A unified scheme for the benchmarking of upper limb functions in neurological disorders.

BACKGROUND: In neurorehabilitation, we are witnessing a growing awareness of the importance of standardized quantitative assessment of limb functions. Detailed assessments of the sensorimotor deficits following neurological disorders are crucial. So far, this assessment has relied mainly on clinical scales, which showed several drawbacks. Different technologies could provide more objective and repeatable measurements. However, the current literature lacks practical guidelines for this purpose. Nowadays, the integration of available metrics, protocols, and algorithms into one harmonized benchmarking ecosystem for clinical and research practice is necessary. METHODS: This work presents a benchmarking framework for upper limb capacity. The scheme resulted from a multidisciplinary and iterative discussion among several partners with previous experience in benchmarking methodology, robotics, and clinical neurorehabilitation. We merged previous knowledge in benchmarking methodologies for human locomotion and direct clinical and engineering experience in upper limb rehabilitation. The scheme was designed to enable an instrumented evaluation of arm capacity and to assess the effectiveness of rehabilitative interventions with high reproducibility and resolution. It includes four elements: (1) a taxonomy for motor skills and abilities, (2) a list of performance indicators, (3) a list of required sensor modalities, and (4) a set of reproducible experimental protocols. RESULTS: We proposed six motor primitives as building blocks of most upper-limb daily-life activities and combined them into a set of functional motor skills. We identified the main aspects to be considered during clinical evaluation, and grouped them into ten motor abilities categories. For each ability, we proposed a set of performance indicators to quantify the proposed ability on a quantitative and high-resolution scale. Finally, we defined the procedures to be followed to perform the benchmarking assessment in a reproducible and reliable way, including the definition of the kinematic models and the target muscles. CONCLUSIONS: This work represents the first unified scheme for the benchmarking of upper limb capacity. To reach a consensus, this scheme should be validated with real experiments across clinical conditions and motor skills. This validation phase is expected to create a shared database of human performance, necessary to have realistic comparisons of treatments and drive the development of new personalized technologies.

Dietary habits in patients with fibromyalgia: a cross-sectional study.

OBJECTIVES: To the scarce information on dietary habits in fibromyalgia (FM), it is added that there are no comparative studies with other rheumatic diseases. The objective of this study was to characterise the dietary habits of patients with FM by comparing, for the first time, with healthy controls (HC) and rheumatoid arthritis (RA). METHODS: This cross-sectional, observational study was based on data obtained from the Dietfibrom project for FM and from the IMID Consortium for RA and HC. All participants completed a food frequency questionnaire evaluating their weekly dietary intake of main food groups. The three cohorts were compared using a multiple logistic regression model adjusted for age, sex, and body mass index. RESULTS: After quality control, n=287 FM, n=1,983 HC and n=1,942 RA patients were analysed. We found that FM had a profound impact in the diet compared to HC, reducing the consumption of dairy (OR=0.32, p<0.0001), bread and/or whole grain cereals (OR=0.59, p=0.0006), fresh fruit (OR=0.66, P=0.008), and fish (OR=0.64, p=0.002). These same four food groups were also significantly reduced in FM patients in comparison to RA patients (p<0.0005 in all cases). Additionally, a lower consumption of pasta, rice and/or potatoes was also observed in FM compared to RA (OR=0.72, p=0.028). CONCLUSIONS: The present cross-sectional study shows that FM is associated to a significant change in the normal dietary patterns. These results underscore the importance of diet in this prevalent disease and are a warning of the potential long-range effects of a deficient nutritional status.

Genetic variation at the glycosaminoglycan metabolism pathway contributes to the risk of psoriatic arthritis but not psoriasis.

OBJECTIVE: Psoriatic arthritis (PsA) is a chronic inflammatory arthritis affecting up to 30% of patients with psoriasis (Ps). To date, most of the known risk loci for PsA are shared with Ps, and identifying disease-specific variation has proven very challenging. The objective of the present study was to identify genetic variation specific for PsA. METHODS: We performed a genome-wide association study in a cohort of 835 patients with PsA and 1558 controls from Spain. Genetic association was tested at the single marker level and at the pathway level. Meta-analysis was performed with a case-control cohort of 2847 individuals from North America. To confirm the specificity of the genetic associations with PsA, we tested the associated variation using a purely cutaneous psoriasis cohort (PsC, n=614) and a rheumatoid arthritis cohort (RA, n=1191). Using network and drug-repurposing analyses, we further investigated the potential of the PsA-specific associations to guide the development of new drugs in PsA. RESULTS: We identified a new PsA risk single-nucleotide polymorphism at B3GNT2 locus (p=1.10e-08). At the pathway level, we found 14 genetic pathways significantly associated with PsA (pFDR<0.05). From these, the glycosaminoglycan (GAG) metabolism pathway was confirmed to be disease-specific after comparing the PsA cohort with the cohorts of patients with PsC and RA. Finally, we identified candidate drug targets in the GAG metabolism pathway as well as new PsA indications for approved drugs. CONCLUSION: These findings provide insights into the biological mechanisms that are specific for PsA and could contribute to develop more effective therapies.

Serum drug levels of biologic agents in the management of rheumatoid arthritis and spondyloarthritis: a systematic review.

The utility of monitoring drug levels in rheumatoid arthritis and spondyloarthritis patients on biological therapy is called into question. The objective was to study relevant clinical questions on the topic, i.e., (1) whether drug levels predict relapse in patients whose biologic was optimized because of remission or low disease activity; (2) whether information about drug levels influences the prognosis of patients with primary or secondary failure to a biological therapy; and (3) whether methotrexate (MTX) influences the association between drug levels and response. Medline, Embase, Cochrane databases were screened, from inception to December 2016 in search for all studies related to the three research questions about. Overall characteristics and outcomes of the studies were collected in a table of evidence and the quality of the studies was assessed with the Newcastle-Ottawa scale or the GRADEpro. Two studies responded the first question, 5 the second, and 7 the third. Studies were small and with limitations, but suggest that measurement drug levels may be useful in patients in remission; that higher drug levels predict a longer relapse-free optimization, and in patients with failure to a biological agent, treatment may need individual adjustment according to the presence of drug levels or antidrug-antibodies. In addition, MTX influences the association between response and drug levels. Monitoring drug levels would allow optimal use of current biological therapies, but more studies and of better quality are needed to draw definitive conclusions.

Urine metabolome profiling of immune-mediated inflammatory diseases.

BACKGROUND: Immune-mediated inflammatory diseases (IMIDs) are a group of complex and prevalent diseases where disease diagnostic and activity monitoring is highly challenging. The determination of the metabolite profiles of biological samples is becoming a powerful approach to identify new biomarkers of clinical utility. In order to identify new metabolite biomarkers of diagnosis and disease activity, we have performed the first large-scale profiling of the urine metabolome of the six most prevalent IMIDs: rheumatoid arthritis, psoriatic arthritis, psoriasis, systemic lupus erythematosus, Crohn's disease, and ulcerative colitis. METHODS: Using nuclear magnetic resonance, we analyzed the urine metabolome in a discovery cohort of 1210 patients and 100 controls. Within each IMID, two patient subgroups were recruited representing extreme disease activity (very high vs. very low). Metabolite association analysis with disease diagnosis and disease activity was performed using multivariate linear regression in order to control for the effects of clinical, epidemiological, or technical variability. After multiple test correction, the most significant metabolite biomarkers were validated in an independent cohort of 1200 patients and 200 controls. RESULTS: In the discovery cohort, we identified 28 significant associations between urine metabolite levels and disease diagnosis and three significant metabolite associations with disease activity (P FDR < 0.05). Using the validation cohort, we validated 26 of the diagnostic associations and all three metabolite associations with disease activity (P FDR < 0.05). Combining all diagnostic biomarkers using multivariate classifiers we obtained a good disease prediction accuracy in all IMIDs and particularly high in inflammatory bowel diseases. Several of the associated metabolites were found to be commonly altered in multiple IMIDs, some of which can be considered as hub biomarkers. The analysis of the metabolic reactions connecting the IMID-associated metabolites showed an over-representation of citric acid cycle, phenylalanine, and glycine-serine metabolism pathways. CONCLUSIONS: This study shows that urine is a source of biomarkers of clinical utility in IMIDs. We have found that IMIDs show similar metabolic changes, particularly between clinically similar diseases and we have found, for the first time, the presence of hub metabolites. These findings represent an important step in the development of more efficient and less invasive diagnostic and disease monitoring methods in IMIDs.

A genome-wide association study identifies SLC8A3 as a susceptibility locus for ACPA-positive rheumatoid arthritis.

OBJECTIVE: RA patients with serum ACPA have a strong and specific genetic background. The objective of the study was to identify new susceptibility genes for ACPA-positive RA using a genome-wide association approach. METHODS: A total of 924 ACPA-positive RA patients with joint damage in hands and/or feet, and 1524 healthy controls were genotyped in 582 591 single-nucleotide polymorphisms (SNPs) in the discovery phase. In the validation phase, the most significant SNPs in the genome-wide association study representing new candidate loci for RA were tested in an independent cohort of 863 ACPA-positive patients with joint damage and 1152 healthy controls. All individuals from the discovery and validation cohorts were Caucasian and of Southern European ancestry. RESULTS: In the discovery phase, 60 loci not previously associated with RA risk showed evidence for association at P < 5×10(-4) and were tested for replication in the validation cohort. A total of 12 loci were replicated at the nominal level (P < 0.05, same direction of effect as in the discovery phase). When combining the discovery and validation cohorts, an intronic SNP in the Solute Carrier family 8 gene (SLC8A3) was found to be associated with ACPA-positive RA at a genome-wide level of significance RA [odds ratio (95% CI): 1.42 (1.25, 1.6), Pcombined = 3.19×10(-8)]. CONCLUSIONS: SLC8A3 was identified as a new risk locus for ACPA-positive RA. This study demonstrates the advantage of analysing relevant subsets of RA patients to identify new genetic risk variants.

A deletion at ADAMTS9-MAGI1 locus is associated with psoriatic arthritis risk.

OBJECTIVE: Copy number variants (CNVs) have been associated with the risk to develop multiple autoimmune diseases. Our objective was to identify CNVs associated with the risk to develop psoriatic arthritis (PsA) using a genome-wide analysis approach. METHODS: A total of 835 patients with PsA and 1498 healthy controls were genotyped for CNVs using the Illumina HumanHap610 BeadChip genotyping platform. Genomic CNVs were characterised using CNstream analysis software and analysed for association using the χ(2) test. The most significant genomic CNV associations with PsA risk were independently tested in a validation sample of 1133 patients with PsA and 1831 healthy controls. In order to test for the specificity of the variants with PsA aetiology, we also analysed the association to a cohort of 822 patients with purely cutaneous psoriasis (PsC). RESULTS: A total of 165 common CNVs were identified in the genome-wide analysis. We found a highly significant association of an intergenic deletion between ADAMTS9 and MAGI1 genes on chromosome 3p14.1 (p=0.00014). Using the independent patient and control cohort, we validated the association between ADAMTS9-MAGI1 deletion and PsA risk (p=0.032). Using next-generation sequencing, we characterised the 26 kb associated deletion. Finally, analysing the PsC cohort we found a lower frequency of the deletion compared with the PsA cohort (p=0.0088) and a similar frequency to that of healthy controls (p>0.3). CONCLUSIONS: The present genome-wide scan for CNVs associated with PsA risk has identified a new deletion associated with disease risk and which is also differential from PsC risk.

Exploring EEG-based motor imagery decoding: a dual approach using spatial features and spectro-spatial Deep Learning model IFNet.

Introduction: In recent years, the decoding of motor imagery (MI) from electroencephalography (EEG) signals has become a focus of research for brain-machine interfaces (BMIs) and neurorehabilitation. However, EEG signals present challenges due to their non-stationarity and the substantial presence of noise commonly found in recordings, making it difficult to design highly effective decoding algorithms. These algorithms are vital for controlling devices in neurorehabilitation tasks, as they activate the patient's motor cortex and contribute to their recovery. Methods: This study proposes a novel approach for decoding MI during pedalling tasks using EEG signals. A widespread approach is based on feature extraction using Common Spatial Patterns (CSP) followed by a linear discriminant analysis (LDA) as a classifier. The first approach covered in this work aims to investigate the efficacy of a task-discriminative feature extraction method based on CSP filter and LDA classifier. Additionally, the second alternative hypothesis explores the potential of a spectro-spatial Convolutional Neural Network (CNN) to further enhance the performance of the first approach. The proposed CNN architecture combines a preprocessing pipeline based on filter banks in the frequency domain with a convolutional neural network for spectro-temporal and spectro-spatial feature extraction. Results and discussion: To evaluate the approaches and their advantages and disadvantages, EEG data has been recorded from several able-bodied users while pedalling in a cycle ergometer in order to train motor imagery decoding models. The results show levels of accuracy up to 80% in some cases. The CNN approach shows greater accuracy despite higher instability.

Experimental validation of an upper limb benchmarking framework in healthy and post-stroke individuals: a pilot study.

In the context of neurorehabilitation, there have been rapid and continuous improvements in sensors-based clinical tools to quantify limb performance. As a result of the increasing integration of technologies in the assessment procedure, the need to integrate evidence-based medicine with benchmarking has emerged in the scientific community. In this work, we present the experimental validation of our previously proposed benchmarking scheme for upper limb capabilities in terms of repeatability, reproducibility, and clinical meaningfulness. We performed a prospective multicenter study on neurologically intact young and elderly subjects and post-stroke patients while recording kinematics and electromyography. 60 subjects (30 young healthy, 15 elderly healthy, and 15 post-stroke) completed the benchmarking protocol. The framework was repeatable among different assessors and instrumentation. Age did not significantly impact the performance indicators of the scheme for healthy subjects. In post-stroke subjects, the movements presented decreased smoothness and speed, the movement amplitude was reduced, and the muscular activation showed lower power and lower intra-limb coordination.We revised the original framework reducing it to three motor skills, and we extracted 14 significant performance indicators with a good correlation with the ARAT clinical scale. The applicability of the scheme is wide, and it may be considered a valuable tool for upper limb functional evaluation in the clinical routine.

Early poststroke clinically significant fatigue predicts functional independence: a prospective longitudinal study.

Background: Poststroke fatigue is a prevalent issue among stroke survivors, significantly impeding functional recovery and diminishing their quality of life. Aim: This prospective cohort study aims to investigate the association between poststroke fatigue and the extent of functional recovery in survivors of ischemic and hemorrhagic strokes. Additionally, it seeks to delineate the temporal progression of poststroke fatigue in these two stroke subtypes. Methods: We assessed a cohort of 79 patients recovering from acute ischemic or hemorrhagic strokes. Poststroke fatigue was quantified using the Fatigue Severity Scale (FSS) and the Numeric Rating Scale (NRSfatigue). Patients' condition was evaluated using the National Institute of Health Stroke Scale (NIHSS), and functional independence levels were determined using the Barthel Index for Activities of Daily Living (BIADL) and the Modified Rankin Scale (MRS). Depressive mood and pain were measured using the Beck Depression Inventory (BDI) and the Numeric Rating Scale for pain (NRSpain), respectively. Results: Our primary findings indicate that the early manifestation of clinically significant fatigue (CSF) is predictive of a poorer trajectory in functional independence levels during recovery. Furthermore, we observed differing patterns of fatigue progression between ischemic and hemorrhagic strokes. Fatigue tends to ameliorate over time in hemorrhagic stroke cases, paralleling functional recovery, while it remains stable over time in ischemic stroke cases. Conclusion: Our results underscore the detrimental impact of early poststroke fatigue on long-term outcomes. Furthermore, they highlight the imperative of managing poststroke fatigue, particularly during the subacute phase of stroke recovery.

Modulation of neuronal dynamics by sustained and activity-dependent continuous-wave near-infrared laser stimulation.

Significance: Near-infrared laser illumination is a non-invasive alternative/complement to classical stimulation methods in neuroscience but the mechanisms underlying its action on neuronal dynamics remain unclear. Most studies deal with high-frequency pulsed protocols and stationary characterizations disregarding the dynamic modulatory effect of sustained and activity-dependent stimulation. The understanding of such modulation and its widespread dissemination can help to develop specific interventions for research applications and treatments for neural disorders. Aim: We quantified the effect of continuous-wave near-infrared (CW-NIR) laser illumination on single neuron dynamics using sustained stimulation and an open-source activity-dependent protocol to identify the biophysical mechanisms underlying this modulation and its time course. Approach: We characterized the effect by simultaneously performing long intracellular recordings of membrane potential while delivering sustained and closed-loop CW-NIR laser stimulation. We used waveform metrics and conductance-based models to assess the role of specific biophysical candidates on the modulation. Results: We show that CW-NIR sustained illumination asymmetrically accelerates action potential dynamics and the spiking rate on single neurons, while closed-loop stimulation unveils its action at different phases of the neuron dynamics. Our model study points out the action of CW-NIR on specific ionic-channels and the key role of temperature on channel properties to explain the modulatory effect. Conclusions: Both sustained and activity-dependent CW-NIR stimulation effectively modulate neuronal dynamics by a combination of biophysical mechanisms. Our open-source protocols can help to disseminate this non-invasive optical stimulation in novel research and clinical applications.

Seven-chain adaptive immune receptor repertoire analysis in rheumatoid arthritis reveals novel features associated with disease and clinically relevant phenotypes.

BACKGROUND: In rheumatoid arthritis (RA), the activation of T and B cell clones specific for self-antigens leads to the chronic inflammation of the synovium. Here, we perform an in-depth quantitative analysis of the seven chains that comprise the adaptive immune receptor repertoire (AIRR) in RA. RESULTS: In comparison to controls, we show that RA patients have multiple and strong differences in the B cell receptor repertoire including reduced diversity as well as altered isotype, chain, and segment frequencies. We demonstrate that therapeutic tumor necrosis factor inhibition partially restores this alteration but find a profound difference in the underlying biochemical reactivities between responders and non-responders. Combining the AIRR with HLA typing, we identify the specific T cell receptor repertoire associated with disease risk variants. Integrating these features, we further develop a molecular classifier that shows the utility of the AIRR as a diagnostic tool. CONCLUSIONS: Simultaneous sequencing of the seven chains of the human AIRR reveals novel features associated with the disease and clinically relevant phenotypes, including response to therapy. These findings show the unique potential of AIRR to address precision medicine in immune-related diseases.

Magnetoinductive metasurface of capacitively-loaded split rings for local field homogenization in a 7 T MRI birdcage: A simulation study.

The transmit field B1+ in a 7 T birdcage is inherently inhomogeneous due to the effects of wavelengths on tissue. This work investigates the homogenization of this field through metasurfaces that consist of a two-dimensional planar array of capacitively loaded conducting rings. The metasurfaces are placed in the intermediate space between the head and the birdcage on either side of the head. The periodical structure of this type of metasurface supports magnetoinductive waves because of the mutual inductive coupling existing between the elements of the array. The analysis takes advantage of this coupling and exploits the excitation of a standing magnetoinductive wave across the arrays, which creates a strong local field that contributes to locally homogenize the field of the birdcage. The presence of the arrays does not detune the birdcage, so that they can be used with commercial birdcages that operate both to transmit and to receive.

An EEG database for the cognitive assessment of motor imagery during walking with a lower-limb exoskeleton.

One important point in the development of a brain-machine Interface (BMI) commanding an exoskeleton is the assessment of the cognitive engagement of the subject during the motor imagery tasks conducted. However, there are not many databases that provide electroencephalography (EEG) data during the use of a lower-limb exoskeleton. The current paper presents a database designed with an experimental protocol aiming to assess not only motor imagery during the control of the device, but also the attention to gait on flat and inclined surfaces. The research was conducted as an EUROBENCH subproject in the facilities sited in Hospital Los Madroños, Brunete (Madrid). The data validation reaches accuracies over 70% in the assessment of motor imagery and attention to gait, which marks the present database as a valuable resource for researches interested on developing and testing new EEG-based BMIs.

The complex landscape of TMS devices: A brief overview.

The increasing application of TMS in research and therapy has spawned an ever-growing number of commercial and non-commercial TMS devices and technology development. New CE-marked devices appear at a rate of approximately one every two years, with new FDA-approved application of TMS occurring at a similar rate. With the resulting complex landscape of TMS devices and their application, accessible information about the technological characteristics of the TMS devices, such as the type of their circuitry, their pulse characteristics, or permitted protocols would be beneficial. We here present an overview and open access database summarizing key features and applications of available commercial and non-commercial TMS devices (http://www.tmsbase.info). This may guide comparison and decision making about the use of these devices. A bibliometric analysis was performed by identifying commercial and non-commercial TMS devices from which a comprehensive database was created summarizing their publicly available characteristics, both from a technical and clinical point of view. In this document, we introduce both the commercial devices and prototypes found in the literature. The technical specifications that unify these devices are briefly analysed in two separate tables: power electronics, waveform, protocols, and coil types. In the prototype TMS systems, the proposed innovations are focused on improving the treatment regarding the patient: noise cancellation, controllable parameters, and multiple stimulation. This analysis shows that the landscape of TMS is becoming increasingly fragmented, with new devices appearing ever more frequently. The review provided here can support development of benchmarking frameworks and comparison between TMS systems, inform the choice of TMS platforms for specific research and therapeutic applications, and guide future technology development for neuromodulation devices. This standardisation strategy will allow a better end-user choice, with an impact on the TMS manufacturing industry and a homogenisation of patient samples in multi-centre clinical studies. As an open access repository, we envisage the database to grow along with the dynamic development of TMS devices and applications through community-lead curation.

Spasticity evaluation with the Amadeo Tyromotion device in patients with hemispheric stroke.

Objective: The objective of this study is to verify the reliability and the concurrent and discriminant validity of the measurements of spasticity offered by the robotic device, quantifying the (1) test-retest reliability, (2) correlation with the clinical evaluation using the Modified Ashworth Scale (MAS), (3) inter-rater reliability between the two physiotherapists, and (4) ability to discriminate between healthy and stroke patients. Methods: A total of 20 stroke patients and 20 healthy volunteers participated in the study. Two physical therapists (PT1 and PT2) independently evaluated the hand spasticity of stroke subjects using the MAS. Spasticity was assessed, both in healthy and stroke patients, with the Amadeo device at three increasing velocities of passive movement for three consecutive repeated assessments, while raw data of force and position were collected through an external program. Data analysis: The intraclass correlation coefficient (ICC) and the weighted kappa were computed to estimate the reliability of the Amadeo device measurements, the inter-rater reliability of MAS, and the correlation between the MAS and Amadeo device measurements. The discriminant ability of the Amadeo device was assessed by comparing the stroke and healthy subjects' spasticity measurements with the percentage of agreements with 0 in MAS for healthy subjects. Results: The test-retest reliability of the Amadeo device was high with ICC at all three velocities (ICC = 0.908, 0.958, and 0.964, respectively) but lower if analyzed with weighted kappa correlation (0.584, 0.748, and 0.749, respectively) as mean values for each velocity. The correlation between Amadeo and the clinical scale for stroke patients with weighted kappa correlation was poor (0.280 ± 0.212 for PT1 and 0.290 ± 0.155 for PT2). The inter-rater reliability of the clinical MAS was high (ICC = 0.911). Conclusion: Both MAS and Amadeo spasticity scores showed good reliability. The Amadeo scores did not show a strong clinical correlation with the MAS in stroke patients. Hitherto, Amadeo evaluation shows trends that are consistent with the characteristics of spasticity, such as an increase in spasticity as the speed of muscle stretching increases. The ability of the device to discriminate between stroke patients and healthy controls is low. Future studies adopting an instrumental gold standard for spasticity may provide further insight into the validity of these measurements.

Legged locomotion over irregular terrains: state of the art of human and robot performance.

Legged robotic technologies have moved out of the lab to operate in real environments, characterized by a wide variety of unpredictable irregularities and disturbances, all this in close proximity with humans. Demonstrating the ability of current robots to move robustly and reliably in these conditions is becoming essential to prove their safe operation. Here, we report an in-depth literature review aimed at verifying the existence of common or agreed protocols and metrics to test the performance of legged system in realistic environments. We primarily focused on three types of robotic technologies, i.e., hexapods, quadrupeds and bipeds. We also included a comprehensive overview on human locomotion studies, being it often considered the gold standard for performance, and one of the most important sources of bioinspiration for legged machines. We discovered that very few papers have rigorously studied robotic locomotion under irregular terrain conditions. On the contrary, numerous studies have addressed this problem on human gait, being nonetheless of highly heterogeneous nature in terms of experimental design. This lack of agreed methodology makes it challenging for the community to properly assess, compare and predict the performance of existing legged systems in real environments. On the one hand, this work provides a library of methods, metrics and experimental protocols, with a critical analysis on the limitations of the current approaches and future promising directions. On the other hand, it demonstrates the existence of an important lack of benchmarks in the literature, and the possibility of bridging different disciplines, e.g., the human and robotic, towards the definition of standardized procedures that will boost not only the scientific development of better bioinspired solutions, but also their market uptake.

Static magnetic field stimulation over motor cortex modulates resting functional connectivity in humans.

Focal application of transcranial static magnetic field stimulation (tSMS) over the human motor cortex induces local changes in cortical excitability. Whether tSMS can also induce distant network effects, and how these local and distant effects may vary over time, is currently unknown. In this study, we applied 10 min tSMS over the left motor cortex of healthy subjects using a real/sham parallel design. To measure tSMS effects at the sensori-motor network level, we used resting-state fMRI. Real tSMS, but not sham, reduced functional connectivity within the stimulated sensori-motor network. This effect of tSMS showed time-dependency, returning to sham levels after the first 5 min of fMRI scanning. With 10 min real tSMS over the motor cortex we did not observe effects in other functional networks examined (default mode and visual system networks). In conclusion, 10 min of tSMS over a location within the sensori-motor network reduces functional connectivity within the same functional network.

Making Bipedal Robot Experiments Reproducible and Comparable: The Eurobench Software Approach.

This study describes the software methodology designed for systematic benchmarking of bipedal systems through the computation of performance indicators from data collected during an experimentation stage. Under the umbrella of the European project Eurobench, we collected approximately 30 protocols with related testbeds and scoring algorithms, aiming at characterizing the performances of humanoids, exoskeletons, and/or prosthesis under different conditions. The main challenge addressed in this study concerns the standardization of the scoring process to permit a systematic benchmark of the experiments. The complexity of this process is mainly due to the lack of consistency in how to store and organize experimental data, how to define the input and output of benchmarking algorithms, and how to implement these algorithms. We propose a simple but efficient methodology for preparing scoring algorithms, to ensure reproducibility and replicability of results. This methodology mainly constrains the interface of the software and enables the engineer to develop his/her metric in his/her favorite language. Continuous integration and deployment tools are then used to verify the replicability of the software and to generate an executable instance independent of the language through dockerization. This article presents this methodology and points at all the metrics and documentation repositories designed with this policy in Eurobench. Applying this approach to other protocols and metrics would ease the reproduction, replication, and comparison of experiments.

Food groups associated with immune-mediated inflammatory diseases: a Mendelian randomization and disease severity study.

BACKGROUND/OBJECTIVES: Immune-mediated inflammatory diseases (IMIDs) are prevalent diseases. There is, however, a lack of understanding of the link between diet and IMIDs, how much dietary patterns vary between them and if there are food groups associated with a worsening of the disease. SUBJECTS/METHODS: To answer these questions we analyzed a nation-wide cohort of n = 11,308 patients from six prevalent IMIDs and 2050 healthy controls. We compared their weekly intake of the major food categories, and used a Mendelian randomization approach to determine which dietary changes are caused by disease. Within each IMID, we analyzed the association between food frequency and disease severity. RESULTS: After quality control, n = 11,230 recruited individuals were used in this study. We found that diet is profoundly altered in all IMIDs: at least three food categories are significantly altered in each disease (P < 0.05). Inflammatory bowel diseases showed the largest differences compared to controls (n ≥ 8 categories, P < 0.05). Mendelian randomization analysis supported that some of these dietary changes, like vegetable reduction in Crohn's Disease (P = 2.5 × 10-10, OR(95% CI) = 0.73(0.65, 0.80)), are caused by the disease. Except for Psoriatic Arthritis and Systemic Lupus Erythematosus, we have found ≥2 food groups significantly associated with disease severity in the other IMIDs (P < 0.05). CONCLUSIONS: This cross-disease study demonstrates that prevalent IMIDs are associated to a significant change in the normal dietary patterns. This variation is highly disease-specific and, in some cases, it is caused by the disease itself. Severity in IMIDs is also associated with specific food groups. The results of this study underscore the importance of studying diet in IMIDs.