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Background: Platelet receptors ACKR3 and CXCR4 play a crucial role in a variety of cardiovascular diseases. Like most chemokine receptors, CXCR4 is a G protein coupled receptor that induces platelet activation. In contrast, the atypical chemokine receptor 3 (ACKR3) lacks the ability to activate heterotrimeric G proteins and its activation leads to platelet inhibition and attenuates thrombus formation. In nucleated cells, heterodimerization of ACKR3 with CXCR4 regulates CXCL12‐dependent signalling. The aim of our study was to investigate the formation of ACKR3/CXCR4 heterodimers in platelets and the subsequent consequences for platelet function. Methods and Results: Using a proximity ligation assay (PLA, Duolink®) to screen for CXCR4/ACKR3 heterodimerization inducing compounds, we found that ACKR3 agonism but not conventional platelet agonists or endogen ligands lead to heterodimer formation. To further characterize the formation of ACKR3/CXCR4 heterodimers, we studied the CXCL12‐dependent platelet activation via CXCR4. Both, CXCL12‐dependent platelet aggregation and collagen‐dependent ex vivo thrombus formation were significantly downregulated by ACKR3 agonism. Moreover, platelet intracellular calcium and Akt signalling were increased by CXCL12 and again suppressed by ACKR3‐specific agonists. Previously, CXCL12 was shown to decrease platelet cAMP levels via CXCR4. Treatment with a specific ACKR3 agonist counteracted this CXCL12/CXCR4‐dependent cAMP decrease. Conclusion: Our results reveal that the formation of platelet ACKR3/CXCR4 heterodimers is dependent on ACKR3 rather than CXCR4. Furthermore, ACKR3 agonism induced heterodimerization is associated with mitigating CXCL12/CXCR4‐dependent platelet activation possibly by modulating CXCR4‐dependent G protein signalling. Our results indicate possible ACKR3 agonist functions and reinforce the potential therapeutic applications of ACKR3 agonists. [ABSTRACT FROM AUTHOR]

In vulnerable atherosclerotic plaques, intraplaque hemorrhages (IPH) result in hemolysis of red blood cells and release of hemoglobin and free hemin. Hemin activates platelets and leads to thrombosis. Agonism of the inhibitory platelet receptor ACKR3 inhibits hemin‐dependent platelet activation and thrombus formation. To characterize the effect of hemin and ACKR3 agonism on isolated human platelets, multi‐color flow cytometry and classical experimental setup such as light transmission aggregometry and a flow chamber assay were used. Hemin induces platelet aggregation and ex vivo platelet‐dependent thrombus formation on immobilized collagen under a low shear rate of 500 s−1, indicating that free hemin is a strong activator of platelet‐dependent thrombosis. Recently, we described that ACKR3 is a prominent inhibitory receptor of platelet activation. Specific ACKR3 agonists but not conventional antiplatelet compounds such as COX‐1 inhibitor (indometacin), ADP‐receptor blocker (cangrelor), or PAR1 inhibitor (ML161) inhibit both hemin‐dependent aggregation and thrombus formation. To further characterize the effect of hemin on platelet subpopulations, we established a multi‐color flow cytometry assay. We found that hemin induces procoagulant (CD42bpos/PAC‐1neg/AnnexinVpos), aggregatory (CD42bpos/PAC‐1pos/AnnexinVneg), and inflammatory (CD42bpos/CXCR4pos/ACKR3pos/AnnexinVpos) platelet subpopulations. Treatment with ACKR3 agonists significantly decreased the formation of procoagulant and ACKR3pos platelets in response to hemin. We conclude that hemin is a strong activator for the formation of procoagulant platelets and thrombus formation which is dependent on the function of ACKR3. Activation of ACKR3 using specific agonists may offer a therapeutic strategy to regulate the vulnerability of atherosclerotic plaques in areas of IPH. [ABSTRACT FROM AUTHOR]

Background: Digitalization in disaster medicine holds significant potential to accelerate rescue operations and ultimately save lives. Mass casualty incidents demand rapid and accurate information management to coordinate effective responses. Currently, first responders manually record triage results on patient cards, and brief information is communicated to the command post via radio communication. Although this process is widely used in practice, it involves several time-consuming and error-prone tasks. To address these issues, we designed, implemented, and evaluated an app-based mobile triage system. This system allows users to document responder details, triage categories, injury patterns, GPS locations, and other important information, which can then be transmitted automatically to the incident commanders. Objective: This study aims to design and evaluate an app-based mobile system as a triage and coordination tool for emergency and disaster medicine, comparing its effectiveness with the conventional paper-based system. Methods: A total of 38 emergency medicine personnel participated in a within-subject experimental study, completing 2 triage sessions with 30 patient cards each: one session using the app-based mobile system and the other using the paper-based tool. The accuracy of the triages and the time taken for each session were measured. Additionally, we implemented the User Experience Questionnaire along with other items to assess participants' subjective ratings of the 2 triage tools. Results: Our 2 (triage tool) × 2 (tool order) mixed multivariate analysis of variance revealed a significant main effect for the triage tool (P <.001). Post hoc analyses indicated that participants were significantly faster (P <.001) and more accurate (P =.005) in assigning patients to the correct triage category when using the app-based mobile system compared with the paper-based tool. Additionally, analyses showed significantly better subjective ratings for the app-based mobile system compared with the paper-based tool, in terms of both school grading (P <.001) and across all 6 scales of the User Experience Questionnaire (all P <.001). Of the 38 participants, 36 (95%) preferred the app-based mobile system. There was no significant main effect for tool order (P =.24) or session order (P =.06) in our model. Conclusions: Our findings demonstrate that the app-based mobile system not only matches the performance of the conventional paper-based tool but may even surpass it in terms of efficiency and usability. This advancement could further enhance the potential of digitalization to optimize processes in disaster medicine, ultimately leading to the possibility of saving more lives. [ABSTRACT FROM AUTHOR]

Background: In cases of terrorism, disasters, or mass casualty incidents, far-reaching life-and-death decisions about prioritizing patients are currently made using triage algorithms that focus solely on the patient's current health status rather than their prognosis, thus leaving a fatal gap of patients who are under- or overtriaged. Objective: The aim of this proof-of-concept study is to demonstrate a novel approach for triage that no longer classifies patients into triage categories but ranks their urgency according to the anticipated survival time without intervention. Using this approach, we aim to improve the prioritization of casualties by respecting individual injury patterns and vital signs, survival likelihoods, and the availability of rescue resources. Methods: We designed a mathematical model that allows dynamic simulation of the time course of a patient's vital parameters, depending on individual baseline vital signs and injury severity. The 2 variables were integrated using the well-established Revised Trauma Score (RTS) and the New Injury Severity Score (NISS). An artificial patient database of unique patients with trauma (N=82,277) was then generated and used for analysis of the time course modeling and triage classification. Comparative performance analysis of different triage algorithms was performed. In addition, we applied a sophisticated, state-of-the-art clustering method using the Gower distance to visualize patient cohorts at risk for mistriage. Results: The proposed triage algorithm realistically modeled the time course of a patient's life, depending on injury severity and current vital parameters. Different casualties were ranked by their anticipated time course, reflecting their priority for treatment. Regarding the identification of patients at risk for mistriage, the model outperformed the Simple Triage And Rapid Treatment's triage algorithm but also exclusive stratification by the RTS or the NISS. Multidimensional analysis separated patients with similar patterns of injuries and vital parameters into clusters with different triage classifications. In this large-scale analysis, our algorithm confirmed the previously mentioned conclusions during simulation and descriptive analysis and underlined the significance of this novel approach to triage. Conclusions: The findings of this study suggest the feasibility and relevance of our model, which is unique in terms of its ranking system, prognosis outline, and time course anticipation. The proposed triage-ranking algorithm could offer an innovative triage method with a wide range of applications in prehospital, disaster, and emergency medicine, as well as simulation and research. [ABSTRACT FROM AUTHOR]