Transitive reasoning in the adult domestic hen in a six-term series task.

Transitive inference (TI) is a disjunctive syllogism that allows an individual to indirectly infer a relationship between two components, by knowing their respective relationship to a third component (if A > B and B > C, then A > C). The common procedure is the 5-term series task, in which individuals are tested on indirect, unlearned relations. Few bird species have been tested for TI to date, which limits our knowledge of the phylogenetic spread of such reasoning ability.

Effect of the social environment on olfaction and social skills in wild-type and a mouse model of autism.

Autism spectrum disorders (ASD) are complex, polygenic and heterogenous neurodevelopmental conditions. The severity of autism-associated variants is influenced by environmental factors, particularly social experiences during the critical neurodevelopmental period. While early behavioral interventions have shown efficacy in some children with autism, pharmacological support for core features - impairments in social interaction and communication, and stereotyped or restricted behaviors - is currently lacking.

A first complete catalog of highly expressed genes in eight chicken tissues reveals uncharacterized gene families specific for the chicken testis.

Based on next-generation sequencing, we established a repertoire of differentially overexpressed genes (DoEGs) in eight adult chicken tissues: the testis, brain, lung, liver, kidney, muscle, heart, and intestine. With 4,499 DoEGs, the testis had the highest number and proportion of DoEGs compared with the seven somatic tissues. The testis DoEG set included the highest proportion of long noncoding RNAs (lncRNAs; 1,851, representing 32% of the lncRNA genes in the whole genome) and the highest proportion of protein-coding genes (2,648, representing 14.

CoNIC Challenge: Pushing the frontiers of nuclear detection, segmentation, classification and counting.

Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome. To drive innovation in this area, we setup a community-wide challenge using the largest available dataset of its kind to assess nuclear segmentation and cellular composition. Our challenge, named CoNIC, stimulated the development of reproducible algorithms for cellular recognition with real-time result inspection on public leaderboards.