Gait quality assessed by trunk accelerometry after total knee arthroplasty and its association with patient related outcome measures

Background: With an increasingly younger population and more active patients, assessment of functional outcome is more important than ever in patients undergoing total knee arthroplasty. Accelerometers have been used successfully to objectively evaluate gait quality in other fields. The aim of this study was to assess gait quality with accelerometers before and after surgery, and to assess added value of resulting parameters to patient reported outcome measures scores. Methods: Sixty-five patients (mean age 65 years (range 41–75)) who underwent primary total knee arthroplasty were evaluated using a tri-axial trunk accelerometer preoperatively and 1 year after surgery. Gait quality parameters derived from the accelerometry data were evaluated in three dimensions at both time points. Factor analysis was performed on all outcome variables and changes from before to 1 year after surgery in the most representative variable for each factor were studied. Findings: Factor analysis identified three separate gait quality factors, with questionnaire and gait quality parameters loading on different factors. Both gait quality factor scores and questionnaire factor scores improved significantly 1 year after surgery. As expected based on the factor analysis, only weak to moderate associations were found between patient reported outcome measures and gait quality before surgery, after surgery and in change scores. Interpretation: The independence of patient reported outcome measures and gait quality parameters measured with trunk accelerometry indicates that gait quality parameters provide additional information on functional outcome after total knee arthroplasty. Providing caretakers with objectively measurable targets using accelerometry could help improve outcome of these patients

GPA33 is expressed on multiple human blood cell types and distinguishes CD4(+) central memory T cells with and without effector function

The Ig superfamily protein glycoprotein A33 (GPA33) has been implicated in immune dysregulation, but little is known about its expression in the immune compartment. Here, we comprehensively determined GPA33 expression patterns on human blood leukocyte subsets, using mass and flow cytometry. We found that GPA33 was expressed on fractions of B, dendritic, natural killer and innate lymphoid cells. Most prominent expression was found in the CD4(+) T cell compartment. Naive and CXCR5(+) regulatory T cells were GPA33(high), and naive conventional CD4(+) T cells expressed intermediate GPA33 levels. The expression pattern of GPA33 identified functional heterogeneity within the CD4(+) central memory T cell (Tcm) population. GPA33(+) CD4(+) Tcm cells were fully undifferentiated, bona fide Tcm cells that lack immediate effector function, whereas GPA33(-) Tcm cells exhibited rapid effector functions and may represent an early stage of differentiation into effector/effector memory T cells before loss of CD62L. Expression of GPA33 in conventional CD4(+) T cells suggests a role in localization and/or preservation of an undifferentiated state. These results form a basis to study the function of GPA33 and show it to be a useful marker to discriminate between different cellular subsets, especially in the CD4(+) T cell lineage.Immunobiology of allogeneic stem cell transplantation and immunotherapy of hematological disease

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