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DNA damage response (DDR) in eukaryotes is essential for the maintenance of genome integrity in challenging environments. The regulatory mechanisms of DDR have been well-established in yeast and humans. However, increasing evidence supports the idea that plants seem to employ different signaling pathways that remain largely unknown. Here, we report the role of MODIFIER OF SNC1, 4-ASSOCIATED COMPLEX SUBUNIT 5A (MAC5A) in DDR in Arabidopsis (Arabidopsis thaliana). Lack of MAC5A in mac5a mutants causes hypersensitive phenotypes to methyl methanesulfonate (MMS), a DNA damage inducer. Consistent with this observation, MAC5A can regulate alternative splicing of DDR genes to maintain the proper response to genotoxic stress. Interestingly, MAC5A interacts with the 26S proteasome (26SP) and is required for its proteasome activity. MAC core subunits are also involved in MMS-induced DDR. Moreover, we find that MAC5A, the MAC core subunits, and 26SP may act collaboratively to mediate high-boron-induced growth repression through DDR. Collectively, our findings uncover the crucial role of MAC in MMS-induced DDR in orchestrating growth and stress adaptation in plants.

 

Modeling unknown systems from data is a precursor of system optimization and sequential decision making. In this paper, we focus on learning a Markov model from a single trajectory of states. Suppose that the transition model has a small rank despite having a large state space, meaning that the system admits a low-dimensional latent structure. We show that one can estimate the full transition model accurately using a trajectory of length that is proportional to the total number of states. We propose two maximum-likelihood estimation methods: a convex approach with nuclear norm regularization and a nonconvex approach with rank constraint. We explicitly derive the statistical rates of both estimators in terms of the Kullback-Leiber divergence and the [Formula: see text] error and also establish a minimax lower bound to assess the tightness of these rates. For computing the nonconvex estimator, we develop a novel DC (difference of convex function) programming algorithm that starts with the convex M-estimator and then successively refines the solution till convergence. Empirical experiments demonstrate consistent superiority of the nonconvex estimator over the convex one. 

High-temperature poling eliminates light-scattering domain walls in a relaxor ferroelectric. 

Microneedle patch devices have been widely utilized for transdermal drug delivery in pain management, but is challenged by accurate control of drug release and subsequent diffusion to human body. The recent emerging wearable electronics that could be integrated with microneedle devices offer a facile approach to address such a challenge. Here a 3D‐printed microheater integrated drug‐encapsulated microneedle patch system for drug delivery is presented. The ink solution comprised polydimethylsiloxane (PDMS) and multiwalled carbon nanotubes (MWCNTs) with a mass concentration of up to 45% (≈10 times higher of existing ones) is prepared and used to print crack‐free stretchable microheaters on substrates with a broad range of materials and geometric curves. The adhesion strength of the printed microheater on the microneedle patch in elevated temperatures is measured to evaluate their integration performance. Assessments of encapsulated drug release into rat's skin are confirmed by examining degradation of microneedles, skin morphologies, and released fluorescent signals. Results and demonstrations established here creates a new opportunity for developing sensor controlled smart microneedle patch systems by integrating with wearable electronics, potentially useful in clinical and biomedical research.