bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clinical evaluation of the Multimapping technique for simultaneous myocardial T1and T2mapping
Authors: Jarkman Charlotta , Carlhäll Carl-Johan , Henningsson Markus 
Published: June 2022

AbstractThe Multimapping technique was recently proposed for simultaneous myocardial T1and T2mapping. In this study we evaluate its correlation with clinical reference mapping techniques in patients with a range of cardiovascular diseases (CVD), compare image quality and inter- and intra-observer repeatability. Multimapping consists of a ECG-triggered, 2D single-shot bSSFP readout with inversion recovery and T2preparation modules, acquired across 10 cardiac cycles. The sequence was implemented at 1.5T and compared to clinical reference mapping techniques, Modified Look-Locker inversion recovery (MOLLI) and T2prepared bSSFP with four echo times (T2bSSFP), and compared in 47 patients with CVD (of which 44 were analyzed). In diseased myocardial segments (defined as presence of late gadolinium enhancement) there was a high correlation between Multimapping and MOLLI for native myocardium T1(r2=0.73), ECV (r2=0.91) and blood T1(r2=0.88), and Multimapping and T2bSSFP for native myocardial T2(r2=0.80). In healthy myocardial segments a bias for native T1(Multimapping=1116±21 ms, MOLLI=1002±21,P<0.001), post-contrast T1(Multimapping=479±31 ms, MOLLI=426±27 ms, 0.001), ECV (Multimapping=21.5±1.9%, MOLLI=23.7±2.3%,P=0.001) and native T2(Multimapping=48.0±3.0 ms, T2bSSFP=53.9±3.5 ms,P<0.001) was observed. The image quality for Multimapping was scored as higher for all mapping techniques (native T1, post- contrast T1, ECV and T2bSSFP) compared to the clinical reference techniques. The inter- and intra- observer agreement was excellent (intraclass correlation coefficient, ICC>0.9) for most measurements, except for inter-observer repeatability of Multimapping native T1(ICC=0.87), post-contrast T1(ICC=0.73) and T2bSSFP native T2(ICC=0.88). Multimapping show high correlations with clinical reference mapping techniques for T1, T2and ECV in a diverse cohort of patients with different cardiovascular diseases. Multimapping enables simultaneous T1and T2mapping and can be performed in a short breath-hold, with image quality superior to that of the clinical reference techniques.
A proposed general variant classification framework using chronic pancreatitis as a disease model
Authors: Masson Emmanuelle , Zou Wen-Bin , Génin Emmanuelle , Cooper David N. , Gac Gerald Le , Fichou Yann , Pu Na , Rebours Vinciane , Férec Claude , Liao Zhuan , Chen Jian-Min 
Published: June 2022

AbstractThe widely used ACMG-AMP variant classification categories (pathogenic, likely pathogenic, uncertain significance, likely benign and benign) were specifically developed for variants in Mendelian disease genes, classifying variants discretely with respect to a simple causal versus benign dichotomy. A general variant classification framework taking into account the continuum of clinical phenotypes, the continuum of the variants’ genetic effects and the different pathological roles of the genes implicated, is however lacking. Herein, we used chronic pancreatitis (CP), which clinically manifests as hereditary, familial, idiopathic or alcoholic forms, as a disease model. Based upon cross-gene and cross-variant comparisons, we firstly assigned the four most studied CP genes (PRSS1, CFTR, SPINK1 and CTRC) to two distinct categories in terms of causality: CP-causing (PRSS1 and SPINK1) and CP-predisposing (CFTR and CTRC). We then employed two new classificatory categories, “predisposing” and “likely predisposing”, to replace ACMG-AMP’s “pathogenic” and “likely pathogenic” categories in CP-predisposing genes, thereby classifying all pathologically relevant variants in these genes as “predisposing”. In the case of CP-causing genes, the two new classificatory categories served to expand the five ACMG-AMP categories whilst two thresholds (allele frequency and functional) were introduced to discriminate pathogenic from predisposing variants. Our proposed five-category (predisposing, likely predisposing, uncertain significance, likely benign and benign) and seven-category (pathogenic, likely pathogenic, predisposing, likely predisposing, uncertain significance, likely benign and benign) frameworks (with respect to disease-predisposing and disease-causing genes, respectively) retain the backbone of the five ACMG-AMP categories while rendering them readily applicable to variant classification in other disease contexts.
Towards Assessing Subcortical “Deep Brain” Biomarkers of PTSD with Functional Near-Infrared Spectroscopy
Authors: Balters Stephanie , Schlichting Marc R. , Foland-Ross Lara , Brigadoi Sabrina , Miller Jonas G. , Kochenderfer Mykel J. , Garrett Amy S. , Reiss Allan L. 
Published: June 2022

AbstractAssessment of brain function with functional near-infrared spectroscopy (fNIRS) is limited to the outer regions of the cortex. Previously, we demonstrated the feasibility of inferring activity in subcortical “deep brain” regions using cortical fMRI and fNIRS activity in healthy adults. Access to subcortical regions subserving emotion and arousal using affordable and portable fNIRS is likely to be transformative for clinical diagnostic and treatment planning. Here, we validate the feasibility of inferring activity in subcortical regions that are central to the pathophysiology of PTSD (i.e., amygdala and hippocampus) using cortical fMRI and simulated fNIRS activity in a sample of adolescents diagnosed with PTSD (N=20, mean age=15.3±1.9 years) and age-matched healthy controls (N=20, mean age=14.5±2.0 years) as they performed a facial expression task. We tested different prediction models, including linear regression, a multi-layer perceptron neural network, and a k-nearest neighbors model. Inference of subcortical fMRI activity with cortical fMRI showed high prediction performance for the amygdala (r>0.91) and hippocampus (r>0.95) in both groups. Using fNIRS simulated data, relatively high prediction performance for deep brain regions was maintained in healthy controls (r>0.79), as well as in youths with PTSD (r>0.75). The linear regression and neural network models provided the best predictions.
Clinical Holds in Early Oncology Drug Development
Authors: Snyder Alexandra , De Alwis Dinesh , Goonewardene Asthika , Hegde Priti S. 
Published: June 2022

AbstractClinical holds in oncology are necessary to safeguard patients. Researchers are alerted to holds by news sources, but a systematic evaluation of clinical holds in early oncology drug development is lacking. Analysis of publicly disclosed clinical holds in oncology from 2016-2021 identified 39 holds. The majority (n=29) were for toxicity-related reasons, with fewer for chemistry, manufacturing and controls (CMC) (n=7) or other reasons (n=3). Toxicity-related holds took a median of 74 days till resolution, whereas chemistry, manufacturing and controls (CMC)-related holds took a median of 108 days to resolve. Acknowledging the limited sample size and scope of stock market conditions, toxicity-related clinical holds impacted the market value of small/medium sized biotechs by a median of -15%, which is far more than large biopharma (median 0%). These data suggest that toxicity-related clinical holds are common in early oncology and can have a more detrimental impact on small/medium sized biotech sponsors, the latter of which could have substantial financial repercussions, particularly in “biotech bear markets” where public investing in the sector has fallen out of favor (as in 2021-2022).
Predictive steering: Integration of artificial motor signals in self-motion estimation
Authors: van Helvert Milou J.L. , Selen Luc P.J. , van Beers Robert J. , Medendorp W. Pieter 
Published: June 2022

AbstractThe brain’s computations for active and passive self-motion estimation can be unified with a single model that optimally combines vestibular and visual signals with sensory predictions based on motor efference copies. It is unknown whether this theoretical framework also applies to the integration of artificial motor signals, like the motor signals that occur when driving a car. Here, we examined if training humans to control a self-motion platform would lead to the construction of an accurate internal model of the mapping between the steering movement and the vestibular reafference. Participants (n = 15) were seated on a linear motion platform and actively controlled the platform’s velocity using a steering wheel to translate their body to a memorized visual target location (Motion condition). We compared their steering behavior to that of participants (n = 15) who remained stationary and instead aligned a non-visible line with the target (Stationary condition). To probe learning, the gain between the steering wheel angle and the platform velocity or line velocity changed abruptly twice during the experiment. These gain changes were virtually undetectable in the displacement error in the Motion condition, whereas clear deviations were observed in the Stationary condition. These results show that participants in the Motion condition made within-trial changes to their steering behavior immediately after the gain changes. This suggests that they continuously compared the vestibular reafference to internal predictions, and thus employed and updated an internal forward model of the mapping between the steering movement and the vestibular reafference.New & NoteworthyPerception of self-motion is known to depend on the integration of sensory signals and, when the motion is self-generated, the predicted sensory reafference based on motor efference copies. Here we show, using a closed-loop steering experiment with a direct coupling between the steering movement and the vestibular self-motion feedback, that humans are also able to integrate artificial motor signals, like the motor signals that occur when driving a car.
Rab11-FIP1C is dispensable for HIV-1 replication in primary CD4+T cells but its role is cell-type-dependent in immortalized human T-cell lines
Authors: de Céspedes Melissa V. , Hoffman Huxley K. , Carter Hannah , Simons Lacy M. , Naing Lwar , Ablan Sherimay D. , Hultquist Judd F. , van Engelenburg Schuyler B. , Freed Eric O. 
Published: June 2022

AbstractThe HIV-1 envelope glycoprotein (Env) contains a long cytoplasmic tail harboring highly conserved motifs that direct Env trafficking and incorporation into virions and promote efficient virus spread. The cellular trafficking factor Rab11a family interacting protein 1C (FIP1C) has been implicated in the directed trafficking of Env to sites of viral assembly. In this study, we confirm that siRNA-mediated depletion of FIP1C in HeLa cells modestly reduces Env incorporation into virions. To determine whether FIP1C is required for Env incorporation and HIV-1 replication in physiologically relevant cells, CRISPR/Cas9 technology was used to knock out the expression of this protein in several human T-cell lines – Jurkat E6.1, SupT1 and H9 – and in primary human CD4+T cells.FIP1Cknock-out caused modest reductions in Env incorporation in SupT1 cells but did not inhibit virus replication in SupT1 or Jurkat E6.1 T-cell lines. In H9 cells,FIP1Cknock-out caused a cell-density-dependent defect in virus replication. In primary CD4+T cells,FIP1Cknock-out had no effect on HIV-1 replication. Furthermore, HTLV-I transformed cell lines that are permissive for HIV-1 replication do not express FIP1C. Mutation of an aromatic motif in the Env cytoplasmic tail – Y795W – implicated in FIP1C-mediated Env incorporation impaired virus replication independently of FIP1C expression in SupT1, Jurkat E6.1, H9, and primary T cells. Together, these results indicate that while FIP1C may contribute to HIV-1 Env incorporation in some contexts, additional and potentially redundant host factors are likely required for Env incorporation and virus dissemination in T cells.ImportanceThe incorporation of the HIV-1 envelope (Env) glycoproteins, gp120 and gp41, into virus particles is critical for virus infectivity. Gp41 contains a long cytoplasmic tail that has been proposed to interact with host cell factors, including the trafficking factor Rab11a family interacting protein 1C (FIP1C). To investigate the role of FIP1C in relevant cell types – human T-cell lines and primary CD4+T cells – we used CRISPR/Cas9 to knock out FIP1C expression and examined the effect on HIV-1 Env incorporation and virus replication. We observed that in two of the T-cell lines examined (Jurkat E6.1 and SupT1) and in primary CD4+T cells, FIP1C knockout did not disrupt HIV-1 replication, whereas FIP1C knockout reduced Env expression and delayed replication in H9 cells. The results indicate that while FIP1C may contribute to Env incorporation in some cell lines, it is not an essential factor for efficient HIV-1 replication in primary CD4+ T cells.
Epstein-Barr Virus DNAemia and Post-Transplant Lymphoproliferative Disorder in Pediatric Solid Organ Transplant Recipients
Authors: Chang Yeh-Chung , Young Rebecca R. , Mavis Alisha M. , Chambers Eileen T. , Kirmani Sonya , Kelly Matthew S. , Kalu Ibukunoluwa C. , Smith Michael J. , Lugo Debra J. 
Published: June 2022

AbstractBackgroundPediatric solid organ transplant (SOT) recipients commonly have Epstein-Barr virus (EBV) DNAemia and are at risk of developing post-transplant lymphoproliferative disorder (PTLD). EBV DNAemia has not been analyzed on a continuous scale in this population.MethodsAll children ≤ 18 years of age who underwent SOT at a single center between January 1, 2007 and July 31, 2018 were included in this retrospective study. Transplant episodes in which PTLD occurred were compared to transplant episodes without PTLD. Multivariable logistic regression was used to identify factors associated with the development of EBV DNAemia and maximum height of EBV DNAemia. A Cox proportional hazards model was used to calculate hazard ratios for time to PTLD.ResultsOf 275 total transplant recipients and 294 transplant episodes, there were 14 episodes of PTLD. Intestinal and multivisceral transplant were strongly associated with PTLD (p=0.002). Risk factors for the development of EBV DNAemia include donor and recipient positive EBV serologies (p=0.001) and older age (p=0.001). Maximum level of EBV DNAemia was significantly associated with development of PTLD (p<0.0001). Every one log (log10) increase in the maximum level of EBV DNAemia was associated with a more than doubling of the hazard on developing PTLD (HR: 2.18, 95% CI 1.19-3.99).ConclusionsTransplant type was strongly associated with development of PTLD in pediatric SOT recipients. EBV serologies and age were associated with the development of EBV DNAemia and height of DNAemia. High levels of EBV DNAemia were strongly associated with an increased hazard of PTLD.
Prevalence and determinants of chronic respiratory diseases in adults in Khartoum State, Sudan
Authors: Ahmed Rana , Osman Nada , Noory Bandar , Osman Rashid , ElHassan Hana , Eltigani Hind , Nightingale Rebecca , Amaral Andre FS , Patel Jaymini , Burney Peter G. , Mortimer Kevin , ElSony Asma 
Published: June 2022

SUMMARYBackgroundChronic respiratory diseases are considered a significant cause of morbidity and mortality worldwide, although data from Africa are limited. This study aimed to determine the prevalence and determinants of chronic respiratory diseases in Khartoum, Sudan.MethodsData was collected from 516 participants, aged≥40, who had completed a questionnaire and undertook pre- and post-bronchodilator spirometry testing. Trained field workers conducted questionnaires and spirometry. Survey-weighted prevalence of respiratory symptoms and spirometric abnormalities were estimated. Regression analysis models were used to identify risk factors for chronic lung diseases.ResultsUsing the NHANESIII reference equations, the prevalence of Chronic Airflow Obstruction (CAO) was 10%. The main risk factor was older age 60-69 years (Odds ratio 3.16, 95% Confidence Interval 1.20 – 8.31). Lower education, high body mass index and a history of tuberculosis were also identified as significant risk factors. The prevalence of a low forced vital capacity (FVC) using NHANES III was 62.7% [SE 2.2] and 11.3% [SE 1.4] using locally derived values.ConclusionThe prevalence of spirometric abnormality mainly (low FVC); was high suggesting that chronic respiratory disease is of substantial public health importance in urban Sudan. Strategies for the prevention and control of these problems are needed.
Modelling Lockdown Effects on Controlling the Spread of COVID-19
Authors: Chow W.K. , Chow C.L. 
Published: June 2022

AbstractThe COVID-19 variant omicron is spreading rapidly, infecting about 1.2 million people in 2 months in Hong Kong from early January 2022. Locking down the city at the beginning of outbreak for an adequate period is effective in mitigation and suppression of disease transmission. However, it is difficult to implement the locking down proposal without strong supporting argument because of the accompanied economic loss. An appropriate mathematical model to provide key predictive information on the local epidemic and evaluate the effects of lockdown is reported in this paper. The number of susceptible citizens, infection cases and recovery number under some assumption on isolating citizens are predicted by solving the ordinary differential equations analytically. Observed infected cases during the fifth wave of outbreak in Hong Kong is taken as an example to illustrate the concept. Three lockdown scenarios are proposed and assessed by the developed mathematical approach. Early lockdown is illustrated to keep infected cases low, therefore very effective in controlling the spread by isolating the citizens in their own units.
Relating neighborhood deprivation to childhood obesity in the ABCD Study®: evidence for theories of neuroinflammation and neuronal stress
Authors: Adise Shana , Marshall Andrew T. , Kan Eric , Gonzalez Marybel , Sowell Elizabeth R. 
Published: June 2022

AbstractObjectiveWe evaluated whether the relationships between area deprivation (ADI), body mass index (BMI) and brain structure (e.g., cortical thickness, subcortical volume) during pre-adolescence supported the neuroinflammation (NI) and/or neuronal stress (NS) theories of overeating. The NI theory proposes that ADI causes structural alteration in the brain due to the neuroinflammatory effects of overeating unhealthy foods. The NS theory proposes that ADI-related stress negatively impacts brain structure, which causes stress-related overeating and subsequent obesity.MethodsData were gathered from the Adolescent Brain Cognitive DevelopmentSM Study® (9-12-years-old; n=2872, 51.3% female). Linear mixed-effects models identified brain regions that were associated with both ADI and BMI; longitudinal mediation models assessed potential causal pathways. The NI model included ADI and BMI at 9/10-years-old and brain data at 11/12-years-old. The NS model included ADI and brain data at 9/10-years-old and BMI at 11/12-years-old.ResultsIn the NI model, BMI at 9/10-years-old positively mediated the relationship between AD and cortical thinning in the cuneus, lingual, and paracentral gyrus and larger volume of the Ventral DC at 11/12-years-old. In the NS model, cortical thinning in the lateral orbitofrontal cortex, lingual gyrus and larger volume of the Ventral DC at 9/10-years-old partially mediated the relationship between ADI and BMI at 11/12-years-old.ConclusionGreater area deprivation may indicate fewer access to resources that support healthy development, like nutritious food and non-stressful environments. Our findings provide evidence in support of the neuroinflammation and stress theories of overeating, specifically, with greater ADI influencing health outcomes of obesity via brain structure alterations.
Correlates of protection, thresholds of protection, and immunobridging in SARS-CoV-2 infection
Authors: Khoury David S , Schlub Timothy E , Cromer Deborah , Steain Megan , Fong Youyi , Gilbert Peter B , Subbarao Kanta , Triccas James A , Kent Stephen J , Davenport Miles P 
Published: June 2022

AbstractSeveral studies show neutralizing antibody levels are an important correlate of immune protection from COVID-19 and have estimated the relationship between neutralizing antibodies and protection. However, a number of these studies appear to yield quite different estimates of the level of neutralizing antibodies required for protection. Here we show that after normalization of antibody titers current studies converge on a consistent relationship between antibody levels and protection from COVID-19.
Computer-assisted analysis of routine EEG to identify hidden biomarkers of epilepsy: protocol for a systematic review
Authors: Lemoine Émile , Briard Joel Neves , Rioux Bastien , Podbielski Renata , Nauche Bénédicte , Toffa Denahin , Keezer Mark , Lesage Frédéric , Nguyen Dang K. , Assi Elie Bou 
Published: June 2022

AbstractBackgroundThe diagnosis of epilepsy frequently relies on the visual interpretation of the electroencephalogram (EEG) by a neurologist. The hallmark of epilepsy on EEG is the interictal epileptiform discharge (IED). This marker lacks sensitivity: it is only captured in a small percentage of 30-minute routine EEGs in patients with epilepsy. In the past three decades, there has been growing interest in the use of computational methods to analyze the EEG without relying on the detection of IEDs, but none have made it to the clinical practice. We aim to review the diagnostic accuracy of quantitative methods applied to ambulatory EEG analysis to guide the diagnosis and management of epilepsy.MethodsThe protocol complies with the recommendations for systematic reviews of diagnostic test accuracy by Cochrane. We will search MEDLINE, EMBASE, EBM reviews, IEEE Explore along with grey literature for articles, conference papers and conference abstracts published after 1961. We will include observational studies that present a computational method to analyze the EEG for the diagnosis of epilepsy in adults or children without relying on the identification of IEDs or seizures. The reference standard is the diagnosis of epilepsy by a physician. We will report the estimated pooled sensitivity and specificity, and receiver operating characteristic area-under-the-curve (ROC AUC) for each marker. If possible, we will perform a meta-analysis of the sensitivity and specificity and ROC AUC for each individual marker. We will assess the risk of bias using an adapted QUADAS-2 tool. We will also describe the algorithms used for signal processing, feature extraction and predictive modeling, and comment on the reproducibility of the different studies.DiscussionDespite the promise to unveil epileptiform patterns that cannot be seen by the naked eye, computational analysis of ambulatory EEG has not yet been successfully translated to the clinical setting. We hope to produce recommendations for future studies on computer-assisted EEG interpretation for the diagnosis and management of epilepsy.Systematic review registrationPROSPERO #292261