It has been reported that HILIC column chemistry has a great effect on the number of detected metabolites in LC-HRMS-based untargeted metabolite profiling studies. However, no systematic investigation has been carried out with regard to the optimisation of mobile phase characteristics. In this study using 223 metabolite standards, we explored the retention mechanisms on three zwitterionic columns with varied mobile phase composition, demonstrated the interference from poor chromatographic peak shapes on the output of data extraction, and assessed the quality of chromatographic signals and the separation of isomers under each LC condition. As expected, on the ZIC-cHILIC column the acidic metabolites showed improved chromatographic performance at low pH which can be attributed to the opposite arrangement of the permanently charged groups on this column in comparison with the ZIC-HILIC column. Using extracts from the protozoan parasite Leishmania, we compared the numbers of repeatedly detected LC-HRMS features under different LC conditions with putative identification of metabolites not amongst the standards being based on accurate mass (±3ppm). Besides column chemistry, the pH of the mobile phase plays a key role in not only determining the retention mechanisms of solutes but also the output of the LC-HRMS data processing. Fast evaporation of ammonium carbonate produced less ion suppression in ESI source and consequently improved the detectability of the metabolites in low abundance in comparison with other ammonium salts. Our results show that the combination of a ZIC-pHILIC column with an ammonium carbonate mobile phase, pH 9.2, at 20mM in the aqueous phase or 10mM in both aqueous and organic mobile phase components, provided the most suitable LC conditions for LC-HRMS-based untargeted metabolite profiling of Leishmania parasite extracts. The signal reliability of the mass spectrometer used in this study (Exactive Orbitrap) was also investigated.
Human ferritin is regarded as an attractive and promising vaccine platform because of its uniform structure, good plasticity, and desirable thermal and chemical stabilities. Besides, it is biocompatible and presumed safe when used as a vaccine carrier. However, there is a lack of knowledge of how different antigen insertion sites on the ferritin nanocage impact the resulting protein stability and performance. To address this question, we selected Epstein–Barr nuclear antigen 1 as a model epitope and fused it at the DNA level with different insertion sites, namely, the N- and C-termini of ferritin, to engineer proteins E1F1 and F1E1, respectively. Protein properties including hydrophobicity and thermal, pH, and chemical stability were investigated both by molecular dynamics (MD) simulation and by experiments. Both methods demonstrate that the insertion site plays an important role in protein properties. The C-terminus insertion (F1E1) leads to a less hydrophobic surface and more tolerance to the external influence of high temperature, pH, and high concentration of chemical denaturants compared to N-terminus insertion (E1F1). Simulated protein hydrophobicity and thermal stability by MD were in high accordance with experimental results. Thus, MD simulation can be used as a valuable tool to engineer nanovaccine candidates, cutting down costs by reducing the experimental effort and accelerating vaccine design.
Due to the lack of labeled data, previous research on text-to-SQL parsing mainly focuses on English. Representative English datasets include ATIS, WikiSQL, Spider, etc. This paper presents DuSQL, a larges-scale and pragmatic Chinese dataset for the cross-domain text-to-SQL task, containing 200 databases, 813 tables, and 23,797 question/SQL pairs. Our new dataset has three major characteristics. First, by manually analyzing questions from several representative applications, we try to figure out the true distribution of SQL queries in real-life needs. Second, DuSQL contains a considerable proportion of SQL queries involving row or column calculations, motivated by our analysis on the SQL query distributions. Finally, we adopt an effective data construction framework via human-computer collaboration. The basic idea is automatically generating SQL queries based on the SQL grammar and constrained by the given database. This paper describes in detail the construction process and data statistics of DuSQL. Moreover, we present and compare performance of several open-source textto-SQL parsers with minor modification to accommodate Chinese, including a simple yet effective extension to IRNet for handling calculation SQL queries.
The pumping of antitumor drugs by P-glycoprotein (P-gp) causes multidrug resistance (MDR) and consequent failure of chemotherapy. However, the understanding on the molecular mechanism of P-gp for transporting substrates is still far from adequate. Herein, the transport of a typical antitumor drug, doxorubicin, by P-gp is investigated using targeted molecular dynamics (MD) simulations and molecular mechanics Poisson–Boltzmann surface area (MM-PBSA) analysis. The MM-PBSA analysis identifies the driving forces for the transport of doxorubicin toward the extracellular space as electrostatic repulsions in the initial stage, which are contributed by positively charged residues (R148, K181, K189, K285, K291, K734, R789, K826, K934, and K1000) and then hydrophobic interactions provided by hydrophobic residues (L65, M69, F336, I340, F343, Y953, V982, F983, and M986). The contributions of these residues are further validated by targeted MD simulations, which shows blocked pumping after the mutation of these important residues to glycine. The MM-PBSA and minimum distance analyses of each residue during the transport reveal that the positively charged residues promote the transport of doxorubicin through long-range electrostatic repulsions and the hydrophobic residues provide a pathway through continuous hydrophobic interactions to maintain the transport. The results have thus provided molecular insights into the function of P-gp and would be beneficial in the design of potent P-gp inhibitors against MDR in the medication of cancers.
The association cortices of the brain are essential for integrating multimodal information that subserves complex and high-order cognitive functions. To delineate the changing pattern of associative cortices can provide critical insight into brain development, aging, plasticity, and disease-triggered functional abnormalities. However, how to quantitatively characterize the association capability of the brain is elusive. Here, we developed a new method of association index (Asso) at the voxel level to quantitatively characterize the brain association ability. Using the Asso method, we found high Asso values in association cortical networks, and low values in visual and limbic networks, suggesting a pattern of significant gradient distribution in neural functions. The spatial distribution patterns of Asso show high similarities across different thresholds suggesting that Asso mapping is a threshold-free method. In addition, compared with functional connectivity strength, i.e., degree centrality method, Asso mapping showed different patterns for association cortices and primary cortices. Finally, the Asso method was applied to investigate aging effects and identified similar findings with previous studies. All these results indicated that Asso can characterize the brain association patterns effectively and open a new avenue to reveal a neural basis for development, aging, and brain disorders.
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