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Tar spot is a devasting corn disease caused by the obligate fungal pathogen Phyllachora maydis. Since its initial identification in the United States in 2015, P. maydis has become an increasing threat to corn production. Despite this, P. maydis has remained largely understudied at the molecular level due to difficulties surrounding its obligate lifestyle. Here, we generated a significantly improved P. maydis nuclear and mitochondrial genome using a combination of long- and short-read technologies and also provide the first transcriptomic analysis of primary tar spot lesions. Our results show that P. maydis is deficient in inorganic nitrogen utilization, is likely heterothallic, and encodes for significantly more protein coding genes, including secreted enzymes and effectors, than previous determined. Furthermore, our expression analysis suggests that following primary tar spot lesion formation, P. maydis might reroute carbon flux away from DNA replication and cell division pathways and towards pathways previously implicated in having significant roles in pathogenicity, such as autophagy and secretion. Together, our results identified several highly expressed unique secreted factors that likely contribute to host recognition and subsequent infection, greatly increasing our knowledge of the biological capacity of P. maydis, which have much broader implications for mitigating tar spot of corn. 

The utility of a match in a two-sided matching market often depends on a variety of characteristics of the two agents (e.g., a buyer and a seller) to be matched. In contrast to the matching market literature, this utility may best be modeled by a general matching utility distribution. In “Asymptotically Optimal Control of a Centralized Dynamic Matching Market with General Utilities,” Blanchet, Reiman, Shah, Wein, and Wu consider general matching utilities in the context of a centralized dynamic matching market. To analyze this difficult problem, they combine two asymptotic techniques: extreme value theory (and regularly varying functions) and fluid asymptotics of queueing systems. A key trade-off in this problem is market thickness: Do we myopically make the best match that is currently available, or do we allow the market to thicken in the hope of making a better match in the future while avoiding agent abandonment? Their asymptotic analysis derives quite explicit results for this problem and reveals how the optimal amount of market thickness increases with the right tail of the matching utility distribution and the amount of market imbalance. Their use of regularly varying functions also allows them to consider correlated matching utilities (e.g., buyers have positively correlated utilities with a given seller), which is ubiquitous in matching markets.

 

Fungicides reduce fungal pathogen populations and are essential to food security. Understanding the impacts of fungicides on crop microbiomes is vital to minimizing unintended consequences while maintaining their use for plant protection. However, fungicide disturbance of plant microbiomes has received limited attention, and has not been examined in different agricultural management systems. We used amplicon sequencing of fungi and prokaryotes in maize and soybean microbiomes before and after foliar fungicide application in leaves and roots from plots under long-term no-till and conventional tillage management. We examined fungicide disturbance and resilience, which revealed consistent non-target effects and greater resiliency under no-till management. Fungicides lowered pathogen abundance in maize and soybean and decreased the abundance of Tremellomycetes yeasts, especially Bulleribasidiaceae, including core microbiome members. Fungicide application reduced network complexity in the soybean phyllosphere, which revealed altered co-occurrence patterns between yeast species of Bulleribasidiaceae, and Sphingomonas and Hymenobacter in fungicide treated plots. Results indicate that foliar fungicides lower pathogen and non-target fungal abundance and may impact prokaryotes indirectly. Treatment effects were confined to the phyllosphere and did not impact belowground microbial communities. Overall, these results demonstrate the resilience of no-till management to fungicide disturbance, a potential novel ecosystem service provided by no-till agriculture.

 

Do dopaminergic reward structures represent the expected utility of information similarly to a reward? Optimal experimental design models from Bayesian decision theory and statistics have proposed a theoretical framework for quantifying the expected value of information that might result from a query. In particular, this formulation quantifies the value of information before the answer to that query is known, in situations where payoffs are unknown and the goal is purely epistemic: That is, to increase knowledge about the state of the world. Whether and how such a theoretical quantity is represented in the brain is unknown. Here we use an event-related functional MRI (fMRI) task design to disentangle information expectation, information revelation and categorization outcome anticipation, and response-contingent reward processing in a visual probabilistic categorization task. We identify a neural signature corresponding to the expectation of information, involving the left lateral ventral striatum. Moreover, we show a temporal dissociation in the activation of different reward-related regions, including the nucleus accumbens, medial prefrontal cortex, and orbitofrontal cortex, during information expectation versus reward-related processing.

 

Abstract We report on the development and extensive characterization of co-sputtered tantala–zirconia (Ta 2 O 5 -ZrO 2 ) thin films, with the goal to decrease coating Brownian noise in present and future gravitational-wave detectors. We tested a variety of sputtering processes of different energies and deposition rates, and we considered the effect of different values of cation ratio η = Zr/(Zr + Ta) and of post-deposition heat treatment temperature T a on the optical and mechanical properties of the films. Co-sputtered zirconia proved to be an efficient way to frustrate crystallization in tantala thin films, allowing for a substantial increase of the maximum annealing temperature and hence for a decrease of coating mechanical loss φ c . The lowest average coating loss was observed for an ion-beam sputtered sample with η = 0.485 ± 0.004 annealed at 800 °C, yielding φ ¯ c = 1.8 × 1 0 − 4 rad. All coating samples showed cracks after annealing. Although in principle our measurements are sensitive to such defects, we found no evidence that our results were affected. The issue could be solved, at least for ion-beam sputtered coatings, by decreasing heating and cooling rates down to 7 °C h −1 . While we observed as little optical absorption as in the coatings of current gravitational-wave interferometers (0.5 parts per million), further development will be needed to decrease light scattering and avoid the formation of defects upon annealing. 

We present Fermi Gamma-ray Burst Monitor (Fermi-GBM) and Swift Burst Alert Telescope (Swift-BAT) searches for gamma-ray/X-ray counterparts to gravitational-wave (GW) candidate events identified during the third observing run of the Advanced LIGO and Advanced Virgo detectors. Using Fermi-GBM onboard triggers and subthreshold gamma-ray burst (GRB) candidates found in the Fermi-GBM ground analyses, the Targeted Search and the Untargeted Search, we investigate whether there are any coincident GRBs associated with the GWs. We also search the Swift-BAT rate data around the GW times to determine whether a GRB counterpart is present. No counterparts are found. Using both the Fermi-GBM Targeted Search and the Swift-BAT search, we calculate flux upper limits and present joint upper limits on the gamma-ray luminosity of each GW. Given these limits, we constrain theoretical models for the emission of gamma rays from binary black hole mergers.