AimsHyperphosphorylated tau neuronal cytoplasmic inclusions (ht‐NCI) are the best protein correlate of clinical decline in Alzheimer's disease (AD). Qualitative evidence identifies ht‐NCI ...accumulating in the isodendritic core before the entorhinal cortex. Here, we used unbiased stereology to quantify ht‐NCI burden in the locus coeruleus (LC) and dorsal raphe nucleus (DRN), aiming to characterize the impact of AD pathology in these nuclei with a focus on early stages.MethodsWe utilized unbiased stereology in a sample of 48 well‐characterized subjects enriched for controls and early AD stages. ht‐NCI counts were estimated in 60‐μm‐thick sections immunostained for p‐tau throughout LC and DRN. Data were integrated with unbiased estimates of LC and DRN neuronal population for a subset of cases.ResultsIn Braak stage 0, 7.9% and 2.6% of neurons in LC and DRN, respectively, harbour ht‐NCIs. Although the number of ht‐NCI+ neurons significantly increased by about 1.9× between Braak stages 0 to I in LC (P = 0.02), we failed to detect any significant difference between Braak stage I and II. Also, the number of ht‐NCI+ neurons remained stable in DRN between all stages 0 and II. Finally, the differential susceptibility to tau inclusions among nuclear subdivisions was more notable in LC than in DRN.ConclusionsLC and DRN neurons exhibited ht‐NCI during AD precortical stages. The ht‐NCI increases along AD progression on both nuclei, but quantitative changes in LC precede DRN changes.
Stereological analysis of tau pathology in the locus coeruleus and dorsal raphe nucleus in early Alzheimer's disease demonstrate that early involvement of brain stem nuclei has important functional implications.
iPTF16geu Goobar, A.; Amanullah, R.; Kulkarni, S. R. ...
Science (American Association for the Advancement of Science),
04/2017, Letnik:
356, Številka:
6335
Journal Article
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We report the discovery of a multiply imaged, gravitationally lensed type Ia supernova, iPTF16geu (SN 2016geu), at redshift z = 0.409. This phenomenon was identified because the light from the ...stellar explosion was magnified more than 50 times by the curvature of space around matter in an intervening galaxy. We used high-spatial-resolution observations to resolve four images of the lensed supernova, approximately 0.3 arc seconds from the center of the foreground galaxy. The observations probe a physical scale of ~1 kiloparsec, smaller than is typical in other studies of extragalactic gravitational lensing. The large magnification and symmetric image configuration imply close alignment between the lines of sight to the supernova and to the lens. The relative magnifications of the four images provide evidence for substructures in the lensing galaxy.
Early observations of Type Ia supernovae (SNe Ia) provide a unique probe of their progenitor systems and explosion physics. Here we report the intermediate Palomar Transient Factory (iPTF) discovery ...of an extraordinarily young SN Ia, iPTF 16abc. By fitting a power law to our early light curve, we infer that first light for the SN, that is, when the SN could have first been detected by our survey, occurred only days before our first detection. In the ∼24 hr after discovery, iPTF 16abc rose by ∼2 mag, featuring a near-linear rise in flux for days. Early spectra show strong C ii absorption, which disappears after ∼7 days. Unlike the extensively observed Type Ia SN 2011fe, the colors of iPTF 16abc are blue and nearly constant in the days after explosion. We show that our early observations of iPTF 16abc cannot be explained by either SN shock breakout and the associated, subsequent cooling or the SN ejecta colliding with a stellar companion. Instead, we argue that the early characteristics of iPTF 16abc, including (i) the rapid, near-linear rise, (ii) the nonevolving blue colors, and (iii) the strong C ii absorption, are the result of either ejecta interaction with nearby, unbound material or vigorous mixing of radioactive 56Ni in the SN ejecta, or a combination of the two. In the next few years, dozens of very young normal SNe Ia will be discovered, and observations similar to those presented here will constrain the white dwarf explosion mechanism.
We present the best 265 sampled R-band light curves of spectroscopically identified Type Ia supernovae (SNe) from the Palomar Transient Factory (PTF; 2009-2012) survey and the intermediate Palomar ...Transient Factory (iPTF; 2013-2017). A model-independent light-curve template is built from our data-set with the purpose to investigate average properties and diversity in our sample. We searched for multiple populations in the light-curve properties using machine learning tools. We also utilized the long history of our light curves, up to 4000 days, to exclude any significant pre- or post- supernova flares. From the shapes of light curves we found the average rise time in the R band to be 16.8&#x2212;0.6+0.5'>16.8 +0.5 −0.6 16.8−0.6+0.5 days. Although PTF/iPTF were single-band surveys, by modelling the residuals of the SNe in the Hubble–Lemaître diagram, we estimate the average colour excess of our sample to be 〈 E ( B − V )〉 ≈ 0.05(2) mag and thus the mean corrected peak brightness to be M R = −19.02 ± 0.02 +5log&#x2061;(H0kms&#x2212;1Mpc&#x2212;1/70)'>+5log(H 0 kms −1 Mpc −1 /70) +5log(H0kms−1Mpc−1/70) mag with only weak dependennce on light–curve shape. The intrinsic scatter is found to be σ R = 0.186 ± 0.033 mag for the redshift range 0.05 < z < 0.1, without colour corrections of individual SNe. Our analysis shows that Malmquist bias becomes very significant at z = 0.13. A similar limitation is expected for the ongoing Zwicky Transient Facility (ZTF) survey using the same telescope, but new camera expressly designed for ZTF.
Interpretation of chest radiographs is a challenging task prone to errors, requiring expert readers. An automated system that can accurately classify chest radiographs may help streamline the ...clinical workflow.
To develop a deep learning-based algorithm that can classify normal and abnormal results from chest radiographs with major thoracic diseases including pulmonary malignant neoplasm, active tuberculosis, pneumonia, and pneumothorax and to validate the algorithm's performance using independent data sets.
This diagnostic study developed a deep learning-based algorithm using single-center data collected between November 1, 2016, and January 31, 2017. The algorithm was externally validated with multicenter data collected between May 1 and July 31, 2018. A total of 54 221 chest radiographs with normal findings from 47 917 individuals (21 556 men and 26 361 women; mean SD age, 51 16 years) and 35 613 chest radiographs with abnormal findings from 14 102 individuals (8373 men and 5729 women; mean SD age, 62 15 years) were used to develop the algorithm. A total of 486 chest radiographs with normal results and 529 with abnormal results (1 from each participant; 628 men and 387 women; mean SD age, 53 18 years) from 5 institutions were used for external validation. Fifteen physicians, including nonradiology physicians, board-certified radiologists, and thoracic radiologists, participated in observer performance testing. Data were analyzed in August 2018.
Deep learning-based algorithm.
Image-wise classification performances measured by area under the receiver operating characteristic curve; lesion-wise localization performances measured by area under the alternative free-response receiver operating characteristic curve.
The algorithm demonstrated a median (range) area under the curve of 0.979 (0.973-1.000) for image-wise classification and 0.972 (0.923-0.985) for lesion-wise localization; the algorithm demonstrated significantly higher performance than all 3 physician groups in both image-wise classification (0.983 vs 0.814-0.932; all P < .005) and lesion-wise localization (0.985 vs 0.781-0.907; all P < .001). Significant improvements in both image-wise classification (0.814-0.932 to 0.904-0.958; all P < .005) and lesion-wise localization (0.781-0.907 to 0.873-0.938; all P < .001) were observed in all 3 physician groups with assistance of the algorithm.
The algorithm consistently outperformed physicians, including thoracic radiologists, in the discrimination of chest radiographs with major thoracic diseases, demonstrating its potential to improve the quality and efficiency of clinical practice.
Aims: Alzheimer's disease (AD) is a progressive and irreversible disease. There is strong evidence that the progression of the phospho‐tau neurofibrillary cytoskeletal changes, rather than the ...β‐amyloid burden, is crucial in determining the severity of the dementia in AD. The Braak and Braak staging system (BB) focuses mainly on the cortical cytoskeletal pathology and classifies this progressive pathology into six stages, spreading from the transentorhinal region to primary cortices. Although it is reported elsewhere that the midbrain's dorsal raphe nucleus (DR), which is connected with those areas of the cerebral cortex undergoing early changes during BB I and II, exhibits AD‐related cytoskeletal pathology, this nucleus has not been considered by the BB. Methods: To determine during which BB stage and how frequently the DR is affected by AD‐related neurofibrillary changes, we studied the DR of 118 well‐characterized individuals of the Brain Bank of the Brazilian Aging Brain Study Group categorized according to the BB. Thirty‐eight of these individuals were staged as BB = 0, and 80 as BB ≥ 1. Results: In all of the BB ≥ 1 individuals (cortical neurofibrillary changes were present at least in the transentorhinal region) and in more than 1/5 of the BB = 0 individuals neurofibrillary changes were detected in the supratrochlear subnucleus of the DR. Conclusions: These observations: (i) support the hypothesis of transneuronal spread of neurofibrillary changes from the DR to its interconnected cortical brain areas; and (ii) indicate that the supratrochlear subnucleus of the DR is affected by neurofibrillary changes before the transentorhinal cortex during the disease process underlying AD.
Abstract
We present a new technique to infer dust locations towards reddened Type Ia supernovae and to help discriminate between an interstellar and a circumstellar origin for the observed ...extinction. Using Monte Carlo simulations, we show that the time evolution of the light-curve shape and especially of the colour excess E(B − V) places strong constraints on the distance between dust and the supernova. We apply our approach to two highly reddened Type Ia supernovae for which dust distance estimates are available in the literature: SN 2006X and SN 2014J. For the former, we obtain a time-variable E(B − V) and from this derive a distance of $27.5^{+9.0}_{-4.9}$ or $22.1^{+6.0}_{-3.8}$ pc depending on whether dust properties typical of the Large Magellanic Cloud (LMC) or the Milky Way (MW) are used. For the latter, instead, we obtain a constant E(B − V) consistent with dust at distances larger than ∼50 and 38 pc for LMC- and MW-type dust, respectively. Values thus extracted are in excellent agreement with previous estimates for the two supernovae. Our findings suggest that dust responsible for the extinction towards these supernovae is likely to be located within interstellar clouds. We also discuss how other properties of reddened Type Ia supernovae – such as their peculiar extinction and polarization behaviour and the detection of variable, blue-shifted sodium features in some of these events – might be compatible with dust and gas at interstellar-scale distances.
We discuss the general framework of a stochastic two-player, hybrid differential game, and we apply it to the modelling of a “match race” between two sailing boats, namely a competition in which the ...goal of both players is to proceed in the windward direction, while trying to slow down the other player. We provide a convergent approximation scheme for the computation of the value function of the game, and we validate the approach on some typical racing scenarios.
Summary Malignant pleural mesothelioma (MPM) is an aggressive tumor with no effective therapy. However PD-L1/PD-1 immunity checkpoint therapies gave encouraging results; TLR3 is a programmed death ...factor, which triggering up-regulates PD-L1. As PD-1/PD-L1 blocking antibodies could restore antitumor immune responses alone or in combination with TLR3 agonists, we investigated PD-L1/PD-1 and TLR3 expressions in MPM to select patients for immunotherapy. Sixty-eight pleural surgical specimens, including 58 MPM (epithelioid, n = 34; biphasic, n = 11; sarcomatoid, n = 13) and 10 benign lesions, were studied. PD-L1 expression was assessed using E1L3N and SP142 clones in tumor cells (TCs) and in tumor-infiltrating lymphocytes (TILs) (positivity threshold of 1%), and compared with overall survival. PD-1, CD3 and CD8 expression by TILs, and TLR3 expression by TCs were analyzed concomitantly. PD-L1 was more expressed by sarcomatoid subtype than by other MPM (62% versus 23% and 9% for E1L3N; 38% versus 11% for SP142) ( P = .01 and .04, respectively). Specificity and sensitivity of E1L3N and SP142 were of 53% and 98%, and 90% and 86%, respectively. PD-L1 expression by TILs and TCs correlated for SP142 ( P = .023), and PD-L1 SP142 expression by TCs was associated with shorter overall survival ( P = .016). TLR3 was expressed in most MPM, but weakly in sarcomatoid MPM. We confirm by comparing two commercially available antibodies that PD-L1 expression is higher in sarcomatoid MPM and correlates with a shorter survival. Whereas TLR3 agonists could be tested in MPM expressing TLR3, the sarcomatoid subtype could benefit from anti–PD-L1/PD-1 therapies alone or in combination.
Using characteristics to treat advection terms in time-dependent PDEs leads to a class of schemes, e.g., semi-Lagrangian and Lagrange–Galerkin schemes, which preserve stability under large Courant ...numbers, and may therefore be appealing in many practical situations. Unfortunately, the need of locating the feet of characteristics may cause a serious drop of efficiency in the case of unstructured space grids, and thus prevent the use of large time-step schemes on complex geometries. In this paper, we perform an in-depth analysis of the main recipes available for characteristic location, and propose a technique to improve the efficiency of this phase, using additional information related to the advecting vector field. This results in a clear improvement of execution times in the unstructured case, thus extending the range of applicability of large time-step schemes.
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