The presence and impact of herpes virus DNA in recipient cornea and aqueous humor on graft survival following penetrating keratoplasty
JOURNAL OF THE FORMOSAN MEDICAL ASSOCIATION
Authors: Jeng, Yu-Ting; Tsai, Ching-Yao; Kuo, Li-Lin; Woung, Lin-Chung; Lin, Shu-Yi; Tsai, I-Lun
Abstract
Background/Purpose: Reactivation of herpes viruses poses threat to corneal graft survival. This study evaluated the presence of herpes simplex virus type 1 (HSV-1), HSV type 2 (HSV-2), and cytomegalovirus (CMV) DNA in recipient corneas and the aqueous humor of patients undergoing penetrating keratoplasty (PKP), and the impact on graft survival. Methods: This retrospective study reviewed 90 eyes of 71 patients underwent PKP between 2008 and 2016. Cornea and aqueous humor samples were sent for polymerase chain reaction (PCR) testing for viral DNA. The main outcomes were PCR results and graft survival. Results: Recipient corneas tested positive for HSV-1 in 47 eyes (52.2%), for HSV-2 in 24 eyes (26.7%), and for CMV in seven eyes (7.8%). Aqueous humor tested positive for HSV-1 in 44 eyes (48.9%), for HSV-2 in 25 eyes (27.8%), and for CMV in eight eyes (8.9%). The presence of aqueous HSV-1 DNA was associated with higher risk of graft failure (p = 0.005), whereas corneal HSV-1 DNA was not. The presence of HSV-2 DNA had no significant impact on graft survival. Aqueous CMV DNA was associated with higher risk of graft failure in univariate model, but not in multivariate model. Conclusion: There were high positive rates of HSV-1, HSV-2, and CMV DNA in recipient corneas and aqueous humor at the time of PKP, even among patients not suspected of latent viral infection. The presence of aqueous HSV-1 DNA was associated with higher risk of graft failure. Copyright (C) 2019, Formosan Medical Association. Published by Elsevier Taiwan LLC.
Detection of abnormalities in wireless capsule endoscopy based on extreme learning machine
SIGNAL IMAGE AND VIDEO PROCESSING
Authors: Ellahyani, Ayoub; Jaafari, Ilyas El; Charfi, Said; Ansari, Mohamed El
Abstract
Wireless capsule endoscopy (WCE) is a device that can move through human body and capture the small bowel entirely. Thus, it is presented as an excellent diagnostic tool for evaluation of gastrointestinal diseases compared with traditional endoscopies. However, the diagnosis by the physicians is tedious since it requires reviewing the video extracted from the capsule and analysing all of its frames. This tedious task has fuelled the efforts of researchers to provide automated diagnostic techniques for WCE frameworks to detect symptoms of gastrointestinal illness. In this paper, a new computer-aided diagnosis method for abnormalities detection in WCE images is proposed. After a preprocessing step, we extract from these images the descriptor we feed to a kernel extreme learning machine to perform the classification process. The descriptor used in this work is a combination between the histogram of oriented gradients (HOG) that were extracted using the hue component of the HSV colour space, and a modified rotation-invariant local binary pattern. The proposed approach has been tested on different datasets, and the results obtained are satisfactory when compared to the state-of-the-art works.