bluuebunny/crossref_metadata_2025_split huggingface dataset:
Supra-Temporalis Approach for Treating Zygomaticomaxillary Complex Fracture
Authors: Xing Zhankui , Ren Rong , Xia Xin , Yang Lan 
Published: January 2021

Purpose:
There are multiple approaches described to access the zygomaticomaxillary complex (ZMC) fractures: lateral eyebrow, upper blepharoplasty, coronal, subciliary, subtarsal, infraorbital, transconjunctival, and transoral. All these approaches have their advantages, disadvantages, and indications according to location of fracture, degree of displacement, and surgeon's experience with a specific technique. However, there is not a good approach for treating the zygomatic arch or body fracture. In this paper, the authors described a supra-temporalis approach to treat the zygomatic arch or body fracture.

Patients and Methods:
Eight patients with traumatically ZMC fractures who received open reduction and internal stable fixation with supra-temporalis approach were retrospectively reviewed. A minimized supra-temporalis incision and trans-temporalis fascia access was used. Blunt dissection was performed perpendicularly to the fractured zygomatic arch and body. The open reduction and internal fixation of ZMC fractures were performed. After confirming that the fracture was fixed rigidly, the incision was closed layer by layer.

Results:
Using this approach, the zygomatic arch, body, frontozygomatic suture, and fracture stumps were exposed perpendicularly. No extensive incision was needed and minimal invasion was realized. Postoperative CT scan showed that the fractures been repositioned and fixed in the normal position. Facial asymmetry was reconstructed and keep in the follow-up.

Conclusions:
Supra-temporalis approach gave an optimal view of the bony field, which allowed surgeons to work perpendicularly to the fracture, and facilitated the reduction of the displaced fractured stumps. It was regarded as an ideal and valuable alternative in this potentially complicated procedure.
Simultaneous Condylar Reconstruction by Free Ramus Osteotomy Graft After Complete Condylectomy for Osteochondroma
Authors: Hoang Tuan-Anh , Lee Kevin C. , Chuang Sung-Kiang 
Published: January 2021

Abstract
Mandibular condyle osteochondromas cause morphologic and functional disturbances. Multiple options exist for reconstructing the condylar segment following complete condylectomy. In this series, we describe 3 cases of mandibular condyle osteochondroma treated with complete condylectomy, orthognathic surgery, and a novel free ramus osteotomy graft. This is the first report to reconstruct the temporomandibular joint using a free ramus graft. Through this single-staged approach we were able to avoid recurrence, preserve function, and restore facial balance without a separate donor site or an alloplastic implant.
SAINT: automatic taxonomy embedding and categorization by Siamese triplet network
Authors: Lu Yang Young , Wang Yiwen , Zhang Fang , Bai Jiaxing , Wang Ying 
Published: January 2021

AbstractMotivationUnderstanding the phylogenetic relationship among organisms is the key in contemporary evolutionary study and sequence analysis is the workhorse towards this goal. Conventional approaches to sequence analysis are based on sequence alignment, which is neither scalable to large-scale datasets due to computational inefficiency nor adaptive to next-generation sequencing (NGS) data. Alignment-free approaches are typically used as computationally effective alternatives yet still suffering the high demand of memory consumption. One desirable sequence comparison method at large-scale requires succinctly-organized sequence data management, as well as prompt sequence retrieval given a never-before-seen sequence as query.ResultsIn this paper, we proposed a novel approach, referred to as SAINT, for efficient and accurate alignment-free sequence comparison. Compared to existing alignment-free sequence comparison methods, SAINT offers advantages in two aspects: (1) SAINT is a weakly-supervised learning method where the embedding function is learned automatically from the easily-acquired data; (2) SAINT utilizes the non-linear deep learning-based model which potentially better captures the complicated relationship among genome sequences. We have applied SAINT to real-world datasets to demonstrate its empirical utility, both qualitatively and quantitatively. Considering the extensive applicability of alignment-free sequence comparison methods, we expect SAINT to motivate a more extensive set of applications in sequence comparison at large scale.AvailabilityThe open source, Apache licensed, python-implemented code will be available upon acceptance.Supplementary informationSupplementary data are available atBioinformaticsonline.
Design of Specific Primer Sets for the Detection of SARS-CoV-2 Variants of Concern B.1.1.7, B.1.351, P.1, B.1.617.2 using Artificial Intelligence
Authors: Perez-Romero Carmina A. , Tonda Alberto , Mendoza-Maldonado Lucero , Coz Etienne , Tabeling Patrick , Vanhomwegen Jessica , Claassen Eric , Garssen Johan , Kraneveld Aletta D. , Lopez-Rincon Alejandro 
Published: January 2021

ABSTRACTAs the COVID-19 pandemic continues, new SARS-CoV-2 variants with potentially dangerous features have been identified by the scientific community. Variant B.1.1.7 lineage clade GR from Global Initiative on Sharing All Influenza Data (GISAID) was first detected in the UK, and it appears to possess an increased transmissibility. At the same time, South African authorities reported variant B.1.351, that shares several mutations with B.1.1.7, and might also present high transmissibility. Earlier this year, a variant labelled P.1 with 17 non-synonymous mutations was detected in Brazil. Recently the World Health Organization has raised concern for the variants B.1.617.2 mainly detected in India but now exported worldwide. It is paramount to rapidly develop specific molecular tests to uniquely identify new variants. Using a completely automated pipeline built around deep learning and evolutionary algorithms techniques, we designed primer sets specific to variants B.1.1.7, B.1.351, P.1 and respectively. Starting from sequences openly available in the GISAID repository, our pipeline was able to deliver the primer sets for each variant. In-silico tests show that the sequences in the primer sets present high accuracy and are based on 2 mutations or more. In addition, we present an analysis of key mutations for SARS-CoV-2 variants. Finally, we tested the designed primers for B.1.1.7 using RT-PCR. The presented methodology can be exploited to swiftly obtain primer sets for each new variant, that can later be a part of a multiplexed approach for the initial diagnosis of COVID-19 patients.
Optimising expression quantitative trait locus mapping workflows for single-cell studies
Authors: Cuomo Anna S.E. , Alvari Giordano , Azodi Christina B. ,   single-cell eQTLGen consortium, McCarthy Davis J. , Bonder Marc Jan 
Published: January 2021

AbstractSingle-cell RNA-sequencing (scRNA-seq) has enabled the unbiased, high-throughput quantification of gene expression specific to cell types and states. With the cost of scRNA-seq decreasing and techniques for sample multiplexing improving, population-scale scRNA-seq, and thus single-cell expression quantitative trait locus (sc-eQTL) mapping, is increasingly feasible. Mapping of sc-eQTL provides additional resolution to study the regulatory role of common genetic variants on gene expression across a plethora of cell types and states, and promises to improve our understanding of genetic regulation across tissues in both health and disease. While previously established methods for bulk eQTL mapping can, in principle, be applied to sc-eQTL mapping, there are a number of open questions about how best to process scRNA-seq data and adapt bulk methods to optimise sc-eQTL mapping. Here, we evaluate the role of different normalisation and aggregation strategies, covariate adjustment techniques, and multiple testing correction methods to establish best practice guidelines. We use both real and simulated datasets across single-cell technologies to systematically assess the impact of these different statistical approaches and provide recommendations for future single-cell eQTL studies that can yield up to twice as many eQTL discoveries as default approaches ported from bulk studies.
Shape Recovery of Deformed Biomolecular Droplets: Dependence on Condensate Viscoelasticity
Authors: Zhou Huan-Xiang 
Published: January 2021

SUMMARYA theoretical study on the shape dynamics of phase-separated biomolecular droplets is presented, highlighting the importance of condensate viscoelasticity. Previous studies on shape dynamics have modeled biomolecular condensates as purely viscous, but recent data have shown them to be viscoelastic. Here we present an exact analytical solution for the shape recovery dynamics of deformed biomolecular droplets. The shape recovery of viscous droplets has an exponential time dependence, with the time constant given by the “viscocapillary” ratio, i.e., viscosity over interfacial tension. In contrast, the shape recovery dynamics of viscoelastic droplets is multi-exponential, with shear relaxation yielding additional time constants. During shape recovery, viscoelastic droplets exhibit shear thickening (increase in apparent viscosity) at fast shear relaxation rates but shear thinning (decrease in apparent viscosity) at slow shear relaxation rates. These results highlight the importance of viscoelasticity and expand our understanding of how material properties affect condensate dynamics in general, including aging.
Automated annotation of rare-cell types from single-cell RNA-sequencing data through synthetic oversampling
Authors: Bej Saptarshi , Galow Anne-Marie , David Robert , Wolfien Markus , Wolkenhauer Olaf 
Published: January 2021

AbstractThe research landscape of single-cell and single-nuclei RNA sequencing is evolving rapidly, and one area that is enabled by this technology, is the detection of rare cells. An automated, unbiased and accurate annotation of rare subpopulations is challenging. Once rare cells are identified in one dataset, it will usually be necessary to generate other datasets to enrich the analysis (e.g., with samples from other tissues). From a machine learning perspective, the challenge arises from the fact that rare cell subpopulations constitute an imbalanced classification problem.We here introduce a Machine Learning (ML)-based oversampling method that uses gene expression counts of already identified rare cells as an input to generate synthetic cells to then identify similar (rare) cells in other publicly available experiments. We utilize single-cell synthetic oversampling (sc-SynO), which is based on the Localized Random Affine Shadowsampling (LoRAS) algorithm. The algorithm corrects for the overall imbalance ratio of the minority and majority class.We demonstrate the effectiveness of the method for two independent use cases, each consisting of two published datasets. The first use case identifies cardiac glial cells in snRNA-Seq data (17 nuclei out of 8,635). This use case was designed to take a larger imbalance ratio (∼1 to 500) into account and only uses single-nuclei data. The second use case was designed to jointly use snRNA-Seq data and scRNA-Seq on a lower imbalance ratio (∼1 to 26) for the training step to likewise investigate the potential of the algorithm to consider both single cell capture procedures and the impact of “less” rare-cell types. For validation purposes, all datasets have also been analyzed in a traditional manner using common data analysis approaches, such as the Seurat3 workflow.Our algorithm identifies rare-cell populations with a high accuracy and low false positive detection rate. A striking benefit of our algorithm is that it can be readily implemented in other and existing workflows. The code basis is publicly available at FairdomHub (https://fairdomhub.org/assays/1368) and can easily be transferred to train other customized approaches.
The Generalizability of Clinical Prediction Models for Patients with Acute Coronary Syndromes: Results from Independent External Validations
Authors: Wessler Benjamin S. , Nelson Jason , Park Jinny G. , McGinnes Hannah , Upshaw Jenica , Van Calster Ben , van Klaveren David , Steyerberg Ewout , Kent David M. 
Published: January 2021

AbstractPurposeIt is increasingly recognized that clinical prediction models (CPMs) often do not perform as expected when they are tested on new databases. Independent external validations of CPMs are recommended but often not performed. Here we conduct independent external validations of acute coronary syndrome (ACS) CPMs.MethodsA systematic review identified CPMs predicting outcomes for patients with ACS. Independent external validations were performed by evaluating model performance using individual patient data from 5 large clinical trials. CPM performance with and without various recalibration techniques was evaluated with a focus on CPM discrimination (c-statistic, % relative change in c-statistic) as well as calibration (Harrell’s Eavg, E90, Net Benefit).ResultsOf 269 ACS CPMs screened, 23 (8.5%) were compatible with at least one of the trials and 28 clinically appropriate external validations were performed. The median c statistic of the CPMs in the derivation cohorts was 0.76 (IQR, 0.74 to 0.78). The median c-statistic in these external validations was 0.70 (IQR, 0.66 to 0.71) reflecting a 24% decrement in discrimination. However, this decrement in discrimination was due mostly to narrower case-mix in the validation cohorts compared to derivation cohorts, as reflected in the median model based c-statistic [0.71 (IQR 0.66 to 0.75). The median calibration slope in external validations was 0.84 (IQR, 0.72 to 0.98) and the median Eavg (standardized by the outcome rate) was 0.4 (IQR, 0.3 to 0.8). Net benefit indicates that most CPMs had a high risk of causing net harm when not recalibrated, particularly for decision thresholds not near the overall outcome rate.ConclusionIndependent external validations of published ACS CPMs demonstrate that models tested in our sample had relatively well-preserved discrimination but poor calibration when externally validated. Applying ‘off-the-shelf’ CPMs often risks net harm unless models are recalibrated to the populations on which they are used.
Excess mortality associated with the COVID-19 pandemic among Californians 18–65 years of age, by occupational sector and occupation: March through October 2020
Authors: Chen Yea-Hung , Glymour Maria , Riley Alicia , Balmes John , Duchowny Kate , Harrison Robert , Matthay Ellicott , Bibbins-Domingo Kirsten 
Published: January 2021

AbstractBackgroundThough SARS-CoV-2 outbreaks have been documented in occupational settings and though there is speculation that essential workers face heightened risks for COVID-19, occupational differences in excess mortality have, to date, not been examined. Such information could point to opportunities for intervention, such as workplace modifications and prioritization of vaccine distribution.Methods and findingsUsing death records from the California Department of Public Health, we estimated excess mortality among Californians 18–65 years of age by occupational sector and occupation, with additional stratification of the sector analysis by race/ethnicity. During the COVID-19 pandemic, working age adults experienced a 22% increase in mortality compared to historical periods. Relative excess mortality was highest in food/agriculture workers (39% increase), transportation/logistics workers (28% increase), facilities (27%) and manufacturing workers (23% increase). Latino Californians experienced a 36% increase in mortality, with a 59% increase among Latino food/agriculture workers. Black Californians experienced a 28% increase in mortality, with a 36% increase for Black retail workers. Asian Californians experienced an 18% increase, with a 40% increase among Asian healthcare workers. Excess mortality among White working-age Californians increased by 6%, with a 16% increase among White food/agriculture workers.ConclusionsCertain occupational sectors have been associated with high excess mortality during the pandemic, particularly among racial and ethnic groups also disproportionately affected by COVID-19. In-person essential work is a likely venue of transmission of coronavirus infection and must be addressed through strict enforcement of health orders in workplace settings and protection of in-person workers. Vaccine distribution prioritizing in-person essential workers will be important for reducing excess COVID mortality.
Getting Blood from a Stone: Improving Neural Inferences without Additional Neural Data
Authors: Halpern David J. , Gureckis Todd M. 
Published: January 2021

AbstractIn recent years, the cognitive neuroscience literature has come under criticism for containing many low-powered studies, limiting the ability to make reliable statistical inferences. Typically, the suggestion for increasing power is to collect more data with neural signals. However, many studies in cognitive neuroscience use parameters estimated from behavioral data in order to make inferences about neural signals (such as fMRI BOLD signal). In this paper, we explore how cognitive neuroscientists can learn more about their neuroimaging signal by collecting data onbehavior alone. We demonstrate through simulation that knowing more about the marginal distribution of behavioral parameters can improve inferences about the mapping between cognitive processes and neural data. In realistic settings of the correlation between cognitive and neural parameters, additional behavioral data can lead to the same improvement in the precision of inferences more cheaply and easily than collecting additional data from subjects in a neuroimaging study. This means that when conducting an neuroimaging study, researchers now have two knobs to turn in a design analysis: the number of subjects collected in the scanner and the number of behavioral subjects collected outside the scanner (in the lab or online).
Piezo1 and BKCachannels in human atrial fibroblasts: interplay and remodelling in atrial fibrillation
Authors: Jakob Dorothee , Klesen Alexander , Allegrini Benoit , Darkow Elisa , Aria Diana , Emig Ramona , Chica Ana Simon , Rog-Zielinska Eva A. , Guth Tim , Beyersdorf Friedhelm , Kari Fabian A. , Proksch Susanne , Hatem Stéphane N. , Karck Matthias , Künzel Stephan R , Guizouarn Hélène , Schmidt Constanze , Kohl Peter , Ravens Ursula , Peyronnet Rémi 
Published: January 2021

AbstractAimsAtrial Fibrillation (AF) is an arrhythmia of increasing prevalence in the aging population of developed countries. One of the important indicators of AF is sustained atrial dilatation, highlighting the importance of mechanical overload in the pathophysiology of AF. The mechanisms by which atrial cells, including fibroblasts, sense and react to changing mechanical forces, are not fully elucidated. Here, we characterise stretch-activated ion channels (SAC) in human atrial fibroblasts and changes in SAC-presence and -activity associated with AF.Methods and ResultsUsing primary cultures of human atrial fibroblasts, isolated from patients in sinus rhythm or sustained AF, we combine electrophysiological, molecular and pharmacological tools to identify SAC. Two electrophysiological SAC-signatures were detected, indicative of cation-nonselective and potassium-selective channels. Using siRNA-mediated knockdown, we identified the nonselective SAC as Piezo1. Biophysical properties of the potassium-selective channel, its sensitivity to calcium, paxilline and iberiotoxin (blockers), and NS11021 (activator), indicated presence of calcium-dependent ‘big potassium channels’, BKCa. In cells from AF patients, Piezo1 activity and mRNA expression levels were higher than in cells from sinus rhythm patients, while BKCaactivity (but not expression) was downregulated. Both Piezo1-knockdown and removal of extracellular calcium from the patch pipette resulted in a significant reduction of BKCacurrent during stretch. No co-immunoprecipitation of Piezo1 and BKCawas detected.ConclusionsHuman atrial fibroblasts contain at least two types of ion channels that are activated during stretch: Piezo1 and BKCa. While Piezo1 is directly stretch-activated, the increase in BKCaactivity during mechanical stimulation appears to be mainly secondary to calcium influxviaSAC such as Piezo1. During sustained AF, Piezo1 is increased, while BKCaactivity is reduced, highlighting differential regulation of both channels. Our data support the presence and interplay of Piezo1 and BKCain human atrial fibroblasts in the absence of physical interactions between the two channel proteins.
Current strategic limitations of phylogenetic tools badly impact the inference of an evolutionary tree
Authors: Nasika Shamantha , Runthala Ashish 
Published: January 2021

AbstractFor drawing an evolutionary relationship among several protein sequences, the phylogenetic tree is usually constructed through maximum likelihood-based algorithms. To improve the accuracy of these methodologies, many parameters like bootstrap methods, correlation coefficient and residue-substitution models are presumably over-ranked to derive biologically credible relationships. Although the accuracy of protein sequence alignment and the substitution matrix are preliminary constraints to define the biological accuracy of the overlapped sequences/residues, the alignment is not iteratively optimized through the statistical testing of residue-substitution models. The study majorly highlights the potential pitfalls that significantly affect the accuracy of an evolutionary protocol. It emphasizes the need for a more accurate scrutiny of the entire phylogenetic methodology. The need of iterative optimizations is illustrated to construct a biologically credible and not mathematically optimal tree for a sequence dataset.
Elimination of glutamatergic transmission from Hb9 interneurons does not impact treadmill locomotion
Authors: Koronfel Lina M. , Kanning Kevin C. , Alcos Angelita , Henderson Christopher E. , Brownstone Robert M. 
Published: January 2021

ABSTRACTThe spinal cord contains neural circuits that can produce the rhythm and pattern of locomotor activity. It has previously been postulated that a rhythmogenic population of glutamatergic neurons, termed Hb9 interneurons, contributes to this rhythmogenesis. The homeobox gene, Hb9, is expressed in these interneurons as well as motor neurons. We developed a mouse line in which cre recombinase activity is inducible in neurons expressing Hb9. We then used this line to eliminate vesicular glutamate transporter 2 from Hb9 interneurons, and found that there were no deficits in treadmill locomotion. We conclude that glutamatergic neurotransmission by Hb9 interneurons is not required for locomotor rhythmogenesis. The role of these neurons in neural circuits remains elusive.