Sample collection and amino acids analysis of extracellular fluid of mouse brain slices with low flow push–pull perfusion

The Analyst ◽  
2015 ◽  
Vol 140 (19) ◽  
pp. 6563-6570 ◽  
Author(s):  
G. Ojeda-Torres ◽  
L. Williams ◽  
D. E. Featherstone ◽  
S. A. Shippy

Low flow push–pull perfusion is used to measure extracellular glutamate levels from mouse brain tissue slices.

2014 ◽  
Author(s):  
Giorgio Mattei ◽  
Irene Cristiani ◽  
Chiara Magliaro ◽  
Arti Ahluwalia

This study is aimed at characterizing soft tissue slices using a vibratome. In particular, the effect of two sectioning parameters (i.e. step size and sectioning speed) on resultant slice thickness was investigated for fresh porcine liver as well as for paraformaldehyde-fixed (PFA-fixed) and fresh murine brain. A simple framework for embedding, sectioning and imaging the slices was established to derive their thickness, which was evaluated through a purposely developed graphical user interface. Sectioning speed and step size had little effect on the thickness of fresh liver slices. Conversely, the thickness of PFA-fixed murine brain slices was found to be dependent on the step size, but not on the sectioning speed. In view of these results, fresh brain tissue was sliced varying the step size only, which was found to have a significant effect on resultant slice thickness. Although precision-cut slices (i.e. with regular thickness) were obtained for all the tissues, slice accuracy (defined as the match between the nominal step size chosen and the actual slice thickness obtained) was found to increase with tissue stiffness from fresh liver to PFA-fixed brain. This quantitative investigation can be very helpful for establishing the most suitable slicing setup for a given tissue.


Author(s):  
Jiwoon Kwon ◽  
Sung J. Lee ◽  
Ghatu Subhash ◽  
Michael King ◽  
Malisa Sarntinoranont

Shock-induced traumatic brain injury (TBI) and post traumatic stress disorder (PTSD) have received increasing attention because many soldiers returning from Iraq and Afghanistan suffer from these disorders. The shock loading duration is typically on the order of few hundred microseconds and hence the strain rate of deformation is very high. Therefore, in the current study, high-rate loading experiments were conducted on brain tissue slices which mimic loading durations encountered in shock loading [1]. The polymer split Hopkinson pressure bar (PSHPB) was used to generate high rate loading as a high speed digital camera captured the deformation of brain tissue. To further clarify initial injury events, post-test damage was assessed through histological studies. This experimental model provides the opportunity for time-resolved visualization of actual tissue deformation thus allowing improved ability to isolate damage-sensitive tissue regions.


2014 ◽  
Author(s):  
Giorgio Mattei ◽  
Irene Cristiani ◽  
Chiara Magliaro ◽  
Arti Ahluwalia

This study is aimed at characterizing soft tissue slices using a vibratome. In particular, the effect of two sectioning parameters (i.e. step size and sectioning speed) on resultant slice thickness was investigated for fresh porcine liver as well as for paraformaldehyde-fixed (PFA-fixed) and fresh murine brain. A simple framework for embedding, sectioning and imaging the slices was established to derive their thickness, which was evaluated through a purposely developed graphical user interface. Sectioning speed and step size had little effect on the thickness of fresh liver slices. Conversely, the thickness of PFA-fixed murine brain slices was found to be dependent on the step size, but not on the sectioning speed. In view of these results, fresh brain tissue was sliced varying the step size only, which was found to have a significant effect on resultant slice thickness. Although precision-cut slices (i.e. with regular thickness) were obtained for all the tissues, slice accuracy (defined as the match between the nominal step size chosen and the actual slice thickness obtained) was found to increase with tissue stiffness from fresh liver to PFA-fixed brain. This quantitative investigation can be very helpful for establishing the most suitable slicing setup for a given tissue.


1970 ◽  
Vol 120 (2) ◽  
pp. 345-351 ◽  
Author(s):  
D. D. Clarke ◽  
W. J. Nicklas ◽  
S. Berl

1. The effect of fluoroacetate and fluorocitrate on the compartmentation of the glutamate–glutamine system was studied in brain slices with l-[U-14C]glutamate, l-[U-14C]aspartate, [1-14C]acetate and γ-amino[1-14C]butyrate as precursors and in homogenates of brain tissue with [1-14C]acetate. The effect of fluoroacetate was also studied in vivo in mouse brain with [1-14C]acetate as precursor. 2. Fluoroacetate and fluorocitrate inhibit the labelling of glutamine from all precursors but affect the labelling of glutamate to a much lesser extent. This effect is not due to inhibition of glutamine synthetase. It is interpreted as being due to selective inhibition of the metabolism of a small pool of glutamate that preferentially labels glutamine.


The fate of uniformly labelled 14 C glucose in rat-brain slices has been followed by a quantitative application of the radio paper-chromatography technique. After 60 min incubation with brain tissue approximately 60% of the glucose disappearing from the medium was accounted for as lactic acid, about 20% as CO 2 and most of the remainder as free amino-acids. Of the total glucose metabolized approximately 9% was converted into glutamic acid, 1.5% alanine, 3% γ -amino-butyric acid and 2.4% aspartic acid. Glutamic acid was the first of the amino-acids to be formed from glucose, and was detectable after 3 min incubation of brain tissue with 14 C glucose. Insulin had no effect on glucose metabolism in brain slices. Under anaerobic conditions the total glucose metabolized by brain slices was only about 10% of that found under aerobic conditions; of the total glucose disappearing from the medium anaerobically about 80% was accounted for as lactic acid and the remainder as free unchanged glucose in the tissue cells.


ACS Omega ◽  
2020 ◽  
Vol 5 (46) ◽  
pp. 29698-29705
Author(s):  
Yuansen Guo ◽  
Tunan Chen ◽  
Shi Wang ◽  
Xiaojie Zhou ◽  
Hua Zhang ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document