Cyclosporin A Inhibits the Influenza Virus Replication through Cyclophilin A-Dependent and -Independent Pathways

The immunosuppressive drug cyclosporin A (CsA) has inhibitory effects on the replication of several viruses. The antiviral effects are through targeting the interaction between viral proteins and host factor cyclophilin A (CypA). CypA has been identified to interact with influenza A virus M1 protein and impair the early stage of the viral life cycle. In order to identify the effect of CsA on influenza virus replication, a CypA-depleted 293T cell line, which was named as 293T/CypA−, was constructed. The cytopathic effect (CPE) assay and the growth curve results indicated that CsA specifically suppressed the influenza A virus replication in a dose-dependent manner. CsA treatment had no effect on the viral genome replication and transcription but selectively suppressed the viral proteins expression. Further studies indicated that CsA could impair the nuclear export of viral mRNA in the absence of CypA. In addition, the antiviral activity of CsA was independent of calcineurin signaling. Finally, CsA could enhance the binding between CypA and M1. The above results suggested that CsA inhibited the replication of influenza A virus through CypA-dependent and -independent pathways

EvoMoE: An Evolutional Mixture-of-Experts Training Framework via Dense-To-Sparse Gate

Mixture-of-experts (MoE) is becoming popular due to its success in improving the model quality, especially in Transformers. By routing tokens with a sparse gate to a few experts (i.e., a small pieces of the full model), MoE can easily increase the model parameters to a very large scale while keeping the computation cost in a constant level. Most existing works just initialize some random experts, set a fixed gating strategy (e.g., Top-k), and train the model from scratch in an ad-hoc way. We identify that these MoE models are suffering from the immature experts and unstable sparse gate, which are harmful to the convergence performance. In this paper, we propose an efficient end-to-end MoE training framework called EvoMoE. EvoMoE starts from training one single expert and gradually evolves into a large and sparse MoE structure. EvoMoE mainly contains two phases: the expert-diversify phase to train the base expert for a while and spawn multiple diverse experts from it, and the gate-sparsify phase to learn an adaptive sparse gate and activate a dynamic number of experts. EvoMoE naturally decouples the joint learning of both the experts and the sparse gate and focuses on learning the basic knowledge with a single expert at the early training stage. Then it diversifies the experts and continues to train the MoE with a novel Dense-to-Sparse gate (DTS-Gate). Specifically, instead of using a permanent sparse gate, DTS-Gate begins as a dense gate that routes tokens to all experts, then gradually and adaptively becomes sparser while routes to fewer experts. Evaluations are conducted on three popular models and tasks, including RoBERTa for masked language modeling task, GPT for language modeling task and Transformer for machine translation task. The results show that EvoMoE outperforms existing baselines, including Switch, BASE Layer, Hash Layer and StableMoE

Phylogenetic signal in gut microbial community rather than in rodent metabolic traits

This work was supported by the National Natural Science Foundation of China (32090020, 32271575, 32070449, 31872232, and 32270508) and the Strategic Priority Research Program of the Chinese Academy of Sciences (XDPB16).Peer reviewedPublisher PD

Effects of LED spectrum on circadian rhythmic expression of clock genes and Aanat2 in the brain of juvenile European seabass (Dicentrarchus labrax)

The circadian rhythm is a physiological phenomenon that occurs in various organisms with a cycle of about 24 hours. Light is one of the important environmental factors affecting biological rhythm. To clarify whether a shift in light spectrum can influence the circadian expression in fish brain, a total of 175 European seabasses [body weight: 32.5 ± 0.71) g; body length: (13.78 ± 0.35) cm] were exposed to white light (WL), red light (RL), yellow light (YL), green light (GL) or blue light (BL). After 50 days of exposure, circadian expressions of four core clock genes (Clock, Bmal1, Per2, Cry1) and Aanat2 gene in brain were examined. The results showed that the temporal expression patterns of positive clock gens (Clock and Bmal1) showed increases during the scotophase and decreases during the photophase, with peaks near the middle of the darkness. Clock gene expression showed a stable circadian rhythm (R2 = 0.578-0.824, P=0.000- 0.027) in all light groups while Bmal1 showed circadian rhythm in WL, GL and RL, not in BL and YL. Daily expression patterns of the negative clock genes oscillated in the opposite phase from the positive clock genes, showing increasing mRNA levels during the light, decreases during the dark, and peaks near the shift from night to day, except Per2 in RL and Cry1 in BL. Compared with WL, the acrophases of Clock and Bmal1 were delayed under all light treatments (BL: + 3.7h, +6.73h; RL: +2.4h,+1.35h; YL: + 4.94h, 2.00h; GL: +0.05, +0.16h). Cry1 showed advanced acrophase under all light treatments (BL: -10.74 h, GL: -3.81 h, RL: -3.93 h, YL: -7.56 h) but Per2 showed delayed acrophase in all light treatments (GL: +0.86 h, RL: +10.35 h, YL: +9.62 h), except in BL (-0.43 h). The acrophase of Aanat2 was advanced by all monochromatic light, the Aanat2 level was significantly increased in RL compared with other light treatment. Therefore, the results indicate that RL may regulate the expression of Aanat2 gene by affecting the expression of clock gene in fish brain. Spectrum can affect the biological clock system of fish, and unreasonable spectrum may disturb the rhythm of gene expression of biological clock of fish. Under the irradiation of light spectrum, some clock genes still maintain obvious circadian oscillation, while the rhythm of some clock genes is not obvious and may be destroyed. Our findings suggest a primary role of light spectrum information to the fish brain circadian system

Variation detection based on next-generation sequencing of type Chinese 1 strains of Toxoplasma gondii with different virulence from China

A: Summary of annotation for SNPs; B: Summary of annotation for indels; C: Summary of annotation for SVs; D: Summary of annotation for CNVs. (DOCX 18 kb

A targeted next-generation sequencing method for identifying clinically relevant mutation profiles in lung adenocarcinoma

Molecular profiling of lung cancer has become essential for prediction of an individual’s response to targeted therapies. Next-generation sequencing (NGS) is a promising technique for routine diagnostics, but has not been sufficiently evaluated in terms of feasibility, reliability, cost and capacity with routine diagnostic formalin-fixed, paraffin-embedded (FFPE) materials. Here, we report the validation and application of a test based on Ion Proton technology for the rapid characterisation of single nucleotide variations (SNVs), short insertions and deletions (InDels), copy number variations (CNVs), and gene rearrangements in 145 genes with FFPE clinical specimens. The validation study, using 61 previously profiled clinical tumour samples, showed a concordance rate of 100% between results obtained by NGS and conventional test platforms. Analysis of tumour cell lines indicated reliable mutation detection in samples with 5% tumour content. Furthermore, application of the panel to 58 clinical cases, identified at least one actionable mutation in 43 cases, 1.4 times the number of actionable alterations detected by current diagnostic tests. We demonstrated that targeted NGS is a cost-effective and rapid platform to detect multiple mutations simultaneously in various genes with high reproducibility and sensitivity