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Chronic administration of selective serotonin reuptake inhibitors (SSRIs), which up-regulates central serotonin (5-HT) system function, enhances adult hippocampal neurogenesis. However, the relationship between central 5-HT system and adult neurogenesis has not fully been understood. Here, we report that lowering 5-HT level in adulthood is also able to enhance adult hippocampal neurogenesis. We used tamoxifen (TM)-induced Cre in Pet1-CreER\(^{T2}\) mice to either deplete central serotonergic (5-HTergic) neurons or inactivate 5-HT synthesis in adulthood and explore the role of central 5-HT in adult hippocampal neurogenesis. A dramatic increase in hippocampal neurogenesis is present in these two central 5-HT-deficient mice and it is largely prevented by administration of agonist for 5-HTR2c receptor. In addition, the survival of new-born neurons in the hippocampus is enhanced. Furthermore, the adult 5-HT-deficient mice showed reduced depression-like behaviors but enhanced contextual fear memory. These findings demonstrate that lowering central 5-HT function in adulthood can also enhance adult hippocampal neurogenesis, thus revealing a new aspect of central 5-HT in regulating adult neurogenesis.
An expanded evaluation of protein function prediction methods shows an improvement in accuracy
(2016)
Background
A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging.
Results
We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2.
Conclusions
The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent.