Social Mobility Through Mathematics Proficiency for English Language Learners

College admission is contingent upon students’ high school performances, especially mathematics proficiency that is crucial in qualifying for the projected science, technology, engineering, and mathematics professions of the future. This paper reviews some concerns that hinder the efforts of English language learners (ELLs), often the children of immigrants, to achieve social mobility through a college education. ELLs consistently fail to achieve proficiency on mathematics assessments as measured by the National Assessment for Educational Progress and local assessments such as the Florida Comprehensive Assessment Test. Consequently, many ELLs do not attend college. The article examines implications for educators and policymakers for resolving some of the issues that impede transforming ELLs into academic and societal achievers. Actions taken by educators and policymakers might assist ELLs in navigating the challenges encountered in their pursuit of a college education

Examining the Relationship Between Math Scores and English Language Proficiency

Multiple studies propose that English proficiency dictates English language learners’ (ELLs) performances on mathematics assessments. The current study investigates the predictive power of English proficiency on mathematics scores, while controlling for gender, socioeconomic status (SES), and grade level among ELLs at a south Florida elementary school. Krashen’s theory of comprehensible input as a precursor to second language acquisition provides the framework for this quantitative, correlation study. Mathematics scores from the Florida Comprehensive Assessment Test for Grade 3–5 ELLs (N = 177) were analyzed using multiple linear regression. Analysis reveals English proficiency as a statistically significant predictor of mathematics scores. Mathematics scores increase simultaneously with English proficiency but inversely with grade level. Grade level moderates the influence of English proficiency on mathematics scores. Gender and SES have no significant moderating influence

Spike sorting for large, dense electrode arrays

Developments in microfabrication technology have enabled the production of neural electrode arrays with hundreds of closely spaced recording sites, and electrodes with thousands of sites are under development. These probes in principle allow the simultaneous recording of very large numbers of neurons. However, use of this technology requires the development of techniques for decoding the spike times of the recorded neurons from the raw data captured from the probes. Here we present a set of tools to solve this problem, implemented in a suite of practical, user-friendly, open-source software. We validate these methods on data from the cortex, hippocampus and thalamus of rat, mouse, macaque and marmoset, demonstrating error rates as low as 5%

Variant R94C in TNNT2‐encoded troponin T predisposes to pediatric restrictive dardiomyopathy and sudden death through impaired thin filament relaxation resulting in myocardial diastolic dysfunction

Background Pediatric-onset restrictive cardiomyopathy (RCM) is associated with high mortality, but underlying mechanisms of disease are under investigated. RCM-associated diastolic dysfunction secondary to variants i

Viral Endomyocardial Infection Is an Independent Predictor and Potentially Treatable Risk Factor for Graft Loss and Coronary Vasculopathy in Pediatric Cardiac Transplant Recipients

ObjectivesThis study sought to evaluate the outcome and prevalence of viral endomyocardial infection after cardiac transplantation.BackgroundViral myocardial infection causes heart failure, but its role after cardiac transplantation is unclear. We hypothesized that viral infection of the cardiac allograft reduces graft survival.MethodsBetween June 1999 and November 2004, 94 pediatric cardiac transplant patients were screened for the presence of viral genome in serial endomyocardial biopsies (EMBs) using polymerase chain reaction (PCR) assays. Graft loss, advanced transplant coronary artery disease (TCAD), and acute rejection (AR) were compared in the PCR-positive (n = 37) and PCR-negative (n = 57) groups, using time-dependent Kaplan-Meier and Cox regression analyses. From November 2002 to November 2004, intravenous immunoglobulin therapy (IVIG) was administered to patients with PCR-positive EMBs. The outcomes of the IVIG-treated, PCR-positive patients (n = 20) were compared with IVIG-untreated, PCR-positive patients (n = 17).ResultsViral genomes were detected in EMBs from 37 (39%) patients; parvovirus B19, adenovirus, and Epstein-Barr virus (EBV) were the most common. The PCR-positive group (n = 37, 25% graft loss at 2.4 years) had decreased graft survival (p < 0.001) compared with the PCR-negative group (n = 57, 25% graft loss at 8.7 years) and developed advanced TCAD prematurely (p = 0.001). The number of AR episodes was similar in both groups. On multivariate analysis, presence of viral genome was an independent risk factor for graft loss (relative risk: 4.2, p = 0.015). The time to advanced TCAD after becoming PCR-positive was longer in the IVIG-treated patients (p = 0.03) with a trend toward improved graft survival (p = 0.06).ConclusionsViral endomyocardial infection is an independent predictor of graft loss in pediatric cardiac transplant recipients. This effect appears to be mediated through premature development of advanced TCAD. IVIG therapy in this subgroup may improve survival and merits further investigation

The Nested States Model: An Empirical Framework for Integrating the Brain and the Mind

Philosophy of mind has made substantial progress on biologically-rooted approaches to understanding the mind and subjectivity through the enactivist perspective, but research on subjectivity within neuroscience has not kept apace. Indeed, we possess no principled means of relating experiential phenomena to neurophysiological processes. Here, we present the Nested States Model as a framework to guide empirical investigation into the relationship between subjectivity and neurobiology. Building on recent work in phenomenology and philosophy of mind, we develop an account of experiential states as layered, or nested. We argue that this nested structure is also apparent in brain activity. The recognition of this structural homology – that both experiential and brain states can be characterized as systems of nested states – brings our views of subjective mental states into broad alignment with our understanding of general principles and properties of brain activity. This alignment enables a more systematic approach to formulating specific hypotheses and predictions about how the two domains relate to one another

The Role of Internal Signals in Structuring V1 Population Activity

Neuronal responses to repeated presentations of identical visual stimuli are variable. The source of this variability is unknown, but it is commonly treated as noise. We argue that this variability reflects, and is due to, computations internal to the brain. Relatively little research has examined the effect on neuronal responses of fluctuations in internal signals such as cortical state and attention, leaving a number of uncontrolled parameters that may contribute to neuronal variability. Attention increases neuronal response gain in a spatial and feature selective manner. We hypothesize that fluctuations in the strength and focus of attention are a major source of neuronal response variability and covariability. We first examine a simple model of a gain-modulating signal acting on a population of neurons and show that fluctuations in attention can increase individual and shared variability. To test our model’s predictions experimentally, we devised a cued-spatial attention, change-detection task to induce varying degrees of fluctuation in the subject’s attentional signal. We use multi-electrode recordings in primary visual cortex of macaques performing this task. We demonstrate that attention gain-modulates responses of V1 neurons in a manner consistent with results from higher-order areas. Our results also indicate neuronal covariability is elevated in conditions in which attention fluctuates. Overall, our results suggest that attentional fluctuations are an important contributor to neuronal variability and open the door to the use of statistical methods for inferring the state of these signals on behaviorally relevant timescales

Correlated variability in population activity: noise or signature of internal computations?

Neuronal responses to repeated presentations of identical visual stimuli are variable. The source of this variability is unknown, but it is commonly treated as noise and seen as an obstacle to understanding neuronal activity. We argue that this variability is not noise but reflects, and is due to, computations internal to the brain. Internal signals such as cortical state or attention interact with sensory information processing in early sensory areas. However, little research has examined the effect of fluctuations in these signals on neuronal responses, leaving a number of uncontrolled parameters that may contribute to neuronal variability. One such variable is attention, which increases neuronal response gain in a spatial and feature selective manner. Both the strength of this modulation and the focus of attention are likely to vary from trial to trial, and we hypothesize that these fluctuations are a major source of neuronal response variability and covariability. We first examine a simple model of a gain-modulating signal acting on a population of neurons and show that fluctuations in attention can increase individual and shared variability and generate a variety of correlation structures that are relevant to population coding, including limited range and differential correlations. To test our model’s predictions experimentally, we devised a cued-spatial attention, change-detection task to induce varying degrees of fluctuation in the subject’s attentional signal by changing whether the subject must attend to one stimulus location while ignoring another, or attempt to attend to multiple locations simultaneously. We use multi-electrode recordings with laminar probes in primary visual cortex of macaques performing this task. We demonstrate that attention gain-modulates responses of V1 neurons in a manner that is consistent with results from higher-order areas. Consistent with our model’s predictions, our preliminary results indicate neuronal covariability is elevated in conditions in which attention fluctuates and that neurons are nearly independent when attention is focused. Overall, our results suggest that attentional fluctuations are an important contributor to neuronal variability and open the door to the use of statistical methods for inferring the state of these signals on a trial-by-trial basis

The Role of Internal Signals in Structuring V1 Population Activity

Neuronal responses to repeated presentations of identical visual stimuli are variable. The cause of this variability is unknown, but it is commonly treated as noise and seen as an obstacle to understanding neuronal activity. We offer an alternative explanation: this variability is not noise but reflects, and is due to, computations internal to the brain. Internal signals such as cortical state or attention interact with sensory information processing in early sensory areas. However, little research has examined the effect of fluctuations in these signals on neuronal responses, leaving a number of uncontrolled parameters that may contribute to neuronal variability. One such variable is attention. We hypothesize that fluctuations in attentional signals contribute to neuronal response variability and that controlling for such fluctuations will reduce this variability. To study this interaction, we use multi-electrode recordings with laminar probes in primary visual cortex of macaques while subjects perform a cued-spatial attention, change-detection task. We induce varying degrees of fluctuation in the subject’s attentional signal by changing whether the subject must attend to one stimulus location while ignoring another, or attempt to attend to both locations simultaneously. We demonstrate that attention increases stimulusevoked firing rates and gain-modulates the tuning curves of V1 neurons in a manner that is consistent with results from higher order areas. Future experiments will examine the effect of attentional fluctuations on neuronal response variability and interneuronal correlations as well as the laminar profile of these effects. Under this hypothesis, this variability can aid, rather than hinder, our understanding of brain function

Management of Advanced Heart Failure in Children with Cancer Therapy-Related Cardiac Dysfunction

The evolution of cancer therapies has led to marked improvement in survival of those affected by childhood malignancies, while also increasing the recognition of early and late toxicities associated with cancer therapies. Cardiotoxicity can include cardiomyopathy/heart failure, coronary artery disease, stroke, pericardial disease, arrhythmias, and valvular and vascular dysfunction as a result of exposure to chemotherapy and/or radiation. Anthracyclines remain the most common cause of chemotherapy-induced cardiomyopathy (CCM) with varying clinical presentations including: acute, early onset, and late-onset. Many individuals develop cardiac dysfunction over the long-term, ranging from subclinical cardiac dysfunction to end-stage symptomatic heart failure. The focus of this review is on characterization of symptomatic heart failure in children with cancer therapy-related cardiac dysfunction (CTRCD) primarily due to CCM and utilization of advanced heart failure therapies, including ventricular assist device (VAD) support and heart transplantation, with consideration of unique patient-related factors