Effect of multiple freeze-thaw cycles on the detection of anti-SARS-CoV-2 IgG antibodies.

Several studies have investigated the effect of repeated freeze-thaw (F/T) cycles on RNA detection for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). However, no data are available regarding the effect of repeated F/T cycles on SARS-CoV-2 antibody detection in serum. We investigated the effect of multiple F/T cycles on anti-SARS-CoV-2 IgG detection using an ELISA test targeting the nucleocapsid antibodies. Ten positive and 1 negative SARS-CoV-2 IgG sera from 11 participants, in replicates of 5, were subjected to a total of 16 F/T cycles and stored at 4 °C until tested by ELISA. Statistical analysis was performed to test for F/T cycle effect. None of the 10 positive sera became negative after 16 F/T cycles. There was no significant difference in the OD average reading between the first and last F/T cycles, except for one serum with a minimal decline in the OD. The random effect linear regression of log (OD) on the number of cycles showed no significant trend, with a slope consistent with zero (B=-0.0001; 95 % CI -0.0008; 0.0006; P-value=0.781). These results suggest that multiple F/T cycles had no effect on the ability of the ELISA assay to detect SARS-CoV-2 IgG antibodies.

Performance evaluation of five ELISA kits for detecting anti-SARS-COV-2 IgG antibodies.

OBJECTIVES: To evaluate and compare the performances of five commercial ELISA assays (EDI, AnshLabs, Dia.Pro, NovaTec, and Lionex) for detecting anti-SARS-CoV-2 IgG. METHODS: Seventy negative control samples (collected before the COVID-19 pandemic) and samples from 101 RT-PCR-confirmed SARS-CoV-2 patients (collected at different time points from symptom onset: ≤7, 8-14 and >14 days) were used to compare the sensitivity, specificity, agreement, and positive and negative predictive values of each assay with RT-PCR. A concordance assessment between the five assays was also conducted. Cross-reactivity with other HCoV, non-HCoV respiratory viruses, non-respiratory viruses, and nuclear antigens was investigated. RESULTS: Lionex showed the highest specificity (98.6%; 95% CI 92.3-99.8), followed by EDI and Dia.Pro (97.1%; 95% CI 90.2-99.2), NovaTec (85.7%; 95% CI 75.7-92.1), then AnshLabs (75.7%; 95% CI 64.5-84.2). All ELISA kits cross-reacted with one anti-MERS IgG-positive sample, except Lionex. The sensitivity was low during the early stages of the disease but improved over time. After 14 days from symptom onset, Lionex and NovaTec showed the highest sensitivity at 87.9% (95% CI 72.7-95.2) and 86.4% (95% CI 78.5-91.7), respectively. The agreement with RT-PCR results based on Cohen's kappa was as follows: Lionex (0.89) > NovaTec (0.70) > Dia.Pro (0.69) > AnshLabs (0.63) > EDI (0.55). CONCLUSION: The Lionex and NovaLisa IgG ELISA kits, demonstrated the best overall performance.

Role of non-coding RNA networks in leukemia progression, metastasis and drug resistance.

Early-stage detection of leukemia is a critical determinant for successful treatment of the disease and can increase the survival rate of leukemia patients. The factors limiting the current screening approaches to leukemia include low sensitivity and specificity, high costs, and a low participation rate. An approach based on novel and innovative biomarkers with high accuracy from peripheral blood offers a comfortable and appealing alternative to patients, potentially leading to a higher participation rate.Recently, non-coding RNAs due to their involvement in vital oncogenic processes such as differentiation, proliferation, migration, angiogenesis and apoptosis have attracted much attention as potential diagnostic and prognostic biomarkers in leukemia. Emerging lines of evidence have shown that the mutational spectrum and dysregulated expression of non-coding RNA genes are closely associated with the development and progression of various cancers, including leukemia. In this review, we highlight the expression and functional roles of different types of non-coding RNAs in leukemia and discuss their potential clinical applications as diagnostic or prognostic biomarkers and therapeutic targets.