bluuebunny/crossref_metadata_2025_split huggingface dataset:
A large-scale population-based epidemiological study on the prevalence of central sensitization syndromes in Japan
Authors: Haruyama Yasuo , Sairenchi Toshimi , Uchiyama Koji , Suzuki Keisuke , Hirata Koichi , Kobashi Gen 
Published: December 2021

AbstractA cross-sectional study of 21,665 Japanese residents was performed to investigate the prevalence of central sensitization syndromes (CSS). CSS were assessed using the Central Sensitization Inventory (CSI-A). CSS were defined as a CSI-A score of 40 or higher. Age, sex, district, 10 CSS-related diseases (CSI-B), lifestyle, and mental factors were rated in a self-reported survey. The prevalence of CSS and its relationship with potential factors were examined by sex using descriptive and logistic regression models. The prevalence of CSS was 4.2% in all participants and was significantly higher in women (4.9%) than in men (2.7%). Adjusted odds ratios correlated with CSS for an age of 80–97 years versus 60–79 years (2.07 and 2.89), one or more CSI-B diseases (3.58 and 3.51), few sleeping hours (2.18 and 1.98), high perceived stress (5.00 and 4.91), low (2.94 and 2.71) and high (0.45 and 0.66) resilience versus moderate resilience, and exercise habits (0.68 and 0.55) in men and women (all P < 0.05). The relationship between CSS and age 20 and 59 years, ex-smokers, coffee intake, and alcohol intake differed by sex. The prevalence of CSS was estimated to be low in the healthy population. CSS correlated with CSS-related diseases and some positive and negative factors.
Efficacy of AAV serotypes to target Schwann cells after intrathecal and intravenous delivery
Authors: Kagiava A. , Richter J. , Tryfonos C. , Leal-Julià M. , Sargiannidou I. , Christodoulou C. , Bosch A. , Kleopa K. A. 
Published: December 2021

AbstractTo optimize gene delivery to myelinating Schwann cells we compared clinically relevant AAV serotypes and injection routes. AAV9 and AAVrh10 vectors expressing either EGFP or the neuropathy-associated gene GJB1/Connexin32 (Cx32) under a myelin specific promoter were injected intrathecally or intravenously in wild type and Gjb1-null mice, respectively. Vector biodistribution in lumbar roots and sciatic nerves was higher in AAVrh10 injected mice while EGFP and Cx32 expression rates and levels were similar between the two serotypes. A gradient of biodistribution away from the injection site was seen with both intrathecal and intravenous delivery, while similar expression rates were achieved despite higher vector amounts injected intravenously. Quantified immune cells in relevant tissues were similar to non-injected littermates. Overall, AAV9 and AAVrh10 efficiently transduce Schwann cells throughout the peripheral nervous system with both clinically relevant routes of administration, although AAV9 and intrathecal injection may offer a more efficient approach for treating demyelinating neuropathies.
Lifestyle and mental health 1 year into COVID-19
Authors: Barbieri Paolo Nicola , Giuntella Osea , Saccardo Silvia , Sadoff Sally 
Published: December 2021

AbstractIn previous work, Giuntella et al. (Proc Natl Acad Sci 118:e2016632118, 2021), we documented large disruptions to physical activity, sleep, time use and mental health among young adults at the onset of the COVID-19 pandemic in Spring 2020. This study explores the trends 1 year into COVID-19, as vaccines began to roll out, COVID-19 deaths declined, and social distancing measures eased in the United States. We combine biometric and survey data from multiple cohorts of college students spanning Spring 2019 through Spring 2021 (N = 1179). Our results show persistent impacts of the pandemic on physical activity and mental health. One year into the pandemic, daily steps averaged about 6300 per day compared to about 9800 per day prior to the pandemic, a 35% decline. Almost half of participants were at risk of clinical depression compared to a little over one-third prior to the pandemic, a 36% increase. The impacts on screen time, social interactions and sleep duration at the onset of COVID-19 largely dissipated over the course of the pandemic, though screen time remained significantly higher than pre-pandemic levels. In contrast to the sharp changes in lifestyle and mental health documented as the pandemic emerged in March 2020, we do not find evidence of behavioral changes or improvements in mental well-being over the course of Spring 2021 as the pandemic eased.
Elastic Correlation Adjusted Regression (ECAR) scores for high dimensional variable importance measuring
Authors: Zhou Yuan , Fa Botao , Wei Ting , Sun Jianle , Yu Zhangsheng , Zhang Yue 
Published: December 2021

AbstractInvestigation of the genetic basis of traits or clinical outcomes heavily relies on identifying relevant variables in molecular data. However, characteristics such as high dimensionality and complex correlation structures of these data hinder the development of related methods, resulting in the inclusion of false positives and negatives. We developed a variable importance measure method, termed the ECAR scores, that evaluates the importance of variables in the dataset. Based on this score, ranking and selection of variables can be achieved simultaneously. Unlike most current approaches, the ECAR scores aim to rank the influential variables as high as possible while maintaining the grouping property, instead of selecting the ones that are merely predictive. The ECAR scores’ performance is tested and compared to other methods on simulated, semi-synthetic, and real datasets. Results showed that the ECAR scores improve the CAR scores in terms of accuracy of variable selection and high-rank variables’ predictive power. It also outperforms other classic methods such as lasso and stability selection when there is a high degree of correlation among influential variables. As an application, we used the ECAR scores to analyze genes associated with forced expiratory volume in the first second in patients with lung cancer and reported six associated genes.
Tracking deep-sea internal wave propagation with a differential pressure gauge array
Authors: Yang Chu-Fang , Chi Wu-Cheng , van Haren Hans , Lin Ching-Ren , Kuo Ban-Yuan 
Published: December 2021

AbstractTemperature is used to trace ocean density variations, and reveals internal waves and turbulent motions in the deep ocean, called ‘internal motions.’ Ambient temperature detected by geophysical differential pressure gauges (DPGs) may provide year-long, complementary observations. Here, we use data from four DPGs fixed on the ocean bottom and a high-resolution temperature sensor (T-sensor) 13 m above the seafloor as a square-kilometer array deployed offshore ~ 50 km east of Taiwan facing the open Pacific Ocean to examine the impact of temperature on DPG signals related to internal motions. The DPG signals correlate with T-sensor temperature variations between 0.002 and 0.1 mHz, but have time shifts partially caused by slow thermal conduction from the ambient seafloor to the DPG chamber and partially by internal motion propagation time across the array. Applying beamforming-frequency-wavenumber analysis and linear regression to the arrayed T-sensor and DPG data, we estimate the propagating slowness of the internal motions to be between 0.5 and 7.4 s m−1 from the northwest and northeast quadrants of the array. The thermal relaxation time of the DPGs is within 103–104 s. This work shows that a systematic scan of DPG data at frequencies < 0.1 mHz may help shed light on patterns of internal wave propagation in the deep ocean, especially in multi-scale arrays.
A brain extraction algorithm for infant T2 weighted magnetic resonance images based on fuzzy c-means thresholding
Authors: Bae Inyoung , Chae Jong-Hee , Han Yeji 
Published: December 2021

AbstractIt is challenging to extract the brain region from T2-weighted magnetic resonance infant brain images because conventional brain segmentation algorithms are generally optimized for adult brain images, which have different spatial resolution, dynamic changes of imaging intensity, brain size and shape from infant brain images. In this study, we propose a brain extraction algorithm for infant T2-weighted images. The proposed method utilizes histogram partitioning to separate brain regions from the background image. Then, fuzzy c-means thresholding is performed to obtain a rough brain mask for each image slice, followed by refinement steps. For slices that contain eye regions, an additional eye removal algorithm is proposed to eliminate eyes from the brain mask. By using the proposed method, accurate masks for infant T2-weighted brain images can be generated. For validation, we applied the proposed algorithm and conventional methods to T2 infant images (0–24 months of age) acquired with 2D and 3D sequences at 3T MRI. The Dice coefficients and Precision scores, which were calculated as quantitative measures, showed the highest values for the proposed method as follows: For images acquired with a 2D imaging sequence, the average Dice coefficients were 0.9650 ± 0.006 for the proposed method, 0.9262 ± 0.006 for iBEAT, and 0.9490 ± 0.006 for BET. For the data acquired with a 3D imaging sequence, the average Dice coefficient was 0.9746 ± 0.008 for the proposed method, 0.9448 ± 0.004 for iBEAT, and 0.9622 ± 0.01 for BET. The average Precision was 0.9638 ± 0.009 and 0.9565 ± 0.016 for the proposed method, 0.8981 ± 0.01 and 0.8968 ± 0.008 for iBEAT, and 0.9346 ± 0.014 and 0.9282 ± 0.019 for BET for images acquired with 2D and 3D imaging sequences, respectively, demonstrating that the proposed method could be efficiently used for brain extraction in T2-weighted infant images.
Placozoan fiber cells: mediators of innate immunity and participants in wound healing
Authors: Mayorova Tatiana D. , Hammar Katherine , Jung Jae H. , Aronova Maria A. , Zhang Guofeng , Winters Christine A. , Reese Thomas S. , Smith Carolyn L. 
Published: December 2021

AbstractPlacozoa is a phylum of non-bilaterian marine animals. These small, flat organisms adhere to the substrate via their densely ciliated ventral epithelium, which mediates mucociliary locomotion and nutrient uptake. They have only six morphological cell types, including one, fiber cells, for which functional data is lacking. Fiber cells are non-epithelial cells with multiple processes. We used electron and light microscopic approaches to unravel the roles of fiber cells in Trichoplax adhaerens, a representative member of the phylum. Three-dimensional reconstructions of serial sections of Trichoplax showed that each fiber cell is in contact with several other cells. Examination of fiber cells in thin sections and observations of live dissociated fiber cells demonstrated that they phagocytose cell debris and bacteria. In situ hybridization confirmed that fiber cells express genes involved in phagocytic activity. Fiber cells also are involved in wound healing as evidenced from microsurgery experiments. Based on these observations we conclude that fiber cells are multi-purpose macrophage-like cells. Macrophage-like cells have been described in Porifera, Ctenophora, and Cnidaria and are widespread among Bilateria, but our study is the first to show that Placozoa possesses this cell type. The phylogenetic distribution of macrophage-like cells suggests that they appeared early in metazoan evolution.
Bacterial challenge-associated metabolic phenotypes in Hermetia illucens defining nutritional and functional benefits
Authors: Ho Phuc N. , Klanrit Poramate , Hanboonsong Yupa , Yordpratum Umaporn , Suksawat Manida , Kulthawatsiri Thanaporn , Jirahiranpat Anyarin , Deewai Suthicha , Mackawan Panya , Sermswan Rasana W. , Namwat Nisana , Loilome Watcharin , Khampitak Tueanjit , Wangwiwatsin Arporn , Phetcharaburanin Jutarop 
Published: December 2021

AbstractBlack soldier fly (BSF, Hermetia illucens) is popular for its applications in animal feed, waste management and antimicrobial peptide source. The major advantages of BSF larva include their robust immune system and high nutritional content that can be further developed into more potential agricultural and medical applications. Several strategies are now being developed to exploit their fullest capabilities and one of these is the immunity modulation using bacterial challenges. The mechanism underlying metabolic responses of BSF to different bacteria has, however, remained unclear. In the current study, entometabolomics was employed to investigate the metabolic phenoconversion in response to either Escherichia coli, Staphylococcus aureus, or combined challenges in BSF larva. We have, thus far, characterised 37 metabolites in BSF larva challenged with different bacteria with the major biochemical groups consisting of amino acids, organic acids, and sugars. The distinct defense mechanism-specific metabolic phenotypes were clearly observed. The combined challenge contributed to the most significant metabolic phenoconversion in BSF larva with the dominant metabolic phenotypes induced by S. aureus. Our study suggested that the accumulation of energy-related metabolites provided by amino acid catabolism is the principal metabolic pathway regulating the defense mechanism. Therefore, combined challenge is strongly recommended for raising BSF immunity as it remarkably triggered amino acid metabolisms including arginine and proline metabolism and alanine, aspartate and glutamate metabolism along with purine metabolism and pyruvate metabolism that potentially result in the production of various nutritional and functional metabolites.
Adaptation and validation of a German version of the Dickman impulsivity inventory for the assessment of functional and dysfunctional impulsivity
Authors: Hüpen Philippa , Henn Alina T. , Habel Ute 
Published: December 2021

AbstractImpulsive behavior tends to have a negative connotation in the sense that it is usually associated with detrimental or dysfunctional outcomes. However, under certain circumstances, impulsive behaviors may also have beneficial or functional outcomes. Dickman’s Impulsivity Inventory (DII) measures these two distinct aspects of impulsivity, namely, dysfunctional impulsivity (the tendency to act with less forethought than do most people which leads to difficulties) and functional impulsivity (the tendency to act with little forethought when the situation is optimal). In the present study, we translated the DII into German and validated the German version in a sample of 543 adults. The original 23-item model was considered unsuitable for the German version as suggested by fit indices of a confirmatory factor analysis. Exploratory factor analyses rather supported a 16-item version. Further psychometric analyses and inferential statistical analyses on the final German DII indicated its appropriateness for use in German-speaking populations and support a two-factor solution of the DII. Finally, exploratory analyses on the German DII suggest differential relationships between dysfunctional and functional impulsivity and self-reported lifestyle-related variables (smoking, alcohol usage, and sports behavior).
Complex correlations between microstructure and magnetic behavior in SrFe12O19 hexaferrite nanoparticles
Authors: Maltoni Pierfrancesco , Ivanov Sergey A. , Barucca Gianni , Varvaro Gaspare , Peddis Davide , Mathieu Roland 
Published: December 2021

AbstractThe magnetic properties of SrFe12O19 (SFO) hard hexaferrites are governed by the complex relation to its microstructure, determining their relevance for permanent magnets´ applications. A set of SFO nanoparticles obtained by sol–gel self-combustion synthesis was selected for an in-depth structural X-Rays powder diffraction (XRPD) characterization by means of G(L) line-profile analysis. The obtained crystallites´ size distribution reveal a clear dependence of the size along the [001] direction on the synthesis approach, resulting in the formation of platelet-like crystallites. In addition, the size of the SFO nanoparticles was determined by transmission electron microscopy (TEM) analysis and the average number of crystallites within a particle was estimated. These results have been evaluated to illustrate the formation of single-domain state below a critical value, and the activation volume was derived from time dependent magnetization measurements, aiming to clarify the reversal magnetization process of hard magnetic materials.
Sports related concussion: an emerging era in digital sports technology
Authors: Powell Dylan , Stuart Sam , Godfrey Alan 
Published: December 2021

AbstractSports-related concussion (SRC) is defined as a mild traumatic brain injury (mTBI) leading to complex impairment(s) in neurological function with many seemingly hidden or difficult to measure impairments that can deteriorate rapidly without any prior indication. Growing numbers of SRCs in professional and amateur contact sports have prompted closer dialog regarding player safety and welfare. Greater emphasis on awareness and education has improved SRC management, but also highlighted the difficulties of diagnosing SRC in a timely manner, particularly during matches or immediately after competition. Therefore, challenges exist in off-field assessment and return to play (RTP) protocols, with current traditional (subjective) approaches largely based on infrequent snapshot assessments. Low-cost digital technologies may provide more objective, integrated and personalized SRC assessment to better inform RTP protocols whilst also enhancing the efficiency and precision of healthcare assessment. To fully realize the potential of digital technologies in the diagnosis and management of SRC will require a significant paradigm shift in clinical practice and mindset. Here, we provide insights into SRC clinical assessment methods and the translational utility of digital approaches, with a focus on off-field digital techniques to detect key SRC metrics/biomarkers. We also provide insights and recommendations to the common benefits and challenges facing digital approaches as they aim to transition from novel technologies to an efficient, valid, reliable, and integrated clinical assessment tool for SRC. Finally, we highlight future opportunities that digital approaches have in SRC assessment and management including digital twinning and the “digital athlete”.
KSHV transactivator-derived small peptide traps coactivators to attenuate MYC and inhibits leukemia and lymphoma cell growth
Authors: Shimoda Michiko , Lyu Yuanzhi , Wang Kang-Hsin , Kumar Ashish , Miura Hiroki , Meckler Joshua F. , Davis Ryan R. , Chantarasrivong Chanikarn , Izumiya Chie , Tepper Clifford G. , Nakajima Ken-ichi , Tuscano Joseph , Barisone Gustavo , Izumiya Yoshihiro 
Published: December 2021

AbstractIn herpesvirus replicating cells, host cell gene transcription is frequently down-regulated because important transcriptional apparatuses are appropriated by viral transcription factors. Here, we show a small peptide derived from the Kaposi’s sarcoma-associated herpesvirus transactivator (K-Rta) sequence, which attenuates cellular MYC expression, reduces cell proliferation, and selectively kills cancer cell lines in both tissue culture and a xenograft tumor mouse model. Mechanistically, the peptide functions as a decoy to block the recruitment of coactivator complexes consisting of Nuclear receptor coactivator 2 (NCOA2), p300, and SWI/SNF proteins to the MYC promoter in primary effusion lymphoma cells. Thiol(SH)-linked alkylation for the metabolic sequencing of RNA (SLAM seq) with target-transcriptional analyses further confirm that the viral peptide directly attenuates MYC and MYC-target gene expression. This study thus provides a unique tool to control MYC activation, which may be used as a therapeutic payload to treat MYC-dependent diseases such as cancers and autoimmune diseases.
Multi‐stream densely connected network for semantic segmentation
Authors: Jia Dayu , Cao Jiale , Pan Jing , Pang Yanwei 
Published: December 2021

AbstractSemantic segmentation is a challenging task in computer vision which is widely used in autonomous driving and scene understanding. State‐of‐the‐art semantic segmentation networks, like DeepLab and PSPNet, make full use of multiple feature information to improve spatial resolution. However, the feature resolution in the scale‐axis is not dense enough for practical applications. To tackle this problem, a multi‐stream network is designed with atrous convolutional layers at multiple rates to capture objects and context at multiple scales. Furthermore, intra‐connections and inter‐connections are designed to fuse multi‐scale features densely which produce a feature pyramid with much larger scale diversity and larger receptive field by involving small quantity of computation. The proposed module can be easily used in other methods and it helps to increase the performance. Compared with existing methods, the proposed network, called Multi‐stream Densely Connected Network, reaches competitive results on ADE20K dataset, PASCAL VOC 2012 dataset, and Cityscapes dataset.
Data augmentation and shadow image classification for shadow detection
Authors: Li Guoquan , Wen Lingyun , Huang Zhengwen , Xia Ruiyang , Pang Yu 
Published: December 2021

AbstractShadow detection is an important branch of computer vision. Recently, convolutional neural network (CNN)‐based methods for shadow detection have achieved better performance than methods based on manually designed features. However, CNNs are extremely hungry for data and the training of CNN‐based shadow detector requires time‐consuming and expensive pixel‐level annotations. To alleviate this problem in shadow detection, a method of data augmentation based on generative adversarial network (GAN), named ShadowGAN, has been proposed. Given a shadow mask and a shadow‐free image, our ShadowGAN can generate shadow images with labels. To guide the training of ShadowGAN and get more realistic shadow images, loss is further implemented to impose a restriction between real shadow images and generated shadow images. The effectiveness of ShadowGAN is demonstrated by training existing shadow detectors on enlarged dataset. In addition, to better make use of shadow‐free images in shadow detection, shadow image classification task is added for the shadow detectors. Experiments show that this task can guide the feature extraction network to learn more robust shadow features. At last, these two methods are combined and a better performance of shadow detection is achieved.
Nachtlärminduzierte Schlafstörungen und Herz-Kreislauf-Risiko
Authors: Hahad Omar , Röösli Martin , Daiber Andreas , Münzel Thomas 
Published: December 2021

ZusammenfassungBeeinträchtigungen des Schlafes im Sinne von Insomnien, d. h. Ein- und Durchschlafschwierigkeiten, frühmorgendliches Erwachen und ein chronisch unerholsamer Schlaf, sind weit verbreitet in der Bevölkerung und gehen mit einer Vielzahl von körperlichen und psychischen Gesundheitsstörungen einher. Die umweltbedingten Ursachen für Schlafstörungen umfassen eine ganze Reihe von Faktoren, wobei nächtlicher Lärm als eine wichtige Ursache gilt. Aktuelle Daten der Europäischen Umweltagentur zeigen, dass Umgebungslärm (Straßenverkehrs-, Schienen-, Flug- und Industrielärm) für starke Schlafstörungen bei 6,5 Millionen Personen in Europa sorgt. Neue epidemiologische und mechanistische Feldstudien zeigen, dass vor allem nächtlicher Verkehrslärm unter anderem zu einer eingeschränkten Gefäßfunktion, thromboinflammatorischen Veränderungen, einem Anstieg von Stresshormonen und einem erhöhten Blutdruck führen kann, die bedeutsame Risikofaktoren für Herz-Kreislauf-Erkrankungen darstellen. Gemäß
der Europäischen Umweltagentur führt der Umgebungslärm jährlich zu 48000 zusätzlichen Fällen von ischämischen Herzerkrankungen sowie 12000 vorzeitigen Todesfällen.