bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparing activated brain regions between noisy and conventional galvanic vestibular stimulation using functional magnetic resonance imaging
Authors: Mitsutake Tsubasa , Sakamoto Maiko , Horikawa Etsuo 
Published: March 2021

Objective
Galvanic vestibular stimulation (GVS) enhances vestibular sensory inputs in vestibular afferents. However, it is unclear whether noisy and conventional GVS activate different regions of the brain. The purpose of this study was to investigate the differences in activated brain regions between those two interventions using functional MRI (fMRI).

Methods
Twenty-four healthy volunteers who met the inclusion/exclusion criteria were randomly assigned to the noisy GVS or conventional GVS groups. Brain activity was measured during stimulation and compared with that during resting fMRI. This study used a blocked design comprising four task-rest blocks, each consisting of a 30-s period of vestibular stimulation followed by a 30-s period of rest. We evaluated the differences in contrast images between the noisy and conventional GVS groups.

Results
The noisy GVS group showed significantly increased activation in the vestibular system-related brain regions, including the insula and central operculum. The conventional GVS group showed significant activity in multisensory areas, including the supramarginal gyrus, central operculum and opercular part of the inferior frontal gyrus. Thus, the noisy GVS group showed significantly increased activity in the insula, putamen and central operculum compared with the conventional GVS group.

Conclusions
Noisy GVS could increase brain activity in the insular peripheral region compared to conventional GVS. Our results extend the literature about the importance of the stochastic resonance of noise addition for the vestibular system.
Identifying Patterns of Association and Transition in the Use of Addictive Substances over Five Decades in the United States
Authors: Ray Sumanta , Aruru Meghana , Pyne Saumyadipta 
Published: March 2021

AbstractObjectivesTo conduct weighted itemset analysis to identify patterns of polysubstance use from National Survey on Drug Use and Health (NSDUH) data.MethodsWe computed weighted support for every combination of one or more substances, termed as a drugset, used by individuals in the nationally representative NSDUH data over 5 decades (1965-2014). A computational framework for efficient representation and search of patterns of association between drugsets and demographics of user groups over time was developed. A new method for mining rules of transition between pairs of substances used within a time-interval was given.ResultsWe identified the frequent drugsets from individual substance use data, and determined their representation among different demographic groups at different intervals. An interesting pattern of use of pain relievers and tranquilizers was detected for the age-group of 26-34 years. Transition rules for heroin use in the last decade (2004-2015) of data were mined.ConclusionsComputation of weighted supports over time for every possible drugset in the data and their association with specific user groups produced a framework for generation and testing new and interesting hypotheses. The framework is useful to explore different combinations of substances used among diverse demographic groups including those that have received less attention in this problem.
The effect of International Monetary Fund programmes on population health
Authors: Nosrati Elias , Marmot Michael , King Lawrence P. 
Published: March 2021

BackgroundAs one of the world’s most powerful international financial organisations, the International Monetary Fund (IMF) is uniquely positioned to shape global developmental trajectories by influencing domestic policy arrangements. However, its role in shaping population health is understudied.MethodsWe use previously unavailable cross-national time-series data and an instrumental-variables method to examine the causal impact of the IMF’s structural adjustment programmes on age-standardised all-cause mortality rates and disability-adjusted life years (DALYs) in 187 countries between 1990 and 2017. For this purpose, we specify two-way fixed-effects regression models.FindingsAccording to our baseline models, IMF programmes cause 392 excess all-cause deaths (95% CI: 176–608; p = 0.0004) and 4,205 excess DALYs (95% CI: 2,429–5,981; p = 0.000004) per 100,000 population. This aggregate effect appears to be driven by IMF-mandated privatisation reforms, which lead to 562 excess all-cause deaths (95% CI: 267–857; p = 0.0002) and 5,285 excess DALYs (95% CI: 2,749–7,822; p = 0.00004) per 100,000 population.InterpretationStructural adjustment programmes play a significant role in perpetuating preventable disability and death in developing contexts. The IMF’s policy reforms, especially those pertaining to the privatisation of state-owned enterprises, increase excess mortality rates and disease burdens in the world’s most vulnerable regions.FundingNone.
Comparison between one and two dose SARS-CoV-2 vaccine prioritisation for a fixed number of vaccine doses
Authors: Hill Edward M. , Keeling Matt J. 
Published: March 2021

AbstractThe swift development of SARS-CoV-2 vaccines has been met with worldwide commendation. How-ever, in the context of an ongoing pandemic there is an interplay between infection and vaccination. Whilst infection can grow exponentially, vaccination rates are generally limited by supply and logistics. With the first SARS-CoV-2 vaccines receiving medical approval requiring two doses, there has been scrutiny on the spacing between doses; an elongated period between doses allows more of the population to receive a first vaccine dose in the short-term generating wide-spread partial immunity. Focusing on data from England, we investigated prioritisation of a one dose or two dose vaccination schedule given a fixed number of vaccine doses and with respect to a measure of maximising averted deaths. We optimised outcomes for two different estimates of population size and relative risk of mortality for at-risk groups within the Phase 1 vaccine priority order. Vaccines offering relatively high protection from the first dose favour strategies that prioritise giving more people one dose, although with increasing vaccine supply eventually those eligible and accepting vaccination will receive two doses. Whilst optimal dose timing can substantially reduce the overall mortality risk, there needs to be careful consideration of the logistics of vaccine delivery.
A digitization theory of the Weber–Fechner law
Authors: Choe Haengjin 
Published: March 2021

AbstractEver since the publication of Shannon’s article about information theory, there have been many attempts to apply information theory to the neuroscience field. Meanwhile, the Weber– Fechner law of psychophysics states that the magnitude of a subjective sensation of a person increases in proportion to the logarithm of the intensity of the external physical-stimulus. It is hardly surprising that we assign the amount of information to the response in the Weber– Fechner law. But, to date no one has succeeded in applying information theory directly to that law: the direct links between information theory and that response in the Weber–Fechner law have not yet been found. The proposed theory unveils a link between information theory and that response, and differs subtly from the field such as neural coding that involves complicated calculations and models. Because my theory targets the Weber–Fechner law which is a macroscopic phenomenon, this theory does not involve complicated calculations. My theory is expected to mark a new era in the fields of sensory perception research. My theory must be studied in parallel with the fields of microscopic scale such as neural coding. This article ultimately aims to provide the fundamental concepts and their applications so that a new field of research on stimuli and responses can be created.
Peripheral Inflammatory Cytokine Signature Mirrors Motor Deficits in Mucolipidosis IV
Authors: Misko Albert , Weinstock Laura , Sankar Sitara , Furness Amanda , Grishchuk Yulia , Wood Levi B. 
Published: March 2021

AbstractMucolipidosis IV (MLIV) is an autosomal-recessive pediatric disease that leads to motor and cognitive deficits and loss of vision. It is caused by loss of function of the lysosomal channel transient receptor potential mucolipin-1 and is associated with an early pro-inflammatory brain phenotype, including increased cytokine expression. We thus hypothesized that peripheral blood cytokines would reflect inflammatory changes in the brain and would be linked to motor dysfunction. To test this, we collected plasma from MLIV patients and parental controls concomitantly with assessment of motor function using the Brief Assessment of Motor Function and Modified Ashworth scores. We found that MLIV patients had prominently increased cytokine levels compared to familial controls and identified profiles of cytokines correlated with motor dysfunction, including IFN-γ, IFN-α2, IL-17, IP-10. We found that IP-10 was a key differentiating factor separating MLIV cases from controls based on data from human plasma, mouse plasma, and mouse brain. Like MLIV patients, IL-17 and IP-10 were up-regulated in blood of symptomatic mice. Together, our data indicate that MLIV is characterized by increased blood cytokines, which are strongly related to underlying neurological and functional deficits in MLIV patients. Moreover, our data identify the interferon pro-inflammatory axis in both human and mouse signatures, suggesting an importance for interferon signaling in MLIV.
Axes of Prognosis: Identifying Subtypes of COVID-19 Outcomes
Authors: Whitfield Emma , Coffey Claire , Zhang Huayu , Shi Ting , Wu Xiaodong , Li Qiang , Wu Honghan 
Published: March 2021

AbstractCOVID-19 is a disease with vast impact, yet much remains unclear about patient outcomes. Most approaches to risk prediction of COVID-19 focus on binary or tertiary severity outcomes, despite the heterogeneity of the disease. In this work, we identify heterogeneous subtypes of COVID-19 outcomes by considering ‘axes’ of prognosis. We propose two innovative clustering approaches − ‘Layered Axes’ and ‘Prognosis Space’ – to apply on patients’ outcome data. We then show how these clusters can help predict a patient’s deterioration pathway on their hospital admission, using random forest classification. We illustrate this methodology on a cohort from Wuhan in early 2020. We discover interesting subgroups of poor prognosis, particularly within respiratory patients, and predict respiratory subgroup membership with high accuracy. This work could assist clinicians in identifying appropriate treatments at patients’ hospital admission. Moreover, our method could be used to explore subtypes of ‘long COVID’ and other diseases with heterogeneous outcomes.
Long lockdowns and rainy days: Modeling the interactive roles of weather, behavior, and restrictions in COVID-19 transmission in the Netherlands
Authors: Mitas Ondrej , Kokkinou Alinda 
Published: March 2021

AbstractExtant research on the role of weather in COVID-19 has produced ambiguous results and much methodological debate. Following advice emerging from this methodological debate, we take a step further in modeling effects of weather on COVID-19 spread by including interactions between weather, behavior, baseline cases, and restrictions in our model. Our model was based on secondary infection, hospitalization, restriction, weather, and mobility data per day nested with safety region in the Netherlands. Our findings show significant but inconsistent interactions. The robust effects of weather on COVID-19 spread persisted over and above these interactions, highlighting the need to account for weather with nuance and caution in public policy, communication, and forecasting.
Homophily in risk and behavior complicate understanding the COVID-19 epidemic curve
Authors: Fefferman Nina H. , Silk Matthew J. , Pasquale Dana K. , Moody James 
Published: March 2021

AbstractNew COVID-19 diagnoses have dropped faster than expected in the United States. Interpretations of the decrease have focused on changing factors (e.g. mask-wearing, vaccines, etc.), but predictive models largely ignore heterogeneity in behaviorally-driven exposure risks among distinct groups. We present a simplified compartmental model with differential mixing in two behaviorally distinct groups. We show how homophily in behavior, risk, and exposure can lead to early peaks and rapid declines that critically do not signal the end of the outbreak. Instead, higher exposure risk groups may more rapidly exhaust available susceptibles while the lower risk group are still in a (slower) growth phase of their outbreak curve. This simplified model demonstrates that complex incidence curves, such as those currently seen in the US, can be generated without changes to fundamental drivers of disease dynamics. Correct interpretation of incidence curves will be critical for policy decisions to effectively manage the pandemic.
Persistence and detection of anti-SARS-CoV-2 antibodies: immunoassay heterogeneity and implications for serosurveillance
Authors: Perez-Saez Javier , Zaballa María-Eugenia , Yerly Sabine , Andrey Diego O. , Meyer Benjamin , Eckerle Isabella , Balavoine Jean-François , Chappuis François , Pittet Didier , Trono Didier , Kherad Omar , Vuilleumier Nicolas , Kaiser Laurent , Guessous Idris , Stringhini Silvia , Azman Andrew S ,   for the Specchio-COVID19 Study Group
Published: March 2021

AbstractSerologic studies have been critical in tracking the evolution of the COVID-19 pandemic. The reliability of serologic studies for quantifying the proportion of the population that have been infected depends on the extent of antibody decay as well as on assay performance in detecting both recent and older infections. Data on anti-SARS-CoV-2 antibodies persistence remain sparse, especially from infected individuals with few to no symptoms. In a cohort of mostly mild/asymptomatic SARS-CoV-2-infected individuals tested with three widely-used immunoassays, antibodies persisted for at least 8 months after infection, although detection depended on immunoassay choice, with one of them missing up to 40% of past infections. Simulations reveal that without appropriate adjustment for time-varying assay sensitivity, seroprevalence surveys may underestimate infection rates. As the immune landscape becomes more complex with naturally-infected and vaccinated individuals, assay choice and appropriate assay-performance-adjustment will become even more important for the interpretation of serologic studies.
Epitope-resolved serology test differentiates the clinical outcome of COVID-19 and identifies defects in antibody response in SARS-CoV-2 variants
Authors: Voss Courtney , Esmail Sally , Liu Xuguang , Knauer Michael J. , Ackloo Suzanne , Kaneko Tomonori , Lowes Lori , Stogios Peter , Seitova Almagul , Hutchinson Ashley , Yusifov Farhad , Skarina Tatiana , Evdokimova Elena , Loppnau Peter , Ghiabi Pegah , Haijian Taraneh , Zhong Shanshan , Abdoh Husam , Hedley Benjamin D. , Bhayana Vipin , Martin Claudio M. , Slessarev Marat , Chin-Yee Benjamin , Fraser Douglas D. , Chin-Yee Ian , Li Shawn S-C. 
Published: March 2021

BACKGROUNDThe role of humoral immunity in the coronavirus disease 2019 (COVID-19) is not fully understood owing, in large part, to the complexity of antibodies produced in response to the SARS-CoV-2 infection. There is a pressing need for serology tests to assess patient-specific antibody response and predict clinical outcome.METHODSUsing SARS-CoV-2 proteome and peptide microarrays, we screened 146 COVID-19 patients plasma samples to identify antigens and epitopes. This enabled us to develop a master epitope array and an epitope-specific agglutination assay to gauge antibody responses systematically and with high resolution.RESULTSWe identified 54 linear epitopes from the Spike (S) and Nucleocapsid (N) protein and showed that epitopes enabled higher resolution antibody profiling than protein antigens. Specifically, we found that antibody responses to the S(811-825), S(881-895) and N(156-170) epitopes negatively or positively correlated with clinical severity or patient survival. Moreover, we found that the P681H and S235F mutations associated with the coronavirus variant B.1.1.7 altered the specificity of the corresponding epitopes.CONCLUSIONSEpitope-resolved antibody testing not only offers a high-resolution alternative to conventional immunoassays to delineate the complex humoral immunity to SARS-CoV-2 and differentiate between neutralizing and non-neutralizing antibodies, it may also be used as predictor of clinical outcome. The epitope peptides can be readily modified to detect antibodies against variants in both the peptide array and latex agglutination formats.FUNDINGOntario Research Fund (ORF)-COVID-19 Rapid Research Fund, the Toronto COVID-19 Action Fund, Western University, the Lawson Health Research Institute, the London Health Sciences Foundation, and the AMOSO Innovation Fund.
DNA methylomes derived from alveolar macrophages display distinct patterns in latent tuberculosis - implication for interferon gamma release assay status determination
Authors: Pehrson Isabelle , Das Jyotirmoy , Idh Nina , Karlsson Lovisa , Rylander Helena , af Segerstad Hilma Hård , Reuterswärd Elsa , Marttala Emma , Paues Jakob , Méndez-Aranda Melissa , Ugarte-Gil César , Lerm Maria 
Published: March 2021

AbstractHost innate immune cells, including alveolar macrophages, have been identified as key players in the early eradication of Mycobacterium tuberculosis and in the maintenance of an anti-mycobacterial immune memory, which is believed to be induced through epigenetic changes. The aim of the study was to elucidate whether exposure to M. tuberculosis induced a different DNA methylation pattern of alveolar macrophages and pulmonary T lymphocytes.Alveolar macrophages and T lymphocytes were isolated from induced sputum obtained from individuals living in Lima, which is an area high endemic for tuberculosis. To determine the latent tuberculosis infection status of the subjects, an interferon-γ release assay was performed. We evaluated the DNA methylomes of the alveolar macrophages and T lymphocytes using the Illumina Infinium Human Methylation 450K Bead Chip array, revealing a distinct DNA methylation pattern in alveolar macrophages allowing the discrimination of asymptomatic individuals with latent tuberculosis infection from non-infected individuals. Pathway analysis revealed that cell signalling of inflammation and chemokines in alveolar macrophages play a role in latent tuberculosis infection. In conclusion, we demonstrated that DNA methylation in alveolar macrophages can be used to determine the tuberculosis infection status of individuals in a high endemic setting.
A Differential DNA Methylome Signature of Pulmonary Immune Cells from Individuals Converting to Latent Tuberculosis Infection
Authors: Karlsson Lovisa , Das Jyotirmoy , Nilsson Moa , Tyrén Amanda , Pehrson Isabelle , Idh Nina , Paues Jakob , Ugarte-Gil Cesar , Méndez-Aranda Melissa , Lerm Maria 
Published: March 2021

AbstractTuberculosis (TB), caused byMycobacterium tuberculosis, spreads via aerosols and the first encounter with the immune system is with the pulmonary resident immune cells. The role of epigenetic regulations through DNA methylation in the immune cells is emerging. We have previously shown that capacity to killM. tuberculosisis reflected in the DNA methylome. The aim of this study was to investigate epigenetic modifications in the pulmonary immune cells in a cohort of medical students with a previously documented increased risk of TB exposure, longitudinally. Sputum samples containing alveolar macrophages (AMs) and T cells were collected before and after study subjects worked in hospital departments with a high-risk of TB exposure. DNA methylome analysis revealed that a unique DNA methylation profile was present already at inclusion in subjects who developed latent TB during the study. The profile was both reflected in different overall DNA methylation distribution as well as more profound alterations in the methylation status of a unique set of CpG-sites. Over-representation analysis of the DMGs showed enrichment in pathways related to metabolic reprograming of macrophages and T cell migration and IFN-γ production. In conclusion, we identified a unique DNA methylation signature in individuals, while still IGRA-negative and who later developed latent TB. Epigenetic regulation was found in pathways that have previously been reported to be important in TB. Together the study suggests that DNA methylation status of pulmonary immune cells can predict IGRA conversion.
The Spike-specific IgA in milk commonly-elicited after SARS-Cov-2 infection is concurrent with a robust secretory antibody response, exhibits neutralization potency strongly correlated with IgA binding, and is highly durable over time
Authors: Fox Alisa , Marino Jessica , Amanat Fatima , Oguntuyo Kasopefoluwa , Hahn-Holbrook Jennifer , Lee Benhur , Krammer Florian , Zolla-Pazner Susan , Powell Rebecca L. 
Published: March 2021

AbstractApproximately 10% of infants will experience COVID-19 illness requiring advanced care (1). A potential mechanism to protect this population could be provided by passive immunity through the milk of a previously infected mother. We and others have reported on the presence of SARS-CoV-2-specific antibodies in human milk (2-5). We now report the prevalence of SARS-CoV-2 IgA in the milk of 75 COVID-19-recovered participants, and find that 88% of samples are positive for Spike-specific IgA. In a subset of these samples, 95% exhibited robust IgA activity as determined by endpoint binding titer, with 50% considered high-titer. These IgA positive specimens were also positive for Spike-specific antibodies bearing the secretory component. Levels of IgA antibodies and antibodies bearing secretory component were shown to be strongly positively correlated. The secretory IgA response was dominant among the milk samples tested compared to the IgG response, which was present in 75% of samples and found to be of high-titer in only 13% of cases. Our IgA durability analysis using 28 paired samples, obtained 4-6 weeks and 4-10 months after infection, found that all samples exhibited persistently significant Spike-specific IgA, with 43% of donors exhibiting increasing IgA titers over time. Finally, COVID-19 and pre-pandemic control milk samples were tested for the presence of neutralizing antibodies; 6 of 8 COVID-19 samples exhibited neutralization of Spike-pseudotyped VSV (IC50 range, 2.39 – 89.4ug/mL) compared to 1 of 8 controls. IgA binding and neutralization capacities were found to be strongly positively correlated. These data are highly relevant to public health, not only in terms of the protective capacity of these antibodies for breastfed infants, but also for the potential use of such antibodies as a COVID-19 therapeutic, given that secretory IgA is highly stable not only in milk and the infant mouth and gut, but in all mucosa including the gastrointestinal tract, upper airway, and lungs (6).