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AbstractAlthough the safety performance of guardrail end terminals is tested using crash tests in the U.S., occupant injury risks are evaluated based on the flail-space model. This approach developed in the early 1980s neglects the influence of safety features (e.g. seatbelt, airbags, etc.) installed in late model vehicles. In this study, a vehicle (sedan, 1100 kg), a guardrail end terminal (ET-Plus) and a human body model (Global Human Body Model Consortium, GHBMC) were integrated to simulate car-to-end terminal crashes. Five velocities, two offsets, and two angles were used as pre-impact conditions. In all the 20 simulations, kinematics and kinetic data were recorded in GHBMC and vehicle models to calculate the GHBMC injury probabilities and vehicle-based injury metrics, correspondingly. Pre-impact velocity was observed to have the largest effect on the occupant injury measures. All the body-region and full-body injury risks increased with the increasing velocity. Meanwhile, the angles had a larger effect than offset to the change of full-body injury risk (9.1% vs. 0.3%). All the vehicle-based metrics had good correlations to full-body injury probabilities. Occupant Impact Velocity (OIVx), Acceleration Severity Index (ASI), and Theoretical Head Impact Velocity (THIV) had a good correlation to chest, thigh, upper tibia, and lower tibia injuries. All the other correlations (e.g. brain/head injuries) were not statistically significant. The results pointed out that more vehicle-based metrics (ASI and THIV) could help improve the predictability in terms of occupant injury risks in the tests. Numerical methodology could be used to assess head and brain injury probabilities, which were not predictable by any vehicle-based metrics. [ABSTRACT FROM AUTHOR]

Rotational jumps are crucial techniques in sports competitions. Estimating ground reaction forces (GRFs), a constituting component of jumps, through a biomechanical model-based approach allows for analysis, even in environments where force plates or machine learning training data would be impossible. In this study, rotational jump movements involving twists on land were measured using inertial measurement units (IMUs), and GRFs and body loads were estimated using a 3D forward dynamics model. Our forward dynamics and optimization calculation-based estimation method generated and optimized body movements using cost functions defined by motion measurements and internal body loads. To reduce the influence of dynamic acceleration in the optimization calculation, we estimated the 3D orientation using sensor fusion, comprising acceleration and angular velocity data from IMUs and an extended Kalman filter. As a result, by generating cost function-based movements, we could calculate biomechanically valid GRFs while following the measured movements, even if not all joints were covered by IMUs. The estimation approach we developed in this study allows for measurement condition- or training data-independent 3D motion analysis. [ABSTRACT FROM AUTHOR]

In simple terms, consciousness is constituted by multiple goals for action and the continuous adjudication of such goals to implement action, which is referred to as the maps of meaning (MoM) consciousness theory. The MoM theory triangulates through three parallel corollaries: action (behavior), mechanism (morphology/pathophysiology), and goals (teleology). (1) An organism’s consciousness contains fluid, nested goals. These goals are not intentionality, but intersectionality, via the Darwinian byproduct of embodiment meeting the world, i.e., Darwinian inclusive fitness or randomization and then survival of the fittest. (2) These goals are formed via a gradual descent under inclusive fitness and are the abstraction of a "match" between the evolutionary environment and the organism. (3) Human consciousness implements the brain efficiency hypothesis, genetics, epigenetics, and experience-crystallized efficiencies, not necessitating best or objective but fitness, i.e., perceived efficiency based on one’s adaptive environment. These efficiencies are objectively arbitrary but determine the operation and level of one’s consciousness, termed as extreme thrownness. (4) Since inclusive fitness drives efficiencies in the physiologic mechanism, morphology, and behavior (action) and originates one’s goals, embodiment is necessarily entangled to human consciousness as it is at the intersection of mechanism or action (both necessitating embodiment) occurring in the world that determines fitness. (5) Perception is the operant process of consciousness and is the de facto goal adjudication process of consciousness. Goal operationalization is fundamentally efficiency-based via one’s unique neuronal mapping as a byproduct of genetics, epigenetics, and experience. (6) Perception involves information intake and information discrimination, equally underpinned by efficiencies of inclusive fitness via extreme thrownness. Perception is not a ‘frame rate’ but Bayesian priors of efficiency based on one’s extreme thrownness. (7) Consciousness and human consciousness are modular (i.e., a scalar level of richness, which builds up like building blocks) and dimensionalized (i.e., cognitive abilities become possibilities as the emergent phenomena at various modularities such as the stratified factors in factor analysis). (8) The meta dimensions of human consciousness seemingly include intelligence quotient, personality (five-factor model), richness of perception intake, and richness of perception discrimination, among other potentialities. (9) Future consciousness research should utilize factor analysis to parse modularities and dimensions of human consciousness and animal models. [ABSTRACT FROM AUTHOR]

We report our research progress on interactive evolutionary computation (IEC). Following description of IEC features, we present our research on IEC user modeling, acceleration of IEC search, several IEC frameworks, evolutionary multi-objective optimization with IEC, and IEC for human science. IEC research is categorized into three fields in general; major part of IEC papers is IEC application-oriented research; almost all the others are research that aims to reduce IEC user fatigue; and very little work researches the use of IEC for human science. In particular, IEC is a data analysis and processing method and tool for the discovery of human psychological and physiological knowledge. We include several of our IEC application-oriented research projects in this paper, and focus on two other research directions, i.e., IEC algorithm research to reduce user fatigue, and IEC for human science research. [ABSTRACT FROM AUTHOR]

With advancements in nanotechnology and innovative materials, Graphene Oxide nanoparticles (GONP) have attracted lots of attention among the diverse types of nanomaterials owing to their distinctive physicochemical characteristics. However, the usage at scientific and industrial level has also raised concern to their toxicological interaction with biological system. Understanding these interactions is crucial for developing guidelines and recommendations for applications of GONP in various sectors, like biomedicine and environmental technologies. This review offers crucial insights and an in-depth analysis to the biological processes associated with GONP immunotoxicity with multiple cell lines including human whole blood cultures, dendritic cells, macrophages, and multiple cancer cell lines. The complicated interactions between graphene oxide nanoparticles and the immune system, are highlighted in this work, which reveals a range of immunotoxic consequences like inflammation, immunosuppression, immunostimulation, hypersensitivity, autoimmunity, and cellular malfunction. Moreover, the immunotoxic effects are also highlighted with respect to in vivo models like mice and zebrafish, insighting GO Nanoparticles' cytotoxicity. The study provides invaluable review for researchers, policymakers, and industrialist to understand and exploit the beneficial applications of GONP with a controlled measure to human health and the environment.

Ochratoxin A (OTA) is a common fungal toxin frequently detected in food and human plasma samples. Currently, the physiologically based toxicokinetic (PBTK) model plays an active role in dose translation and can improve and enhance the risk assessment of toxins. In this study, the PBTK model of OTA in rats and humans was established based on knowledge of OTA-specific absorption, distribution, metabolism, and excretion (ADME) in order to better explain the disposition of OTA in humans and the discrepancies with other species. The models were calibrated and optimized using the available kinetic and toxicokinetic (TK) data, and independent test datasets were used for model evaluation. Subsequently, sensitivity analyses and population simulations were performed to characterize the extent to which variations in physiological and specific chemical parameters affected the model output. Finally, the constructed models were used for dose extrapolation of OTA, including the rat-to-human dose adjustment factor (DAF) and the human exposure conversion factor (ECF). The results showed that the unbound fraction (Fup) of OTA in plasma of rat and human was 0.02–0.04% and 0.13–4.21%, respectively. In vitro experiments, the maximum enzyme velocity (Vmax) and Michaelis–Menten constant (Km) of OTA in rat and human liver microsomes were 3.86 and 78.17 μg/g min−1, 0.46 and 4.108 μg/mL, respectively. The predicted results of the model were in good agreement with the observed data, and the models in rats and humans were verified. The PBTK model derived a DAF of 0.1081 between rats and humans, whereas the ECF was 2.03. The established PBTK model can be used to estimate short- or long-term OTA exposure levels in rats and humans, with the capacity for dose translation of OTA to provide the underlying data for risk assessment of OTA.

This paper proposes a method to reduce phantom shell effects that occur during the absorbed power density (APD) derivation using a negative permittivity material (NPM). In this study, APD is examined as a primary parameter to assess the effectiveness of the proposed method, especially following the introduction of APD above 6 GHz, in accordance with 2020 ICNIRP guidelines. As the frequency increases, the impact of the phantom shell can affect APD measurement results. To investigate this, a dipole antenna operating in the $6\sim 10$ GHz frequency range was used as the radiation source. Therefore, this study proposes a method to reduce effects by using NPM. The selection of the NPM is achieved through input impedance calculations method. Simulation results indicate that before applying the proposed method, the APD difference between the presence and absence of the phantom shell ranged from 20.6% at 6 GHz (W/ shell =100, W/o shell =82.9 W/m2) to 69.3% at 10 GHz (W/ shell=52.3, W/o shell=30.9 W/m2). After applying the method, these differences reduced to 6.9% at 6 GHz (proposed method=77.2, W/o shell=82.9 W/m2) and 13.5% at 10 GHz (proposed method=35.1, W/o shell=30.9 W/m2). This study is the first to highlight the impact of phantom shell effects on APD, revealing potential overestimations in the 6-10 GHz range and suggesting that these effects may worsen at higher frequencies. The proposed method effectively addresses these issues within current standards while providing insights for future standards development in higher frequency bands.

In simple terms, consciousness is constituted by multiple goals for action and the continuous adjudication of such goals to implement action, which is referred to as the maps of meaning (MoM) consciousness theory. The MoM theory triangulates through three parallel corollaries: action (behavior), mechanism (morphology/pathophysiology), and goals (teleology). (1) An organism’s consciousness contains fluid, nested goals. These goals are not intentionality, but intersectionality, via the Darwinian byproduct of embodiment meeting the world, i.e., Darwinian inclusive fitness or randomization and then survival of the fittest. (2) These goals are formed via a gradual descent under inclusive fitness and are the abstraction of a “match” between the evolutionary environment and the organism. (3) Human consciousness implements the brain efficiency hypothesis, genetics, epigenetics, and experience-crystallized efficiencies, not necessitating best or objective but fitness, i.e., perceived efficiency based on one’s adaptive environment. These efficiencies are objectively arbitrary but determine the operation and level of one’s consciousness, termed as extreme thrownness. (4) Since inclusive fitness drives efficiencies in the physiologic mechanism, morphology, and behavior (action) and originates one’s goals, embodiment is necessarily entangled to human consciousness as it is at the intersection of mechanism or action (both necessitating embodiment) occurring in the world that determines fitness. (5) Perception is the operant process of consciousness and is the de facto goal adjudication process of consciousness. Goal operationalization is fundamentally efficiency-based via one’s unique neuronal mapping as a byproduct of genetics, epigenetics, and experience. (6) Perception involves information intake and information discrimination, equally underpinned by efficiencies of inclusive fitness via extreme thrownness. Perception is not a ‘frame rate’ but Bayesian priors of efficiency based on one’s extreme thrownness. (7) Consciousness and human consciousness are modular (i.e., a scalar level of richness, which builds up like building blocks) and dimensionalized (i.e., cognitive abilities become possibilities as the emergent phenomena at various modularities such as the stratified factors in factor analysis). (8) The meta dimensions of human consciousness seemingly include intelligence quotient, personality (five-factor model), richness of perception intake, and richness of perception discrimination, among other potentialities. (9) Future consciousness research should utilize factor analysis to parse modularities and dimensions of human consciousness and animal models.

With the rise in the aging population, an increase in the number of semidisabled elderly individuals has been noted, leading to notable challenges in medical and healthcare, exacerbated by a shortage of nursing staff. This study aims to enhance the human feature recognition capabilities of bath scrubbing robots operating in a water fog environment. The investigation focuses on semantic segmentation of human features using deep learning methodologies. Initially, 3D point cloud data of human bodies with varying sizes are gathered through light detection and ranging to establish human models. Subsequently, a hybrid filtering algorithm was employed to address the impact of the water fog environment on the modeling and extraction of human regions. Finally, the network is refined by integrating the spatial feature extraction module and the channel attention module based on PointNet. The results indicate that the algorithm adeptly identifies feature information for 3D human models of diverse body sizes, achieving an overall accuracy of 95.7%. This represents a 4.5% improvement compared with the PointNet network and a 2.5% enhancement over mean intersection over union. In conclusion, this study substantially augments the human feature segmentation capabilities, facilitating effective collaboration with bath scrubbing robots for caregiving tasks, thereby possessing significant engineering application value.

Abstract Background Upper-limb rehabilitation robots provide repetitive reaching movement training to post-stroke patients. Beyond a pre-determined set of movements, a robot-aided training protocol requires optimization to account for the individuals’ unique motor characteristics. Therefore, an objective evaluation method should consider the pre-stroke motor performance of the affected arm to compare one’s performance relative to normalcy. However, no study has attempted to evaluate performance based on an individual’s normal performance. Herein, we present a novel method for evaluating upper limb motor performance after a stroke based on a normal reaching movement model. Methods To represent the normal reaching performance of individuals, we opted for three candidate models: (1) Fitts’ law for the speed-accuracy relationship, (2) the Almanji model for the mouse-pointing task of cerebral palsy, and (3) our proposed model. We first obtained the kinematic data of healthy (n = 12) and post-stroke (n = 7) subjects with a robot to validate the model and evaluation method and conducted a pilot study with a group of post-stroke patients (n = 12) in a clinical setting. Using the models obtained from the reaching performance of the less-affected arm, we predicted the patients’ normal reaching performance to set the standard for evaluating the affected arm. Results We verified that the proposed normal reaching model identifies the reaching of all healthy (n = 12) and less-affected arm (n = 19; 16 of them showed an R 2 > 0.7) but did not identify erroneous reaching of the affected arm. Furthermore, our evaluation method intuitively and visually demonstrated the unique motor characteristics of the affected arms. Conclusions The proposed method can be used to evaluate an individual’s reaching characteristics based on an individuals normal reaching model. It has the potential to provide individualized training by prioritizing a set of reaching movements.

Abstract At the molecular level, the body is composed, on average, of water for 62%, fat for 15%, 17% of protein, and 6% of minerals. In this work, we propose a heuristic methodology using hydration models as a base to realize an automatic and noninvasive procedure to estimate an ad hoc map of the complex dielectric permittivity of a generic human tissue in the frequency range of microwaves based on their solid and water content.

Rotational jumps are crucial techniques in sports competitions. Estimating ground reaction forces (GRFs), a constituting component of jumps, through a biomechanical model-based approach allows for analysis, even in environments where force plates or machine learning training data would be impossible. In this study, rotational jump movements involving twists on land were measured using inertial measurement units (IMUs), and GRFs and body loads were estimated using a 3D forward dynamics model. Our forward dynamics and optimization calculation-based estimation method generated and optimized body movements using cost functions defined by motion measurements and internal body loads. To reduce the influence of dynamic acceleration in the optimization calculation, we estimated the 3D orientation using sensor fusion, comprising acceleration and angular velocity data from IMUs and an extended Kalman filter. As a result, by generating cost function-based movements, we could calculate biomechanically valid GRFs while following the measured movements, even if not all joints were covered by IMUs. The estimation approach we developed in this study allows for measurement condition- or training data-independent 3D motion analysis.

Predicting the ground reaction force (GRF) and ground reaction moment (GRM) with a biomechanical model-based approach has an advantage for biomechanical gait analysis in situations where a statistical model cannot be used due to a lack of training data. However, the current prediction methods using a biomechanical model have some issues for clinical application. The present study developed a new inertial measurement unit (IMU)-based method to predict the GRF, the GRM, and the joint kinematics and kinetics with a 3D biomechanical model and simple system. The present method predicts them using a 3D forward dynamics model that computationally generates human movements that minimize the hybrid cost function defined by physical loads and errors between the motion of the model and that of the participants recorded by six IMUs, which allows the prediction system to use only a relatively small number of IMUs. We investigated the prediction accuracy during walking by comparing the new method with a conventional analysis using a force plate and motion capture system. As a result, we observed strong and excellent correlations between the prediction and measurement of the anterior GRF, vertical GRF, sagittal GRM, hip flexion angle, knee flexion angle, hip flexion torque, and ankle dorsiflexion torque. Considering the accuracy of previous studies and that required for gait analysis, the present method could predict them with practical accuracy due to estimated biomechanically valid motions based on optimization using the hybrid cost function that includes a biomechanical evaluation. Moreover, the prediction system has an advantage for clinical applications because the present method observed practical accuracy that has the potential to be applied to some sports analysis and can analyze 3D motion with a simple system consisting of a small number of hardware components and a software.

Research has demonstrated that Taekwondo training helps to enhance the coordination capabilities in people with developmental coordination disorders. These excellent results depend on many factors, including the behavior of the muscular activation patterns of psychomotor exercises during Taekwondo training. Our basic idea is to study the behavior of the muscular activation pattern of Taekwondo training (performed by athletes) and to apply the adapted behavior of the muscular activation pattern to other subjects with reduced coordination capabilities to enhance them, in line with the sustainable human development goals. This paper presents a preliminary feasibility study and a first step in this direction using a virtual simulation. First, the Taekwondo front-kick exercise was studied and reproduced using a virtual human model in OpenSim. Second, some perturbations were applied to the virtual human model to analyze the behavior of the muscular activation patterns. Third, functional electrical stimulation (FES) patterns were properly simulated to reproduce the same sequence (and value) of signals of muscular activation in another subject. The proposed methodology was conceived on the basis of a simple example of a Taekwondo kick by using a virtual human model, but its general application can fit all kinds of psychomotor exercises. If future works confirm the simulation results presented in this paper with real implementation, the methodology proposed here could be applied every time human capabilities must be increased with or without sports training (e.g., remaining seated on a chair or lying on a bed). [ABSTRACT FROM AUTHOR]

Background: Upper-limb rehabilitation robots provide repetitive reaching movement training to post-stroke patients. Beyond a pre-determined set of movements, a robot-aided training protocol requires optimization to account for the individuals' unique motor characteristics. Therefore, an objective evaluation method should consider the pre-stroke motor performance of the affected arm to compare one's performance relative to normalcy. However, no study has attempted to evaluate performance based on an individual's normal performance. Herein, we present a novel method for evaluating upper limb motor performance after a stroke based on a normal reaching movement model. Methods: To represent the normal reaching performance of individuals, we opted for three candidate models: (1) Fitts' law for the speed-accuracy relationship, (2) the Almanji model for the mouse-pointing task of cerebral palsy, and (3) our proposed model. We first obtained the kinematic data of healthy (n = 12) and post-stroke (n = 7) subjects with a robot to validate the model and evaluation method and conducted a pilot study with a group of post-stroke patients (n = 12) in a clinical setting. Using the models obtained from the reaching performance of the less-affected arm, we predicted the patients' normal reaching performance to set the standard for evaluating the affected arm. Results: We verified that the proposed normal reaching model identifies the reaching of all healthy (n = 12) and less-affected arm (n = 19; 16 of them showed an R2 > 0.7) but did not identify erroneous reaching of the affected arm. Furthermore, our evaluation method intuitively and visually demonstrated the unique motor characteristics of the affected arms. Conclusions: The proposed method can be used to evaluate an individual's reaching characteristics based on an individuals normal reaching model. It has the potential to provide individualized training by prioritizing a set of reaching movements. [ABSTRACT FROM AUTHOR]

At the molecular level, the body is composed, on average, of water for 62%, fat for 15%, 17% of protein, and 6% of minerals. In this work, we propose a heuristic methodology using hydration models as a base to realize an automatic and noninvasive procedure to estimate an ad hoc map of the complex dielectric permittivity of a generic human tissue in the frequency range of microwaves based on their solid and water content. [ABSTRACT FROM AUTHOR]

Sleep apnea (SA) is a very prevalent sleep breathing disorder mainly characterized by intermittent hypoxemia and sleep fragmentation, with ensuing systemic inflammation, oxidative stress, and immune deregulation. These perturbations promote the risk of end-organ morbidity, such that SA patients are at increased risk of cardiovascular, neurocognitive, metabolic and malignant disorders. Investigating the potential mechanisms underlying SA-induced end-organ dysfunction requires the use of comprehensive experimental models at the cell, animal and human levels. This review is primarily focused on the experimental models employed to date in the study of the consequences of SA and tackles 3 different approaches. First, cell culture systems whereby controlled patterns of intermittent hypoxia cycling fast enough to mimic the rates of episodic hypoxemia experienced by patients with SA. Second, animal models consisting of implementing realistic upper airway obstruction patterns, intermittent hypoxia, or sleep fragmentation such as to reproduce the noxious events characterizing SA. Finally, human SA models, which consist either in subjecting healthy volunteers to intermittent hypoxia or sleep fragmentation, or alternatively applying oxygen supplementation or temporary nasal pressure therapy withdrawal to SA patients. The advantages, limitations, and potential improvements of these models along with some of their pertinent findings are reviewed. [ABSTRACT FROM AUTHOR]

In recent years, research on occupant behavior models has been promoted for vehicle motion control that includes occupant comfort as a control target. In previous research, modeling and verification focusing mainly on behavior, such as occupant head motion, has been conducted. But in order to accurately predict occupant comfort with a model, it is necessary to model and verify not only the behavior but also the joint torque required to maintain posture. When the occupants maintain their posture against the inertial force associated with the motion of the vehicle, they utilize the seat reaction force with the joint torque. So, in order to accurately model the joint torque, it is necessary to measure and model the joint torque and the seat reaction force separately. Therefore, in this research, we tried to make a occupants behavior model and parameter identification method that predicts joint torque and seat reaction force separately. We focused on the occupant’s head and torso motion among the whole body, and these are modeled in the form of an inverted double pendulum. And the seatback reaction force is set as an input in order to accurately predict the joint torque exerted by the occupants. Then, by utilizing existing occupant behavior analysis technology and we measured joint torque and seat reaction force in addition to the behavior of seated occupants and identified each parameter of the model. The model is experimentally verified, and as an example of the use of the proposed method, experiments and parameter identification are performed on occupants with different gaze points, and the changes in occupant’s joint torque control when view conditions are different were quantitatively clarified.

Metabolic (dysfunction) associated fatty liver disease (MAFLD) is one of the most prevalent liver diseases and has no approved therapeutics. The high failure rates witnessed in late-phase MAFLD drug trials reflect the complexity of the disease, and how the disease develops and progresses remains to be fully understood. In vitro, human disease models play a pivotal role in mechanistic studies to unravel novel disease drivers and in drug testing studies to evaluate human-specific responses. This review focuses on MAFLD disease modeling using human cell and organoid models. The spectrum of patient-derived primary cells and immortalized cell lines employed to model various liver parenchymal and non-parenchymal cell types essential for MAFLD development and progression is discussed. Diverse forms of cell culture platforms utilized to recapitulate tissue-level pathophysiology in different stages of the disease are also reviewed. [ABSTRACT FROM AUTHOR]

Lifting is a main task for manual material handling (MMH), and it is also associated with lower back pain. There are many studies in the literature on predicting lifting strategies, optimizing lifting motions, and reducing lower back injury risks. This survey focuses on optimization-based biomechanical lifting models for MMH. The models can be classified as two-dimensional and three-dimensional models, as well as skeletal and musculoskeletal models. The optimization formulations for lifting simulations with various cost functions and constraints are reviewed. The corresponding equations of motion and sensitivity analysis are briefly summarized. Different optimization algorithms are utilized to solve the lifting optimization problem, such as sequential quadratic programming, genetic algorithm, and particle swarm optimization. Finally, the applications of the optimization-based lifting models to digital human modeling which refers to modeling and simulation of humans in a virtual environment, back injury prevention, and ergonomic safety design are summarized. [ABSTRACT FROM AUTHOR]

In developed countries, the aging of the population and the associated increase in age-related diseases are causing major unresolved medical, social, and environmental matters. Therefore, research on aging has become one of the most important and urgent issues in life sciences. If the molecular mechanisms of the onset and progression of neurodegenerative diseases are elucidated, we can expect to develop disease-modifying methods to prevent neurodegeneration itself. Since the discovery of induced pluripotent stem cells (iPSCs), there has been an explosion of disease models using disease-specific iPSCs derived from patient-derived somatic cells. By inducing the differentiation of iPSCs into neurons, disease models that reflect the patient-derived pathology can be reproduced in culture dishes, and are playing an active role in elucidating new pathological mechanisms and as a platform for new drug discovery. At the same time, however, we are faced with a new problem: how to recapitulate aging in culture dishes. It has been pointed out that cells differentiated from pluripotent stem cells are juvenile, retain embryonic traits, and may not be fully mature. Therefore, attempts are being made to induce cell maturation, senescence, and stress signals through culture conditions. It has also been reported that direct conversion of fibroblasts into neurons can reproduce human neurons with an aged phenotype. Here, we outline some state-of-the-art insights into models of neuronal aging in vitro. New frontiers in which stem cells and methods for inducing differentiation of tissue regeneration can be applied to aging research are just now approaching, and we need to keep a close eye on them. These models are forefront and intended to advance our knowledge of the molecular mechanisms of aging and contribute to the development of novel therapies for human neurodegenerative diseases associated with aging. [ABSTRACT FROM AUTHOR]

Heart failure (HF) is a common disease that causes significant limitations on the organism's capacity and, in extreme cases, leads to death. Clinically, iron deficiency (ID) plays an essential role in heart failure by deteriorating the patient's condition and is a prognostic marker indicating poor clinical outcomes. Therefore, in HF patients, supplementation of iron is recommended. However, iron treatment may cause adverse effects by increasing iron-related apoptosis and the production of oxygen radicals, which may cause additional heart damage. Furthermore, many knowledge gaps exist regarding the complex interplay between iron deficiency and heart failure. Here, we describe the current, comprehensive knowledge about the role of the proteins involved in iron metabolism. We will focus on the molecular and clinical aspects of iron deficiency in HF. We believe that summarizing the new advances in the translational and clinical research regarding iron deficiency in heart failure should broaden clinicians' awareness of this comorbidity. [ABSTRACT FROM AUTHOR]

As health-care budgets are continuously under increasing demands, Artificial Intelligence resources such as digital heart twins could save millions of dollars by predicting results and preventing unnecessary surgery. Can we start to make digital human body twins to plant and predict health outcomes for a patient? By using a way to design competent simulation models from real objects, digital twins were created through IoT. But the digital twin is a complicated system and a very long-drawn step away from its possibilities. Researchers must design all components of entities or structures. There is a need to collect and merge various types of data. Many engineering researchers and participants aren't sure about which technologies and resources to use. The 3D digital twin model offers a reference guide for digital twin comprehension and implementation. This paper aims to investigate and outline the recent technologies and tools used for digital twin applications from a 3-D digital model perspective, such as references to technologies and tools for future digital twin applications. [ABSTRACT FROM AUTHOR]

In developed countries, the aging of the population and the associated increase in age-related diseases are causing major unresolved medical, social, and environmental matters. Therefore, research on aging has become one of the most important and urgent issues in life sciences. If the molecular mechanisms of the onset and progression of neurodegenerative diseases are elucidated, we can expect to develop disease-modifying methods to prevent neurodegeneration itself. Since the discovery of induced pluripotent stem cells (iPSCs), there has been an explosion of disease models using disease-specific iPSCs derived from patient-derived somatic cells. By inducing the differentiation of iPSCs into neurons, disease models that reflect the patient-derived pathology can be reproduced in culture dishes, and are playing an active role in elucidating new pathological mechanisms and as a platform for new drug discovery. At the same time, however, we are faced with a new problem: how to recapitulate aging in culture dishes. It has been pointed out that cells differentiated from pluripotent stem cells are juvenile, retain embryonic traits, and may not be fully mature. Therefore, attempts are being made to induce cell maturation, senescence, and stress signals through culture conditions. It has also been reported that direct conversion of fibroblasts into neurons can reproduce human neurons with an aged phenotype. Here, we outline some state-of-the-art insights into models of neuronal aging in vitro. New frontiers in which stem cells and methods for inducing differentiation of tissue regeneration can be applied to aging research are just now approaching, and we need to keep a close eye on them. These models are forefront and intended to advance our knowledge of the molecular mechanisms of aging and contribute to the development of novel therapies for human neurodegenerative diseases associated with aging.

Research has demonstrated that Taekwondo training helps to enhance the coordination capabilities in people with developmental coordination disorders. These excellent results depend on many factors, including the behavior of the muscular activation patterns of psychomotor exercises during Taekwondo training. Our basic idea is to study the behavior of the muscular activation pattern of Taekwondo training (performed by athletes) and to apply the adapted behavior of the muscular activation pattern to other subjects with reduced coordination capabilities to enhance them, in line with the sustainable human development goals. This paper presents a preliminary feasibility study and a first step in this direction using a virtual simulation. First, the Taekwondo front-kick exercise was studied and reproduced using a virtual human model in OpenSim. Second, some perturbations were applied to the virtual human model to analyze the behavior of the muscular activation patterns. Third, functional electrical stimulation (FES) patterns were properly simulated to reproduce the same sequence (and value) of signals of muscular activation in another subject. The proposed methodology was conceived on the basis of a simple example of a Taekwondo kick by using a virtual human model, but its general application can fit all kinds of psychomotor exercises. If future works confirm the simulation results presented in this paper with real implementation, the methodology proposed here could be applied every time human capabilities must be increased with or without sports training (e.g., remaining seated on a chair or lying on a bed).

The objective of this systematic review is to investigate the various approaches that have been undertaken in finite element analysis (FEA) of human–seat interactions and synthesize the existing knowledge. With advances in numerical simulation and digital human modeling, FEA has emerged as a powerful tool to study seating comfort and discomfort. FEA employs various biomechanical factors to predict the contact stress and pressure distribution in a particular seat design. Given the complexity of human–seat interaction, several modeling and processing steps are required to conduct realistic FEA. The steps of how to perform an FEA simulation on human–seat interactions, the different models used, the model mesh compositions, and the material properties are discussed and reviewed in this paper. This can be used as a guideline for future studies in the context of FEA of human–seat interactions. [ABSTRACT FROM AUTHOR]

The interactions of medical implants in the human body with electromagnetic fields from newly introduced high-field technologies such as near-field wireless power transfer (WPT) are of great concern. In this study, the effects of implants on the specific absorption rate (SAR) in a head model were computationally evaluated in the immediate vicinity of a WPT system operating at 6.78 MHz with a transferred power of 50 W. The SAR in the head model located 30 mm above the WPT system was evaluated with a skull plate, bone plates (different shapes), miniplate, fixtures, and a deep brain stimulator. The results indicated that even small implants had notable effects on the SAR distribution and corresponding local peak and mass-averaged SAR values. Apart from the size and shape of the implant, the crucial factor influencing the SAR was the implant’s position with respect to the WPT system. Therefore, various position configurations were simulated for the WPT system to determine the worst case scenario for each specific implant. Although the local peak SAR value was increased by a factor of 600 in the worst-case scenario (for the skull plate), the SAR $_{\text{1}g}$ and SAR $_{\text{10}g}$ were only increased by factors of seven and four, respectively. Compliance with international safety limits was studied, followed by computing the maximum allowable transmit power (MATP). It was found that, without the implant, the MATP satisfying SAR $_{\text{1}g}$ was 43 W for the designed WPT system, and was reduced to 6.9 W in the presence of the skull plate. [ABSTRACT FROM AUTHOR]

To achieve simple and accurate modeling of human-like behavior with the aim of realizing a model-based design (MBD) methodology incorporating vehicle occupants, this research applied a simplified two-mass system for the upper body of a vehicle occupant and control laws derived based on natural human characteristics. To express the behavior of a seated occupant in response to lateral inputs, the motion of the upper body with respect to the vehicle and the motion of the head with respect to the upper body are modeled using a two-mass system projected onto a plane that includes the horizontal and vertical vehicle axes. Torques to maintain the posture calculated by the control laws were applied to each joint. This research focused on somatic and vestibular sensations as natural human characteristics. Somatic sensations are a source of information concerning the relative spatial and positional relationships between the body and its supporting surfaces (in this research, a vehicle). Seated occupant behavior to hold the upper body upright in the vehicle was defined as somatic feedback, which calculates torque based on the upper body posture angle. On the other hand, vestibular sensations are a source of information concerning the acceleration applied to the head. The vestibular system contains two types of receptor organs: the semicircular canals and the otoliths. The semicircular canals are the receptor organs for rotational acceleration of the head and are sensitive to rapid head motions. The otoliths are the receptor organs for linear acceleration of the head and are sensitive to slow head motions. In this research, we focused on the otoliths and otolithic feedback was defined as the tilting motion of the head against lateral acceleration, which generates torque based on the head posture angle and the lateral acceleration of the head. Validation experiment was performed on a test bench using a vibration generator and vehicle tests confirmed that the proposed model is capable of generally reproducing occupant behavior in response to lateral acceleration inputs.

Abstract Objectives This clinical randomized study aimed to evaluate the early plaque formation on nonresorbable polytetrafluoroethylene (PTFE) membranes having either a dense (d‐PTFE) or an expanded (e‐PTFE) microstructure and exposed to the oral cavity. Material and Methods Twelve individuals were enrolled in this study. In a split‐mouth design, five test membranes (e‐PTFE) with a dual‐layer configuration and five control membranes (d‐PTFE) were bonded on the buccal surfaces of posterior teeth of each subject. All study subjects refrained from toothbrushing during the study period. Specimens were detached from the teeth at 4 and 24 hr and subjected to viability counting, confocal microscopy, and scanning electron microscopy. Plaque samples were harvested from neighboring teeth at baseline, 4, and 24 hr, as control. Wilcoxon signed rank test was applied. Results No bond failure of the membranes was reported. Between the early and late time points, viable bacterial counts increased on all membranes, with no difference between the test and control. The number of Staphylococcus spp. decreased on the tooth surfaces and increased on both membranes overtime, with a significant difference compared to teeth. The total biomass and average biofilm thickness of live and dead cells were significantly greater at the d‐PTFE barriers after 4 hr. Conclusion This study demonstrated that the e‐PTFE membrane was associated with a lesser degree of biofilm accumulation during the initial exposure compared to the d‐PTFE membrane. The present experimental setup provides a valuable toolbox to study the in vivo behavior of different membranes used in guided bone regeneration (GBR).

With advancements in nanotechnology and innovative materials, Graphene Oxide nanoparticles (GONP) have attracted lots of attention among the diverse types of nanomaterials owing to their distinctive physicochemical characteristics. However, the usage at scientific and industrial level has also raised concern to their toxicological interaction with biological system. Understanding these interactions is crucial for developing guidelines and recommendations for applications of GONP in various sectors, like biomedicine and environmental technologies. This review offers crucial insights and an in-depth analysis to the biological processes associated with GONP immunotoxicity with multiple cell lines including human whole blood cultures, dendritic cells, macrophages, and multiple cancer cell lines. The complicated interactions between graphene oxide nanoparticles and the immune system, are highlighted in this work, which reveals a range of immunotoxic consequences like inflammation, immunosuppression, immunostimulation, hypersensitivity, autoimmunity, and cellular malfunction. Moreover, the immunotoxic effects are also highlighted with respect to in vivo models like mice and zebrafish, insighting GO Nanoparticles' cytotoxicity. The study provides invaluable review for researchers, policymakers, and industrialist to understand and exploit the beneficial applications of GONP with a controlled measure to human health and the environment. [Display omitted] • Graphene oxide possess flexible physiochemical characteristics for biomedical application. • GO and its derivative possess immunotoxic consequences with in vivo models. • Detailed investigation of GO immnotoxicity is defined. • The perilous effects determines biocompatibility of GO for biomedical applications. [ABSTRACT FROM AUTHOR]

Ochratoxin A (OTA) is a common fungal toxin frequently detected in food and human plasma samples. Currently, the physiologically based toxicokinetic (PBTK) model plays an active role in dose translation and can improve and enhance the risk assessment of toxins. In this study, the PBTK model of OTA in rats and humans was established based on knowledge of OTA-specific absorption, distribution, metabolism, and excretion (ADME) in order to better explain the disposition of OTA in humans and the discrepancies with other species. The models were calibrated and optimized using the available kinetic and toxicokinetic (TK) data, and independent test datasets were used for model evaluation. Subsequently, sensitivity analyses and population simulations were performed to characterize the extent to which variations in physiological and specific chemical parameters affected the model output. Finally, the constructed models were used for dose extrapolation of OTA, including the rat-to-human dose adjustment factor (DAF) and the human exposure conversion factor (ECF). The results showed that the unbound fraction (F up) of OTA in plasma of rat and human was 0.02–0.04% and 0.13–4.21%, respectively. In vitro experiments, the maximum enzyme velocity (V max) and Michaelis–Menten constant (K m) of OTA in rat and human liver microsomes were 3.86 and 78.17 μg/g min−1, 0.46 and 4.108 μg/mL, respectively. The predicted results of the model were in good agreement with the observed data, and the models in rats and humans were verified. The PBTK model derived a DAF of 0.1081 between rats and humans, whereas the ECF was 2.03. The established PBTK model can be used to estimate short- or long-term OTA exposure levels in rats and humans, with the capacity for dose translation of OTA to provide the underlying data for risk assessment of OTA. [Display omitted] • The species-specific PBTK models were developed for OTA. • PSA showed that physiological variables have significant effects on TK of OTA in humans. • The PBTK model was used to translate the dose adjustment factor of OTA between rat and human. • The human exposure conversion factor of OTA was estimated by the model. [ABSTRACT FROM AUTHOR]

Tissue engineering has been successful in reproducing human skin equivalents while incorporating new approaches such as three‐dimensional (3D) bioprinting. The latter method offers a plethora of advantages including increased production scale, ability to incorporate multiple cell types and printing on demand. However, the quality of printed skin equivalents compared to those developed manually has never been assessed. To leverage the benefits of this method, it is imperative that 3D‐printed skin should be structurally and functionally similar to real human skin. Here, we developed four bilayered human skin epidermal‐dermal equivalents: non‐printed dermis and epidermis (NN), printed dermis and epidermis (PP), printed epidermis and non‐printed dermis (PN), and non‐printed epidermis and printed dermis (NP). The effects of printing induced shear stress [0.025 kPa (epidermis); 0.049 kPa (dermis)] were characterized both at the cellular and at the tissue level. At cellular level, no statistically significant differences in keratinocyte colony‐forming efficiency (CFE) (p = 0.1641) were observed. In the case of fibroblasts, no significant differences in the cell alignment index (p < 0.1717) and their ability to contract collagen gel (p = 0.851) were detected. At the tissue levels, all the four skin equivalents were characterized using histological and immunohistochemical analysis with no significant differences found in either epidermal basal cell count, thickness of viable epidermis, and relative intensity of filaggrin and claudin‐1. Our results demonstrated that 3D printing can achieve the same high‐quality skin constructs as have been developed traditionally, thus opening new avenues for numerous high‐throughput industrial and clinical applications. [ABSTRACT FROM AUTHOR]

The initial recommendation propranolol usage in managing infantile hemangioma was in 2008 followed by various researches assessing the dosage, efficacy, and other parameters. Itraconazole is a world-wide tolerated antifungal but only a few studies have focused on its assessment in the treatment of infantile hemangiomas (IH). This study aimed to investigate the newly proposed antifungal drug ICZ and characterize different aspects of its usage as an antiangiogenic drug. This was an interventional clinical trial to assess the efficacy of ICZ versus propranolol in the treatment of infantile hemangioma with studying the change in serum angiopoietin 2 (Ang2). A total of 36 pediatric patients were divided into two equal groups: firstly treated with oral itraconazole and secondly treated by oral propranolol. Response to treatment was observed using a modified IH score. In itraconazole-treated infants, good response was observed in 44.4% of the patients. This was slightly higher than the propranolol group which showed 22.2% with good response. We observed a decrease in serum ang2 level after usage of ICZ and propranolol and the change in serum Ang2 level before and after treatment in each group was statistically significant (p <.001). Oral itraconazole can be an equivalent option for oral propranolol while safer and shorter treatment periods. [ABSTRACT FROM AUTHOR]

In this paper we discuss the idea of the aquarium fish genus Xiphophorus as a model organism for the study of cancer. Cutaneous malignant melanoma is a form of carcinoma for which both environmental factors and hereditary predisposition are major causative factors. Fish melanoma models have been used in studies of both spontaneous and induced melanoma formation. Genetic hybrids between platyfish (Xiphophorus maculatus) and swordtails (X. hellerii) have been studied since the 1920s to identify genetic determinants of pigmentation and carcinogenesis. Many Xiphophorus varieties are fertile hybrids, obtained following interspecific hybridization and/or artificial selection. Artificial selection led ornamental varieties to exacerbate colors and contrasts, which affected the level of expression of pigments in pigment cells. In this context and considering the polyphyletic/hybrid origin of many varieties of Xiphophorus, the premises were created to increase the frequency of carcinogenesis or increase the predisposition to cancer in these fish. Under the simultaneous action of genetic improvement of coloration by artificial selection and natural selection caused by mortality/melanoma, a resultant, a trade-off between death and beauty has been created. [ABSTRACT FROM AUTHOR]

To effectively study the skin and its pathology, various platforms have been used to date, with in vitro 3D skin models being considered the future gold standard. These models have generally been engineered from primary cell lines. However, their short life span leading to the use of various donors, imposes issues with genetic variation. Human pluripotent stem cell (hPSC)‐technology holds great prospects as an alternative to the use of primary cell lines to study the pathophysiology of human skin diseases. This is due to their potential to generate an unlimited number of genetically identical skin models that closely mimic the complexity of in vivo human skin. During the past decade, researchers have therefore started to use human embryonic and induced pluripotent stem cells (hESC/iPSC) to derive skin resident‐like cells and components. These have subsequently been used to engineer hPSC‐derived 3D skin models. In this review, we focus on the advantages, recent developments, and future perspectives in using hPSCs as an alternative cell source for modelling human skin diseases in vitro. [ABSTRACT FROM AUTHOR]

Subject of Research.The paper considers a flight control system for the longitudinal movement of an aircraft with a human-pilot in a closed loop. Computer simulation setting of the selected pilot behavioral model is carried out in the compensatory tracking mode. The parameters correspond to the optimal behavior of the pilot providing the best aircraft dynamic characteristics. Method. Padé approximation was used when creating a computer program for calculations. Frequency and optimal methods, and handling qualities scale were used for quality assessment of the control system dynamic properties. Main Results. Numerical values of the pilot behavior model parameters are found on the example of a normal aerodynamic scheme, in which the elevator serves as an element of the tail unit. The numerical values estimation of the pilot model parameters is performed. The simulation results are given.Practical Relevance. The proposed approach to the pilot behavior simulating process during piloting simplifies, accelerates, and reduces the cost of an aircraft test program. Software simulation can be used at the test stage and before tests on flight simulators and will give the possibility to identify unsatisfactory handling characteristics of the aircraft and its control system and quickly correct them.

Sleep apnea (SA) is a very prevalent sleep breathing disorder mainly characterized by intermittent hypoxemia and sleep fragmentation, with ensuing systemic inflammation, oxidative stress, and immune deregulation. These perturbations promote the risk of end-organ morbidity, such that SA patients are at increased risk of cardiovascular, neurocognitive, metabolic and malignant disorders. Investigating the potential mechanisms underlying SA-induced end-organ dysfunction requires the use of comprehensive experimental models at the cell, animal and human levels. This review is primarily focused on the experimental models employed to date in the study of the consequences of SA and tackles 3 different approaches. First, cell culture systems whereby controlled patterns of intermittent hypoxia cycling fast enough to mimic the rates of episodic hypoxemia experienced by patients with SA. Second, animal models consisting of implementing realistic upper airway obstruction patterns, intermittent hypoxia, or sleep fragmentation such as to reproduce the noxious events characterizing SA. Finally, human SA models, which consist either in subjecting healthy volunteers to intermittent hypoxia or sleep fragmentation, or alternatively applying oxygen supplementation or temporary nasal pressure therapy withdrawal to SA patients. The advantages, limitations, and potential improvements of these models along with some of their pertinent findings are reviewed.

Introduction: Idiopathic pulmonary fibrosis (IPF) is a progressive, fatal lung disease with a poor prognosis and increasing incidence. Pirfenidone and nintedanib are the only approved treatments for IPF but have limited efficacy and their mechanisms of action are poorly understood. Here we have examined the effects of pirfenidone and nintedanib in a human model of lung fibrogenesis, and compared these with the putative anti-fibrotic compounds Lipoxin A4 (LXA4), and senicapoc, a KCa3.1 ion channel blocker. Methods: Early fibrosis was induced in cultured human lung parenchyma using TGFβ1 for 7 days, ± pirfenidone, nintedanib, or LXA4. Pro-fibrotic responses were examined by RT-PCR, immunohistochemistry and soluble collagen secretion. Results: Thirty six out of eighty four IPF and fibrosis-associated genes tested were significantly upregulated by TGFβ1 in human lung parenchyma with a ≥0.5 log2FC (n = 32). Nintedanib (n = 13) reduced the mRNA expression of 14 fibrosis-associated genes including MMPs (MMP1,−4,−13,−14), integrin α2, CXCR4 and PDGFB, but upregulated α-smooth muscle actin (αSMA). Pirfenidone only reduced mRNA expression for MMP3 and −13. Senicapoc (n = 11) previously attenuated the expression of 28 fibrosis-associated genes, including αSMA, several growth factors, collagen type III, and αV/β6 integrins. Pirfenidone and nintedanib significantly inhibited TGFβ1-induced fibroblast proliferation within the tissue, but unlike senicapoc, neither pirfenidone nor nintedanib prevented increases in tissue αSMA expression. LXA4 was ineffective. Conclusions: Pirfenidone and nintedanib demonstrate modest anti-fibrotic effects and provide a benchmark for anti-fibrotic activity of new drugs in human lung tissue. Based on these data, we predict that the KCa3.1 blocker senicapoc will show greater benefit than either of these licensed drugs in IPF. [ABSTRACT FROM AUTHOR]

Online retailers are challenged to present their products in an appropriate way to attract customers' attention. To test the impact of product presentation features on customers' visual attention, webcam eye tracking might be an alternative to infrared eye tracking, especially in situations where face-to-face contact is difficult. The aim of this study was to examine whether webcam eye tracking is suitable for investigating the influence of certain exogenous factors on customers' visual attention when visiting online clothing shops. For this purpose, screenshots of two websites of two well-known online clothing retailers were used as stimuli. Linear regression analyses were conducted to determine the influence of the spatial position and the presence of a human model on the percentage of participants visiting a product depiction. The results show that products presented by human models and located in the upper middle area of a website were visited by more participants. From this, we were able to derive recommendations for optimising product presentation in online clothing shops. Our results fit well with those of other studies on visual attention conducted with infrared eye tracking, suggesting that webcam eye tracking could be an alternative to infrared eye tracking, at least for similar research questions. [ABSTRACT FROM AUTHOR]

Shape matching is a fundamental operation in digital geometry processing and computer graphics. Challenges in shape matching include finding correspondences of partial shapes with deformations, as well as topological noise and ambiguities. This paper presents a partial shape correspondence algorithm based on the concept of the functional map. An iterative dense matching algorithm, incorporating sparse and guided dense matching, is proposed along with a new objective function including both descriptor matching error and transformation error. Rank estimation with the rank direction is proposed to achieve more accurate slope approximation of the functional map. The slope is beneficial because it directly influences the matching efficiency. The experimental results obtained using FAUST and SHREC′16 datasets demonstrate the effectiveness of our proposed algorithm for matching the shapes of different human subjects and shapes with large missing parts compared with state-of-the art algorithms. The proposed algorithm provides an average geodesic distance of

Metabolic (dysfunction) associated fatty liver disease (MAFLD) is one of the most prevalent liver diseases and has no approved therapeutics. The high failure rates witnessed in late-phase MAFLD drug trials reflect the complexity of the disease, and how the disease develops and progresses remains to be fully understood. In vitro, human disease models play a pivotal role in mechanistic studies to unravel novel disease drivers and in drug testing studies to evaluate human-specific responses. This review focuses on MAFLD disease modeling using human cell and organoid models. The spectrum of patient-derived primary cells and immortalized cell lines employed to model various liver parenchymal and non-parenchymal cell types essential for MAFLD development and progression is discussed. Diverse forms of cell culture platforms utilized to recapitulate tissue-level pathophysiology in different stages of the disease are also reviewed.

Heart failure (HF) is a common disease that causes significant limitations on the organism’s capacity and, in extreme cases, leads to death. Clinically, iron deficiency (ID) plays an essential role in heart failure by deteriorating the patient’s condition and is a prognostic marker indicating poor clinical outcomes. Therefore, in HF patients, supplementation of iron is recommended. However, iron treatment may cause adverse effects by increasing iron-related apoptosis and the production of oxygen radicals, which may cause additional heart damage. Furthermore, many knowledge gaps exist regarding the complex interplay between iron deficiency and heart failure. Here, we describe the current, comprehensive knowledge about the role of the proteins involved in iron metabolism. We will focus on the molecular and clinical aspects of iron deficiency in HF. We believe that summarizing the new advances in the translational and clinical research regarding iron deficiency in heart failure should broaden clinicians’ awareness of this comorbidity.

The CD4+ and CD8+ T cell immune response against T. cruzi, the parasite causing Chagas disease, are relevant for both parasite control and disease pathogenesis. Several studies have been focused on their phenotype and functionally, but only a few have drilled down to identify the parasite proteins that are processed and presented to these cells, especially to CD4+ T lymphocytes. Although approximately 10,000 proteins are encoded per haploid T. cruzi genome, fewer than 200 T cell epitopes from 49 T. cruzi proteins have been identified so far. In this context, a detailed knowledge of the specific targets of T cell memory response emerges as a prime tool for the conceptualization and development of prophylactic or therapeutic vaccines, an approach with great potential to prevent and treat this chronic disease. Here, we review the available information about this topic in a comprehensive manner and discuss the future challenges in the field.

The CD4+ and CD8+ T cell immune response against T. cruzi , the parasite causing Chagas disease, are relevant for both parasite control and disease pathogenesis. Several studies have been focused on their phenotype and functionally, but only a few have drilled down to identify the parasite proteins that are processed and presented to these cells, especially to CD4+ T lymphocytes. Although approximately 10,000 proteins are encoded per haploid T. cruzi genome, fewer than 200 T cell epitopes from 49 T. cruzi proteins have been identified so far. In this context, a detailed knowledge of the specific targets of T cell memory response emerges as a prime tool for the conceptualization and development of prophylactic or therapeutic vaccines, an approach with great potential to prevent and treat this chronic disease. Here, we review the available information about this topic in a comprehensive manner and discuss the future challenges in the field. [ABSTRACT FROM AUTHOR]