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Research on food-derived immunoregulatory peptides has attracted increasing attention of scientists worldwide. However, the structure–activity relationship of rice immunopeptides was not clearly. Herein, 114 rice immunopeptides were obtained by simulating the enzymatic hydrolysis of rice proteins and were further analyzed by NetMHCIipan-4.0. Subsequently, the molecular docking was used to simulate the binding of immunoreactive peptides to major histocompatibility complex class II (MHC-II) molecules. Results show that S, R, D, E, and T amino acid could easily form hydrogen bonds with MHC-II molecules, thus enhancing innate and adaptive immunity. Finally, glucose-modified rice immunopeptides were to investigate the binding of the peptides with MHC-II molecules after glycosylation modification; this provided a theoretical basis for the targeted modification of the generated immunopeptides. All in all, the present study provides a theoretical foundation to further utilize rice processing byproducts and other food products to enhance immunity.

Some food-derived bioactive peptides exhibit prominent immunoregulatory activity. We previously demonstrated that the rice-derived PEP1 peptide, GIAASPFLQSAAFQLR, has strong immunological activity. However, the mechanism of this action is still unclear. In the present study, full-length transcripts of mouse dendritic cells (DC2.4) treated with PEP1 were sequenced using the PacBio sequencing platform, and the transcriptomes were compared via RNA sequencing (RNA-Seq). The characteristic markers of mature DCs, the cluster of differentiation CD86, and the major histocompatibility complex (MHC-II), were significantly upregulated after the PEP1 treatment. The molecular docking suggested that hydrogen bonding and electrostatic interactions played important roles in the binding between PEP1, MHC-II, and the T-cell receptor (TCR). In addition, the PEP1 peptide increased the release of anti-inflammatory factors (interleukin-4 and interleukin-10) and decreased the release of pro-inflammatory factors (interleukin-6 and tumor necrosis factor-α). Furthermore, the RNA-seq results showed the expression of genes involved in several signaling pathways, such as the NF-κB, MAPK, JAK-STAT, and TGF-β pathways, were regulated by the PEP1 treatment, and the changes confirmed the immunomodulatory effect of PEP1 on DC2.4 cells. This findings revealed that the PEP1 peptide, derived from the byproduct of rice processing, is a potential natural immunoregulatory alternative for the treatment of inflammation.

Abstract Brucella, a gram-negative intracellular bacterium, causing Brucellosis, a zoonotic disease with a range of clinical manifestations, from asymptomatic to fever, fatigue, loss of appetite, joint and muscle pain, and back pain, severe patients have developed serious diseases affecting various organs. The mRNA vaccine is an innovative type of vaccine that is anticipated to supplant traditional vaccines. It is widely utilized for preventing viral infections and for tumor immunotherapy. However, research regarding its effectiveness in preventing bacterial infections is limited. In this study, we analyzed the epitopes of two proteins of brucella, the TonB-dependent outer membrane receptor BtuB and the LPS assembly protein LptD, which is involved in nutrient transport and LPS synthesis in Brucella. In order to effectively stimulate cellular and humoral immunity, we utilize a range of immunoinformatics tools such as VaxiJen, AllergenFPv.1.0 and SignalP 5.0 to design proteins. Finally, five cytotoxic T lymphocyte (CTL) cell epitopes, ten helper T lymphocyte (HTL) cell epitopes, and eight B cell epitopes were selected to construct the vaccine. Computer simulations are also used to verify the immune response of the vaccine. The codon optimization, in silico cloning showed that the vaccine can efficiently transcript and translate in E. coli. The secondary structure of mRNA vaccines and the secondary and tertiary structures of vaccine peptides were predicted and then docked with TLR-4. Finally, the stability of the developed vaccine was confirmed through molecular dynamics simulation. These analyses showed that the design the multi-epitope mRNA vaccine could potentially target extracellular protein of prevalent Brucella, which provided novel strategies for developing the vaccine.

Abstract Brucella is a typical facultative intracellular bacterium that can cause zoonotic infections. For Brucella, it is difficult to eliminate with current medical treatment. Therefore, a multi-epitope vaccine (MEV) should be designed to prevent Brucella infection. For this purpose, we applied the reverse vaccinology approach from Omp10, Omp25, Omp31 and BtpB. Finally, we obtained 13 cytotoxic T lymphocyte (CTL) epitopes, 17 helper T lymphocyte (HTL) epitopes, 9 linear B cell epitopes, and 2 conformational B cell epitopes for further study. To keep the protein folded normally, we linked AAY, GPGPG, and KK to CTL epitopes, HTL epitopes, and B cell epitopes, respectively. The N-terminal of the vaccine peptide is supplemented with appropriate adjuvants to enhance immunogenicity. To evaluate its immunogenicity, stability, safety, and feasibility, a final MEV containing 806 amino acids was constructed by linking linkers and adjuvants. In addition, molecular docking and molecular dynamics simulations were performed to verify the affinity and stability of the MEV-TLR4. Then, codon adaptation and in silico cloning studies were carried out to identify the possible codons for expressing the MEV. In animal experiments, the results demonstrated that the MEV had high immunogenicity. Collectively, this study provided a theoretical basis for the development of a Brucella vaccine.

Abstract Amorphous oxide semiconductor thin‐film transistors (AOS TFTs) are ever‐increasingly utilized in displays. However, to bring high mobility and excellent stability together is a daunting challenge. Here, the carrier transport/relaxation bilayer stacked AOS TFTs are investigated to solve the mobility‐stability conflict. The charge transport layer (CTL) is made of amorphous In‐rich InSnZnO, which favors big average effective coordination number for all cations and more edge‐shared structures for better charge transport. Praseodymium‐doped InSnZnO is used as the charge relaxation layer (CRL), which substantially shortens the photoelectron lifetime as revealed by femtosecond transient absorption spectroscopy. The CTL and CRL with the thickness suitable for industrial production respectively afford minute potential barrier fluctuation for charge transport and fast relaxation for photo‐generated carriers, resulting in transistors with an ultrahigh mobility (75.5 cm2 V−1 s−1) and small negative‐bias‐illumination‐stress/positive‐bias‐temperature‐stress voltage shifts (−1.64/0.76 V). The design concept provides a promising route to address the mobility‐stability conflict for high‐end displays.

Abstract High‐performance bilayer In2O3/IGZO thin‐film transistors (TFTs) fabricated by pulsed laser deposition are reported. The TFTs exhibit an on/off current ratio of 109, a reversed subthreshold slope (ss) of 0.08 V dec−1, and a high saturation mobility of 47.9 cm2 V−1 s−1. The reliability of the mobility values is critically validated and assessed by four‐probe measurements, the transfer‐length method, and the temperature‐dependence. X‐ray photoelectron spectra are combined with C–V measurements to characterize the interface, and the results show that a two‐dimensional electron gas (2DEG)‐like state accumulates at the In2O3/IGZO interface. However, this state only forms in the subthreshold region and does not cause the high carrier mobility in the region above the threshold. Instead, the enhanced carrier mobility results from the intrinsic high mobility of the In2O3, the smooth surface, and the low‐defect states in the In2O3/IGZO bilayer with a good percolation transport path.

Background: Cell composition deconvolution (CCD) is a type of bioinformatic task to estimate the cell fractions from bulk gene expression profiles, such as RNA-seq. Many CCD models were developed to perform linear regression analysis using reference gene expression signatures of distinct cell types. Reference gene expression signatures could be generated from cell-specific gene expression profiles, such as scRNA-seq. However, the batch effects and dropout events frequently observed across scRNA-seq datasets have limited the performances of CCD methods., Methods: We developed a deep neural network (DNN) model, HASCAD, to predict the cell fractions of up to 15 immune cell types. HASCAD was trained using the bulk RNA-seq simulated from three scRNA-seq datasets that have been normalized by using a Harmony-Symphony based strategy. Mean square error and Pearson correlation coefficient were used to compare the performance of HASCAD with those of other widely used CCD methods. Two types of datasets, including a set of simulated bulk RNA-seq, and three human PBMC RNA-seq datasets, were arranged to conduct the benchmarks., Results: HASCAD is useful for the investigation of the impacts of immune cell heterogeneity on the therapeutic effects of immune checkpoint inhibitors, since the target cell types include the ones known to play a role in anti-tumor immunity, such as three subtypes of CD8 T cells and three subtypes of CD4 T cells. We found that the removal of batch effects in the reference scRNA-seq datasets could benefit the task of CCD. Our benchmarks showed that HASCAD is more suitable for analyzing bulk RNA-seq data, compared with the two widely used CCD methods, CIBERSORTx and quanTIseq. We applied HASCAD to analyze the liver cancer samples of TCGA-LIHC, and found that there were significant associations of the predicted abundance of Treg and effector CD8 T cell with patients' overall survival., Conclusion: HASCAD could predict the cell composition of the PBMC bulk RNA-seq and classify the cell type from pure bulk RNA-seq. The model of HASCAD is available at https://github.com/holiday01/HASCAD ., (© 2023. The Author(s).)

Motivation: Computational promoter prediction (CPP) tools designed to classify prokaryotic promoter regions usually assume that a transcription start site (TSS) is located at a predefined position within each promoter region. Such CPP tools are sensitive to any positional shifting of the TSS in a windowed region, and they are unsuitable for determining the boundaries of prokaryotic promoters., Results: TSSUNet-MB is a deep learning model developed to identify the TSSs of σ 70 promoters. Mononucleotide and bendability were used to encode input sequences. TSSUNet-MB outperforms other CPP tools when assessed using the sequences obtained from the neighborhood of real promoters. TSSUNet-MB achieved a sensitivity of 0.839 and specificity of 0.768 on sliding sequences, while other CPP tool cannot maintain both sensitivities and specificities in a compatible range. Furthermore, TSSUNet-MB can precisely predict the TSS position of σ 70 promoter-containing regions with a 10-base accuracy of 77.6%. By leveraging the sliding window scanning approach, we further computed the confidence score of each predicted TSS, which allows for more accurately identifying TSS locations. Our results suggest that TSSUNet-MB is a robust tool for finding σ 70 promoters and identifying TSSs., Competing Interests: Declaration of Competing Interest None declared., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Many studies have utilized computational methods, including cell composition deconvolution (CCD), to correlate immune cell polarizations with the survival of cancer patients, including those with hepatocellular carcinoma (HCC). However, currently available cell deconvolution estimated (CDE) tools do not cover the wide range of immune cell changes that are known to influence tumor progression., Results: A new CCD tool, HCCImm, was designed to estimate the abundance of tumor cells and 16 immune cell types in the bulk gene expression profiles of HCC samples. HCCImm was validated using real datasets derived from human peripheral blood mononuclear cells (PBMCs) and HCC tissue samples, demonstrating that HCCImm outperforms other CCD tools. We used HCCImm to analyze the bulk RNA-seq datasets of The Cancer Genome Atlas (TCGA)-liver hepatocellular carcinoma (LIHC) samples. We found that the proportions of memory CD8 + T cells and Tregs were negatively associated with patient overall survival (OS). Furthermore, the proportion of naïve CD8 + T cells was positively associated with patient OS. In addition, the TCGA-LIHC samples with a high tumor mutational burden had a significantly high abundance of nonmacrophage leukocytes., Conclusions: HCCImm was equipped with a new set of reference gene expression profiles that allowed for a more robust analysis of HCC patient expression data. The source code is provided at https://github.com/holiday01/HCCImm., (© 2023 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

Background: Carbapenemase-producing Klebsiella pneumoniae causes high mortality owing to the limited therapeutic options available. Here, we investigated an emergent carbapenem-resistant K. pneumoniae strain with hypervirulence found among KPC-2-producing strains in Taiwan., Methods: KPC-producing K. pneumoniae strains were collected consecutively from clinical specimens at the Taipei Veterans General Hospital between January 2012 and December 2014. Capsular types and the presence of rmpA/rmpA2 were analysed, and PFGE and MLST performed using these strains. The strain positive for rmpA/rmpA2 was tested in an in vivo mouse lethality study to verify its virulence and subjected to WGS to delineate its genomic features., Results: A total of 62 KPC-2-producing K. pneumoniae strains were identified; all of these belonged to ST11 and capsular genotype K47. One strain isolated from a fatal case with intra-abdominal abscess (TVGHCRE225) harboured rmpA and rmpA2 genes. This strain was resistant to tigecycline and colistin, in addition to carbapenems, and did not belong to the major cluster in PFGE. TVGHCRE225 exhibited high in vivo virulence in the mouse lethality experiment. WGS showed that TVGHCRE225 acquired a novel hybrid virulence plasmid harbouring a set of virulence genes (iroBCDN, iucABCD, rmpA and rmpA2, and iutA) compared with the classic ST11 KPC-2-producing strain., Conclusions: We identified an XDR ST11 KPC-2-producing K. pneumoniae strain carrying a hybrid virulent plasmid in Taiwan. Active surveillance focusing on carbapenem-resistant hypervirulent K. pneumoniae strains is necessary, as the threat to human health is imminent.