Bowen Li

Oct 26, 2024 | biorxiv.org | Dong Liu |Xiaofeng Lu |Xiaoning Wang |Bowen Li

AbstractBackground: Sprouting blood vessels, reaching the aimed location, and establishing the proper connections are vital for building vascular networks. Such biological processes are subject to precise molecular regulation. So far, the mechanistic insights into understanding how blood vessels grow to the correct position are limited. In particular, the guiding cues and the signaling-originating cells remain elusive.

Oct 16, 2024 | nature.com | Bin Zheng |Bowen Li

AbstractAs a transdermal drug delivery method, microneedles offer minimal invasiveness, painlessness, and precise in-situ treatment. However, current microneedles rely on passive diffusion, leading to uncontrollable drug penetration. To overcome this, we developed a pneumatic microneedle patch that uses live Enterobacter aerogenes as microengines to actively control drug delivery.

Aug 5, 2024 | onlinelibrary.wiley.com | Lihua Chen |Hui Ming |Bowen Li |Chen Yang

Conflict of Interest The authors declare no conflict of interest. Supporting Information Filename Description smll202403869-sup-0001-SuppMat.docx9.7 MB Supporting Information References 1, , , , CA Cancer J Clin 2023, 73, 17. 2, , Int J Clin Exp Pathol 2020, 13, 1615. 3 Cancer Stat Facts: Cervical Cancer, (accessed: 20th October 2023), https://seer.cancer.gov/statfacts/html/cervix.html. 4, , , , , , , , , , , , , Adv. Sci. (Weinh) 2024, 11, 2308027.

Jun 28, 2024 | nature.com | Bowen Li |Jianzhong Chen

AbstractTransition metal-catalyzed asymmetric hydrogenation is one of the most efficient methods for the preparation of chiral α-substituted propionic acids. However, research on this method, employing cleaner earth-abundant metal catalysts, is still insufficient in both academic and industrial contexts.

Jun 19, 2024 | medium.com | Bowen Li

Learning note of linear regressionLinear regression aims to find the best-fit line for the data. It means the error between predicted values and actual values should be minimized. So, we need to calculate the best values for m and b to find the best fit line. See below:# The equation like below# y is the variable we are trying to predict# x is the variable used for prediction# m is the rate of change# b is the y-intercepty=mx+b In the context of the linear regression, m is weights.