Short-Term Retinoic Acid Treatment Increases In Vivo, but Decreases In Vitro, Epidermal Transglutaminase-K Enzyme Activity and Immunoreactivity

Epidermal transglutaminase-K is believed to catalyze the covalent linking of loricrin and involucrin to form cross-linked (CE) envelopes. In normal skin, transglutaminase-K is expressed as a band immediately below the stratum corneum, whereas in psoriasis and healing skin its expression is considerably expanded throughout the suprabasal layers. We have investigated whether the hyperproliferative state induced by short-term application of topical retinoic acid is similarly characterized by an increase in transglutaminase-K enzyme activity and immunoreactivity.Retinoic acid (0.1% cream) or vehicle were applied to human skin and occluded for 4 d. Skin biopsies were obtained for measurement of transglutaminase-K and transglutaminase-C activity and immunoreactivity. For comparison, cultured normal human keratinocytes were incubated for 4 d in the presence of 1 μM retinoic acid and the subsequent transglutaminase-K activity and immunoreactivity measured. Transglutaminase-K activity was increased 2.8 times in retinoic acid compared to vehicle-treated skin (p < 0.005, n = 12) whereas there was no significant difference in transglutaminase-C activity. However, transglutaminase-K mRNA levels were not significantly different between retinoic acid- and vehicle-treated skin. In vehicle-treated skin, transglutaminase-K immunoreactivity was limited to a narrow, substratum corneal band, but was considerably expanded in a diffuse suprabasal pattern in retinoic acid-treated epidermis. In contrast, transglutaminase-K immunostaining was decreased and its enzymatic activity reduced sixfold in retinoic acid-treated keratinocytes (p < 0.01, n = 4).These results demonstrate that retinoic acid treatment in vivo, in contrast to in vitro, leads to not only increased transglutaminase-K protein expression but also increased enzymatic activity in the absence of detectable increases in mRNA levels.These data, taken with the previously reported lack of in vivo modulation of the differentiation markers keratins 1 and 10 by retinoic acid, indicate that certain aspects of keratinocyte terminal differentiation that are altered in vitro by retinoic acid do not occur in vivo in human skin

Statistical approach to time-to-impact estimation suitable for real-time near-sensor implementation

We present a method to estimate the time-to-impact (TTI) from a sequence of images. The method is based on detecting and tracking local extremal points. Their endurance within and between pixels is measured, accumulated, and used to achieve the TTI. This method, which improves on an earlier proposal, is entirely different from the ordinary optical flow technique and allows for fast and low-complex processing. The method is inspired by insects, which have some TTI capability without the possibility to compute high-complex optical flow. The method is further suitable for near-sensor image processing architectures. (c) The Authors. Published by SPIE under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI

Parameterisation invariant statistical shape models

In this paper novel theory to automate shape modelling is described. The main idea is to develop a theory that is intrinsically defined for curves as opposed to a finite sample of points along the curves. The major problem here is to define shape variation in a way that is invariant to curve parameterisations. Instead of representing continous curves using landmarks, the problem is treated analytically and numerical approximations are introduced at the latest stage. The problem is solved by calculating the covariance matrix of the shapes using a scalar product that is invariant to global reparameterisations. An algorithm for implementing the ideas is proposed and it is compared to a state of the art algorithm of automatic shape modelling. The problems with stability in former formulations are solved and the resulting models are of higher quality.

Comparison of different augmentation techniques for improved generalization performance for gleason grading

The fact that deep learning based algorithms used for digital pathology tend to overfit to the site of the training data is well-known. Since an algorithm that does not generalize is not very useful, we have in this work studied how different data augmentation techniques can reduce this problem but also how data from different sites can be normalized to each other. For both of these approaches we have used cycle generative adversarial networks (GAN); either to generate more examples to train on or to transform images from one site to another. Furthermore, we have investigated to what extent standard augmentation techniques improve the generalization performance. We performed experiments on four datasets with slides from prostate biopsies, stained with HE, detailed annotated with Gleason grades. We obtained results similar to previous studies, with accuracies of 77% for Gleason grading for images from the same site as the training data and 59% for images from other sites. However, we also found out that the use of traditional augmentation techniques gave better performance compared to when using cycle GANs, either to augment the training data or to normalize the test data

Quadrotor Control on SU(2)× R3with SLAM Integration

We present a trajectory tracking controller for a quadrotor unmanned aerial vehicle (UAV) configured on SU(2) × R3, and relate this result to a family of geometric tracking controllers on SO(3) × R3. The theoretical results are verified in several simulation examples, and the controller is subsequently implemented in practice and integrated with a simultaneous localization and mapping (SLAM) system through an onboard extended Kalman filter (EKF). The proposed con-trol system can be used for inventorying tasks in a supermarket environment without the need for external positioning systems

Efficient real-time radial distortion correction for UAVs

In this paper we present a novel algorithm for onboard radial distortion correction for unmanned aerial vehicles (UAVs) equipped with an inertial measurement unit (IMU), that runs in real-time. This approach makes calibration procedures redundant, thus allowing for exchange of optics extemporaneously. By utilizing the IMU data, the cameras can be aligned with the gravity direction. This allows us to work with fewer degrees of freedom, and opens up for further intrinsic calibration. We propose a fast and robust minimal solver for simultaneously estimating the focal length, radial distortion profile and motion parameters from homographies. The proposed solver is tested on both synthetic and real data, and perform better or on par with state-of-the-art methods relying on pre-calibration procedures. Code available at: https://github.com/marcusvaltonen/HomLib.

Retinoic acid and synthetic analogs differentially activate retinoic acid receptor dependent transcription

SummaryWe have developed an assay where the potency of retinoids in retinoic acid receptor (RAR) mediated transcriptional activation can be rapidly evaluated. In this assay hRAR-[alpha], hRAR-[beta] and hRAR-[gamma] were expressed in CV-1 cells together with a reporter gene containing a retinoic acid responsive element (TRE3-tk-CAT). Concentrations required to obtain half-maximum induction (ED50 of CAT-activity were determined for several retinoids, e.g., all-trans-retinoic acid (RA), 13-cis-retinoic acid (13-cis-RA), arotinoid acid (TTNPB) and m-carboxy-arotinoid acid (m-carboxy-TTNPB, an inactive arotinoid analog). The ED50 values for RA decreased in the order of RAR-[alpha] (24 nM) &gt; RAR-[beta] (4.0 nM) &gt; RAR-[gamma] (1.3 nM), while the ED50 values for TTNPB and 13-cis-RA decreased in the order of RAR-[alpha] (6.5 nM, 190 nM) &gt; RAR-[gamma] (2.3 nM, 140 nM) &gt; RAR-[beta] (0.6 nM, 43 nM), respectively. No significant inductions were obtained when cells were treated with m-carboxy-TTNPB, even at 10 [mu]M concentrations. The fold induction of CAT-activity for all compounds tested decreased in the order of RAR-[alpha] &gt; RAR-[beta] &gt; RAR-[gamma].Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/28304/1/0000058.pd

Trust Your IMU : Consequences of Ignoring the IMU Drift

In this paper, we argue that modern pre-integration methods for inertial measurement units (IMUs) are accurate enough to ignore the drift for short time intervals. This allows us to consider a simplified camera model, which in turn admits further intrinsic calibration. We develop the first-ever solver to jointly solve the relative pose problem with unknown and equal focal length and radial distortion profile while utilizing the IMU data. Furthermore, we show significant speed-up compared to state-of-the-art algorithms, with small or negligible loss in accuracy for partially calibrated setups.The proposed algorithms are tested on both synthetic and real data, where the latter is focused on navigation using unmanned aerial vehicles (UAVs). We evaluate the proposed solvers on different commercially available low-cost UAVs, and demonstrate that the novel assumption on IMU drift is feasible in real-life applications. The extended intrinsic auto-calibration enables us to use distorted input images, making tedious calibration processes obsolete, compared to current state-of-the-art methods. Code available at: https://github.com/marcusvaltonen/DronePoseLib.