Synthetic protein circuits for programmable control of mammalian cell death.

Natural cell death pathways such as apoptosis and pyroptosis play dual roles: they eliminate harmful cells and modulate the immune system by dampening or stimulating inflammation. Synthetic protein circuits capable of triggering specific death programs in target cells could similarly remove harmful cells while appropriately modulating immune responses. However, cells actively influence their death modes in response to natural signals, making it challenging to control death modes.

An Intelligent Framework for Fault Diagnosis of Centrifugal Pump Leveraging Wavelet Coherence Analysis and Deep Learning.

This paper proposes an intelligent framework for the fault diagnosis of centrifugal pumps (CPs) based on wavelet coherence analysis (WCA) and deep learning (DL). The fault-related impulses in the CP vibration signal are often attenuated due to the background interference noises, thus affecting the sensitivity of the traditional statistical features towards faults. Furthermore, extracting health-sensitive information from the vibration signal needs human expertise and background knowledge.

The microenvironment dictates glycocalyx construction and immune surveillance.

Efforts to identify anti-cancer therapeutics and understand tumor-immune interactions are built with models that do not match the microenvironmental characteristics of human tissues. Using models which mimic the physical properties of healthy or cancerous tissues and a physiologically relevant culture medium, we demonstrate that the chemical and physical properties of the microenvironment regulate the composition and topology of the glycocalyx. Remarkably, we find that cancer and age-related changes in the physical properties of the microenvironment are sufficient to adjust immune surveillance via the topology of the glycocalyx, a previously unknown phenomenon observable only with a physiologically relevant culture medium.

Design of a mucin-selective protease for targeted degradation of cancer-associated mucins.

Targeted protein degradation is an emerging strategy for the elimination of classically undruggable proteins. Here, to expand the landscape of targetable substrates, we designed degraders that achieve substrate selectivity via recognition of a discrete peptide and glycan motif and achieve cell-type selectivity via antigen-driven cell-surface binding. We applied this approach to mucins, O-glycosylated proteins that drive cancer progression through biophysical and immunological mechanisms.