The precise annotation and accurate identification of neural structures are prerequisites for studying mammalian brain function. The orientation of neurons and neural circuits is usually determined by mapping brain images to coarse axial-sampling planar reference atlases. However, individual differences at the cellular level likely lead to position errors and an inability to orient neural projections at single-cell resolution. Here, we present a high-throughput precision imaging method that can acquire a co-localized brain-wide data set of both fluorescent-labelled neurons and counterstained cell bodies at a voxel size of 0.32 × 0.32 × 2.0 μm in 3 days for a single mouse brain. We acquire mouse whole-brain imaging data sets of multiple types of neurons and projections with anatomical annotation at single-neuron resolution. The results show that the simultaneous acquisition of labelled neural structures and cytoarchitecture reference in the same brain greatly facilitates precise tracing of long-range projections and accurate locating of nuclei.

PurposeThe paper aims to examine the impact of ownership structure and board composition on voluntary disclosures of listed companies in China.Design/methodology/approachUsing an OLS‐regression model to test the relationship among ownership structure, board composition and the level of voluntary disclosure. The sample is based on 559 firm observations in 2002.FindingsHigher blockholder ownership and foreign listing/shares ownership is associated with increased disclosure. However, managerial ownership, state ownership, and legal‐person ownership are not related to disclosure. An increase in independent directors increases corporate disclosure and CEO duality is associated with lower disclosure. The paper also finds that larger firms had greater disclosure, while firms with growth opportunities are reluctant to disclose information voluntarily.Research limitations/implicationsFirstly, the sample is comprised of companies listed on Shanghai Stock Exchange in 2002 and only 45.7 percent of representative firms listed in China. Secondly, the disclosure checklist does not cover all voluntary disclosure in corporations as employed and supported in several prior studies. Thirdly, the award of checklist items may be subjected to errors.Practical implicationsThis paper indicates the relationship among ownership structure, board composition and corporate voluntary disclosure, and provides evidence for Chinese regulators to improve corporate governance and optimize ownership structure.Originality/valueDistinct from prior empirical research based on disclosure behavior in developed‐western markets, this study examines the impact of ownership structure and board composition on voluntary disclosures of listed companies in the Asian setting of China.

Dendritic and axonal morphology reflects the input and output of neurons and is a defining feature of neuronal types1,2, yet our knowledge of its diversity remains limited. Here, to systematically examine complete single-neuron morphologies on a brain-wide scale, we established a pipeline encompassing sparse labelling, whole-brain imaging, reconstruction, registration and analysis. We fully reconstructed 1,741 neurons from cortex, claustrum, thalamus, striatum and other brain regions in mice. We identified 11 major projection neuron types with distinct morphological features and corresponding transcriptomic identities. Extensive projectional diversity was found within each of these major types, on the basis of which some types were clustered into more refined subtypes. This diversity follows a set of generalizable principles that govern long-range axonal projections at different levels, including molecular correspondence, divergent or convergent projection, axon termination pattern, regional specificity, topography, and individual cell variability. Although clear concordance with transcriptomic profiles is evident at the level of major projection type, fine-grained morphological diversity often does not readily correlate with transcriptomic subtypes derived from unsupervised clustering, highlighting the need for single-cell cross-modality studies. Overall, our study demonstrates the crucial need for quantitative description of complete single-cell anatomy in cell-type classification, as single-cell morphological diversity reveals a plethora of ways in which different cell types and their individual members may contribute to the configuration and function of their respective circuits.