A versatile toolbox for semi-automatic cell-by-cell object-based colocalization analysis.

Differential fluorescence labeling and multi-fluorescence imaging followed by colocalization analysis is commonly used to investigate cellular heterogeneity in situ. This is particularly important when investigating the biology of tissues with diverse cell types. Object-based colocalization analysis (OBCA) tools can employ automatic approaches, which are sensitive to errors in cell segmentation, or manual approaches, which can be impractical and tedious. Here, we present a novel set of tools for OBCA using a semi-automatic approach, consisting of two ImageJ plugins, a Microsoft Excel macro, and a MATLAB script. One ImageJ plugin enables customizable processing of multichannel 3D images for enhanced visualization of features relevant to OBCA, and another enables semi-automatic colocalization quantification. The Excel macro and the MATLAB script enable data organization and 3D visualization of object data across image series. The tools are well suited for experiments involving complex and large image data sets, and can be used in combination or as individual components, allowing flexible, efficient and accurate OBCA. Here we demonstrate their utility in immunohistochemical analyses of the developing central nervous system, which is characterized by complexity in the number and distribution of cell types, and by high cell packing densities, which can both create challenging situations for OBCA.

Molecular Profiling Defines Evolutionarily Conserved Transcription Factor Signatures of Major Vestibulospinal Neuron Groups.

Vestibulospinal neurons are organized into discrete groups projecting from brainstem to spinal cord, enabling vertebrates to maintain proper balance and posture. The two largest groups are the lateral vestibulospinal tract (LVST) group and the contralateral medial vestibulospinal tract (cMVST) group, with different projection lateralities and functional roles. In search of a molecular basis for these differences, we performed RNA sequencing on LVST and cMVST neurons from mouse and chicken embryos followed by immunohistofluorescence validation. Focusing on transcription factor (TF)-encoding genes, we identified TF signatures that uniquely distinguish the LVST from the cMVST group and further parse different rhombomere-derived portions comprising the cMVST group. Immunohistofluorescence assessment of the CNS from spinal cord to cortex demonstrated that these TF signatures are restricted to the respective vestibulospinal groups and some neurons in their immediate vicinity. Collectively, these results link the combinatorial expression of TFs to developmental and functional subdivisions within the vestibulospinal system.

Interaction-induced resonance in conductance and thermopower of quantum wires.

We study the effect of electron-electron interaction on the transport properties of short clean quantum wires adiabatically connected to reservoirs. Interactions lead to resonances in a multichannel wire at particular values of the Fermi energy. We investigate in detail the resonance in a two-channel wire. The (negative) conductance correction peaks at the resonance, and decays exponentially as the Fermi energy is tuned away, the resonance width being given by the temperature. Likewise, the thermopower shows a characteristic structure, which is surprisingly well approximated by the so-called Mott formula. Finally, fourfold splitting of the resonance in a magnetic field provides a unique signature of the effect.

On the Mott formula for the thermopower of non-interacting electrons in quantum point contacts.

We calculate the linear response thermopower S of a quantum point contact using the Landauer formula and therefore assume non-interacting electrons. The purpose of the paper is to compare analytically and numerically the linear thermopower S of non-interacting electrons to the low-temperature approximation, [Formula: see text], and the so-called Mott expression, [Formula: see text], where G(µ,T) is the (temperature-dependent) conductance. This comparison is important, since the Mott formula is often used to detect deviations from single-particle behaviour in the thermopower of a point contact.