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Quantification of tissue magnetic susceptibility using MRI offers a non-invasive measure of important tissue components in the brain, such as iron and myelin, potentially providing valuable information about normal and pathological conditions during aging. Despite many advances made in recent years on imaging techniques of quantitative susceptibility mapping (QSM), accurate and robust automated segmentation tools for QSM images that can help generate universal and sharable susceptibility measures in a biologically meaningful set of structures are still not widely available. In the present study, we developed an automated process to segment brain nuclei and quantify tissue susceptibility in these regions based on a susceptibility multi-atlas library, consisting of 10 atlases with T1-weighted images, gradient echo (GRE) magnitude images and QSM images of brains with different anatomic patterns. For each atlas in this library, 10 regions of interest in iron-rich deep gray matter structures that are better defined by QSM contrast were manually labeled, including caudate, putamen, globus pallidus internal/external, thalamus, pulvinar, subthalamic nucleus, substantia nigra, red nucleus and dentate nucleus in both left and right hemispheres. We then tested different pipelines using different combinations of contrast channels to bring the set of labels from the multi-atlases to each target brain and compared them with the gold standard manual delineation. The results showed that the segmentation accuracy using dual contrasts QSM/T1 pipeline outperformed other dual-contrast or single-contrast pipelines. The dice values of 0.77 ± 0.09 using the QSM/T1 multi-atlas pipeline rivaled with the segmentation reliability obtained from multiple evaluators with dice values of 0.79 ± 0.07 and gave comparable or superior performance in segmenting subcortical nuclei in comparison with standard FSL FIRST or recent multi-atlas package of volBrain. The segmentation performance of the QSM/T1 multi-atlas was further tested on QSM images acquired using different acquisition protocols and platforms and showed good reliability and reproducibility with average dice of 0.79 ± 0.08 to manual labels and 0.89 ± 0.04 in an inter-protocol manner. The extracted quantitative magnetic susceptibility values in the deep gray matter nuclei also correlated well between different protocols with inter-protocol correlation constants all larger than 0.97. Such reliability and performance was ultimately validated in an external dataset acquired at another study site with consistent susceptibility measures obtained using the QSM/T1 multi-atlas approach in comparison to those using manual delineation. In summary, we designed a susceptibility multi-atlas tool for automated and reliable segmentation of QSM images and for quantification of magnetic susceptibilities. It is publicly available through our cloud-based platform (www.mricloud.org). Further improvement on the performance of this multi-atlas tool is expected by increasing the number of atlases in the future.

Author(s): J. Ayres [sup.1] [sup.2] [sup.3] , M. Berben [sup.2] [sup.3] , M. Culo [sup.2] [sup.3] [sup.10] , Y.-T. Hsu [sup.2] [sup.3] , E. van Heumen [sup.4] [sup.5] , Y. [...], Strange metals possess highly unconventional electrical properties, such as a linear-in-temperature resistivity.sup.1-6, an inverse Hall angle that varies as temperature squared.sup.7-9 and a linear-in-field magnetoresistance.sup.10-13. Identifying the origin of these collective anomalies has proved fundamentally challenging, even in materials such as the hole-doped cuprates that possess a simple bandstructure. The prevailing consensus is that strange metallicity in the cuprates is tied to a quantum critical point at a doping p* inside the superconducting dome.sup.14,15. Here we study the high-field in-plane magnetoresistance of two superconducting cuprate families at doping levels beyond p*. At all dopings, the magnetoresistance exhibits quadrature scaling and becomes linear at high values of the ratio of the field and the temperature, indicating that the strange-metal regime extends well beyond p*. Moreover, the magnitude of the magnetoresistance is found to be much larger than predicted by conventional theory and is insensitive to both impurity scattering and magnetic field orientation. These observations, coupled with analysis of the zero-field and Hall resistivities, suggest that despite having a single band, the cuprate strange-metal region hosts two charge sectors, one containing coherent quasiparticles, the other scale-invariant 'Planckian' dissipators. Measurements of high-field magnetotransport in overdoped cuprates indicate that the strange-metal regime exists beyond the critical doping, and that it has both coherent and incoherent contributions.

The article "Tetraspanin CD53 Promotes Inflammation but Restrains Mucus Production in a Mouse Model of Allergic Airway Inflammation" explores the role of CD53 in allergic airway disease. The study reveals that CD53 deficiency leads to increased proinflammatory cytokine production in mast cells but reduced airway inflammation in mice. Additionally, CD53 negatively regulates mast cell signaling, cytokine production, and mucus production, highlighting its complex and multifaceted role in asthma. The research suggests that CD53 plays a crucial role in immune cell function and inflammatory responses in allergic airway inflammation. [Extracted from the article]

Background Transitional care programs help improve continuity of care and post-discharge outcomes for frail older adults who are hospitalized. In this study, we examined the effectiveness of a transitional care model, based in a long-term care (LTC) home, on the functional independence of older hospitalized patients post-discharge. Methods We used a propensity-score matched cohort, whereby cases comprised patients who were admitted to a transitional care program--called the Sub-Acute Care for Frail Elderly (SAFE) Unit--following a hospitalization between March 1, 2018 and June 30, 2019. Controls were matched to Usual Care patients discharged from hospitals within the same health region and accrual period who did not receive transitional care in the SAFE Unit. Outcomes included acute care, LTC, and home care use within six-month post-discharge. Results Compared to Usual Care, SAFE Unit patients were less likely to be admitted into an LTC home (RR 0.44, 95% CI 0.23-0.86) within six months post-discharge. Additionally, on average, SAFE Unit patients spent 34 fewer days in LTC homes than controls. SAFE Unit patients also incurred significantly fewer home care service days (median: 52 days, IQR: 12-132 days) than Usual Care patients (median: 65.5 days, IQR: 19-158 days), particularly in terms of their reliance on general nursing and personal support. Both groups had similar risks of six-month hospital readmission and having an ED visit. Conclusion Rehabilitative and restorative-focused care provided through transitional programs, such as the SAFE Unit, have the potential to enable independent living for older hospitalized patients discharged to the community. [ABSTRACT FROM AUTHOR]

We present the results of deep Chandra imaging of the central region of the Extended Groth Strip, the AEGIS-X Deep (AEGIS-XD) survey. When combined with previous Chandra observations of a wider area of the strip, AEGIS-X Wide (AEGIS-XW), these provide data to a nominal exposure depth of 800 ks in the three central ACIS-I fields, a region of approximately 0.29 deg2. This is currently the third deepest X-ray survey in existence; a factor shallower than the Chandra Deep Fields (CDFs), but over an area ∼3 times greater than each CDF. We present a catalog of 937 point sources detected in the deep Chandra observations, along with identifications of our X-ray sources from deep ground-based, Spitzer, GALEX, and Hubble Space Telescope imaging. Using a likelihood ratio analysis, we associate multiband counterparts for 929/937 of our X-ray sources, with an estimated 95% reliability, making the identification completeness approximately 94% in a statistical sense. Reliable spectroscopic redshifts for 353 of our X-ray sources are available predominantly from Keck (DEEP2/3) and MMT Hectospec, so the current spectroscopic completeness is ∼38%. For the remainder of the X-ray sources, we compute photometric redshifts based on multiband photometry in up to 35 bands from the UV to mid-IR. Particular attention is given to the fact that the vast majority the X-ray sources are active galactic nuclei and require hybrid templates. Our photometric redshifts have mean accuracy of and an outlier fraction of approximately 5%, reaching with less than 4% outliers in the area covered by CANDELS . The X-ray, multiwavelength photometry, and redshift catalogs are made publicly available.