Single-cell RNA-seq landscape midbrain cell responses to red spotted grouper nervous necrosis virus infection.

Viral nervous necrosis (VNN) is an acute and serious fish disease caused by nervous necrosis virus (NNV) which has been reported massive mortality in more than fifty teleost species worldwide. VNN causes damage of necrosis and vacuolation to central nervous system (CNS) cells in fish. It is difficult to identify the specific type of cell targeted by NNV, and to decipher the host immune response because of the functional diversity and highly complex anatomical and cellular composition of the CNS. In this study, we found that the red spotted grouper NNV (RGNNV) mainly attacked the midbrain of orange-spotted grouper (Epinephelus coioides). We conducted single-cell RNA-seq analysis of the midbrain of healthy and RGNNV-infected fish and identified 35 transcriptionally distinct cell subtypes, including 28 neuronal and 7 non-neuronal cell types. An evaluation of the subpopulations of immune cells revealed that macrophages were enriched in RGNNV-infected fish, and the transcriptional profiles of macrophages indicated an acute cytokine and inflammatory response. Unsupervised pseudotime analysis of immune cells showed that microglia transformed into M1-type activated macrophages to produce cytokines to reduce the damage to nerve tissue caused by the virus. We also found that RGNNV targeted neuronal cell types was GLU1 and GLU3, and we found that the key genes and pathways by which causes cell cytoplasmic vacuoles and autophagy significant enrichment, this may be the major route viruses cause cell death. These data provided a comprehensive transcriptional perspective of the grouper midbrain and the basis for further research on how viruses infect the teleost CNS.

DIMENSION: Dynamic MR imaging with both k-space and spatial prior knowledge obtained via multi-supervised network training.

Dynamic MR image reconstruction from incomplete k-space data has generated great research interest due to its capability in reducing scan time. Nevertheless, the reconstruction problem is still challenging due to its ill-posed nature. Most existing methods either suffer from long iterative reconstruction time or explore limited prior knowledge. This paper proposes a dynamic MR imaging method with both k-space and spatial prior knowledge integrated via multi-supervised network training, dubbed as DIMENSION. Specifically, the DIMENSION architecture consists of a frequential prior network for updating the k-space with its network prediction and a spatial prior network for capturing image structures and details. Furthermore, a multi-supervised network training technique is developed to constrain the frequency domain information and the spatial domain information. The comparisons with classical k-t FOCUSS, k-t SLR, L+S and the state-of-the-art CNN-based method on in vivo datasets show our method can achieve improved reconstruction results in shorter time.

Effects of nanoplastic exposure on the immunity and metabolism of red crayfish (Cherax quadricarinatus) based on high-throughput sequencing.

Previous studies have shown that nanoplastics (NPs) are harmful pollutants that threaten aquatic organisms and ecosystems, however, less research has been conducted on the hazards of NPs for aquaculture animals. In this study, Cherax quadricarinatus was used as an experimental model to evaluate the possible effects of three concentrations (25, 250 and 2500 µg/L) of NPs on red crayfish. The toxicological effects of NPs on this species were investigated based on transcriptomics and microbiome. A total of 67,668 genes were obtained from the transcriptome. The annotation rate of the four major libraries (Nr, KEGG, KOG, Swissprot) was 40.17 %, and the functions of differential genes were mainly related to antioxidant activity, metabolism and immune processes. During the experiment, the activities of superoxide dismutase (SOD) and catalase (CAT) in the high concentration group were significantly decreased, while the concentration of malondialdehyde (MDA) increased after nanoplastics (NPs) exposure, and SOD1, Jafrac1 were significantly reduced at high concentrations. expression is inhibited. The immune genes LYZ and PPO2 were highly expressed at low concentrations and suppressed at high concentrations. After 14 days of exposure to NPs, significant changes in gut microbiota were observed, such as decreased abundances of Actinobacteria, Bacteroidetes, and Firmicutes. NPs compromise host health by inducing changes in microbial communities and the production of beneficial bacterial metabolites. Overall, these results suggest that NPs affect immune-related gene expression and antioxidant enzyme activity in red crayfish and cause redox imbalance in the body, altering the composition and diversity of the gut microbiota.

Highly undersampled magnetic resonance imaging reconstruction using autoencoding priors.

PURPOSE: Although recent deep learning methodologies have shown promising results in fast MR imaging, how to explore it to learn an explicit prior and leverage it into the observation constraint is still desired. METHODS: A denoising autoencoder (DAE) network is leveraged as an explicit prior to address the highly undersampling MR image reconstruction problem. First, inspired by the observation that the prior information learned from high-dimension signals is more effective than that from the low-dimension counterpart in image restoration tasks, we train the network in a multichannel scenario and apply the learned network to single-channel image reconstruction by a variables augmentation technique. Second, because of the fact that multiple implementations of artificial noise generation in DAE favors a better underlying result, we introduce a 2-sigma rule to complement each other for improving the final reconstruction. The whole algorithm is tackled by proximal gradient descent. RESULTS: Experimental results under varying sampling trajectories and acceleration factors consistently demonstrate the superiority of the enhanced autoencoding priors, in terms of peak signal-to-noise ratio, structural similarity, and high-frequency error norm. CONCLUSION: A simple and effective way to incorporate the DAE prior into highly undersampling MR reconstruction is proposed. Once the DAE prior is obtained, it can be applied to the reconstruction tasks with different sampling trajectories and acceleration factors, and achieves superior performance in comparison with state-of-the-art methods.

The complete mitochondrial genome of Allogalathea elegans (Adams & White, 1848) (Decapoda: Galatheidae).

The genus Allogalathea belongs to the subfamily Galatheoidea of the family Galatheidae. Here, we report a mitogenome of Allogalathea elegans (Adams & White, 1848). In this study, we obtained the complete mitochondrial genome of Allogalathea elegans by sequencing, which was 16,263 bp in length. The mitogenome contained 37 genes, including the typical set of 13 protein-coding genes (PCGs), 22 transfer RNA (tRNA) genes, and 2 Ribosomal RNA (rRNA) genes. The nucleotides A, C, G, and T distribution was 36.40%, 19.44%, 9.09%, and 35.07%, respectively. The length of the total protein-coding genes was 11,172 bp, which accounts for 68.69% of the whole mitochondrial genome. The phylogenetic result generated by IQ-Tree based on 13 PGCs showed that the infraorder Anomura is monophyletic, and the infraorder Anomura is a sister group of the infraorder Glypheidea. The discovery of the complete mitochondrial genome of A. elegans would help to conduct in-depth research on the infraorder Anomura.

The complete mitochondrial genome of Hypseleotris cyprinoides (Perciformes: eleotridae).

In this study, we obtained the complete mitochondrial genome of Hypseleotris cyprinoides, which was 16520 bp in length. The mitogenome contained 37 genes, including the typical set of 13 protein-coding genes (PCGs), 22 transfer RNA (tRNA) genes, and 2 Ribosomal RNA (rRNA) genes. A, C, G, and T distribution was 28.57%, 29.91%, 16.99%, and 24.53%, respectively. The length of the total protein-coding genes was 11441 bp, which accounts for 66.80% of the whole mitochondrial genome. The Maximum Likelihood (ML) phylogenetic analysis based on the concatenated nucleotide sequences of 13 PCGs showed that H.cyprinoides as a sister species to Hypseleotris klunzingeri was clustered in the family Hypseleotris. The discovery of the complete mitochondrial genome of H.cyprinoides would help to conduct in-depth research on Hypseleotris.

The ERß-CXCL19/CXCR4-NFκB pathway is critical in mediating the E2-induced inflammation response in the orange-spotted grouper (Epinephelus coioides).

The main physiological function of 17ß-estradiol (E2) in vertebrates is to regulate sexual development and reproduction. In fish, especially hermaphroditic fish, estrogen is often used to aid reproduction, but it also can trigger an inflammatory response. However, the molecular mechanism for this E2-induced inflammatory reaction is not clear. In this study, we found that the ERß-CXCL19/CXCR4-NFκB cascade regulated the E2-induced inflammatory response in the orange-spotted grouper (Epinephelus coioides). Strikingly, E2 treatment resulted in significantly high expression of inflammatory cytokines and induced phosphorylation and degradation of IκBα and translocation of NFκB subunit p65 to the nucleus in grouper spleen cells. However, the E2-induced inflammatory response could be prevented by the broad estrogen receptor (ER) ligand ICI 182,780. Moreover, the luciferase assay showed that E2 induced the inflammatory response by activating the promotor of chemokine CXCL19 through ERß1 and ERß2. Knockdown of CXCL19 blocked the E2-induced inflammatory response and NFκB nucleus translocation. Additionally, knockdown of chemokines CXCR4a and CXCR4b together, but not alone, blocked the E2-induced inflammatory response. The immunofluorescence assay and co-immunoprecipitation analysis showed that CXCL19 mediated the E2-induced inflammatory response by activating CXCR4a or CXCR4b. Taken together, these results showed that the ERß-CXCL19/CXCR4-NFκB pathway mediated the E2-induced inflammatory response in grouper. These findings are valuable for future comparative immunological studies and provide a theoretical basis for mitigating the adverse reactions that occur when using E2 to help fish reproduce.

Polystyrene nanoplastics alter virus replication in orange-spotted grouper (Epinephelus coioides) spleen and brain tissues and spleen cells.

Polystyrene nanoplastics (PS-NPs) are known to impair the function of the digestive system, intestinal flora, immune system, and nervous system of marine organisms. We tested whether PS-NPs influence viral infection of orange-spotted grouper (Epinephelus coioides). We found that grouper spleen (GS) cells took up PS-NPs at exposure concentrations of 5, 50, and 500 µg/mL and experienced cytotoxicity at 50 and 500 µg/mL concentrations. At 12 h after exposure to 50 µg/mL of PS-NPs, the replication of Singapore grouper iridovirus (SGIV) and red-spotted grouper nervous necrosis virus (RGNNV) increased in GS cells after their invasion. Juvenile fish exposed to 300 and 3000 µg/L of PS-NPs for 7 d showed PS-NPs uptake to the spleen and vacuole formation in brain tissue. Moreover, PS-NPs exposure accelerated SGIV replication in the spleen and RGNNV replication in the brain. PS-NP exposure also decreased the expression of toll-like receptor genes and interferon-related genes before and after virus invasion in vitro and in vivo, thus reducing the resistance of cells and tissues to viral replication. This is the first report that PS-NPs have toxic effects on GS cells and spleen and brain tissues, and it provides new insights into assessing the impact of PS-NPs on marine fish.

DeepcomplexMRI: Exploiting deep residual network for fast parallel MR imaging with complex convolution.

This paper proposes a multi-channel image reconstruction method, named DeepcomplexMRI, to accelerate parallel MR imaging with residual complex convolutional neural network. Different from most existing works which rely on the utilization of the coil sensitivities or prior information of predefined transforms, DeepcomplexMRI takes advantage of the availability of a large number of existing multi-channel groudtruth images and uses them as target data to train the deep residual convolutional neural network offline. In particular, a complex convolutional network is proposed to take into account the correlation between the real and imaginary parts of MR images. In addition, the k-space data consistency is further enforced repeatedly in between layers of the network. The evaluations on in vivo datasets show that the proposed method has the capability to recover the desired multi-channel images. Its comparison with state-of-the-art methods also demonstrates that the proposed method can reconstruct the desired MR images more accurately.