Braswellbak1645

43.Lipid-oligonucleotide (LONs) based bioconjugates represent an emerging class of therapeutic agents, allowing the delivery of therapeutic oligonucleotide sequences. The LON development requests accurate and efficient analytical methods. In this contribution, LON analysis methods were developed in cyclodextrin-modified capillary zone electrophoresis (CD-CZE). The LONs selected in this study feature different structures, including i) the oligonucleotide length (from 10 to 20 nucleotides), ii) the inter-nucleotide linkage chemistry (phosphodiester PDE or phosphorothioate PTO), and iii) the lipidic part single- (LONsc) or double-chain (LONdc) lipids. In CD-CZE, the effect of several parameters on the electrophoretic peaks was investigated (buffer, CD, and capillary temperature). The binding interaction between LON and Me-β-CD was studied in affinity capillary electrophoresis and revealed a 11 LONCD complex. Non-linear regression and three usual linearization methods (y-reciprocal, x-reciprocal, and double-reciprocal) were used to determine the binding constants (K values of 2.5.104 M-1 and 2.0.104 M-1 for LON PDE and LON PTO, respectively). Quantitative methods with good performances and analysis time lower than 5 min were achieved. Importantly, the developed analysis allows a separation between the i) full-length sequence LONs and their truncated sequences, (n-1), (n-2), and (n-4)-mers and ii) LONsc, LONdc and their corresponding unconjugated oligonucleotides. This work highlights the interest of CD-CZE methods for LON analysis.The rapid and sensitive assay is the goal for advancing analytical methods and techniques to save time and achieve the early diagnosis, which are of crucial importance in clinic. The concept of synergistic effects for fastening reaction and improving sensitivity was constructed by introducing iodide (I-) to the typical Fenton's reaction system as a model reaction, which was calculated theoretically and demonstrated experimentally. In an acid medium, the simultaneous presence of Fe2+ and I- could significantly improve the oxidation capability and rate of H2O2 to etch gold nanorods (AuNRs) because of the synergistic effect, which was further successfully applied to the rapid and sensitive assay of cholesterol, glucose and uric acid in human serum. In this work, the synergistic effect greatly improved the reaction rate and sensitivity, which showed potential applications in biological sensing and clinic diagnosis.Relying on the specific coordination of Ag+ and mismatched cytosine-cytosine (C-C), the high-efficiency inhibition of urease by Ag+ ion, and the rapid and sensitive response of phenol red to pH, a sensitive ratiometric sensor has been designed for visual detection of human immunodeficiency virus gene (HIV DNA). This sensor utilizes the HIV DNA to initiate catalytic hairpin assembly (CHA) process, releasing Ag+ to inhibit subsequent urease-catalyzed urea hydrolysis and prevent the pH of the solution from rising. The CHA process and the absorbance ratio of phenol red at different wavelengths (A559/A432) amplify the signal, allowing the sensor to detect HIV DNA from 10 to 130 nM in a sensitive and highly selective manner with a low detection limit of 7.8 nM. In addition, this sensor can visually distinguish different concentrations of HIV DNA within a certain range and possesses a good recovery in 1% of serum samples, which will provide new ideas for biosensor design, dipstick test, blood test, and other clinical disease prevention.Single-use technologies are increasingly used in biopharmaceutical manufacturing. Despite their advantages, these plastic assemblies draw concern because they are a potential source of contamination due to extractable and leachable compounds (E&Ls). Characterising E&Ls from such materials is a necessary step in establishing their suitability for use. Therefore, there is an urgent need for sensitive methods to identify and quantitatively assess compounds in plastic materials. Accelerated solvent extraction (ASE) is a powerful technique that can be reliably used for this purpose. In this study, ASE followed by liquid chromatography and Orbitrap-based High Resolution Accurate Mass (HRAM) mass analysis was found to be an efficient and versatile method for the determination of additives in different multilayer polymer systems from single-use bags. ASE optimisation was performed using a design of experiments approach. The type of solvent, temperature, swelling agent addition, static time and number of cycles were the selected variables. Optimum conditions were dependent on the type of plastic film. Ethyl acetate and cyclohexane were selected individually as optimum solvents. selleck chemical Optimum temperatures were 90-100 °C. Pressure was set at 1500 psi and extraction time was 30 min in 2 cycles. Swelling agent addition was necessary with polar extraction solvents. More than 100 additives and degradation products were confidently identified by HRAM MS. Correlations between the type and levels of identified additives and the type of polymer system were established. In addition, degradation behaviour and pathways for some additives can be addressed.The importance of lipidomics to unveil crucial aspects in the nutrition field is afforded in this article. With this aim, historical facts such as demonization of fats, enthronization of carbohydrates, and subsequent changes in the food pyramid are first discussed. After considering basic and analytical aspects of lipidomics and the upstream information this omics provides, its key role in personalized nutrition (PN), and the importance of lipids as nutrition biomarkers are critically discussed by appropriate examples. Pendent challenges to clarify the role of lipidomics in nutrition are overcome limiting factors, design of new lipidomics-based biomarkers, unveil mechanisms involved in lipidomics processes, and integrate lipidomics with other omics for a more complete and validated information useful in PN. The conclusions of this study also include the scant role of analytical chemists in the lipidomics-nutrition binomial, basically supported on analytical data.