Single Dendrite Research Articles

Dendrite injury triggers neuroprotection in Drosophila models of neurodegenerative disease.

Dendrite defects and loss are early cellular alterations observed across neurodegenerative diseases that play a role in early disease pathogenesis. Dendrite degeneration can be modeled by expressing pathogenic polyglutamine disease transgenes in Drosophila neurons in vivo. Here, we show that we can protect against dendrite loss in neurons modeling neurodegenerative polyglutamine diseases through injury to a single primary dendrite branch. We find that this neuroprotection is specific to injury-induced activation of dendrite regeneration: neither injury to the axon nor injury just to surrounding tissues induces this response. We show that the mechanism of this regenerative response is stabilization of the actin (but not microtubule) cytoskeleton. We also demonstrate that this regenerative response may extend to other neurodegenerative diseases. Together, we provide evidence that activating dendrite regeneration pathways has the potential to slow-or even reverse-dendrite loss in neurodegenerative disease.

Rab6-Mediated Polarized Transport of Synaptic Vesicle Precursors Is Essential for the Establishment of Neuronal Polarity and Brain Formation.

Neurons are highly polarized cells that are composed of a single axon and multiple dendrites. Axon-dendrite polarity is essential for proper tissue formation and brain functions. Intracellular protein transport plays an important role in the establishment of neuronal polarity. However, the regulatory mechanism of polarized transport remains unclear. Here, we show that Rab6, a small GTPase that acts on the regulation of intracellular vesicular trafficking, plays key roles in neuronal polarization and brain development. Central nervous system-specific Rab6a/b double knock-out (Rab6 DKO) mice of both sexes exhibit severe dysplasia of the neocortex and the cerebellum. In the Rab6 DKO neocortex, impaired axonal extension of neurons results in hypoplasia of the intermediate zone. In vitro, deletion of Rab6a and Rab6b in cultured neurons from both sexes causes the abnormal accumulation of synaptic vesicle precursors (SVPs) adjacent to the Golgi apparatus, which leads to defects in axonal extension and the loss of axon-dendrite polarity. Moreover, Rab6 DKO causes significant expansion of lysosomes in the soma in neurons. Overall, our results reveal that Rab6-mediated polarized transport of SVPs is crucial for neuronal polarization and subsequent brain formation.

On different implementations of boundary conditions in the meshless RBF-FD method for phase-field modelling of dendritic solidification

Dendritic morphology is one of the most common microstructures in solidifying metallic materials. The phase-field method represents one of the most suitable approaches for modelling the evolution of dendritic morphology. In this paper, the meshless RBF-FD method and forward Euler scheme are used to solve the partial differential equations arising from the phase-field model for dendritic growth. We consider the growth of a single dendrite into a supercooled pure melt. On the computational domain’s surfaces, we apply symmetric boundary conditions. Special care has to be taken in the RBF-FD method to satisfy boundary conditions accurately. In this paper, we test four different implementations of boundary conditions. In the first one, the boundary conditions are incorporated when constructing an interpolation problem in local support domains containing boundary nodes. In the second one, the interpolation problem in the local support domains does not consider boundary conditions, which are satisfied by solving a system of linear equations for values in all boundary nodes at each time step. The third one complements the second one with the use of ghost nodes. The fourth implementation is an alternative one, where the values in ghost nodes are determined by direct mirroring. The accuracy and computational efficiency of all four implementations are compared. We discuss the advantages and disadvantages of each implementation. We show that using ghost nodes is recommended for implementing Neumann boundary conditions in the RBF-FD method.

Characterization of Kinetics-Controlled Morphologies in the Growth of Silver Crystals from a Primary Lead Melt

Silver, a precious metal, can be recovered as a by-product of the processing of non-ferrous metals such as lead. In this work, silver crystals grown from the controlled cooling of a 10% silver–90% lead melt have been examined to quantify crystal morphologies developed under industrial conditions. X-ray tomography (XCT) is adapted to quantify the size and morphology of silver crystal structures grown from the Ag-Pb melt. The examination utilized high X-ray energies and small sample sizes to mitigate attenuation and enhance image quality. Examination of single crystal dendrites under high magnification demonstrates that silver crystals, even those grown under commercial conditions, yield a Face-Centered Cubic (FCC) crystalline lattice, which could be important for the practical extension of this work to the commercial production of Ag nano-crystals and crystalline supra-molecular structures. The crystals observed are composed of multiple twinned euhedral grains in a variety of dendritic to acicular arrangements, yielding a substantial heterogeneity of crystalline forms. XCT data were used to generate size and shape descriptors for the individual crystals. The results were compared to an equivalent set of descriptors generated from laser sizing examination of a sample of unconsolidated crystals from the same experimental run. The correspondence to within 9% of the crystal equivalent diameters determined independently by the XCT and laser sizing demonstrates a favorable outcome in particle sizing as achieved by visual inspection of XCT results. XCT examination of crystal assemblages identifies small octahedral crystals and larger triangular platelets. The structures expected for FCC crystals grown at thermodynamically controlled conditions are not observed in our systems, suggesting the possibility of the first crystal nuclei form at such conditions, but their growth transition to kinetically controlled mechanisms occurs as their size increases above a threshold cutoff. Based on literature observations, this size threshold is much smaller than the resolution of the XCT instrumentation employed herein. Our characterization data are in fact consistent with thermodynamics/kinetics—and then kinetics-controlled mechanisms—as the crystal size increases. This observation is important because the systems considered here are representative of commercial processes. As such, this work extends prior crystal growth concepts, which were explored in aqueous systems often probed by electrodeposition.

In Vitro and In Vivo Analysis of Neuronal Polarity.

Neuronal development is characterized by the unidirectional flow of signal from the axon to the dendrites via synapses. Neuronal polarization is a critical step during development that allows the specification of the different neuronal processes as a single axon and multiple dendrites both structurally and functionally, allowing the unidirectional flow of information. Along with extrinsic and intrinsic signaling, a whole network of molecular complexes involved in positive and negative feedback loops play a major role in this critical distinction of neuronal processes. As a result, neuronal morphology is drastically altered during establishment of polarity. In this chapter, we discuss how we can analyze the morphological alterations of neurons in vitro in culture to assess the development and polarity status of the neuron. We also discuss how these studies can be conducted in vivo, where polarity studies pose a greater challenge with promising results for addressing multiple pathological conditions. Our experimental model is limited to rodent hippocampal/cortical neurons in culture and cortical neurons in brain tissues, which are well-characterized model systems for understanding neuronal polarization.

Effect of the Nb content on the microstructure evolution and properties of the CrFeCoNiNbx layers prepared by laser cladding

Marine engineering components, such as ship stern shafts, are often subject to local overload, wear and seawater erosion. In order to improve the performance and service life of marine engineering components, the CrFeCoNiNb x ( x = 0, 0.25, 0.5, 0.75 and 1) high-entropy alloy (HEA) coating were prepared on the 42CrMo substrate by laser cladding. The microstructure, microhardness, wear behaviour and the corrosion resistance of the prepared HEA coatings with different Nb contents were evaluated. Results show that the cladding layer of CrFeCoNiNb0 is composed of single dendrites with a small amount of short rod-shaped protrusions distributed along the dendrites. The addition of Nb promotes growing of the original dendrite structures into interdendritic structures with internal substructures retained. Apart from the variations in the microstructure, the formation of the Laves phase, which is both hard and corrosion resistant, is also an important factor in the performance of the cladding. This variation leads to the increase of the microhardness of the cladding layer, accompanying with the improvement of wear resistance property. Notably, the improvement of microhardness is ascribed to the combined contribution from the refinement strengthening, the solid-solution strengthening and the dispersion strengthening by Laves phase. The improvement of the corrosion resistance is mainly attributed to dense passivation film formed by the Cr and Nb on the surface of the cladding layer. The above results suggest that the CrFeCoNiNb x cladding layer could achieve synergistic interaction between the mechanical properties and the corrosion resistance on stern shaft surface.

Growth mechanism of highly twinned Al13Fe4 dendrites obtained from a rapidly solidified Al-5at.% Fe melt

We report the formation of large and highly twinned dendrites of the Al13Fe4 approximant phase embedded in an fcc Al-rich matrix. Using a rapid cooling technique, the approximant appears as a 10-fold dendrite. Within each arm, all grains share a common [010] direction. The grain distributions within the arm are quite complex and a single dendrite arm can contain up to four different orientations. Using several techniques, including Electron Back-Scattered Diffraction (EBSD) and Transmission Electron Microscopy (TEM), it has been possible to identify three types of twins, namely {100}, {001} and {201̄} twins. From these observations and previous reports, we propose a growth mechanism to explain the formation of such specific 10-fold motifs. It corresponds to the heteroepitaxial growth of the Al13Fe4 approximant from a well-facetted decagonal Al–Fe quasicrystalline seed.

Microglia are dispensable for developmental dendrite pruning of mitral cells in mice.

During early development, neurons in the brain often form excess synaptic connections. Later, they strengthen some connections while eliminating others to build functional neuronal circuits. In the olfactory bulb, a mitral cell initially extends multiple dendrites to multiple glomeruli but eventually forms a single primary dendrite through the activity-dependent dendrite pruning process. Recent studies have reported that microglia facilitate synapse pruning during the circuit remodeling in some systems. It has remained unclear whether microglia are involved in the activity-dependent dendrite pruning in the developing brains. Here, we examined whether microglia are required for the developmental dendrite pruning of mitral cells in mice. To deplete microglia in the fetal brain, we treated mice with a CSF1R inhibitor, PLX5622, from pregnancy. Microglia were reduced by >90% in mice treated with PLX5622. However, dendrite pruning of mitral cells was not significantly affected. Moreover, we found no significant differences in the number, density, and size of excitatory synapses formed in mitral cell dendrites. We also found no evidence for the role of microglia in the activity-dependent dendrite remodeling of layer 4 neurons in the barrel cortex. In contrast, the density of excitatory synapses (dendritic spines) in granule cells in the olfactory bulb was significantly increased in mice treated with PLX5622 at P6, suggesting a role for the regulation of dendritic spines. Our results indicate that microglia do not play a critical role in activity-dependent dendrite pruning at the neurite level during early postnatal development in mice.Significance StatementSynapse elimination is essential for activity-dependent circuit remodeling in the developing brains of mammals. Recent studies suggested that microglia play a critical role in the synapse elimination. This study found that microglia are dispensable for the activity-dependent dendrite pruning in developing mitral cells and layer 4 neurons in the barrel cortex. Thus, microglia are not critical for activity-dependent dendrite pruning at the neurite level during normal developmental process.

A Crystallographic Basis for Critically Evaluating the Mechanisms for Secondary Grain Formation During Directional Solidification

AbstractA crystallography-based method is presented for the critical appraisal of possible mechanisms that trigger the formation of secondary grains during directional solidification. The method permits an analysis of a large population of defects, while avoiding the pitfalls of the metallographic sectioning approach that is affected by dendrite stereology. Here, the nickel-base superalloy CMSX-4, an alloy commonly used for single crystal turbine blade applications, is studied. All secondary grains originate exclusively at the external surface and when the off-axial primary $$\langle 0\,0\,1\rangle$$ ⟨ 0 0 1 ⟩ crystal orientations are measured, are evident at both the converging and diverging dispositions of the single crystal primary dendrites without a noticeable bias. Almost all of the secondary grains have low misorientations, with an average misorientation between 5 to 15 deg. No systematic deviation between the individual $$\langle 0\,0\,1\rangle$$ ⟨ 0 0 1 ⟩ orientations of the secondary grain and the single crystal is observed. A significant twist contribution about an axis within ~ 30 deg from one of the secondary arms occurs when primary arms converge on the external surface, but both twist and tilt prevail for the diverging case. Both nucleation and buoyancy driven thermo-solutal convection can be eliminated as potential mechanisms. Thermo-mechanical deformation is deduced to be the most likely mechanism; deformation must originate in the vicinity of the primary dendrite tips. It is proposed that dendrite deflection arises primarily from the resistance encountered by the primary tips with the external surface during axial contraction in the presence of a dominant vertical thermal gradient.

A mathematical study of the efficacy of possible negative feedback pathways involved in neuronal polarization

Neuronal polarization, a process wherein nascent neurons develop a single long axon and multiple short dendrites, can occur within in vitro cell cultures without environmental cues. This is an apparently random process in which one of several short processes, called neurites, grows to become long, while the others remain short. In this study, we propose a minimum model for neurite growth, which involves bistability and random excitations reflecting actin waves. Positive feedback is needed to produce the bistability, while negative feedback is required to ensure that no more than one neurite wins the winner-takes-all contest. By applying the negative feedback to different aspects of the neurite growth process, we demonstrate that targeting the negative feedback to the excitation amplitude results in the most persistent polarization. Also, we demonstrate that there are optimal ranges of values for the neurite count, and for the excitation rate and amplitude that best maintain the polarization. Finally, we show that a previously published model for neuronal polarization based on competition for limited resources shares key features with our best-performing minimal model: bistability and negative feedback targeted to the size of random excitations.

Application of a meshless space-time adaptive approach to phase-field modelling of polycrystalline solidification

We have developed a 2-D numerical meshless adaptive approach for phase-field modelling of dendritic solidification. The quadtree-based approach decomposes the computational domain into quadtree sub-domains of different sizes. The algorithm generates uniformly-distributed computational nodes in each quadtree sub-domain. We apply the meshless radial basis function generated finite difference method and the forward Euler scheme to discretise governing equations in each computational node. The fixed ratio between the characteristic size and the node spacing of a quadtree sub-domain ensures space adaptivity. The adaptive time-stepping accelerates the calculations further. In the framework of previous research studies, we used the approach to solve quantitative phase-field models for single dendrite growth in pure melts and dilute binary alloys. In the present study, we upgrade the solution procedure for the modelling growth of multiple differently oriented dendrites. Along with the space-time adaptive approach, we apply non-linear preconditioning of the phase-field equation to increase computational efficiency. We investigate a novel numerical approach’s accuracy and computational efficiency by simulating the equiaxed dendrite growth from a dilute binary alloy.

Initiation of dendritic NMDA spikes co-regulated via distance-dependent and dynamic distribution of the spine number and morphology in neuron dendrites

Dendritic spines are small membranous protrusions that receive synaptic inputs from other neurons, enabling the initiation of dendritic N-methyl-D-aspartic (NMDA) spikes and somatic action potentials. During learning and memory processes, both the number of spines on a dendrite and the morphology of individual spines are constantly changing. The individual influence of spine number and morphology on dendritic NMDA spikes has already been revealed, but the functional significance of the co-regulation of spine number and morphology on NMDA spikes remains elusive. Here, we systematically investigated the initiation of local dendritic NMDA spikes by the dynamic distributions of the spine number and morphology on single dendrites in reconstructed neuron models. Different from the traditional cognition, we found the threshold number of spines required to generate local dendrite NMDA spikes on distal dendrites is fewer than that on proximal ones, because the thinner distal dendrites own higher impedance. As for the spine morphology, the presence of more α-amino-3-hydroxy-5-methyl-4-isoxazole-propionic acid (AMPA) receptors on the spine leads to larger NMDA spikes rather than an increase in the spine dimension alone. Furthermore, we first suggested that a single dendrite containing spines with gradually increasing head diameters away from the soma could generate larger NMDA spikes than that irrational distribution of spine morphology containing spines with decreasing head diameters, which can be compensated by the increasing spine number. Complementarily, the distance-dependent distribution of spine number and morphology co-regulate the intension of dendritic NMDA spikes. These findings about the threshold for NMDA spikes provide novel insights into the role of the irrational dynamic distribution of the spine number and morphology in senescence and disease processes such as Alzheimer’s disease, schizophrenia, and Parkinson’s disease, which causes abnormal neuron firing.

Methodology for development of single cell dendritic spine (SCDS) synaptic tagging and capture model using Virtual Cell (VCell)

Single cell dendritic spine modelling methodology has been adopted to explain structural plasticity and respective change in the neuronal volume previously. However, the single cell dendrite methodology has not been employed previously to explain one of the important aspects of memory allocation i.e., Synaptic tagging and Capture (STC) hypothesis. It is difficult to relate the physical properties of STC pathways to structural changes and synaptic strength. We create a mathematical model based on earlier reported synaptic tagging networks. We built the model using Virtual Cell (VCell) software and used it to interpret experimental data and investigate the behavior and characteristics of known Synaptic tagging candidates.•We investigate processes associated with synaptic tagging candidates and compare them to the assumptions based on the STC hypothesis.•We assess the behavior of several reported synaptic tagging candidates against the requirements outlined in the synaptic tagging hypothesis.

Revealing Morphology Evolution of Lithium Dendrites by Large‐Scale Simulation Based on Machine Learning Force Field

AbstractSolving the dendrite growth problem is critical for the development of lithium metal anode for high‐capacity batteries. In this work, a machine learning force field model in combination with a self‐consistent continuum solvation model is used to simulate the morphology evolution of dendrites in a working electrolyte environment. The dynamic evolution of the dendrite morphology can be described in two stages. In the first stage, the energy reduction of the surface atoms induces localized reorientation of the originally single‐crystal dendrite and the formation of multiple domains. In the second stage, the energy reduction of internal atoms drives the migration of grain boundaries and the slipping of crystal domains. The results indicate that the formation of multiple domains might help to stabilize the dendrite, as a higher temperature trajectory in a single crystal dendrite without domains shows a higher dendrite collapsing rate. Several possible modes of morphological evolutions are also investigated, including surface diffusion of adatoms and configuration twists from [100] exposed surfaces to [110] exposed surfaces. In summary, reducing the surface and grain boundary energy drives the morphology evolution. Based on the analysis of these driving forces, some guidelines are suggested for designing a more stable lithium metal anode.

N-WASP-Arp2/3 signaling controls multiple steps of dendrite maturation in Purkinje cells in vivo.

During neural development, the actin filament network must be precisely regulated to form elaborate neurite structures. N-WASP tightly controls actin polymerization dynamics by activating an actin nucleator Arp2/3. However, the importance of N-WASP-Arp2/3 signaling in the assembly of neurite architecture in vivo has not been clarified. Here, we demonstrate that N-WASP-Arp2/3 signaling plays a crucial role in the maturation of cerebellar Purkinje cell (PC) dendrites in vivo in mice. N-WASP was expressed and activated in developing PCs. Inhibition of Arp2/3 and N-WASP from the beginning of dendrite formation severely disrupted the establishment of a single stem dendrite, which is a characteristic basic structure of PC dendrites. Inhibition of Arp2/3 after stem dendrite formation resulted in hypoplasia of the PC dendritic tree. Cdc42, an upstream activator of N-WASP, is required for N-WASP-Arp2/3 signaling-mediated PC dendrite maturation. In addition, overactivation of N-WASP is also detrimental to dendrite formation in PCs. These findings reveal that proper activation of N-WASP-Arp2/3 signaling is crucial for multiple steps of PC dendrite maturation in vivo.

Operando Optoelectrochemical Analysis of Single Zinc Dendrites with a Reflective Nanopore Electrode.

Dendrites can severely impair zinc battery performance. An in-depth understanding of the dynamic morphology evolution of dendrites with operando approaches is pivotal when addressing these issues. However, in previous studies, the corresponding electrochemical signals are usually ensemble and averaged. It is very challenging to obtain detailed information about the key morphology-performance relationship. Herein, correlated high-resolution operando optical and electrochemical studies of single dendrites on Pt reflective nanopore electrodes are reported. The zinc deposition and dissolution can be directly imaged by a high NA optical microscope, while corresponding galvanic charging and discharging curves are obtained. The correlated information of morphology changes and dynamic overpotential fluctuations under different circumstances unveils the competition between active growth vs. passivation. The isolated zinc formation at the single dendrite level is also evaluated. The methodology can be further extended to elucidate the direct relationship between dendrite evolution and electrochemical responses in various battery systems.

Phase Field Simulation Research on the Microstructural Evolution of Monocrystalline and Polycrystalline Silicon

This work simulates the morphological evolution process of the solidification interface of silicon crystal. Based on the phase field model of single dendrite growth of pure material in a single-phase system, the control equation of the phase field is re-optimized, and an interface free energy anisotropy equation that can simulate the competitive growth of multiple crystal grains is established. The competitive growth of polysilicon is then simulated and analyzed. The results show that when the degree of undercooling exceeds a certain value, the non-facet crystals are transformed into facet crystals. The main branches in each direction are relatively thick when the anisotropy is small. With increasing anisotropy, the main branches in each direction show gradual thinning, and edges and corners appear on the interface. The dendrites are no longer smooth, and they transform from non-facet crystals to facet crystals. The main branches of different grains inhibit each other when multiple crystal grains compete for growth. The growth of the main branches is curved, which is different from existing branches. The experimental results can more realistically simulate the evolution process of single-crystal silicon and polycrystalline silicon crystal micromorphology.

Nanostructure of the Interphase Layer between a Single Li Dendrite and Sulfide Electrolyte in All-Solid-State Li Batteries

Nanostructure of the Interphase Layer between a Single Li Dendrite and Sulfide Electrolyte in All-Solid-State Li Batteries

Dendritic Morphology Affects the Velocity and Amplitude of Back-propagating Action Potentials

The back-propagating action potential (bpAP) is crucial for neuronal signal integration and synaptic plasticity in dendritic trees. Its properties (velocity and amplitude) can be affected by dendritic morphology. Due to limited spatial resolution, it has been difficult to explore the specific propagation process of bpAPs along dendrites and examine the influence of dendritic morphology, such as the dendrite diameter and branching pattern, using patch-clamp recording. By taking advantage of Optopatch, an all-optical electrophysiological method, we made detailed recordings of the real-time propagation of bpAPs in dendritic trees. We found that the velocity of bpAPs was not uniform in a single dendrite, and the bpAP velocity differed among distinct dendrites of the same neuron. The velocity of a bpAP was positively correlated with the diameter of the dendrite on which it propagated. In addition, when bpAPs passed through a dendritic branch point, their velocity decreased significantly. Similar to velocity, the amplitude of bpAPs was also positively correlated with dendritic diameter, and the attenuation patterns of bpAPs differed among different dendrites. Simulation results from neuron models with different dendritic morphology corresponded well with the experimental results. These findings indicate that the dendritic diameter and branching pattern significantly influence the properties of bpAPs. The diversity among the bpAPs recorded in different neurons was mainly due to differences in dendritic morphology. These results may inspire the construction of neuronal models to predict the propagation of bpAPs in dendrites with enormous variation in morphology, to further illuminate the role of bpAPs in neuronal communication.

Efficient dendritic learning as an alternative to synaptic plasticity hypothesis

Synaptic plasticity is a long-lasting core hypothesis of brain learning that suggests local adaptation between two connecting neurons and forms the foundation of machine learning. The main complexity of synaptic plasticity is that synapses and dendrites connect neurons in series and existing experiments cannot pinpoint the significant imprinted adaptation location. We showed efficient backpropagation and Hebbian learning on dendritic trees, inspired by experimental-based evidence, for sub-dendritic adaptation and its nonlinear amplification. It has proven to achieve success rates approaching unity for handwritten digits recognition, indicating realization of deep learning even by a single dendrite or neuron. Additionally, dendritic amplification practically generates an exponential number of input crosses, higher-order interactions, with the number of inputs, which enhance success rates. However, direct implementation of a large number of the cross weights and their exhaustive manipulation independently is beyond existing and anticipated computational power. Hence, a new type of nonlinear adaptive dendritic hardware for imitating dendritic learning and estimating the computational capability of the brain must be built.