bluuebunny/crossref_metadata_2025_split huggingface dataset:
A simple framework for Mendelian randomisation of latent continuous exposures with discrete measurements
Authors: Tudball Matthew J. , Bowden Jack , Hughes Rachael A. , Ly Amanda , Munafò Marcus R. , Tilling Kate , Zhao Qingyuan , Davey Smith George 
Published: August 2020

AbstractA key assumption in Mendelian randomisation is that the relationship between the genetic instruments and the outcome is fully mediated by the exposure measurement, known as the exclusion restriction assumption. However, in epidemiological studies, the exposure measurement is often a discrete marker for some latent continuous trait. For example, latent liability to schizophrenia can be thought of as underlying the binary diagnosis measure. Genetically-driven variation in the outcome can exist within categories of the exposure measurement, thus violating this assumption. We propose a framework to clarify this violation, deriving a simple expression for the resulting bias and showing that it may inflate or deflate effect estimates but will not reverse their sign. We then characterise a set of assumptions and a straight-forward method for estimating the effect of standard deviation increases in the latent exposure. Our method relies on a sensitivity parameter which can be interpreted as the genetic variance of the latent exposure. We show that this method can be applied in both the one-sample and two-sample settings. We conclude by demonstrating our method in an applied example and re-analysing two papers which are likely to suffer from this type of bias, allowing meaningful interpretation of their effect sizes.
Estimation of case-fatality rate in COVID-19 patients with hypertension and diabetes mellitus in the New York State
Authors: Ge Yang , Sun Shengzhi , Shen Ye 
Published: August 2020

AbstractWe estimated the case-fatality rate (CFR) and ratios (RR) in adult COVID-19 cases with hypertension and diabetes mellitus in the New York State. We found that the elderly population had a higher CFR, but the elevated CFR ratios associated with comorbidities are more pronounced for the younger population.
Non-invasive lung cancer diagnosis and prognosis based on multi-analyte liquid biopsy
Authors: Chen Kezhong , Sun Jianlong , Zhao Heng , Jiang Ruijingfang , Zheng Jianchao , Li Zhilong , Peng Jiaxi , Shen Haifeng , Zhang Kai , Zhao Jin , Zhu Shida , Wang Yuying , Yang Fan , Wang Jun 
Published: August 2020

AbstractChest LDCT provides an effective approach for lung cancer screening, yet has been found to generate a large number of false positives during practice due to excessive diagnosis of pulmonary lesions of indeterminate clinical significance. In this study, we performed comprehensive genetic and epigenetic profiling of cfDNA from lung cancer patients and individuals bearing benign lung lesions, using ultra-deep targeted sequencing and targeted bisulfite sequencing. We found that cfDNA mutation profile alone has relatively limited power in distinguishing malignant from benign plasma, while cfDNA methylation profiling showed a better performance for classification of the two groups and combination of genetic and epigenetic features of cfDNA along with serum protein marker further improved the classification accuracy. We also identified novel methylation-based prognostic markers and showed that an integrated model that combined cfDNA mutational status and methylation-based prognostic markers improved prediction for lung cancer survival. Our results highlight the potential of the multi-analyte assay for non-invasive lung cancer diagnosis and prognosis.
CLEP: A Hybrid Data- and Knowledge-Driven Framework for Generating Patient Representations
Authors: Bharadhwaj Vinay Srinivas , Ali Mehdi , Birkenbihl Colin , Mubeen Sarah , Lehmann Jens , Hofmann-Apitius Martin , Tapley Hoyt Charles , Domingo-Fernández Daniel 
Published: August 2020

AbstractAs machine learning and artificial intelligence become more useful in the interpretation of biomedical data, their utility depends on the data used to train them. Due to the complexity and high dimensionality of biomedical data, there is a need for approaches that combine prior knowledge around known biological interactions with patient data. Here, we present CLEP, a novel approach that generates new patient representations by leveraging both prior knowledge and patient-level data. First, given a patient-level dataset and a knowledge graph containing relations across features that can be mapped to the dataset, CLEP incorporates patients into the knowledge graph as new nodes connected to their most characteristic features. Next, CLEP employs knowledge graph embedding models to generate new patient representations that can ultimately be used for a variety of downstream tasks, ranging from clustering to classification. We demonstrate how using new patient representations generated by CLEP significantly improves performance in classifying between patients and healthy controls for a variety of machine learning models, as compared to the use of the original transcriptomics data. Furthermore, we also show how incorporating patients into a knowledge graph can foster the interpretation and identification of biological features characteristic of a specific disease or patient subgroup. Finally, we released CLEP as an open source Python package together with examples and documentation.
A generic decision-making ability predicts psychopathology in adolescents and young adults and is reflected in distinct brain connectivity patterns
Authors: Moutoussis Michael , Garzón Benjamín , Neufeld Sharon , Bach Dominik R. , Rigoli Francesco ,   NSPN Consortium, Guitart-Masip Marc , Dolan Raymond J. 
Published: August 2020

AbstractDecision-making underpins many important facets of our lives. Here, we assessed if a general ability factor underpins decision-making abilities. Using factor analysis of 32 decision-making measures in 830 adolescents and young adults, we identified a common factor we refer to as ‘decision acuity’ that was distinct from IQ and reflected advantageous decision-making abilities. Decision acuity decreased with low general social functioning and aberrant thinking. Crucially, decision acuity and IQ had dissociable neural signatures in terms of resting-state functional connectivity involving specific neural networks. Finally, decision acuity was reliable and its relationship with functional connectivity was stable when measured in the same individuals 18 months later. We conclude that our behavioural and brain data demonstrate a new cognitive construct encapsulating ability to perform decision-making across distinct domains, and that the expression of this construct may be important for understanding psychopathology.
Investigating real-life emotions in romantic couples: a mobile EEG study
Authors: Packheiser Julian , Berretz Gesa , Rook Noemi , Bahr Celine , Schockenhoff Lynn , Güntürkün Onur , Ocklenburg Sebastian 
Published: August 2020

AbstractThe neural basis of emotional processing has been largely investigated in constrained spatial environments such as stationary EEGs or fMRI scanners using highly artificial stimuli like standardized pictures depicting emotional scenes. Typically, such standardized experiments have low ecological validity and it remains unclear whether their results reflect neuronal processing in real-life affective situations at all. Critically, emotional situations do not only encompass the perception of emotions, but also behavioral components associated with them. In this study, we aimed to investigate real-life emotions by recording couples in their homes using mobile EEG technology during embracing, kissing and emotional speech. We focused on asymmetries in affective processing as emotions have been demonstrated to be strongly lateralized in the brain. We found higher alpha and beta power asymmetry during kissing and embracing on frontal electrodes during emotional kisses and speech compared to a neutral control condition indicative of stronger left-hemispheric activation. In contrast, we found lower alpha power asymmetry at parieto-occipital electrode sites in the emotional compared to the neutral condition indicative of stronger right-hemispheric activation. Our findings are in line with models of emotional lateralization that postulate a valence-specific processing over frontal cortices and right-hemispheric dominance in emotional processing in parieto-occipital regions. Overall, we could thus support theories of emotional asymmetries which suggest that affective processing is not uniformly lateralized across the brain using a highly ecologically valid paradigm.
Interaction between neuronal encoding and population dynamics during categorization task switching in parietal cortex
Authors: Mohan Krithika , Zhu Oliver , Freedman David 
Published: August 2020

AbstractPrimates excel at categorization, a cognitive process for assigning stimuli into behaviorally relevant groups. Categories are encoded in multiple brain areas and tasks, yet it remains unclear how neural encoding and dynamics support cognitive tasks with different demands. We recorded from parietal cortex during flexible switching between categorization tasks with distinct cognitive and motor demands, and also studied recurrent neural networks (RNNs) trained on the same tasks. In the one-interval categorization task (OIC), monkeys rapidly reported their decisions with a saccade. In the delayed match-to-category (DMC) task, monkeys decided whether sequentially presented stimuli were categorical matches. Neuronal category encoding generalized across tasks, but categorical encoding was more binary-like in the DMC task and more graded in the OIC task. Furthermore, analysis of the trained RNNs supports the hypothesis that binary-like encoding in the DMC task arises through compression of graded feature encoding by population attractor dynamics underlying short-term working memory.
Mantis shrimp rank the shape of an object over its color during recognition
Authors: Patel Rickesh N. , Khil Veniamin , Abdurahmonova Laylo , Driscoll Holland , Patel Sarina , Pettyjohn-Robin Olivia , Shah Ahmad , Goldwasser Tamar , Sparklin Benjamin , Cronin Thomas W. 
Published: August 2020

SummaryMantis shrimp are predatory crustaceans that commonly occupy burrows in shallow, tropical waters worldwide. Most of these animals inhabit structurally complex, benthic environments with an abundance of visual features that are regularly observed, including conspecifics, predators, prey, and landmarks for use in navigation. While these animals are capable of learning and discriminating color and polarization, it is unknown what specific attributes of a visual object are important for its recognition. Here we show that mantis shrimp of the speciesNeogonodactylus oerstediican learn the shape of a trained target. Furthermore, when the shape and color of a target which they had been trained to identify were placed in conflict,N. oerstediisignificantly chose the target of the trained shape over the target of the trained color. Thus, we conclude that the shape of a target is more important than its color for its recognition byN. oerstedii. Our findings suggest that the shapes of learned structures, such as landmarks or other animals, are important forN. oerstediiduring object recognition.
Predicting Sex from Resting-State fMRI Across Multiple Independent Acquired Datasets
Authors: Al Zoubi Obada , Misaki Masaya , Tsuchiyagaito Aki , Zotev Vadim , White Evan ,   Tulsa 1000 Investigators, Paulus Martin , Bodurka Jerzy 
Published: August 2020

AbstractSex is an important biological variable often used in analyzing and describing the functional organization of the brain during cognitive and behavioral tasks. Several prior studies have shown that blood-oxygen-level-dependent (BOLD) functional MRI (fMRI) functional connectivity (FC) can be used to differentiate sex among individuals. Herein, we demonstrate that sex can be further classified with high accuracy using the intrinsic BOLD signal fluctuations from resting-state fMRI (rs-fMRI). We adopted the amplitude of low-frequency fluctuation (ALFF), and the fraction of ALFF (fALFF) features from the automated anatomical atlas (AAL) and Power’s functional atlas as an input to different machine learning (ML) methods. Using datasets from five independently acquired subject cohorts and with eight fMRI scanning sessions, we comprehensively assessed unbiased performance using nested-cross validation for within-sample and across sample accuracies. The results demonstrated high prediction accuracies for the Human Connectome Project (HCP) dataset (area under cure (AUC) > 0.89). The yielded accuracies suggest that sex difference is embodied and well-pronounced in the low-frequency BOLD signal fluctuation. The performance degrades with the heterogeneity of the cohort and suggests that other factors,.e.g. psychiatric disorders and demographics influences the BOLD signal and may interact with the classification of sex. In addition, the results revealed high learning generalizability with the HCP scan, but not across different datasets. The intraclass correlation coefficient (ICC) across HCP scans showed moderate-to-good reliability based on atlas selection (ICC = 0.65 [0.63-0.67] and ICC= 0.78 [0.76-0.80].). We also assessed the effect of scan duration on the predictability of sex and showed that sex differences could be detected even with a short rs-fMRI scan (e.g., 2 minutes). Moreover, we provided statistical maps of the brain regions differentially recruited by or predicting sex using Shapely values and determined an overlap with previous reports of brain response due to sex differences. Altogether, our analysis suggests that sex differences are well-pronounced in rs-fMRI and should be considered seriously in any study design, analysis, or interpretation.
Variable branching characteristics of peripheral taste neurons indicates differential convergence
Authors: Huang Tao , Ohman Lisa C. , Clements Anna V. , Whiddon Zachary D. , Krimm Robin F. 
Published: August 2020

ABSTRACTTaste neurons are functionally and molecularly diverse, but their morphological diversity remains completely unexplored. Using sparse cell genetic labeling, we provide the first reconstructions of peripheral taste neurons. The branching characteristics across 96 taste neurons show surprising diversity in their complexities. Individual neurons had 1 to 17 separate arbors entering between 1 to 7 taste buds, 18 of these neurons also innervated non-taste epithelia. Axon branching characteristics are similar in gustatory neurons from male and female mice. Cluster analysis separated the neurons into four groups according to branch complexity. The primary difference between clusters was the amount of the nerve fiber within the taste bud available to contact taste-transducing cells. Consistently, we found that the maximum number of taste-transducing cells capable of providing convergent input onto individual gustatory neurons varied with a range of 1-22 taste-transducing cells. Differences in branching characteristics across neurons indicate that some neurons likely receive input from a larger number of taste-transducing cells than other neurons (differential convergence). By dividing neurons into two groups based on the type of taste-transducing cell most contacted, we found that neurons contacting primarily sour transducing cells were more heavily branched than those contacting primarily sweet/bitter/umami transducing cells. This suggests that neuron morphologies may differ across functional taste quality. However, the considerable remaining variability within each group also suggests differential convergence within each functional taste quality. Each possibility has functional implications for the system.Significance statementTaste neurons are considered relay cells, communicating information from taste-transducing cells to the brain, without variation in morphology. By reconstructing peripheral taste neuron morphologies for the first time, we found that some peripheral gustatory neurons are simply branched, and can receive input from only a few taste-transducing cells. Other taste neurons are heavily branched, contacting many more taste-transducing cells than simply branched neurons. Based on the type of taste-transducing cell contacted, branching characteristics are predicted to differ across (and within) quality types (sweet/bitter/umami vs sour). Therefore, functional differences between neurons likely depends on the number of taste-transducing cells providing input and not just the type of cell providing input.
H-MAGMA, inheriting a shaky statistical foundation, yields excess false positives
Authors: Yurko Ronald , Roeder Kathryn , Devlin Bernie , G’Sell Max 
Published: August 2020

AbstractThe ‘snp-wise mean model’ of Multi-marker Analysis of GenoMic Annotation is often used to perform gene-level testing for association with disease and other phenotypes. This methodology, in turn, forms the foundation for H-MAGMA. Unfortunately, that foundation is unsound, with implications for H-MAGMA results published inNature Neuroscienceregarding genes associated with psychiatric disorders: e.g., only 125 of H-MAGMA’s 275 reported discoveries for autism replicate when the foundation’s flaws are corrected.
Diagnostic performance of the faecal immunochemical test for patients with low-risk symptoms of colorectal cancer in primary care: a service evaluation in the South West of England
Authors: Bailey Sarah ER , Abel Gary A , Atkins Alex , Byford Rachel , Davies Sarah-Jane , Mays Joe , McDonald Timothy J , Miller Jon , Neck Catherine , Renninson John , Thomas Paul , Walter Fiona M , Warren Sarah , Hamilton Willie 
Published: August 2020

AbstractObjectivesTo evaluate the faecal immunochemical test (FIT) for primary care clinicians to triage patients with low-risk symptoms of possible colorectal cancer, and to estimate its diagnostic performance.DesignService delivery evaluation.SettingAll primary and secondary care providers in the South West of England, approximate population 4 million.Participants3890 patients aged ≥50 years presenting in primary care with low-risk symptoms of colorectal cancer, following NICE NG12 and DG30, with a FIT (HM-JACKarc assay) analysed from 01/06/2018 to 31/12/2018.Main outcome measuresDiagnosis of colorectal cancer.Results618 (15.9%) patients tested positive at a threshold of 10μg Hb/g faeces (median 36μg Hb/g faeces (IQR 17 to 149)); 458 (74.1%) of these had an urgent referral to specialist lower gastrointestinal (GI) services within three months. 43 were diagnosed with colorectal cancer within 12 months. 3272 patients tested negative; 324 (9.9%) were referred on an urgent lower GI pathway in secondary care within three months. 8 were diagnosed with colorectal cancer within 12 months. The positive predictive value of FIT for colorectal cancer in the low-risk symptomatic population was 7.0% (95% CI 5.1% to 9.3%) and the negative predictive value was 99.8% (CI 99.5% to 99.9%). Sensitivity was 84.3% (CI 71.4% to 93.0%),and specificity 85.0% (CI 83.8% to 86.1%). The area under the ROC curve was 0.92 (CI 0.86 to 0.96). A threshold of 37μg Hb/g faeces would identify patients with an individual 3% risk of cancer.ConclusionsFIT performs exceptionally well to triage patients with low-risk symptoms of colorectal cancer in primary care. The threshold value of 10μg Hb/g faeces represents a risk of cancer below 3% used in current NICE guidance; however, this lower value may be appropriate to meet the national aspiration of improving cancer diagnostics.
Importance and assessment of quality of life in symptomatic permanent atrial fibrillation: Patient focus groups from the RATE-AF trial
Authors: Jones Jacqueline , Stanbury Mary , Haynes Sandra , Bunting Karina V , Lobban Trudie , Camm A John , Calvert Melanie J. , Kotecha Dipak 
Published: August 2020

AbstractAimsTo establish the extent and impact of symptoms in patients with atrial fibrillation (AF), the importance of different aspects of quality of life (QoL), and how we should assess wellbeing.MethodsFocus groups of patients with symptomatic permanent AF in a trial of heart rate control; the RATE-AF trial randomised 160 patients aged ≥60 years with permanent AF and at least NYHA class II dyspnoea to either digoxin or beta-blockers. Patient and public representatives led the focus groups and performed all data acquisition and analysis, using thematic approaches to interpret patient views about QoL and its measurement.ResultsSubstantial impairment of health-related QoL was noted in 160 trial patients, with impact on all domains apart from mental health. Eight women and 11 men aged 61–87 years participated in the focus groups. Common themes were a lack of information from healthcare professionals about AF, a lack of focus on QoL in consultations, and a sense of frustration, isolation and reduced confidence. There was marked variability in symptoms in individual patients, with some describing severe impact on activities of daily living, and profound interaction with comorbidities such as arthritis. Day-to-day variation in QoL and difficulty in attributing symptom burden to AF or other comorbidities led to challenges in questionnaire completion. Consensus was reached that collecting both general and AF-specific QoL would be useful in routine practice, along with participation in peer support, which was empowering for the patients.ConclusionsThe impact of comorbidities is poorly appreciated in the context of AF, with considerable variability in QoL that requires both generic and AF-specific assessment. Improvement in QoL should direct the appraisal, and reappraisal, of treatment decisions for patients with permanent AF.
Mass Spectrometric Characterization of Narcolepsy-Associated Pandemic 2009 Influenza Vaccines
Authors: Ambati Aditya , Luo Guo , Pradhan Elora , Louis Jacob , Lin Ling , Lieb Ryan , Ollila Hanna Maria , Poiret Thomas , Adams Christopher , Mignot Emmanuel 
Published: August 2020

AbstractThe onset of narcolepsy, an irreversible sleep disorder, has been associated with 2009 influenza pandemic (pH1N1) infections in China, and with ASO3-adjuvanted pH1N1 vaccinations using Pandemrix in Europe. Intriguingly, however, the increased incidence was only observed following vaccination with Pandemrix but not Arepanrix in Canada. In this study, the mutational burden of actual vaccine lots of Pandemrix (n=6) and Arepanrix (n=5) sourced from Canada, and Northern Europe were characterized by mass spectrometry. The four most abundant influenza proteins across both vaccines were nucleoprotein NP, hemagglutinin HA, matrix protein M1, with the exception that Pandemrix harbored a significantly increased proportion of neuraminidase NA (7.5%) as compared to Arepanrix (2.6%). Most significantly, 17 motifs in HA, NP, and M1 harbored mutations, which significantly differed in Pandemrix versus Arepanrix. Among these, a 6-fold higher deamidation of HA146 (N to D) in Arepanrix was found relative to Pandemrix, while NP257 (T to A) and NP424 (T to I) were increased in Pandemrix. DQ0602 binding and tetramer analysis with mutated epitopes were conducted in Pandemrix-vaccinated cases versus controls but were unremarkable. Pandemrix harbored lower mutational burden than Arepanrix, indicating higher similarity to wild-type 2009 pH1N1, which could explain differences in narcolepsy susceptibility amongst the vaccines.