Increased tryptophan (Trp) catabolism in the tumor microenvironment (TME) can mediate immune suppression by upregulation of interferon (IFN)-γ-inducible indoleamine 2,3-dioxygenase (IDO1) and/or ectopic expression of the predominantly liver-restricted enzyme tryptophan 2,3-dioxygenase (TDO). Whether these effects are due to Trp depletion in the TME or mediated by the accumulation of the IDO1 and/or TDO (hereafter referred to as IDO1/TDO) product kynurenine (Kyn) remains controversial. Here we show that administration of a pharmacologically optimized enzyme (PEGylated kynureninase; hereafter referred to as PEG-KYNase) that degrades Kyn into immunologically inert, nontoxic and readily cleared metabolites inhibits tumor growth. Enzyme treatment was associated with a marked increase in the tumor infiltration and proliferation of polyfunctional CD8 lymphocytes. We show that PEG-KYNase administration had substantial therapeutic effects when combined with approved checkpoint inhibitors or with a cancer vaccine for the treatment of large B16-F10 melanoma, 4T1 breast carcinoma or CT26 colon carcinoma tumors. PEG-KYNase mediated prolonged depletion of Kyn in the TME and reversed the modulatory effects of IDO1/TDO upregulation in the TME.

Peripheral nerve regeneration remains one of the greatest challenges in regenerative medicine. Deprivation of sensory and/or motor functions often occurs with severe injuries even treated by the most advanced microsurgical intervention. Although electrical stimulation represents an essential nonpharmacological therapy that proved to be beneficial for nerve regeneration, the postoperative delivery at surgical sites remains daunting. Here, a fully biodegradable, self-electrified, and miniaturized device composed of dissolvable galvanic cells on a biodegradable scaffold is achieved, which can offer both structural guidance and electrical cues for peripheral nerve regeneration. The electroactive device can provide sustained electrical stimuli beyond intraoperative window, which can promote calcium activity, repopulation of Schwann cells, and neurotrophic factors. Successful motor functional recovery is accomplished with the electroactive device in behaving rodent models. The presented materials options and device schemes provide important insights into self-powered electronic medicine that can be critical for various types of tissue regeneration and functional restoration.

Illuminating interactions between proteins and small drug molecules is a long-standing challenge in the field of drug discovery. Despite the importance of understanding these interactions, most previous works are limited by hand-designed scoring functions and insufficient conformation sampling. The recently-proposed graph neural network-based methods provides alternatives to predict protein-ligand complex conformation in a one-shot manner. However, these methods neglect the geometric constraints of the complex structure and weaken the role of local functional regions. As a result, they might produce unreasonable conformations for challenging targets and generalize poorly to novel proteins. In this paper, we propose Trigonometry-Aware Neural networKs for binding structure prediction, TANKBind, that builds trigonometry constraint as a vigorous inductive bias into the model and explicitly attends to all possible binding sites for each protein by segmenting the whole protein into functional blocks. We construct novel contrastive losses with local region negative sampling to jointly optimize the binding interaction and affinity. Extensive experiments show substantial performance gains in comparison to state-of-the-art physics-based and deep learning-based methods on commonly-used benchmark datasets for both binding structure and affinity predictions with variant settings. We release our code at https://github.com/luwei0917/TankBind.

The technique of the multiple phase encoding for optical security and verification systems is presented in this paper. This technique is based on a 4-f optical correlator that is a common architecture for optical image encryption and verification systems. However, two or more phase masks are iteratively retrieved by use of the proposed multiple phases retrieval algorithm (MPRA) to obtain the target image. The convergent speed of the iteration process in the MPRA is significantly increased and the recovered image is much more similar to the target image than those in previous approaches. In addition, the quantization effects due to the finite resolution of the phase levels in practical implementation are discussed. The relationships between the number of phase masks and the quantized phase levels are also investigated. According to the simulation results, two and three phase masks are enough to design an efficient security verification system with 64 and 32 phase levels, respectively.