Characterization of protein-protein interactions between the nucleocapsid protein and membrane protein of the avian infectious bronchitis virus

Avian infectious bronchitis virus (IBV) is one of the major viral respiratory diseases of chickens. Better understanding of the molecular mechanism of viral pathogenesis may contribute significantly to the development of prophylactic, therapeutic and diagnostic reagents as well as help in infection control. Avian IBV belongs to the Coronaviridaes and is similar to the other known coronaviruses. Previous studies have indicated that protein–protein interactions between nucleocapsid (N) and the membrane (M) proteins in coronavirus are related to coronavirus viral assembly. However, cases of IBV are seldom reported. In this study, yeast two-hybrid and  co-immunoprecipitation techniques were applied to investigate possible interactions between IBV N and M proteins. We found that interaction of the N and M proteins took place in vivo and the residues 168 – 225 of the M protein and the residues 150 - 210 of the N protein were determined to be involved in their interaction. These results may provide some useful information on the molecular mechanism of IBV’s N and M proteins, which will facilitate therapeutic strategies aiming at the disruption of the association between membrane and nucleocapsid proteins and indicate a new drug target for IBV.Key words: Co-immunoprecipitation, membrane protein, nucleocapsid protein, protein-protein interaction, yeast two-hybrid

COFFEE: Counterfactual Fairness for Personalized Text Generation in Explainable Recommendation

Personalized text generation has broad industrial applications, such as explanation generation for recommendations, conversational systems, etc. Personalized text generators are usually trained on user written text, e.g., reviews collected on e-commerce platforms. However, due to historical, social, or behavioral reasons, there may exist bias that associates certain linguistic quality of user written text with the users' protected attributes such as gender, race, etc. The generators can identify and inherit these correlations and generate texts discriminately w.r.t. the users' protected attributes. Without proper intervention, such bias can adversarially influence the users' trust and reliance on the system. From a broader perspective, bias in auto-generated contents can reinforce the social stereotypes about how online users write through interactions with the users. In this work, we investigate the fairness of personalized text generation in the setting of explainable recommendation. We develop a general framework for achieving measure-specific counterfactual fairness on the linguistic quality of personalized explanations. We propose learning disentangled representations for counterfactual inference and develop a novel policy learning algorithm with carefully designed rewards for fairness optimization. The framework can be applied for achieving fairness on any given specifications of linguistic quality measures, and can be adapted to most of existing models and real-world settings. Extensive experiments demonstrate the superior ability of our method in achieving fairness while maintaining high generation performance

An Efficient Approach for Real-Time Prediction of Rate of Penetration in Offshore Drilling

Predicting the rate of penetration (ROP) is critical for drilling optimization because maximization of ROP can greatly reduce expensive drilling costs. In this work, the typical extreme learning machine (ELM) and an efficient learning model, upper-layer-solution-aware (USA), have been used in ROP prediction. Because formation type, rock mechanical properties, hydraulics, bit type and properties (weight on the bit and rotary speed), and mud properties are the most important parameters that affect ROP, they have been considered to be the input parameters to predict ROP. The prediction model has been constructed using industrial reservoir data sets that are collected from an oil reservoir at the Bohai Bay, China. The prediction accuracy of the model has been evaluated and compared with the commonly used conventional artificial neural network (ANN). The results indicate that ANN, ELM, and USA models are all competent for ROP prediction, while both of the ELM and USA models have the advantage of faster learning speed and better generalization performance. The simulation results have shown a promising prospect for ELM and USA in the field of ROP prediction in new oil and gas exploration in general, as they outperform the ANN model. Meanwhile, this work provides drilling engineers with more choices for ROP prediction according to their computation and accuracy demand

CritiqueLLM: Scaling LLM-as-Critic for Effective and Explainable Evaluation of Large Language Model Generation

Since the natural language processing (NLP) community started to make large language models (LLMs), such as GPT-4, act as a critic to evaluate the quality of generated texts, most of them only train a critique generation model of a specific scale on specific datasets. We argue that a comprehensive investigation on the key factor of LLM-based evaluation models, such as scaling properties, is lacking, so that it is still inconclusive whether these models have potential to replace GPT-4's evaluation in practical scenarios. In this paper, we propose a new critique generation model called CritiqueLLM, which includes a dialogue-based prompting method for high-quality referenced / reference-free evaluation data. Experimental results show that our model can achieve comparable evaluation performance to GPT-4 especially in system-level correlations, and even outperform GPT-4 in 3 out of 8 tasks in a challenging reference-free setting. We conduct detailed analysis to show promising scaling properties of our model in the quality of generated critiques. We also demonstrate that our generated critiques can act as scalable feedback to directly improve the generation quality of LLMs.Comment: 18 pages, 5 figure

Identification of compound heterozygous variants in the noncoding RNU4ATAC gene in a Chinese family with two successive foetuses with severe microcephaly

Background: Whole-exome sequencing (WES) over the last few years has been increasingly employed for clinical diagnosis. However, one caveat with its use is that it inevitably fails to detect disease-causative variants that occur within noncoding RNA genes. Our experience in identifying pathogenic variants in the noncoding RNU4ATAC gene, in a Chinese family where two successive foetuses had been affected by severe microcephaly, is a case in point. These foetuses exhibited remarkably similar phenotypes in terms of their microcephaly and brain abnormalities; however, the paucity of other characteristic phenotypic features had made a precise diagnosis impossible. Given that no external causative factors had been reported/identified during the pregnancies, we sought a genetic cause for the phenotype in the proband, the second affected foetus. Results: A search for chromosomal abnormalities and pathogenic copy number variants proved negative. WES was also negative. These initial failures prompted us to consider the potential role of RNU4ATAC, a noncoding gene implicated in microcephalic osteodysplastic primordial dwarfism type-1 (MOPD1), a severe autosomal recessive disease characterised by dwarfism, severe microcephaly and neurological abnormalities. Subsequent targeted sequencing of RNU4ATAC resulted in the identification of compound heterozygous variants, one being the most frequently reported MOPD1-causative mutation (51G>A), whereas the other was a novel 29T>A variant. Four distinct lines of evidence (allele frequency in normal populations, evolutionary conservation of the affected nucleotide, occurrence within a known mutational hotspot for MOPD1-causative variants and predicted effect on RNA secondary structure) allowed us to conclude that 29T>A is a new causative variant for MOPD1. Conclusions: Our findings highlight the limitations of WES in failing to detect variants within noncoding RNA genes and provide support for a role for whole-genome sequencing as a first-tier genetic test in paediatric medicine. Additionally, the identification of a novel RNU4ATAC variant within the mutational hotspot for MOPD1-causative variants further strengthens the critical role of the 5′ stem-loop structure of U4atac in health and disease. Finally, this analysis enabled us to provide prenatal diagnosis and genetic counselling for the mother’s third pregnancy, the first report of its kind in the context of inherited RNU4ATAC variants

Nao-Xue-Shu

Aim. To determine one traditional Chinese medicine (TCM) Nao-Xue-Shu oral liquid which protects and improves secondary brain insults (SBI) in hypertensive cerebral hemorrhage (HCH). Methods. 158 patients with HCH were divided into routine clinical medicine plus Nao-Xue-Shu oral liquid (n=78) as treatment group, and routine clinical medicine (n=80) only served as the control group. The incidence of SBI and the classification of a favorable prognosis and a bad prognosis using the Glasgow outcome scale (GOS) were assessed to evaluate the clinical effects. The changes of IL-6 and TNF-α levels were determined to study the mechanism of the effects for the TCM. Results. The incidence of SBI at the end of week 2 was 8.97% in the treatment group and 23.75% in the control group, and the difference was significant (P<0.001). The incidence of a favorable prognosis was 48.72% in the treatment group and 32.72% in the control group, and the difference was significant (P<0.01) at the end of week 2. These findings indicate clear differences for IL-6 and TNF-α at the end of week 1 and week 2 compared with before treatment for the treatment group and a marked difference at the end of week 2 between the two groups. It also shows a significant difference between the end of week 2 and before treatment for IL-6 and TNF-α for the control group, although the difference was much smaller than the treatment group. Conclusion. Nao-Xue-Shu oral liquid could protect against the occurrence of SBI and improve HCH and SBI patients. It may also decrease the damage and the mass effects of the hematoma by reducing IL-6 and TNF-α to obtain the effects, and thus it is a potentially suitable drug for HCH and SBI

The Prevalence of Colistin Resistant Strains and Antibiotic Resistance Gene Profiles in Funan River, China

Anthropogenic activities near urban rivers may have significantly increased the acquisition and dissemination of antibiotic resistance. In this study, we investigated the prevalence of colistin resistant strains in the Funan River in Chengdu, China. A total of 18 mcr-1-positive isolates (17 Escherichia coli and 1 Enterobacter cloacae) and 6 mcr-3-positive isolates (2 Aeromonas veronii and 4 Aeromonas hydrophila) were detected, while mcr-2, mcr-4 and mcr-5 genes were not detected in any isolates. To further explore the overall antibiotic resistance in the Funan River, water samples were assayed for the presence of 15 antibiotic resistance genes (ARGs) and class 1 integrons gene (intI1). Nine genes, sul1, sul2, intI1, aac(6′)-Ib-cr, blaCTX-M, tetM, ermB, qnrS, and aph(3′)-IIIa were found at high frequencies (70–100%) of the water samples. It is worth noting that mcr-1, blaKPC, blaNDM and vanA genes were also found in water samples, the genes that have been rarely reported in natural river systems. The absolute abundance of selected antibiotic resistance genes [sul1, aac(6′)-Ib-cr, ermB, blaCTX-M, mcr-1, and tetM] ranged from 0 to 6.0 (log10 GC/mL) in water samples, as determined by quantitative polymerase chain reaction (qPCR). The sul1, aac(6′)-Ib-cr, and ermB genes exhibited the highest absolute abundances, with 5.8, 5.8, and 6.0 log10 GC/mL, respectively. The absolute abundances of six antibiotic resistance genes were highest near a residential sewage outlet. The findings indicated that the discharge of resident sewage might contribute to the dissemination of antibiotic resistant genes in this urban river. The observed high levels of these genes reflect the serious degree of antibiotic resistant pollution in the Funan River, which might present a threat to public health

Metagenomic Sequencing From Mosquitoes in China Reveals a Variety of Insect and Human Viruses

We collected 8,700 mosquitoes in three sites in China, which belonged to seven species. Their viromes were tested using metagenomic sequencing and bioinformatic analysis. The abundant viral sequences were detected and annotated belonging to more than 50 viral taxonomic families. The results were verified by PCR, followed by phylogenetic analysis. In the present study, we identified partial viral genes of dengue virus (DENV), a novel circovirus (CCV), densovirus (DNV), Japanese encephalitis virus (JEV), and Wuhan mosquito virus (WMV) in mosquitoes. Metagenomic analysis and PCR amplification revealed three DENV sequences, which were as homologous to the NS3 gene of DENV from Singapore isolated in 2005, with at least 91% nucleotide (nt) identity. Seven fragments of JEV encoding structural proteins were identified belonging to genotype I. They all shared high homology with structural protein genes of JEV isolated from Laos in 2009. The production of infectious virus particles of the newly isolated virus YunnanJEV2017-4 increased after passage from the BHK-21 cell line to the Vero cell line. Novel circovirus-related genes were identified and as being related to an unnamed gene of a mosquito circovirus (MCCV) sequence from the USA isolated in 2011, with at least 41% nt identity: this distant relationship suggests that the parent virus might belong to a novel circovirus genus. Additionally, numerous known viruses and some unknown viruses were also detected in mosquitoes from Yunnan province, China, which will be tested for propagation

Metagenomic Analysis of Flaviviridae in Mosquito Viromes Isolated From Yunnan Province in China Reveals Genes From Dengue and Zika Viruses

More than 6,000 mosquitoes of six species from six sites were collected and tested for their virome using metagenomics sequencing and bioinformatic analysis. The identified viral sequences belonged to more than 50 viral families. The results were verified by PCR of selected viruses in all mosquitoes, followed by phylogenetic analysis. In the present study, we identified the partial dengue virus (DENV), Zika virus (ZIKV), and Japanese encephalitis virus (JEV) sequences in mosquitoes. Metagenomic analysis and the PCR amplification revealed three DENV sequences, one of which encodes a partial envelope protein. Two ZIKV sequences both encoding partial nonstructural protein 3 and one JEV sequence encoding the complete envelope protein were identified. There was variability in the viral titers of the newly isolated virus JEV-China/YN2016-1 of different passage viruses. The newly identified Zika virus gene from ZIKV-China/YN2016-1 was an Asian genotype and shared the highest nucleotide sequence identity (97.1%) with a ZIKV sequence from Thailand isolated in 2004. Phylogenetic analysis of ZIKV-China/YN2016-1 and ZIKV-China/YN2016-2 with known Flavivirus genes indicated that ZIKV has propagated in Yunnan province, China