Multimodal imaging-based therapeutic fingerprints for optimizing personalized interventions: Application to neurodegeneration

Publication date: 1 October 2018
Source:NeuroImage, Volume 179
Author(s): Yasser Iturria-Medina, Félix M. Carbonell, Alan C. Evans
Personalized Medicine (PM) seeks to assist the patients according to their specific treatment needs and potential intervention responses. However, in the neurological context, this approach is limited by crucial methodological challenges, such as the requirement for an understanding of the causal disease mechanisms and the inability to predict the brain's response to therapeutic interventions. Here, we introduce and validate the concept of the personalized Therapeutic Intervention Fingerprint (pTIF), which predicts the effectiveness of potential interventions for controlling a patient's disease evolution. Each subject's pTIF can be inferred from multimodal longitudinal imaging (e.g. amyloid-β, metabolic and tau PET; vascular, functional and structural MRI). We studied an aging population (N = 331) comprising cognitively normal and neurodegenerative patients, longitudinally scanned using six different neuroimaging modalities. We found that the resulting pTIF vastly outperforms cognitive and clinical evaluations on predicting individual variability in gene expression (GE) profiles. Furthermore, after regrouping the patients according to their predicted primary single-target interventions, we observed that these pTIF-based subgroups present distinctively altered molecular pathway signatures, supporting the across-population identification of dissimilar pathological stages, in active correspondence with different therapeutic needs. The results further evidence the imprecision of using broad clinical categories for understanding individual molecular alterations and selecting appropriate therapeutic needs. To our knowledge, this is the first study highlighting the direct link between multifactorial brain dynamics, predicted treatment responses, and molecular alterations at the patient level. Inspired by the principles of PM, the proposed pTIF framework is a promising step towards biomarker-driven assisted therapeutic interventions, with additional important implications for selective enrollment of patients in clinical trials.



https://ift.tt/2LM7cft

Estimating the functional dimensionality of neural representations

Publication date: 1 October 2018
Source:NeuroImage, Volume 179
Author(s): Christiane Ahlheim, Bradley C. Love
Recent advances in multivariate fMRI analysis stress the importance of information inherent to voxel patterns. Key to interpreting these patterns is estimating the underlying dimensionality of neural representations. Dimensions may correspond to psychological dimensions, such as length and orientation, or involve other coding schemes. Unfortunately, the noise structure of fMRI data inflates dimensionality estimates and thus makes it difficult to assess the true underlying dimensionality of a pattern. To address this challenge, we developed a novel approach to identify brain regions that carry reliable task-modulated signal and to derive an estimate of the signal's functional dimensionality. We combined singular value decomposition with cross-validation to find the best low-dimensional projection of a pattern of voxel-responses at a single-subject level. Goodness of the low-dimensional reconstruction is measured as Pearson correlation with a test set, which allows to test for significance of the low-dimensional reconstruction across participants. Using hierarchical Bayesian modeling, we derive the best estimate and associated uncertainty of underlying dimensionality across participants. We validated our method on simulated data of varying underlying dimensionality, showing that recovered dimensionalities match closely true dimensionalities. We then applied our method to three published fMRI data sets all involving processing of visual stimuli. The results highlight three possible applications of estimating the functional dimensionality of neural data. Firstly, it can aid evaluation of model-based analyses by revealing which areas express reliable, task-modulated signal that could be missed by specific models. Secondly, it can reveal functional differences across brain regions. Thirdly, knowing the functional dimensionality allows assessing task-related differences in the complexity of neural patterns.



https://ift.tt/2sSq3P1

Added value of money on motor performance feedback: Increased left central beta-band power for rewards and fronto-central theta-band power for punishments

Publication date: 1 October 2018
Source:NeuroImage, Volume 179
Author(s): Raphaël Hamel, Félix-Antoine Savoie, Angélina Lacroix, Kevin Whittingstall, Maxime Trempe, Pierre-Michel Bernier
Monetary rewards and punishments have been shown to respectively enhance retention of motor memories and short-term motor performance, but their underlying neural bases in the context of motor control tasks remain unclear. Using electroencephalography (EEG), the present study tested the hypothesis that monetary rewards and punishments are respectively reflected in post-feedback beta-band (20–30 Hz) and theta-band (3–8 Hz) oscillatory power. While participants performed upper limb reaching movements toward visual targets using their right hand, the delivery of monetary rewards and punishments was manipulated as well as their probability (i.e., by changing target size). Compared to unrewarded and unpunished trials, monetary rewards and the successful avoidance of punishments both entailed greater beta-band power at left central electrodes overlaying contralateral motor areas. In contrast, monetary punishments and reward omissions both entailed increased theta-band power at fronto-central scalp sites. Additional analyses revealed that beta-band power was further increased when rewards were lowly probable. In light of previous work demonstrating similar beta-band modulations in basal ganglia during reward processing, the present results may reflect functional communication of reward-related information between the basal ganglia and motor cortical regions. In turn, the increase in fronto-central theta-band power after monetary punishments may reflect an emphasized cognitive need for behavioral adjustments. Globally, the present work identifies possible neural substrates for the growing behavioral evidence showing beneficial effects of monetary feedback on motor learning and performance.



https://ift.tt/2HOm5eI

Long-range temporal correlations in the brain distinguish conscious wakefulness from induced unconsciousness

Publication date: 1 October 2018
Source:NeuroImage, Volume 179
Author(s): Thomas Thiery, Tarek Lajnef, Etienne Combrisson, Arthur Dehgan, Pierre Rainville, George A. Mashour, Stefanie Blain-Moraes, Karim Jerbi
Rhythmic neuronal synchronization across large-scale networks is thought to play a key role in the regulation of conscious states. Changes in neuronal oscillation amplitude across states of consciousness have been widely reported, but little is known about possible changes in the temporal dynamics of these oscillations. The temporal structure of brain oscillations may provide novel insights into the neural mechanisms underlying consciousness. To address this question, we examined long-range temporal correlations (LRTC) of EEG oscillation amplitudes recorded during both wakefulness and anesthetic-induced unconsciousness. Importantly, the time-varying EEG oscillation envelopes were assessed over the course of a sevoflurane sedation protocol during which the participants alternated between states of consciousness and unconsciousness. Both spectral power and LRTC in oscillation amplitude were computed across multiple frequency bands. State-dependent differences in these features were assessed using non-parametric tests and supervised machine learning. We found that periods of unconsciousness were associated with increases in LRTC in beta (15–30Hz) amplitude over frontocentral channels and with a suppression of alpha (8–13Hz) amplitude over occipitoparietal electrodes. Moreover, classifiers trained to predict states of consciousness on single epochs demonstrated that the combination of beta LRTC with alpha amplitude provided the highest classification accuracy (above 80%). These results suggest that loss of consciousness is accompanied by an augmentation of temporal persistence in neuronal oscillation amplitude, which may reflect an increase in regularity and a decrease in network repertoire compared to the brain's activity during resting-state consciousness.



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On testing for spatial correspondence between maps of human brain structure and function

Publication date: September 2018
Source:NeuroImage, Volume 178
Author(s): Aaron F. Alexander-Bloch, Haochang Shou, Siyuan Liu, Theodore D. Satterthwaite, David C. Glahn, Russell T. Shinohara, Simon N. Vandekar, Armin Raznahan
A critical issue in many neuroimaging studies is the comparison between brain maps. Nonetheless, it remains unclear how one should test hypotheses focused on the overlap or spatial correspondence between two or more brain maps. This "correspondence problem" affects, for example, the interpretation of comparisons between task-based patterns of functional activation, resting-state networks or modules, and neuroanatomical landmarks. To date, this problem has been addressed with remarkable variability in terms of methodological approaches and statistical rigor. In this paper, we address the correspondence problem using a spatial permutation framework to generate null models of overlap by applying random rotations to spherical representations of the cortical surface, an approach for which we also provide a theoretical statistical foundation. We use this method to derive clusters of cognitive functions that are correlated in terms of their functional neuroatomical substrates. In addition, using publicly available data, we formally demonstrate the correspondence between maps of task-based functional activity, resting-state fMRI networks and gyral-based anatomical landmarks. We provide open-access code to implement the methods presented for two commonly-used tools for surface based cortical analysis (https://ift.tt/2sXf3zW). This spatial permutation approach constitutes a useful advance over widely-used methods for the comparison of cortical maps, thereby opening new possibilities for the integration of diverse neuroimaging data.



https://ift.tt/2LNXaug

Proteome response of dental pulp cells to exogenous FGF8

Publication date: 15 July 2018
Source:Journal of Proteomics, Volume 183
Author(s): Rozaliya Tsikandelova, Petko Mladenov, Sébastien Planchon, Silvia Kalenderova, Maria Praskova, Zornitsa Mihaylova, Pavel Stanimirov, Vanyo Mitev, Jenny Renaut, Nikolay Ishkitiev
FGF8 specifies early tooth development by directing the migration of the early tooth founder cells to the site of tooth emergence. To date the effect of the FGF8 in adult dental pulp has not been studied. We have assessed the regenerative potential of FGF8 by evaluating changes in the proteome landscape of dental pulp following short- and long-term exposure to recombinant FGF8 protein. In addition, we carried out qRT PCR analysis to determine extracellular/adhesion gene marker expression and assessed cell proliferation and mineralization in response to FGF8 treatment. 2D and mass spectrometry data showed differential expression of proteins implicated in cytoskeleton/ECM remodeling and migration, cell proliferation and odontogenic differentiation as evidenced by the upregulation of gelsolin, moesin, LMNA, WDR1, PLOD2, COPS5 and downregulation of P4HB. qRT PCR showed downregulation of proteins involved in cell-matrix adhesion such as ADAMTS8, LAMB3 and ANOS1 and increased expression of the angiogenesis marker PECAM1. We have observed that, FGF8 treatment was able to boost dental pulp cell proliferation and to enhance dental pulp mineralization. Collectively, our data suggest that, FGF8 treatment could promote endogenous healing of the dental pulp via recruitment of dental pulp progenitors as well as by promoting their angiogenic and odontogenic differentiation.SignificanceDental pulp cells (DP) have been studied extensively for the purposes of mineralized tissue repair, particularly for the reconstruction of hard and soft tissue maxillofacial defects. Canonical FGF signaling has been implicated throughout multiple stages of tooth development by regulating cell proliferation, differentiation, survival as well as cellular migration. FGF8 expression is indispensible for normal tooth development and particularly for the migration of early tooth progenitors to the sites of tooth emergence. The present study provides proteome and qRT PCR data with regard to the future application and biological relevance of FGF8 in dental regenerative medicine.Authors with ORCIDRozaliya Tsikandelova - 0000-0003-0178-3767Zornitsa Mihaylova - 0000-0003-1748-4489Sébastien Planchon - 0000-0002-0455-0574Nikolay Ishkitiev - 0000-0002-4351-5579

Graphical abstract

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Use of liquid isoelectric focusing (OFFGEL) on the discovery of meat tenderness biomarkers

Publication date: 15 July 2018
Source:Journal of Proteomics, Volume 183
Author(s): Lorea R. Beldarrain, Noelia Aldai, Brigitte Picard, Enrique Sentandreu, Jose L. Navarro, Miguel A. Sentandreu
Protein biomarkers of meat tenderness are known to be of primary importance for the prediction of meat quality, and hence, industry profitability. Proteome analysis was performed on meat from 8 Main Anjou beef cattle, previously classified as tender or tough meats by Warner Bratzler shear force measurements. Myofibrillar fraction of Longissimus thoracis muscle was separated by a novel fractionation approach based on liquid isoelectric focusing (OFFGEL) and further analyzed by SDS-PAGE and liquid chromatography coupled to tandem mass spectrometry.Obtained OFFGEL fraction profiles were reproducible allowing the comparison of both meat qualities and revealing 7 protein bands capable to discriminate between tender and tough samples. The proteins present in these bands were troponin T, Heat Shock protein beta-1, creatine kinase, actin, troponin C, myosins 1 and 2 and myozenin-1. The latter protein has not been previously reported as a marker of meat tenderness.SignificanceThis study introduces an innovative proteomic approach for the study of muscle proteome. The fact of obtaining fractions in liquid state after OFFGEL fractionation allows for a faster analysis of proteins by mass spectrometry, being an interesting alternative to more classical proteomic approaches based on two dimensional gel electrophoresis (2-DE).

Graphical abstract

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Identification and efficacy of glycine, serine and threonine metabolism in potentiating kanamycin-mediated killing of Edwardsiella piscicida

Publication date: 15 July 2018
Source:Journal of Proteomics, Volume 183
Author(s): Jin-zhou Ye, Xiang-min Lin, Zhi-xue Cheng, Yu-bin Su, Wan-xin Li, Far-man Ali, Jun Zheng, Bo Peng
We previously showed that glucose potentiated kanamycin to kill multidrug-resistant Edwardsiella piscicida through activation of the TCA cycle. However, whether other regulatory mechanism is involved requires further investigation. By quantitative proteomics technology, iTRAQ, we systematically mapped the altered proteins in the presence of glucose and identified 94 differentially expressed proteins. The analysis of the altered proteins by pathways, amino acid biosynthesis and metabolism were enriched. And the most significantly altered eight amino acids tyrosine, phenylalanine, valine, leucine, isoleucine, glycine, serine and threonine were investigated for their potentiation of kanamycin to kill EIB202, where glycine, serine and threonine showed the strongest efficacy than the others. The combinations of glycine and serine or glucose with glycine, serine or threonine had the best effects. Moreover, pyruvate dehydrogenase, α-ketoglutarate dehydrogenase and succinate dehydrogenase activities were increased as well as the proton motive force (PMF) and intracellular kanamycin. Finally, inhibitors that disrupt PMF production abolished the potentiation. These results shed light on the mechanism of how glucose promoting the amino acids biosynthesis and metabolism to potentiate kanamycin to kill antibiotic-resistant bacteria. More importantly, our results suggested that adjusting amino acid biosynthesis and metabolism might be a strategy to become phenotypic resistance to antibiotics in bacteria.SignificanceTackling antibiotic resistance is an emerging issue in current years. Despite the efforts made toward developing new antibiotics, the progress is still lagged behind expectation. Novel strategies are required. The use of metabolite to revert antibiotic resistant is highly appreciated in recent years due to the less toxicity, more economic and high efficacy. As a continued study of our previous report on glucose potentiating kanamycin to kill antibiotic-resistant bacteria. The current study further expands the previous discovery on the mechanism of how glucose potentiate this effect. This result provides more basis on the action of glucose in reverting antibiotic resistance. And more importantly, we may derive more metabolites other than glucose to manage antibiotic resistance.

Graphical abstract

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Editorial Board

Publication date: 15 July 2018
Source:Journal of Proteomics, Volume 183





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Differences between self- and peer-rated likability in relation to social anxiety and depression in adolescents with mild intellectual disabilities

Publication date: September 2018
Source:Research in Developmental Disabilities, Volume 80
Author(s): Anke M. Klein, Esther O. Houtkamp, Elske Salemink, Jeanine M.D. Baartmans, Mike Rinck, Mariët J. van der Molen
BackgroundSocial anxiety and depressive symptoms are relatively common in adolescents with Mild to Borderline Intellectual Disabilities (MBID). Unfortunately, there are only a few studies that focus on examining processes underlying social anxiety and depression in these adolescents.AimsThe aim was to examine the differences between self- and peer-rated likability in relation to social anxiety and depression in the classroom environment.Methods and Procedures631 normative non-clinical adolescents with MBID completed questionnaires to measure social anxiety, depression, and the estimation of their own likability by peers. Peer-reported likability was derived from peer-rating scales on likability.Outcomes and ResultsAdolescents with higher levels of social anxiety significantly rated their own likability as lower than their non-anxious peers. However, socially adolescents were equally liked by their peers. Adolescents with higher levels of depression were significantly less liked by their peers, but still underestimated their own likability than adolescents with lower levels of depression.Conclusions and ImplicationsSocial anxiety and depression are linked to a biased interpretation of likability, but only depression is linked to actually being less liked by peers. Social anxiety and depression are partly based on similar underlying cognitive biases.



https://ift.tt/2ybiiZp

Informing Environmental Health Decisions Through Data Integration: Proceedings of a Workshop—in Brief.

Integrating large quantities of data from multiple, disparate sources can create new opportunities to understand complex environmental health questions. Currently, efforts are under way to develop methods to reliably integrate data from sources or designed experiments that are not traditionally used in environmental health research, such as electronic health records (EHRs), geospatial datasets, and crowd-based sources. However, combining new types and larger quantities of data to inform a specific decision also presents many new challenges.

https://ift.tt/2JPI9ed

The Safety and Quality of Abortion Care in the United States.

Abortion is a legal medical procedure that has been provided to millions of American women. Since the Institute of Medicine first reviewed the health implications of national legalized abortion in 1975, there has been a plethora of related scientific research, including well-designed randomized clinical trials, systematic reviews, and epidemiological studies examining abortion care. This research has focused on examining the relative safety of abortion methods and the appropriateness of methods for different clinical circumstances. With this growing body of research, earlier abortion methods have been refined, discontinued, and new approaches have been developed.

https://ift.tt/2LQzlBU

Sexual Harassment of Women: Climate, Culture, and Consequences in Academic Sciences, Engineering, and Medicine [Prepublication Draft].

Over the last few decades, research, activity, and funding has been devoted to improving the recruitment, retention, and advancement of women in the fields of science, engineering, and medicine. In recent years the diversity of those participating in these fields, particularly the participation of women, has improved and there are significantly more women entering careers and studying science, engineering, and medicine than ever before. However, as women increasingly enter these fields they face biases and barriers and it is not surprising that sexual harassment is one of these barriers.

https://ift.tt/2JXjy74

Understanding Pathways to a Paradigm Shift in Toxicity Testing and Decision-Making: Proceedings of a Workshop—in Brief.

Advances in new tools and tests of chemical toxicity—from high throughput, cell-based, in vitro studies to tissue chips to environment-wide association studies—have led to a new understanding about the effects of chemical exposures in humans. These new approaches are faster, less expensive, and increasingly more relevant to human exposures than legacy animal toxicity testing approaches. Additionally, the passage of the Frank R. Lautenberg Chemical Safety for the 21st Century Act (Lautenberg Act), which amends the Toxic Substances Control Act (TSCA), has encouraged opportunities for industry and government agencies to use data from emerging toxicity testing approaches, particularly in risk assessment and analysis contexts. However, many questions remain about whether and how to make the paradigm shift away from traditional approaches and toward using new data streams as the basis for the wide array of research, policy, and regulatory decisions facing the environmental health field.

https://ift.tt/2LQBe1M

Advancing Disease Modeling in Animal-Based Research in Support of Precision Medicine: Proceedings of a Workshop.

Precision medicine is focused on the individual and will require the rapid and accurate identification and prioritization of causative factors of disease. To move forward and accelerate the delivery of the anticipated benefits of precision medicine, developing predictable, reproducible, and reliable animal models will be essential. In order to explore the topic of animal-based research and its relevance to precision medicine, the National Academies of Sciences, Engineering, and Medicine convened a 2-day workshop on October 5 and 6, 2017. The workshop was designed to focus on the development, implementation, and interpretation of model organisms to advance and accelerate the field of precision medicine. Participants examined the extent to which next-generation animal models, designed using patient data and phenotyping platforms targeted to reveal and inform disease mechanisms, will be essential to the successful implementation of precision medicine. This publication summarizes the presentations and discussions from the workshop.

https://ift.tt/2JPZUtH

Editorial Board

Publication date: 1 July 2018
Source:Acta Biomaterialia, Volume 74





https://ift.tt/2LNTrwJ

Platelet-derived growth factor-coated decellularized meniscus scaffold for integrative healing of meniscus tears

Publication date: Available online 14 June 2018
Source:Acta Biomaterialia
Author(s): Kwang Il Lee, Merissa Olmer, Jihye Baek, Darryl D. D'Lima, Martin K. Lotz
The aim of this study was to examine the potential of platelet-derived growth factor (PDGF)-coated decellularized meniscus scaffold in mediating integrative healing of meniscus tears by inducing endogenous cell migration.Fresh bovine meniscus was chemically decellularized and covalently conjugated with heparin and PDGF-BB. In vitro PDGF release kinetics was measured. The scaffold was transplanted into experimental tears in avascular bovine meniscus explants and cultured for 2 and 4 weeks. The number migrating and proliferating cells at the borderline between the scaffold and injured explant and PDGF receptor-β (PDGFR β) expressing cells were counted. The alignment of the newly produced ECM and collagen was analyzed by Safranin-O, picrosirius red staining, and differential interference contrast (DIC). Tensile testing of the explants was performed after culture for 2 and 4 weeks.Heparin conjugated scaffold showed immobilization of high levels of PDGF-BB, with sustained release over 2 weeks. Insertion of the PDGF-BB treated scaffold in defects in avascular meniscus led to increased PDGFR β expression, cell migration and proliferation into the defect zone. Safranin-O, picrosirius red staining and DIC showed tissue integration between the scaffold and injured explants. Tensile properties of injured explants treated with PDGF-BB coated scaffold were significantly higher than in the scaffold without PDGF.In conclusion, PDGF-BB-coated scaffold increased PDGFR β expression and promoted migration of endogenous meniscus cells to the defect area. New matrix was formed that bridged the space between the native meniscus and the scaffold and this was associated with improved biomechanical properties. The PDGF-BB-coated scaffold will be promising for clinical translation to healing of meniscus tears.Statement of SignificanceMeniscus tears are the most common injury of the knee joint. The most prevalent forms that occur in the inner third typically do not spontaneously heal and represent a major risk factor for the development of knee osteoarthritis. The goal of this project was to develop an approach that is readily applicable for clinical use.We selected a natural and readily available decellularized meniscus scaffold and conjugated it with PDGF, which we had previously found to have strong chemotactic activity for chondrocytes and progenitor cells.The present results show that insertion of the PDGF-conjugated scaffold in defects in avascular meniscus led to endogenous cell migration and proliferation into the defect zone with tissue integration between the scaffold and injured explants and improved tensile properties.This PDGF-conjugated scaffold will be promising for a translational approach to healing of meniscus tears.

Graphical abstract

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Dual surface modification of PDMS-based silicone implants to suppress capsular contracture

Publication date: Available online 14 June 2018
Source:Acta Biomaterialia
Author(s): Byoung Yong Yoo, Byung Hwi Kim, Jae Sang Lee, Byung Ho Shin, Heeyeon Kwon, Won-Gun Koh, Chan Yeong Heo
In this study, we report a new physicochemical surface on poly(dimethylsiloxane) (PDMS)-based silicone implants in an effort to minimize capsular contracture. Two different surface modification strategies, namely, microtexturing as a physical cue and multilayer coating as a chemical cue, were combined to achieve synergistic effects. The deposition of uniformly sized microparticles onto uncured PDMS surfaces and the subsequent removal after curing generated microtextured surfaces with concave hemisphere micropatterns. The size of the individual micropattern was controlled by the microparticle size. Micropatterns of three different sizes (37.16, 70.22, and 97.64 μm) smaller than 100 μm were produced for potential application to smooth and round-shaped breast implants. The PDMS surface was further chemically modified by layer-by-layer (LbL) deposition of poly-L-lysine and hyaluronic acid. Short-term in vitro experiments demonstrated that all the PDMS samples were cytocompatible. However, lower expression of TGF-β and α-SMA, the major profibrotic cytokine and myofibroblast marker, respectively, was observed in only multilayer-coated PDMS samples with larger size micropatterns (70.22 and 97.64 μm), thereby confirming the synergistic effects of physical and chemical cues. An in vivo study conducted for 8 weeks after implantation in rats also indicated that PDMS samples with larger size micropatterns and multilayer coating most effectively inhibited capsular contracture based on analyses of tissue inflammation, number of macrophage, fibroblast and myofibroblast, TGF-β expression, collagen density, and capsule thickness.Statement of SignificanceAlthough PDMS-based silicone implants have been widely used for various applications including breast implants, they usually cause typical side effect called as capsular contracture. Prior studies have shown that microtexturing and surface coating could reduce capsular contracture. However, previous methods are limited in application scope and difficult to obtain FDA approval because of large and non-uniform size of microtexture as well as the use of toxic chemical components. Here, those issues could be addressed by creating microtexture less than 100 μm with narrow size distribution and using layer-by-layer deposition of biocompatible polymer without using any toxic compounds. Furthermore, this is first attempt to combine microtexture with multilayer coating to obtain synergetic effects in minimizing the capsular contracture.

Graphical abstract

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Development of tactile sensory circuits in the CNS

Publication date: December 2018
Source:Current Opinion in Neurobiology, Volume 53
Author(s): Takuji Iwasato, Reha S. Erzurumlu
Molecular identification of neuronal types and genetic and imaging approaches to characterize their properties reveal morphological, physiological and dynamic aspects of sensory circuit development. Here we focus on the mouse tactile sensory circuitry, with particular emphasis on the main trigeminal pathway that connects the whiskers, the major tactile organ in rodents, to the neocortex. At each level of this pathway, neurogenesis, axonal elongation, pathfinding, target recognition and circuit reorganization including dendritic refinement of cortical layer 4 neurons occur contemporaneously and a multitude of molecular signals are used in differing combinations. We highlight recent advances in development of tactile circuitry and note gaps in our understanding.



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Deep Learning and Conditional Random Fields-based Depth Estimation and Topographical Reconstruction from Conventional Endoscopy

Publication date: Available online 14 June 2018
Source:Medical Image Analysis
Author(s): Faisal Mahmood, Nicholas J. Durr
Colorectal cancer is the fourth leading cause of cancer deaths worldwide and the second leading cause in the United States. The risk of colorectal cancer can be mitigated by the identification and removal of premalignant lesions through optical colonoscopy. Unfortunately, conventional colonoscopy misses more than 20% of the polyps that should be removed, due in part to poor contrast of lesion topography. Imaging depth and tissue topography during a colonoscopy is difficult because of the size constraints of the endoscope and the deforming mucosa. Most existing methods make unrealistic assumptions which limits accuracy and sensitivity. In this paper, we present a method that avoids these restrictions, using a joint deep convolutional neural network-conditional random field (CNN-CRF) framework for monocular endoscopy depth estimation. Estimated depth is used to reconstruct the topography of the surface of the colon from a single image. We train the unary and pairwise potential functions of a CRF in a CNN on synthetic data, generated by developing an endoscope camera model and rendering over 200,000 images of an anatomically-realistic colon.We validate our approach with real endoscopy images from a porcine colon, transferred to a synthetic-like domain via adversarial training, with ground truth from registered computed tomography measurements. The CNN-CRF approach estimates depths with a relative error of 0.152 for synthetic endoscopy images and 0.242 for real endoscopy images. We show that the estimated depth maps can be used for reconstructing the topography of the mucosa from conventional colonoscopy images. This approach can easily be integrated into existing endoscopy systems and provides a foundation for improving computer-aided detection algorithms for detection, segmentation and classification of lesions.

Graphical abstract

https://ift.tt/2JO0Q1V