A Cross-Correlation Analysis of Mg II Absorption Line Systems and Luminous Red Galaxies from the SDSS DR5

We analyze the cross-correlation of 2,705 unambiguously intervening Mg II (2796,2803A) quasar absorption line systems with 1,495,604 luminous red galaxies (LRGs) from the Fifth Data Release of the Sloan Digital Sky Survey within the redshift range 0.36<=z<=0.8. We confirm with high precision a previously reported weak anti-correlation of equivalent width and dark matter halo mass, measuring the average masses to be log M_h(M_[solar]h^-1)=11.29 [+0.36,-0.62] and log M_h(M_[solar]h^-1)=12.70 [+0.53,-1.16] for systems with W[2796A]>=1.4A and 0.8A<=W[2796A]<1.4A, respectively. Additionally, we investigate the significance of a number of potential sources of bias inherent in absorber-LRG cross-correlation measurements, including absorber velocity distributions and the weak lensing of background quasars, which we determine is capable of producing a 20-30% bias in angular cross-correlation measurements on scales less than 2'. We measure the Mg II - LRG cross-correlation for 719 absorption systems with v<60,000 km s^-1 in the quasar rest frame and find that these associated absorbers typically reside in dark matter haloes that are ~10-100 times more massive than those hosting unambiguously intervening Mg II absorbers. Furthermore, we find evidence for evolution of the redshift number density, dN/dz, with 2-sigma significance for the strongest (W>2.0A) absorbers in the DR5 sample. This width-dependent dN/dz evolution does not significantly affect the recovered equivalent width-halo mass anti-correlation and adds to existing evidence that the strongest Mg II absorption systems are correlated with an evolving population of field galaxies at z<0.8, while the non-evolving dN/dz of the weakest absorbers more closely resembles that of the LRG population.Comment: 21 pages, 19 figures; Published in Astrophysical Journa

Quasar Clustering from SDSS DR5: Dependences on Physical Properties

Using a homogenous sample of 38,208 quasars with a sky coverage of $4000 {\rm deg^2}$ drawn from the SDSS Data Release Five quasar catalog, we study the dependence of quasar clustering on luminosity, virial black hole mass, quasar color, and radio loudness. At $z<2.5$, quasar clustering depends weakly on luminosity and virial black hole mass, with typical uncertainty levels $\sim 10$ for the measured correlation lengths. These weak dependences are consistent with models in which substantial scatter between quasar luminosity, virial black hole mass and the host dark matter halo mass has diluted any clustering difference, where halo mass is assumed to be the relevant quantity that best correlates with clustering strength. However, the most luminous and most massive quasars are more strongly clustered (at the $\sim 2\sigma$ level) than the remainder of the sample, which we attribute to the rapid increase of the bias factor at the high-mass end of host halos. We do not observe a strong dependence of clustering strength on quasar colors within our sample. On the other hand, radio-loud quasars are more strongly clustered than are radio-quiet quasars matched in redshift and optical luminosity (or virial black hole mass), consistent with local observations of radio galaxies and radio-loud type 2 AGN. Thus radio-loud quasars reside in more massive and denser environments in the biased halo clustering picture. Using the Sheth et al.(2001) formula for the linear halo bias, the estimated host halo mass for radio-loud quasars is $\sim 10^{13} h^{-1}M_\odot$, compared to $\sim 2\times 10^{12} h^{-1}M_\odot$ for radio-quiet quasar hosts at $z\sim 1.5$.Comment: Updated version; accepted for publication in Ap

A simplified multiple-retrieving small-bowel biopsy tube

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/44440/1/10620_2005_Article_BF02231909.pd

Researching COVID to enhance recovery (RECOVER) tissue pathology study protocol: Rationale, objectives, and design.

ImportanceSARS-CoV-2 infection can result in ongoing, relapsing, or new symptoms or organ dysfunction after the acute phase of infection, termed Post-Acute Sequelae of SARS-CoV-2 (PASC), or long COVID. The characteristics, prevalence, trajectory and mechanisms of PASC are poorly understood. The objectives of the Researching COVID to Enhance Recovery (RECOVER) tissue pathology study (RECOVER-Pathology) are to: (1) characterize prevalence and types of organ injury/disease and pathology occurring with PASC; (2) characterize the association of pathologic findings with clinical and other characteristics; (3) define the pathophysiology and mechanisms of PASC, and possible mediation via viral persistence; and (4) establish a post-mortem tissue biobank and post-mortem brain imaging biorepository.MethodsRECOVER-Pathology is a cross-sectional study of decedents dying at least 15 days following initial SARS-CoV-2 infection. Eligible decedents must meet WHO criteria for suspected, probable, or confirmed infection and must be aged 18 years or more at the time of death. Enrollment occurs at 7 sites in four U.S. states and Washington, DC. Comprehensive autopsies are conducted according to a standardized protocol within 24 hours of death; tissue samples are sent to the PASC Biorepository for later analyses. Data on clinical history are collected from the medical records and/or next of kin. The primary study outcomes include an array of pathologic features organized by organ system. Causal inference methods will be employed to investigate associations between risk factors and pathologic outcomes.DiscussionRECOVER-Pathology is the largest autopsy study addressing PASC among US adults. Results of this study are intended to elucidate mechanisms of organ injury and disease and enhance our understanding of the pathophysiology of PASC

The status of digital pathology and associated infrastructure within Alzheimer's Disease Centers.

Digital pathology (DP) has transformative potential, especially for Alzheimer disease and related disorders. However, infrastructure barriers may limit adoption. To provide benchmarks and insights into implementation barriers, a survey was conducted in 2019 within National Institutes of Health's Alzheimer's Disease Centers (ADCs). Questions covered infrastructure, funding sources, and data management related to digital pathology. Of the 35 ADCs to which the survey was sent, 33 responded. Most respondents (81%) stated that their ADC had digital slide scanner access, with the most frequent brand being Aperio/Leica (62.9%). Approximately a third of respondents stated there were fees to utilize the scanner. For DP and machine learning (ML) resources, 41% of respondents stated none was supported by their ADC. For scanner purchasing and operations, 50% of respondents stated they received institutional support. Some were unsure of the file size of scanned digital images (37%) and total amount of storage space files occupied (50%). Most (76%) were aware of other departments at their institution working with ML; a similar (76%) percentage were unaware of multiuniversity or industry partnerships. These results demonstrate many ADCs have access to a digital slide scanner; additional investigations are needed to further understand hurdles to implement DP and ML workflows

A molecular pathology, neurobiology, biochemical, genetic and neuroimaging study of progressive apraxia of speech

Progressive apraxia of speech (PAOS) is a neurodegenerative syndrome of multiple etiologies which affects spoken communication. Here, the authors characterized the molecular pathology, biochemistry, genetics and longitudinal neuroimaging of 32 autopsy-confirmed patients with PAOS who were followed over 10 years