Contributors:Reyna I. Martinez-De Luna, Ray Y. Ku, Alexandria M. Aruck, Francesca Santiago, Andrea S. Viczian, Diego San Mauro, Michael E. Zuber
Intermediate filament proteins are structural components of the cellular cytoskeleton with cell-type specific expression and function. Glial fibrillary acidic protein (GFAP) is a type III intermediate filament protein and is up-regulated in glia of the nervous system in response to injury and during neurodegenerative diseases. In the retina, GFAP levels are dramatically increased in Müller glia and are thought to play a role in the extensive structural changes resulting in Müller cell hypertrophy and glial scar formation. In spite of similar changes to the morphology of Xenopus Müller cells following injury, we found that Xenopus lack a gfap gene. Other type III intermediate filament proteins were, however, significantly induced following rod photoreceptor ablation and retinal ganglion cell axotomy. The recently available X. tropicalis and X. laevis genomes indicate a small deletion most likely resulted in the loss of the gfap gene during anuran evolution. Lastly, a survey of representative species from all three extant amphibian orders including the Anura (frogs, toads), Caudata (salamanders, newts), and Gymnophiona (caecilians) suggests that deletion of the gfap locus occurred in the ancestor of all Anura after its divergence from the Caudata ancestor around 290 million years ago. Our results demonstrate that extensive changes in Müller cell morphology following retinal injury do not require GFAP in Xenopus, and other type III intermediate filament proteins may be involved in the gliotic response.
Contributors:Yi Ding, Gabriele Colozza, Kelvin Zhang, Yuki Moriyama, Diego Ploper, Eric A. Sosa, Maria D.J. Benitez, Edward M. De Robertis
RNA sequencing has allowed high-throughput screening of differential gene expression in many tissues and organisms. Xenopus laevis is a classical embryological and cell-free extract model system, but its genomic sequence had been lacking due to difficulties arising from allotetraploidy. There is currently much excitement surrounding the release of the completed X. laevis genome (version 9.1) by the Joint Genome Institute (JGI), which provides a platform for genome-wide studies. Here we present a deep RNA-seq dataset of transcripts expressed in dorsal and ventral lips of the early Xenopus gastrula embryo using the new genomic information, which was further annotated by blast searches against the human proteome. Overall, our findings confirm previous results from differential screenings using other methods that uncovered classical dorsal genes such as Chordin, Noggin and Cerberus, as well as ventral genes such as Sizzled, Ventx, Wnt8 and Bambi. Complete transcriptome-wide tables of mRNAs suitable for data mining are presented, which include many novel dorsal- and ventral-specific genes. RNA-seq was very quantitative and reproducible, and allowed us to define dorsal and ventral signatures useful for gene set expression analyses (GSEA). As an example of a new gene, we present here data on an organizer-specific secreted protein tyrosine kinase known as Pkdcc (protein kinase domain containing, cytoplasmic) or Vlk (vertebrate lonesome kinase). Overexpression experiments indicate that Pkdcc can act as a negative regulator of Wnt/ β-catenin signaling independently of its kinase activity. We conclude that RNA-Seq in combination with the X. laevis complete genome now available provides a powerful tool for unraveling cell-cell signaling pathways during embryonic induction.
Contributors:Bulbul Chakravarti, Chheten Sherpa, Devasrie Bose, Kakoli Paul Chowdhury, Kavita Khadar, Y. Clare Zhang, Deb N. Chakravarti
Type 1 diabetes (T1D) is a chronic autoimmune disease in which the pancreatic β-cells fail to produce insulin. In addition to such change in the endocrine function, the exocrine function of the pancreas is altered as well. To understand the molecular basis of the changes in both endocrine and exocrine pancreatic functions due to T1D, the proteome profile of the pancreas of control and diabetic mouse was compared using two dimensional gel electrophoresis (2D-GE) and the differentially expressed proteins identified by electrospray ionization liquid chromatography-tandem mass spectrometry (ESI-LC-MS/MS). Among several hundred protein spots analyzed, the expression levels of 27 protein spots were found to be up-regulated while that of 16 protein spots were down-regulated due to T1D. We were able to identify 23 up-regulated and 9 down-regulated protein spots and classified them by bioinformatic analysis into different functional categories: (i) exocrine enzymes (or their precursors) involved in the metabolism of proteins, lipids, and carbohydrates; (ii) chaperone/stress response; and (iii) growth, apoptosis, amino acid metabolism or energy metabolism. Several proteins were found to be present in multiple forms, possibly resulting from proteolysis and/or post-translational modifications. Succinate dehydrogenase [ubiquinone] flavoprotein subunit, which is the major catalytic subunit of succinate dehydrogenase (SDH), was found to be one of the proteins whose expression was increased in T1D mouse pancreata. Since altered expression of a protein can modify its functional activity, we tested and observed that the activity of SDH, a key metabolic enzyme, was increased in the T1D mouse pancreata as well. The potential role of the altered expression of different proteins in T1D associated pathology in mouse is discussed.
Contributors:Karinne Ramirez-Amaro, Michael Beetz, Gordon Cheng
In this study, we present a framework that infers human activities from observations using semantic representations. The proposed framework can be utilized to address the difficult and challenging problem of transferring tasks and skills to humanoid robots. We propose a method that allows robots to obtain and determine a higher-level understanding of a demonstrator's behavior via semantic representations. This abstraction from observations captures the “essence” of the activity, thereby indicating which aspect of the demonstrator's actions should be executed in order to accomplish the required activity. Thus, a meaningful semantic description is obtained in terms of human motions and object properties. In addition, we validated the semantic rules obtained in different conditions, i.e., three different and complex kitchen activities: 1) making a pancake; 2) making a sandwich; and 3) setting the table. We present quantitative and qualitative results, which demonstrate that without any further training, our system can deal with time restrictions, different execution styles of the same task by several participants, and different labeling strategies. This means, the rules obtained from one scenario are still valid even for new situations, which demonstrates that the inferred representations do not depend on the task performed. The results show that our system correctly recognized human behaviors in real-time in around 87.44% of cases, which was even better than a random participant recognizing the behaviors of another human (about 76.68%). In particular, the semantic rules acquired can be used to effectively improve the dynamic growth of the ontology-based knowledge representation. Hence, this method can be used flexibly across different demonstrations and constraints to infer and achieve a similar goal to that observed. Furthermore, the inference capability introduced in this study was integrated into a joint space control loop for a humanoid robot, an iCub, for achieving similar goals to the human demonstrator online.
Contributors:Floris Goerlandt, Jakub Montewka, Weibin Zhang, Pentti Kujala
Winter navigation is a complex but common operation in the Northern Baltic Sea areas. In Finnish waters, the safety of the wintertime maritime transportation system is managed through the Finnish–Swedish winter navigation system. This system results in different operational modes of ship navigation, with vessels either navigating independently or under icebreaker assistance. A recent risk analysis indicates that during icebreaker assistance, convoys operations are among the most hazardous, with convoy collisions the most important risk events. While the accident likelihood per exposure time is rather low, accidents occur almost every winter. Even though these typically lead to less serious consequences, accidents leading to ship loss and oil pollution have occurred and may occur in the future. One aspect of ship convoy navigation in ice conditions is the distance kept between the icebreaker and the ships in the convoy, a form of the well-known ship domain concept. While operational experience naturally is a valuable source of information for decision making about the distance of navigation in convoys, systematic analyses are lacking. The aim of this paper is to investigate selected operational aspects of convoy navigation in ice conditions in the Finnish waters of the Gulf of Finland, based on data of the Automatic Identification System and sea ice hindcast data. Focus is on obtaining qualitative and quantitative knowledge concerning distances between vessels in escort and convoy operations and the respective transit speeds, conditional to ice conditions. Such empirical knowledge can support operational decision making, contributing to wintertime maritime safety.
Contributors:Stein J. Janssen, Teun Teunis, Eva van Dijk, Marco L. Ferrone, John H. Shin, Francis Hornicek, Joseph H. Schwab
General questionnaires are often used to assess quality of life in patients with spine metastases, although a disease-specific survey did not exist until recently. The Spine Oncology Study Group has developed an outcomes questionnaire (SOSG-OQ) to measure quality of life in these patients. However, a scoring system was not developed, and the questionnaire was not validated in a group of patients, nor was it compared with other general quality of life questionnaires such as the EuroQol 5 Dimensions (EQ-5D) questionnaire.
Contributors:Aleksandra Faust, Ivana Palunko, Patricio Cruz, Rafael Fierro, Lydia Tapia
Cargo-bearing unmanned aerial vehicles (UAVs) have tremendous potential to assist humans by delivering food, medicine, and other supplies. For time-critical cargo delivery tasks, UAVs need to be able to quickly navigate their environments and deliver suspended payloads with bounded load displacement. As a constraint balancing task for joint UAV-suspended load system dynamics, this task poses a challenge. This article presents a reinforcement learning approach for aerial cargo delivery tasks in environments with static obstacles. We first learn a minimal residual oscillations task policy in obstacle-free environments using a specifically designed feature vector for value function approximation that allows generalization beyond the training domain. The method works in continuous state and discrete action spaces. Since planning for aerial cargo requires very large action space (over 106 actions) that is impractical for learning, we define formal conditions for a class of robotics problems where learning can occur in a simplified problem space and successfully transfer to a broader problem space. Exploiting these guarantees and relying on the discrete action space, we learn the swing-free policy in a subspace several orders of magnitude smaller, and later develop a method for swing-free trajectory planning along a path. As an extension to tasks in environments with static obstacles where the load displacement needs to be bounded throughout the trajectory, sampling-based motion planning generates collision-free paths. Next, a reinforcement learning agent transforms these paths into trajectories that maintain the bound on the load displacement while following the collision-free path in a timely manner. We verify the approach both in simulation and in experiments on a quadrotor with suspended load and verify the method's safety and feasibility through a demonstration where a quadrotor delivers an open container of liquid to a human subject. The contributions of this work are two-fold. First, this article presents a solution to a challenging, and vital problem of planning a constraint-balancing task for an inherently unstable non-linear system in the presence of obstacles. Second, AI and robotics researchers can both benefit from the provided theoretical guarantees of system stability on a class of constraint-balancing tasks that occur in very large action spaces.
Contributors:D. López-López, R. Gómez-Nieto, M.J. Herrero-Turrión, N. García-Cairasco, D. Sánchez-Benito, M.D. Ludeña, D.E. López
Genetic animal models of epilepsy are an important tool for further understanding the basic cellular mechanisms underlying epileptogenesis and for developing novel antiepileptic drugs. We conducted a comparative study of gene expression in the inferior colliculus, a nucleus that triggers audiogenic seizures, using two animal models, the Wistar audiogenic rat (WAR) and the genetic audiogenic seizure hamster (GASH:Sal). For this purpose, both models were exposed to high intensity auditory stimulation, and 60min later, the inferior colliculi were collected. As controls, intact Wistar rats and Syrian hamsters were subjected to stimulation and tissue preparation protocols identical to those performed on the experimental animals. Ribonucleic acid was isolated, and microarray analysis comparing the stimulated Wistar and WAR rats showed that the genomic profile of these animals displayed significant (fold change, |FC|≥2.0 and p<0.05) upregulation of 38 genes and downregulation of 47 genes. Comparison of gene expression profiles between stimulated control hamsters and stimulated GASH:Sal revealed the upregulation of 10 genes and the downregulation of 5 genes.
Contributors:Charlotte L. Edwardson, Elisabeth A.H. Winkler, Danielle H. Bodicoat, Tom Yates, Melanie J. Davies, David W. Dunstan, Genevieve N. Healy
Research indicates that high levels of sedentary behaviour (sitting or lying with low energy expenditure) are adversely associated with health. A key factor in improving our understanding of the impact of sedentary behaviour (and patterns of sedentary time accumulation) on health is the use of objective measurement tools that collect date and time-stamped activity information. One such tool is the activPAL monitor. This thigh-worn device uses accelerometer-derived information about thigh position to determine the start and end of each period spent sitting/lying, standing and stepping, as well as stepping speed, step counts and postural transitions. The activPAL is increasingly being used within field-based research for its ability to measure sitting/lying via posture. We summarise key issues to consider when using the activPAL in physical activity and sedentary behaviour field-based research with adult populations. It is intended that the findings and discussion points be informative for researchers who are currently using activPAL monitors or are intending to use them. Pre-data collection decisions, monitor preparation and distribution, data collection considerations, and manual and automated data processing possibilities are presented using examples from current literature and experiences from two research groups from the UK and Australia.