bluuebunny/crossref_metadata_2025_split huggingface dataset:
Factors Associated With Non-enrollment of Center-Based Cardiovascular Rehabilitation Program Among Transient Ischemic Attack or Mild Stroke Patients
Authors: Meng Guangxia , Qazi Hammad , Chen Helen 
Published: November 2020

Purpose:
Cardiovascular rehabilitation programs (CRPs) are effective in secondary stroke prevention, yet the enrollment rate is suboptimal. This study aims to identify demographic and clinical factors and patient-reported reasons for non-enrollment in a center-based outpatient CRP among patients with transient ischemic attack (TIA) or mild stroke.

Methods:
This mixed-method retrospective chart review was conducted in an outpatient CRP affiliated with a tertiary care hospital in Canada from January 2009 to October 2017. A total of 621 patients with TIA or mild stroke were included. Multiple logistic regression was used to determine the relationship between demographic and clinical predictors with non-enrollment. A thematic analysis of multidisciplinary progress notes was done for the non-enrollment subgroup of patients to understand the patient-reported reasons.

Results:
The non-enrollment rate was 42%. Travel distance to CRP (OR = 1.024; 95% CI, 1.010-1.038), age (OR = 1.023; 95% CI, 1.004-1.042), and current smoking status (OR = 1.935; 95% CI, 1.230-3.042) were associated with non-enrollment. The patient-reported reasons for non-enrollment were occurrence of new medical events and comorbidities, their perceptions of health and CRP, transportation, work/time conflict, and distance.

Conclusions:
This study found that patients with TIA or mild stroke who were older, lived farther from the CRP center, or were current smokers were less likely to enroll in a CRP. The present findings may help clinicians identify patients unlikely to enroll in a CRP and allow the implementation of interventions focused on health education and physical activity to improve enrollment. Future research should validate these factors in multiple settings using prospective mixed methods so that interventions can be developed to address non-enrollment in the CRP.
Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity
Authors: Mishra Anusha , Hall Catherine N. , Howarth Clare , Freeman Ralph D. 
Published: November 2020

Functional neuroimaging using MRI relies on measurements of blood oxygen level-dependent (BOLD) signals from which inferences are made about the underlying neuronal activity. This is possible because neuronal activity elicits increases in blood flow via neurovascular coupling, which gives rise to the BOLD signal. Hence, an accurate interpretation of what BOLD signals mean in terms of neural activity depends on a full understanding of the mechanisms that underlie the measured signal, including neurovascular and neurometabolic coupling, the contribution of different cell types to local signalling, and regional differences in these mechanisms. Furthermore, the contributions of systemic functions to cerebral blood flow may vary with ageing, disease and arousal states, with regard to both neuronal and vascular function. In addition, recent developments in non-invasive imaging technology, such as high-field fMRI, and comparative inter-species analysis, allow connections between non-invasive data and mechanistic knowledge gained from invasive cellular-level studies. Considered together, these factors have immense potential to improve BOLD signal interpretation and bring us closer to the ultimate purpose of decoding the mechanisms of human cognition. This theme issue covers a range of recent advances in these topics, providing a multidisciplinary scientific and technical framework for future work in the neurovascular and cognitive sciences.
This article is part of the theme issue ‘Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity'.
The thermodynamics of thinking: connections between neural activity, energy metabolism and blood flow
Authors: Buxton Richard B. 
Published: November 2020

Several current functional neuroimaging methods are sensitive to cerebral metabolism and cerebral blood flow (CBF) rather than the underlying neural activity itself. Empirically, the connections between metabolism, flow and neural activity are complex and somewhat counterintuitive: CBF and glycolysis increase more than seems to be needed to provide oxygen and pyruvate for oxidative metabolism, and the oxygen extraction fraction is relatively low in the brain anddecreaseswhen oxygen metabolism increases. This work lays a foundation for the idea that this unexpected pattern of physiological changes is consistent with basic thermodynamic considerations related to metabolism. In the context of this thermodynamic framework, the apparent mismatches in metabolic rates and CBF are related to preserving the entropy change of oxidative metabolism, specifically the O2/CO2ratio in the mitochondria. However, the mechanism supporting this CBF response is likely not owing to feedback from a hypothetical O2sensor in tissue, but rather is consistent with feed-forward control by signals from both excitatory and inhibitory neural activity. Quantitative predictions of the thermodynamic framework, based on models of O2and CO2transport and possible neural drivers of CBF control, are in good agreement with a wide range of experimental data, including responses to neural activation, hypercapnia, hypoxia and high-altitude acclimatization.This article is part of the theme issue ‘Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity’.
Cross-species neuroscience: closing the explanatory gap
Authors: Barron Helen C. , Mars Rogier B. , Dupret David , Lerch Jason P. , Sampaio-Baptista Cassandra 
Published: November 2020

Neuroscience has seen substantial development in non-invasive methods available for investigating the living human brain. However, these tools are limited to coarse macroscopic measures of neural activity that aggregate the diverse responses of thousands of cells. To access neural activity at the cellular and circuit level, researchers instead rely on invasive recordings in animals. Recent advances in invasive methods now permit large-scale recording and circuit-level manipulations with exquisite spatio-temporal precision. Yet, there has been limited progress in relating these microcircuit measures to complex cognition and behaviour observed in humans. Contemporary neuroscience thus faces an explanatory gap between macroscopic descriptions of the human brain and microscopic descriptions in animal models. To close the explanatory gap, we propose adopting a cross-species approach. Despite dramatic differences in the size of mammalian brains, this approach is broadly justified by preserved homology. Here, we outline a three-armed approach for effective cross-species investigation that highlights the need to translate different measures of neural activity into a common space. We discuss how a cross-species approach has the potential to transform basic neuroscience while also benefiting neuropsychiatric drug development where clinical translation has, to date, seen minimal success.
This article is part of the theme issue ‘Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity’.
Regional variation in neurovascular coupling and why we still lack a Rosetta Stone
Authors: Ekstrom Arne D. 
Published: November 2020

Functional magnetic resonance imaging (fMRI) is the dominant tool in cognitive neuroscience although its relation to underlying neural activity, particularly in the human brain, remains largely unknown. A major research goal, therefore, has been to uncover a ‘Rosetta Stone’ providing direct translation between the blood oxygen level-dependent (BOLD) signal, the local field potential and single-neuron activity. Here, I evaluate the proposal that BOLD signal changes equate to changes in gamma-band activity, which in turn may partially relate to the spiking activity of neurons. While there is some support for this idea in sensory cortices, findings in deeper brain structures like the hippocampus instead suggest both regional and frequency-wise differences. Relatedly, I consider four important factors in linking fMRI to neural activity: interpretation of correlations between these signals, regional variability in local vasculature, distributed neural coding schemes and varying fMRI signal quality. Novel analytic fMRI techniques, such as multivariate pattern analysis (MVPA), employ the distributed patterns of voxels across a brain region to make inferences about information content rather than whether a small number of voxels go up or down relative to baseline in response to a stimulus. Although unlikely to provide a Rosetta Stone, MVPA, therefore, may represent one possible means forward for better linking BOLD signal changes to the information coded by underlying neural activity.
This article is part of the theme issue ‘Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity’.
Forging a path to mesoscopic imaging success with ultra-high field functional magnetic resonance imaging
Authors: Weldon Kimberly B. , Olman Cheryl A. 
Published: November 2020

Functional magnetic resonance imaging (fMRI) studies with ultra-high field (UHF, 7+ Tesla) technology enable the acquisition of high-resolution images. In this work, we discuss recent achievements in UHF fMRI at the mesoscopic scale, on the order of cortical columns and layers, and examine approaches to addressing common challenges. As researchers push to smaller and smaller voxel sizes, acquisition and analysis decisions have greater potential to degrade spatial accuracy, and UHF fMRI data must be carefully interpreted. We consider the impact of acquisition decisions on the spatial specificity of the MR signal with a representative dataset with 0.8 mm isotropic resolution. We illustrate the trade-offs in contrast with noise ratio and spatial specificity of different acquisition techniques and show that acquisition blurring can increase the effective voxel size by as much as 50% in some dimensions. We further describe how different sources of degradations to spatial resolution in functional data may be characterized. Finally, we emphasize that progress in UHF fMRI depends not only on scientific discovery and technical advancement, but also on informal discussions and documentation of challenges researchers face and overcome in pursuit of their goals.This article is part of the theme issue ‘Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity’.
Acinetobacter lanii sp. nov., Acinetobacter shaoyimingii sp. nov. and Acinetobacter wanghuae sp. nov., isolated from faeces of Equus kiang
Authors: Zhu Wentao , Dong Kui , Yang Jing , Lu Shan , Lai Xin-He , Pu Ji , Jin Dong , Huang Yuyuan , Zhang Sihui , Zhou Juan , Huang Ying , Xu Jianguo 
Published: November 2020

Six aerobic, non-motile, non-haemolytic, Gram-stain-negative, oxidase-negative strains (185T, 187, 323-1T, 194, dk386T and dk771) were recovered from different faecal samples of Equus kiang on the Qinghai–Tibet Plateau. In the 16S rRNA gene sequences, one strain pair, 185T/187, shared highest similarity to

Acinetobacter equi

114T (97.9 %), and the other two (323-1T/194 and dk771T/dk386) to

Acinetobacter harbinensis

CGMCC 1.12528T (98.6 and 97.0 %, respectively). Phylogenomic tree analysis showed that these six strains formed three separate clades in the genus

Acinetobacter

. Digital DNA–DNA hybridization values of each pair of the isolates with all members of the genus

Acinetobacter

were far below 70 %. The main cellular fatty acids of all six strains were C18 : 1
ω9c, C16 : 0 and summed feature 3 (C16 : 1
ω7c/C16 : 1
ω6c). Q-9 was the predominant respiratory quinone for strains 185T, 323-1T and dk386T. The major polar lipids were diphosphatidylglycerol, phosphatidylethanolamine and phosphatidylglycerol. Based on the genotypic, phenotypic and biochemical analyses, these six strains represent three novel species of the genus

Acinetobacter

, for which the names Acinetobacter lanii sp. nov., Acinetobacter shaoyimingii sp. nov. and Acinetobacter wanghuae sp. nov. are proposed. The type strains are 185T (=CGMCC 1.13636T=JCM 33607T), 323-1T (=CGMCC 1.13940T=JCM 33608T) and dk386T (=CGMCC 1.16589T=JCM 33592T), respectively.
Mutations in TP53 and other heterogeneous genes help to distinguish metastases from new primary malignancies
Authors: Prall Owen W. J. , Vedururu Ravikiran , Lau Peter , Fellowes Andrew 
Published: November 2020

ABSTRACTBackgroundDistinguishing metastases from new primary malignancies or vice versa is important because misclassification can result in inappropriate management. However, for some cases this distinction can be challenging, particularly for squamous cell carcinomas in which the usual surgical pathology approach, predominantly morphology and immunohistochemistry, are frequently non-contributory. We analysed tumor-associated mutations in order to determine whether they could help with this diagnostic dilemma.MethodsMutations in specific genes were identified with cBioPortal, a large publically available tumor sequence data set. Genes were selected based upon either their high overall prevalence of mutation, or their inclusion in an in-house tumor sequencing set. Tumor types analysed included various common adenocarcinomas, squamous cell carcinomas from multiple sites, urothelial carcinoma and melanoma. Individual mutations and sets of mutations within gene cohorts were compared by their diversity (or heterogeneity) index, prevalence and cumulative prevalence. We demonstrated the utility of this method by performing in-house sequencing of candidate genes in tumors from three patients for which morphology and immunohistochemistry were unable to distinguish between a metastasis and a new primary malignancy.ResultsSequence data from relatively small cohorts of candidate genes readily identified highly diverse, low prevalence mutation profiles in most common malignancies including squamous cell carcinomas. The diversity index predicted the likelihood of an identical mutation profile occurring in an unrelated tumor. High yield gene cohorts could be predicted based on the primary tumor type. Most cohorts included TP53 due to both its high mutation prevalence and high mutation index of diversity. Identical, low prevalence mutations in multiple tumors from patients in the three case studies provided strong diagnostic certainty for metastases rather than new primary malignancies.ConclusionsMost common tumors, including squamous cell carcinomas, have a readily identifiable mutation profiles that occur at a sufficiently low prevalence to effectively barcode or fingerprint the tumor. An identical mutation profile in a primary tumor and a new lesion provides strong evidence for a metastasis and effectively excludes a new primary malignancy, providing diagnostic confidence and aiding clinical management certainty.
A hidden Markov model reliably characterizes ketamine-induced spectral dynamics in macaque LFP and human EEG
Authors: Garwood Indie C. , Chakravarty Sourish , Donoghue Jacob , Kahali Pegah , Chamadia Shubham , Akeju Oluwaseun , Miller Earl K. , Brown Emery N. 
Published: November 2020

AbstractKetamine is an NMDA receptor antagonist commonly used to maintain general anesthesia. At anesthetic doses, ketamine causes bursts of 30-50 Hz oscillations alternating with 0.1 to 10 Hz oscillations. These dynamics are readily observed in local field potentials (LFPs) of non-human primates (NHPs) and electroencephalogram (EEG) recordings from human subjects. However, a detailed statistical analysis of these dynamics has not been reported. We characterize ketamine’s neural dynamics using a hidden Markov model (HMM). The HMM observations are sequences of spectral power in 10 Hz frequency bands between 0 to 50 Hz, where power is averaged within each band and scaled between 0 and 1. We model the observations as realizations of multivariate beta probability distributions that depend on a discrete-valued latent state process whose state transitions obey Markov dynamics. Using an expectation-maximization algorithm, we fit this beta-HMM to LFP recordings from 2 NHPs, and separately, to EEG recordings from 9 human subjects who received anesthetic doses of ketamine. Together, the estimated beta-HMM parameters and optimal state trajectory revealed an alternating pattern of states characterized primarily by gamma burst and slow oscillation activity, as well as intermediate states in between. The mean duration of the gamma burst state was 2.5s([1.9,3.4]s) and 1.2s([0.9,1.5]s) for the two NHPs, and 2.7s([1.9,3.8]s) for the human subjects. The mean duration of the slow oscillation state was 1.6s([1.1,2.5]s) and 0.7s([0.6,0.9]s) for the two NHPs, and 2.8s([1.9,4.3]s) for the human subjects. Our beta-HMM framework provides a useful tool for experimental data analysis. Our characterizations of the gamma-burst process offer detailed, quantitative constraints that can inform the development of rhythm-generating neuronal circuit models that give mechanistic insights into this phenomenon and how ketamine produces altered states of arousal.
Assessing the magnitude of and factors associated to demand for long acting reversible and permanent contraceptive methods among sexually active women in Kenya
Authors: Waithaka Michael W. , Gichangi Peter , Thiongo Mary 
Published: November 2020

AbstractIntroductionThough there has been an increase in use of long acting and permanent methods of contraception (LAPMs) globally over the last decade, the rates of unintended pregnancy still remain high. In Sub-Saharan African and especially in Kenya, while there has been increase in the uptake of LAPMs over the past years, there are limited recently available evidences on the real magnitude, recent trends and factors associated to demand for LAPMs among sexually active women in the reproductive age.MethodsIn this study, we used data from seven survey rounds (2014 to 2018) of a nationally representative Performance Monitoring and Accountability 2020 (PMA2020) household and female survey. PMA2020 survey is based on a multi-stage cluster sample design to draw a probability sample of households and eligible females. In this analysis, both descriptive and inferential statistics were used for data analysis and interpretations. Statistical significance was considered for p-values <0.05. STATA 16.0 software was used for all analyses.ResultsAmong the 17,455 sexually active women in the reproductive age included in this study, 83.1% had demand for LAPMs. The total demand for LAPMs significantly decreased from 85.0% in 2014 to 81.0% in 2018. Age of the respondents, marital status, parity, rural/urban residence, county of residence and access to Family Planning/contraceptives information via media in the last 12 months were significantly associated with demand for LAPMs.ConclusionThe total demand for LAPMs among sexually active women in Kenya is high, with the bigger share of the demand being unmet. Targeted programs to satisfy the existing demand of LAPMs and address the issue of unmet need for LAPMs should be put in place to ensure no woman is left behind. Similarly, programmers/advocates should utilize the locally available channels e.g. the media to generate new demand and overturn the decreasing demand for LAPMs.STRENGTHS AND LIMITATIONS OF THIS STUDYThe nationally representative Performance Monitoring and Accountability 2020 (PMA2020) surveys are modelled on the insight from Demographic and Health Survey (DHS).PMA2020 uses standardized questionnaires (with questions extracted from DHS which have been validated and are extensively used in FP programs) to gather data about households and individual females that are comparable across program countries and consistent with existing national surveys.There are strengths to the PMA2020 survey which include inclusion of a large sample of women, use of data collectors without medical training and real-time data collection with sufficient controls for quality assurance.There are some limitations to consider when interpreting the data. Some outputs of this study utilized pooled data from seven-rounds of PMA2020 survey.
Associations between solid fuel use and early child development among 3 to 4 years old children in Bangladesh: Evidence from a nationally representative survey
Authors: Rana Juwel , Gutierrez Patricia Luna , Haque Syed Emdadul , Nazif-Muñoz José Ignacio , Mitra Dipak K. , Oulhote Youssef 
Published: November 2020

AbstractBackgroundHousehold Air Pollution (HAP) from solid fuel use (SFU) may have impacts on children’s health in low-resources countries. Despite these potential health effects, SFU is still highly prevalent in Bangladesh.ObjectivesThis study was conducted to assess the associations between SFU and early childhood development index (ECDI) among under-five children in Bangladesh and explore the potential effect modification by sex and urbanicity.Materials and methodsThis cross-sectional study used Bangladesh Multiple Indicator Cluster Survey (MICS) 2019, a nationally representative survey data collected by UNICEF from all 64 districts in Bangladesh. The ECDI consisted of ten different items across four developmental domains: literacy-numeracy, physical, social-emotional development, and learning skills in the early years of life (36 to 59 months). A total of 9,395 children aged 36 to 59 months were included in this analysis. We used multilevel Poisson regression models with a robust variance where SFU was a proxy indicator for HAP exposure.ResultsChildren exposed to SFU were 1.47 times more likely to be not developmentally on track (95% CI: 1.25, 1.73; <0.001)compared to children with no SFU exposure. Two sub-domains explained these associations, SFU was significantly associated with socio-emotional development (prevalence ratio [PR]: 1.17; 95% CI: 1.01, 1.36; p=0.035), and learning-cognitive development (PR: 1.90; 95% CI: 1.39, 2.60; p<0.001). Associations between SFU and ECDI were not significantly different (p-difference=0.210) between girls (PR: 1.64; 95% CI: 1.31, 2.07) and boys (PR: 1.37; 95% CI: 1.13, 1.65). Likewise, urbanicity did not modify the associations between SFU and ECDI outcomes.ConclusionBangladeshi children aged 36-59 months exposed to SFU exhibited delays in childhood development compared to unexposed children. Public health policies should promote a better early life environment for younger children to meet their developmental milestones by reducing the high burden of HAP exposure in low-resource settings where most disadvantaged kids struggle to reach their full developmental potentials.