High level of polarized engraftment of porcine intrahepatic cholangiocyte organoids in decellularized liver scaffolds.

In Europe alone, each year 5500 people require a life-saving liver transplantation, but 18% die before receiving one due to the shortage of donor organs. Whole organ engineering, utilizing decellularized liver scaffolds repopulated with autologous cells, is an attractive alternative to increase the pool of available organs for transplantation. The development of this technology is hampered by a lack of a suitable large-animal model representative of the human physiology and a reliable and continuous cell source. We have generated porcine intrahepatic cholangiocyte organoids from adult stem cells and demonstrate that these cultures remained stable over multiple passages whilst retaining the ability to differentiate into hepatocyte- and cholangiocyte-like cells. Recellularization onto porcine scaffolds was efficient and the organoids homogeneously differentiated, even showing polarization. Our porcine intrahepatic cholangiocyte system, combined with porcine liver scaffold paves the way for developing whole liver engineering in a relevant large-animal model.

Improving mobility and participation of older people with vertigo, dizziness and balance disorders in primary care using a care pathway: feasibility study and process evaluation.

BACKGROUND: Community-dwelling older people are frequently affected by vertigo, dizziness and balance disorders (VDB). We previously developed a care pathway (CPW) to improve their mobility and participation by offering standardized approaches for general practitioners (GPs) and physical therapists (PTs). We aimed to assess the feasibility of the intervention, its implementation strategy and the study procedures in preparation for the subsequent main trial. METHODS: This 12-week prospective cohort feasibility study was accompanied by a process evaluation designed according to the UK Medical Research Council's Guidance for developing and evaluating complex interventions. Patients with VDB (≥65 years), GPs and PTs in primary care were included. The intervention consisted of a diagnostic screening checklist for GPs and a guide for PTs. The implementation strategy included specific educational trainings and a telephone helpline. Data for mixed-method process evaluation were collected via standardized questionnaires, field notes and qualitative interviews. Quantitative data were analysed using descriptive statistics, qualitative data using content analysis. RESULTS: A total of five GP practices (seven single GPs), 10 PT practices and 22 patients were included in the study. The recruitment of GPs and patients was challenging (response rates: GP practices: 28%, PT practices: 39%). Ninety-one percent of the patients and all health professionals completed the study. The health professionals responded well to the educational trainings; the utilization of the telephone helpline was low (one call each from GPs and PTs). Familiarisation with the routine of application of the intervention and positive attitudes were emphasized as facilitators of the implementation of the intervention, whereas a lack of time was mentioned as a barrier. Despite difficulties in the GPs' adherence to the intervention protocol, the GPs, PTs and patients saw benefit in the intervention. The patients' treatment adherence to physical therapy was good. There were minor issues in data collection, but no unintended consequences. CONCLUSION: Although the process evaluation provided good support for the feasibility of study procedures, the intervention and its implementation strategy, we identified a need for improvement in recruitment of participants, the GP intervention part and the data collection procedures. The findings will inform the main trial to test the interventions effectiveness in a cluster RCT. TRIAL REGISTRATION: Projektdatenbank Versorgungsforschung Deutschland (German registry Health Services Research) VfD_MobilE-PHY_17_003910, date of registration: 30.11.2017; Deutsches Register Klinischer Studien (German Clinical Trials Register) DRKS00022918, date of registration: 03.09.2020 (retrospectively registered).

Cartilage Regeneration in Preannealed Silk Elastin-Like Co-Recombinamers Injectable Hydrogel Embedded with Mature Chondrocytes in an Ex Vivo Culture Platform.

Tissue engineering for cartilage repair requires biomaterials that show rapid gelation and adequate mechanical properties. Although the use of hydrogel is the most promising biomaterial, it often lacks in rigidity and anchorage of cells when they are surrounded by synovial fluid while they are subjected to heavy loads. We developed and produced the Silk Elastin-Like co-Recombinamer (SELR), which contains both the physical interaction from elastin motifs and from silk motifs. In the first part of this work, we set up and optimized a preannealing treatment based on the evolution of silk motifs into ß-sheet structures in order to fulfill the required mechanical properties of hydrogels for cartilage repair. The new preannealed SELRs (pA(EIS)2-(I5R)6) were characterized with the combination of several experimental techniques (CD, TEM, SEM, and rheology) to provide a deep insight into the material features. Finally, the regeneration properties of the pA(EIS)2-(I5R)6 hydrogel embedded with chondrocytes were evaluated. After 4 weeks of culturing in a standardized and representative ex vivo model, the biochemical and histological analysis revealed the production of glycosaminglycans and collagen. Moreover, the immunohistochemistry showed the absence of fibro-cartilage and the presence of hyaline cartilage. Hence, we conclude that the pA(EIS)2-(I5R)6 hydrogel presents improved mechanical properties while conserving the injectability, which leads to successful regeneration of hyaline cartilage in an ex vivo model.

Influence of age and cognitive demand on motor decision making under uncertainty: a study on goal directed reaching movements.

In everyday life, we constantly make decisions about actions to be performed subsequently. Research on motor decision making has provided empirical evidence for an influence of decision uncertainty on movement execution in young adults. Further, decision uncertainty was suggested to be increased in older adults due to limited cognitive resources for the integration of information and the prediction of the decision outcomes. However, the influence of cognitive aging on decision uncertainty during motor decision making and movement execution has not been investigated, yet. Thus, in the current study, we presented young and older adults with a motor decision making task, in which participants had to decide on pointing towards one out of five potential targets under varying cognitive demands. Statistical analyses revealed stronger decreases in correctly deciding upon the pointing target, i.e. task performance, from low to higher cognitive demand in older as compared to young adults. Decision confidence also decreased more strongly in older adults with increasing cognitive demand, however, only when collapsing across correct and incorrect decision trials, but not when considering correct decision trials, only. Further, older adults executed reaching movements with longer reaction times and increased path length, though the latter, again, not when considering correct decision trials, only. Last, reaction time and variability in movement execution were both affected by cognitive demand. The outcomes of this study provide a differentiated picture of the distinct and joint effects of aging and cognitive demand during motor decision making.

Failure of motor function-A Developmental Embodiment Research perspective on the systemic effects of stress.

Humans are capable to skillfully perform a huge variety of complex movements seemingly effortless and to flexibly adjust movement execution to ever-changing environmental conditions, often without apparent differences in the movement outcome. This impressive ability has sparked scientific interest in the mechanisms underlying movement execution for decades. In this perspective article, we argue that investigating the processes and mechanisms leading to failure of motor functions is a fruitful approach to advance the field of human motor neuroscience and beyond. The study of failure of motor function in specific populations (patient groups, skilled experts) has already provided tremendous insight in the systemic characteristics and multi-level functional dependencies of movement execution. However, particularly the transient failure of function in everyday motor actions remains a blind spot. Coming from the perspective of Developmental Embodiment Research, we argue that the integration of a developmental embodiment and lifespan perspective with existing systemic and multi-level methodological approaches of failure of function analyses provides an integrative, interdisciplinary framework, which will allow us to overcome this shortcoming. We further suggest that stress-induced failure of motor function situations might represent a promising starting point for this endeavor. Identifying the involved cross-level functional dependencies of acute and chronic stress on transient and persistent motor functioning would further advance our knowledge on the mechanisms underlying movement execution, and would allow to identify targets for intervention and prevention across the whole spectrum of motor function and failure.

Attention allocation in complementary joint action: How joint goals affect spatial orienting.

When acting jointly, individuals often attend and respond to the same object or spatial location in complementary ways (e.g., when passing a mug, one person grasps its handle with a precision grip; the other receives it with a whole-hand grip). At the same time, the spatial relation between individuals' actions affects attentional orienting: one is slower to attend and respond to locations another person previously acted upon than to alternate locations ("social inhibition of return", social IOR). Achieving joint goals (e.g., passing a mug), however, often requires complementary return responses to a co-actor's previous location. This raises the question of whether attentional orienting, and hence the social IOR, is affected by the (joint) goal our actions are directed at. The present study addresses this question. Participants responded to cued locations on a computer screen, taking turns with a virtual co-actor. They pursued either an individual goal or performed complementary actions with the co-actor, in pursuit of a joint goal. Four experiments showed that the social IOR was significantly modulated when participant and co-actor pursued a joint goal. This suggests that attentional orienting is affected not only by the spatial but also by the social relation between two agents' actions. Our findings thus extend research on interpersonal perception-action effects, showing that the way another agent's perceived action shapes our own depends on whether we share a joint goal with that agent.

Writing while walking: The impact of cognitive-motor multi-tasking on collision avoidance in human locomotion.

BACKGROUND: When moving in public space, individuals are challenged with having to master multiple cognitive and motor demands, either simultaneously or in short succession. Empirical evidence suggests that cognitive-motor multi-tasking during walking may impact one or both, cognitive and motor performance. These performance changes may result from unintentional task-interference effects, but also from strategic behavioral changes to cope with the multiple task demands. Strategic changes in human walking behavior have been uncovered in experimental scenarios, in which individuals avoid colliding with other individuals or objects in the environment. However, whether collision avoidance behavior is sensitive to cognitive-motor multi-task demands has remained underexplored, yet. Thus, with this study, we aimed at systematically studying cognitive-motor multi-task effects on collision avoidance during human locomotion. METHODS: Ten healthy participants (23.9 ± 4.3 years, 4 female) were walking at their preferred speed from a predefined start to end position under four experimental conditions: walking only (BL), walking while having to avoid a collision with another person (IO), writing a text message on a mobile phone while walking (cognitive-motor dual-task, DT), and writing while walking with collision avoidance demand (multi-task, MT). Parameters quantifying locomotor as well as collision avoidance behavior (path length, walking speed, minimum distance, path and speed adjustment) were assessed using optical motion tracking. In addition, performance in the writing task (errors, writing speed) was examined. RESULTS: Participants' locomotor behavior was significantly affected by experimental conditions, with additive effects of multi-task demands on both path length (BL = DT < IO < MT) and walking speed (BL > IO > DT > MT). Further, participants showed an increased error rate and writing speed in the writing task when walking as compared to when standing still, independent of the presence of an interferer. Importantly, collision avoidance behavior was selectively influenced by cognitive-motor multi-task demands, with an increased minimum distance to the other person in the MT-condition, but no differences in path or speed adjustment. DISCUSSION: Our results suggest significant multi-tasking effects of writing a message on the mobile phone while walking on both locomotor behavior and writing task performance. Collision avoidance behavior seems to be selectively affected by multi-task demands, reflected in an increased minimum passing distance, without overt changes in path or speed adjustments. This may be indicative for a strategic change in collision avoidance behavior towards a more cautious strategy to account for altered attention allocation and less visual feedback when writing while walking.

A statistical machine learning approach linking molecular conformational changes to altered mechanical characteristics of skin due to thermal injury.

This article develops statistical machine learning models to predict the mechanical properties of skin tissue subjected to thermal injury based on the Raman spectra associated with conformational changes of the molecules in the burned tissue. Ex vivo porcine skin tissue samples were exposed to controlled burn conditions at 200 °F for five different durations: (i) 10s, (ii) 20s, (iii) 30s, (iv) 40s, and (v) 50s. For each burn condition, Raman spectra of wavenumbers 500-2000 cm-1 were measured from the tissue samples, and tensile testing on the same samples yielded their material properties, including, ultimate tensile strain, ultimate tensile stress, and toughness. Partial least squares regression models were established such that the Raman spectra, describing conformational changes in the tissue, could accurately predict ultimate tensile stress, toughness, and ultimate tensile strain of the burned skin tissues with R2 values of 0.8, 0.8, and 0.7, respectively, using leave-two-out cross validation scheme. An independent assessment of the resultant models showed that amino acids, proteins & lipids, and amide III components of skin tissue significantly influence the prediction of the properties of the burned skin tissue. In contrast, amide I has a lesser but still noticeable effect. These results are consistent with similar observations found in the literature on the mechanical characterization of burned skin tissue.

Predicting Problematic Behavior in Autism Spectrum Disorder Using Medical History and Environmental Data.

Autism spectrum disorder (ASD), characterized by social, communication, and behavioral abnormalities, affects 1 in 36 children according to the CDC. Several co-occurring conditions are often associated with ASD, including sleep and immune disorders and gastrointestinal (GI) problems. ASD is also associated with sensory sensitivities. Some individuals with ASD exhibit episodes of challenging behaviors that can endanger themselves or others, including aggression and self-injurious behavior (SIB). In this work, we explored the use of artificial intelligence models to predict behavior episodes based on past data of co-occurring conditions and environmental factors for 80 individuals in a residential setting. We found that our models predict occurrences of behavior and non-behavior with accuracies as high as 90% for some individuals, and that environmental, as well as gastrointestinal, factors are notable predictors across the population examined. While more work is needed to examine the underlying connections between the factors and the behaviors, having reasonably accurate predictions for behaviors has the potential to improve the quality of life of some individuals with ASD.

Normothermic Ex Vivo Liver Platform Using Porcine Slaughterhouse Livers for Disease Modeling.

Metabolic and toxic liver disorders, such as fatty liver disease (steatosis) and drug-induced liver injury, are highly prevalent and potentially life-threatening. To allow for the study of these disorders from the early stages onward, without using experimental animals, we collected porcine livers in a slaughterhouse and perfused these livers normothermically. With our simplified protocol, the perfused slaughterhouse livers remained viable and functional over five hours of perfusion, as shown by hemodynamics, bile production, indocyanine green clearance, ammonia metabolism, gene expression and histology. As a proof-of-concept to study liver disorders, we show that an infusion of free fatty acids and acetaminophen results in early biochemical signs of liver damage, including reduced functionality. In conclusion, the present platform offers an accessible system to perform research in a functional, relevant large animal model while avoiding using experimental animals. With further improvements to the model, prolonged exposure could make this model a versatile tool for studying liver diseases and potential treatments.

A Developmental Framework for Embodiment Research: The Next Step Toward Integrating Concepts and Methods.

Embodiment research is at a turning point. There is an increasing amount of data and studies investigating embodiment phenomena and their role in mental processing and functions from across a wide range of disciplines and theoretical schools within the life sciences. However, the integration of behavioral data with data from different biological levels is challenging for the involved research fields such as movement psychology, social and developmental neuroscience, computational psychosomatics, social and behavioral epigenetics, human-centered robotics, and many more. This highlights the need for an interdisciplinary framework of embodiment research. In addition, there is a growing need for a cross-disciplinary consensus on level-specific criteria of embodiment. We propose that a developmental perspective on embodiment is able to provide a framework for overcoming such pressing issues, providing analytical tools to link timescales and levels of embodiment specific to the function under study, uncovering the underlying developmental processes, clarifying level-specific embodiment criteria, and providing a matrix and platform to bridge disciplinary boundaries among the involved research fields.

Optimized collusion prevention for online exams during social distancing.

Online education is important in the COVID-19 pandemic, but online exam at individual homes invites students to cheat in various ways, especially collusion. While physical proctoring is impossible during social distancing, online proctoring is costly, compromises privacy, and can lead to prevailing collusion. Here we develop an optimization-based anti-collusion approach for distanced online testing (DOT) by minimizing the collusion gain, which can be coupled with other techniques for cheating prevention. With prior knowledge of student competences, our DOT technology optimizes sequences of questions and assigns them to students in synchronized time slots, reducing the collusion gain by 2-3 orders of magnitude relative to the conventional exam in which students receive their common questions simultaneously. Our DOT theory allows control of the collusion gain to a sufficiently low level. Our recent final exam in the DOT format has been successful, as evidenced by statistical tests and a post-exam survey.

TLR2-activated human langerhans cells promote Th17 polarization via IL-1beta, TGF-beta and IL-23.

The cytokines IL-6, IL-1beta, TGF-beta, and IL-23 are considered to promote Th17 commitment. Langerhans cells (LC) represent DC in the outer skin layers of the epidermis, an environment extensively exposed to pathogenic attack. The question whether organ-resident DC like LC can evoke Th17 immune response is still open. Our results show that upon stimulation by bacterial agonists, epidermal LC and LC-like cells TLR2-dependently acquire the capacity to polarize Th17 cells. In Th17 cells, expression of retinoid orphan receptor gammabeta was detected. To clarify if IL-17(+)cells could arise per se by stimulated LC we did not repress Th1/Th2 driving pathways by antibodies inhibiting differentiation. In CD1c(+)/langerin(+) monocyte-derived LC-like cells (MoLC), macrophage-activating lipopeptide 2, and peptidoglycan (PGN) induced the release of the cytokines IL-6, IL-1beta, and IL-23. TGF-beta, a cytokine required for LC differentiation and survival, was found to be secreted constitutively. Anti-TLR2 inhibited secretion of IL-6, IL-1beta, and IL-23 by MoLC, while TGF-beta was unaffected. The amount of IL-17 and the ratio of IL-17 to IFN-gamma expression was higher in MoLC- than in monocyte-derived DC-cocultured Th cells. Anti-IL-1beta, -TGF-beta and -IL-23 decreased the induction of Th17 cells. Interestingly, blockage of TLR2 on PGN-stimulated MoLC prevented polarization of Th cells into Th17 cells. Thus, our findings indicate a role of TLR2 in eliciting Th17 immune responses in inflamed skin.

Biomimetic Cell-Laden MeHA Hydrogels for the Regeneration of Cartilage Tissue.

Methacrylated hyaluronic acid (MeHA) and chondroitin sulfate (CS)-biofunctionalized MeHA (CS-MeHA), were crosslinked in the presence of a matrix metalloproteinase 7 (MMP7)-sensitive peptide. The synthesized hydrogels were embedded with either human mesenchymal stem cells (hMSCs) or chondrocytes, at low concentrations, and subsequently cultured in a stem cell medium (SCM) or chondrogenic induction medium (CiM). The pivotal role of the synthesized hydrogels in promoting the expression of cartilage-related genes and the formation of neocartilage tissue despite the low concentration of encapsulated cells was assessed. It was found that hMSC-laden MeHA hydrogels cultured in an expansion medium exhibited a significant increase in the expression of chondrogenic markers compared to hMSCs cultured on a tissue culture polystyrene plate (TCPS). This favorable outcome was further enhanced for hMSC-laden CS-MeHA hydrogels, indicating the positive effect of the glycosaminoglycan binding peptide on the differentiation of hMSCs towards a chondrogenic phenotype. However, it was shown that an induction medium is necessary to achieve full span chondrogenesis. Finally, the histological analysis of chondrocyte-laden MeHA hydrogels cultured on an ex vivo osteochondral platform revealed the deposition of glycosaminoglycans (GAGs) and the arrangement of chondrocyte clusters in isogenous groups, which is characteristic of hyaline cartilage morphology.

Deep adaptive registration of multi-modal prostate images.

Artificial intelligence, especially the deep learning paradigm, has posed a considerable impact on cancer imaging and interpretation. For instance, fusing transrectal ultrasound (TRUS) and magnetic resonance (MR) images to guide prostate cancer biopsy can significantly improve the diagnosis. However, multi-modal image registration is still challenging, even with the latest deep learning technology, as it requires large amounts of labeled transformations for network training. This paper aims to address this problem from two angles: (i) a new method of generating large amount of transformations following a targeted distribution to improve the network training and (ii) a coarse-to-fine multi-stage method to gradually map the distribution from source to target. We evaluate both innovations based on a multi-modal prostate image registration task, where a T2-weighted MR volume and a reconstructed 3D ultrasound volume are to be aligned. Our results demonstrate that the use of data generation can significantly reduce the registration error by up to 62%. Moreover, the multi-stage coarse-to-fine registration technique results in a mean surface registration error (SRE) of 3.66 mm (with the initial mean SRE of 9.42 mm), which is found to be significantly better than the one-step registration with a mean SRE of 4.08 mm.

Cellulose Nanofibril Hydrogel Promotes Hepatic Differentiation of Human Liver Organoids.

To replicate functional liver tissue in vitro for drug testing or transplantation, 3D tissue engineering requires representative cell models as well as scaffolds that not only promote tissue production but also are applicable in a clinical setting. Recently, adult liver-derived liver organoids are found to be of much interest due to their genetic stability, expansion potential, and ability to differentiate toward a hepatocyte-like fate. The current standard for culturing these organoids is a basement membrane hydrogel like Matrigel (MG), which is derived from murine tumor material and apart from its variability and high costs, possesses an undefined composition and is therefore not clinically applicable. Here, a cellulose nanofibril (CNF) hydrogel is investigated with regard to its potential to serve as an alternative clinical grade scaffold to differentiate liver organoids. The results show that its mechanical properties are suitable for differentiation with overall, either equal or improved, functionality of the hepatocyte-like cells compared to MG. Therefore, and because of its defined and tunable chemical definition, the CNF hydrogel presents a viable alternative to MG for liver tissue engineering with the option for clinical use.

Target Uncertainty During Motor Decision-Making: The Time Course of Movement Variability Reveals the Effect of Different Sources of Uncertainty on the Control of Reaching Movements.

The processes underlying motor decision-making have recently caught considerable amount of scientific attention, focusing on the integration of empirical evidence from sensorimotor control research with psychological theories and computational models on decision-making. Empirical studies on motor decision-making suggest that the kinematics of goal-directed reaching movements are sensitive to the level of target uncertainty during movement planning. However, the source of uncertainty as a relevant factor influencing the process of motor decision-making has not been sufficiently considered, yet. In this study, we test the assumption that the source of target uncertainty has an effect on motor decision-making, which can be proven by analyzing movement variability during the time course of movement execution. Ten healthy young adults performed three blocks with 66 trials of goal-directed reaching movements in each block, across which the source and level of reach target uncertainty at movement onset were manipulated ("no uncertainty", "extrinsic uncertainty", and "intrinsic uncertainty"). Fingertip position of the right index finger was recorded using an optical motion tracking system. Standard kinematic measures (i.e., path length and movement duration) as well as variability of fingertip position across the time course of movement execution and at movement end were analyzed. In line with previous studies, we found that a high level of extrinsic target uncertainty leads to increased overall movement duration, which could be attributed to increased path length in this condition, as compared to intrinsic and no target uncertainty (all p < 0.001). Movement duration and path length did not show any differences between the latter two conditions. However, the time course analysis of movement variability revealed significant differences between these two conditions, with increased variability of fingertip position in the presence of intrinsic target uncertainty (Condition × Sampling point: p = 0.01), though considerably less than under high extrinsic target uncertainty (p ≤ 0.001). These findings suggest that both the level and source of uncertainty have a significant effect on the processing of potential action plans during motor decision-making, which can be revealed through the analysis of the time course of movement variability at the end-effector level.

Corrigendum: Target Uncertainty During Motor Decision-Making: The Time Course of Movement Variability Reveals the Effect of Different Sources of Uncertainty on the Control of Reaching Movements.

[This corrects the article DOI: 10.3389/fpsyg.2019.00041.].

Single-ended prediction of listening effort using deep neural networks.

The effort required to listen to and understand noisy speech is an important factor in the evaluation of noise reduction schemes. This paper introduces a model for Listening Effort prediction from Acoustic Parameters (LEAP). The model is based on methods from automatic speech recognition, specifically on performance measures that quantify the degradation of phoneme posteriorgrams produced by a deep neural net: Noise or artifacts introduced by speech enhancement often result in a temporal smearing of phoneme representations, which is measured by comparison of phoneme vectors. This procedure does not require a priori knowledge about the processed speech, and is therefore single-ended. The proposed model was evaluated using three datasets of noisy speech signals with listening effort ratings obtained from normal hearing and hearing impaired subjects. The prediction quality was compared to several baseline models such as the ITU-T standard P.563 for single-ended speech quality assessment, the American National Standard ANIQUE+ for single-ended speech quality assessment, and a single-ended SNR estimator. In all three datasets, the proposed new model achieved clearly better prediction accuracies than the baseline models; correlations with subjective ratings were above 0.9. So far, the model is trained on the specific noise types used in the evaluation. Future work will be concerned with overcoming this limitation by training the model on a variety of different noise types in a multi-condition way in order to make it generalize to unknown noise types.