to find the best approach for analyzing metaproteome samples, using a mock community with 32 species in different abundances.
2019-02-12 | PXD008017 | Pride
Project description:Behavioral medicine is devoting increasing attention to the topic of participant engagement and its role in effective mobile health (mHealth) behavioral interventions. Several definitions of the term "engagement" have been proposed and discussed, especially in the context of digital health behavioral interventions. We consider that engagement refers to specific interaction and use patterns with the mHealth tools such as smartphone applications for intervention, whereas adherence refers to compliance with the directives of the health intervention, independent of the mHealth tools. Through our analysis of participant interaction and self-reported behavioral data in a college student health study with incentives, we demonstrate an example of measuring "effective engagement" as engagement behaviors that can be linked to the goals of the desired intervention. We demonstrate how clustering of one year of weekly health behavior self-reports generate four interpretable clusters related to participants' adherence to the desired health behaviors: healthy and steady, unhealthy and steady, decliners, and improvers. Based on the intervention goals of this study (health promotion and behavioral change), we show that not all app usage metrics are indicative of the desired outcomes that create effective engagement. As such, mHealth intervention design might consider eliciting not just more engagement or use overall, but rather, effective engagement defined by use patterns related to the desired behavioral outcome.
| S-EPMC7173729 | biostudies-literature
Project description:Current models of word-meaning access typically assume that lexical-semantic representations of ambiguous words (e.g., 'bark of the dog/tree') reach a relatively stable state in adulthood, with only the relative frequencies of meanings and immediate sentence context determining meaning preference. However, recent experience also affects interpretation: recently encountered word-meanings become more readily available (Rodd et al., 2016, 2013). Here, 3 experiments investigated how multiple encounters with word-meanings influence the subsequent interpretation of these ambiguous words. Participants heard ambiguous words contextually-disambiguated towards a particular meaning and, after a 20- to 30-min delay, interpretations of the words were tested in isolation. We replicate the finding that 1 encounter with an ambiguous word biased the later interpretation of this word towards the primed meaning for both subordinate (Experiments 1, 2, 3) and dominant meanings (Experiment 1). In addition, for the first time, we show cumulative effects of multiple repetitions of both the same and different meanings. The effect of a single subordinate exposure persisted after a subsequent encounter with the dominant meaning, compared to a dominant exposure alone (Experiment 1). Furthermore, 3 subordinate word-meaning repetitions provided an additional boost to priming compared to 1, although only when their presentation was spaced (Experiments 2, 3); massed repetitions provided no such boost (Experiments 1, 3). These findings indicate that comprehension is guided by the collective effect of multiple recently activated meanings and that the spacing of these activations is key to producing lasting updates to the lexical-semantic network. (PsycINFO Database Record
| S-EPMC6012009 | biostudies-literature
Project description:ObjectiveRoutine surveillance imaging for patients with resected non-small cell lung cancer is standard for the detection of disease recurrence and new primary lung cancers. However, surveillance intensity varies widely in practice, and its impact on long-term outcomes is poorly understood. We hypothesized that surveillance intensity was not associated with 5-year overall survival in patients with resected stage I non-small cell lung cancer. Additionally, we examined patterns of recurrence and new primary lung cancer development.MethodsCancer registrars at Commission on Cancer accredited institutions re-abstracted records to augment National Cancer Database patient data with information on comorbidities, imaging surveillance including intent and result of imaging, and recurrence (2007-2012). Pathologic stage I non-small cell lung cancer patients undergoing computed-tomography surveillance were placed into three imaging surveillance groups based on clinical practice guidelines: high intensity (3 month), moderate intensity (6 month), and low intensity (annual). Kaplan Meier analysis and Cox regression were used to compare overall survival among the three surveillance groups.Results2442 patients were identified, with 805 (33%), 1216 (50%), and 421 (17%) patients in the high, moderate, and low surveillance intensity groups, respectively. Five-year overall survival was similar between intensity groups (p=0.547). Surveillance on asymptomatic patients detected 210 (63%) cases of locoregional recurrences and 128 (72%) cases of new primary lung cancer.ConclusionsIn a unique national dataset of long-term outcomes for stage I non-small cell lung cancer, surveillance intensity was not associated with 5-year overall survival.
| S-EPMC6528489 | biostudies-literature
Project description: Not available
| S-EPMC8200736 | biostudies-literature
Project description:Metaproteomics, the study of protein expression in microbial communities, is a versatile tool for environmental microbiology. Achieving sufficiently high metaproteome coverage to obtain a comprehensive picture of the activities and interactions in microbial communities is one of the current challenges in metaproteomics. An essential step to maximize the number of identified proteins is peptide separation via liquid chromatography (LC) prior to mass spectrometry (MS). Thorough optimization and comparison of LC methods for metaproteomics are, however, currently lacking. Here, we present an extensive development and test of different 1D and 2D-LC approaches for metaproteomic peptide separations. We used fully characterized mock community samples to evaluate metaproteomic approaches with very long analytical columns (50 and 75 cm) and long gradients (up to 12 h). We assessed a total of over 20 different 1D and 2D-LC approaches in terms of number of protein groups and unique peptides identified, peptide spectrum matches (PSMs) generated, the ability to detect proteins of low-abundance species, the effect of technical replicate runs on protein identifications and method reproducibility. We show here that, while 1D-LC approaches are faster and easier to set up and lead to more identifications per minute of runtime, 2D-LC approaches allow for a higher overall number of identifications with up to >10,000 protein groups identified. We also compared the 1D and 2D-LC approaches to a standard GeLC workflow, in which proteins are pre-fractionated via gel electrophoresis. This method yielded results comparable to the 2D-LC approaches, however with the drawback of a much increased sample preparation time. Based on our results, we provide recommendations on how to choose the best LC approach for metaproteomics experiments, depending on the study aims.
| S-EPMC6383543 | biostudies-literature
Project description:The un-biased and reproducible interpretation of high-content gene sets from large-scale genomic experiments is crucial to the understanding of biological themes, validation of experimental data, and the eventual development of plans for future experimentation. To derive biomedically-relevant information from simple gene lists, a mathematical association to scientific language and meaningful words or sentences is crucial. Unfortunately, existing software for deriving meaningful and easily-appreciable scientific textual 'tokens' from large gene sets either rely on controlled vocabularies (Medical Subject Headings, Gene Ontology, BioCarta) or employ Boolean text searching and co-occurrence models that are incapable of detecting indirect links in the literature. As an improvement to existing web-based informatic tools, we have developed Textrous!, a web-based framework for the extraction of biomedical semantic meaning from a given input gene set of arbitrary length. Textrous! employs natural language processing techniques, including latent semantic indexing (LSI), sentence splitting, word tokenization, parts-of-speech tagging, and noun-phrase chunking, to mine MEDLINE abstracts, PubMed Central articles, articles from the Online Mendelian Inheritance in Man (OMIM), and Mammalian Phenotype annotation obtained from Jackson Laboratories. Textrous! has the ability to generate meaningful output data with even very small input datasets, using two different text extraction methodologies (collective and individual) for the selecting, ranking, clustering, and visualization of English words obtained from the user data. Textrous!, therefore, is able to facilitate the output of quantitatively significant and easily appreciable semantic words and phrases linked to both individual gene and batch genomic data.
| S-EPMC3639949 | biostudies-literature