Evaluation of a Semiautomated System for the Quantitation of Human Adenovirus DNA from Clinical Samples.

Human adenoviruses (HAdVs) cause severe disease in immunocompromised patients. Quantitation of HAdV DNA in peripheral blood is used to assess the risk of disseminated disease and to monitor response to therapy. The lower limit of detection, precision, and linearity of the semiautomated AltoStar adenovirus quantitative PCR (qPCR) was evaluated using reference HAdV-E4 in EDTA plasma and respiratory virus matrix. Qualitative and quantitative agreement was determined using 122 clinical EDTA plasma specimens previously tested using a laboratory-developed HAdV qPCR. The 95% lower limit of detection (LLOD) was 33 IU/mL (95% confidence interval [CI], 10 to 56) for EDTA plasma and 188 IU/mL (95% CI, 145 to 304) for respiratory swab matrix. In both matrices, the AltoStar HAdV qPCR was linear from 7.0 to 2.0 log10 IU/mL. For the clinical specimens, overall agreement was 96.7% (95% CI, 91.8 to 99.1), positive percent agreement was 95.5% (95% CI, 87.6 to 98.5), and negative percent agreement was 98.2% (95% CI, 88.5 to 99.7). Passing-Bablok analysis of specimens quantifiable by both methods revealed a regression line of Y = 1.11 · X + 0.00; there was positive proportional bias (95% CI of the slope, 1.05 to 1.22) but no systematic bias (95% CI of the Y-intercept, -0.43 to 0.23) compared to the reference. The AltoStar platform provides accurate quantitation of HAdV DNA and provides a semiautomated option for the clinical monitoring of HAdV following transplantation. IMPORTANCE Accurate quantification of human adenovirus DNA in the peripheral blood plays a critical role in the management of adenovirus infections in transplant recipients. Many laboratories utilize in-house laboratory-based PCR assays for the quantification of human adenovirus, as there are few commercial options available. Here, we describe the analytical and clinical performance of the semiautomated AltoStar adenovirus quantitative PCR (Altona Diagnostics). This platform provides sensitive, precise, and accurate quantification of adenovirus DNA that is well suited for virological testing following transplantation. Prior to implementing a new quantitative test in the clinical laboratory, a rigorous evaluation is required to determine assay performance characteristics and to correlate results to current in-house methods of quantitation.

An 8-gene machine learning model improves clinical prediction of severe dengue progression.

BACKGROUND: Each year 3-6 million people develop life-threatening severe dengue (SD). Clinical warning signs for SD manifest late in the disease course and are nonspecific, leading to missed cases and excess hospital burden. Better SD prognostics are urgently needed. METHODS: We integrated 11 public datasets profiling the blood transcriptome of 365 dengue patients of all ages and from seven countries, encompassing biological, clinical, and technical heterogeneity. We performed an iterative multi-cohort analysis to identify differentially expressed genes (DEGs) between non-severe patients and SD progressors. Using only these DEGs, we trained an XGBoost machine learning model on public data to predict progression to SD. All model parameters were "locked" prior to validation in an independent, prospectively enrolled cohort of 377 dengue patients in Colombia. We measured expression of the DEGs in whole blood samples collected upon presentation, prior to SD progression. We then compared the accuracy of the locked XGBoost model and clinical warning signs in predicting SD. RESULTS: We identified eight SD-associated DEGs in the public datasets and built an 8-gene XGBoost model that accurately predicted SD progression in the independent validation cohort with 86.4% (95% CI 68.2-100) sensitivity and 79.7% (95% CI 75.5-83.9) specificity. Given the 5.8% proportion of SD cases in this cohort, the 8-gene model had a positive and negative predictive value (PPV and NPV) of 20.9% (95% CI 16.7-25.6) and 99.0% (95% CI 97.7-100.0), respectively. Compared to clinical warning signs at presentation, which had 77.3% (95% CI 58.3-94.1) sensitivity and 39.7% (95% CI 34.7-44.9) specificity, the 8-gene model led to an 80% reduction in the number needed to predict (NNP) from 25.4 to 5.0. Importantly, the 8-gene model accurately predicted subsequent SD in the first three days post-fever onset and up to three days prior to SD progression. CONCLUSIONS: The 8-gene XGBoost model, trained on heterogeneous public datasets, accurately predicted progression to SD in a large, independent, prospective cohort, including during the early febrile stage when SD prediction remains clinically difficult. The model has potential to be translated to a point-of-care prognostic assay to reduce dengue morbidity and mortality without overwhelming limited healthcare resources.

Phospholipase A2, a nonnegligible enzyme superfamily in gastrointestinal diseases.

Gastrointestinal tract is important for digestion, absorption, detoxification and immunity. Gastrointestinal diseases are mainly caused by the imbalance of protective and attacking factors in gastrointestinal mucosa, which can seriously harm human health. Phospholipase A2 (PLA2) is a large family closely involved in lipid metabolism and is found in almost all human cells. A growing number of studies have revealed that its metabolites are deeply implicated in various inflammatory pathways and also regulates the maintenance of numerous biological events such as dietary digestion, membrane remodeling, barrier action, and host immunity. In addition to their phospholipase activity, some members of the superfamily also have other catalytic activities. Based on the in-depth effects of phospholipase A2 on bioactive lipid metabolism and inflammatory cytokines, PLA2 and its metabolites are likely to be involved in the pathogenesis, development or prevention of gastrointestinal diseases. Therefore, this review will focus on the physiological and pathogenic roles of several important PLA2 enzymes in the gastrointestinal tract, and reveals the potential of PLA2 as a therapeutic target for gastrointestinal diseases.

Role of bile acids in liver diseases mediated by the gut microbiome.

The intensive crosstalk between the liver and the intestine performs many essential functions. This crosstalk is important for natural immune surveillance, adaptive immune response regulation and nutrient metabolism and elimination of toxic bacterial metabolites. The interaction between the gut microbiome and bile acids is bidirectional. The gut microbiome regulates the synthesis of bile acids and their biological signaling activity and circulation via enzymes. Similarly, bile acids also shape the composition of the gut microbiome by modulating the host's natural antibacterial defense and the intestinal immune system. The interaction between bile acids and the gut microbiome has been implicated in the pathophysiology of many intestinal and extra intestinal diseases, especially liver diseases. As essential mediators of the gut-liver crosstalk, bile acids regulate specific host metabolic pathways and modulate the inflammatory responses through farnesoid X-activated receptor and G protein-coupled bile acid receptor 1. Several clinical trials have demonstrated the signaling effects of bile acids in the context of liver diseases. We hypothesize the existence of a gut microbiome-bile acids-liver triangle and explore the potential therapeutic strategies for liver diseases targeting the triangle.

Profiling SARS-CoV-2 mutation fingerprints that range from the viral pangenome to individual infection quasispecies.

BACKGROUND: The genome of SARS-CoV-2 is susceptible to mutations during viral replication due to the errors generated by RNA-dependent RNA polymerases. These mutations enable the SARS-CoV-2 to evolve into new strains. Viral quasispecies emerge from de novo mutations that occur in individual patients. In combination, these sets of viral mutations provide distinct genetic fingerprints that reveal the patterns of transmission and have utility in contact tracing. METHODS: Leveraging thousands of sequenced SARS-CoV-2 genomes, we performed a viral pangenome analysis to identify conserved genomic sequences. We used a rapid and highly efficient computational approach that relies on k-mers, short tracts of sequence, instead of conventional sequence alignment. Using this method, we annotated viral mutation signatures that were associated with specific strains. Based on these highly conserved viral sequences, we developed a rapid and highly scalable targeted sequencing assay to identify mutations, detect quasispecies variants, and identify mutation signatures from patients. These results were compared to the pangenome genetic fingerprints. RESULTS: We built a k-mer index for thousands of SARS-CoV-2 genomes and identified conserved genomics regions and landscape of mutations across thousands of virus genomes. We delineated mutation profiles spanning common genetic fingerprints (the combination of mutations in a viral assembly) and a combination of mutations that appear in only a small number of patients. We developed a targeted sequencing assay by selecting primers from the conserved viral genome regions to flank frequent mutations. Using a cohort of 100 SARS-CoV-2 clinical samples, we identified genetic fingerprints consisting of strain-specific mutations seen across populations and de novo quasispecies mutations localized to individual infections. We compared the mutation profiles of viral samples undergoing analysis with the features of the pangenome. CONCLUSIONS: We conducted an analysis for viral mutation profiles that provide the basis of genetic fingerprints. Our study linked pangenome analysis with targeted deep sequenced SARS-CoV-2 clinical samples. We identified quasispecies mutations occurring within individual patients and determined their general prevalence when compared to over 70,000 other strains. Analysis of these genetic fingerprints may provide a way of conducting molecular contact tracing.

TTN-AS1 as a potential diagnostic and prognostic biomarker for multiple cancers.

The long noncoding RNAs (lncRNAs) are non-coding RNAs that are more than 200 nucleotides in length, and one of several types of non-coding RNAs (ncRNAs). The lncRNAs function in diverse biological processes in normal cells, such as cellular differentiation and cell cycle regulation. There is also evidence that some aberrantly regulated lncRNAs function as oncogenes or tumor suppressor genes in various cancers. For example, TTN-AS1 is a lncRNA that binds to titin mRNA (TTN) and has pro-oncogenic effects in many cancers. Overexpression of TTN-AS1 correlates with poor prognosis in breast cancer, lung cancer, digestive system neoplasms, reproductive system cancers, and other cancers. Furthermore, increased TTN-AS1 expression correlates with more advanced pathology and tumor malignancy. In this review, we comprehensively summarize recent studies on the molecular mechanisms of TTN-AS1 regulation and the role of TTN-AS1 in the carcinogenesis and progression of numerous tumors.

Predictive Factors and Nomogram to Evaluate the Risk of Symptomatic Intracerebral Hemorrhage for Stroke Patients Receiving Thrombectomy.

BACKGROUND: Symptomatic intracerebral hemorrhage (sICH) is a severe complication of mechanical thrombectomy (MT). This study is to identify predictive factors and create a nomogram to evaluate the risk of sICH after MT treatment. METHODS: We conducted a retrospective analysis on 127 consecutive stroke patients treated by MT therapy. We evaluated multiple predictive factors for the incidence of sICH using univariate and multivariate logistic regressions. Based on the identified and other possible factors, a nomogram was constructed to predict the risk of sICH. RESULTS: We identified several predictive factors for sICH in the univariate analysis, including thrombectomy maneuvers >3 (odds ratio [OR], 4.42; 95% confidence interval [CI], 1.25-15.6; P = 0.0211), admission blood glucose (OR, 1.29; 95% CI, 1.13-1.48; P = 0.0002), diabetes mellitus (OR, 4.44; 95% CI, 1.64-12.0; P = 0.0033), and admission National Institutes of Health Stroke Scale (NIHSS) score (OR, 1.05; 95% CI, 1.01-1.10; P = 0.0263). The multivariate analysis showed that admission NIHSS score and blood glucose significantly affected the prognosis. Moreover, the proposed nomogram showed reliable identification ability with an area under the curve of 0.82 (95% CI, 0.71-0.93), specificity of 0.745, sensitivity of 0.762, accuracy of 0.748, and negative predictive value of 0.941. CONCLUSIONS: Our study identified the admission NIHSS score and admission blood glucose level as predictive factors for sICH. Moreover, the proposed nomogram based on possible factors showed reliable predictive performance in evaluating the risk of sICH.

Risk factors, clinical features, and short-term prognosis of spontaneous fungal peritonitis in cirrhosis: A matched case-control study.

BACKGROUND: Spontaneous peritonitis is one of the most common infectious complications in cirrhotic patients with ascites. Spontaneous fungal peritonitis (SFP) is a type of spontaneous peritonitis that is a less recognized but devastating complication in end-stage cirrhosis. Although high mortality was previously noted, scant data are available to fully define the factors responsible for the occurrence of SFP and its mortality. AIM: To illustrate the differences between SFP and spontaneous bacterial peritonitis (SBP) and discuss the risk factors for the occurrence of SFP and its short-term mortality. METHODS: We performed a matched case-control study between January 1, 2007 and December 30, 2018. Patients with SFP were included in a case group. Sex-, age-, and time-matched patients with SBP were included in a control group and were further divided into control-1 group (positive bacterial culture) and control-2 group (negative bacterial culture). The clinical features and laboratory parameters, severity models, and prognosis were compared between the case and control groups. Logistic regression analysis was used to determine the risk factors for occurrence, and the Cox regression model was used to identify the predictive factors for short-term mortality of SFP. RESULTS: Patients with SFP exhibited more severe systemic inflammation, higher ascites albumin and polymorphonuclear neutrophils, and a worsened 15-d mortality than patients in the control groups. Antibiotic administration (case vs control-1: OR = 1.063, 95%CI: 1.012-1.115, P = 0.014; case vs control-2: OR = 1.054, 95%CI: 1.014-1.095, P = 0.008) remarkably increased the occurrence of SFP or fungiascites. Hepatorenal syndrome (HR = 5.328, 95%CI: 1.050-18.900) and total bilirubin (µmol/L; HR = 1.005, 95%CI: 1.002-1.008) represented independent predictors of SFP-related early mortality. CONCLUSION: Long-term antibiotic administration increases the incidence of SFP, and hepatorenal syndrome and total bilirubin are closely related to short-term mortality.

Risk prediction for severe disease and better diagnostic accuracy in early dengue infection; the Colombo dengue study.

BACKGROUND: A major challenge in dengue management in resource limited settings is the confirmation of diagnosis. Clinical features of dengue often overlap with other infections and molecular diagnostic tools are not readily accessible to clinicians at hospitals. In addition, the prediction of plasma leakage in dengue is also difficult. Hematocrit level and ultrasound scans (combined with clinical parameters) are helpful to detect plasma leakage once it has happened, not before. METHODS: Colombo Dengue Study (CDS) is a prospective cohort study of clinically suspected adult dengue patients recruited from the National hospital of Sri Lanka (within the first 3 days of fever) that aimed to a) identify clinical and basic laboratory test parameters to differentiate dengue from non-dengue fever, b) evaluate the comparative efficacy of loop-mediated isothermal amplification (LAMP) for dengue diagnosis (vs. NS1 antigen test and RT-qPCR) and c) identify early associations that are predictive of plasma leakage or severe dengue. The basic laboratory tests considered here included hematological parameters, serum biochemistry and inflammatory markers. RESULTS: Only 70% of clinically suspected patients were confirmed as having dengue by either the NS1 antigen test or RT-qPCR. On a Bayesian latent class model which assumes no "gold standard", LAMP performed equally or better than RT-qPCR and NS1 antigen test respectively. When confirmed dengue patients were compared with others, the earlier group had significantly lower lymphocyte counts and higher aspartate aminotransferase levels (AST) within the first 3 days of fever. Confirmed dengue patients with plasma leakage had a lower mean age and a higher median baseline AST level compared to those without plasma leakage (p < 0.05). CONCLUSION: Clinical suspicion overestimates the true number of dengue patients. RT-LAMP is a potentially useful low-cost diagnostic tool for dengue diagnosis. Confirmed dengue patients had significantly higher AST levels and lower lymphocyte counts in early disease compared to others. In confirmed dengue patients, younger age and a higher AST level in early infection were associated with subsequent plasma leakage.

Membrane Trafficking Protein CDP138 Regulates Fat Browning and Insulin Sensitivity through Controlling Catecholamine Release.

CDP138 is a calcium- and lipid-binding protein that is involved in membrane trafficking. Here, we report that mice without CDP138 develop obesity under normal chow diet (NCD) or high-fat diet (HFD) conditions. CDP138-/- mice have lower energy expenditure, oxygen consumption, and body temperature than wild-type (WT) mice. CDP138 is exclusively expressed in adrenal medulla and is colocalized with tyrosine hydroxylase (TH), a marker of sympathetic nervous terminals, in the inguinal fat. Compared with WT controls, CDP138-/- mice had altered catecholamine levels in circulation, adrenal gland, and inguinal fat. Adrenergic signaling on cyclic AMP (cAMP) formation and hormone-sensitive lipase (HSL) phosphorylation induced by cold challenge but not by an exogenous ß3 adrenoceptor against CL316243 were decreased in adipose tissues of CDP138-/- mice. Cold-induced beige fat browning, fatty acid oxidation, thermogenesis, and related gene expression were reduced in CDP138-/- mice. CDP138-/- mice are also prone to HFD-induced insulin resistance, as assessed by Akt phosphorylation and glucose transport in skeletal muscles. Our data indicate that CDP138 is a regulator of stress response and plays a significant role in adipose tissue browning, energy balance, and insulin sensitivity through regulating catecholamine secretion from the sympathetic nervous terminals and adrenal gland.

Neutrophil Elastase Regulates Emergency Myelopoiesis Preceding Systemic Inflammation in Diet-induced Obesity.

Inflammation plays a significant role in the development of obesity-related complications, but the molecular events that initiate and propagate such inflammation remain unclear. Here, we report that mice fed a high-fat diet (HFD) for as little as 1-3 days show increased differentiation of myeloid progenitors into neutrophils and monocytes but reduced B lymphocyte production in the bone marrow. Levels of neutrophil elastase (NE) and the nuclear factors CCAAT/enhancer-binding protein α (C/EBPα) and growth factor-independent 1 (GFI-1) are elevated in hematopoietic stem and progenitor cells from HFD-fed mice, but mice lacking either NE or C/EBPα are resistant to HFD-induced myelopoiesis. NE deletion increases expression of the inhibitory isoform of p30 C/EBPα, impairs the transcriptional activity of p42 C/EBPα, and reduces expression of the C/EBPα target gene GFI-1 in hematopoietic stem and progenitor cells, suggesting a mechanism by which NE regulates myelopoiesis. Furthermore, NE deletion prevents HFD-induced vascular leakage. Thus, HFD feeding rapidly activates bone marrow myelopoiesis through the NE-dependent C/EBPα-GFI-1 pathway preceding vascular damage and systemic inflammation.

Hepatitis B Virus Core Antigen Stimulates IL-6 Expression via p38, ERK and NF-κB Pathways in Hepatocytes.

BACKGROUND: Hepatitis B virus (HBV) causes both acute and chronic liver injury. Viral proteins are involved in the pathological progress. Hepatitis B core antigen (HBcAg), a component of viral nucleocapsid, is not only essential for HBV lifecycle, but also exhibits strong immunogenicity. The cytoplasmic location of HBcAg in liver biopsy is associated with liver injury and inflammation, but the exact mechanisms remain to be elaborated. METHODS: Huh7, SMMC-7721 and L-02 cells were transfected with pEGFP-N1-HBcAg to establish an intracellular HBcAg expression model. The mRNA and protein levels of Interleukin (IL)-6 were detected by qPCR and ELISA respectively. The signaling pathway-related proteins were investigated by western blot and immunofluorescence assay. RESULTS: HBcAg increased the expression and secretion of IL-6 through activating extracellular signal-related kinase (ERK), p38 mitogen-activated protein kinase (p38 MAPK) and nuclear factor-kappa B (NF-κB). These activations can be blocked by specific inhibitors of the three pathways. CONCLUSIONS: HBcAg actives p38, ERK1/2 and NF-κB to enhance the production of IL-6 in hepatocytes. This provides a molecular mechanism to explain the association of cytoplasmic HBcAg with severe liver injury and inflammation.