AMAISE: a machine learning approach to index-free sequence enrichment.

Metagenomics holds potential to improve clinical diagnostics of infectious diseases, but DNA from clinical specimens is often dominated by host-derived sequences. To address this, researchers employ host-depletion methods. Laboratory-based host-depletion methods, however, are costly in terms of time and effort, while computational host-depletion methods rely on memory-intensive reference index databases and struggle to accurately classify noisy sequence data. To solve these challenges, we propose an index-free tool, AMAISE (A Machine Learning Approach to Index-Free Sequence Enrichment). Applied to the task of separating host from microbial reads, AMAISE achieves over 98% accuracy. Applied prior to metagenomic classification, AMAISE results in a 14-18% decrease in memory usage compared to using metagenomic classification alone. Our results show that a reference-independent machine learning approach to host depletion allows for accurate and efficient sequence detection.

Resolution of confluent and reticulated papillomatosis after bariatric surgery.

Confluent and reticulated papillomatosis (CARP), a rare dermatologic disorder characterized by hyperpigmented papules that subsequently develop into plaques with reticulated margins, is frequently confused with acanthosis nigricans. The aetiology and pathogenesis of CARP is not yet fully understood, but it is often present in individuals with obesity and PCOS. This case report describes an African American adolescent female with obesity with a rash diagnosed as CARP after unsuccessful treatment with antifungals and corticosteroids. Her dermatosis proved recalcitrant to antibiotics and metformin but started to resolve immediately after bariatric surgery. This case report supports insulin resistance as a contributor to CARP's pathogenesis and as well as its association with obesity. Clinically significant weight reduction should be considered in the management of this challenging skin condition.

Embryonic transcription factor expression in mice predicts medial amygdala neuronal identity and sex-specific responses to innate behavioral cues.

The medial subnucleus of the amygdala (MeA) plays a central role in processing sensory cues required for innate behaviors. However, whether there is a link between developmental programs and the emergence of inborn behaviors remains unknown. Our previous studies revealed that the telencephalic preoptic area (POA) embryonic niche is a novel source of MeA destined progenitors. Here, we show that the POA is comprised of distinct progenitor pools complementarily marked by the transcription factors Dbx1 and Foxp2. As determined by molecular and electrophysiological criteria this embryonic parcellation predicts postnatal MeA inhibitory neuronal subtype identity. We further find that Dbx1-derived and Foxp2+ cells in the MeA are differentially activated in response to innate behavioral cues in a sex-specific manner. Thus, developmental transcription factor expression is predictive of MeA neuronal identity and sex-specific neuronal responses, providing a potential developmental logic for how innate behaviors could be processed by different MeA neuronal subtypes.