A case of persistent folliculitis in a 21-year-old man was demonstrated to be due to Ancylostoma caninum larvae. Treatment with oral thiabendazole was curative. Cutaneous larva migrans may be due to A caninum, but this presentation appears to be unique. The literature concerning etiology and pathogenesis of larva migrans is discussed with reference to this case.

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Interstellar dust corrupts nearly every stellar observation, and accounting for it is crucial to measuring physical properties of stars. We model the dust distribution as a spatially varying latent field with a Gaussian process (GP) and develop a likelihood model and inference method that scales to millions of astronomical observations. Modeling interstellar dust is complicated by two factors. The first is integrated observations. The data come from a vantage point on Earth and each observation is an integral of the unobserved function along our line of sight, resulting in a complex likelihood and a more difficult inference problem than in classical GP inference. The second complication is scale; stellar catalogs have millions of observations. To address these challenges we develop , a scalable approach to GP inference with integrated observations based on stochastic variational inference. We study on synthetic data and the Ananke dataset, a high-fidelity mechanistic model of the Milky Way with millions of stars.reliably infers the spatial dust map with well-calibrated posterior uncertainties.