Two sympathetic nerve supplies to brown adipose tissue of the rat

1969 ◽  
Vol 47 (1) ◽  
pp. 57-63 ◽  
Author(s):  
D. M. Derry ◽  
E. Schönbaum ◽  
G. Steiner
Keyword(s):  
Blood Vessel ◽  
Blood Vessels ◽  
Sympathetic Nerve ◽  
Nerve Fibers ◽  
Brown Fat ◽  
Adrenergic Neurons ◽  
Small Vessels ◽  
Sympathetic Nerve Fibers ◽  
Brown Adipose ◽  
Intrinsic Ganglia

The fluorescent histochemical technique of Falck for demonstrating catecholamines in sympathetic nerve fibers was modified for use in brown fat. In normal interscapular and mediastinal brown fat, the nerve fibers surrounded the arterial Mood vessels and all parenchymal cells. Both immunosympathectomy and surgical denervation gave an almost identical histological picture of massive loss of nerves from the blood vessels only. The parenchymal innervation remained intact. The blood vessels retained single isolated nerve fibers, which were relatively more numerous on the small vessels and which were connected with the parenchymal innervation. After sympathetic nerve fibers were depleted of catecholamines by treating the rat with reserpine, the parenchymal nerves reestablished catecholamine fluorescence at a faster rate than the blood vessel nerves. Intrinsic (tissue) ganglia in the brown fat were resistant to immunosympathectomy. These ganglia contained cells which were very brightly fluorescent. These results indicate that there are two anatomically, immunologically, and pharmacologically different nerve supplies to brown fat, one to the blood vessels and the other predominantly to the parenchyma. It was concluded that the parenchymal nerve supply is derived from the intrinsic ganglia via 'short' adrenergic neurons, and the blood vessel innervation is derived from the sympathetic chain via 'long' adrenergic neurons.

Sympathetic nerve development in the brown adipose tissue of the rat

1970 ◽  
Vol 48 (3) ◽  
pp. 160-168 ◽  
Author(s):  
D. M. Berry ◽  
H. Daniel
Keyword(s):  
Blood Vessels ◽  
Sympathetic Nerve ◽  
Nerve Fibers ◽  
Sympathetic Chain ◽  
Fiber Network ◽  
Sympathetic Nerve Fibers ◽  
Arterial Blood ◽  
Brown Adipose ◽  
Catecholamine Fluorescence ◽  
Nerve Development

With the Falck fluorescent histochemical method for catecholamines, the development of sympathetic nerve fibers in the brown fat of the rat was studied. At birth a low level of catecholamine fluorescence was found in preterminal axon bundles, which have been called here sheathed axons. The fluorescence in these bundles reached a maximum at about 5 days of age. Parenchymal nerve catecholamine fluorescence was discernible at 2 to 3 days of age. These nerves progressively got brighter until adult levels had been reached at about 10–15 days. The sympathetic nerve fiber network seen on arterial blood vessels in the adult was not seen in the young rat until 8–10 days of age. These blood vessel nerves reached maturity at about 15–21 days. The parenchymal nerve innervation was shown to originate in the sympathetic chain. The sympathetic chain gave off sheathed axon bundles which reach the parenchyma by passing along septa or beside blood vessels.

Neural control of the kidney: functionally specific renal sympathetic nerve fibers

2000 ◽  
Vol 279 (5) ◽  
pp. R1517-R1524 ◽  
Author(s):  
Gerald F. DiBona
Keyword(s):  
Blood Vessels ◽  
Sympathetic Nerve ◽  
Neural Control ◽  
Afferent Input ◽  
Nerve Fibers ◽  
Granular Cells ◽  
Renal Sympathetic Nerve ◽  
Sympathetic Nerve Fibers ◽  
Reflex Arc ◽  
Renal Sympathetic

The sympathetic nervous system provides differentiated regulation of the functions of various organs. This differentiated regulation occurs via mechanisms that operate at multiple sites within the classic reflex arc: peripherally at the level of afferent input stimuli to various reflex pathways, centrally at the level of interconnections between various central neuron pools, and peripherally at the level of efferent fibers targeted to various effectors within the organ. In the kidney, increased renal sympathetic nerve activity regulates the functions of the intrarenal effectors: the tubules, the blood vessels, and the juxtaglomerular granular cells. This enables a physiologically appropriate coordination between the circulatory, filtration, reabsorptive, excretory, and renin secretory contributions to overall renal function. Anatomically, each of these effectors has a dual pattern of innervation consisting of a specific and selective innervation by unmyelinated slowly conducting C-type renal sympathetic nerve fibers in addition to an innervation that is shared among all the effectors. This arrangement permits the maximum flexibility in the coordination of physiologically appropriate responses of the tubules, the blood vessels, and the juxtaglomerular granular cells to a variety of homeostatic requirements.

scholarly journals Retinal Vessel Segmentation by Deep Residual Learning with Wide Activation

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Yuliang Ma ◽  
Xue Li ◽  
Xiaopeng Duan ◽  
Yun Peng ◽  
Yingchun Zhang
Keyword(s):  
Blood Vessel ◽  
Blood Vessels ◽  
Area Under The Curve ◽  
Retinal Vessel ◽  
Vessel Segmentation ◽  
Superior Performance ◽  
Retinal Blood Vessel ◽  
Low Contrast ◽  
Blood Vessel Segmentation ◽  
Small Vessels

Purpose. Retinal blood vessel image segmentation is an important step in ophthalmological analysis. However, it is difficult to segment small vessels accurately because of low contrast and complex feature information of blood vessels. The objective of this study is to develop an improved retinal blood vessel segmentation structure (WA-Net) to overcome these challenges. Methods. This paper mainly focuses on the width of deep learning. The channels of the ResNet block were broadened to propagate more low-level features, and the identity mapping pathway was slimmed to maintain parameter complexity. A residual atrous spatial pyramid module was used to capture the retinal vessels at various scales. We applied weight normalization to eliminate the impacts of the mini-batch and improve segmentation accuracy. The experiments were performed on the DRIVE and STARE datasets. To show the generalizability of WA-Net, we performed cross-training between datasets. Results. The global accuracy and specificity within datasets were 95.66% and 96.45% and 98.13% and 98.71%, respectively. The accuracy and area under the curve of the interdataset diverged only by 1%∼2% compared with the performance of the corresponding intradataset. Conclusion. All the results show that WA-Net extracts more detailed blood vessels and shows superior performance on retinal blood vessel segmentation tasks.

Loss of sympathetic nerve fibers in vital intertrochanteric bone cylinders lateral to osteonecrosis of the femoral head

2013 ◽  
Vol 80 (2) ◽  
pp. 188-194 ◽  
Author(s):  
Johannes Beckmann ◽  
Matthias Knödl ◽  
Eva Bauser ◽  
Markus Tingart ◽  
Joachim Grifka ◽  
...  
Keyword(s):  
Femoral Head ◽  
Sympathetic Nerve ◽  
Nerve Fibers ◽  
Sympathetic Nerve Fibers

Topography and distribution of sympathetic nerve fibers in the rat temporomandibular joint: immunocytochemistry and ultrastructure

2001 ◽  
Vol 203 (5) ◽  
pp. 357-366 ◽  
Author(s):  
M. A. Kido ◽  
Jing-Qi Zhang ◽  
Harue Muroya ◽  
Takayoshi Yamaza ◽  
Yoshihiro Terada ◽  
...  
Keyword(s):  
Temporomandibular Joint ◽  
Sympathetic Nerve ◽  
Nerve Fibers ◽  
Sympathetic Nerve Fibers

Morphological Observation of Sympathetic Nerve Fibers in the Human Posterior Longitudinal Ligament

Spine ◽  
2014 ◽  
Vol 39 (26) ◽  
pp. 2119-2126 ◽  
Author(s):  
Haiyan Li ◽  
Xuexiao Ma ◽  
Xiaolin Wu ◽  
Fengxia Liu ◽  
Tengbo Yu ◽  
...  
Keyword(s):  
Sympathetic Nerve ◽  
Posterior Longitudinal Ligament ◽  
Nerve Fibers ◽  
Morphological Observation ◽  
Sympathetic Nerve Fibers
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