Functional Neuroanatomy of Second Language Sentence Comprehension: An fMRI Study of Late Learners of American Sign Language

The neurobiology of sentence comprehension is well-studied but the properties and characteristics of sentence processing networks remain unclear and highly debated. Sign languages (i.e., visual-manual languages), like spoken languages, have complex grammatical structures and thus can provide valuable insights into the specificity and function of brain regions supporting sentence comprehension. The present study aims to characterize how these well-studied spoken language networks can adapt in adults to be responsive to sign language sentences, which contain combinatorial semantic and syntactic visual-spatial linguistic information. Twenty native English-speaking undergraduates who had completed introductory American Sign Language (ASL) courses viewed videos of the following conditions during fMRI acquisition: signed sentences, signed word lists, English sentences and English word lists. Overall our results indicate that native language (L1) sentence processing resources are responsive to ASL sentence structures in late L2 learners, but that certain L1 sentence processing regions respond differently to L2 ASL sentences, likely due to the nature of their contribution to language comprehension. For example, L1 sentence regions in Broca's area were significantly more responsive to L2 than L1 sentences, supporting the hypothesis that Broca's area contributes to sentence comprehension as a cognitive resource when increased processing is required. Anterior temporal L1 sentence regions were sensitive to L2 ASL sentence structure, but demonstrated no significant differences in activation to L1 than L2, suggesting its contribution to sentence processing is modality-independent. Posterior superior temporal L1 sentence regions also responded to ASL sentence structure but were more activated by English than ASL sentences. An exploratory analysis of the neural correlates of L2 ASL proficiency indicates that ASL proficiency is positively correlated with increased activations in response to ASL sentences in L1 sentence processing regions. Overall these results suggest that well-established fronto-temporal spoken language networks involved in sentence processing exhibit functional plasticity with late L2 ASL exposure, and thus are adaptable to syntactic structures widely different than those in an individual's native language. Our findings also provide valuable insights into the unique contributions of the inferior frontal and superior temporal regions that are frequently implicated in sentence comprehension but whose exact roles remain highly debated

On the Potts model partition function in an external field

We study the partition function of Potts model in an external (magnetic) field, and its connections with the zero-field Potts model partition function. Using a deletion-contraction formulation for the partition function Z for this model, we show that it can be expanded in terms of the zero-field partition function. We also show that Z can be written as a sum over the spanning trees, and the spanning forests, of a graph G. Our results extend to Z the well-known spanning tree expansion for the zero-field partition function that arises though its connections with the Tutte polynomial

Integration of Machine Learning and Mechanistic Models Accurately Predicts Variation in Cell Density of Glioblastoma Using Multiparametric MRI

Glioblastoma (GBM) is a heterogeneous and lethal brain cancer. These tumors are followed using magnetic resonance imaging (MRI), which is unable to precisely identify tumor cell invasion, impairing effective surgery and radiation planning. We present a novel hybrid model, based on multiparametric intensities, which combines machine learning (ML) with a mechanistic model of tumor growth to provide spatially resolved tumor cell density predictions. The ML component is an imaging data-driven graph-based semi-supervised learning model and we use the Proliferation-Invasion (PI) mechanistic tumor growth model. We thus refer to the hybrid model as the ML-PI model. The hybrid model was trained using 82 image-localized biopsies from 18 primary GBM patients with pre-operative MRI using a leave-one-patient-out cross validation framework. A Relief algorithm was developed to quantify relative contributions from the data sources. The ML-PI model statistically significantly outperformed (p \u3c 0.001) both individual models, ML and PI, achieving a mean absolute predicted error (MAPE) of 0.106 ± 0.125 versus 0.199 ± 0.186 (ML) and 0.227 ± 0.215 (PI), respectively. Associated Pearson correlation coefficients for ML-PI, ML, and PI were 0.838, 0.518, and 0.437, respectively. The Relief algorithm showed the PI model had the greatest contribution to the result, emphasizing the importance of the hybrid model in achieving the high accuracy

Self-authorship and creative industries workers’ career decision-making

Career decision-making is arguably at its most complex within professions where work is precarious and career calling is strong. This article reports from a study that examined the career decision-making of creative industries workers, for whom career decisions can impact psychological well-being and identity just as much as they impact individuals’ work and career. The respondents were 693 creative industries workers who used a largely open-ended survey to create in-depth reflections on formative moments and career decision-making. Analysis involved the theoretical model of self-authorship, which provides a way of understanding how people employ their sense of self to make meaning of their experiences. The self-authorship process emerged as a complex, non-linear and consistent feature of career decision-making. Theoretical contributions include a non-linear view of self-authorship that exposes the authorship of visible and covert multiple selves prompted by both proactive and reactive identity work

Navigating to new frontiers in behavioral neuroscience: traditional neuropsychological tests predict human performance on a rodent-inspired radial-arm maze

We constructed an 11-arm, walk-through, human radial-arm maze (HRAM) as a translational instrument to compare existing methodology in the areas of rodent and human learning and memory research. The HRAM, utilized here, serves as an intermediary test between the classic rat radial-arm maze (RAM) and standard human neuropsychological and cognitive tests. We show that the HRAM is a useful instrument to examine working memory ability, explore the relationships between rodent and human memory and cognition models, and evaluate factors that contribute to human navigational ability. One-hundred-and-fifty-seven participants were tested on the HRAM, and scores were compared to performance on a standard cognitive battery focused on episodic memory, working memory capacity, and visuospatial ability. We found that errors on the HRAM increased as working memory demand became elevated, similar to the pattern typically seen in rodents, and that for this task, performance appears similar to Miller's classic description of a processing-inclusive human working memory capacity of 7 ± 2 items. Regression analysis revealed that measures of working memory capacity and visuospatial ability accounted for a large proportion of variance in HRAM scores, while measures of episodic memory and general intelligence did not serve as significant predictors of HRAM performance. We present the HRAM as a novel instrument for measuring navigational behavior in humans, as is traditionally done in basic science studies evaluating rodent learning and memory, thus providing a useful tool to help connect and translate between human and rodent models of cognitive functioning

Effects of Anti-VEGF on Predicted Antibody Biodistribution: Roles of Vascular Volume, Interstitial Volume, and Blood Flow

BACKGROUND: The identification of clinically meaningful and predictive models of disposition kinetics for cancer therapeutics is an ongoing pursuit in drug development. In particular, the growing interest in preclinical evaluation of anti-angiogenic agents alone or in combination with other drugs requires a complete understanding of the associated physiological consequences. METHODOLOGY/PRINCIPAL FINDINGS: Technescan™ PYP™, a clinically utilized radiopharmaceutical, was used to measure tissue vascular volumes in beige nude mice that were naïve or administered a single intravenous bolus dose of a murine anti-vascular endothelial growth factor (anti-VEGF) antibody (10 mg/kg) 24 h prior to assay. Anti-VEGF had no significant effect (p>0.05) on the fractional vascular volumes of any tissues studied; these findings were further supported by single photon emission computed tomographic imaging. In addition, apart from a borderline significant increase (p = 0.048) in mean hepatic blood flow, no significant anti-VEGF-induced differences were observed (p>0.05) in two additional physiological parameters, interstitial fluid volume and the organ blood flow rate, measured using indium-111-pentetate and rubidium-86 chloride, respectively. Areas under the concentration-time curves generated by a physiologically-based pharmacokinetic model changed substantially (>25%) in several tissues when model parameters describing compartmental volumes and blood flow rates were switched from literature to our experimentally derived values. However, negligible changes in predicted tissue exposure were observed when comparing simulations based on parameters measured in naïve versus anti-VEGF-administered mice. CONCLUSIONS/SIGNIFICANCE: These observations may foster an enhanced understanding of anti-VEGF effects in murine tissues and, in particular, may be useful in modeling antibody uptake alone or in combination with anti-VEGF

Motivations and reasons for women attending a Breast Self-Examination training program: A qualitative study

<p>Abstract</p> <p>Background</p> <p>Breast cancer is a major threat to Taiwanese women's health. Despite the controversy surrounding the effectiveness of breast self-examination (BSE) in reducing mortality, BSE is still advocated by some health departments. The aim of the study is to provide information about how women decide to practice BSE and their experiences through the training process. Sixty-six women aged 27-50 were recruited.</p> <p>Methods</p> <p>A descriptive study was conducted using small group and individual in-depth interviews to collect data, and using thematic analysis and constant comparison techniques for data analysis.</p> <p>Results</p> <p>It was found that a sense of self-security became an important motivator for entering BSE training. The satisfaction in obtaining a sense of self-security emerged as the central theme. Furthermore, a ladder motivation model was developed to explain the participants' motivations for entering BSE training. The patterns of motivation include opportunity taking, clarifying confusion, maintaining health, and illness monitoring, which were connected with the risk perception for breast cancer.</p> <p>Conclusions</p> <p>We recognize that the way women decide to attend BSE training is influenced by personal and social factors. Understanding the different risk assessments women rely on in making their health decisions is essential. This study will assist researchers and health professionals to gain a better understanding of alternative ways to deal with breast health, and not to be limited by the recommendations of the health authorities.</p

1956: Abilene Christian College Bible Lectures - Full Text

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Green Tea Polyphenols Rescue of Brain Defects Induced by Overexpression of DYRK1A

Individuals with partial HSA21 trisomies and mice with partial MMU16 trisomies containing an extra copy of the DYRK1A gene present various alterations in brain morphogenesis. They present also learning impairments modeling those encountered in Down syndrome. Previous MRI and histological analyses of a transgenic mice generated using a human YAC construct that contains five genes including DYRK1A reveal that DYRK1A is involved, during development, in the control of brain volume and cell density of specific brain regions. Gene dosage correction induces a rescue of the brain volume alterations. DYRK1A is also involved in the control of synaptic plasticity and memory consolidation. Increased gene dosage results in brain morphogenesis defects, low BDNF levels and mnemonic deficits in these mice. Epigallocatechin gallate (EGCG) — a member of a natural polyphenols family, found in great amount in green tea leaves — is a specific and safe DYRK1A inhibitor. We maintained control and transgenic mice overexpressing DYRK1A on two different polyphenol-based diets, from gestation to adulthood. The major features of the transgenic phenotype were rescued in these mice