Pathogenic variants in the genes encoding the non-canonical TGFB signaling components TAK1 (MAP3K7), TAB2 and PKA-Cα (PRKACA) cause rare multisystem disorders, which may include congenital heart disease (CHD). To investigate the role of TAK1 signaling in CHD, we performed genetic analysis of CHD patients and discovered an increased burden of rare TAB2 and TAK1 variants in patients with extracardiac abnormalities. To address the mechanism of TAK1 in heart development, we performed experiments in cell and animal models. Zebrafish tak1 and tab2 mutants presented with cardiac and extracardiac developmental defects, and tak1 mutant hearts showed downregulation of genes encoding core cardiac transcription factors, sarcomeric proteins and extracellular matrix proteins. In vitro experiments indicated that TAK1 via TAB2 and PKA-Cα is activated at the primary cilium during cardiomyogenesis; activation at this site is enhanced by TGFB/BMP ligands. Inactivation of TAK1 inhibited ciliary signaling and cardiomyocyte differentiation, and patient-derived TAK1 variants reduced its ciliary localization. In conclusion, our data establish a pivotal role for TAK1 and its upstream regulators at the primary cilium in heart development and syndromic CHD.
C. Doganli, Oskar Kaaber Thomsen, Daniel A. Baird et al.· PLoS Biology· 4 citations
A distributed game-theoretic framework for joint task offloading and service caching in STINs, providing provable equilibrium guarantees is developed, formulated as a non-cooperative stochastic game among IoT devices that autonomously determine their computing, association, and satellite caching strategies.
Filothei Linardatou, Maria Diamanti, E. Tsiropoulou et al.· IEEE Open Journal of the Com...· 0 citations
Over-the-Air Computation (AirComp) Federated Learning (FL) is actively studied as a communication-efficient technique for distributed Artificial Intelligence (AI) model training. To mitigate the impact of wireless channels on the aggregated global model while addressing client energy sustainability, recent efforts have explored integrating Reconfigurable Intelligent Surfaces (RIS) and Simultaneous Wireless Information and Power Transfer (SWIPT) into AirComp FL. In this context, literature has mainly focused on radio resource allocation for optimized SWIPT and RIS-assisted Downlink (DL) model broadcasting and Uplink (UL) AirComp model aggregation. Nevertheless, existing works largely treat the communication design of AirComp FL in isolation, neglecting the tight coupling between radio and compute resource allocation. In this paper, we address this gap by modeling the radio-compute dependency in AirComp FL and optimizing harvested energy to sustain client-side local training and model transmissions. To this end, we jointly optimize the RIS configuration, SWIPT power-splitting ratio, DL transmission time, and local computing frequency to minimize the total communication and computation overhead in latency and energy. The original non-convex problem is decomposed into two independent subproblems, which are solved iteratively via a combination of low-rank optimization and min-max convex reformulation techniques. Numerical evaluations confirm that integrating RIS and SWIPT into AirComp FL leads to higher accuracy, and reduced latency and energy overheads across the FL pipeline.
Stefanos Voikos, P. Charatsaris, Maria Diamanti et al.· IEEE Transactions on Wireles...· 0 citations
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