Conditional associative learning examined in a paralyzed patient with amyotrophic lateral sclerosis using brain-computer interface technology

Background Brain-computer interface methodology based on self-regulation of slow-cortical potentials (SCPs) of the EEG (electroencephalogram) was used to assess conditional associative learning in one severely paralyzed, late-stage ALS patient. After having been taught arbitrary stimulus relations, he was evaluated for formation of equivalence classes among the trained stimuli. Methods A monitor presented visual information in two targets. The method of teaching was matching to sample. Three types of stimuli were presented: signs (A), colored disks (B), and geometrical shapes (C). The sample was one type, and the choice was between two stimuli from another type. The patient used his SCP to steer a cursor to one of the targets. A smiley was presented as a reward when he hit the correct target. The patient was taught A-B and B-C (sample – comparison) matching with three stimuli of each type. Tests for stimulus equivalence involved the untaught B-A, C-B, A-C, and C-A relations. An additional test was discrimination between all three stimuli of one equivalence class presented together versus three unrelated stimuli. The patient also had sessions with identity matching using the same stimuli. Results The patient showed high accuracy, close to 100%, on identity matching and could therefore discriminate the stimuli and control the cursor correctly. Acquisition of A-B matching took 11 sessions (of 70 trials each) and had to be broken into simpler units before he could learn it. Acquisition of B-C matching took two sessions. The patient passed all equivalence class tests at 90% or higher. Conclusion The patient may have had a deficit in acquisition of the first conditional association of signs and colored disks. In contrast, the patient showed clear evidence that A-B and B-C training had resulted in formation of equivalence classes. The brain-computer interface technology combined with the matching to sample method is a useful way to assess various cognitive abilities of severely paralyzed patients, who are without reliable motor control

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

A review of equity issues in quantitative studies on health inequalities: the case of asthma in adults

<p>Abstract</p> <p>Background</p> <p>The term 'inequities' refers to avoidable differences rooted in injustice. This review examined whether or not, and how, quantitative studies identifying inequalities in risk factors and health service utilization for asthma explicitly addressed underlying inequities. Asthma was chosen because recent decades have seen strong increases in asthma prevalence in many international settings, and inequalities in risk factors and related outcomes.</p> <p>Methods</p> <p>A review was conducted of studies that identified social inequalities in asthma-related outcomes or health service use in adult populations. Data were extracted on use of equity terms (objective evidence), and discussion of equity issues without using the exact terms (subjective evidence).</p> <p>Results</p> <p>Of the 219 unique articles retrieved, 21 were eligible for inclusion. None used the terms equity/inequity. While all but one article traced at least partial pathways to inequity, only 52% proposed any intervention and 55% of these interventions focused exclusively on the more proximal, clinical level.</p> <p>Conclusions</p> <p>Without more in-depth and systematic examination of inequities underlying asthma prevalence, quantitative studies may fail to provide the evidence required to inform equity-oriented interventions to address underlying circumstances restricting opportunities for health.</p

Digital ulcers predict a worse disease course in patients with systemic sclerosis

Objective: Systemic sclerosis (SSc) is a systemic autoimmune disease with high morbidity and significant mortality. There is a great need of predictors that would allow risk stratification of patients with SSc and ultimately initiation of treatment early enough to ensure optimal clinical results. In this study, we evaluated whether a history of digital ulcers (HDU) at presentation may be a predictor of vascular outcomes and of overall clinical worsening and death in patients with SSc. Methods: Patients from the EULAR Scleroderma Trials and Research (EUSTAR) database, satisfying at inclusion the 1980 American College of Rheumatology classification criteria for SSc, who had a follow-up of at least 3 years since baseline or who have died, were included in the analysis. HDU at presentation as a predictor of disease worsening or death was evaluated by Cox proportional hazards regression analysis. Results :3196 patients matched the inclusion criteria (male sex 13.2%, 33.4% diffuse subset). At presentation, 1092/3196 patients had an HDU (34.1%). In multivariable analysis adjusting for age, gender and all parameters considered potentially significant, HDU was predictive for the presence of active digital ulcers (DUs) at prospective visits (HR (95% CI)): 2.41(1.91 to 3.03), p&lt;0.001, for an elevated systolic pulmonary arterial pressure on heart ultrasound (US-PAPs):1.36 (1.03 to 1.80), p=0.032, for any cardiovascular event (new DUs, elevated US-PAPs or LV failure):3.56 (2.26 to 5.62), p&lt;0.001, and for death (1.53 (1.16 to 2.02), p=0.003). Conclusions :In patients with SSc, HDU at presentation predicts the occurrence of DUs at follow-up and is associated with cardiovascular worsening and decreased survival

Malignant inflammation in cutaneous T-cell lymphoma: a hostile takeover

Cutaneous T-cell lymphomas (CTCL) are characterized by the presence of chronically inflamed skin lesions containing malignant T cells. Early disease presents as limited skin patches or plaques and exhibits an indolent behavior. For many patients, the disease never progresses beyond this stage, but in approximately one third of patients, the disease becomes progressive, and the skin lesions start to expand and evolve. Eventually, overt tumors develop and the malignant T cells may disseminate to the blood, lymph nodes, bone marrow, and visceral organs, often with a fatal outcome. The transition from early indolent to progressive and advanced disease is accompanied by a significant shift in the nature of the tumor-associated inflammation. This shift does not appear to be an epiphenomenon but rather a critical step in disease progression. Emerging evidence supports that the malignant T cells take control of the inflammatory environment, suppressing cellular immunity and anti-tumor responses while promoting a chronic inflammatory milieu that fuels their own expansion. Here, we review the inflammatory changes associated with disease progression in CTCL and point to their wider relevance in other cancer contexts. We further define the term "malignant inflammation" as a pro-tumorigenic inflammatory environment orchestrated by the tumor cells and discuss some of the mechanisms driving the development of malignant inflammation in CTCL

Real-time brain computer interface using imaginary movements

Backgroun

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives