ABSTRACT
Gravitational potentials that change in time induce fluctuations in the observed cosmic microwave background (CMB) temperature. Cosmological structure moving transverse to our line of sight provides a specific example known as the moving lens effect. Here, we explore how the observed CMB temperature fluctuations, combined with the observed matter overdensity, can be used to infer the transverse velocity of cosmological structures on large scales. We show that near-future CMB surveys and galaxy surveys will have the statistical power to make a first detection of the moving lens effect, and we discuss applications for the reconstructed transverse velocity.
ABSTRACT
Here we present a deep learning-based image analysis platform (DLAP), tailored to autonomously quantify cell numbers, and fluorescence signals within cellular compartments, derived from RNAscope or immunohistochemistry. We utilised DLAP to analyse subtypes of tyrosine hydroxylase (TH)-positive dopaminergic midbrain neurons in mouse and human brain-sections. These neurons modulate complex behaviour, and are differentially affected in Parkinson's and other diseases. DLAP allows the analysis of large cell numbers, and facilitates the identification of small cellular subpopulations. Using DLAP, we identified a small subpopulation of TH-positive neurons (~5%), mainly located in the very lateral Substantia nigra (SN), that was immunofluorescence-negative for the plasmalemmal dopamine transporter (DAT), with ~40% smaller cell bodies. These neurons were negative for aldehyde dehydrogenase 1A1, with a lower co-expression rate for dopamine-D2-autoreceptors, but a ~7-fold higher likelihood of calbindin-d28k co-expression (~70%). These results have important implications, as DAT is crucial for dopamine signalling, and is commonly used as a marker for dopaminergic SN neurons.