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BACKGROUND: Omadacycline is the first aminomethyl-tetracycline variety to successfully enter clinical applications. To support regular therapeutic drug monitoring (TDM) in clinical practice, an ultra-high-performance liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS) method was developed that would allow omadacycline quantification in human serum. METHODS: Proteins were precipitated from serum samples using methanol. Tigecycline was used as the internal standard. Mobile phase A was formic acid in water (0.1% v/v) and mobile phase B was methanol. UPLC-MS/MS was performed for analyte separation using a gradient elution program at a flow rate of 0.3 mL/min and a total run time of 5 min. The chromatography column was a ZORBAX PRHD SB-Aq (3 × 50 mm, 1.8 µm, Agilent, USA). The multiple reaction monitoring transitions at m/z = 557.4/470.3 and 586.5/513.3 were selected for omadacycline and tigecycline in the positive mode, respectively. RESULTS: The validated curve ranges were 0.5-25.0 µg/mL. This method exhibited acceptable selectivity, matrix effects, and recovery. The inter- and intra-run accuracies ranged from 93.5% to 114.8%, and the inter- and intra-run precisions were between 1.29% and 5.55%. CONCLUSIONS: The LC-MS/MS method provided a simple, specific, and rapid quantification of omadacycline in the serum of patients with pulmonary infection.
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ImportanceBreath analysis has been explored as a non-invasive means to detect COVID-19. However, the impact of the emerging variants such as Omicron on the exhaled breath profile and hence the accuracy of breath analysis is unknown. ObjectiveTo evaluate the diagnostic accuracies of breath analysis on detecting COVID-19 patients in periods where Delta and Omicron were most prevalent. Design, Setting, and ParticipantsA convenience cohort of patients testing positive and negative for COVID-19 using reverse transcriptase polymerase chain reaction (RT-PCR) were studied and included 167 COVID and non-COVID patients recruited between April 2021 and May 2022, which covers the period when Delta (and other variants prior to Delta) was the dominant variant (April - December 2021) and when Omicron was the dominant variant (January - May 2022). The breath from those patients were collected and analyzed for volatile organic compounds (VOCs) with a newly developed portable gas chromatography-based breath analyzer. Diagnostic patterns and algorithms were developed. ResultsA total of 205 breath samples were analyzed from 167 COVID and non-COVID patients. The RT-PCR was conducted within 18 hours of the breath analysis to confirm the COVID status of the patients. Among 94 COVID positive samples, 41 samples were collected from the patients in 2021 who were assumed to be infected by the Delta variant (or other variants occurring in 2021) and 53 samples from the patients in 2022 who were assumed to be infected by the Omicron variant (BA.1 and BA.2). Breath analysis using a set of 4 VOC biomarkers was able to distinguish between COVID (Delta and other variants in 2021) and non-COVID with an overall accuracy of 94.7%. However, the accuracy dropped significantly to 82.1% when the same set of biomarkers were applied to the Omicron variant with and 21 out of 53 COVID positive being misidentified. A new set of 4 VOC biomarkers were found to distinguish the Omicron variant and non-COVID, which yielded an overall accuracy of 90.9%. Breath analysis was also found to be able to distinguish between COVID (for all the variants occurring between April 2021 and May 2022) and non-COVID with an overall accuracy of 90.2%, and between the Omicron variant and the earlier variants (Delta and other variants occurring in 2021) with an overall accuracy of 91.5%. Conclusions and RelevanceBreath analysis of VOCs using point of care gas chromatography may be a promising diagnostic modality for detection of COVID and similar diseases that result in VOC production. However, similar to other diagnostic modalities such as rapid antigen testing, challenges are posed by the dynamic emergence of viral variants. The results of this study warrant additional investment and evaluation on how to overcome these challenges and to exploit breath analysis to improve the diagnosis and care of patients. Key PointsO_ST_ABSQuestionC_ST_ABSCan volatile organic compounds (VOCs) in exhaled breath provide diagnostic information on COVID-19? Will variants such as Omicron B.1.1.529 and others affect the accuracy in breath analysis? FindingsA set of 4 VOC biomarkers were found to distinguish between Delta (and the variants occurring in 2021) from non-COVID. The Omicron variant (occurring in 2022) significantly affects VOC profiles requiring the search for a new set of VOC biomarkers to distinguish between Omicron and non-COVID. MeaninThese findings demonstrate the ability of breath analysis to distinguish between COVID and non-COVID, but also reveal the significant difference in the exhaled breath profile between COVID-19 patients during the period when Delta was most prevalent and when Omicron was most prevalent.
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COVID-19 pandemic has caused tens of thousands of deaths and is now a severe threat to global health. Clinical practice has demonstrated that the SARS-CoV-2 S1 specific antibodies and viral antigens can be used as diagnostic and prognostic markers of COVID-19. However, the popular point-of-care biomarker detection technologies, such as the lateral-flow test strips, provide only yes/no information and have very limited sensitivities. Thus, it has a high false negative rate and cannot be used for the quantitative evaluation of patients immune response. Conventional ELISA (enzyme-linked immunosorbent assay), on the other hand, can provide quantitative, accurate, and sensitive results, but it involves complicated and expensive instruments and long assay time. In addition, samples need to be sent to centralized labs, which significantly increases the turn-around time. Here, we present a microfluidic ELISA technology for rapid (15-20 minutes), quantitative, sensitive detection of SARS-CoV-2 biomarkers using SARS-CoV-2 specific IgG and viral antigen - S protein in serum. We also characterized various humanized monoclonal IgG, and identified a candidate with a high binding affinity towards SARS-CoV-2 S1 protein that can serve as the calibration standard of anti-SARS-CoV-2 S1 IgG in serological analyses. Furthermore, we demonstrated that our microfluidic ELISA platform can be used for rapid affinity evaluation of monoclonal anti-S1 antibodies. The microfluidic ELISA device is highly portable and requires less than 10 L of samples for each channel. Therefore, our technology will greatly facilitate rapid and quantitative analysis of COVID-19 patients and vaccine recipients at point-of-care.
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This paper explores the existing gene doping problems of athletes in bioethical aspect,describes the development of gene doping,and points out that strengthening the anti-doping education,further improving legal system and strengthening an effective supervision and anti-doping research are main focus of anti-doping work currently.
