Development of a Fast SARS-CoV-2 IgG ELISA, Based on Receptor-Binding Domain, and Its Comparative Evaluation Using Temporally Segregated Samples From RT-PCR Positive Individuals

SARS-CoV-2 antibody detection assays are crucial for gathering seroepidemiological information and monitoring the sustainability of antibody response against the virus. The SARS-CoV-2 Spike protein's receptor-binding domain (RBD) is a very specific target for anti-SARS-CoV-2 antibodies detection. Moreover, many neutralizing antibodies are mapped to this domain, linking antibody response to RBD with neutralizing potential. Detection of IgG antibodies, rather than IgM or total antibodies, against RBD is likely to play a larger role in understanding antibody-mediated protection and vaccine response. Here we describe a rapid and stable RBD-based IgG ELISA test obtained through extensive optimization of the assay components and conditions. The test showed a specificity of 99.79% (95% CI: 98.82-99.99%) in a panel of pre-pandemic samples (n = 470) from different groups, i.e., pregnancy, fever, HCV, HBV, and autoantibodies positive. Test sensitivity was evaluated using sera from SARS-CoV-2 RT-PCR positive individuals (n = 312) and found to be 53.33% (95% CI: 37.87-68.34%), 80.47% (95% CI: 72.53-86.94%), and 88.24% (95% CI: 82.05-92.88%) in panel 1 (days 0-13), panel 2 (days 14-20) and panel 3 (days 21-27), respectively. Higher sensitivity was achieved in symptomatic individuals and reached 92.14% (95% CI: 86.38-96.01%) for panel 3. Our test, with a shorter runtime, showed higher sensitivity than parallelly tested commercial ELISAs for SARS-CoV-2-IgG, i.e., Euroimmun and Zydus, even when equivocal results in the commercial ELISAs were considered positive. None of the tests, which are using different antigens, could detect anti-SARS-CoV-2 IgGs in 10.5% RT-PCR positive individuals by the fourth week, suggesting the lack of IgG response

Impulse oscillometry: The state-of-art for lung function testing

Impulse oscillometry (IOS) is a variant of forced oscillation technique, described by Dubois over 50 years ago, which permits passive measurement of lung mechanics. In this method, sound waves are superimposed on normal tidal breathing, and the disturbances in flow and pressure caused by the external waves are used to calculate parameters describing the resistance to airflow and reactive parameters that mostly relate to efficient storage and return of energy by the lung. It requires minimal patient cooperation and can be done easily in subjects who are unable to perform spirometry. Importantly, IOS can differentiate small airway obstruction from large airway obstruction and is more sensitive than spirometry for peripheral airway disease. It has been used to study various respiratory disorders, especially asthma and is suitable for measuring bronchodilatory response as well as bronchoprovocation testing. IOS parameters seem to be able to pick up early changes in lung functon such that they are superior to spirometry in predicting loss of control in asthmatic patients and possibly in identifying early airway disease in smokers. Such comparisons, especially for chronic obstructive pulmonary disease, are made difficult by widespread use of spirometric parameters as the diagnostic gold standard. Here, we discuss the principles and technique of IOS and review its application in obstructive airway diseases

Exhaled breath condensate metabolome clusters for endotype discovery in asthma

Abstract Background Asthma is a complex, heterogeneous disorder with similar presenting symptoms but with varying underlying pathologies. Exhaled breath condensate (EBC) is a relatively unexplored matrix which reflects the signatures of respiratory epithelium, but is difficult to normalize for dilution. Methods Here we explored whether internally normalized global NMR spectrum patterns, combined with machine learning, could be useful for diagnostics or endotype discovery. Nuclear magnetic resonance (NMR) spectroscopy of EBC was performed in 89 asthmatic subjects from a prospective cohort and 20 healthy controls. A random forest classifier was built to differentiate between asthmatics and healthy controls. Clustering of the spectra was done using k-means to identify potential endotypes. Results NMR spectra of the EBC could differentiate between asthmatics and healthy controls with 80% sensitivity and 75% specificity. Unsupervised clustering within the asthma group resulted in three clusters (n = 41,11, and 9). Cluster 1 patients had lower long-term exacerbation scores, when compared with other two clusters. Cluster 3 patients had lower blood eosinophils and higher neutrophils, when compared with other two clusters with a strong family history of asthma. Conclusion Asthma clusters derived from NMR spectra of EBC show important clinical and chemical differences, suggesting this as a useful tool in asthma endotype-discovery

MOESM1 of Exhaled breath condensate metabolome clusters for endotype discovery in asthma

Additional file 1: Figure S1. Dynamic adaptive binning achieved optimal binning on the spectra. Figure S2. Changes in error rates of the random forest model at different steps of optimization. Figure S3. Boxplots of annotated bins which are top predictors in random forest model showing difference between asthmatics and healthy controls (A) and a table of p values for compounds showing statistical significance (B). Table S1. Most important NMR bins according to the random forest model along with the compounds annotated at that particular position

Survival outcomes post percutaneous coronary intervention: Why the hype about stent type? Lessons from a healthcare system in India - Fig 6

<p>A. A linear trend was seen between the probability of death and stented length (i.e., total length of implanted stents) The risk of death increased significantly with total stented length (Fig 6A). After the age of 50 years, the risk of adverse outcomes increased significantly with age (Fig 6B). There was no difference in outcomes between BMSs and DESs wider than 4 mm (Fig 6C).</p

Absolute standardized differences in baseline characteristics, stratified according to stent type.

<p>(Left) Before matching. (Right) After matching. BMS, bare-metal stent; DES, drug-eluting stent.</p

Procedural details.

<p>Procedural details.</p

Univariate Kaplan-Meier curves for 1-year outcomes after PCI, stratified by stent type.

<p>(A) All-cause mortality. (B) Combined outcome of death or repeat PCI in the same vessel. BMS, bare-metal stent; DES, drug-eluting stent; PCI, percutaneous coronary intervention.</p