Analysis of the therapeutic interaction provided by a humanoid robot serving stroke survivors as a therapeutic assistant for arm rehabilitation

Objective: To characterize a socially active humanoid robot's therapeutic interaction as a therapeutic assistant when providing arm rehabilitation (i.e., arm basis training (ABT) for moderate-to-severe arm paresis or arm ability training (AAT) for mild arm paresis) to stroke survivors when using the digital therapeutic system Evidence-Based Robot-Assistant in Neurorehabilitation (E-BRAiN) and to compare it to human therapists' interaction. Methods: Participants and therapy: Seventeen stroke survivors receiving arm rehabilitation (i.e., ABT [n = 9] or AAT [n = 8]) using E-BRAiN over a course of nine sessions and twenty-one other stroke survivors receiving arm rehabilitation sessions (i.e., ABT [n = 6] or AAT [n = 15]) in a conventional 1:1 therapist-patient setting. Analysis of therapeutic interaction: Therapy sessions were videotaped, and all therapeutic interactions (information provision, feedback, and bond-related interaction) were documented offline both in terms of their frequency of occurrence and time used for the respective type of interaction using the instrument THER-I-ACT. Statistical analyses: The therapeutic interaction of the humanoid robot, supervising staff/therapists, and helpers on day 1 is reported as mean across subjects for each type of therapy (i.e., ABT and AAT) as descriptive statistics. Effects of time (day 1 vs. day 9) on the humanoid robot interaction were analyzed by repeated-measures analysis of variance (rmANOVA) together with the between-subject factor type of therapy (ABT vs. AAT). The between-subject effect of the agent (humanoid robot vs. human therapist; day 1) was analyzed together with the factor therapy (ABT vs. AAT) by ANOVA. Main results and interpretation: The overall pattern of the therapeutic interaction by the humanoid robot was comprehensive and varied considerably with the type of therapy (as clinically indicated and intended), largely comparable to human therapists' interaction, and adapted according to needs for interaction over time. Even substantially long robot-assisted therapy sessions seemed acceptable to stroke survivors and promoted engaged patients' training behavior. Conclusion: Humanoid robot interaction as implemented in the digital system E-BRAiN matches the human therapeutic interaction and its modification across therapies well and promotes engaged training behavior by patients. These characteristics support its clinical use as a therapeutic assistant and, hence, its application to support specific and intensive restorative training for stroke survivors.

Gene-environment interplay in externalizing behavior from childhood through adulthood

BACKGROUND

Genetic and environmental influences on externalizing problems are often studied separately. Here, we extended prior work by investigating the implications of gene-environment interplay in childhood for early adult externalizing behavior. Genetic nurture would be indicated if parents' genetic predisposition for externalizing behavior operates through the family environment in predicting offspring early adult externalizing behavior. Evocative gene-environment correlation would be indicated if offspring genetic predisposition for externalizing behavior operates through child externalizing behavior in affecting the family environment and later early adult externalizing behavior.

METHOD

Longitudinal data from seven waves of the TRacking Adolescents' Individual Lives Survey, a prospective cohort study of Dutch adolescents followed from age 11 to age 29 (n at baseline = 2,734) were used. Child externalizing behavior was assessed using self and parent reports. Family dysfunction was assessed by parents. Early adult externalizing behavior was assessed using self-reports. Genome-wide polygenic scores for externalizing problems were constructed for mothers, fathers, and offspring.

RESULTS

Offspring polygenic score and child behavior each predicted early adult externalizing problems, as did family dysfunction to a small extent. Parents' polygenic scores were not associated with offspring's early adult externalizing behavior. Indirect effect tests indicated that offspring polygenic score was associated with greater family dysfunction via child externalizing behavior (evocative gene-environment correlation) but the effect was just significant and the effect size was very small. Parents' polygenic scores did not predict family dysfunction, thus the data do not provide support for genetic nurture.

CONCLUSIONS

A very small evocative gene-environment correlation was detected but effect sizes were much more pronounced for stability in externalizing behavior from childhood through early adulthood, which highlights the necessity to intervene early to prevent later problems.

SOMSpec as a General Purpose Validated Self-Organising Map Tool for Rapid Protein Secondary Structure Prediction From Infrared Absorbance Data

A protein’s structure is the key to its function. As protein structure can vary with environment, it is important to be able to determine it over a wide range of concentrations, temperatures, formulation vehicles, and states. Robust reproducible validated methods are required for applications including batch-batch comparisons of biopharmaceutical products. Circular dichroism is widely used for this purpose, but an alternative is required for concentrations above 10 mg/mL or for solutions with chiral buffer components that absorb far UV light. Infrared (IR) protein absorbance spectra of the Amide I region (1,600–1700 cm−1) contain information about secondary structure and require higher concentrations than circular dichroism often with complementary spectral windows. In this paper, we consider a number of approaches to extract structural information from a protein infrared spectrum and determine their reliability for regulatory and research purpose. In particular, we compare direct and second derivative band-fitting with a self-organising map (SOM) approach applied to a number of different reference sets. The self-organising map (SOM) approach proved significantly more accurate than the band-fitting approaches for solution spectra. As there is no validated benchmark method available for infrared structure fitting, SOMSpec was implemented in a leave-one-out validation (LOOV) approach for solid-state transmission and thin-film attenuated total reflectance (ATR) reference sets. We then tested SOMSpec and the thin-film ATR reference set against 68 solution spectra and found the average prediction error for helix (α + 310) and β-sheet was less than 6% for proteins with less than 40% helix. This is quantitatively better than other available approaches. The visual output format of SOMSpec aids identification of poor predictions. We also demonstrated how to convert aqueous ATR spectra to and from transmission spectra for structure fitting. Fourier self-deconvolution did not improve the average structure predictions.

Destructive Photon Echo Formation in Six-Wave Mixing Signals of a MoSe2 Monolayer

Monolayers of transition metal dichalcogenides display a strong excitonic optical response. Additionally encapsulating the monolayer with hexagonal boron nitride allows to reach the limit of a purely homogeneously broadened exciton system. On such a MoSe2 -based system, ultrafast six-wave mixing spectroscopy is performed and a novel destructive photon echo effect is found. This process manifests as a characteristic depression of the nonlinear signal dynamics when scanning the delay between the applied laser pulses. By theoretically describing the process within a local field model, an excellent agreement with the experiment is reached. An effective Bloch vector representation is developed and thereby it is demonstrated that the destructive photon echo stems from a destructive interference of successive repetitions of the heterodyning experiment.

Risk factors in preadolescent boys and girls for the development of eating pathology in young adulthood

OBJECTIVE

Despite a growing literature on potential risk factors for eating disorders, longitudinal research starting before adolescence is scarce, and little is known about risk factors in males. We investigated risk factors in preadolescent boys and girls for the development of eating pathology in adolescence and young adulthood.

METHOD

This study is part of TRAILS (TRacking Adolescents' Individual Lives Survey), a Dutch population-based cohort study (N = 2,229) from preadolescence into adulthood. Potential risk factors were measured at age 11, based on self-report, reports of one of the parents, and records of the Preventive Child Healthcare. Variables included sociodemographic variables, pregnancy and perinatal factors, eating- and weight-related factors, psychological functioning, stressful experiences and family factors. At age 19, two-stage screening including interviews by eating disorder experts was used to examine the prevalence of eating disorders. At age 22 and 26, eating pathology was assessed by the Eating Disorder Diagnostic Scale.

RESULTS

Preadolescent anxious distress and high weight were associated with eating pathology in adolescence and young adulthood in both boys and girls. Overeating in preadolescence was found to be a prodromal symptom of eating disorders during late adolescence. No evidence was found for sex-specific risk factors.

DISCUSSION

Anxious preadolescents with high weight are at increased risk for the development of eating pathology later on. Clinicians should be aware of eating disorder symptoms - like overeating - in this high-risk group of children, and could consider an early intervention to prevent the development of full-blown eating disorders.