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Human induced pluripotent stem cell-derived mesenchymal stem cells (iMSCs) have been believed to be a promising alternative for the stem cell transplantation therapy. The exosomes (Exo) from iMSCs play an important role in several kinds of life activities. The role of exosomes from iMSCs in severe acute pancreatitis (SAP) induced myocardial injury (MI) has not been investigated. The Exo were isolated from iMSCs through differential centrifugation method. The SAP rat model was established with 5% sodium taurocholate injection into the distal end of the bilepancreatic duct. RT-PCR and western blotting were used to measure related gene expression. Masson trichrome and Sirius Red stainings were used to evaluate MI injury. Cardiac function was detected through cardiac ultrasound.Exo promoted cell viability through activating Akt/nuclear factor E2 related factors 2 (Nrf2)/heme oxygenase 1 (HO-1) signaling pathway in vitro. Exo improved MI induced by SAP through activating Akt/Nrf2/HO-1 signaling pathway. Exo improved cardiac function, and suppressed oxidative status in the SAP model. Exo increased the expression of von Willebrand Factor (vWF) and vascular endothelial growth factor (VEGF) through activating Nrf2/HO-1 signaling pathway. Our data indicated that the Exo from iMSCs could improve MI caused by SAP through activating Nrf2/HO-1 axis. These findings firstly unfold the potential application of Exo from iMSCs in treating MI induced by SAP. Abbreviations: LVEF: Left ventricular ejection fraction; LVFS: left ventricular fractional shorten; LVDd: left ventricular end-diastolic diameter; LVDs: left ventricular end-systolic diameter; MI: Myocardial infarction; MSCs: Mesenchymal stem cells; iPSCs: Human-induced pluripotent stem cells; SAP: Severe acute pancreatitis; iMSCs: iPSCs derived VEGF: MSCs; vascular endothelial growth factor; Nrf2: Nuclear factor erythroid 2-related factor; RT-PCR: Real-time polymerase chain reaction; HE: Hematoxylin-eosin; MODS: Multiple organ dysfunction syndrome; PI3K: Phosphatidylinositol 3-kinase; SOD: Superoxide dismutase; FBS: Fetal bovine serum; ECL: Enhanced chemiluminescence; IHC: Immunohistochemistry. [ABSTRACT FROM AUTHOR]

The Coronavirus Disease 2019 (COVID-19) has spread all over the world and impacted many people's lives. The characteristics of COVID-19 and other types of pneumonia have both similarities and differences, which confused doctors initially to separate and understand them. Here we presented a retrospective analysis for both COVID-19 and other types of pneumonia by combining the COVID-19 clinical data, eICU and MIMIC-III databases. Machine learning models, including logistic regression, random forest, XGBoost and deep learning neural networks, were developed to predict the severity of COVID-19 infections as well as the mortality of pneumonia patients in intensive care units (ICU). Statistical analysis and feature interpretation, including the analysis of two-level attention mechanisms on both temporal and non-temporal features, were utilized to understand the associations between different clinical variables and disease outcomes. For the COVID-19 data, the XGBoost model obtained the best performance on the test set (AUROC = 1.000 and AUPRC = 0.833). On the MIMIC-III and eICU pneumonia datasets, our deep learning model (Bi-LSTM_Attn) was able to identify clinical variables associated with death of pneumonia patients (AUROC = 0.924 and AUPRC = 0.802 for 24-hour observation window and 12-hour prediction window). The results highlighted clinical indicators, such as the lymphocyte counts, that may help the doctors to predict the disease progression and outcomes for both COVID-19 and other types of pneumonia. [ABSTRACT FROM AUTHOR]

Objective: To investigate the relationship among the gut microbiome, serum metabolomic profile and RNA m6A methylation in patients with sepsis-associated encephalopathy (SAE), 16S rDNA technology, metabolomics and gene expression validation were applied. Methods: Serum and feces were collected from patients with and without (SAE group and non-SAE group, respectively, n = 20). The expression of serum markers and IL-6 was detected by enzyme-linked immunosorbent assay (ELISA), and blood clinical indicators were detected using a double antibody sandwich immunochemiluminescence method. The expression of RNA m6A regulator were checked by Q-RTPCR. The gut microbiome was analyzed by 16S rDNA sequencing and the metabolite profile was revealed by liquid chromatography-mass spectrometry (LC-MS/MS). Results: In the SAE group, the IL-6, ICAM-5 and METTL3 levels were significantly more than those in the non-SAE group, while the FTO levels were significantly decreased in the SAE group. The diversity was decreased in the SAE gut microbiome, as characterized by a profound increase in commensals of the Acinetobacter , Methanobrevibacter , and Syner-01 genera , a decrease in [ Eubacterium ]_ hallii _group, while depletion of opportunistic organisms of the Anaerofilum , Catenibacterium , and Senegalimassilia genera were observed in both groups. The abundance of Acinetobacter was positively correlated with the expression of METTL3. The changes between the intestinal flora and the metabolite profile showed a significant correlation. Sphingorhabdus was negatively correlated with 2-ketobutyric acid, 9-decenoic acid, and l-leucine, and positively correlated with Glycyl-Valine [Eubacterium]_hallii _group was positively correlated with 2-methoxy-3-methylpyazine, acetaminophen, and synephrine acetonide. Conclusion: The gut microbiota diversity was decreased. The serum metabolites and expression of RNA m6A regulators in PBMC were significantly changed in the SAE group compared to the non-SAE group. The results revealed that serum and fecal biomarkers could be used for SAE screening. [ABSTRACT FROM AUTHOR]

No prognostic tools for the prediction of COVID-19 pneumonia severity and mortality are available. We explored whether CURB-65, PSI, and APACHE-II could predict COVID-19 pneumonia severity and mortality. We included 167 patients with confirmed COVID-19 pneumonia in this retrospective study. The severity and 30-day mortality of COVID-19 pneumonia were predicted using PSI, CURB-65, and APACHE-II scales. Kappa test was performed to compare the consistency of the three scales. There was a significant difference in the distribution of the scores of the three scales (P < 0.001). Patients with PSI class ⩽III, CURB-65 ⩽1, and APACHE-II-I all survived. The ROC analysis showed the areas under the curve of the PSI, CURB-65, and APACHE-II scales were 0.83 (95% CI, 0.74–0.93), 0.80 (95% CI, 0.69–0.90), and 0.83 (95% CI, 0.75–0.92), respectively. Our findings suggest that PSI and CURB-65 might be useful to predict the severity and mortality of COVID-19 pneumonia. [ABSTRACT FROM AUTHOR]

Sepsis is an emergency systemic illness caused by pathogen infection and the combined result of the underactivity and overactivity of a patient's own immune system. However, the molecular mechanism of this illness remains largely unknown. Lipopolysaccharide (LPS) was injected to establish a sepsis model, and heart tissue was used to analyze transcriptome changes in mice. LPS injection was used to develop a sepsis model, which resulted in cardiac tissue rearrangement and inflammatory response activation. An RNA-sequencing-based transcriptome assay using mouse heart tissue with or without LPS injection showed that 3,326 and 1,769 genes were upregulated and downregulated, respectively (>2-fold changes; P<0.05). Furthermore, these differentially expressed genes were classified into 20 pathways, including 'Wnt signaling pathway', 'VEGF signaling pathway' and 'TGF-β signaling pathway', and these altered genes were enriched in 41 Gene Ontology terms. The application of Wnt3a inhibited the activation of the LPS-induced inflammatory response and activated Wnt signaling, as well as protecting against LPS-mediated cardiac tissue damage in mice. In contrast, inhibition of Wnt signaling by injection of its inhibitor IWR induced plasminogen activator inhibitor-1 expression and resulted in cardiac structure derangement, which was similar to the symptoms caused by injection of LPS, suggesting that LPS-induced damage to heart tissue may be via inhibition of Wnt signaling. The present analyses showed that Wnt signaling serves a pivotal role in sepsis development and may improve our understanding of the molecular basis underlying sepsis. [ABSTRACT FROM AUTHOR]

Pneumonia is a persistent and pervasive disease, the effects of which can be severe. MicroRNA (miR)-127-5p has been utilized as a novel biomarker for the diagnosis of severe pneumonia. The present study aimed to investigate the function of miR-127-5p during severe pneumonia. An in vitro model of severe pneumonia in Ana-1 murine macrophages was established using lipopolysaccharide (LPS). Subsequently, reverse transcription-quantitative PCR and ELISA were performed to detect the mRNA and protein expression levels of interleukin (IL)-1β, IL-6 and tumor necrosis factor (TNF)-α. Western blotting was also performed to measure the activity of AKT and NF-κB. The results indicated that compared with the control group, LPS treatment increased TNF receptor-associated factor 1 (TRAF1) expression levels and reduced miR-127-5p expression levels. Furthermore, the results revealed that the 3'-untranslated region of TRAF1 was targeted by miR-127-5p. miR-127-5p mimic reduced LPS-induced increases in IL-1β, IL-6 and TNF-α expression by targeting TRAF1, which was potentially mediated by inactivation of the AKT and NF-κB signaling pathways. Collectively, the results demonstrated that miR-127-5p may attenuate severe pneumonia by reducing LPS-induced inflammatory cytokine production, and inactivating the AKT and NF-κB signaling pathways by targeting TRAF1. [ABSTRACT FROM AUTHOR]