Lab-Attenuated Rabies Virus Facilitates Opening of the Blood-Brain Barrier by Inducing Matrix Metallopeptidase 8.

Infection with laboratory-attenuated rabies virus (RABV), but not wild-type (wt) RABV, can enhance the permeability of the blood-brain barrier (BBB), which is considered a key determinant for RABV pathogenicity. A previous study showed that the enhancement of BBB permeability is directly due not to RABV infection but to virus-induced inflammatory molecules. In this study, the effect of the matrix metallopeptidase (MMP) family on the permeability of the BBB during RABV infection was evaluated. We found that the expression level of MMP8 was upregulated in mice infected with lab-attenuated RABV but not with wt RABV. Lab-attenuated RABV rather than wt RABV activates inflammatory signaling pathways mediated by the nuclear factor κB (NF-κB) and mitogen-activated protein kinase (MAPK) pathways. Activated NF-κB (p65) and AP-1 (c-Fos) bind to the MMP8 promoter, resulting in upregulation of its transcription. Analysis of mouse brains infected with the recombinant RABV expressing MMP8 indicated that MMP8 enhanced BBB permeability, leading to infiltration of inflammatory cells into the central nervous system (CNS). In brain-derived endothelial cells, treatment with MMP8 recombinant protein caused the degradation of tight junction (TJ) proteins, and the application of an MMP8 inhibitor inhibited the degradation of TJ proteins after RABV infection. Furthermore, an in vivo experiment using an MMP8 inhibitor during RABV infection demonstrated that BBB opening was diminished. In summary, our data suggest that the infection of lab-attenuated RABV enhances the BBB opening by upregulating MMP8. IMPORTANCE The ability to change BBB permeability was associated with the pathogenicity of RABV. BBB permeability was enhanced by infection with lab-attenuated RABV instead of wt RABV, allowing immune cells to infiltrate into the CNS. We found that MMP8 plays an important role in enhancing BBB permeability by degradation of TJ proteins during RABV infection. Using an MMP8 selective inhibitor restores the reduction of TJ proteins. We reveal that MMP8 is upregulated via the MAPK and NF-κB inflammatory pathways, activated by lab-attenuated RABV infection but not wt RABV. Our findings suggest that MMP8 has a critical role in modulating the opening of the BBB during RABV infection, which provides fresh insight into developing effective therapeutics for rabies and infection with other neurotropic viruses.

Potential Target Discovery and Drug Repurposing for Coronaviruses: Study Involving a Knowledge Graph-Based Approach.

BACKGROUND: The global pandemics of severe acute respiratory syndrome, Middle East respiratory syndrome, and COVID-19 have caused unprecedented crises for public health. Coronaviruses are constantly evolving, and it is unknown which new coronavirus will emerge and when the next coronavirus will sweep across the world. Knowledge graphs are expected to help discover the pathogenicity and transmission mechanism of viruses. OBJECTIVE: The aim of this study was to discover potential targets and candidate drugs to repurpose for coronaviruses through a knowledge graph-based approach. METHODS: We propose a computational and evidence-based knowledge discovery approach to identify potential targets and candidate drugs for coronaviruses from biomedical literature and well-known knowledge bases. To organize the semantic triples extracted automatically from biomedical literature, a semantic conversion model was designed. The literature knowledge was associated and integrated with existing drug and gene knowledge through semantic mapping, and the coronavirus knowledge graph (CovKG) was constructed. We adopted both the knowledge graph embedding model and the semantic reasoning mechanism to discover unrecorded mechanisms of drug action as well as potential targets and drug candidates. Furthermore, we have provided evidence-based support with a scoring and backtracking mechanism. RESULTS: The constructed CovKG contains 17,369,620 triples, of which 641,195 were extracted from biomedical literature, covering 13,065 concept unique identifiers, 209 semantic types, and 97 semantic relations of the Unified Medical Language System. Through multi-source knowledge integration, 475 drugs and 262 targets were mapped to existing knowledge, and 41 new drug mechanisms of action were found by semantic reasoning, which were not recorded in the existing knowledge base. Among the knowledge graph embedding models, TransR outperformed others (mean reciprocal rank=0.2510, Hits@10=0.3505). A total of 33 potential targets and 18 drug candidates were identified for coronaviruses. Among them, 7 novel drugs (ie, quinine, nelfinavir, ivermectin, asunaprevir, tylophorine, Artemisia annua extract, and resveratrol) and 3 highly ranked targets (ie, angiotensin converting enzyme 2, transmembrane serine protease 2, and M protein) were further discussed. CONCLUSIONS: We showed the effectiveness of a knowledge graph-based approach in potential target discovery and drug repurposing for coronaviruses. Our approach can be extended to other viruses or diseases for biomedical knowledge discovery and relevant applications.

[Intrinsic "self-consistent" phenomenon based on holistic view of traditional Chinese medicine].

The fundamental principle of traditional Chinese medicine(TCM) is holism, and it is crucial for TCM to address the key issue of the "holistic view" of Chinese herbal medicine. While the overall regulatory effects of Chinese herbal medicine have been widely recognized, the holistic internal logic of individual ingredients of Chinese herbal medicines require further clarification. In order to comprehensively understand the mechanism of action of Chinese herbal medicine, this paper combined the holistic view of Chinese herbal medicine with differentiation thinking to explore the intrinsic logical relationships within Chinese herbal medicine. Starting from the perspective of the coexistence of multiple components in Chinese herbal medicine, this paper systematically examined the "self-consistent" phenomenon within single Chinese herbal medicine. This phenomenon refers to the consistent or opposing actions of various components in terms of their physical and chemical properties, pharmacokinetic effects, biological effects, flavors and properties, and TCM efficacy. The paper summarized various logical relationships of syndrome differentiation exhibited by the same Chinese herbal medicine, analyzed the underlying reasons, and focused on analyzing external factors affecting the "self-consistent" phenomenon in the efficacy of Chinese herbal medicine, aiming to better elucidate the theoretical basis of the pharmacological effects of Chinese herbal medicine, further enrich the scientific connotation of the holistic view of Chinese herbal medicine, and provide theoretical guidance for the preparation process, compatibility patterns, and formulation design of Chinese herbal medicine.

hucMSC-Derived Exosomes Alleviate the Deterioration of Colitis via the miR-146a/SUMO1 Axis.

Human umbilical cord mesenchymal stem cell-derived exosome (hucMSC-Ex) plays an important role in tissue repair and immunomodulation, leading to the mitigation of inflammatory bowel disease. However, the preventive function of hucMSC-Ex in the onset and progression of colitis-associated colon cancer (CAC) is poorly understood. In the current study, dextran sodium sulfate/azoxymethane-induced colitis mouse model was established, and the mice disease activity index, body weight, colon length, tumor counts, survival curve, tissue H&E/immunohistochemistry, and cytokines expression were analyzed to evaluate the effects of hucMSC-Ex on CAC. In addition, miR-146a mimics were transfected into colonic epithelial cells (fetal human cells) to evaluate their role in the hucMSC-Ex-mediated regulation of SUMO1. The results showed that hucMSC-Ex inhibits the expression of SUMO1 to reduce the process of CAC progression. Further analysis indicated that miR-146a targets and inhibits SUMO1 expression and its binding to ß-catenin. In conclusion, our findings showed that hucMSC-Ex is effective in alleviating the deterioration of colitis via the miR-146a-mediated inhibition of SUMO1, which is crucial in this disease process.

Extracting clinical named entity for pituitary adenomas from Chinese electronic medical records.

OBJECTIVE: Pituitary adenomas are the most common type of pituitary disorders, which usually occur in young adults and often affect the patient's physical development, labor capacity and fertility. Clinical free texts noted in electronic medical records (EMRs) of pituitary adenomas patients contain abundant diagnosis and treatment information. However, this information has not been well utilized because of the challenge to extract information from unstructured clinical texts. This study aims to enable machines to intelligently process clinical information, and automatically extract clinical named entity for pituitary adenomas from Chinese EMRs. METHODS: The clinical corpus used in this study was from one pituitary adenomas neurosurgery treatment center of a 3A hospital in China. Four types of fine-grained texts of clinical records were selected, which included notes from present illness, past medical history, case characteristics and family history of 500 pituitary adenoma inpatients. The dictionary-based matching, conditional random fields (CRF), bidirectional long short-term memory with CRF (BiLSTM-CRF), and bidirectional encoder representations from transformers with BiLSTM-CRF (BERT-BiLSTM-CRF) were used to extract clinical entities from a Chinese EMRs corpus. A comprehensive dictionary was constructed based on open source vocabularies and a domain dictionary for pituitary adenomas to conduct the dictionary-based matching method. We selected features such as part of speech, radical, document type, and the position of characters to train the CRF-based model. Random character embeddings and the character embeddings pretrained by BERT were used respectively as the input features for the BiLSTM-CRF model and the BERT-BiLSTM-CRF model. Both strict metric and relaxed metric were used to evaluate the performance of these methods. RESULTS: Experimental results demonstrated that the deep learning and other machine learning methods were able to automatically extract clinical named entities, including symptoms, body regions, diseases, family histories, surgeries, medications, and disease courses of pituitary adenomas from Chinese EMRs. With regard to overall performance, BERT-BiLSTM-CRF has the highest strict F1 value of 91.27% and the highest relaxed F1 value of 95.57% respectively. Additional evaluations showed that BERT-BiLSTM-CRF performed best in almost all entity recognition except surgery and disease course. BiLSTM-CRF performed best in disease course entity recognition, and performed as well as the CRF model for part of speech, radical and document type features, with both strict and relaxed F1 value reaching 96.48%. The CRF model with part of speech, radical and document type features performed best in surgery entity recognition with relaxed F1 value of 95.29%. CONCLUSIONS: In this study, we conducted four entity recognition methods for pituitary adenomas based on Chinese EMRs. It demonstrates that the deep learning methods can effectively extract various types of clinical entities with satisfying performance. This study contributed to the clinical named entity extraction from Chinese neurosurgical EMRs. The findings could also assist in information extraction in other Chinese medical texts.

COVID term: a bilingual terminology for COVID-19.

BACKGROUND: The coronavirus disease (COVID-19), a pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has shown its destructiveness with more than one million confirmed cases and dozens of thousands of death, which is highly contagious and still spreading globally. World-wide studies have been conducted aiming to understand the COVID-19 mechanism, transmission, clinical features, etc. A cross-language terminology of COVID-19 is essential for improving knowledge sharing and scientific discovery dissemination. METHODS: We developed a bilingual terminology of COVID-19 named COVID Term with mapping Chinese and English terms. The terminology was constructed as follows: (1) Classification schema design; (2) Concept representation model building; (3) Term source selection and term extraction; (4) Hierarchical structure construction; (5) Quality control (6) Web service. We built open access for the terminology, providing search, browse, and download services. RESULTS: The proposed COVID Term include 10 categories: disease, anatomic site, clinical manifestation, demographic and socioeconomic characteristics, living organism, qualifiers, psychological assistance, medical equipment, instruments and materials, epidemic prevention and control, diagnosis and treatment technique respectively. In total, COVID Terms covered 464 concepts with 724 Chinese terms and 887 English terms. All terms are openly available online (COVID Term URL: http://covidterm.imicams.ac.cn ). CONCLUSIONS: COVID Term is a bilingual terminology focused on COVID-19, the epidemic pneumonia with a high risk of infection around the world. It will provide updated bilingual terms of the disease to help health providers and medical professionals retrieve and exchange information and knowledge in multiple languages. COVID Term was released in machine-readable formats (e.g., XML and JSON), which would contribute to the information retrieval, machine translation and advanced intelligent techniques application.

ECCParaCorp: a cross-lingual parallel corpus towards cancer education, dissemination and application.

BACKGROUND: The increasing global cancer incidence corresponds to serious health impact in countries worldwide. Knowledge-powered health system in different languages would enhance clinicians' healthcare practice, patients' health management and public health literacy. High-quality corpus containing cancer information is the necessary foundation of cancer education. Massive non-structural information resources exist in clinical narratives, electronic health records (EHR) etc. They can only be used for training AI models after being transformed into structured corpus. However, the scarcity of multilingual cancer corpus limits the intelligent processing, such as machine translation in medical scenarios. Thus, we created the cancer specific cross-lingual corpus and open it to the public for academic use. METHODS: Aiming to build an English-Chinese cancer parallel corpus, we developed a workflow of seven steps including data retrieval, data parsing, data processing, corpus implementation, assessment verification, corpus release, and application. We applied the workflow to a cross-lingual, comprehensive and authoritative cancer information resource, PDQ (Physician Data Query). We constructed, validated and released the parallel corpus named as ECCParaCorp, made it openly accessible online. RESULTS: The proposed English-Chinese Cancer Parallel Corpus (ECCParaCorp) consists of 6685 aligned text pairs in Xml, Excel, Csv format, containing 5190 sentence pairs, 1083 phrase pairs and 412 word pairs, which involved information of 6 cancers including breast cancer, liver cancer, lung cancer, esophageal cancer, colorectal cancer, and stomach cancer, and 3 cancer themes containing cancer prevention, screening, and treatment. All data in the parallel corpus are online, available for users to browse and download ( http://www.phoc.org.cn/ECCParaCorp/ ). CONCLUSIONS: ECCParaCorp is a parallel corpus focused on cancer in a cross-lingual form, which is openly accessible. It would make up the imbalance of scarce multilingual corpus resources, bridge the gap between human readable information and machine understanding data resources, and would contribute to intelligent technology application as a preparatory data foundation e.g. cancer-related machine translation, cancer system development towards medical education, and disease-oriented knowledge extraction.

Development of oligonucleotide microarray for accurate and simultaneous detection of avian respiratory viral diseases.

BACKGROUND: Avian influenza virus (AIV), infectious bronchitis virus (IBV), and Newcastle disease virus (NDV) are important avian pathogens that can cause enormous economic loss on the poultry industry. Different respiratory etiological agents may induce similar clinical signs that make differential diagnosis difficult. Importantly, AIV brings about severe threat to human public health. Therefore, a novel method that can distinguish these viruses quickly and simultaneously is urgently needed. RESULTS: In this study, an oligonucleotide microarray system was developed. AIV, including H5, H7, and H9 subtypes; NDV; and IBV were simultaneously detected and differentiated on a microarray. Three probes specific for AIV, NDV, and IBV, as well as three other probes for differentiating H5, H7, and H9 of AIV, were first designed and jet-printed to predetermined locations of initiator-integrated poly(dimethylsiloxane) for the synchronous detection of the six pathogens. The marked multiplex reverse transcription polymerase chain reaction (PCR) products were hybridized with the specific probes, and the results of hybridization were read directly with the naked eyes. No cross-reaction was observed with 10 other subtypes of AIV and infectious bursal disease virus, indicating that the oligonucleotide microarray assay was highly specific. The sensitivity of the method was at least 100 times higher than that of the conventional PCR, and the detection limit of NDV, AIV, H5, H7, and H9 can reach 0.1 EID50 (50% egg infective dose), except that of IBV, which was 1 EID50 per reaction. In the validation of 93 field samples, AIV, IBV, and NDV were detected in 53 (56.99%) samples by oligonucleotide microarray and virus isolation and in 50 (53.76%) samples by conventional PCR. CONCLUSIONS: We have successfully developed an approach to differentiate AIV, NDV, IBV, H5, H7, and H9 subtypes of AIV using oligonucleotide microarray. The microarray is an accurate, high-throughput, and relatively simple method for the rapid detection of avian respiratory viral diseases. It can be used for the epidemiological surveillance and diagnosis of AIV, IBV, and NDV.

Novel protein chip for the detection of antibodies against infectious bronchitis virus.

BACKGROUND: Infectious bronchitis (IB) caused by the IB virus (IBV) can cause acute damage to chickens around the world. Therefore, rapid diagnosis and immune status determination are critical for controlling IBV outbreaks. Enzyme-linked immunosorbent assays (ELISAs) have been widely used in the detection of IBV antibodies in the early infection and continuous infection of IB because they are more sensitive and quicker than other diagnostic methods. RESULTS: We have developed two indirect microarray methods to detect antibodies against IBV: a chemiluminescent immunoassay test (CIT) and a rapid diagnostic test (RDT). IBV nonstructural protein 5 (nsp5) was expressed, purified from Escherichia coli, and used to spot the initiator integrated poly(dimethylsiloxane), which can provide a near "zero" background for serological assays. Compared with the IDEXX IBV Ab Test kit, CIT and RDT have a sensitivity and specificity of at least 98.88% and 91.67%, respectively. No cross-reaction was detected with antibodies against avian influenza virus subtypes (H5, H7, and H9), Newcastle disease virus, Marek's disease virus, infectious bursal disease virus, and chicken anemia virus. The coefficients of variation of the reproducibility of the intra- and inter-assays for CIT ranged from 0.8 to 18.63%. The reproducibility of RDT was consistent with the original results. The application of the IBV nsp5 protein microarray showed that the positive rate of the CIT was 96.77%, that of the nsp5 ELISA was 91.40%, and that of the RDT was 90.32%. Furthermore, the RDT, which was visible to the naked eye, could be completed within 15 min. Our results indicated that compared with nsp5 ELISA, the CIT was more sensitive, and the RDT had similar positive rates but was faster. Furthermore, the two proposed methods were specific and stable. CONCLUSIONS: Two microarray assays, which were rapid, specific, sensitive, and relatively simple, were developed for the detection of an antibody against IBV. These methods can be of great value for the surveillance of pathogens and monitoring the efficiency of vaccination.

A novel harmony search algorithm based on teaching-learning strategies for 0-1 knapsack problems.

To enhance the performance of harmony search (HS) algorithm on solving the discrete optimization problems, this paper proposes a novel harmony search algorithm based on teaching-learning (HSTL) strategies to solve 0-1 knapsack problems. In the HSTL algorithm, firstly, a method is presented to adjust dimension dynamically for selected harmony vector in optimization procedure. In addition, four strategies (harmony memory consideration, teaching-learning strategy, local pitch adjusting, and random mutation) are employed to improve the performance of HS algorithm. Another improvement in HSTL method is that the dynamic strategies are adopted to change the parameters, which maintains the proper balance effectively between global exploration power and local exploitation power. Finally, simulation experiments with 13 knapsack problems show that the HSTL algorithm can be an efficient alternative for solving 0-1 knapsack problems.

The matrix protein of lyssavirus hijacks autophagosome for efficient egress by recruiting NEDD4 through its PPxY motif.

Lyssaviruses are well-known worldwide and often cause fatal encephalitis. Previous studies have shown that autophagy is beneficial for the replication of rabies virus (RABV), the representative lyssavirus, but the detailed mechanism remains obscure. In this study, we showed that the rabies virus matrix protein (RABV-M) used its PPxY motif to interact with the E3 ubiquitin-protein ligase NEDD4. NEDD4 then recruited MAP1LC3/LC3 via its LC3-interacting region (LIR). Interestingly, after binding to the ubiquitinated RABV-M, NEDD4 could bind more LC3 and enhance autophagosome accumulation, while NEDD4 knockdown significantly reduced M-induced autophagosome accumulation. Further study revealed that RABV-M prevented autophagosome-lysosome fusion and facilitated viral budding. Inhibition of RABV-M-induced autophagosome accumulation reduced the production of extracellular virus-like particles. We also found that M proteins of most lyssaviruses share the same mechanism to accumulate autophagosome by hijacking NEDD4. Collectively, this study revealed a novel strategy for lyssaviruses to achieve efficient viral replication by exploiting the host autophagy system.Abbreviations: ABLV: Australian bat lyssavirus; ATG5: autophagy related 5; Baf A1:bafilomycin A1;co-IP: co-immunoprecipitation; CQ: chloroquine; DAPI:4',6-diamidino-2'-phenylindole; DMSO: dimethyl sulfoxide; EBLV:European bat lyssavirus; GFP: green fluorescent protein; GST:glutathione S-transferase; hpi: hours post-infection; hpt: hourspost-transfection; LIR: LC3-interactingregion;MAP1LC3/LC3: microtubule-associated protein 1 light chain 3; mCherry:red fluorescent protein; MOI: multiplicity of infection; NC: negativecontrol; MVB: multivesicular body; NEDD4: neural precursorcell-expressed developmentally down-regulated 4; RABV: rabies virus;SQSTM1/p62: sequestosome 1; VLP: virus-like particle; VPS4B: vacuolarprotein sorting 4B; TEM: transmission electron microscopy; WB:western blotting; WT: wild-type; µm: micrometer; µM: micromole.

Lassa virus Z protein hijacks the autophagy machinery for efficient transportation by interrupting CCT2-mediated cytoskeleton network formation.

The Lassa virus (LASV) is a widely recognized virulent pathogen that frequently results in lethal viral hemorrhagic fever (VHF). Earlier research has indicated that macroautophagy/autophagy plays a role in LASV replication, but, the precise mechanism is unknown. In this present study, we show that LASV matrix protein (LASV-Z) is essential for blocking intracellular autophagic flux. LASV-Z hinders actin and tubulin folding by interacting with CCT2, a component of the chaperonin-containing T-complexes (TRiC). When the cytoskeleton is disrupted, lysosomal enzyme transit is hampered. In addition, cytoskeleton disruption inhibits the merge of autophagosomes with lysosomes, resulting in autophagosome accumulation that promotes the budding of LASV virus-like particles (VLPs). Inhibition of LASV-Z-induced autophagosome accumulation blocks the LASV VLP budding process. Furthermore, it is found that glutamine at position 29 and tyrosine at position 48 on LASV-Z are important in interacting with CCT2. When these two sites are mutated, LASV-mut interacts with CCT2 less efficiently and can no longer inhibit the autophagic flux. These findings demonstrate a novel strategy for LASV-Z to hijack the host autophagy machinery to accomplish effective transportation.Abbreviation: 3-MA: 3-methyladenine; ATG5: autophagy related 5; ATG7: autophagy related 7; Baf-A1: bafilomycin A1; CCT2: chaperonin containing TCP1 subunit 2; co-IP: co-immunoprecipitation; CTSD: cathepsin D; DAPI: 4',6-diamidino-2'-phenylindole; DMSO: dimethyl sulfoxide; EGFR: epidermal growth factor receptor; GFP: green fluorescent protein; hpi: hours post-infection; hpt: hours post-transfection; LAMP1: lysosomal-associated membrane protein 1; LASV: lassa virus; MAP1LC3/LC3: microtubule-associated protein 1 light chain 3; mCherry: red fluorescent protein; PM: plasma membrane; SQSTM1/p62: sequestosome 1; STX6: syntaxin 6; VLP: virus-like particle; TEM: transmission electron microscopy; TRiC: chaperonin-containing T-complex; WB: western blotting; µm: micrometer; µM: micromole.

Effects of DNA methylation and its application in inflammatory bowel disease (Review).

Inflammatory bowel disease (IBD) is marked by persistent inflammation, and its development and progression are linked to environmental, genetic, immune system and gut microbial factors. DNA methylation (DNAm), as one of the protein modifications, is a crucial epigenetic process used by cells to control gene transcription. DNAm is one of the most common areas that has drawn increasing attention recently, with studies revealing that the interleukin (IL)­23/IL­12, wingless­related integration site, IL­6­associated signal transducer and activator of transcription 3, suppressor of cytokine signaling 3 and apoptosis signaling pathways are involved in DNAm and in the pathogenesis of IBD. It has emerged that DNAm­associated genes are involved in perpetuating the persistent inflammation that characterizes a number of diseases, including IBD, providing a novel therapeutic strategy for exploring their treatment. The present review discusses DNAm­associated genes in the pathogenesis of IBD and summarizes their application as possible diagnostic, prognostic and therapeutic biomarkers in IBD. This may provide a reference for the particular form of IBD and its related methylation genes, aiding in clinical decision­making and encouraging therapeutic alternatives.

Lyssavirus M protein degrades neuronal microtubules by reprogramming mitochondrial metabolism.

Infection with neurotropic viruses may result in changes in host behavior, which are closely associated with degenerative changes in neurons. The lyssavirus genus comprises highly neurotropic viruses, including the rabies virus (RABV), which has been shown to induce degenerative changes in neurons, marked by the self-destruction of axons. The underlying mechanism by which the RABV degrades neuronal cytoskeletal proteins remains incomplete. In this study, we show that infection with RABV or overexpression of its M protein can disrupt mitochondrial metabolism by binding to Slc25a4. This leads to a reduction in NAD+ production and a subsequent influx of Ca2+ from the endoplasmic reticulum and mitochondria into the cytoplasm of neuronal cell lines, activating Ca2+-dependent proteinase calpains that degrade α-tubulin. We further screened the M proteins of different lyssaviruses and discovered that the M protein of the dog-derived RABV strain (DRV) does not degrade α-tubulin. Sequence analysis of the DRV M protein and that of the lab-attenuated RABV strain CVS revealed that the 57th amino acid is vital for M-induced microtubule degradation. We generated a recombinant RABV with a mutation at the 57th amino acid position in its M protein and showed that this mutation reduces α-tubulin degradation in vitro and axonal degeneration in vivo. This study elucidates the mechanism by which lyssavirus induces neuron degeneration.IMPORTANCEPrevious studies have suggested that RABV (rabies virus, the representative of lyssavirus) infection induces structural abnormalities in neurons. But there are few articles on the mechanism of lyssavirus' effect on neurons, and the mechanism of how RABV infection induces neurological dysfunction remains incomplete. The M protein of lyssavirus can downregulate cellular ATP levels by interacting with Slc25a4, and this decrease in ATP leads to a decrease in the level of NAD+ in the cytosol, which results in the release of Ca2+ from the intracellular calcium pool, the endoplasmic reticulum, and mitochondria. The presence of large amounts of Ca2+ in the cytoplasm activates Ca2+-dependent proteases and degrades microtubule proteins. The amino acid 57 of M protein is the key site determining its disruption of mitochondrial metabolism and subsequent neuron degeneration.

A broadly applicable protein-polymer adjuvant system for antiviral vaccines.

Although protein subunit vaccines generally have acceptable safety profiles with precise antigenic content, limited immunogenicity can lead to unsatisfactory humoral and cellular immunity and the need for vaccine adjuvants and delivery system. Herein, we assess a vaccine adjuvant system comprising Quillaja Saponaria-21(QS-21) and cobalt porphyrin polymeric micelles that enabling the display of His-tagged antigen on its surface. The nanoscale micelles promote antigen uptake and dendritic cell activation to induce robust cytotoxic T lymphocyte response and germinal center formation. Using the recombinant protein antigens from influenza A and rabies virus, the micelle adjuvant system elicited robust antiviral responses and protected mice from lethal challenge. In addition, this system could be combined with other antigens to induce high titers of neutralizing antibodies in models of three highly pathogenic viral pathogens: Ebola virus, Marburg virus, and Nipah virus. Collectively, our results demonstrate this polymeric micelle adjuvant system can be used as a potent nanoplatform for developing antiviral vaccine countermeasures that promote humoral and cellular immunity.

Chinese Clinical Named Entity Recognition From Electronic Medical Records Based on Multisemantic Features by Using Robustly Optimized Bidirectional Encoder Representation From Transformers Pretraining Approach Whole Word Masking and Convolutional Neural Networks: Model Development and Validation.

BACKGROUND: Clinical electronic medical records (EMRs) contain important information on patients' anatomy, symptoms, examinations, diagnoses, and medications. Large-scale mining of rich medical information from EMRs will provide notable reference value for medical research. With the complexity of Chinese grammar and blurred boundaries of Chinese words, Chinese clinical named entity recognition (CNER) remains a notable challenge. Follow-up tasks such as medical entity structuring, medical entity standardization, medical entity relationship extraction, and medical knowledge graph construction largely depend on medical named entity recognition effects. A promising CNER result would provide reliable support for building domain knowledge graphs, knowledge bases, and knowledge retrieval systems. Furthermore, it would provide research ideas for scientists and medical decision-making references for doctors and even guide patients on disease and health management. Therefore, obtaining excellent CNER results is essential. OBJECTIVE: We aimed to propose a Chinese CNER method to learn semantics-enriched representations for comprehensively enhancing machines to understand deep semantic information of EMRs by using multisemantic features, which makes medical information more readable and understandable. METHODS: First, we used Robustly Optimized Bidirectional Encoder Representation from Transformers Pretraining Approach Whole Word Masking (RoBERTa-wwm) with dynamic fusion and Chinese character features, including 5-stroke code, Zheng code, phonological code, and stroke code, extracted by 1-dimensional convolutional neural networks (CNNs) to obtain fine-grained semantic features of Chinese characters. Subsequently, we converted Chinese characters into square images to obtain Chinese character image features from another modality by using a 2-dimensional CNN. Finally, we input multisemantic features into Bidirectional Long Short-Term Memory with Conditional Random Fields to achieve Chinese CNER. The effectiveness of our model was compared with that of the baseline and existing research models, and the features involved in the model were ablated and analyzed to verify the model's effectiveness. RESULTS: We collected 1379 Yidu-S4K EMRs containing 23,655 entities in 6 categories and 2007 self-annotated EMRs containing 118,643 entities in 7 categories. The experiments showed that our model outperformed the comparison experiments, with F1-scores of 89.28% and 84.61% on the Yidu-S4K and self-annotated data sets, respectively. The results of the ablation analysis demonstrated that each feature and method we used could improve the entity recognition ability. CONCLUSIONS: Our proposed CNER method would mine the richer deep semantic information in EMRs by multisemantic embedding using RoBERTa-wwm and CNNs, enhancing the semantic recognition of characters at different granularity levels and improving the generalization capability of the method by achieving information complementarity among different semantic features, thus making the machine semantically understand EMRs and improving the CNER task accuracy.

Inhibition of miR-200b-3p confers broad-spectrum resistance to viral infection by targeting TBK1.

The host innate immune system's defense against viral infections depends heavily on type I interferon (IFN-I) production. Research into the mechanisms of virus-host interactions is essential for developing novel antiviral therapies. In this study, we compared the effect of the five members of the microRNA-200 (miR-200) family on IFN-I production during viral infection and found that miR-200b-3p displayed the most pronounced regulatory effect. During viral infection, we discovered that the transcriptional level of microRNA-200b-3p (miR-200b-3p) increased with the infection of influenza virus (IAV) and vesicular stomatitis virus (VSV), and miR-200b-3p production was modulated by the activation of the ERK and p38 pathways. We identified cAMP response element binding protein (CREB) as a novel transcription factor that binds to the miR-200b-3p promoter. MiR-200b-3p reduces NF-κB and IRF3-mediated IFN-I production by targeting the 3' untranslated region (3' UTR) of TBK1 mRNA. Applying miR-200b-3p inhibitor enhances IFN-I production in IAV and VSV-infected mouse models, thus inhibiting viral replication and improving mouse survival ratio. Importantly, in addition to IAV and VSV, miR-200b-3p inhibitors exhibited potent antiviral effects against multiple pathogenic viruses threatening human health worldwide. Overall, our study suggests that miR-200b-3p might be a potential therapeutic target for broad-spectrum antiviral therapy. IMPORTANCE The innate immune response mediated by type I interferon (IFN-I) is essential for controlling viral replication. MicroRNAs (miRNAs) have been found to regulate the IFN signaling pathway. In this study, we describe a novel function of miRNA-200b-3p in negatively regulating IFN-I production during viral infection. miRNA-200b-3p was upregulated by the MAPK pathway activated by IAV and VSV infection. The binding of miRNA-200b-3p to the 3' UTR of TBK1 mRNA reduced IFN-I activation mediated by IRF3 and NF-κB. Application of miR-200b-3p inhibitors exhibited potent antiviral effects against multiple RNA and DNA viruses. These results provide fresh insight into understanding the impact of miRNAs on host-virus interactions and reveal a potential therapeutic target for common antiviral intervention.

Incidence of Metabolic Syndrome and Its Risk Factors in Elderly with Nonalcoholic Fatty Liver Disease.

Purpose: This study aimed to determine the incidence of metabolic syndrome (MetS) and its predictors in older patients with nonalcoholic fatty liver disease. Patients and Methods: This retrospective cohort study analyzed repeated health surveillance data collected between 2009 and 2018 at Mackay Memorial Hospital, Taiwan. MetS was defined based on the modified National Cholesterol Education Program Adult Treatment Panel III (Taiwan revision). Participants were diagnosed with fatty liver disease using abdominal ultrasonography. The exclusion criteria included age <65 years, having viral hepatitis, frequent alcohol consumption, and pre-existing MetS. Logistic regression analysis was conducted, adjusting for sex and age. Results: We enrolled 758 older participants; 457 (60.3%) with preexisting metabolic syndrome were excluded. We studied the remaining 301 participants (39.7%), with a mean age of 71.3 ± 5.4 years. The cumulative incidence of MetS was 43.5% after a mean follow-up period of 4.2 years; moreover, it was higher in women as well as in participants with diabetes and hypertriglyceridemia. After adjusting for age and sex, we identified the following risk factors for MetS: baseline high fasting plasma glucose levels (adjusted odds ratio [aOR] =1.75; 95% confidence interval [CI] 1.03-2.95), baseline hypertriglyceridemia (aOR = 2.26; 95% CI 1.15-4.47), and baseline large waist circumference (aOR =1.71; 95% CI 1.01-2.89). Furthermore, increased waist circumference and fasting plasma glucose levels at follow-up were significant risk factors. Conclusion: There is a high incidence of MetS among older individuals with nonalcoholic fatty liver disease; further, women and individuals with diabetes or hypertriglyceridemia are at risk of developing MetS. Moreover, waist circumference and fasting plasma glucose levels were positively associated with the risk of MetS.

The CH24H metabolite, 24HC, blocks viral entry by disrupting intracellular cholesterol homeostasis.

Cholesterol-24-hydroxylase (CH24H or Cyp46a1) is a reticulum-associated membrane protein that plays an irreplaceable role in cholesterol metabolism in the brain and has been well-studied in several neuro-associated diseases in recent years. In the present study, we found that CH24H expression can be induced by several neuroinvasive viruses, including vesicular stomatitis virus (VSV), rabies virus (RABV), Semliki Forest virus (SFV) and murine hepatitis virus (MHV). The CH24H metabolite, 24-hydroxycholesterol (24HC), also shows competence in inhibiting the replication of multiple viruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). 24HC can increase the cholesterol concentration in multivesicular body (MVB)/late endosome (LE) by disrupting the interaction between OSBP and VAPA, resulting in viral particles being trapped in MVB/LE, ultimately compromising VSV and RABV entry into host cells. These findings provide the first evidence that brain cholesterol oxidation products may play a critical role in viral infection.

Synergistic effects of multiword sequences structure, function, frequency and association on raters' evaluations of essay quality.

Despite accumulated research findings confirming the link of multiword sequences (MWSs) structures and functions to essay quality, as well as the connection between MWSs statistical features (e.g., their frequency and association strengths in BNC/COCA) and writing quality, to date no study integrated these two separate lines of investigations. It remains to investigate whether and how MWSs structures, functions and their statistical features jointly affect writing quality. Drawing on 900 rated argumentative essays composed by Chinese grade 12 students in National Matriculation Test, the present study employed CollGram to automatically identify the nativelike 4-word sequences in these essays and to analyze their frequency and Mutual Information (MI) scores in COCA. The structures and functions of frequent nativelike 4-word sequences were also analyzed manually. A serial of linear mixed-effect models was constructed to investigate their main effects as well as interaction effects on essay scores. The best fit model revealed the links of higher essay scores to higher MI scores, to more noun-phrase sequences, to more stance sequences, as well as to fewer referential sequences. Additionally, the interaction of prepositional phrase sequences and their frequency in COCA affected essay scores, so did the interaction of verb phrase sequences and their MI in COCA, as well as the interaction of noun phrase sequences and their MI in COCA. The findings provide new insights into the complex interaction between MWSs structures, functions and their statistical features, as well as their joint effects on writing quality.