bluuebunny/crossref_metadata_2025 huggingface dataset:
Development and Evaluation of a Procedure to Identify Possible Gonorrhea Treatment Failure Cases in Illinois
Authors: Smith Marguerite , Choat Lesli , McKinney-Colman Lynette , Brikshavana Danucha
Published: May 2021

Background

Cephalosporins are the last effective class of antibiotics to treat gonorrhea infections. In Illinois, gonorrhea cases have increased by 70.9% from 2015 to 2019. Because of the concern of antimicrobial resistance and the increasing number of cases, the Illinois Department of Public Health Sexually Transmitted Diseases Section established a procedure to identify possible gonorrhea treatment failure cases.

Materials and Methods

A procedure was developed that identifies patients who have had 2 gonorrhea cases in the last 60 days, and the first case was treated with the Centers for Disease Control and Prevention–recommended treatment. Interview records were faxed to the local health department (LHD) where the patient resides. Descriptive statistics were used to analyze interview record data. A process evaluation was conducted using telephone interviews with LHDs to obtain qualitative feedback on the procedure.

Results

A total of 310 interview records were sent for investigation in 2018 and 2019 with 263 returned. Of those returned, 140 identified reexposure, 104 were unable to be located, 12 refused to be interviewed, 6 had treatment reported incorrectly, and 1 had a possible treatment failure. From telephone interviews with 6 LHDs, 1 question was removed and 2 questions were added to the interview record.

Conclusions

Antibiotic-resistant gonorrhea could occur in Illinois at any time. Monitoring for antibiotic-resistant gonorrhea cases is necessary as gonorrhea morbidity continues to increase. This procedure may prove to be a model for other states.
Timing and Clinical Significance of Fluid Overload in Pediatric Acute Respiratory Distress Syndrome*
Authors: Black Celeste G. , Thomas Neal J. , Yehya Nadir
Published: May 2021

Objectives:

Fluid overload is associated with worse outcomes in adult and pediatric acute respiratory distress syndrome. However, the time-course of fluid overload and its relationship to outcome has not been described. We aimed to determine the relationship between the timing of fluid overload and outcomes over the first 7 days after acute respiratory distress syndrome onset in children.

Design:

Retrospective cohort study.

Setting:

Single tertiary care PICU.

Patients:

Intubated children with acute respiratory distress syndrome between 2011 and 2019.

Interventions:

None.

Measurements and Main Results:

Daily and cumulative total fluid intake, total output, urine output, and fluid balance were collected for each 24-hour period from days 1 to 7 after acute respiratory distress syndrome onset. We tested the association between daily cumulative fluid metrics with PICU mortality and probability of extubation by 28 days using multivariable logistic and competing risk regression, respectively. In a subset of children, plasma was collected on day 1 and day 3 of acute respiratory distress syndrome and angiopoietin-2 quantified. Of 723 children with acute respiratory distress syndrome, 132 died (18%). In unadjusted analysis, nonsurvivors had higher cumulative fluid balance starting on day 3. In multivariable analysis, a positive cumulative fluid balance on days 5 through 7 was associated with increased mortality. Higher cumulative fluid balance on days 4 to 7 was associated with lower probability of extubation. Elevated angiopoietin-2 on day 1 predicted early (within 3 d) fluid overload greater than or equal to 10%, and elevated angiopoietin-2 on day 3 predicted late (between days 4 and 7) fluid overload.

Conclusions:

Fluid overload after day 4 of acute respiratory distress syndrome, but not before, was associated with worse outcomes. Higher angiopoietin-2 predicted subsequent fluid overload. Our results suggest that future interventions aimed at managing fluid overload may have differential efficacy depending on when in the time-course of acute respiratory distress syndrome they are initiated.
Which GAN? A comparative study of generative adversarial network-based fast MRI reconstruction
Authors: Lv Jun , Zhu Jin , Yang Guang
Published: May 2021

Fast magnetic resonance imaging (MRI) is crucial for clinical applications that can alleviate motion artefacts and increase patient throughput.
K
-space undersampling is an obvious approach to accelerate MR acquisition. However, undersampling of
k
-space data can result in blurring and aliasing artefacts for the reconstructed images. Recently, several studies have been proposed to use deep learning-based data-driven models for MRI reconstruction and have obtained promising results. However, the comparison of these methods remains limited because the models have not been trained on the same datasets and the validation strategies may be different. The purpose of this work is to conduct a comparative study to investigate the generative adversarial network (GAN)-based models for MRI reconstruction. We reimplemented and benchmarked four widely used GAN-based architectures including DAGAN, ReconGAN, RefineGAN and KIGAN. These four frameworks were trained and tested on brain, knee and liver MRI images using twofold, fourfold and sixfold accelerations, respectively, with a random undersampling mask. Both quantitative evaluations and qualitative visualization have shown that the RefineGAN method has achieved superior performance in reconstruction with better accuracy and perceptual quality compared to other GAN-based methods.

This article is part of the theme issue ‘Synergistic tomographic image reconstruction: part 1’.
Acinetobacter pollinis sp. nov., Acinetobacter baretiae sp. nov. and Acinetobacter rathckeae sp. nov., isolated from floral nectar and honey bees
Authors: Alvarez-Perez Sergio , Baker Lydia J. , Morris Megan M. , Tsuji Kaoru , Sanchez Vivianna A. , Fukami Tadashi , Vannette Rachel L. , Lievens Bart , Hendry Tory A.
Published: May 2021

A detailed evaluation of eight bacterial isolates from floral nectar and animal visitors to flowers shows evidence that they represent three novel species in the genus

Acinetobacter

. Phylogenomic analysis shows the closest relatives of these new isolates are

Acinetobacter apis

,

Acinetobacter boissieri

and

Acinetobacter nectaris

, previously described species associated with floral nectar and bees, but high genome-wide sequence divergence defines these isolates as novel species. Pairwise comparisons of the average nucleotide identity of the new isolates compared to known species is extremely low (<83 %), thus confirming that these samples are representative of three novel

Acinetobacter

species, for which the names Acinetobacter pollinis sp. nov., Acinetobacter baretiae sp. nov. and Acinetobacter rathckeae sp. nov. are proposed. The respective type strains are SCC477T (=TSD-214T=LMG 31655T), B10AT (=TSD-213T=LMG 31702T) and EC24T (=TSD-215T=LMG 31703T=DSM 111781T).
Cumulative incidence of SARS-CoV-2 infections among adults in Georgia, USA, August-December 2020
Authors: Chamberlain Allison T. , Toomey Kathleen E. , Bradley Heather , Hall Eric W. , Fahimi Mansour , Lopman Benjamin A. , Luisi Nicole , Sanchez Travis , Drenzek Cherie , Shioda Kayoko , Siegler Aaron J , Sullivan Patrick Sean
Published: May 2021

Background

Reported COVID-19 cases underestimate the true number of SARS-CoV-2 infections. Data on all infections, including asymptomatic infection, are needed to guide state testing and prevention programs. To minimize biases in estimates from seroprevalence surveys and reported cases, we conducted a state-wide probability survey of Georgia households and estimated cumulative incidence of SARS-CoV-2 infections adjusted for antibody waning.

Methods

From August to December 2020, we mailed kits to self-collect specimens (nasal swabs and blood spots) to a random sample of Georgia addresses. One randomly-selected adult household member completed a survey and returned specimens for virus and antibody testing. We estimated cumulative incidence of SARS-CoV-2 infections adjusted for waning antibodies, reported fraction, and infection fatality ratio (IFR). Differences in seropositivity among demographic, geographic and clinical subgroups were explored with weighted prevalence ratios (PR).

Results

Among 1,370 Georgia adult participants, adjusted cumulative incidence of SARS-CoV-2 was 16.1% (95% credible interval (CrI): 13.5-19.2%) as of November 16, 2020. The reported fraction was 26.6% and IFR was 0.78%. Non-Hispanic Black (PR: 2.03, CI 1.0, 4.1) and Hispanic adults (PR: 1.98, CI 0.74, 5.31) were more likely than non-Hispanic White adults to be seropositive. Seropositivity in metropolitan Atlanta’s Fulton and DeKalb counties was similar to seropositivity elsewhere in Georgia (7.8% vs. 8.8%).

Conclusions

As of mid-November 2020, one in 6 adults in Georgia had been infected with SARS-CoV-2. The scope of the COVID-19 epidemic in Georgia is likely substantially underestimated by reported cases.

Main point

Using data from a probability survey of households in Georgia, USA, we estimated that 1.3 million adults aged ≥18 years experienced SARS-CoV-2 infections by November 16, 2020, of whom 1 in 4 were reported and of whom 0.78% died.
Multivariate Modeling of Direct and Proxy GWAS Indicates Substantial Common Variant Heritability of Alzheimer’s Disease
Authors: de la Fuente Javier , Grotzinger Andrew D. , Marioni Riccardo E. , Nivard Michel G. , Tucker-Drob Elliot M.
Published: May 2021

Genome-wide association studies (GWAS) of proxy-phenotypes using family history of disease (GWAX) substantially boost power for genetic discovery when combined with direct case-control GWAS, most prominently in the context of Alzheimer’s Disease (AD). However, despite twin study heritability estimates of approximately 60%, recent SNP-based estimates of common variant heritability of AD from meta-analyzed GWAS-GWAX data have been particularly low (2.5%), calling into question the prospects of continued progress in AD genetics. We demonstrate that commonly used approaches for combining GWAX and GWAS data produce dramatic underestimates of heritability, and we introduce a multivariate method for estimating individual SNP effects and recovering unbiased estimates of SNP heritability when combining GWAS and GWAX summary data. We estimate the SNP heritability of Clinical AD diagnoses excluding the APOE region at ∼6-10%, with the corresponding estimate for biological AD (based on prevalence rate estimates from recently published molecular imaging data) as high as ∼20%. Common variant risk for AD appears to represent a very strong effect of APOE superimposed upon a relatively diffuse polygenic signal that is distributed across the genome.
Subgroups of young type 2 diabetes in India reveal insulin deficiency as a major driver
Authors: Prasad Rashmi B , Asplund Olof , Shukla Sharvari R , Wagh Rucha , Kunte Pooja , Bhat Dattatrey , Parikh Malay , Shah Meet , Phatak Sanat , Käräjämäki Annemari , Datta Anupam , Kakati Sanjeeb , Tuomi Tiinamaija , Saboo Banshi , Ahlqvist Emma , Groop Leif , Yajnik Chittaranjan S
Published: May 2021

Aim/Hypothesis

Five subgroups were described in European diabetes patients using a data driven machine learning approach on commonly measured variables. We aimed to test the applicability of this phenotyping in Indian young-onset type 2 diabetes patients.

Methods

We applied the European derived centroids to the Indian type 2 diabetes patients diagnosed before 45 years of age from the WellGen (n = 1612) cohort. We also applied de novo k-means clustering to the WellGen cohort to validate the subgroups. We then compared clinical and metabolic-endocrine characteristics and the complication rates between the subgroups. We also compared characteristics of the WellGen subgroups with those of two young European cohorts ANDIS (n= 962) and DIREVA (n=420). Subgroups were also assessed in two other Indian cohorts, Ahmedabad (n = 187) and PHENOEINDY-2 (n = 205).

Results

Both Indian and European young type 2 diabetes patients were predominantly classified into severely insulin-deficient (SIDD) and mild obesity-related (MOD) subgroups, while the severely insulin-resistant (SIRD) and mild age-related (MARD) subgroups were rare. In WellGen, SIDD (53%) was more common than MOD (38%), contrary to figures in Europeans (Swedish: 26% vs 68%, Finnish: 24% vs 71% respectively). A higher proportion of SIDD compared to MOD was also seen in Ahmedabad (57% vs 33%) and in PHENOEINDY-2 (67% vs 23%). Both in Indians and Europeans, the SIDD subgroup was characterized by insulin deficiency and hyperglycemia, MOD by obesity, SIRD by severe insulin resistance and MARD by mild metabolic-endocrine disturbances. In WellGen, nephropathy and retinopathy were more prevalent in SIDD compared to MOD while the latter had higher prevalence of neuropathy.

Conclusions /Interpretation

Our data identified insulin deficiency as the major driver of type 2 diabetes in young Indians, unlike in young European patients in whom obesity and insulin resistance predominate. Our results provide useful clues to pathophysiological mechanisms and susceptibility to complications in young Indian type 2 diabetes, and suggest a need to review management strategies.
Can we use machine learning to discover risk factors? Testing the proof of
principle using data on >11,000 predictors and mortality in the UK
Biobank
Authors: Madakkatel Iqbal , Zhou Ang , McDonnell Mark , Hyppönen Elina
Published: May 2021

Background

We present a simple and fast hypothesis-free machine learning pipeline
for risk factor discovery that accounts for non-linearity and interaction in
large biomedical databases with minimal variable pre-processing.

Methods

Mortality models were built using gradient boosting decision trees
(GBDT) and important predictors were identified using SHAP values. Cox
models controlled for false discovery rate were used for interpretability
and further validation. The pipeline was tested using information from
502,506 UK Biobank participants, aged 37–73 years at recruitment and
followed over seven years for mortality registrations.

Results

From the 11,639 predictors included in GBDT, 193 potential risk factors
had SHAP values 0.05 or greater and were selected for further modelling. Of
the total variable importance summed up, 60% was directly health related,
and baseline characteristics, sociodemographics, and lifestyle factors each
contributed about 10%.

Cox models adjusted for baseline characteristics, showed evidence for an
association with mortality for 166 out of the 193 predictors. These included
mostly well-known risk factors (e,g, age, sex, ethnicity, education,
material deprivation, smoking, physical activity, self-rated health, BMI,
and many disease outcomes), and the pipeline was able to detect associations
in the presence of interactions and non-linear relationships. For 19
predictors we saw evidence for an association in the unadjusted but not
adjusted analyses, suggesting bias by confounding..

Conclusion

Our GBDT-SHAP pipeline was able to identify relevant predictors ‘hidden’
within thousands of variables, providing a fast and pragmatic solution for
the first stage of hypothesis free risk factor identification.

What was known before this study?

Existing studies have used ML for variable selection in general
settings, however, we are not aware of studies integrating
epidemiological approaches with ML for risk factor discovery in
deeply phenotyped large scale population cohorts. We present a
simple and fast method for risk factor discovery using GBDT-SHAP
pipeline, followed by subsequent standard epidemiological analyses.
We test this pipeline using mortality prediction in the UK Biobank
as an example.

What this study adds?

Machine learning pipeline integrated with traditional
epidemiological practices as described in our study can be used a
simple and fast method for discovering potential risk factors in
extensively phenotyped high dimensional biomedical databases.
GBDT-SHAP pipeline was able to detect associations with factors
presenting with interactions with other explanatory variables and
non-linear relationships with the outcome with minimal variable
pre-processing. However, ML does not replace the requirement for
content knowledge and more refined modelling to ensure lack of
confounding and accurate interpretation.
Evaluation the angle of posterosuperior horn of normal fetal Sylvian fissure and its morphological changes by trans-cerebellar section
Authors: Pingping Xu , Dirong Zhang , Yu Shi , Fengbei Kong , Chunxiao Yao , Ying She , Guoru Wu
Published: May 2021

Objective

On the basis of retrospectively analysis the trans-cerebellar section showing the Sylvian fissure of normal fetus is better than trans-thalamic section in middle and late trimester, we prospectively studied the morphological changes of the Sylvian fissure of normal fetus on the trans-cerebellar section in order to provide valuable information for the diagnosis of fetal cerebral cortical dysplasia.

Methods

A prospective cross-sectional study was conducted on 845 normal fetuses at 21 to 32 weeks of gestation from January 2019 to September 2020. The angle of the posterosuperior horn of the Sylvian fissure was measured. Based on the angle, the morphology of the Sylvian fissure was divided into four shapes included shape (Angle >90°), П shape (Angle ≈90°), π shape (Angle <90°) and 工 shape (Angle ≈0°).

Results

The angle of the posterosuperior horn of the Sylvian fissure was negatively correlated with gestational age which correlation coefficient was 0.966 (P < 0.001). Taking gestational age as the independent variable and the angle of posterosuperior horn of the Sylvian fissure as the dependent variable, it showed that there was a linear relationship between the gestational age and the angle of posterosuperior horn of the Sylvian fissure. We got a simple correlation formula that the angle of posterosuperior horn of the Sylvian fissure (°) =140-13×(gestational weeks-21). It was found that the morphological changes of the Sylvian fissure were related to the gestational age. The morphology of the Sylvian fissure was -shaped at 21 to 24 weeks of gestation, П-shaped at 25 to 26 weeks of gestation, π-shaped at 26 to 30 weeks of gestation, and the Sylvian fissure was almost closed and appeared 工 shape after 31 to 32 weeks of gestation.

Conclusion

This study preliminarily elucidates that the morphological changes of the posterosuperior horn of the Sylvian fissure of normal fetuses at 21 to 32 weeks of gestation through the trans-cerebellar section, which could provide valuable information for the evaluation of the normal development of the Sylvian fissure and the prenatal diagnosis of cerebral cortical hypoplasia of fetuses.
Evaluation of the depth and width of normal fetal Sylvian fissure by trans-cerebellar section
Authors: xu pingping , zhang dirong , shi yu , kong fengbei , yao chunxiao , she ying , wu guoru
Published: May 2021

Abstract
Objective On the basis of retrospectively analysis the trans-cerebellar section showing the Sylvian fissure of normal fetus is better than trans-thalamic section in middle and late trimester, we prospectively established the normal reference range of developmental parameters related to the Sylvian fissure of normal fetus in the trans-cerebellar section in order to provide valuable information for the diagnosis of fetal cerebral cortical dysplasia.
Methods A prospective cross-sectional study was conducted on 845 normal fetuses at 21 to 32 weeks of gestation from January 2019 to September 2020. The depth and width of the Sylvian fissure was measured respectively, and regression analysis was performed according to different gestational age groups.
Results The depth of Sylvian fissure was positively correlated with gestational weeks, and the width of Sylvian fissure was negatively correlated with gestational weeks, with correlation coefficients 0.751 and 0.825 respectively (all P < 0.001).Taking gestational weeks as the independent variable, and the depth and width of Sylvian fissure of fetus as the dependent variables, linear regression analysis showed that there was a linear relationship between the independent variables and the dependent variables. The obtained equation was simplified to a formula: Fetal Sylvian fissure depth (mm)=7+0.6X(gestational weeks-21), Sylvian fissure width (mm)=8-0.6X(gestational weeks-21).
Conclusion The reference range of the depth and width of Sylvian fissure of normal fetus at 21 to 32 weeks of pregnancy through the trans-cerebellar section was established, which could provide valuable information for the evaluation of the normal development of the lateral fissure of fetus and the prenatal diagnosis of fetal cortical hypoplasia.
Key words
Fetus; Sylvian fissure; depth; width; trans-cerebellar section
Results of an Academic Dialysis Program-Wide SARS-CoV-2 Vaccination Effort
Authors: Bowman Brendan T. , Lobo Benjamin J. , Sharma Binu , Ma Jennie Z.
Published: May 2021

Patients with End Stage Kidney Disease requiring dialysis are exceedingly vulnerable to SARS-CoV-2 infection with high hospitalization rates and mortality. Despite this risk, little is known about real world dialysis patient SARS-CoV-2 vaccination acceptance. Surveys of the general population suggest significant vaccine hesitancy and high potential for refusal. From January 27th to March 12th 2021, the University of Virginia (UVA) Health System, in partnership with the Virginia Department of Health / Blue Ridge Health District (BRHD) provided on-site mobile vaccination clinics at 12 UVA dialysis sites. We conducted a cross-sectional study to evaluate vaccine acceptance and evaluate factors associated with refusal. Of 859 dialysis patients with complete vaccination data, 80% received at least one dose of vaccine and 87% of these vaccinations were provided by the UVA/BRHD partnership. The overall patient refusal rate was low at 14%. Patients refusing SARS-CoV-2 vaccine were more likely to be female, younger and missing a documented flu vaccination during the 2020-2021 season. Attributes such as race or prior infection with SARS-CoV-2 were not significantly associated with vaccine refusal. In conclusion, dialysis patients in our program were surprisingly likely to accept vaccination for SARS-CoV-2. Identifying attributes associated with refusal may help target populations at high risk of vaccine refusal.
Association of machine learning-derived measures of body fat distribution with cardiometabolic diseases in >40,000 individuals
Authors: Agrawal Saaket , Klarqvist Marcus D. R. , Diamant Nathaniel , Stanley Takara L. , Ellinor Patrick T. , Mehta Nehal N. , Philippakis Anthony , Ng Kenney , Claussnitzer Melina , Grinspoon Steven K. , Batra Puneet , Khera Amit V.
Published: May 2021

Background

The clinical implications of BMI-independent variation in fat distribution are not fully understood.

Methods

We studied MRI imaging data of 40,032 UK Biobank participants. Using previously quantified visceral (VAT), abdominal subcutaneous (ASAT), and gluteofemoral (GFAT) adipose tissue volume in up to 9,041 to train convolutional neural networks (CNNs), we quantified these depots in the remainder of the participants. We derived new metrics for each adipose depot – fully independent of BMI – by quantifying deviation from values predicted by BMI (e.g. VAT adjusted for BMI, VATadjBMI) and determined associations with cardiometabolic diseases.

Results

CNNs based on two-dimensional projection images enabled near-perfect estimation of VAT, ASAT, and GFAT, with r2 in a holdout testing dataset (r2 = 0.978-0.991). Using the newly derived measures of local adiposity – residualized based on BMI – we note marked heterogeneity in associations with cardiometabolic diseases. Taking presence of type 2 diabetes as an example, VATadjBMI was associated with significantly increased risk (odds ratio per standard deviation increase (OR/SD) 1.49; 95%CI: 1.43-1.55), while ASATadjBMI was largely neutral (OR/SD 1.08; 95%CI: 1.03-1.14) and GFATadjBMI conferred protection (OR/SD 0.75; 95%CI: 0.71-0.79). Similar patterns were observed for coronary artery disease.

Conclusions

Deep learning models trained on a simplified MRI input enable near perfect quantification of VAT, ASAT, and GFAT. For any given BMI, measures of local adiposity have variable and divergent associations with cardiometabolic diseases.
Key kinematic features in early training predict performance of adult female mice in a single pellet reaching and grasping task
Authors: Mykins Michael , Espinoza-Wade Eric , An Xu , Lau Billy You Bun , Krishnan Keerthi
Published: May 2021

Detailed analyses of overly trained animal models have been long employed to decipher foundational features of skilled motor tasks and their underlying neurobiology. However, initial trial-and-error features that ultimately give rise to skilled, stereotypic movements, and the underlying neurobiological basis of flexibility in learning, to stereotypic movement in adult animals are still unclear. Knowledge obtained from addressing these questions is crucial to improve quality of life in patients affected by movement disorders.

We sought to determine if known kinematic parameters of skilled movement in humans could predict learning of motor efficiency in mice during the single pellet reaching and grasping assay. Mice were food restricted to increase motivation to reach for a high reward food pellet. Their attempts to retrieve the pellet were recorded for 10 minutes a day for continuous 4 days. Individual successful and failed reaches for each mouse were manually tracked using Tracker Motion Analysis Software to extract time series data and kinematic features. We found the number of peaks and time to maximum velocity were strong predictors of individual variation in failure and success, respectively. Overall, our approach validates the use of select kinematic features to describe fine motor skill acquisition in mice and establishes peaks and time to maximum velocity as predictive measure of natural variation in motion efficiency in mice. This manually curated dataset, and kinematic parameters would be useful in comparing with pose estimation generated from deep learning approaches.
Inhibition-Dominated Rich-Club Shapes Dynamics in Cortical Microcircuits
Authors: Hafizi Hadi , Nigam Sunny , Barnathan Josh , Ren Naixin , Stevenson Ian H , Masmanidis Sotiris C , Newman Ehren L , Sporns Olaf , Beggs John M
Published: May 2021

Functional networks of cortical neurons contain highly interconnected hubs, forming a rich-club structure. However, the cell type composition within this distinct subnetwork and how it influences large-scale network dynamics is unclear. Using spontaneous activity recorded from hundreds of cortical neurons in orbitofrontal cortex of awake behaving mice and from organotypic cultures, we show that the rich-club is disproportionately composed of inhibitory neurons, and that inhibitory neurons within the rich-club are significantly more synchronous than other neurons. At the population level, neurons in the rich-club exert higher than expected Granger causal influence on overall population activity at a broad range of frequencies compared to other neurons. Finally, neuronal avalanche duration is significantly correlated with the fraction of rich neurons that participate in the avalanche. Together, these results suggest an unexpected role of a highly connected, inhibition-rich subnetwork in driving and sustaining activity in local cortical networks.

SIGNIFICANCE STATEMENT

It is widely believed that the relative abundance of excitatory and inhibitory neurons in cortical circuits is roughly 4:1. This relative abundance has been widely used to construct numerous cortical network models. Here we show that contrary to this notion, a sub-network of highly connected hub neurons (rich-club) consists of a higher abundance of inhibitory neurons compared to that found in the entire network or the non-rich subnetwork. Inhibitory hub neurons contribute to higher synchrony within the rich club compared to the rest of the network. Strikingly, higher activation of the inhibition-dominated rich club strongly correlates with longer avalanches in cortical circuits. Our findings reveal how network topology combined with cell-type specificity orchestrates population wide activity in cortical microcircuits.
Accuracy and Power Analysis of Social Networks Built From Count Data
Authors: Hart Jordan D. A. , Franks Daniel W. , Brent Lauren J. N. , Weiss Michael N.
Published: May 2021

Power analysis is used to estimate the probability of correctly rejecting a null hypothesis for a given statistical model and dataset. Conventional power analyses assume complete information, but the stochastic nature of behavioural sampling can mean that true and estimated networks are poorly correlated. Power analyses do not currently take the effect of sampling into account. This could lead to inaccurate estimates of statistical power, potentially yielding misleading results.

Here we develop a method for computingnetwork correlation: the correlation between an estimated social network and its true network, using a Gamma-Poisson model of social event rates for networks constructed from count data. We use simulations to assess how the level of network correlation affects the power of nodal regression analyses. We also develop a generic method of power analysis applicable to any statistical test, based on the concept of diminishing returns.

We demonstrate that our network correlation estimator is both accurate and moderately robust to its assumptions being broken. We show that social differentiation, mean social event rate, and the harmonic mean of sampling times positively impacts the strength of network correlation. We also show that the required level of network correlation to achieve a given power level depends on many factors, but that 0.80 network correlation usually corresponds to around 0.80 power for nodal regression in ideal circumstances.

We provide guidelines for using our network correlation estimator to verify the accuracy of networks built from count data, and to conduct power analysis. This can be used prior to data collection, in post hoc analyses, or even for subsetting networks in dynamic network analysis. The network correlation estimator and custom power analysis methods have been made available as an R package.
HIPPOCAMPAL DNA METHYLATION, DNAm AGE AND SPATIAL MEMORY PERFORMANCE IN YOUNG AND OLD RATS
Authors: Chiavellini Priscila , Lehmann Marianne , Canatelli Mallat Martina , Zoller Joseph A. , Herenu Claudia B. , Morel Gustavo R. , Horvath Steve , Goya Rodolfo G.
Published: May 2021

In humans and rats, aging is associated with a progressive deterioration of spatial learning and memory. These functional alterations are correlated with morphological and molecular changes in the brain, particularly in the hippocampus. Here, we assessed the age-related changes in the DNA methylation (DNAm) landscape in the rat hippocampus and assessed the correlation of spatial memory performance with hippocampal DNAm age in young (2.6 mo.) and old (26.6 mo.) rats.

Spatial memory performance was assessed with a modified version of the Barnes maze test. In order to evaluate learning ability as well as spatial memory retention, we assessed the time spent (permanence) by animals in goal sector 1 (GS1) and 3 (GS3) when the escape box was removed. The rat pan-tissue clock was applied to DNA methylation profiles of hippocampal tissue. The bisulfite converted genomic DNA was analyzed by Illumina Infinium HorvathMammalMethylChip40. The Horvath Mammal Methyl Chip40 assay provides quantitative measurements of DNA methylation for 22528 CpG dinucleotides that map to the Rattus norvegicus UCSC 6.0 genome. An enrichment pathway analysis revealed that neuron fate commitment, brain development, and central nervous system development were processes whose underlying genes were enriched in positively methylated CpGs. In the old rat hippocampi, the methylation levels of CpGs proximal to transcription factors associated with genes Pax5, Lbx1, Nr2f2, Hnf1b, Zic1, Zic4, Hoxd9; Hoxd10, Gli3, Gsx1 and Lmx1b, and Nipbl showed a significant regression with spatial memory performance. Regression analysis of different memory performance indices with hippocampal DNAm age was significant when data from young and old rats were taken together. The above results suggest that age-related hypermethylation of certain gene families, like Zic and Gli, may play a causal role in the decline in spatial memory in old rats. Hippocampal DNAm age seems to be a reliable index of spatial memory performance in young and old rats.
Top-down generation of low-resolution representations improves visual perception and imagination
Authors: Bi Zedong , Tian Liang
Published: May 2021

Abstract

Perception or imagination requires top-down signals from high-level cortex to primary visual cortex (V1) to reconstruct or simulate the representations bottom-up stimulated by the seen images. Interestingly, top-down signals in V1 have lower spatial resolution than bottom-up representations. It is unclear why the brain uses low-resolution signals to reconstruct or simulate high-resolution representations. By modeling the top-down pathway of the visual system using the decoder of variational auto-encoder (VAE), we reveal that low-resolution top-down signals can better reconstruct or simulate the information contained in the sparse activities of V1 simple cells, which facilitates perception and imagination. This advantage of low-resolution generation is related to facilitating high-level cortex to form geometry-respecting representations observed in experiments. Moreover, our finding inspires a simple artificial- intelligence (AI) technique to significantly improve the generation quality and diversity of sketches, a style of drawings made of thin lines. Specifically, instead of directly using original sketches, we use blurred sketches to train VAE or GAN (generative adversarial network), and then infer the thin-line sketches from the VAE- or GAN- generated blurred sketches. Collectively, our work suggests that low-resolution top-down generation is a strategy the brain uses to improve visual perception and imagination, and advances sketch-generation AI techniques.
Ankle and Toe Brachial Index Extraction from Clinical Reports For Peripheral Artery Disease Identification: Unlocking Clinical Data through Novel Methods
Authors: Friberg Julia E. , Qazi Abdul H. , Boyle Brenden , Franciscus Carrie , Vaughan-Sarrazin Mary , Westerman Dax , Patterson Olga V. , Parr Sharidan K. , Matheny Michael E. , Arya Shipra , Smolderen Kim G. , Lund Brian C. , Gobbel Glenn T. , Girotra Saket
Published: May 2021

Importance

Despite its high prevalence and poor outcomes, research on peripheral artery disease (PAD) remains limited due to the poor accuracy of billing codes for identifying PAD in health systems.

Objective

Design a natural language processing (NLP) system that can extract ankle brachial index (ABI) and toe brachial index (TBI) values and evaluate the performance of extracted ABI/TBI values to identify patients with PAD in the Veterans Health Administration (VHA).

Design, Setting, Participants

From a corpus of 392,244 ABI test reports at 94 VHA facilities during 2015-2017, we selected a random sample of 800 documents for NLP development. Using machine learning, we designed the NLP system to extract ABI and TBI values and laterality (right or left).

Performance was optimized through sequential iterations of 10-fold cross validation and error analysis on 3 sets of 200 documents each, and tested on a final, independent set of 200 documents.

Performance of NLP-extracted ABI and TBI values to identify PAD in a random sample of Veterans undergoing ABI testing was compared to structured chart review.

Exposure

ABI ≤0.9, or TBI ≤0.7 in either right or left limb was used to define PAD at the patient-level

Main Outcome

Precision (or positive predictive value), recall (or sensitivity), F-1 measure (overall measure of accuracy, defined as harmonic mean of precision and recall)

Results

The NLP system had an overall precision of 0.85, recall of 0.93 and F1-measure of 0.89 to correctly identify ABI/TBI values and laterality. The F-1 measure was similar for both ABI and TBI (0.88 to 0.91). Recall was higher for ABI (0.95 to 0.97) while precision was higher for TBI (0.94 to 0.95). Among 261 patients with ABI testing (49% with PAD), the NLP system achieved a positive predictive value of 92.3%, sensitivity of 83.1% and specificity of 93.1% to identify PAD when compared to a structured chart review.

Conclusion

We have successfully developed and validated an NLP system to extract ABI and TBI values which can be used to accurately identify PAD within the VHA. Our findings have broad implications for PAD research and quality improvement efforts in large health systems.
Yet another lockdown? A large-scale study on people’s unwillingness to be confined during the first 5 months of the COVID-19 pandemic in Spain
Authors: Martinez-Garcia Marina , Rabasa Alejandro , Barber Xavier , Polotskaya Kristina , Roomp Kristof , Oliver Nuria
Published: May 2021

Population confinements have been one of the most widely adopted non-pharmaceutical interventions (NPIs) implemented by governments across the globe to help contain the spread of the SARS-CoV-2 virus. While confinement measures have been proven to be effective to reduce the number of infections, they entail significant economic and social costs. Thus, different policy makers and social groups have exhibited varying levels of acceptance of this type of measures. In this context, understanding the factors that determine the willingness of individuals to be confined during a pandemic is of paramount importance, particularly, to policy and decision-makers. In this paper, we study the factors that influence the unwillingness to be confined during the COVID-19 pandemic by means of a large-scale, online population survey deployed in Spain. We apply both quantitative (logistic regression) and qualitative (automatic pattern discovery) methods and consider socio-demographic, economic and psychological factors, together with the 14-day cumulative incidence per 100,000 inhabitants. Our analysis of 109,515 answers to the survey covers data spanning over a 5-month time period to shed light on the impact of the passage of time. We find evidence of pandemic fatigue as the percentage of those who report an unwillingness to be in confinement increases over time; we identify significant gender differences, with women being generally less likely than men to be able to sustain long-term confinement of at least 6 months; we uncover that the psychological impact was the most important factor to determine the willingness to be in confinement at the beginning of the pandemic, to be replaced by the economic impact as the most important variable towards the end of our period of study. Our results highlight the need to design gender and age specific public policies, to implement psychological and economic support programs and to address the evident pandemic fatigue as the success of potential future confinements will depend on the population’s willingness to comply with them.
Social inequalities in COVID-19 vaccine acceptance and uptake for children and adolescents in Montreal, Canada: a cross-sectional study
Authors: McKinnon Britt , Quach Caroline , Dubé Ève , Nguyen Cat Tuong , Zinszer Kate
Published: May 2021

Background

The success of current and prospective COVID-19 vaccine campaigns for children and adolescents will in part depend on the willingness of parents to accept vaccination. This study examined social determinants of parental COVID-19 vaccine acceptance and uptake for children and adolescents.

Methods

We used cross-sectional data from an ongoing COVID-19 cohort study in Montreal, Canada and included all parents of 2 to 18-year-olds who completed an online questionnaire between May 18 and June 26, 2021 (n=809). We calculated child age-adjusted prevalence estimates of vaccine acceptance by parental education, race/ethnicity, birthplace, household income, and neighbourhood, and used multinomial logistic regression to estimate adjusted prevalence differences (aPD) and ratios (aPR). Social determinants of vaccine uptake were estimated for the vaccine-eligible sample of 12 to 18 year-olds (n=306).

Results

Intention to vaccinate children against COVID-19 was high, with only 12.4% of parents unlikely to have their child vaccinated. Parents with younger children were less likely to accept vaccination, as were those from lower-income households, racialized groups, and those born outside Canada. The percent of parents whose child was vaccinated or very likely to be vaccinated was 18.4 percentage points lower among those with annual household incomes <$100,000 vs. ≥$150,000 (95% CI: 10.1 to 26.7). Racialized parents reported greater unwillingness to vaccinate compared to White parents (aPD=10.3; 95% CI: 1.5, 19.1). Vaccine-eligible adolescents from the most deprived neighbourhood were half as likely to be vaccinated compared to those from the least deprived neighbourhood (aPR = 0.48; 95% CI: 0.18 to 0.77).

Interpretation

This study identified marked social inequalities in COVID-19 vaccine acceptance and uptake for children and adolescents. Efforts are needed to reach disadvantaged and marginalized populations with tailored strategies that promote informed decision making and facilitate access to vaccination.
Association of Obesity with COVID-19 Severity and Mortality: A Systemic Review and Meta-Regression
Authors: Singh Romil , Rathore Sawai Singh , Khan Hira , Karale Smruti , Bhurwal Abhishek , Tekin Aysun , Jain Nirpeksh , Mehra Ishita , Anand Sohini , Reddy Sanjana , Sidhu Guneet Singh , Panagopoulos Anastasios , Pattan Vishwanath , Kashyap Rahul , Bansal Vikas
Published: May 2021

Objective

To estimate the association of obesity with severity (defined as use of invasive mechanical ventilation or intensive care unit admission) and all-cause mortality in coronavirus disease 2019 (COVID-19) patients.

Patients and Methods

A systematic search was conducted from inception of COVID-19 pandemic through January 31st, 2021 for full-length articles focusing on the association of increased BMI/ Obesity and outcome in COVID-19 patients with help of various databases including Medline (PubMed), Embase, Science Web, and Cochrane Central Controlled Trials Registry. Preprint servers such as BioRxiv, MedRxiv, ChemRxiv, and SSRN were also scanned. Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines were used for study selection and data extraction. The severity in hospitalized COVID-19 patients, such as requirement of invasive mechanical ventilation and intensive care unit admission with high BMI/ Obesity was the chief outcome. While all-cause mortality in COVID-19 hospitalized patients with high BMI/ Obesity was the secondary outcome.

Results

A total of 576,784 patients from 100 studies were included in this meta-analysis. Being obese was associated with increased risk of severe disease (RR=1.46, 95% CI 1.34-1.60, p<0.001, I2= 92 %). Similarly, high mortality was observed in obese patients with COVID-19 disease (RR=1.12, 95% CI 1.06-1.19, p<0.001, I2= 88%). In a multivariate meta-regression on severity outcome, the covariate of female gender, pulmonary disease, diabetes, older age, cardiovascular diseases, and hypertension was found to be significant and explained R2= 50% of the between-study heterogeneity for severity. Similarly, for mortality outcome, covariate of female gender, proportion of pulmonary disease, diabetes, hypertension, and cardiovascular diseases were significant, these covariates collectively explained R2=53% of the between-study variability for mortality.

Conclusions

Our findings suggest that obesity is significantly associated with increased severity and higher mortality among COVID-19 patients. Therefore, the inclusion of obesity or its surrogate body mass index in prognostic scores and streamlining the management strategy and treatment guidelines to account for the impact of obesity in patient care management is recommended.
Emergent population activity in metric-free and metric networks of neurons with stochastic spontaneous spikes and dynamic synapses
Authors: Zendrikov Dmitrii , Paraskevov Alexander
Published: May 2021

We show that networks of excitatory neurons with stochastic spontaneous spiking activity and short-term synaptic plasticity can exhibit spontaneous repetitive synchronization in so-called population spikes. The major reason for this is that synaptic plasticity nonlinearly modulates the interaction between neurons. For large-scale two-dimensional networks, where the connection probability decreases exponentially with increasing distance between the neurons resulting in a small-world network connectome, a population spike occurs in the form of circular traveling waves diverging from seemingly non-stationary nucleation sites. The latter is in drastic contrast to the case of networks with a fixed fraction of steady pacemaker neurons, where the set of a few spontaneously formed nucleation sites is stationary. Despite the spatial non-stationarity of their nucleation, population spikes may occur surprisingly regularly. From a theoretical viewpoint, these findings show that the regime of nearly-periodic population spikes, which mimics respiratory rhythm, can occur strictly without stochastic resonance. In addition, the observed spatiotemporal effects serve as an example of transient chimera patterns.
Dietary restriction andclockdelay eye aging to extend lifespan inD. melanogaster
Authors: Hodge Brian A. , Meyerhof Geoffrey T. , Katewa Subhash D. , Lian Ting , Lau Charles , Bar Sudipta , Leung Nicole , Li Menglin , Li-Kroeger David , Melov Simon , Schilling Birgit , Montell Craig , Kapahi Pankaj
Published: May 2021

Many vital processes in the eye are under circadian regulation, and circadian dysfunction has emerged as a potential driver of eye aging. Dietary restriction is one of the most robust lifespan-extending therapies and amplifies circadian rhythms with age. Herein, we demonstrate that dietary restriction extends lifespan inD. melanogasterby promoting circadian homoeostatic processes that protect the visual system from age- and light- associated damage. Disrupting circadian rhythms in the eye by inhibiting the transcription factor, Clock (CLK), or CLK-output genes, accelerated visual senescence, induced a systemic immune response, and shortened lifespan. Flies subjected to dietary restriction were protected from the lifespan-shortening effects of photoreceptor activation. Inversely, photoreceptor inactivation, achieved via mutating rhodopsin or housing flies in constant darkness, primarily extended lifespan in flies reared on a high-nutrient diet. Our findings establish the eye as a diet-sensitive modulator of lifespan and indicate that vision is an antagonistically pleiotropic process that contributes to organismal aging.
Fish diversity in a doubly landlocked country - a description of the fish fauna of Uzbekistan using DNA barcoding
Authors: Sheraliev Bakhtiyor , Peng Zuogang
Published: May 2021

Uzbekistan is one of two doubly landlocked countries in the world, where all rivers are endorheic basins. Although fish diversity is relatively poor in Uzbekistan compared to other regions, the fish fauna of the region has not yet been fully studied. The aim of this study was to establish a reliable barcoding reference database for fish in Uzbekistan. A total of 666 specimens, belonging to 59 species within 39 genera, 16 families, and 9 orders, were subjected to polymerase chain reaction amplification in the barcode region and sequenced. The length of the 666 barcodes was 682 bp. The average K2P distances within species, genera, and families were 0.22%, 6.33%, and 16.46%, respectively. The average interspecific distance was approximately 28.8 times higher than the mean intraspecific distance. The Barcode Index Number (BIN) discordance report showed that 666 specimens represented 55 BINs, of which five were singletons, 45 were taxonomically concordant, and five were taxonomically discordant. The barcode gap analysis demonstrated that 89.3% of the fish species examined could be discriminated by DNA barcoding. These results provide new insights into fish diversity in the inland waters of Uzbekistan and can provide a basis for the development of further studies on fish fauna.