Biophysical Modulations of Functional Connectivity

Resting-state low frequency oscillations have been detected in many functional magnetic resonance imaging (MRI) studies and appear to be synchronized between functionally related areas. Converging evidence from MRI and other imaging modalities suggest that this activity has an intrinsic neuronal origin. Multiple consistent networks have been found in large populations, and have been shown to be stable over time. Further, these patterns of functional connectivity have been shown to be altered in healthy controls under various physiological challenges. This review will present the biophysical characterization of functional connectivity, and examine the effects of physical state manipulations (such as anesthesia, fatigue, and aging) in healthy controls.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90432/1/brain-2E2011-2E0039.pd

DeepBrain: Functional Representation of Neural In-Situ Hybridization Images for Gene Ontology Classification Using Deep Convolutional Autoencoders

This paper presents a novel deep learning-based method for learning a functional representation of mammalian neural images. The method uses a deep convolutional denoising autoencoder (CDAE) for generating an invariant, compact representation of in situ hybridization (ISH) images. While most existing methods for bio-imaging analysis were not developed to handle images with highly complex anatomical structures, the results presented in this paper show that functional representation extracted by CDAE can help learn features of functional gene ontology categories for their classification in a highly accurate manner. Using this CDAE representation, our method outperforms the previous state-of-the-art classification rate, by improving the average AUC from 0.92 to 0.98, i.e., achieving 75% reduction in error. The method operates on input images that were downsampled significantly with respect to the original ones to make it computationally feasible

Learning and Matching Multi-View Descriptors for Registration of Point Clouds

Critical to the registration of point clouds is the establishment of a set of accurate correspondences between points in 3D space. The correspondence problem is generally addressed by the design of discriminative 3D local descriptors on the one hand, and the development of robust matching strategies on the other hand. In this work, we first propose a multi-view local descriptor, which is learned from the images of multiple views, for the description of 3D keypoints. Then, we develop a robust matching approach, aiming at rejecting outlier matches based on the efficient inference via belief propagation on the defined graphical model. We have demonstrated the boost of our approaches to registration on the public scanning and multi-view stereo datasets. The superior performance has been verified by the intensive comparisons against a variety of descriptors and matching methods

Engineering The Unicellular Alga Phaeodactylum tricornutum For High-Value Plant Triterpenoid Production

Plant triterpenoids constitute a diverse class of organic compounds that play a major role in development, plant defense and environmental interaction. Several triterpenes have demonstrated potential as pharmaceuticals. One example is betulin, which has shown promise as a pharmaceutical precursor for the treatment of certain cancers and HIV. Major challenges for triterpenoid commercialization include their low production levels and their cost‐effective purification from the complex mixtures present in their natural hosts. Therefore, attempts to produce these compounds in industrially relevant microbial systems such as bacteria and yeasts have attracted great interest. Here we report the production of the triterpenes betulin and its precursor lupeol in the photosynthetic diatom Phaeodactylum tricornutum, a unicellular eukaryotic alga. This was achieved by introducing three plant enzymes in the microalga: a Lotus japonicus oxidosqualene cyclase and a Medicago truncatula cytochrome P450 along with its native reductase. The introduction of the L. japonicus oxidosqualene cyclase perturbed the mRNA expression levels of the native mevalonate and sterol biosynthesis pathway. The best performing strains were selected and grown in a 550L pilot scale photobioreactor facility. To our knowledge, this is the most extensive pathway engineering undertaken in a diatom and the first time that a sapogenin has been artificially produced in a microalga, demonstrating the feasibility of the photo‐bio‐production of more complex high‐value, metabolites in microalgae

Predictive gene lists for breast cancer prognosis: A topographic visualisation study

<p>Abstract</p> <p>Background</p> <p>The controversy surrounding the non-uniqueness of predictive gene lists (PGL) of small selected subsets of genes from very large potential candidates as available in DNA microarray experiments is now widely acknowledged <abbrgrp><abbr bid="B1">1</abbr></abbrgrp>. Many of these studies have focused on constructing discriminative semi-parametric models and as such are also subject to the issue of random correlations of sparse model selection in high dimensional spaces. In this work we outline a different approach based around an unsupervised patient-specific nonlinear topographic projection in predictive gene lists.</p> <p>Methods</p> <p>We construct nonlinear topographic projection maps based on inter-patient gene-list relative dissimilarities. The Neuroscale, the Stochastic Neighbor Embedding(SNE) and the Locally Linear Embedding(LLE) techniques have been used to construct two-dimensional projective visualisation plots of 70 dimensional PGLs per patient, classifiers are also constructed to identify the prognosis indicator of each patient using the resulting projections from those visualisation techniques and investigate whether <it>a-posteriori </it>two prognosis groups are separable on the evidence of the gene lists.</p> <p>A literature-proposed predictive gene list for breast cancer is benchmarked against a separate gene list using the above methods. Generalisation ability is investigated by using the mapping capability of Neuroscale to visualise the follow-up study, but based on the projections derived from the original dataset.</p> <p>Results</p> <p>The results indicate that small subsets of patient-specific PGLs have insufficient prognostic dissimilarity to permit a distinction between two prognosis patients. Uncertainty and diversity across multiple gene expressions prevents unambiguous or even confident patient grouping. Comparative projections across different PGLs provide similar results.</p> <p>Conclusion</p> <p>The random correlation effect to an arbitrary outcome induced by small subset selection from very high dimensional interrelated gene expression profiles leads to an outcome with associated uncertainty. This continuum and uncertainty precludes any attempts at constructing discriminative classifiers.</p> <p>However a patient's gene expression profile could possibly be used in treatment planning, based on knowledge of other patients' responses.</p> <p>We conclude that many of the patients involved in such medical studies are <it>intrinsically unclassifiable </it>on the basis of provided PGL evidence. This additional category of 'unclassifiable' should be accommodated within medical decision support systems if serious errors and unnecessary adjuvant therapy are to be avoided.</p

Generic 3D Representation via Pose Estimation and Matching

Though a large body of computer vision research has investigated developing generic semantic representations, efforts towards developing a similar representation for 3D has been limited. In this paper, we learn a generic 3D representation through solving a set of foundational proxy 3D tasks: object-centric camera pose estimation and wide baseline feature matching. Our method is based upon the premise that by providing supervision over a set of carefully selected foundational tasks, generalization to novel tasks and abstraction capabilities can be achieved. We empirically show that the internal representation of a multi-task ConvNet trained to solve the above core problems generalizes to novel 3D tasks (e.g., scene layout estimation, object pose estimation, surface normal estimation) without the need for fine-tuning and shows traits of abstraction abilities (e.g., cross-modality pose estimation). In the context of the core supervised tasks, we demonstrate our representation achieves state-of-the-art wide baseline feature matching results without requiring apriori rectification (unlike SIFT and the majority of learned features). We also show 6DOF camera pose estimation given a pair local image patches. The accuracy of both supervised tasks come comparable to humans. Finally, we contribute a large-scale dataset composed of object-centric street view scenes along with point correspondences and camera pose information, and conclude with a discussion on the learned representation and open research questions.Comment: Published in ECCV16. See the project website http://3drepresentation.stanford.edu/ and dataset website https://github.com/amir32002/3D_Street_Vie

A propensity matched case-control study comparing efficacy, safety and costs of the subcutaneous vs. transvenous implantable cardioverter defibrillator.

BACKGROUND: Subcutaneous implantable cardioverter defibrillators (S-ICD) have become more widely available. However, comparisons with conventional transvenous ICDs (TV-ICD) are scarce. METHODS: We conducted a propensity matched case-control study including all patients that underwent S-ICD implantation over a five-year period in a single tertiary centre. Controls consisted of all TV-ICD implant patients over a contemporary time period excluding those with pacing indication, biventricular pacemakers and those with sustained monomorphic ventricular tachycardia requiring anti-tachycardia pacing. Data was collected on device-related complications and mortality rates. A cost efficacy analysis was performed. RESULTS: Sixty-nine S-ICD cases were propensity matched to 69 TV-ICD controls. During a mean follow-up of 31±19 (S-ICD) and 32±21months (TV-ICD; p=0.88) there was a higher rate of device-related complications in the TV-ICD group predominantly accounted for by lead failures (n=20, 29% vs. n=6, 9%; p=0.004). The total mean cost for each group, including the complication-related costs was £9967±4511 ($13,639±6173) and £12,601±1786 ($17,243±2444) in the TV-ICD and S-ICD groups respectively (p=0.0001). Even though more expensive S-ICD was associated with a relative risk reduction of device-related complication of 70% with a HR of 0.30 (95%CI 0.12-0.76; p=0.01) compared to TV-ICDs. CONCLUSIONS: TV-ICDs are associated with increased device-related complication rates compared to a propensity matched S-ICD group during a similar follow-up period. Despite the existing significant difference in unit cost of the S-ICD, overall S-ICD costs may be mitigated versus TV-ICDs over a longer follow-up period

Distal junctional kyphosis in patients with Scheuermann’s disease: a retrospective radiographic analysis

Purpose To investigate the relationship between preoperative and postoperative spinopelvic alignment and occurrence of DJK/DJF. Study design/setting This was a retrospective observational cohort study. Patient sample The sample included 40 patients who underwent posterior correction of SK from January 2006 to December 2014. Outcome measures Correlation analysis between the preoperative and postoperative spinopelvic alignment parameters and development of DJK over the course of the study period were studied. Methods Whole spine X-rays obtained before surgery, 3 months after surgery and at the latest follow-up were analyzed. The following parameters were measured: maximum of thoracic kyphosis (TK), lumbar lordosis (LL), sagittal vertical axis (SVA), pelvic incidence (PI), pelvic tilt (PT), sacral slope (SS), lower instrumented vertebra (LIV) and LIV plumb line. Development of DJK was considered as the primary end point of the study. The patient population was split into a control and DJK group, with 34 patients and 6 patients, respectively. Statistic analysis was performed using unpaired t test for normal contribution and Mann–Whitney test for skew distributed values. The significance level was set to 0.05. Results DJK occurred in 15% (n = 6) over the study period. There was a significantly lower postoperative TK for the group with DJK (42.4 ± 5.3 vs 49.8 ± 6.7, p = 0.015). LIV plumb line showed higher negative values in the DJK group (−43.6 ± 25.1 vs −2.2 ± 17.8, p = 0.0435). Furthermore, postoperative LL changes were lower for the DJK group (33.84 ± 13.86% vs 31.77 ± 14.05, p < 0.0001.) The age of the patients who developed DJK was also significantly lower than that of the control group (16.8 ± 1.7 vs 19.6 ± 4.9, p = 0.0024.) Conclusions SK patients who developed DJK appeared to have a significantly higher degree of TK correction and more negative LIV plumb line. In addition, there may be a higher risk for DJK in patients undergoing corrective surgery at a younger age

Same-day discharge following catheter ablation of atrial fibrillation: A safe and cost-effective approach

Introduction: The frequency of catheter ablation for atrial fibrillation (AF) has increased dramatically, stretching resources. Discharge on the same day as treatment may increase the efficiency and throughput. There are limited data regarding the safety of this strategy. / Methods: We performed a retrospective analysis of consecutive patients undergoing AF ablation in a tertiary center and in a district general hospital, and identified those discharged on the same day of treatment. The safety endpoint was any complication and/or presentation to hospital in the 48‐h and at 30 days postdischarge. We performed an economic analysis to calculate potential cost saving. / Results: Among a total population of 2628 patients, we identified 727 subjects (61.1 ± 12.5 years, 69.6% male) undergoing day‐case AF ablation. Cryoballoon technique was used in 79.2% of the day‐cases, and 91.6% of the procedures were performed under conscious sedation. 1.8% (13) of the participants met the safety composite endpoint at 48‐h, however only 0.7% (5) required at least 1 day of hospitalization. Bleeding or hematoma at the femoral access site (0.5%) and pericarditic chest pain (0.5%) were the main reasons for readmission. None experienced cardiac tamponade or other life‐threatening complications in the 48‐h postdischarge. Overall rate of complication and/or presentation to hospital at 30 days was 3.7%. Our day‐case policy resulted in an annual cost‐saving of approximately of £83 927 for our hospital. / Conclusion: In this large multicentre cohort, same‐day discharge in selected patients following AF ablation appears to be safe and cost‐effective, with a very low rate of early readmission or post‐discharge complication

Validation of Decentralised Smart Contracts Through Game Theory and Formal Methods

Decentralised smart contracts represent the next step in the development of protocols that support the interaction of independent players without the presence of a coercing authority. Based on protocols a` la BitCoin for digital currencies, smart contracts are believed to be a potentially enabling technology for a wealth of future applications. The validation of such an early developing technology is as necessary as it is complex. In this paper we combine game theory and formal models to tackle the new challenges posed by the validation of such systems