Publications by authors named "Kai-Kuo Wang"
The polyunsaturated fatty acids (PUFAs), particularly eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), are critical determinants of the nutritional quality of fish. To rapidly and non-destructively determine the muscular PUFAs in living fish, an accuracy technique is urgently needed. In this study, we combined skin hyperspectral imaging (HSI) and machine learning (ML) methods to assess the muscular PUFAs contents of common carp.
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- Fish cells, particularly grass carp kidney (CIK) cells, are more challenging to transfect compared to mammalian cells, necessitating a better gene delivery method.
- A novel nanocarrier made from α-lactalbumin (α-NC) was developed, showing effective absorption of nucleic acids and low toxicity, outperforming traditional liposomal transfection reagents.
- This system allowed for successful co-transfection of key genetic materials, resulting in a stable transgenic CIK cell line with integrated Cas9 and GFP, thus providing a streamlined approach for creating stable transgenic fish cell lines.
Article Synopsis
- The study investigates how DNA methylation and chromatin accessibility influence gene expression in the allotetraploid common carp, focusing on liver and muscle tissues.
- Researchers found significant differences in DNA methylation levels between the A and B subgenomes, but these differences did not correspond to biased gene expression patterns.
- The B subgenome displayed more open chromatin regions, leading to higher gene expression levels compared to the A subgenome, indicating that chromatin accessibility is a key factor in regulating subgenome expression dominance.
Article Synopsis
- Hyperspectral imaging (HSI) has been used to evaluate the texture of processed meats, but its effectiveness on live fish muscle, particularly in common carp, was previously untested.
- The study involved scanning skin regions of live common carp to collect hyperspectral data and measuring eight texture indicators for four different muscle regions.
- Machine learning models, especially BP-ANN, PLSR, and LS-SVM, were found to effectively predict muscle texture parameters from skin HSI data, leading to the creation of visual prediction maps for different muscle textures.