bluuebunny/crossref_metadata_2025_split huggingface dataset:
Besieged in the Bronx: Lessons from an in-hospital mass casualty
Authors: Chu Julianne L. , Castaldi Maria , Bridges Kristen , O’Driscoll Kieran M. , Rigdon Amanda R. , Shayesteh Ali , Robinson Sam , Narula Samir , Vemulapalli Pratibha , Gilchrist Brian F. 
Published: August 2023

BACKGROUND
An active shooter in a hospital is an emergency extraordinaire. We report a single institution's response to the largest active shooter mass casualty event in American History.

METHODS
Review of notification, flow of prioritized patients, and key elements of the day's dynamic after a hospital attack by a lone gunman were commenced. The review includes outcomes on seven victims and assailants.

RESULTS
“Code Silver” announced: open display of a weapon. Concise, known, and published chain of command implemented. All house staff to the Emergency Department (ED) via text blast. Operating room (OR) notified. Injured to ED, then triaged to OR. Armed NYPD stationed throughout OR. Senior surgeons controlled key triage during attack with flow controlled from the ED and OR control desk. One fatality plus shooter.

CONCLUSION
Success favors the prepared. The response to attack, readiness of medical personnel, mitigation, and recovery have brought the following recommendations: (1) single entrance access; (2) armed, professional guards at all entrances; (3) camouflage metal detectors; (4) mandatory, recurrent hospital-wide active shooter training, mock, and table top; (5) published physician chain of command; (6) intercom code system known to all hospital personnel indicating a weapon is openly displayed; (7) a “no fly” list of former employees who are prohibited on premises; (8) stop the bleed training with kits on every floor; (9) one voice, one face to disseminate information.

LEVEL OF EVIDENCE
Prognostic and Epidemiological; Level I.
Benchmark Pathology Report Text Corpus with Cancer Type Classification
Authors: Kefeli Jenna , Tatonetti Nicholas 
Published: August 2023

AbstractIn cancer research, pathology report text is a largely un-tapped data source. Pathology reports are routinely generated, more nuanced than structured data, and contain added insight from pathologists. However, there are no publicly-available datasets for benchmarking report-based models. Two recent advances suggest the urgent need for a benchmark dataset. First, improved optical character recognition (OCR) techniques will make it possible to access older pathology reports in an automated way, increasing data available for analysis. Second, recent improvements in natural language processing (NLP) techniques using AI allow more accurate prediction of clinical targets from text. We apply state-of-the-art OCR and customized post- processing to publicly available report PDFs from The Cancer Genome Atlas, generating a machine-readable corpus of 9,523 reports. We perform a proof-of-principle cancer-type classification across 32 tissues, achieving 0.992 average AU-ROC. This dataset will be useful to researchers across specialties, including research clinicians, clinical trial investigators, and clinical NLP researchers.
The Relationship of Duffy Gene Polymorphism, High Sensitivity C-Reactive Protein, and Long-term Outcomes
Authors: Ha Edward T. , Taylor Kent D. , Raffield Laura M , Briggs Matt , Yee Aaron , Elemento Olivier , Parikh Manish , Peterson Stephen J. , Frishman William , Gerszten Robert E. , Wilson James G. , Kelsey Karl , Tahir Usman A. , Reiner Alex , Auer Paul , Seeman Teresa , Rich Stephen S. , Carson April P. , Post Wendy S. , Rotter Jerome I. , Aronow Wilbert S. 
Published: August 2023

AbstractBackgroundBlack adults have higher incidence of all-cause death and worse cardiovascular outcomes when compared to other populations. The Duffy chemokine receptor is not expressed in a large majority of Black adults and the clinical implications of this are unclear.MethodsHere, we investigated the relationship of Duffy receptor status, high-sensitivity C-reactive protein (hs-CRP), and long-term cardiovascular outcomes in Black members of two contemporary, longitudinal cohort studies (the Jackson Heart Study and Multi-Ethnic Study of Atherosclerosis). Data on 4,307 Black participants (2,942 Duffy null and 1,365 Duffy receptor positive, as defined using Single Nucleotide Polymorphism (SNP) rs2814778) were included in this analysis.ResultsDuffy null was not independently associated with elevated levels of serum hs-CRP levels once conditioning for knownCRPlocus alleles in linkage disequilibrium with the Duffy gene. Duffy null status was not found to be independently associated with higher incidence of all-cause mortality or secondary outcomes after adjusting for possible confounders in Black participants.ConclusionsThese findings suggest that increased levels of hs-CRP found in Duffy null individuals is due to co-inheritance of CRP alleles known to influence circulating levels hs-CRP and that Duffy null status was not associated with worse adverse outcomes over the follow-up period in this cohort of well-balanced Black participants.
Much more than a name change: Impact of the new steatotic liver disease nomenclature on clinical algorithms and disease classification in U.S. adults and adolescents
Authors: Ma Ning , Bansal Meena , Chu Jaime , Branch Andrea D. 
Published: August 2023

AbstractBackground and Aims:The newly proposed nomenclature for steatotic liver diseases (SLD) aims to reduce the stigma associated with “non-alcoholic fatty liver disease” (NAFLD), increase awareness, and provide a framework for delineating pathogenic pathways.Approach and Results:We projected the new nomenclature’s diagnostic scheme onto National Health and Nutrition Examination Survey (NHANES) data and determined SLD prevalence, fibrosis risk factors, subtypes, and consistency with previous classifications. Steatosis grade and fibrosis stage were estimated from vibration controlled transient elastography (VCTE). At a threshold of 240 dB/m, 62.1% [95% confidence interval (CI), 59.8-64.3%] of adults (≥ 20 years) and 30.5% (95% CI, 27.1-34.0%) of adolescents (12-19 years) had SLD. By American Gastroenterological Association criteria, 19.3 million (95% CI, 15.8-22.8) adults with SLD qualify for hepatology referral. Over 98% of adults but only 85% of adolescents with NAFLD met criteria for definite MASLD. Significant fibrosis (≥ 8.6 kPa) occurred in 13.5 million (95% CI, 10.9-16.2) adults with MASLD; risk factors varied by race and ethnicity. Significant fibrosis occurred in over 1.5 million adults without any identified LD and was associated with lead (Pb) exposure, odds ratio = 3.89 (95% CI, 2.00-7.56).Conclusions:The overarching term, SLD, changes the diagnostic algorithm and creates an umbrella classification that highlights the extraordinary prevalence of liver steatosis. The more precise nomenclature establishes a valuable patient-centric platform for research and clinical care, clarifying risk groups and risk factors, including adolescents with NAFLD but without definite MASLD and adults without SLD in whom toxic exposures may increase fibrosis risk.
SARS-CoV-2 infection of human pluripotent stem cell-derived vascular cells reveals smooth muscle cells as key mediators of vascular pathology during infection
Authors: Richards Alexsia , Khalil Andrew , Friesen Max , Whitfield Troy W. , Gao Xinlei , Lungjangwa Tenzin , Kamm Roger , Wan Zhengpeng , Gehrke Lee , Mooney David , Jaenisch Rudolf 
Published: August 2023

AbstractAlthough respiratory symptoms are the most prevalent disease manifestation of infection by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), nearly 20% of hospitalized patients are at risk for thromboembolic events. This prothrombotic state is considered a key factor in the increased risk of stroke, which is observed clinically during both acute infection and long after symptoms clear. Here we develop a model of SARS-CoV-2 infection using human-induced pluripotent stem cell-derived endothelial cells (ECs), pericytes (PCs), and smooth muscle cells (SMCs) to recapitulate the vascular pathology associated with SARS-CoV-2 exposure. Our results demonstrate that perivascular cells, particularly SMCs, are a susceptible vascular target for SARS-CoV-2 infection. Utilizing RNA sequencing, we characterize the transcriptomic changes accompanying SARS-CoV-2 infection of SMCs, PCs, and ECs. We observe that infected SMCs shift to a pro-inflammatory state and increase the expression of key mediators of the coagulation cascade. Further, we show human ECs exposed to the secretome of infected SMCs produce hemostatic factors that contribute to vascular dysfunction, despite not being susceptible to direct infection. The findings here recapitulate observations from patient sera in human COVID-19 patients and provide mechanistic insight into the unique vascular implications of SARS-CoV-2 infection at a cellular level.
Deep learning methods in metagenomics: a review
Authors: Roy Gaspar , Prifti Edi , Belda Eugeni , Zucker Jean-Daniel 
Published: August 2023

AbstractThe ever-decreasing cost of sequencing and the growing potential applications of metagenomics have led to an unprecedented surge in data generation. One of the most prevalent applications of metagenomics is the study of microbial environments, such as the human gut. The gut microbiome plays a crucial role in human health, providing vital information for patient diagnosis and prognosis. However, analyzing metagenomic data remains challenging due to several factors, including reference catalogs, sparsity, and compositionality. Deep learning (DL) enables novel and promising approaches that complement state-of-the-art microbiome pipelines. DL-based methods can address almost all aspects of microbiome analysis, including novel pathogen detection, sequence classification, patient stratification, and disease prediction. Beyond generating predictive models, a key aspect of these methods is also their interpretability. This article reviews deep learning approaches in metagenomics, including convolutional networks (CNNs), autoencoders, and attention-based models. These methods aggregate contextualized data and pave the way for improved patient care and a better understanding of the microbiome’s key role in our health.Author summaryIn our study, we look at the vast world of research in metagenomics, the study of genetic material from environmental samples, spurred by the increasing affordability of sequencing technologies. Our particular focus is the human gut microbiome, an environment teeming with microscopic life forms that plays a central role in our health and well-being. However, navigating through the vast amounts of data generated is not an easy task. Traditional methods hit roadblocks due to the unique nature of metagenomic data. That’s where deep learning (DL), a today well known branch of artificial intelligence, comes in. DL-based techniques complement existing methods and open up new avenues in microbiome research. They’re capable of tackling a wide range of tasks, from identifying unknown pathogens to predicting disease based on a patient’s unique microbiome. In our article, we provide a very comprehensive review of different DL strategies for metagenomics, including convolutional networks, autoencoders, and attention-based models. We are convinced that these techniques significantly enhance the field of metagenomic analysis in its entirety, paving the way for more accurate data analysis and, ultimately, better patient care. The PRISMA augmented diagram of our review is illustrated inFig 1.
Many morphs: parsing gesture signals from the noise
Authors: Mielke Alexander , Badihi Gal , Graham Kirsty E. , Grund Charlotte , Hashimoto Chie , Piel Alex K. , Safryghin Alexandra , Slocombe Katie E. , Stewart Fiona , Wilke Claudia , Zuberbühler Klaus , Hobaiter Catherine 
Published: August 2023

AbstractParsing signals from noise is a general problem for signallers and recipients, as well as for researchers studying communicative systems. Substantial research efforts have been invested in comparing how other species encode information and meaning in their signals, and how signalling is structured. However, our ability to do so depends on identifying and discriminating signals that represent meaningful units of analysis. Early approaches to defining signal repertoires applied top- down approaches, classifying cases into predefined signal types. Recently, more labour-intensive methods have taken a bottom-up approach describing the features of each signal in detail and clustering cases into types based on patterns of similarity between them in multi-dimensional feature-space that were previously undetectable. Nevertheless, it remains essential to assess whether the resulting repertoires are composed of relevant units from the perspective of the species using them, and redefining repertoires when additional data makes more detailed analyses feasible. In this paper we provide a framework that takes data from the largest set of wild chimpanzee (Pan troglodytes) gestures currently available, splitting gesture types at a fine scale based on modifying features of gesture expression and then determining whether this splitting process increases the information content of the communication system. Our method allows different features of interest to be incorporated into the splitting process, providing substantial future flexibility across - for example - species, populations, and levels of signal granularity. In doing so we provide a powerful tool allowing researchers interested in gestural communication to establish repertoires of relevant units for subsequent analyses within and between systems of communication.
Modulation of premotor cortex excitability mitigates the behavioral and electrophysiological abnormalities in a Parkinson’s Disease Mouse Model
Authors: Choi In Sun , Kim Jinmo , Choi Joon Ho , Choi Ji-Woong , Rah Jong-Cheol 
Published: August 2023

AbstractThe subthalamic nucleus (STN) is important in halting ongoing behaviors, referred to as stop-signal responses. The prefrontal regions innervating the STN exhibit increased activity during the stop-signal responses, and optogenetic activation of these neurons inhibits impulsive actions in rodents. High-frequency electrical stimulation of the STN effectively treats motor symptoms of Parkinson’s disease (PD), yet its underlying circuit mechanisms are unclear. Here, we investigated the involvement of STN-projecting premotor (M2) neurons in PD mouse models and the impact of deep brain stimulation targeting the STN (DBS-STN). We found that M2 neurons exhibited enhanced burst firing and synchronous oscillations in the PD mouse model. Remarkably, high-frequency stimulation of STN-projecting M2 neurons, simulating antidromic activation, during DBS-STN relieved motor symptoms and hyperexcitability. These changes were attributed to reduced firing frequency vs. current relationship through normalized hyperpolarization-activated inward current (Ih). The M2 neurons in the PD model mouse displayed increased Ih, which was reversed by high-frequency stimulation. Additionally, the infusion of ZD7288, an HCN channel blocker, into the M2 replicated the effects of high-frequency stimulation. In conclusion, our study unveils excessive excitability and suppressive motor control through M2-STN synapses in the PD mouse model. Antidromic excitation of M2 neurons during deep brain stimulation of the STN alleviates this suppression, thereby improving motor impairment. These findings provide insights into the circuit-level dynamics underlying deep brain stimulation’s therapeutic effects in PD. Targeting M2-STN synapses may be useful for future therapeutic strategies.Significance StatementOur study provides insight into the mechanisms underlying motor impairment in Parkinson’s disease (PD) and the therapeutic effect of deep brain stimulation (DBS). By elucidating the role of hyperpolarization-activated cyclic nucleotide-gated (HCN) channels in modulating the hyperexcitability of M2 neurons, we identify potential targets for future PD treatment strategies. Understanding the excessive excitability and suppressive motor control through M2-STN synapses in PD mouse models contributes to our knowledge of circuit-level dynamics underlying DBS effects. These findings have significant implications for improving motor symptoms and advancing the development of more precise and effective interventions for PD patients.HighlightsSTN-projecting M2 neurons show increased burst firing in PD mice.High-frequency stimulation relieves M2 hyperexcitability and motor symptoms.Reduction in M2 hyperexcitability by DBS linked to normalized Ih.ZD7288 infusion in M2 replicates high-frequency stimulation effects.Targeted modulation of M2 neurons may alleviate PD symptoms.
The Moa the Merrier: Resolving When the Dinornithiformes Went Extinct
Authors: Foxon Floe 
Published: August 2023

AbstractThe Moa (Aves: Dinornithiformes) are an extinct group of the ratite clade from New Zealand. The overkill hypothesis asserts that the first New Zealand settlers hunted the Moa to extinction by 1450 CE, whereas the staggered survival hypothesis allows for Moa survival until after Europeans began to arrive on New Zealand. Alleged Moa sightings post-1450 CE may shed light on these competing hypotheses. A dataset of 97 alleged Moa sightings from circa 1675 CE to 1993 CE was constructed, with sightings given subjective quality ratings corresponding to various statistical probabilities. Cumulative probabilities of Moa persistence were calculated with a conservative survival model using these probabilistic sighting-records; a method recently applied to sightings of the Thylacine. Cumulative persistence probability fell sharply after 1408 CE, and across pessimistic and optimistic variations of the model, it was more likely than not that the Moa were extinct by 1770 CE. Probabilistic sighting-record models favour the overkill hypothesis, and give very low probabilities of Moa persistence around the time of European arrival. Eyewitness data on Moa sightings are amenable to scientific study, and these methods may be applied to similar animals.
Genetic Characterization of Glyoxalase Pathway in Oral Streptococci and its Contribution to Interbacterial Competition
Authors: Zeng Lin , Noeparvar Payam , Burne Robert A , Glezer Benjamin S. 
Published: August 2023

AbstractSubstantial quantities of Reactive Electrophile Species (RES), including methylglyoxal and glyoxal, are generated by microbes and humans. To understand the impact of RES on oral microbial homeostasis, genetic analyses were performed on the glyoxalase pathway inStreptococcus mutans(SMU) andStreptococcus sanguinis(SSA). Loss of glyoxalase I (LguL), which catalyzes the rate-limiting reaction in RES degradation, reduced methylglyoxal and glyoxal tolerance to a far greater extent in SMU than in SSA, decreasing the competitiveness of SMU over SSA in planktonic cultures. MICs showed an overall greater RES tolerance by SMU than SSA; a finding consistent with the ability of methylglyoxal to induce the expression oflguLin SMU, but not in SSA. Computational analysis identified a novel paralogue of LguL in most streptococci represented by SMU.1112c in SMU. ΔSMU.1112c showed a minor decrease in methylglyoxal tolerance under certain conditions, but a significant growth defect on fructose; a phenotype reversed by the deletion of a fructose-1-phosphate-generating sugar: phosphotransferase system or addition of glutathione (GSH) to the medium. Further, deletion of the glucose-PTS in SMU increased RES tolerance partly through enhanced expression of the pyruvate-dehydrogenase complex. Consistent with the requirement of GSH for methylglyoxal detoxification, deletion of glutathione synthetase (gshAB) in SMU significantly reduced RES resistance. This study reveals the critical roles of RES in fitness and interbacterial competition and the effects of PTS in modulating RES metabolism. The fact that RES may impact the pathogenic potential of the oral microbiome via differential effects on beneficial and pathogenic species warrants further investigation.ImportanceAs highly reactive byproducts of sugar metabolism, very little is known regarding the contribution of methylglyoxal or related aldehyde compounds to oral health. The need to better understand the influence of these reactive electrophile species (RES) to microbial physiology and ecology is made more urgent by the widespread condition of hyperglycemia in humans, which is associated with elevated RES levels. Our study showed a significantly greater ability of a major caries pathobiont,Streptococcus mutans, to tolerate methylglyoxal and glyoxal than many commensal oral streptococci. Genetic analysis of methylglyoxal degradation in the pathobiont and commensals identified significant differences in genetic structure and gene regulation patterns that could contribute to differential fitness by constituents of the dental microbiota and ecologic shift in the presence of RES.
Benchmarking informatics approaches for virus discovery: Caution is needed when combiningin silicoidentification methods
Authors: Hegarty Bridget , Riddell V James , Bastien Eric , Langenfeld Kathryn , Lindback Morgan , Saini Jaspreet S. , Wing Anthony , Zhang Jessica , Duhaime Melissa 
Published: August 2023

AbstractBackgroundThe identification of viruses from environmental metagenomic samples using informatics tools has offered critical insights in microbiome studies. However, it remains difficult for researchers to know for their specific study which tool(s) and settings are best suited to maximize capture of viruses while minimizing false positives. Studies are increasingly combining multiple tool outputs attempting to recover more viruses, but no combined approach has been benchmarked for accuracy. Here, we benchmarked 63 viral identification ‘rulesets’ against mock metagenomes composed of publicly available viral, bacterial, archaeal, fungal, and protist sequences. These rulesets are based on combinations of four single-tool rules and two multi-tool tuning rules. We applied these rulesets to various aquatic metagenomes and filtering strategies to evaluate the impact of habitat and viral enrichment on individual and combined tool performance. We provide a packaged pipeline for researchers that want to replicate our process.ResultsWe found that combining rules increased viral recall, but at the expense of increased false positives. Six of the 63 combinations tested had equivalent accuracies to the highest one (MCC=0.77, padj≥ 0.05). All of the six high accuracy rulesets included VirSorter2, five included our “tuning removal” rule, and no high performing rulesets used more than four of our six rules. DeepVirFinder, VIBRANT, and VirSorter were each found once in these high accuracy rulesets, but never in combination with each other. Our validation suggests that the MCC plateau at 0.77 is caused by inaccurate labeling of the data that viral identification tools rely on for training and validation. In the aquatic metagenomes, our “highest MCC” ruleset identified a higher proportion of viral sequences in the virus-enriched samples (44-46%) than the non-enriched, cellular metagenomes (7-19%).ConclusionWhile improved algorithms may lead to more accurate viral identification tools, this should be done in tandem with curating accurately labeled viral gene and sequence databases. For most applications, we recommend the use of the ruleset that uses VirSorter2 and our empirically derived tuning removal rule. By providing a rigorous overview of the behavior ofin silicoviral identification strategies, our findings guide the use of existing viral identification tools and offer a blueprint for feature engineering of new tools that will lead to higher-confidence viral discovery in microbiome studies.