bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluating the Implementation of Injury Prevention Strategies in
Rugby Union and League: A Systematic Review using the RE-AIM
Framework
Authors: Barden Craig , Bekker Sheree , Brown James Craig , Stokes Keith A , McKay Carly D. 
Published: July 2020

AbstractRugby (union and league) has come under intense scrutiny due to its injury risk.
Various interventions have been introduced to protect players from injury, with
many deemed efficacious and advocated for use across various worldwide contexts.
However, their implementation is less clear. The objective of this systematic
review was to determine whether injury prevention interventions in rugby have
evaluated their ‘reach’,
‘effectiveness’, ‘adoption’,
‘implementation’ and
‘maintenance’ as per the RE-AIM Multi-Dimension Item
Checklist. Six electronic databases were searched in November 2019. Inclusion
criteria included: English language, peer-reviewed journal article, original
research, field-based rugby code, prospective intervention. Of the 4253 studies
identified, 74 met the full inclusion criteria. Protective equipment,
predominately mouthguards, was the intervention of interest in 44 studies. Other
interventions included multimodal national injury prevention programmes, law
changes and neuromuscular training programmes. ‘Effectiveness’
was the highest scoring RE-AIM dimension (55%), followed by
‘reach’ (26%). All other RE-AIM dimensions scored below
20%. Research currently focuses on determining intervention
‘effectiveness’. For injury prevention strategies to have their
desired impact, there must be a shift to address all determinants associated
with implementation. Consideration should be given to how this can be achieved
by adopting specific reporting checklists, research frameworks and study
designs.
Neonatal Morbidity of Monoamniotic Twin Pregnancies: A Systematic Review and Meta-analysis
Authors: Buca Danilo , Di Mascio Daniele , Khalil Asma , Acharya Ganesh , Van Mieghem Tim , Hack Karien , Murata Masaharu , Anselem Olivia , D'Amico Alice , Muzii Ludovico , Liberati Marco , Nappi Luigi , D'Antonio Francesco 
Published: July 2020

Objective This study was aimed to report the incidence of neonatal morbidity in monochorionic monoamniotic (MCMA) twin pregnancies according to gestational age at birth and type of management adopted (inpatient or outpatient).
Study Design Medline and Embase databases were searched. Inclusion criteria were nonanomalous MCMA twins. The primary outcome was a composite score of neonatal morbidity, defined as the occurrence of at least one of the following outcomes: respiratory morbidity, overall neurological morbidity, severe neurological morbidity, and infectious morbidity, necrotizing enterocolitis at different gestational age windows (24–30, 31–32, 33–34, and 35–36 weeks). Secondary outcomes were the individual components of the primary outcome and admission to neonatal intensive care unit (NICU). Subanalysis according to the type of surveillance strategy (inpatient compared with outpatient) was also performed. Random effect meta-analyses were used to analyze the data.
Results A total of 14 studies including 685 MCMA twin pregnancies without fetal anomalies were included. At 24 to 30, 31 to 32, 33 to 34, and 35 to 36 weeks of gestation, the rate of composite morbidity was 75.4, 65.5, 37.6, and 18.5%, respectively, the rate of respiratory morbidity was 74.2, 59.1, 35.5, and 12.2%, respectively, while overall neurological morbidity occurred in 15.3, 10.2, 4.3, and 0% of the cases, respectively. Infectious morbidity complicated 13, 4.2, 3.1, and 0% of newborns while 92.1, 81.6, 58.7, and 0% of cases required admission to NICU. Morbidity in pregnancies delivered between 35 and 36 weeks of gestation was affected by the very small sample size of cases included. When comparing the occurrence of overall morbidity according to the type of management (inpatient or outpatient), there was no difference between the two surveillance strategies (p = 0.114).
Conclusion MCMA pregnancies are at high risk of composite neonatal morbidity, mainly respiratory morbidity that gradually decreases with increasing gestational age at delivery with a significant reduction for pregnancies delivered between 33 and 34 weeks. We found no difference in the occurrence of neonatal morbidity between pregnancies managed as inpatient or outpatient.
Key Points
Modern bio and chemical sensors and neuromorphic devices based on organic semiconductors
Authors: Shaposhnik Polina A. , Zapunidi Sergey A. , Shestakov Mikhail V. , Agina Elena V. , Ponomarenko Sergey A. 
Published: July 2020

This review summarizes and highlights the current state-of-the-art of research on chemical sensors and biosensors in liquid environment and neuromorphic devices based on electrolyte-gated organic transistors with the active semiconductor layer of organicπ-conjugated materials (small molecules, oligomers and polymers). The architecture and principles of operation of electrolyte-gated organic transistors and the main advantages and drawbacks of these devices are considered in detail. The criteria for the selection of organic semiconductors for these devices are presented. The causes of degradation of semiconductor layers and ways of their elimination are discussed. Examples of the use of electrolyte-gated organic transistors as bio and chemical sensors, artificial synapses and computing devices are given.The bibliography includes 132 references.
Predicting personality from patterns of behavior collected with smartphones
Authors: Stachl Clemens , Au Quay , Schoedel Ramona , Gosling Samuel D. , Harari Gabriella M. , Buschek Daniel , Völkel Sarah Theres , Schuwerk Tobias , Oldemeier Michelle , Ullmann Theresa , Hussmann Heinrich , Bischl Bernd , Bühner Markus 
Published: July 2020

Significance
Smartphones are sensor-rich computers that can easily be used to collect extensive records of behaviors, posing serious threats to individuals’ privacy. This study examines the extent to which individuals’ personality dimensions (assessed at broad domain and narrow facet levels) can be predicted from six classes of behavior: 1) communication and social behavior, 2) music consumption, 3) app usage, 4) mobility, 5) overall phone activity, and 6) day- and night-time activity, in a large sample. The cross-validated results show which Big Five personality dimensions are predictable and which specific patterns of behavior are indicative of which dimensions, revealing communication and social behavior as most predictive overall. Our results highlight the benefits and dangers posed by the widespread collection of smartphone data.
CACNA1S haploinsufficiency confers resistance to New World arenavirus infection
Authors: Sarute Nicolás , Ross Susan R. 
Published: July 2020

Significance
It is well known that genetic differences among individuals can influence their susceptibility to infectious disease. Our results, using New World arenavirus-infected mice heterozygous for the α1S chain of the VGCC, human cells heterozygous for a mutation of this chain, and drugs that target this receptor, highlight the influence of genetic background on the outcome of infection and zoonoses. These findings also confirm the use of VGCCs as potential therapeutic targets and pave the way for understanding the relationship between genetics, susceptibility to infection, and antiviral drug efficacy.
Regulation of myonuclear positioning and muscle function by the skeletal muscle-specific CIP protein
Authors: Liu Jianming , Huang Zhan-Peng , Nie Mao , Wang Gang , Silva William J. , Yang Qiumei , Freire Paula P. , Hu Xiaoyun , Chen Huaqun , Deng Zhongliang , Pu William T. , Wang Da-Zhi 
Published: July 2020

SignificanceThe arrangement of nuclei in myofibers, which are multinucleated skeletal muscle cells, is essential for their proper function. Abnormal nuclear positioning in myofibers is a common feature of several skeletal muscle diseases, including centronuclear myopathy and muscular dystrophy. Here, we show an isoform of the CIP protein (sk-CIP) contributes to the regulation of the positioning of nuclei in myofibers by interacting with both the LINC complex (Linker of Nucleoskeleton and Cytoskeleton) and proteins in the microtubule-organizing center (MTOC). Through these interactions, sk-CIP appears to function as a skeletal muscle-specific anchoring protein that regulates nuclear positioning in myofibers. Further investigation and understanding of myofiber nuclear positioning may facilitate the development of novel therapies for some diseases of skeletal muscle.
Microbial tryptophan metabolites regulate gut barrier function via the aryl hydrocarbon receptor
Authors: Scott Samantha A. , Fu Jingjing , Chang Pamela V. 
Published: July 2020

Significance
The gut microbiome comprises trillions of microorganisms that inhabit the mammalian intestines. These microbes regulate many aspects of host physiology, including defense mechanisms against factors that contribute to inflammatory bowel diseases (IBDs). Despite the abundance of the gut microbiota, little is known regarding how these microbes modulate these host processes, including the barrier function of the intestinal epithelium, which controls intestinal permeability associated with IBDs. Here, we discover that three gut microbially produced, small-molecule metabolites, which derive from dietary tryptophan, improve intestinal barrier integrity and protect against inflammation caused by IBDs. Our studies identify a host receptor and downstream targets of the metabolites, which could serve as potential pathways for prophylactic and therapeutic treatments for ameliorating morbidity in IBDs.
The human cerebellum has almost 80% of the surface area of the neocortex
Authors: Sereno Martin I. , Diedrichsen Jörn , Tachrount Mohamed , Testa-Silva Guilherme , d’Arceuil Helen , De Zeeuw Chris 
Published: July 2020

Significance
The cerebellum has long been recognized as a partner of the cerebral cortex, and both have expanded greatly in human evolution. The thin cerebellar cortex is even more tightly folded than the cerebral cortex. By scanning a human cerebellum specimen at ultra-high magnetic fields, we were able to computationally reconstruct its surface down to the level of the smallest folds, revealing that the cerebellar cortex has almost 80% of the surface area of the cerebral cortex. By performing the same procedure on a monkey brain, we found that the surface area of the human cerebellum has expanded even more than that of the human cerebral cortex, suggesting a role in characteristically human behaviors, such as toolmaking and language.
Flow-accelerated platelet biogenesis is due to an elasto-hydrodynamic instability
Authors: Bächer Christian , Bender Markus , Gekle Stephan 
Published: July 2020

Significance
To maintain the high number of blood platelets in mammalian blood, an exceptionally efficient process for platelet biogenesis is required. While recent in vitro experiments demonstrate blood flow as a key factor accelerating biogenesis, the biophysical mechanism behind this acceleration remains unclear. Here we use computer simulations to show how fluid flow can indeed strongly increase biogenesis. The key aspect of our work is that we introduce a physical mechanism, akin to the well-known Rayleigh–Plateau instability of a liquid jet, as the likely origin of accelerated platelet production. Our findings can lead to a more efficient design of microfluidic bioreactors for platelet production, but also explain the exceptionally strong coupling of fluid flow and platelet biogenesis in vivo.
Bacterial synthesis of C3-C5 diols via extending amino acid catabolism
Authors: Wang Jian , Li Chenyi , Zou Yusong , Yan Yajun 
Published: July 2020

SignificanceTo date, most industrially relevant bioproduction processes rely on sugar-based feedstocks, whereas utilization of ever-increasing protein wastes or hydrolysates, e.g., amino acids (AAs), for chemical production has been less explored. Currently, AAs that generated from cheap protein-rich wastes or overproduced from industrial fermentation mainly serve as animal feed additives and flavor ingredients. Considering the natural abundance and structural diversity of AAs, they may serve as new platform chemicals for chemical expansion in microbial systems. Through combination of a common catabolism of charged AAs and a diol production pathway, we devise a general metabolic platform that converts multiple AAs and glucose into C3-C5 diols. Our work presents a platform that enriches the pathway repertoire for nonnatural diols with expanded feedstock flexibility.
Kinetically distinct processing pathways diversify the CD8+T cell response to a single viral epitope
Authors: Cosma Gabriela L. , Lobby Jenna L. , Fay Elizabeth J. , Siciliano Nicholas A. , Langlois Ryan A. , Eisenlohr Laurence C. 
Published: July 2020

SignificanceCD8+T cells eliminate infections and cancers through recognition of antigen-derived peptides displayed at the cell surface in combination with MHC class I molecules. We show that a single glycoprotein-derived epitope is generated from two sources: 1) the conventional cohort that is delivered to the endoplasmic reticulum, a fraction failing quality control and undergoing ERAD, and 2) an exceedingly minor fraction that is mislocalized to the cytosol during translation and immediately degraded. Notably, peptide derived from mislocalized antigen is delivered to the cell surface with faster kinetics and drives greater CD8+T cell expansion and functionality. These findings provide key insights for development of vaccines intended to elicit CD8+T cell-mediated protection.
CD4 T cell-intrinsic role for the T helper 17 signature cytokine IL-17: Effector resistance to immune suppression
Authors: Crawford Michael P. , Sinha Sushmita , Renavikar Pranav S. , Borcherding Nicholas , Karandikar Nitin J. 
Published: July 2020

SignificanceCD4+ T helper (Th) cells come in several flavors, largely defined by their cytokine profiles. Th17 cells, characterized by the production of IL-17 family cytokines, play important roles in the body’s response to infections and cancer and in the pathogenesis of autoimmune diseases. This study reveals an unexpected role for the T helper 17 signature cytokines: IL-17A, IL-17F, and IL-17AF. We show that these cytokines can act directly on CD4 T cells to make them resistant to immune regulation. This resistance is mediated through IL-1β–mediated and IL-6–mediated pathways in a T cell-intrinsic manner. These findings have broad implications in multiple settings involving immune-mediated responses (including autoimmunity, cancer therapy, and chronic infectious disease).
Unroofing site-specific α-synuclein–lipid interactions at the plasma membrane
Authors: Kaur Upneet , Lee Jennifer C. 
Published: July 2020

Significance
α-Synuclein is a neuronal protein with an ill-defined biological function that is central to Parkinson’s disease etiology. While considered to be involved in exocytosis, how α-synuclein facilitates synaptic vesicle fusion and release remains an open question. To address this, we investigated α-synuclein–lipid interactions at the plasma membrane through the technique of cellular unroofing, which uncovers an intact basal membrane. We conclusively show that α-synuclein is recruited to exocytic sites, preferring liquid-ordered lipid domains. Importantly, heterogeneous populations of α-synuclein conformers are revealed by measurements of fluorescence lifetime distributions, which are not adequately described by current models of α-synuclein structures. Membrane-bound α-synuclein is conformationally dynamic, exquisitely sensitive to lipid/protein composition, enabling the protein to carry out its function.
Hydrogels as dynamic memory with forgetting ability
Authors: Yu Chengtao , Guo Honglei , Cui Kunpeng , Li Xueyu , Ye Ya Nan , Kurokawa Takayuki , Gong Jian Ping 
Published: July 2020

Significance
Life provides the best demonstration of complex and adaptive nonequilibrium system, which executes biological functions through nonequilibrium structure transformation. Creating lifelike materials to achieve part of or full biological functions is a grand challenge. Traditional memories from hard and dry materials are static, with no ability of forgetting; here we propose to use soft and wet hydrogels to achieve dynamic memories with spontaneous but learning-strength-dependent forgetting ability by using nonequilibrium structure transformation, in analogy to the human brain. We believe the concept of dynamic memorizing–forgetting behavior proposed here inspires further research on developing lifelike materials based on the nonequilibrium process of soft matter.
CASTLE: cell adhesion with supervised training and learning environment
Authors: Gilbert S G , Krautter F , Cooper D , Chimen M , Iqbal A J , Spill F 
Published: July 2020

AbstractDifferent types of microscopy are used to uncover signatures of cell adhesion and mechanics. Automating the identification and analysis often involve sacrificial routines of cell manipulation such asin vitrostaining. Phase-contrast microscopy (PCM) is rarely used in automation due to the difficulties with poor quality images. However, it is the least intrusive method to provide insights into the dynamics of cells, where other types of microscopy are too destructive to monitor. In this study, we propose an efficient workflow to automate cell counting and morphology in PCM images. We introduce Cell Adhesion with Supervised Training and Learning Environment (CASTLE), available as a series of additional plugins to ImageJ. CASTLE combines effective techniques for phase-contrast image processing with statistical analysis and machine learning algorithms to interpret the results. The proposed workflow was validated by comparing the results to a manual count and manual segmentation of cells in images investigating different adherent cell types, including monocytes, neutrophils and platelets. In addition, the effect of different molecules on cell adhesion was characterised using CASTLE. For example, we demonstate that Galectin-9 leads to differences in adhesion of leukocytes. CASTLE also provides information using machine learning techniques, namely principal component analysis andk-means clustering, to distinguish morphology currently inaccessible with manual methods. All scripts and documentation are open-source and available at the corresponding GitLab project.
A combination of residual and long–short-term memory networks for bearing fault diagnosis based on time-series model analysis
Authors: Wang Youming , Cheng Lin 
Published: July 2020

Abstract
Data-driven methods have been considered as an effective tool for detecting the nonlinear and complex changes of time-series data and extracting early fault features from bearing vibration measurements in industrial applications. Due to the lack of a feature extraction ability of the residual network, which is an existing typical intelligent fault diagnosis deep model of bearing vibration signal, it is difficult to capture the long-term dependence between the time-series data. To overcome this problem, we propose a combination of residual and long–short-term memory networks (Resnet-LSTM) and develop a fused time-series model. The two-dimensional signal of bearing vibration is input into the residual network and the local feature is extracted by embedding a residual layer. In addition, the bearing feature information is loaded into a long-term memory unit and the forgetting mechanism is introduced to extract the global features of the time-series data. The advantage of the proposed method is that it takes full advantage of all the local deep features and global time-series features from the bearing vibration signal. This approach enables us to learn sequential features in different interval lengths and capture the local sequence features of the data information flow, which can improve the fault diagnosis accuracy of existing methods. Experimental results demonstrate that the proposed method outperforms other common methods in single and compound fault diagnoses of bearings.
Dose quantification in carbon ion therapy using in-beam positron emission tomography
Authors: Rutherford Harley , Chacon Andrew , Mohammadi Akram , Takyu Sodai , Tashima Hideaki , Yoshida Eiji , Nishikido Fumihiko , Hofmann Theresa , Pinto Marco , Franklin Daniel R , Yamaya Taiga , Parodi Katia , Rosenfeld Anatoly B , Guatelli Susanna , Safavi-Naeini Mitra 
Published: July 2020

Abstract
This work presents an iterative method for the estimation of the absolute dose distribution in patients undergoing carbon ion therapy, via analysis of the distribution of positron annihilations resulting from the decay of positron-emitting fragments created in the target volume. The proposed method relies on the decomposition of the total positron-annihilation distributions into profiles of the three principal positron-emitting fragment species - 11C, 10C and 15O. A library of basis functions is constructed by simulating a range of monoenergetic 12C ion irradiations of a homogeneous polymethyl methacrylate phantom and measuring the resulting one-dimensional positron-emitting fragment profiles and dose distributions. To estimate the dose delivered during an arbitrary polyenergetic irradiation, a linear combination of factors from the fragment profile library is iteratively fitted to the decomposed positron annihilation profile acquired during the irradiation, and the resulting weights combined with the corresponding monoenergetic dose profiles to estimate the total dose distribution. A total variation regularisation term is incorporated into the fitting process to suppress high-frequency noise. The method was evaluated with 14 different polyenergetic 12C dose profiles in a polymethyl methacrylate target: one which produces a flat biological dose, 10 with randomised energy weighting factors, and three with distinct dose maxima or minima within the spread-out Bragg peak region. The proposed method is able to calculate the dose profile with mean relative errors of 0.8%, 1.0% and 1.6% from the 11C, 10C, 15O fragment profiles, respectively, and estimate the position of the distal edge of the SOBP to within an average of 0.7 mm, 1.9 mm and 1.2 mm of its true location.
Influence of Tourist Experience On Tourist Destinations Against Loyalty Through The Value of Traveling
Authors: Sukaris  , Suyono Joko , Ratnasahara Elisabeth Damarsari 
Published: July 2020

Abstract
Today, the owners of tourist destinations are aware of the inportance of brand strategy, they are also aware that the creation of experience and value for tourists is the most important part in achieving competitive advantage. Only tourist destinations providing impressive experiences and best value that can create tourist loyalty on tourist destinations, and only this loyalty is related to the sustainability of tourist destinations in the future. The research objective was to examine the conceptual model of the influence of experience on tourist destinations on tourist loyalty through the value of traveling. Data collection was done with a one-time collection approach through questionnaires to tourists who have finished visiting Lamongan Tourism Bahari. In answering the research objectives and assessing the model compiled, the analysis technique used was technical analysis of Structural Equation Modeling (SEM) using the LISREL 8.8 software program. The results show that the experience of tourists after a visit has a significant effect on the value perceived by tourists after visiting tourist destinations, tourists experience after visiting has a significant effect on tourists loyalty and the value felt by tourists after visiting has a significant effect on tourists loyalty.