bluuebunny/crossref_metadata_2025_split huggingface dataset:
A functional ultrasound brain GPS for automatic vascular-based neuronavigation
Authors: Nouhoum M. , Ferrier J. , Osmanski B.-F. , Ialy-Radio N. , Pezet S. , Tanter M. , Deffieux T. 
Published: July 2021

AbstractRecent advances in ultrasound imaging triggered by transmission of ultrafast plane waves have rendered functional ultrasound (fUS) imaging a valuable neuroimaging modality capable of mapping cerebral vascular networks, but also for the indirect capture of neuronal activity with high sensitivity thanks to the neurovascular coupling. However, the expansion of fUS imaging is still limited by the difficulty to identify cerebral structures during experiments based solely on the Doppler images and the shape of the vessels. In order to tackle this challenge, this study introduces the vascular brain positioning system (BPS), a GPS of the brain. The BPS is a whole-brain neuronavigation system based on the on-the-fly automatic alignment of ultrafast ultrasensitive transcranial Power Doppler volumic images to common templates such as the Allen Mouse Brain Common Coordinates Framework. This method relies on the online registration of the complex cerebral vascular fingerprint of the studied animal to a pre-aligned reference vascular atlas, thus allowing rapid matching and identification of brain structures. We quantified the accuracy of the automatic registration using super-resolution vascular images obtained at the microscopic scale using Ultrasound Localization Microscopy and found a positioning error of 44 µm and 96 µm for intra-animal and inter-animal vascular registration, respectively. The proposed BPS approach outperforms the manual vascular landmark recognition performed by expert neuroscientists (inter-annotator errors of 215 µm and 259 µm). Using the online BPS approach coupled with the Allen Atlas, we demonstrated the capability of the system to position itself automatically over chosen anatomical structures and to obtain corresponding functional activation maps even in complex oblique planes. Finally, we show that the system can be used to acquire and estimate functional connectivity matrices automatically. The proposed functional ultrasound on-the-fly neuronavigation approach allows automatic brain navigation and could become a key asset to ensure standardized experiments and protocols for non-expert and expert researchers.
Quantitative MRI-based radiomics for noninvasively predicting molecular subtypes and survival in glioma patients
Authors: Yan Jing , Zhang Bin , Zhang Shuaitong , Cheng Jingliang , Liu Xianzhi , Wang Weiwei , Dong Yuhao , Zhang Lu , Mo Xiaokai , Chen Qiuying , Fang Jin , Wang Fei , Tian Jie , Zhang Shuixing , Zhang Zhenyu 
Published: July 2021

AbstractGliomas can be classified into five molecular groups based on the status of IDH mutation, 1p/19q codeletion, and TERT promoter mutation, whereas they need to be obtained by biopsy or surgery. Thus, we aimed to use MRI-based radiomics to noninvasively predict the molecular groups and assess their prognostic value. We retrospectively identified 357 patients with gliomas and extracted radiomic features from their preoperative MRI images. Single-layered radiomic signatures were generated using a single MR sequence using Bayesian-regularization neural networks. Image fusion models were built by combing the significant radiomic signatures. By separately predicting the molecular markers, the predictive molecular groups were obtained. Prognostic nomograms were developed based on the predictive molecular groups and clinicopathologic data to predict progression-free survival (PFS) and overall survival (OS). The results showed that the image fusion model incorporating radiomic signatures from contrast-enhanced T1-weighted imaging (cT1WI) and apparent diffusion coefficient (ADC) achieved an AUC of 0.884 and 0.669 for predicting IDH and TERT status, respectively. cT1WI-based radiomic signature alone yielded favorable performance in predicting 1p/19q status (AUC = 0.815). The predictive molecular groups were comparable to actual ones in predicting PFS (C-index: 0.709 vs. 0.722, P = 0.241) and OS (C-index: 0.703 vs. 0.751, P = 0.359). Subgroup analyses by grades showed similar findings. The prognostic nomograms based on grades and the predictive molecular groups yielded a C-index of 0.736 and 0.735 in predicting PFS and OS, respectively. Accordingly, MRI-based radiomics may be useful for noninvasively detecting molecular groups and predicting survival in gliomas regardless of grades.
Lead exposure is associated with functional and microstructural changes in the healthy human brain
Authors: Takeuchi Hikaru , Taki Yasuyuki , Nouchi Rui , Yokoyama Ryoichi , Kotozaki Yuka , Nakagawa Seishu , Sekiguchi Atsushi , Iizuka Kunio , Hanawa Sugiko , Araki Tsuyoshi , Miyauchi Carlos Makoto , Sakaki Kohei , Nozawa Takayuki , Ikeda Shigeyuki , Yokota Susum , Daniele Magistro , Sassa Yuko , Kawashima Ryuta 
Published: July 2021

AbstractLead is a toxin known to harm many organs in the body, particularly the central nervous system, across an individual’s lifespan. To date, no study has yet investigated the associations between body lead level and the microstructural properties of gray matter areas, and brain activity during attention-demanding tasks. Here, utilizing data of diffusion tensor imaging, functional magnetic resonance imaging and cognitive measures among 920 typically developing young adults, we show greater hair lead levels are weakly but significantly associated with (a) increased working memory-related activity in the right premotor and pre-supplemental motor areas, (b) lower fractional anisotropy (FA) in white matter areas near the internal capsule, (c) lower mean diffusivity (MD) in the dopaminergic system in the left hemisphere and other widespread contingent areas, and (d) greater MD in the white matter area adjacent to the right fusiform gyrus. Higher lead levels were also weakly but significantly associated with lower performance in tests of high-order cognitive functions, such as the psychometric intelligence test, greater impulsivity measures, and higher novelty seeking and extraversion. These findings reflect the weak effect of daily lead level on the excitability and microstructural properties of the brain, particularly in the dopaminergic system.
Butyrophilin-like 2 regulates site-specific adaptations of intestinal γδ intraepithelial lymphocytes
Authors: Panea Casandra , Zhang Ruoyu , VanValkenburgh Jeffrey , Ni Min , Adler Christina , Wei Yi , Ochoa Francisca , Schmahl Jennifer , Tang Yajun , Siao Chia-Jen , Poueymirou William , Espert Jennifer , Lim Wei Keat , Atwal Gurinder S. , Murphy Andrew J. , Sleeman Matthew A. , Hovhannisyan Zaruhi , Haxhinasto Sokol 
Published: July 2021

AbstractTissue-resident γδ intraepithelial lymphocytes (IELs) orchestrate innate and adaptive immune responses to maintain intestinal epithelial barrier integrity. Epithelia-specific butyrophilin-like (Btnl) molecules induce perinatal development of distinct Vγ TCR+ IELs, however, the mechanisms that control γδ IEL maintenance within discrete intestinal segments are unclear. Here, we show that Btnl2 suppressed homeostatic proliferation of γδ IELs preferentially in the ileum. High throughput transcriptomic characterization of site-specific Btnl2-KO γδ IELs reveals that Btnl2 regulated the antimicrobial response module of ileal γδ IELs. Btnl2 deficiency shapes the TCR specificities and TCRγ/δ repertoire diversity of ileal γδ IELs. During DSS-induced colitis, Btnl2-KO mice exhibit increased inflammation and delayed mucosal repair in the colon. Collectively, these data suggest that Btnl2 fine-tunes γδ IEL frequencies and TCR specificities in response to site-specific homeostatic and inflammatory cues. Hence, Btnl-mediated targeting of γδ IEL development and maintenance may help dissect their immunological functions in intestinal diseases with segment-specific manifestations.
Language Skills of Children With and Without Mathematics Difficulty
Authors: Chow Jason C. , Majeika Caitlyn E. , Sheaffer Amanda W. 
Published: July 2021

Purpose
Language is an important skill required for children to succeed in school. Higher language skills are associated with school readiness in young children and general mathematics performance. However, many students with mathematics difficulty (MD) may be more likely to present difficulties with language skills than their peers. The purpose of this report was to compare the language performance of children with and without MD.

Method

We compared child vocabulary, morphology, and syntax between first- and second-grade children (
N
= 247) classified as with or without MD, controlling for child working memory.

Results

Children with MD (
n
= 119) significantly underperformed compared with their peers (
n
= 155) on all language measures. The largest difference between children with and without MD was in syntax.

Conclusions
Children with MD present poorer language skills than their peers, which aligns with previous research linking the importance of syntax with mathematics learning. More research is needed to better understand the complex links between language skills and mathematical development.
Gender Differences in Identifying Facial, Prosodic, and Semantic Emotions Show Category- and Channel-Specific Effects Mediated by Encoder's Gender
Authors: Lin Yi , Ding Hongwei , Zhang Yang 
Published: July 2021

PurposeThe nature of gender differences in emotion processing has remained unclear due to the discrepancies in existing literature. This study examined the modulatory effects of emotion categories and communication channels on gender differences in verbal and nonverbal emotion perception.MethodEighty-eight participants (43 females and 45 males) were asked to identify three basic emotions (i.e., happiness, sadness, and anger) and neutrality encoded by female or male actors from verbal (i.e., semantic) or nonverbal (i.e., facial and prosodic) channels.ResultsWhile women showed an overall advantage in performance, their superiority was dependent on specific types of emotion and channel. Specifically, women outperformed men in regard to two basic emotions (happiness and sadness) in the nonverbal channels and only the anger category with verbal content. Conversely, men did better for the anger category in the nonverbal channels and for the other two emotions (happiness and sadness) in verbal content. There was an emotion- and channel-specific interaction effect between the two types of gender differences, with male subjects showing higher sensitivity to sad faces and prosody portrayed by the female encoders.ConclusionThese findings reveal explicit emotion processing as a highly dynamic complex process with significant gender differences tied to specific emotion categories and communication channels.Supplemental Materialhttps://doi.org/10.23641/asha.15032583
A Window Into Functional Communication: Leveraging Naturalistic Speech Samples in Primary Progressive Aphasia
Authors: Gallée Jeanne , Volkmer Anna 
Published: July 2021

Purpose
Naturalistic speech samples should be routinely collected in the assessment of individuals with communication difficulties. However, even when these samples are collected, they are often underutilized. We propose that the analysis of naturalistic speech samples can greatly enhance our understanding and evaluation of the functional impact of primary progressive aphasia (PPA) on communication. First, we review the current practices of evaluating PPA. Second, we provide a framework to optimize the collection, analysis, and interpretation of speech samples to accomplish this goal. In particular, we demonstrate how speech samples can be evaluated for measures of informativeness, the presence of atypical patterns of speech, articulatory rate, and pausing, all of which are helpful metrics in characterizing disordered speech. These factors can be leveraged to identify both the strengths and difficulties an individual may face in everyday communication.

Conclusion
The collection of naturalistic speech in both clinical and naturalistic settings with typical communication partners is highly recommended to best diagnose, monitor, and inform treatment plans for individuals with PPA.
Interactions between stearic acid and calcite surfaces: Experimental and computer simulation studies
Authors: Zhang Lihua , Liu Laibao , Li Xiaopeng , Tang Youhong , Liu Chuanbei , Zhang Hong‐Ping 
Published: July 2021

AbstractCalcite surface was modified with stearic acids, and the interaction between them was investigated both experimentally and theoretically. Stearic‐acid‐modified calcite powders were investigated with Fourier transform infrared spectroscopy, X‐ray diffraction, zeta potential analyser and contact angle measurement. Then, the density functional theory calculations were performed to explore the interaction at the atomic scale. The experimental results and simulation indicated that stearic acids interact with calcite surface via chelation between the double‐bond O atom of –COOH and the Ca atom on calcite surface. The terminal methyl group of the stearic acids decreases the hydrophilicity of the calcite surface, and the interaction between different crystal faces of calcite is different.
Few‐shot action recognition using task‐adaptive parameters
Authors: Zong Pengcheng , Chen Peng , Yu Tianwei , Yan Lingqiang , Huan Ruohong 
Published: July 2021

AbstractFew‐shot action recognition aims to recognise unseen actions given a few examples. Thus, this letter proposes a model named meta relation network (Meta RN) to address such problem. This model contains two parts: a MetaNet and a relation network. Relation network is utilised to extract video features and classify actions. A second‐order pooling followed by power normalization is used for feature enhancement, and target videos are finally classified by exploring nonlinear distance relations. The MetaNet module is designed to model different task distributions and generate task‐adaptive parameters for the embedding layer of the relation network in different tasks. Experimental results on two public action recognition datasets demonstrate that the network achieves higher accuracies than several state‐of‐the‐art approaches.
A novel adversarial transfer learning in deep convolutional neural network for intelligent diagnosis of gas‐insulated switchgear insulation defect
Authors: Wang Yanxin , Yan Jing , Jing Qianzhen , Qi Zhenkang , Wang Jianhua , Geng Yingsan 
Published: July 2021

AbstractRecently, numerous data‐driven fault diagnosis methods have been developed, and the tasks involving the same distribution of training and test data have been well solved. However, considering the particularity of gas‐insulated switchgear (GIS), collecting massive data, especially with the same distribution, is difficult. Therefore, existing fault diagnosis methods hardly achieve satisfactory insulation defect diagnosis with small datasets. Aiming at solving this problem, a novel domain adversarial transfer convolutional neural network (DATCNN) is proposed, realising the diagnosis of GIS insulation defects on small samples. First, a residual CNN is built to learn feature representations from the source and target domains. Second, the domain adversarial training strategy is used for feature transfer, where a conditional adversarial mechanism is introduced, and the joint distribution of features and labels is improved to a random linear combination, which realises the simultaneous adaptation of features and labels. Finally, the Nesterov accelerated gradient descent optimisation algorithm is used to speed up the gradient convergence. DATCNN has 99.15% and ≥89.5% diagnosis accuracy for GIS insulation defects in the laboratory and on‐site, respectively. Comprehensive experiment results show the effectiveness and superiority of the proposed method in diagnosing GIS insulation defects with small samples.
CyclingNet: Detecting cycling near misses from video streams in complex urban scenes with deep learning
Authors: Ibrahim Mohamed R. , Haworth James , Christie Nicola , Cheng Tao 
Published: July 2021

AbstractCycling is a promising sustainable mode for commuting and leisure in cities. However, the perception of cycling as a risky activity reduces its wide expansion as a commuting mode. A novel method called CyclingNet has been introduced here for detecting cycling near misses from video streams generated by a mounted frontal camera on a bike regardless of the camera position, the conditions of the built environment, the visual conditions and without any restrictions on the riding behaviour. CyclingNet is a deep computer vision model based on a convolutional structure embedded with self‐attention bidirectional long‐short term memory (LSTM) blocks that aim to understand near misses from both sequential images of scenes and their optical flows. The model is trained on scenes of both safe rides and near misses. After 42 hours of training on a single GPU, the model shows high accuracy on the training, testing and validation sets. The model is intended to be used for generating information that can draw significant conclusions regarding cycling behaviour in cities and elsewhere, which could help planners and policy‐makers to better understand the requirement of safety measures when designing infrastructure or drawing policies. As for future work, the model can be pipelined with other state‐of‐the‐art classifiers and object detectors simultaneously to understand the causality of near misses based on factors related to interactions of road users, the built and the natural environments.
Modeling accretion shocks at the disk–envelope interface
Authors: van Gelder M. L. , Tabone B. , van Dishoeck E. F. , Godard B. 
Published: July 2021

Context.As material from an infalling protostellar envelope hits the forming disk, an accretion shock may develop which could (partially) alter the envelope material entering the disk. Observations with the Atacama Large Millimeter/submillimeter Array (ALMA) indicate that emission originating from warm SO and SO2might be good tracers of such accretion shocks.Aims.The goal of this work is to test under what shock conditions the abundances of gas-phase SO and SO2increase in an accretion shock at the disk–envelope interface.Methods.Detailed shock models including gas dynamics were computed using the Paris-Durham shock code for nonmagnetizedJ-type accretion shocks in typical inner envelope conditions. The effect of the preshock density, shock velocity, and strength of the ultraviolet (UV) radiation field on the abundance of warm SO and SO2is explored. Compared with outflows, these shocks involve higher densities (~107cm−3), lower shock velocities (~few km s−1), and large dust grains (~0.2 μm) and thus probe a different parameter space.Results.Warm gas-phase chemistry is efficient in forming SO under mostJ-type shock conditions considered. In lower-velocity (~3 km s−1) shocks, the abundance of SO is increased through subsequent reactions starting from thermally desorbed CH4toward H2CO and finally SO. In higher velocity (≳4 km s−1) shocks, both SO and SO2are formed through reactions of OH and atomic S. The strength of the UV radiation field is crucial for SO and in particular SO2formation through the photodissociation of H2O. Thermal desorption of SO and SO2ice is only relevant in high-velocity (≳5 km s−1) shocks at high densities (≳107cm−3). Both the composition in the gas phase, in particular the abundances of atomic S and O, and in ices such as H2S, CH4, SO, and SO2play a key role in the abundances of SO and SO2that are reached in the shock.Conclusions.Warm emission from SO and SO2is a possible tracer of accretion shocks at the disk–envelope interface as long as a local UV field is present. Observations with ALMA at high-angular resolution could provide further constraints given that other key species for the gas-phase formation of SO and SO2, such as H2S and H2CO, are also covered. Moreover, theJames WebbSpace Telescope will give access to other possible slow, dense shock tracers such as H2, H2O, and [S I] 25 μm.
SARS-CoV-2-Infektion des Verdauungstrakts – Experimentelle Ansätze einer Organoid-basierten in vitro Modellierung
Authors: Hentschel Viktoria , Groß Rüdiger , Krüger Jana , Münch Jan , Müller Martin , Kleger Alexander 
Published: July 2021

Zusammenfassung
SARS-CoV-2 ist eine neuartige humanpathogene Coronavirus-Variante, deren Prädilektion für den Atemwegstrakt zu einer raschen pandemischen Verbreitung durch viruspartikelhaltige Aerosole geführt hat. Die individuelle Organsuszeptibilität wird maßgeblich durch die Besatzdichte mit dem membranständigen Rezeptormolekül ACE2 bestimmt, das als zentraler Interaktionspartner für das virale Spike-Protein den Adhäsions- und Fusionsprozess vermittelt und somit die Grundvoraussetzung zur Aufnahme des Virusgenoms in die Wirtszelle schafft. Ausgehend von einem umfangreichen Datensatz klinischer Studien und Fallberichte, gilt es mittlerweile als gesichert, dass auch bestimmte Zellpopulationen des Verdauungstrakts sowie des funktionell angegliederten olfaktorisch-gustatorischen Systems über die erforderliche Rezeptorenausstattung verfügen und somit durch SARS-CoV-2 „angreifbar“ sind. Zahlreiche Berichte über gastrointestinale Beschwerden und Laborabnormalitäten sind als Indizien für relevante Organdysfunktionen zu werten und untermauern die klinische Bedeutsamkeit einer Mitbeteiligung des Verdauungstrakts im Rahmen einer SARS-CoV-2-Infektion. Organoide sind dreidimensional wachsende In-vitro-Replikate von Organgeweben und nehmen insbesondere dank der organtypisch komplexen zellulären Zusammensetzung und Imitation der physiologischen Funktionsweise von Primärzellen einen hohen Stellenwert für die infektiologische Grundlagenforschung ein. Diese Übersichtsarbeit befasst sich thematisch mit den pathophysiologischen Aspekten der Infektion verdauungsrelevanter Organe mit SARS-CoV-2 unter besonderer Würdigung existierender organoid- oder primärzellkulturbasierter Infektionsmodelle und der daraus hervorgegangenen Erkenntnisse.
Augmentative and Alternative Communication Supports for Language and Literacy in Preschool: Considerations for Down Syndrome and Autism Spectrum Disorder
Authors: Barton-Hulsey Andrea , Phinney Sarah , Collins Sara 
Published: July 2021

AbstractChildren with Down syndrome and children with autism spectrum disorder have a range of speech abilities during preschool that impacts access to both language and literacy instruction. It is the responsibility of the speech-language pathologist to advocate for and provide intervention using augmentative and alternative communication (AAC) through individualized assessment. This article provides a review of the literature supporting the use of AAC during preschool for both language and literacy development in children with Down syndrome and children with autism spectrum disorder who have limited speech. A small scale exploratory report is discussed to highlight differences in early literacy skills found in children in each group. Implications for AAC intervention during preschool to support both language and literacy are discussed.