Individualized lipid profile in urine-derived extracellular vesicles from clinical patients with Mycobacterium tuberculosis infections.

Background: Lipids are a key nutrient source for the growth and reproduction of Mycobacterium tuberculosis (Mtb). Urine-derived extracellular vesicles (EVs), because of its non-invasive sampling, lipid enrichment, and specific sorting character, have been recognized as a promising research target for biomarker discovery and pathogenesis elucidation in tuberculosis (TB). We aim to profile lipidome of Mtb-infected individuals, offer novel lipid signatures for the development of urine-based TB testing, and provide new insights into the lipid metabolism after Mtb infection. Methods: Urine-derived extracellular vesicles from 41 participants (including healthy, pulmonary tuberculosis, latent tuberculosis patients, and other lung disease groups) were isolated and individually detected using targeted lipidomics and proteomics technology platforms. Biomarkers were screened by multivariate and univariate statistical analysis and evaluated by SPSS software. Correlation analyses were performed on lipids and proteins using the R Hmisc package. Results: Overall, we identified 226 lipids belonging to 14 classes. Of these, 7 potential lipid biomarkers for TB and 6 for latent TB infection (LTBI) were identified, all of which were classified into diacylglycerol (DAG), monoacylglycerol (MAG), free fatty acid (FFA), and cholesteryl ester (CE). Among them, FFA (20:1) was the most promising biomarker target in diagnosing TB/LTBI from other compared groups and also have great diagnostic performance in distinguishing TB from LTBI with AUC of 0.952. In addition, enhanced lipolysis happened as early as individuals got latent Mtb infection, and ratio of raft lipids was gradually elevated along TB progression. Conclusion: This study demonstrated individualized lipid profile of urinary EVs in patients with Mtb infection, revealed novel potential lipid biomarkers for TB/LTBI diagnosis, and explored mechanisms by which EV lipid raft-dependent bio-processes might affect pathogenesis. It lays a solid foundation for the subsequent diagnosis and therapeutic intervention of TB.

Risk factors and predictive nomograms for bedside emergency endoscopic treatment following endotracheal intubation in cirrhotic patients with esophagogastric variceal bleeding.

Data on emergency endoscopic treatment following endotracheal intubation in patients with esophagogastric variceal bleeding (EGVB) remain limited. This retrospective study aimed to explore the efficacy and risk factors of bedside emergency endoscopic treatment following endotracheal intubation in severe EGVB patients admitted in Intensive Care Unit. A total of 165 EGVB patients were enrolled and allocated to training and validation sets in a randomly stratified manner. Univariate and multivariate logistic regression analyses were used to identify independent risk factors to construct nomograms for predicting the prognosis related to endoscopic hemostasis failure rate and 6-week mortality. In result, white blood cell counts (p = 0.03), Child-Turcotte-Pugh (CTP) score (p = 0.001) and comorbid shock (p = 0.005) were selected as independent clinical predictors of endoscopic hemostasis failure. High CTP score (p = 0.003) and the presence of gastric varices (p = 0.009) were related to early rebleeding after emergency endoscopic treatment. Furthermore, the 6-week mortality was significantly associated with MELD scores (p = 0.002), the presence of hepatic encephalopathy (p = 0.045) and postoperative rebleeding (p < 0.001). Finally, we developed practical nomograms to discern the risk of the emergency endoscopic hemostasis failure and 6-week mortality for EGVB patients. In conclusion, our study may help identify severe EGVB patients with higher hemostasis failure rate or 6-week mortality for earlier implementation of salvage treatments.

Active regression model for clinical grading of COVID-19.

Background: In the therapeutic process of COVID-19, the majority of indicators that physicians have for assisting treatment have come from clinical tests represented by proteins, metabolites, and immune levels in patients' blood. Therefore, this study constructs an individualized treatment model based on deep learning methods, aiming to realize timely intervention based on clinical test indicator data of COVID-19 patients and provide an important theoretical basis for optimizing medical resource allocation. Methods: This study collected clinical data from a total of 1,799 individuals, including 560 controls for non-respiratory infectious diseases (Negative), 681 controls for other respiratory virus infections (Other), and 558 coronavirus infections (Positive) for COVID-19. We first used the Student T-test to screen for statistically significant differences (Pvalue<0.05); we then used the Adaptive-Lasso method stepwise regression to screen the characteristic variables and filter the features with low importance; we then used analysis of covariance to calculate the correlation between variables and filter the highly correlated features; and finally, we analyzed the feature contribution and screened the best combination of features. Results: Feature engineering reduced the feature set to 13 feature combinations. The correlation coefficient between the projected results of the artificial intelligence-based individualized diagnostic model and the fitted curve of the actual values in the test group was 0.9449 which could be applied to the clinical prognosis of COVID-19. In addition, the depletion of platelets in patients with COVID-19 is an important factor affecting their severe deterioration. With the progression of COVID-19, there is a slight decrease in the total number of platelets in the patient's body, particularly as the volume of larger platelets sharply decreases. The importance of plateletCV (count*mean platelet volume) in evaluating the severity of COVID-19 patients is higher than the count of platelets and mean platelet volume. Conclusion: In general, we found that for patients with COVID-19, the increase in mean platelet volume was a predictor for SARS-Cov-2. The rapid decrease of platelet volume and the decrease of total platelet volume are dangerous signals for the aggravation of SARS-Cov-2 infection. The analysis and modeling results of this study provide a new perspective for individualized accurate diagnosis and treatment of clinical COVID-19 patients.

Role of Hydrogen Sulfide and Hypoxia in Hepatic Angiogenesis of Portal Hypertension.

The pathogenesis of portal hypertension remains unclear, and is believed to involve dysfunction of liver sinusoidal endothelial cells (LSEC), activation of hepatic stellate cells (HSC), dysregulation of endogenous hydrogen sulfide (H2S) synthesis, and hypoxia-induced angiogenic responses. H2S, a novel gas transmitter, plays an important role in various pathophysiological processes, especially in hepatic angiogenesis. Inhibition of endogenous H2S synthase by pharmaceutical agents or gene silencing may enhance the angiogenic response of endothelial cells. Hypoxia-inducible factor-1 (HIF-1) is the main transcription factor of hypoxia, which induces hepatic angiogenesis through up-regulation of vascular endothelial growth factor (VEGF) in HSC and LSEC. H2S has also been shown to be involved in the regulation of VEGF-mediated angiogenesis. Therefore, H2S and HIF-1 may be potential therapeutic targets for portal hypertension. The effects of H2S donors or prodrugs on the hemodynamics of portal hypertension and the mechanism of H2S-induced angiogenesis are promising areas for future research.

Use of Pleural Fluid Digital PCR Analysis to Improve the Diagnosis of Pleural Tuberculosis.

The diagnosis of pleural tuberculosis (TB) remains difficult due to the paucity of Mycobacterium tuberculosis in pleural fluid (PF). This study aimed to improve pleural TB diagnosis using highly sensitive digital PCR (dPCR) technique. A total of 310 patients with evidence of PF were consecutively enrolled, 183 of whom suffered from pleural TB and 127 from non-TB. PF samples were prospectively collected and total DNA was extracted. The copy numbers of M. tuberculosis insertion sequence (IS) 6110 and IS1081 in DNA were quantified using dPCR. The overall area under the curve of IS6110-dPCR was greater than that of IS1081-dPCR (0.85 versus 0.79). PF IS6110 OR IS1081-dPCR (according to their cut-off values, "positive" was defined as either of them was positive, while "negative" was defined as both of them were negative) had higher sensitivity and equal specificity compared with single target-dPCR. The sensitivity of PF IS6110 OR IS1081-dPCR for total, definite, and probable pleural TB was 59.0% (95% CI = 51.5% to 66.2%), 72.8% (95% CI = 62.6% to 81.6%), and 45.1% (95% CI = 34.6% to 55.8%), respectively. Its specificity was 100% (95% CI = 97.1% to 100.0%). PF IS6110 OR IS1081-dPCR showed a higher sensitivity than smear microscopy (57.4% versus 7.1%), mycobacterial culture (55.3% versus 31.8%), and Xpert MTB/RIF (57.6% versus 23.0%). Long antituberculosis treatment time (>1 month) was found to be associated with negative dPCR results in pleural TB patients. This study indicates that PF IS6110 OR IS1081-dPCR is an accurate molecular assay, which is more sensitive than routine etiological tests and has the potential to enhance the definite diagnosis of pleural TB. IMPORTANCE Pleural TB is one of the most frequent causes of pleural effusion, especially in areas with high burden of TB. Due to the paucibacillary nature of the disease, the diagnostic sensitivities of all available bacteriological and molecular tests remain poor. There is an urgent need to develop new efficient methods. Digital PCR (dPCR) is the third generation of PCR that enables the exact quantification of trace nucleic acids in samples. This study evaluates the diagnostic performance of pleural fluid (PF) dPCR analysis for pleural TB, and shows that PF IS6110 OR IS1081-dPCR has a higher sensitivity than routine etiological tests such as smear microscopy, mycobacterial culture, and Xpert MTB/RIF. This work provides a new choice for improving the definite diagnosis of pleural TB.

Integrin α5 Is Regulated by miR-218-5p in Endothelial Progenitor Cells.

BACKGROUND: Endothelial cell injury is a common nidus of renal injury in patients and consistent with the high prevalence of AKI reported during the coronavirus disease 2019 pandemic. This cell type expresses integrin α5 (ITGA5), which is essential to the Tie2 signaling pathway. The microRNA miR-218-5p is upregulated in endothelial progenitor cells (EPCs) after hypoxia, but microRNA regulation of Tie2 in the EPC lineage is unclear. METHODS: We isolated human kidney-derived EPCs (hkEPCs) and surveyed microRNA target transcripts. A preclinical model of ischemic kidney injury was used to evaluate the effect of hkEPCs on capillary repair. We used a genetic knockout model to evaluate the effect of deleting endogenous expression of miR-218 specifically in angioblasts. RESULTS: After ischemic in vitro preconditioning, miR-218-5p was elevated in hkEPCs. We found miR-218-5p bound to ITGA5 mRNA transcript and decreased ITGA5 protein expression. Phosphorylation of 42/44 MAPK decreased by 73.6% in hkEPCs treated with miR-218-5p. Cells supplemented with miR-218-5p downregulated ITGA5 synthesis and decreased 42/44 MAPK phosphorylation. In a CD309-Cre/miR-218-2-LoxP mammalian model (a conditional knockout mouse model designed to delete pre-miR-218-2 exclusively in CD309+ cells), homozygotes at e18.5 contained avascular glomeruli, whereas heterozygote adults showed susceptibility to kidney injury. Isolated EPCs from the mouse kidney contained high amounts of ITGA5 and showed decreased migratory capacity in three-dimensional cell culture. CONCLUSIONS: These results demonstrate the critical regulatory role of miR-218-5p in kidney EPC migration, a finding that may inform efforts to treat microvascular kidney injury via therapeutic cell delivery.

High levels of plasma S100A9 at admission indicate an increased risk of death in severe tuberculosis patients.

OBJECTIVE: This study aims to evaluate plasma S100A9 levels in tuberculosis (TB) patients with admission to the ICU as a marker to predict the risk of death for pulmonary severe TB. METHODS: This study enrolled 256 severe TB patients admitted to Beijing Chest Hospital from Jan to Dec 2019. The S100A9 levels were measured by ELISA. Standard clinical parameters were collected. The non-parametric Mann-Whitney test, t-test, and chi-square test were applied to statistical comparison. A multivariable analysis was performed to identify risk factors for death. RESULTS: The plasma S100A9 levels were higher in non-survivors (25.88, 16.77-44.64) compared to survivors (15.51, 13.67-19.94). S100A9 performed better than Acute Physiology and Chronic Health Evaluation (APACHE II) score in predicting death, with AUC of 0.725, sensitivity of 65.5%, and specificity of 80.3%. By combining APACHE II score together with the S100A9 levels we got an AUC of 0.754 (95% CI 0.68 to 0.82) in predicting death. Lastly, S100A9 levels were significantly higher in patients with APACHE II score >17.5, sputum smear-positive, early death, and high cavitary lesions numbers, all of which were related to TB progression. CONCLUSION: Measurement and monitoring levels of plasma S100A9 in severe TB patients could facilitate the evaluation of patients with high risk at the early stage, which may help to improve the treatment outcome for TB patients.

Evaluation of digital PCR assay in detection of M.tuberculosis IS6110 and IS1081 in tuberculosis patients plasma.

BACKGROUND: Tuberculosis is still a significant diagnostic and therapeutic challenge with high proportion of smear- and culture- negative incidences worldwide. The conventional diagnostic tests are time-consuming and have a low sensitivity. Digital PCR is a novel technology which can detect target sequences with relatively low abundance and obtain the absolute copy numbers of the targets. METHODS: We assessed the accuracy of dPCR in TB diagnosis using more than 250 specimens, and for the first time, we selected M.tuberculosis-specific IS1081 in addition to widely used IS6110 as the amplification targets for dPCR. The quantification of target DNA was calculated using QuantaSoft Version 1.7.4.0917 (BioRad), and SPSS version 13.0 software (SPSS Inc., Chicago, IL, USA) was used for statistical analyses. RESULTS: IS6110-dPCR was more sensitive than IS1081, with the sensitivity and specificity accounting for 40.6 and 93.4% respectively. When we classified the TB patients by personal factors for high copy number of M.tuberculosis derived DNA in plasma: bilateral TB, extrapulmonary TB and disseminated TB, the sensitivity of both IS6110- and IS1081- dPCR was the highest in patients with disseminated TB (IS6110, 100%; IS1081, 68.8%), while their sensitivity was a bit higher in patients with extrapulmonary TB (IS6110, 50.0%; IS1081, 39.3%) than that in bilateral TB (IS6110, 43.3%; IS1081, 33.3%). Compared with traditional TB diagnostic tests, joint detection IS6110 & IS1081-dPCR was not as sensitive as smear microscope or mycobacterial culture, but it was higher than IS6110 qPCR (p < 0.05) and was able to detect 47.4% of smear-negative TB patients. CONCLUSION: Our study suggested that plasma IS6110-dPCR is a rapid, moderate accurate and less-invasive method to detect M.tuberculosis DNA in plasma of TB patients and IS6110 & IS1081-dPCR has a potential to aid diagnosis of smear-negative TB.

Small RNA Profiles of Serum Exosomes Derived From Individuals With Latent and Active Tuberculosis.

Tuberculosis (TB) has been the leading lethal infectious disease worldwide since 2014, and about one third of the world's population has a latent TB infection (LTBI). This is largely attributed to the difficulties in diagnosis and treatment of TB and LTBI patients. Exosomes offer a new perspective on investigation of the process of TB infection. In this study, we performed small RNA sequencing to explore small RNA profiles of serum exosomes derived from LTBI and TB patients and healthy controls (HC). Our results revealed distinct miRNA profile of the exosomes in the three groups. We screened 250 differentially expressed miRNAs including 130 specifically expressed miRNAs. Some miRNAs were further validated to be specifically expressed in LTBI (hsa-let-7e-5p, hsa-let-7d-5p, hsa-miR-450a-5p, and hsa-miR-140-5p) and TB samples (hsa-miR-1246, hsa-miR-2110, hsa-miR-370-3P, hsa-miR-28-3p, and hsa-miR-193b-5p). Additionally, we demonstrated four expression panels in LTBI and TB groups, and six expression patterns among the three groups. These specifically expressed miRNAs and differentially expressed miRNAs in different panels and patterns provide potential biomarkers for detection/diagnosis of latent and active TB using exosomal miRNAs. Additionally, we also discovered plenty of small RNAs derived from genomic repetitive sequences, which might play roles in host immune responses along with Mtb infection progresses. Overall, our findings provide important reference and an improved understanding about miRNAs and repetitive region-derived small RNAs in exosomes during the Mtb infectious process, and facilitate the development of potential molecular targets for detection/diagnosis of latent and active tuberculosis.

A Two-Way Proteome Microarray Strategy to Identify Novel Mycobacterium tuberculosis-Human Interactors.

Tuberculosis (TB) is still a serious threat to human health which is caused by mycobacterium tuberculosis (Mtb). The main reason for failure to eliminate TB is lack of clearly understanding the molecular mechanism of Mtb pathogenesis. Determining human Mtb-interacting proteins enables us to characterize the mechanism and identify potential molecular targets for TB diagnosis and treatment. However, experimentally systematic Mtb interactors are not readily available. In this study, we performed an unbiased, comprehensive two-way proteome microarray based approach to systematically screen global human Mtb interactors and determine the binding partners of Mtb effectors. Our results, for the first time, screened 84 potential human Mtb interactors. Bioinformatic analysis further highlighted these protein candidates might engage in a wide range of cellular functions such as activation of DNA endogenous promoters, transcription of DNA/RNA and necrosis, as well as immune-related signaling pathways. Then, using Mtb proteome microarray followed His tagged pull-down assay and Co-IP, we identified one interacting partner (Rv0577) for the protein candidate NRF1 and three binding partners (Rv0577, Rv2117, Rv2423) for SMAD2, respectively. This study gives new insights into the profile of global Mtb interactors potentially involved in Mtb pathogenesis and demonstrates a powerful strategy in the discovery of Mtb effectors.