Clearing the path for whole-mount labeling and quantification of neuron and vessel density in adipose tissue.

 0 Người đánh giá. Xếp hạng trung bình 0

Tác giả: Pia Benedikt-Kühnast, Sandra Eder, Tobias Eisenberg, Sebastian Forstreiter, Gernot F Grabner, Arvand Haschemi, Michaela Lang, Thomas Rattei, Thomas Rauchenwald, Roko Sango, Martina Schweiger, Heimo Wolinski

Ngôn ngữ: eng

Ký hiệu phân loại: 006.31 Machine learning

Thông tin xuất bản: England : Journal of cell science , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 177510

 White adipose tissue (WAT) comprises a plethora of cell types beyond adipocytes forming a regulatory network that ensures systemic energy homeostasis. Intertissue communication is facilitated by metabolites and signaling molecules that are spread by vasculature and nerves. Previous works have indicated that WAT responds to environmental cues by adapting the abundance of these 'communication routes'
  however, the high intra-tissue heterogeneity questions the informative value of bulk or single-cell analyses and underscores the necessity of whole-mount imaging. The applicability of whole-mount WAT-imaging is currently limited by two factors - (1) methanol-based tissue clearing protocols restrict the usable antibody portfolio to methanol-resistant antibodies and (2) the vast amounts of data resulting from 3D imaging of whole-tissue samples require high computational expertise and advanced equipment. Here, we present a protocol for whole-mount WAT clearing, overcoming the constraints of antibody-methanol sensitivity. Additionally, we introduce TiNeQuant (for 'tissue network quantifier') a Fiji tool for automated 3D quantification of neuron or vascular network density, which we have made freely available. Given TiNeQuants versatility beyond WAT, it simplifies future efforts studying neuronal or vascular alterations in numerous pathologies.
Tạo bộ sưu tập với mã QR

THƯ VIỆN - TRƯỜNG ĐẠI HỌC CÔNG NGHỆ TP.HCM

ĐT: (028) 36225755 | Email: tt.thuvien@hutech.edu.vn

Copyright @2024 THƯ VIỆN HUTECH