“All Colors and Hues”: An Autoethnography of a Multiethnic Family's Strategies for Bilingualism and Multiculturalism

This two‐year autoethnographic action research study explores the processes a multiethnic/multiracial family uses to maintain their children's heritage language of Spanish and the family's multiculturalism. Data sources (including interviews and participant observations in the home and the dual‐language school) specifically focus on the eldest child, Nelia, from her kindergarten and first‐grade years where she attended a public dual‐language program. The findings illuminate the integral link between the family's ideology toward valuing bilingualism and the necessity of school support.     

Abnormal singing can identify patients with right hemisphere cortical strokes at risk for impaired prosody

Despite lacking aphasia seen with left hemisphere (LH) infarcts involving the middle cerebral artery territory, right hemisphere (RH) strokes can result in significant difficulties in affective prosody. These impairments may be more difficult to identify but lead to significant communication problems.We determine if evaluation of singing can accurately identify stroke patients with cortical RH infarcts at risk for prosodic impairment who may benefit from rehabilitation.A prospective cohort of 36 patients evaluated with acute ischemic stroke was recruited. Participants underwent an experimental battery evaluating their singing, prosody comprehension, and prosody production. Singing samples were rated by 2 independent reviewers as subjectively “normal” or “abnormal,” and analyzed for properties of the fundamental frequency. Relationships between infarct location, singing, and prosody performance were evaluated using t tests and chi-squared analysis.Eighty percent of participants with LH cortical strokes were unable to successfully complete any of the tasks due to severe aphasia. For the remainder, singing ratings corresponded to stroke location for 68% of patients. RH cortical strokes demonstrated a lower mean fundamental frequency while singing than those with subcortical infarcts (176.8 vs 130.4, P = 0.02). They also made more errors on tasks of prosody comprehension (28.6 vs 16.0, P < 0.001) and production (40.4 vs 18.4, P < 0.001).Patients with RH cortical infarcts are more likely to exhibit impaired prosody comprehension and production and demonstrate the poor variation of tone when singing compared to patients with subcortical infarcts. A simple singing screen is able to successfully identify patients with cortical lesions and potential prosodic deficits.     

Napping facilitates word learning in early lexical development

Little is known about the role that night‐time sleep and daytime naps play in early cognitive development. Our aim was to investigate how napping affects word learning in 16‐month‐olds. Thirty‐four typically developing infants were assigned randomly to nap and wake groups. After teaching two novel object–word pairs to infants, we tested their initial performance with an intermodal preferential looking task in which infants are expected to increase their target looking time compared to a distracter after hearing its auditory label. A second test session followed after approximately a 2‐h delay. The delay contained sleep for the nap group or no sleep for the wake group. Looking behaviour was measured with an automatic eye‐tracker. Vocabulary size was assessed using the Oxford Communicative Development Inventory. A significant interaction between group and session was found in preferential looking towards the target picture. The performance of the nap group increased after the nap, whereas that of the wake group did not change. The gain in performance correlated positively with the expressive vocabulary size in the nap group. These results indicate that daytime napping helps consolidate word learning in infancy.     

Validating drug repurposing signals using electronic health records: a case study of metformin associated with reduced cancer mortality

Objectives Drug repurposing, which finds new indications for existing drugs, has received great attention recently. The goal of our work is to assess the feasibility of using electronic health records (EHRs) and automated informatics methods to efficiently validate a recent drug repurposing association of metformin with reduced cancer mortality.Methods By linking two large EHRs from Vanderbilt University Medical Center and Mayo Clinic to their tumor registries, we constructed a cohort including 32 415 adults with a cancer diagnosis at Vanderbilt and 79 258 cancer patients at Mayo from 1995 to 2010. Using automated informatics methods, we further identified type 2 diabetes patients within the cancer cohort and determined their drug exposure information, as well as other covariates such as smoking status. We then estimated HRs for all-cause mortality and their associated 95% CIs using stratified Cox proportional hazard models. HRs were estimated according to metformin exposure, adjusted for age at diagnosis, sex, race, body mass index, tobacco use, insulin use, cancer type, and non-cancer Charlson comorbidity index.Results Among all Vanderbilt cancer patients, metformin was associated with a 22% decrease in overall mortality compared to other oral hypoglycemic medications (HR 0.78; 95% CI 0.69 to 0.88) and with a 39% decrease compared to type 2 diabetes patients on insulin only (HR 0.61; 95% CI 0.50 to 0.73). Diabetic patients on metformin also had a 23% improved survival compared with non-diabetic patients (HR 0.77; 95% CI 0.71 to 0.85). These associations were replicated using the Mayo Clinic EHR data. Many site-specific cancers including breast, colorectal, lung, and prostate demonstrated reduced mortality with metformin use in at least one EHR.Conclusions EHR data suggested that the use of metformin was associated with decreased mortality after a cancer diagnosis compared with diabetic and non-diabetic cancer patients not on metformin, indicating its potential as a chemotherapeutic regimen. This study serves as a model for robust and inexpensive validation studies for drug repurposing signals using EHR data.     

Exploring relation types for literature-based discovery

Objective Literature-based discovery (LBD) aims to identify “hidden knowledge” in the medical literature by: (1) analyzing documents to identify pairs of explicitly related concepts (terms), then (2) hypothesizing novel relations between pairs of unrelated concepts that are implicitly related via a shared concept to which both are explicitly related. Many LBD approaches use simple techniques to identify semantically weak relations between concepts, for example, document co-occurrence. These generate huge numbers of hypotheses, difficult for humans to assess. More complex techniques rely on linguistic analysis, for example, shallow parsing, to identify semantically stronger relations. Such approaches generate fewer hypotheses, but may miss hidden knowledge. The authors investigate this trade-off in detail, comparing techniques for identifying related concepts to discover which are most suitable for LBD.Materials and methods A generic LBD system that can utilize a range of relation types was developed. Experiments were carried out comparing a number of techniques for identifying relations. Two approaches were used for evaluation: replication of existing discoveries and the “time slicing” approach.¹Results Previous LBD discoveries could be replicated using relations based either on document co-occurrence or linguistic analysis. Using relations based on linguistic analysis generated many fewer hypotheses, but a significantly greater proportion of them were candidates for hidden knowledge.Discussion and Conclusion The use of linguistic analysis-based relations improves accuracy of LBD without overly damaging coverage. LBD systems often generate huge numbers of hypotheses, which are infeasible to manually review. Improving their accuracy has the potential to make these systems significantly more usable.     

Cluster Analysis of Vulnerable Groups in Acute Traumatic Brain Injury Rehabilitation

Objective

To analyze the complex relation between various social indicators that contribute to socioeconomic status and health care barriers.