Sample Volume Research Articles

Self-calibrating colorimetric sensor assisted deep learning strategy for efficient and precise Fe(II) detection

Colorimetry is to determine the component content usually comparing or measuring the “RGB” values, which has the advantages of quick response and visual comparison. However, the widely reported “RGB” models are limited by requiring professional operation such as accurate sampling, insufficient information, cumbersome calculation, etc., which has significantly restricted the promotional application. Inspired by the PAA-PVA gel with excellent absorbing-swelling ability and superior response ability, indefinite volume addition has a significant difference in the swelling phenomenon of PAA-PVA hydrogel, the extent of this enlargement is directly related to the amount of testing sample absorbed, which can be applied to reflect testing sample volume added. In addition, benefited from a comprehensive and precise parameter network, the deep learning (DL) algorithm solves the defects such as ambient light effect and manual extract RGB values of the colorimetric sensing analysis strategy. Considering Fe(II) is an essential element for life science and environmental monitoring, we have developed a self-calibrating colorimetric sensor assisted deep learning strategy for the Fe(II) detection with indefinite volume. It can directly complete the analysis of Fe(II) concentration via captured images, without going through a complicated process similar to the RGB model. Specifically, we integrated the advantages of colorimetric sensing strategy, absorbing-swelling hydrogel, and DL algorithm to develop a phenanthroline (PHEN) indicator doped PAA-PVA colorimetric sensor (PHEN-PAA-PVA). Then, 2,500 colorimetric response images were collected as the training dataset and assessed 2 DL algorithms and 7 machine learning (ML) algorithms. The convolutional neural network (CNN) model exhibited the most efficiency to quantify 1 × 10−5–9 × 10−4 mol/L Fe(II), with a limit of detection (LOD) of 3.3 × 10−6 mol/L. It provides a promising and blooming in-situ detection approach for Fe(II) analysis, contributes to health management and environment monitoring.

Facile synthesis of magnetic layered double hydroxide/metal–organic framework MIL-100(Fe) for simultaneous extraction and enantiomeric determination of three chiral triazole fungicides in water and juice samples

For the first time, magnetic layered double hydroxide/metal–organic framework (Fe3O4@CuZnAl-LDH@MIL-100(Fe)) was successfully fabricated and applied for enrichment of triazole fungicides from water and juice samples prior to chiral HPLC-UV analysis. Several key parameters influencing the extraction efficiency including extraction time, desorption time, sample solution pH, the ionic strength of sample solution, adsorbent amount, desorption volume, desorption solvent and sample volume were investigated by Plackett-Burman design and Box-Behnken design. Under the optimum conditions, the limit of detections (LODs) and limit of quantifications (LOQs) were in the ranges of 0.35 to 1.20 μg L−1 and from 1.00 to 3.80 μg L−1, respectively. The average spiked recoveries and enrichment factors ranged from 86.28-98.22 % and 21.6–23.8, respectively. The linearity was in the range of (5–1000 μg L−1) with satisfactory correlation coefficients (R2) values (0.9987–0.9999) and a good precision (RSDs ≤ 5.74 %). Moreover, the computational simulation was first employed to analyze adsorption properties of MIL-100(Fe) against triazole fungicides. This work provides a promising method for trace chiral pesticide analysis in aqueous samples.

Simultaneous prediction of petrophysical properties and formation layered thickness from acoustic logging data using a modular cascading residual neural network (MCARNN) with physical constraints

Predicting petrophysical properties from logging data using deep neural networks (DNNs) improves the efficiency of subsurface exploration. Traditional methods, however, heavily rely on data pre-processing. Therefore, a novel Modular Cascading Residual Neural Network (MCARNN) is proposed to simultaneously retrieve layered thickness and petrophysical properties of porous media directly from raw acoustic logging data without pre-processing. The MCARNN mainly comprises two cascading modules: the first is tasked with retrieving layered thickness, while the second one further reconstructs petrophysical properties based on the thickness information. To more accurately simulate the uncertainties of the real world, we incorporate some known geophysical knowledge, including the distribution range of actual petrophysical parameters, physical constraints among porous medium parameters, configurations of logging instruments, and stratified geological models. During this process, all Biot's porous parameters are independently randomized to cover a wide range of geological rock types. Furthermore, to enhance MCARNN's generalization ability under different random noise distributions, we independently generate the training and testing datasets using distinct numerical algorithms, thus preventing the “inverse crime” phenomenon. Additionally, varying levels of Gaussian white noises are added to the training dataset, and the transmitter-receiver configuration of the logging instrument is varied to enhance the training dataset. Two numerical experiments are implemented to validate the reliability and superiority of the MCARNN. It is shown that the proposed MCARNN can not only accurately predict porous petrophysical parameters when the background layer configurations are known but also be able to simultaneously reconstruct layered thickness and petrophysical parameters with low model misfit. Notably, MCARNN successfully predicts the porous velocity dispersion curves within a broad frequency band based on limited frequency points—a task typically requiring auxiliary equations in traditional inversion methods, demonstrating the advanced predictive capability of the proposed MCARNN. Through this research, we not only address the deficiencies in existing real-world logging datasets in terms of sample volume and label reliability but also effectively integrate rock physics models with data-driven neural networks, providing a novel and effective pathway for reservoir parameter prediction in the field of geophysical logging.

Perspectives of FTIR as Promising Tool for Pathogen Diagnosis, Sanitary and Welfare Monitoring in Animal Experimentation Models: A Review Based on Pertinent Literature.

Currently, there is a wide application in the literature of the use of the Fourier Transform Infrared Spectroscopy (FTIR) technique. This basic tool has also proven to be efficient for detecting molecules associated with hosts and pathogens in infections, as well as other molecules present in humans and animals' biological samples. However, there is a crisis in science data reproducibility. This crisis can also be observed in data from experimental animal models (EAMs). When it comes to rodents, a major challenge is to carry out sanitary monitoring, which is currently expensive and requires a large volume of biological samples, generating ethical, legal, and psychological conflicts for professionals and researchers. We carried out a survey of data from the relevant literature on the use of this technique in different diagnostic protocols and combined the data with the aim of presenting the technique as a promising tool for use in EAM. Since FTIR can detect molecules associated with different diseases and has advantages such as the low volume of samples required, low cost, sustainability, and provides diagnostic tests with high specificity and sensitivity, we believe that the technique is highly promising for the sanitary and stress and the detection of molecules of interest of infectious or non-infectious origin.

Development and validation of an ultra-performance liquid chromatography-tandem mass spectrometry method for the quantification of the antimalarial drug pyronaridine in human whole blood

Malaria remains a major health concern, aggravated by emerging resistance of the parasite to existing treatments. The World Health Organization recently endorsed the use of artesunate-pyronaridine to treat uncomplicated malaria. However, there is a lack of clinical pharmacokinetic (PK) data of pyronaridine, particularly in special populations such as children and pregnant women. Existing methods for the quantification of pyronaridine in biological matrices to support PK studies exhibit several drawbacks. These include limited sensitivity, a large sample volume required, and extensive analysis time. To overcome these limitations, an ultra-performance reversed-phase liquid chromatography tandem-mass spectrometry method to determine pyronaridine was developed and validated according to international guidelines. The method enabled fast and accurate quantification of pyronaridine in whole blood across a clinically relevant concentration range of 0.500–500 ng/mL (r2 ≥ 0.9963), with a required sample volume of 50 µL. Pyronaridine was extracted from whole blood using liquid-liquid extraction, effectively eliminating the matrix effect and preventing ion enhancement or suppression. The method achieved a satisfactory reproducible sample preparation recovery of 77%, accuracy (as bias) and precision were within ±8.2% and ≤5.3%, respectively. Stability experiments demonstrated that pyronaridine was stable for up to 315 days when stored at −70°C. Adjustments to the chromatographic system substantially reduced carry-over and improved sensitivity compared to prior methods. The method was successfully applied to quantify pyronaridine in whole blood samples from a selection of pregnant malaria patients participating in the PYRAPREG clinical trial (PACTR202011812241529) in the Democratic Republic of the Congo, demonstrating its suitability to support future PK studies. Furthermore, the enhanced sensitivity allows for the determination of pyronaridine up to 42 days post-treatment initiation, enabling assessment of the terminal elimination half-life.

Rapid preconcentration and determination of Co (II) ions in aqueous medium using ultrasound assisted cloud point extraction method

A flame atomic absorption spectrophotometric technique was studied for the preconcentration and determination of of Co2+ ions in trace amounts after ultrasound enhanced enrichment of its 1-(2-pyridylazo)-2-naphthol (PAN) complexes by cloud point extraction. The Co2+ ions were firstly complexed with PAN molecules at pH 4 and the complex transferred to a surfactant (Tergitol NP-7) rich phase with a very small volume under ultrasound waves. The surfactant rich phase was separated and dissolved by 1 mL, 1.0 M HNO3 in ethanol prior to determination of Co2+ concentration by flame atomic absorption spectrophotometry. The optimization steps of ultrasound interaction time, solution pH and surfactant volumes were achieved by response surface methodology (RSM) which is a combination of statistical approaches. Sample volume, PAN concentration and and possible interfering ions were optimized conventionally. The Co2+ ions were extracted only in 150 s at pH 4 quantitatively under optimum conditions (˃95%). The accuracy and validity of developed UA-CPE was granted by employing a certified reference material wastewater UME CRM 1204. The technique was applied to wastewater and natural water with satisfactory results.

Enhancing drug development and clinical studies with patient-centric sampling using microsampling techniques: Opportunities, challenges, and insights into liquid chromatography-mass spectrometrystrategies.

Microsampling has revolutionized pharmaceutical drug development and clinical research by reducing sample volume requirements, allowing sample collection at home or nontraditional sites, minimizing animal and patient burden, and enabling more flexible study designs. This perspective paper discusses the transformative impact of microsampling and patient-centric sampling (PCS) techniques, emphasizing their advantages in drug development and clinical trials. We highlight the integration of liquid chromatography-mass spectrometry (LC-MS) strategies for analyzing PCS samples, focusing on our research experience and a review of current literatures. The paper reviews commercially available PCS devices, their regulatory status, and their application in clinical trials, underscoring the benefits of PCS in expanding patient enrollment diversity and improving study designs. We also address the operational challenges of implementing PCS, including the need for bridging studies to ensure data comparability between traditional and microsampling methods, and the analytical challenges posed by PCS samples. The paper proposes future directions for PCS, including the development of global regulatory standards, technological advancements to enhance user experience, the increased concern of sustainability and patient data privacy, and the integration of PCS with other technologies for improved performance in drug development and clinical studies. By advancing microsampling and PCS techniques, we aim to foster patient-centric approaches in pharmaceutical sciences, ultimately enhancing patient care and treatment efficacy.

Determination of phenytoin at trace levels in domestic wastewater and synthetic urine samples by gas chromatography-mass spectrometry after its preconcentration by simple liquid-phase microextraction.

This work presents a sensitive and accurate analytical method for the determination of phenytoin at trace levels in domestic wastewater and synthetic urine samples by gas chromatography-mass spectrometry (GC-MS) after the metal sieve-linked double syringe liquid-phase microextraction (MSLDS-LPME) method. A metal sieve was produced in our laboratory in order to disperse water-immiscible extraction solvents into aqueous media. Univariate optimization studies for the selection of proper extraction solvent, extraction solvent volume, mixing cycle, and initial sample volume were carried out. Under the optimum MSLDS-LPME conditions, mass-based dynamic range, limit of quantitation (LOQ), limit of detection (LOD), and percent relative standard deviation (%RSD) for the lowest concentration in calibration plot were figured out to be 100.5-10964.2 μg kg-1, 150.6 μg kg-1, 45.2 μg kg-1, and 9.4%, respectively. Detection power was improved as 187.7-folds by the developed MSLDS-LPME-GC-MS system while enhancement in calibration sensitivity was recorded as 188.0-folds. In the final step of this study, the accuracy and applicability of the proposed system were tested by matrix matching calibration strategy. Percent recovery results for domestic wastewater and synthetic urine samples were calculated as 95.6-110.3% and 91.7-106.6%, respectively. These results proved the accuracy and applicability of the proposed preconcentration method, and the obtained analytical results showed the efficiency of the lab-made metal sieve apparatus.

Adapting Fabric Phase Sorptive Extraction as an Innovative Multitool for Sample Transfer and Extraction in Pharmacokinetic Analysis Followed by LC-MS Determination of Levofloxacin in Plasma Samples.

Fabric phase sorptive extraction (FPSE) is a simple microextraction technique that allows analytes to be rescued from matrix components while using a small volume of samples to analyze complex biological systems. This study used FPSE as a microextraction tool and a sample storage and transfer device. Levofloxacin as a model molecule was applied intravenously (IV) to New Zealand male rabbits. The samples were simultaneously extracted by using FPSE and protein precipitation methods. The final solutions were analyzed using LC-MS equipped with an ACE C18 LC Column (150 mm × 4.6 mm, 5 μm) at 25 °C employed in isocratic elution mode using solution A (0.1% formic acid in water)/solution B (0.1% formic acid in acetonitrile) (80:20, v/v). The total analysis time was less than 15 min. The developed method was validated using the ICH M10 bioanalytical method validation and study sample analysis guidelines. The results obtained using FPSE were statistically identical to those obtained using protein precipitation. The plasma samples applied onto FPSE (10 μL onto 1.0 cm × 1.0 cm Biofluid Sampler) were stored in three different temperatures [refrigerator (2-8 °C), at ambient temperature (20 ± 5 °C), and in the stability cabinet (40 °C, 75% humidity)] and three different storage conditions (Eppendorf tubes, plastic containers, and straw paper envelopes). Levofloxacin in plasma samples adsorbed by FPSE biofluid sampler remained stable at 2-8 °C in Eppendorf tubes for at least 1 week. This study showed that FPSE could be used as a sample storage and transfer device for pharmacokinetic applications that need to work with small sample volumes and discard aggressive cold chains to store and transfer the plasma samples.

Lab on a bead with oscillatory centrifugal microfluidics for fast and complete mixing enables fast and accurate biomedical assays

Rapid mixing and precise timing are key for accurate biomedical assay measurement, particularly when the result is determined as the rate of a reaction: for example rapid immunoassay in which the amount of captured target is kinetically determined; determination of the concentration of an enzyme or enzyme substrate; or as the final stage in any procedure that involves a capture reagent when an enzyme reaction is used as the indicator. Rapid mixing and precise timing are however difficult to achieve in point-of-care devices designed for small sample volumes and fast time to result. By using centrifugal microfluidics and transposing the reaction surface from a chamber to a single mm-scale bead we demonstrate an elegant and easily manufacturable solution. Reagents (which may be, for example, an enzyme, enzyme substrate, antibody or antigen) are immobilised on the surface of a single small bead (typically 1–2 mm in diameter) contained in a cylindrical reaction chamber subjected to periodically changing rotational accelerations which promote both mixing and uniform mass-transfer to the bead surface. The gradient of Euler force across the chamber resulting from rotational acceleration of the disc, dΩdisc/dt, drives circulation of fluid in the chamber. Oscillation of Euler force by oscillation of rotational acceleration with period, T, less than that of the hydrodynamic relaxation time of the fluid, folds the fluid streamlines. Movement of the bead in response to the fluid and the changing rotational acceleration provides a dynamically changing chamber shape, further folding and expanding the fluid. Bead rotation and translation driven by fluid flow and disc motion give uniformity of reaction over the surface. Critical parameters for mixing and reaction uniformity are the ratio of chamber radius to bead radius, rchamber/rbead, and the product Trchamber(dΩdisc/dt), of oscillation period and Euler force gradient across the fluid. We illustrate application of the concept using the reaction of horse radish peroxidase (HRP) immobilised on the bead surface with its substrate tetramethylbenzidine (TMB) in solution. Acceleration from rest to break a hydrophobic valve provided precise timing for TMB contact with the bead. Solution uniformity from reaction on the surface of the bead in volumes 20–50 uL was obtained in times of 2.5 s or less. Accurate measurement of the amount of surface-bound HRP by model fitting to the measured kinetics of colour development at 10 s intervals is demonstrated.

AptaShield: A Universal Signal-Transduction System for Fast and High-Throughput Optical Molecular Biosensing.

Biosensing technologies are often described to provide facile, sensitive, and minimally to noninvasive detection of molecular analytes across diverse scientific, environmental, and clinical diagnostic disciplines. However, commercialization has been very limited mostly due to the difficulty of biosensor reconfiguration for different analyte(s) and limited high-throughput capabilities. The immobilization of different biomolecular probes (e.g., antibodies, peptides, and aptamers) requires the sensor surface chemistry to be tailored to provide optimal probe coupling, orientation, and passivation and prevent nonspecific interactions. To overcome these challenges, here we report the development of a solution-phase biosensor consisting of an engineered aptamer, the AptaShield, capable of universally binding to any antigen recognition site (Fab') of fluorescently labeled immunoglobulins (IgG) produced in rabbits. The resulting AptaShield biosensor relies on a low affinity dynamic equilibrium between the fluorescently tagged aptamer and IgG to generate a specific Förster resonance energy transfer (FRET) signal. As the analyte binds to the IgG, the AptaShield DNA aptamer-IgG complex dissociates, leading to an analyte concentration-dependent decrease of the FRET signal. The biosensor demonstrates high selectivity, specificity, and reproducibility for analyte quantification in different biological fluids (e.g., urine and blood serum) in a one-step and low sample volume (0.5-6.25 μL) format. The AptaShield provides a universal signal transduction mechanism as it can be coupled to different rabbit antibodies without the need for aptamer modification, therefore representing a robust high-throughput solution-phase technology suitable for point-of-care applications, overcoming the current limitations of gold standard enzyme-linked immunosorbent assays (ELISA) for molecular profiling.

Identification and evaluation of Escherichia coli strain ATCC 8739 as a surrogate for thermal inactivation of enterohemorrhagic Escherichia coli in fruit nectars: Impact of applied techniques on the decimal reduction time

The objective of this study was to identify a suitable surrogate for E. coli O157:H7 strain 19685/91 and O113:H21 strain TS18/08, by assessing their thermal resistance at temperatures of 60 °C, 65 °C, and 72 °C in strawberry nectar. The influence of the matrix and the research methodology on the decimal reduction time (D-value) was investigated. Thermal kinetics and safety assessment demonstrated that E. coli ATCC 8739 is a suitable surrogate. The study demonstrated that the presence of fruit particles in the nectar increased thermal resistance of the tested strains. Variations in D-values were observed depending on the research method employed, with D-values in glass capillaries were up to 6.6 times lower compared to larger sample volumes. Encapsulation of E. coli ATCC 8739 exhibited high efficiency of 90.25 ± 0.26% and maintained stable viable counts after 26 days of storage in strawberry nectar at 4 °C. There were no significant differences in thermal resistance between surrogates directly inoculated into strawberry nectar and those encapsulated in alginate beads. Additionally, the encapsulated strains did not migrate outside the beads. Therefore, encapsulated E. coli ATCC 8739 in alginate beads can be effectively utilized in industrial settings to validate thermal treatments as a reliable and safe method.

Deep learning-assisted self-volume-calibrating colorimetric sensor for chloride ion detection

Chloride ions (Cl−) are widely present in nature, and accurate measurement of Cl− is of great significance for health management and water quality monitoring. Based on the principle of argentometry, where Ag+ react with Cl− in silver measurement to produce insoluble AgCl, we developed a colorimetric sensor composed of AgNO3, 2′,7′-dichlorofluorescein (DCFS) and starch, which is defined as ADS sensor. Cl− react with Ag+ in the ADS sensor to form positively charged AgCl colloids, which can adsorb negatively charged DCFS dyes and cause a color change in DCFS, thus providing sensing information about Cl− concentrations. To eliminate the error caused by the unfixed sample volume, a novel self-volume-calibrating strategy based on the unique shape of the sample holder was proposed. We further utilized deep learning (DL) algorithms to analyze data from 3,900 colorimetric images, enabling rapid determination of 1 × 10−5 to 7 × 10−2 mol/L Cl− with unfixed sample volumes. The Class Activation Mapping (CAM) algorithm was also used to visualize the decision-making mechanism of Convolutional Neural Network (CNN), verifying that the colorimetric regions and volume change regions of the sensor is the primary decision-making information for CNN. Compared with traditional method, this approach has the advantages of low cost, wide detection range, simple operation and rapid response. We envision that this method for Cl− detection can be used as an alternative and promising tool for the detection of a wider variety of analytes.

Abstract P20: Unveiling the Influence of Tumor Microenvironment and Spatial Heterogeneity on Temozolomide Resistance in Glioblastoma using an Advanced Human in vitro Model of the Blood-brain Barrier and Glioblastoma

Abstract Glioblastoma (GBM) is the most common primary malignant brain cancer in adults, with a dismal prognosis of 15 months. This is despite decades of research and improvements in surgery and radiotherapy. Temozolomide (TMZ) is the only first-in-line chemotherapeutic; however, resistance is frequent and multifactorial. While many molecular and genetic factors have been linked to TMZ resistance, the role of the solid tumor morphology and the tumor microenvironment (TME), particularly the blood-brain barrier (BBB), is unknown. Complex 3D in vitro models are able to recapitulate aspects of clinical disease such as the tumor microenvironment, such that research into the role of the TME and how it affects tumor biology and therapy resistance can be studied more easily and accurately. We have developed a complex 3D in vitro model for GBM and its surrounding BBB, that recapitulates important clinical features such as a dense tumor core with tumor cells that invade along the perivascular space; and a perfusable BBB with a physiological permeability with morphology that is altered in the presence of a tumor spheroid. We demonstrate that TMZ sensitivity decreases with increasing cancer cell spatial organization, and that the BBB can contribute to TMZ resistance. Proteomic analysis of cultured microtissues using low volume sample workflows revealed proteins linked to aggressive tumors and TMZ resistance. Notably, proteomic analysis revealed a potential role for cell cycle proteins in TMZ resistance. Preliminary data with tumor spheroids formed by patient derived GBM progenitor cells revealed a similar trend of an increase in proteins associated with tumor aggressiveness upon co-culture with a BBB. The data demonstrate the utility of combining complex physiological in vitro models and next generation mass spectrometry for interrogating the tumour microenvironment, tumor biology and accurate in vitro therapy validation. Citation Format: Maxine SY Lam, Joey JY Aw, Damien Tan, Ragavi Vijayakumar, Hui Yi Grace Lim, Swathi Yada, Qing You Pang, Nick Barker, Carol Tang, Beng Ti Ang, Radoslaw M. Sobota, Andrea Pavesi. Unveiling the Influence of Tumor Microenvironment and Spatial Heterogeneity on Temozolomide Resistance in Glioblastoma using an Advanced Human in vitro Model of the Blood-brain Barrier and Glioblastoma [abstract]. In: Proceedings of Frontiers in Cancer Science; 2023 Nov 6-8; Singapore. Philadelphia (PA): AACR; Cancer Res 2024;84(8_Suppl):Abstract nr P20.

Analysis of Three Dimethyl Sulfides in Freshwater Lakes Using Headspace Solid-Phase Microextraction-Gas Chromatography with Flame Photometric Detection

Dimethyl sulfides are ubiquitous odorous substances in eutrophic freshwater bodies. In this study, a simple headspace solid-phase microextraction-gas chromatography-flame photometric detection method was developed to detect three representative algal-derived dimethyl sulfides in freshwater lake water samples: dimethyl monosulfide (DMS), dimethyl disulfide (DMDS), and dimethyl trisulfide (DMTS). The effects of extraction fiber, temperature, pH, ionic strength, and sample volume were investigated orthogonally, and the optimized method was applied to analyze surface water samples from Lake Ulansuhai in Inner Mongolia, China. Optimal extraction was obtained with a 50/30 µm DVB/CAR/PDMS extraction fiber, 20% ion concentration, 87 min extraction time, and 50 °C extraction temperature. The correlation coefficients of the standardized working curves for DMS, DMDS, and DMTS were 0.9967, 0.9907, and 0.9994, respectively, indicating good linear relationships. Limits of detection were in the nanogram range, and the recoveries of the spiked standards for DMS, DMDS, and DMTS were 97.22~99.07%, 93.39~99.34%, and 91.17~99.25%, with relative standard deviations of 5.18~5.94%, 3.08~6.25%, and 2.56~5.47%, respectively. This method is stable and reliable, and can be used for the determination of volatile sulfides in freshwater lake water.

A 3-step method for preparing cryopreserved samples of apheresis products for post-thaw analysis yields a higher percentage of viable cells.

Standard flow cytometry protocols for CD34+ cell enumeration designed for fresh samples are not appropriate for cryopreserved products. Special protocols have been developed to remove the cryoprotectant by quickly washing a freshly thawed sample. Exposing cells to a large volume of hypotonic solution and subsequent washing process was hypothesized to cause lab-induced cell death. Moreover, standard gating strategies must be altered to avoid reporting falsely high viabilities. We developed a novel method whereby thawed samples were diluted step-wise to 1:2 by 3 additions of 1/3 sample volume using 1% Human Albumin in Dextran 40 (10% Low Molecular Weight Dextran in 0.9% NaCl) separated by 5 min between each addition. An additional 1:10 dilution was required to obtain a desired cell concentration for flow cytometry testing resulting in a 1:20 dilution. Twenty samples were tested simultaneously in a method comparison; the new method demonstrated significant increases in mean cell viabilities for white blood cells, hematopoietic progenitor cells, and T cells as well as reduced standard deviations for each parameter. Slow, step-wise dilutions of freshly thawed samples of cryopreserved apheresis products to 1:20 yielded higher and more precise viability measurements compared to quickly washing samples to remove DMSO.

Covalent organic framework aerogel for high-performance solid-phase extraction of tetracycline antibiotics: Experiment and simulated calculation on adsorption behavior

Three-dimensional sponge-architecture covalent organic frameworks (COFs)-aerogel was successfully designed and synthesized via a freeze-drying template approach, and utilized as an efficient sorbent in solid-phase extraction (SPE). A method for selective enrichment of pharmaceutical contaminants including tetracycline, chlortetracycline, methacycline and oxytetracycline in the environment and food samples was proposed by combining with high performance liquid chromatography (HPLC). To understand the adsorption mechanism, selectivity test and molecular dynamics (MD) simulated calculation were both carried out. The experimental and in-silico results demonstrated that the COFs-aerogel possessed high selectivity for contaminants with H bond acceptors/donors and good efficiency with maximum adsorption capacity up to 294.1 mg/g. The SPE-based HPLC method worked well in the range of 8–1000 ng/mL, with the need of little dose of adsorbent and sample volume while no need of spectrometer, outgoing the reported adsorbents. Under the optimized conditions, the intra-day and inter-day relative standard deviations (RSD) of repeatability were within 2.78–6.29 % and 2.44–8.42 % (n = 5). The results meet the current detection requirement for practical applications, and could be extended for further design of promising adsorbents.

New Insights into the Hygroscopic Character of Ionic Liquids: Study of Fourteen Representatives of Five Cation and Four Anion Families.

Over the past three decades, the synthesis of new ionic liquids (ILs) and the expansion of their use in newer applications have grown exponentially. From the beginning of this vertiginous period, it was known that many of them were hygroscopic, which in some cases limited their use or altered the value of their measured physical properties with all the problems that this entails. In an earlier article, we addressed the hygroscopic grade achieved by the ILs 1-ethyl-3-methylimidazolium chloride, 1-ethyl-3-methylimidazolium bromide, 1-ethyl-3-methylimidazolium methyl sulfate, 1-ethyl-3-methylimidazolium ethyl sulfate, 1-ethyl-3-methylpyridinium ethyl sulfate, 1-ethyl-3-methylimidazolium tosylate, 1-ethyl-3-methylimidazolium tetrafluoroborate, 1-butyl-3-methylimidazolium tetrafluoroborate, 1-dodecyl-3-methylimidazolium tetrafluoroborate, 1-butyl-3-methylpyridinium tetrafluoroborate, 1-butyl-1-methylpiperidinium bis(trifluoromethyl sulfonyl)imide, 1-methyl-1-propylpyrrolidinium bis(trifluoromethyl sulfonyl)imide, 1-butyl-1-methylpyrrolidinium bis(trifluoromethyl sulfonyl)imide, and methyl trioctyl ammonium bis(trifluoromethyl sulfonyl)imide. The objective was to determine the influence of the chemical nature of the compounds, exposed surface area, sample volume, agitation, and temperature. For this purpose, we exposed the samples to abrupt increases in relative humidity from 15 to 100% for days in an atmosphere chamber and then proceeded with the reverse process in a gentle manner. The results show that the sorption of water from the atmosphere depends on the nature of the IL, especially the anion, with the chloride anion being of particular importance (chloride ≫ alkyl sulfates~bromide > tosylate ≫ tetrafluoroborate). It has also been proven for the EMIM-ES and EMIM-BF4 samples that the mechanism of moisture capture is both absorption and adsorption, and that the smaller the exposed surface area, the higher the ratio of the mass of water per unit area.

Recent Advances in Dielectric Properties-Based Soil Water Content Measurements

Dielectric properties are crucial in understanding the behavior of water within soil, particularly the soil water content (SWC), as they measure a material’s ability to store an electric charge and are influenced by water and other minerals in the soil. However, a comprehensive review paper is needed that synthesizes the latest developments in this field, identifies the key challenges and limitations, and outlines future research directions. In addition, various factors, such as soil salinity, temperature, texture, probing space, installation gap, density, clay content, sampling volume, and environmental factors, influence the measurement of the dielectric permittivity of the soil. Therefore, this review aims to address the research gap by critically analyzing the current state-of-the-art dielectric properties-based methods for SWC measurements. The motivation for this review is the increasing importance of precise SWC data for various applications such as agriculture, environmental monitoring, and hydrological studies. We examine time domain reflectometry (TDR), frequency domain reflectometry (FDR), ground-penetrating radar (GPR), remote sensing (RS), and capacitance, which are accurate and cost-effective, enabling real-time water resource management and soil health understanding through measuring the travel time of electromagnetic waves in soil and the reflection coefficient of these waves. SWC can be estimated using various approaches, such as TDR, FDR, GPR, and microwave-based techniques. These methods are made possible by increasing the dielectric permittivity and loss factor with SWC. The available dielectric properties are further synthesized on the basis of mathematical models relating apparent permittivity to water content, providing an updated understanding of their development, applications, and monitoring. It also analyzes recent mathematical calibration models, applications, algorithms, challenges, and trends in dielectric permittivity methods for estimating SWC. By consolidating recent advances and highlighting the remaining challenges, this review article aims to guide researchers and practitioners toward more effective strategies for SWC measurements.

Effect of heating-assisted ultrasonic surface rolling on the microstructure evolution and wear behavior of martensitic steel

In this study, a plastic deformation layer and a nano-gradient structure were prepared on the surface of high-strength martensitic steel using the Heating-Assisted Ultrasonic Surface Rolling (HUSR) technique. The microstructure, texture evolution, and wear performance of the plastic deformation layer were characterized and analyzed using techniques such as Electron Backscatter Diffraction (EBSD) and Transmission Electron Microscopy (TEM). The influence of HUSR treatment on the friction and wear behavior of martensitic steel was discussed. The results indicate significant changes in the texture components, dislocation structures, and grain distribution in the plastic deformation layer prepared by HUSR. The predominant textures in the plastic deformation layer are Rotated Cube {001}<110>, Cube {001}<100>, F {111}<112>, and E {111}<110>. HUSR treatment induces the formation of abundant deformation twins and stacking faults (SF) on the surface of sample. This ultimately results in a 28.3 % increase in the surface hardness of the HUSR sample and the introduction of residual compressive stress of −746.2 MPa. The friction coefficient and wear volume of the HUSR sample are significantly reduced. After HUSR treatment, the martensitic steel exhibits excellent wear resistance.