Cytotoxic Mediators in Paradoxical HIV-Tuberculosis Immune Reconstitution Inflammatory Syndrome

Tuberculosis-associated immune reconstitution inflammatory syndrome (TB-IRIS) frequently complicates combined antiretroviral therapy and antituberculosis therapy in HIV-1–coinfected tuberculosis patients. The immunopathological mechanisms underlying TB-IRIS are incompletely defined, and improved understanding is required to derive new treatments and to reduce associated morbidity and mortality. We performed longitudinal and cross-sectional analyses of human PBMCs from paradoxical TB-IRIS patients and non-IRIS controls (HIV-TB–coinfected patients commencing antiretroviral therapy who did not develop TB-IRIS). Freshly isolated PBMC stimulated with heat-killed Mycobacterium tuberculosis H37Rv (hkH37Rv) were used for IFN-γ ELISPOT and RNA extraction. Stored RNA was used for microarray and RT-PCR, whereas corresponding stored culture supernatants were used for ELISA. Stored PBMC were used for perforin and granzyme B ELISPOT and flow cytometry. There were significantly increased IFN-γ responses to hkH37Rv in TB-IRIS, compared with non-IRIS PBMC (p = 0.035). Microarray analysis of hkH37Rv-stimulated PBMC indicated that perforin 1 was the most significantly upregulated gene, with granzyme B among the top five (log(2) fold difference 3.587 and 2.828, respectively), in TB-IRIS. Downstream experiments using RT-PCR, ELISA, and ELISPOT confirmed the increased expression and secretion of perforin and granzyme B. Moreover, granzyme B secretion reduced in PBMC from TB-IRIS patients during corticosteroid treatment. Invariant NKT cell (CD3(+)Vα24(+)) proportions were higher in TB-IRIS patients (p = 0.004) and were a source of perforin. Our data implicate the granule exocytosis pathway in TB-IRIS pathophysiology. Further understanding of the immunopathogenesis of this condition will facilitate development of specific diagnostic and improved therapeutic options

2015/16 seasonal vaccine effectiveness against hospitalisation with influenza a(H1N1)pdm09 and B among elderly people in Europe: Results from the I-MOVE+ project

We conducted a multicentre test-negative caseâ\u80\u93control study in 27 hospitals of 11 European countries to measure 2015/16 influenza vaccine effectiveness (IVE) against hospitalised influenza A(H1N1)pdm09 and B among people aged â\u89¥ 65 years. Patients swabbed within 7 days after onset of symptoms compatible with severe acute respiratory infection were included. Information on demographics, vaccination and underlying conditions was collected. Using logistic regression, we measured IVE adjusted for potential confounders. We included 355 influenza A(H1N1)pdm09 cases, 110 influenza B cases, and 1,274 controls. Adjusted IVE against influenza A(H1N1)pdm09 was 42% (95% confidence interval (CI): 22 to 57). It was 59% (95% CI: 23 to 78), 48% (95% CI: 5 to 71), 43% (95% CI: 8 to 65) and 39% (95% CI: 7 to 60) in patients with diabetes mellitus, cancer, lung and heart disease, respectively. Adjusted IVE against influenza B was 52% (95% CI: 24 to 70). It was 62% (95% CI: 5 to 85), 60% (95% CI: 18 to 80) and 36% (95% CI: -23 to 67) in patients with diabetes mellitus, lung and heart disease, respectively. 2015/16 IVE estimates against hospitalised influenza in elderly people was moderate against influenza A(H1N1)pdm09 and B, including among those with diabetes mellitus, cancer, lung or heart diseases

A k-Nearest Neighbors Method for Classifying User Sessions in E-Commerce Scenario

This paper addresses the problem of classification of user sessions in an online store into two classes: buying sessions (during which a purchase confirmation occurs) and browsing sessions. As interactions connected with a purchase confirmation are typically completed at the end of user sessions, some information describing active sessions may be observed and used to assess the probability of making a purchase. The authors formulate the problem of predicting buying sessions in a Web store as a supervised classification problem where there are two target classes, connected with the fact of finalizing a purchase transaction in session or not, and a feature vector containing some variables describing user sessions. The presented approach uses the k-Nearest Neighbors (k-NN) classification. Based on historical data obtained from online bookstore log files a k-NN classifier was built and its efficiency was verified for different neighborhood sizes. A 11-NN classifier was the most effective both in terms of buying session predictions and overall predictions, achieving sensitivity of 87.5% and accuracy of 99.85%

Supervised machine learning to support the diagnosis of bacterial infection in the context of COVID-19

Background: Bacterial infection has been challenging to diagnose in patients with COVID-19. We developed and evaluated supervised machine learning algorithms to support the diagnosis of secondary bacterial infection in hospitalized patients during COVID-19. Methods: Inpatient data at three London hospitals for the first COVD-19 wave in March and April 2020 were extracted. Demographic, blood test, and microbiology data for individuals with and without SARS-CoV-2 positive PCR were obtained. A Gaussian-Naïve Bayes (GNB), Support Vector Machine (SVM), and Artificial Neuronal Network (ANN) were trained and compared using the area under the receiver operating characteristic curve (AUCROC). The best performing algorithm (SVM with 21 blood test variables) was prospectively piloted in July 2020. AUCROC was calculated for the prediction of a positive microbiological sample within 48 hours of admission. Results: A total of 15,599 daily blood profiles for 1,186 individual patients were identified to train the algorithms. 771/1186 (65%) individuals were SARS-CoV-2 PCR positive. Clinically significant microbiology results were present for 166/1186 (14%) patients during admission. A SVM algorithm trained with 21 routine blood test variables and over 8000 individual profiles had the best performance. AUCROC was 0.913, sensitivity 0.801, and specificity 0.890. Prospective testing on 54 patients on admission (28/54, 52% SARS-CoV-2 PCR positive) demonstrated an AUCROC of 0.960 (0.90-1.00). Conclusion: A SVM using 21 routine blood test variables had excellent performance at inferring the likelihood of positive microbiology. Further prospective evaluation of the algorithms ability to support decision making for the diagnosis of bacterial infection in COVID-19 cohorts is underway

Bacterial and fungal co-infection in individuals with coronavirus: A rapid review to support COVID-19 antimicrobial prescribing

Background To explore and describe the current literature surrounding bacterial/fungal co-infection in patients with coronavirus infection. Methods MEDLINE, EMBASE, and Web of Science were searched using broad based search criteria relating to coronavirus and bacterial co-infection. Articles presenting clinical data for patients with coronavirus infection (defined as SARS-1, MERS, SARS-COV-2, and other coronavirus) and bacterial/fungal co-infection reported in English, Mandarin, or Italian were included. Data describing bacterial/fungal co-infections, treatments, and outcomes were extracted. Secondary analysis of studies reporting antimicrobial prescribing in SARS-COV-2 even in the absence of co-infection was performed. Results 1007 abstracts were identified. Eighteen full texts reported bacterial/fungal co-infection were included. Most studies did not identify or report bacterial/fungal coinfection (85/140;61%). 9/18 (50%) studies reported on COVID-19, 5/18 (28%) SARS-1, 1/18 (6%) MERS, and 3/18 (17%) other coronavirus. For COVID-19, 62/806 (8%) patients were reported as experiencing bacterial/fungal co-infection during hospital admission. Secondary analysis demonstrated wide use of broad-spectrum antibacterials, despite a paucity of evidence for bacterial coinfection. On secondary analysis, 1450/2010 (72%) of patients reported received antimicrobial therapy. No antimicrobial stewardship interventions were described. For non-COVID-19 cases bacterial/fungal co-infection was reported in 89/815 (11%) of patients. Broad-spectrum antibiotic use was reported. Conclusions Despite frequent prescription of broad-spectrum empirical antimicrobials in patients with coronavirus associated respiratory infections, there is a paucity of data to support the association with respiratory bacterial/fungal co-infection. Generation of prospective evidence to support development of antimicrobial policy and appropriate stewardship interventions specific for the COVID-19 pandemic are urgently required

Hypercytokinaemia accompanies HIV-tuberculosis immune reconstitution inflammatory syndrome.

Increased access to combination antiretroviral therapy in areas co-endemic for tuberculosis (TB) and HIV-1 infection is associated with an increased incidence of immune reconstitution inflammatory syndrome (TB-IRIS) whose cause is poorly understood. A case-control analysis of pro- and anti-inflammatory cytokines in TB-IRIS patients sampled at clinical presentation, and similar control patients with HIV-TB prescribed combined antiretroviral therapy who did not develop TB-IRIS. Peripheral blood mononuclear cells were cultured in the presence or absence of heat-killed Mycobacterium tuberculosis for 6 and 24 h. Stimulation with M. tuberculosis increased the abundance of many cytokine transcripts with interleukin (IL)-1β, IL-5, IL-6, IL-10, IL-13, IL-17A, interferon (IFN)-γ, granulocyte-macrophage colony-stimulating factor (GM-CSF) and tumour necrosis factor (TNF) being greater in stimulated TB-IRIS cultures. Analysis of the corresponding proteins in culture supernatants, revealed increased IL-1β, IL-2, IL-6, IL-8, IL-10, IL-12p40, IFN-γ, GM-CSF and TNF in TB-IRIS cultures. In serum, higher concentrations of TNF, IL-6, and IFN-γ were observed in TB-IRIS patients. Serum IL-6 and TNF decreased during prednisone therapy in TB-IRIS patients. These data suggest that cytokine release contributes to pathology in TB-IRIS. IL-6 and TNF were consistently elevated and decreased in serum during corticosteroid therapy. Specific blockade of these cytokines may be rational approach to immunomodulation in TB-IRIS

Matrix metalloproteinases and tissue damage in HIV-tuberculosis immune reconstitution inflammatory syndrome

The HIV-TB-associated immune reconstitution inflammatory syndrome (TB-IRIS) can complicate combined treatments for HIV-1 and TB. Little is known about tissue damage in TB-IRIS. Matrix metalloproteinases (MMPs) degrade components of the extracellular matrix and consequently may play a role in such immunopathology. Here we investigated the involvement of MMPs in TB-IRIS. We determined MMP transcript abundance and secreted protein in Mycobacterium tuberculosis stimulated PBMCs from 22 TB-IRIS patients and 22 non-IRIS controls. We also measured MMP protein levels in corresponding serum and the effect of prednisone — which reduces the duration of symptoms in IRIS patients — or placebo treatment on MMP transcript and circulating MMP protein levels. PBMCs from TB-IRIS had increased MMP-1, -3, -7, and -10 transcript levels when compared with those of controls at either 6 or 24 h. Similarly, MMP-1, -3, -7, and -10 protein secretion in stimulated cultures was higher in TB-IRIS than in controls. Serum MMP-7 concentration was elevated in TB-IRIS and 2 weeks of corticosteroid therapy decreased this level, although not significantly. TB-IRIS is associated with a distinct pattern of MMP gene and protein activation. Modulation of dysregulated MMP activity may represent a novel therapeutic approach to alleviate TB-IRIS in HIV-TB patients undergoing treatmen

CovidNudge: diagnostic accuracy of a novel lab-free point-of-care diagnostic for SARS-CoV-2

Background Access to rapid diagnosis is key to the control and management of SARS-CoV-2. Reverse Transcriptase-Polymerase Chain Reaction (RT-PCR) testing usually requires a centralised laboratory and significant infrastructure. We describe the development and diagnostic accuracy assessment of a novel, rapid point-of-care RT-PCR test, the DnaNudge® platform CovidNudge test, which requires no laboratory handling or sample pre-processing. Methods Nasopharyngeal swabs are inserted directly into a cartridge which contains all reagents and components required for RT-PCR reactions, including multiple technical replicates of seven SARS-CoV-2 gene targets (rdrp1, rdrp2, e-gene, n-gene, n1, n2 and n3) and human ribonuclease P (RNaseP) as positive control. Between April and May 2020, swab samples were tested in parallel using the CovidNudge direct-to-cartridge platform and standard laboratory RT-PCR using swabs in viral transport medium. Samples were collected from three groups: self-referred healthcare workers with suspected COVID-19 (Group 1, n=280/386; 73%); patients attending the emergency department with suspected COVID-19 (Group 2, n=15/386; 4%) and hospital inpatient admissions with or without suspected COVID-19 (Group 3, n=91/386; 23%). Results Of 386 paired samples tested across all groups, 67 tested positive on the CovidNudge platform and 71 with standard laboratory RT-PCR. The sensitivity of the test varied by group (Group 1 93% [84-98%], Group 2 100% [48-100%] and Group 3 100% [29-100%], giving an average sensitivity of 94.4% (95% confidence interval 86-98%) and an overall specificity of 100% (95%CI 99-100%; Group 1 100% [98-100%]; Group 2 100% [69-100%] and Group 3 100% [96-100%]). Point of care testing performance was comparable during a period of high (25%) and low (3%) background prevalence. Amplification of the viral nucleocapsid (n1, n2, n3) targets were most sensitive for detection of SARS-CoV2, with the assay able to detect 1×104 viral particles in a single swab. Conclusions The CovidNudge platform offers a sensitive, specific and rapid point of care test for the presence of SARS-CoV-2 without laboratory handling or sample pre-processing. The implementation of such a device could be used to enable rapid decisions for clinical care and testing programs. Evidence before this study The WHO has highlighted the development of rapid, point-of-care diagnostics for detection of SARS-CoV-2 as a key priority to tackle COVID-19. The Foundation for Innovative Diagnostics (FIND) has identified over 90 point-of-care, near patient or mobile tests for viral detection of SARS-CoV-2. However, the most widely available rapid tests to date require some sample handling which limits their use at point-of-care. In addition, pressure on supply chains is restricting access to current diagnostics and alternatives are needed urgently. Added value of this study We describe the development and clinical validation of COVID nudge, a novel point-of-care RT-PCR diagnostic, evaluated during the first wave of the SARS-CoV-2 epidemic. The platform is able to achieve high analytic sensitivity and specificity from dry swabs within a self-contained cartridge. The lack of downstream sample handling makes it suitable for use in a range of clinical settings, without need for a laboratory or specialized operator. Multiplexed assays within the cartridge allow inclusion of a positive human control, which reduces the false negative testing rate due to insufficient sampling. Implication of the available evidence Point-of-care testing can relieve pressure on centralized laboratories and increase overall testing capacity, complementing existing approaches. These findings support a role for COVID Nudge as part of strategies to improve access to rapid diagnostics to SARS-CoV-2. Since May 2020, the system has been implemented in UK hospitals and is being rolled out nationwide. Competing Interest Statement CT, RS, MS, CI, MK, TH, SDM, FL, JB and AO are employees of DnaNudge. CT is named on the patent for method and apparatus for analyzing biological specimens on the DnaNudge platform (US Patent No: US 10,093,965 B216. LSPM has consulted for bioMerieux (2013 to 2020), DNAelectronics (2015), Dairy Crest (2017 to 2018), Pfizer (2018-2020), and Umovis Lab (2020), received speaker fees from Profile Pharma (2018), received research grants from the National Institute for Health Research (2013 to 2019), Leo Pharma (2016), and CW+ Charity (2018 to 2019), and received educational support from Eumedica (2016 to 2017). NM has received speaker fees from Beyer (2016) and Pfizer (2019) and received educational support from Eumedica (2016) and Baxter (2017). All other authors have no conflicts of interest to declare. Funding Statement The work was supported by the Biomedical Research Centre of Imperial College NHS Trust. M.M.G. is supported in part by the NIHR Imperial Biomedical Research Centre. GC is an NIHR Research Professor and Investigator within the NIHR London In-vitro Diagnostic Collaborative. Part of this work was supported by the National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Healthcare Associated Infections and Antimicrobial Resistance at Oxford University in partnership with Public Health England (PHE) [grant HPRU-2012-10041] and the NIHR Biomedical Research Centre, Oxford. The views expressed in this publication are those of the authors and not necessarily those of the NHS, the National Institute for Health Research, the Department of Health or Public Health England