A bimodal distribution of haze in Pluto's atmosphere.
Ontology highlight
ABSTRACT:
SUBMITTER: Fan S
PROVIDER: S-EPMC8752795 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Recent efforts in systems immunology lead researchers to build quantitative models of cell activation and differentiation. One goal is to account for the distributions of proteins from single-cell measurements by flow cytometry or mass cytometry as readout of biological regulation. In that context, large cell-to-cell variability is often observed in biological quantities. We show here that these readouts, viewed in logarithmic scale may result in two easily-distinguishable modes, while the underlying distribution (in linear scale) is unimodal. We introduce a simple mathematical test to highlight this mismatch. We then dissect the flow of influence of cell-to-cell variability proposing a graphical model which motivates higher-dimensional analysis of the data. Finally we show how acquiring additional biological information can be used to reduce uncertainty introduced by cell-to-cell variability, helping to clarify whether the data is uni- or bimodal. This communication has cautionary implications for manual and automatic gating strategies, as well as clustering and modeling of single-cell measurements. © 2018 International Society for Advancement of Cytometry.
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Project description:Interacting human activities underlie the patterns of many social, technological, and economic phenomena. Here we present clear empirical evidence from Short Message correspondence that observed human actions are the result of the interplay of three basic ingredients: Poisson initiation of tasks and decision making for task execution in individual humans as well as interaction among individuals. This interplay leads to new types of interevent time distribution, neither completely Poisson nor power-law, but a bimodal combination of them. We show that the events can be separated into independent bursts which are generated by frequent mutual interactions in short times following random initiations of communications in longer times by the individuals. We introduce a minimal model of two interacting priority queues incorporating the three basic ingredients which fits well the distributions using the parameters extracted from the empirical data. The model can also embrace a range of realistic social interacting systems such as e-mail and letter communications when taking the time scale of processing into account. Our findings provide insight into various human activities both at the individual and network level. Our analysis and modeling of bimodal activity in human communication from the viewpoint of the interplay between processes of different time scales is likely to shed light on bimodal phenomena in other complex systems, such as interevent times in earthquakes, rainfall, forest fire, and economic systems, etc.
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Project description:Auxin polar transport, local maxima, and gradients have become an important model system for studying self-organization. Auxin distribution is regulated by auxin-dependent positive feedback loops that are not well-understood at the molecular level. Previously, we showed the involvement of the RHO of Plants (ROP) effector INTERACTOR of CONSTITUTIVELY active ROP 1 (ICR1) in regulation of auxin transport and that ICR1 levels are posttranscriptionally repressed at the site of maximum auxin accumulation at the root tip. Here, we show that bimodal regulation of ICR1 levels by auxin is essential for regulating formation of auxin local maxima and gradients. ICR1 levels increase concomitant with increase in auxin response in lateral root primordia, cotyledon tips, and provascular tissues. However, in the embryo hypophysis and root meristem, when auxin exceeds critical levels, ICR1 is rapidly destabilized by an SCF(TIR1/AFB) [SKP, Cullin, F-box (transport inhibitor response 1/auxin signaling F-box protein)]-dependent auxin signaling mechanism. Furthermore, ectopic expression of ICR1 in the embryo hypophysis resulted in reduction of auxin accumulation and concomitant root growth arrest. ICR1 disappeared during root regeneration and lateral root initiation concomitantly with the formation of a local auxin maximum in response to external auxin treatments and transiently after gravitropic stimulation. Destabilization of ICR1 was impaired after inhibition of auxin transport and signaling, proteasome function, and protein synthesis. A mathematical model based on these findings shows that an in vivo-like auxin distribution, rootward auxin flux, and shootward reflux can be simulated without assuming preexisting tissue polarity. Our experimental results and mathematical modeling indicate that regulation of auxin distribution is tightly associated with auxin-dependent ICR1 levels.
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Project description:In this work, we study the Sakaguchi-Kuramoto model with natural frequency following a bimodal distribution. By using Ott-Antonsen ansatz, we reduce the globally coupled phase oscillators to low dimensional coupled ordinary differential equations. For symmetrical bimodal frequency distribution, we analyze the stabilities of the incoherent state and different partial synchronous states. Different types of bifurcations are identified and the effect of the phase lag on the dynamics is investigated. For asymmetrical bimodal frequency distribution, we observe the revival of the incoherent state, and then the conditions for the revival are specified.
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Project description:The severity of a tropical cyclone (TC) is often summarized by its lifetime maximum intensity (LMI), and the climatological LMI distribution is a fundamental feature of the climate system. The distinctive bimodality of the LMI distribution means that major storms (LMI >96 kt) are not very rare compared with less intense storms. Rapid intensification (RI) is the dramatic strengthening of a TC in a short time, and is notoriously difficult to forecast or simulate. Here we show that the bimodality of the LMI distribution reflects two types of storms: those that undergo RI during their lifetime (RI storms) and those that do not (non-RI storms). The vast majority (79%) of major storms are RI storms. Few non-RI storms (6%) become major storms. While the importance of RI has been recognized in weather forecasting, our results demonstrate that RI also plays a crucial role in the TC climatology.
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Project description:ObjectiveBimodality in the distribution of glucose has been used to define the cut point for the diagnosis of diabetes. Previous studies on bimodality have primarily been in populations with a high prevalence of type 2 diabetes, including one study in a white Caucasian population. All studies included participants with known diabetes. The aim of this study was to assess whether a bimodal structure is a general phenomenon in fasting plasma glucose (FPG) and 2-h plasma glucose that is useful for deriving a common cut point for diabetes in populations of different origin, both including and excluding known diabetes.Research design and methodsThe Evaluation of Screening and Early Detection Strategies for Type 2 Diabetes and Impaired Glucose Tolerance (DETECT-2) project is an international collaboration pooling surveys from all continents. These studies include surveys in which plasma glucose was measured during an oral glucose tolerance test; in total, 43 studies (135,383 participants) from 27 countries were included. A mixture of two normal distributions was fitted to plasma glucose levels, and a cut point for normal glycemia was estimated as their intersection. In populations with a biologically meaningful cut point, bimodality was tested for significance.ResultsDistributions of FPG and 2-h plasma glucose did not, in general, produce bimodal structures useful for deriving cut points for diabetes. When present, the cut points produced were inconsistent over geographical regions.ConclusionsDeriving cut points for normal glycemia from distributions of FPG and 2-h plasma glucose does not appear to be suitable for defining diagnostic cut points for diabetes.
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Project description:BackgroundMany human diseases and phenotypes are related to RNA expression, levels of which are influenced by a wide spectrum of genetic and exposure-related factors. In a large genome-wide study of muscle tissue expression, we found that some genes exhibited a bimodal distribution of RNA expression, in contrast to what is usually assumed in studies of a single healthy tissue. As bimodality has classically been considered a hallmark of genetic control, we assessed the genome-wide prevalence, cause, and association of this phenomenon with diabetes-related phenotypes in skeletal muscle tissue from 225 healthy Pima Indians using exon array expression chips.ResultsTwo independent batches of microarrays were used for bimodal assessment and comparison. Of the 17,881 genes analyzed, eight (GSTM1, HLA-DRB1, ERAP2, HLA-DRB5, MAOA, ACTN3, NR4A2, and THNSL2) were found to have bimodal expression replicated in the separate batch groups, while 24 other genes had evidence of bimodality in only one group. Some bimodally expressed genes had modest associations with pre-diabetic phenotypes, of note ACTN3 with insulin resistance. Most of the other bimodal genes have been reported to be involved with various other diseases and characteristics. Association of expression with cis genetic variation in a subset of 149 individuals found all but one of the confirmed bimodal genes and nearly half of all potential ones to be highly significant expression quantitative trait loci (eQTL). The rare prevalence of these bimodally expressed genes found after controlling for batch effects was much lower than the prevalence reported in other studies. Additional validation in data from separate muscle expression studies confirmed the low prevalence of bimodality we observed.ConclusionsWe conclude that the prevalence of bimodal gene expression is quite rare in healthy muscle tissue (<0.2%), and is much lower than limited reports from other studies. The major cause of these clearly bimodal expression patterns in homogeneous tissue appears to be cis-polymorphisms, indicating that such bimodal genes are, for the most part, eQTL. The high frequency of disease associations reported with these genes gives hope that this unique feature may identify or actually be an underlying factor responsible for disease development.
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Project description:In grasses such as rice or maize, the distribution of genic GC content is well known to be bimodal. It is mainly driven by GC content at third codon positions (GC3 for short). This feature is thought to be specific to grasses as closely related species like banana have a unimodal GC3 distribution. GC3 is associated with numerous genomics features and uncovering the origin of this peculiar distribution will help understanding the potential roles and consequences of GC3 variations within and between genomes. Until recently, the origin of the peculiar GC3 distribution in grasses has remained unknown. Thanks to the recent publication of several complete genomes and transcriptomes of nongrass monocots, we studied more than 1,000 groups of one-to-one orthologous genes in seven grasses and three outgroup species (banana, palm tree, and yam). Using a maximum likelihood-based method, we reconstructed GC3 at several ancestral nodes. We found that the bimodal GC3 distribution observed in extant grasses is ancestral to both grasses and most monocot species, and that other species studied here have lost this peculiar structure. We also found that GC3 in grass lineages is globally evolving very slowly and that the decreasing GC3 gradient observed from 5' to 3' along coding sequences is also conserved and ancestral to monocots. This result strongly challenges the previous views on the specificity of grass genomes and we discuss its implications for the possible causes of the evolution of GC content in monocots.
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Project description:Risk assessment of pesticide impacts on remote ecosystems makes use of model-estimated degradation in air. Recent studies suggest these degradation rates to be overestimated, questioning current pesticide regulation. Here, we investigated the concentrations of 76 pesticides in Europe at 29 rural, coastal, mountain, and polar sites during the agricultural application season. Overall, 58 pesticides were observed in the European atmosphere. Low spatial variation of 7 pesticides suggests continental-scale atmospheric dispersal. Based on concentrations in free tropospheric air and at Arctic sites, 22 pesticides were identified to be prone to long-range atmospheric transport, which included 15 substances approved for agricultural use in Europe and 7 banned ones. Comparison between concentrations at remote sites and those found at pesticide source areas suggests long atmospheric lifetimes of atrazine, cyprodinil, spiroxamine, tebuconazole, terbuthylazine, and thiacloprid. In general, our findings suggest that atmospheric transport and persistence of pesticides have been underestimated and that their risk assessment needs to be improved.
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