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  1. Abstract

    Autophagy, as an intracellular degradation system, plays a critical role in plant immunity. However, the involvement of autophagy in the plant immune system and its function in plant nematode resistance are largely unknown. Here, we show that root-knot nematode (RKN;Meloidogyne incognita) infection induces autophagy in tomato (Solanum lycopersicum) and differentatgmutants exhibit high sensitivity to RKNs. The jasmonate (JA) signaling negative regulators JASMONATE-ASSOCIATED MYC2-LIKE 1 (JAM1), JAM2 and JAM3 interact with ATG8s via an ATG8-interacting motif (AIM), and JAM1 is degraded by autophagy during RKN infection. JAM1 impairs the formation of a transcriptional activation complex between ETHYLENE RESPONSE FACTOR 1 (ERF1) and MEDIATOR 25 (MED25) and interferes with transcriptional regulation of JA-mediated defense-related genes by ERF1. Furthermore, ERF1 acts in a positive feedback loop and regulates autophagy activity by transcriptionally activatingATGexpression in response to RKN infection. Therefore, autophagy promotes JA-mediated defense against RKNs via forming a positive feedback circuit in the degradation of JAMs and transcriptional activation by ERF1.

  2. Free, publicly-accessible full text available October 1, 2023
  3. Pesticides benefit agriculture by increasing crop yield, quality, and security. However, pesticides may inadvertently harm bees, which are valuable as pollinators. Thus, candidate pesticides in development pipelines must be assessed for toxicity to bees. Leveraging a dataset of 382 molecules with toxicity labels from honey bee exposure experiments, we train a support vector machine (SVM) to predict the toxicity of pesticides to honey bees. We compare two representations of the pesticide molecules: (i) a random walk feature vector listing counts of length- L walks on the molecular graph with each vertex- and edge-label sequence and (ii) the Molecular ACCess System (MACCS) structural key fingerprint (FP), a bit vector indicating the presence/absence of a list of pre-defined subgraph patterns in the molecular graph. We explicitly construct the MACCS FPs but rely on the fixed-length- L random walk graph kernel (RWGK) in place of the dot product for the random walk representation. The L-RWGK-SVM achieves an accuracy, precision, recall, and F1 score (mean over 2000 runs) of 0.81, 0.68, 0.71, and 0.69, respectively, on the test data set—with L = 4 being the mode optimal walk length. The MACCS-FP-SVM performs on par/marginally better than the L-RWGK-SVM, lends more interpretability, but varies moremore »in performance. We interpret the MACCS-FP-SVM by illuminating which subgraph patterns in the molecules tend to strongly push them toward the toxic/non-toxic side of the separating hyperplane.« less
  4. Both the computational costs and the accuracy of the invariant-imbedding T-matrix method escalate with increasing the truncation number N at which the expansions of the electromagnetic fields in terms of vector spherical harmonics are truncated. Thus, it becomes important in calculation of the single-scattering optical properties to choose N just large enough to satisfy an appropriate convergence criterion; this N we call the optimal truncation number. We present a new convergence criterion that is based on the scattering phase function rather than on the scattering cross section. For a selection of homogeneous particles that have been used in previous single-scattering studies, we consider how the optimal N may be related to the size parameter, the index of refraction, and particle shape. We investigate a functional form for this relation that generalizes previous formulae involving only size parameter, a form that shows some success in summarizing our computational results. Our results indicate clearly the sensitivity of optimal truncation number to the index of refraction, as well as the difficulty of cleanly separating this dependence from the dependence on particle shape.
  5. The molecular tetravalent oxidation state for praseodymium is observed in solution via oxidation of the anionic trivalent precursor [K][Pr 3+ (NP(1,2-bis- t Bu-diamidoethane)(NEt 2 )) 4 ] (1-Pr(NP*)) with AgI at −35 °C. The Pr 4+ complex is characterized in solution via cyclic voltammetry, UV-vis-NIR electronic absorption spectroscopy, and EPR spectroscopy. Electrochemical analyses of [K][Ln 3+ (NP(1,2-bis- t Bu-diamidoethane)(NEt 2 )) 4 ] (Ln = Nd and Dy) by cyclic voltammetry are reported and, in conjunction with theoretical modeling of electronic structure and oxidation potential, are indicative of principal ligand oxidations in contrast to the metal-centered oxidation observed for 1-Pr(NP*). The identification of a tetravalent praseodymium complex in in situ UV-vis and EPR experiments is further validated by theoretical modeling of the redox chemistry and the UV-vis spectrum. The latter study was performed by extended multistate pair-density functional theory (XMS-PDFT) and implicates a multiconfigurational ground state for the tetravalent praseodymium complex.
  6. Abstract

    Sensitivities of the backscattering properties to the microphysical properties (in particular, size and shape) of mineral dust aerosols are examined based on TAMUdust2020, a comprehensive single‐scattering property database of irregular aerosol particles. We develop the bulk mineral dust particle models based on size‐resolved particle ensembles with randomly distorted shapes and spectrally resolved complex refractive indices, which are constrained by using in situ observations reported in the literature. The light detection and ranging (lidar) ratio is more sensitive to particle shape than particle size, while the depolarization ratio depends strongly on particle size. The simulated bulk backscattering properties (i.e., the lidar ratio and the depolarization ratio) of typical mineral dust particles with effective radii of 0.5–3 µm are reasonably consistent with lidar observations made during several field campaigns. The present dust bulk optical property models are applicable to lidar‐based remote sensing of dust aerosol properties.