Miracle-dz/UniFAR-FTUs huggingface dataset:
Prevalence of pain in amyotrophic lateral sclerosis: a systematic review and meta-analysis

Abstract Objectives: Physical pain is a known symptom in amyotrophic lateral sclerosis (ALS), but no systematically derived prevalence estimate is available. The aim of this study was to determine the pooled prevalence of pain in ALS, relative to its method of measurement and pain characteristics. Methods: A systematic search across multiple databases was conducted on January 16, 2020. Random-effects meta-analyses of single proportions were performed on prevalence data. Heterogeneity was determined using the I 2 statistic. Where available, pain location, intensity, and type or source were compared. Results: 2552 articles were identified. Twenty-one eligible studies were included. All studies used observational designs (14 cross-sectional, 6 cohort, 1 case-control). Pooled prevalence of pain in ALS across all studies was 60% (95% CI = 50–69%), with a high degree of heterogeneity (I 2 = 94%, p < .001). Studies that used only validated measures had lower heterogeneity (I 2 = 82%, p = 0.002), compared to those that used tailored measures, or tailored supplemented with validated measures (I 2 = 90%, p < 0.001 and I 2 = 83%, p < 0.001, respectively). In a subset of studies (N = 9), the most commonly reported pain location was the upper limbs including shoulders/extremities (41.5%). A further study subset (N = 7) showed moderate-severe intensity pain was most frequently reported. Type of pain was commonly related to cramp or spasm. Conclusions: Experiencing physical pain in ALS occurs with high prevalence. Deriving consensus on which specific tools should be used to assess, monitor and compare symptoms of pain in this population will reduce current heterogeneity in approaches and increase the likelihood of ameliorating distressing experiences more effectively.
Optimization of airflow and aeration cycles in a new structured bed reactor configuration for carbon and nitrogen removal

ABSTRACT The Structured Bed Reactor with Recirculation and Intermittent Aeration (SBRRIA) is a reactor configuration that presents high efficiency of organic matter and nitrogen removal, besides low sludge production. However, operational parameters, as the recirculation rate, aeration time, and airflow, are not fully established. A bench-scale structured bed reactor with intermittent aeration was fed with synthetic effluent simulating the characteristics of sanitary sewage. The reactor was operated for 280 days with an operational hydraulic retention time (HRT) of 10 h. The reactor was operated without effluent recirculation for the first time since this approach was not yet reported, and was named Structured Bed Reactor with Intermittent Aeration (SBRIA). The COD removal was higher than 81% for all operational conditions, and the total nitrogen removal ranged from 10 to 80%. The highest efficiencies were obtained with an aeration time of 1 h 45 min (total cycle of 3 h) and an airflow rate of 4.5 L.min−1. Different nitrification and denitrification behaviours were observed, resulting in nitrification efficiencies over 90% when the reactor was submitted to higher aeration times and denitrification efficiencies above 90% when the reactor was submitted to low aeration times. The airflow ranges tested in this study affected the nitrification and the total nitrogen efficiencies. Even without effluent recirculation, the temporal profile showed that there were no peaks in the concentration of the nitrogen forms in the reactor effluent, saving electrical energy up to 75% due to pumping. GRAPHICAL ABSTRACT
Synthesis and characterization of cerium oxide by electrochemical methods

Ceria-based materials have been synthesized by electrochemical process. Electrodeposition is an interesting cheap method which can be performed at ambient pressure and rather low temperature (less than 100 °C). Moreover, it is easy to control in situ the film thickness. Ceria coatings were obtained by an indirect electrodeposition method. A potentiostatic technique (–0.7 V/SCE) was used to first reduce a hydroxide precursor (O2 or NO3–) before leading to the formation of cerium oxide after 2h of deposition time. This work focused on the characterization of ceria films deposited onto stainless steel in view of high temperature fuel cell applications. The chosen deposition conditions lead to quite adherent, homogenous and covering films. The microstructure and the crystallinity of the ceria thin layers were characterized by SEM, TEM and XRD measurements. Electrochemical microscopy (SECM) was also used to locally study the conductive properties of ceria layers and the homogeneity of the deposited films. Finally, electrochemical characterizations such as impedance spectroscopy were performed under air atmosphere. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)
Spectral reflectance of carbonate mineral mixtures and bidirectional reflectance theory: Quantitative analysis techniques for application in remote sensing

Abstract High‐spectral resolution imaging spectrometers, which acquire remotely sensed data in many contiguous spectral bands, allow for the direct identification of surface mineralogy by comparing pixel and laboratory spectra. The advent of such technology requires a better understanding of reflectance spectroscopy, therefore visible and near‐infrared (0.4–2.5 μm) reflectance spectra of carbonates are discussed in this paper. Electronic processes in cations and vibrational processes involving the crystal lattice produce the main spectral absorption features. Subsequently, mineral impurities are reflected in the reflectance spectra. A simple semi‐empirical model is presented for determination of artificial spectral reflectance of mineral mixtures based on their single‐component reflectivity. The model is used to explain the effect of particle size and distribution, iron, water bounded by clay minerals, and organic material on the reflectivity of carbonate minerals. Similarly, reflectance spectra of calcit.
An integrative model using flow cytometry identifies nosocomial infection after trauma

Supplemental digital content is available in the text. BACKGROUND Flow cytometry (FCM) is a rapid diagnostic tool for monitoring immune cell function. We sought to determine if assessment of cell phenotypes using standardized FCM could be used to identify nosocomial infection after trauma. METHODS Prospective study of trauma patients at a Level I center from 2014 to 2018. Clinical and FCM data were collected within 24 hours of admission. Random forest (RF) models were developed to estimate the risk of severe sepsis (SS), organ space infection (OSI), and ventilator-associated pneumonia (VAP). Variables were selected using backward elimination and models were validated with leave-one-out. RESULTS One hundred and thirty-eight patients were included (median age, 30 years [23–44 years]; median Injury Severity Score, 20 (14–29); 76% (105/138) Black; 60% (83/138) gunshots). The incidence of SS was 8.7% (12/138), OSI 16.7% (23/138), and VAP 18% (25/138). The final RF SS model resulted in five variables (RBCs transfused in first 24 hours; absolute counts of CD56− CD16+ lymphocytes, CD4+ T cells, and CD56 bright natural killer [NK] cells; percentage of CD16+ CD56+ NK cells) that identified SS with an AUC of 0.89, sensitivity of 0.98, and specificity of 0.78. The final RF OSI model resulted in four variables (RBC in first 24 hours, shock index, absolute CD16+ CD56+ NK cell counts, percentage of CD56 bright NK cells) that identified OSI with an AUC of 0.76, sensitivity of 0.68, and specificity of 0.82. The RF VAP model resulted in six variables (Sequential [Sepsis-related] Organ Failure Assessment score: Injury Severity Score; CD4− CD8− T cell counts; percentages of CD16− CD56− NK cells, CD16− CD56+ NK cells, and CD19+ B lymphocytes) that identified VAP with AUC of 0.86, sensitivity of 0.86, and specificity of 0.83. CONCLUSIONS Combined clinical and FCM data can assist with early identification of posttraumatic infections. The presence of NK cells supports the innate immune response that occurs during acute inflammation. Further research is needed to determine the functional role of these innate cell phenotypes and their value in predictive models immediately after injury. LEVEL OF EVIDENCE Prognostic, level III.
Effect of pore constriction on adsorption behaviour in nanoporous carbon slit pore: a computer simulation

A Grand Canonical Monte Carlo simulation (GCMC) method is used to study the effects of pore constriction on the adsorption of argon at 87.3 K in carbon slit pores of infinite and finite lengths. It is shown that the pore constriction affects the pattern of adsorption isotherm. First, the isotherm of the composite pore is greater than that of the uniform pore having the same width as the larger cavity of the composite pore. Secondly, the hysteresis loop of the composite pore is smaller than and falls between those of uniform pores. Two types of hysteresis loops have been observed, irrespective of the absence or presence of constriction and their presence depend on pore width. One hysteresis loop is associated with the compression of adsorbed particles and this phenomenon occurs after pore has been filled with particles. The second hysteresis loop is the classical condensation–evaporation loop. The hysteresis loop of a composite pore depends on the sizes of the larger cavity and the constriction. Generally, it is found that the pore blocking effect is not manifested in composite slit pores, and this result does not support the traditional inkbottle pore hypothesis.
Band Representation-Based Semi-Supervised Low-Light Image Enhancement: Bridging the Gap Between Signal Fidelity and Perceptual Quality

It has been widely acknowledged that under-exposure causes a variety of visual quality degradation because of intensive noise, decreased visibility, biased color, etc. To alleviate these issues, a novel semi-supervised learning approach is proposed in this paper for low-light image enhancement. More specifically, we propose a deep recursive band network (DRBN) to recover a linear band representation of an enhanced normal-light image based on the guidance of the paired low/normal-light images. Such design philosophy enables the principled network to generate a quality improved one by reconstructing the given bands based upon another learnable linear transformation which is perceptually driven by an image quality assessment neural network. On one hand, the proposed network is delicately developed to obtain a variety of coarse-to-fine band representations, of which the estimations benefit each other in a recursive process mutually. On the other hand, the extracted band representation of the enhanced image in the recursive band learning stage of DRBN is capable of bridging the gap between the restoration knowledge of paired data and the perceptual quality preference to high-quality images. Subsequently, the band recomposition learns to recompose the band representation towards fitting perceptual regularization of high-quality images with the perceptual guidance. The proposed architecture can be flexibly trained with both paired and unpaired data. Extensive experiments demonstrate that our method produces better enhanced results with visually pleasing contrast and color distributions, as well as well-restored structural details.
P2GT: Fine-Grained Genomic Data Access Control With Privacy-Preserving Testing in Cloud Computing

With the rapid development of bioinformatics and the availability of genetic sequencing technologies, genomic data has been used to facilitate personalized medicine. Cloud computing, features as low cost, rich storage and rapid processing can precisely respond to the challenges brought by the emergence of massive genomic data. Considering the security of cloud platform and the privacy of genomic data, we first introduce P2GT which utilizes key-policy attribute-based encryption to realize genomic data access control with unbounded attributes, and employs equality test algorithm to achieve personalized medicine test by matching digitized single nucleotide polymorphisms (SNPs) directly on the users’ ciphertext without encrypting multiple times. We then propose an enhanced scheme P2GT+, which adopts identity-based encryption with equality test supporting flexible joint authorization to realize privacy-preserving paternity test, genetic compatibility test and disease susceptibility test over the encrypted SNPs with P2GT. We prove the security of proposed schemes and conduct extensive experiments with the 1,000 Genomes dataset. The results show that P2GT and P2GT+ are practical and scalable enough to meet the privacy-preserving and authorized genetic testing requirements in cloud computing.
Model of cation adsorption on allophanic andisols I. Theory and algorithm

Abstract A new model of cation adsorption on allophanic Andisols was proposed. This model assumes that cations are adsorbed in the internal space of the hollow spherical ball of allophane either in the form of a diffuse ion or through the formation of surface complexes with SO- groups arranged on the inner surface swarm. The distinctive characteristics of this model is that the mean-field approximation was not adopted, but the Coulomb potential among charged particles was directly evaluated by using the primitive restricted model (Valeau and Cohen 1980: J. Chem. Phys., 72, 5935–5941) and the grand canonical Monte Carlo (GCMC) simulation. This report introduces the theory and the algorithm of the GCMC simulation.
SiamCAN: Real-Time Visual Tracking Based on Siamese Center-Aware Network

In this article, we present a novel Siamese center-aware network (SiamCAN) for visual tracking, which consists of the Siamese feature extraction subnetwork, followed by the classification, regression, and localization branches in parallel. The classification branch is used to distinguish the target from background, and the regression branch is introduced to regress the bounding box of the target. To reduce the impact of manually designed anchor boxes to adapt to different target motion patterns, we design the localization branch to localize the target center directly to assist the regression branch generating accurate results. Meanwhile, we introduce the global context module into the localization branch to capture long-range dependencies for more robustness to large displacements of the target. A multi-scale learnable attention module is used to guide these three branches to exploit discriminative features for better performance. Extensive experiments on 9 challenging benchmarks, namely VOT2016, VOT2018, VOT2019, OTB100, LTB35, LaSOT, TC128, UAV123 and VisDrone-SOT2019 demonstrate that SiamCAN achieves leading accuracy with high efficiency. Our source code is available at https://isrc.iscas. ac.cn/gitlab/research/siamcan.
Structural insights into membrane remodeling by SNX1

Significance Coat proteins play a central role in the intracellular transport pathways by coupling two main functions: bending the membrane to generate transport carriers and binding to cargoes for their sorting into these carriers. Studies thus far have mostly solved the structure of coat proteins in solution, but their functional form requires assembly on the membrane into protein complexes. Here, we have pursued cryo-EM to reveal in molecular detail how SNX1 assembles on the membrane to deform the membrane. When compared to a previously solved retromer-SNX complex, our elucidation also suggests how retromer affects SNX in this complex as well as the intermediary stages of this coat assembly. The sorting nexin (SNX) family of proteins deform the membrane to generate transport carriers in endosomal pathways. Here, we elucidate how a prototypic member, SNX1, acts in this process. Performing cryoelectron microscopy, we find that SNX1 assembles into a protein lattice that consists of helical rows of SNX1 dimers wrapped around tubular membranes in a crosslinked fashion. We also visualize the details of this structure, which provides a molecular understanding of how various parts of SNX1 contribute to its ability to deform the membrane. Moreover, we have compared the SNX1 structure with a previously elucidated structure of an endosomal coat complex formed by retromer coupled to a SNX, which reveals how the molecular organization of the SNX in this coat complex is affected by retromer. The comparison also suggests insight into intermediary stages of assembly that results in the formation of the retromer-SNX coat complex on the membrane.
Comparative study on nano-scale III-V MOSFETs with various channel materials using quantum-corrected Monte Carlo simulation

We investigate the ability of the nano-scale III-V MOSFETs with InGaAs, GaAs or InP channels by using the quantum-corrected Monte Carlo (MC) simulation. The InGaAs channel shows the largest average electron velocity at the bottleneck, vs, because of the smallest electron effective mass, m * in the Γ valley. However, it is degraded by the electron rebound from the drain through the accumulation in the L valleys, when the gate voltage, Vgs, is highly biased. The electron rebound is more pronounced in the GaAs channel, because of the narrow Γ - L valley separation. Meanwhile, the InP channel shows the smallest vs because of the largest m * in the Γ valley. However, the electron rebound is less pronounced, because of the smaller accumulation in the L valleys. On the other hand, the electron density at the potential bottleneck, nb, is largest in the InP channel, because of the largest gate capacitance owing to the highest density of states, DOS. Eventually, the InP channel shows the largest drain current, Ids (© 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)
Geometric Distortion Correction of Renal Diffusion Tensor Imaging Using the Reversed Gradient Method

Abstract Renal echo planar diffusion tensor imaging (DTI) has clinical potential but suffers from geometric distortion. We evaluated feasibility of reversed gradient distortion correction in 10 diabetic patients and 6 volunteers. Renal area, apparent diffusion coefficient, fractional anisotropy, and tensor eigenvalues were measured on uncorrected and distortion-corrected DTI. Corrected DTI correlated better than uncorrected DTI (r = 0.904 vs 0.840, P = 0.002) with reference anatomic T2-weighted imaging, with no significant difference in DTI metrics.
Barrier-to-autointegration-factor (Banf1) modulates DNA double-strand break repair pathway choice via regulation of DNA-dependent kinase (DNA-PK) activity

Abstract DNA repair pathways are essential to maintain the integrity of the genome and prevent cell death and tumourigenesis. Here, we show that the Barrier-to-Autointegration Factor (Banf1) protein has a role in the repair of DNA double-strand breaks. Banf1 is characterized as a nuclear envelope protein and mutations in Banf1 are associated with the severe premature aging syndrome, Néstor–Guillermo Progeria Syndrome. We have previously shown that Banf1 directly regulates the activity of PARP1 in the repair of oxidative DNA lesions. Here, we show that Banf1 also has a role in modulating DNA double-strand break repair through regulation of the DNA-dependent Protein Kinase catalytic subunit, DNA-PKcs. Specifically, we demonstrate that Banf1 relocalizes from the nuclear envelope to sites of DNA double-strand breaks. We also show that Banf1 can bind to and directly inhibit the activity of DNA-PKcs. Supporting this, cellular depletion of Banf1 leads to an increase in non-homologous end-joining and a decrease in homologous recombination, which our data suggest is likely due to unrestrained DNA-PKcs activity. Overall, this study identifies how Banf1 regulates double-strand break repair pathway choice by modulating DNA-PKcs activity to control genome stability within the cell.
TLR3 Activation by Zika Virus Stimulates Inflammatory Cytokine Production Which Dampens the Antiviral Response Induced by RIG-I-Like Receptors

Zika virus (ZIKV) has a pronounced neurotropism, and infections with this virus can cause serious neurological disorders, most notably microcephaly and Guillain-Barré syndrome. Our studies reveal that during ZIKV infection, recognition of viral RNA by TLR3 enhances the production of inflammatory cytokines and suppresses the interferon response triggered by RIG-I-like receptors (RLR) in a SOCS3-dependent manner, thus facilitating virus replication. ABSTRACT Infection with the Zika virus (ZIKV), a member of the Flaviviridae family, can cause serious neurological disorders, most notably microcephaly in newborns. In this study, we investigated the innate immune response to ZIKV infection in cells of the nervous system. In human neural progenitor cells (hNPCs), a target for ZIKV infection and likely involved in ZIKV-associated neuropathology, viral infection failed to elicit an antiviral interferon (IFN) response. However, pharmacological inhibition of Toll-like receptor 3 (TLR3) partially restored this deficit. Analogous results were obtained in human induced pluripotent stem cell (iPSC)-derived astrocytes, which are capable of mounting a strong antiviral cytokine response. There, ZIKV is sensed by both RIG-I and MDA5 and induces an IFN response as well as expression of proinflammatory cytokines, such as interleukin-6 (IL-6). Upon inhibition of TLR3, also in astrocytes the antiviral cytokine response was enhanced, whereas amounts of proinflammatory cytokines were reduced. To study the underlying mechanism, we used human epithelial cells as an easy-to-manipulate model system. We found that ZIKV is sensed in these cells by RIG-I to induce a robust IFN response and by TLR3 to trigger the expression of proinflammatory cytokines, including IL-6. ZIKV-induced upregulation of IL-6 activated the STAT3 pathway, which decreased STAT1 phosphorylation in a SOCS3-dependent manner, thus reducing the IFN response. In conclusion, we show that TLR3 activation by ZIKV suppresses IFN responses triggered by RIG-I-like receptors (RLR). IMPORTANCE Zika virus (ZIKV) has a pronounced neurotropism, and infections with this virus can cause serious neurological disorders, most notably microcephaly and Guillain-Barré syndrome. Our studies reveal that during ZIKV infection, recognition of viral RNA by TLR3 enhances the production of inflammatory cytokines and suppresses the interferon response triggered by RIG-I-like receptors (RLR) in a SOCS3-dependent manner, thus facilitating virus replication. The discovery of this cross talk between antiviral (RLR) and inflammatory (TLR) responses may have important implications for our understanding of ZIKV-induced pathogenesis.