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In this study, the authors developed and assessed the accuracy of a machine learning algorithm to identify skin cancers using images of biopsies.

Here, seeking to understand a possible cause of the declining popluations of Brood X cicadas in Ohio and Indiana, the authors investigated the presence of Wolbachia, an inherited bacterial symbiont that lives in the reproductive cells of approximately 60% of insect species in these cicadas. Following their screening of one-hundred 17-year periodical cicadas, they only identified the presence of Wolbachia infection in less than 2%, suggesting that while Wolbachia can infect cicadas it appears uncommon in the Brood X cicadas they surveyed.

Supernovas are powerful explosions that result from gravitational collapse of a massive star. Using photometric analysis Arora et al. set out to investigate whether 2020pni (located in galaxy UGC 9684) was a supernova. They were ultimately able to identify 2020pni as a Type II-L supernova and determine it's distance from earth.

In this study, a deep learning model is used to classify post-traumatic stress disorder patients through novel markers to assist in finding candidate biomarkers for the disorder.

The sequence of nitrogenous bases that make up the DNA of organisms can contain hidden mathematical sequences. Here the authors used BioPython, a programming tool, to find an organism that displays Gijswijt’s Sequence in its genome. In this manner they found that the common carp best displays Gijswijt’s Sequence in its genome.

In this study, the authors identify new potential targets to treat advanced diffuse large B-cell lymphoma after treatment relapse and loss of CD19 expression.

In this article, the authors identify the characteristics that make a book a best-seller. Knowing what, besides content, predicts the success of a book can help publishers maximize the success of their print products.

The authors use machine learning on MRI images of brain tissue to predict tumor onset as an avenue for early detection of brain cancer.

Black goji berries have attracted interest for their high levels of anthocyanin pigment, which believed to have health-boosting effects. Yu and Zhu research a method for measuring goji berry quality by detecting anthocyanin content under different conditions.

The authors assessed the atmospheric and oceanic parameters necessary for tidally-locked exoplanets to be habitable.