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First-time Reported Detecting Cats’ Kidney Disease from Common Cat Litter Innovation Research Made in Taiwan

In modern society, many people have cats as members in their family. It is a duty of the owner to pay attention to cats’ healthy conditions. However, with a busy schedule, owners have difficulty to notice the change of cats’ behaviors, hence may ignore the alert signal of cats’ disease. For elder cats, the most common disease is kidney disease. There are 4 stages in cats’ kidney disease. If the disease can be detected in earlier stage, with proper treatment, the kidney disease can be well controlled to slow down the illness progression. In our team, for the first time all around the world, we used common cat litters to detect cats’ urine urea concentration and to detect cats’ kidney disease. The work was led by Prof. Hsiao-Wen Zan from Department of Photonics, NCTU, Prof. Hsin-Fei Meng from Institute of Physics, NCTU, and Vice Dean Ming-Ju Huang from Jong-Shing Animal Hospital. The detection technology is our previously developed “Dual Optical Fiber Reaction Tank”. We link two optical fibers with a 3D-printed reaction tank, to-gether with a commercial low-cost LED and a photo detector, to realize a real-time detection system. The set-up was reported in Biosensors and Bioelectronics, a leading journal in biosensor field, in 2019.

 

In the “Dual Optical Fiber Reaction Tank”, we demonstrated a stable, real-time, and robust sys-tem to detect urea concentration. In most optical-fiber-based biosensing systems, the optical sig-nal coupling is crucial and slight vibration may affect the coupling to generate noise signal. In our set-up, the liquid in the reaction tank serves as wave-guiding connector between two optical fibers. A rough alignment between the two fibers is already enough to build a stable system. Al-so, the influence from ambient light can be greatly suppressed. With this robust design, in our previous publication, the system was successfully used to detect the salivary urea in chronic kid-ney disease patients. Today, we also show that the system can be used to detect urine urea con-centration from cat litters. By taking a part of the cat litters, after washing and filtering, we ob-tain a clear solution as diluted urine. With a known cat litter, we establish the calibration curve by using artificial urea solutions. Then, the calibration curve can well explain the concentration of urine urea from the cat litter, and also well reflect the cat kidney disease. The proposed system can be used in Animal Clinics to quickly screen cats’ kidney disease. 

 

To further promote the in-home applications, in our ongoing work, we are developing a urea de-tecting probe by collaborating with our long-term collaborator, Dr. Olivier Soppera in CNRS IS2M, France. We have co-supervised many PhD students to develop a unique “photo-direct-write” semiconductor technology. Such a “photo-direct-write” technology can form semiconduc-tor devices on an arbitrary substrate, hence is very suitable to fabricate an integrated sensing probe. In our prior reports, we already demonstrated DUV-laser-write IGZO transistor and the Two-Photon NIR Laser graphene-like conductive carbon in TiO2. In 2020, we are able to demonstrate the urea sensing probe for in-home cat litter detection.

 

The above mentioned inter-disciplinary and international collaborations are both supported by MoST research projects. The results are published in leading journals such as Biosensors and Bioelectronics and Advanced Materials. The announced technology facilitates the development of non-invasive health detection for both human beings and for animals.

 

Reference on International Publication:
1. ”A low-cost, portable and easy-operated salivary urea sensor for point-of-care application”, Biosensors and Bioelectronics, vol. 132, 352-359, May 2019.   https://doi.org/10.1016/j.bios.2019.03.007

 

 

 

Media Contact

Shih Yu Huang
Dept. of Engineering and Technologies, MOST

syuhuang@most.gov.tw
+886-2-2737-7374

Related Link(s)

守護貓咪的健康—全球獨創!貓砂偵測腎病
Last Modified : 2020/01/14