Recent Advances in the Diagnosis and Treatment of Influenza Pneumonia

A potentially fatal complication of influenza infection is the development of pneumonia, caused either directly by the influenza virus, or by secondary bacterial infection. Pneumonia related to the 2009 influenza A pandemic was found to be underestimated by commonly used pneumonia severity scores in many cases, and to be rapidly progressive, leading to respiratory failure. Confirmation of etiology by laboratory testing is warranted in such cases. Rapid antigen and immunofluorescence testing are useful screening tests, but have limited sensitivity. Confirmation of pandemic H1N1 influenza A infection can only be made by real-time reverse-transcriptase polymerase chain reaction (rRT-PCR) or viral culture. The most effective preventive measure is annual influenza vaccination in selected individuals. Decisions to administer antiviral medications for influenza treatment or chemoprophylaxis should be based upon clinical and epidemiological factors, and should not be delayed by confirmatory laboratory testing results. Neuraminidase inhibitors (NI) are the agents of choice

Antiviral Protein of Momordica charantia

The new antiviral activity of the protein extracted from Momordica charantia was determined with different subtypes of influenza A. The protein was purified from the seed of M. charantia using an anion exchanger and a Fast Protein Liquid Chromatography (FPLC) system. At the concentration of 1.401 mg/mL, the protein did not exhibit cytotoxicity in Madin-Darby canine kidney cells (MDCK) but inhibited FFU influenza A/PR/8/34 H1N1 virus at 56.50%, 65.72%, and 100% inhibition by the protein treated before the virus (pretreated), the protein treated alongside with the virus (simultaneously treated), and the protein treated after the virus (posttreated) during incubation, respectively. Using 5, 25, and 100 TCID50 of influenza A/New Caledonia/20/99 H1N1, A/Fujian/411/01 H3N2 and A/Thailand/1(KAN-1)/2004 H5N1, the IC50 was calculated to be 100, 150, and 200; 75, 175, and 300; and 40, 75, and 200 μg/mL, respectively. Our present finding indicated that the plant protein inhibited not only H1N1 and H3N2 but also H5N1 subtype. As a result of the broad spectrum of its antiviral activity, this edible plant can be developed as an effective therapeutic agent against various and even new emerging subtypes of influenza A

Performance of 6 HCV genotyping 9G test for HCV genotyping in clinical samples

Abstract Background A treatment of HCV infection depends on the genotype and sub-genotype. Therefore, accurate HCV genotyping is critical for selecting the appropriate treatment regimen. Method This study included 280 plasma samples to evaluate the performance of 6 HCV Genotyping 9G test. The performance of 6 HCV Genotyping 9G test for accurate detection of HCV 1a, 1b, 2, 3, 4, and 6 genotypes was evaluated by comparing it with LiPA 2.0 assay and sequencing. Results 6 HCV Genotyping 9G test and LiPA 2.0 assay demonstrated 83.9% (n = 235) agreement. 39/45 samples that showed discrepant results between the two tests were analyzed by sequencing. Sequencing genotyped 39 discrepant samples as 0 (HCV 1a), 24 (HCV 1b), 1 (HCV 6f), 12 (HCV 6i), and 2 (HCV-negative). Results of 6 HCV Genotyping 9G test were very similar to the sequencing as it detected 1, 23, 1, 12, and 2 samples as HCV 1a, 1b, 3 & 6a or 6f, 6i or 6n, and negative, respectively. However, LiPA 2.0 assay showed complete disagreement with sequencing, as it did not detect any of these 39 samples correctly. These results indicate that LiPA 2.0 assay has limitations in identifying HCV genotypes 1b, and 6. The sensitivity, specificity, PPV, and NPV of 6 HCV Genotyping 9G test were 99.5, 98.8, 99.5, and 98.8%, respectively. It is important to note that HCV Genotyping 9G test showed 98.3 and 100% sensitivity for HCV 1b and 6 genotyping, respectively. However, LiPA 2.0 assay demonstrated 57.9 and 71.7% sensitivity for these genotypes. Conclusions 6 HCV Genotyping 9G test identifies HCV 1a, 1b, 2, 3, and 6 with good agreement with sequencing. Hence, 6 HCV Genotyping 9G test has a high clinical value because it can provide critical information to physicians and assist them to use the correct drug for efficient hepatitis C treatment

Additional file 1: of Performance of 6 HCV genotyping 9G test for HCV genotyping in clinical samples

Table S1. Comparison of 6 HCV Genotyping 9G Test and LiPA 2.0 with the sequencing in 46 discordant samples. Table S2. TP, TN, FP, and FN results of 6 HCV Genotyping 9G Test and LiPA 2.0 with the sequencing in 274 samples. Table S3. TP, TN, FP, and FN results of 6 HCV Genotyping 9G Test (n = 274). (DOCX 86 kb

Quantitative influenza follow-up testing (QIFT)--a novel biomarker for the monitoring of disease activity at the point-of-care.

BACKGROUND: Influenza infections induce considerable disease burden in young children. Biomarkers for the monitoring of disease activity at the point-of-care (POC) are currently lacking. Recent methodologies for fluorescence-based rapid testing have been developed to provide improved sensitivities with the initial diagnosis. The present study aims to explore the utility of second-generation rapid testing during longitudinal follow-up of influenza patients (Rapid Influenza Follow-up Testing = RIFT). Signal/control fluorescent readouts (Quantitative Influenza Follow-up Testing = QIFT) are evaluated as a potential biomarker for the monitoring of disease activity at the POC. METHODS AND FINDINGS: RIFT (SOFIA) and QIFT were performed at the POC and compared to blinded RT-PCR at the National Reference Centre for Influenza. From 10/2011-4/2013, a total of 2048 paediatric cases were studied prospectively; 273 cases were PCR-confirmed for influenza. During follow-up, RIFT results turned negative either prior to PCR (68%), or simultaneously (30%). The first negative RIFT occurred after a median of 8 days with a median virus load (VL) of 5.6×10∧3 copies/ml and cycle threshold of 37, with no evidence of viral rebound. Binning analysis revealed that QIFT differentiated accurately between patients with low, medium and high viral titres. QIFT increase/decrease showed 88% agreement (sensitivity = 52%, specificity = 95%) with VL increase/decrease, respectively. QIFT-based viral clearance estimates showed similar values compared to PCR-based estimates. Variations in viral clearance rates were lower in treated compared to untreated patients. The study was limited by use of non-invasive, semi-quantitative nasopharyngeal samples. VL measurements below the limit of detection could not be quantified reliably. CONCLUSIONS: During follow-up, RIFT provides a first surrogate measure for influenza disease activity. A "switch" from positive to negative values may indicate a drop in viral load below a critical threshold, where rebound is no longer expected. QIFT may provide a useful tool for the monitoring of disease burden and viral clearance at the POC