Plasma-induced nanoparticle aggregation for stratifying COVID-19 patients according to disease severity.

Stratifying patients according to disease severity has been a major hurdle during the COVID-19 pandemic. This usually requires evaluating the levels of several biomarkers, which may be cumbersome when rapid decisions are required. In this manuscript we show that a single nanoparticle aggregation test can be used to distinguish patients that require intensive care from those that have already been discharged from the intensive care unit (ICU). It consists of diluting a platelet-free plasma sample and then adding gold nanoparticles. The nanoparticles aggregate to a larger extent when the samples are obtained from a patient in the ICU. This changes the color of the colloidal suspension, which can be evaluated by measuring the pixel intensity of a photograph. Although the exact factor or combination of factors behind the different aggregation behavior is unknown, control experiments demonstrate that the presence of proteins in the samples is crucial for the test to work. Principal component analysis demonstrates that the test result is highly correlated to biomarkers of prognosis and inflammation that are commonly used to evaluate the severity of COVID-19 patients. The results shown here pave the way to develop nanoparticle aggregation assays that classify COVID-19 patients according to disease severity, which could be useful to de-escalate care safely and make a better use of hospital resources.

Immunodetection of Lung IgG and IgM Antibodies against SARS-CoV-2 via Enzymatic Liquefaction of Respiratory Samples from COVID-19 Patients.

Lung-secreted IgG and IgM antibodies are valuable biomarkers for monitoring the local immune response against respiratory infections. These biomarkers are found in lower airway secretions that need to be liquefied prior to analysis. Traditional methods for sample liquefaction rely on reducing disulfide bonds, which may damage the structure of the biomarkers and hamper their immunodetection. Here, we propose an alternative enzymatic method that uses O2 bubbles generated by endogenous catalase enzymes in order to liquefy respiratory samples. The proposed method is more efficient for liquefying medium- and high-viscosity samples and does not fragment the antibodies. This prevents damage to antigen recognition domains and recognition sites for secondary antibodies that can decrease the signal of immunodetection techniques. The suitability of the enzymatic method for detecting antibodies in respiratory samples is demonstrated by detecting anti-SARS-CoV-2 IgG and IgM to viral N-protein with gold standard ELISA in bronchial aspirate specimens from a multicenter cohort of 44 COVID-19 patients. The enzymatic detection sharply increases the sensitivity toward IgG and IgM detection compared to the traditional approach based on liquefying samples with dithiothreitol. This improved performance could reveal new mechanisms of the early local immune response against respiratory infections that may have gone unnoticed with current sample treatment methods.

Optimized detection of lung IL-6 via enzymatic liquefaction of low respiratory tract samples: application for managing ventilated patients.

Lung IL-6 is a promising biomarker for predicting respiratory failure during pulmonary infections. This biomarker is found in respiratory samples which need to be liquefied prior to analysis. Traditional liquefying methods use reducing agents such as dithiothreitol (DTT). However, DTT impairs immunodetection and does not liquefy highly viscous samples. We propose an enzymatic method that liquefies samples by means of generating O2 bubbles with endogenous catalase. Low respiratory tract specimens from 48 mechanically ventilated patients (38 with SARS-CoV-2 infection) were treated with DTT or with the enzymatic method. We used turbidimetry to compare the liquefaction degree and IL-6 was quantified with ELISA. Finally, we used AUC-ROC, time-to-event and principal component analysis to evaluate the association between respiratory compromise or local inflammation and IL-6 determined with both methods. Enzymatically treated samples were better liquefied than those reduced by DTT, which resulted in higher ELISA signals. Lung IL-6 levels obtained with the enzymatic procedure were negatively correlated with the oxygenation index (PaO2/FiO2) and the time of mechanical ventilation. The proposed enzymatic liquefaction method improves the sensitivity for lung IL-6 detection in respiratory samples, which increases its predictive power as a biomarker for evaluating respiratory compliance.

Nanoparticle transfer biosensors for the non-invasive detection of SARS-CoV-2 antigens trapped in surgical face masks.

Detecting SARS-CoV-2 antigens in respiratory tract samples has become a widespread method for screening new SARS-CoV-2 infections. This requires a nasopharyngeal swab performed by a trained healthcare worker, which puts strain on saturated healthcare services. In this manuscript we describe a new approach for non-invasive COVID-19 diagnosis. It consists of using mobile biosensors for detecting viral antigens trapped in surgical face masks worn by patients. The biosensors are made of filter paper containing a nanoparticle reservoir. The nanoparticles transfer from the biosensor to the mask on contact, where they generate colorimetric signals that are quantified with a smartphone app. Sample collection requires wearing a surgical mask for 30 min, and the total assay time is shorter than 10 min. When tested in a cohort of 27 patients with mild or no symptoms, an area under the receiving operating curve (AUROC) of 0.99 was obtained (96.2 % sensitivity and 100 % specificity). Serial measurements revealed a high sensitivity and specificity when masks were worn up to 6 days after diagnosis. Surgical face masks are inexpensive and widely available, which makes this approach easy to implement anywhere. The excellent sensitivity, even when tested with asymptomatic patient samples, along with the mobile detection scheme and non-invasive sampling procedure, makes this biosensor design ideal for mass screening.

Colorimetric Detection of Sepsis-Derived Hyperdegranulation with Plasmonic Nanosensors.

Hyperdegranulation of neutrophilic granulocytes is a common finding in sepsis that directly contributes to the heightened immune response leading to organ dysfunction. Currently, cell degranulation is detected by flow cytometry, which requires large infrastructure that is not always available at the point of care. Here, we propose a plasmonic assay for detecting the degranulation status of septic cells colorimetrically. It is based on triggering the aggregation of gold nanoparticles with cationic granule proteins. Cells from septic patients contain fewer granules and therefore release less cationic proteins than healthy cells. This results in red-colored assays than can be easily detected by eye. The assay can selectively detect cationic granule proteins even in the presence of an excess of unrelated proteins, which is key to detect degranulation with high specificity. Coupling this signal generation mechanism with a magnetic purification step enabled the identification of septic cells with the same performance as flow cytometry. This makes the proposed method a promising alternative for diagnosing sepsis in decentralized healthcare schemes.

Low Albumin Levels Are Associated with Poorer Outcomes in a Case Series of COVID-19 Patients in Spain: A Retrospective Cohort Study.

There is limited information available describing the clinical and epidemiological features of Spanish patients requiring hospitalization for coronavirus disease 2019 (COVID-19). In this observational study, we aimed to describe the clinical characteristics and epidemiological features of severe (non-ICU) and critically patients (ICU) with COVID-19 at triage, prior to hospitalization. Forty-eight patients (27 non-ICU and 21 ICU) with positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection were analyzed (mean age, 66 years, [range, 33-88 years]; 67% males). There were no differences in age or sex among groups. Initial symptoms included fever (100%), coughing (85%), dyspnea (76%), diarrhea (42%) and asthenia (21%). ICU patients had a higher prevalence of dyspnea compared to non-ICU patients (95% vs. 61%, p = 0.022). ICU-patients had lymphopenia as well as hypoalbuminemia. Lactate dehydrogenase (LDH), C-reactive protein (CRP), and procalcitonin were significantly higher in ICU patients compared to non-ICU (p < 0.001). Lower albumin levels were associated with poor prognosis measured as longer hospital length (r = -0.472, p < 0.001) and mortality (r = -0.424, p = 0.003). As of 28 April 2020, 10 patients (8 ICU and 2 non-ICU) have died (21% mortality), and while 100% of the non-ICU patients have been discharged, 33% of the ICU patients still remained hospitalized (5 in ICU and 2 had been transferred to ward). Critically ill patients with COVID-19 present lymphopenia, hypoalbuminemia and high levels of inflammation.

Th1 and Th17 hypercytokinemia as early host response signature in severe pandemic influenza.

INTRODUCTION: Human host immune response following infection with the new variant of A/H1N1 pandemic influenza virus (nvH1N1) is poorly understood. We utilize here systemic cytokine and antibody levels in evaluating differences in early immune response in both mild and severe patients infected with nvH1N1. METHODS: We profiled 29 cytokines and chemokines and evaluated the haemagglutination inhibition activity as quantitative and qualitative measurements of host immune responses in serum obtained during the first five days after symptoms onset, in two cohorts of nvH1N1 infected patients. Severe patients required hospitalization (n = 20), due to respiratory insufficiency (10 of them were admitted to the intensive care unit), while mild patients had exclusively flu-like symptoms (n = 15). A group of healthy donors was included as control (n = 15). Differences in levels of mediators between groups were assessed by using the non parametric U-Mann Whitney test. Association between variables was determined by calculating the Spearman correlation coefficient. Viral load was performed in serum by using real-time PCR targeting the neuraminidase gene. RESULTS: Increased levels of innate-immunity mediators (IP-10, MCP-1, MIP-1beta), and the absence of anti-nvH1N1 antibodies, characterized the early response to nvH1N1 infection in both hospitalized and mild patients. High systemic levels of type-II interferon (IFN-gamma) and also of a group of mediators involved in the development of T-helper 17 (IL-8, IL-9, IL-17, IL-6) and T-helper 1 (TNF-alpha, IL-15, IL-12p70) responses were exclusively found in hospitalized patients. IL-15, IL-12p70, IL-6 constituted a hallmark of critical illness in our study. A significant inverse association was found between IL-6, IL-8 and PaO2 in critical patients. CONCLUSIONS: While infection with the nvH1N1 induces a typical innate response in both mild and severe patients, severe disease with respiratory involvement is characterized by early secretion of Th17 and Th1 cytokines usually associated with cell mediated immunity but also commonly linked to the pathogenesis of autoimmune/inflammatory diseases. The exact role of Th1 and Th17 mediators in the evolution of nvH1N1 mild and severe disease merits further investigation as to the detrimental or beneficial role these cytokines play in severe illness.

Computerised sepsis protocol management. Description of an early warning system. / Protocolo informático de manejo integral de la sepsis. Descripción de un sistema de identificación precoz.

INTRODUCTION: New strategies need to be developed for the early recognition and rapid response for the management of sepsis. To achieve this purpose, the Multidisciplinary Sepsis Team (MST) developed the Computerised Sepsis Protocol Management (PIMIS). The aim of this study was to evaluate the convenience of using PIMIS, as well as the activity of the MST. METHODS: An analysis was performed on the data collected from solicited MST consultations (direct activation of PIMIS by attending physician or telephone request) and unsolicited ones (by referral from the microbiology laboratory or an automatic referral via the hospital vital signs recording software [SIDCV]), as well as the hospital department, source of infection, treatment recommendation, and acceptance of this. RESULTS: Of the 1,581 first consultations, 65.1% were solicited consultations (84.1% activation of PIMIS and 15.9% by telephone). The majority of unsolicited consultations were generated by the microbiology laboratory (95.2%), and 4.8% from the SIDCV. Referral from solicited consultations were generated sooner (5.63days vs 8.47days; P<.001) and came from clinical specialties rather than from the surgical ward (73.0% vs 39.1%; P<.001). A recommendation was made for antimicrobial prescription change in 32% of first consultations. The treating physician accepted 78.1% of recommendations. CONCLUSIONS: The high rate of solicited consultations and acceptance of recommended prescription changes suggest that a MST is seen as a helpful resource, and that PIMIS software is perceived to be useful and convenient to use, as it is the main source of referral.