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Vaccines trigger an immunological response that includes B and T cells, with B cells producing antibodies. SARS-CoV-2 immunity weakens over time after vaccination. Discovering key changes in antigen-reactive antibodies over time after vaccination could help improve vaccine efficiency. In this study, we collected data on blood antibody levels in a cohort of healthcare workers vaccinated for COVID-19 and obtained 73 antigens in samples from four groups according to the duration after vaccination, including 104 unvaccinated healthcare workers, 534 healthcare workers within 60 days after vaccination, 594 healthcare workers between 60 and 180 days after vaccination, and 141 healthcare workers over 180 days after vaccination. Our work was a reanalysis of the data originally collected at Irvine University. This data was obtained in Orange County, California, USA, with the collection process commencing in December 2020. British variant (B.1.1.7), South African variant (B.1.351), and Brazilian/Japanese variant (P.1) were the most prevalent strains during the sampling period. An efficient machine learning based framework containing four feature selection methods (least absolute shrinkage and selection operator, light gradient boosting machine, Monte Carlo feature selection, and maximum relevance minimum redundancy) and four classification algorithms (decision tree, k-nearest neighbor, random forest, and support vector machine) was designed to select essential antibodies against specific antigens. Several efficient classifiers with a weighted F1 value around 0.75 were constructed. The antigen microarray used for identifying antibody levels in the coronavirus features ten distinct SARS-CoV-2 antigens, comprising various segments of both nucleocapsid protein (NP) and spike protein (S). This study revealed that S1 + S2, S1.mFcTag, S1.HisTag, S1, S2, Spike.RBD.His.Bac, Spike.RBD.rFc, and S1.RBD.mFc were most highly ranked among all features, where S1 and S2 are the subunits of Spike, and the suffixes represent the tagging information of different recombinant proteins. Meanwhile, the classification rules were obtained from the optimal decision tree to explain quantitatively the roles of antigens in the classification. This study identified antibodies associated with decreased clinical immunity based on populations with different time spans after vaccination. These antibodies have important implications for maintaining long-term immunity to SARS-CoV-2.
RESUMO
Porous materials are deemed to be capable for promoting hydrate formation, while for the purpose of hydrate-based gas storage, those systems containing porous materials often cannot meet the requirement of high storage density. To increase the storage density, an adsorption-hydration sequence method was designed and systematically examined in this study. Methane storage and release in ZIF-8 slurries and fixed beds were investigated. The ZIF-8 retained 98.62%, while the activated carbon lost 62.17% of their adsorption capacities in slurry. In ZIF-8 fixed beds, methane storage density of 127.41 V/Vbed was acquired, while the gas loss during depressurization accounted for 21.50% of the gas uptake. In the ZIF-8 slurry, the storage density was effectively increased with the adsorption-hydration sequence method, and the gas loss during depressurization was much smaller than that in fixed beds. In the slurry, the gas uptake and gas loss decreased with the decrease of the chilling temperature. The largest gas uptake and storage density of 78.84 mmol and 133.59 V/Vbed were acquired in the slurry with ZIF-8 content of 40 wt.% at 268.15 K, meanwhile, the gas loss just accounted for 14.04% of the gas uptake. Self-preservation effect was observed in the slurry, and the temperature for the slowest gas release was found to be 263.15 K, while the release ratio at 10 h reached to 43.42%. By increasing the back pressure, the gas release rate could be effectively controlled. The gas release ratio at 1.1 MPa at 10 h was just 11.08%. The results showed that the application of adsorption-hydration sequence method in ZIF-8 slurry is a prospective manner for gas transportation.
RESUMO
In this study, 7 stains of Rhodopseudomonas sp. were selected from 36 photosynthetic bacteria stains storied in our laboratory. Rhodopseudomonas sp. strain 99-28 has the highest 5-aminolevulinic acid(ALA) production ability in these 7 strains. Rhodopseudomonas sp. 99-28 strain was mutated using ultraviolet radiation and a mutant strain L-1, which ALA production is higher than wild strain 99-28 about one times, was obtained. The elements affecting ALA formation of strain 99-28 and L-1 were studied. Under the optimal condition( pH 7.5, supplement of ALA dehydratase(ALAD) inhibitor, levulinic acid(LA) and precursors of ALA synthesis, glycine and succinat, 3000 Ix of light density), ALA formation of mutant L-1 was up to 22.15 mg/L. Strain L-1 was used to treat wastewater to remove COD(Cr) and produce ALA. ALA production was 2.819 mg/L, 1.531 mg/L, 2.166 mg/L, and 2.424 mg/L in monosodium glutamate wastewater(MGW), succotash wastewater(SW), brewage wastewater(BW), and citric acid wastewater(CAW) respectively. More than 90% of COD(Cr) was removed in four kinds of wastewater. When LA, glycin and succinate were supplied, ALA production was dramatically increased, however, COD(Cr) could hardly be removed.
