437 research outputs found
Comparative study on photometric normalization algorithms for an innovative, robust and real-time eye gaze tracker
Adult Human Vascular Smooth Muscle Cells on 3D Silk Fibroin Nonwovens Release Exosomes Enriched in Angiogenic and Growth-Promoting Factors
Background. Our earlier works showed the quick vascularization of mouse skin grafted Bombyx mori 3D silk fibroin nonwoven scaffolds (3D-SFnws) and the release of exosomes enriched in angiogenic/growth factors (AGFs) from in vitro 3D-SFnws-stuck human dermal fibroblasts (HDFs). Here, we explored whether coronary artery adult human smooth muscle cells (AHSMCs) also release AGFs-enriched exosomes when cultured on 3D-SFnws in vitro. Methods. Media with exosome-depleted FBS served for AHSMCs and human endothelial cells (HECs) cultures on 3D-SFnws or polystyrene. Biochemical methods and double-antibody arrays assessed cell growth, metabolism, and intracellular TGF-β and NF-κB signalling pathways activation. AGFs conveyed by CD9+/CD81+ exosomes released from AHSMCs were double-antibody array analysed and their angiogenic power evaluated on HECs in vitro. Results. AHSMCs grew and consumed D-glucose more intensely and showed a stronger phosphorylation/activation of TAK-1, SMAD-1/-2/-4/-5, ATF-2, c-JUN, ATM, CREB, and an IκBα phosphorylation/inactivation on SFnws vs. polystyrene, consistent overall with a proliferative/secretory phenotype. SFnws-stuck AHSMCs also released exosomes richer in IL-1α/-2/-4/-6/-8; bFGF; GM-CSF; and GRO-α/-β/-γ, which strongly stimulated HECs’ growth, migration, and tubes/nodes assembly in vitro. Conclusions. Altogether, the intensified AGFs exosomal release from 3D-SFnws-attached AHSMCs and HDFs could advance grafts’ colonization, vascularization, and take in vivo—noteworthy assets for prospective clinical applications
Lung nodule detection on thoracic computed tomography images: Preliminary evaluation of a computerâ aided diagnosis system
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135039/1/mp5762.pd
Uncertainty quantification in medical image segmentation with normalizing flows
Medical image segmentation is inherently an ambiguous task due to factors
such as partial volumes and variations in anatomical definitions. While in most
cases the segmentation uncertainty is around the border of structures of
interest, there can also be considerable inter-rater differences. The class of
conditional variational autoencoders (cVAE) offers a principled approach to
inferring distributions over plausible segmentations that are conditioned on
input images. Segmentation uncertainty estimated from samples of such
distributions can be more informative than using pixel level probability
scores. In this work, we propose a novel conditional generative model that is
based on conditional Normalizing Flow (cFlow). The basic idea is to increase
the expressivity of the cVAE by introducing a cFlow transformation step after
the encoder. This yields improved approximations of the latent posterior
distribution, allowing the model to capture richer segmentation variations.
With this we show that the quality and diversity of samples obtained from our
conditional generative model is enhanced. Performance of our model, which we
call cFlow Net, is evaluated on two medical imaging datasets demonstrating
substantial improvements in both qualitative and quantitative measures when
compared to a recent cVAE based model.Comment: 12 pages. Accepted to be presented at 11th International Workshop on
Machine Learning in Medical Imaging. Source code will be updated at
https://github.com/raghavian/cFlo
In vitro effects of particulate matter associated with a wildland fire in the north-west of Italy
Wildland fires, increasing in recent decades in the Mediterranean region due to climate change, can contribute to PM levels and composition. This study aimed to investigate biological effects of PM2.5 (Ø 10 (Ø 10 and PM2.5 were measured during the fire suggesting that near and distant sites were influenced by fire pollutants. The PM10 and PM2.5 extracts induced a significant mutagenicity in all sites and the mutagenic effect was increased with respect to historical data. All extracts induced a slight increase of the estrogenic activity but a possible antagonistic activity of PM samples collected near fire was observed. No cytotoxicity or DNA damage was detected. Results confirm that fires could be relevant for human health, since they can worsen the air quality increasing PM concentrations, mutagenic and estrogenic effects
Computerâ aided diagnosis of pulmonary nodules on CT scans: Segmentation and classification using 3D active contours
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135040/1/mp7129.pd
Will silk fibroin nanofiber scaffolds ever hold a usefulplace in Translational Regenerative Medicine?
Presently, some view silk fibroin-based biomaterials as obsolete, being outperformed by a host of newly discovered
biomaterials. But several lines of evidence support the notion that silk fibroin proteins, especially those from B. mori and
spiders and their recombinant forms, particularly in the form of electrospun nanofiber scaffolds, still represent promising tools
for human tissue engineering/regeneration. Inevitably, the allure of recently reported biomaterials turns away many scientists
and resources from the aim of more deeply elucidating the biological interactions of the various kinds of silk fibroin nanofiber
scaffolds in vivo. But, even the biological features of newly reported biomaterials are not investigated in adequate depth.
Hence, collaborative efforts among biomaterialists, biomedical experts, and private firms must be undertaken on a much
greater scale than hitherto done to assess the real usefulness of silk fibroin proteins, thereby allowing or denying their useful
introduction into the fields of Translational Regenerative Medicine
Preserving Differential Privacy in Convolutional Deep Belief Networks
The remarkable development of deep learning in medicine and healthcare domain
presents obvious privacy issues, when deep neural networks are built on users'
personal and highly sensitive data, e.g., clinical records, user profiles,
biomedical images, etc. However, only a few scientific studies on preserving
privacy in deep learning have been conducted. In this paper, we focus on
developing a private convolutional deep belief network (pCDBN), which
essentially is a convolutional deep belief network (CDBN) under differential
privacy. Our main idea of enforcing epsilon-differential privacy is to leverage
the functional mechanism to perturb the energy-based objective functions of
traditional CDBNs, rather than their results. One key contribution of this work
is that we propose the use of Chebyshev expansion to derive the approximate
polynomial representation of objective functions. Our theoretical analysis
shows that we can further derive the sensitivity and error bounds of the
approximate polynomial representation. As a result, preserving differential
privacy in CDBNs is feasible. We applied our model in a health social network,
i.e., YesiWell data, and in a handwriting digit dataset, i.e., MNIST data, for
human behavior prediction, human behavior classification, and handwriting digit
recognition tasks. Theoretical analysis and rigorous experimental evaluations
show that the pCDBN is highly effective. It significantly outperforms existing
solutions
Three-Layered Silk Fibroin Tubular Scaffold for the Repair and Regeneration of Small Caliber Blood Vessels: From Design to in vivo Pilot Tests
Silk fibroin (SF) is an eligible biomaterial for the development of small caliber vascular grafts for substitution, repair, and regeneration of blood vessels. This study presents the properties of a newly designed multi-layered SF tubular scaffold for vascular grafting (SilkGraf). The wall architecture consists of two electrospun layers (inner and outer) and an intermediate textile layer. The latter was designed to confer high mechanical performance and resistance on the device, while electrospun layers allow enhancing its biomimicry properties and host\u2019s tissues integration. In vitro cell interaction studies performed with adult Human Coronary Artery Endothelial Cells (HCAECs), Human Aortic Smooth Muscle Cells (HASMCs), and Human Aortic Adventitial Fibroblasts (HAAFs) demonstrated that the electrospun layers favor cell adhesion, survival, and growth. Once cultured in vitro on the SF scaffold the three cell types showed an active metabolism (consumption of glucose and glutamine, release of lactate), and proliferation for up to 20 days. HAAF cells grown on SF showed a significantly lower synthesis of type I procollagen than on polystyrene, meaning a lower fibrotic effect of the SF substrate. The cytokine and chemokine expression patterns were investigated to evaluate the cells\u2019 proliferative and pro-inflammatory attitude. Interestingly, no significant amounts of truly pro-inflammatory cytokines were secreted by any of the three cell types which exhibited a clearly proliferative profile. Good hemocompatibility was observed by complement activation, hemolysis, and hematology assays. Finally, the results of an in vivo preliminary pilot trial on minipig and sheep to assess the functional behavior of implanted SF-based vascular graft identified the sheep as the more apt animal model for next medium-to-long term preclinical trials
- …