1,964 research outputs found
Design aspects and characterization of hydrogel-based bioinks for extrusion-based bioprinting
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Systemic Circular Economy Solutions for Fiber Reinforced Composites
This open access book provides an overview of the work undertaken within the FiberEUse project, which developed solutions enhancing the profitability of composite recycling and reuse in value-added products, with a cross-sectorial approach. Glass and carbon fiber reinforced polymers, or composites, are increasingly used as structural materials in many manufacturing sectors like transport, constructions and energy due to their better lightweight and corrosion resistance compared to metals. However, composite recycling is still a challenge since no significant added value in the recycling and reprocessing of composites is demonstrated. FiberEUse developed innovative solutions and business models towards sustainable Circular Economy solutions for post-use composite-made products. Three strategies are presented, namely mechanical recycling of short fibers, thermal recycling of long fibers and modular car parts design for sustainable disassembly and remanufacturing. The validation of the FiberEUse approach within eight industrial demonstrators shows the potentials towards new Circular Economy value-chains for composite materials
The optimal connection model for blood vessels segmentation and the MEA-Net
Vascular diseases have long been regarded as a significant health concern.
Accurately detecting the location, shape, and afflicted regions of blood
vessels from a diverse range of medical images has proven to be a major
challenge. Obtaining blood vessels that retain their correct topological
structures is currently a crucial research issue. Numerous efforts have sought
to reinforce neural networks' learning of vascular geometric features,
including measures to ensure the correct topological structure of the
segmentation result's vessel centerline. Typically, these methods extract
topological features from the network's segmentation result and then apply
regular constraints to reinforce the accuracy of critical components and the
overall topological structure. However, as blood vessels are three-dimensional
structures, it is essential to achieve complete local vessel segmentation,
which necessitates enhancing the segmentation of vessel boundaries.
Furthermore, current methods are limited to handling 2D blood vessel
fragmentation cases. Our proposed boundary attention module directly extracts
boundary voxels from the network's segmentation result. Additionally, we have
established an optimal connection model based on minimal surfaces to determine
the connection order between blood vessels. Our method achieves
state-of-the-art performance in 3D multi-class vascular segmentation tasks, as
evidenced by the high values of Dice Similarity Coefficient (DSC) and
Normalized Surface Dice (NSD) metrics. Furthermore, our approach improves the
Betti error, LR error, and BR error indicators of vessel richness and
structural integrity by more than 10% compared to other methods, and
effectively addresses vessel fragmentation and yields blood vessels with a more
precise topological structure.Comment: 19 page
Artificial Light at Night Disrupts Pain Behavior and Cerebrovascular Structure in Mice
Artificial Light at Night Disrupts Pain Behavior and Cerebrovascular Structure in Mice
Jacob R. Bumgarner
Circadian rhythms are intrinsic biological processes that fluctuate in function with a period of approximately 24 hours. These rhythms are precisely synchronized to the 24- hour day of the Earth by external rhythmic signaling cues. Solar light-dark cycles are the most potent environmental signaling cue for terrestrial organisms to align internal rhythms with the external day. Proper alignment and synchrony of internal circadian rhythms with external environmental rhythms are essential for health and optimal biological function.
The modern human environment on Earth is no longer conducive to properly aligned circadian rhythms. Following the industrial revolution, artificial lighting and an ever-growing 24-hour global economy have shifted humans away from natural environments suited for rhythmic behavior and physiology. Humans, and much of the natural environment, are routinely exposed to circadian rhythm disruptors. The most pervasive disruptor of circadian rhythms is artificial light at night (ALAN).
A growing 80% of humans on Earth are exposed to ALAN beyond natural nighttime environmental lighting levels. ALAN exposure is associated with numerous negative consequences on behavior and physiology, including neuroinflammation, cardiovascular disease, and altered immune function. This dissertation examines two previously uninvestigated effects of ALAN exposure on physiology and behavior in mice.
In Part 1, I investigated the effects of ALAN exposure on pain behavior in mice. I observed that ALAN exposure had detrimental effects on rodent pain behavior in contexts of both health and models of human disease. ALAN exposure heightened responsiveness to noxious cold stimuli and innocuous mechanical touch. Differences in these effects were noted based on sex and disease state. I conclude this section with a report on the mechanisms by which ALAN exposure altered pain behavior.
In Part 2, I investigated the effects of ALAN exposure on cerebrovascular structure in mice. To conduct these investigations, I first developed VesselVio, an open-source application for the analysis and visualization of vasculature datasets. Using this application and additional analytical frameworks, I examined the effects of short-term ALAN exposure on hippocampal vasculature in mice. ALAN exposure reduced hippocampal vascular density in mice, with notable regional sex differences. I also observed that ALAN exposure altered hippocampal vascular network connectivity and structure, with persistent regional sex differences.
The data in this dissertation contribute to the ever-growing field of circadian rhythm biology focused on studying circadian rhythm disruption. These data highlight the continuing need to mitigate the pervasiveness of ALAN in human and natural environments. Most importantly, the results presented in this dissertation emphasize the need to consider ALAN as a mitigating factor for the treatment of both cardiovascular disease and pain
Surface-Based tools for Characterizing the Human Brain Cortical Morphology
Tesis por compendio de publicacionesThe cortex of the human brain is highly convoluted. These characteristic convolutions
present advantages over lissencephalic brains. For instance, gyrification allows an expansion
of cortical surface area without significantly increasing the cranial volume, thus
facilitating the pass of the head through the birth channel. Studying the human brain’s
cortical morphology and the processes leading to the cortical folds has been critical for an
increased understanding of the pathological processes driving psychiatric disorders such
as schizophrenia, bipolar disorders, autism, or major depression. Furthermore, charting
the normal developmental changes in cortical morphology during adolescence or aging
can be of great importance for detecting deviances that may be precursors for pathology.
However, the exact mechanisms that push cortical folding remain largely unknown.
The accurate characterization of the neurodevelopment processes is challenging. Multiple
mechanisms co-occur at a molecular or cellular level and can only be studied through
the analysis of ex-vivo samples, usually of animal models. Magnetic Resonance Imaging
can partially fill the breach, allowing the portrayal of the macroscopic processes surfacing
on in-vivo samples.
Different metrics have been defined to measure cortical structure to describe the brain’s
morphological changes and infer the associated microstructural events. Metrics such as
cortical thickness, surface area, or cortical volume help establish a relation between the
measured voxels on a magnetic resonance image and the underlying biological processes.
However, the existing methods present limitations or room for improvement.
Methods extracting the lines representing the gyral and sulcal morphology tend to
over- or underestimate the total length. These lines can provide important information
about how sulcal and gyral regions function differently due to their distinctive ontogenesis.
Nevertheless, some methods label every small fold on the cortical surface as a sulcal
fundus, thus losing the perspective of lines that travel through the deeper zones of a sulcal
basin. On the other hand, some methods are too restrictive, labeling sulcal fundi only for
a bunch of primary folds.
To overcome this issue, we have proposed a Laplacian-collapse-based algorithm that
can delineate the lines traversing the top regions of the gyri and the fundi of the sulci
avoiding anastomotic sulci. For this, the cortex, represented as a 3D surface, is segmented
into gyral and sulcal surfaces attending to the curvature and depth at every point
of the mesh. Each resulting surface is spatially filtered, smoothing the boundaries. Then,
a Laplacian-collapse-based algorithm is applied to obtain a thinned representation of the
morphology of each structure. These thin curves are processed to detect where the extremities
or endpoints lie. Finally, sulcal fundi and gyral crown lines are obtained by
eroding the surfaces while preserving the structure topology and connectivity between
the endpoints. The assessment of the presented algorithm showed that the labeled sulcal lines were close to the proposed ground truth length values while crossing through the
deeper (and more curved) regions. The tool also obtained reproducibility scores better or
similar to those of previous algorithms.
A second limitation of the existing metrics concerns the measurement of sulcal width.
This metric, understood as the physical distance between the points on opposite sulcal
banks, can come in handy in detecting cortical flattening or complementing the information
provided by cortical thickness, gyrification index, or such features. Nevertheless,
existing methods only provided averaged measurements for different predefined sulcal
regions, greatly restricting the possibilities of sulcal width and ignoring the intra-region
variability.
Regarding this, we developed a method that estimates the distance from each sulcal
point in the cortex to its corresponding opposite, thus providing a per-vertex map of the
physical sulcal distances. For this, the cortical surface is sampled at different depth levels,
detecting the points where the sulcal banks change. The points corresponding to each sulcal
wall are matched with the closest point on a different one. The distance between those
points is the sulcal width. The algorithm was validated against a simulated sulcus that
resembles a simple fold. Then the tool was used on a real dataset and compared against
two widely-used sulcal width estimation methods, averaging the proposed algorithm’s
values into the same region definition those reference tools use. The resulting values were
similar for the proposed and the reference methods, thus demonstrating the algorithm’s
accuracy.
Finally, both algorithms were tested on a real aging population dataset to prove the
methods’ potential in a use-case scenario. The main idea was to elucidate fine-grained
morphological changes in the human cortex with aging by conducting three analyses: a
comparison of the age-dependencies of cortical thickness in gyral and sulcal lines, an
analysis of how the sulcal and gyral length changes with age, and a vertex-wise study of
sulcal width and cortical thickness.
These analyses showed a general flattening of the cortex with aging, with interesting
findings such as a differential age-dependency of thickness thinning in the sulcal and
gyral regions. By demonstrating that our method can detect this difference, our results
can pave the way for future in vivo studies focusing on macro- and microscopic changes
specific to gyri or sulci. Our method can generate new brain-based biomarkers specific
to sulci and gyri, and these can be used on large samples to establish normative models
to which patients can be compared. In parallel, the vertex-wise analyses show that sulcal
width is very sensitive to changes during aging, independent of cortical thickness. This
corroborates the concept of sulcal width as a metric that explains, in the least, the unique
variance of morphology not fully captured by existing metrics. Our method allows for
sulcal width vertex-wise analyses that were not possible previously, potentially changing
our understanding of how changes in sulcal width shape cortical morphology.
In conclusion, this thesis presents two new tools, open source and publicly available, for estimating cortical surface-based morphometrics. The methods have been validated
and assessed against existing algorithms. They have also been tested on a real dataset,
providing new, exciting insights into cortical morphology and showing their potential for
defining innovative biomarkers.Programa de Doctorado en Ciencia y TecnologĂa BiomĂ©dica por la Universidad Carlos III de MadridPresidente: Juan Domingo Gispert LĂłpez.- Secretario: Norberto Malpica González de Vega.- Vocal: Gemma Cristina MontĂ© Rubi
Polyphenolic Compounds in Wine and Beer
This reprint describes the polyphenolic composition of wine and beer, with a special emphasis on extractive and analytical aspects. Furthermore, the effects of wine and beer polyphenols on human health are studied in the depth
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