Adaptive Manipulation Research Articles

Reactive Scheduling Based on Adaptive Manipulator Operations in a Job Shop Configuration with Two Machines

Manufacturing systems are affected by uncertainties, such as machine failure or tool breakage, which result in system downtime and productivity deterioration. In machining processes, system downtime must be reduces. This study aims to establish an automated scheduling technique that flexibly responds to unforeseen events, such as machine failure, based on adaptive operations of the handling manipulator instead of an operation schedule for the machine tools. We propose an “adaptive manipulation” procedure for establishing a reactive revision policy. The reactive revision policy modifies a portion of the manipulator operation sequence, followed by the machine operation sequence. We conduct a physical scheduling simulation on a material-handling manipulator system imitating a job-shop manufacturing system. Through simulations involving machine breakdown scenarios, the applicability of the reactive revision policy based on adaptive manipulation is demonstrated.

Special Issue on New Technologies for Robotic Manipulators and Their Industrial Applications

The industrial robot is more precisely an “automatically controlled, reprogrammable, multipurpose manipulator, programmable in three or more axes, which can be either fixed in place or mobile” (ISO 8373:2012). According to the International Federation of Robotics, by 2018, more than 400,000 new units were being installed annually, and the global average robot density in the manufacturing industry was 99 robots per 10,000 employees. More than 30% of all installed robots were in the automotive industry, the biggest customer for robots. Research on measuring and calibrating, modeling, programming and controlling, and integrating systems has been conducted to give robotic manipulators a wider variety of industrial applications. This special issue covers technical and academic efforts related to new technologies that improve the accuracy and facilitate the implementation of robotic manipulators in industrial applications. The first paper, by Ibaraki et al., outlines technical issues and future research directions for the implementation of model-based numerical compensation schemes for industrial robots. The random forest method is used by Kato et al. to construct a calibration model for positioning errors and identify industrial robots’ positioning errors. A procedure for the quasi-static compliance calibration of serial articulated industrial manipulators is proposed by Theissen et al. A review of the kinematic modeling theory and a derived algorithm to identify error sources for a six-axis industrial robot are presented by Alam et al. Nagao et al. derive a forward kinematics model and identify the kinematics parameters for the calibration of a robot-type machine tool. A novel trajectory generation algorithm, including a corner smoothing method for high-speed and high-accuracy machining by industrial robots, is proposed by Tajima et al. Sato et al. study the vibration characteristics of an industrial robot and derive a mathematical model that represents the dynamic behavior of the system. In the context of smart manufacturing, a multilayer quality inspection framework including a measurement instrument and a robot manipulator is introduced by Azamfirei et al. To support mass customization and the development of reconfigurable manufacturing systems, Inoue et al. propose an autonomous mobile robotic manipulator. Yonemoto and Suwa present an adaptive manipulation procedure to establish an automated scheduling technique that flexibly responds to unforeseen events, such as machine failures. Sasatake et al. introduce a learning system that is based on a method for calculating the similarity between tools, and they test it on a robot system for doing housework. Finally, for better knowledge of the key challenges that manufacturers experience in implementing collaborative industrial robots, an industrial survey is conducted by Andersson et al. The editors sincerely appreciate the contributions of all the authors as well as the work of the reviewers. We are confident that this special issue will further encourage research and engineering work to increase our understanding and knowledge of robotic manipulators and their industrial applications.

Evolution of the Electromagnetic Manipulation: From Tunable to Programmable and Intelligent Metasurfaces.

Looking back on the development of metamaterials in the past 20 years, metamaterials have gradually developed from three-dimensional complex electromagnetic structures to a two-dimensional metasurface with a low profile, during which a series of subversive achievements have been produced. The form of electromagnetic manipulation of the metasurface has evolved from passive to active tunable, programmable, and other dynamic and real-time controllable forms. In particular, the proposal of coding and programmable metasurfaces endows metasurfaces with new vitality. By describing metamaterials through binary code, the digital world and the physical world are connected, and the research of metasurfaces also steps into a new era of digitalization. However, the function switch of traditional programmable metamaterials cannot be achieved without human instruction and control. In order to achieve richer and more flexible function regulation and even higher level metasurface design, the intelligence of metamaterials is an important direction in its future development. In this paper, we review the development of tunable, programmable, and intelligent metasurfaces over the past 5 years, focusing on basic concepts, working principles, design methods, manufacturing, and experimental validation. Firstly, several manipulation modes of tunable metasurfaces are discussed; in particular, the metasurfaces based on temperature control, mechanical control, and electrical control are described in detail. It is demonstrated that the amplitude and phase responses can be flexibly manipulated by the tunable metasurfaces. Then, the concept, working principle, and design method of digital coding metasurfaces are briefly introduced. At the same time, we introduce the active programmable metasurfaces from the following aspects, such as structure, coding method, and three-dimensional far-field results, to show the excellent electromagnetic manipulation ability of programmable metasurfaces. Finally, the basic concepts and research status of intelligent metasurfaces are discussed in detail. Different from the previous programmable metamaterials, which must be controlled by human intervention, the new intelligent metamaterials control system will realize autonomous perception, autonomous decision-making, and even adaptive functional manipulation to a certain extent.

GEP-EpiSeeker: a gene expression programming-based method for epistatic interaction detection in genome-wide association studies

BackgroundIdentification of epistatic interactions provides a systematic way for exploring associations among different single nucleotide polymorphism (SNP) and complex diseases. Although considerable progress has been made in epistasis detection, efficiently and accurately identifying epistatic interactions remains a challenge due to the intensive growth of measuring SNP combinations.ResultsIn this work, we formulate the detection of epistatic interactions by a combinational optimization problem, and propose a novel evolutionary-based framework, called GEP-EpiSeeker, to detect epistatic interactions using Gene Expression Programming. In GEP-EpiSeeker, we propose several tailor-made chromosome rules to describe SNP combinations, and incorporate Bayesian network-based fitness evaluation into the evolution of tailor-made chromosomes to find suspected SNP combinations, and adopt the Chi-square test to identify optimal solutions from suspected SNP combinations. Moreover, to improve the convergence and accuracy of the algorithm, we design two genetic operators with multiple and adjacent mutations and an adaptive genetic manipulation method with fuzzy control to efficiently manipulate the evolution of tailor-made chromosomes. We compared GEP-EpiSeeker with state-of-the-art methods including BEAM, BOOST, AntEpiSeeker, MACOED, and EACO in terms of power, recall, precision and F1-score on the GWAS datasets of 12 DME disease models and 10 DNME disease models. Our experimental results show that GEP-EpiSeeker outperforms comparative methods.ConclusionsHere we presented a novel method named GEP-EpiSeeker, based on the Gene Expression Programming algorithm, to identify epistatic interactions in Genome-wide Association Studies. The results indicate that GEP-EpiSeeker could be a promising alternative to the existing methods in epistasis detection and will provide a new way for accurately identifying epistasis.

Toward next-generation learned robot manipulation

The ever-changing nature of human environments presents great challenges to robot manipulation. Objects that robots must manipulate vary in shape, weight, and configuration. Important properties of the robot, such as surface friction and motor torque constants, also vary over time. Before robot manipulators can work gracefully in homes and businesses, they must be adaptive to such variations. This survey summarizes types of variations that robots may encounter in human environments and categorizes, compares, and contrasts the ways in which learning has been applied to manipulation problems through the lens of adaptability. Promising avenues for future research are proposed at the end.

Robotics and Automation in Textile Industry

For Many years, the application of automation has resulted in significant benefits to industrial world. High levels of consistency and precision in work pieces and high levels of repeatability and accuracy in manufacturing equipment have been required. Economic Justification can be shown only for large quantities of production. To achieve this, we need adaptive manipulation systems having some robotics mechanisms. Robotics is no longer a restricted field; it is a universal subject! As a result, the application of robotics in the industrial world as well as the textile industry has resulted in significant benefits. Application of robotics in textile industry is directed at minimizing human efforts in labour-intensive processes. Today automation in textile industry is often to be synonymous with Robotics. Since computer plays a key role in robotics, the word robot has a specific meaning and it has an emphasis in industry specially related to textiles.

Fake face detection via adaptive manipulation traces extraction network

With the proliferation of face image manipulation (FIM) techniques such as Face2Face and Deepfake, more fake face images are spreading over the internet, which brings serious challenges to public confidence. Face image forgery detection has made considerable progresses in exposing specific FIM, but it is still in scarcity of a robust fake face detector to expose face image forgeries under complex scenarios such as with further compression, blurring, scaling, etc. Due to the relatively fixed structure, convolutional neural network (CNN) tends to learn image content representations. However, CNN should learn subtle manipulation traces for image forensics tasks. Thus, we propose an adaptive manipulation traces extraction network (AMTEN), which serves as pre-processing to suppress image content and highlight manipulation traces. AMTEN exploits an adaptive convolution layer to predict manipulation traces in the image, which are reused in subsequent layers to maximize manipulation artifacts by updating weights during the back-propagation pass. A fake face detector, namely AMTENnet, is constructed by integrating AMTEN with CNN. Experimental results prove that the proposed AMTEN achieves desirable pre-processing. When detecting fake face images generated by various FIM techniques, AMTENnet achieves an average accuracy up to 98.52%, which outperforms the state-of-the-art works. When detecting face images with unknown post-processing operations, the detector also achieves an average accuracy of 95.17%.

From Whole Blood to Isolated Pro-Metastasis Immune Cells: An Ex Vivo Approach to Isolate and Manipulate Immune Cells Contributing to Tumor Metastasis.

Immune evasion hallmark has grabbed wide attention in cancer progression on the clinical level. Accordingly, innate and adaptive immune cells isolation and manipulation is essential in order to assess their activity and role in the tumor microenvironment (TME). This could open a gate toward a personalized therapy by a simple aspiration of blood sample from patients. Here, we describe the isolation of peripheral blood mononuclear cells (PBMCs) using Ficoll plus media in order to achieve the highest yield of immune cells that can be further processed and used in isolation of specific immune cells such as macrophages and cytotoxic T cells (CD8+ cells). Among the highly metastatic macrophages are the M2. This protocol describes the optimized techniques to isolate monocytes from whole blood, differentiate them into M2. This is followed by genetic and epigenetic (using synthetic nucleotides of noncoding RNAs) manipulation of these isolated immune cells in a tumor culture media, in addition to measurement of released cytokines using specific ELISA kit. In the last decade, new groups of noncoding RNAs have been emerged which are microRNAs and long noncoding RNAs. First, they were known as "junk DNA" with unknown regulatory functions. Despite the limited knowledge of these molecules, basic expression profiling is proving to be clinically relevant to cancer diagnosis, metastasis, and prognosis. Here, we describe methods used in molecular biology to assess the epigenetic expression of ncRNAs and their impact on other messenger RNA transcripts in M2 macrophages that could serve as future biomarkers in the context of tumor biology and metastasis or could open a gate in the treatment of cancer.

OMNIVIL-An Autonomous Mobile Manipulator for Flexible Production.

Flexible production is a key element in modern industrial manufacturing. Autonomous mobile manipulators can be used to execute various tasks: from logistics, to pick and place, or handling. Therefore, autonomous robotic systems can even increase the flexibility of existing production environments. However, the application of robotic systems is challenging due to their complexity and safety concerns. This paper addresses the design and implementation of the autonomous mobile manipulator OMNIVIL. A holonomic kinematic design provides high maneuverability and the implemented sensor setup with the underlying localization strategies are robust against typical static and dynamic uncertainties in industrial environments. For a safe and efficient human–robot collaboration (HRC), a novel workspace monitoring system (WMS) is developed to detect human co-workers and other objects in the workspace. The multilayer sensor setup and the parallel data analyzing capability provide superior accuracy and reliability. An intuitive zone-based navigation concept is implemented, based on the workspace monitoring system. Preventive behaviors are predefined for a conflict-free interaction with human co-workers. A workspace analyzing tool is implemented for adaptive manipulation, which significantly simplifies the determination of suitable platform positions for a manipulation task.

Adaptive Task-Space Manipulator Control with Parametric Uncertainties in Kinematics and Dynamics

This paper aims to deal with the problem of robot tracking control in the presence of parametric uncertainties in kinematics and dynamics. We propose a simple and effective adaptive control scheme that includes adaptation laws for unknown constant kinematic and dynamic parameters. In addition, instead of convolution-type filtered differentiation, we designed a new observer to estimate velocity in the task space, and the proposed adaptive control requires no acceleration measurement in the joint space. Using the Lyapunov stability and Barbalat’s lemma, we show that by appropriately choosing design parameters, the tracking errors and estimation errors in task space can asymptotically converge to zero. Through numerical simulation on a two-link robot with a fixed camera, we illustrate the design procedures and demonstrate the feasibility of the proposed adaptive control scheme for the trajectory tracking of robot manipulators.

On Minimizing Analog Variation Errors to Resolve the Scalability Issue of ReRAM-Based Crossbar Accelerators

Crossbar accelerators with a resistive random-access memory (ReRAM) are a promising solution for accelerating neural network applications. The advantages of achieving high computation throughput per watt make ReRAM-based crossbar accelerators become a potential solution for accelerating inference operations in the Internet of Things and edge devices. Due to the analog variation errors, the launched ReRAM-based crossbar accelerators can only perform well when each ReRAM cell is used to represent a limited number of data bits. To make such ReRAM-based crossbar accelerators applicable in wide application scenarios, several proposed researches target at binary neural networks and focus on the chip designs in relieving the implementation challenges on computation accuracy for realizing single-bit ReRAM-based crossbar accelerators. Even though several small-sized ReRAM-based crossbar accelerators are announced, the scalability issue hinders ReRAM-based crossbar accelerators from being scaled up. That is, when there are more and more wordline in an ReRAM-based crossbar accelerator, the analog variation error is amplified and thus seriously degrades the computation accuracy. In this work, we propose an adaptive data manipulation strategy to substantially reduce analog variation errors so as to fill up the gap on scaling up the ReRAM-based crossbar accelerators. In particular, a weightrounding design is proposed to manipulate data to minimize overlapping variation so that the number of wordlines can be scaled up. In addition, an input subcycling design is proposed to further trade tolerable errors with neural networks' execution time. Moreover, a bitline redundant design is proposed to trade acceptable space overhead for eliminating the analog variation errors. The emulation experiments show that the proposed adaptive data manipulation strategy can improve the accuracy in running MNIST and CIFAR-10 by 1.3× and 2.6× with nearly no management penalty and hardware cost. The experimental results also show the close-to-ideal-case accuracy by substantially reducing analog variation errors.

Enhanced Attraction of Arthropod Vectors to Infected Vertebrates: A Review of Empirical Evidence

A large diversity of parasites manipulates their hosts in various ways to complete their own life cycle. Enhancing the attractiveness of their host to vectors has been suggested as a strategy al-lowing vector-borne parasites to increase their transmission. Indeed, a higher attraction of he-matophagous, arthropod vectors to infected vertebrates compared to uninfected individuals has been found in many systems (e.g. Trypanosoma-tsetse flies, Leishmania-sand flies, Borrelia-ticks) but was most often verified in the Plasmodium-mosquitoes model. However, a number of studies found no difference in attractiveness, or a higher attractiveness of uninfected hosts. In this review, we present studies reporting a comparison of the attractiveness and/or the biting rate of infected and uninfected vertebrates. We then discuss several biological factors and exper-imental design aspects that can explain discrepancies between studies. Finally, we stress the im-portance of investigating the mechanisms of parasite-induced increased attractiveness of infected hosts to conclude that such observations are cases of adaptive manipulation.

Structural design of a piezoelectric meta-structure with nonlinear electrical Bi-link networks for elastic wave control

This study reports a structural optimization work of a piezoelectric meta-structure with nonlinear electrical switched Bi-link electronic networks for adaptive wave propagation manipulation and vibration control applications. The investigated meta-structure consists in a periodic arrangement of elementary cells shaping the beam substructure, each of these comprising two piezoelectric elements with connected electrical terminals through semi-passive nonlinear electrical interface, which therefore forms the so-called Bi-link electrical connection. In order to optimize the investigated structure for wave propagation control, the effects of adjusting the geometric/material parameters and locations of the two piezoelectric elements in one periodic cell are analyzed and summarized in detail. Four kinds of structural optimization methods including eighteen structural optimization sub-methods for the open circuit condition and the SSDI Bi-link condition are concluded and discussed in this research. Results show that the performance of these new resonant-type band gaps can be manipulated to meet the targeted aim in terms of wave propagation characteristics in different frequency domains by proper tuning of the investigated parameters.

Reintroducing Cuvier’s gazelle. Better than expected from captive-bred founders

The use of captive-bred animals as founder stock for reintroduction is sometimes discouraged due to their low genetic diversity and even accumulation of deleterious alleles. In October 2016, 43 Cuvier’s gazelles (12 males and 31 females), managed under a European Endangered Species Programme (EEP) and housed in captivity, formed the base of a reintroduction project in Tunisia. The project approach used soft-release techniques. Upon arrival, animals were released in acclimatisation pens, so they could adjust to the new conditions gradually before true release. This study reports on the three-year period gazelles were in the acclimatisation pens before release into the wild. To assess the suitability of captive-bred Cuvier’s gazelles as founder stock for reintroduction, the demographic parameters of the reintroduced population were studied for three reproductive seasons in Tunisia (2017–2019). The demographic parameters of the reintroduced population were also compared to those from the source captive population as a control during the first breeding season. If the animals used as founders were unsuited, a decrease in demographic parameters could be expected over time in the reintroduced population, as well as lower demographic variables compared to the source population. Contrary to expectations, during the three-year study period, all demographic variables increased in the population reintroduced in Tunisia, except juvenile mortality, which decreased. Moreover, none of the demographic values of the gazelles in Tunisia were significantly different from the source population. We hypothesize that in the extremely bottlenecked captive Cuvier’s gazelle population used as founder stock, genetic diversity was still high enough to surmount the presumably deleterious effects of inbreeding. This is probably due to very high heritability (h2), a parameter providing information on the quantitative genetic variation associated with multi-locus quantitative traits previously found in this population. Although reintroduction programs have traditionally been undertaken purely as management exercises, ours was designed to meet a research objective as well. We wanted to find out the adaptive variation in sex ratio in offspring of female Cuvier’s gazelles using the size of the enclosure as a proxy reflecting their body condition. As found in captivity using consanguinity level as a proxy of body condition, in the reintroduced population, mothers in large enclosures produced more daughters while those in the small ones produced more sons, which supports adaptive manipulation of the birth sex ratio favoured by natural selection in reintroduced Cuvier’s gazelles.

Tutorial Review of Bio-Inspired Approaches to Robotic Manipulation for Space Debris Salvage.

We present a comprehensive tutorial review that explores the application of bio-inspired approaches to robot control systems for grappling and manipulating a wide range of space debris targets. Current robot manipulator control systems exploit limited techniques which can be supplemented by additional bio-inspired methods to provide a robust suite of robot manipulation technologies. In doing so, we review bio-inspired control methods because this will be the key to enabling such capabilities. In particular, force feedback control may be supplemented with predictive forward models and software emulation of viscoelastic preflexive joint behaviour. This models human manipulation capabilities as implemented by the cerebellum and muscles/joints respectively. In effect, we are proposing a three-level control strategy based on biomimetic forward models for predictive estimation, traditional feedback control and biomimetic muscle-like preflexes. We place emphasis on bio-inspired forward modelling suggesting that all roads lead to this solution for robust and adaptive manipulator control. This promises robust and adaptive manipulation for complex tasks in salvaging space debris.

Near-Infrared Spectroscopy for Monitoring Sternocleidomastoid Muscular Oxygenation during Isometric Flexion for Patients with Mild Nonspecific Neck Pain: A Pilot Study.

Since there is merit in noninvasive monitoring of muscular oxidative metabolism for near-infrared spectroscopy in a wide range of clinical scenarios, the present study attempted to evaluate the clinical usability for featuring the modulatory strategies of sternocleidomastoid muscular oxygenation using near-infrared spectroscopy in mild nonspecific neck pain patients. The muscular oxygenation variables of the dominant or affected sternocleidomastoid muscles of interest were extracted at 25% of the maximum voluntary isometric contraction from ten patients (5 males and 5 females, 23.6 ± 4.2 years) and asymptomatic individuals (6 males and 4 females, 24.0 ± 5.1 years) using near-infrared spectroscopy. Only a shorter half-deoxygenation time of oxygen saturation during a sternocleidomastoid isometric contraction was noted in patients compared to asymptomatic individuals (10.43 ± 1.79 s vs. 13.82 ± 1.42 s, p < 0.001). Even though the lack of statically significant differences in most of the muscular oxygenation variables failed to refine the definite pathogenic mechanisms underlying nonspecific neck pain, the findings of modulatory strategies of faster deoxygenation implied that near-infrared spectroscopy appears to have practical potential to provide relevant physiological information regarding muscular oxidative metabolism and constituted convincing preliminary evidences of the adaptive manipulations rather than pathological responses of oxidative metabolism capacity of sternocleidomastoid muscles in nonspecific neck patients with mild disability.

Electrophoresis-Based Adaptive Manipulation of Nanowires in Fluid Suspension

Automated, highly precise online manipulation of nanoscale and microscale objects is essential to achieve scalable nanomanufacturing. However, nanoparticles and microparticles exhibit as yet unpredictable and, therefore, uncontrolled variations in their structures or compositions that can limit their functions and properties. In this article, we present an electric field-based adaptive manipulation scheme to precisely control the motion of individual nanowires, online estimate their unknown mobilities, and rapidly plan the desired trajectories with the estimated mobilities. The input saturation is considered in the adaptive controller, and the closed-loop system is proved to be asymptotically stable. The proposed motion planners (MPs), ${{\tt Bi}}$ - ${{\tt iSST}}$ s, are built on and extended by the stable sparse rapidly exploring random tree ( ${{\tt SST}}$ )-based kinodynamic motion-planning algorithms. Two sparse trees are maintained to increase the probability of finding a solution. The ${{\tt Bi}}$ - ${{\tt iSST}}$ algorithms use the workspace information, heuristics, and optimization to effectively guide the search process. When compared with the state-of-the-art algorithms, a ${{\tt Bi}}$ - ${{\tt iSST}}$ variant, the ${{\tt opt}}$ - ${{\tt Bi}}$ - ${{\tt iSST}}$ algorithm, quickly updates feasible solutions with the online estimated mobilities of multiple nanowires and converges to a near-optimal, minimum-time solution to increase the efficiency of simultaneous manipulation of the nanowires. Therefore, without complex characterization of each nanowire’s mobility, the nanowires can be steered simultaneously and efficiently to achieve precisely controlled positions without collisions. Simulation and experimental results confirm that the proposed integrated adaptive manipulation scheme precisely, independently, and simultaneously manipulates the motion of multiple nanowires.

Earnings management: a strategic adaptation or deliberate manipulation?

PurposeThis study aims to clarify the relationship between ethical orientation and earnings management perception phenomenon in the organization. It discusses to what extent earnings management is considered as a strategic adaptation or deliberate manipulation in an organization. The study also aims to expand the domain of ethical perspective of earnings management by considering mediating and moderating role of investor sentiment and corporate social responsibility (CSR) as inward pressure and outward commitment surrounding the organization, adopting a combined perspective of strategic management and also accounting discipline than is normally found in the ethics and earnings management literature.Design/methodology/approachThe study opted for literature synthesis to define key concepts surrounding ethics and earnings management perception in the organization. Besides, it attempted to identify influential mediators and moderators in explaining the earnings management phenomenon in the organization. Consequently, the study identified the gaps in current research to draw upon a more holistic conceptual framework. The rationale for the research was justified within the body of research.FindingsThe study suggested research propositions based on the literature synthesis in view of ethics and earnings management perception in the organization. More specifically, it has proposed a conceptual framework, explaining the relationship between ethical orientation and a multi-dimensional view of earnings management perception. It is envisaged that the mediating and moderating role of investor sentiment and CSR incorporated in this conceptual study will improve the predictive value of the proposed framework and offer additional insights about factors that inhibit or advance ethical orientation and earnings management practices in the organization.Research limitations/implicationsThis paper suffers from the obvious limitation of lacking empirical investigation. However, it does provide a theoretical rationale for the argument that alteration of earnings can be controlled if ethical orientation is emphasized in the organization apart from insulating internal and external pressures to manage such phenomenon from happening in the organization. Perhaps, the most important direction for future research is further extension and validation of this framework by performing an empirical investigation to produce newer insights into this phenomenon.Originality/valueThis conceptual study is different from previous studies on the grounds it has considered unexplored issues linking inward pressures and outward commitments in explaining this phenomenon further. To bridge the critical knowledge gap of earnings management phenomenon, a mediating effect of investor sentiment as an inward pressure and a moderating role of CSR as an outward commitment are also integrated within the model. The proposed model neither formulated nor tested empirically in previous studies locally or, perhaps, globally, therefore, stands out as an original contribution in the study of ethical orientation and earnings management perception.

Neuroinflammation-Associated Aspecific Manipulation of Mouse Predator Fear by Toxoplasma gondii

SummaryIn rodents, the decrease of felid aversion induced by Toxoplasma gondii, a phenomenon termed fatal attraction, is interpreted as an adaptive manipulation by the neurotropic protozoan parasite. With the aim of understanding how the parasite induces such specific behavioral modifications, we performed a multiparametric analysis of T. gondii-induced changes on host behavior, physiology, and brain transcriptome as well as parasite cyst load and distribution. Using a set of complementary behavioral tests, we provide strong evidence that T. gondii lowers general anxiety in infected mice, increases explorative behaviors, and surprisingly alters predator aversion without selectivity toward felids. Furthermore, we show a positive correlation between the severity of the behavioral alterations and the cyst load, which indirectly reflects the level of inflammation during brain colonization. Taken together, these findings refute the myth of a selective loss of cat fear in T. gondii-infected mice and point toward widespread immune-related alterations of behaviors.

A molecular war: convergent and ontogenetic evidence for adaptive host manipulation in related parasites infecting divergent hosts.

Mermithids (phylum Nematoda) and hairworms (phylum Nematomorpha) somehow drive their arthropod hosts into water, which is essential for the worms' survival after egression. The mechanisms behind this behavioural change have been investigated in hairworms, but not in mermithids. Establishing a similar mechanistic basis for host behavioural change between these two distantly related parasitic groups would provide strong convergent evidence for adaptive manipulation and insight into how these parasites modify and/or create behaviour. Here, we search for this convergence, and also contrast changes in physiology between hosts infected with immature and mature mermithids to provide the first ontogenetic evidence for adaptive manipulation by disentangling host response and pathology from the parasite's apparent manipulative effects. We used SWATH-mass spectrometry on brains of Forficula auricularia (earwig) and Bellorchestia quoyana (sandhopper), infected with the mermithids Mermis nigrescens and Thaumamermis zealandica, respectively, at both immature and mature stages of infection, to quantify proteomic changes resulting from mermithid infection. Across both hosts (and hairworm-infected hosts, from earlier studies), the general function of dysregulated proteins was conserved. Proteins involved in energy generation/mobilization were dysregulated, corroborating reports of erratic/hyperactive behaviour in infected hosts. Dysregulated proteins involved in axon/dendrite and synapse modulation were also common to all hosts, suggesting neuronal manipulation is involved in inducing positive hydrotaxis. Furthermore, downregulation of CamKII and associated proteins suggest manipulation of memory also contributes to the behavioural shift.