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Orozco, C.

Publications and source records attributed to Orozco, C..

2 recordsLinked to original sources

Evolution of songbird vocal imitation involved multiple cellular innovations

A central goal of evolutionary neuroscience is to link behavioral adaptations to changes across the central nervous system. The dorsal telencephalon (i.e., pallium) varies widely in macrostructure across vertebrate clades and is thought to underlie the diversity of complex vertebrate behaviors. Yet, pallial cell types appear comparatively constrained in their evolutionary specializations relative to other parts of the nervous system, even across species with notable behavioral adaptations. Instead, differences among pallial neurons largely reflect their topographic organization. Here, we show that although transcriptomic identities of cell types in the songbird pallium largely follow this pattern, multiple cellular innovations exist within the vocal imitation brain regions distributed across the pallium. These include behavior-linked specializations to glutamatergic cell types in each region and the presence of PV- and SST-like GABAergic neurons unique to vocal imitation circuits. Additionally, we identify a concerted increase in glial composition that is accounted for by elevated proportions of astrocytes across vocal imitation circuits. These findings demonstrate that complex learned behaviors, such as vocal imitation, can be associated with the emergence of novel, behavior-associated cell types in the pallium; suggesting that selective pressures can, in some uncommon cases, favor functional specialization over conserved developmental constraints.

neuroscience↗

Breast Cancer Clustering Integrating Complete Gene Expression Profiles and Genetic Ancestry

Breast cancer (BC) remains the leading cause of cancer-related mortality among women globally. Precise subtyping of BC is critical for optimizing treatment strategies. This study explored the capacity of bulk RNA- seq data to improve breast cancer characterization by analysis of complete expression profiles. We analyzed RNA-seq 274 tumor samples and six healthy tissue samples from diverse geographical origins. Using over 9,800 SNPs directly genotyped from RNA-seq data, we successfully predicted broad genetic ancestry, identifying European, African, Asian, South Asian, and Admixed American origins. Molecular subtyping through PAM50 showed ambiguous classifications for about half of the samples, underscoring the limitations of current molecular diagnostic tools. Unsupervised clustering separated tumors in three main clusters. Cluster C1 demonstrated immune activation and inflammatory response pathways, while C2 highlighted metabolic and immune interaction processes. Cluster C3 exhibited enriched metabolic regulation and adipokine signaling pathways. In silico drug sensitivity analysis identified potential therapeutic strategies, including vinorelbine and AZD6482, with cluster-specific efficacy. Our findings emphasize the integration of ancestry-informed data and complete transcriptomic profiles to redefine BC subtyping. These insights offer a foundation for more equitable, ancestry-informed therapeutic strategies and highlight the importance of diversity in cancer research.

cancer biology↗