Microvascular blood flow and skin temperature changes in the fingers following a deep inspiratory gasp

2002 ◽  
Vol 23 (2) ◽  
pp. 365-373 ◽  
Author(s):  
John Allen ◽  
John R Frame ◽  
Alan Murray
Keyword(s):  
Blood Flow ◽  
Skin Temperature ◽  
Microvascular Blood Flow ◽  
Temperature Changes

scholarly journals Contactless Monitoring of Microcirculation Reaction on Local Temperature Changes

2019 ◽  
Vol 9 (22) ◽  
pp. 4947 ◽  
Author(s):  
Volynsky ◽  
Margaryants ◽  
Mamontov ◽  
Kamshilin
Keyword(s):  
Blood Flow ◽  
Skin Temperature ◽  
Polarized Light ◽  
Thermal Exposure ◽  
Thermal Impact ◽  
Vasomotor Response ◽  
Temperature Changes ◽  
Custom Made ◽  
Electrocardiogram Ecg ◽  
System Operating

Assessment of skin blood flow is an important clinical task which is required to study mechanisms of microcirculation regulation including thermoregulation. Contactless assessment of vasomotor reactivity in response to thermal exposure is currently not available. The aim of this study is to show the applicability of the imaging photoplethysmography (IPPG) method to measure quantitatively the vasomotor response to local thermal exposure. Seventeen healthy subjects aged 23 ± 7 years participated in the study. A warm transparent compress applied to subject’s forehead served as a thermal impact. A custom-made IPPG system operating at green polarized light was used to monitor the subject’s face continuously and simultaneously with skin temperature and electrocardiogram (ECG) recordings. We found that the thermal impact leads to an increase in the amplitude of blood pulsations (BPA) simultaneously with the skin temperature increase. However, a multiple increase in BPA remained after the compress was removed, whereas the skin temperature returned to the baseline. Moreover, the BPA increase and duration of the vasomotor response was associated with the degree of external heating. Therefore, the IPPG method allows us to quantify the parameters of capillary blood flow during local thermal exposure to the skin. This proposed technique of assessing the thermal reactivity of microcirculation can be applied for both clinical use and for biomedical research.

Investigation of Gender Differences in Sleeping Comfort at Different Environmental Temperatures

2011 ◽  
Vol 21 (6) ◽  
pp. 811-820 ◽  
Author(s):  
Li Pan ◽  
Zhiwei Lian ◽  
Li Lan
Keyword(s):  
Gender Differences ◽  
Blood Flow ◽  
Sleep Quality ◽  
Ambient Temperature ◽  
Skin Temperature ◽  
Finger Blood Flow ◽  
Mean Skin Temperature ◽  
Finger Temperature ◽  
Temperature Changes ◽  
Subjective Evaluations

The purpose of this investigation was to determine whether there is gender difference in sleep comfort of healthy individuals at various temperatures. During winter, sleep quality was examined under different indoor temperatures (17, 20 and 23°C) using questionnaires and electroencephalogram (EEG). To explore the mechanism responsible for gender differences in comfortable sleeping temperatures, mean skin temperature, finger temperature and finger blood flow were measured. The results showed that females would prefer a higher ambient temperature during sleep than the men. The mean skin temperature for females was higher than that of males, whereas finger skin temperature and finger blood flow were significantly lower in females than in males. Furthermore, skin temperature and finger blood flow were more sensitive to ambient temperature with females than in males. The gender differences in preferred sleeping temperature could therefore be related to these physiological characteristics. Both subjective evaluations and EEG found better sleep quality in males under the same temperatures compared to females. Skin temperature changes over the course of the night also demonstrated longer periods of deep sleep in males compared to females.

Measuring Facial Skin Temperature Changes Caused by Mental Work-Load with Infrared Thermography

2016 ◽  
Vol 136 (11) ◽  
pp. 1581-1585 ◽  
Author(s):  
Tota Mizuno ◽  
Takeru Sakai ◽  
Shunsuke Kawazura ◽  
Hirotoshi Asano ◽  
Kota Akehi ◽  
...  
Keyword(s):  
Skin Temperature ◽  
Infrared Thermography ◽  
Work Load ◽  
Facial Skin ◽  
Mental Work ◽  
Temperature Changes ◽  
Mental Work Load

1715-P: Impaired Postprandial Adipose Tissue Microvascular Blood Flow in Healthy People with a Family History of Type 2 Diabetes

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 1715-P
Author(s):  
KATHERINE ROBERTS-THOMSON ◽  
RYAN D. RUSSELL ◽  
DONGHUA HU ◽  
TIMOTHY M. GREENAWAY ◽  
ANDREW C. BETIK ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Blood Flow ◽  
Adipose Tissue ◽  
Family History ◽  
Healthy People ◽  
Microvascular Blood Flow ◽  
History Of

Nitric oxide release in rat skeletal muscle capillary

1996 ◽  
Vol 270 (5) ◽  
pp. H1696-H1703 ◽  
Author(s):  
D. Mitchell ◽  
K. Tyml
Keyword(s):  
Nitric Oxide ◽  
Blood Flow ◽  
Leukocyte Adhesion ◽  
Microvascular Blood Flow ◽  
Capillary Length ◽  
Nitric Oxide Release ◽  
Longus Muscle ◽  
Potent Vasodilator ◽  
Capillary Bed ◽  
Synthase Inhibitor

Nitric oxide (NO) has been shown to be a potent vasodilator released from endothelial cells (EC) in large blood vessels, but NO release has not been examined in the capillary bed. Because the capillary bed represents the largest source of EC, it may be the largest source of vascular NO. In the present study, we used intravital microscopy to examine the effect of the NO synthase inhibitor, NG-nitro-L-arginine methyl ester (L-NAME), on the microvasculature of the rat extensor digitorum longus muscle. L-NAME (30 mM) applied locally to a capillary (300 micron(s) from the feeding arteriole) reduced red blood cell (RBC) velocity [VRBC; control VRBC = 238 +/- 58 (SE) micron/s; delta VRBC = -76 +/- 8%] and RBC flux (4.4 +/- 0.7 to 2.8 +/- 0.7 RBC/s) significantly in the capillary, but did not change feeding arteriole diameter (Dcon = 6.3 +/- 0.7 micron, delta D = 5 +/- 7%) or draining venule diameter (Dcon = 10.1 +/- 0.6 micron, delta D = 4 +/- 2%). Because of the VRBC change, the flux reduction was equivalent to an increased local hemoconcentration from 1.8 to 5 RBCs per 100 micron capillary length. L-NAME also caused an increase in the number of adhering leukocytes in the venule from 0.29 to 1.43 cells/100 micron. L-NAME (30 mM) applied either to arterioles or to venules did not change capillary VRBC. Bradykinin (BK) locally applied to the capillary caused significant increases in VRBC (delta VRBC = 111 +/- 23%) and in arteriolar diameter (delta D = 40 +/- 5%). This BK response was blocked by capillary pretreatment with 30 mM L-NAME (delta VRBC = -4 +/- 27%; delta D = 5 +/- 9% after BK). We concluded that NO may be released from capillary EC both basally and in response to the vasodilator BK. We hypothesize that 1) low basal levels of NO affect capillary blood flow by modulating local hemoconcentration and leukocyte adhesion, and 2) higher levels of NO (stimulated by BK) may cause a remote vasodilation to increase microvascular blood flow.

scholarly journals Two-step machine learning method for the rapid analysis of microvascular flow in intravital video microscopy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ossama Mahmoud ◽  
Mahmoud El-Sakka ◽  
Barry G. H. Janssen
Keyword(s):  
Machine Learning ◽  
Blood Flow ◽  
Human Error ◽  
Image Data ◽  
Video Microscopy ◽  
Microvascular Blood Flow ◽  
Image Processing Algorithm ◽  
Step Algorithm ◽  
3D Cnn

AbstractMicrovascular blood flow is crucial for tissue and organ function and is often severely affected by diseases. Therefore, investigating the microvasculature under different pathological circumstances is essential to understand the role of the microcirculation in health and sickness. Microvascular blood flow is generally investigated with Intravital Video Microscopy (IVM), and the captured images are stored on a computer for later off-line analysis. The analysis of these images is a manual and challenging process, evaluating experiments very time consuming and susceptible to human error. Since more advanced digital cameras are used in IVM, the experimental data volume will also increase significantly. This study presents a new two-step image processing algorithm that uses a trained Convolutional Neural Network (CNN) to functionally analyze IVM microscopic images without the need for manual analysis. While the first step uses a modified vessel segmentation algorithm to extract the location of vessel-like structures, the second step uses a 3D-CNN to assess whether the vessel-like structures have blood flowing in it or not. We demonstrate that our two-step algorithm can efficiently analyze IVM image data with high accuracy (83%). To our knowledge, this is the first application of machine learning for the functional analysis of microvascular blood flow in vivo.

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