Mount Vernon, IA, United States
Mount Vernon, IA, United States

Cornell College is a private liberal arts college in Mount Vernon, Iowa. Originally called the Iowa Conference Seminary, the school was founded in 1853 by Reverend Samuel M. Fellows. Four years later, in 1857, the name was changed to Cornell College, in honor of iron tycoon William Wesley Cornell, who was a distant relative of Ezra Cornell . Wikipedia.


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Lord C.,Cornell College | Bishop S.L.,University of California at San Francisco
Annual Review of Clinical Psychology | Year: 2015

This article provides a selective review of advances in scientific knowledge about autism spectrum disorder (ASD), using DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, fifth edition) diagnostic criteria as a framework for the discussion. We review literature that prompted changes to the organization of ASD symptoms and diagnostic subtypes in DSM-IV, and we examine the rationale for new DSM-5 specifiers, modifiers, and severity ratings as well as the introduction of the diagnosis of social (pragmatic) communication disorder. Our goal is to summarize and critically consider the contribution of clinical psychology research, along with that of other disciplines, to the current conceptualization of ASD. © 2015 by Annual Reviews. All rights reserved.


Grant
Agency: Department of Health and Human Services | Branch: National Institutes of Health | Program: STTR | Phase: Phase I | Award Amount: 192.70K | Year: 2015

DESCRIPTION provided by applicant N methyladenosine m A was recently discovered to be a widespread base modification present in thousands of mammalian mRNAs In addition to its prevalence throughout the transcriptome researchers have also revealed that m A is a reversible modification suggesting that dynamic regulation of mRNA methylation is a novel and widespread RNA regulatory mechanism in cells Much of our understanding of the physiological importance of m A comes from studies of m A demethylases Indeed disruption of the m A demethylase FTO leads to dysfunction of dopaminergic pathways in the brain and an abnormal response to cocaine in mice Additionally FTO genetic mutations have been strongly associated with diseases including melanoma and breast cancer in humans Despite the importance of FTO for human health and disease tools which directly measure FTO activity have not been developed In this proposal we use a simple yet innovative RNA aptamer based strategy to develop assays which measure the activity of FTO and other m A demethylating enzymes The results of this Phase I SBIR will be the development of an optimized fluorescence assay for measuring m A demethylase activity and demonstration of the compatibility of this tool for high throughput screening of small molecule FTO inhibitors This application will enable us to develop the first commercially viable assay for measuring FTO activity which will fulfill an important need in the RNA methylation and FTO research communities Furthermore these experiments will enable the development of HTS assays for the identification of novel inhibitors of FTO and other RNA demethylase enzymes PUBLIC HEALTH RELEVANCE Disruption of the FTO gene has been strongly associated with a variety of human diseases and FTO was recently shown to influence dopaminergic pathways and the response to drugs of abuse Researchers recently discovered that FTO functions to demethylate the highly prevalent base modification N methyladenosine m A in mRNAs however tools for measuring FTO activity have not yet been developed The goal of this project is to develop an assay for measuring m A demethylase activity which can eventually be used in high throughput screens to identify small molecule inhibitors of FTO and other m A demethylases This tool will enable the discovery of drugs which target m A demethylating enzymes and will facilitate the development of novel therapies for human disease


Men who have sex with men (MSM) bear a disproportionately higher burden of HIV infection than the general population. MSM in the Middle East and North Africa (MENA) are a largely hidden population because of a prevailing stigma towards this type of sexual behavior, thereby limiting the ability to assess infection transmission patterns among them. It is widely perceived that data are virtually nonexistent on MSM and HIV in this region. The objective of this review was to delineate, for the first time, the evidence on the epidemiology of HIV among MSM in MENA. This was a systematic review of all biological, behavioral, and other related data on HIV and MSM in MENA. Sources of data included PubMed (Medline), international organizations' reports and databases, country-level reports and databases including governmental and nongovernmental organization publications, and various other institutional documents. This review showed that onsiderable data are available on MSM and HIV in MENA. While HIV prevalence continues at low levels among different MSM groups, HIV epidemics appear to be emerging in at least few countries, with a prevalence reaching up to 28% among certain MSM groups. By 2008, the contribution of MSM transmission to the total HIV notified cases increased and exceeded 25% in several countries. The high levels of risk behavior (4-14 partners on average in the last six months among different MSM populations) and of biomarkers of risks (such as herpes simplex virus type 2 at 3%-54%), the overall low rate of consistent condom use (generally below 25%), the relative frequency of male sex work (20%-76%), and the substantial overlap with heterosexual risk behavior and injecting drug use suggest potential for further spread. This systematic review and data synthesis indicate that HIV epidemics appear to be emerging among MSM in at least a few MENA countries and could already be in a concentrated state among several MSM groups. There is an urgent need to expand HIV surveillance and access to HIV testing, prevention, and treatment services in a rapidly narrowing window of opportunity to prevent the worst of HIV transmission among MSM in the Middle East and North Africa. Please see later in the article for the Editors' Summary.


Peterson J.C.,Cornell College
Journal of consulting and clinical psychology | Year: 2013

To describe a mixed-methods approach to develop and test a basic behavioral science-informed intervention to motivate behavior change in 3 high-risk clinical populations. Our theoretically derived intervention comprised a combination of positive affect and self-affirmation (PA/SA), which we applied to 3 clinical chronic disease populations. We employed a sequential mixed methods model (EVOLVE) to design and test the PA/SA intervention in order to increase physical activity in people with coronary artery disease (post-percutaneous coronary intervention [PCI]) or asthma (ASM) and to improve medication adherence in African Americans with hypertension (HTN). In an initial qualitative phase, we explored participant values and beliefs. We next pilot tested and refined the intervention and then conducted 3 randomized controlled trials with parallel study design. Participants were randomized to combined PA/SA versus an informational control and were followed bimonthly for 12 months, assessing for health behaviors and interval medical events. Over 4.5 years, we enrolled 1,056 participants. Changes were sequentially made to the intervention during the qualitative and pilot phases. The 3 randomized controlled trials enrolled 242 participants who had undergone PCI, 258 with ASM, and 256 with HTN (n = 756). Overall, 45.1% of PA/SA participants versus 33.6% of informational control participants achieved successful behavior change (p = .001). In multivariate analysis, PA/SA intervention remained a significant predictor of achieving behavior change (p < .002, odds ratio = 1.66), 95% CI [1.22, 2.27], controlling for baseline negative affect, comorbidity, gender, race/ethnicity, medical events, smoking, and age. The EVOLVE method is a means by which basic behavioral science research can be translated into efficacious interventions for chronic disease populations.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: Smart and Connected Health | Award Amount: 299.88K | Year: 2016

The rapid adoption of Electronic Health Records (EHRs) across the U.S. healthcare systems coupled with the capability of linking EHRs to research biorepositories provides a unique opportunity for conducting large-scale Precision Medicine research. A critical step to make such research possible is identification of cohorts by defining inclusion and exclusion criteria that algorithmically select sets of patients based on available clinical data. For most of the existing research, the criteria for generating those patient cohorts are defined manually, which makes the entire process slow, labor intensive and not scalable. This project develops patient similarity learning algorithms to enable automatic cohort identification, which will accelerate the research of precision medicine.

The massive clinical data around patients are highly heterogeneous and sparse. Although there are some patient similarity learning algorithms, they typically work with a single type of patient data (e.g., just using diagnosis information in patient EHR) and cannot handle those challenges mentioned above effectively. This project develops advanced patient similarity learning algorithms by 1) learning composite patient similarities through a refinement process from multiple base similarity measures, with each base similarity being evaluated from a specific source of patient data or a specific form of patient representation; and 2) integrating information from multiple related auxiliary domains, such as drug, disease, and genomic information. Those information effectively regularizes the patient similarity learning process and makes it less sensitive to data sparsity.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: PALEOCLIMATE PROGRAM | Award Amount: 149.60K | Year: 2015

This award generally aims to use cave systems and speleothems as natural archives of environmental conditions related to tropical cyclones and variations in ocean and atmospheric conditions. This research is important because it will help expand the scientific understanding of the nature and timing of past tropical cyclone activity, especially during periods of varying regional (i.e., Indo-Pacific sea surface temperature and Pacific temperature gradients) and extra-tropical (i.e., Northern Hemisphere temperature) climatic conditions. Since tropical cyclones are responsible for the majority of extreme rainfall events in some regions, an improved assessment of their dynamics can aid in developing models of long-term water budgets and storm-related risks. Investing in understanding tropical cyclones has significant economic and social returns in terms of saved lives and protected property. Furthermore, this award will advance research and education at a primarily undergraduate institution thereby providing an early experience for students in the conduct of research.

Specifically, the research project will involve the installation of instruments to monitor meteorological, chemical, and hydrologic conditions at three caves spanning a near-coastal transect across northwestern Australia. Environmental variables (e.g., temperature, relative humidity, barometric pressure) in each cave will be integrated with meteorological and rainwater data (including rainfall amounts and stable isotopic compositions) collected at each site, along with the oxygen isotopic ratios of plate-grown spelean carbonate. These data will help develop a holistic understanding of cave responses, both hydrologic and isotopic, to extreme rainfall events such as those that characterize many tropical cyclones.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: PALEOCLIMATE PROGRAM | Award Amount: 104.08K | Year: 2016

This collaborative project generally aims to develop a high resolution aragonite stalagmite record of Holocene Indo-Australian Summer Monsoon (IASM) variability from cave KNI-51, located at the southern margin of the Indo-Pacific tropical rain belt (TRB), a region bounded by the austral and boreal summer intertropical convergence zones.

Regional monsoons represent the dominant component of low latitude hydroclimate and are sensitive to a wide array of sub-orbital forcings including solar irradiance, ENSO, and volcanic and anthropogenic aerosols. Tropical societies and ecosystems rely heavily on monsoon rainfall, and thus understanding the origin and nature of decadal-scale hydroclimate variability is critical to understanding the dynamics at play in such systems.

Recent field studies of Indo-Pacific hydroclimate suggests that over the last millennium, the TRB may have contracted during the Little Ice Age (LIA) thereby producing reduced monsoon rainfall along both the northern and southern margins of the TRB. In contrast, paleohydrologic and modeling studies show that the global TRB shifted southward meridionally at this time, creating anti-phasing (dry/wet) of rainfall between the TRB northern and southern margins.

The researchers have developed a sub-decadal resolved (~4 year) late Holocene (the last 3,000 years) IASM reconstruction from cave KNI-51 that, when integrated with paleomonsoon records from Southeast Asia and the Maritime Continent, reveal not only TRB contraction during the LIA, but expansion and contraction at multi-decadal to centennial time scales over the entirety of the late Holocene.

The specific research goals of the project are to extend the KNI-51 stalagmite record through the middle and early Holocene (9,000-3,000 years ago) to examine the nature of TRB dynamics during conditions distinct from those of the late Holocene, including elevated contrasts between summer insolation in the Northern and Southern Hemispheres, lower eustatic sea level (and increased exposure of Indo-Pacific continental shelf), intervals of reduced Atlantic meridional overturning circulation, and the El Nino-Southern Oscillation (ENSO) regime.

To better understand atmospheric circulation associated with TRB dynamics, these proxy data will be integrated with climate dynamical analyses of the 6,000 year time slice simulations conducted within the Coupled Model Intercomparison Project phase 5/Paleoclimate Modeling Intercomparison Project phase 3 (CMIP5/PMIP3) framework and with the newly available Last Millennium Ensemble (LME) simulations conducted by the National Center for Atmospheric Research (NCAR).

The project involves the potential for a unique view of TRB variability over the last 9,000 years and provides an important test of the skill of CMIP5-class models to accurately reproduce associated Indo-Pacific atmospheric dynamics. As the TRB is closely tied to tropical methane production, this research will help refine estimates of regional tropical methane fluxes during the Holocene. The research will be conducted with extensive involvement of undergraduate students thereby providing experience in advanced paleoclimate research and data analysis techniques.


Grant
Agency: NSF | Branch: Continuing grant | Program: | Phase: OFFICE OF MULTIDISCIPLINARY AC | Award Amount: 440.09K | Year: 2015

This project was developed at an NSF Ideas Lab on Cracking the Olfactory Code and is jointly funded by the Physics of Living Systems program in the Physics Division, the Mathematical Biology program in the Division of Mathematical Sciences, the Chemistry of Life Processes program in the Chemistry Division, and the Neural Systems Cluster in the Division of Integrative Organismal Systems. The project is a synergistic combination of laboratory experiments and computer modeling that will lead to better understanding of how animals use the sense of smell to navigate in the real world. Almost universally, from flies to mice to dogs, animals use odors to find critical resources, such as food, shelter, and mates. To date, no engineered device can replicate this function and understanding the code used by the brain will lead to many novel applications. Cracking codes, from neural codes to the Enigma code of WWII, is aided by a deep understanding of the content of messages that are being transmitted and how they will be used by their intended receivers. To crack the olfactory code, the team will focus on how odors move in landscapes, how animals extract spatial and temporal cues from odor landscapes, and how they use movement for enhancing these cues while progressing towards their targets. The proposed work encompasses physical measurement of odor plumes, behavioral measurement of animals paths through olfactory environments, electrophysiological and optical measurement of neural activity during olfactory navigation, perturbations of the environment via virtual reality and of neuronal hardware via genetics, and multilevel mathematical modeling. The PIs will teach and work with undergraduate, graduate and postdoctoral students and especially recruit students from underrepresented groups in science. The projects results may lead to improved methods for the detection of explosives, new olfactory robots to replace trained animals, and new theoretically-grounded advances in robotic control. The project will inform the development of technologies that interfere with the ability of flying insects (including disease vectors and crop pests) to locate their odor target, thus opening a new door for developing green technologies to solve problems that are of global economic and humanitarian importance.

This proposal is a synergistic combination of laboratory experiments and computational modeling that will probe how animals use olfaction to navigate in their environment. Specifically, this effort seeks to solve the difficult problem of olfactory navigation through the following aims: (i) Generate and quantify standardized, naturalistic odor environments that can be used to perform empirical and theoretical tests of navigation strategies; (ii) Determine phenomenological algorithms for odor-guided navigation through behavioral experiments in diverse animal species; (iii) Determine how odor cues for navigation are encoded and used in the nervous system by recording neuronal data and simulating putative neural circuits that implement these processes; (iv) Manipulate olfactory environments and neural circuitry, to evaluate model robustness. In contrast to previous attempts to understand olfactory navigation, the present strategy emphasizes mechanisms that are biologically feasible and explores the wide range of temporal and spatial scales in which animals successfully navigate. The project will generate datasets of immediate use and importance to scientists in theoretical biology and mathematics, engineering (fluid mechanics, electronic olfaction, and robotics) and biology (neuroscience, ecology and evolution).


Grant
Agency: NSF | Branch: Continuing grant | Program: | Phase: COGNEURO | Award Amount: 101.01K | Year: 2016

Learning to make choices that bring about good outcomes and avoid bad ones is a lifelong challenge. Such learning is particularly consequential during adolescence, when increased exploration and autonomy confer many opportunities to make new choices. Poor decision-making represents one of the greatest perils of adolescence, with mortality rates doubling during this developmental stage, in large part due to risky or impulsive actions. However, the neural and cognitive mechanisms underpinning this developmental period of increased risky decision-making are not well understood. The overarching goal of this proposal is to characterize how the dynamic developmental trajectory of brain circuitry involved in learning through positive and negative experience shapes real-world choices. Drawing upon behavioral, computational, and neuroimaging approaches, this work will examine how neurocognitive changes in value-based learning may give rise to a window of increased risky and impulsive decision-making during adolescence. A refined understanding of the mechanisms underlying developmental changes in real-world decision-making has broad relevance across a number of societal domains including public policy, adolescent health, and juvenile justice.

This proposal will test whether risky and impulsive choice may stem in part from developmental changes in two specific aspects of how individuals learn from experience: (i) the relative weighting individuals place upon positive versus negative outcomes of past actions and (ii) the degree to which individuals form and recruit mental models of the potential future consequences of their actions. A developmental sample of participants, spanning late childhood to young adulthood, will complete sequential decision-making tasks in which they make a series of choices that can yield good or bad outcomes. By applying computational reinforcement-learning models to participants choices in these tasks, we can precisely quantify developmental changes in these component processes of learning. Functional magnetic resonance imaging (fMRI) will be used to characterize corresponding developmental changes in the brain circuitry engaged during learning. We will assess whether these neurocognitive changes in learning are predictive of participants reports of their real-world risky and impulsive behavior, and whether they have distinct explanatory power from that of behavioral economic tasks that are commonly used to index risky and impulsive choice tendencies, but do not involve learning. A longitudinal follow-up session will enable assessment of the covariance between changes in learning and real-world risky and impulsive behavior as participants advance in their transition through adolescence. This work holds the potential to provide a more detailed mechanistic account of 
how reinforcement learning mediates the dynamic relationship between brain and behavior over the course of development.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: Dimensions of Biodiversity | Award Amount: 1.00M | Year: 2015

How is biodiversity generated and maintained? Much evidence suggests that parasites play an important role in both the origin and the maintenance of biological diversity. This project focuses on one of the most diverse groups of organisms on the planet: herbivorous insects, their parasites, and their microbes. The project targets three economically important groups of organisms: plants in the pumpkin/cucumber family, true fruit flies that attack these plants, and parasitic wasps that kill the flies. These wasps belong to a highly diverse and little studied group of species. Each wasp species can kill only one fly species; wasps attacking the wrong species of fly die. These bi-directional lethal interactions may be mediated by microbes (in wasps, flies, or both), by traits of flies immune systems, or both. This project is designed to uncover the mechanisms (evolutionary, ecological, and immunological) affecting interactions that may help explain the diversity of life. Many species of true fruit flies are major agricultural pests; this project will greatly increase knowledge about factors contributing to their susceptibility to parasitoids.

The project tests hypotheses that predict that: 1) defenses of parasites and their hosts affect diversification rates; 2) mechanisms of virulence differ among lineages, and 3) selection arising from predator-prey interactions can affect rates of species-formation. To discover and identify mechanisms of diversification, participants will generate and analyze molecular 1) high-resolution genetic data, multiple nuclear loci, and mtCOI haplotypes to delineate species, and resolve deeper phylogenetic relationships; 2) microsatellites and ddRAD-seq markers to discover and quantify fine-scale genetic diversity within and among populations; 3) phylogenies and field experiments to test hypotheses about mechanisms generating and controlling diversity on ancient, recent, and contemporary timescales. Undergraduate students from all participating colleges and universities will participate in the research.

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