Search NASA⌕ Search

Engineering topics

Li, Yin

Publications and source records attributed to Li, Yin.

Overexpression of the Mas1 gene mitigated LPS-induced inflammatory injury in mammary epithelial cells by inhibiting the NF-κB/MAPKs signaling pathways

Breast infection is the primary etiology of mastitis in dairy cows, leading to a reduction in the quality of dairy products and resulting in substantial economic losses for animal husbandry. Although antibiotic treatment can eliminate the pathogenic microorganisms that induce mastitis, it cannot repair the inflammatory damage of mammary epithelial cells and blood milk barrier. Mas1 is a G protein-coupled receptor, and its role in lipopolysaccharide (LPS) -induced inflammatory injury to mammary epithelial cells has not been studied. LPS treatment of EpH4 EV cells led to a significant downregulation of Mas1 transcript levels, which attracted our great interest, suggesting that Mas1 may be an important target for the treatment of mastitis. Therefore, this study intends to verify the role of Mas1 in the inflammatory injury of EpH4 EV cells by gene overexpression technology and gene silencing technology. The findings demonstrated that the overexpression of the Mas1 gene effectively reversed the activation of the nuclear factor-κB/mitogen-activated protein kinase (NF-κB/MAPK) signaling pathways induced by LPS, while also suppressing the upregulation of pro-inflammatory mediators. Furthermore, overexpression of the Mas1 gene reversed the downregulation of zonula occludens 1 (ZO-1), Occludin, and Claudin-3 caused by LPS, suggesting that Mas1 could promote to repair the blood-milk barrier. However, the silencing of the Mas1 gene using siRNA resulted in a contrasting effect. These results indicated that Mas1 alleviated the inflammatory injury of mammary epithelial cells induced by LPS.

Yan, Shuping↗

A differentiable perturbation-based weak lensing shear estimator

Upcoming imaging surveys will use weak gravitational lensing to study the large-scale structure of the Universe, demanding sub-per cent accuracy for precise cosmic shear measurements. We present a new differentiable implementation of our perturbation-based shear estimator (fpfs), using jax, which is publicly available as part of a new suite of analytic shear algorithms called anacal. This code can analytically calibrate the shear response of any non-linear observable constructed with the fpfs shapelets and detection modes utilizing autodifferentiation (ad), generalizing the formalism to include a family of shear estimators with corrections for detection and selection biases. Using the ad capability of jax, it calculates the full Hessian matrix of the non-linear observables, which improves the previously presented second-order noise bias correction in the shear estimation. As an illustration of the power of the new anacal framework, we optimize the effective galaxy number density in the space of the generalized shear estimators using an LSST-like galaxy image simulation for the 10 yr LSST. For the generic shear estimator, the magnitude of the multiplicative bias |m| is below 3 × 10 –3 (99.7 per cent confidence interval), and the effective galaxy number density is improved by 5 per cent. We also discuss some planned future additions to the anacal software suite to extend its applicability beyond the fpfs measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗