bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dense Optic Nerve Head Deformation Estimated using CNN as a Structural Biomarker of Glaucoma Progression
Authors: Salehi Ali , Balasubramanian Madhusudhanan 
Published: September 2021

ABSTRACTPurposeTo present a new structural biomarker for detecting glaucoma progression based on structural transformation of the optic nerve head (ONH) region.MethodsA dense ONH deformation was estimated using deep learning methods namely DDCNet-Multires, FlowNet2, and FlowNet-Correlation, and legacy computational methods namely the topographic change analysis (TCA) and proper orthogonal decomposition (POD) methods using longitudinal confocal scans of the ONH for each study eye. A candidate structural biomarker of glaucoma progression in a study eye was estimated as average magnitude of flow velocities within the ONH region. The biomarker was evaluated using longitudinal confocal scans of 12 laser-treated and 12 contralateral normal eyes of 12 primates from the LSU Experimental Glaucoma Study (LEGS); and 36 progressing eyes and 21 longitudinal normal eyes from the UCSD Diagnostic Innovations in Glaucoma Study (DIGS). Area under the ROC curves (AUC) was used to assess the diagnostic accuracy of the candidate biomarker.ResultsAUROC (95% CI) for LEGS were: 0.83 (0.79, 0.88) for DDCNet-Multires; 0.83 (0.78, 0.88) for FlowNet2; 0.83 (0.78, 0.88) for FlowNet-Correlation; 0.94 (0.91, 0.97) for POD; and 0.86 (0.82, 0.91) for TCA methods. For DIGS: 0.89 (0.80, 0.97) for DDCNet-Multires; 0.82 (0.71, 0.93) for FlowNet2; 0.93 (0.86, 0.99) for FlowNet-Correlation; 0.86 (0.76, 0.96) for POD; and 0.86 (0.77, 0.95) for TCA methods. Lower diagnostic accuracy of the learning-based methods for LEG study eyes were due to image alignment errors in confocal sequences.ConclusionDeep learning methods trained to estimate generic deformation were able to detect ONH deformation from confocal images and provided a higher diagnostic accuracy when compared to the classical optical flow and legacy biomarkers of glaucoma progression. Because it is difficult to validate the estimates of dense ONH deformation in clinical population, our validation using ONH sequences under controlled experimental conditions confirms the diagnostic accuracy of the biomarkers observed in the clinical population. Performance of these deep learning methods can be further improved by fine-tuning these networks using longitudinal ONH sequences instead of training the network to be a general-purpose deformation estimator.
Advancing convergent mixed methods design using the Diamond Approach for clinical multiple case studies: an example using data on time to treatment in aneurysmal subarachnoid haemorrhage
Authors: Nguyen Thuy Phuong , Stirling Christine , Kitsos Gemma , Jose Kim , Nichols Linda , Chandra Ronil V. , Rehman Sabah , Smith Karen , Mosley Ian , Lai Leon , Asadi Hamed , Dubey Arvind , Froelich Jens , Thrift Amanda , Gall Seana 
Published: September 2021

AbstractUsing a new approach to the analysis and synthesis of a clinically focused mixed-methods multiple case study of aneurysmal subarachnoid haemorrhage (aSAH), we explored barriers and facilitators to timely treatment. In this paper we provide guidance for the multiple steps of analysis and synthesis of qualitative and quantitative data from across and within 27 case studies. Results showed that median (IQR) time to treatment was 15.1 (9.0, 24.1) hours. Only 37% of cases had treatment within 12-hours of onset. Early recognition of aSAH, good coordination, and availability of resources for treatment were main facilitators for treatment within 12 hours from onset. Lack of recognition of aSAH at onset and lack of resources for immediate in-hospital treatment were major barriers.
Common genetic alterations of SPOP-MATH domain in prostate cancer tissues and association with pathological tumor characteristics*
Authors: Abumsimir Berjas , Mrabti Mohammed , Laraqui Abdelilah , Saif Imane , Lamsisi Maryame , Ennaji Youssef , Ameur Ahmed , Koraishi Saad Ibnsouda , Ennaji Moulay Mustapha 
Published: September 2021

AbstractSPOP gene has a critical role in prostate cancer development and found high mutated in the prostate tumor through various populations. MATH domain represents an important site for SPOP-DNA linkage and other sensitive gene-gene interactions. To investigate the genetic alterations of the MATH domain of SPOP gene in prostate cancer biopsies and correlation with clinical and pathological parameters; DNA samples from 50 prostate cancer tissues were genotyped and confirmed by Sanger sequencing. The frequency and distribution of high frequent mutations were determined and correlated with the patient’s tumor characteristics. Among 50 samples 34 (68%) were carrying one or more common mutations. Novel frame shift deletion mutation: c.255delA (p.Leu86Phefs) was detected in eight patients (16%), in addition to five novel missense mutations with moderate frequency (6%) namely: c.209G>C (p.Arg70Pro), c.215A>C (p.Asn72Thr), c.334G>A (p.Glu112Lys), c.373T>C (p.Phe125Leu), and c.388G>A (p.Asp130Asn), All missense mutations located in MATH domain. The effects of novel mutations described in the MATH domain are uncertain. No significant differences between carriers and noncarriers of common mutations detected regarding Gleason score, prostate-specific antigen concentration PSA, and tumor stage [p > 0.05]. Clinical significance of mutations detected on prostate tumors progression can be investigated in future analysis. Our findings revealed novel SPOP alterations in prostate cancer tissues probably associated with cancer development.
A Machine Learning Approach to Identifying Delirium from Electronic Health Records
Authors: Kim Jae Hyun , Hua May , Whittington Robert A. , Lee Junghwan , Liu Cong , Ta Casey N. , Marcantonio Edward R. , Goldberg Terry E. , Weng Chunhua 
Published: September 2021

ABSTRACTBackgroundDespite the well-known impact of delirium on long-term clinical outcomes, identification of delirium in electronic health records (EHR) remains difficult due to inadequate assessment or documentation of delirium. The purpose of this research is to present a classification model that identifies delirium using retrospective EHR data. The classification model would support the additional identification of delirium cases otherwise undocumented during routine practice.MethodsDelirium was confirmed with the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU). Age, sex, Elixhauser comorbidity index, drug exposures, and diagnoses were used as features to train the logistic regression and multi-layer perceptron models. The clinical notes from the EHR were parsed to supplement the features that were not recorded in the structured data. The model performance was evaluated with a 5-fold cross-validation area under the receiver operating characteristic curve (AUC).ResultsSeventy-six patients (17 cases and 59 controls) with at least one CAM-ICU evaluation result during ICU stay from January 30, 2018 to February 20, 2018 were included in the model. The multi-layer perceptron model achieved the best performance in identifying delirium; mean AUC of 0.967 ± 0.019. The mean positive predictive value (PPV), mean negative predicted value (NPV), mean sensitivity, and mean specificity of the MLP model were 0.9, 0.88, 0.56, and 0.95, respectively.ConclusionA simple classification model showed a mean AUC over 0.95. This model promises to identify delirium cases with EHR data, thereby enable a sustainable infrastructure to build a retrospective cohort of delirium in the ICU. The cohort would be useful for the evaluation of long-term sequelae of delirium in ICU.
Single cell multi-omics reveals early elevated function and multiple fates within human progenitor exhausted CD8+ T cells
Authors: Cai Curtis , Samir Jerome , Pirozyan Mehdi R. , Adikari Thiruni N. , Gupta Money , Leung Preston , Hughes Brendan , Van der Byl Willem , Rizzetto Simone , Elthala Auda , Keoshkerian Elizabeth , Palgen Jean-Louis , Peters Timothy , Nguyen Thi H. O. , Louie Raymond , Kedzierska Katherine , Gaudieri Silvana , Bull Rowena A. , Lloyd Andrew R. , Luciani Fabio 
Published: September 2021

AbstractT-cell exhaustion is a hallmark of hepatitis C virus (HCV) infection and limits protective immunity in chronic viral infections and cancer. Limited knowledge exists of the initial viral and immune dynamics that characterise exhaustion in humans. We studied longitudinal blood samples from a unique cohort of subjects with primary infection using single cell multi-omics to identify the functions and phenotypes of HCV-specific CD8+ T cells. Early elevated IFN-γ response against the transmitted virus was associated with the rate of immune escape, larger clonal expansion, and early onset of exhaustion. Irrespective of disease outcome we discovered progenitors of early-exhaustion with intermediate expression of PD-1. Intra clonal analysis revealed distinct trajectories with multiple fates suggesting evolutionary plasticity of precursor cells. These findings challenge current paradigm on the contribution of CD8+ T cells to HCV disease outcome and provide data for future studies on T-cell differentiation in human infections.One sentence summaryProgenitors of T-cell exhaustion in acute HCV infection
Effect of human behavior on the evolution of viral strains during an epidemic
Authors: Azizi Asma , Komarova Natalia L. , Wodarz Dominik 
Published: September 2021

AbstractIt is well known in the literature that human behavior can change as a reaction to disease observed in others, and that such behavioral changes can be an important factor in the spread of an epidemic. It has been noted that human behavioral traits in disease avoidance are under selection in the presence of infectious diseases. Here we explore a complimentary trend: the pathogen itself might experience a force of selection to become less “visible”, or less “symptomatic”, in the presence of such human behavioral trends. Using a stochastic SIR agent-based model, we investigated the co-evolution of two viral strains with cross-immunity, where the resident strain is symptomatic while the mutant strain is asymptomatic. We assumed that individuals exercised self-regulated social distancing (SD) behavior if one of their neighbors was infected with a symptomatic strain. We observed that the proportion of asymptomatic carriers increased over time with a stronger effect corresponding to higher levels of self-regulated SD. Adding mandated SD made the effect more significant, while the existence of a time-delay between the onset of infection and the change of behavior reduced the advantage of the asymptomatic strain. These results were consistent under random geometric networks, scale-free networks, and a synthetic network that represented the social behavior of the residents of New Orleans.
Benchmarking feature quality assurance strategies for non-targeted metabolomics
Authors: El Abiead Yasin , Milford Maximilian , Schoeny Harald , Rusz Mate , Salek Reza M , Koellensperger Gunda 
Published: September 2021

ABSTRACTAutomated data pre-processing (DPP) forms the basis of any liquid chromatography-high resolution mass spectrometry-driven non-targeted metabolomics experiment. However, current strategies for quality control of this important step have rarely been investigated or even discussed. We exemplified how reliable benchmark peak lists could be generated for eleven publicly available datasets acquired across different instrumental platforms. Moreover, we demonstrated how these benchmarks can be utilized to derive performance metrics for DPP and tested whether these metrics can be generalized for entire datasets. Relying on this principle, we cross-validated different strategies for quality assurance of DPP, including manual parameter adjustment, variance of replicate injection-based metrics, unsupervised clustering performance, automated parameter optimization, and deep learning-based classification of chromatographic peaks. Overall, we want to highlight the importance of assessing DPP performance on a regular basis.
Reconstruction of the binding pathway of an anti-HIV drug, Indinavir, in complex with the HTLV-1 protease by Unaggregated Unbiased Molecular Dynamics simulation
Authors: Sohraby Farzin , Aryapour Hassan 
Published: September 2021

AbstractRetroviruses are a growing concern for the health of human beings, and one of the dangerous members of this family is the Human T-cell Leukemia Virus 1 (HTLV-1) virus. It has affected more than 20 million people so far, and since there are no registered treatments against it yet, urgent treatment solutions are needed. One of the most promising drug targets to fight this virus is the protease enzyme of the virus’s protein machinery. In this study, by utilizing a computational method called Unaggregated Unbiased Molecular Dynamics (UUMD), we reconstructed the binding pathway of a HTLV-1 protease inhibitor, Indinavir, to find the details of the binding pathway, the influential residues, and also the stable states of the binding pathway. We achieved the native conformation of the inhibitor in 6 rounds, 360 replicas by performing over 4 micro-seconds of UMD simulations. We found 3 Intermediate states between the solvated state and the native conformation state in the binding pathway. We also discovered that aromatic residues such as Trp98 and Trp98′, catalytic residues Asp32 and Asp32′, and the flap region’s residues have the most influential roles in the binding pathway and also have the most contribution to the total interaction energies. We believe that the details found in this study would be a great guide for developing new treatment solutions against the HTLV-1 virus by inhibiting the HTLV-1 protease.
Reassortment Network of Influenza A Virus
Authors: Gong Xingfei , Hu Mingda , Chen Wei , Yang Haoyi , Wang Boqian , Yue Junjie , Jin Yuan , Liang Long , Ren Hongguang 
Published: September 2021

AbstractInfluenza A virus (IAV) genomes are composed of eight single-stranded RNA segments. Genetic exchange through reassortment of the segmented genomes often endows IAVs with new genetic characteristics, which may affect transmissibility and pathogenicity of the viruses. However, a comprehensive understanding of the reassortment history of IAVs remains lacking. To this end, we assembled 40296 whole-genome sequences of IAVs for analysis. Using a new clustering method based on Mean Pairwise Distances in the phylogenetic trees, we classified each segment of IAVs into clades. Correspondingly, reassortment events among IAVs were detected by checking the segment clade compositions of related genomes under specific environment factors and time period. We systematically identified 1927 possible reassortment events of IAVs and constructed their reassortment network. Interestingly, minimum spanning tree of the reassortment network reproved that swine act as an intermediate host in the reassortment history of IAVs between avian species and human. Moreover, reassortment patterns among related subtypes constructed in this study are consistent with previous studies. Taken together, our genome-wide reassorment analysis of all the IAVs offers an overview of the leaping evolution of the virus and a comprehensive network representing the relationships of IAVs.AvailabilitySource code freely available for download at https://github.com/ElevenStr/IAVreassortment, implemented in python.Lead Contactbioren@163.com
Transcriptional networks underpinning ploidy related increased leaf potassium in neo-tetraploids
Authors: Fischer Sina , Flis Paulina , Zhao Fang-Jie , Salt David E. 
Published: September 2021

AbstractNeo-tetraploid Arabidopsis thaliana have elevated leaf potassium (K) driven by processes within the root. The root transcriptome of neo-tetraploids is distinct from diploids, with evidence of altered K homeostasis. Mutational analysis revealed that the canonical K-uptake transporters AKT1 and HAK5 are not required for this elevated leaf K in neo-tetraploids, while the endodermis, root hairs, and SOS signaling are. Contrasting the root transcriptomes of neo-tetraploids and diploids of mutants that block the neo-tetraploid K phenotype, allowed us to identify 91 differentially expressed genes associated with elevated leaf K in neo-tetraploids. This set of genes connects WGD to elevated leaf K, and is enriched in functions such as cell wall and Casparian strip development, and ion-transport, in the endodermis, root hairs, and procambium. This gene set provides tools to test the intriguing idea of recreating the physiological effects of WGD within a diploid genome.
Evolutionary innovations through gain and loss of genes in the ectomycorrhizal Boletales
Authors: Wu Gang , Miyauchi Shingo , Morin Emmanuelle , Kuo Alan , Drula Elodie , Varga Torda , Kohler Annegret , Feng Bang , Cao Yang , Lipzen Anna , Daum Christopher , Hundley Hope , Pangilinan Jasmyn , Johnson Jenifer , Barry Kerrie , LaButti Kurt , Ng Vivian , Ahrendt Steven , Min Byoungnam , Choi In-Geol , Park Hongjae , Plett Jonathan M. , Magnuson Jon , Spatafora Joseph W. , Nagy László G. , Henrissat Bernard , Grigoriev Igor V. , Yang Zhu-Liang , Xu Jianping , Martin Francis M. 
Published: September 2021

SUMMARYIn this study, we aim to identify genomic traits of the transitions to the ectomycorrhizal ecology within the Boletales, one of the most diverse lineages of symbiotrophic fungi.We sequenced the genomes and compared the gene repertoires of symbiotrophic Boletales species to their saprotrophic brown-rot relatives. We also reconstructed gene duplication/loss histories along a time-calibrated phylogeny.We showed that the rate of gene duplication is constant along the backbone of Boletales phylogeny with large loss events in lineages leading to several families. The rate of gene family expansion sharply increased in the late Miocene and mostly took place in Boletaceae.Most of the ectomycorrhizal Boletales are characterized by a large genome size due to transposable element (TE) expansions and a reduction in the diversity of plant cell wall degrading enzymes (PCWDEs) compared to their brown-rot relatives. However, several species in the Boletaceae, Paxillaceae and Boletinellaceae have kept a substantial set of endoglucanases and LPMOs acting on cellulose/hemicellulose and fungal polysaccharides suggesting that they may partly decompose organic matter by a combined activity of oxidative and hydrolytic enzymes.The present study provides novel insights on our understanding of the mechanisms that influence the evolutionary diversification of boletes and symbiosis evolution.
Overriding defective FPR chemotaxis signaling in diabetic neutrophil stimulates infection control in diabetic wound
Authors: Roy Ruchi , Zayas Janet , Wood Stephen J. , Mohamed Mohamed F. , Frausto Dulce M. , Estupinian Ricardo , Giurini Eileena F. , Kuzel Timothy M. , Zloza Andrew , Reiser Jochen , Shafikhani Sasha H. 
Published: September 2021

AbstractInfection is a major co-morbidity that contributes to impaired healing in diabetic wounds. Although impairments in diabetic neutrophils have been blamed for this co-morbidity, what causes these impairments and whether they can be overcome, remain largely unclear. Diabetic neutrophils, extracted from diabetic individuals, exhibit chemotaxis impairment but this peculiar functional impairment has been largely ignored because it appears to contradict the clinical findings which blame excessive neutrophil influx (neutrophilia) as a major impediment to healing in chronic diabetic ulcers. Here, we report that exposure to glucose in diabetic range results in impaired chemotaxis signaling through the FPR1 chemokine receptor in neutrophils, culminating in reduced chemotaxis and delayed neutrophil trafficking in wound in diabetic animals, and rendering diabetic wound vulnerable to infection. We further show that at least some auxiliary chemokine receptors remain functional under diabetic conditions and their engagement by the pro-inflammatory cytokine CCL3, overrides the requirement for FPR1 signaling and substantially improves infection control by jumpstarting the neutrophil response toward infection, and stimulates healing in diabetic wound. We posit that CCL3 may have real therapeutic potential for the treatment of diabetic foot ulcers if it is applied topically after the surgical debridement process which is intended to reset chronic ulcers into acute fresh wounds.
Laminar microcircuitry of visual cortex producing attention-associated electric fields
Authors: Westerberg Jacob A. , Schall Michelle S. , Maier Alexander , Woodman Geoffrey F. , Schall Jeffrey D. 
Published: September 2021

AbstractCognitive operations are widely studied by measuring electric fields through EEG and ECoG. However, despite their widespread use, the component neural circuitry giving rise to these signals remains unknown. Specifically, the functional architecture of cortical columns which results in attention-associated electric fields has not been explored. Here we detail the laminar cortical circuitry underlying an attention-associated electric field often measured over posterior regions of the brain in humans and monkeys. First, we identified visual cortical area V4 as one plausible contributor to this attention-associated electric field through inverse modeling of cranial EEG in macaque monkeys performing a visual attention task. Next, we performed laminar neurophysiological recordings on the prelunate gyrus and identified the electric-field-producing dipoles as synaptic activity in distinct cortical layers of area V4. Specifically, activation in the extragranular layers of cortex resulted in the generation of the attention-associated dipole. Feature selectivity of a given cortical column determined the overall contribution to this electric field. Columns selective for the attended feature contributed more to the electric field than columns selective for a different feature. Lastly, the laminar profile of synaptic activity generated by V4 was sufficient to produce an attention-associated signal measurable outside of the column. These findings suggest that the top-down recipient cortical layers produce an attention-associated electric field capable of being measured extracranially and the relative contribution of each column depends upon the underlying functional architecture.
Reach-dependent reorientation of rotational dynamics in motor cortex
Authors: Sabatini David A. , Kaufman Matthew T. 
Published: September 2021

AbstractDuring reaching, neurons in motor cortex exhibit complex, time-varying activity patterns. Though single-neuron activity correlates with movement parameters, movement correlations explain neural activity only partially. Neural responses also reflect population-level dynamics thought to generate outputs. These dynamics have previously been described as “rotational”, such that activity orbits in neural state space. Here, we find two essential features previously missed. First, the planes in which rotations occur differ for different reaches. Second, this variation in planes reflects the overall location of activity in neural state space. Our “location-dependent rotations” model fits nearly all motor cortex activity during reaching and enables higher-quality decoding of reach kinematics from single-trial spiking. Varying rotational planes allows motor cortex to more simply produce richer outputs than possible under previous models. Finally, our model links representational and dynamical ideas: a representation-like signal is present as the state space location, which dynamics then convert into time-varying command signals.