Inflammatory profiles revealed the dysregulation of cytokines in adult patients of HFMD

Role of Non-Coding RNA in Neurological Complications Associated With Enterovirus 71

Enterovirus 71 (EV71) is the main pathogenic virus that causes hand, foot, and mouth disease (HFMD). Studies have reported that EV71-induced infections including aseptic meningitis, acute flaccid paralysis, and even neurogenic pulmonary edema, can progress to severe neurological complications in infants, young children, and the immunosuppressed population. However, the mechanisms through which EV71 causes neurological diseases have not been fully explored. Non-coding RNAs (ncRNAs), are RNAs that do not code for proteins, play a key role in biological processes and disease development associated with EV71. In this review, we summarized recent advances concerning the impacts of ncRNAs on neurological diseases caused by interaction between EV71 and host, revealing the potential role of ncRNAs in pathogenesis, diagnosis and treatment of EV71-induced neurological complications.

Machine learning and statistical approaches for classification of risk of coronary artery disease using plasma cytokines

Background

As per the 2017 WHO fact sheet, Coronary Artery Disease (CAD) is the primary cause of death in the world, and accounts for 31% of total fatalities. The unprecedented 17.6 million deaths caused by CAD in 2016 underscores the urgent need to facilitate proactive and accelerated pre-emptive diagnosis. The innovative and emerging Machine Learning (ML) techniques can be leveraged to facilitate early detection of CAD which is a crucial factor in saving lives. The standard techniques like angiography, that provide reliable evidence are invasive and typically expensive and risky. In contrast, ML model generated diagnosis is non-invasive, fast, accurate and affordable. Therefore, ML algorithms can be used as a supplement or precursor to the conventional methods. This research demonstrates the implementation and comparative analysis of K Nearest Neighbor (k-NN) and Random Forest ML algorithms to achieve a targeted “At Risk” CAD classification using an emerging set of 35 cytokine biomarkers that are strongly indicative predictive variables that can be potential targets for therapy. To ensure better generalizability, mechanisms such as data balancing, repeated k-fold cross validation for hyperparameter tuning, were integrated within the models. To determine the separability efficacy of “At Risk” CAD versus Control achieved by the models, Area under Receiver Operating Characteristic (AUROC) metric is used which discriminates the classes by exhibiting tradeoff between the false positive and true positive rates.

Results

A total of 2 classifiers were developed, both built using 35 cytokine predictive features. The best AUROC score of .99 with a 95% Confidence Interval (CI) (.982,.999) was achieved by the Random Forest classifier using 35 cytokine biomarkers. The second-best AUROC score of .954 with a 95% Confidence Interval (.929,.979) was achieved by the k-NN model using 35 cytokines. A p-value of less than 7.481e-10 obtained by an independent t-test validated that Random Forest classifier was significantly better than the k-NN classifier with regards to the AUROC score.

Presently, as large-scale efforts are gaining momentum to enable early, fast, reliable, affordable, and accessible detection of individuals at risk for CAD, the application of powerful ML algorithms can be leveraged as a supplement to conventional methods such as angiography. Early detection can be further improved by incorporating 65 novel and sensitive cytokine biomarkers. Investigation of the emerging role of cytokines in CAD can materially enhance the detection of risk and the discovery of mechanisms of disease that can lead to new therapeutic modalities.

Pathogenesis Study of Enterovirus 71 Using a Novel Human SCARB2 Knock-In Mouse Model

Enterovirus 71 (EV71) can cause a severe hand-foot-mouth disease in children. However, the precise mechanism of EV71-associated disease, particularly the neuropathogenesis and pulmonary disorder, is still not fully understood because no suitable animal models are available. The human scavenger receptor class B, member 2 (hSCARB2), is a cellular receptor for EV71. Here, we generated a novel knock-in (KI) mouse model using the CRISPR/Cas9 system to insert the hSCARB2 gene into the mouse Rosa26 locus to study the pathogenesis of EV71. The hSCARB2 KI mice infected with clinical isolates of EV71 showed neurological symptoms, such as ataxia, paralysis, and death. Viral replication was detected in mainly astrocytes and a limited number of neurons and microglia, accompanied by gliosis. Vascular leakage and alveoli filled with erythrocytes were detected, suggesting that edema and hemorrhage, which are observed in human patients, also occurred in EV71-infected KI mice. In addition, proinflammatory cytokines and chemokines were significantly increased in the serum of infected KI mice. These pathological features of the KI mice after infection resembled those of EV71 encephalomyelitis in humans. Therefore, our KI mouse model is suitable to study the pathogenesis of EV71 and is of great significance for development of antiviral drugs and vaccines to treat or prevent EV71 infection.IMPORTANCE Enterovirus 71 (EV71) is associated with severe hand-foot-mouth disease. Recently, outbreaks of EV71 infection with high mortality have been reported in the Asia-Pacific region, posing a great challenge for global public health. To date, the precise mechanism of EV71-induced disease, particularly the neuropathogenesis and respiratory disorders, is still not fully understood because no suitable animal models are available. Human scavenger receptor class B, member 2 (hSCARB2), has been identified as a cellular receptor for EV71. Here, we introduce a novel CRISPR/Cas9-mediated hSCARB2 knock-in (KI) mouse model for the study of EV71 pathogenesis, which is of great significance for the development of antiviral drugs and vaccines.

Comparison of Host Cytokine Response in Piglets Infected With Toxigenic and Non-toxigenic Staphylococcus hyicus

Staphylococcus hyicus is the most common causative agent of exudative epidermitis (EE) in piglets. Staphylococcus hyicus can be grouped into toxigenic and non-toxigenic strains based on its ability to cause EE in pigs. However, the inflammatory response of piglets infected with toxigenic and non-toxigenic S. hyicus has not been elucidated. In this study, we evaluated the serum cytokine profile in piglets inoculated with toxigenic and non-toxigenic S. hyicus strains and recorded the clinical signs in piglets. Fifteen piglets were divided into three groups (n = 5) and inoculated with a toxigenic strain (ZC-4), a non-toxigenic strain (CF-1), and PBS (control), respectively. The changes in serum levels of cytokines (interleukin [IL]-1β, IL-4, IL-6, IL-8, IL-10, IL-12, granulocyte-macrophage colony-stimulating factor, interferon-γ, transforming growth factor-β1, and tumor necrosis factor-α) were evaluated using a cytokine array at 6, 24, 48, and 72 h post inoculation. The results showed that piglets infected with the toxigenic strain exhibited more severe clinical signs and higher mortality than those infected with the non-toxigenic strain. The serum levels of pro-inflammatory cytokine IL-1β were significantly increased in toxigenic-and non-toxigenic-strain-infected piglets compared to those in the control group (p < 0.05), while the anti-inflammatory cytokine IL-10 was significantly up-regulated only in toxigenic group than in control group (p < 0.05). These results indicated that piglets infected with toxigenic and non-toxigenic S. hyicus showed differential infection status and inflammatory responses. Both toxigenic- and non-toxigenic- S. hyicus infection could induce a pro-inflammatory reaction in piglets. In addition, the toxigenic strain induced a strong anti-inflammatory response in piglets as indicated by the increased serum level of IL-10, which may be associated with the severe clinical signs and increased mortality and may be the key cytokine response responsible for pathogenic mechanisms of S. hyicus.

Bioinformatics Analysis of Key micro-RNAs and mRNAs under the Hand, Foot, and Mouth Disease Virus Infection

To clarify crucial key micro-RNAs and mRNAs associated with hand, foot, and mouth disease (HFMD) virus infection, we conducted this bioinformatics analysis from four GEO datasets. The following datasets were used for the analysis: GSE85829, GSE94551, GSE52780, and GSE45589. Differentially expressed genes (DEGs) were acquired, and the analysis of functional and pathway enrichment and the relative regulatory network were conducted. After screening common differentially expressed miRNAs (DE-miRNAs), five key miRNAs were acquired: miR-100-3p, miR-125a-3p, miR-1273g-3p, miR-5585-3p, and miR-671-5p. There were three common enriched GO terms between miRNA-derived prediction and mRNA-derived analysis: biosynthetic process, cytosol, and nucleoplasm. There was one common KEGG pathway, i.e., cell cycle shared between miRNA-based and mRNA-based enrichment. Using TarBase V8 in DIANA tools, we acquired 1,520 potential targets (mRNA) from the five key DE-miRNAs, among which the159 DE-mRNAs also included 11 DEGs. These common DEGs showed a PPI network mainly connected by SMC1A, SMARCC1, SF3B3, LIG1, and BRMS1L. Together, changes in five key miRNAs and 11 key mRNAs may play crucial roles in HFMD progression. A combination of these roles may benefit the early diagnosis and treatment of HFMD.

BNIP3 deletion ameliorated enterovirus 71 infection-induced hand, foot and mouth disease via inhibiting apoptosis, autophagy, and inflammation in mice

Bcl2/adenovirus E1B protein-interacting protein 3 (BNIP3) plays a key role in cellular response to stress by regulating apoptosis and selective autophagy. The present study aimed to determine the effects of BNIP3 on enterovirus (EV) 71 infection-induced hand, foot and mouth disease (HFMD), and the apoptosis, autophagy and inflammatory in mice and SH-SY5Y human neuroblastoma cell line. Neonatal BALB/c mice were injected with EV 71 strain to induce the HFMD. Western blotting and ELISA were used to measure the protein expression and cytokine levels. The BNIP3 mRNA and protein levels in the brain were increased in EV 71-infected mice. By contrast, the BNIP3-knockout (KO) mice with EV 71 infection had higher health score and survival rate. BNIP3 deletion reversed the increase of cleaved-caspase 3, cleaved-caspase 8, Bax, LC3 II and LC3 II/LC3 I levels, and the decrease of Bcl2 and Bcl2/Bax and LC3 I levels in the brain of mice with EV 71 infection. The EV 71 infection-induced increase of tumor necrosis factor (TNF)-α, monocyte chemotactic protein (MCP)-1, interleukin (IL)-1β, IL-6, interferon (IFN)-α and IFN-γ levels were inhibited in BNIP3-KO mice. BNIP3 knockdown with small interfering RNA (siRNA) inhibited the EV 71 infection-induced the increases of apoptosis, autophagy and inflammatory factors in SH-SY5Y cells. BNIP3 overexpression further facilitated the EV 71 infection-induced increase of these inflammatory factors in SH-SY5Y cells. These results demonstrated that BNIP3 deletion ameliorated EV 71 infection-induced HFMD via inhibiting apoptosis, autophagy and inflammation in mice. BNIP3 may be a therapeutic target for HFMD.