Analysis of Additives in Milk Powders with SPE-HPLC or 2D-HPLC Method

Dairy products are beneficial to human health, especially for formula-fed newborns. According to the regulation of FDA and China national food safety standard, food additives such as benzoic acid, sorbic acid, natamycin, lysozyme, saccharin sodium, and aspartame are not permitted to be added to milk powder. So, the establishment of accurate and convenient methods for the analysis of these food additives in milk powder is critical to people’s health. For the reason of the complex matrix of infant milk powders, we compared six sample pretreatment methods (liquid-liquid extraction, organic precipitation, heavy precipitation, and three different solid-phase extraction (SPE) methods (C18, HLB, MAX)) from recovery, easy operation, time cost, and organic solvent usage aspects. Finally, Poly-Sery HLB cartridge was confirmed as the most appropriate material for its high recovery and time cost merits. We are also introducing two-dimensional liquid chromatography (2DLC) method for the simultaneous determination of five major proteins and seven food additives in milk powders. Optimization of switching mode, choice of columns, mobile phase, and flow speed was discussed. We also compared limit of detection (LOD), recovery, and sample treatment with the results of high-performance liquid chromatography (HPLC). Results show that 2DLC is simpler, faster, and more accurate than the HPLC method

Learning Agility and Adaptive Legged Locomotion via Curricular Hindsight Reinforcement Learning

Agile and adaptive maneuvers such as fall recovery, high-speed turning, and sprinting in the wild are challenging for legged systems. We propose a Curricular Hindsight Reinforcement Learning (CHRL) that learns an end-to-end tracking controller that achieves powerful agility and adaptation for the legged robot. The two key components are (I) a novel automatic curriculum strategy on task difficulty and (ii) a Hindsight Experience Replay strategy adapted to legged locomotion tasks. We demonstrated successful agile and adaptive locomotion on a real quadruped robot that performed fall recovery autonomously, coherent trotting, sustained outdoor speeds up to 3.45 m/s, and tuning speeds up to 3.2 rad/s. This system produces adaptive behaviours responding to changing situations and unexpected disturbances on natural terrains like grass and dirt

A Fast and Validated HPLC Method for Simultaneous Determination of Dopamine, Dobutamine, Phentolamine, Furosemide, and Aminophylline in Infusion Samples and Injection Formulations

A simple, fast, and validated HPLC method was developed for the simultaneous quantization of five cardiovascular agents: dopamine (DPM), dobutamine (DBM), phentolamine (PTM), furosemide (FSM), and aminophylline (APL) either in infusion samples or in an injection dosage form. The proposed method was achieved with a 150 mm × 4.6 mm, 5.0 μm C18 column, by using a simple linear gradient. Mobile phase A was buffer (50 mM KH2PO4) and mobile Phase B was acetonitrile at a flow rate of 1.0 mL/min. The column temperature was kept at 30°C, and the injection volume was 20 μL. All analytes were separated simultaneously at a retention time (tr) of 3.93, 5.84, 7.06, 8.76, and 9.67 min for DPM, DBM, PTM, FSM, and APL, respectively, with a total run time of less than 15.0 min. The proposed method was validated according to ICH guidelines with respect to accuracy, precision, linearity, limit of detection, limit of quantitation, and robustness. Linearity was obtained over a concentration range of 12.0–240.0, 12.0–240.0, 20.0–200.0, 6.0–240.0, and 10.0–200.0 μg/mL DPM, DBM, PTM, FSM, and APL, respectively. Interday and intraday accuracy and precision data were recorded in the acceptable limits. The new method has successfully been applied for quantification of all five drugs in their injection dosage form, infusion samples, and for evaluation of the stability of investigated drugs in mixtures for endovenous use. The results of the stability study showed that mixtures of DPM, DBM, PTM, FSM, and APL in 5% glucose or 0.9% sodium chloride injection were stable for 48 hours when stored in polypropylene syringes at 25°C

Simultaneous determination of five diuretic drugs using quantitative analysis of multiple components by a single marker

Abstract Background Loop diuretics are commonly used in clinical practice to manage high fluid loads and to control fluid balance. In this paper, a novel quantitative analysis method for multiple components with a single marker (QAMS) was developed for the simultaneous determination of 5 diuretic drugs furosemide, torasemide, azosemide, etacrynic acid, and bumetanide, by HPLC. Qualitative analysis was performed using relative retention time and ultraviolet (UV) spectral similarity as the double indicator. The QAMS method was conducted with etacrynic acid as an internal reference substance. The quantities of the other four diuretics were calculated by using the relative correction factors for etacrynic acid. The quantities of the 5 diuretic drugs were also determined by the external standard method (ESM). Chromatographic separation was achieved on a Shimadzu HC-C18 column (150 mm × 4.6 mm, 5 µm) using 50 mM potassium dihydrogen phosphate (pH adjusted to 4.0 with phosphoric acid) with acetonitrile (64:36, v/v) as the mobile phase at a flow rate of 1.0 mL/min and a column temperature of 30 ℃. Results Under these conditions, the 5 diuretic drugs were well separated, showing linear relationships within certain ranges. The quantitative results showed that there was no significant difference between the QAMS and ESM methods. Conclusions Overall, the HPLC-QAMS analytical scheme established in this study is a simple, efficient, economical, and accurate method for the quantitative evaluation of 5 diuretic drugs

Analysis on fat-soluble components of sinapis semina from different habitats by GCâMS

A simple and rapid gas chromatography/mass spectrometry (GC/MS) analysis method was developed for the determination of fat-soluble parts of sinapis semina. Four major compounds were chosen as marker compounds to evaluate the method. Various extraction techniques were evaluated and the greatest efficiency was observed with sonication extraction using diethyl ether. The method was valuated as follows: acceptable apparatus suitability was obtained by testing the resolutions, tailing factors and theoretical plate number of the marker compounds; the precision and reproducibility, expressed as relative standard deviation (RSD), fell within the prescribed limits. Eight samples of sinapis semina collected from markets in Xi'an were monitored by using the method. The fingerprints of those samples were analyzed by hierarchical cluster analysis (HCA) similarity analysis. The result indicated that the combination of fingerprint and HCA could be used to analyze sinapis semina from different habitats. Keywords: Sinapis semina, Sonication extraction, GC/MS, Fingerprint, HC

Mass Transfer and Droplet Behaviors in Liquid-Liquid Extraction Process Based on Multi-Scale Perspective: A Review

Liquid-liquid extraction is an important separation technology in the chemical industry, and its separation efficiency depends on thermodynamics (two-phase equilibrium), hydrodynamics (two-phase mixing and contact), and mass transfer (molecular diffusion). For hydrodynamics, the dispersion size of droplets reflects the mixing of two phases and determines the mass transfer contact area of the two phases. Therefore, a deep understanding of the droplet dispersion mechanism can help guide process intensification. The mass transfer and droplet behaviors in the liquid-liquid extraction process are reviewed based on three scales: equipment, droplets, and the interface between two liquids. Studies on the interaction between mass transfer and other performance parameters in extraction equipment as well as liquid-liquid two-phase flow models are reviewed at the equipment scale. The behaviors of droplet breakage and coalescence and the kernel function of the population balance equation are reviewed at the droplet scale. Studies on dynamic interfacial tension and interaction between interfaces are reviewed at the interface scale. Finally, the connection among each scale is summarized, the existing problems are analyzed, and some future research directions are proposed in the last section

Sensitive Quantification of Liensinine Alkaloid Using a HPLC-MS/MS Method and Its Application in Microvolume Rat Plasma

Liensinine, an important alkaloid in lotus seed, exhibits multiple functions such as anti-AIDS, anticancer, antidepressant, and antihypertensive properties. In this study, a highly sensitive HPLC-MS/MS method was developed and validated for the quantification of liensinine in microvolume rat plasma as low as 45 μL. Chromatographic separation was carried out using a reverse-phase Gemini-C18 column (100 mm × 3 mm i.d. × 5 μm), and mass selective detection using multiple reaction monitoring was attained using an electrospray ionization source, which operated in the positive mode. Dauricine was used as the internal standard. The precursor-to-product ion transition m/z 611.15 > 206.10 was selected for the detection of liensinine; m/z 625.25 > 206.10 was used for the detection of dauricine. The developed method is linear over the concentration range of 0.05–1000 ng/mL with an excellent coefficient of determination (R2 = 0.991). The recoveries ranged from 92.57% to 95.88% at three quality control levels. Intraday and interday precision and accuracy are less than 12.2% and 6.59%, respectively. The lower limit of quantification (LLOQ) is 0.05 ng/mL. The matrix effect was insignificant and acceptable. The validated method was successfully applied to the pharmacokinetic study of liensinine in rats. This method can be used for in vivo studies as well as quality control of traditional Chinese medicines and herbal tea containing liensinine alkaloid

Multimodal data matters: language model pre-training over structured and unstructured electronic health records

The massive amount of electronic health records (EHR) has created enormous potential in improving healthcare. Clinical codes (structured data) and clinical narratives (unstructured data) are two important textual modalities in EHR. Clinical codes convey diagnostic and treatment information during the hospital, and clinical notes carry narratives of clinical providers for patient encounters. They do not exist in isolation and can complement each other in most real-life clinical scenarios. However, most existing EHR-oriented studies either focus on a particular modality or integrate data from different modalities in a straightforward manner, which ignores the intrinsic interactions between them. To address these issues, we proposed a Medical Multimodal Pre-trained Language Model, named MedM-PLM, to learn enhanced EHR representations over structured and unstructured data. In MedM-PLM, two Transformer-based neural network components are firstly adopted to learn representative characteristics from each modality. A cross-modal module is then introduced to model their interactions. We pre-trained MedM-PLM on the MIMIC-III dataset and verified the effectiveness of the model on three downstream clinical tasks, i.e., medication recommendation, 30-day readmission prediction and ICD coding. Extensive experiments demonstrate the power of MedM-PLM compared with state-of-the-art methods. Further analyses and visualizations show the robustness of our model, which could potentially provide more comprehensive interpretations for clinical decision-making.Comment: 30 pages, 5 figure

Quantification of the ion transport mechanism in protective polymer coatings on lithium metal anodes.

Protective Polymer Coatings (PPCs) have been proposed to protect lithium metal anodes in rechargeable batteries to stabilize the Li/electrolyte interface and to extend the cycle life by reducing parasitic reactions and improving the lithium deposition morphology. However, the ion transport mechanism in PPCs remains unclear. Specifically, the degree of polymer swelling in the electrolyte and the influence of polymer/solvent/ion interactions are never quantified. Here we use poly(acrylonitrile-co-butadiene) (PAN-PBD) with controlled cross-link densities to quantify how the swelling ratio of the PPC affects conductivity, Li+ ion selectivity, activation energy, and rheological properties. The large difference in polarities between PAN (polar) and PBD (non-polar) segments allows the comparison of PPC properties when swollen in carbonate (high polarity) and ether (low polarity) electrolytes, which are the two most common classes of electrolytes. We find that a low swelling ratio of the PPC increases the transference number of Li+ ions while decreasing the conductivity. The activation energy only increases when the PPC is swollen in the carbonate electrolyte because of the strong ion-dipole interaction in the PAN phase, which is absent in the non-polar PBD phase. Theoretical models using Hansen solubility parameters and a percolation model have been shown to be effective in predicting the swelling behavior of PPCs in organic solvents and to estimate the conductivity. The trade-off between conductivity and the transference number is the primary challenge for PPCs. Our study provides general guidelines for PPC design, which favors the use of non-polar polymers with low polarity organic electrolytes