Background
Proton pump inhibitors (PPIs) have been known to induce type I hypersensitivity reactions. However, severe delayed‐type hypersensitivity reactions (DHR) induced by PPI, such as ...Stevens‐Johnson syndrome (SJS), toxic epidermal necrolysis (TEN), or drug rash with eosinophilia and systemic symptoms (DRESS), are rarely reported. We conducted a study of a large series of PPI‐related DHR, followed up their tolerability to alternative anti‐ulcer agents, and investigated the T‐cell reactivity to PPI in PPI‐related DHR patients.
Methods
We retrospectively analyzed patients with PPI‐related DHR from multiple medical centers in Taiwan during the study period January 2003 to April 2016. We analyzed the causative PPI, clinical manifestations, organ involvement, treatment, and complications. We also followed up the potential risk of cross‐hypersensitivity or tolerability to other PPI after their hypersensitivity episodes. Drug lymphocyte activation test (LAT) was conducted by measuring granulysin and interferon‐γ to confirm the causalities.
Results
There were 69 cases of PPI‐related DHR, including SJS/TEN (n=27) and DRESS (n=10). The LAT by measuring granulysin showed a sensitivity of 59.3% and specificity of 96.4%. Esomeprazole was the most commonly involved in PPI‐related DHR (51%). Thirteen patients allergic to one kind of PPI could tolerate other structurally different PPI without cross‐hypersensitivity reactions, whereas three patients developed cross‐hypersensitivity reactions to alternative structurally similar PPI. The cross‐reactivity to structurally similar PPI was also observed in LAT assay.
Conclusions
PPIs have the potential to induce life‐threatening DHR. In patients when PPI is necessary for treatment, switching to structurally different alternatives should be considered.
We present a new approach for macromolecular structure determination from multiple particles in electron cryo-tomography (cryo-ET) data sets. Whereas existing subtomogram averaging approaches are ...based on 3D data models, we propose to optimise a regularised likelihood target that approximates a function of the 2D experimental images. In addition, analogous to Bayesian polishing and contrast transfer function (CTF) refinement in single-particle analysis, we describe the approaches that exploit the increased signal-to-noise ratio in the averaged structure to optimise tilt-series alignments, beam-induced motions of the particles throughout the tilt-series acquisition, defoci of the individual particles, as well as higher-order optical aberrations of the microscope. Implementation of our approaches in the open-source software package RELION aims to facilitate their general use, particularly for those researchers who are already familiar with its single-particle analysis tools. We illustrate for three applications that our approaches allow structure determination from cryo-ET data to resolutions sufficient for de novo atomic modelling.
Blue electrophosphorescence in organic light‐emitting diodes (OLEDs) is enhanced by the use of 3,6‐bis(triphenylsilyl)carbazole (see figure). This carbazole derivative with sterically bulky and ...large‐gap triphenylsilyl groups is an electrochemically and morphologically stable efficient host material for blue electrophosphorescence. When utilized in OLEDs, high efficiencies of up to 16 %, 30.6 cd A–1, and 26.7 lm W–1 are achieved.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virions are surrounded by a lipid bilayer from which spike (S) protein trimers protrude
. Heavily glycosylated S trimers bind to the ...angiotensin-converting enzyme 2 receptor and mediate entry of virions into target cells
. S exhibits extensive conformational flexibility: it modulates exposure of its receptor-binding site and subsequently undergoes complete structural rearrangement to drive fusion of viral and cellular membranes
. The structures and conformations of soluble, overexpressed, purified S proteins have been studied in detail using cryo-electron microscopy
, but the structure and distribution of S on the virion surface remain unknown. Here we applied cryo-electron microscopy and tomography to image intact SARS-CoV-2 virions and determine the high-resolution structure, conformational flexibility and distribution of S trimers in situ on the virion surface. These results reveal the conformations of S on the virion, and provide a basis from which to understand interactions between S and neutralizing antibodies during infection or vaccination.
The quantum anomalous Hall (QAH) effect is a consequence of non-zero Berry curvature in momentum space. The QAH insulator harbours dissipation-free chiral edge states in the absence of an external ...magnetic field. However, the topological Hall (TH) effect, a hallmark of chiral spin textures, is a consequence of real-space Berry curvature. Here, by inserting a topological insulator (TI) layer between two magnetic TI layers, we realized the concurrence of the TH effect and the QAH effect through electric-field gating. The TH effect is probed by bulk carriers, whereas the QAH effect is characterized by chiral edge states. The appearance of the TH effect in the QAH insulating regime is a consequence of chiral magnetic domain walls that result from the gate-induced Dzyaloshinskii-Moriya interaction and occurs during the magnetization reversal process in the magnetic TI sandwich samples. The coexistence of chiral edge states and chiral spin textures provides a platform for proof-of-concept dissipationless spin-textured spintronic applications.
Biodegradable Piezoelectric Force Sensor Curry, Eli J.; Ke, Kai; Chorsi, Meysam T. ...
Proceedings of the National Academy of Sciences,
01/2018, Letnik:
115, Številka:
5
Journal Article
Recenzirano
Odprti dostop
Measuring vital physiological pressures is important for monitoring health status, preventing the buildup of dangerous internal forces in impaired organs, and enabling novel approaches of using ...mechanical stimulation for tissue regeneration. Pressure sensors are often required to be implanted and directly integrated with native soft biological systems. Therefore, the devices should be flexible and at the same time biodegradable to avoid invasive removal surgery that can damage directly interfaced tissues. Despite recent achievements in degradable electronic devices, there is still a tremendous need to develop a force sensor which only relies on safe medical materials and requires no complex fabrication process to provide accurate information on important biophysiological forces. Here, we present a strategy for material processing, electromechanical analysis, device fabrication, and assessment of a piezoelectric Poly-L-lactide (PLLA) polymer to create a biodegradable, biocompatible piezoelectric force sensor, which only employs medical materials used commonly in Food and Drug Administration-approved implants, for the monitoring of biological forces. We show the sensor can precisely measure pressures in a wide range of 0–18 kPa and sustain a reliable performance for a period of 4 d in an aqueous environment. We also demonstrate this PLLA piezoelectric sensor can be implanted inside the abdominal cavity of a mouse to monitor the pressure of diaphragmatic contraction. This piezoelectric sensor offers an appealing alternative to present biodegradable electronic devices for the monitoring of intraorgan pressures. The sensor can be integrated with tissues and organs, forming self-sensing bionic systems to enable many exciting applications in regenerative medicine, drug delivery, and medical devices.
Abstract
The S=3/2 Kitaev honeycomb model (KHM) is a quantum spin liquid (QSL) state coupled to a static Z
2
gauge field. Employing an SO(6) Majorana representation of spin3/2’s, we find an exact ...representation of the conserved plaquette fluxes in terms of static
Z
2
gauge fields akin to the S=1/2 KHM which enables us to treat the remaining interacting matter fermion sector in a parton mean-field theory. We uncover a ground-state phase diagram consisting of gapped and gapless QSLs. Our parton description is in quantitative agreement with numerical simulations, and is furthermore corroborated by the addition of a 001 single ion anisotropy (SIA) which continuously connects the gapless Dirac QSL of our model with that of the S=1/2 KHM. In the presence of a weak 111 SIA, we discuss an emergent chiral QSL within a perturbation theory.
Bulk metallic glasses (BMGs) are usually based on a single principal element such as Zr, Cu, Mg and Fe. In this work, we report the formation of a series of high mixing entropy BMGs based on multiple ...major elements, which have unique characteristics of excellent glass-forming ability and mechanical properties compared with conventional BMGs. The high mixing entropy BMGs based on multiple major elements might be of significance in scientific studies, potential applications, and providing a novel approach in search for new metallic glass-forming systems.
► High mixing entropy bulk metallic glasses. ► Excellent glass-forming ability. ► Unique mechanical properties.
Although huge progress has been made on scene analysis in recent years, most existing works assume the input images to be in day-time with good lighting conditions. In this work, we aim to address ...the night-time scene parsing (NTSP) problem, which has two main challenges: 1) labeled night-time data are scarce, and 2) over- and under-exposures may co-occur in the input night-time images and are not explicitly modeled in existing pipelines. To tackle the scarcity of night-time data, we collect a novel labeled dataset, named NightCity , of 4,297 real night-time images with ground truth pixel-level semantic annotations. To our knowledge, NightCity is the largest dataset for NTSP. In addition, we also propose an exposure-aware framework to address the NTSP problem through augmenting the segmentation process with explicitly learned exposure features. Extensive experiments show that training on NightCity can significantly improve NTSP performances and that our exposure-aware model outperforms the state-of-the-art methods, yielding top performances on our dataset as well as existing datasets.
Existing salient instance detection (SID) methods typically learn from pixel-level annotated datasets. In this paper, we present the first weakly-supervised approach to the SID problem. Although weak ...supervision has been considered in general saliency detection, it is mainly based on using class labels for object localization. However, it is non-trivial to use only class labels to learn instance-aware saliency information, as salient instances with high semantic affinities may not be easily separated by the labels. As the subitizing information provides an instant judgement on the number of salient items, it is naturally related to detecting salient instances and may help separate instances of the same class while grouping different parts of the same instance. Inspired by this observation, we propose to use class and subitizing labels as weak supervision for the SID problem. We propose a novel weakly-supervised network with three branches: a Saliency Detection Branch leveraging class consistency information to locate candidate objects; a Boundary Detection Branch exploiting class discrepancy information to delineate object boundaries; and a Centroid Detection Branch using subitizing information to detect salient instance centroids. This complementary information is then fused to produce a salient instance map. To facilitate the learning process, we further propose a progressive training scheme to reduce label noise and the corresponding noise learned by the model, via reciprocating the model with progressive salient instance prediction and model refreshing. Our extensive evaluations show that the proposed method plays favorably against carefully designed baseline methods adapted from related tasks.
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