Estimation of low-level components lost through chromatographic separations with finite detection limits

Deep reinforcement learning for the direct optimization of gradient separations in liquid chromatography

While Reinforcement Learning (RL) has already proven successful in performing complex tasks, such as controlling large-scale epidemics, mitigating influenza and playing computer games beyond expert level, it is currently largely unexplored in the field of separation sciences. This paper therefore aims to introduce RL, specifically proximal policy optimization (PPO), in liquid chromatography, and evaluate whether it can be trained to optimize separations directly, based solely on the outcome of a single generic separation as input, and a reward signal based on the resolution between peak pairs (taking a value between [-1,1]). More specifically, PPO algorithms or agents were trained to select linear (1-segment) or multi-segment (2-, 3-, or 16-segment) gradients in 1 experiment, based on the outcome of an initial, generic linear gradient (ϕstart=0.3, ϕend=1.0, and tg=20min), to improve separations. The size of the mixtures to be separated varied between 10 and 20 components. Furthermore, two agents, selecting 16-segment gradients, were trained to perform this optimization using either 2 or 3 experiments, in sequence, to investigate whether the agents could improve separations further, based on previous outcomes. Results showed that the PPO agent can improve separations given the outcome of one generic scouting run as input, by selecting ϕ-programs tailored to the mixture under consideration. Allowing agents more freedom in selecting multi-segment gradients increased the reward from 0.891 to 0.908 on average; and allowing the agents to perform an additional experiment increased the reward from 0.908 to 0.918 on average. Finally, the agent outperformed random experiments as well as standard experiments (ϕstart=0.0, ϕend=1.0, and tg=20min) significantly; as random experiments resulted in average rewards between 0.220 and 0.283, and standard experiments resulted in average rewards of 0.840. In conclusion, while there is room for improvement, the results demonstrate the potential of RL in chromatography and present an interesting future direction for the automated optimization of separations.

Aqueous Extract of Artemisia annua Shows In Vitro Antimicrobial Activity and an In Vivo Chemopreventive Effect in a Small-Cell Lung Cancer Model

Artemisia annua (A. annua) has been used as a medicinal plant in the treatment of several infectious and non-infectious diseases in the forms of tea and press juice since ancient times. The aim of this study was to evaluate the aqueous extract of A. annua (AAE) as an antimicrobial agent in vitro and to evaluate its chemopreventive efficacy in vivo in a small-cell lung cancer (SCLC) animal model. The dried powder of AAE was prepared using the Soxhlet extraction system from the leaves of Artemisia annua. The in vitro activity of AAE was determined against Candida albicans (C. albicans), Enterococcus faecalis (E. faecalis), Klebsiella pneumoniae (K. pneumoniae), and methicillin-resistant Staphylococcus aureus (MRSA) using the agar well diffusion method and propidium iodide (PI)-stained microbial death under a confocal microscope. The pretreatment of mice with AAE was initiated two weeks before the first dose of benzo[a]pyrene and continued for 21 weeks. The chemopreventive potential of the extract was evaluated by flow cytometry and biochemical and histopathological analyses of the tissues and serum accordingly, after sacrificing the mice. The data revealed the antimicrobial potential of AAE against all the species investigated, as it showed growth-inhibitory activity by MIC, as well as confocal microscopy. The pretreatment of AAE exhibited significant protection in carcinogen-modulated, average body weight (ABW), and relative organ weight (ROW) cancer biomarkers in the serum and antioxidants in the lungs. The hematoxylin and eosin (H&E) staining of the tissues revealed that AAE prevented malignancy in the lungs. AAE also induced apoptosis and decreased intracellular reactive oxygen species (ROS) in the lung cells analyzed by flow cytometry. The current findings demonstrated the use of AAE as an alternative medicine in the treatment of infectious disease and the chemoprevention of lung cancer. To our knowledge, this is the first study that summarizes the chemopreventive potential of AAE in a lung cancer model in vivo. However, further investigations are suggested to understand the role of AAE to potentiate the therapeutic index of the commercially available drugs that show multiple drug resistance against microbial growth and high toxicity during cancer chemotherapy.

Simulating comprehensive two-dimensional gas chromatography mass spectrometry data with realistic run-to-run shifting to evaluate the robustness of tile-based Fisher ratio analysis

Untargeted analysis of comprehensive two-dimensional (2D) gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS) data has the potential to be hindered by run-to-run retention time shifting. To address this challenge, tile-based Fisher ratio (F-ratio) analysis (FRA) has been developed, which utilizes a supervised, untargeted approach involving a chromatographic segmentation routine termed "tiling" combined with the ANOVA F-ratio statistic to discover class-distinguishing analytes while minimizing false positives arising from shifting. The tiling algorithm is designed to account for retention shifting in both separation dimensions. Although applications of FRA have been reported, there remains a need to thoroughly evaluate the robustness of FRA for different levels of run-to-run retention shifting in order to broaden the scope of its application. To this end, a novel method of simulating GC×GC-TOFMS chromatograms with realistic run-to-run shifting is presented by random generation of low-frequency "shift functions". The dimensionless retention-time precision, <δ_r>, which is four times the standard deviation in retention time normalized to the peak width-at-base is used as a key modeling variable along with the 2D chromatographic saturation, α_e,2D, and within-class relative standard deviation in peak area, RSD_wc. We demonstrate that all three of these variables operate together to impact true positive discovery. To quantify the "success" of true positive discovery, GC×GC-TOFMS datasets for various combinations of <δ_r>, α_e,2D, and RSD_wc were simulated and then analyzed by FRA using a wide range of relative tile areas (RTA), which is a dimensionless measure of tile size. Since each hit in the FRA hit list was known a priori as either a true or false positive based on the simulation inputs, receiver operating characteristic (ROC) curves were readily constructed. Then, the area under the ROC curve (AUROC) was used as a metric for discovery "success" for various combinations of the modeling variables. Based on the results of this study, recommendations for tile size selection and experimental design are provided, and further supported by comparison to previous tile-based FRA applications. For instance, values for <δ_r>, α_e,2D, and RSD_wc obtained from a GC×GC-TOFMS dataset of yeast metabolites suggested an optimum RTA of 6.25, corresponding closely to the RTA of 4.00 employed in the study, implying the simulation results obtained here can be generalized to real datasets.

Determination of the Signal-To-Noise Ratio Enhancement in Comprehensive Three-Dimensional Gas Chromatography

We investigate the extent to which comprehensive three-dimensional gas chromatography (GC³) provides a signal enhancement (SE) and a signal-to-noise ratio enhancement (S/N_Rel) relative to one-dimensional (1D)-GC. Specifically, the SE is defined as the ratio of the tallest ³D peak height from the GC³ separation to the 1D peak height from the unmodulated 1D-GC separation. A model is proposed which allows the analyst to predict the theoretically attainable SE (SE_T) based upon the peak width and sampling density inputs. The model is validated via comparison of the SE_T to the experimentally measured SE (SE_M) obtained using total-transfer GC³ (100% duty cycle for both modulators) with time-of-flight mass spectrometry detection. Two experimental conditions were studied using the same GC³ column set, differing principally in the modulation period from the ¹D to ²D columns: 4 s versus 8 s. Under the first set of conditions, the average SE_M was 97 (±22), in excellent agreement with the SE_T of 97 (±18). The second set of conditions improved the average SE_M to 181 (±27), also in agreement with the average SE_T of 176 (±26). The average S/N_Rel following correction for the mass spectrum acquisition frequency was 38.8 (±11.2) and 59.0 (±27.2) for the two sets of conditions. The enhancement in S/N is largely attributed to moving the signal to a higher frequency domain where the impact of "low frequency" noise is less detrimental. The findings here provide strong evidence that GC³ separations can provide enhanced detectability relative to 1D-GC and comprehensive two-dimensional gas chromatography (GC×GC) separations.

A comparison of 2 micron inner diameter open tubular column liquid chromatography with pressure-driven isocratic, slip-flow, and electrochromatographic modes of operation: a theoretical study

Modifications to the flow profile used in open tube capillary liquid chromatography (OT-CLC) include using slip-flow walls and using electroosmosis as a fluid pump as practiced in electrochromatography. These modifications are implemented experimentally by changing the capillary surface and solvent conditions which results in the change of boundary conditions at the capillary wall. In this paper we employ a theory-based study and compare the zone broadening of simple solutes using parabolic flow from a liquid pump, slip-flow from a highly hydrophobic inner surface with water eluent, and electroosmosis for the conditions of pure water and dilute salt utilizing 2 µm inner diameter OT capillaries. In general, the two types of flow other than parabolic exhibit thin zones in the early part of the chromatogram, consistent with previous studies of slip-flow and electroosmotic flow used in electrochromatography. Electrochromatography is shown to yield higher efficiency and less zone broadening than parabolic and slip-flow conditions used in this study. Nonetheless, it is found that the zone standard deviations are shown to be similar for these flow profiles as is the number of plates for these different flow profiles under the conditions utilized here. It is revealed that these modifications do not warrant the effort to maintain the special solvent conditions when compared to gradient elution OT-CLC, which gives a nearly constant peak width throughout the chromatogram, is easiest to implement, and is the method of choice for complex analysis.