A 3D biophysical model for cancer spheroid cell-enhanced invasion in collagen-oriented fiber microenvironment

Bacterial biofilms represent a promising opportunity for engineering of microbial communities. However, our ability to control spatial structure in biofilms remains limited. Here we engineerEscherichia coliwith a light-activated transcriptional promoter (pDawn) to optically regulate expression of an adhesin gene (Ag43). When illuminated with patterned blue light, long-term viable biofilms with spatial resolution down to 25 μm can be formed on a variety of substrates and inside enclosed culture chambers without the need for surface pretreatment. A biophysical model suggests that the patterning mechanism involves stimulation of transiently surface-adsorbed cells, lending evidence to a previously proposed role of adhesin expression during natural biofilm maturation. Overall, this tool—termed “Biofilm Lithography”—has distinct advantages over existing cell-depositing/patterning methods and provides the ability to grow structured biofilms, with applications toward an improved understanding of natural biofilm communities, as well as the engineering of living biomaterials and bottom–up approaches to microbial consortia design.

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Global earthworm distribution and activity windows based on soil hydromechanical constraints

Communications Biology ◽

10.1038/s42003-021-02139-5 ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Siul A. Ruiz ◽

Samuel Bickel ◽

Dani Or

Keyword(s):

Soil Structure ◽

Mechanistic Model ◽

Biophysical Model ◽

Ecosystem Functions ◽

Soil Conditions ◽

Agricultural Systems ◽

Occurrence Patterns ◽

Additional Constraints ◽

Earthworm Activity ◽

Good Agreement

AbstractEarthworm activity modifies soil structure and promotes important hydrological ecosystem functions for agricultural systems. Earthworms use their flexible hydroskeleton to burrow and expand biopores. Hence, their activity is constrained by soil hydromechanical conditions that permit deformation at earthworm’s maximal hydroskeletal pressure (≈200kPa). A mechanistic biophysical model is developed here to link the biomechanical limits of earthworm burrowing with soil moisture and texture to predict soil conditions that permit bioturbation across biomes. We include additional constraints that exclude earthworm activity such as freezing temperatures, low soil pH, and high sand content to develop the first predictive global map of earthworm habitats in good agreement with observed earthworm occurrence patterns. Earthworm activity is strongly constrained by seasonal dynamics that vary across latitudes largely due to soil hydromechanical status. The mechanistic model delineates the potential for earthworm migration via connectivity of hospitable sites and highlights regions sensitive to climate.

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A model of on/off transitions in neurons of the deep cerebellar nuclei: deciphering the underlying ionic mechanisms

The Journal of Mathematical Neuroscience ◽

10.1186/s13408-021-00105-3 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Hugues Berry ◽

Stéphane Genet

Keyword(s):

Cerebellar Nuclei ◽

Biophysical Model ◽

High Threshold ◽

Deep Cerebellar Nuclei ◽

Functional Link ◽

Electrophysiological Properties ◽

Voltage Dependent ◽

Ionic Mechanisms ◽

The Central Nervous System ◽

Overall Functioning

AbstractThe neurons of the deep cerebellar nuclei (DCNn) represent the main functional link between the cerebellar cortex and the rest of the central nervous system. Therefore, understanding the electrophysiological properties of DCNn is of fundamental importance to understand the overall functioning of the cerebellum. Experimental data suggest that DCNn can reversibly switch between two states: the firing of spikes (F state) and a stable depolarized state (SD state). We introduce a new biophysical model of the DCNn membrane electro-responsiveness to investigate how the interplay between the documented conductances identified in DCNn give rise to these states. In the model, the F state emerges as an isola of limit cycles, i.e. a closed loop of periodic solutions disconnected from the branch of SD fixed points. This bifurcation structure endows the model with the ability to reproduce the $\text{F}\to \text{SD}$ F → SD transition triggered by hyperpolarizing current pulses. The model also reproduces the $\text{F}\to \text{SD}$ F → SD transition induced by blocking Ca currents and ascribes this transition to the blocking of the high-threshold Ca current. The model suggests that intracellular current injections can trigger fully reversible $\text{F}\leftrightarrow \text{SD}$ F ↔ SD transitions. Investigation of low-dimension reduced models suggests that the voltage-dependent Na current is prominent for these dynamical features. Finally, simulations of the model suggest that physiological synaptic inputs may trigger $\text{F}\leftrightarrow \text{SD}$ F ↔ SD transitions. These transitions could explain the puzzling observation of positively correlated activities of connected Purkinje cells and DCNn despite the former inhibit the latter.

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Prediction study on the spatiotemporal distribution of Yesso scallop larvae based on a coupled biophysical model

Aquaculture ◽

10.1016/j.aquaculture.2021.736598 ◽

2021 ◽

pp. 736598

Author(s):

Qiaofeng Ma ◽

Yunkuan Han ◽

Yanbin Xi ◽

Jingming Huang ◽

Zhaojun Sheng ◽

...

Keyword(s):

Spatiotemporal Distribution ◽

Biophysical Model ◽

Yesso Scallop ◽

Scallop Larvae

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Dynamic modulation of spike timing-dependent calcium influx during corticostriatal upstates

Journal of Neurophysiology ◽

10.1152/jn.00232.2013 ◽

2013 ◽

Vol 110 (7) ◽

pp. 1631-1645 ◽

Cited By ~ 13

Author(s):

R. C. Evans ◽

Y. M. Maniar ◽

K. T. Blackwell

Keyword(s):

Synaptic Plasticity ◽

Slow Wave Sleep ◽

Calcium Influx ◽

Spike Timing ◽

Medium Spiny Neuron ◽

Calcium Transients ◽

Biophysical Model ◽

Published Data ◽

High Calcium

The striatum of the basal ganglia demonstrates distinctive upstate and downstate membrane potential oscillations during slow-wave sleep and under anesthetic. The upstates generate calcium transients in the dendrites, and the amplitude of these calcium transients depends strongly on the timing of the action potential (AP) within the upstate. Calcium is essential for synaptic plasticity in the striatum, and these large calcium transients during the upstates may control which synapses undergo plastic changes. To investigate the mechanisms that underlie the relationship between calcium and AP timing, we have developed a realistic biophysical model of a medium spiny neuron (MSN). We have implemented sophisticated calcium dynamics including calcium diffusion, buffering, and pump extrusion, which accurately replicate published data. Using this model, we found that either the slow inactivation of dendritic sodium channels (NaSI) or the calcium inactivation of voltage-gated calcium channels (CDI) can cause high calcium corresponding to early APs and lower calcium corresponding to later APs. We found that only CDI can account for the experimental observation that sensitivity to AP timing is dependent on NMDA receptors. Additional simulations demonstrated a mechanism by which MSNs can dynamically modulate their sensitivity to AP timing and show that sensitivity to specifically timed pre- and postsynaptic pairings (as in spike timing-dependent plasticity protocols) is altered by the timing of the pairing within the upstate. These findings have implications for synaptic plasticity in vivo during sleep when the upstate-downstate pattern is prominent in the striatum.

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Occupant behaviour and thermal comfort in buildings: Monitoring the end user

E3S Web of Conferences ◽

10.1051/e3sconf/201911104056 ◽

2019 ◽

Vol 111 ◽

pp. 04056

Author(s):

Loes Visser ◽

Boris Kingma ◽

Eric Willems ◽

Wendy Broers ◽

Marcel Loomans ◽

...

Keyword(s):

Thermal Comfort ◽

Energy Performance ◽

The Body ◽

Activity Level ◽

Biophysical Model ◽

Zone Model ◽

Occupant Behaviour ◽

Ambient Conditions ◽

Skin Temperatures ◽

Thermoregulatory Behaviour

Studies indicate that the energy performance gap between real and calculated energy use can be explained for 80% by occupant behaviour. This human factor may be composed of routine and thermoregulatory behaviour. When occupants do not feel comfortable due to high or low operative temperatures and resulting high or low skin temperatures, they are likely to exhibit thermoregulatory behaviour. The aim of this study is to monitor and understand this thermoregulatory behaviour of the occupant. This is a detailed study of two females living in a rowhouse in the city of Heerlen (Netherlands). During a monitoring period of three weeks over a time span of three months the following parameters were monitored: activity level, clothing, micro climate, skin temperatures and thermal comfort and sensation. Their micro climate was measured at five positions on the body to assess exposed near body conditions and skin temperature. Every two hours they filled in a questionnaire regarding their thermal comfort and sensation level (7-point scale), clothing, activities and thermoregulatory behaviour. The most comfortable (optimal) temperature was calculated for each person by adopting a biophysical model, a thermoneutral zone model. This study shows unique indivual comfort patterns in relation to ambient conditions. An example is given how this information can be used to calculate the buildings energy comsumption.

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Polar cod in jeopardy under the retreating Arctic sea ice

Communications Biology ◽

10.1038/s42003-019-0649-2 ◽

2019 ◽

Vol 2 (1) ◽

Cited By ~ 6

Author(s):

Mats Brockstedt Olsen Huserbråten ◽

Elena Eriksen ◽

Harald Gjøsæter ◽

Frode Vikebø

Keyword(s):

Sea Ice ◽

Barents Sea ◽

Keystone Species ◽

Ice Cover ◽

Arctic Sea Ice ◽

Biophysical Model ◽

The Arctic ◽

Polar Cod ◽

Arctic Sea ◽

Shelf Sea

Abstract The Arctic amplification of global warming is causing the Arctic-Atlantic ice edge to retreat at unprecedented rates. Here we show how variability and change in sea ice cover in the Barents Sea, the largest shelf sea of the Arctic, affect the population dynamics of a keystone species of the ice-associated food web, the polar cod (Boreogadus saida). The data-driven biophysical model of polar cod early life stages assembled here predicts a strong mechanistic link between survival and variation in ice cover and temperature, suggesting imminent recruitment collapse should the observed ice-reduction and heating continue. Backtracking of drifting eggs and larvae from observations also demonstrates a northward retreat of one of two clearly defined spawning assemblages, possibly in response to warming. With annual to decadal ice-predictions under development the mechanistic physical-biological links presented here represent a powerful tool for making long-term predictions for the propagation of polar cod stocks.

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Electrical stimulation of retinal neurons in epiretinal and subretinal configuration using a multicapacitor array

Journal of Neurophysiology ◽

10.1152/jn.00909.2011 ◽

2012 ◽

Vol 107 (10) ◽

pp. 2742-2755 ◽

Cited By ~ 79

Author(s):

Max Eickenscheidt ◽

Martin Jenkner ◽

Roland Thewes ◽

Peter Fromherz ◽

Günther Zeck

Keyword(s):

Electrical Stimulation ◽

Ganglion Cells ◽

Ex Vivo ◽

Biophysical Model ◽

Retinal Neurons ◽

Direct Stimulation ◽

Tungsten Electrode ◽

Partial Restoration ◽

Low Amplitude ◽

Stimulation Of

Electrical stimulation of retinal neurons offers the possibility of partial restoration of visual function. Challenges in neuroprosthetic applications are the long-term stability of the metal-based devices and the physiological activation of retinal circuitry. In this study, we demonstrate electrical stimulation of different classes of retinal neurons with a multicapacitor array. The array—insulated by an inert oxide—allows for safe stimulation with monophasic anodal or cathodal current pulses of low amplitude. Ex vivo rabbit retinas were interfaced in either epiretinal or subretinal configuration to the multicapacitor array. The evoked activity was recorded from ganglion cells that respond to light increments by an extracellular tungsten electrode. First, a monophasic epiretinal cathodal or a subretinal anodal current pulse evokes a complex burst of action potentials in ganglion cells. The first action potential occurs within 1 ms and is attributed to direct stimulation. Within the next milliseconds additional spikes are evoked through bipolar cell or photoreceptor depolarization, as confirmed by pharmacological blockers. Second, monophasic epiretinal anodal or subretinal cathodal currents elicit spikes in ganglion cells by hyperpolarization of photoreceptor terminals. These stimuli mimic the photoreceptor response to light increments. Third, the stimulation symmetry between current polarities (anodal/cathodal) and retina-array configuration (epi/sub) is confirmed in an experiment in which stimuli presented at different positions reveal the center-surround organization of the ganglion cell. A simple biophysical model that relies on voltage changes of cell terminals in the transretinal electric field above the stimulation capacitor explains our results. This study provides a comprehensive guide for efficient stimulation of different retinal neuronal classes with low-amplitude capacitive currents.

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Spike-Timing-Dependent Hebbian Plasticity as Temporal Difference Learning

Neural Computation ◽

10.1162/089976601750541787 ◽

2001 ◽

Vol 13 (10) ◽

pp. 2221-2237 ◽

Cited By ~ 118

Author(s):

Rajesh P. N. Rao ◽

Terrence J. Sejnowski

Keyword(s):

Cortical Neuron ◽

Action Potentials ◽

Learning Rule ◽

Spike Timing ◽

Biophysical Model ◽

Excitatory Synapses ◽

Temporal Difference ◽

Temporal Difference Learning ◽

Neocortical Neurons ◽

Hebbian Plasticity

A spike-timing-dependent Hebbian mechanism governs the plasticity of recurrent excitatory synapses in the neocortex: synapses that are activated a few milliseconds before a postsynaptic spike are potentiated, while those that are activated a few milliseconds after are depressed. We show that such a mechanism can implement a form of temporal difference learning for prediction of input sequences. Using a biophysical model of a cortical neuron, we show that a temporal difference rule used in conjunction with dendritic backpropagating action potentials reproduces the temporally asymmetric window of Hebbian plasticity observed physiologically. Furthermore, the size and shape of the window vary with the distance of the synapse from the soma. Using a simple example, we show how a spike-timing-based temporal difference learning rule can allow a network of neocortical neurons to predict an input a few milliseconds before the input's expected arrival.

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