bluuebunny/crossref_metadata_2025_split huggingface dataset:
Return to Full Participation Following Concussion in the National Football League, 2015 Through 2020
Authors: Mack Christina D. , Herzog Mackenzie M. , Solomon Gary , Putukian Margot , Lee Rebecca Y. , Matava Matthew J. , Cárdenas Javier , Theodore Nicholas , Sills Allen 
Published: June 2022

Objective:
Quantify days missed, games missed, injury burden, and time to return to full participation (RTFP) among National Football League (NFL) players who sustained a concussion.

Design:
Retrospective cohort study.

Setting:
2015 through 2020 NFL seasons.

Participants:
National Football League players diagnosed with a concussion from 2015 to 2020.

Interventions:
National Football League-mandated graduated RTFP protocol.

Main Outcome Measures:
Days missed, games missed, burden, and time to RTFP, overall and by position.

Results:
An annual average of 3639 player-days of participation and 255 games were missed across NFL because of concussion. Concussed players missed a median of 9 days (mean = 15.0), a relatively stable metric over 6 years, with slight variation by position. Offensive linemen, tight ends, running backs, and linebackers missed the most days per concussion; defensive secondary, offensive linemen, and wide receivers sustained the highest injury burden. Postconcussion, 59% of players missed one or more scheduled games. Among players concussed in a Sunday game, 38% played in a Sunday game one week later.

Conclusions:
The 9-day median time missed post-concussion may be related to emphasis on graduated phase-based concussion management. No concussed player returned to competition on the day of injury, and less than 40% participated in games the following week. Further work is needed to better understand characteristics of concussions that take longer to return and movement through stages of return.
Imaging of the Left Atrial Appendage Before Occluder Device Placement: Evaluation of Virtual Monoenergetic Images in a Single-Bolus Dual-Phase Protocol
Authors: Laukamp Kai Roman , Dastmalchian Sara , Tandon Yasmeen K. , Ciancibello Leslie , Pennig Lenhard , Lennartz Simon , Al-Kindi Sadeer , Rajagopalan Sanjay , Bera Kaustav , Hokamp Nils Große , Gilkeson Robert , Gupta Amit 
Published: June 2022

Purpose
Preimplantation cardiac computed tomography (CT) for assessment of the left atrial appendage (LAA) enables correct sizing of the device and the detection of contraindications, such as thrombi. In the arterial phase, distinction between false filling defects and true thrombi can be hampered by insufficient contrast medium distribution. A delayed scan can be used to further differentiate both conditions, but contrast in these acquisitions is relatively lower. In this study, we investigated whether virtual monoenergetic images (VMI) from dual-energy spectral detector CT (SDCT) can be used to enhance contrast and visualization in the delayed phase.

Materials and Methods
Forty-nine patients receiving SDCT imaging of the LAA were retrospectively enrolled. The imaging protocol comprised dual-phase acquisitions with single-bolus contrast injection. Conventional images (CI) from both phases and 40-keV VMI from the delayed phase were reconstructed. Attenuation, signal-, and contrast-to-noise ratios (SNR/CNR) were calculated by placing regions-of-interest in the LAA, left atrium, and muscular portion of interventricular septum. Two radiologists subjectively evaluated conspicuity and homogeneity of contrast distribution within the LAA.

Results
Contrast of the LAA decreased significantly in the delayed phase but was significantly improved by VMI, showing comparable attenuation, SNR, and CNR to CI from the arterial phase (attenuation/SNR/CNR, CI arterial phase: 266.0 ± 117.0 HU/14.2 ± 7.2/6.6 ± 3.9; CI-delayed phase: 107.6 ± 35.0 HU/5.9 ± 3.0/1.0 ± 1.0; VMI delayed phase: 260.3 ± 108.6 HU/18.2 ± 10.6/4.8 ± 3.4). The subjective reading confirmed the objective findings showing improved conspicuity and homogeneity in the delayed phase.

Conclusions
The investigated single-bolus dual-phase acquisition protocol provided improved visualization of the LAA. Homogeneity of contrast media was higher in the delayed phase, while VMI maintained high contrast.
Spectral invariants of ergodic symbolic systems for pattern recognition and anomaly detection
Authors: Ghalyan Najah F. , Bhattacharya Chandrachur , Ghalyan Ibrahim F. , Ray Asok 
Published: June 2022

Despite tangible advances in machine learning (ML) over the last few decades, many of the ML techniques still suffer from fundamental issues like overfitting and lack of explainability. These issues mandate requirements for mathematical rigor to ensure robust learning from observed data. In this context, topological invariants in data manifolds provide a rich representation of the underlying dynamical system, which can be utilized for developing a mathematically rigorous ML tool to characterize the dynamical behaviour and operational phases of the underlying process. This paper aims to investigate spectral invariants of symbolic systems for detecting changes in topological characteristics of data manifolds. A novel ML approach is proposed, where commutator norms are used on sequences of endomorphisms to symbolically describe dynamical systems on probability spaces with ergodic measures. The objective here is to detect topological invariants of data manifolds that can be used for signal processing, pattern recognition, and anomaly detection. The proposed ML approach is validated on models of selected chaotic dynamical systems for prompt detection of phase transitions.
This article is part of the theme issue ‘Data-driven prediction in dynamical systems’.
Machine learning-based statistical closure models for turbulent dynamical systems
Authors: Qi Di , Harlim John 
Published: June 2022

We propose a machine learning (ML) non-Markovian closure modelling framework for accurate predictions of statistical responses of turbulent dynamical systems subjected to external forcings. One of the difficulties in this statistical closure problem is the lack of training data, which is a configuration that is not desirable in supervised learning with neural network models. In this study with the 40-dimensional Lorenz-96 model, the shortage of data is due to the stationarity of the statistics beyond the decorrelation time. Thus, the only informative content in the training data is from the short-time transient statistics. We adopt a unified closure framework on various truncation regimes, including and excluding the detailed dynamical equations for the variances. The closure framework employs a Long-Short-Term-Memory architecture to represent the higher-order unresolved statistical feedbacks with a choice of ansatz that accounts for the intrinsic instability yet produces stable long-time predictions. We found that this unified agnostic ML approach performs well under various truncation scenarios. Numerically, it is shown that the ML closure model can accurately predict the long-time statistical responses subjected to various time-dependent external forces that have larger maximum forcing amplitudes and are not in the training dataset.This article is part of the theme issue ‘Data-driven prediction in dynamical systems’.
Localized non-intrusive reduced-order modelling in the operator inference framework
Authors: Geelen Rudy , Willcox Karen 
Published: June 2022

This paper presents data-driven learning of localized reduced models. Instead of a global reduced basis, the approach employs multiple local approximation subspaces. This localization permits adaptation of a reduced model to local dynamics, thereby keeping the reduced dimension small. This is particularly important for reduced models of nonlinear systems of partial differential equations, where the solution may be characterized by different physical regimes or exhibit high sensitivity to parameter variations. The contribution of this paper is a non-intrusive approach that learns the localized reduced model from snapshot data using operator inference. In the offline phase, the approach partitions the state space into subregions and solves a regression problem to determine localized reduced operators. During the online phase, a local basis is chosen adaptively based on the current system state. The non-intrusive nature of localized operator inference makes the method accessible, portable and applicable to a broad range of scientific problems, including those that use proprietary or legacy high-fidelity codes. We demonstrate the potential for achieving large computational speedups while maintaining good accuracy for a Burgers’ equation governing shock propagation in a one-dimensional domain and a phase-field problem governed by the Cahn–Hilliard equation.This article is part of the theme issue ‘Data-driven prediction in dynamical systems’.
Data-driven prediction in dynamical systems: recent developments
Authors: Ghadami Amin , Epureanu Bogdan I. 
Published: June 2022

In recent years, we have witnessed a significant shift toward ever-more complex and ever-larger-scale systems in the majority of the grand societal challenges tackled in applied sciences. The need to comprehend and predict the dynamics of complex systems have spurred developments in large-scale simulations and a multitude of methods across several disciplines. The goals of understanding and prediction in complex dynamical systems, however, have been hindered by high dimensionality, complexity and chaotic behaviours. Recent advances in data-driven techniques and machine-learning approaches have revolutionized how we model and analyse complex systems. The integration of these techniques with dynamical systems theory opens up opportunities to tackle previously unattainable challenges in modelling and prediction of dynamical systems. While data-driven prediction methods have made great strides in recent years, it is still necessary to develop new techniques to improve their applicability to a wider range of complex systems in science and engineering. This focus issue shares recent developments in the field of complex dynamical systems with emphasis on data-driven, data-assisted and artificial intelligence-based discovery of dynamical systems.This article is part of the theme issue 'Data-driven prediction in dynamical systems'.
Different approaches to processing environmental DNA samples in turbid waters have distinct effects for fish, bacterial and archaea communities
Authors: Turba Rachel , Thai Glory H. , Jacobs David K. 
Published: June 2022

AbstractCoastal lagoons are an important habitat for endemic and threatened species in California that have suffered impacts from urbanization and increased drought. Environmental DNA has been promoted as a way to aid in the monitoring of biological communities, but much remains to be understood on the biases introduced by different protocols meant to overcome challenges presented by unique systems under study. Turbid water is one methodologic challenge to eDNA recovery in these systems as it quickly clogs filters, preventing timely processing of samples. We investigated biases in community composition produced by two solutions to overcome slow filtration due to turbidity: freezing of water prior to filtration (for storage purposes and long-term processing), and use of sediment (as opposed to water samples). Bias assessments of community composition in downstream eDNA analysis was conducted for two sets of primers, 12S (fish) and 16S (bacteria and archaea). Our results show that freezing water prior to filtration had different effects on community composition for each primer, especially for the 16S, when using a filter of larger pore size (3 μm). Nevertheless, pre-freezing water samples can still be a viable alternative for storage and processing of turbid water samples when focusing on fish communities (12S). The use of sediment samples as an alternative to processing water samples should be done with caution, and at minimum the number of biological replicates and/or volume sampled should be increased.
A non-classical mechanism of β-lactam resistance in Methicillin-Resistant Staphylococcus aureus (MRSA) and its effect on virulence
Authors: Satishkumar Nidhi , Lai Li-Yin , Mukkayyan Nagaraja , Vogel Bruce E. , Chatterjee Som S. 
Published: June 2022

AbstractMethicillin-Resistant Staphylococcus aureus (MRSA) are pathogenic bacteria that are infamously resistant to β-lactam antibiotics, a property attributed to the mecA gene. Recent studies have reported that mutations associated with the promoter region of pbp4 demonstrated high levels of β-lactam resistance, suggesting the role of PBP4 as an important non-mecA mediator of β-lactam resistance. The pbp4 promoter-associated mutations have been detected in strains with or without mecA. Our previous studies that were carried out in strains devoid of mecA described that pbp4 promoter-associated mutations lead to PBP4 overexpression and β-lactam resistance. In this study, by introducing various pbp4 promoter-associated mutations in the genome of an MRSA strain, we demonstrate that PBP4 overexpression can supplement mecA-associated resistance in S. aureus and can lead to increased β-lactam resistance. The promoter and regulatory region of pbp4 is shared with a divergently transcribed gene, abcA, which encodes for a multidrug exporter. We demonstrate that the promoter mutations caused an upregulation of pbp4 and downregulation of abcA, confirming that the resistant phenotype is associated with PBP4 overexpression only. PBP4 has also been associated with staphylococcal pathogenesis, however, its exact role remains unclear. Using a C. elegans model, we demonstrate that strains having increased PBP4 expression are less virulent compared to wild-type strains, suggesting that β-lactam resistance mediated via PBP4 likely comes at the cost of virulence.ImportanceOur study demonstrates the ability of PBP4 to be an important mediator of β-lactam resistance in not only Methicillin-susceptible Staphylococcus aureus (MSSA) background strains as previously demonstrated, but also in MRSA strains. When present together, PBP2a and PBP4 overexpression can produce increased levels of β-lactam resistance, causing complications in treatment. Thus, this study suggests the importance of monitoring PBP4-associated resistance in clinical settings, as well as understanding the mechanistic basis of associated resistance, so that treatments targeting PBP4 may be developed. This study also demonstrates that S. aureus strains with increased PBP4 expression are less pathogenic, providing important hints about the role of PBP4 in S. aureus resistance and pathogenesis.
Factors determining success of the chronically instrumented unanesthetized fetal sheep model of human development: a retrospective cohort study
Authors: Wakefield Colin , Cao Mingju , Burns Patrick , Fecteau Gilles , Desrochers Andre , Frasch Martin G 
Published: June 2022

AbstractAimChronically instrumented non-anesthetized fetal sheep (CINAFS) have been the mainstay model of human fetal development for 60 years. As a large “two for one” animal model, with instrumentation of the ewe and her fetus, the model poses challenges to implement de novo and to maintain overtime at the highest standards of operating procedures to ensure its ongoing performance. A common, yet conventionally underreported issue researchers face is the rate of animal loss. Here, we investigate what determines the success of the pregnant sheep model.MethodsWe conducted a retrospective cohort study consisting of 82 experiments spanning the course of six years. Our team identified ten variables that we anticipated were likely to influence the experimental outcome, such as the time of year, animal size, and surgical complexity.ResultsThe single variable identified in this study as determining the successful outcome of the experiments is the experience level of the team.ConclusionThe CINAFS model offers enormous potential to further our understanding of human fetal development and to create interventional technologies. However, to improve the outcomes of CINAFS models, improved communication and training are needed. We discuss the implications of our findings for the successful implementation of this challenging yet scientifically advantageous animal model of human physiology.Key pointsThe fetal sheep model closely mirrors the physiology of human fetal developmentIn addition to its high translational potential, this model is known to have some generally not reported rate of experimental failureWe show that factors such as animal characteristics & surgical complexity do not influence the experimental outcomesInstead, the key factor in model experimental success is the level of the research team’s experienceThe key factors to improve the animal model outcomes are an intra- and inter-team communication
Molecular evolution of IRG1 shapes itaconate production in metazoans and alleviates the “double-edged dilemma” of innate immune defense
Authors: Szeligowski Richard V. , Miros Francois , Saez Andres , DeCiucis Marisa , Wagner Gunter P. , Shen Hongying 
Published: June 2022

AbstractItaconate is an innate immune metabolite specifically produced in stimulated immune cells via the decarboxylation of the TCA cycle intermediate cis-aconitate. Due to its inhibition of succinate-related metabolic processes, itaconate exhibits antimicrobial properties at the expense of potentially disrupting the hosts’ own central energy metabolism, a “double-edged dilemma” of immunometabolism. To understand the evolutionary logic of itaconate biosynthesis, we investigate the evolutionary trajectory of the Irg1 gene, which codes for the itaconate-producing enzyme cis-aconitate decarboxylase (CAD). Phylogenetic analysis reveals a putative independent acquisition of metazoan and fungal Irg1 from prokaryotic sources. The metazoan Irg1 underwent duplication in vertebrates and a subsequent loss of one paralog in mammals, a process that removes the mitochondrial targeting sequences (MTS) and relocates CAD outside of the mitochondrial matrix thus preventing a direct inhibition of energy metabolism. Experiments in the most diverged metazoan species that are known to contain Irg1, oysters and amphioxus, reveal that the expression of primitive Irg1 genes is induced by innate immune stimulants in invertebrates and basal chordates, suggesting an already specialized role of itaconate production for innate immune defense in early bilaterians. Our combined in silico and experimental analysis of Irg1 highlights that a trend of tightened transcriptional regulation and sequence-level change optimizes itaconate biosynthesis for innate immunity, a mechanism that may be broadly utilized to resolve other types of double-edged dilemmas in immunometabolism.
Binding of a blast fungus Zinc-finger fold effector to a hydrophobic pocket in the host exocyst subunit Exo70 modulates immune recognition in rice
Authors: De la Concepcion Juan Carlos , Fujisaki Koki , Bentham Adam R. , Mireles Neftaly Cruz , de Medina Hernandez Victor Sanchez , Shimizu Motoki , Lawson David M. , Kamoun Sophien , Terauchi Ryohei , Banfield Mark J. 
Published: June 2022

AbstractExocytosis plays an important role in plant-microbe interactions, both in pathogenesis and symbiosis. Exo70 proteins are integral components of the exocyst, an octameric complex that mediates tethering of vesicles to membranes in eukaryotes. Although plant Exo70s are known to be targeted by pathogen effectors, the underpinning molecular mechanisms and the impact of this interaction on infection is poorly understood. Here, we show the molecular basis of the association between the effector AVR- Pii of the blast fungus Maganaporthe oryzae and rice Exo70 alleles OsExo70F2 and OsExo70F3, which is sensed by the immune receptor pair Pii via an integrated RIN4/NOI domain. The crystal structure of AVR-Pii in complex with OsExo70F2 reveals that the effector binds to a conserved hydrophobic pocket in Exo70, defining a new effector/target binding interface. Structure-guided and random mutagenesis validates the importance of AVR-Pii residues at the Exo70 binding interface to sustain protein association and disease resistance in rice when challenged with fungal strains expressing effector mutants. Further, the structure of AVR-Pii defines a novel Zinc- finger effector fold (ZiF) distinct from the MAX fold previously described for the majority of characterized M. oryzae effectors. Our data suggests that blast fungus ZiF effectors bind a conserved Exo70 interface to manipulate plant exocytosis and that these effectors are also baited by plant immune receptors, pointing to new opportunities for engineering disease resistance.Significance statementPlant diseases destroy ∼20-30% of annual crop production, contributing to global food insecurity. Discovering how pathogen effectors target host proteins to promote virulence is essential for understanding pathogenesis and can be used for developing disease resistant crops. Here, we reveal the structural basis of how an effector from the blast pathogen (AVR-Pii) binds a specific host target (rice Exo70), and how this underpins immune recognition. This has implications for understanding the molecular mechanisms of blast disease and for the engineering of new recognition specificities in plant immune receptors to confer resistance to a major crop pathogen.
An integrated approach to study chromatin and transcriptional dynamics throughout the cell cycle without pharmacological inhibition
Authors: Shlyueva Daria , Teed-Singer Sarah , Zhan Yingqian , Koche Richard , Helin Kristian 
Published: June 2022

ABSTRACTThe cellular and nuclear states are constantly changing and closely linked to DNA replication and cell division, defining cell cycle phases. Pharmacological inhibition is a widely used strategy to enrich for specific phases to study them in isolation. However, chemical-induced cell cycle synchronization may influence chromatin openness and gene expression compared to unperturbed cell cycle states. Here, we use different synchronization methods to obtain G1, S and G2/M phases from mouse embryonic stem cells (mESCs) and profile their chromatin accessibility and post- translational modifications as well as steady and nascent transcripts levels. We demonstrate that synchronization with thymidine and nocodazole leads to dramatic changes in chromatin compaction and gene expression, which only partially resemble bona fide cell cycle-dependent differences. Blocking with CDK1 inhibitor results in efficient synchronization and evokes moderate changes in chromatin accessibility, resembling G2/M phase. Correlative analysis suggests that cell cycle-specific variations in chromatin openness in unperturbed mESCs are mediated by CDK1 substrates and CTCF. This integrated strategy can be applied to most cultured cell lines under any conditions and holds the potential to further our understanding of cell cycle- dependent susceptibility to external cues and chromatin regulation.