16 research outputs found
Diurnal self-aggregation
Convective self-aggregation is a modelling paradigm for thunderstorm
organisation over a constant-temperature tropical sea surface. This setup can
give rise to cloud clusters over timescales of weeks. In reality, sea surface
temperatures do oscillate diurnally, affecting the atmospheric state. Over
land, surface temperatures vary more strongly, and rain rate is significantly
influenced. Here, we carry out a substantial suite of cloud-resolving numerical
experiments, and find that even weak surface temperature oscillations enable
qualitatively different dynamics to emerge: the spatial distribution of
rainfall is only homogeneous during the first day. Already on the second day,
the rain field is firmly structured. In later days, the clustering becomes
stronger and alternates from day-to-day. We show that these features are robust
to changes in resolution, domain size, and surface temperature, but can be
removed by a reduction of the amplitude of oscillation, suggesting a transition
to a clustered state. Maximal clustering occurs at a scale of
, a scale we relate to the emergence of
mesoscale convective systems. At rainfall is strongly
enhanced and far exceeds the rainfall expected at random. We explain the
transition to clustering using simple conceptual modelling. Our results may
help clarify how continental extremes build up and how cloud clustering over
the tropical ocean could emerge much faster than through conventional
self-aggregation alone.Comment: 27 pages, 4 main figures, 7 supplementary figures, 2 main tables, 1
supplementary tabl
Publication bias and the canonization of false facts
In the process of scientific inquiry, certain claims accumulate enough
support to be established as facts. Unfortunately, not every claim accorded the
status of fact turns out to be true. In this paper, we model the dynamic
process by which claims are canonized as fact through repeated experimental
confirmation. The community's confidence in a claim constitutes a Markov
process: each successive published result shifts the degree of belief, until
sufficient evidence accumulates to accept the claim as fact or to reject it as
false. In our model, publication bias --- in which positive results are
published preferentially over negative ones --- influences the distribution of
published results. We find that when readers do not know the degree of
publication bias and thus cannot condition on it, false claims often can be
canonized as facts. Unless a sufficient fraction of negative results are
published, the scientific process will do a poor job at discriminating false
from true claims. This problem is exacerbated when scientists engage in
p-hacking, data dredging, and other behaviors that increase the rate at which
false positives are published. If negative results become easier to publish as
a claim approaches acceptance as a fact, however, true and false claims can be
more readily distinguished. To the degree that the model accurately represents
current scholarly practice, there will be serious concern about the validity of
purported facts in some areas of scientific research
Circling in on convective organization
Cold pools (CPs) contribute to convective organization. However, it is unclear by which mechanisms organization occurs. By using a particle method to track CP gust fronts in large eddy simulations, we characterize the basic collision modes between CPs. Our results show that CP interactions, where three expanding gust fronts force an updraft, are key at triggering new convection. Using this, we conceptualize CP dynamics into a parameterâfree mathematical model: circles expand from initially random points in space. Where two expanding circles collide, a stationary front is formed. However, where three expanding circles enclose a single point, a new expanding circle is seeded. This simple model supports three fundamental features of CP dynamics: precipitation cells constitute a spatially interacting system; CPs come in generations; and scales steadily increase throughout the diurnal cycle. Finally, this model provides a framework for how CPs act to cause convective selfâorganization, clustering, and extremes
Mapping transcriptional heterogeneity and metabolic networks in fatty livers at single-cell resolution
Summary: Non-alcoholic fatty liver disease is a heterogeneous disease with unclear underlying molecular mechanisms. Here, we perform single-cell RNA sequencing of hepatocytes and hepatic non-parenchymal cells to map the lipid signatures in mice with non-alcoholic fatty liver disease (NAFLD). We uncover previously unidentified clusters of hepatocytes characterized by either high or low srebp1 expression. Surprisingly, the canonical lipid synthesis driver Srebp1 is not predictive of hepatic lipid accumulation, suggestive of other drivers of lipid metabolism. By combining transcriptional data at single-cell resolution with computational network analyses, we find that NAFLD is associated with high constitutive androstane receptor (CAR) expression. Mechanistically, CAR interacts with four functional modules: cholesterol homeostasis, bile acid metabolism, fatty acid metabolism, and estrogen response. Nuclear expression of CAR positively correlates with steatohepatitis in human livers. These findings demonstrate significant cellular differences in lipid signatures and identify functional networks linked to hepatic steatosis in mice and humans
Four simple rules that are sufficient to generate the mammalian blastocyst
<div><p>Early mammalian development is both highly regulative and self-organizing. It involves the interplay of cell position, predetermined gene regulatory networks, and environmental interactions to generate the physical arrangement of the blastocyst with precise timing. However, this process occurs in the absence of maternal information and in the presence of transcriptional stochasticity. How does the preimplantation embryo ensure robust, reproducible development in this context? It utilizes a versatile toolbox that includes complex intracellular networks coupled to cellâcell communication, segregation by differential adhesion, and apoptosis. Here, we ask whether a minimal set of developmental rules based on this toolbox is sufficient for successful blastocyst development, and to what extent these rules can explain mutant and experimental phenotypes. We implemented experimentally reported mechanisms for polarity, cellâcell signaling, adhesion, and apoptosis as a set of developmental rules in an agent-based in silico model of physically interacting cells. We find that this model quantitatively reproduces specific mutant phenotypes and provides an explanation for the emergence of heterogeneity without requiring any initial transcriptional variation. It also suggests that a fixed time point for the cellsâ competence of fibroblast growth factor (FGF)/extracellular signalâregulated kinase (ERK) sets an embryonic clock that enables certain scaling phenomena, a concept that we evaluate quantitatively by manipulating embryos in vitro. Based on these observations, we conclude that the minimal set of rules enables the embryo to experiment with stochastic gene expression and could provide the robustness necessary for the evolutionary diversification of the preimplantation gene regulatory network.</p></div