scholarly journals Apt interpretation of comprehensive lipoprotein data in large-scale epidemiology – disclosure of fundamental structural and metabolic relationships

2021 ◽  
Author(s):  
Mika Ala-Korpela ◽  
Siyu Zhao ◽  
Marjo-Riitta Järvelin ◽  
Ville-Petteri Mäkinen ◽  
Pauli Ohukainen
Keyword(s):  
Particle Size ◽  
Lipid Composition ◽  
Apolipoprotein B ◽  
Large Scale ◽  
Lipoprotein Metabolism ◽  
Lipoprotein Subclass ◽  
Lipoprotein Subclasses ◽  
Size Dependent ◽  
Log Linear ◽  
The Relationship

AbstractAimsQuantitative lipoprotein analytics by NMR spectroscopy is currently commonplace in large-scale studies. One methodology has become widespread and is currently being utilised also in large biobanks. It allows comprehensive characterisation of 14 lipoprotein subclasses, clinical lipids, apolipoprotein A-I and B. The details of these data are conceptualised here in relation to lipoprotein metabolism with particular attention to the fundamental characteristics of subclass particle numbers, lipid concentrations and compositional measures.Methods and ResultsThe NMR methodology was applied to fasting serum samples from Northern Finland Birth Cohort 1966 and 1986 with 5,651 and 5,605 participants, respectively. All results were highly coherent between the cohorts. Circulating lipid concentrations in a particular lipoprotein subclass arise predominantly as the result of the circulating number of those subclass particles. The spherical lipoprotein particle shape, with a radially oriented surface monolayer, imposes size-dependent biophysical constraints for the lipid composition of individual subclass particles and inherently restricts the accommodation of metabolic changes via compositional modifications. The new finding that the relationship between lipoprotein subclass particle concentrations and the particle size is log-linear reveal that circulating lipoprotein particles are also under rather strict metabolic constraints for both their absolute and relative concentrations.ConclusionThe fundamental structural and metabolic relationships between lipoprotein subclasses elucidated in this study empower detailed interpretation of lipoprotein metabolism. Understanding the intricate details of these extensive data is consequential for the precise interpretation of novel therapeutic opportunities and for fully utilising the potential of forthcoming analyses of genetic and metabolic data in extensive biobanks.One-sentence SummaryNMR spectroscopy facilitates comprehensive characterisation of lipoprotein subclass metabolism and offers additional value to epidemiology, genetics and pharmacology in large-scale studies and biobanks.Key MessagesThe circulating particle number of a lipoprotein subclass is the defining measure for its lipid concentrations; the particle lipid composition is only in a minor role. The relationship between circulating lipoprotein subclass particle concentrations and the particle size is log-linear.The overall structure of lipoprotein subclass particles with a spherical shape and an oriented surface monolayer poses strong size-dependent biomolecular constraints for their lipid composition.The circulating lipoprotein subclass particle concentrations in humans are metabolically constraint for both elemental absolute and relative concentration ranges.The smallest HDL particle concentrations are negatively associated with those of large HDL and generally the associations of the smallest HDL particles are similar to those of apolipoprotein B-containing particles.The apolipoprotein B-containing particles constitute less than 10% of all lipoprotein particles but carry around two thirds of circulating lipoprotein lipids. LDL and IDL particles amount to almost 90% of all apolipoprotein B-containing particles.The supplemental role of lipoprotein subclass data in cardiometabolic risk assessment is slight.In the current era of biobanks and big data, the combination of lipoprotein subclass data with drug-target Mendelian randomization analyses provides great scientific synergy, intricate details and potential cost savings in drug development.Graphical abstract / key messages

scholarly journals On the treatment of particulate organic matter sinking in large-scale models of marine biogeochemical cycles

2008 ◽  
Vol 5 (1) ◽  
pp. 55-72 ◽  
Author(s):  
I. Kriest ◽  
A. Oschlies
Keyword(s):  
Particle Size ◽  
Organic Matter ◽  
Water Column ◽  
Size Distribution ◽  
Power Law ◽  
Particulate Organic Matter ◽  
Large Scale ◽  
Regional Patterns ◽  
Size Dependent ◽  
Biogeochemical Models

Abstract. Various functions have been suggested and applied to represent the sedimentation and remineralisation of particulate organic matter (POM) in numerical ocean models. Here we investigate some representations commonly used in large-scale biogeochemical models: a constant sinking speed, a sinking speed increasing with depth, a spectrum of particles with different size and different size-dependent sinking velocities, and a model that assumes a power law particle size distribution everywhere in the water column. The analysis is carried out for an idealised one-dimensional water column, under stationary boundary conditions for surface POM. It focuses on the intrinsic assumptions of the respective sedimentation function and their effect on POM mass, mass flux, and remineralisation profiles. A constant and uniform sinking speed does not appear appropriate for simulations exceeding a few decades, as the sedimentation profile is not consistent with observed profiles. A spectrum of size classes, together with size-dependent sinking and constant remineralisation, causes the sinking speed of total POM to increase with depth. This increase is not strictly linear with depth. Its particular form will further depend on the size distribution of the POM ensemble at the surface. Assuming a power law particle size spectrum at the surface, this model results in unimodal size distributions in the ocean interior. For the size-dependent sinking model, we present an analytic integral over depth and size that can explain regional variations of remineralisation length scales in response to regional patterns in trophodynamic state.

scholarly journals On the treatment of particulate organic matter sinking in large-scale models of marine biogeochemical cycles

2007 ◽  
Vol 4 (4) ◽  
pp. 3005-3040
Author(s):  
I. Kriest ◽  
A. Oschlies
Keyword(s):  
Particle Size ◽  
Organic Matter ◽  
Water Column ◽  
Size Distribution ◽  
Power Law ◽  
Particulate Organic Matter ◽  
Large Scale ◽  
Regional Patterns ◽  
Size Dependent ◽  
Biogeochemical Models

Abstract. Various functions have been suggested and applied to represent the sedimentation and remineralisation of particulate organic matter (POM) in numerical ocean models. Here we investigate some representations commonly used in large-scale biogeochemical models: a constant sinking speed, a sinking speed increasing with depth, a spectrum of particles with different size and different size-dependent sinking velocities, and a model that assumes a power-law particle size distribution everywhere in the water column. The analysis is carried out for an idealised one-dimensional water column, under stationary boundary conditions for surface POM. It focuses on the intrinsic assumptions of the respective sedimentation function and their effect on POM mass, mass flux, and remineralisation profiles. A constant and uniform sinking speed does not appear appropriate for simulations exceeding a few decades, as the sedimentation profile is not consistent with observed profiles. A spectrum of size classes, together with size-dependent sinking and constant remineralisation, causes the sinking speed of total POM to increase with depth. This increase is not strictly linear with depth. Its particular form will further depend on the size distribution of the POM ensemble at the surface. Assuming a power-law particle size spectrum at the surface, this model results in unimodal size distributions in the ocean interior. For the size-dependent sinking model, we present an analytic integral over depth and size that can explain regional variations of remineralisation length scales in response to regional patterns in trophodynamic state.

scholarly journals Influence of Particle Size Distribution on the Critical State of Rockfill

2019 ◽  
Vol 2019 ◽  
pp. 1-7 ◽  
Author(s):  
Gui Yang ◽  
Yang Jiang ◽  
Sanjay Nimbalkar ◽  
Yifei Sun ◽  
Nenghui Li
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Critical State ◽  
Large Scale ◽  
Triaxial Tests ◽  
Power Law Function ◽  
Maximum Particle ◽  
Effect Of Particle Size ◽  
The Relationship

In order to study the effect of particle size distribution on the critical state of rockfill, a series of large-scale triaxial tests on rockfill with different maximum particle sizes were performed. It was observed that the intercept and gradient of the critical state line in the e−p′ plane decreased as the grading broadened with the increase in particle size while the gradient of the critical state line in the p′−q plane increased as the particle size increased. A power law function is found to appropriately describe the relationship between the critical state parameters and maximum particle size of rockfill.

Relationship between total plasma homocysteine and the risk of aneurysms – a meta-analysis

VASA ◽  
2020 ◽  
pp. 1-6
Author(s):  
Hanji Zhang ◽  
Dexin Yin ◽  
Yue Zhao ◽  
Yezhou Li ◽  
Dejiang Yao ◽  
...  
Keyword(s):  
Large Scale ◽  
Meta Analysis ◽  
Single Species ◽  
Total Plasma ◽  
Control Groups ◽  
Randomized Controlled ◽  
Randomized Controlled Studies ◽  
The Difference ◽  
The Relationship ◽  
Healthy Participants

Summary: Our meta-analysis focused on the relationship between homocysteine (Hcy) level and the incidence of aneurysms and looked at the relationship between smoking, hypertension and aneurysms. A systematic literature search of Pubmed, Web of Science, and Embase databases (up to March 31, 2020) resulted in the identification of 19 studies, including 2,629 aneurysm patients and 6,497 healthy participants. Combined analysis of the included studies showed that number of smoking, hypertension and hyperhomocysteinemia (HHcy) in aneurysm patients was higher than that in the control groups, and the total plasma Hcy level in aneurysm patients was also higher. These findings suggest that smoking, hypertension and HHcy may be risk factors for the development and progression of aneurysms. Although the heterogeneity of meta-analysis was significant, it was found that the heterogeneity might come from the difference between race and disease species through subgroup analysis. Large-scale randomized controlled studies of single species and single disease species are needed in the future to supplement the accuracy of the results.

New ''Cold War''

2020 ◽  
pp. 27-34
Author(s):  
Vladimir Batiuk
Keyword(s):  
Cold War ◽  
Nuclear Weapons ◽  
Armed Conflict ◽  
Large Scale ◽  
Arms Race ◽  
Ideological Struggle ◽  
Nuclear Arms Race ◽  
The Cold War ◽  
The Relationship ◽  
Nuclear Arms

In this article, the ''Cold War'' is understood as a situation where the relationship between the leading States is determined by ideological confrontation and, at the same time, the presence of nuclear weapons precludes the development of this confrontation into a large-scale armed conflict. Such a situation has developed in the years 1945–1989, during the first Cold War. We see that something similar is repeated in our time-with all the new nuances in the ideological struggle and in the nuclear arms race.

Investigating Diseases and Chemicals in COVID-19 Literature with Text Mining (Preprint)

2020 ◽  
Author(s):  
Amir Karami ◽  
Brandon Bookstaver ◽  
Melissa Nolan
Keyword(s):  
Text Mining ◽  
Literature Review ◽  
Topic Modeling ◽  
Large Scale ◽  
Clinical Manifestations ◽  
International Health ◽  
Research Papers ◽  
Strategic Plans ◽  
Funding Agencies ◽  
The Relationship

BACKGROUND The COVID-19 pandemic has impacted nearly all aspects of life and has posed significant threats to international health and the economy. Given the rapidly unfolding nature of the current pandemic, there is an urgent need to streamline literature synthesis of the growing scientific research to elucidate targeted solutions. While traditional systematic literature review studies provide valuable insights, these studies have restrictions, including analyzing a limited number of papers, having various biases, being time-consuming and labor-intensive, focusing on a few topics, incapable of trend analysis, and lack of data-driven tools. OBJECTIVE This study fills the mentioned restrictions in the literature and practice by analyzing two biomedical concepts, clinical manifestations of disease and therapeutic chemical compounds, with text mining methods in a corpus containing COVID-19 research papers and find associations between the two biomedical concepts. METHODS This research has collected papers representing COVID-19 pre-prints and peer-reviewed research published in 2020. We used frequency analysis to find highly frequent manifestations and therapeutic chemicals, representing the importance of the two biomedical concepts. This study also applied topic modeling to find the relationship between the two biomedical concepts. RESULTS We analyzed 9,298 research papers published through May 5, 2020 and found 3,645 disease-related and 2,434 chemical-related articles. The most frequent clinical manifestations of disease terminology included COVID-19, SARS, cancer, pneumonia, fever, and cough. The most frequent chemical-related terminology included Lopinavir, Ritonavir, Oxygen, Chloroquine, Remdesivir, and water. Topic modeling provided 25 categories showing relationships between our two overarching categories. These categories represent statistically significant associations between multiple aspects of each category, some connections of which were novel and not previously identified by the scientific community. CONCLUSIONS Appreciation of this context is vital due to the lack of a systematic large-scale literature review survey and the importance of fast literature review during the current COVID-19 pandemic for developing treatments. This study is beneficial to researchers for obtaining a macro-level picture of literature, to educators for knowing the scope of literature, to journals for exploring most discussed disease symptoms and pharmaceutical targets, and to policymakers and funding agencies for creating scientific strategic plans regarding COVID-19.

Simulation on Extrusion Comminution Model of Roller Press

2010 ◽  
Vol 156-157 ◽  
pp. 1702-1707
Author(s):  
Xiang Wen Cheng ◽  
Jinchao Liu ◽  
Qi Zhi Ding ◽  
Li Ming Song ◽  
Zhan Lin Wang
Keyword(s):  
Experimental Data ◽  
Particle Size ◽  
Field Experiments ◽  
Size Ratio ◽  
Optimum Operating ◽  
Extrusion Force ◽  
Particle Size Ratio ◽  
Small Constant ◽  
Working Parameters ◽  
The Relationship

How to predict the relationship among particle size and among product size, to establish the relationship between the granularity and working parameters in the process of grinding and to determine the optimum operating parameters. With proposing BS squeeze crush model by L. Bass and the idea of roll surface division as the material uneven extrusion force are adopted. Based on field experiments the experimental data is analyzed, the select function and the breakage functions are fitted with MATLAB software, and obtaining their model. The comminution model is determined by the roller division. We obtain the model parameter through the experimental data. Through model analysis shows: the relationship between particle breakage and energy absorption, namely the smaller size of the same power, the lower broken; the breakage diminishes with the decrease of particle size ratio and it will be tending to a small constant when the smaller particle size ratio. The breakage functions rapidly decrease within ratio of between 0.2-0.7. This shows: the energy consumption will rapidly increase when the particle size of less than 0.2 in broken; the selection diminish with the decrease of particle size. Pressure (8-9MPa) should be the most appropriate value.

scholarly journals Strategic resources and smallholder performance at the bottom of the pyramid

2019 ◽  
Vol 22 (3) ◽  
pp. 365-380 ◽  
Author(s):  
Matthias Olthaar ◽  
Wilfred Dolfsma ◽  
Clemens Lutz ◽  
Florian Noseleit
Keyword(s):  
Large Scale ◽  
Business Environment ◽  
Agricultural Economics ◽  
Local Market ◽  
Bottom Of The Pyramid ◽  
Fine Grained ◽  
Strategic Resources ◽  
Relative Contribution ◽  
The Relationship ◽  
Resource Based Theory

In a competitive business environment at the Bottom of the Pyramid smallholders supplying global value chains may be thought to be at the whims of downstream large-scale players and local market forces, leaving no room for strategic entrepreneurial behavior. In such a context we test the relationship between the use of strategic resources and firm performance. We adopt the Resource Based Theory and show that seemingly homogenous smallholders deploy resources differently and, consequently, some do outperform others. We argue that the ‘resource-based theory’ results in a more fine-grained understanding of smallholder performance than approaches generally applied in agricultural economics. We develop a mixed-method approach that allows one to pinpoint relevant, industry-specific resources, and allows for empirical identification of the relative contribution of each resource to competitive advantage. The results show that proper use of quality labor, storage facilities, time of selling, and availability of animals are key capabilities.

scholarly journals Lack of an association between gallstone disease and bilirubin levels with risk of colorectal cancer: a Mendelian randomisation analysis

2021 ◽  
Author(s):  
Richard Culliford ◽  
Alex J. Cornish ◽  
Philip J. Law ◽  
Susan M. Farrington ◽  
Kimmo Palin ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Large Scale ◽  
Causal Effect ◽  
Gallstone Disease ◽  
Epidemiological Studies ◽  
Mendelian Randomisation ◽  
Linear Relationships ◽  
Potential Risk Factors ◽  
The Relationship ◽  
Circulating Levels

Abstract Background Epidemiological studies of the relationship between gallstone disease and circulating levels of bilirubin with risk of developing colorectal cancer (CRC) have been inconsistent. To address possible confounding and reverse causation, we examine the relationship between these potential risk factors and CRC using Mendelian randomisation (MR). Methods We used two-sample MR to examine the relationship between genetic liability to gallstone disease and circulating levels of bilirubin with CRC in 26,397 patients and 41,481 controls. We calculated the odds ratio per genetically predicted SD unit increase in log bilirubin levels (ORSD) for CRC and tested for a non-zero causal effect of gallstones on CRC. Sensitivity analysis was applied to identify violations of estimator assumptions. Results No association between either gallstone disease (P value = 0.60) or circulating levels of bilirubin (ORSD = 1.00, 95% confidence interval (CI) = 0.96–1.03, P value = 0.90) with CRC was shown. Conclusions Despite the large scale of this study, we found no evidence for a causal relationship between either circulating levels of bilirubin or gallstone disease with risk of developing CRC. While the magnitude of effect suggested by some observational studies can confidently be excluded, we cannot exclude the possibility of smaller effect sizes and non-linear relationships.

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