Effects of Home Exercise on Immediate and Delayed Affect and Mood Among Rural Individuals at Risk for Type 2 Diabetes

Physical activity is important for reducing overweight and obesity and related health consequences. This study examined changes in mood following 16 weeks of exercise in a sample of 29 individuals residing in a rural area and at risk for developing Type 2 diabetes mellitus (T2DM). Significant positive mood changes were detected, with moderate to large effect sizes. Assessments also revealed significant delayed postexercise positive emotion changes. These findings extend research on the mood benefits of exercise to individuals residing in rural settings and at risk for T2DM and suggest that to gain a full understanding of the exercise-affect relation, investigators need to assess affect at delayed intervals following exercise

Comparison of Pittsburgh compound B and florbetapir in cross-sectional and longitudinal studies.

IntroductionQuantitative in vivo measurement of brain amyloid burden is important for both research and clinical purposes. However, the existence of multiple imaging tracers presents challenges to the interpretation of such measurements. This study presents a direct comparison of Pittsburgh compound B-based and florbetapir-based amyloid imaging in the same participants from two independent cohorts using a crossover design.MethodsPittsburgh compound B and florbetapir amyloid PET imaging data from three different cohorts were analyzed using previously established pipelines to obtain global amyloid burden measurements. These measurements were converted to the Centiloid scale to allow fair comparison between the two tracers. The mean and inter-individual variability of the two tracers were compared using multivariate linear models both cross-sectionally and longitudinally.ResultsGlobal amyloid burden measured using the two tracers were strongly correlated in both cohorts. However, higher variability was observed when florbetapir was used as the imaging tracer. The variability may be partially caused by white matter signal as partial volume correction reduces the variability and improves the correlations between the two tracers. Amyloid burden measured using both tracers was found to be in association with clinical and psychometric measurements. Longitudinal comparison of the two tracers was also performed in similar but separate cohorts whose baseline amyloid load was considered elevated (i.e., amyloid positive). No significant difference was detected in the average annualized rate of change measurements made with these two tracers.DiscussionAlthough the amyloid burden measurements were quite similar using these two tracers as expected, difference was observable even after conversion into the Centiloid scale. Further investigation is warranted to identify optimal strategies to harmonize amyloid imaging data acquired using different tracers

The Arecibo Legacy Fast ALFA Survey: III. HI Source Catalog of the Northern Virgo Cluster Region

We present the first installment of HI sources extracted from the Arecibo Legacy Fast ALFA (ALFALFA) extragalactic survey, initiated in 2005. Sources have been extracted from 3-D spectral data cubes and then examined interactively to yield global HI parameters. A total of 730 HI detections are catalogued within the solid angle 11h44m < R.A.(J2000) < 14h00m and +12deg < Dec.(J2000) < +16deg, and redshift range -1600 \kms < cz < 18000 \kms. In comparison, the HI Parkes All-Sky Survey (HIPASS) detected 40 HI signals in the same region. Optical counterparts are assigned via examination of digital optical imaging databases. ALFALFA HI detections are reported for three distinct classes of signals: (a) detections, typically with S/N > 6.5; (b) high velocity clouds in the Milky Way or its periphery; and (c) signals of lower S/N (to ~ 4.5) which coincide spatially with an optical object of known similar redshift. Although this region of the sky has been heavily surveyed by previous targeted observations based on optical flux-- or size-- limited samples, 69% of the extracted sources are newly reported HI detections. The resultant positional accuracy of HI sources is 20" (median). The median redshift of the sample is ~7000 \kms and its distribution reflects the known local large scale structure including the Virgo cluster. Several extended HI features are found in the vicinity of the Virgo cluster. A small percentage (6%) of HI detections have no identifiable optical counterpart, more than half of which are high velocity clouds in the Milky Way vicinity; the remaining 17 objects do not appear connected to or associated with any known galaxy.Comment: Astronomical Journal, in pres

The ALMA Interferometric Pipeline Heuristics

We describe the calibration and imaging heuristics developed and deployed in the ALMA interferometric data processing pipeline, as of ALMA Cycle 9. The pipeline software framework is written in Python, with each data reduction stage layered on top of tasks and toolkit functions provided by the Common Astronomy Software Applications package. This framework supports a variety of tasks for observatory operations, including science data quality assurance, observing mode commissioning, and user reprocessing. It supports ALMA and VLA interferometric data along with ALMA and NRO45m single dish data, via different stages and heuristics. In addition to producing calibration tables, calibrated measurement sets, and cleaned images, the pipeline creates a WebLog which serves as the primary interface for verifying the data quality assurance by the observatory and for examining the contents of the data by the user. Following the adoption of the pipeline by ALMA Operations in 2014, the heuristics have been refined through annual development cycles, culminating in a new pipeline release aligned with the start of each ALMA Cycle of observations. Initial development focused on basic calibration and flagging heuristics (Cycles 2-3), followed by imaging heuristics (Cycles 4-5), refinement of the flagging and imaging heuristics with parallel processing (Cycles 6-7), addition of the moment difference analysis to improve continuum channel identification (2020 release), addition of a spectral renormalization stage (Cycle 8), and improvement in low SNR calibration heuristics (Cycle 9). In the two most recent Cycles, 97% of ALMA datasets were calibrated and imaged with the pipeline, ensuring long-term automated reproducibility. We conclude with a brief description of plans for future additions, including self-calibration, multi-configuration imaging, and calibration and imaging of full polarization data.Comment: accepted for publication by Publications of the Astronomical Society of the Pacific, 65 pages, 20 figures, 10 tables, 2 appendice

Relationships between plasma lipids species, gender, risk factors and Alzheimer’s disease

Background: Lipid metabolism is altered in Alzheimer’s disease (AD); however, the relationship between AD risk factors (age, APOE ɛ4, and gender) and lipid metabolism is not well defined. Objective: We investigated whether altered lipid metabolism associated with increased age, gender, and APOE status may contribute to the development of AD by examining these risk factors in healthy controls and also clinically diagnosed AD individuals. Methods: We performed plasma lipidomic profiling (582 lipid species) of the Australian Imaging, Biomarkers and Lifestyle flagship study of aging cohort (AIBL) using liquid chromatography-mass spectrometry. Linear regression and interaction analysis were used to explore the relationship between risk factors and plasma lipid species. Results: We observed strong associations between plasma lipid species with gender and increasing age in cognitively normal individuals. However, APOE ɛ4 was relatively weakly associated with plasma lipid species. Interaction analysis identified differential associations of sphingolipids and polyunsaturated fatty acid esterified lipid species with AD based on age and gender, respectively. These data indicate that the risk associated with age, gender, and APOE ɛ4 may, in part, be mediated by changes in lipid metabolism. Conclusion: This study extends our existing knowledge of the relationship between the lipidome and AD and highlights the complexity of the relationships between lipid metabolism and AD at different ages and between men and women. This has important implications for how we assess AD risk and also for potential therapeutic strategies involving modulation of lipid metabolic pathways

Serum neurofilament dynamics predicts neurodegeneration and clinical progression in presymptomatic Alzheimer's disease

Neurofilament light chain (NfL) is a promising fluid biomarker of disease progression for various cerebral proteopathies. Here we leverage the unique characteristics of the Dominantly Inherited Alzheimer Network and ultrasensitive immunoassay technology to demonstrate that NfL levels in the cerebrospinal fluid (n = 187) and serum (n = 405) are correlated with one another and are elevated at the presymptomatic stages of familial Alzheimer's disease. Longitudinal, within-person analysis of serum NfL dynamics (n = 196) confirmed this elevation and further revealed that the rate of change of serum NfL could discriminate mutation carriers from non-mutation carriers almost a decade earlier than cross-sectional absolute NfL levels (that is, 16.2 versus 6.8 years before the estimated symptom onset). Serum NfL rate of change peaked in participants converting from the presymptomatic to the symptomatic stage and was associated with cortical thinning assessed by magnetic resonance imaging, but less so with amyloid-β deposition or glucose metabolism (assessed by positron emission tomography). Serum NfL was predictive for both the rate of cortical thinning and cognitive changes assessed by the Mini-Mental State Examination and Logical Memory test. Thus, NfL dynamics in serum predict disease progression and brain neurodegeneration at the early presymptomatic stages of familial Alzheimer's disease, which supports its potential utility as a clinically useful biomarker

Airway sizes and proportions in children quantified by a video-bronchoscopic technique

Background: A quantitative understanding of airway sizes and proportions and a reference point for comparisons are important to a bronchoscopist. The aims of this study were to measure large airway areas, and define proportions and predictors of airway size in children. Methods: A validated videobronchoscope technique was used to measure in-vivo airway cross-sectional areas (cricoid, right (RMS) and left (LMS) main stem and major lobar bronchi) of 125 children. Airway proportions were calculated as ratios of airways to cricoid areas and to endotracheal tube (ETT) areas. Mann Whitney U, T-tests, and one-way ANOVA were used for comparisons and standard univariate and backwards, stepwise multivariate regression analyses were used to define airway size predictors. Results: Airways size increased progressively with increasing age but proportions remained constant. The LMS was 21% smaller than the RMS. Gender differences in airways' size were not significant in any age group or airway site. Cricoid area related best to body length (BL): cricoid area (mm2) = 26.782 + 0.254*BL (cm) while the RMS and LMS area related best to weight: RMS area (mm2) = 23.938 + 0.394*Wt (kg) and LMS area (mm2) = 20.055 + 0.263*Wt (kg) respectively. Airways to cricoid ratios were larger than airway to ETT ratios (p=0.0001). Conclusions: The cricoid and large airways progressively increase in size but maintain constant proportional relationships to the cricoid across childhood. The cricoid area correlates with body length while the RMS and LMS are best predicted by weight. These data provide for quantitative comparisons of airway lesions

Concordant peripheral lipidome signatures in two large clinical studies of Alzheimer’s disease

© 2020, The Author(s). Changes to lipid metabolism are tightly associated with the onset and pathology of Alzheimer’s disease (AD). Lipids are complex molecules comprising many isomeric and isobaric species, necessitating detailed analysis to enable interpretation of biological significance. Our expanded targeted lipidomics platform (569 species across 32 classes) allows for detailed lipid separation and characterisation. In this study we examined peripheral samples of two cohorts (AIBL, n = 1112 and ADNI, n = 800). We are able to identify concordant peripheral signatures associated with prevalent AD arising from lipid pathways including; ether lipids, sphingolipids (notably GM3 gangliosides) and lipid classes previously associated with cardiometabolic disease (phosphatidylethanolamine and triglycerides). We subsequently identified similar lipid signatures in both cohorts with future disease. Lastly, we developed multivariate lipid models that improved classification and prediction. Our results provide a holistic view between the lipidome and AD using a comprehensive approach, providing targets for further mechanistic investigation

Comparing cortical signatures of atrophy between late-onset and autosomal dominant Alzheimer disease

Defining a signature of cortical regions of interest preferentially affected by Alzheimer disease (AD) pathology may offer improved sensitivity to early AD compared to hippocampal volume or mesial temporal lobe alone. Since late-onset Alzheimer disease (LOAD) participants tend to have age-related comorbidities, the younger-onset age in autosomal dominant AD (ADAD) may provide a more idealized model of cortical thinning in AD. To test this, the goals of this study were to compare the degree of overlap between the ADAD and LOAD cortical thinning maps and to evaluate the ability of the ADAD cortical signature regions to predict early pathological changes in cognitively normal individuals. We defined and analyzed the LOAD cortical maps of cortical thickness in 588 participants from the Knight Alzheimer Disease Research Center (Knight ADRC) and the ADAD cortical maps in 269 participants from the Dominantly Inherited Alzheimer Network (DIAN) observational study. Both cohorts were divided into three groups: cognitively normal controls (nADRC = 381; nDIAN = 145), preclinical (nADRC = 153; nDIAN = 76), and cognitively impaired (nADRC = 54; nDIAN = 48). Both cohorts underwent clinical assessments, 3T MRI, and amyloid PET imaging with either 11C-Pittsburgh compound B or 18F-florbetapir. To generate cortical signature maps of cortical thickness, we performed a vertex-wise analysis between the cognitively normal controls and impaired groups within each cohort using six increasingly conservative statistical thresholds to determine significance. The optimal cortical map among the six statistical thresholds was determined from a receiver operating characteristic analysis testing the performance of each map in discriminating between the cognitively normal controls and preclinical groups. We then performed within-cohort and cross-cohort (e.g. ADAD maps evaluated in the Knight ADRC cohort) analyses to examine the sensitivity of the optimal cortical signature maps to the amyloid levels using only the cognitively normal individuals (cognitively normal controls and preclinical groups) in comparison to hippocampal volume. We found the optimal cortical signature maps were sensitive to early increases in amyloid for the asymptomatic individuals within their respective cohorts and were significant beyond the inclusion of hippocampus volume, but the cortical signature maps performed poorly when analyzing across cohorts. These results suggest the cortical signature maps are a useful MRI biomarker of early AD-related neurodegeneration in preclinical individuals and the pattern of decline differs between LOAD and ADAD.Fil: Dincer, Aylin. Washington University in St. Louis; Estados UnidosFil: Gordon, Brian A.. Washington University in St. Louis; Estados UnidosFil: Hari-Raj, Amrita. Ohio State University; Estados UnidosFil: Keefe, Sarah J.. Washington University in St. Louis; Estados UnidosFil: Flores, Shaney. Washington University in St. Louis; Estados UnidosFil: McKay, Nicole S.. Washington University in St. Louis; Estados UnidosFil: Paulick, Angela M.. Washington University in St. Louis; Estados UnidosFil: Shady Lewis, Kristine E.. University of Kentucky; Estados UnidosFil: Feldman, Rebecca L.. Washington University in St. Louis; Estados UnidosFil: Hornbeck, Russ C.. Washington University in St. Louis; Estados UnidosFil: Allegri, Ricardo Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Ances, Beau M.. Washington University in St. Louis; Estados UnidosFil: Berman, Sarah B.. University of Pittsburgh; Estados UnidosFil: Brickman, Adam M.. Columbia University; Estados UnidosFil: Brooks, William S.. Neuroscience Research Australia; Australia. University of New South Wales; AustraliaFil: Cash, David M.. UCL Queen Square Institute of Neurology; Reino UnidoFil: Chhatwal, Jasmeer P.. Harvard Medical School; Estados UnidosFil: Farlow, Martin R.. Indiana University; Estados UnidosFil: Fougère, Christian la. German Center for Neurodegenerative Diseases; Alemania. University Hospital of Tübingen; AlemaniaFil: Fox, Nick C.. UCL Queen Square Institute of Neurology; Reino UnidoFil: Fulham, Michael J.. Royal Prince Alfred Hospital; Australia. University of Sydney; AustraliaFil: Jack, Clifford R.. Mayo Clinic; Estados UnidosFil: Joseph-Mathurin, Nelly. Washington University in St. Louis; Estados UnidosFil: Karch, Celeste M.. Washington University in St. Louis; Estados UnidosFil: Lee, Athene. University Brown; Estados UnidosFil: Levin, Johannes. German Center for Neurodegenerative Diseases; Alemania. Ludwig Maximilians Universitat; Alemania. Munich Cluster for Systems Neurology; AlemaniaFil: Masters, Colin L.. University of Melbourne; AustraliaFil: McDade, Eric M.. Washington University in St. Louis; Estados UnidosFil: Oh, Hwamee. University Brown; Estados UnidosFil: Perrin, Richard J.. Washington University in St. Louis; Estados Unido

The Eighth Data Release of the Sloan Digital Sky Survey: First Data from SDSS-III

The Sloan Digital Sky Survey (SDSS) started a new phase in August 2008, with new instrumentation and new surveys focused on Galactic structure and chemical evolution, measurements of the baryon oscillation feature in the clustering of galaxies and the quasar Ly alpha forest, and a radial velocity search for planets around ~8000 stars. This paper describes the first data release of SDSS-III (and the eighth counting from the beginning of the SDSS). The release includes five-band imaging of roughly 5200 deg^2 in the Southern Galactic Cap, bringing the total footprint of the SDSS imaging to 14,555 deg^2, or over a third of the Celestial Sphere. All the imaging data have been reprocessed with an improved sky-subtraction algorithm and a final, self-consistent photometric recalibration and flat-field determination. This release also includes all data from the second phase of the Sloan Extension for Galactic Understanding and Evolution (SEGUE-2), consisting of spectroscopy of approximately 118,000 stars at both high and low Galactic latitudes. All the more than half a million stellar spectra obtained with the SDSS spectrograph have been reprocessed through an improved stellar parameters pipeline, which has better determination of metallicity for high metallicity stars.Comment: Astrophysical Journal Supplements, in press (minor updates from submitted version