bluuebunny/crossref_metadata_2025_split huggingface dataset:
Drug Survival of Biologic Therapy in Elderly Patients With Rheumatoid Arthritis Compared With Nonelderly Patients
Authors: Jung Seung Min , Lee Sang-Won , Song Jason Jungsik , Park Sung-Hwan , Park Yong-Beom 
Published: December 2020

Objective
Although the proportion of elderly patients with rheumatoid arthritis (RA) is increasing, the persistency of biologic therapy in elderly patients requires additional investigation. This study evaluated the drug survival of biologic therapy and associated factors in elderly compared with nonelderly patients.

Methods
This longitudinal observational study included RA patients who were enrolled in the Korean College of Rheumatology Biologics Registry (NCT01965132, started from January 1, 2013) between 2013 and 2015. We compared the retention rate of biologic therapy between elderly (age ≥70 years) and nonelderly (age <70 years) patients, and investigated the causes and predictors of biologic withdrawal in both groups.

Results
Of 682 patients, 122 were aged 70 years or older. The retention rate of biologic therapy at 24 months was 57.8% and 46.5% in nonelderly and elderly patients, respectively (p = 0.027). Biologic withdrawal due to adverse events and inefficacy within 24 months was not significantly different between the 2 groups, although adverse events were more common in elderly patients (20.6% vs 12.8%, p = 0.360). Drug withdrawal due to patient refusal was more common in elderly patients (9.8% vs 1.8%, p < 0.001). In elderly patients, biologic withdrawal was associated with current smoking and older age at disease onset, whereas the use of tumor necrosis factor inhibitors, nonuse of methotrexate, and combination of corticosteroid were important in nonelderly patients.

Conclusions
Elderly RA patients are more likely to discontinue biologic agents within 24 months. To increase the retention rate of biologic therapy, rheumatologists should consider patient characteristics before and during biologic therapy.
MRI Features Associated With the Detection of Microbial Pathogens by CT-Guided Biopsy in Septic Spondylodiscitis
Authors: Chotard Emilie , Jacquier Hervé , Bart Géraldine , Richette Pascal , Rioux Christophe , Joly Véronique , Goossens Julia , Palazzo Elisabeth , Forien Marine , Jelin Germain , Yazdanpanah Yazdan , Dieudé Philippe , Le Goff Benoît , Ottaviani Sébastien 
Published: December 2020

Objective
The aim of this study was to assess the magnetic resonance imaging (MRI) features associated with microbial pathogen detection by computed tomography (CT)–guided biopsy in patients with suspected septic spondylodiscitis.

Methods
For the last 10-year period, we analyzed the medical records of patients who underwent MRI and CT-guided biopsy for suspected septic spondylodiscitis. Clinical characteristics were recorded. The following MRI features were assessed: edema or contrast enhancement of the intervertebral disc, adjacent vertebrae, epidural and paravertebral space, presence of abscess, and paravertebral edema size. A positive biopsy was defined by pathogen identification on bacterial analysis or the presence of granuloma on histology. Predictors of a positive biopsy were assessed with a logistic regression model.

Results
We examined data for 61 patients (34 [56%] male; mean age, 59.9 ± 18.0 years); for 35 patients (57%), CT-guided biopsy was positive for a pathogen. The 4 MRI findings significantly associated with a positive biopsy were epiduritis, greater than 50% vertebral endplate edema, loss of intradiscal cleft, and abscess. The size of paravertebral edema was greater with a positive than negative biopsy (median, 15.9 [interquartile range, 11.3–21.3] vs 7.3 [4.6–12.9] mm; p = 0.004). On multivariable analysis, epiduritis was the only independent predictor of a positive biopsy (adjusted odds ratio, 7.4 [95% confidence interval, 1.7–31.4]; p = 0.006).

Conclusions
Epiduritis and the size of paravertebral edema on MRI are associated with detection of a microbial pathogen in suspected septic spondylodiscitis. For patients without these MRI signs, the need for further investigations such as enriched or prolonged cultures, a second CT-guided biopsy, or even surgical biopsy need to be discussed.
Predictors of Physical Activity in Patients With Fibromyalgia
Authors: Kaleth Anthony S. , Bigatti Silvia M. , Slaven James E. , Kelly Nicholas , Ang Dennis C. 
Published: December 2020

Background/Objective
The aim of this study was to identify psychological factors that influence moderate-vigorous physical activity (MVPA) participation in patients with fibromyalgia.

Methods
In this secondary data analysis, 170 patients received personalized exercise plans and completed baseline and follow-up assessments of self-reported physical activity at weeks 12, 24, and 36. Structural equation modeling was used to examine the predictive strengths of psychological factors (exercise self-efficacy, perceived barriers, and intention) on MVPA participation.

Results
Using a threshold increase in MVPA of 10 or greater metabolic equivalent hours per week (MET h/wk), 3 groups were defined based on subjects who achieved a minimum increase of 10 MET h/wk that was sustained for at least 12 weeks (SUS-PA), achieved an increase of 10 MET h/wk that was not sustained for at least 12 weeks (UNSUS-PA), and did not achieve an increase of 10 MET h/wk (LO-PA). Increases in exercise self-efficacy and intention and reductions in perceived barriers were associated with increased volume of PA, showing the greatest change in the SUS-PA, followed by UNSUS-PA. For the LO-PA group, there was no change in exercise self-efficacy, a decrease in intention, and an increase in barriers. Using path analysis, exercise self-efficacy and perceived barriers were associated with higher volumes of physical activity via greater intention to engage in MVPA.

Conclusions
For patients with fibromyalgia, exercise self-efficacy, perceived barriers, and intention to exercise are important constructs for increasing physical activity. Our findings provide guidance for practitioners who seek to promote physical activity in fibromyalgia and suggestions for researchers aiming to improve prediction models.
SnapHiC: a computational pipeline to map chromatin contacts from single cell Hi-C data
Authors: Yu Miao , Abnousi Armen , Zhang Yanxiao , Li Guoqiang , Lee Lindsay , Chen Ziyin , Fang Rongxin , Wen Jia , Sun Quan , Li Yun , Ren Bing , Hu Ming 
Published: December 2020

AbstractSingle cell Hi-C (scHi-C) analysis has been increasingly used to map the chromatin architecture in diverse tissue contexts, but computational tools to define chromatin contacts at high resolution from scHi-C data are still lacking. Here, we describe SnapHiC, a method that can identify chromatin loops at high resolution and accuracy from scHi-C data. We benchmark SnapHiC against HiCCUPS, a common tool for mapping chromatin contacts in bulk Hi-C data, using scHi-C data from 742 mouse embryonic stem cells. We further demonstrate its utility by analyzing single-nucleus methyl-3C-seq data from 2,869 human prefrontal cortical cells. We uncover cell-type-specific chromatin loops and predict putative target genes for non-coding sequence variants associated with neuropsychiatric disorders. Our results suggest that SnapHiC could facilitate the analysis of cell-type-specific chromatin architecture and gene regulatory programs in complex tissues.
Rapid SARS-CoV-2 Detection and Classification Using Phase Imaging with Computational Specificity
Authors: Goswami Neha , He Yuchen R. , Deng Yu-Heng , Oh Chamteut , Sobh Nahil , Valera Enrique , Bashir Rashid , Ismail Nahed , Kong Hyun J. , Nguyen Thanh H. , Best-Popescu Catherine , Popescu Gabriel 
Published: December 2020

AbstractEfforts to mitigate the COVID-19 crisis revealed that fast, accurate, and scalable testing is crucial for curbing the current impact and that of future pandemics. We propose an optical method for directly imaging unlabeled viral particles and using deep learning for detection and classification. An ultrasensitive interferometric method was used to image four virus types with nanoscale optical pathlength sensitivity. Pairing these data with fluorescence images for ground truth, we trained semantic segmentation models based on U-Net, a particular type of convolutional neural network. The trained network was applied to classify the viruses from the interferometric images only, containing simultaneously SARS-CoV-2, H1N1 (influenza-A), HAdV (adenovirus), and ZIKV (Zika). Remarkably, due to the nanoscale sensitivity in the input data, the neural network was able to identify SARS-CoV-2 vs. the other viruses with 96% accuracy. The inference time for each image is 60 ms, on a common graphic processing unit. This approach of directly imaging unlabeled viral particles may provide an extremely fast test, of less than a minute per patient. As the imaging instrument operates on regular glass slides, we envision this method as potentially testing on patient breath condensates.The necessary high throughput can be achieved by translating concepts from digital pathology, where a microscope can scan hundreds of slides automatically.One Sentence SummaryThis work proposes a rapid (<1 min.), label-free testing method for SARS-CoV-2 detection, using quantitative phase imaging and deep learning.
Novel virus-like particle vaccine encoding the circumsporozoite protein ofPlasmodium falciparumis immunogenic and induces functional antibody responses
Authors: Kurtovic Liriye , Wetzel David , Reiling Linda , Drew Damien R. , Palmer Catherine , Kouskousis Betty , Hanssen Eric , Wines Bruce D. , Hogarth P. Mark , Suckow Manfred , Jenzelewski Volker , Piontek Michael , Chan Jo-Anne , Beeson James G. 
Published: December 2020

ABSTRACTRTS,S is the leading malaria vaccine in development, but has demonstrated only moderate protective efficacy in clinical trials. RTS,S is a virus-like particle (VLP) that uses the human hepatitis B virus as scaffold to display the malaria sporozoite antigen, circumsporozoite protein (CSP). Particle formation requires fourfold excess scaffold antigen, and as a result, CSP represents only a small portion of the final vaccine construct. Alternative VLP or nanoparticle platforms that reduce the amount of scaffold antigen and increase the amount of the target CSP antigen present in particles may enhance vaccine immunogenicity and efficacy. Here, we describe the production and characterization of a novel VLP that uses the small surface antigen (dS) of duck hepatitis B virus to display CSP. The CSP-dS fusion protein successfully formed VLPs without the need for excess scaffold antigen, and thus CSP represented a larger portion of the vaccine construct. Importantly, this is the first report of a dS-based vaccine that formed particles without excess scaffold protein. CSP-dS formed large particles approximately 31-74 nm in size and were confirmed to display CSP on the surface. The CSP-dS VLP was highly immunogenic in mice and induced antibodies to multiple regions of CSP, even when administered at a lower vaccine dosage. Vaccine-induced antibodies demonstrated functional activity, including the ability to interact with complement and Fcγ-receptors, both previously identified as important in malaria immunity. Our novel platform to produce VLPs without excess scaffold protein has wide implications for the future development of innovative vaccines for malaria and other infectious diseases.
Effects of temperature on development, reproduction and size ofTrichogramma achaeae: implications for biological control
Authors: Chen Long , Sørensen Jesper Givskov , Enkegaard Annie 
Published: December 2020

AbstractThe performance of biological control agents (BCAs) in outdoor crops is strongly regulated by ambient temperature. Understanding the thermal biology of BCAs and manipulating their thermal performance could improve biological control efficacy. In this study, the effects of temperature on several life history parameters (longevity, fecundity, development time, wing size) of the recently commercialised egg parasitoidTrichogramma achaeaeNagaraja & Nagarkatti (Hymenoptera: Trichogrammatidae) was examined. First, parasitoids were reared at 23 °C and tested in the laboratory at four constant temperatures (15, 20, 25 and 30 °C). Results demonstrated that temperature significantly altered all above parameters. Second, developmental acclimation was applied to manipulate the laboratory performance. Parasitoids were allowed to develop at either of the above four temperatures and their performance were compared at 23 °C. Results showed that developmental acclimation had a significant impact on fecundity, development time and wing size but not on female longevity. Our results have implications for improving the performance ofT. achaeaein mass production and for its application for biological control under different thermal conditions.HighlightsThe temperature dependent performance ofTrichogramma achaeaewas characterisedAcclimation significantly influenced fecundity, development and body sizeThe overall performance was not improved by acclimationThe female fecundity could be a proxy for the overall performance ofT. achaeae
Hapo-G, Haplotype-Aware Polishing Of Genome Assemblies
Authors: Aury Jean-Marc , Istace Benjamin 
Published: December 2020

ABSTRACTSingle-molecule sequencing technologies have recently been commercialized by Pacific Biosciences and Oxford Nanopore with the promise of sequencing long DNA fragments (kilobases to megabases order) and then, using efficient algorithms, provide high quality assemblies in terms of contiguity and completeness of repetitive regions. However, the error rate of long-read technologies is higher than that of short-read technologies. This has a direct consequence on the base quality of genome assemblies, particularly in coding regions where sequencing errors can disrupt the coding frame of genes. In the case of diploid genomes, the consensus of a given gene can be a mixture between the two haplotypes and can lead to premature stop codons. Several methods have been developed to polish genome assemblies using short reads and generally, they inspect the nucleotide one by one, and provide a correction for each nucleotide of the input assembly. As a result, these algorithms are not able to properly process diploid genomes and they typically switch from one haplotype to another. Herein we proposed Hapo-G (Haplotype-Aware Polishing Of Genomes), a new algorithm capable of incorporating phasing information from short reads to polish genome assemblies and in particular assemblies of diploid and heterozygous genomes.
Toward asleep DBS: Cortico basal-ganglia neural activity during interleaved propofol/ketamine sedation mimics NREM/REM sleep activity
Authors: Guang Jing , Baker Halen , Nizri Orilia Ben-Yishay , Firman Shimon , Werner-Reiss Uri , Kapuller Vadim , Israel Zvi , Bergman Hagai 
Published: December 2020

AbstractDeep brain stimulation (DBS) is currently a standard long-term treatment for advanced motor symptoms in Parkinson’s disease (PD). In an effort to enable DBS under sedation, asleep DBS, we characterized the cortico-basal ganglia neuronal network of two non-human primates under propofol, ketamine and interleaved propofol-ketamine (IPK) sedation. Further, we compared these sedation states in the healthy and Parkinsonian condition to those of healthy sleep. Ketamine increases high frequency power and synchronization while propofol increases low frequency power and synchronization in polysomnography and neuronal activity recordings. Thus, ketamine does not mask the low frequency oscillations used for physiological navigation toward basal ganglia DBS targets. The brain state under ketamine and propofol mimicked rapid eye movement (REM) and Non-REM (NREM) sleep activity, respectively, and the IPK protocol imitates the NREM-REM sleep cycle. These promising results are the first step towards asleep DBS with non-distorted physiological navigation.
Circadian Rhythm Disruption Results in Visual Dysfunction
Authors: Mathew Deepa , Bhatwadekar Ashay D. 
Published: December 2020

AbstractCircadian rhythm disruption (CRD) contributes to the development of multiple metabolic and neurodegenerative diseases. However, its effect on vision is not understood. We evaluated the impact of CRD on retinal morphology, physiology, and vision after housing mice in a disruption inducing shorter light/dark cycle (L10:D10). Interestingly, the mice under L10:D10 exhibited three different entrainment behaviors; ‘entrained’, ‘freerunning’, and ‘zigzagging.’ These behavior groups under CRD exhibited reduced visual acuity, retinal thinning, and a decrease in the number of rod photoreceptors. Intriguingly, the electroretinogram response was decreased only in the mice exhibiting ‘entrained’ behavior. The retinal proteome showed distinct changes with each entrainment behavior. These results demonstrate that CRD leads to photoreceptor degeneration and visual dysfunction. We uniquely show the effect of entrainment behavior on retinal protein composition and physiology. Our data has broader implications in understanding and mitigating the effect of CRD on vision health.Significance StatementArtificial light is increasingly in use for the past 70 years. The aberrant light exposure and round-the-clock nature of work lead to the disruption of a biological clock. The mammalian retina possesses an autonomous clock that could reset with light exposure. Yet, the effect of altered light exposure on vision is not studied. Here, we report visual dysfunction after exposure to a circadian disrupting altered light/dark cycle. We also report behavior dependent changes in retinal protein composition and function. Our data provide evidence for the negative impact of CRD on vision and its potential role in retinal diseases’ etiology.
Cryo-EM structure of amyloid fibrils formed by the entire low complexity domain of TDP-43
Authors: Li Qiuye , Michael Babinchak W. , Surewicz Witold K. 
Published: December 2020

ABSTRACTAmyotrophic lateral sclerosis and several other neurodegenerative diseases are associated with brain deposits of TDP-43 aggregates. Cryo-EM structure of amyloid formed from the entire TDP-43 low complexity domain reveals single protofilament fibrils containing a large (138-residue), tightly packed core with structural features that differ from those previously found for fibrils formed from short protein fragments. The atomic model provides insight into potential structural perturbations caused by phosphorylation and disease-related mutations.
AdRoit: an accurate and robust method to infer complex transcriptome composition
Authors: Yang Tao , Alessandri-Haber Nicole , Fury Wen , Schaner Michael , Breese Robert , LaCroix-Fralish Michael , Kim Jinrang , Adler Christina , Macdonald Lynn E. , Atwal Gurinder S. , Bai Yu 
Published: December 2020

AbstractBulk RNA sequencing technology provides the opportunity to understand biology at the whole transcriptome level without the prohibitive cost of single cell profiling. Advances in spatial transcriptomics enable to dissect tissue organization and function by genome-wide gene expressions. However, the readout of both technologies is the overall gene expression across potentially many cell types without directly providing the information of cell type constitution. Although several in-silico approaches have been proposed to deconvolute RNA-Seq data composed of multiple cell types, many suffer a deterioration of performance in complex tissues. Here we present AdRoit, anaccurate and robust method infer the cell composition fromtranscriptome data comprised of multiple cell types. AdRoit uses gene expression profile obtained from single cell RNA sequencing as a reference. It employs an adaptive learning approach to correct the sequencing technique difference between the single cell data and the bulk or spatial transcriptome data, enabling cross-platform readout comparability. Our systematic benchmarking and applications, which include deconvoluting complex mixtures that encompass 30 cell types, demonstrate its superior sensitivity and specificity compared to other existing methods as well as its utilities. In addition, AdRoit is computationally efficient and runs orders of magnitude faster than many existing methods.
Decoding neurobiological spike trains using recurrent neural networks; a case study with electrophysiological auditory cortex recordings
Authors: Szabó Péter , Barthó Péter 
Published: December 2020

AbstractRecent advancements in multielectrode methods and spike-sorting algorithms enable the in vivo recording of the activities of many neurons at a high temporal resolution. These datasets offer new opportunities in the investigation of the biological neural code, including the direct testing of specific coding hypotheses, but they also reveal the limitations of present decoder algorithms. Classical methods rely on a manual feature extraction step, resulting in a feature vector, like the firing rates of an ensemble of neurons. In this paper, we present a recurrent neural-network based decoder and evaluate its performance on experimental and artificial datasets. The experimental datasets were obtained by recording the auditory cortical responses of rats exposed to sound stimuli, while the artificial datasets represent preset encoding schemes. The task of the decoder was to classify the action potential timeseries according to the corresponding sound stimuli. It is illustrated that, depending on the coding scheme, the performance of the recurrent-network based decoder can exceed the performance of the classical methods. We also show how randomized copies of the training datasets can be used to reveal the role of candidate spike-train features. We conclude that artificial neural network decoders can be a useful alternative to classical population vector based techniques in studies of the biological neural code.