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Abstract: Hypofibrinolysis is a documented abnormality in conditions with high risk of vascular occlusion. A key inhibitor of fibrinolysis is α2-antiplasmin (α2AP), and we hypothesize that the Affimer technology, comprising small conformational proteins with 2 9-amino-acid variable regions, can be used to modulate α2AP activity and facilitate fibrinolysis. Using a phage display system, a library of Affimers was screened against α2AP. A total of 28 α2AP-specific Affimers were isolated, of which 1, termed Affimer A11, inhibited protein function and enhanced fibrinolysis. Affimer A11 displayed a monomeric form and consistently reduced the lysis time of clots made from plasma samples of individuals with type 2 diabetes mellitus (n = 15; from 150.8 ± 100.9 to 109.8 ± 104.8 minutes) and those with cardiovascular disease (n = 15; 117.6 ± 40.6 to 79.7 ± 33.3 minutes; P < .01 for both groups). The effects of A11 on fibrinolysis were maintained when clots were made from whole blood samples. Mechanistic studies demonstrated that A11 did not affect clot structure or interfere with the incorporation of α2AP into fibrin networks but significantly enhanced plasmin activity and accelerated plasmin generation. Affimer A11 reduced α2AP binding to plasmin(ogen), whereas molecular modeling demonstrated interactions with α2AP in an area responsible for binding to plasminogen, explaining the effects on both plasmin activity and generation. Affimer A11, at 0.15 to 0.60 mg/mL, had the ability to bind 70% to 90% of plasma α2AP. In conclusion, we demonstrate that Affimers are viable tools for inhibiting α2AP function and facilitating fibrinolysis, making them potential future therapeutic agents to reduce thrombosis risk., (© 2024 by The American Society of Hematology. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), permitting only noncommercial, nonderivative use with attribution. All other rights reserved.)

Introduction: Cannabis is increasingly available to individuals in the United States, with the majority of states legalizing medical or recreational cannabis use. Cannabis expectancies (e.g., positive expectations from cannabis use) are related to more frequent cannabis use and associated with greater odds of lapse following a cessation attempt., Methods: To evaluate the relationship between expectancies and cannabis- and health-related outcomes, we surveyed adults who used medical cannabis for chronic pain (n = 633; 52.2 % female; 82.1 % white) over a two-year period. Then, we performed a principal components analysis (PCA) on the Cannabis Expectancies Questionnaire to derive components of cannabis expectancies. We performed k-means clustering to identify subgroups with similar expectancies. The relationship between subgroup assignment and cannabis use outcomes (frequency, quantity), and physical and mental health functioning were evaluated., Results: The PCA identified a three-component solution and k-means clustering identified four subgroups: low expectancies, negative expectancies, amotivation expectancies, and positive expectancies. Participants' cannabis expectancies were dynamic over time. After adjusting for demographics, expectancy subgroup was able to predict six-month cannabis use frequency (χ2(3) = 11.244; p = 0.010) and mental health functioning (χ2(3) = 24.926; p < 0.001), but not quantity (χ2(3) = 2.741, p = 0.433) or physical health functioning (χ2(3) = 5.110, p = 0.164)., Conclusion: In a large cohort of individuals who use medical cannabis, four subgroups with differing cannabis expectancies emerged: low expectancies, negative expectancies, amotivation expectancies, and positive expectancies. These subgroups predicted subsequent outcomes and may be important for targeted intervention approaches to reduce cannabis use and improve functioning., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)