Enhancing the selectivity of liquid chromatography-mass spectrometry by using trilinear decomposition on LC-MS data: An application to three-way calibration of coeluting analytes in human plasma.

The high selectivities of liquid chromatography and mass spectrometry make liquid chromatography-mass spectrometry one of the most popular tools for quantitative analysis in complex chemical, biological, and environmental systems, while the potential mathematical selectivity of liquid chromatography-mass spectrometry is rarely investigated. This work discussed the mathematical selectivity of liquid chromatography-mass spectrometry by three-way calibration based on the trilinear model, with an application to quantitative analysis of coeluting aromatic amino acids in human plasma. By the trilinear decomposition of the constructed liquid chromatography-mass spectrometry-sample trilinear model and individual regression of the decomposed relative intensity versus concentration, the proposed three-way calibration method successfully achieved quantitative analysis of coeluting aromatic amino acids in human plasma, even in the presence of uncalibrated interferent(s) and a varying background. This analytical method can ease the requirements for sample preparation and complete chromatographic separation of components, reduce the use of organic solvents, decrease the time of chromatographic separation, and increase the peak capacity of liquid chromatography-mass spectrometry. As a "green analytical method", the liquid chromatography-mass spectrometry three-way calibration method can provide a promising tool for direct and fast quantitative analysis in complex systems containing uncalibrated spectral interferents, especially for the situation where the coelution problem is difficult to overcome.

Heterotypic immunity from prior SARS-CoV-2 infection but not COVID-19 vaccination associates with lower endemic coronavirus incidence.

Immune responses from prior severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and COVID-19 vaccination mitigate disease severity, but they do not fully prevent subsequent infections, especially from genetically divergent strains. We examined the incidence of and immune differences against human endemic coronaviruses (eCoVs) as a proxy for response against future genetically heterologous coronaviruses (CoVs). We assessed differences in symptomatic eCoV and non-CoV respiratory disease incidence among those with known prior SARS-CoV-2 infection or previous COVID-19 vaccination but no documented SARS-CoV-2 infection or neither exposure. Retrospective cohort analyses suggest that prior SARS-CoV-2 infection, but not previous COVID-19 vaccination alone, associates with a lower incidence of subsequent symptomatic eCoV infection. There was no difference in non-CoV incidence, implying that the observed difference was eCoV specific. In a second cohort where both cellular and humoral immunity were measured, those with prior SARS-CoV-2 spike protein exposure had lower eCoV-directed neutralizing antibodies, suggesting that neutralization is not responsible for the observed decreased eCoV disease. The three groups had similar cellular responses against the eCoV spike protein and nucleocapsid antigens. However, CD8+ T cell responses to the nonstructural eCoV proteins nsp12 and nsp13 were higher in individuals with previous SARS-CoV-2 infection as compared with the other groups. This association between prior SARS-CoV-2 infection and decreased incidence of eCoV disease may therefore be due to a boost in CD8+ T cell responses against eCoV nsp12 and nsp13, suggesting that incorporation of nonstructural viral antigens in a future pan-CoV vaccine may improve vaccine efficacy.

Interference-free quantitation of aromatic amino acids in two complex systems by three-way calibration with ultraviolet-visible spectrophotometer: Exploration of trilinear decomposition of spectrum-pH data.

Aromatic amino acids play an extremely important role in life activities and participate in many biological processes. Their concentration levels are associated with a variety of diseases, such as phenylketonuria and colorectal cancer. Therefore, the quantification of aromatic amino acids is an important task. In the present work, a novel and rapid three-way analytical method was proposed to detect the levels of aromatic amino acids in prostate cancer cells (PC3 cells) and Dulbecco's modified minimal essential medium (DMEM cell culture), by using the affordable ultraviolet-visible spectrophotometer. First, spectrum-pH second-order data were designed per sample; Second, properties of the resulted spectrum-pH-sample three-way data were investigated by utilizing the parallel factor analysis (PARAFAC), alternating trilinear decomposition (ATLD), and constrained alternating trilinear decomposition (CATLD) algorithms, and a flexible scanning approach for determining the constraint parameters of CATLD was proposed; Third, a three-way calibration method based on the CATLD algorithm with the proposed scanning approach was developed for interference-free quantification of aromatic amino acids in these systems. The average relative predictive errors of validation (ARPEV) for phenylalanine, tyrosine, and tryptophan were 1.4%, 3.0%, and 0.7% in prostate cancer cells, and ARPEV for phenylalanine, tyrosine, and tryptophan were 4.1%, 1.2%, and 0.7% in DMEM cell culture. The predicted contents of tyrosine and tryptophan in DMEM cell culture were 64.2 ± 2.9 µg mL-1, 5.6 ± 0.3 µg mL-1, there are no significant differences in the concentrations between the developed analytical method and high performance liquid chromatography method. The proposed spectrum-pH-sample three-way calibration method based on CATLD algorithm can provide an interesting analytical strategy with high selectivity and accuracy for ultraviolet-visible spectrophotometer.

Heterotypic responses against nsp12/nsp13 from prior SARS-CoV-2 infection associates with lower subsequent endemic coronavirus incidence.

Immune responses from prior SARS-CoV-2 infection and COVID-19 vaccination do not prevent re-infections and may not protect against future novel coronaviruses (CoVs). We examined the incidence of and immune differences against human endemic CoVs (eCoV) as a proxy for response against future emerging CoVs. Assessment was among those with known SARS-CoV-2 infection, COVID-19 vaccination but no documented SARS-CoV-2 infection, or neither exposure. Retrospective cohort analyses suggest that prior SARS-CoV-2 infection, but not COVID-19 vaccination alone, protects against subsequent symptomatic eCoV infection. CD8+ T cell responses to the non-structural eCoV proteins, nsp12 and nsp13, were significantly higher in individuals with previous SARS-CoV-2 infection as compared to the other groups. The three groups had similar cellular responses against the eCoV spike and nucleocapsid, and those with prior spike exposure had lower eCoV-directed neutralizing antibodies. Incorporation of non-structural viral antigens in a future pan-CoV vaccine may improve protection against future heterologous CoV infections.

Selectivity Quantification with the Fluorescent Quantitative Model-Assisted Semi-Selective Probe (Carbon Dots): Accurate Determination of Chlortetracycline in Aqueous Environments with Interference.

Probes such as carbon dots (C-dots) have extensive and important applications in the quantitative analysis of complex biological and environmental systems. However, the development of probes is often hindered by incomplete selectivity, i.e., a probe that responds to one substance is also prone to respond to coexisting structurally similar substances. Therefore, the above dilemma often leads to be developed as semi-selective probes, so that the development of probes is abandoned halfway. This work shows how a semi-selective probe can enhance selectivity by combining a proper multivariate calibration model. Primarily, we developed a semi-selective fluorescent probe that responded to tetracyclines (TCs) with discarded tobacco leaves. Then, we introduced the multivariate quantitative fluorescence model (QFM) to enhance its selectivity and solve the problem of fluorescence spectral shift. For the determination of chlortetracycline (CTC) with this semi-selective C-dots probe in mineral and lake water samples and compared to the traditional quantitative model, the introduced QFM resulted in an average relative predictive error (ARPE) in mineral water spiked samples decreased from 57.1 to 5.6%, which reduced the ARPE in the lake water spiked samples from 18.1 to 4.7%. The above results show that the QFM-assisted semi-selective probe C-dots strategy (QFMC-dots) can enhance selectivity, and QFMC-dots achieved high-selective and accurate determination of CTC in interfering mineral and lake water samples, with the limit of detection and limit of quantitation of 0.55 and 1.66 µM, respectively. The proposed strategy of enhancing selectivity by introducing a proper multivariate calibration model can reduce the difficulty and increase success rate of developing probes, which can be expected to provide an interesting alternative for the development of probes, especially when encountering semi-selective problems.

Waste tobacco leaves derived carbon dots for tetracycline detection: Improving quantitative accuracy with the aid of chemometric model.

The recycling and reutilization of biomass wastes are significant for environmental protection and sustainable development. Recently, there have many studies on utilizing biomass wastes to produce carbon dots. Whereas, the spectrum shift effect that occurs in the quantitative application of carbon dots as fluorescent probes limits the accuracy of the quantitative analysis. In this work, waste tobacco leaves were used as the carbon source for synthesizing a novel carbon dots (CDs(WTL)) through a facile hydrothermal method. The CDs(WTL) possess a series of excellent properties, including good water solubility, well stability, and high fluorescence quantum yield. The fluorescent intensity of the CDs(WTL) can be quenched by tetracycline (TC) obviously, but there is a spectrum shift. In order to use the CDs(WTL) as fluorescent probes to quantify TC with higher accuracy, a quantification fluorescence model (QFM) was introduced to overcome this spectrum shift effect that often occurs. The coefficient of determination (R2) of traditional quantification model (TQ), partial least squares (PLS), and QFM are 0.9672, 0.9834, and 0.9991, respectively; the average relative predictive error (ARPE) of TQ, PLS, and QFM are 8.8%, 4.5%, and 3.9% for the spiked water samples, and 21.9%, 22.0%, and 2.9% for spiked tablet samples, respectively. The obtained results suggest that QFM is more accurate than PLS and TQ for the TC detection. By utilizing QFM, the spike recoveries (mean ± standard deviation) in three kinds of real tablet samples produced by different manufacturers are 98.9 ± 3.6%, 102.5 ± 6.2%, and 98.5 ± 2.7%, respectively; the spike recovery in river water samples is 99.4 ± 5.0%. In addition, high performance liquid chromatography (HPLC) was used as a reference method, the F and t tests suggest that there are no significant differences on the precision and accuracy between QFM and HPLC methods.