Normal discrimination of spatial frequency and contrast across visual hemifields in left-onset Parkinson’s disease: evidence against perceptual hemifield biases

Individuals with Parkinson's disease (PD) with symptom onset on the left side of the body (LPD) show a mild type of left-sided visuospatial neglect, whereas those with right-onset (RPD) generally do not. The functional mechanisms underlying these observations are unknown. Two hypotheses are that the representation of left-space in LPD is either compressed or reduced in salience. We tested these hypotheses psychophysically. Participants were 31 non-demented adults with PD (15 LPD, 16 RPD) and 17 normal control adults (NC). The spatial compression hypothesis was tested by showing two sinusoidal gratings, side by side. One grating's spatial frequency (SF) was varied across trials, following a staircase procedure, whereas the comparison grating was held at a constant SF. While fixating on a central target, participants estimated the point at which they perceived the two gratings to be equal in SF. The reduced salience hypothesis was tested in a similar way, but by manipulating the contrast of the test grating rather than its SF. There were no significant differences between groups in the degree of bias across hemifields for SF discrimination or for contrast discrimination. Results did not support either the spatial compression hypothesis or the reduced salience hypothesis. Instead, they suggest that at this perceptual level, LPD do not have a systematically biased way of representing space in the left hemifield that differs from healthy individuals, nor do they perceive stimuli on the left as less salient than stimuli on the right. Neglect-like syndrome in LPD instead presumably arises from dysfunction of higher-order attention.Published versio

Dysregulation of visual motion inhibition in major depression

Individuals with depression show depleted concentrations of the inhibitory neurotransmitter GABA in occipital (visual) cortex, predicting weakened inhibition within their visual systems. Yet, visual inhibition in depression remains largely unexplored. To fill this gap, we examined the inhibitory process of centersurround suppression (CSS) of visual motion in depressed individuals. Perceptual performance in discriminating the direction of motion was measured as a function of stimulus presentation time and contrast in depressed individuals (n¼27) and controls (n¼22). CSS was operationalized as the accuracy difference between conditions using large (7.5°) and small (1.5°) grating stimuli. Both depressed and control participants displayed the expected advantage in accuracy for small stimuli at high contrast. A significant interaction emerged between subject group, contrast level and presentation time, indicating that alterations of CSS in depression were modulated by stimulus conditions. At high contrast, depressed individuals showed significantly greater CSS than controls at the 66 ms presentation time (where the effect peaked in both groups). The results' specificity and dependence on stimulus features such as contrast, size and presentation time suggest that they arise from changes in early visual processing, and are not the results of a generalized deficit or cognitive bias.Accepted versio

Functional correlates of optic flow motion processing in Parkinson’s disease

The visual input created by the relative motion between an individual and the environment, also called optic flow, influences the sense of self-motion, postural orientation, veering of gait, and visuospatial cognition. An optic flow network comprising visual motion areas V6, V3A, and MT+, as well as visuo-vestibular areas including posterior insula vestibular cortex (PIVC) and cingulate sulcus visual area (CSv), has been described as uniquely selective for parsing egomotion depth cues in humans. Individuals with Parkinson’s disease (PD) have known behavioral deficits in optic flow perception and visuospatial cognition compared to age- and education-matched control adults (MC). The present study used functional magnetic resonance imaging (fMRI) to investigate neural correlates related to impaired optic flow perception in PD. We conducted fMRI on 40 non-demented participants (23 PD and 17 MC) during passive viewing of simulated optic flow motion and random motion. We hypothesized that compared to the MC group, PD participants would show abnormal neural activity in regions comprising this optic flow network. MC participants showed robust activation across all regions in the optic flow network, consistent with studies in young adults, suggesting intact optic flow perception at the neural level in healthy aging. PD participants showed diminished activity compared to MC particularly within visual motion area MT+ and the visuo-vestibular region CSv. Further, activation in visuo-vestibular region CSv was associated with disease severity. These findings suggest that behavioral reports of impaired optic flow perception and visuospatial performance may be a result of impaired neural processing within visual motion and visuo-vestibular regions in PD.Published versio

VETA-1 x ray detection system

The alignment and X-ray imaging performance of the Advanced X-ray Astrophysics Facility (AXAF) Verification Engineering Test Article-I (VETA-I) was measured by the VETA-I X-Ray Detection System (VXDS). The VXDS was based on the X-ray detection system utilized in the AXAF Technology Mirror Assembly (TMA) program, upgraded to meet the more stringent requirements of the VETA-I test program. The VXDS includes two types of X-ray detectors: (1) a High Resolution Imager (HRI) which provides X-ray imaging capabilities, and (2) sealed and flow proportional counters which, in conjunction with apertures of various types and precision translation stages, provide the most accurate measurement of VETA-I performance. Herein we give an overview of the VXDS hardware including X-ray detectors, translation stages, apertures, proportional counters and flow counter gas supply system and associated electronics. We also describe the installation of the VXDS into the Marshall Space Flight Center (MSFC) X-Ray Calibration Facility (XRCF). We discuss in detail the design and performance of those elements of the VXDS which have not been discussed elsewhere; translation systems, flow counter gas supply system, apertures and thermal monitoring system

Habitat diversity and structure regulate British bird richness: implications of non-linear relationships for conservation

Spatial environmental heterogeneity (EH) is an important factor determining species richness among many taxa across spatial scales. Increased EH may support higher diversity mainly by providing a higher number of ecological niches. However, the shapes of the EH-diversity relationships and their influence on diversity measures at landscape scales are poorly understood. We used random forests regression models to assess the relationships between different components of EH and bird species richness across Great Britain. Bird data were obtained using BTO/JNCC/RSPB Breeding Bird Survey methods across 335 UK Countryside Survey (CS) 1-km squares in 2000. Data on components of EH, including; vegetation, habitat diversity, and habitat structure were collected in associated field surveys. Using the results of our EH component-bird richness models, we applied the case of the likely decline of the ash tree, a species of conservation concern and a key component of British landscape complexity, to create predictive scenarios of future bird richness. We found that EH components had a strong positive effect on bird richness and identified six key components that explained over 70% of variance in bird richness. Bird richness responses were strongly dependent on the specific EH components and were generally non-linear, especially for habitat structural variables, such as lines of trees and hedges. Our predictive scenarios showed a decrease in bird species richness only for simulated ash tree decreases within the habitat structural variables of over 90%, and only for areas where this tree species was a particularly abundant component of the landscape. Our findings, showing that bird richness responses differ for EH components, and that non-linear responses are common, could help the ‘design’ of landscapes that enhance bird diversity. In particular, our study indicates that, in some cases, increasing the occurrence of key structural components of habitat (such as ensuring a minimum of 700 m of managed hedges or a minimum of 70 individual trees per km square), could have disproportionally positive impacts on bird richness

Prey Records for the Eastern Indigo Snake (Drymarchon couperi)

Prey items for the federally protected Eastern Indigo Snake (Drymarchon couperi) were compiled from published and gray literature, field observations, necropsies, dissection of museum specimens, and personal communications from reliable sources. One hundred and eighty-six records were obtained for 48 different prey species. Anurans, Gopher Tortoises, snakes, and rodents comprised ca. 85% of the prey items. Most records (n = 143) that mentioned size were from adult indigos; 17 were from juveniles. Prey records were collected from 1940-2008 and were available for all months of the year. These data confirm that Eastern Indigo Snakes eat a wide assortment of prey of varying sizes. This strategy allows D. couperi to potentially forage successfully in many different types of habitats and under fluctuating environmental conditions, a valuable trait for a top-level predator that requires a large home range

Adaptive immune signature in HER2-positive breast cancer in NCCTG (Alliance) N9831 and NeoALTTO trials

Breast cancer; Predictive markersCáncer de mama; Marcadores predictivosCàncer de mama; Marcadors predictiusTrastuzumab acts in part through the adaptive immune system. Previous studies showed that enrichment of immune-related gene expression was associated with improved outcomes in HER2-positive (HER2+) breast cancer. However, the role of the immune system in response to lapatinib is not fully understood. Gene expression analysis was performed in 1,268 samples from the North Central Cancer Treatment Group (NCCTG) N9831 and 244 samples from the NeoALTTO trial. In N9831, enrichment of CD45 and immune-subset signatures were significantly associated with improved outcomes. We identified a novel 17-gene adaptive immune signature (AIS), which was found to be significantly associated with improved RFS among patients who received adjuvant trastuzumab (HR 0.66, 95% CI 0.49–0.90, Cox regression model p = 0.01) but not in patients who received chemotherapy alone (HR 0.96, 95% CI 0.67–1.40, Cox regression model p = 0.97). This result was validated in NeoALTTO. Overall, AIS-low patients had a significantly lower pathologic complete response (pCR) rate compared with AIS-high patients (χ2 p < 0.0001). Among patients who received trastuzumab alone, pCR was observed in 41.7% of AIS-high patients compared with 9.8% in AIS-low patients (OR of 6.61, 95% CI 2.09–25.59, logistic regression model p = 0.003). More importantly, AIS-low patients had a higher pCR rate with an addition of lapatinib (51.1% vs. 9.8%, OR 9.65, 95% CI 3.24–36.09, logistic regression model p < 0.001). AIS-low patients had poor outcomes, despite receiving adjuvant trastuzumab. However, these patients appear to benefit from an addition of lapatinib. Further studies are needed to validate the significance of this signature to identify patients who are more likely to benefit from dual anti-HER2 therapy. ClinicalTrials.gov Identifiers: NCT00005970 (NCCTG N9831) and NCT00553358 (NeoALTTO).Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under Award Numbers U10CA180882 and U24CA196171 (to the Alliance for Clinical Trials in Oncology); UG1CA233180, UG1CA232760, UG1CA233373, and U10CA180821. https://acknowledgments.alliancefound.org. Also supported in part by funds from the Department of Defense W81XWH-18-1-0562 and −0563 and W81XWH-16-1-0265 and 0266, as well as the Breast Cancer Research Foundation (BCRF-19-161), Bankhead-Coley Research Program (6BC05), Susan G. Komen Foundation (SAC190091), and the DONNA Foundation. The content is solely the authors’ responsibility and does not necessarily represent the official views of the National Institutes of Health. Genentech/Roche supplied trastuzumab for both trials. Presented at the Spotlight Session at San Antonio Breast Cancer Symposium 2016 and the ASCO Annual Meeting 2018. Portions of this paper have been published in abstract form: Journal of Clinical Oncology 36, no. 15_suppl (May 20, 2018) 577

Partnering to promote service continuity in the event of an emergency: a successful collaboration between two interlibrary loan departments

Readers may use articles without permission of copyright owners, as long as the author and MLA are acknowledged and the use is educational and not for profit

A Knowledge Distillation Ensemble Framework for Predicting Short and Long-term Hospitalisation Outcomes from Electronic Health Records Data

The ability to perform accurate prognosis of patients is crucial for proactive clinical decision making, informed resource management and personalised care. Existing outcome prediction models suffer from a low recall of infrequent positive outcomes. We present a highly-scalable and robust machine learning framework to automatically predict adversity represented by mortality and ICU admission from time-series vital signs and laboratory results obtained within the first 24 hours of hospital admission. The stacked platform comprises two components: a) an unsupervised LSTM Autoencoder that learns an optimal representation of the time-series, using it to differentiate the less frequent patterns which conclude with an adverse event from the majority patterns that do not, and b) a gradient boosting model, which relies on the constructed representation to refine prediction, incorporating static features of demographics, admission details and clinical summaries. The model is used to assess a patient's risk of adversity over time and provides visual justifications of its prediction based on the patient's static features and dynamic signals. Results of three case studies for predicting mortality and ICU admission show that the model outperforms all existing outcome prediction models, achieving PR-AUC of 0.891 (95$$ CI: 0.878 - 0.969) in predicting mortality in ICU and general ward settings and 0.908 (95$$ CI: 0.870-0.935) in predicting ICU admission.Comment: 14 page