Research on the Correlation between Neuronal Damage and Drug Resistance Gene Product P-Gp Following Status Epilepsy

2012 ◽  
Vol 550-553 ◽  
pp. 1010-1013
Author(s):  
Song Yan Liu ◽  
Rui Tao Mao ◽  
Hua Cai ◽  
Xue Mei Han
Keyword(s):  
Drug Resistance ◽  
Image Analysis ◽  
Status Epilepticus ◽  
Neuronal Damage ◽  
Intractable Epilepsy ◽  
Neuronal Injury ◽  
Control Group ◽  
Analysis Method ◽  
Image Analysis Method ◽  
P Glycoprotein

Objective: To study the association between neuronal injury following status epilepsy and expression of P-glycoprotein, discuss the association between intractable epilepsy and neuronal injury. Method: To establish a mice status epilepticus model by lithium-pilocarpine injected intraperitoneal, The mice were randomly divided into control group 6h, 12h, 1d, 3d, 5d and 7d after status epilepticus(SE) .To research the neuronal injury by image analysis method, expression of P-gp in blood was studied by flow cyometry .To analyze the association between neuronal injury and expression of P-gp by Pearson statistics. Result: The neuronal injury was observed after status epilepsy. Neuronal injury is most obvious 3-7 days after status epilepsy, expression of P-gp increased simultaneously. The severity of neuronal injury has a positive correlation to expression of P-gp. Conclusion: Association between intractable epilepsy and neuronal injury exists.

scholarly journals Automated image analysis method for oil-release test of lipid-based materials

MethodsX ◽  
2021 ◽  
pp. 101447
Author(s):  
Fabio Valoppi ◽  
Petri Lassila ◽  
Ari Salmi ◽  
Edward Haeggström
Keyword(s):  
Image Analysis ◽  
Automated Image Analysis ◽  
Analysis Method ◽  
Image Analysis Method ◽  
Release Test

A Computerized Image Analysis Method for Measuring Elastic Tissue.

1989 ◽  
Vol 93 (3) ◽  
pp. 358-362 ◽  
Author(s):  
Thomas J. Flotte ◽  
Johanna M. Seddon ◽  
Yuqing Zhang ◽  
Robert J. Glynn ◽  
Kathleen M. Egan ◽  
...  
Keyword(s):  
Image Analysis ◽  
Elastic Tissue ◽  
Analysis Method ◽  
Image Analysis Method ◽  
Computerized Image Analysis

ASSESSMENT OF OSTEOARTHRITIS INITIATIVE–KELLGREN AND LAWRENCE SCORING PROJECTS QUALITY USING COMPUTER ANALYSIS

2010 ◽  
Vol 13 (04) ◽  
pp. 197-201 ◽  
Author(s):  
Lior Shamir ◽  
David T. Felson ◽  
Luigi Ferrucci ◽  
Ilya G. Goldberg
Keyword(s):  
Image Analysis ◽  
Gold Standard ◽  
Population Studies ◽  
Detection Accuracy ◽  
X Rays ◽  
Analysis Method ◽  
Image Analysis Method ◽  
X Ray ◽  
Osteoarthritis Initiative ◽  
Kellgren And Lawrence

The detection of knee osteoarthritis (OA) is a subjective task, and even two highly experienced and well-trained readers might not always agree on a specific case. This problem is noticeable in OA population studies, in which different scoring projects provide significantly different scores for the same knee X-rays. Here we propose a method for quantitative assessment and comparison of knee X-ray scoring projects in OA population studies. The method works by applying an image analysis method that automatically detects OA in knee X-ray images, and comparing the consistency of the scores when using each of the scoring projects as "gold standard." The method was applied to compare the osteoarthritis initiative (OAI) clinic reading derived Kellgren and Lawrence (K&L) scores to central reading, and showed that when using the derived K&L scores the automatic image analysis method was able to accurately differentiate between healthy joints and moderate OA joints in ~70% of the cases. When the OAI central reading scores were used as gold standard, the detection accuracy was elevated to ~77%. These results show that the OAI central readings scores are more consistent with the X-rays, indicating that the central reading better reflects the radiographic features associated with OA, compared to the OAI K&L scores derived from clinic readings.

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