Flexible Meso Electronics and Photonics Based on Cocoon Silk and Applications

Flexible electronics, applicable to enlarged health, AI big data medications, etc., have been one of the most important technologies of this century. Due to its particular mechanical properties, biocompatibility, and biodegradability, cocoon silk (or SF, silk fibroin) plays a key role in flexible electronics/photonics. The review begins with an examination of the hierarchical meso network structures of SF materials and introduces the concepts of meso reconstruction, meso doping, and meso hybridization based on the correlation between the structure and performance of silk materials. The SF meso functionalization was developed according to intermolecular nuclear templating. By implementation of the techniques of meso reconstruction and functionalization in the refolding of SF materials, extraordinary performance can be achieved. Relying on this strategy, particularly designed flexible electronic and photonic components can be developed. This review covers the latest ideas and technologies of meso flexible electronics and photonics based on SF materials/meso functionalization. As silk materials are biocompatible and human skin-friendly, SF meso flexible electronic/photonic components can be applied to wearable or implanted devices. These devices are applicable in human physiological signals and activities sensing/monitoring. In the case of human-machine interaction, the devices can be applicable in in-body information transmission, computation, and storage, with the potential for the combination of artificial intelligence and human intelligence.

3D intrusions transport active surface microbial assemblages to the dark ocean

Subtropical oceans contribute significantly to global primary production, but the fate of the picophytoplankton that dominate in these low-nutrient regions is poorly understood. Working in the subtropical Mediterranean, we demonstrate that subduction of water at ocean fronts generates 3D intrusions with uncharacteristically high carbon, chlorophyll, and oxygen that extend below the sunlit photic zone into the dark ocean. These contain fresh picophytoplankton assemblages that resemble the photic-zone regions where the water originated. Intrusions propagate depth-dependent seasonal variations in microbial assemblages into the ocean interior. Strikingly, the intrusions included dominant biomass contributions from nonphotosynthetic bacteria and enrichment of enigmatic heterotrophic bacterial lineages. Thus, the intrusions not only deliver material that differs in composition and nutritional character from sinking detrital particles, but also drive shifts in bacterial community composition, organic matter processing, and interactions between surface and deep communities. Modeling efforts paired with global observations demonstrate that subduction can flux similar magnitudes of particulate organic carbon as sinking export, but is not accounted for in current export estimates and carbon cycle models. Intrusions formed by subduction are a particularly important mechanism for enhancing connectivity between surface and upper mesopelagic ecosystems in stratified subtropical ocean environments that are expanding due to the warming climate.

Effective dispersal patterns in prairie plant species across human-modified landscapes

Effective dispersal among plant populations is dependent on vector behaviour, landscape features and availability of adequate habitats. To capture landscape feature effects on dispersal, studies must be conducted at scales reflecting single-generation dispersal events (mesoscale). Many studies are conducted at large scales where genetic differentiation is due to dispersal occurring over multiple generations, making it difficult to interpret the effects of specific landscape features on vector behaviour. Genetic structure at the mesoscale may be determined by ecological and evolutionary processes, such as the consequences of vector behaviour on patterns of gene flow. We used chloroplast haplotypes and nuclear genome SNP surveys to identify landscape features influencing seed and pollen dispersal at a mesoscale within the Rogue River Valley in southern Oregon. We evaluated biotic and abiotic vector behaviour by contrasting two annual species with differing dispersal mechanisms; Achyrachaena mollis (Asteraceae) is a self-pollinating and anemochoric species, and Plectritis congesta (Caprifoliaceae) is biotically pollinated with barochoric seeds. Using landscape genetics methods, we identified features of the study region that conduct or restrict dispersal. We found chloroplast haplotypes were indicative of historic patterns of gene flow prior to human modification of landscapes. Seed dispersal of A. mollis was best supported by models of isolation by distance, while seed-driven gene flow of P. congesta was determined by the distribution of preserved natural spaces and quality habitat. Nuclear genetic structure was driven by both pollen and seed dispersal, and both species responded to contemporary landscape changes, such as urban and agricultural conversion, and habitat availability.

Romer-EPTI: rotating-view motion-robust super-resolution EPTI for SNR-efficient distortion-free in-vivo mesoscale dMRI and microstructure imaging

Purpose

To overcome the major challenges in dMRI acquisition, including low SNR, distortion/blurring, and motion vulnerability.

Methods

A novel Romer-EPTI technique is developed to provide distortion-free dMRI with significant SNR gain, high motion-robustness, sharp spatial resolution, and simultaneous multi-TE imaging. It introduces a ROtating-view Motion-robust supEr-Resolution technique (Romer) combined with a distortion/blurring-free EPTI encoding. Romer enhances SNR by a simultaneous multi-thick-slice acquisition with rotating-view encoding, while providing high motion-robustness through a motion-aware super-resolution reconstruction, which also incorporates slice-profile and real-value diffusion, to resolve high-isotropic-resolution volumes. The in-plane encoding is performed using distortion/blurring-free EPTI, which further improves effective spatial resolution and motion robustness by preventing not only T2/T2*-blurring but also additional blurring resulting from combining encoded volumes with inconsistent geometries caused by dynamic distortions. Self-navigation was incorporated to enable efficient phase correction. Additional developments include strategies to address slab-boundary artifacts, achieve minimal TE for SNR gain at 7T, and achieve high robustness to strong phase variations at high b-values.

Results

Using Romer-EPTI, we demonstrate distortion-free whole-brain mesoscale in-vivo dMRI at both 3T (500-μm-iso) and 7T (485-μm-iso) for the first time, with high SNR efficiency (e.g., 25 × ), and high image quality free from distortion and slab-boundary artifacts with minimal blurring. Motion experiments demonstrate Romer-EPTI's high motion-robustness and ability to recover sharp images in the presence of motion. Romer-EPTI also demonstrates significant SNR gain and robustness in high b-value (b=5000s/mm2) and time-dependent dMRI.

Conclusion

Romer-EPTI significantly improves SNR, motion-robustness, and image quality, providing a highly efficient acquisition for high-resolution dMRI and microstructure imaging.

Between neurons and networks: investigating mesoscale brain connectivity in neurological and psychiatric disorders

The study of brain connectivity has been a cornerstone in understanding the complexities of neurological and psychiatric disorders. It has provided invaluable insights into the functional architecture of the brain and how it is perturbed in disorders. However, a persistent challenge has been achieving the proper spatial resolution, and developing computational algorithms to address biological questions at the multi-cellular level, a scale often referred to as the mesoscale. Historically, neuroimaging studies of brain connectivity have predominantly focused on the macroscale, providing insights into inter-regional brain connections but often falling short of resolving the intricacies of neural circuitry at the cellular or mesoscale level. This limitation has hindered our ability to fully comprehend the underlying mechanisms of neurological and psychiatric disorders and to develop targeted interventions. In light of this issue, our review manuscript seeks to bridge this critical gap by delving into the domain of mesoscale neuroimaging. We aim to provide a comprehensive overview of conditions affected by aberrant neural connections, image acquisition techniques, feature extraction, and data analysis methods that are specifically tailored to the mesoscale. We further delineate the potential of brain connectivity research to elucidate complex biological questions, with a particular focus on schizophrenia and epilepsy. This review encompasses topics such as dendritic spine quantification, single neuron morphology, and brain region connectivity. We aim to showcase the applicability and significance of mesoscale neuroimaging techniques in the field of neuroscience, highlighting their potential for gaining insights into the complexities of neurological and psychiatric disorders.

Mesoscience in Hollow Multi-Shelled Structures

The prevalence of mesoscale complexity in materials science underscores the significance of the compromise in competition principle, which gives rise to the emergence of mesoscience. This principle offers valuable insights into understanding the formation process, characteristics, and performance of complex material systems, ultimately guiding the future design of such intricate materials. Hollow multi-shelled structures (HoMS) represent a groundbreaking multifunctional structural system that encompasses several spatial regimes. A plethora of mesoscale cases within HoMS present remarkable opportunities for exploring, understanding, and utilizing mesoscience, varying from the formation process of HoMS, to the mesoscale structural parameters, and finally the distinctive mass/energy transfer behaviors exhibited by HoMS. The compromise in competition between the diffusion and reaction contributes to the successful formation of multi-shells of HoMS, allowing for precise regulation of the structural parameters by dynamically varying the interplay between two dominances. Moreover, the distinct roles played by the shells and cavities within HoMS significantly influence the energy/mass transfer processes with the unique temporal-spatial resolution, providing guidance for customizing the application performance. Hopefully, the empirical and theoretical anatomy of HoMS following mesoscience would fuel new discoveries within this promising and complex multifunctional material system.

(Nano)Granules-Involving Aggregation at a Passage to the Nanoscale as Viewed in Terms of a Diffusive Heisenberg Relation

We are looking at an aggregation of matter into granules. Diffusion plays a pivotal role here. When going down to the nanometer scale (the so-called nanoscale quantum-size effect limit), quantum mechanics, and the Heisenberg uncertainty relation, may take over the role of classical diffusion, as viewed typically in the mesoscopic/stochastic limit. A d-dimensional entropy-production aggregation of the granules-involving matter in the granule-size space is considered in terms of a (sub)diffusive realization. It turns out that when taking a full d-dimensional pathway of the aggregation toward the nanoscale, one is capable of disclosing a Heisenberg-type (diffusional) relation, setting up an upper uncertainty bound for the (sub)diffusive, very slow granules-including environment that, within the granule-size analogy invoked, matches the quantum limit of h/2πμ (μ-average mass of a granule; h-the Planck's constant) for the diffusion coefficient of the aggregation, first proposed by Fürth in 1933 and qualitatively foreseen by Schrödinger some years before, with both in the context of a diffusing particle. The classical quantum passage uncovered here, also termed insightfully as the quantum-size effect (as borrowed from the quantum dots' parlance), works properly for the three-dimensional (d = 3) case, making use of a substantial physical fact that the (nano)granules interact readily via their surfaces with the also-granular surroundings in which they are immersed. This natural observation is embodied in the basic averaging construction of the diffusion coefficient of the entropy-productive (nano)aggregation of interest.

Predicting the Elastic Modulus of Recycled Concrete Considering Material Nonuniformity: Mesoscale Numerical Method

The evaluation of the elastic modulus of recycled concrete is one of the focuses of civil engineering and structural engineering, which is not only related to the stability of building structures but also related to the resource utilization of concrete. Therefore, based on the IRSM method in mesoscale, a novel model for predicting the elastic modulus of recycled concrete is proposed which has the advantages of being low-cost and high-precision, amongst others, compared to theoretical and experimental methods. Then, the influence of coarse aggregate, contact surface, gelling material, and air bubbles on the elastic modulus of recycled concrete is studied. The IRSM model includes four processes: Identification, Reconstruction, Simulation, and Monte Carlo, which can accurately reconstruct the geometric characteristics of coarse aggregate, efficiently reconstruct the coarse aggregate accumulation model, and quickly analyze the elastic modulus of concrete, as well as fully consider the nonuniform characteristics of coarse aggregate distribution and shape. Compared with the experimental results, the error is less than 5%, which verifies the rationality of the IRSM method. The results of the parametric analysis show that the influence of each factor on the elastic modulus of concrete in descending order is elastic modulus of cement, elastic modulus of coarse aggregate, content of coarse aggregate, content of air voids, elastic modulus of contacting surface, and thickness of contacting surface, and the corresponding Pearson's Coefficients are 0.688, 0.427, 0.412, -0.269, 0.188, and -0.061, respectively, in which the content of air voids and thickness of contact surface have a negative effect on the elastic modulus of concrete. These influences mainly affect the deformation resistance (elastic modulus) of concrete through "force chain" adjustment, including the force transfer effect, number of paths, and integrity.

Using the power of innate immunoprofiling to understand vaccine design, infection, and immunity

In the field of immunology, a systems biology approach is crucial to understanding the immune response to infection and vaccination considering the complex interplay between genetic, epigenetic, and environmental factors. Significant progress has been made in understanding the innate immune response, including cell players and critical signaling pathways, but many questions remain unanswered, including how the innate immune response dictates host/pathogen responses and responses to vaccines. To complicate things further, it is becoming increasingly clear that the innate immune response is not a linear pathway but is formed from complex networks and interactions. To further our understanding of the crosstalk and complexities, systems-level analyses and expanded experimental technologies are now needed. In this review, we discuss the most recent immunoprofiling techniques and discuss systems approaches to studying the global innate immune landscape which will inform on the development of personalized medicine and innovative vaccine strategies.

Meso-Py: Dual Brain Cortical Calcium Imaging in Mice during Head-Fixed Social Stimulus Presentation

We present a cost-effective, compact foot-print, and open-source Raspberry Pi-based widefield imaging system. The compact nature allows the system to be used for close-proximity dual-brain cortical mesoscale functional-imaging to simultaneously observe activity in two head-fixed animals in a staged social touch-like interaction. We provide all schematics, code, and protocols for a rail system where head-fixed mice are brought together to a distance where the macrovibrissae of each mouse make contact. Cortical neuronal functional signals (GCaMP6s; genetically encoded Ca2+ sensor) were recorded from both mice simultaneously before, during, and after the social contact period. When the mice were together, we observed bouts of mutual whisking and cross-mouse correlated cortical activity across the cortex. Correlations were not observed in trial-shuffled mouse pairs, suggesting that correlated activity was specific to individual interactions. Whisking-related cortical signals were observed during the period where mice were together (closest contact). The effects of social stimulus presentation extend outside of regions associated with mutual touch and have global synchronizing effects on cortical activity.

How it feels in a cell

Life emerges from thousands of biochemical processes occurring within a shared intracellular environment. We have gained deep insights from in vitro reconstitution of isolated biochemical reactions. However, the reaction medium in test tubes is typically simple and diluted. The cell interior is far more complex: macromolecules occupy more than a third of the space, and energy-consuming processes agitate the cell interior. Here, we review how this crowded, active environment impacts the motion and assembly of macromolecules, with an emphasis on mesoscale particles (10-1000 nm diameter). We describe methods to probe and analyze the biophysical properties of cells and highlight how changes in these properties can impact physiology and signaling, and potentially contribute to aging, and diseases, including cancer and neurodegeneration.

Distinct Features of Interictal Activity Predict Seizure Localization and Burden in a Mouse Model of Childhood Epilepsy

The epileptic brain is distinguished by spontaneous seizures and interictal epileptiform discharges (IEDs). Basic patterns of mesoscale brain activity outside of seizures and IEDs are also frequently disrupted in the epileptic brain and likely influence disease symptoms, but are poorly understood. We aimed to quantify how interictal brain activity differs from that in healthy individuals, and identify what features of interictal activity influence seizure occurrence in a genetic mouse model of childhood epilepsy. Neural activity across the majority of the dorsal cortex was monitored with widefield Ca2+ imaging in mice of both sexes expressing a human Kcnt1 variant (Kcnt1m/m ) and wild-type controls (WT). Ca2+ signals during seizures and interictal periods were classified according to their spatiotemporal features. We identified 52 spontaneous seizures, which emerged and propagated within a consistent set of susceptible cortical areas, and were predicted by a concentration of total cortical activity within the emergence zone. Outside of seizures and IEDs, similar events were detected in Kcnt1m/m and WT mice, suggesting that the spatial structure of interictal activity is similar. However, the rate of events whose spatial profile overlapped with where seizures and IEDs emerged was increased, and the characteristic global intensity of cortical activity in individual Kcnt1m/m mice predicted their epileptic activity burden. This suggests that cortical areas with excessive interictal activity are vulnerable to seizures, but epilepsy is not an inevitable outcome. Global scaling of the intensity of cortical activity below levels found in the healthy brain may provide a natural mechanism of seizure protection.SIGNIFICANCE STATEMENT Defining the scope and structure of an epilepsy-causing gene variant's effects on mesoscale brain activity constitutes a major contribution to our understanding of how epileptic brains differ from healthy brains, and informs the development of precision epilepsy therapies. We provide a clear roadmap for measuring how severely brain activity deviates from normal, not only in pathologically active areas, but across large portions of the brain and outside of epileptic activity. This will indicate where and how activity needs to be modulated to holistically restore normal function. It also has the potential to reveal unintended off-target treatment effects and facilitate therapy optimization to deliver maximal benefit with minimal side-effect potential.

Imaging the columnar functional organization of human area MT+ to axis-of-motion stimuli using VASO at 7 Tesla

Cortical columns of direction-selective neurons in the motion sensitive area (MT) have been successfully established as a microscopic feature of the neocortex in animals. The same property has been investigated at mesoscale (<1 mm) in the homologous brain area (hMT+, V5) in living humans by using ultra-high field functional magnetic resonance imaging (fMRI). Despite the reproducibility of the selective response to axis-of-motion stimuli, clear quantitative evidence for the columnar organization of hMT+ is still lacking. Using cerebral blood volume (CBV)-sensitive fMRI at 7 Tesla with submillimeter resolution and high spatial specificity to microvasculature, we investigate the columnar functional organization of hMT+ in 5 participants perceiving axis-of-motion stimuli for both blood oxygenation level dependent (BOLD) and vascular space occupancy (VASO) contrast mechanisms provided by the used slice-selective slab-inversion (SS-SI)-VASO sequence. With the development of a new searchlight algorithm for column detection, we provide the first quantitative columnarity map that characterizes the entire 3D hMT+ volume. Using voxel-wise measures of sensitivity and specificity, we demonstrate the advantage of using CBV-sensitive fMRI to detect mesoscopic cortical features by revealing higher specificity of axis-of-motion cortical columns for VASO as compared to BOLD contrast. These voxel-wise metrics also provide further insights on how to mitigate the highly debated draining veins effect. We conclude that using CBV-VASO fMRI together with voxel-wise measurements of sensitivity, specificity and columnarity offers a promising avenue to quantify the mesoscopic organization of hMT+ with respect to axis-of-motion stimuli. Furthermore, our approach and methodological developments are generalizable and applicable to other human brain areas where similar mesoscopic research questions are addressed.

Acquisition and Analysis of Excised Neocortex from Pediatric Patients with Focal Cortical Dysplasia Using Mesoscale Diffusion MRI

Non-invasive classification of focal cortical dysplasia (FCD) subtypes remains challenging from a radiology perspective. Quantitative imaging biomarkers (QIBs) have the potential to distinguish subtypes that lack pathognomonic features and might help in defining the extent of abnormal connectivity associated with each FCD subtype. A key motivation of diagnostic imaging is to improve the localization of a "lesion" that can guide the surgical resection of affected tissue, which is thought to cause seizures. Conversely, surgical resections to eliminate or reduce seizures provided unique opportunities to develop magnetic resonance imaging (MRI)-based QIBs by affording long scan times to evaluate multiple contrast mechanisms at the mesoscale (0.5 mm isotropic voxel dimensions). Using ex vivo hybrid diffusion tensor imaging on a 9.4 T MRI scanner, the grey to white matter ratio of scalar indices was lower in the resected middle temporal gyrus (MTG) of two neuropathologically confirmed cases of FCD compared to non-diseased control postmortem fixed temporal lobes. In contrast, fractional anisotropy was increased within FCD and also adjacent white matter tracts. Connectivity (streamlines/mm³) in the MTG was higher in FCD, suggesting that an altered connectivity at the lesion locus can potentially provide a tangible QIB to distinguish and characterize FCD abnormalities. However, as illustrated here, a major challenge for a robust tractographical comparison lies in the considerable differences in the ex vivo processing of bioptic and postmortem samples. Mesoscale diffusion MRI has the potential to better define and characterize epileptic tissues obtained from surgical resection to advance our understanding of disease etiology and treatment.

Close, but not too close: a mesoscopic description of (a)symmetry and membrane shaping mechanisms

Biomembranes are fundamental to our understanding of the cell, the basic building block of all life. An intriguing aspect of membranes is their ability to assume a variety of shapes, which is crucial for cell function. Here, we review various membrane shaping mechanisms with special focus on the current understanding of how local curvature and local rigidity induced by membrane proteins leads to emerging forces and consequently large-scale membrane deformations. We also argue that describing the interaction of rigid proteins with membranes purely in terms of local membrane curvature is incomplete and that changes in the membrane rigidity moduli must also be considered.

Water-Reaching Platform for Longitudinal Assessment of Cortical Activity and Fine Motor Coordination Defects in a Huntington Disease Mouse Model

Huntington disease (HD), caused by dominantly inherited expansions of a CAG repeat results in characteristic motor dysfunction. Although gross motor defects have been extensively characterized in multiple HD mouse models using tasks such as rotarod and beam walking, less is known about forelimb deficits. We develop a high-throughput alternating reward/nonreward water-reaching task and training protocol conducted daily over approximately two months to simultaneously monitor forelimb impairment and mesoscale cortical changes in GCaMP activity, comparing female zQ175 (HD) and wild-type (WT) littermate mice, starting at ∼5.5 months. Behavioral analysis of the water-reaching task reveals that HD mice, despite learning the water-reaching task as proficiently as wild-type mice, take longer to learn the alternating event sequence as evident by impulsive (noncued) reaches and initially display reduced cortical activity associated with successful reaches. At this age gross motor defects determined by tapered beam assessment were not apparent. Although wild-type mice displayed no significant changes in cortical activity and reaching trajectory throughout the testing period, HD mice exhibited an increase in cortical activity, especially in the secondary motor and retrosplenial cortices, over time, as well as longer and more variable reaching trajectories by approximately seven months. HD mice also experienced a progressive reduction in successful performance. Tapered beam and rotarod tests as well as reduced DARPP-32 expression (striatal medium spiny neuron marker) after water-reaching assessment confirmed HD pathology. The water-reaching task can be used to inform on a daily basis, HD and other movement disorder onset and manifestation, therapeutic intervention windows, and test drug efficacy.

Head-mounted optical imaging and optogenetic stimulation system for use in behaving primates

Advances in optical technology have revolutionized studies of brain function in freely behaving mice. Here, we describe an optical imaging and stimulation device for use in primates that easily attaches to an intracranial chamber. It consists of affordable commercially available or 3D-printed components: a monochromatic camera, a small standard lens, a wireless μLED stimulator powered by an induction coil, and an LED array for illumination. We show that the intrinsic imaging performance of this device is comparable to a standard benchtop system in revealing the functional organization of the visual cortex for awake macaques in a primate chair or under anesthesia. Imaging revealed neural modulatory effects of wireless focal optogenetic stimulation aimed at identified functional domains. With a 1 to 2 cm field of view, 100× larger than previously used in primates without head restraint, our device permits widefield optical imaging and optogenetic stimulation for ethological studies in primates.

Investigating the Role of Amazonian Mesoscale Wind Patterns and Strength on the Spatial Distribution of Martian Bedrock Exposures

The Martian highlands contain Noachian-aged areally-extensive (>225 km²) bedrock exposures that have been mapped using thermal and visible imaging datasets. Given their age, crater density and impact gardening should have led to the formation of decameter scale layers of regolith that would overlie and bury these outcrops if composed of competent materials like basaltic lavas. However, many of these regions lack thick regolith layers and show clear exposures of bedrock materials with elevated thermal inertia values compared to the global average. Hypothesized reasons for the lack of regolith include: (a) relatively weaker material properties than lavas, where friable materials are comminuted and deflated during wind erosion, (b) long-term protection from regolith development through burial and later exhumation through one or more surface processes, and (c) spatially concentrated aeolian erosion and wind energetics on well-lithified basaltic substrates. To test the third hypothesis, we used the Mars Regional Atmospheric Modeling System to calculate wind erosive strength at 10 regions throughout the Martian highlands and compared it to their thermophysical properties by using thermal infrared data derived from the Thermal Emission Spectrometer to understand the effect that Amazonian mesoscale wind patterns may have on the exposure of bedrock. We also investigated the effect of planet obliquity, Ls of perihelion, and atmospheric mean pressure on wind erosion potential. We found no evidence for increased aeolian activity over bedrock-containing regions relative to surrounding terrains, including at the mafic floor unit at Jezero crater (Máaz formation), supporting the first or second hypotheses for these regions.

Oxygen Variability in the Offshore Northern Benguela Upwelling System From Glider Data

Despite their role in modulating the marine ecosystem, variability and drivers of low-oxygen events in the offshore northern Benguela Upwelling System (BenUS) have been rarely investigated due to the events' episodicity which is difficult to resolve using shipboard measurements. We address this issue using 4 months of high-resolution glider data collected between February and June 2018, 100 km offshore at 18°S. We find that oxygen (O₂) concentrations in the offshore northern Benguela are determined by the subsurface alternation of low-oxygen Angola-derived water and oxygenated water from the south at 100-500 m depth. We observe intermittent hypoxia (O₂ < 60 μmol kg^-1) which occurs on average for ∼30% of the 4 months deployment and is driven by the time-varying subsurface pulses of Angola-derived tropical water. Hypoxic events are rather persistent at depths of 300-450 m, while they are more sporadic and have weekly duration at shallower depths (100-300 m). We find extreme values of hypoxia, with O₂ minima of 16 μmol kg^-1, associated with an anticyclonic eddy spinning from the undercurrent flowing on the BenUS shelf and showing no surface signature. Fine-scale patchiness and water mass mixing are associated with cross-frontal stirring by a large anticyclone recirculating tropical water into the northern BenUS. The dominance of physical drivers and their high variability on short time scales reveal a dynamic coupling between Angola and Benguela, calling for long-term and high-resolution measurements and studies focusing on future changes of both tropical O₂ minima and lateral fluxes in this region.

Modeling Oxidation of AlCoCrFeNi High-Entropy Alloy Using Stochastic Cellular Automata

Together with the thermodynamics and kinetics, the complex microstructure of high-entropy alloys (HEAs) exerts a significant influence on the associated oxidation mechanisms in these concentrated solid solutions. To describe the surface oxidation in AlCoCrFeNi HEA, we employed a stochastic cellular automata model that replicates the mesoscale structures that form. The model benefits from diffusion coefficients of the principal elements through the native oxides predicted by using molecular simulations. Through our examination of the oxidation behavior as a function of the alloy composition, we corroborated that the oxide scale growth is a function of the complex chemistry and resultant microstructures. The effect of heat treatment on these alloys is also simulated by using reconstructed experimental micrographs. When they are in a single-crystal structure, no segregation is noted for α-Al₂O₃ and Cr₂O₃, which are the primary scale-forming oxides. However, a coexistent separation between Al₂O₃ and Cr₂O₃ oxide scales with the Al-Ni- and Cr-Fe-rich regions is predicted when phase-separated microstructures are incorporated into the model.

Layer-specific microstructural patterns of anterior hippocampus in Alzheimer's disease with ex vivo diffusion MRI at 14.1 T

High-resolution ex vivo diffusion MRI (dMRI) can provide exquisite mesoscopic details and microstructural information of the human brain. Microstructural pattern of the anterior part of human hippocampus, however, has not been well elucidated with ex vivo dMRI, either in normal or disease conditions. The present study collected high-resolution (0.1 mm isotropic) dMRI of post-mortem anterior hippocampal tissues from four Alzheimer's diseases (AD), three primary age-related tauopathy (PART), and three healthy control (HC) brains on a 14.1 T spectrometer. We evaluated how AD affected dMRI-based microstructural features in different layers and subfields of anterior hippocampus. In the HC samples, we found higher anisotropy, lower diffusivity, and more streamlines in the layers within cornu ammonis (CA) than those within dentate gyrus (DG). Comparisons between disease groups showed that (1) anisotropy measurements in the CA layers of AD, especially stratum lacunosum (SL) and stratum radiatum (SR), had higher regional variability than the other two groups; (2) streamline density in the DG layers showed a gradually increased variance from HC to PART to AD; (3) AD also showed the higher variability in terms of inter-layer connectivity than HC or PART. Moreover, voxelwise correlation analysis between the coregistered dMRI and histopathology images revealed significant correlations between dMRI measurements and the contents of amyloid beta (Aβ)/tau protein in specific layers of AD samples. These findings may reflect layer-specific microstructural characteristics in different hippocampal subfields at the mesoscopic resolution, which were associated with protein deposition in the anterior hippocampus of AD patients.

Active emulsions in living cell membranes driven by contractile stresses and transbilayer coupling

The spatiotemporal organization of proteins and lipids on the cell surface has direct functional consequences for signaling, sorting, and endocytosis. Earlier studies have shown that multiple types of membrane proteins, including transmembrane proteins that have cytoplasmic actin binding capacity and lipid-tethered glycosylphosphatidylinositol-anchored proteins (GPI-APs), form nanoscale clusters driven by active contractile flows generated by the actin cortex. To gain insight into the role of lipids in organizing membrane domains in living cells, we study the molecular interactions that promote the actively generated nanoclusters of GPI-APs and transmembrane proteins. This motivates a theoretical description, wherein a combination of active contractile stresses and transbilayer coupling drives the creation of active emulsions, mesoscale liquid order (lo) domains of the GPI-APs and lipids, at temperatures greater than equilibrium lipid phase segregation. To test these ideas, we use spatial imaging of molecular clustering combined with local membrane order, and we demonstrate that mesoscopic domains enriched in nanoclusters of GPI-APs are maintained by cortical actin activity and transbilayer interactions and exhibit significant lipid order, consistent with predictions of the active composite model.

Combining Cortical Voltage Imaging and Hippocampal Electrophysiology for Investigating Global, Multi-Timescale Activity Interactions in the Brain

A new generation of optogenetic tools for analyzing neural activity has been contributing to the elucidation of classical open questions in neuroscience. Specifically, voltage imaging technologies using enhanced genetically encoded voltage indicators have been increasingly used to observe the dynamics of large circuits at the mesoscale. Here, we describe how to combine cortical wide-field voltage imaging with hippocampal electrophysiology in awake, behaving mice. Furthermore, we highlight how this method can be useful for different possible investigations, using the characterization of hippocampal–neocortical interactions as a case study.

Challenges and advances in optical 3D mesoscale imaging

Optical mesoscale imaging is a rapidly developing field that allows the visualisation of larger samples than is possible with standard light microscopy, and fills a gap between cell and organism resolution. It spans from advanced fluorescence imaging of micrometric cell clusters to centimetre-size complete organisms. However, with larger volume specimens, new problems arise. Imaging deeper into tissues at high resolution poses challenges ranging from optical distortions to shadowing from opaque structures. This manuscript discusses the latest developments in mesoscale imaging and highlights limitations, namely labelling, clearing, absorption, scattering, and also sample handling. We then focus on approaches that seek to turn mesoscale imaging into a more quantitative technique, analogous to quantitative tomography in medical imaging, highlighting a future role for digital and physical phantoms as well as artificial intelligence.

The Diurnal Path to Persistent Convective Self-Aggregation

Clustering of tropical thunderstorms constitutes an important climate feedback because it influences the radiative balance. Convective self-aggregation (CSA) is a profound modeling paradigm for explaining the clustering of tropical oceanic thunderstorms. However, CSA is hampered in the realistic limit of fine model resolution when cold pools-dense air masses beneath thunderstorm clouds-are well-resolved. Studies on CSA usually assume the surface temperature to be constant, despite realistic surface temperatures varying significantly between night and day. Here we mimic the diurnal cycle in cloud-resolving numerical experiments by prescribing a surface temperature oscillation. Our simulations show that the diurnal cycle enables CSA at fine resolutions, and that the process is even accelerated by finer resolutions. We attribute these findings to vigorous combined cold pools emerging in symbiosis with mesoscale convective systems. Such cold pools suppress buoyancy in extended regions (∼100 km) and enable the formation of persistent dry patches. Our findings help clarify how the tropical cloud field forms sustained clusters under the diurnal forcing and may have implications for the origin of extreme thunderstorm rainfall and tropical cyclones.

The mesoscale order of nacreous pearls

A pearl's distinguished beauty and toughness are attributable to the periodic stacking of aragonite tablets known as nacre. Nacre has naturally occurring mesoscale periodicity that remarkably arises in the absence of discrete translational symmetry. Gleaning the inspiring biomineral design of a pearl requires quantifying its structural coherence and understanding the stochastic processes that influence formation. By characterizing the entire structure of pearls (∼3 mm) in a cross-section at high resolution, we show that nacre has medium-range mesoscale periodicity. Self-correcting growth mechanisms actively remedy disorder and topological defects of the tablets and act as a countervailing process to long-range disorder. Nacre has a correlation length of roughly 16 tablets (∼5.5 µm) despite persistent fluctuations and topological defects. For longer distances (>25 tablets , ∼8.5 µm), the frequency spectrum of nacre tablets follows [Formula: see text] behavior, suggesting that growth is coupled to external stochastic processes-a universality found across disparate natural phenomena, which now includes pearls.

High resolution stereolithography fabrication of perfusable scaffolds to enable long-term meso-scale hepatic culture for disease modeling

Microphysiological systems (MPS), comprising human cell cultured in formats that capture features of the three-dimensional (3D) microenvironments of native human organs under microperfusion, are promising tools for biomedical research. Here we report the development of a mesoscale physiological system (MePS) enabling the long-term 3D perfused culture of primary human hepatocytes at scales of over 10⁶cells per MPS. A central feature of the MePS, which employs a commercially-available multiwell bioreactor for perfusion, is a novel scaffold comprising a dense network of nano- and micro-porous polymer channels, designed to provide appropriate convective and diffusive mass transfer of oxygen and other nutrients while maintaining physiological values of shear stress. The scaffold design is realized by a high resolution stereolithography fabrication process employing a novel resin. This new culture system sustains mesoscopic hepatic tissue-like cultures with greater hepatic functionality (assessed by albumin and urea synthesis, and CYP3A4 activity) and lower inflammation markers compared to comparable cultures on the commercial polystyrene scaffold. To illustrate applications to disease modeling, we established an insulin-resistant phenotype by exposing liver cells to hyperglycemic and hyperinsulinemic media. Future applications of the MePS include the co-culture of hepatocytes with resident immune cells and the integration with multiple organs to model complex liver-associated diseases.

Understanding the Role of Endothelial Glycocalyx in Mechanotransduction via Computational Simulation: A Mini Review

Endothelial glycocalyx (EG) is a forest-like structure, covering the lumen side of blood vessel walls. EG is exposed to the mechanical forces of blood flow, mainly shear, and closely associated with vascular regulation, health, diseases, and therapies. One hallmark function of the EG is mechanotransduction, which means the EG senses the mechanical signals from the blood flow and then transmits the signals into the cells. Using numerical modelling methods or in silico experiments to investigate EG-related topics has gained increasing momentum in recent years, thanks to tremendous progress in supercomputing. Numerical modelling and simulation allows certain very specific or even extreme conditions to be fulfilled, which provides new insights and complements experimental observations. This mini review examines the application of numerical methods in EG-related studies, focusing on how computer simulation contributes to the understanding of EG as a mechanotransducer. The numerical methods covered in this review include macroscopic (i.e., continuum-based), mesoscopic [e.g., lattice Boltzmann method (LBM) and dissipative particle dynamics (DPD)] and microscopic [e.g., molecular dynamics (MD) and Monte Carlo (MC) methods]. Accounting for the emerging trends in artificial intelligence and the advent of exascale computing, the future of numerical simulation for EG-related problems is also contemplated.

Mesoscale Mechanisms in Viscoplastic Deformation of Metals and Their Applications to Constitutive Models

Deformation of metals has attracted great interest for a long time. However, the constitutive models for viscoplastic deformation at high strain rates are still under intensive development, and more physical mechanisms are expected to be involved. In this work, we employ the newly-proposed methodology of mesoscience to identify the mechanisms governing the mesoscale complexity of collective dislocations, and then apply them to improving constitutive models. Through analyzing the competing effects of various processes on the mesoscale behavior, we have recognized two competing mechanisms governing the mesoscale complex behavior of dislocations, i.e., maximization of the rate of plastic work, and minimization of the elastic energy. Relevant understandings have also been discussed. Extremal expressions have been proposed for these two mesoscale mechanisms, respectively, and a stability condition for mesoscale structures has been established through a recently-proposed mathematical technique, considering the compromise between the two competing mechanisms. Such a stability condition, as an additional constraint, has been employed subsequently to close a two-phase model mimicking the practical dislocation cells, and thus to take into account the heterogeneous distributions of dislocations. This scheme has been exemplified in three increasingly complicated constitutive models, and improves the agreements of their results with experimental ones.

Reduced Order Multiscale Simulation of Diffuse Damage in Concrete

Damage in concrete structures initiates as the growth of diffuse microcracks that is followed by damage localisation and eventually leads to structural failure. Weak changes such as diffuse microcracking processes are failure precursors. Identification and characterisation of these failure precursors at an early stage of concrete degradation and application of suitable precautionary measures will considerably reduce the costs of repair and maintenance. To this end, a reduced order multiscale model for simulating microcracking-induced damage in concrete at the mesoscale level is proposed. The model simulates the propagation of microcracks in concrete using a two-scale computational methodology. First, a realistic concrete specimen that explicitly resolves the coarse aggregates in a mortar matrix was generated at the mesoscale. Microcrack growth in the mortar matrix is modelled using a synthesis of continuum micromechanics and fracture mechanics. Model order reduction of the two-scale model is achieved using a clustering technique. Model predictions are calibrated and validated using uniaxial compression tests performed in the laboratory.

Computational Generation of Virtual Concrete Mesostructures

Concrete is a heterogeneous material with a disordered material morphology that strongly governs the behaviour of the material. In this contribution, we present a computational tool called the Concrete Mesostructure Generator (CMG) for the generation of ultra-realistic virtual concrete morphologies for mesoscale and multiscale computational modelling and the simulation of concrete. Given an aggregate size distribution, realistic generic concrete aggregates are generated by a sequential reduction of a cuboid to generate a polyhedron with multiple faces. Thereafter, concave depressions are introduced in the polyhedron using Gaussian surfaces. The generated aggregates are assembled into the mesostructure using a hierarchic random sequential adsorption algorithm. The virtual mesostructures are first calibrated using laboratory measurements of aggregate distributions. The model is validated by comparing the elastic properties obtained from laboratory testing of concrete specimens with the elastic properties obtained using computational homogenisation of virtual concrete mesostructures. Finally, a 3D-convolutional neural network is trained to directly generate elastic properties from voxel data.

Mesoscale Process Modeling of a Thick Pultruded Composite with Variability in Fiber Volume Fraction

Pultruded fiber-reinforced polymer composites are susceptible to microstructural nonuniformity such as variability in fiber volume fraction (Vf), which can have a profound effect on process-induced residual stress. Until now, this effect of non-uniform Vf distribution has been hardly addressed in the process models. In the present study, we characterized the Vf distribution and accompanying nonuniformity in a unidirectional fiber-reinforced pultruded profile using optical light microscopy. The identified nonuniformity in Vf was subsequently implemented in a mesoscale thermal-chemical-mechanical process model, developed explicitly for the pultrusion process. In our process model, the constitutive material behavior was defined locally with respect to the corresponding fiber volume fraction value in different-sized representative volume elements. The effect of nonuniformity on the temperature and cure degree evolution, and residual stress was analyzed in depth. The results show that the nonuniformity in fiber volume fraction across the cross-section increased the absolute magnitude of the predicted residual stress, leading to a more scattered residual stress distribution. The observed Vf gradient promotes tensile residual stress at the core and compressive residual stress at the outer regions. Consequently, it is concluded that it is essential to take the effects of nonuniformity in fiber distribution into account for residual stress estimations, and the proposed numerical framework was found to be an efficient tool to study this aspect.

Cellular and Widefield Imaging of Sound Frequency Organization in Primary and Higher Order Fields of the Mouse Auditory Cortex

The mouse auditory cortex (ACtx) contains two core fields-primary auditory cortex (A1) and anterior auditory field (AAF)-arranged in a mirror reversal tonotopic gradient. The best frequency (BF) organization and naming scheme for additional higher order fields remain a matter of debate, as does the correspondence between smoothly varying global tonotopy and heterogeneity in local cellular tuning. Here, we performed chronic widefield and two-photon calcium imaging from the ACtx of awake Thy1-GCaMP6s reporter mice. Data-driven parcellation of widefield maps identified five fields, including a previously unidentified area at the ventral posterior extreme of the ACtx (VPAF) and a tonotopically organized suprarhinal auditory field (SRAF) that extended laterally as far as ectorhinal cortex. Widefield maps were stable over time, where single pixel BFs fluctuated by less than 0.5 octaves throughout a 1-month imaging period. After accounting for neuropil signal and frequency tuning strength, BF organization in neighboring layer 2/3 neurons was intermediate to the heterogeneous salt and pepper organization and the highly precise local organization that have each been described in prior studies. Multiscale imaging data suggest there is no ultrasonic field or secondary auditory cortex in the mouse. Instead, VPAF and a dorsal posterior (DP) field emerged as the strongest candidates for higher order auditory areas.

Key Points in Air Pollution Meteorology

Although emissions have a direct impact on air pollution, meteorological processes may influence inmission concentration, with the only way to control air pollution being through the rates emitted. This paper presents the close relationship between air pollution and meteorology following the scales of atmospheric motion. In macroscale, this review focuses on the synoptic pattern, since certain weather types are related to pollution episodes, with the determination of these weather types being the key point of these studies. The contrasting contribution of cold fronts is also presented, whilst mathematical models are seen to increase the analysis possibilities of pollution transport. In mesoscale, land-sea and mountain-valley breezes may reinforce certain pollution episodes, and recirculation processes are sometimes favoured by orographic features. The urban heat island is also considered, since the formation of mesovortices determines the entry of pollutants into the city. At the microscale, the influence of the boundary layer height and its evolution are evaluated; in particular, the contribution of the low-level jet to pollutant transport and dispersion. Local meteorological variables have a major influence on calculations with the Gaussian plume model, whilst some eddies are features exclusive to urban environments. Finally, the impact of air pollution on meteorology is briefly commented on.

Mesoscale diffusion magnetic resonance imaging of the ex vivo human hippocampus

Mesoscale diffusion magnetic resonance imaging (MRI) endeavors to bridge the gap between macroscopic white matter tractography and microscopic studies investigating the cytoarchitecture of human brain tissue. To ensure a robust measurement of diffusion at the mesoscale, acquisition parameters were arrayed to investigate their effects on scalar indices (mean, radial, axial diffusivity, and fractional anisotropy) and streamlines (i.e., graphical representation of axonal tracts) in hippocampal layers. A mesoscale resolution afforded segementation of the pyramidal cell layer (CA1-4), the dentate gyrus, as well as stratum moleculare, radiatum, and oriens. Using ex vivo samples, surgically excised from patients with intractable epilepsy (n = 3), we found that shorter diffusion times (23.7 ms) with a b-value of 4,000 s/mm2 were advantageous at the mesoscale, providing a compromise between mean diffusivity and fractional anisotropy measurements. Spatial resolution and sample orientation exerted a major effect on tractography, whereas the number of diffusion gradient encoding directions minimally affected scalar indices and streamline density. A sample temperature of 15°C provided a compromise between increasing signal-to-noise ratio and increasing the diffusion properties of the tissue. Optimization of the acquisition afforded a system's view of intra- and extra-hippocampal connections. Tractography reflected histological boundaries of hippocampal layers. Individual layer connectivity was visualized, as well as streamlines emanating from individual sub-fields. The perforant path, subiculum and angular bundle demonstrated extra-hippocampal connections. Histology of the samples confirmed individual cell layers corresponding to ROIs defined on MR images. We anticipate that this ex vivo mesoscale imaging will yield novel insights into human hippocampal connectivity.

3D Mesoscale Finite Element Modelling of Concrete under Uniaxial Loadings

Concrete exhibits a complex mechanical behavior, especially when approaching failure. Its behavior is governed by the interaction of the heterogeneous structures of the material at the first level of observation below the homogeneous continuum, i.e., at the mesoscale. Concrete is assumed to be a three-phase composite of coarse aggregates, mortar, and the interfacial transitional zone (ITZ) between them. Finite element modeling on a mesoscale requires appropriate meshes that discretize the three concrete components. As the weakest link in concrete, ITZ plays an important role. However, meshing ITZ is a challenging issue, due to its very reduced thickness. Representing ITZ with solid elements of such reduced size would produce very expensive finite element meshes. An alternative is to represent ITZ as zero-thickness interface elements. This work adopts interface elements for ITZ. Damage plasticity model is adopted to describe the softening behavior of mortar in compression, while cohesive fractures describe the cracking process. Numerical experiments are presented. First example deals with the estimation of concrete Young’s modulus. Experimental tests were performed to support the numerical test. A second experiment simulates a uniaxial compression test and last experiment simulates a uniaxial tensile test, where results are compared to data from the literature.

Exploring the dynamics of flagellar dynein within the axoneme with Fluctuating Finite Element Analysis

Flagellar dyneins are the molecular motors responsible for producing the propagating bending motions of cilia and flagella. They are located within a densely packed and highly organised super-macromolecular cytoskeletal structure known as the axoneme. Using the mesoscale simulation technique Fluctuating Finite Element Analysis (FFEA), which represents proteins as viscoelastic continuum objects subject to explicit thermal noise, we have quantified the constraints on the range of molecular conformations that can be explored by dynein-c within the crowded architecture of the axoneme. We subsequently assess the influence of crowding on the 3D exploration of microtubule-binding sites, and specifically on the axial step length. Our calculations combine experimental information on the shape, flexibility and environment of dynein-c from three distinct sources; negative stain electron microscopy, cryo-electron microscopy (cryo-EM) and cryo-electron tomography (cryo-ET). Our FFEA simulations show that the super-macromolecular organisation of multiple protein complexes into higher-order structures can have a significant influence on the effective flexibility of the individual molecular components, and may, therefore, play an important role in the physical mechanisms underlying their biological function.

Ex vivo mesoscopic diffusion MRI correlates with seizure frequency in patients with uncontrolled mesial temporal lobe epilepsy

The role of hippocampal connectivity in mesial temporal lobe epilepsy (mTLE) remains poorly understood. The use of ex vivo hippocampal samples excised from patients with mTLE affords mesoscale diffusion magnetic resonance imaging (MRI) to identify individual cell layers, such as the pyramidal (PCL) and granule cell layers (GCL), which are thought to be impacted by seizure activity. Diffusion tensor imaging (DTI) of control (n = 3) and mTLE (n = 7) hippocampi on an 11.7 T MRI scanner allowed us to reveal intra‐hippocampal connectivity and evaluate how epilepsy affected mean (MD), axial (AD), and radial diffusivity (RD), as well as fractional anisotropy (FA). Regional measurements indicated a volume loss in the PCL of the cornu ammonis (CA) 1 subfield in mTLE patients compared to controls, which provided anatomical context. Diffusion measurements, as well as streamline density, were generally higher in mTLE patients compared to controls, potentially reflecting differences due to tissue fixation. mTLE measurements were more variable than controls. This variability was associated with disease severity, as indicated by a strong correlation (r = 0.87) between FA in the stratum radiatum and the frequency of seizures in patients. MD and RD of the PCL in subfields CA3 and CA4 also correlated strongly with disease severity. No correlation of MR measures with disease duration was evident. These results reveal the potential of mesoscale diffusion MRI to examine layer‐specific diffusion changes and connectivity to determine how these relate to clinical measures. Improving the visualization of intra‐hippocampal connectivity will advance the development of novel hypotheses about seizure networks.

BRICseq Bridges Brain-wide Interregional Connectivity to Neural Activity and Gene Expression in Single Animals

Comprehensive analysis of neuronal networks requires brain-wide measurement of connectivity, activity, and gene expression. Although high-throughput methods are available for mapping brain-wide activity and transcriptomes, comparable methods for mapping region-to-region connectivity remain slow and expensive because they require averaging across hundreds of brains. Here we describe BRICseq (brain-wide individual animal connectome sequencing), which leverages DNA barcoding and sequencing to map connectivity from single individuals in a few weeks and at low cost. Applying BRICseq to the mouse neocortex, we find that region-to-region connectivity provides a simple bridge relating transcriptome to activity: the spatial expression patterns of a few genes predict region-to-region connectivity, and connectivity predicts activity correlations. We also exploited BRICseq to map the mutant BTBR mouse brain, which lacks a corpus callosum, and recapitulated its known connectopathies. BRICseq allows individual laboratories to compare how age, sex, environment, genetics, and species affect neuronal wiring and to integrate these with functional activity and gene expression.

Robust Multiscale Identification of Apparent Elastic Properties at Mesoscale for Random Heterogeneous Materials with Multiscale Field Measurements

The aim of this work is to efficiently and robustly solve the statistical inverse problem related to the identification of the elastic properties at both macroscopic and mesoscopic scales of heterogeneous anisotropic materials with a complex microstructure that usually cannot be properly described in terms of their mechanical constituents at microscale. Within the context of linear elasticity theory, the apparent elasticity tensor field at a given mesoscale is modeled by a prior non-Gaussian tensor-valued random field. A general methodology using multiscale displacement field measurements simultaneously made at both macroscale and mesoscale has been recently proposed for the identification the hyperparameters of such a prior stochastic model by solving a multiscale statistical inverse problem using a stochastic computational model and some information from displacement fields at both macroscale and mesoscale. This paper contributes to the improvement of the computational efficiency, accuracy and robustness of such a method by introducing (i) a mesoscopic numerical indicator related to the spatial correlation length(s) of kinematic fields, allowing the time-consuming global optimization algorithm (genetic algorithm) used in a previous work to be replaced with a more efficient algorithm and (ii) an ad hoc stochastic representation of the hyperparameters involved in the prior stochastic model in order to enhance both the robustness and the precision of the statistical inverse identification method. Finally, the proposed improved method is first validated on in silico materials within the framework of 2D plane stress and 3D linear elasticity (using multiscale simulated data obtained through numerical computations) and then exemplified on a real heterogeneous biological material (beef cortical bone) within the framework of 2D plane stress linear elasticity (using multiscale experimental data obtained through mechanical testing monitored by digital image correlation).

Automated task training and longitudinal monitoring of mouse mesoscale cortical circuits using home cages

We report improved automated open-source methodology for head-fixed mesoscale cortical imaging and/or behavioral training of home cage mice using Raspberry Pi-based hardware. Staged partial and probabilistic restraint allows mice to adjust to self-initiated headfixation over 3 weeks' time with ~50% participation rate. We support a cue-based behavioral licking task monitored by a capacitive touch-sensor water spout. While automatically head-fixed, we acquire spontaneous, movement-triggered, or licking task-evoked GCaMP6 cortical signals. An analysis pipeline marked both behavioral events, as well as analyzed brain fluorescence signals as they relate to spontaneous and/or task-evoked behavioral activity. Mice were trained to suppress licking and wait for cues that marked the delivery of water. Correct rewarded go-trials were associated with widespread activation of midline and lateral barrel cortex areas following a vibration cue and delayed frontal and lateral motor cortex activation. Cortical GCaMP signals predicted trial success and correlated strongly with trial-outcome dependent body movements.

Plasmonic nanoparticles assemblies templated by helical bacteria and resulting optical activity

Plasmonic nanoparticles (NPs) adsorbing onto helical bacteria can lead to formation of NP helicoids with micron scale pitch. Associated chiroptical effects can be utilized as bioanalytical tool for bacterial detection and better understanding of the spectral behavior of helical self-assembled structures with different scales. Here, we report that enantiomerically pure helices with micron scale of chirality can be assembled on Campylobacter jejuni, a helical bacterium known for severe stomach infections. These organisms have right-handed helical shapes with a pitch of 1-2 microns and can serve as versatile templates for a variety of NPs. The bacteria itself shows no observable rotatory activity in the visible, red, and near-IR ranges of electromagnetic spectrum. The bacterial dispersion acquires chiroptical activity at 500-750 nm upon plasmonic functionalization with Au NPs. Finite-difference time-domain simulations confirmed the attribution of the chiroptical activity to the helical assembly of gold nanoparticles. The position of the circular dichroism peaks observed for these chiral structures overlaps with those obtained before for Au NPs and their constructs with molecular and nanoscale chirality. This work provides an experimental and computational pathway to utilize chiroplasmonic particles assembled on bacteria for bioanalytical purposes.

Mesoscale Simulation to Study Constitutive Properties of TATB/F2314 PBX

Material Point Method (MPM) mesoscale simulation was used to study the constitutive relation of a polymer bonded explosive (PBX) consisting of 1,3,5-triamino-2,4,6-trinitrobenzene (TATB) and a fluorine polymer binder F2314. The stress-strain variations of the PBX were calculated for different temperatures and different porosities, and the results were found to be consistent with experimental observations. The stress-strain relations at different temperatures were used to develop the constitutive equation of the PBX by using numerical data fitting. Stress-strain data for different porosities were used to establish the constitutive equation by fitting the simulation data to an improved Hashion-Shtrikman model. The equation can be used to predict the shear modulus and bulk modulus of the PBX at different densities of the sample. The constitutive equations developed for TATB/F2314 PBX by MPM mesoscale simulation are important equations for the numerical simulations of the PBX at macroscale. The method presented in this study provides an alternative approach for studying the constitutive relations of PBX.

Macro- and mesoscale pattern interdependencies in complex networks

Identifying and explaining the structure of complex networks at different scales has become an important problem across disciplines. At the mesoscale, modular architecture has attracted most of the attention. At the macroscale, other arrangements-e.g. nestedness or core-periphery-have been studied in parallel, but to a much lesser extent. However, empirical evidence increasingly suggests that characterizing a network with a unique pattern typology may be too simplistic, since a system can integrate properties from distinct organizations at different scales. Here, we explore the relationship between some of these different organizational patterns: two at the mesoscale (modularity and in-block nestedness); and one at the macroscale (nestedness). We show experimentally and analytically that nestedness imposes bounds to modularity, with exact analytical results in idealized scenarios. Specifically, we show that nestedness and modularity are interdependent. Furthermore, we analytically evidence that in-block nestedness provides a natural combination between nested and modular networks, taking structural properties of both. Far from a mere theoretical exercise, understanding the boundaries that discriminate each architecture is fundamental, to the extent that modularity and nestedness are known to place heavy dynamical effects on processes, such as species abundances and stability in ecology.

Longitudinal monitoring of mesoscopic cortical activity in a mouse model of microinfarcts reveals dissociations with behavioral and motor function

Small vessel disease is characterized by sporadic obstruction of small vessels leading to neuronal cell death. These microinfarcts often escape detection by conventional magnetic resonance imaging and are identified only upon postmortem examination. Our work explores a brain-wide microinfarct model in awake head-fixed mice, where occlusions of small penetrating arterioles are reproduced by endovascular injection of fluorescent microspheres. Mesoscopic functional connectivity was mapped longitudinally in awake GCaMP6 mice using genetically encoded calcium indicators for transcranial wide-field calcium imaging. Microsphere occlusions were quantified and changes in cerebral blood flow were measured with laser speckle imaging. The neurodeficit score in microinfarct mice was significantly higher than in sham, indicating impairment in motor function. The novel object recognition test showed a reduction in the discrimination index in microinfarct mice compared to sham. Graph-theoretic analysis of functional connectivity did not reveal significant differences in functional connectivity between sham and microinfarct mice. While behavioral tasks revealed impairments following microinfarct induction, the absence of measurable functional alterations in cortical activity has a less straightforward interpretation. The behavioral alterations produced by this model are consistent with alterations observed in human patients suffering from microinfarcts and support the validity of microsphere injection as a microinfarct model.

Phytoplankton Community Structure Is Driven by Stratification in the Oligotrophic Mediterranean Sea

The phytoplankton community composition, structure, and biomass were investigated under stratified and oligotrophic conditions during summer for three consecutive years in the Mediterranean Sea. Our results reveal that the phytoplankton community structure was strongly influenced by vertical stratification. The thermocline separated two different phytoplankton communities in the two layers of the euphotic zone, characterized by different nutrient and light availability. Picoplankton dominated in terms of abundance and biomass at all the stations sampled and throughout the photic zone. However, the structure of the picoplanktonic community changed with depth, with Synechococcus and heterotrophic prokaryotes dominating in surface waters down to the base of the thermocline, and Prochlorococcus and picoeukaryotes contributing relatively more to the community in the deep chlorophyll maximum (DCM). Light and nutrient availability also influenced the communities at the DCM layer. Prochlorococcus prevailed in deeper DCM waters characterized by lower light intensities and higher picophytoplankton abundance was related to lower nutrient concentrations at the DCM. Picoeukaryotes were the major phytoplankton contributors to carbon biomass at surface (up to 80%) and at DCM (more than 40%). Besides, contrarily to the other phytoplankton groups, picoeukaryotes cell size progressively decreased with depth. Our research shows that stratification is a major factor determining the phytoplankton community structure; and underlines the role that picoeukaryotes might play in the carbon flux through the marine food web, with implications for the community metabolism and carbon fate in the ecosystem.

A high-throughput neurohistological pipeline for brain-wide mesoscale connectivity mapping of the common marmoset

Understanding the connectivity architecture of entire vertebrate brains is a fundamental but difficult task. Here we present an integrated neuro-histological pipeline as well as a grid-based tracer injection strategy for systematic mesoscale connectivity mapping in the common marmoset (Callithrix jacchus). Individual brains are sectioned into ~1700 20 µm sections using the tape transfer technique, permitting high quality 3D reconstruction of a series of histochemical stains (Nissl, myelin) interleaved with tracer labeled sections. Systematic in-vivo MRI of the individual animals facilitates injection placement into reference-atlas defined anatomical compartments. Further, by combining the resulting 3D volumes, containing informative cytoarchitectonic markers, with in-vivo and ex-vivo MRI, and using an integrated computational pipeline, we are able to accurately map individual brains into a common reference atlas despite the significant individual variation. This approach will facilitate the systematic assembly of a mesoscale connectivity matrix together with unprecedented 3D reconstructions of brain-wide projection patterns in a primate brain.

Graphene Foam: Hole-Flake Network for Uniaxial Supercompression and Recovery Behavior

We employed the coarse-grained molecular dynamics simulation method to systematically study the uniaxial supercompression and recovery behavior of multiporous graphene foam, in which a mesoscopic three-dimensional network with hole-graphene flakes was proposed. The network model not only considers the physical cross-links and interlayer van der Waals interactions, but also introduces a hole in the flake to approach the imperfection of pristine graphene and the hierarchical porous configuration of real foam material. We first recreated a typical two-stage supercompression stress-strain relationship and the corresponding time-dependent recovery as well as a U-type nominal Poisson ratio. Then the recovery unloading at different strains and multicycle compression-uncompression were both conducted; the initial elastic moduli in the multicycles were found to be the same, and a multilevel residual strain was disclosed. Importantly, the residual strain is not exactly the plastic one, part of which can resurrect in the subsequent loading-unloading-holding. The mesoscopic mechanism of viscoelastic and residual deformation for the recovery can be attributed to the van der Waals repulsion and mechanical interlocking among the hole-flakes; interestingly, the local tensile stress was observed in the virial stress distribution. Particularly, an abnormal turning point in the length-time curve for the mean bead-bond length was captured during the supercompression. After the point, the length abnormally increases for different size ratios of the hole to the flake, which is in line with the mesostructure evolution. The finding may provide a mesoscopic criterion for the supercompression of graphene foam related materials.

Mesoscale structure, mechanics, and transport properties of source rocks' organic pore networks

In source rocks, natural hydrocarbons are generated from organic matter dispersed in a fine-grained mineral matrix. The potential recovery of hydrocarbons is therefore influenced by the geometry of the organic hosted porous networks. Here, the three-dimensional structures of such networks are revealed using electron tomography with a subnanometer resolution. The reconstructions are first characterized in terms of morphology and topology and then used to build a multiscale simulation tool to study the mechanics and the transport properties of confined fluids. Our results offer evidence of the prevalent role of connected nanopores, which subsequently constitutes a material limit for long-term hydrocarbon production.

Organic matter is responsible for the generation of hydrocarbons during the thermal maturation of source rock formation. This geochemical process engenders a network of organic hosted pores that governs the flow of hydrocarbons from the organic matter to fractures created during the stimulation of production wells. Therefore, it can be reasonably assumed that predictions of potentially recoverable confined hydrocarbons depend on the geometry of this pore network. Here, we analyze mesoscale structures of three organic porous networks at different thermal maturities. We use electron tomography with subnanometric resolution to characterize their morphology and topology. Our 3D reconstructions confirm the formation of nanopores and reveal increasingly tortuous and connected pore networks in the process of thermal maturation. We then turn the binarized reconstructions into lattice models including information from atomistic simulations to derive mechanical and confined fluid transport properties. Specifically, we highlight the influence of adsorbed fluids on the elastic response. The resulting elastic energy concentrations are localized at the vicinity of macropores at low maturity whereas these concentrations present more homogeneous distributions at higher thermal maturities, due to pores’ topology. The lattice models finally allow us to capture the effect of sorption on diffusion mechanisms with a sole input of network geometry. Eventually, we corroborate the dominant impact of diffusion occurring within the connected nanopores, which constitute the limiting factor of confined hydrocarbon transport in source rocks.

Recent highlights in nanoscale and mesoscale friction

Friction is the oldest branch of non-equilibrium condensed matter physics and, at the same time, the least established at the fundamental level. A full understanding and control of friction is increasingly recognized to involve all relevant size and time scales. We review here some recent advances on the research focusing of nano- and mesoscale tribology phenomena. These advances are currently pursued in a multifaceted approach starting from the fundamental atomic-scale friction and mechanical control of specific single-asperity combinations, e.g., nanoclusters on layered materials, then scaling up to the meso/microscale of extended, occasionally lubricated, interfaces and driven trapped optical systems, and eventually up to the macroscale. Currently, this "hot" research field is leading to new technological advances in the area of engineering and materials science.