Re: Controversies in Odontogenic Tumours Review

Letter to the Edito

Molecular and neuronal correlates of social fear in mice

Fear is a basic adaptive emotional response to threatening environmental stimuli. From an evolutionary standpoint, presence and efficient functionality of the neural substrates of fear are imperative for an organism survival. Human anxiety disorders are caused by the impaired functionality of systems within the brain that code for and regulate our responses to fearful and anxiogenic stimuli. Anxiety and fear-based psychopathologies include social anxiety disorder (SAD), generalized anxiety disorder, panic disorders, obsessive-compulsive disorders. SAD is characterized by excessive fear and avoidance of social situations and severely deteriorates the quality of life of the afflicted individual. Treatment for SAD is majorly phenomenological which is mostly caused by the sparse understanding of the neural and molecular underpinnings of this disorder. Another problem is that although these psychopathologies are twice as prevalent in women in comparison to men, most of the current research uses males as primary subjects. To reveal the molecular and neuronal underpinnings of SAD, we have established a model of social fear using a social fear conditioning (SFC) paradigm in male mice which resembles SAD in humans. Using this model we were able to show that local infusion of neuropeptide oxytocin (OXT) which is known for its prosocial and anxiolytic properties into the lateral septum (LS) reverses social fear in male mice. Social fear conditioned (SFC+) mice showed an increase in OXT receptor (OXTR) binding in the LS which normalized after social fear extinction, while local OXT release in response to social stimuli was found to be blunted in LS of SFC+ mice. In lieu of these findings, and to address the abovementioned concerns, I used the SFC paradigm to: (1) Reveal the role of endogenous OXT system in the regulation of social fear in female mice, and (2) assess the contribution of epigenetic mechanisms in the regulation of social fear memory in male mice. In order to study the endogenous OXT system in females, I chose the state of lactating mice which have an activated brain OXT system as a model. SFC+ lactating mice did not show any SFC-induced fear in comparison to virgin females. This lack of SFC-induced social fear could be reinstated by intracerebroventricular (icv) infusion of OXTR antagonist (OXTR-A). Conversely, icv infusion of OXT reversed SFC-induced social fear in virgin females. cFos immunohistochemistry revealed increased activation of the LS in SFC+ virgin mice in comparison to the SFC- controls, and this returned to baseline levels after extinction, whereas LS-activity remained dampened throughout SFC in lactating mice. I also found an increased in the number of OXT-positive fibers within the LS of lactating mice along with increased OXT release in the LS of lactating mice in response to the extinction of social fear. Moreover, calbindin staining of OXTR-Venus mice revealed most of the OXTR-expressing neurons within the LS to be GABAergic interneurons. Corroborating this, local-LS application of the OXTR-A revived, and OXT reversed SFC-induced social fear in lactating and virgin mice respectively implicating LS-OXT system in the reversal of SFC-induced social fear in lactating mice. In line with the pharmacological manipulations, viral activation of the OXTR-positive neurons within the LS facilitated extinction of social fear whereas constitutive genetic knockdown of OXTR in the mouse brain impaired extinction of social fear. Finally, I was also able to show that specific chemogenetic silencing of magnocellular OXTergic SON afferents to the LS completely blocked social contact in lactating mice. In the second half of my project, I focused on delineating the epigenetic mechanisms which could underlie the formation of social fear and social fear extinction memory. cFos immunohistochemistry revealed increased activity within the LS of SFC+ male CD1 mice post-acquisition of social fear which reverted to baseline after extinction while such an effect was absent in the case of cued fear conditioning. Following this, I checked for mRNA levels of class I HDACs and found an increase in Hdac1 in SFC+ mice which again went back to baseline after the extinction of social fear. Pre-extinction pharmacological blockade of HDAC1 within the LS using MS275 led to facilitation of extinction only in the case of social fear. Finally, I performed a microarray to identify the set of genes which are differentially expressed in the LS of SFC+ and SFC- mice. Cross-referencing these genes with the set of putative HDAC1 regulated genes led me to a final set of genes which could underlie the HDAC1-mediated regulation of social fear extinction. Taken together, my data show that molecular mechanisms within the LS are crucial for regulation of traumatic events associated with a social context in male and female mice. In the case of female mice, I was able to convincingly show that endogenous OXT-mediated activation of OXTR-positive GABAergic neurons within the LS is essential for countering SFC-induced social fear. In the case of males, I was able to show that HDAC1 regulates social fear extinction memory formation within the LS. Such molecular and neuronal mechanism probably help define the emotional response of an individual towards socially relevant environmental stimuli and form the neuronal correlates of social fear in mice. Thus, their better understanding might help us develop efficient therapeutic strategies for emotionally crippling psychopathologies such as SAD

Transforming the Knowledge Gap for Local Planning Officials: Impacts of Continuing Education in a Master Citizen Planner Program

In an era of increasing complexity, the majority of local land-use decisions in the United States are made by volunteer citizen planners. Often these elected or appointed volunteers enter their positions with a passion for their communities but without appropriate background training. The Michigan Citizen Planner Program was developed to address this gap. The study described in this article investigated the self-assessed impacts on graduates of basic and advanced training. Findings suggest that training conducted as the result of collaboration by university Extension, other state agencies, and nonprofit groups is essential to realizing the positive community development impacts expected by citizens and local officials

Viewpoint Planning based on Shape Completion for Fruit Mapping and Reconstruction

Robotic systems in agriculture do not only enable increasing automation of farming activities but also represent new challenges for robotics due to the unstructured environment and the non-rigid structures of crops. Especially, active perception for fruit mapping and harvesting is a difficult task since occlusions frequently occur and image segmentation provides only limited accuracy on the actual shape of the fruits. In this paper, we present a viewpoint planning approach that explictly uses the shape prediction from collected data to guide the sensor to view as yet unobserved parts of the fruits. We developed a novel pipeline for continuous interaction between prediction and observation to maximize the information gain about sweet pepper fruits. We adapted two different shape prediction approaches, namely parametric superellipsoid fitting and model based non-rigid latent space registration, and integrated them into our Region of Interest (RoI) viewpoint planner. Additionally, we used a new concept of viewpoint dissimilarity to aid the planner to select good viewpoints and for shortening the planning times. Our simulation experiments with a UR5e arm equipped with a Realsense L515 sensor provide a quantitative demonstration of the efficacy of our iterative shape completion based viewpoint planning. In comparative experiments with a state-of-the-art viewpoint planner, we demonstrate improvement not only in the estimation of the fruit sizes, but also in their reconstruction. Finally, we show the viability of our approach for mapping sweet peppers with a real robotic system in a commercial glasshouse.Comment: Agricultural Automation, Viewpoint Planning, Active Perceptio

A generalized thermodynamical approach to transverse momentum spectra in high energy collision

Analysis of transverse momentum distributions is a useful tool to understand the dynamics of relativistic particles produced in high energy collision. Finding an accurate distribution function to approximate the spectra is a vastly developing area of research in particle physics. In this work, we have provided a detailed theoretical description of the application of the Pearson statistical framework in high energy physics proposed for the first time in Ref [6]. Here, the transverse momentum spectra of pions measured by experiments at RHIC and LHC are also investigated in the framework of relativistic statistical thermodynamics using Pearson distribution

DawnIK: Decentralized Collision-Aware Inverse Kinematics Solver for Heterogeneous Multi-Arm Systems

Although inverse kinematics of serial manipulators is a well studied problem, challenges still exist in finding smooth feasible solutions that are also collision aware. Furthermore, with collaborative and service robots gaining traction, different robotic systems have to work in close proximity. This means that the current inverse kinematics approaches have to not only avoid collisions with themselves but also collisions with other robot arms. Therefore, we present a novel approach to compute inverse kinematics for serial manipulators that take into account different constraints while trying to reach a desired end-effector position and/or orientation that avoids collisions with themselves and other arms. Unlike other constraint based approaches, we neither perform expensive inverse Jacobian computations nor do we require arms with redundant degrees of freedom. Instead, we formulate different constraints as weighted cost functions to be optimized by a non-linear optimization solver. Our approach is superior to the state-of-the-art CollisionIK in terms of collision avoidance in the presence of multiple arms in confined spaces with no detected collisions at all in all the experimental scenarios. When the probability of collision is low, our approach shows better performance at trajectory tracking as well. Additionally, our approach is capable of simultaneous yet decentralized control of multiple arms for trajectory tracking in intersecting workspace without any collisions.Comment: Salih Marangoz and Rohit Menon have equal authorshi

Graph-based View Motion Planning for Fruit Detection

Crop monitoring is crucial for maximizing agricultural productivity and efficiency. However, monitoring large and complex structures such as sweet pepper plants presents significant challenges, especially due to frequent occlusions of the fruits. Traditional next-best view planning can lead to unstructured and inefficient coverage of the crops. To address this, we propose a novel view motion planner that builds a graph network of viable view poses and trajectories between nearby poses, thereby considering robot motion constraints. The planner searches the graphs for view sequences with the highest accumulated information gain, allowing for efficient pepper plant monitoring while minimizing occlusions. The generated view poses aim at both sufficiently covering already detected and discovering new fruits. The graph and the corresponding best view pose sequence are computed with a limited horizon and are adaptively updated in fixed time intervals as the system gathers new information. We demonstrate the effectiveness of our approach through simulated and real-world experiments using a robotic arm equipped with an RGB-D camera and mounted on a trolley. As the experimental results show, our planner produces view pose sequences to systematically cover the crops and leads to increased fruit coverage when given a limited time in comparison to a state-of-the-art single next-best view planner.Comment: 7 pages, 10 figures, accepted at IROS 202

Viewpoint Push Planning for Mapping of Unknown Confined Spaces

Viewpoint planning is an important task in any application where objects or scenes need to be viewed from different angles to achieve sufficient coverage. The mapping of confined spaces such as shelves is an especially challenging task since objects occlude each other and the scene can only be observed from the front, posing limitations on the possible viewpoints. In this paper, we propose a deep reinforcement learning framework that generates promising views aiming at reducing the map entropy. Additionally, the pipeline extends standard viewpoint planning by predicting adequate minimally invasive push actions to uncover occluded objects and increase the visible space. Using a 2.5D occupancy height map as state representation that can be efficiently updated, our system decides whether to plan a new viewpoint or perform a push. To learn feasible pushes, we use a neural network to sample push candidates on the map based on training data provided by human experts. As simulated and real-world experimental results with a robotic arm show, our system is able to significantly increase the mapped space compared to different baselines, while the executed push actions highly benefit the viewpoint planner with only minor changes to the object configuration.Comment: In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 202

Reactive Correction of Object Placement Errors for Robotic Arrangement Tasks

When arranging objects with robotic arms, the quality of the end result strongly depends on the achievable placement accuracy. However, even the most advanced robotic systems are prone to positioning errors that can occur at different steps of the manipulation process. Ignoring such errors can lead to the partial or complete failure of the arrangement. In this paper, we present a novel approach to autonomously detect and correct misplaced objects by pushing them with a robotic arm. We thoroughly tested our approach both in simulation and on real hardware using a Robotiq two-finger gripper mounted on a UR5 robotic arm. In our evaluation, we demonstrate the successful compensation for different errors injected during the manipulation of regular shaped objects. Consequently, we achieve a highly reliable object placement accuracy in the millimeter range

HDAC1-mediated regulation of GABA signaling within the lateral septum facilitates long-lasting social fear extinction in male mice

Social anxiety disorder (SAD) is caused by traumatic social experiences. It is characterized by intense fear and avoidance of social contexts, which can be robustly mimicked by the social fear conditioning (SFC) paradigm. The extinction phase of the SFC paradigm is akin to exposure therapy for SAD and requires learning to disassociate the trauma with the social context. Learning-induced acetylation of histones is critical for extinction memory formation and its endurance. Although class I histone deacetylases (HDACs) regulate the abovementioned learning process, there is a lack of clarity in isoforms and spatial specificity in HDAC function in social learning. Utilizing the SFC paradigm, we functionally characterized the role of HDAC1, specifically in the lateral septum (LS), in regulating the formation of long-term social fear extinction memory. We measured a local increase in activity-inducing HDAC1 phosphorylation at serine residues of social fear-conditioned (SFC+) mice in response to the extinction of social fear. We also found that LS-HDAC1 function negatively correlates with acute social fear extinction learning using pharmacological and viral approaches. Further, inhibition of LS-HDAC1 enhanced the expression of the GABA-A receptor β1 subunit (Gabrb1) in SFC+ mice, and activation of GABA-A receptors facilitated acute extinction learning. Finally, the facilitation of extinction learning by HDAC1 inhibition or GABA-A receptor activation within the LS led to the formation of long-lasting extinction memory, which persisted even 30 days after extinction. Our results show that HDAC1-mediated regulation of GABA signaling in the LS is crucial for the formation of long-lasting social fear extinction memory