Diabetic cardiomyopathy (DCM) is the principal cause of death in people with diabetes. However, there is currently no effective strategy to prevent the development of DCM. Although cyclovirobuxine D (CVB-D) has been widely used to treat multiple cardiovascular diseases, the possible beneficial effects of CVB-D on DCM remained unknown. The present aim was to explore the potential effects and underlying mechanisms of CVB-D on DCM. We explored the effects of CVB-D in DCM by using high fat high sucrose diet and streptozotocin-induced rat DCM model. Cardiac function and survival in rats with DCM were improved via the amelioration of oxidative damage after CVB-D treatment. Our data also demonstrated that pre-treatment with CVB-D exerted a remarkable cytoprotective effect against high glucose-or H 2 o 2-induced neonatal rat cardiomyocyte damage via the suppression of reactive oxygen species accumulation and restoration of mitochondrial membrane potential; this effect was associated with promotion of Nrf2 nuclear translocation and its downstream antioxidative stress signals (NQO-1, Prdx1). Overall, the present data has provided the first evidence that CVB-D has potential therapeutic in DCM, mainly by activation of the Nrf2 signalling pathway to suppress oxidative stress. Our findings also have positive implications on the novel promising clinical applications of CVB-D. Diabetic cardiomyopathy (DCM) is usually characterised by cardiac structure and functional disorders in individuals with diabetes independent of hypertension or ischemic coronary artery disease 1-3. Although it is the principal cause of death in patients with diabetes, no effective strategies currently exist to prevent the progression of DCM 4. The pathogenesis of DCM involves in many factors such as oxidative stress, chronic low-grade inflammation 5 , autophagy 6 , and pyroptosis 7 , etc. The accumulated evidences confirm that cardiomyocyte injuries induced by oxidative stress are the predominant contributors to the pathophysiological process of DCM 8. Reactive oxygen species (ROS) overproduction induced by hyperglycaemia, free fatty acids, and glycosylation end products results in myocardial structural damage and functional or metabolic disorders, which are considered to be the key pathological signal of DCM 9. Therefore, amelioration of oxidative stress may be a therapeutic strategy to prevent the progression of DCM. Nuclear factor (carotenoid-derived 2)-like 2 (Nrf2) is the major transcription factor in the cellular antioxidant response 10. The expression and activity of Nrf2 are regulated by cullin 3-based ubiquitin E3 ligases, such as Kelch-like ECH-related protein 1 (Keap1). Upon exposure to various stress conditions, Nrf2 is uncoupled from
In this paper, we empirically examine the impact of performance feedback on the outcome of crowdsourcing contests. We develop a dynamic structural model to capture the economic processes that drive contest participants' behavior, and estimate the model using a rich data set collected from a major online crowdsourcing design platform. The model captures key features of the crowdsourcing context, including a large participant pool, entries by new participants throughout the contest, exploitation (revision of previous submissions) and exploration (radically novel submissions) behaviors by contest incumbents, and the participants' strategic choice among these entry, exploration, and exploitation decisions in a dynamic game. We find that the cost associated with exploratory actions is higher than the cost associated with exploitative actions. High-performers prefer the exploitative strategy, while low-performers tend to make fewer follow-up submissions and prefer the exploratory strategy. Using counter-factual simulations, we compare the outcome of crowdsourcing contests under alternative feedback disclosure policies and award levels. Our simulation results suggest that the full feedback policy (providing feedback throughout the contest) may not be optimal.The late feedback policy (providing feedback only in the second half of the contest) leads to a better overall contest outcome.
Problem definition: This paper studies the role of seekers’ problem specification in crowdsourcing contests for design problems. Academic/practical relevance: Platforms hosting design contests offer detailed guidance for seekers to specify their problems when launching a contest. Yet problem specification in such crowdsourcing contests is something the theoretical and empirical literature has largely overlooked. We aim to fill this gap by offering an empirically validated model to generate insights for the provision of information at contest launch. Methodology: We develop a game-theoretic model featuring different types of information (categorized as “conceptual objectives” or “execution guidelines”) in problem specifications and assess their impact on design processes and submission qualities. Real-world data are used to empirically test hypotheses and policy recommendations generated from the model, and a quasi-natural experiment provides further empirical validation. Results: We show theoretically and verify empirically that with more conceptual objectives disclosed in the problem specification, the number of participants in a contest eventually decreases; with more execution guidelines in the problem specification, the trial effort provision by each participant increases; and the best solution quality always increases with more execution guidelines but eventually decreases with more conceptual objectives. Managerial implications: To maximize the best solution quality in crowdsourced design problems, seekers should always provide more execution guidelines and only a moderate number of conceptual objectives.
In this paper, we empirically examine the impact of performance feedback on the outcome of crowdsourcing contests. We develop a dynamic structural model to capture the economic processes that drive contest participants’ behavior and estimate the model using a detailed data set about real online logo design contests. Our rich model captures key features of the crowdsourcing context, including a large participant pool; entries by new participants throughout the contest; exploitation (revision of previous submissions) and exploration (radically novel submissions) behaviors by contest incumbents; and the participants’ strategic choice among these entry, exploration, and exploitation decisions in a dynamic game. Using counterfactual simulations, we compare the outcome of crowdsourcing contests under alternative feedback disclosure policies and award levels. Our simulation results suggest that, despite its prevalence on many platforms, the full feedback policy (providing feedback throughout the contest) may not be optimal. The late feedback policy (providing feedback only in the second half of the contest) leads to a better overall contest outcome. This paper was accepted by Gabriel Weintraub, revenue management and market analytics department.
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