Preverbal infants produce more protophones with artificial objects compared to natural objects.

Protophones are considered to be precursors of speech. These vocalizations have been notably discussed in relation to toys and their importance for developing language skills. However, little is known about how natural objects, compared to artificial objects, may affect protophone production, an approach that could additionally help reconstruct how language evolved.

Automatic brain MRI motion artifact detection based on end-to-end deep learning is similarly effective as traditional machine learning trained on image quality metrics.

Head motion artifacts in magnetic resonance imaging (MRI) are an important confounding factor concerning brain research as well as clinical practice. For this reason, several machine learning-based methods have been developed for the automatic quality control of structural MRI scans. Deep learning offers a promising solution to this problem, however, given its data-hungry nature and the scarcity of expert-annotated datasets, its advantage over traditional machine learning methods in identifying motion-corrupted brain scans is yet to be determined.

T cell immunity ameliorates COVID-19 disease severity and provides post-exposure prophylaxis after peptide-vaccination, in Syrian hamsters.

Background: The emergence of novel SARS-CoV-2 variants that resist neutralizing antibodies drew the attention to cellular immunity and calls for the development of alternative vaccination strategies to combat the pandemic. Here, we have assessed the kinetics of T cell responses and protective efficacy against severe COVID-19 in pre- and post-exposure settings, elicited by PolyPEPI-SCoV-2, a peptide based T cell vaccine.

Methods: 75 Syrian hamsters were immunized subcutaneously with PolyPEPI-SCoV-2 on D0 and D14.