A Model for the Detection of Moving Targets in Visual Clutter Inspired by Insect Physiology

We present a computational model for target discrimination based on intracellular recordings from neurons in the fly visual system. Determining how insects detect and track small moving features, often against cluttered moving backgrounds, is an intriguing challenge, both from a physiological and a computational perspective. Previous research has characterized higher-order neurons within the fly brain, known as ‘small target motion detectors’ (STMD), that respond robustly to moving features, even when the velocity of the target is matched to the background (i.e. with no relative motion cues). We recorded from intermediate-order neurons in the fly visual system that are well suited as a component along the target detection pathway. This full-wave rectifying, transient cell (RTC) reveals independent adaptation to luminance changes of opposite signs (suggesting separate ON and OFF channels) and fast adaptive temporal mechanisms, similar to other cell types previously described. From this physiological data we have created a numerical model for target discrimination. This model includes nonlinear filtering based on the fly optics, the photoreceptors, the 1st order interneurons (Large Monopolar Cells), and the newly derived parameters for the RTC. We show that our RTC-based target detection model is well matched to properties described for the STMDs, such as contrast sensitivity, height tuning and velocity tuning. The model output shows that the spatiotemporal profile of small targets is sufficiently rare within natural scene imagery to allow our highly nonlinear ‘matched filter’ to successfully detect most targets from the background. Importantly, this model can explain this type of feature discrimination without the need for relative motion cues

A comparative analysis of predictive models of morbidity in intensive care unit after cardiac surgery – Part II: an illustrative example

<p>Abstract</p> <p>Background</p> <p>Popular predictive models for estimating morbidity probability after heart surgery are compared critically in a unitary framework. The study is divided into two parts. In the first part modelling techniques and intrinsic strengths and weaknesses of different approaches were discussed from a theoretical point of view. In this second part the performances of the same models are evaluated in an illustrative example.</p> <p>Methods</p> <p>Eight models were developed: Bayes linear and quadratic models, <it>k</it>-nearest neighbour model, logistic regression model, Higgins and direct scoring systems and two feed-forward artificial neural networks with one and two layers. Cardiovascular, respiratory, neurological, renal, infectious and hemorrhagic complications were defined as morbidity. Training and testing sets each of 545 cases were used. The optimal set of predictors was chosen among a collection of 78 preoperative, intraoperative and postoperative variables by a stepwise procedure. Discrimination and calibration were evaluated by the area under the receiver operating characteristic curve and Hosmer-Lemeshow goodness-of-fit test, respectively.</p> <p>Results</p> <p>Scoring systems and the logistic regression model required the largest set of predictors, while Bayesian and <it>k</it>-nearest neighbour models were much more parsimonious. In testing data, all models showed acceptable discrimination capacities, however the Bayes quadratic model, using only three predictors, provided the best performance. All models showed satisfactory generalization ability: again the Bayes quadratic model exhibited the best generalization, while artificial neural networks and scoring systems gave the worst results. Finally, poor calibration was obtained when using scoring systems, <it>k</it>-nearest neighbour model and artificial neural networks, while Bayes (after recalibration) and logistic regression models gave adequate results.</p> <p>Conclusion</p> <p>Although all the predictive models showed acceptable discrimination performance in the example considered, the Bayes and logistic regression models seemed better than the others, because they also had good generalization and calibration. The Bayes quadratic model seemed to be a convincing alternative to the much more usual Bayes linear and logistic regression models. It showed its capacity to identify a minimum core of predictors generally recognized as essential to pragmatically evaluate the risk of developing morbidity after heart surgery.</p

Higher Plant Cytochrome b5 Polypeptides Modulate Fatty Acid Desaturation

BACKGROUND: Synthesis of polyunsaturated fatty acids (PUFAs) in the endoplasmic reticulum of plants typically involves the fatty acid desaturases FAD2 and FAD3, which use cytochrome b(5) (Cb5) as an electron donor. Higher plants are reported to have multiple isoforms of Cb5, in contrast to a single Cb5 in mammals and yeast. Despite the wealth of information available on the roles of FAD2 and FAD3 in PUFA synthesis, information regarding the contributions of various Cb5 isoforms in desaturase-mediated reactions is limited. RESULTS: The present functional characterization of Cb5 polypeptides revealed that all Arabidopsis Cb5 isoforms are not similarly efficient in ω-6 desaturation, as evidenced by significant variation in their product outcomes in yeast-based functional assays. On the other hand, characterization of Cb5 polypeptides of soybean (Glycine max) suggested that similar ω-6 desaturation efficiencies were shared by various isoforms. With regard to ω-3 desaturation, certain Cb5 genes of both Arabidopsis and soybean were shown to facilitate the accumulation of more desaturation products than others when co-expressed with their native FAD3. Additionally, similar trends of differential desaturation product accumulation were also observed with most Cb5 genes of both soybean and Arabidopsis even if co-expressed with non-native FAD3. CONCLUSIONS: The present study reports the first description of the differential nature of the Cb5 genes of higher plants in fatty acid desaturation and further suggests that ω-3/ω-6 desaturation product outcome is determined by the nature of both the Cb5 isoform and the fatty acid desaturases

Isolated and dynamical horizons and their applications

Over the past three decades, black holes have played an important role in quantum gravity, mathematical physics, numerical relativity and gravitational wave phenomenology. However, conceptual settings and mathematical models used to discuss them have varied considerably from one area to another. Over the last five years a new, quasi-local framework was introduced to analyze diverse facets of black holes in a unified manner. In this framework, evolving black holes are modeled by dynamical horizons and black holes in equilibrium by isolated horizons. We review basic properties of these horizons and summarize applications to mathematical physics, numerical relativity and quantum gravity. This paradigm has led to significant generalizations of several results in black hole physics. Specifically, it has introduced a more physical setting for black hole thermodynamics and for black hole entropy calculations in quantum gravity; suggested a phenomenological model for hairy black holes; provided novel techniques to extract physics from numerical simulations; and led to new laws governing the dynamics of black holes in exact general relativity.Comment: 77 pages, 12 figures. Typos and references correcte

A Flow Cytometry-Based FRET Assay to Identify and Analyse Protein-Protein Interactions in Living Cells

Försters resonance energy transfer (FRET) microscopy is widely used for the analysis of protein interactions in intact cells. However, FRET microscopy is technically challenging and does not allow assessing interactions in large cell numbers. To overcome these limitations we developed a flow cytometry-based FRET assay and analysed interactions of human and simian immunodeficiency virus (HIV and SIV) Nef and Vpu proteins with cellular factors, as well as HIV Rev multimer-formation.Amongst others, we characterize the interaction of Vpu with CD317 (also termed Bst-2 or tetherin), a host restriction factor that inhibits HIV release from infected cells and demonstrate that the direct binding of both is mediated by the Vpu membrane-spanning region. Furthermore, we adapted our assay to allow the identification of novel protein interaction partners in a high-throughput format.The presented combination of FRET and FACS offers the precious possibility to discover and define protein interactions in living cells and is expected to contribute to the identification of novel therapeutic targets for treatment of human diseases

Genome-Wide Fitness and Expression Profiling Implicate Mga2 in Adaptation to Hydrogen Peroxide

Caloric restriction extends lifespan, an effect once thought to involve attenuation of reactive oxygen species (ROS) generated by aerobic metabolism. However, recent evidence suggests that caloric restriction may in fact raise ROS levels, which in turn provides protection from acute doses of oxidant through a process called adaptation. To shed light on the molecular mechanisms of adaptation, we designed a series of genome-wide deletion fitness and mRNA expression screens to identify genes involved in adaptation to hydrogen peroxide. Combined with known transcriptional interactions, the integrated data implicate Yap1 and Skn7 as central transcription factors of both the adaptive and acute oxidative responses. They also identify the transcription factors Mga2 and Rox1 as active exclusively in the adaptive response and show that Mga2 is essential for adaptation. These findings are striking because Mga2 and Rox1 have been thought to control the response to hypoxic, not oxidative, conditions. Expression profiling of mga2Δ and rox1Δ knockouts shows that these factors most strongly regulate targets in ergosterol, fatty-acid, and zinc metabolic pathways. Direct quantitation of ergosterol reveals that its basal concentration indeed depends on Mga2, but that Mga2 is not required for the decrease in ergosterol observed during adaptation

Improvement of Cardiac Function in Mouse Myocardial Infarction after Transplantation of Epigenetically-Modified Bone Marrow Progenitor Cells

OBJECTIVE: To study usefulness of bone marrow progenitor cells (BPCs) epigenetically altered by chromatin modifying agents in mediating heart repair after myocardial infarction in mice. METHODS AND RESULTS: We tested the therapeutic efficacy of bone marrow progenitor cells treated with the clinically-used chromatin modifying agents Trichostatin A (TSA, histone deacetylase inhibitor) and 5Aza-2-deoxycytidine (Aza, DNA methylation inhibitor) in a mouse model of acute myocardial infarction (AMI). Treatment of BPCs with Aza and TSA induced expression of pluripotent genes Oct4, Nanog, Sox2, and thereafter culturing these cells in defined cardiac myocyte-conditioned medium resulted in their differentiation into cardiomyocyte progenitors and subsequently into cardiac myocytes. Their transition was deduced by expression of repertoire of markers: Nkx2.5, GATA4, cardiotroponin T, cardiotroponin I, α-sarcomeric actinin, Mef2c and MHC-α. We observed that the modified BPCs had greater AceH3K9 expression and reduced histone deacetylase1 (HDAC1) and lysine-specific demethylase1 (LSD1) expression compared to untreated BPCs, characteristic of epigenetic changes. Intra-myocardial injection of modified BPCs after AMI in mice significantly improved left ventricular function. These changes were ascribed to differentiation of the injected cells into cardiomyocytes and endothelial cells. CONCLUSION: Treatment of BPCs with Aza and TSA converts BPCs into multipotent cells, which can then be differentiated into myocyte progenitors. Transplantation of these modified progenitor cells into infarcted mouse hearts improved left ventricular function secondary to differentiation of cells in the niche into myocytes and endothelial cells

Stiffness in total knee arthroplasty

Stiffness is a relatively uncommon complication after total knee arthroplasty. It has been defined as a painful limitation in the range of movement (ROM). Its pathogenesis is still unclear even if some risk factors have been identified. Patient-related conditions may be difficult to treat. Preoperative ROM is the most important risk factor, but an association with diabetes, reflex sympathetic dystrophy, and general pathologies such as juvenile rheumatoid arthritis and ankylosing spondylitis has been demonstrated. Moreover, previous surgery may be an additional cause of an ROM limitation. Postoperative factors include infections, arthrofibrosis, heterotrophic ossifications, and incorrect rehabilitation protocol. Infections represent a challenging problem for the orthopaedic surgeon, and treatment may require long periods of antibiotics administration. However, it is widely accepted that an aggressive rehabilitation protocol is mandatory for a proper ROM recovery and to avoid the onset of arthrofibrosis and heterotrophic ossifications. Finally, surgery-related factors represent the most common cause of stiffness; they include errors in soft-tissue balancing, component malpositioning, and incorrect component sizing. Although closed manipulation, arthroscopic and open arthrolysis have been proposed, they may lead to unpredictable results and incomplete ROM recovery. Revision surgery must be proposed in the case of well-documented surgical errors. These operations are technically demanding and may be associated with high risk of complications; therefore they should be accurately planned and properly performed