gt 3x accelerometer  (ActiGraph llc)

Journal: JCI Insight

Article Title: Oxidative hotspots on actin promote skeletal muscle weakness in rheumatoid arthritis

doi: 10.1172/jci.insight.126347

Figure Lengend Snippet: (A) An illustration of the composite disease activity score (DAS), with a 44-joint count (red circles) to assess swelling and 53-joint count to assess pain (DAS can range from 0.23 to 9.87). Mean ± SEM DAS was 3.3 ± 0.4 (n = 11, see Supplemental Table 3 for details). (B) Mean ± SEM of isometric specific force of quadriceps femoris from patients with RA and healthy controls (n = 11 per group). (C) Cross-sectional area (CSA) of quadriceps femoris measured by CT scans (mean ± SEM, n = 11). (D) Total daily activity in minutes measured with Actilife accelerometers (mean ± SEM, n = 11) and (E) percentage time spent in each defined activity category. (F) Overview of the oxidative 3-nitrotyrosine (3-NT) and malondialdehyde (MDA) modified amino acids on skeletal muscle actin (SD1–SD4) identified by mass spectrometry in patients with RA (n = 5). The actin model is adapted from the 2ZWH crystal structure of the Protein Data Bank Europe (PDBe). Tyrosine residues (Y) were nitrated (3-NT), whereas histidine (H), glutamine (Q) and asparagine (N) were MDA modified. (G–I) The actin monomer model illustrating that the oxidative hotspots in patients with RA (green) coincide with hotspots in mice with arthritis (pink). Amino acids depicted in red ribbons represent the residues that had the identical modification on actin in RA patients and CFA mice (5 out of 11). Generated with UCSF Chimera (82). Statistical analysis was performed using 2-tailed Student’s t test. A P value less than 0.05 was considered significant. *P < 0.05.

Article Snippet: The daily activity of patients with RA and control subjects was recorded with accelerometers (GT, ActiGraph).

Techniques: Activity Assay, Modification, Mass Spectrometry, Generated

Journal: Digital Health

Article Title: Mobile health interventions to promote physical activity and reduce sedentary behaviour in the workplace: A systematic review

doi: 10.1177/2055207619839883

Figure Lengend Snippet: Characteristics of included studies.

Article Snippet: Simons et al. 2018 (app development and feasibility) Simons et al. 2018 (results of RCT) Belgium , Multiple workplaces in Flanders, Belgium (including retail, catering, social employment and factories) , Study 2, 2018b = Cluster RCT (study 1, 2018a was a qualitative evaluation and impact on PA/SB not reported) , n = 130 (29 clusters) 49% M, 51% F Age IG: 24.8±3.1 CG: 25.1±3.0 Lower educated (i.e. no university or college degree) working young adults, not meeting PA guidelines at baseline (<150 min MVPA/week) , Wearable activity monitor and smartphone app , Wrist-worn Fitbit Charge activity monitor (Fitbit, USA) used with ‘Active Coach’ app for monitoring PA , Educational brochure on PA only (generic information) , PA , Daily minutes of light, moderate and vigorous intensity PA ( OB - ActiGraph™ GT-3x+ accelerometer) , Daily steps (from Fitbit) Self-reported context-specific PA (IPAQ) Psychosocial variables: social support, attitude (perceived benefits and barriers), self-efficacy, knowledge and intentions Engagement: usage statisticsProcess evaluation interviews: Opinions on Fitbit and app (e.g. usability, preferred features) , 21 weeks.

Techniques: Activity Assay, Software