signaling pathways in elastic tissues

Abstract For many years elastin was considered as the matrix component structurally required to provide tissue elasticity. However, the expanded knowledge on the regulation of connective tissue homeostasis has revealed that elastic fibers also represent a source of elastokines and are the target of a number of signaling pathways mainly involving the TGF-β/BMP axis. A better understanding of these complex regulatory networks may pave the way for targeted therapeutic strategies in a number of genetic as well as acquired diseases and for the development of new functionalized biomaterials

Image Thresholding Technique Based On Fuzzy Partition And Entropy Maximization

Thresholding is a commonly used technique in image segmentation because of its fast and easy application. For this reason threshold selection is an important issue. There are two general approaches to threshold selection. One approach is based on the histogram of the image while the other is based on the gray scale information located in the local small areas. The histogram of an image contains some statistical data of the grayscale or color ingredients. In this thesis, an adaptive logical thresholding method is proposed for the binarization of blueprint images first. The new method exploits the geometric features of blueprint images. This is implemented by utilizing a robust windows operation, which is based on the assumption that the objects have "e;C"e; shape in a small area. We make use of multiple window sizes in the windows operation. This not only reduces computation time but also separates effectively thin lines from wide lines. Our method can automatically determine the threshold of images. Experiments show that our method is effective for blueprint images and achieves good results over a wide range of images. Second, the fuzzy set theory, along with probability partition and maximum entropy theory, is explored to compute the threshold based on the histogram of the image. Fuzzy set theory has been widely used in many fields where the ambiguous phenomena exist since it was proposed by Zadeh in 1965. And many thresholding methods have also been developed by using this theory. The concept we are using here is called fuzzy partition. Fuzzy partition means that a histogram is parted into several groups by some fuzzy sets which represent the fuzzy membership of each group because our method is based on histogram of the image . Probability partition is associated with fuzzy partition. The probability distribution of each group is derived from the fuzzy partition. Entropy which originates from thermodynamic theory is introduced into communications theory as a commonly used criteria to measure the information transmitted through a channel. It is adopted by image processing as a measurement of the information contained in the processed images. Thus it is applied in our method as a criterion for selecting the optimal fuzzy sets which partition the histogram. To find the threshold, the histogram of the image is partitioned by fuzzy sets which satisfy a certain entropy restriction. The search for the best possible fuzzy sets becomes an important issue. There is no efficient method for the searching procedure. Therefore, expansion to multiple level thresholding with fuzzy partition becomes extremely time consuming or even impossible. In this thesis, the relationship between a probability partition (PP) and a fuzzy C-partition (FP) is studied. This relationship and the entropy approach are used to derive a thresholding technique to select the optimal fuzzy C-partition. The measure of the selection quality is the entropy function defined by the PP and FP. A necessary condition of the entropy function arriving at a maximum is derived. Based on this condition, an efficient search procedure for two-level thresholding is derived, which makes the search so efficient that extension to multilevel thresholding becomes possible. A novel fuzzy membership function is proposed in three-level thresholding which produces a better result because a new relationship among the fuzzy membership functions is presented. This new relationship gives more flexibility in the search for the optimal fuzzy sets, although it also increases the complication in the search for the fuzzy sets in multi-level thresholding. This complication is solved by a new method called the "e;Onion-Peeling"e; method. Because the relationship between the fuzzy membership functions is so complicated it is impossible to obtain the membership functions all at once. The search procedure is decomposed into several layers of three-level partitions except for the last layer which may be a two-level one. So the big problem is simplified to three-level partitions such that we can obtain the two outmost membership functions without worrying too much about the complicated intersections among the membership functions. The method is further revised for images with a dominant area of background or an object which affects the appearance of the histogram of the image. The histogram is the basis of our method as well as of many other methods. A "e;bad"e; shape of the histogram will result in a bad thresholded image. A quadtree scheme is adopted to decompose the image into homogeneous areas and heterogeneous areas. And a multi-resolution thresholding method based on quadtree and fuzzy partition is then devised to deal with these images. Extension of fuzzy partition methods to color images is also examined. An adaptive thresholding method for color images based on fuzzy partition is proposed which can determine the number of thresholding levels automatically. This thesis concludes that the "e;C"e; shape assumption and varying sizes of windows for windows operation contribute to a better segmentation of the blueprint images. The efficient search procedure for the optimal fuzzy sets in the fuzzy-2 partition of the histogram of the image accelerates the process so much that it enables the extension of it to multilevel thresholding. In three-level fuzzy partition the new relationship presentation among the three fuzzy membership functions makes more sense than the conventional assumption and, as a result, performs better. A novel method, the "e;Onion-Peeling"e; method, is devised for dealing with the complexity at the intersection among the multiple membership functions in the multilevel fuzzy partition. It decomposes the multilevel partition into the fuzzy-3 partitions and the fuzzy-2 partitions by transposing the partition space in the histogram. Thus it is efficient in multilevel thresholding. A multi-resolution method which applies the quadtree scheme to distinguish the heterogeneous areas from the homogeneous areas is designed for the images with large homogeneous areas which usually distorts the histogram of the image. The new histogram based on only the heterogeneous area is adopted for partition and outperforms the old one. While validity checks filter out the fragmented points which are only a small portion of the whole image. Thus it gives good thresholded images for human face images

Matrisomal components involved in regenerative wound healing in axolotl and acomys: implications for biomaterial development

Achieving regeneration in humans has been a long-standing goal of many researchers. Whereas amphibians like the axolotl (Ambystoma mexicanum) are capable of regenerating whole organs and even limbs, most mammals heal their wounds via fibrotic scarring. Recently, the African spiny mouse (Acomys sp.) has been shown to be injury resistant and capable of regenerating several tissue types. A major focal point of research with Acomys has been the identification of drivers of regeneration. In this search, the matrisome components related to the extracellular matrix (ECM) are often overlooked. In this review, we compare Acomys and axolotl skin wound healing and blastema-mediated regeneration by examining their wound healing responses and comparing the expression pattern of matrisome genes, including glycosaminoglycan (GAG) related genes. The goal of this review is to identify matrisome genes that are upregulated during regeneration and could be potential candidates for inclusion in pro-regenerative biomaterials. Research papers describing transcriptomic or proteomic coverage of either skin regeneration or blastema formation in Acomys and axolotl were selected. Matrisome and GAG related genes were extracted from each dataset and the resulting lists of genes were compared. In our analysis, we found several genes that were consistently upregulated, suggesting possible involvement in regenerative processes. Most of the components have been implicated in regulation of cell behavior, extracellular matrix remodeling and wound healing. Incorporation of such pro-regenerative factors into biomaterials may help to shift pro-fibrotic processes to regenerative responses in treated wounds.European Union’s Horizon 2020 ;Grant Agreement No. 955722info:eu-repo/semantics/publishedVersio

Harmonization of brain PET images in multi-center PET studies using Hoffman phantom scan

Background: Image harmonization has been proposed to minimize heterogeneity in brain PET scans acquired in multi-center studies. However, standard validated methods and software tools are lacking. Here, we assessed the performance of a framework for the harmonization of brain PET scans in a multi-center European clinical trial. / Method: Hoffman 3D brain phantoms were acquired in 28 PET systems and reconstructed using site-specific settings. Full Width at Half Maximum (FWHM) of the Effective Image Resolution (EIR) and harmonization kernels were estimated for each scan. The target EIR was selected as the coarsest EIR in the imaging network. Using “Hoffman 3D brain Analysis tool,” indicators of image quality were calculated before and after the harmonization: The Coefficient of Variance (COV%), Gray Matter Recovery Coefficient (GMRC), Contrast, Cold-Spot RC, and left-to-right GMRC ratio. A COV% ≤ 15% and Contrast ≥ 2.2 were set as acceptance criteria. The procedure was repeated to achieve a 6-mm target EIR in a subset of scans. The method’s robustness against typical dose-calibrator-based errors was assessed. / Results: The EIR across systems ranged from 3.3 to 8.1 mm, and an EIR of 8 mm was selected as the target resolution. After harmonization, all scans met acceptable image quality criteria, while only 13 (39.4%) did before. The harmonization procedure resulted in lower inter-system variability indicators: Mean ± SD COV% (from 16.97 ± 6.03 to 7.86 ± 1.47%), GMRC Inter-Quartile Range (0.040–0.012), and Contrast SD (0.14–0.05). Similar results were obtained with a 6-mm FWHM target EIR. Errors of ± 10% in the DRO activity resulted in differences below 1 mm in the estimated EIR. / Conclusion: Harmonizing the EIR of brain PET scans significantly reduced image quality variability while minimally affecting quantitative accuracy. This method can be used prospectively for harmonizing scans to target sharper resolutions and is robust against dose-calibrator errors. Comparable image quality is attainable in brain PET multi-center studies while maintaining quantitative accuracy

Spectral analysis and resolving spatial ambiguities in human sound localization

This dissertation provides an overview of my research over the last five years into the spectral analysis involved in human sound localization. The work involved conducting psychophysical tests of human auditory localization performance and then applying analytical techniques to analyze and explain the data. It is a fundamental thesis of this work that human auditory localization response directions are primarily driven by the auditory localization cues associated with the acoustic filtering properties of the external auditory periphery, i.e., the head, torso, shoulder, neck, and external ears. This work can be considered as composed of three parts. In the first part of this work, I compared the auditory localization performance of a human subject and a time-delay neural network model under three sound conditions: broadband, high-pass, and low-pass. A “black-box” modeling paradigm was applied. The modeling results indicated that training the network to localize sounds of varying center-frequency and bandwidth could degrade localization performance results in a manner demonstrating some similarity to human auditory localization performance. As the data collected during the network modeling showed that humans demonstrate striking localization errors when tested using bandlimited sound stimuli, the second part of this work focused on human sound localization of bandpass filtered noise stimuli. Localization data was collected from 5 subjects and for 7 sound conditions: 300 Hz to 5 kHz, 300 Hz to 7 kHz, 300 Hz to 10 kHz, 300 Hz to 14 kHz, 3 to 8 kHz, 4 to 9 kHz, and 7 to 14 kHz. The localization results were analyzed using the method of cue similarity indices developed by Middlebrooks (1992). The data indicated that the energy level in relatively wide frequency bands could be driving the localization response directions, just as in Butler’s covert peak area model (see Butler and Musicant, 1993). The question was then raised as to whether the energy levels in the various frequency bands, as described above, are most likely analyzed by the human auditory localization system on a monaural or an interaural basis. In the third part of this work, an experiment was conducted using virtual auditory space sound stimuli in which the monaural spectral cues for auditory localization were disrupted, but the interaural spectral difference cue was preserved. The results from this work showed that the human auditory localization system relies primarily on a monaural analysis of spectral shape information for its discrimination of directions on the cone of confusion. The work described in the three parts lead to the suggestion that a spectral contrast model based on overlapping frequency bands of varying bandwidth and perhaps multiple frequency scales can provide a reasonable algorithm for explaining much of the current psychophysical and neurophysiological data related to human auditory localization

Copper-Heparin Inhalation Therapy To Repair Emphysema:A Scientific Rationale

Current pharmacotherapy of chronic obstructive pulmonary disease (COPD) aims at reducing respiratory symptoms and exacerbation frequency. Effective therapies to reduce disease progression, however, are still lacking. Furthermore, COPD medications showed less favorable effects in emphysema than in other COPD phenotypes. Elastin fibers are reduced and disrupted, whereas collagen levels are increased in emphysematous lungs. Protease/antiprotease imbalance has historically been regarded as the sole cause of emphysema. However, it is nowadays appreciated that emphysema may also be provoked by perturbations in the sequential repair steps following elastolysis. Essentiality of fibulin-5 and lysyl oxidase-like 1 in the elastin restoration process is discussed, and it is argued that copper deficiency is a plausible reason for failing elastin repair in emphysema patients. Since copper-dependent lysyl oxidases crosslink elastin as well as collagen fibers, copper supplementation stimulates accumulation of both proteins in the extracellular matrix. Restoration of abnormal elastin fibers in emphysematous lungs is favorable, whereas stimulating pulmonary fibrosis formation by further increasing collagen concentrations and organization is detrimental. Heparin inhibits collagen crosslinking while stimulating elastin repair and might therefore be the ideal companion of copper for emphysema patients. Efficacy and safety considerations may lead to a preference of pulmonary administration of copper-heparin over systemic administration

Experimental study of pedestrian flow through a bottleneck

In this work the results of a bottleneck experiment with pedestrians are presented in the form of total times, fluxes, specific fluxes, and time gaps. A main aim was to find the dependence of these values from the bottleneck width. The results show a linear decline of the specific flux with increasing width as long as only one person at a time can pass, and a constant value for larger bottleneck widths. Differences between small (one person at a time) and wide bottlenecks (two persons at a time) were also found in the distribution of time gaps.Comment: accepted for publication in J. Stat. Mec

Abnormalities in reparative function of lung-derived mesenchymal stromal cells in emphysema

Mesenchymal stromal cells (MSCs) may provide crucial support in the regeneration of destructed alveolar tissue (emphysema) in COPD. We hypothesized that lung-derived MSCs (LMSCs) from emphysema patients are hampered in their repair capacity, either intrinsically or due to their interaction with the damaged micro-environment. LMSCs were isolated from lung tissue of controls and severe emphysema patients, and characterized at baseline. Additionally, LMSCs were seeded onto control and emphysematous decellularized lung tissue scaffolds and assessed for deposition of extracellular matrix (ECM). We observed no differences in surface markers, differentiation/proliferation potential and expression of ECM genes between control- and COPD-derived LMSCs. Notably, COPD-derived LMSCs displayed lower expression of FGF10 and HGF mRNA, and HGF and decorin protein. When seeded on control decellularized lung tissue scaffolds, control and COPD-derived LMSCs showed no differences in engraftment, proliferation or survival within 2 weeks, with similar ability to deposit new matrix on the scaffolds. Moreover, LMSC numbers and ability to deposit new matrix was not compromised on emphysematous scaffolds. Collectively, our data show that LMSCs from COPD patients compared to controls show less expression of FGF10 mRNA, HGF mRNA and protein and decorin protein, while other features including the mRNA expression of various ECM molecules are unaffected. Furthermore, COPD-derived LMSCs are capable of engraftment, proliferation and functioning on native lung tissue scaffolds. The damaged, emphysematous micro-environment as such does not hamper the potential of LMSCs. Thus, specific intrinsic deficiencies in growth factor production by diseased LMSCs may contribute to impaired alveolar repair in emphysema

Traffic Instabilities in Self-Organized Pedestrian Crowds

In human crowds as well as in many animal societies, local interactions among individuals often give rise to self-organized collective organizations that offer functional benefits to the group. For instance, flows of pedestrians moving in opposite directions spontaneously segregate into lanes of uniform walking directions. This phenomenon is often referred to as a smart collective pattern, as it increases the traffic efficiency with no need of external control. However, the functional benefits of this emergent organization have never been experimentally measured, and the underlying behavioral mechanisms are poorly understood. In this work, we have studied this phenomenon under controlled laboratory conditions. We found that the traffic segregation exhibits structural instabilities characterized by the alternation of organized and disorganized states, where the lifetime of well-organized clusters of pedestrians follow a stretched exponential relaxation process. Further analysis show that the inter-pedestrian variability of comfortable walking speeds is a key variable at the origin of the observed traffic perturbations. We show that the collective benefit of the emerging pattern is maximized when all pedestrians walk at the average speed of the group. In practice, however, local interactions between slow- and fast-walking pedestrians trigger global breakdowns of organization, which reduce the collective and the individual payoff provided by the traffic segregation. This work is a step ahead toward the understanding of traffic self-organization in crowds, which turns out to be modulated by complex behavioral mechanisms that do not always maximize the group's benefits. The quantitative understanding of crowd behaviors opens the way for designing bottom-up management strategies bound to promote the emergence of efficient collective behaviors in crowds.Comment: Article published in PLoS Computational biology. Freely available here: http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.100244

Decreased cortical thickness mediates the relationship between premature birth and cognitive performance in adulthood

Cortical thickness (CTh) reflects cortical properties such as dendritic complexity and synaptic density, which are not only vulnerable to developmental disturbances caused by premature birth but also highly relevant for cognitive performance. We tested the hypotheses whether CTh in young adults is altered after premature birth and whether these aberrations are relevant for general cognitive abilities. We investigated CTh based on brain structural magnetic resonance imaging and surface‐based morphometry in a large and prospectively collected cohort of 101 very premature‐born adults (<32 weeks of gestation and/or birth weight [BW] below 1,500 g) and 111 full‐term controls at 26 years of age. Cognitive performance was assessed by full‐scale intelligence quotient (IQ) using the Wechsler Adult Intelligence Scale. CTh was reduced in frontal, parietal, and temporal associative cortices predominantly in the left hemisphere in premature‐born adults compared to controls. We found a significant positive association of CTh with both gestational age and BW, particularly in the left hemisphere, and a significant negative association between CTh and intensity of neonatal treatment within limited regions bilaterally. Full‐scale IQ and CTh in the left hemisphere were positively correlated. Furthermore, CTh in the left hemisphere acted as a mediator on the association between premature birth and full‐scale IQ. Results provide evidence that premature born adults have widespread reduced CTh that is relevant for their general cognitive performance. Data suggest lasting reductions in cortical microstructure subserving CTh after premature birth