Two alternative cell-surface display systems were developed in Pichia pastoris using the alpha-agglutinin and Flo1p (FS) anchor systems, respectively. Both the anchor cell wall proteins were obtained originally from Saccharomyces cerevisiae. Candida antarctica lipase B (CALB) was displayed functionally on the cell surface of P. pastoris using the anchor proteins alpha-agglutinin and FS. The activity of CALB displayed on P. pastoris was tenfold higher than that of S. cerevisiae. The hydrolytic and synthetic activities of CALB fused with alpha-agglutinin and FS anchored on P. pastoris were investigated. The hydrolytic activities of both lipases displayed on yeast cells surface were more than 200 U/g dry cell after 120 h of culture (200 and 270 U/g dry cell, respectively). However, the synthetic activity of CALB fused with alpha-agglutinin on P. pastoris was threefold higher than that of the FS fusion protein when applied to the synthesis of ethyl caproate. Similarly, the CALB displayed on P. pastoris using alpha-agglutinin had a higher catalytic efficiency with respect to the synthesis of other short-chain flavor esters than that displayed using the FS anchor. Interestingly, for some short-chain esters, the synthetic activity of displaying CALB fused with alpha-agglutinin on P. pastoris was even higher than that of the commercial CALB Novozyme 435.

A Pichia pastoris cell-surface display system was constructed using the Sed1 anchor system that has been developed in Saccharomyces cerevisiae. Candida antarctica lipase B (CALB) was used as the model protein and was fused to an anchor that consisted of 338 amino acids of Sed1. The resulting fusion protein CALBSed1 was expressed under the control of the alcohol oxidase 1 promoter (pAOX1). Immunofluorescence microscopy of immunolabeled Pichia pastoris revealed that CALB was displayed on the cell surface. Western blot analysis showed that the fusion protein CALBSed1 was attached covalently to the cell wall and was highly glycosylated. The hydrolytic activity of the displayed CALB was more than 220 U/g dry cells after 120 h of culture. The displayed protein also exhibited a higher degree of thermostability than free CALB.

Despite stringent power consumption requirements in many applications, over years organic light‐emitting diode (OLED) displays still suffer unsatisfactory energy efficiency due to poor light extraction. Approaches have been reported for OLED light out‐coupling, but they in general are not applicable for OLED displays due to difficulties in display image quality and fabrication complexity and compatibility. Thus to date, an effective and feasible light extraction technique that can boost efficiencies and yet keep image quality is still lacking and remains a great challenge. Here, a highly effective and scalable extraction‐enhancing OLED display pixel structure is proposed based on embedding the OLED inside a three‐dimensional reflective concave structure covered with a patterned high‐index filler. It can couple as much internal emission as possible into the filler region and then redirect otherwise confined light for out‐coupling. Comprehensive multi‐scale optical simulation validates that ultimately high light extraction efficiency approaching ≈80% and excellent viewing characteristics are simultaneously achievable with optimized structures using highly transparent top electrodes. This scheme is scalable and wavelength insensitive, and generally applicable to all red, green, and blue pixels in high‐resolution full‐color displays. Results of this work are believed to shed light on the development of future generations of advanced OLED displays.

Predicting the fluid behavior of complex microfluidic channel networks using convolutional neural networks.

green and red LED devices reached more than 20% in recent years, while the EQE of pure blue (460-470 nm) is still lower than 10%, [1b,3] which has greatly hindered the development of trichromatic display fields. Besides the structural optimizing of devices, designing stable and bright pure blue emissive MHPs via a simple and effective method is still a key part for improving the final EQE values.Three typical strategies for pure blue emissive perovskites are available: composition engineering (e.g., Br-Cl hybridization), quantum confinement strategy (e.g., synthesis of small size Br-based quantum dots), and dimensional engineering (e.g., quasi-two dimension Br-based nanoplatelets (NPls)). [4] Among them, composition engineering through Br-Cl hybridization may cause unavoidable phase segregation under photo-excitation or electrical bias, leading to redshift or multiple emissions in photoluminescence emission (PL) spectrum. [5] Quantum confinement strategy for Br-based perovskites nanocrystals is widely accepted for blue emitters because of its higher defect tolerance compared with Cl-or Br/ Cl-based MHPs. [1a] However, ultrasmall CsPbBr 3 quantum dots (<5 nm) with uniform size are relatively difficult to achieve due to the ultrafast reaction rate, which easily leads to a broad emission band (FWHM > 30 nm). [1b] For quasi-2D NPls, the emission peak position mainly depends on their thickness, which exhibits a quantum confinement effect when it is smaller than Quasi 2D metal halide perovskite nanoplatelets (NPls), as a kind of important materials to achieve pure blue emission, attract significant attention in pursuit of high gamut trichromatic display. However, in-depth study on the specific growth processes of NPls is still lacking due to the ultrafast reaction rate. Here, a single ligand passivation strategy to investigate the concrete growth mechanism of NPls is proposed, in which the PbBr x (OAm) y clusters play a pivotal template role in guiding the growth of crystals, and the final products with 3-monolayer (3ML) are grown from the intermediate 2ML NPls instead of being synthesized directly. Based on the new discovery about growth mechanism of NPls, the reaction time has been shortened from hours to seconds by introducing hydrobromic acid and ethanol. The ethanol used here is considered as an accelerator for the transition from 2ML to 3ML NPls rather than an initiator for nucleation of products, which is different from the generally accepted viewpoints. With further passivation of hydrobromic acid, the synthesized 3ML NPls show 462 nm emission with quantum yield of 97.04% and great photostability. The novel growth model proposed in this work will provide a paradigm for future design and optimization of new synthesis schemes.

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The field of cancer neoantigen investigation has developed swiftly in the past decade. Predicting novel and true neoantigens derived from large multi-omics data became difficult but critical challenges. The rise of Artificial Intelligence (AI) or Machine Learning (ML) in biomedicine application has brought benefits to strengthen the current computational pipeline for neoantigen prediction. ML algorithms offer powerful tools to recognize the multidimensional nature of the omics data and therefore extract the key neoantigen features enabling a successful discovery of new neoantigens. The present review aims to outline the significant technology progress of machine learning approaches, especially the newly deep learning tools and pipelines, that were recently applied in neoantigen prediction. In this review article, we summarize the current state-of-the-art tools developed to predict neoantigens. The standard workflow includes calling genetic variants in paired tumor and blood samples, and rating the binding affinity between mutated peptide, MHC (I and II) and T cell receptor (TCR), followed by characterizing the immunogenicity of tumor epitopes. More specifically, we highlight the outstanding feature extraction tools and multi-layer neural network architectures in typical ML models. It is noted that more integrated neoantigen-predicting pipelines are constructed with hybrid or combined ML algorithms instead of conventional machine learning models. In addition, the trends and challenges in further optimizing and integrating the existing pipelines are discussed.

This study presents the extraction and verification of a smallsignal model suitable for characterizing THz InP double heterojunction bipolar transistors (DHBTs). The π-type topology is adopted in the intrinsic model. Capacitances C cx and C ce are used to characterize the capacitive parasitics caused by the routing line connecting the collector terminal, base terminal and emitter terminal, respectively. The inductive parasitics introduced by the routing line are also considered. The initial values of the model parameters are extracted using a direct extraction method. The model and extraction method for the model parameters are verified by adopting an InP DHBT with 1 emitter finger and an emitter size of 0.5 µm × 5 µm. The simulation results correspond with the measured results in the frequency range from 200 MHz to 325 GHz.