3D Architectural Analysis of Neurons, Astrocytes, Vasculature & Nuclei in the Motor and Somatosensory Murine Cortical Columns

Characterization of the complex cortical structure of the brain at a cellular level is a fundamental goal of neuroscience which can provide a better understanding of both normal function as well as disease state progression. Many challenges exist however when carrying out this form of analysis. Immunofluorescent staining is a key technique for revealing 3-dimensional structure, but subsequent fluorescence microscopy is limited by the quantity of simultaneous targets that can be labeled and intrinsic lateral and isotropic axial point-spread function (PSF) blurring during the imaging process in a spectral and depth-dependent manner. Even after successful staining, imaging and optical deconvolution, the sheer density of filamentous processes in the neuropil significantly complicates analysis due to the difficulty of separating individual cells in a highly interconnected network of tightly woven cellular arbors. In order to solve these problems, a variety of methodologies were developed and validated for improved analysis of cortical anatomy. An enhanced immunofluorescent staining and imaging protocol was utilized to precisely locate specific functional regions within brain slices at high magnification and collect four-channel, complete cortical columns. A powerful deconvolution routine was established which collected depth variant PSFs using an optical phantom for image restoration. Fractional volume analysis (FVA) was used to provide preliminary data of the proportions of each stained component in order to statistically characterize the variability within and between the functional regions in a depth-dependent and depth-independent manner. Finally, using machine learning techniques, a supervised learning model was developed that could automatically classify neuronal and astrocytic nuclei within the large cortical column datasets based on perinuclear fluorescence. These annotated nuclei were then used as seed points within their corresponding fluorescent channel for cell individualization in a highly interconnected network. For astrocytes, this technique provides the first method for characterization of complex morphology in an automated fashion over large areas without laborious dye filling or manual tracing

Muscle fiber typology substantially influences time to recover from high-intensity exercise

Human fast-twitch muscle fi- bers generate high power in a short amount of time but are easily fatigued, whereas slow-twitch fibers are more fatigue resistant. The transfer of this knowledge to coaching is hampered by the invasive nature of the current evaluation of muscle typology by biopsies. Therefore, a noninvasive method was developed to estimate muscle typology through proton magnetic resonance spectroscopy in the gastrocnemius. The aim of this study was to investigate whether male subjects with an a priori-determined fast typology (FT) are character- ized by a more pronounced Wingate exercise-induced fatigue and delayed recovery compared with subjects with a slow typology (ST). Ten subjects with an estimated higher percentage of fast-twitch fibers and 10 subjects with an estimated higher percentage of slow-twitch fibers underwent the test protocol, consisting of three 30-s all-out Wingate tests. Recovery of knee extension torque was evaluated by maximal voluntary contraction combined with electrical stimulation up to 5 h after the Wingate tests. Although both groups delivered the same mean power across all Wingates, the power drop was higher in the FT group (—61%) compared with the ST group (—41%). The torque at maximal voluntary contraction had fully recovered in the ST group after 20 min, whereas the FT group had not yet recovered 5 h into recovery. This noninvasive estimation of muscle typology can predict the extent of fatigue and time to recover following repeated all-out exercise and may have applications as a tool to individualize training and recovery cycles. NEW & NOTEWORTHY A one-fits-all training regime is present in most sports, though the same training implies different stimuli in athletes with a distinct muscle typology. Individualization of training based on this muscle typology might be important to optimize per- formance and to lower the risk for accumulated fatigue and potentially injury. When conducting research, one should keep in mind that the muscle typology of participants influences the severity of fatigue and might therefore impact the results

Dynamic Simulation of Human Thermoregulation and Heat Transfer for Spaceflight Applications

Models of human thermoregulation and heat transfer date from the early 1970s and have been developed for applications ranging from evaluating thermal comfort in spacecraft and aircraft cabin environments to predicting heat stress during EVAs. Most lumped or compartment models represent the body as an assemblage cylindrical and spherical elements which may be subdivided into layers to describe tissue heterogeneity. Many existing models are of limited usefulness in asymmetric thermal environments, such as may be encountered during an EVA. Conventional whole-body clothing models also limit the ability to describe local surface thermal and evaporation effects in sufficient detail. A further limitation is that models based on a standard man model are not readily scalable to represent large or small subjects. This work describes development of a new human thermal model derived from the 41-node man model. Each segment is divided into four concentric, constant thickness cylinders made up of a central core surrounded by muscle, fat, and skin, respectively. These cylinders are connected by the flow of blood from a central blood pool to each part. The central blood pool is updated at each time step, based on a whole-body energy balance. Results show the model simulates core and surface temperature histories, sweat evaporation and metabolic rates which generally are consistent with controlled exposures of human subjects. Scaling rules are developed to enable simulation of small and large subjects (5th percentile and 95th percentile). Future refinements will include a clothing model that addresses local surface insulation and permeation effects and developing control equations to describe thermoregulatory effects such as may occur with prolonged weightlessness or with aging

Comparison of manual and automatic techniques for substriatal segmentation in C-11-raclopride high-resolution PET studies

Background: The striatum is the primary target in regional C-11-raclopride-PET studies, and despite its small volume, it contains several functional and anatomical subregions. The outcome of the quantitative dopamine receptor study using C-11-raclopride-PET depends heavily on the quality of the region-of-interest (ROI) definition of these subregions. The aim of this study was to evaluate subregional analysis techniques because new approaches have emerged, but have not yet been compared directly.Materials and methods: In this paper, we compared manual ROI delineation with several automatic methods. The automatic methods used either direct clustering of the PET image or individualization of chosen brain atlases on the basis of MRI or PET image normalization. State-of-the-art normalization methods and atlases were applied, including those provided in the FreeSurfer, Statistical Parametric Mapping8, and FSL software packages. Evaluation of the automatic methods was based on voxel-wise congruity with the manual delineations and the test-retest variability and reliability of the outcome measures using data from seven healthy male participants who were scanned twice with C-11-raclopride-PET on the same day.Results: The results show that both manual and automatic methods can be used to define striatal subregions. Although most of the methods performed well with respect to the test-retest variability and reliability of binding potential, the smallest average test-retest variability and SEM were obtained using a connectivity-based atlas and PET normalization (test-retest variability=4.5%, SEM=0.17).Conclusion: The current state-of-the-art automatic ROI methods can be considered good alternatives for subjective and laborious manual segmentation in C-11-raclopride-PET studies.Copyright (C) 2016 Wolters Kluwer Health, Inc. All rights reserved.</div

Framework for simulation-based Trajectory Planning and Execution of Robots equipped with a Laser Scanner for Measurement and Inspection

Shorter product life cycles require ever faster planning processes for the manufacturing of products. This also applies for measuring processes to ensure compliance with geometric workpiece specifications. In addition, these processes must be designed to be increasingly flexible since mass customization steadily increases product variety. Laser scanning systems mounted on robots offer the possibility of measuring a wide variety of geometries with low measurement uncertainty. In this paper, a method is presented with which measurement trajectories can be planned and virtually validated. We thereby combine and extend existing trajectory planning approaches and explicitly integrate robot kinematics into the planning approach to account for feasibility of the planned trajectories. These can then be directly transferred to the available measurement system. This is enabled by a real time interface directly connecting a virtual environment for measurement simulation and the real measurement system

X-ray computed tomography for characterization of expanded polystyrene (EPS) foam

Expanded polystyrene (EPS) foam is widely used in building and construction applications for thermal and acoustic insulation. This material is nearly transparent for X-rays, making it difficult to characterize its pore structure in 3D with X-ray tomography. Because of this difficulty, the pore network is often not investigated and is, thus, poorly known. Since this network controls different physical properties, such as the sound absorption, it is crucial to understand its overall structure. In this manuscript, we show how to reveal the pore network of EPS foams through the combination of high resolution X-ray tomography (micro-CT) and saturation techniques. The foams were saturated with CsCl-brine, which acts as a contrasting agent in X-ray micro-CT imaging. This allowed us to separate the beads, making up the foam, from the pore network. Based on the 3D micro-CT results, we were able to assess a representative elementary volume for the polystyrene, which allows for calculating the acoustical parameters from the Johnson-Champoux-Allard (JCA) model, the pore and bead size distribution. The 3D data was also used as input to simulate sound absorption curves. The parametric study showed that an increase in the bead size influenced the sound absorption of the material. We showed that, by doubling the diameter of beads, the absorption coefficient was doubled in certain ranges of frequency

Spatiotemporal Power of Positron Emission Tomography: Pushing the Limits of Poisson Statistics in High-Resolution Human Neurotransmission Studies

Brain disorders involving dysfunctions in neurotransmissionconstitute one of the most prevalent health problems. Subtledisruptions in human neurotransmission can result in significantdysfunction of cognition, locomotion, or practically any facet ofhuman behaviour. In turn, homeostasis of a specific neurotransmitter system can often be retrieved through pharmacologicalor lifestyle interventions. At present, human neurotransmissioncan be best assayed using positron emission tomography (PET). To date, neurotransmitter-PET (nt-PET) has been employedto investigate neuroreceptor level phenomenon in human behavior/cognition as well as in treatment development. In thecurrent work the goal was to explore and enhance the temporalcapabilities of nt-PET, to allow better characterization of thetemporal facets of neurotransmission.Main obstacles limiting temporal characterization stem fromthe poor signal-to-noise-ratio of the PET measurement. Inparticular, the limitations related to image reconstruction algorithms and in turn the benefits obtained through regionalanalysis were in the focus of the investigations in this work. Themain finding was that the best temporal resolution achieved using a commonly recommended iterative reconstruction methodwas insufficient for temporal characterization, while a newlydeveloped algorithm allowing analytical reconstruction showedbetter temporal resolution without decreasing signal-to-noiseratio. Furthermore, a novel atlas-based regional analysis methodwas found superior to the currently employed manual region-ofinterest definition.The findings made through this work will directly assist theplanning of future neurotransmission studies, and it is wishedthat the observations in this work would spark new, more widespread interest on the application of nt-PET in e.g. cognitivestimulation studies

Optimizing transcranial magnetic stimulation for spaceflight applications

As space agencies aim to reach and build installations on Mars, the crews will face longer exposure to extreme environments that may compromise their health and performance. Transcranial magnetic stimulation (TMS) is a painless non-invasive brain stimulation technique that could support space exploration in multiple ways. However, changes in brain morphology previously observed after long-term space missions may impact the efficacy of this intervention. We investigated how to optimize TMS for spaceflight-associated brain changes. Magnetic resonance imaging T1-weighted scans were collected from 15 Roscosmos cosmonauts and 14 non-flyer participants before, after 6 months on the International Space Station, and at a 7-month follow-up. Using biophysical modeling, we show that TMS generates different modeled responses in specific brain regions after spaceflight in cosmonauts compared to the control group. Differences are related to spaceflight-induced structural brain changes, such as those impacting cerebrospinal fluid volume and distribution. We suggest solutions to individualize TMS to enhance its efficacy and precision for potential applications in long-duration space missions. © 2023, The Author(s)

AI based geometric similarity search supporting component reuse in engineering design

Today, companies are faced with the challenge to develop and produce individualized products in the shortest possible time at very low cost in order to remain attractive under strong competitive pressure. For reasons of efficiency, products are therefore often developed in generations. Proven components are adopted in a new product generation and only some of the components are newly developed to meet new customer requirements. Many companies, therefore, have a large database of 3D CAD product models containing years of engineering experience. Nevertheless, it is often difficult to execute database queries to find which products or components already exist and could be reused or adapted for a new product generation or variant. As a result, many duplicates are created, which are associated with high effort and costs, and the risk of introducing design errors increases. Therefore, the aim of this paper is to develop an automated approach for geometric similarity search that also takes company-specific features of components into account. Machine learning methods are capable of automatically extracting relevant geometric features by learning a suitable representation of the corresponding 3D object. For this purpose, an autoencoder is developed which is trained to extract class-specific feature vectors. To improve the representativeness of those vectors for the similarity search, the architecture and hyperparameters of the autoencoder are optimized based on several experiments. Considering a real use case with a data set from the field of mechanical engineering, it is shown that geometrically similar CAD models can be found very quickly using the learned representation, and that better results are obtained than with conventional methods based on meta information, e.g. volume and bounding box. On the one hand, the fast finding of similar models encourages the reuse of existing solutions. On the other hand, standardization and, thus, economy of scale is promoted