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Traumatic brain injury (TBI) disrupts the blood?brain barrier (BBB), which may exacerbate neuroinflammation post-injury. Few translational studies have examined BBB dysfunction and subsequent neuroinflammation post-TBI in juveniles. We hypothesized that BBB dysfunction positively predicts microglial activation and that vulnerability to BBB dysfunction and associated neuroinflammation are dependent on age at injury. Post-natal day (PND)17 and PND35 rats (n?=?56) received midline fluid percussion injury or sham surgery, and immunoglobulin-G (IgG) stain was quantified as a marker of extravasated blood in the brain and BBB dysfunction. We investigated BBB dysfunction and the microglial response in the hippocampus, hypothalamus, and motor cortex relative to age at injury and days post-injury (DPI; 1, 7, and 25). We measured the morphologies of ionized calcium-binding adaptor molecule 1?labeled microglia using cell body area and perimeter, microglial branch number and length, end-points/microglial cell, and number of microglia. Data were analyzed using generalized hierarchical models. In PND17 rats, TBI increased levels of IgG compared to shams. Independent of age at injury, IgG in TBI rats was higher at 1 and 7 DPI, but resolved by 25 DPI. TBI activated microglia (more cells and fewer end-points) in PND35 rats compared to respective shams. Independent of age at injury, TBI induced morphological changes indicative of microglial activation, which resolved by 25 DPI. TBI rats had fewer cells and end-points per cell at 1 and 7 DPI than 25 DPI. Independent of TBI, PND17 rats had larger, more activated microglia than PND35 rats; PND17 TBI rats had larger cell body areas and perimeters than PND35 TBI rats. Importantly, we found support in both ages that IgG quantification predicted microglial activation after TBI. The number of microglia increased with increasing IgG, whereas branch length decreased with increasing IgG, which together indicate microglial activation. Our results suggest that stabilization of the BBB after pediatric TBI may be an important therapeutic strategy to limit neuroinflammation and promote recovery.

To investigate microglial mechanisms in central and peripheral inflammation after experimental traumatic brain injury (TBI), we inhibited the colony-stimulating factor-1 receptor (CSF-1R) with PLX5622 (PLX). We hypothesized that microglia depletion would attenuate central inflammation acutely with no effect on peripheral inflammation. After randomization, male mice (n?=?105) were fed PLX or control diets (21 days) and then received midline fluid percussion injury or sham injury. Brain and blood were collected at 1, 3, or 7 days post-injury (DPI). Immune cell populations were quantified in the brain and blood by flow cytometry. Cytokines (interleukin [IL]-6, IL-1?, tumor necrosis factor-?, interferon-?, IL-17A, and IL-10) were quantified in the blood using a multi-plex enzyme-linked immunosorbent assay. Data were analyzed using Bayesian multi-variate, multi-level models. PLX depleted microglia at all time points and reduced neutrophils in the brain at 7 DPI. PLX also depleted CD115+ monocytes, reduced myeloid cells, neutrophils, and Ly6Clow monocytes in blood, and elevated IL-6. TBI induced a central and peripheral immune response. TBI elevated leukocytes, microglia, and macrophages in the brain and elevated peripheral myeloid cells, neutrophils, Ly6Cint monocytes, and IL-1? in the blood. TBI lowered peripheral CD115+ and Ly6Clow monocytes in the blood. TBI PLX mice had fewer leukocytes and microglia in the brain at 1 DPI, with elevated neutrophils at 7 DPI compared to TBI mice on a control diet. TBI PLX mice also had fewer peripheral myeloid cells, CD115+, and Ly6Clow monocytes in the blood at 3 DPI, but elevated Ly6Chigh, Ly6Cint, and CD115+ monocyte populations at 7 DPI, compared to TBI mice on a control diet. TBI PLX mice had elevated proinflammatory cytokines and lower anti-inflammatory cytokines in the blood at 7 DPI compared to TBI mice on a control diet. CSF-1R inhibition reduced the immune response to TBI at 1 and 3 DPI, but elevated peripheral inflammation at 7 DPI.

Evaluating the accuracy and calibration of the redshift posteriors produced by photometric redshift (photo- z ) estimators is vital for enabling precision cosmology and extragalactic astrophysics with modern wide-field photometric surveys. Evaluating photo- z posteriors on a per-galaxy basis is difficult, however, as real galaxies have a true redshift but not a true redshift posterior. We introduce PZFlow, a Python package for the probabilistic forward modeling of galaxy catalogs with normalizing flows. For catalogs simulated with PZFlow, there is a natural notion of “true” redshift posteriors that can be used for photo- z validation. We use PZFlow to simulate a photometric galaxy catalog where each galaxy has a redshift, noisy photometry, shape information, and a true redshift posterior. We also demonstrate the use of an ensemble of normalizing flows for photo- z estimation. We discuss how PZFlow will be used to validate the photo- z estimation pipeline of the Dark Energy Science Collaboration, and the wider applicability of PZFlow for statistical modeling of any tabular data.

We present a detailed study of the observational biases of the DECam Ecliptic Exploration Project’s B1 data release and survey simulation software that enables direct statistical comparisons between models and our data. We inject a synthetic population of objects into the images, and then subsequently recover them in the same processing as our real detections. This enables us to characterize the survey’s completeness as a function of apparent magnitudes and on-sky rates of motion. We study the statistically optimal functional form for the magnitude, and develop a methodology that can estimate the magnitude and rate efficiencies for all survey’s pointing groups simultaneously. We have determined that our peak completeness is on average 80% in each pointing group, and our magnitude drops to 25% of this value at m _25 = 26.22. We describe the freely available survey simulation software and its methodology. We conclude by using it to infer that our effective search area for objects at 40 au is 14.8 deg ^2 , and that our lack of dynamically cold distant objects means that there at most 8 × 10 ^3 objects with 60 < a < 80 au and absolute magnitudes H ≤ 8.

We present the first set of trans-Neptunian objects (TNOs) observed on multiple nights in data taken from the DECam Ecliptic Exploration Project. Of these 110 TNOs, 105 do not coincide with previously known TNOs and appear to be new discoveries. Each individual detection for our objects resulted from a digital tracking search at TNO rates of motion, using two-to-four-hour exposure sets, and the detections were subsequently linked across multiple observing seasons. This procedure allows us to find objects with magnitudes m _VR ≈ 26. The object discovery processing also included a comprehensive population of objects injected into the images, with a recovery and linking rate of at least 94%. The final orbits were obtained using a specialized orbit-fitting procedure that accounts for the positional errors derived from the digital tracking procedure. Our results include robust orbits and magnitudes for classical TNOs with absolute magnitudes H ∼ 10, as well as a dynamically detached object found at 76 au (semimajor axis a ≈ 77 au). We find a disagreement between our population of classical TNOs and the CFEPS-L7 three-component model for the Kuiper Belt.

The DECam Ecliptic Exploration Project (DEEP) is a deep survey of the trans-Neptunian solar system being carried out on the 4 m Blanco telescope at the Cerro Tololo Inter-American Observatory in Chile using the Dark Energy Camera (DECam). By using a shift-and-stack technique to achieve a mean limiting magnitude of r ∼ 26.2, DEEP achieves an unprecedented combination of survey area and depth, enabling quantitative leaps forward in our understanding of the Kuiper Belt populations. This work reports results from an analysis of 20, 3 deg ^2 DECam fields along the invariable plane. We characterize the efficiency and false-positive rates for our moving-object detection pipeline, and use this information to construct a Bayesian signal probability for each detected source. This procedure allows us to treat all of our Kuiper Belt object (KBO) detections statistically, simultaneously accounting for efficiency and false positives. We detect approximately 2300 candidate sources with KBO-like motion with signal-to-noise ratios > 6.5. We use a subset of these objects to compute the luminosity function of the Kuiper Belt as a whole, as well as the cold classical (CC) population. We also investigate the absolute magnitude ( H ) distribution of the CCs, and find consistency with both an exponentially tapered power law, which is predicted by streaming instability models of planetesimal formation, and a rolling power law. Finally, we provide an updated mass estimate for the CC Kuiper Belt of ${M}_{{CC}}({H}_{r}\lt 12)\,=\,{0.0017}_{-0.0004}^{+0.0010}{M}_{\oplus }$ , assuming albedo p = 0.15 and density ρ = 1 g cm ^−3 .

The Vera C. Rubin Observatory will, over a period of 10 yr, repeatedly survey the southern sky. To ensure that images generated by Rubin meet the quality requirements for precision science, the observatory will use an active-optics system (AOS) to correct for alignment and mirror surface perturbations introduced by gravity and temperature gradients in the optical system. To accomplish this, Rubin will use out-of-focus images from sensors located at the edge of the focal plane to learn and correct for perturbations to the wave front. We have designed and integrated a deep-learning (DL) model for wave-front estimation into the AOS pipeline. In this paper, we compare the performance of this DL approach to Rubin’s baseline algorithm when applied to images from two different simulations of the Rubin optical system. We show the DL approach is faster and more accurate, achieving the atmospheric error floor both for high-quality images and low-quality images with heavy blending and vignetting. Compared to the baseline algorithm, the DL model is 40× faster, the median error 2× better under ideal conditions, 5× better in the presence of vignetting by the Rubin camera, and 14× better in the presence of blending in crowded fields. In addition, the DL model surpasses the required optical quality in simulations of the AOS closed loop. This system promises to increase the survey area useful for precision science by up to 8%. We discuss how this system might be deployed when commissioning and operating Rubin.

Abstract For workplaces which cannot operate as telework or remotely, there is a critical need for routine occupational SARS-CoV-2 diagnostic testing. Although diagnostic tests including the CDC 2019-Novel Coronavirus (2019-nCoV) Real-Time RT-PCR Diagnostic Panel (CDC Diagnostic Panel) (EUA200001) were made available early in the pandemic, resource scarcity and high demand for reagents and equipment necessitated priority of symptomatic patients. There is a clearly defined need for flexible testing methodologies and strategies with rapid turnaround of results for (1) symptomatic, (2) asymptomatic with high-risk exposures and (3) asymptomatic populations without preexisting conditions for routine screening to address the needs of an on-site work force. We developed a distinct SARS-CoV-2 diagnostic assay based on the original CDC Diagnostic Panel (EUA200001), yet, with minimum overlap for currently employed reagents to eliminate direct competition for limited resources. As the pandemic progressed with testing loads increasing, we modified the assay to include 5-sample pooling and amplicon target multiplexing. Analytical sensitivity of the pooled and multiplexed assays was rigorously tested with contrived positive samples in realistic patient backgrounds. Assay performance was determined with clinical samples previously assessed with an FDA authorized assay. Throughout the pandemic we successfully tested symptomatic, known contact and travelers within our occupational population with a ~ 24–48-h turnaround time to limit the spread of COVID-19 in the workplace. Our singleplex assay had a detection limit of 31.25 copies per reaction. The three-color multiplexed assay maintained similar sensitivity to the singleplex assay, while tripling the throughput. The pooling assay further increased the throughput to five-fold the singleplex assay, albeit with a subtle loss of sensitivity. We subsequently developed a hybrid ‘multiplex-pooled’ strategy to testing to address the need for both rapid analysis of samples from personnel at high risk of COVID infection and routine screening. Herein, our SARS-CoV-2 assays specifically address the needs of occupational healthcare for both rapid analysis of personnel at high-risk of infection and routine screening that is essential for controlling COVID-19 disease transmission. In addition to SARS-CoV-2 and COVID-19, this work demonstrates successful flexible assays developments and deployments with implications for emerging highly transmissible diseases and future pandemics.

Traumatic brain injury (TBI) survivors suffer from a range of morbidities, including post-traumatic endocrinopathies that can cause physical and mental changes in patients, greatly compromising quality of life. This study tested the hypothesis that mild and moderate diffuse TBI leads to chronic deficiencies in corticosterone (CORT) regulation following repeated exposure to restraint stress over time. Young adult male rats (n?=?9?11/group) were subjected to mild or moderate TBI induced by midline fluid percussion injury (mFPI) or control sham surgery. At 6 and 24?h post-injury, both mild and moderate TBI resulted in elevated resting plasma CORT levels compared with uninjured shams. Independent of TBI severity, all rats had lower resting plasma CORT levels at 7, 14, 28, and 54 days post-injury compared with pre-surgery baseline CORT. Circulating levels of CORT were also evaluated under restraint stress and in response to dexamethasone (DEX), a synthetic glucocorticoid. Independent of TBI severity, restraint stress elevated CORT at 30, 60, and 90?min post-stressor initiation at all post-injury time-points. A blunted CORT response to restraint stress was observed with lower CORT levels after restraint at 28 and 54 days compared with 7 days post-injury (DPI), indicative of habituation to the stressor. A high dose of DEX lowered CORT levels at 90?min post-restraint stress initiation compared with low-dose DEX, independent of TBI severity. These results support TBI-induced CORT dysregulation at acute time-points, but additional studies that investigate the onset and progression of endocrinopathies, controlling for habituation to repeated restraint stress, are needed to inform the diagnosis and treatment of such morbidities in TBI survivors.

Few translational studies have examined how age-at-injury affects the glial response to traumatic brain injury (TBI). We hypothesized that rats injured at post-natal day (PND) 17 would exhibit a greater glial response, that would persist into early adulthood, compared to rats injured at PND35. PND17 and PND35 rats (n = 75) received a mild to moderate midline fluid percussion injury or sham surgery. In three cortical regions [peri-injury, primary somatosensory barrel field (S1BF), perirhinal], we investigated the glial response relative to age-at-injury (PND17 or PND35), time post-injury (2 hours, 1 day, 7 days, 25 days, or 43 days), and post-natal age, such that rats injured at PND17 or PND35 were compared at the same post-natal-age (e.g., PND17 + 25D post-injury = PND42; PND35 + 7D post-injury = PND42). We measured Iba1 positive microglia cells (area, perimeter) and quantified their activation status using skeletal analysis (branch length/cell, mean processes/cell, cell abundance). GFAP expression was examined using immunohistochemistry and pixel analysis. Data were analyzed using Bayesian multivariate multi-level models. Independent of age-at-injury, TBI activated microglia (shorter branches, fewer processes) in the S1BF and perirhinal cortex with more microglia in all regions compared to uninjured shams. TBI-induced microglial activation (shorter branches) was sustained in the S1BF into early adulthood (PND60). Overall, PND17 injured rats had more microglial activation in the perirhinal cortex than PND35 injured rats. Activation was not confounded by age-dependent cell size changes, and microglial cell body sizes were similar between PND17 and PND35 rats. There were no differences in astrocyte GFAP expression. Increased microglial activation in PND17 brain-injured rats suggests that TBI upregulates the glial response at discrete stages of development. Age-at-injury and aging with an injury are translationally important because experiencing a TBI at an early age may trigger an exaggerated glial response.

Microglia play a critical role in the neuroimmune response, but little is known about the role of microglia in sleep following an inflammatory trigger. Nevertheless, decades of research have been predicated on the assumption that an inflammatory trigger increases sleep through microglial activation. We hypothesized that mice (n = 30) with depleted microglia using PLX5622 (PLX) would sleep less following the administration of lipopolysaccharide (LPS) to induce inflammation. Brains were collected and microglial morphology was assessed using quantitative skeletal analyses and physiological parameters were recorded using non-invasive piezoelectric cages. Mice fed PLX diet had a transient increase in sleep that dissipated by week 2. Subsequently, following a first LPS injection (0.4 mg/kg), mice with depleted microglia slept more than mice on the control diet. All mice were returned to normal rodent chow to repopulate microglia in the PLX group (10 days). Nominal differences in sleep existed during the microglia repopulation period. However, following a second LPS injection, mice with repopulated microglia slept similarly to control mice during the dark period but with longer bouts during the light period. Comparing sleep after the first LPS injection to sleep after the second LPS injection, controls exhibited temporal changes in sleep patterns but no change in cumulative minutes slept, whereas cumulative sleep in mice with repopulated microglia decreased during the dark period across all days. Repopulated microglia had a reactive morphology. We conclude that microglia are necessary to regulate sleep after an immune challenge.

The objective of this study was to determine the prevalence of sleep-wake disturbances (SWD) following pediatric traumatic brain injury (TBI), and to examine characteristics of TBI and patient demographics that might be predictive of subsequent SWD development. This single-institution retrospective study included patients diagnosed with a TBI during 2008–2019 who also had a subsequent diagnosis of an SWD. Data were collected using ICD-9/10 codes for 207 patients and included the following: age at initial TBI, gender, TBI severity, number of TBIs diagnosed prior to SWD diagnosis, type of SWD, and time from initial TBI to SWD diagnosis. Multinomial logit and negative-binomial models were fit to investigate whether the multiple types of SWD and the time to onset of SWD following TBI could be predicted by patient variables. Distributions of SWD diagnosed after TBI were similar between genders. The probability of insomnia increased with increasing patient age. The probability of ‘difficulty sleeping’ was highest in 7–9 year-old TBI patients. Older TBI patients had shorter time to SWD onset than younger patients. Patients with severe TBI had the shortest time to SWD onset, whereas patients with mild or moderate TBI had comparable times to SWD onset. Multiple TBI characteristics and patient demographics were predictive of a subsequent SWD diagnosis in the pediatric population. This is an important step toward increasing education among providers, parents, and patients about the risk of developing SWD following TBI.

Traumatic brain injury (TBI) and Alzheimer’s disease (AD) are diseases during which the fine-tuned autoregulation of the brain is lost. Despite the stark contrast in their causal mechanisms, both TBI and AD are conditions which elicit a neuroinflammatory response that is coupled with physical, cognitive, and affective symptoms. One commonly reported symptom in both TBI and AD patients is disturbed sleep. Sleep is regulated by circadian and homeostatic processes such that pathological inflammation may disrupt the chemical signaling required to maintain a healthy sleep profile. In this way, immune system activation can influence sleep physiology. Conversely, sleep disturbances can exacerbate symptoms or increase the risk of inflammatory/neurodegenerative diseases. Both TBI and AD are worsened by a chronic pro-inflammatory microenvironment which exacerbates symptoms and worsens clinical outcome. Herein, a positive feedback loop of chronic inflammation and sleep disturbances is initiated. In this review, the bidirectional relationship between sleep disturbances and inflammation is discussed, where chronic inflammation associated with TBI and AD can lead to sleep disturbances and exacerbated neuropathology. The role of microglia and cytokines in sleep disturbances associated with these diseases is highlighted. The proposed sleep and inflammation-mediated link between TBI and AD presents an opportunity for a multifaceted approach to clinical intervention.

Traumatic brain injury (TBI) in children can result in long-lasting social, cognitive, and neurological impairments. In adults, TBI can lead to endocrinopathies (endocrine system disorders), but this is infrequently reported in children. Untreated endocrinopathies can elevate risks of subsequent health issues, such that early detection in pediatric TBI survivors can initiate clinical interventions. To understand the risk of endocrinopathies following pediatric TBI, we identified patients who had experienced a TBI and subsequently developed a new-onset hypothalamic regulated endocrinopathy (n = 498). We hypothesized that pediatric patients who were diagnosed with a TBI were at higher risk of being diagnosed with a central endocrinopathy than those without a prior diagnosis of TBI. In our epidemiological assessment, we identified pediatric patients enrolled in the Arizona Health Care Cost Containment System (AHCCCS) from 2008 to 2014 who were diagnosed with one of 330 TBI International Classification of Diseases (ICD)-9 codes and subsequently diagnosed with one of 14 central endocrinopathy ICD-9 codes. Additionally, the ICD-9 code data from over 600,000 Arizona pediatric patients afforded an estimate of the incidence, prevalence, relative risk, odds ratio, and number needed to harm, regarding the development of a central endocrinopathy after sustaining a TBI in Arizona Medicaid pediatric patients. Children with a TBI diagnosis had 3.22 times the risk of a subsequent central endocrine diagnosis compared with the general population (±0.28). Pediatric AHCCCS patients with a central endocrine diagnosis had 3.2-fold higher odds of a history of a TBI diagnosis than those without an endocrine diagnosis (±0.29). Furthermore, the number of patients with a TBI diagnosis for one patient to receive a diagnosis of a central endocrine diagnosis was 151.2 (±6.12). Female subjects were more likely to present with a central endocrine diagnosis after a TBI diagnosis compared to male subjects (64.1 vs. 35.9%). These results are the first state-wide epidemiological study conducted to determine the risk of developing a hypothalamic-pituitary disorder after a TBI in the pediatric population. Our results contribute to a body of knowledge demonstrating a TBI etiology for idiopathic endocrine disorders, and thus advise physicians with regard to TBI follow-up care that includes preventive screening for endocrine disorders.

This paper presents a new optical imaging survey of four deep drilling fields (DDFs), two Galactic and two extragalactic, with the Dark Energy Camera (DECam) on the 4-m Blanco telescope at the Cerro Tololo Inter-American Observatory (CTIO). During the first year of observations in 2021, >4000 images covering 21 deg2 (seven DECam pointings), with ∼40 epochs (nights) per field and 5 to 6 images per night per filter in g, r, i, and/or z have become publicly available (the proprietary period for this program is waived). We describe the real-Time difference-image pipeline and how alerts are distributed to brokers via the same distribution system as the Zwicky Transient Facility (ZTF). In this paper, we focus on the two extragalactic deep fields (COSMOS and ELAIS-S1) characterizing the detected sources, and demonstrating that the survey design is effective for probing the discovery space of faint and fast variable and transient sources. We describe and make publicly available 4413 calibrated light curves based on difference-image detection photometry of transients and variables in the extragalactic fields. We also present preliminary scientific analysis regarding the Solar system small bodies, stellar flares and variables, Galactic anomaly detection, fast-rising transients and variables, supernovae, and active Galactic nuclei.

We describe the simulated sky survey underlying the second data challenge (DC2) carried out in preparation for analysis of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) by the LSST Dark Energy Science Collaboration (LSST DESC). Significant connections across multiple science domains will be a hallmark of LSST; the DC2 program represents a unique modeling effort that stresses this interconnectivity in a way that has not been attempted before. This effort encompasses a full end-to-end approach: starting from a large N-body simulation, through setting up LSST-like observations including realistic cadences, through image simulations, and finally processing with Rubin's LSST Science Pipelines. This last step ensures that we generate data products resembling those to be delivered by the Rubin Observatory as closely as is currently possible. The simulated DC2 sky survey covers six optical bands in a wide-fast-deep area of approximately 300 deg2, as well as a deep drilling field of approximately 1 deg2. We simulate 5 yr of the planned 10 yr survey. The DC2 sky survey has multiple purposes. First, the LSST DESC working groups can use the data set to develop a range of DESC analysis pipelines to prepare for the advent of actual data. Second, it serves as a realistic test bed for the image processing software under development for LSST by the Rubin Observatory. In particular, simulated data provide a controlled way to investigate certain image-level systematic effects. Finally, the DC2 sky survey enables the exploration of new scientific ideas in both static and time domain cosmology.

The use of high-quality simulated sky catalogs is essential for the success of cosmological surveys. The catalogs have diverse applications, such as investigating signatures of fundamental physics in cosmological observables, understanding the effect of systematic uncertainties on measured signals and testing mitigation strategies for reducing these uncertainties, aiding analysis pipeline development and testing, and survey strategy optimization. The list of applications is growing with improvements in the quality of the catalogs and the details that they can provide. Given the importance of simulated catalogs, it is critical to provide rigorous validation protocols that enable both catalog providers and users to assess the quality of the catalogs in a straightforward and comprehensive way. For this purpose, we have developed the DESCQA framework for the Large Synoptic Survey Telescope Dark Energy Science Collaboration as well as for the broader community. The goal of DESCQA is to enable the inspection, validation, and comparison of an inhomogeneous set of synthetic catalogs via the provision of a common interface within an automated framework. In this paper, we present the design concept and first implementation of DESCQA. In order to establish and demonstrate its full functionality we use a set of interim catalogs and validation tests. We highlight several important aspects, both technical and scientific, that require thoughtful consideration when designing a validation framework, including validation metrics and how these metrics impose requirements on the synthetic sky catalogs.