Notes on molecular fragmentation and parameter settings for a dissipative particle dynamics study of a C(10)E(4)/water mixture with lamellar bilayer formation

The influence of molecular fragmentation and parameter settings on a mesoscopic dissipative particle dynamics (DPD) simulation of lamellar bilayer formation for a C₁₀E₄/water mixture is studied. A "bottom-up" decomposition of C₁₀E₄ into the smallest fragment molecules (particles) that satisfy chemical intuition leads to convincing simulation results which agree with experimental findings for bilayer formation and thickness. For integration of the equations of motion Shardlow's S1 scheme proves to be a favorable choice with best overall performance. Increasing the integration time steps above the common setting of 0.04 DPD units leads to increasingly unphysical temperature drifts, but also to increasingly rapid formation of bilayer superstructures without significantly distorted particle distributions up to an integration time step of 0.12. A scaling of the mutual particle-particle repulsions that guide the dynamics has negligible influence within a considerable range of values but exhibits apparent lower thresholds beyond which a simulation fails. Repulsion parameter scaling and molecular particle decomposition show a mutual dependence. For mapping of concentrations to molecule numbers in the simulation box particle volume scaling should be taken into account. A repulsion parameter morphing investigation suggests to not overstretch repulsion parameter accuracy considerations.

Mesoscopic in vivo human T(2)(*) dataset acquired using quantitative MRI at 7 Tesla

Mesoscopic (0.1-0.5 mm) interrogation of the living human brain is critical for advancing neuroscience and bridging the resolution gap with animal models. Despite the variety of MRI contrasts measured in recent years at the mesoscopic scale, in vivo quantitative imaging of T₂^* has not been performed. Here we provide a dataset containing empirical T₂^* measurements acquired at 0.35 × 0.35 × 0.35 mm³ voxel resolution using 7 Tesla MRI. To demonstrate unique features and high quality of this dataset, we generate flat map visualizations that reveal fine-scale cortical substructures such as layers and vessels, and we report quantitative depth-dependent T₂^* (as well as R₂^*) values in primary visual cortex and auditory cortex that are highly consistent across subjects. This dataset is freely available at https://doi.org/10.17605/OSF.IO/N5BJ7, and may prove useful for anatomical investigations of the human brain, as well as for improving our understanding of the basis of the T₂^*-weighted (f)MRI signal.

Multi-scale network imaging in a mouse model of amyloidosis

The adult neocortex is not hard-wired but instead retains the capacity to reorganise across multiple spatial scales long into adulthood. Plastic reorganisation occurs at the level of mesoscopic sensory maps, functional neuronal assemblies and synaptic ensembles and is thought to be a critical feature of neuronal network function. Here, we describe a series of approaches that use calcium imaging to measure network reorganisation across multiple spatial scales in vivo. At the mesoscopic level, we demonstrate that sensory activity can be measured in animals undergoing longitudinal behavioural assessment involving automated touchscreen tasks. At the cellular level, we show that network dynamics can be longitudinally measured at both stable and transient functional assemblies. At the level of single synapses, we show that functional subcellular calcium imaging approaches can be used to measure synaptic ensembles of dendritic spines in vivo. Finally, we demonstrate that all three levels of imaging can be spatially related to local pathology in a preclinical rodent model of amyloidosis. We propose that multi-scale in vivo calcium imaging can be used to measure parallel plasticity processes operating across multiple spatial scales in both the healthy brain and preclinical models of disease.

Jdpd: an open java simulation kernel for molecular fragment dissipative particle dynamics

Jdpd is an open Java simulation kernel for Molecular Fragment Dissipative Particle Dynamics with parallelizable force calculation, efficient caching options and fast property calculations. It is characterized by an interface and factory-pattern driven design for simple code changes and may help to avoid problems of polyglot programming. Detailed input/output communication, parallelization and process control as well as internal logging capabilities for debugging purposes are supported. The new kernel may be utilized in different simulation environments ranging from flexible scripting solutions up to fully integrated “all-in-one” simulation systems.

New rapid, accurate T2 quantification detects pathology in normal-appearing brain regions of relapsing-remitting MS patients

Introduction

Quantitative T₂ mapping may provide an objective biomarker for occult nervous tissue pathology in relapsing-remitting multiple sclerosis (RRMS). We applied a novel echo modulation curve (EMC) algorithm to identify T₂ changes in normal-appearing brain regions of subjects with RRMS (N = 27) compared to age-matched controls (N = 38).

Methods

The EMC algorithm uses Bloch simulations to model T₂ decay curves in multi-spin-echo MRI sequences, independent of scanner, and scan-settings. T₂ values were extracted from normal-appearing white and gray matter brain regions using both expert manual regions-of-interest and user-independent FreeSurfer segmentation.

Results

Compared to conventional exponential T₂ modeling, EMC fitting provided more accurate estimations of T₂ with less variance across scans, MRI systems, and healthy individuals. Thalamic T₂ was increased 8.5% in RRMS subjects (p < 0.001) and could be used to discriminate RRMS from healthy controls well (AUC = 0.913). Manual segmentation detected both statistically significant increases (corpus callosum & temporal stem) and decreases (posterior limb internal capsule) in T₂ associated with RRMS diagnosis (all p < 0.05). In healthy controls, we also observed statistically significant T₂ differences for different white and gray matter structures.

Conclusions

The EMC algorithm precisely characterizes T₂ values, and is able to detect subtle T₂ changes in normal-appearing brain regions of RRMS patients. These presumably capture both axon and myelin changes from inflammation and neurodegeneration. Further, T₂ variations between different brain regions of healthy controls may correlate with distinct nervous tissue environments that differ from one another at a mesoscopic length-scale.

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EMC technique provides accurate and scanner-invariant T₂ mapping in MS subjects.

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Thalamus T₂ differences distinguish relapsing-remitting MS subjects from controls.

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Normal-appearing brain regions demonstrate T₂ changes in MS patients compared to controls.

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T₂ values reflect anatomic and function-specific differences in healthy controls.

Thermal-mechanical-chemical responses of polymer-bonded explosives using a mesoscopic reactive model under impact loading

A mesoscopic framework is developed to quantify the thermal-mechanical-chemical responses of polymer-bonded explosive (PBX) samples under impact loading. A mesoscopic reactive model is developed for the cyclotetramethylenetetranitramine (HMX) crystal, which incorporates nonlinear elasticity, crystal plasticity, and temperature-dependent chemical reaction. The proposed model was implemented in the finite element code ABAQUS by the user subroutine VUMAT. A series of three-dimensional mesoscale models were constructed and calculated under low-strength impact loading scenarios from 100m/s to 600m/s where only the first wave transit is studied. Crystal anisotropy and microstructural heterogeneity are responsible for the nonuniform stress field and fluctuations of the stress wave front. At a critical impact velocity (≥300m/s), a chemical reaction is triggered because the temperature contributed by the volumetric and plastic works is sufficiently high. Physical quantities, including stress, temperature, and extent of reaction, are homogenized from those across the microstructure at the mesoscale to compare with macroscale measurements, which will advance the continuum-level models. The framework presented in this study has important implications in understanding hot spot ignition processes and improving predictive capabilities in energetic materials.

Innovating e-waste management: From macroscopic to microscopic scales

Waste electrical and electronic equipment (WEEE or e-waste) has become a global problem, due to its potential environmental pollution and human health risk, and its containing valuable resources (e.g., metals, plastics). Recycling for e-waste will be a necessity, not only to address the shortage of mineral resources for electronics industry, but also to decline environmental pollution and human health risk. To systematically solve the e-waste problem, more attention of e-waste management should transfer from macroscopic to microscopic scales. E-waste processing technology should be significantly improved to diminish and even avoid toxic substance entering into downstream of material. The regulation or policy related to new production of hazardous substances in recycled materials should also be carried out on the agenda. All the findings can hopefully improve WEEE legislation for regulated countries and non-regulated countries.

Emergence in the central nervous system

"Emergence" is an idea that has received much attention in consciousness literature, but it is difficult to find characterizations of that concept which are both specific and useful. I will precisely define and characterize a type of epistemic ("weak") emergence and show that it is a property of some neural circuits throughout the CNS, on micro-, meso- and macroscopic levels. I will argue that possession of this property can result in profoundly altered neural dynamics on multiple levels in cortex and other systems. I will first describe emergent neural entities (ENEs) abstractly. I will then show how ENEs function specifically and concretely, and demonstrate some implications of this type of emergence for the CNS.