Impaired dynamics of precapillary sphincters and pericytes at first-order capillaries predict reduced neurovascular function in the aging mouse brain

Changsi Cai 07d472bacc Update 'datacite.yml' 1 год назад
All_Data_v2.xlsx ff086f32cd Upload files to '' 1 год назад
AmiraDataAnalysis.rar add77ce1fe Upload files to '' 1 год назад
DiameterMeasurement.rar bff0d72370 Upload files to '' 1 год назад
IHCAnalysis.rar ffa271c229 Upload files to '' 1 год назад
LICENSE 65f3091f58 Initial commit 1 год назад
MathModel.rar 134533eb78 Upload files to '' 1 год назад
README.md 62c85fdecf Update 'README.md' 1 год назад
datacite.yml 07d472bacc Update 'datacite.yml' 1 год назад

README.md

NATAGING-L01111B

If you have any questions, please contact Changsi Cai, ccai@sund.ku.dk

Impaired dynamics of precapillary sphincters and pericytes at first-order capillaries predict reduced neurovascular function in the aging mouse brain

This folder contains both the raw data and code for data analysis.

All raw data related to the publications are collected in the excel file 'All_Data_v2'

There are four rar code packages for data analysis.

(1) AmiraDataAnalysis.rar

Please unzip the file and load 'RawDataAnl_Vol3_Allcount3_NEW.m' into MATLAB.
This code helps analyze the Amira 3D vasculature shown in Figure 4.

(2) DiameterMeasurement.rar

Please unzip the file and load 'VesselDiameter_ByArea_GUI_MAIN.m' into MATLAB.
This code helps analyze vessel diameter change in 4D (xyzt) scanning.

(3) IHCAnalysis.rar

Please unzip the file and load 'GliaTrans_POI_GUI_MAIN.m' into MATLAB.
This code helps analyze the alpha-SMA density, pericyte and endothelial cell density from the immunohistochemical images in Figure 1.

(4) MathModel.rar

Please unzip the file and load 'amirachangsianal.py'into Python.
This code makes math model of existing vasculatures to estimate the blood pressure and flow at each vessel segment.
datacite.yml
Title Impaired dynamics of precapillary sphincters and pericytes at first-order capillaries predict reduced neurovascular function in the aging mouse brain
Authors Cai,Changsi;Department of Neuroscience, Faculty of Health and Medical Science, University of Copenhagen, 2200 Copenhagen, Denmark;ORCID: 0000-0002-7001-610X
Zambach,Stefan Andreas ;Department of Neuroscience, Faculty of Health and Medical Science, University of Copenhagen, 2200 Copenhagen, Denmark
Grubb,Søren;Department of Neuroscience, Faculty of Health and Medical Science, University of Copenhagen, 2200 Copenhagen, Denmark
Tao,Lechan;Department of Neuroscience, Faculty of Health and Medical Science, University of Copenhagen, 2200 Copenhagen, Denmark; School of Biomedical Engineering, Shanghai Jiao-Tong University, Shanghai, China
He,Chen;Department of Neuroscience, Faculty of Health and Medical Science, University of Copenhagen, 2200 Copenhagen, Denmark
Lind,Barbara Lykke ;Department of Neuroscience, Faculty of Health and Medical Science, University of Copenhagen, 2200 Copenhagen, Denmark
Thomsen,Kirsten Joan ;Department of Neuroscience, Faculty of Health and Medical Science, University of Copenhagen, 2200 Copenhagen, Denmark
Zhang,Xiao;Department of Neuroscience, Faculty of Health and Medical Science, University of Copenhagen, 2200 Copenhagen, Denmark
Hald,Bjørn Olav ;Department of Neuroscience, Faculty of Health and Medical Science, University of Copenhagen, 2200 Copenhagen, Denmark
Nielsen,Reena Murmu ;Department of Neuroscience, Faculty of Health and Medical Science, University of Copenhagen, 2200 Copenhagen, Denmark
Kim,Keyeon;Department of Neuroscience, Faculty of Health and Medical Science, University of Copenhagen, 2200 Copenhagen, Denmark
Devor,Anna ;Department of Biomedical Engineering, Boston University, Boston, USA; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA 02129, USA
Lønstrup,Micael ;Department of Neuroscience, Faculty of Health and Medical Science, University of Copenhagen, 2200 Copenhagen, Denmark
Lauritzen,Martin Johannes ;Department of Neuroscience, Faculty of Health and Medical Science, University of Copenhagen, 2200 Copenhagen, Denmark; Department of Clinical Neurophysiology, Rigshospitalet, 2100 Copenhagen, Denmark; Center for Healthy Aging, Faculty of Health and Medical Science, University of Copenhagen, 2200 Copenhagen, Denmark
Description The microvascular inflow tract (MIT), comprising the penetrating arterioles, precapillary sphincters, and first-order capillaries, is the bottleneck for brain blood flow and energy supply. Exactly how aging alters the structure and function of the MIT remains unclear. By in vivo 4-dimensional two-photon imaging, we reveal an age-dependent decrease in vaso-responsivity accompanied by a decrease in vessel density close to the arterioles and loss of vascular mural cell processes, though the number of mural cell somas and their αSMA density were preserved. The age-related reduction in vascular reactivity was mostly pronounced at precapillary sphincters, highlighting their crucial role in capillary blood flow regulation. Mathematical modeling revealed impaired pressure and flow control in aged mice during vasoconstriction. Interventions that preserve dynamics of cerebral blood vessels may ameliorate age-related decreases in blood flow and prevent brain frailty. This folder contains both the raw data and code for data analysis.All raw data related to the publications are collected in the excel file **All_Data_v2**. There are four rar code packages for data analysis. (1) **AmiraDataAnalysis.rar** Please unzip the file and load 'RawDataAnl_Vol3_Allcount3_NEW.m' into MATLAB. This code helps analyze the Amira 3D vasculature shown in Figure 4. (2) **DiameterMeasurement.rar** Please unzip the file and load 'VesselDiameter_ByArea_GUI_MAIN.m' into MATLAB. This code helps analyze vessel diameter change in 4D (xyzt) scanning. (3) **IHCAnalysis.rar** Please unzip the file and load 'GliaTrans_POI_GUI_MAIN.m' into MATLAB. This code helps analyze the alpha-SMA density, pericyte and endothelial cell density from the immunohistochemical images in Figure 1. (4) **MathModel.rar** Please unzip the file and load 'amirachangsianal.py'into Python. This code makes math model of existing vasculatures to estimate the blood pressure and flow at each vessel segment.
License Creative Commons CC0 1.0 Public Domain Dedication (https://creativecommons.org/publicdomain/zero/1.0/)
References Cai, C., Zambach, S.A., Grubb, S., Thomsen, K.J., Lind, B.L., Hald, B.O., Lønstrup, M., Nielsen, R.M., Lauritzen, M.J., 2021.BioRxiv. Impaired dynamics of brain precapillary sphincters and pericytes at first order capillaries explains reduced neurovascular functions in aging [doi: 10.1101/2021.08.05.455300 ] (IsSupplementTo)
Funding Lundbeck Foundation; R273-2017-1791 and R345-2020-1440 Danish Medical Research Council; 1133-00016A Alice Brenaa Foundation Augustinus Foundation; 19-2858 A. P. Møller Foundation; 20-L-0243 Novo Nordisk foundation; 0064289 Nordea Foundation Grant to the Center for Healthy Aging; 02-2017-1749
Keywords Neuroscience
neurovascular coupling
aging
Precapillary sphincters
pericytes
microcirculation
capillaries
cerebral blood flow
Resource Type Dataset