De novo Explorations of Sarcopenia via a Dynamic Model

Background: The cause of sarcopenia has been observed over decades by clinical trials, which, however, are still insufficient to systematically unravel the enigma of how resistance exercise mediates skeletal muscle mass.Materials and Methods: Here, we proposed a minimal regulatory network and developed a dynamic model to rigorously investigate the mechanism of sarcopenia. Our model is consisted of eight ordinary differential equations and incorporates linear and Hill-function terms to describe positive and negative feedbacks between protein species, respectively.Results: A total of 720 samples with 10 scaled intensities were included in simulations, which revealed the expression level of AKT (maximum around 3.9-fold) and mTOR (maximum around 5.5-fold) at 3, 6, and 24 h at high intensity, and non-monotonic relation (ranging from 1.2-fold to 1.7-fold) between the graded intensities and skeletal muscle mass. Furthermore, continuous dynamics (within 24 h) of AKT, mTOR, and other proteins were obtained accordingly, and we also predicted the delaying effect with the median of maximized muscle mass shifting from 1.8-fold to 4.6-fold during a 4-fold increase of delay coefficient.Conclusion: The de novo modeling framework sheds light on the interdisciplinary methodology integrating computational approaches with experimental results, which facilitates the deeper understandings of exercise training and sarcopenia.

How cementation and fluid flow influence slip behavior at the subduction interface

Much of the complexity of subduction-zone earthquake size and temporal patterns owes to linkages among fluid flow, stress, and fault healing. To investigate these linkages, we introduce a novel numerical model that tracks cementation and fluid flow within the framework of an earthquake simulator. In the model, there are interseismic increases in cohesion across the plate boundary and decreases in porosity and permeability caused by cementation along the interface. Seismogenic slip is sensitive to the effective stress and therefore fluid pressure; in turn, slip events increase porosity by fracturing. The model therefore accounts for positive and negative feedbacks that modify slip behavior through the seismic cycle. The model produces temporal clustering of earthquakes in the seismic record of the Aleutian margin, which has well-documented along-strike variations in locking characteristics. Model results illustrate how physical, geochemical, and hydraulic linkages can affect natural slip behavior. Specifically, coseismic drops in fluid pressure steal energy from large ruptures, suppress slip, moderate the magnitudes of large earthquakes, and lead to aftershocks.

Biogeochemical and plant trait mechanisms drive enhanced methane emissions in response to whole-ecosystem warming

Climate warming perturbs ecosystem carbon (C) cycling, causing both positive and negative feedbacks on greenhouse gas emissions. In 2016, we began a tidal marsh field experiment in two vegetation communities to investigate the mechanisms by which whole-ecosystem warming alters C gain, via plant-driven sequestration in soils, and C loss, primarily via methane (CH4) emissions. Here, we report the results from the first 4 years. As expected, warming of 5.1 ∘C more than doubled CH4 emissions in both plant communities. We propose this was caused by a combination of four mechanisms: (i) a decrease in the proportion of CH4 consumed by CH4 oxidation, (ii) more C substrates available for methanogenesis, (iii) reduced competition between methanogens and sulfate-reducing bacteria, and (iv) indirect effects of plant traits. Plots dominated by Spartina patens consistently emitted more CH4 than plots dominated by Schoenoplectus americanus, indicating key differences in the roles these common wetland plants play in affecting anaerobic soil biogeochemistry and suggesting that plant composition can modulate coastal wetland responses to climate change.

Hotspots of extreme compound drought and heatwaves: Role of feedback and climate oscillations

<p>Compound weather events arise from combination of multiple climatic drivers or hazards and often result in disastrous socio-economic impacts. Compound drought and heatwave (CDHE) events have received considerable attention in recent years, but limited attention is given towards the understanding of feedback relationships between droughts and heatwaves at global hotspots of the compound events. Here, we identify the potential hotspots of extreme compound drought and heatwaves (ECDH) over the globe using standardized precipitation index (SPI) and Excess heat factor (EHF) as metrics for droughts and heatwaves, respectively. Besides the well know positive feedback between droughts and heatwaves, i.e., heatwaves amplify droughts and vice-versa, we hypothesize and test the possibility of negative feedback at distinct hotspots where heatwaves tend to abate droughts. Multiple hotspots were identified with positive and negative feedbacks among drought and heatwave intensities, supporting our hypothesis. We also analyzed the role of different local and large-scale global drivers (such as El-Niño Southern Oscillation) on the feedbacks at the hotspots. Our analysis has implications in predicting extreme compound droughts and heatwaves and provides new insights that will foster further research in this direction.</p>

Biogeochemical and plant trait mechanisms drive enhanced methane emissions in response to whole-ecosystem warming

Climate warming perturbs ecosystem carbon (C) cycling, causing both positive and negative feedbacks on greenhouse gas emissions. In 2016, we began a tidal marsh field experiment in two vegetation communities to investigate the mechanisms by which whole-ecosystem warming alters C gain, via plant-driven sequestration in soils, and C loss, primarily via methane (CH4) emissions. Here, we report the results from the first four years. As expected, warming of 5.1 °C more than doubled CH4 emissions in both plant communities. We propose this was caused by a combination of four mechanisms: (i) a decrease in the proportion of CH4 consumed by CH4 oxidation, (ii) more C substrates available for methanogenesis, (iii) reduced competition between methanogens and sulfate reducing bacteria, and (iv) indirect effects of plant traits. Plots dominated by Spartina patens consistently emitted more CH4 than plots dominated by Schoenoplectus americanus, indicating key differences in the roles these common wetland plants play in affecting anerobic soil biogeochemistry and suggesting that plant composition can modulate coastal wetland responses to climate change.

Fission Yeast Polarization: Modeling Cdc42 Oscillations, Symmetry Breaking, and Zones of Activation and Inhibition

Cells polarize for growth, motion, or mating through regulation of membrane-bound small GTPases between active GTP-bound and inactive GDP-bound forms. Activators (GEFs, GTP exchange factors) and inhibitors (GAPs, GTPase activating proteins) provide positive and negative feedbacks. We show that a reaction–diffusion model on a curved surface accounts for key features of polarization of model organism fission yeast. The model implements Cdc42 membrane diffusion using measured values for diffusion coefficients and dissociation rates and assumes a limiting GEF pool (proteins Gef1 and Scd1), as in prior models for budding yeast. The model includes two types of GAPs, one representing tip-localized GAPs, such as Rga3; and one representing side-localized GAPs, such as Rga4 and Rga6, that we assume switch between fast and slow diffusing states. After adjustment of unknown rate constants, the model reproduces active Cdc42 zones at cell tips and the pattern of GEF and GAP localization at cell tips and sides. The model reproduces observed tip-to-tip oscillations with periods of the order of several minutes, as well as asymmetric to symmetric oscillations transitions (corresponding to NETO “new end take off”), assuming the limiting GEF amount increases with cell size.

CD5 signalosome coordinates antagonist TCR signals to control the generation of Treg cells induced by foreign antigens

CD5 is characterized as an inhibitory coreceptor with an important regulatory role during T cell development. The molecular mechanism by which CD5 operates has been puzzling and its function in mature T cells suggests promoting rather than repressing effects on immune responses. Here, we combined quantitative mass spectrometry and genetic studies to analyze the components and the activity of the CD5 signaling machinery in primary T cells. We found that T cell receptor (TCR) engagement induces the selective phosphorylation of CD5 tyrosine 429, which serves as a docking site for proteins with adaptor functions (c-Cbl, CIN85, CRKL), connecting CD5 to positive (PI3K) and negative (UBASH3A, SHIP1) regulators of TCR signaling. c-CBL acts as a coordinator in this complex enabling CD5 to synchronize positive and negative feedbacks on TCR signaling through the other components. Disruption of CD5 signalosome in mutant mice reveals that it modulates TCR signal outputs to selectively repress the transactivation ofFoxp3and limit the inopportune induction of peripherally induced regulatory T cells during immune responses against foreign antigen. Our findings bring insights into the paradigm of coreceptor signaling, suggesting that, in addition to providing dualistic enhancing or dampening inputs, coreceptors can engage concomitant stimulatory and inhibitory signaling events, which act together to promote specific functional outcomes.

<i>π</i>-theorem generalization of the ice-age theory

Analyzing a dynamical system describing the global climate variations requires, in principle, exploring a large space spanned by the numerous parameters involved in this model. Dimensional analysis is traditionally employed to deal with equations governing physical phenomena to reduce the number of parameters to be explored, but it does not work well with dynamical ice-age models, because, as a rule, the number of parameters in such systems is much larger than the number of independent dimensions. Physical reasoning may, however, allow us to reduce the number of effective parameters and apply dimensional analysis in a way that is insightful. We show this with a specific ice-age model (Verbitsky et al., 2018), which is a low-order dynamical system based on ice-flow physics coupled with a linear climate feedback. In this model, the ratio of positive-to-negative feedback is effectively captured by a dimensionless number called the “V number”, which aggregates several parameters and, hence, reduces the number of governing parameters. This allows us to apply the central theorem of the dimensional analysis, the π theorem, efficiently. Specifically, we show that the relationship between the amplitude and duration of glacial cycles is governed by a property of scale invariance that does not depend on the physical nature of the underlying positive and negative feedbacks incorporated by the system. This specific example suggests a broader idea; that is, the scale invariance can be deduced as a general property of ice age dynamics if the latter are effectively governed by a single ratio between positive and negative feedbacks.