MUSCLE: multi-view and multi-scale attentional feature fusion for microRNA-disease associations prediction.

MicroRNAs (miRNAs) synergize with various biomolecules in human cells resulting in diverse functions in regulating a wide range of biological processes. Predicting potential disease-associated miRNAs as valuable biomarkers contributes to the treatment of human diseases. However, few previous methods take a holistic perspective and only concentrate on isolated miRNA and disease objects, thereby ignoring that human cells are responsible for multiple relationships. In this work, we first constructed a multi-view graph based on the relationships between miRNAs and various biomolecules, and then utilized graph attention neural network to learn the graph topology features of miRNAs and diseases for each view. Next, we added an attention mechanism again, and developed a multi-scale feature fusion module, aiming to determine the optimal fusion results for the multi-view topology features of miRNAs and diseases. In addition, the prior attribute knowledge of miRNAs and diseases was simultaneously added to achieve better prediction results and solve the cold start problem. Finally, the learned miRNA and disease representations were then concatenated and fed into a multi-layer perceptron for end-to-end training and predicting potential miRNA-disease associations. To assess the efficacy of our model (called MUSCLE), we performed 5- and 10-fold cross-validation (CV), which got average the Area under ROC curves of 0.966${\pm }$0.0102 and 0.973${\pm }$0.0135, respectively, outperforming most current state-of-the-art models. We then examined the impact of crucial parameters on prediction performance and performed ablation experiments on the feature combination and model architecture. Furthermore, the case studies about colon cancer, lung cancer and breast cancer also fully demonstrate the good inductive capability of MUSCLE. Our data and code are free available at a public GitHub repository: https://github.com/zht-code/MUSCLE.git.

A multi-source molecular network representation model for protein-protein interactions prediction.

The prediction of potential protein-protein interactions (PPIs) is a critical step in decoding diseases and understanding cellular mechanisms. Traditional biological experiments have identified plenty of potential PPIs in recent years, but this problem is still far from being solved. Hence, there is urgent to develop computational models with good performance and high efficiency to predict potential PPIs. In this study, we propose a multi-source molecular network representation learning model (called MultiPPIs) to predict potential protein-protein interactions. Specifically, we first extract the protein sequence features according to the physicochemical properties of amino acids by utilizing the auto covariance method. Second, a multi-source association network is constructed by integrating the known associations among miRNAs, proteins, lncRNAs, drugs, and diseases. The graph representation learning method, DeepWalk, is adopted to extract the multisource association information of proteins with other biomolecules. In this way, the known protein-protein interaction pairs can be represented as a concatenation of the protein sequence and the multi-source association features of proteins. Finally, the Random Forest classifier and corresponding optimal parameters are used for training and prediction. In the results, MultiPPIs obtains an average 86.03% prediction accuracy with 82.69% sensitivity at the AUC of 93.03% under five-fold cross-validation. The experimental results indicate that MultiPPIs has a good prediction performance and provides valuable insights into the field of potential protein-protein interactions prediction. MultiPPIs is free available at https://github.com/jiboyalab/multiPPIs .

MHGTMDA: Molecular heterogeneous graph transformer based on biological entity graph for miRNA-disease associations prediction.

MicroRNAs (miRNAs) play a crucial role in the prevention, prognosis, diagnosis, and treatment of complex diseases. Existing computational methods primarily focus on biologically relevant molecules directly associated with miRNA or disease, overlooking the fact that the human body is a highly complex system where miRNA or disease may indirectly correlate with various types of biomolecules. To address this, we propose a novel prediction model named MHGTMDA (miRNA and disease association prediction using heterogeneous graph transformer based on molecular heterogeneous graph). MHGTMDA integrates biological entity relationships of eight biomolecules, constructing a relatively comprehensive heterogeneous biological entity graph. MHGTMDA serves as a powerful molecular heterogeneity map transformer, capturing structural elements and properties of miRNAs and diseases, revealing potential associations. In a 5-fold cross-validation study, MHGTMDA achieved an area under the receiver operating characteristic curve of 0.9569, surpassing state-of-the-art methods by at least 3%. Feature ablation experiments suggest that considering features among multiple biomolecules is more effective in uncovering miRNA-disease correlations. Furthermore, we conducted differential expression analyses on breast cancer and lung cancer, using MHGTMDA to further validate differentially expressed miRNAs. The results demonstrate MHGTMDA's capability to identify novel MDAs.

Redox Targeting-based Neutral Aqueous Flow Battery with High Energy Density and Low Cost.

Neutral aqueous flow batteries with common traits of the redox flow batteries, such as the independence of energy and power, scalability and operational flexibility, and additional merits of outstanding safety and low corrosivity show great promise for storing massive electrical energy from solar and wind energy. Particularly, the ferricyanide/ferrocyanide ([Fe(CN)6 ]3-/4- ) couple has been intensively employed as redox mediator to store energy in the catholyte ascribed to its abundance, low corrosivity, remarkable redox reversibility and stability. However, the low energy density arising from poor solubility of [Fe(CN)6 ]3-/4- restricts their commercial applications for energy storage systems. In this study, the practical energy density of a [Fe(CN)6 ]3-/4- -based catholyte is significantly boosted from 10.5 to 92.8 Wh L-1 by combining the counter-ion effect and the single-molecule redox-targeting (SMRT) reactions between [Fe(CN)6 ]3-/4- and Prussian blue (Fe4 [Fe(CN)6 ]3 , PB)/Prussian white (PW). Paired with concentrated K2 S anolyte, we demonstrate a neutral aqueous SMRT-based PB-Fe/S flow battery with ultra-long lifespan over 7000 cycles (4500 h) and ultra-low chemical cost of electrolytes in the cell as 19.26 $ kWh-1 . Remarkably, under the influences of SMRT reactions in the presence of PB granules in the catholyte, the capacity after 7000 cycles of the PB-Fe/S flow battery is 181.8 % of the initial capacity without PB.

Effects of antimony exposure on DNA damage and genome-wide variation in zebrafish (Danio rerio) liver.

Antimony (Sb) is a potentially toxic and carcinogenic cumulative contaminant that poses a serious threat to aquatic ecosystems. To better clarify the genotoxicity of Sb and its mechanism of action. In this study, we investigated DNA damage and genome-wide variation in the liver of a model organism, zebrafish (Danio rerio), under subacute Sb exposure and explored its potential toxicological mechanisms. The results showed that medium and high concentrations of Sb significantly reduced the total antioxidant capacity and increased the content of reactive oxygen species in zebrafish liver, and further studies revealed that it increased oxidative DNA damage and DNA-DNA cross-link (DDC), but had little effect on DNA-protein cross-link (DPC). The result of resequencing showed that the mutation sites of the genes with high concentrations of Sb were higher than those with medium concentrations, and the mutation was mainly a single nucleotide. The pathways significantly enriched for nonsynonymous single nucleotide polymorphisms (SNPs) and insertion/deletion mutations (InDels) variant genes in the coding regions of both the medium and high Sb-treated groups were ECM-receptor interactions, and the high Sb-treated group also included lysine degradation, hematopoietic cell lineage, and cytokine-cytokine receptor interactions. This suggests that ECM-receptor interactions play an important role in the mechanism of antimony toxicity to the liver of zebrafish.

Antimony accumulation in zebrafish (Danio rerio) and its effect on genotoxicity, histopathology, and ultrastructure.

Antimony (Sb) is a toxic metal in aquatic ecosystems. In this study, the accumulation of aqueous Sb in the liver, brain, gills and muscle of zebrafish (Danio rerio) and its effect on genotoxicity, histopathology and ultrastructure alterations were evaluated. The fishes were exposed to different concentrations (0, 8.29, 16.58, 33.16 mg L-1) of aqueous Sb for 18 days. The results showed that the order of Sb accumulation in different tissues was liver > gill > muscle > brain, and the accumulation increased with increasing Sb stress concentration. The mRNA expression levels of Nrf2, Cu/Zn-SOD, Mn-SOD, CAT and GPx genes showed different trends. In addition, significant histopathology and ultrastructure alterations were observed in the liver and gills exposed to Sb. Sb could accumulate in different tissues of zebrafish, inducing the expression of oxidative stress genes and activating antioxidant defense systems. Histological and ultrastructural changes could be used as valid biomarkers for the assessment of aqueous Sb contamination.

Are High- or Low-dose SGLT2 Inhibitors Associated With Cardiovascular and Respiratory Adverse Events? A Meta-analysis.

ABSTRACT: The association between high-dose or low-dose sodium-glucose cotransporter 2 (SGLT2) inhibitors and various cardiovascular and respiratory serious adverse events (SAE) is unclear. Our meta-analysis aimed to define the association between high-dose or low-dose SGLT2 inhibitors and 86 kinds of cardiovascular SAE and 58 kinds of respiratory SAE. We included large cardiorenal outcome trials of SGLT2 inhibitors. Meta-analysis was conducted and stratified by the dose of SGLT2 inhibitors (high dose or low dose) to synthesize risk ratio (RR) and 95% confidence interval (CI). We included 9 trials. Compared with placebo, SGLT2 inhibitors used at high dose or low dose were associated with the decreased risks of 6 kinds of cardiovascular SAE [eg, bradycardia (RR, 0.60; 95% CI, 0.41-0.89), atrial fibrillation (RR, 0.79; 95% CI, 0.69-0.92), and hypertensive emergency (RR, 0.34; 95% CI, 0.15-0.78)] and 6 kinds of respiratory SAE [eg, asthma (RR, 0.59; 95% CI, 0.37-0.93), chronic obstructive pulmonary disease (RR 0.77, 95% CI 0.62-0.96), and sleep apnea syndrome (RR 0.37, 95% CI 0.17-0.81)]. SGLT2 inhibitors used at high dose or low dose did not show significant associations with 132 other cardiopulmonary SAE. For any outcome of interest, the subgroup difference according to the dose of SGLT2 inhibitors was not significant (Psubgroup > 0.05). SGLT2 inhibitors used at whether high dose or low dose are associated with the decreased risks of 12 cardiopulmonary disorders (eg, bradycardia, atrial fibrillation, hypertensive emergency, asthma, chronic obstructive pulmonary disease, and sleep apnea syndrome). These findings may suggest the potential efficacy of high- or low-dose SGLT2 inhibitors for the prevention and treatment of these cardiopulmonary disorders.

A novel CAV derived cell-penetrating peptide efficiently delivers exogenous molecules through caveolae-mediated endocytosis.

Cell-penetrating peptide (CPP) is a promising cargo for delivering bioactive molecules. In this study, the N terminus of VP1 from chicken anemia virus, designated as CVP1, was found to carry enriched arginine residues with α-helix. By confocal imaging, flow cytometry and MTT assay, we identified CVP1 as a novel, safe and efficient CPP. CVP1-FITC peptide could entry different types of cells tested with dose dependence, but without cytotoxic effects. Compared with TAT-FITC peptide, the CVP1-FITC peptide showed much higher cell-penetrating activity. Moreover, CVP1 could successfully deliver ß-glycosidase, poly (I:C) and plasmid into HCT116 cells. Inhibitors and temperature sensitivity analysis further indicated that the cell-penetrating activity of CVP1 was based on ATP-dependent and caveolae-mediated endocytosis. All these data demonstrate that CVP1 has efficient cell-penetrating activity and great potential for developing a novel delivery vector.

Toll-like receptor 3 pathway restricts Marek's disease virus infection.

Marek's disease virus (MDV) is an α-herpesvirus that causes immune suppression and T lymphoma in chickens. Toll-like receptor 3 (TLR3) is critical for the host immune response against MDV infection. Previously, our team demonstrated that pre-treatment of TLR3 agonist poly (I:C) inhibited Marek's disease virus infection in chicken embryo fibroblasts (CEFs). However, whether TLR3 inhibits the aggravation of MDV infection is unknown. In the current study, we found that TLR3 activation in MDV-infected CEFs effectively inhibited virus spread. Using pharmacological approaches, we revealed that pro-inflammatory cytokines and interferon-ß induced by TLR3 could restrict Marek's disease virus infection. This study contributes to elucidating the function and mechanism of the TLR3 pathway in host immune responses against MDV infection.

Double-stranded RNA induces chicken T-cell lymphoma apoptosis by TRIF and NF-κB.

Toll-like receptor-3 (TLR3), a member of the pathogen recognition receptor family, has been reported to activate immune response and to exhibit pro-apoptotic activity against some tumor cells. However it is unclear whether TLR3 has same function against chicken lymphoma. In this paper we investigated the effect of TLR3 activation on a Marek's disease lymphoma-derived chicken cell line, MDCC-MSB1. The TLR3 agonist poly (I:C) activated TLR3 pathway and inhibited tumor cells proliferation through caspase-dependent apoptosis. Using pharmacological approaches, we found that an interferon-independent mechanism involving Toll-IL-1-receptor domain-containing adapter-inducing IFN-α (TRIF) and nuclear factor κB (NF-κB) causes the apoptosis of MDCC-MSB1 cells. This is the first report about the function of TLR3 in chicken T-cell lymphoma, especially in signal pathway. The mechanisms underlying TLR3-mediated apoptosis may contribute to the development of new drug to treat lymphomas and oncovirus infections.

Activation of Toll-like receptor 3 inhibits Marek's disease virus infection in chicken embryo fibroblast cells.

Toll-like receptor 3 (TLR3) is a critical component of the innate immune system against viral infection and controls the activation of adaptive immunity. The role of TLR3 in Marek's disease virus (MDV) infection is not clear. In this study, we found that the abundance of TLR3 mRNA was significantly higher in chicken embryo fibroblast cells (CEF) infected with MDV than in a control group. Activated TLR3 signaling via TLR3 ligand stimulation inhibited replication of the RB1B strain of MDV in CEF cells. In contrast, CEF cells transfected with TLR3 siRNA promoted RB1B infection and replication. However, treatment with other TLR ligands, whether stimulatory (LPS, imiquimod and CpG) or inhibitory (TLR2/4 inhibitor and/or MyD88 inhibitor), had little effect on RB1B infection and replication. In addition, we found that the expression trend of TLR3 mRNA in RB1B-infected CEF cells was similar to that of mdv1-mir-M4-5p (a functional ortholog of oncogenic miR-155 encoded by MDV). Inconsistent with this, the TLR3 protein level was sharply reduced in RB1B-infected CEF cells at 96 hpi, while there was an at least 200-fold increase in miR-M4-5p at the same time point. Additionally, CEF cells transfected with an mdv1-mir-M4-5p mimic promoted RB1B infection and replication, while an mdv1-mir-M4-5p inhibitor inhibited RB1B infection and replication. Similar results were observed in CEF cells transfected with a gga-miR-155 mimic or inhibitor. These findings suggest that TLR3 and MDV-encoded miRNAs might be involved in MDV infection.

Outbreak of Marek's disease in a vaccinated broiler breeding flock during its peak egg-laying period in China.

BACKGROUND: Outbreaks of Marek's disease (MD), caused by Marek's disease virus (MDV), primarily occur in 10-12-week-old hens. CASE PRESENTATION: We report a case of MD in a breeding flock of 24-30-week-old vaccinated broilers in China. The clinical signs in the affected chickens appeared at 24 weeks, and the incidence of tumours peaked at 30 weeks. The morbidity and mortality of the hens were 5 % and 80 %, respectively. Hematoxylin-eosin staining of the tissues showed the typical characteristics of MD. MDV infection was confirmed in the hens with an agar gel diffusion precipitation assay for the MD antigen in the feather follicle epithelium. An MDV strain, designated AH1410, was isolated from the blood lymphocytes. Sequence analyses of the pp38, meq, and gB genes revealed that strain AH1410 had molecular features consistent with a virulent, previously identified MDV. CONCLUSION: Our data provide evidence that not only is MDV becoming more virulent, but that the period of its onset in chickens is expanding. These findings provide the basis the molecular surveillance and further study of virulent MDV mutants and control strategies for MD in China.

Both MicroRNA-155 and Virus-Encoded MiR-155 Ortholog Regulate TLR3 Expression.

MicroRNA-155 (miR-155) has been as an important controller of TLR3 signalling. However, the interactions between miR-155 and TLR3 are poorly understood. Here, we focused on the regulation of the relationship between miR-155 and TLR3. Sequence analyses and firefly luciferase reporter assay revealed that miR-155 target were present in the coding sequences (CDS) of TLR3. And the expression of the TLR3 protein could be inhibited by a miR-155 mimic or by a virally encoded orthologue in chick embryo fibroblast cells. Notably, endogenous miR-155 induction emerged a negative regulation on TLR3 expression in TLR2, 4 and 7 ligands stimulated HD11 cells, an avian macrophage cell line. Moreover, treatment with the miR-155 antagomir increased TLR3 levels while significantly decreased the abundance of TLR3 with miR-155 agomir. In addition, our data showed that miR-155 could inhibit IFN-ß production possibly though TLR3 signal pathway. All these findings might reveal a new mechanism by which miR-155 can regulate the TLR3 immune response.