Parallel Experiments Research Articles

A Direction-Preserved Vessel Trajectory Compression Algorithm Based on Open Window

Ship trajectory data can be used in most marine-related research, and most ship trajectory data come from AIS. The large number of ships and the short reporting period of AIS have resulted in a huge amount of ship trajectory data, which has caused a certain amount of pressure on the relevant research. This paper proposes a direction-preserved vessel trajectory compression method based on Open Window, which can effectively retain the direction change feature points while ensuring the position error. In addition, the method can work in both offline and online modes. Also, the velocity threshold and low-speed redundancy points problems are considered. In order to verify the effect of the proposed method and the adaptability of the method to different feature data, a parallel experiment was performed on port water and coastal water datasets. The results show that our method can compress vessel trajectories while retaining the feature points. Meanwhile, by comparing it with the compression method that is based on distance thresholds, the vessel trajectory compress time is drastically reduced by up to 87.3% in the port water data. The research in this paper provides a new method through which to compress vessel trajectories for research in marine-related fields on vessel trajectory.

The emergence of economic rationality of GPT.

As large language models (LLMs) like GPT become increasingly prevalent, it is essential that we assess their capabilities beyond language processing. This paper examines the economic rationality of GPT by instructing it to make budgetary decisions in four domains: risk, time, social, and food preferences. We measure economic rationality by assessing the consistency of GPT's decisions with utility maximization in classic revealed preference theory. We find that GPT's decisions are largely rational in each domain and demonstrate higher rationality score than those of human subjects in a parallel experiment and in the literature. Moreover, the estimated preference parameters of GPT are slightly different from human subjects and exhibit a lower degree of heterogeneity. We also find that the rationality scores are robust to the degree of randomness and demographic settings such as age and gender but are sensitive to contexts based on the language frames of the choice situations. These results suggest the potential of LLMs to make good decisions and the need to further understand their capabilities, limitations, and underlying mechanisms.

Assimilating a blended dataset of satellite-based estimations and in situ observations to improve WRF-Chem PM2.5 prediction

Continuous improvement in remote sensing observation-based techniques has enabled data inversion assimilation methods to play an increasingly important role in the field of numerical forecasting. Using an artificial intelligence fusion inversion method can overcome the multisource heterogeneity of data, thereby providing a better blended source for data assimilation (DA) and improving the forecasting capability. This study proposed a multimodel stacking machine learning algorithm to estimate surface concentrations of PM2.5 (particulate matter with an aerodynamic equivalent diameter of ≤2.5 μm) using Himawari-8 satellite data. The derived satellite-based PM2.5 estimation was then blended with the in situ observations as physical constraints to obtain a high-resolution multisource blended dataset. To determine the level of improvement provided by the blended dataset, four parallel experiments were conducted during February 2022: a control experiment without DA (noDA), an experiment that assimilated satellite-based estimation dataset (sate-basedDA), an experiment that assimilated multisource blended dataset (blendDA) and an experiment that assimilated in situ observations (siteDA) based on the Gridpoint Statical Interpolation system. Statistically, in comparison with the direct satellite-based PM2.5 estimations, the blended dataset better matched the in situ observations. The accuracy of PM2.5 predictions can be optimized by DA and for the first 24-h period the blended dataset performed better than the traditional ground observations as the assimilation source. Throughout the initial 24-h period, the results of blendDA (siteDA, sate-basedDA) showed an improvement in terms of root-mean-square error, with reductions varying from 6.65 to 20.20 μg/m3 (4.50–19.79 μg/m3, 2.29–10.86 μg/m3).

Reverse Iontophoresis: Noninvasive Assessment of Topical Drug Bioavailability.

Assessing drug disposition in the skin after the application of a topical formulation is difficult. It is hypothesized that reverse iontophoresis (RI), which can extract charged/polar molecules for monitoring purposes, may provide a noninvasive approach for the assessment of local drug bioavailability. The passive and RI extraction of salicylic acid (SA) and nicotine (NIC) from porcine skin in vitro was assessed after a simple solution of the former and a transdermal patch of the latter had been applied for 24 and 8 h, respectively. Immediately after this "passive skin loading", the amount of drug in the stratum corneum (SC) and "viable" tissue (VT) was measured either (a) after tape-stripping and subsequent solvent extraction of both skin layers or (b) following RI extraction over 4 h. Parallel experiments were then performed in vivo in healthy volunteers; in this case, the VT was not sampled and the skin loading period for NIC was only 4 h. RI extraction of both drugs was significantly higher (in vitro and in vivo) than that achieved passively, and the cumulative RI extraction profiles as a function of time were mathematically analyzed using a straightforward compartmental model. Best-fit estimates of drug amounts in the SC and VT (ASC,0 and AVT,0, respectively) at the end of "loading" and two first-order rate constants describing transfer between the model compartments were then determined. The in vitro predictions of ASC,0 and AVT,0 were in excellent agreement with the experimental results, as was the value of the former in vivo. The rate constants derived from the in vitro and in vivo results were also similar. In summary, the results provide proof-of-concept that the RI method has the potential to noninvasively assess relevant metrics of drug bioavailability in the skin.

Abstract B049: Lipid nanoparticle-delivered toll-like receptor agonists are highly effective in cancer immunotherapy

Abstract Background: Tumor immunotherapy has shown promising efficacy in various types of cancer. However, the effectiveness of immunotherapy is often limited by the immune-suppressive microenvironment within tumors. To address this challenge, we developed a method of intratumoral injection using lipid nanoparticles (LNPs) to deliver Toll-like receptor 7, 8, and 9 agonists. LNPs effectively enhance immune activation while reducing systemic responses by increasing drug retention within the tumor. Methods: We encapsulated 30nt-CpG and Resiquimod into LNPs (QTsomeTM). Subcutaneous inoculation of 2 × 106 MC38 cells was performed in mice. Once the average tumor volume reached approximately 100mm3, we divided 15 mice into 3 groups based on tumor volume. Intratumoral injections began on the same day of grouping, with a dosage of 1mg/kg (5 injections every 3 days). Tumor volume and body weight were measured twice a week. We conducted two parallel experiments, each with 7 mice for the MC38 model and 8 mice for the B16 melanoma model in each group, to compare the efficacy of 26nt-CpG and 30nt-CpG. Results: On the 15th day post-dosing, the tumor growth inhibition rate (TGI) was 79.9% (P<0.001), resulting in a 73.7% increase in survival rate. LNP-delivered 26nt-CpG demonstrated a TGI rate of 75.4% (P<0.001), while 30nt-CpG showed a TGI of 81.9% (P<0.001). Interestingly, the 26nt-CpG group exhibited faster weight gain, indicating better safety. In the mouse B16 melanoma model, LNP-delivered 26nt-CpG achieved a TGI rate of 75.2% (P<0.001), slightly higher than 30nt-CpG (71.0%, P<0.001), and also resulted in faster weight gain. Conclusion: In conclusion, the use of LNP-delivered Toll-like receptor agonists demonstrated excellent tumor therapeutic effects and good safety in mouse models. Activation of Toll-like receptors effectively stimulated immune cells such as CD8+ T cells and NK cells, enhancing their ability to kill tumor cells. Direct injection of LNPs into the tumor improved this effect while reducing systemic side effects. This drug holds promise as a broad-spectrum anti-tumor treatment and may have potential for expanding the indications of existing tumor immunotherapies. Citation Format: Jun Bai, Fei Su, Chen Li, Yujing Wu, Jing Li, Xiaobin Zhao, Yongsheng Yang, Robert J Lee. Lipid nanoparticle-delivered toll-like receptor agonists are highly effective in cancer immunotherapy [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2023 Oct 1-4; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2023;11(12 Suppl):Abstract nr B049.

Contributed Session III: Active vision shapes ocular dominance.

Ocular dominance is a basic visual property that shows short-term plasticity in adult humans, where 2h of monocular deprivation leads to a homeostatic shift of ocular dominance in favour of the deprived eye. Using an altered reality setting, we found that this homeostatic plasticity can be triggered without depriving one eye of visual input, but merely perturbing the temporal correspondence between voluntary actions and vision in one eye. Participants wore a VR set; its monocular screens were connected with cameras monitoring the front space, which participants used to perform a complex visuomotor task. During a 60 minute period, the input to the dominant eye was delayed by 333 ms, making it useless for visuomotor coordination. Following this, ocular dominance (quantified by binocular rivalry) was systematically shifted in favour of the delayed eye, a similar effect as that produced by monocular contrast-deprivation. The shift was only observed when participants actively engaged in the visuomotor task, not when they passively watched a confederate perform the same task. We interpret these results in the light of parallel fMRI experiments where monocular deprivation is associated with a global system reconfiguration that pivots around a key area for sensorimotor integration, the Pulvinar. Based on our findings, we suggest that active vision is foundational to weighting sensory information, even at the level of simple visual processes as those setting ocular dominance.

MS-553 Therapy Inhibits BCR Signaling and Increases Survival Dependence on BCL-2 in BTK-Inhibitor Resistant CLL

B-cell receptor (BCR) signaling pathway inhibitors and B-cell lymphoma-2 (BCL-2) antagonist venetoclax (Ven) have transformed the treatment of chronic lymphocytic leukemia (CLL), including in high-risk patients with 17p deletion and/or TP53 mutations and complex karyotype. Despite the durable remissions observed with inhibitors of Bruton's Tyrosine Kinase (BTKi), a significant proportion of patients develop resistance with acquired mutations in BTK and its downstream target phospholipase Cγ2 ( PLCG2). Patients who progress on BTKi including ibrutinib (ibr) often receive Ven but eventually relapse, underscoring an urgent need for new treatment strategies. Protein kinase C-β (PKC-ß) is a protein downstream of BCR signaling (BTK-PLCG2) and is essential for CLL cell survival and proliferation in vivo. Here we investigate MS-553, an inhibitor of PKC-ß, with a focus of combination strategies in CLL patient samples including relapsed/refractory CLL. We show that CLL cells in contact with stroma upregulate PKC-ßII, its immediate downstream effectors, pGSK and pERK as well as ß-catenin in CLL patients including those with mutant TP53 and 17p (n=8). Correspondingly, MS-553 (5µM, 48h) exposure reduced levels of p-PKC-ßII and its downstream effectors (p-ERK, p-GSK) in a dose dependent manner regardless of TP53 mutation in both CLL cells and those supported by NK.Tert (stromal cell line derived from bone marrow, BM, and mimics BM microenvironment). Pre-treatment (48h, 5µM MS-553) of stromal NK.Tert cells with MS-553 prevented the upregulation of PKC-ßII within adjacent CLL cells implicating the stroma as a major source of PKC-ß activation in CLL cells. We also tested whether MS-553 could inhibit PKC-ß signaling in CLL cells exposed to phorbol myristate acetate (PMA-400nM, 90 min), which simulates BCR activation. MS-553 (5µM, 48h) exposure caused downregulation of BTK effectors (pPKC-ßII, pERK, pGSK), BCL-2 family member proteins (MCL-1 and BCLxl), and ß-catenin (n=10). In parallel experiments, we used BH3 profiling to show that CLL cells' (n=8) exposure to MS-553 in vitro developed increased dependence on BCL-2 and BCLxl for survival (Bim, Bad, XXA1_y4ek, 5-fold± 2-fold increase) in both wild type (WT) and mutant (Mut) CLL cells, suggesting a mechanistic rationale for synergy with Ven. To confirm this, CLL cells were exposed to MS-553, Ven or a combination of MS-553 and Ven. ~3-fold and 9-fold synergistic increase in the mitochondrial dysfunction (measured by cytochrome C release, 12h, 5µM MS-553, 1nM Ven) was observed in stromal supported WT and Mut CLL respectively in MS-553 versus Ven+MS-553 treated group. Similarly, ~3-fold increase was observed in WT and Mut CLL alone group and more than 10-fold increase was found in stromal supported WT and Mut group in cell death determined as percent apoptotic index (measured by annexin V-PI staining, 18h, 5µM MS-553, 1nM Ven) in MS-553 versus Ven+MS-553 group respectively. Finally, we validated our preclinical findings in CLL samples obtained from four patients on MS-553 therapy (NCT03492125, Range = cycles 0-19, MS-553 28 days/cycle). All patients showed an increase in survival dependence towards BCL-2 and BCLxl by Cycle 3-6 of MS-553 therapy. This was accompanied by downregulation of ß-catenin, pPKC-ßII, pGSK, pERK along with BCLxl and MCL-1 after Cycle 10 or later of MS-553 therapy (data summary table1). Overall, our data provides clear evidence that MS-553 inhibits BCR signaling in vitro and in patients on MS-553 therapy. It also provides a rationale for combinations with Ven as a treatment partner based on its ability to increase survival dependence on BCL-2.

Adsorption synergy electrocatalytic degradation of phenol by active oxygen-containing species generated in Co-coal based cathode and graphite anode

Abstract The coal base electrodes and efficient coal base loaded cobalt electrodes (Co-CE) were prepared by pyrolysis method of low rank coal united activation method of KOH in order to develop more pores structures. The morphology of electrodes were characterized by Scanning electron microscopy, meanwhile, the type of elements were detected by energy dispersive spectroscopy (EDS). The electrochemical performance of electrodes were tested by cyclic voltammetry and electrochemical impedance spectroscopy. The lamella structures and pores were observed in microtopography of electrodes and the cobalt were successfully loaded in Co-CE from the EDS analysis. The operating conditions of processing time, current density, electrolyte concentration, pH and initial phenol concentration on this electrochemical system in single factor experiment were separately explored, correspondingly, the value was 180 min, 40 mA·cm−2, 0.01 mol·L−1, 2, 100 mg·L−1, and the phenol removal rate (R) were at the range of 47.64–67.84%. In the optimization experiment of JMP design, the removal rate could reach at 83.47%. The response surface methodology was employed for optimizing operation conditions to improve R. And the prediction model obtained for the response can be represented as: R = 66.5275 + 6.7311X 1 – 5.4197X 4 – 5.2303X 5 + 4.9555X 1 2 – 12.5219X 2 2 – 6.2912X 4 2 + 16.0937X 5 2 + 2.4109X 2 X 4 – 7.910X 3 X 4 – 3.0123X 3 X 5 – 2.183X 4 X 5. The optimized conditions were pH 3, 100 mg·L−1 of phenol concentration, 0.1 mol/L of electrolyte concentration, 35 mA/cm2 of current density, and 180 min of processing time. Meanwhile, the predicted R was 90.86%, the actual R of three parallel experiments were 91.2%, 89.3%, 91.05%, which were well consistent with the predicted value. Additionally, the degradation mechanism was proposed as that the adsorption in pore structures synergy electrocatalytic effect of Co-CE. Micro-electric fields formed in pores and the transition metal catalysis accelerated the transformation of cathode hydrogen peroxide to generate hydroxyl radical (·OH). Furthermore, the ·OH were produced both by cathode and anode which promoted the degradation of phenol. This high catalytic activity and low cost Co-CE is a kind of prospective electrode for electrochemical degradation of phenolic wastewater.

A small-scale silica gel column chromatography method for separating carbazole compounds from highly mature crude oil

The concentration of carbazoles in highly mature crude oil is quite low, making it challenging to separate carbazole compounds for the gas chromatography-mass spectrometry (GC–MS) detection. This study presents a small-scale column chromatography method for separating carbazoles from highly mature crude oil using silica gel as a solid phase adsorbent and a Pasteur pipette as a separation device. The carbazole-rich crude oil from the Pearl River Mouth Basin was selected to explore the impact of reagent polarity and injection mode on the separation of carbazoles. The oil sample was eluted with solvents mixed with different volume proportions of n-hexane and dichloromethane and each eluted fraction was collected for GC–MS testing. The results indicated that increasing the reagent polarity caused the aromatic hydrocarbons and carbazole compounds in crude oil to be eluted sequentially. Most aromatic compounds in the crude oil could be selectively eluted using a reagent polarity ratio of 9:1 (Vn-hexane: Vdichloromethane), with no carbazole compounds. A significant amount of carbazole compounds were eluted in the polar segments of 8:2–6:4, with the eluted carbazoles concentration accounting for more than 98 % of the total concentration. Moreover, the concentration and recovery of carbazoles eluted by direct injection mode were about 10 % higher than those after adsorption by silica gel. The standard deviation of the parameter ratio for the separated carbazole compounds in the three groups of repeatable parallel experiments was less than 0.2 %. Our method is superior to traditional two-step method and C18 column method in separation efficiency and damage to human body. This method can be applied to both highly mature crude oil and other kinds of oils including biodegradable oil. It could be a versatile method for the carbazoles separation and provide technical support in unveiling the geochemical implications of these compounds in complex areas.

Reducing Winter Precipitation Biases Over the Western Tibetan Plateau in the Model for Prediction Across Scales (MPAS) With a Revised Parameterization of Orographic Gravity Wave Drag

AbstractClimate models often overestimate the precipitation in western Tibetan Plateau (TP) during winter, due to their poor ability in representing the orographic drag of unresolved complex terrain. In this study, the parameterization scheme of orographic gravity wave drag (OGWD) in the Model for Prediction Across Scales (MPAS) is revised to account for the nonhydrostatic effects (NHE) on the surface momentum flux of vertically‐propagating orographic gravity waves (OGWs). The effect of revised OGWD scheme on the simulation of winter precipitation over the TP is examined using parallel numerical experiments with the original and revised schemes, respectively. The results show that the revised scheme can effectively alleviate the precipitation biases in western TP by improving the atmospheric circulation and water vapor transport (WVT). The NHE reduces the surface wave momentum flux of OGWs which results in weaker zonal OGWD in the mid‐low troposphere and thus stronger westerlies over the TP, reducing the easterly biases in the experiment with the original OGWD scheme. The weakened zonal OGWD promotes a plateau‐scale cyclonic circulation to the north of the TP, which suppresses the northern branch of the bifurcated westerlies detouring the TP. According to quantitative analysis, the WVT into the western TP and surrounding areas by upstream westerlies is notably reduced by the northeasterlies of the cyclonic circulation, which eventually leads to the decrease of precipitation in this region.

Investigation of lithium-ion battery nonlinear degradation by experiments and model-based simulation

Understanding the lithium-ion battery (LIB) nonlinear degradation is essential for battery full-lifespan usage and management. In this study, LIBs are cycled under conditions of low-temperature and high-current charging respectively. By designing a multi-battery parallel aging experiment, the evolution process and changing regulation of lithium ions (Li-ions) loss are quantified. The amount of irreversible lithium loss caused by two side reactions, i.e., the side reaction of SEI film growth and irreversible lithium plating, within the full lifespan of LIBs is measured and analyzed, which reveals that irreversible lithium plating is the dominant reason causing the battery nonlinear degradation. With the quantitative results above, an electrochemical aging coupled model is established, which agrees well with the experimental nonlinear aging. Furthermore, a simulation of the battery secondary capacity diving is conducted, and the formation of the nonlinear aging mechanism is revealed. A porosity reduction theory is proposed, in which the capacity diving of the battery is caused by the exponential growth of irreversible lithium plating, while the exponential growth phenomenon is due to the positive feedback loop formed by the porosity reduction of the negative electrode and the irreversible lithium plating.

Remediation of aniline-contaminated aquifer by combining in-well Rhizobium borbori and circulated groundwater electrolysis

Aniline has become a common groundwater contaminant due to its wide use as a raw material in agriculture and pharmaceutical products. The current technologies for in situ remediation of aniline in groundwater are limited by the strains deficient in bacterial species, limited oxygen supply, excessive waste gas load and cost. Accordingly, we conducted a laboratory sand tank experiment to remediate groundwater contaminated with aniline by combining circulated groundwater electrolysis and in-well Rhizobium borbori, which was isolated from activated sludge. The results of the experiment indicated that the optimum concentration of aniline for Rhizobium borbori is about 5 mg/L, beyond which the maximum cell density and the highest specific growth rate decreases as the aniline concentration increases. The optimized duration for immobilizing the Rhizobium borbori into the bioreactor is 4–5 days. Though the Rhizobium borbori was strongly inhibited by the high-concentration of aniline, the immobilized bioreactor in the 350 mg/L aniline solution successfully formed biofilm. The aniline volatilization had limited influence on the observation of bioremediation performance, and the combination of circulated groundwater and in-well Rhizobium borbori supplied a steady dose of oxygen to the bioreactor efficiently degrading the entire region between the injection and extraction well. In addition, a numerical model for the sand tank remediation experiment was used to estimate the yield coefficient of oxygen to be 0.484 g/g, which indicates the presence of ammonia nitrogen as by-products; accordingly, a smaller wellbore size as well a higher circulation flow rate and intensity of current are recommended to improve the water quality. Despite the positive outcomes and potential of the newly developed technology to degrade subsurface aniline, parallel experiments should be conducted to estimate the environmental risk of the by-products and explore the controlling mechanisms of each component in this comprehensive system.

A transformer and self-cascade operation-based architecture for segmenting high-resolution bridge cracks

High-resolution (HR) crack image segmentation is crucial for accurate bridge safety diagnosis. However, accurately segmenting cracks with their slender topology and random distribution in HR images poses significant challenges. Additionally, the restricted memory capacity of graphics cards presents a significant limitation for HR image segmentation. To tackle this demanding task, a approach called Cascade CATransUNet, consisting of a coordinate attention-enhanced transformer architecture with a self-cascaded design, was proposed in this study. Firstly, CATransUNet, a transformer-based multi-scale feature extraction architecture with the embedment of the coordinate attention mechanism, is customized to enhance the extraction of the crack's main contour both horizontally and vertically. Then, a self-cascade refinement operation is introduced on the basis of CATransUNet to reconstruct the details of the extracted crack features from the global and local levels successively. Furthermore, an optimized boundary loss based on the joint cascade loss function is introduced to improve segmentation quality in boundary areas. The necessity and effectiveness of all the proposed improvements were demonstrated through ablation studies conducted on both open-sourced crack dataset and HR crack images collected on-site. Moreover, the advancement of the proposed method was confirmed in a parallel comparative experiment. The self-cascaded transformer architecture achieved impressive performance with mIoU, mBIoU, and DICE scores exceeding 89.83%, 85.78%, and 96.97% respectively, on HR (4 K) images. Finally, the proposed method was tested through an unmanned aerial vehicle (UAV)-based bridge crack inspection task. The utilization of the Cascade CATransUNet enabled the UAV to accurately detect cracks even from considerable distances. This improvement enhances safety and detection efficiency in UAV inspections, ensuring flexibility in selecting flight paths, thus providing technical support for the promotion and application of UAV-based bridge crack detection technology.

In vitro pharmacological characterization of standard and new lysophosphatidic acid receptor antagonists using dynamic mass redistribution assay.

Lysophosphatidic acid (LPA) is a bioactive phospholipid that acts as an agonist of sixG protein-coupled receptors named LPA receptors (LPA1-6). LPA elicits diverse intracellular events and modulates several biological functions, including cell proliferation, migration, and invasion. Overactivation of the LPA-LPA receptor system is reported to be involved in several pathologies, including cancer, neuropathic pain, fibrotic diseases, atherosclerosis, and type 2 diabetes. Thus, LPA receptor modulators may be clinically relevant in numerous diseases, making the identification and pharmacodynamic characterization of new LPA receptor ligands of strong interest. In the present work, label-free dynamic mass redistribution (DMR) assay has been used to evaluate the pharmacological activity of some LPA1 and LPA2 standard antagonists at the recombinant human LPA1 and LPA2 receptors. These results are compared to those obtained in parallel experiments with the calcium mobilization assay. Additionally, the same experimental protocol has been used for the pharmacological characterization of the new compound CHI. KI 16425, RO 6842262, and BMS-986020 behaved as LPA1 inverse agonists in DMR experiments and as LPA1 antagonists in calcium mobilization assays. Amgen compound 35 behaved as an LPA2 antagonist, while Merck compound 20 from WO2012028243 was detected as an LPA2 inverse agonist using the DMR test. Of note, for all the compounds, similar potency values were estimated by DMR and calcium assay. The new compound CHI was found to be an LPA1 inverse agonist, but with potency lower than that of the standard compounds. In conclusion, we have demonstrated that DMR assay can be successfully used to characterize LPA1 and LPA2 ligands. Compared to the classical calcium mobilization assay, DMR offers some advantages, in particular allowing the identification of inverse agonists. Finally, in the frame of this study, a new LPA1 inverse agonist has been identified.

Recent advances in droplet sequential monitoring methods for droplet sorting.

Droplet microfluidics is an attractive technology to run parallel experiments with high throughput and scalability while maintaining the heterogeneous features of individual samples or reactions. Droplet sorting is utilized to collect the desired droplets based on droplet characterization and in-droplet content evaluation. A proper monitoring method is critical in this process, which governs the accuracy and maximum frequency of droplet handling. Until now, numerous monitoring methods have been integrated in the microfluidic devices for identifying droplets, such as optical spectroscopy, mass spectroscopy, electrochemical monitoring, and nuclear magnetic resonance spectroscopy. In this review, we summarize the features of various monitoring methods integrated into droplet sorting workflow and discuss their suitable condition and potential obstacles in use. We aim to provide a systematic introduction and an application guide for choosing and building a droplet monitoring platform.

Rapid measurement of ageing by automated monitoring of movement of C. elegans populations

Finding new interventions that slow ageing and maintain human health is a huge challenge of our time. The nematode Caenorhabditis elegans offers a rapid in vivo method to determine whether a compound extends its 2 to 3-week lifespan. Measuring lifespan is the standard method to monitor ageing, but a compound that extends lifespan will not necessarily maintain health. Here, we describe the automated monitoring of C. elegans movement from early to mid-adulthood as a faster healthspan-based method to measure ageing. Using the WormGazer™ technology, multiple Petri dishes each containing several C. elegans worms are imaged simultaneously and non-invasively by an array of cameras that can be scaled easily. This approach demonstrates that most functional decline in C. elegans occurs during the first week of adulthood. We find 7 days of imaging is sufficient to measure the dose-dependent efficacy of sulfamethoxazole to slow ageing, compared to 40 days required for a parallel lifespan experiment. Understanding any negative consequences of interventions that slow ageing is important. We show that the long-lived mutant age-1(hx546) stays active for longer than the wild type but it moves slower in early adulthood. Thus, continuous analysis of movement can rapidly identify interventions that slow ageing while simultaneously revealing any negative effects on health.

Abstract 16947: Sotagliflozin, a Dual SGLT 1 and 2 Inhibitor, Has High Membrane Affinity and Hydrocarbon Core Location Compared With Empagliflozin

Background: The dual SGLT-1 and 2 inhibitor sotagliflozin (sota) reduced atherothrombotic events and hospitalization for worsening heart failure in patients with diabetes in clinical trials (SCORED, SOLOIST). Unlike selective SGLT2 inhibitors such as empagliflozin (empa), sota binds with higher affinity to SGLT1, which is located in the intestine, kidney, heart, brain, and vascular endothelial cells. To elucidate the physico-chemical basis for differences in tissue distribution and receptor affinity, we compared the effects of these drugs on membrane binding and molecular location. Methods: Membranes reconstituted from cardiac phospholipid and cholesterol were used to measure drug partitioning across a range of cholesterol concentrations. Multilamellar vesicles were prepared as mixtures of cardiac phospholipid (CPL), cholesterol, and each agent at 30 μM or vehicle. Drug-membrane partitioning was determined by rapid centrifugation and UV/Vis spectrophotometry. In parallel experiments, we used small angle x-ray scattering (SAXS) to identify drug location in model membranes containing phosphatidylcholine and cholesterol. Results: Sota had a membrane partition coefficient (8590 ± 2078) that was 16-fold higher than empa (519 ± 195, p<0.001) in CPL membranes. This high membrane affinity was preserved over a range of cholesterol levels compared to empa (p<0.001). Consistent with high membrane affinity, SAXS analysis showed that sota had a location evidenced by a broad increase in electron density in the hydrocarbon core extending to approximately 20 Å from the membrane center. By contrast, empa had a location limited to the polar headgroup region, consistent with its lower lipophilicity and tissue penetration. Conclusions: Sota had high membrane affinity and distinct location in the hydrocarbon core compared to empa. This may contribute to the effect of its dual SGLT-1 and 2 inhibition in vivo across various tissues including the heart. These distinct membrane interactions may also partially explain the reduced atherothrombotic risk as demonstrated in outcome trials with sota but not selective SGLT-2 inhibitors.

CONTROL INFORMATION OF STATISTICAL DATA BASED ON DISPERSION ANALYSIS

Problem statement. The accuracy and reliability of the source statistical material is the most important task of statistical observation. Even with a good organization of observations or conducting an experiment, for one reason or another, inaccuracies, errors, that is, registration errors, may appear. Analysis of the existing method of information control shows that it is too complicated, uses different criteria depending on the sample size, critical criteria values are selected from tables, calculation is performed using formulas and statistical functions of the Excel function master. The purpose of the article is to develop a method of information control based on dispersion analysis of observation data. Results. A single database of analogue objects is created. To correctly create a combined database, you need to be sure that the combined data belong to the same general population. The complexity of dispersion analysis depends on the size of the samples. If several samples of the same volume are combined, then it is easy to check their homogeneity with the help of the “One-factor dispersion analysis” tool, in the output of which the calculated and critical value F- Fisher's test - are given. The examples show that with the help of dispersion analysis it is possible not only to establish the homogeneity of samples, but also the reason for its violation. A method of dispersion analysis of the homogeneity of samples of different volumes was created using the “Descriptive statistics” tool of the analysis package. The adequacy check of the regression model of the active experiment was performed. The experiment plan determines the accuracy of the regression model. Some point is selected in the factor space and many points in its neighborhood are considered. An experiment is being conducted in this neighborhood, on the basis of which the first model is being built. The main requirement for the model is the ability to predict the direction of further experiments with the required accuracy. And the accuracy of this prediction in all search directions should be the same. A model that satisfies this requirement is called adequate. Checking the feasibility of this condition is called model adequacy analysis. In the process of conducting the experiment, it is necessary to make sure that the measured response values belong to the same general population and the technological process does not require regulation. For this purpose, is carried parallel experiments. After conducting 4 experiments according to the experiment planning matrix, it is necessary to make sure of the received response samples’ homogeneity and the reproducibility of the experiments. Conclusions. The performed calculations prove that: the existing method of information control is too complex and has significant disadvantages − different criteria are used depending on the sample size, critical values of the criteria are selected from tables, the calculation is performed using formulas and statistical functions of the Excel function master; the method of information control based on dispersion analysis does not have these disadvantages and is universal, because there is one criterion for small and large samples, the calculated and critical value of F-criterion are given in the initial information of the tool “One-factor dispersion analysis”, it can be used to create a single database analogue objects and to check the adequacy of the regression model at the active experiment.

Determination of in situ hydrocarbon contents in shale oil plays: Part 3: Quantification of light hydrocarbon evaporative loss in old cores based on preserved shales

Petroleum resource assessment obtained from laboratory tests on old core samples shelved in the open environment tend to underestimate in situ resources. Therefore, hydrocarbon loss and its restoration need to be investigated. The hydrocarbon loss was studied via the difference of programmed pyrolysis parameter (Rock–Eval derived S1) between preserved/fresh cores and their replicas that had been long-term exposed to ambient conditions. However, the in situ hydrocarbon potential is still seemed to be underestimated, because the effect of sample crushing and crucible waiting on pristine S1 detection did not receive enough attention. To solve this issue, 50 preserved shale core samples with Ro from 1.00% to 1.51% were collected from the K1qn1 Formation of northern Songliao Basin, Eastern China. All the samples were subjected to four parallel experiments: Dean–Stark extraction and nuclear magnetic resonance (NMR) T1–T2 mapping, using large rock pieces 3–5 cm in size, and thermal desorption gas chromatography (TD–GC) and Rock–Eval analysis, using 60-mesh powdered samples. In addition, a time series of TD–GC and Rock–Eval analyses were conducted on a preserved shale sample to investigate hydrocarbon loss during sample crushing, Rock–Eval crucible waiting process, and elapse-time exposure to the open environment. Rock–Eval pyrolysis was also conducted on one month-exposed shale cores and solvent-extracted samples. The results show that the total hydrocarbon content of large rock pieces is significantly greater than that of powdered samples. Sample crushing or grinding leads C8− light hydrocarbons to evaporate, and results in a loss of approximately 35% of S1. Rock–Eval crucible waiting process causes C14− hydrocarbons to evaporate, and results in an additional 25% loss of S1. To compensate for the sample crush induced S1 loss, an exponential distribution model was proposed based on the C8+ hydrocarbons in the TD–GC S1 fingerprints. Sample maturity, pristine light hydrocarbon (C14−) proportions, organic matter richness, and oil-bearing pore size primarily control the hydrocarbon loss of old shale samples. The higher the proportion of C14− and the lower the abundance of organic matter, the higher the amount of hydrocarbon loss. Finally, S1 restoration coefficient charts for large rock pieces and powdered samples with Ro ranging from 1.00% to 1.42% are provided. It highlights that previous studies have severely underestimated the in situ S1 when using the Rock–Eval method. This research has great implication for estimating in situ hydrocarbon potential using conventional coring samples.

State of health estimation based on inconsistent evolution for lithium-ion battery module

Estimating state of health for battery module is one of the most significant and challenging techniques to promote the commercialization of electric vehicles. Based on the relationship changes of branch current and its estimation error during aging, a state of health estimation general framework is presented for battery module. Firstly, the parallel battery module aging experiment is designed. In addition, the consistency changes of branches were analyzed. A neural network model utilizing dual back-propagation for estimating branch current errors was developed by employing the experimental data of battery module. Through estimation error of branch current under five working conditions, two aging characteristics are extracted, one is the slope of compensation value and current, the other is the slope of compensation value and current change rate. These features are fed into gaussian process regression training to obtain a state of health estimation model for the battery module. Furthermore, the model is validated with new european driving cycle working condition. Finally, a dual bidirectional long short-term memory neural network is utilized to illustrate the versatility of the presented universal framework, which can effectively estimate state of health of battery module with the maximum relative error of 2.1226 %.