TL;DR: The RADAR-MDD study as mentioned in this paper is a multi-site prospective cohort study, aiming to recruit 600 participants with a history of depressive disorder across three sites: London, Amsterdam and Barcelona, where participants were asked to wear a wrist-worn activity tracker and download several apps onto their smartphones.
Abstract: There is a growing body of literature highlighting the role that wearable and mobile remote measurement technology (RMT) can play in measuring symptoms of major depressive disorder (MDD). Outcomes assessment typically relies on self-report, which can be biased by dysfunctional perceptions and current symptom severity. Predictors of depressive relapse include disrupted sleep, reduced sociability, physical activity, changes in mood, prosody and cognitive function, which are all amenable to measurement via RMT. This study aims to: 1) determine the usability, feasibility and acceptability of RMT; 2) improve and refine clinical outcome measurement using RMT to identify current clinical state; 3) determine whether RMT can provide information predictive of depressive relapse and other critical outcomes. RADAR-MDD is a multi-site prospective cohort study, aiming to recruit 600 participants with a history of depressive disorder across three sites: London, Amsterdam and Barcelona. Participants will be asked to wear a wrist-worn activity tracker and download several apps onto their smartphones. These apps will be used to either collect data passively from existing smartphone sensors, or to deliver questionnaires, cognitive tasks, and speech assessments. The wearable device, smartphone sensors and questionnaires will collect data for up to 2-years about participants’ sleep, physical activity, stress, mood, sociability, speech patterns, and cognitive function. The primary outcome of interest is MDD relapse, defined via the Inventory of Depressive Symptomatology- Self-Report questionnaire (IDS-SR) and the World Health Organisation’s self-reported Composite International Diagnostic Interview (CIDI-SF). This study aims to provide insight into the early predictors of major depressive relapse, measured unobtrusively via RMT. If found to be acceptable to patients and other key stakeholders and able to provide clinically useful information predictive of future deterioration, RMT has potential to change the way in which depression and other long-term conditions are measured and managed.
TL;DR: Biomarker-positive patients with no prior history of stroke or transient ischemic attack may be a optimal target population to receive “dual pathway” therapy with rivaroxaban plus dual antiplatelet therapy for secondary prevention following ACS.
Abstract: Background:Despite dual antiplatelet therapy, persistent thrombin generation and thrombin-mediated platelet activation account in part for the residual risk of atherothrombotic disease among patien...
TL;DR: Histamine receptors (nomenclature as agreed by the NC-IUPHAR Subcommittee on Histamine Receptors) are activated by the endogenous ligand histamine and some agonists at the human H3 receptor display significant ligand bias.
Abstract: Histamine receptors (nomenclature as agreed by the NC-IUPHAR Subcommittee on Histamine Receptors [75, 163]) are activated by the endogenous ligand histamine. Marked species differences exist between histamine receptor orthologues [75]. The human and rat H3 receptor genes are subject to significant splice variance [12]. The potency order of histamine at histamine receptor subtypes is H3 = H4 > H2 > H1 [163]. Some agonists at the human H3 receptor display significant ligand bias [171]. Antagonists of all 4 histamine receptors have clinical uses: H1 antagonists for allergies (e.g. cetirizine), H2 antagonists for acid-reflux diseases (e.g. ranitidine), H3 antagonists for narcolepsy (e.g. pitolisant/WAKIX; Registered) and H4 antagonists for atopic dermatitis (e.g. ZPL-3893787; Phase IIa) [163] and vestibular neuritis (AUV) (SENS-111 (Seliforant, previously UR-63325), entered and completed vestibular neuritis (AUV) Phase IIa efficacy and safety trials, respectively) [205, 8].
TL;DR: Free fatty acid receptors (FFA, nomenclature as agreed by the NC-IUPHAR Subcommittee on free fatty Acid receptors [111, 24]) are activated by free fatty acids.
Abstract: Free fatty acid receptors (FFA, nomenclature as agreed by the NC-IUPHAR Subcommittee on free fatty acid receptors [111, 24]) are activated by free fatty acids. Long-chain saturated and unsaturated fatty acids (including C14.0 (myristic acid), C16:0 (palmitic acid), C18:1 (oleic acid), C18:2 (linoleic acid), C18:3, (α-linolenic acid), C20:4 (arachidonic acid), C20:5,n-3 (EPA) and C22:6,n-3 (docosahexaenoic acid)) activate FFA1 [8, 50, 60] and FFA4 receptors [41, 48, 90], while short chain fatty acids (C2 (acetic acid), C3 (propanoic acid), C4 (butyric acid) and C5 (pentanoic acid)) activate FFA2 [9, 62, 86] and FFA3 [9, 62] receptors. The crystal structure for agonist bound FFA1 has been described [108].