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Mutation of the Catalytic Cysteine in Anopheles gambiae Transglutaminase 3 (AgTG3) Abolishes Plugin Crosslinking Activity without Disrupting Protein Folding Properties

Pham et al. | May 02, 2014

Mutation of the Catalytic Cysteine in <em>Anopheles gambiae</em> Transglutaminase 3 (AgTG3) Abolishes Plugin Crosslinking Activity without Disrupting Protein Folding Properties

Malaria is a major public health issue, especially in developing countries, and vector control is a major facet of malaria eradication efforts. Recently, sterile insect technique (SIT), or the release of sterile mosquitoes into the wild, has shown significant promise as a method of keeping vector populations under control. In this study, the authors investigate the Anopheles gambiae transglutaminase 3 protein (AgT3), which is essential to the mating of the Anopheles mosquito. They show that an active site mutation is able to abolish the activity of the AgT3 enzyme and propose it as a potential target for chemosterilant inhibitors.

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Machine learning predictions of additively manufactured alloy crack susceptibilities

Gowda et al. | Nov 12, 2024

Machine learning predictions of additively manufactured alloy crack susceptibilities

Additive manufacturing (AM) is transforming the production of complex metal parts, but challenges like internal cracking can arise, particularly in critical sectors such as aerospace and automotive. Traditional methods to assess cracking susceptibility are costly and time-consuming, prompting the use of machine learning (ML) for more efficient predictions. This study developed a multi-model ML pipeline that predicts solidification cracking susceptibility (SCS) more accurately by considering secondary alloy properties alongside composition, with Random Forest models showing the best performance, highlighting a promising direction for future research into SCS quantification.

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Mathematical modeling of plant community composition for urban greenery plans

Fang et al. | Jul 05, 2023

Mathematical modeling of plant community composition for urban greenery plans
Image credit: CHUTTERSNAP

Here recognizing the importance of urban green space for the health of humans and other organisms, the authors investigated if mathematical modeling can be used to develop an urban greenery management plan with high eco-sustainability by calculating the composition of a plant community. They optimized and tested their model against green fields in a Beijing city park. Although the compositions predicted by their models differed somewhat from the composition of testing fields, they conclude that by using a mathematical model such as this urban green space can be finely designed to be ecologically and economically sustainable.

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