Improving the Reliability and Accuracy of Population Receptive Field Measures Using a Logarithmically Warped Stimulus.

The population receptive field method, which measures the region in visual space that elicits a BOLD signal in a voxel in retinotopic cortex, is a powerful tool for investigating the functional organization of human visual cortex with fMRI (Dumoulin & Wandell, 2008). However, recent work has shown that population receptive field (pRF) estimates for early retinotopic visual areas can be biased and unreliable, especially for voxels representing the fovea. Here, we show that a 'log-bar' stimulus that is logarithmically warped along the eccentricity dimension produces more reliable estimates of pRF size and location than the traditional moving bar stimulus. The log-bar stimulus was better able to identify pRFs near the foveal representation, and pRFs were smaller in size, consistent with simulation estimates of receptive field sizes in the fovea.

Evaluating the Impact of Early Career Academic Medicine Workshops on Medical Students' Interest.

Introduction Academic medicine is an important field that has had a notable decline in physician interest. The aim of this study was to introduce academic medicine to medical students early in their careers with a workshop in the medical school setting, beyond conferences, to promote even greater interest in the field. Methods This workshop consisted of (1) an informational didactic session using a Microsoft PowerPoint presentation, (2) small-group breakout discussion sessions to review case scenarios, and (3) a faculty panel to provide personal anecdotes and advice to students. The authors administered online pre- and post-workshop surveys to the students. One workshop was presented to first-year medical students and another to second-year medical students at California University of Science and Medicine. Data were analyzed using the IBM SPSS Statistics 27.0 for Windows. Pre- and post-workshop survey question means were compared using a paired t-test. Results There were 104 pre-clerkship student attendees, 83 of whom were in their first year and 21 in their second. Within each class year, there was a statistical significance in pre- and post-workshop survey responses for questions one through four (p < 0.001, p < 0.001, p < 0.001, p < 0.001), but question five responses were not statistically significant (p = 0.78). Conclusion Academic medicine workshops held early in medical students' careers are an effective way to foster interest in the field. Implementing academic medicine scholars' programs, in addition to these workshops, can help provide guidance and resources for students who want to pursue a career in academic medicine.

Using a Virtual Simulation Workshop to Teach Interns Evidence-Based Feedback Techniques.

Background The Accreditation Council for Graduate Medical Education requires residents to demonstrate competence in integrating feedback into their daily practice. With the shift to virtual medical education during the pandemic, the need for new skills in delivering effective feedback through virtual media has emerged. Methodology This study aimed to assess the feasibility of a virtual bootcamp for interns, utilizing virtual simulation workshops to teach effective feedback skills. The curriculum employed a situated learning-guided participation framework. Virtual standardized students participated, and interns engaged in activities such as providing virtual feedback, completing self-assessments, and receiving instruction on feedback principles, including the one-minute preceptor's five micro-skills. Interns repeated the feedback process, with virtual students providing assessments. Data were collected from 105 incoming interns at Arrowhead Regional Medical Center in June 2021 and June 2022, using Zoom® as the online platform. Results Competency assessments revealed a significant post-training increase in proficiency/expert milestones (88% versus 47%, p = 0.007). Interns' self-assessments also significantly improved (18.02 versus 16.74, p = 0.001), particularly for previously trained interns (18.27 versus 16.7). Non-primary care interns outperformed primary care interns in milestone scores. The majority of interns (80%) reported valuable learning experiences during the workshop, with 70% expressing confidence in using the one-minute preceptor technique during residency. The one-minute preceptor step "reinforce what was right" was deemed the easiest, while "obtain commitment" and "explore emotional reaction" presented significant challenges. Conclusions This study demonstrates the potential of virtual workshops to enhance intern competency in delivering effective feedback through formal processes and the one-minute preceptor. These virtual approaches offer innovative alternatives to in-person teaching, enabling evaluation at higher levels of Miller's pyramid of clinical competence.

Switching Frontal Polymerization Mechanisms: FROMP and FRaP.

Two frontal polymerization (FP) mechanisms, frontal ring-opening metathesis polymerization (FROMP) of dicyclopentadiene and frontal radical polymerization (FRaP) of benzyl acrylate and hexanediol diacrylate, were combined for rapid manufacturing of welded thermoset materials. Leveraging the immiscibility of the two different FP resins, welded thermosets and gradient foams of varying composition were achieved by switching of FP mechanisms. The adhesion strength of the welded thermoset materials differed depending on the originating mechanism. Finally, welded thermoset foams of varying porosity and homogeneity were generated through initiation from the bottom of the two resins.

Fleeting impressions of economic value via summary statistical representations.

Visual processing is limited: we cannot exhaustively analyze every object in a scene in a brief glance. However, ensemble perception affords the visual system a rapid shortcut to efficiently evaluate multiple objects. Ensemble processing has been widely tested across basic features. However, ensemble perception could be especially important and valuable for processes that are normally thought to require cognitive deliberative effort. One typical high-level cognitive process that humans engage in frequently is evaluating the value of objects. Here, we presented brief displays of consumer products to human observers and measured their visual sensitivity to the average value of the sets. We found that participants were sensitive to the average value of sets of products even when they did not have explicit memory for every item in the display. Our results show that value judgments can be based on ensemble information. Although value is thought to be an inferential concept, ensemble processing affords the brain a heuristic to efficiently assign value to entire sets of objects. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Early Blindness Shapes Cortical Representations of Auditory Frequency within Auditory Cortex.

Early loss of vision is classically linked to large-scale cross-modal plasticity within occipital cortex. Much less is known about the effects of early blindness on auditory cortex. Here, we examine the effects of early blindness on the cortical representation of auditory frequency within human primary and secondary auditory areas using fMRI. We observe that 4 individuals with early blindness (2 females), and a group of 5 individuals with anophthalmia (1 female), a condition in which both eyes fail to develop, have lower response amplitudes and narrower voxelwise tuning bandwidths compared with a group of typically sighted individuals. These results provide some of the first evidence in human participants for compensatory plasticity within nondeprived sensory areas as a result of sensory loss.SIGNIFICANCE STATEMENT Early blindness has been linked to enhanced perception of the auditory world, including auditory localization and pitch perception. Here we used fMRI to compare neural responses with auditory stimuli within auditory cortex across sighted, early blind, and anophthalmic individuals, in whom both eyes fail to develop. We find more refined frequency tuning in blind subjects, providing some of the first evidence in human subjects for compensation within nondeprived primary sensory areas as a result of blindness early in life.

Uncertainty Quantification Reveals the Importance of Data Variability and Experimental Design Considerations for in Silico Proarrhythmia Risk Assessment.

The Comprehensive in vitro Proarrhythmia Assay (CiPA) is a global initiative intended to improve drug proarrhythmia risk assessment using a new paradigm of mechanistic assays. Under the CiPA paradigm, the relative risk of drug-induced Torsade de Pointes (TdP) is assessed using an in silico model of the human ventricular action potential (AP) that integrates in vitro pharmacology data from multiple ion channels. Thus, modeling predictions of cardiac risk liability will depend critically on the variability in pharmacology data, and uncertainty quantification (UQ) must comprise an essential component of the in silico assay. This study explores UQ methods that may be incorporated into the CiPA framework. Recently, we proposed a promising in silico TdP risk metric (qNet), which is derived from AP simulations and allows separation of a set of CiPA training compounds into Low, Intermediate, and High TdP risk categories. The purpose of this study was to use UQ to evaluate the robustness of TdP risk separation by qNet. Uncertainty in the model parameters used to describe drug binding and ionic current block was estimated using the non-parametric bootstrap method and a Bayesian inference approach. Uncertainty was then propagated through AP simulations to quantify uncertainty in qNet for each drug. UQ revealed lower uncertainty and more accurate TdP risk stratification by qNet when simulations were run at concentrations below 5× the maximum therapeutic exposure (Cmax). However, when drug effects were extrapolated above 10× Cmax, UQ showed that qNet could no longer clearly separate drugs by TdP risk. This was because for most of the pharmacology data, the amount of current block measured was <60%, preventing reliable estimation of IC50-values. The results of this study demonstrate that the accuracy of TdP risk prediction depends both on the intrinsic variability in ion channel pharmacology data as well as on experimental design considerations that preclude an accurate determination of drug IC50-values in vitro. Thus, we demonstrate that UQ provides valuable information about in silico modeling predictions that can inform future proarrhythmic risk evaluation of drugs under the CiPA paradigm.

Corrigendum: Optimization of an In silico Cardiac Cell Model for Proarrhythmia Risk Assessment.

[This corrects the article on p. 616 in vol. 8, PMID: 28878692.].

Reconstructing Tone Sequences from Functional Magnetic Resonance Imaging Blood-Oxygen Level Dependent Responses within Human Primary Auditory Cortex.

Here we show that, using functional magnetic resonance imaging (fMRI) blood-oxygen level dependent (BOLD) responses in human primary auditory cortex, it is possible to reconstruct the sequence of tones that a person has been listening to over time. First, we characterized the tonotopic organization of each subject's auditory cortex by measuring auditory responses to randomized pure tone stimuli and modeling the frequency tuning of each fMRI voxel as a Gaussian in log frequency space. Then, we tested our model by examining its ability to work in reverse. Auditory responses were re-collected in the same subjects, except this time they listened to sequences of frequencies taken from simple songs (e.g., "Somewhere Over the Rainbow"). By finding the frequency that minimized the difference between the model's prediction of BOLD responses and actual BOLD responses, we were able to reconstruct tone sequences, with mean frequency estimation errors of half an octave or less, and little evidence of systematic biases.

Optimization of an In silico Cardiac Cell Model for Proarrhythmia Risk Assessment.

Drug-induced Torsade-de-Pointes (TdP) has been responsible for the withdrawal of many drugs from the market and is therefore of major concern to global regulatory agencies and the pharmaceutical industry. The Comprehensive in vitro Proarrhythmia Assay (CiPA) was proposed to improve prediction of TdP risk, using in silico models and in vitro multi-channel pharmacology data as integral parts of this initiative. Previously, we reported that combining dynamic interactions between drugs and the rapid delayed rectifier potassium current (IKr) with multi-channel pharmacology is important for TdP risk classification, and we modified the original O'Hara Rudy ventricular cell mathematical model to include a Markov model of IKr to represent dynamic drug-IKr interactions (IKr-dynamic ORd model). We also developed a novel metric that could separate drugs with different TdP liabilities at high concentrations based on total electronic charge carried by the major inward ionic currents during the action potential. In this study, we further optimized the IKr-dynamic ORd model by refining model parameters using published human cardiomyocyte experimental data under control and drug block conditions. Using this optimized model and manual patch clamp data, we developed an updated version of the metric that quantifies the net electronic charge carried by major inward and outward ionic currents during the steady state action potential, which could classify the level of drug-induced TdP risk across a wide range of concentrations and pacing rates. We also established a framework to quantitatively evaluate a system's robustness against the induction of early afterdepolarizations (EADs), and demonstrated that the new metric is correlated with the cell's robustness to the pro-EAD perturbation of IKr conductance reduction. In summary, in this work we present an optimized model that is more consistent with experimental data, an improved metric that can classify drugs at concentrations both near and higher than clinical exposure, and a physiological framework to check the relationship between a metric and EAD. These findings provide a solid foundation for using in silico models for the regulatory assessment of TdP risk under the CiPA paradigm.

Characterization of loperamide-mediated block of hERG channels at physiological temperature and its proarrhythmia propensity.

BACKGROUND: Loperamide (Immodium®) is indicated for symptomatic control of diarrhea. It is a µ-opioid receptor agonist, and recently has been associated with misuse and abuse. At therapeutic doses loperamide has not been associated with cardiotoxicity. However, loperamide overdose is associated with proarrhythmia and death - two effects that are likely attributable to its block of cardiac ion channels that are critical for generating action potentials. In this study, we defined loperamide-hERG channel interaction characteristics, and used a ventricular myocyte action potential model to compare loperamide's proarrhythmia propensity to twelve drugs with defined levels of clinical risk. METHODS AND RESULTS: Whole-cell voltage-clamp recordings were performed at 37°C on a HEK293 cell line stably expressing the hERG channel proteins, and loperamide was bath-applied to assess its effects on hERG current. Loperamide suppressed hERG current in a use- and voltage-dependent but frequency-independent manner, with a half-maximal inhibitory concentration <90nM. The onset of current suppression was concentration-dependent and appeared to follow a first-order reaction. Loperamide also altered the voltage-dependence of steady state hERG current properties. Electrophysiological data were integrated into a myocyte model that simulated dynamic drug-hERG channel interaction to estimate Torsade de Pointes risk through comparisons with reference drugs with defined clinical risk. In the context of overdose that would result in loperamide levels far exceeding those produced by therapeutic doses, loperamide is placed in the high risk category, alongside quinidine, bepridil, dofetilide, and sotalol. CONCLUSIONS: The combined in vitro and in silico approach provides mechanistic insight regarding the potential for loperamide to generate cardiotoxicity in overdose situations. This strategy holds promise for improving cardiac safety assessment.

Improving the In Silico Assessment of Proarrhythmia Risk by Combining hERG (Human Ether-à-go-go-Related Gene) Channel-Drug Binding Kinetics and Multichannel Pharmacology.

BACKGROUND: The current proarrhythmia safety testing paradigm, although highly efficient in preventing new torsadogenic drugs from entering the market, has important limitations that can restrict the development and use of valuable new therapeutics. The CiPA (Comprehensive in vitro Proarrhythmia Assay) proposes to overcome these limitations by evaluating drug effects on multiple cardiac ion channels in vitro and using these data in a predictive in silico model of the adult human ventricular myocyte. A set of drugs with known clinical torsade de pointes risk was selected to develop and calibrate the in silico model. METHODS AND RESULTS: Manual patch-clamp data assessing drug effects on expressed cardiac ion channels were integrated into the O'Hara-Rudy myocyte model modified to include dynamic drug-hERG channel (human Ether-à-go-go-Related Gene) interactions. Together with multichannel pharmacology data, this model predicts that compounds with high torsadogenic risk are more likely to be trapped within the hERG channel and show stronger reverse use dependency of action potential prolongation. Furthermore, drug-induced changes in the amount of electronic charge carried by the late sodium and L-type calcium currents was evaluated as a potential metric for assigning torsadogenic risk. CONCLUSIONS: Modeling dynamic drug-hERG channel interactions and multi-ion channel pharmacology improves the prediction of torsadogenic risk. With further development, these methods have the potential to improve the regulatory assessment of drug safety models under the CiPA paradigm.

Ancillary health effects of climate mitigation scenarios as drivers of policy uptake: a review of air quality, transportation and diet co-benefits modeling studies.

Background: Significant mitigation efforts beyond the Nationally Determined Commitments (NDCs) coming out of the 2015 Paris Climate Agreement are required to avoid warming of 2°C above pre-industrial temperatures. Health co-benefits represent selected near term, positive consequences of climate policies that can offset mitigation costs in the short term before the beneficial impacts of those policies on the magnitude of climate change are evident. The diversity of approaches to modeling mitigation options and their health effects inhibits meta-analyses and syntheses of results useful in policy-making. Methods/Design: We evaluated the range of methods and choices in modeling health co-benefits of climate mitigation to identify opportunities for increased consistency and collaboration that could better inform policy-making. We reviewed studies quantifying the health co-benefits of climate change mitigation related to air quality, transportation, and diet published since the 2009 Lancet Commission 'Managing the health effects of climate change' through January 2017. We documented approaches, methods, scenarios, health-related exposures, and health outcomes. Results/Synthesis: Forty-two studies met the inclusion criteria. Air quality, transportation, and diet scenarios ranged from specific policy proposals to hypothetical scenarios, and from global recommendations to stakeholder-informed local guidance. Geographic and temporal scope as well as validity of scenarios determined policy relevance. More recent studies tended to use more sophisticated methods to address complexity in the relevant policy system. Discussion: Most studies indicated significant, nearer term, local ancillary health benefits providing impetus for policy uptake and net cost savings. However, studies were more suited to describing the interaction of climate policy and health and the magnitude of potential outcomes than to providing specific accurate estimates of health co-benefits. Modeling the health co-benefits of climate policy provides policy-relevant information when the scenarios are reasonable, relevant, and thorough, and the model adequately addresses complexity. Greater consistency in selected modeling choices across the health co-benefits of climate mitigation research would facilitate evaluation of mitigation options particularly as they apply to the NDCs and promote policy uptake.

Mechanisms of arrhythmogenesis related to calcium-driven alternans in a model of human atrial fibrillation.

The occurrence of atrial fibrillation (AF) is associated with progressive changes in the calcium handling system of atrial myocytes. Calcium cycling instability has been implicated as an underlying mechanism of electrical alternans observed in patients who experience AF. However, the extent to which calcium-induced alternation of electrical activity in the atria contributes to arrhythmogenesis is unknown. In this study, we investigated the effects of calcium-driven alternans (CDA) on arrhythmia susceptibility in a biophysically detailed, 3D computer model of the human atria representing electrical and structural remodeling secondary to chronic AF. We found that elevated propensity to CDA rendered the atria vulnerable to ectopy-induced arrhythmia. It also increased the complexity and persistence of arrhythmias induced by fast pacing, with unstable scroll waves meandering and frequently breaking up to produce multiple wavelets. Our results suggest that calcium-induced electrical instability may increase arrhythmia vulnerability and promote increasing disorganization of arrhythmias in the chronic AF-remodeled atria, thus playing an important role in the progression of the disease.

How computer simulations of the human heart can improve anti-arrhythmia therapy.

Over the last decade, the state-of-the-art in cardiac computational modelling has progressed rapidly. The electrophysiological function of the heart can now be simulated with a high degree of detail and accuracy, opening the doors for simulation-guided approaches to anti-arrhythmic drug development and patient-specific therapeutic interventions. In this review, we outline the basic methodology for cardiac modelling, which has been developed and validated over decades of research. In addition, we present several recent examples of how computational models of the human heart have been used to address current clinical problems in cardiac electrophysiology. We will explore the use of simulations to improve anti-arrhythmic pacing and defibrillation interventions; to predict optimal sites for clinical ablation procedures; and to aid in the understanding and selection of arrhythmia risk markers. Together, these studies illustrate how the tremendous advances in cardiac modelling are poised to revolutionize medical treatment and prevention of arrhythmia.

Disrupted calcium release as a mechanism for atrial alternans associated with human atrial fibrillation.

Atrial fibrillation (AF) is the most common cardiac arrhythmia, but our knowledge of the arrhythmogenic substrate is incomplete. Alternans, the beat-to-beat alternation in the shape of cardiac electrical signals, typically occurs at fast heart rates and leads to arrhythmia. However, atrial alternans have been observed at slower pacing rates in AF patients than in controls, suggesting that increased vulnerability to arrhythmia in AF patients may be due to the proarrythmic influence of alternans at these slower rates. As such, alternans may present a useful therapeutic target for the treatment and prevention of AF, but the mechanism underlying alternans occurrence in AF patients at heart rates near rest is unknown. The goal of this study was to determine how cellular changes that occur in human AF affect the appearance of alternans at heart rates near rest. To achieve this, we developed a computational model of human atrial tissue incorporating electrophysiological remodeling associated with chronic AF (cAF) and performed parameter sensitivity analysis of ionic model parameters to determine which cellular changes led to alternans. Of the 20 parameters tested, only decreasing the ryanodine receptor (RyR) inactivation rate constant (kiCa) produced action potential duration (APD) alternans seen clinically at slower pacing rates. Using single-cell clamps of voltage, fluxes, and state variables, we determined that alternans onset was Ca2+-driven rather than voltage-driven and occurred as a result of decreased RyR inactivation which led to increased steepness of the sarcoplasmic reticulum (SR) Ca2+ release slope. Iterated map analysis revealed that because SR Ca2+ uptake efficiency was much higher in control atrial cells than in cAF cells, drastic reductions in kiCa were required to produce alternans at comparable pacing rates in control atrial cells. These findings suggest that RyR kinetics may play a critical role in altered Ca2+ homeostasis which drives proarrhythmic APD alternans in patients with AF.

Defibrillation success with high frequency electric fields is related to degree and location of conduction block.

BACKGROUND: We recently demonstrated that high frequency alternating current (HFAC) electric fields can reversibly block propagation in the heart by inducing an oscillating, elevated transmembrane potential (Vm) that maintains myocytes in a refractory state for the field duration and can terminate arrhythmias, including ventricular fibrillation (VF). OBJECTIVES: To quantify and characterize conduction block (CB) induced by HFAC fields and to determine whether the degree of CB can be used to predict defibrillation success. METHODS: Optical mapping was performed in adult guinea pig hearts (n = 14), and simulations were performed in an anatomically accurate rabbit ventricular model. HFAC fields (50-500 Hz) were applied to the ventricles. A novel power spectrum metric of CB-the loss of spectral power in the 1-30 Hz range, termed loss of conduction power (LCP)-was assessed during the HFAC field and compared with defibrillation success and VF vulnerability. RESULTS: LCP increased with field strength and decreased with frequency. Optical mapping experiments conducted on the epicardial surface showed that LCP and the size of CB regions were significantly correlated with VF initiation and termination. In simulations, subsurface myocardial LCP and CB sizes were more closely correlated with VF termination than surface values. Multilinear regression analysis of simulation results revealed that while CB on both the surface and the subsurface myocardium was predictive, subsurface myocardial CB was the better predictor of defibrillation success. CONCLUSIONS: HFAC fields induce a field-dependent state of CB, and defibrillation success is related to the degree and location of the CB.

If I value myself, I value school: the protective effect of self-esteem among abused females.

Children who have been severely maltreated tend to perform significantly below their non-maltreated peers in standardized tests, earn lower grades and have the most discipline issues in the school setting. There is evidence that self-esteem (SE) may be a protective factor for youth with regard to negative emotional outcomes. The role of self-esteem needs to be explored further in more collectivistic cultures. The purpose of this study was to explore the relationship between physical abuse, SE and school attitudes. Participants included 14 females rescued from a city landfill in Nicaragua (ages 7-17 years, M=12.44), half of whom had reported being beaten. SE and attitude toward school (ATS) were assessed using the Spanish Behavior Assessment System for Children. Grade point average (GPA) was obtained from their schools. Females who were beaten had significantly lower SE and a more negative ATS. Their GPA was lower, but not significantly. When SE and abuse were considered together, the effect of abuse on school attitudes was non-significant, suggesting that SE is a protective factor for the effects of abuse on ATS.

The poverty puzzle: the surprising difference between wealthy and poor students for self-efficacy and academic achievement.

This study explored the relationship between intellectual ability, socioeconomic status (SES), academic achievement and self-efficacy in a cross-cultural sample. Data from 90 students (63 students from Central America and 27 from the US) showed that regardless of culture or IQ, students from low SES families had significantly lower grade point averages than students from medium- or high-SES families. Unexpectedly, data showed that regardless of culture or IQ, students from high-SES families had the lowest self-efficacy, but the highest academic performance. Results suggest that self-efficacy is likely to be related to expectations and self-perception beyond IQ or culture.

I am smart, therefore I can: examining the relationship between IQ and self-efficacy across cultures.

The purpose of this article is to examine the relationship between intelligence (IQ) and self-efficacy in children and adolescents living in the United States and Nicaragua. The sample consisted of 90 (46 male, 44 female) students (mean age = 11.57 years, SD = 3.0 years) referred by school administrators and faculty. United States (US) participants (n = 27) resided in rural counties in the Northwest. The other group consisted of 63 students from Central America. A comparison between groups revealed that in the US, sample higher grades and IQ scores are typically associated with higher levels of self-efficacy. However in the Nicaraguan sample, both IQ scores and grades were not associated with self-efficacy, although age was correlated with self-efficacy. Results suggest that the construct of self-efficacy might change depending on whether one belongs to an individualistic or collectivistic society. Additionally, the effects of socioeconomic factors might influence perceived ability even more than intellectual abilities.