A method for the parameterization of ice-phase microphysics is proposed and used to develop a new bulk microphysics scheme. All ice-phase particles are represented by several physical properties that ...evolve freely in time and space. The scheme prognoses four ice mixing ratio variables, total mass, rime mass, rime volume, and number, allowing 4 degrees of freedom for representing the particle properties using a single category. This approach represents a significant departure from traditional microphysics schemes in which ice-phase hydrometeors are partitioned into various predefined categories (e.g., cloud ice, snow, and graupel) with prescribed characteristics. The liquid-phase component of the new scheme uses a standard two-moment, two-category approach. The proposed method and a complete description of the new predicted particle properties (P3) scheme are provided. Results from idealized model simulations of a two-dimensional squall line are presented that illustrate overall behavior of the scheme. Despite its use of a single ice-phase category, the scheme simulates a realistically wide range of particle characteristics in different regions of the squall line, consistent with observed ice particles in real squall lines. Sensitivity tests show that both the prediction of the rime mass fraction and the rime density are important for the simulation of the squall-line structure and precipitation.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Children suffering from microtia have few options for auricular reconstruction. Tissue engineering approaches attempt to replicate the complex anatomy and structure of the ear with autologous ...cartilage but have been limited by access to clinically accessible cell sources. Here we present a full-scale, patient-based human ear generated by implantation of human auricular chondrocytes and human mesenchymal stem cells in a 1:1 ratio. Additional disc construct surrogates were generated with 1:0, 1:1, and 0:1 combinations of auricular chondrocytes and mesenchymal stem cells. After 3 months in vivo, monocellular auricular chondrocyte discs and 1:1 disc and ear constructs displayed bundled collagen fibers in a perichondrial layer, rich proteoglycan deposition, and elastin fiber network formation similar to native human auricular cartilage, with the protein composition and mechanical stiffness of native tissue. Full ear constructs with a 1:1 cell combination maintained gross ear structure and developed a cartilaginous appearance following implantation. These studies demonstrate the successful engineering of a patient-specific human auricle using exclusively human cell sources without extensive in vitro tissue culture prior to implantation, a critical step towards the clinical application of tissue engineering for auricular reconstruction.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Growing evidence suggests that sirtuins, a family of seven distinct NAD-dependent enzymes, are involved in the regulation of neuronal survival. Indeed, SIRT1 has been reported to protect against ...neuronal death, while SIRT2 promotes neurodegeneration. The effect of SIRTs 3-7 on the regulation of neuronal survival, if any, has yet to be reported.
We examined the effect of expressing each of the seven SIRT proteins in healthy cerebellar granule neurons (CGNs) or in neurons induced to die by low potassium (LK) treatment. We report that SIRT1 protects neurons from LK-induced apoptosis, while SIRT2, SIRT3 and SIRT6 induce apoptosis in otherwise healthy neurons. SIRT5 is generally localized to both the nucleus and cytoplasm of CGNs and exerts a protective effect. In a subset of neurons, however, SIRT5 localizes to the mitochondria and in this case it promotes neuronal death. Interestingly, the protective effect of SIRT1 in neurons is not reduced by treatments with nicotinamide or sirtinol, two pharmacological inhibitors of SIRT1. Neuroprotection was also observed with two separate mutant forms of SIRT1, H363Y and H355A, both of which lack deacetylase activity. Furthermore, LK-induced neuronal death was not prevented by resveratrol, a pharmacological activator of SIRT1, at concentrations at which it activates SIRT1. We extended our analysis to HT-22 neuroblastoma cells which can be induced to die by homocysteic acid treatment. While the effects of most of the SIRT proteins were similar to that observed in CGNs, SIRT6 was modestly protective against homocysteic acid toxicity in HT-22 cells. SIRT5 was generally localized in the mitochondria of HT-22 cells and was apoptotic.
Overall, our study makes three contributions - (a) it represents the first analysis of SIRT3-7 in the regulation of neuronal survival, (b) it shows that neuroprotection by SIRT1 can be mediated by a novel, non-catalytic mechanism, and (c) that subcellular localization may be an important determinant in the effect of SIRT5 on neuronal viability.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Long-distance cell migration is an important feature of embryonic development, adult morphogenesis and cancer, yet the mechanisms that drive subpopulations of cells to distinct targets are poorly ...understood. Here, we use the embryonic neural crest (NC) in tandem with theoretical studies to evaluate model mechanisms of long-distance cell migration. We find that a simple chemotaxis model is insufficient to explain our experimental data. Instead, model simulations predict that NC cell migration requires leading cells to respond to long-range guidance signals and trailing cells to short-range cues in order to maintain a directed, multicellular stream. Experiments confirm differences in leading versus trailing NC cell subpopulations, manifested in unique cell orientation and gene expression patterns that respond to non-linear tissue growth of the migratory domain. Ablation experiments that delete the trailing NC cell subpopulation reveal that leading NC cells distribute all along the migratory pathway and develop a leading/trailing cellular orientation and gene expression profile that is predicted by model simulations. Transplantation experiments and model predictions that move trailing NC cells to the migratory front, or vice versa, reveal that cells adopt a gene expression profile and cell behaviors corresponding to the new position within the migratory stream. These results offer a mechanistic model in which leading cells create and respond to a cell-induced chemotactic gradient and transmit guidance information to trailing cells that use short-range signals to move in a directional manner.
In the atmosphere, microphysics refers to the microscale processes that affect cloud and precipitation particles and is a key linkage among the various components of Earth's atmospheric water and ...energy cycles. The representation of microphysical processes in models continues to pose a major challenge leading to uncertainty in numerical weather forecasts and climate simulations. In this paper, the problem of treating microphysics in models is divided into two parts: (i) how to represent the population of cloud and precipitation particles, given the impossibility of simulating all particles individually within a cloud, and (ii) uncertainties in the microphysical process rates owing to fundamental gaps in knowledge of cloud physics. The recently developed Lagrangian particle‐based method is advocated as a way to address several conceptual and practical challenges of representing particle populations using traditional bulk and bin microphysics parameterization schemes. For addressing critical gaps in cloud physics knowledge, sustained investment for observational advances from laboratory experiments, new probe development, and next‐generation instruments in space is needed. Greater emphasis on laboratory work, which has apparently declined over the past several decades relative to other areas of cloud physics research, is argued to be an essential ingredient for improving process‐level understanding. More systematic use of natural cloud and precipitation observations to constrain microphysics schemes is also advocated. Because it is generally difficult to quantify individual microphysical process rates from these observations directly, this presents an inverse problem that can be viewed from the standpoint of Bayesian statistics. Following this idea, a probabilistic framework is proposed that combines elements from statistical and physical modeling. Besides providing rigorous constraint of schemes, there is an added benefit of quantifying uncertainty systematically. Finally, a broader hierarchical approach is proposed to accelerate improvements in microphysics schemes, leveraging the advances described in this paper related to process modeling (using Lagrangian particle‐based schemes), laboratory experimentation, cloud and precipitation observations, and statistical methods.
Plain Language Summary
In the atmosphere, microphysics—the small‐scale processes affecting cloud and precipitation particles such as their growth by condensation, evaporation, and melting—is a critical part of Earth's weather and climate. Because it is impossible to simulate every cloud particle individually owing to their sheer number within even a small cloud, atmospheric models have to represent the evolution of particle populations statistically. There are critical gaps in knowledge of the microphysical processes that act on particles, especially for atmospheric ice particles because of their wide variety and intricacy of their shapes. The difficulty of representing cloud and precipitation particle populations and knowledge gaps in cloud processes both introduce important uncertainties into models that translate into uncertainty in weather forecasts and climate simulations, including climate change assessments. We discuss several specific challenges related to these problems. To improve how cloud and precipitation particle populations are represented, we advocate a “particle‐based” approach that addresses several limitations of traditional approaches and has recently gained traction as a tool for cloud modeling. Advances in observations, including laboratory studies, are argued to be essential for addressing gaps in knowledge of microphysical processes. We also advocate using statistical modeling tools to improve how these observations are used to constrain model microphysics. Finally, we discuss a hierarchical approach that combines the various pieces discussed in this article, providing a possible blueprint for accelerating progress in how microphysics is represented in cloud, weather, and climate models.
Key Points
Microphysics is an important component of weather and climate models, but its representation in current models is highly uncertain
Two critical challenges are identified: representing cloud and precipitation particle populations and knowledge gaps in cloud physics
A possible blueprint for addressing these challenges is proposed to accelerate progress in improving microphysics schemes
Weather forecasts and climate projections of precipitation phase and type in winter storms are challenging due to the complicated underlying microphysical and dynamical processes. In the Canadian ...numerical weather prediction model, explicit freezing rain (FR) at the surface is often overestimated during the winter season for situations in which snow is observed. For a case study simulated using this model with the Predicted Particle Properties (P3) microphysics scheme, the secondary ice production (SIP) process has a major impact on the surface precipitation type. Parameterized SIP substantially reduces FR due to increased collection of supercooled drops with ice particles formed by rime splintering. Hindcast simulations of 40 winter cases show that these results are systematic, and the decreased frequency of FR leads to improved forecast skill relative to observations. Thus, accounting for SIP in the model is critical for accurately simulating precipitation types.
Plain Language Summary
Several types of winter precipitation, including snow, freezing rain (FR) and ice pellets (IP), are associated with hazards such as injuries from people falling, disruption of electrical supply, and breakdown of transportation networks due to the accumulation of ice on surfaces. Forecasts of precipitation type using weather prediction models, as well as projections for a warmer climate, are challenging because of the complicated physical processes involved. In this article, it is shown that the component of the numerical model that is used to represent clouds and precipitation in the Canadian high‐resolution weather forecast system overestimates FR at the expense of snow. This problem is mitigated when the additional process of secondary ice production (here, the generation of new ice particles from collisions of existing ice and supercooled drops) is included in the model. The presence of numerous small ice particles formed by this process decreases the amount of FR and improves forecast skill scores for 40 historic winter cases. Thus, accounting for this process in weather and climate models is important for accurately simulating FR, IP and snow.
Key Points
Secondary ice production (SIP) substantially impacts precipitation phase and type in winter storms
Inclusion of SIP reduces excessive freezing rain (FR) in numerical simulations
Forecast metrics for FR in 40 winter cases are improved when SIP is included in a weather model
Abstract
A novel bulk microphysics scheme that predicts the evolution of ice properties, including aspect ratio (shape), mass, number, size, and density is described, tested, and demonstrated. The ...scheme is named the Ice-Spheroids Habit Model with Aspect-Ratio Evolution (ISHMAEL). Ice is modeled as spheroids and is nucleated as one of two species depending on nucleation temperature. Microphysical process rates determine how shape and other ice properties evolve. A third aggregate species is also employed, diversifying ice properties in the model. Tests of ice shape evolution during vapor growth and riming are verified against wind tunnel data, revealing that the model captures habit-dependent riming and its effect on fall speed. Lagrangian parcel studies demonstrate that the bulk model captures ice property evolution during riming and melting compared with a bin model. Finally, the capabilities of ISHMAEL are shown in a 2D kinematic framework with a simple updraft. A direct result of predicting ice shape evolution is that various states of ice from unrimed to lightly rimed to densely rimed can be modeled without converting ice mass between predefined ice categories (e.g., snow and graupel). This leads to a different spatial precipitation distribution compared with the traditional method of separating snow and graupel and converting between the two categories, because ice in ISHMAEL sorts in physical space based on the amount of rime, which controls the thickness and therefore fall speed. Predicting these various states of rimed ice leads to a reduction in vapor growth rate and an increase in riming rate in a simple updraft compared with the traditional approach.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract
A method to predict the bulk density of graupel
ρ
g
has been added to the two-moment Milbrandt–Yau bulk microphysics scheme. The simulation of graupel using the modified scheme is ...illustrated through idealized simulations of a mesoscale convective system using a 2D kinematic model with a prescribed flow field and different peak updraft speeds. To examine the relative impact of the various approaches to represent rimed ice, simulations were run for various graupel-only and graupel-plus-hail configurations.
Because of the direct feedback of
ρ
g
to terminal fall speeds, the modified scheme produces a much different spatial distribution of graupel, with more mass concentrated in the convective region resulting in changes to the surface precipitation at all locations. With a strong updraft, the model can now produce solid precipitation at the surface in the convective region without a separate hail category. It is shown that a single rimed-ice category is capable of representing a realistically wide range of graupel characteristics in various atmospheric conditions without the need for a priori parameter settings.
Sensitivity tests were conducted to examine various aspects of the scheme that affect the simulated
ρ
g
. Specific parameterizations pertaining to other hydrometeor categories now have a direct impact on the simulation of graupel, including the assumed aerosol distribution for droplet nucleation, which affects the drop sizes of both cloud and rain, and the mass–size relation for snow, which affects its density and hence the embryo density of graupel converted from snow due to riming.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Retinoic acid (RA) is involved in antero-posterior patterning of the chordate body axis and, in jawed vertebrates, has been shown to play a major role at multiple levels of the gene regulatory ...network (GRN) regulating hindbrain segmentation. Knowing when and how RA became coupled to the core hindbrain GRN is important for understanding how ancient signaling pathways and patterning genes can evolve and generate diversity. Hence, we investigated the link between RA signaling and hindbrain segmentation in the sea lamprey Petromyzon marinus, an important jawless vertebrate model providing clues to decipher ancestral vertebrate features. Combining genomics, gene expression, and functional analyses of major components involved in RA synthesis (Aldh1as) and degradation (Cyp26s), we demonstrate that RA signaling is coupled to hindbrain segmentation in lamprey. Thus, the link between RA signaling and hindbrain segmentation is a pan vertebrate feature of the hindbrain and likely evolved at the base of vertebrates.
Abstract
Bulk microphysics parameterizations that are used to represent clouds and precipitation usually allow only solid and liquid hydrometeors. Predicting the bulk liquid fraction on ice allows an ...explicit representation of mixed-phase particles and various precipitation types, such as wet snow and ice pellets. In this paper, an approach for the representation of the bulk liquid fraction into the predicted particle properties (P3) microphysics scheme is proposed and described. Solid-phase microphysical processes, such as melting and sublimation, have been modified to account for the liquid component. New processes, such as refreezing and condensation of the liquid portion of mixed-phase particles, have been added to the parameterization. Idealized simulations using a one-dimensional framework illustrate the overall behavior of the modified scheme. The proposed approach compares well to a Lagrangian benchmark model. Temperatures required for populations of ice crystals to melt completely also agree well with previous studies. The new processes of refreezing and condensation impact both the surface precipitation type and feedback between the temperature and the phase changes. Overall, prediction of the bulk liquid fraction allows an explicit description of new precipitation types, such as wet snow and ice pellets, and improves the representation of hydrometeor properties when the temperature is near 0°C.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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