bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of the NeuroFlow Severity Score and Comparison With Validated Measures for Depression and Anxiety
Authors: Lynch William , Platt Michael L. , Pardes Adam 
Published: February 2021

ABSTRACTPurposeAlthough depression and anxiety are the leading causes of disability in the United States, respectively, fewer than half of people diagnosed with these conditions receive appropriate treatment, and fewer than 10% receive measurement-based care (MBC), which is defined as behavioral health care based on and adapted in response to patient outcomes data collected throughout treatment. The NeuroFlow platform was developed with the goal of making MBC easier to deliver and more accessible within integrated behavioral health care. Data from over 3,000 users of the NeuroFlow platform were used to develop the NeuroFlow Severity Score (NFSS), a potential new measure for depression and anxiety. To begin evaluating the potential usefulness of this new measure, NFSSs were compared with validated measures for depression and anxiety, the Personal Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7) scale, and clinician assessment.MethodsThe NFSS platform is used to record patient-reported and passively collected data related to behavioral health. An artificial-intelligence derived algorithm was developed that condenses this large number of measurements into a single score for longitudinal tracking of an individual’s depression and anxiety symptoms. Linear regression and Bland-Altman analyses were used to evaluate relationships and differences between NFSS and PHQ-9 or GAD-7 scores from over 35,000 NeuroFlow users. The NFSS was also compared to assessment by a panel of expert clinicians for a subset of 250 individuals.ResultsLinear regression results showed a strong correlation between NFSS and PHQ-9 (r=.74, P<.001) and GAD-7 (r=.80, P<.001) changes. There was also a strong positive correlation between the NFSS and expert panel clinical assessment (r=.80-.84, P<.001). Bland-Altman analysis and evaluation of outliers on regression analysis, however, show that the NFSS has significant differences from the PHQ-9.ConclusionsClinicians can reliably use the NFSS as a proxy measure for monitoring symptoms of depression and anxiety longitudinally. The NFSS may identify at-risk individuals who are not identified by the PHQ-9. Further research is warranted to evaluate the sensitivity and specificity of the NFSS.
Enhancing Food Security for Families Vulnerable to COVID-19
Authors: Fabusuyi Tayo , Misra Aditi , Martinez Jonatan , Chen Andong , Jiang Vivian , Jagadish H. V. , Hampshire Robert C. 
Published: February 2021

ABSTRACTThe COVID-19 pandemic has exposed some of the underlying inequities in our society. Vulnerable and low-income communities who have typically struggled with food insecurity have been further impacted by the COVID-19 pandemic. To make matters worse, transit dependent households in the City of Detroit that rely on SNAP benefits from the government have a 54% probability of not having internet access, reducing the possibility of online food delivery. Thus, the motivation for the Detroit Food Delivery Pilot Program, a prepared meal delivery service for food insecure households during the COVID-19 pandemic. Through this program, the City had aided 350 households; over 1,000 unique individuals and has served over 90,000 meals. This had all been made possible through the engagement of 575 volunteers, volunteering over 6,850 delivery miles. Our team helped to identify the magnitude and the needs of the City’s food insecure population; then partnered with the City of Detroit to modify existing food programs to address the crisis, and finally, assessed the impact of the program on the target population. Our analysis revealed that approximately 20,800 households will be classified as food insecure in Detroit and only a fraction of this population is benefitting from the food delivery pilot program. However, on average, the concerns about food sufficiency have abated appreciably from the surveys analyzed. Responses from the beneficiaries of the food delivery pilot program were positive though concerns about the travel behavior of individuals, particularly those from COVID-19 positive households remain.
Creating virtual H&E images using samples imaged on a commercial CODEX platform
Authors: Simonson Paul D. , Ren Xiaobing , Fromm Jonathan R. 
Published: February 2021

ABSTRACTMultiparametric fluorescence imaging via CODEX allows the simultaneous imaging of many biomarkers in a single tissue section. While the digital fluorescence data thus obtained can provide highly specific characterizations of individual cells and microenvironments, the images obtained are different from those usually interpreted by pathologists (i.e., H&E slides and DAB-stained immunohistochemistry slides). Having the fluorescence data plus co-registered H&E or similar data could facilitate adoption of multiparametric imaging into regular workflows, as well as facilitate the transfer of algorithms and machine learning previous developed around H&E slides. Since commercial CODEX instruments do not produce H&E-like images by themselves, we developed a staining protocol and associated image processing to make “virtual H&E” images that can be incorporated into the CODEX workflow. While there are many ways to achieve virtual H&E images, including use of a fluorescent nuclear stain and tissue autofluorescence to simulate eosin staining, we opted to combine fluorescent nuclear staining (via DAPI) with actual eosin staining. We also output images derived from fluorescent nuclear staining and autofluorescence images for additional evaluation.
Modeling the Effect of Population-Wide Vaccination on the Evolution of COVID-19 Epidemic in Canada
Authors: Berkane Soulaimane , Harizi Intissar , Tayebi Abdelhamid 
Published: February 2021

AbstractPopulation-wide vaccination is critical for containing the COVID-19 pandemic when combined with effective testing and prevention measures. Since the beginning of the COVID-19 outbreak, several companies worked tirelessly for the development of an efficient vaccine that would put an end to this pandemic. Today, a number of COVID-19 vaccines have been approved for use by a number of national regulatory organizations. Vaccination campaigns have already started in several countries with different daily-vaccination rates depending on the country’s vaccination capacity. Therefore, we find it timely and extremely important to conduct a study on the effect of population-wide vaccination campaigns on the evolution of the COVID-19 epidemic. To this end, we propose a new deterministic mathematical model to forecast the COVID-19 epidemic evolution under the effect of vaccination and vaccine efficacy. This model, referred to as SIRV, consists of a compartmental SIR (susceptible, infectious and removed) model augmented with an additional state V representing the effectively vaccinated population as well as two inputs representing the daily-vaccination rate and the vaccine efficacy. Using our SIRV model, we predict the evolution of the COVID-19 epidemic in Canada and its most affected provinces (Ontario, Quebec, British Columbia, Alberta, Saskatchewan, and Manitoba), for different daily vaccination rates and vaccine efficacy. Projections suggest that, without vaccination, 219, 000 lives could be lost across Canada by the end of 2021 due to COVID-19. The ongoing vaccination campaign across Canada seems to unfold relatively slowly at an average daily rate close to 1/2 vaccine per 1, 000 population. At this pace, we could be saving more than 77, 496 lives by the end of the year. Doubling the current vaccination efforts (1 vaccine per day per 1, 000 population) could be sufficient to save 125, 839 lives in Canada during the current year 2021. We would like to point out that our study assumes that the vaccine is perfectly safe without any short or long term side-effects. This study has been conducted independently at arm’s length from vaccine manufacturers, using the available data from Canada health services. This study can be easily adapted to other places in the world.
The fragility index in randomised controlled trials of interventions for aneurysmal subarachnoid haemorrhage: a systematic review
Authors: Ramesh Aravind V , Munby Henry N P , Thomas Matt 
Published: February 2021

AbstractBackgroundFragility analysis supplements the p-value and risk of bias assessment in the interpretation of results of randomised controlled trials. In this systematic review we determine the fragility index (FI) and fragility quotient (FQ) of randomized trials in aneurysmal subarachnoid haemorrhage.MethodsThis is a systematic review registered with PROSPERO (ID: CRD42020173604). Randomised controlled trials in adults with aneurysmal subarachnoid haemorrhage were analysed if they reported a statistically significant primary outcome of mortality, function (e.g. modified Rankin Scale), vasospasm or delayed neurological deterioration.ResultsWe identified 3809 records with 17 randomized trials selected for analysis. The median fragility index was 3 (inter-quartile range 0-5) and the median fragility quotient was 0.012 (IQR 0-0.034). Six of nineteen trial outcomes (31.6%) had an fragility index of 0. In seven trials (36.8%), the number of participants lost to follow-up was greater than or equal to the fragility index. Only 17.6% of trials are at low risk of bias.ConclusionsRandomised controlled trial evidence supporting management of aneurysmal subarachnoid haemorrhage is weaker than indicated by conventional analysis using p-values alone. Increased use of fragility analysis by clinicians and researchers could improve the translation of evidence to practice.
Short-term functional outcome in psychotic patients. Results of the Turku Early Psychosis Study (TEPS)
Authors: Salokangas Raimo K. R. , From Tiina , Ilonen Tuula , Luutonen Sinikka , Heinimaa Markus , Armio Reetta-Liina , Laurikainen Heikki , Walta Maija , Paju Janina , Toivonen Anna , Jalo Päivi , Tuominen Lauri , Hietala Jarmo ,   the TEPS group
Published: February 2021

AbstractBackgroundFunctional recovery of patients with clinical and sub-clinical psychosis is associated with clinical, neuropsychological and developmental factors. Less is known how these factors predict functional outcome in same models.AimWe investigated functional outcome and its predictors in patients with first-episode psychosis (FEP) or confirmed vs. non-confirmed clinical high risk to psychosis (CHR-P vs. CHR-N).MethodsAltogether, 130 FEP, 60 CHR-P and 47 CHR-N patients were recruited and extensively examined at baseline (T0) and at 9 (T1) and 18 (T2) months after baseline. Global Assessment of Functioning (GAF) at T0, T1 and T2, and psychotic, depression and anxiety symptoms at T1 and T2 were assessed. Functional outcome was predicted in multivariate repeated ANOVA.ResultsDuring follow-up, GAF improved significantly in FEP and CHR-P but not in CHR-N patients. In FEP, single marital status, low basic education, poor work situation, disorganised symptoms, perceptual deficits and poor premorbid adjustment, in CHR-P, disorganised symptoms and poor premorbid adjustment and in CHR-N, low basic education, poor work situation and general symptoms predicted poor functional outcome. In FEP, psychotic symptoms at T1 and in CHR-P, psychotic and depression symptoms at T1 and anxiety symptoms at T2 associated with poor functioning.DiscussionIn FEP and CHR-P patients, poor premorbid adjustment and disorganised symptomatology are common predictors for functional outcome, while poor education and work situation predict poor functional outcome in FEP and CHR-N patients. Interventions aimed to improve studying and ability to work are most important in improving functioning of patients with clinical or subclinical psychosis.
Maximum likelihood perimetric progression analysis: Using raw (trial-by-trial) response data to estimate progression more robustly
Authors: Jones Pete R. 
Published: February 2021

ABSTRACTPurposeTo describe and demonstrate a more efficient (Maximum Likelihood) method for quantifying visual field progression.DesignMonte Carlo simulation.MethodsTrial-by-trial response data were simulated using a stochastic psychometric model (a “simulated observer”). Simulated Differential Light Sensitivity (DLS) decreased between tests to mimic long-term visual field progression. Progression slopes were fitted, either by fitting a regression slope to independent DLS estimates from each test (conventional method), or by fitting all the raw data combined in a single model (proposed maximum likelihood method).ResultsThe proposed ML method seldom performed worse than a conventional, regression-based approach, and often performed better. For an idealized observer with a lapse (false negative) rate of 0 and a guess (false positive) rate of 0, both methods were equally precise. However, as lapse rate increased, the ML method exhibited less random measurement error. For small numbers of trials this increase in precision translated to a negative progression slope being detected with 95% confidence at least one year/assessment sooner. The only time the ML method was observed to perform worse was when very few trials (N = 4) were combined with very high lapse rates (λ = 0.3): an unlikely but not inconceivable scenario.ConclusionsCombining raw, trial-by-trial response data in a single ML model can provide a more robust estimate of visual field progression than conventional methods (e.g., linear regression), at no additional cost to the patient or clinician (i.e., no additional trials).
Disentangling the effects of climate change, landscape heterogeneity, and scale on phenological metrics
Authors: Newman Erica A. , Breckheimer Ian K. , Park Daniel S. 
Published: February 2021

AbstractPhenology, the study of the timing of cyclical life history events and seasonal changes, is a fundamental aspect of how individual species, communities, and ecosystems will respond to climate change. Both biotic and abiotic phenological patterns are changing rapidly in response to changing seasonal temperatures and other climate-related drivers, and the consequences of these shifts for individual species and entire ecosystems are largely unknown. Landscape-scale simulations can address some of these needs for better predictions by demonstrating how phenology measures can vary with spatial and temporal grain of observations, and how phenological responses can vary with landscape heterogeneity and climate drivers. To explicitly examine the spatial and temporal scale-dependence of multiple phenology measures, we constructed simulated landscapes populated by virtual plant species with realistic phenologies and environmental sensitivities. This enabled us to examine phenology measures and environmental sensitivities along a continuum of spatial and temporal grains, while also controlling other aspects of sampling design. By relating measures of phenology calculated at a given spatiotemporal grain to average environmental conditions at that same grain size, we are able to determine observed environmental sensitivities for multiple phenological metrics at that spatial and temporal scale. We demonstrate that different phenological events change distinctly and predictably with spatial and temporal measurement scale, opening the way to incorporating scaling laws into predictions. Using plant flowering as our example, we identify that the timing of the beginnings or ends of an event (e.g., First Flower date, Last Flower date), can be especially sensitive to the spatial and temporal grain (or resolution) of observations. Our work provides an initial assessment of the role of observation scale in landscape phenology, and a general approach for incorporating scale-dependence into predictions of a variety of phenological time series.
Reducing the efforts to create reproducible analysis code with FieldTrip
Authors: van Es Mats W.J. , Spaak Eelke , Schoffelen Jan-Mathijs , Oostenveld Robert 
Published: February 2021

AbstractThe analysis of EEG and MEG data typically requires a lengthy and complicated sequence of analysis steps, often requiring large amounts of computations, which are ideally represented in analysis scripts. These scripts are often written by researchers without formal training in computer science, resulting in the quality and readability of these analysis scripts to be highly dependent on individual coding expertise and style. Even though the computational outcomes and interpretation of the results can be correct, the inconsistent style and quality of analysis scripts make reviewing the details of the analysis difficult for other researchers that are either involved in the study or not, and the quality of the scripts might compromise the reproducibility of obtained results. This paper describes the design and implementation of a strategy that allows complete reproduction of MATLAB-based scripts with little extra efforts on behalf of the user, which we have implemented as part of the FieldTrip toolbox. Starting from the researchers’ idiosyncratic pipeline scripts, this new functionality allows researchers to automatically create and publish analysis pipeline scripts in a standardized format, along with all relevant intermediate data. We demonstrate the functionality and validate its effectiveness by applying it to the analysis of a recently published MEG study.
A recurrent cortical model can parsimoniously explain the effect of expectations on sensory processes
Authors: Urgen Buse M. , Boyaci Huseyin 
Published: February 2021

AbstractThe effect of prior knowledge and expectations on perceptual and decision-making processes have been extensively studied. Yet, the computational mechanisms underlying those effects have been a controversial issue. Recently, using a recursive Bayesian updating scheme, unmet expectations have been shown to entail further computations, and consequently delay perceptual processes. Here we take a step further and model these empirical findings with a recurrent cortical model, which was previously suggested to approximate Bayesian inference (Heeger, 2017). Our model fitting results show that the cortical model can successfully predict the behavioral effects of expectation. That is, when the actual sensory input does not match with the expectations, the sensory process needs to be completed with additional, and consequently longer, computations. We suggest that this process underlies the delay in perceptual thresholds in unmet expectations. Overall our findings demonstrate that a parsimonious recurrent cortical model can explain the effects of expectation on sensory processes.
Large-scale tandem mass spectrum clustering using fast nearest neighbor searching
Authors: Bittremieux Wout , Laukens Kris , Noble William Stafford , Dorrestein Pieter C. 
Published: February 2021

AbstractRationaleAdvanced algorithmic solutions are necessary to process the ever increasing amounts of mass spectrometry data that is being generated. Here we describe thefalconspectrum clustering tool for efficient clustering of millions of MS/MS spectra.Methodsfalconsucceeds in efficiently clustering large amounts of mass spectral data using advanced techniques for fast spectrum similarity searching. First, high-resolution spectra are binned and converted to low-dimensional vectors using feature hashing. Next, the spectrum vectors are used to construct nearest neighbor indexes for fast similarity searching. The nearest neighbor indexes are used to efficiently compute a sparse pairwise distance matrix without having to exhaustively perform all pairwise spectrum comparisons within the relevant precursor mass tolerance. Finally, density-based clustering is performed to group similar spectra into clusters.ResultsSeveral state-of-the-art spectrum clustering tools were evaluated using a large draft human proteome dataset consisting of 25 million spectra, indicating that alternative tools produce clustering results with different characteristics. Notably,falcongenerates larger highly pure clusters than alternative tools, leading to a larger reduction in data volume without the loss of relevant information for more efficient downstream processing.Conclusionsfalconis a highly efficient spectrum clustering tool. It is publicly available as open source under the permissive BSD license athttps://github.com/bittremieux/falcon.
Somatostatin-positive Interneurons Contribute to Seizures inSCN8AEpileptic Encephalopathy
Authors: Wengert Eric R. , Wedgwood Kyle C.A. , Wagley Pravin K. , Strohm Samantha M. , Panchal Payal S. , Majidi Abrar Idrissi , Wenker Ian C. , Gaykema Ronald P. , Patel Manoj K. 
Published: February 2021

AbstractSCN8Aepileptic encephalopathy is a devastating epilepsy syndrome caused by mutantSCN8Awhich encodes the voltage-gated sodium channel NaV1.6. To date, it is unclear if and how inhibitory interneurons, which express NaV1.6, influence disease pathology. We found that selective expression of the R1872W mutation in somatostatin (SST) interneurons was sufficient to convey susceptibility to audiogenic seizures. SST interneurons from mutant mice were hyperexcitable but hypersensitive to action potential failure via depolarization block under normal and seizure-like conditions. Remarkably, GqDREADD-mediated activation of wild-type SST interneurons resulted in prolonged electrographic seizures and was accompanied by SST hyperexcitability and depolarization block. Aberrantly large persistent sodium currents, a hallmark ofSCN8Amutations, were observed and were found to contribute directly to aberrant SST physiology in computational and pharmacological experiments. These novel findings demonstrate a critical and previously unidentified contribution of SST interneurons to seizure generation not only inSCN8Aencephalopathy, but epilepsy in general.
Information Content Differentiates Enhancers From Silencers in Mouse Photoreceptors
Authors: Friedman Ryan Z. , Granas David M. , Myers Connie A. , Corbo Joseph C. , Cohen Barak A. , White Michael A. 
Published: February 2021

AbstractEnhancers and silencers often depend on the same transcription factors (TFs) and are conflated in genomic assays of TF binding or chromatin state. To identify sequence features that distinguish enhancers and silencers, we assayed massively parallel reporter libraries of genomic sequences targeted by the photoreceptor TF CRX in mouse retinas. Both enhancers and silencers contain more TF motifs than inactive sequences, but relative to silencers, enhancers contain motifs from a more diverse collection of TFs. We developed a measure of information content that describes the number and diversity of motifs in a sequence and found that, while both enhancers and silencers depend on CRX motifs, enhancers have higher information content. The ability of information content to distinguish enhancers and silencers targeted by the same TF illustrates how motif context determines the activity ofcis-regulatory sequences.