Moisture Meter Performance I. Corn Over Five Crop Years

The long-term accuracy of the 1981 Iowa-Illinois moisture-meter calibrations was evaluated by meter-to-oven comparisons on 2999 samples from the 1979-1983 crop years. Although the five-year average accuracy of the trade meters Steinlite SS250, Dickey-john GACII, and Motomco 919 was ±0.5 percentage point relative to the air-oven up to 25% moisture (wb), there was up to ± 0.7 point accuracy variation among crop years. A year-to-year component was added to the previously published variance model; this component represents about 35% of total variance of a meter test relative to an oven test

Sources to Seafood: Mercury Pollution in the Marine Environment

In 2010, the Toxic Metals Superfund Research Program at Dartmouth College brought together a group of 50 scientists and policy stakeholders to form C-MERC, the Coastal and Marine Mercury Ecosystem Research Collaborative. The goal was to review current knowledge—and knowledge gaps—relating to a global environmental health problem, mercury contamination of the world’s marine fish. C-MERC participants attended two workshops over a two-year period, and in 2012 C-MERC authors published a series of peer-reviewed papers in the journals Environmental Health Perspectives and Environmental Research that elucidated key processes related to the inputs, cycling, and uptake of mercury in marine ecosystems, effects on human health, and policy implications. This report synthesizes the knowledge from these papers in an effort to summarize the science relevant to policies being considered at regional, national, and global levels. The Dartmouth Toxic Metals Superfund Research Program uses an interdisciplinary approach to investigate the ways that arsenic and mercury in the environment affect ecosystems and human health. Arsenic and mercury are commonly found in Superfund sites around the U.S. as well as other areas that result in exposures to certain communities. The Research Translation Core of the program communicates program science to government partners, non-governmental organizations, health care providers and associations, universities and the lay community, and facilitates the use of its research for the protection of public health. The Research Translation Core organized the C-MERC effort. The Superfund Research Program of the National Institute of Environmental Health Sciences supports a network of university programs that investigate the complex health and environmental issues associated with contaminants found at the nation’s hazardous waste sites. The Program coordinates with the Environmental Protection Agency and the Agency for Toxic Substances and Disease Registry of the Centers for Disease Control and Prevention, federal entities charged with management of environmental and human health hazards associated with toxic substances

A Cognitive Electrophysiological Signature Differentiates Amnestic Mild Cognitive Impairment from Normal Aging

Background: Noninvasive and effective biomarkers for early detection of amnestic mild cognitive impairment (aMCI) before measurable changes in behavioral performance remain scarce. Cognitive event-related potentials (ERPs) measure synchronized synaptic neural activity associated with a cognitive event. Loss of synapses is a hallmark of the neuropathology of early Alzheimer’s disease (AD). In the present study, we tested the hypothesis that ERP responses during working memory retrieval discriminate aMCI from cognitively normal controls (NC) matched in age and education. Methods: Eighteen NC, 17 subjects with aMCI, and 13 subjects with AD performed a delayed match-to-sample task specially designed not only to be easy enough for impaired participants to complete but also to generate comparable performance between subjects with NC and those with aMCI. Scalp electroencephalography, memory accuracy, and reaction times were measured. Results: Whereas memory performance separated the AD group from the others, the performance of NC and subjects with aMCI was similar. In contrast, left frontal cognitive ERP patterns differentiated subjects with aMCI from NC. Enhanced P3 responses at left frontal sites were associated with nonmatching relative to matching stimuli during working memory tasks in patients with aMCI and AD, but not in NC. The accuracy of discriminating aMCI from NC was 85% by using left frontal match/nonmatch effect combined with nonmatch reaction time. Conclusions: The left frontal cognitive ERP indicator holds promise as a sensitive, simple, affordable, and noninvasive biomarker for detection of early cognitive impairment

Peripheral (Deep) but Not Periventricular MRI White Matter Hyperintensities Are Increased in Clinical Vascular Dementia Compared to Alzheimer\u27s Disease

Background and purpose: Vascular dementia (VAD) is a complex diagnosis at times difficult to distinguish from Alzheimer\u27s disease (AD). MRI scans often show white matter hyperintensities (WMH) in both conditions. WMH increase with age, and both VAD and AD are associated with aging, thus presenting an attribution conundrum. In this study, we sought to show whether the amount of WMH in deep white matter (dWMH), versus periventricular white matter (PVH), would aid in the distinction between VAD and AD, independent of age. Methods: Blinded semiquantitative ratings of WMH validated by objective quantitation of WMH volume from standardized MRI image acquisitions. PVH and dWMH were rated separately and independently by two different examiners using the Scheltens scale. Receiver operator characteristic (ROC) curves were generated using logistic regression to assess classification of VAD (13 patients) versus AD (129 patients). Clinical diagnoses were made in a specialty memory disorders clinic. Results: Using PVH rating alone, overall classification (area under the ROC curve, AUC) was 75%, due only to the difference in age between VAD and AD patients in our study and not PVH. In contrast, dWMH rating produced 86% classification accuracy with no independent contribution from age. A global Longstreth rating that combines dWMH and PVH gave an 88% AUC. Conclusions: Increased dWMH indicate a higher likelihood of VAD versus AD. Assessment of dWMH on MRI scans using Scheltens and Longstreth scales may aid the clinician in distinguishing the two conditions

Salinity and temperature balances at the SPURS central mooring during fall and winter

Author Posting. © The Oceanography Society, 2015. This article is posted here by permission of The Oceanography Society for personal use, not for redistribution. The definitive version was published in Oceanography 28, no. 1 (2015): 56-65, doi:10.5670/oceanog.2015.06.One part of the Salinity Processes in the Upper-ocean Regional Study (SPURS) field campaign focused on understanding the physical processes affecting the evolution of upper-ocean salinity in the region of climatological maximum sea surface salinity in the subtropical North Atlantic (SPURS-1). An upper-ocean salinity budget provides a useful framework for increasing this understanding. The SPURS-1 program included a central heavily instrumented mooring for making accurate measurements of air-sea surface fluxes, as well as other moorings, Argo floats, and gliders that together formed a dense observational array. Data from this array are used to estimate terms in the upper-ocean salinity and heat budgets during the SPURS-1 campaign, with a focus on the first several months (October 2012 to February 2013) when the surface mixed layer was becoming deeper, fresher, and cooler. Specifically, we examine the salinity and temperature balances for an upper-ocean mixed layer, defined as the layer where the density is within 0.4 kg m–3 of its surface value. The gross features of the evolution of upper-ocean salinity and temperature during this fall/winter season are explained by a combination of evaporation and precipitation at the sea surface, horizontal transport of heat and salt by mixed-layer currents, and vertical entrainment of fresher, cooler fluid into the layer as it deepened. While all of these processes were important in the observed seasonal (fall) freshening at this location in the salinity-maximum region, the variability of salinity on monthly-to-intraseasonal time scales resulted primarily from horizontal advection.J.T. Farrar, A.J. Plueddemann, J.B. Edson, and the deployment of the central mooring were supported by NASA grant NNX11AE84G. L. Rainville, C. Lee, C. Eriksen, and the Seaglider program were supported by NASA grant NNX11AE78G. R. Schmitt was supported by NSF grant OCE-1129646. B. Hodges and D. Fratantoni were supported by NASA grant NNX11AE82G. The Prawler moorings were funded by PMEL. The data analysis was also supported by NASA grant NNX14AH38G

Mild Cognitive Impairment: Statistical Models of Transition Using Longitudinal Clinical Data

Mild cognitive impairment (MCI) refers to the clinical state between normal cognition and probable Alzheimer's disease (AD), but persons diagnosed with MCI may progress to non-AD forms of dementia, remain MCI until death, or recover to normal cognition. Risk factors for these various clinical changes, which we term “transitions,” may provide targets for therapeutic interventions. Therefore, it is useful to develop new approaches to assess risk factors for these transitions. Markov models have been used to investigate the transient nature of MCI represented by amnestic single-domain and mixed MCI states, where mixed MCI comprised all other MCI subtypes based on cognitive assessments. The purpose of this study is to expand this risk model by including a clinically determined MCI state as an outcome. Analyses show that several common risk factors play different roles in affecting transitions to MCI and dementia. Notably, APOE-4 increases the risk of transition to clinical MCI but does not affect the risk for a final transition to dementia, and baseline hypertension decreases the risk of transition to dementia from clinical MCI

Alzheimer\u27s Biomarkers are Correlated with Brain Connectivity in Older Adults Differentially During Resting and Task States

β-amyloid (Aβ) plaques and tau-related neurodegeneration are pathologic hallmarks of Alzheimer’s disease (AD). The utility of AD biomarkers, including those measured in cerebrospinal fluid (CSF), in predicting future AD risk and cognitive decline is still being refined. Here, we explored potential relationships between functional connectivity (FC) patterns within the default-mode network (DMN), age, CSF biomarkers (Aβ42 and pTau181), and cognitive status in older adults. Multiple measures of FC were explored, including a novel time series-based measure [total interdependence (TI)]. In our sample of 27 cognitively normal older adults, no significant associations were found between levels of Aβ42 or pTau181 and cognitive scores or regional brain volumes. However, we observed several novel relationships between these biomarkers and measures of FC in DMN during both resting-state and a short-term memory task. First, increased connectivity between bilateral anterior middle temporal gyri was associated with higher levels of CSF Aβ42 and Aβ42/pTau181 ratio (reflecting lower AD risk) during both rest and task. Second, increased bilateral parietal connectivity during the short-term memory task, but not during rest, was associated with higher levels of CSF pTau181 (reflecting higher AD risk). Third, increased connectivity between left middle temporal and left parietal cortices during the active task was associated with decreased global cognitive status but not CSF biomarkers. Lastly, we found that our new TI method was more sensitive to the CSF Aβ42-connectivity relationship whereas the traditional cross-correlation method was more sensitive to levels of CSF pTau181 and cognitive status. With further refinement, resting-state connectivity and task-driven connectivity measures hold promise as non-invasive neuroimaging markers of Aβ and pTau burden in cognitively normal older adults