Solvent Mixtures Research Articles

Solubility study, model correlation and thermodynamics of 3-acetyl-4-hydroxy-2H-chromen-2-one and its chlorinated derivatives in binary solvent mixtures at temperatures from 293.15 to 313.15 K

The solubility of 3-acetyl-4-hydroxy-2H-chromen-2-one (GK-1), 3-acetyl-6-chloro-4-hydroxy-2H-chromen-2-one (GK-2), and 3-acetyl-7-chloro-4-hydroxy-2H-chromen-2-one (GK-3) in binary solvent mixtures of methanol and ethanol was investigated using the gravimetric method over a temperature range of 293.15 K to 313.15 K under atmospheric pressure. Experimental results showed that the mole fraction solubility of GK-1, GK-2, and GK-3 increased with rising temperature and higher co-solvent proportions (0.10 to 0.90 mol fraction). Theoretical mole fraction solubility predictions were made using the Apelblat, Van’t Hoff, Yaws, CNIBS/R-K, and modified Jouyban-Acree models, all of which showed good agreement with the experimental data. Additionally, apparent thermodynamic modeling of GK-1, GK-2, and GK-3 was conducted using the Van’t Hoff equation. The solubility and thermodynamic data obtained are valuable for the processes of production, isolation, separation, and crystallization of these compounds.

Developing Sustainable Wood Preservatives: The Antifungal Efficiency of Afzelia quanzensis Welv. and Androstachys johnsonii Prain Sawdust Extracts from Mozambique

This study aimed to both develop and assess the antifungal efficacy of extractives derived from different sets of sawdust originating from two hardwood species, namely chanfuta (Afzelia quanzensis Welv.) and mecrusse (Androstachys johnsonnii Prain). These hardwood species possess inherent characteristics of high natural durability. The primary objective was to use these extractives to impregnate perishable wood species, enhancing their durability and augmenting their commercial value. Collected wood sawdust was initially sieved to remove residues and unwanted materials and conditioned until 12% moisture content. Subsequently, the sawdust was Soxhlet-extracted using a mixture of organic solvents, including acetone, ethanol, and toluene. After evaporating the solvents, the resulting extractives were used to prepare a preservative solution with ethanol and acetone. The extractive solutions from each wood species were mixed with malt extract agar and then diluted to various concentrations: 0.125 mg/mL, 0.25 mg/mL, 0.5 mg/mL, 1.25 mg/mL, 2.0 mg/mL, and 2.5 mg/mL. For each concentration, fungal plugs from the periphery of actively growing cultures were moved to the centre of Petri dishes and placed in controlled laboratory conditions for incubation. The antifungal efficacy was assessed against specific wood-decaying fungi, including brown rot fungi (Coniophora puteana, Postia placenta, Lentinus lapideus) and white rot (Trametes versicolor). The evaluation involved daily monitoring of the linear expansion along two perpendicular radii for each fungus expressed as a percentage of the empty Petri dish area. The results indicated that the chanfuta extractives inhibited the growth of brown rot fungi at a concentration of 0.25 mg/mL and white rot fungi at 2.0 mg/mL. Similarly, the mecrusse extractives inhibit brown rot at 0.5 mg/mL and white rot at 2.0 mg/mL. The fatty acids Oleic (C18:1) present in the chanfuta extractives solution and linoleic (C18:2) in mecrusse extractives contributed to restraining the fungal growth. These results suggest that sawdust extractives from both wood species exhibit promising potential for creating environmentally friendly wood preservatives, which, with effective treatments, could extend the lifespan of perishable wood species

Green low-melting mixture solvents/ionic liquids-based carbon materials and lithium-ion batteries recycling leachate unexpectedly cause water pollution from dissolved organic matter

Low-melting mixture solvents (LoMMSs) and ionic liquids (ILs) are regarded as green solvents for the recovery of lithium-ion batteries (LIBs) cathode with high sustainability. Unexpectedly, we find for the first time that the release of LoMMSs- or ILs-based carbon materials and LIBs recycling leachate into water can lead to significant pollution from dissolved organic matter (DOM). Moreover, COD, NH4–N and total P concentration in river from Jingjinji Region is relatively high due to the high concentration of DOM. This work would provide us a hint that the application of so-called green LoMMSs and ILs in materials preparation and LIBs recovery should be treated with high caution in order to minimize DOM pollution for the rivers in Jingjinji Region.

Beating the Odds with Binuclear N‐Heterocyclic Carbene Metallacycles: A Practical and Efficient Full‐Color Tunable Fluorescence System

AbstractAchieving full‐color emission with just two emitters presents a significant challenge. Two N‐heterocyclic carbene metallacycles (NHC‐M; M ═ Ag, Au) featuring a tetraphenylethene core, combining covalent and coordination bonds are synthesized to restrict rotation within the NHC‐M‐BC (BC = bicyclic) metallacycles and greatly enhanced their quantum yields. The enhancement is accomplished by adjusting the CH3CN/H2O solvent mixture, allowing emission tuning from blue to green for NHC‐Ag‐BC. Further diversification of the emission spectrum, including access to high‐quality white light (CIE coordinates 0.33, 0.34), is facilitated through the addition of sulforhodamine B via fluorescence resonance energy transfer (FRET). The compatibility of NHC‐Ag‐BC with agarose gel extends its applicability to UV‐LEDs chromic coatings, as well as information encryption and anti‐counterfeiting materials. The results underscore the viability of dual‐fluorophore systems for achieving full‐color emission and highlight the potential for developing versatile, multi‐colored functional materials.

A novel bio-aerogel based on agroforestry waste chestnut shell for enhanced oil-water separation performance

Bio-based aerogels have attracted much attention due to their biodegradability and excellent oil-water separation properties. However, the preparation of inexpensive green aerogels with high separation efficiency is still a great challenge. In this paper, low-density, high-adsorption capacity and superhydrophobic chestnut shell-based bio-aerogels were prepared by chemical cross-linking and chemical vapor deposition using agricultural and forestry waste chestnut shells as the precursor of aerogels to achieve high efficiency of oil-water separation and to achieve the goal of “treating waste with waste”. The covalent cross-linking of chestnut shell cellulose and cross-linking agent to form silicone-containing functional groups improved the pore structure, hydrophobicity and mechanical properties of chestnut shell cellulose, and under the action of capillary force, the oil was retained in the pores of the bio-aerogels, which achieved the selective adsorption of oil and organic solvents in the oil-water mixture, with a separation efficiency of more than 98%. After 10 cycles, the bio-aerogel still has good reusability. This eco-friendly and low-cost aerogel provides a practical method for resource conversion and recycling, as well as a green and innovative way for the treatment of oily wastewater.

Use of a rugged mid-infrared spectrometer for in situ process analysis of liquids

The widespread application of mid-infrared (MIR) spectroscopy for process monitoring is currently limited by the poor transmission of MIR light through fibre optics. In this work, the performance of a novel and robust MIR spectrometer has been evaluated for practical deployment in a pilot plant or production environment. The spectrometer utilises a Sagnac interferometer design containing no moving parts and is directly attached to an attenuated total reflectance probe, eliminating the need for fibre optics. The quantitative performance of the spectrometer for the in situ analysis of ternary solvent mixtures was assessed. The predictions obtained by partial least squares were accurate (root mean square error of prediction of < 1% w/w) and comparable to those of a benchmark Michelson-based spectrometer with a fibre-coupled probe, which is more amenable to process development in a laboratory or pilot plant. Calibration transfer between the two spectrometers was performed using the spectral space transformation method to mimic the scenario of the scale-up of a process from the laboratory to pilot scale or from a pilot plant to production scale, where the two different MIR instruments might be deployed. The ability to perform in situ reaction monitoring with the robust Sagnac-based spectrometer was then demonstrated. Spectra acquired during an esterification reaction were resolved using multivariate curve resolution, to produce concentration profiles of each component. These results demonstrate the suitability of this rugged spectrometer for quantitative in situ monitoring of liquid processes, opening up new opportunities for process monitoring in the MIR region.

Multi-focal lipid membrane characterization by combination of DAS-deconvolution and anisotropy: Novel insight of fluorescence analysis

Three analogue solvatochromic probes, Laurdan, Prodan, and Acdan, are extensively used in the study of biological sciences. Their locations in lipid membranes vary greatly in depth, and their fluorescence responds to their surrounding environment based on their corresponding locations in the membrane. Utilizing the fluorescence lifetimes (τ) and emission peaks (λ) acquired from time-resolved emission spectrum, one can effectively determine the local lipid environment using the analytical approach refer to as τ and λ plots. Herein, τ and λ plot was created using the aforementioned probes to expand the analytical field according to their location. Furthermore, the solvent modeling method in τ and λ plot was upgraded to artificially emulate the complex environment in lipid membranes by utilizing liquid paraffin and glycerol to assess the contribution of viscosity to each fluorescence distribution. According to the results from a series of solvent mixtures, the effect of solvent viscosity on lifetime values was confirmed in the short lifetime region (∼ 3 ns). However, it was impossible to emulate the long lifetime values (4 ns ∼) observed in lipid membranes containing 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) in the range of viscosity applied in this study. From the insight of the limiting anisotropy (r∞), the τ and λ plot was divided into a solvent-like region with isotropic environment (r∞ < 0.15) and a highly ordered region enough to define as anisotropic environment (0.15 <r∞) at τ: 4 ns. Also, the membrane-specific distribution was illustrated as 4 ns <τ and λ < 460 nm from this work. Updated analytical model was created to visualize multiple fluorescence components of each probe in 6 types of lipid bilayers, confirming the different distributions between these probes. Our results well-illustrated the multiplicity of lipid environments modeled with solvent and ordered environments in each lipid bilayer systems.

Preparation of amorphous Nd/Dy-based metal organic framework@MXene for solar driven selective photocatalytic and serving as sensor for fluorescence quenching detection, and biological activity

The development of a new Neodymium/Dysprosium metal–organic framework, referred to as Nd/Dy-BTC MOF, based on benzene-1,2,4-tricarboxylic acid, has been achieved through an in situ growth process on 2D transition metal carbides (MXene) surfaces. This synthesis was conducted via a solvothermal method utilizing a solvent mixture of water, ethanol, and dimethylformamide. The primary objective of this research is to investigate the framework’s efficacy as a photocatalyst for the degradation of anionic dye, as well as its potential for sensing certain explosives. The Nd/Dy-MOF@MXene has been characterized by various analysis techniques. The prepared Nd/Dy-MOF@MXene was utilized as catalyst in selective degradation of methyl orange dye. The study examined the influence of pH and catalyst concentration, revealing that the catalyst achieves peak efficiency of 93.55% when exposed to sunlight in an acidic medium. The reusability of the catalyst shows the highest efficient photocatalyst after four cycles of reusability. The detection of explosives, specifically 2,4,6-trinitrophenol, through photoluminescence techniques has been conducted, utilizing the Stern-Volmer equation to evaluate the quenching efficiency. The findings indicated remarkable efficiency and selectivity of Nd/Dy-MOF@MXene for 2,4,6-trinitrophenol, achieving a quenching efficiency of 91%. Furthermore, the reusability tests demonstrated that Nd/Dy-MOF@MXene exhibits outstanding recyclability, maintaining performance over five cycles. The antibacterial activity of Nd/Dy-MOF@MXene was investigated against Gram-positive and Gram-negative strains due to indication of medicine properties of Nd/Dy-MOF@MXene.

(−)-Epicatechin Solubility in Aqueous Mixtures of Eutectic Solvents and Their Constituents

(−)-Epicatechin Solubility in Aqueous Mixtures of Eutectic Solvents and Their Constituents

Mild and Scalable Conditions for the Solvothermal Synthesis of Imine‐Linked Covalent Organic Frameworks

AbstractA convenient method was developed that allows for the synthesis of highly crystalline and porous imine‐linked covalent organic frameworks (COFs) in hours. The use of an apolar solvent in combination with a precise amount of water and acetic acid was crucial to obtain materials of optimal quality. Fifteen different COFs could be produced under the same reaction conditions, using a green solvent mixture of n‐butanol, acetic acid and water at 70 °C for 16 hours with stirring. The crystallinity of the COFs produced in this manner is similar or better than that obtained by traditional solvothermal synthesis. The method could be easily scaled to synthesize over ten grams of COF in one batch. Optical microscopy, FTIR spectroscopy and in situ Raman spectroscopy gave insight in the role of the solvent on the aggregation of COF nanosheets and the resulting crystallinity, porosity and robustness of the material.

Towards the prediction of drug solubility in binary solvent mixtures at various temperatures using machine learning

Drug solubility is an important parameter in the drug development process, yet it is often tedious and challenging to measure, especially for expensive drugs or those available in small quantities. To alleviate these challenges, machine learning (ML) has been applied to predict drug solubility as an alternative approach. However, the majority of existing ML research has focused on the predictions of aqueous solubility and/or solubility at specific temperatures, which restricts the model applicability in pharmaceutical development. To bridge this gap, we compiled a dataset of 27,000 solubility datapoints, including solubility of small molecules measured in a range of binary solvent mixtures under various temperatures. Next, a panel of ML models were trained on this dataset with their hyperparameters tuned using Bayesian optimization. The resulting top-performing models, both gradient boosted decision trees (light gradient boosting machine and extreme gradient boosting), achieved mean absolute errors (MAE) of 0.33 for LogS (S in g/100 g) on the holdout set. These models were further validated through a prospective study, wherein the solubility of four drug molecules were predicted by the models and then validated with in-house solubility experiments. This prospective study demonstrated that the models accurately predicted the solubility of solutes in specific binary solvent mixtures under different temperatures, especially for drugs whose features closely align within the solutes in the dataset (MAE < 0.5 for LogS). To support future research and facilitate advancements in the field, we have made the dataset and code openly available.Scientific contributionOur research advances the state-of-the-art in predicting solubility for small molecules by leveraging ML and a uniquely comprehensive dataset. Unlike existing ML studies that predominantly focus on solubility in aqueous solvents at fixed temperatures, our work enables prediction of drug solubility in a variety of binary solvent mixtures over a broad temperature range, providing practical insights on the modeling of solubility for realistic pharmaceutical applications. These advancements along with the open access dataset and code support significant steps in the drug development process including new molecule discovery, drug analysis and formulation.Graphical

Hydration behavior of D-calcium pantothenate (vitamin B5) in the presence of sugar-based deep eutectic solvents at different temperatures: experimental and theoretical study

Considerable efforts have been devoted in recent years to enhancing the efficacy medicinal substance, leading to the discovery of innovative drug formulations and delivery techniques. The successful design of these processes necessitates a profound understanding at the molecular level of how these substances interact with biological membranes. Thorough thermodynamic investigations provide invaluable insights into these interactions and aid in selecting suitable compounds for pharmaceutical production. This study aims to determine the density and speed of sound for D-calcium pantothenate in mixtures of water and deep eutectic solvents (DESs), specifically choline chloride/sucrose, choline chloride/ glucose, and choline chloride/ fructose (with 2:1 molar ratio) over a temperature range of 288.15 K to 318.15 K under atmospheric pressure. In order to predict the behavior of molecules, COSMO model (the Conductor-Like Screening Model) offer complementary strengths in quantum chemistry. This approach allows for calculating solvation free energies, making it ideal for predicting properties like solubility, where understanding solvent-solute interactions is crucial. By correlating the measured parameters using standard relationships, important partial molar parameters such as apparent molar volumes and apparent molar isentropic compressibility are calculated. Additionally, apparent molar isobaric expansion, and Hepler’s constant are derived from the density and speed of sound data. The experimental apparent molar volumes, and apparent molar isentropic compressibility data is fitted to the Redlich-Meyer equation to obtain significant quantities such as standard partial molar volume, and partial molar isentropic compression. The comprehensive thermodynamic analysis of this studied system holds immense significance for advancements in the pharmaceutical industry.

A Preliminary Antidepressant Assessment of a Novel Piperoyl Amide (Y3) Isolated and Elucidated from Piper nigrum Drupes Extract, Justifying Interaction Over MAO-A enzyme: An in vivo, in vitro and Molecular Docking Approach

This research aims to confirm the preliminary antidepressant activity of a newly discovered piperoyl amide (Y3) obtained from the extract of Piper nigrum (P. nigrum) drupes, through the inhibition of MAO-A enzyme. Column chromatography was employed for isolation and purification of Novel piperoyl-alkyl amide (Y3) which was eluted in a solvent mixture of Chloroform-Methanol (97:3). Structure elucidation was performed by implying spectroscopic techniques. Invitro in-comparison MAO activity assessment was performed between Y3 and piperine further confirmed by Molecular docking via Auto Dock Tools 1.5.6, Vina, and PyMOL. Invivo antidepressant activity was evaluated by the Despair Test in albino mice. Novel piperoyl-alkyl amide (Y3) was isolated and purified by column chromatography and elucidated spectroscopically. The antidepressant activity of Y3 at 10 and 20 mg/kg doses shown a significant decrease in immobility-time (IT) in contrast to stressed-control group at 107.0±7.6 sec (P&lt;0.05) and 96.0±7.6 sec (P&lt;0.01), respectively. Y3 shown a decent MAO-A inhibitory activity but lower than piperine showing IC50=20.24 µM, Vmax=1.375±0.3 nM/min/mg, Km=1.379×10-16 µM with a stronger interaction and better affinity (-12.6 kcal/mol) towards the active-site of MAO-A. Y3 was isolated and elucidated as (12E,14E)-15-(benzo[d] [1,3] dioxol-5-yl)-N-ethylpentadeca-12,14-dienamide. It proved a good antidepressant at 10 and 20 mg/kg doses. Molecular docking over MAO-A and QSAR studies depicted a better affinity score of Y3 than Piperine. Keywords: Piperoyl amide, Structure elucidation, antidepressant activity, molecular modeling, Piperine

HPLC-MS/MS based method for the determination of 2-(3-hydroxy-5-phosphonooxymethyl-2-methyl-4-pyridyl)-1,3-thiazolidine-4-carboxylic acid in human plasma

The report presents first high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) based method for the determination of plasma 2-(3-hydroxy-5-phosphonooxymethyl-2-methyl-4-pyridyl)-1,3-thiazolidine-4-carboxylic acid (HPPTCA), an adduct of cysteine and active form of vitamin B6 pyridoxal 5′-phosphate. The assay employs 4-deoxypyridoxine (4-DPD) as an internal standard. Sample preparation procedure primarily involves acetonitrile (ACN) extraction of HPPTCA from plasma proteins, sample deproteinization by ultrafiltration, and dilution of ultrafiltrate with mobile phase prior to chromatographic analysis. The chromatographic separations of HPPTCA and 4-DPD are achieved within 6 min at 20 °C on X-Bridge Glycan BEH Amide (100 × 2.1 mm, 2.5 μm) column using gradient elution. The eluent consists of 0.1% formic acid in a mixture of solvent A (water and ACN (95:5, v: v)) and solvent B (water and ACN (5:95, v: v)) delivered at a flow rate of 0.3 mL/min. The assay linearity was observed within 0.25-10 µmol/L in plasma. The limit of quantification was found to be 0.25 µmol/L. The method was successfully applied to plasma samples delivered by apparently healthy donors showing that the HPLC-MS/MS assay is suitable for human plasma screening. The presence of HPPTCA was confirmed in eleven of fifteen study samples. The HPPTCA concentration ranged from 0.55 to 8.39 µmol/L.

Selective Chromogenic Chemosensors for Arsenite Anion: A Facile Approach to Analyzing Arsenite in Honey, Milk, and Water Samples.

In this study, two chemosensors, N5R1 and N5R2, based on 5-(4-nitrophenyl)-2-furaldehyde, with varying electron-withdrawing groups, were synthesized and effectively employed for the colorimetric selective detection of arsenite anions in a DMSO/H2O solvent mixture (8 : 2, v/v). Chemosensors N5R1 and N5R2 exhibited a distinct color change upon binding with arsenite, accompanied by a spectral shift toward the near-infrared region (Δλmax exceeding 200 nm). These chemosensors established stability between a pH range 6-12. Among them, N5R2 displayed the lowest detection limit of 17.63 ppb with a high binding constant of 2.6163×105 M-1 for arsenite. The binding mechanism involved initial hydrogen bonding between the NH binding site and the arsenite anion, followed by deprotonation and an intramolecular charge transfer (ICT) mechanism. The mechanism was confirmed through UV and 1H NMR titrations, cyclic voltammetric studies, and theoretical calculations. The interactions between the sensor and arsenite anions were further analyzed using global reactivity parameters (GRPs). Practical applications were demonstrated through the utilization of test strips and molecular logic gates. Real water samples, honey, and milk samples were successfully analyzed by both chemosensors for the sensing of arsenite.

Exploration of the Solubility Hyperspace of Selected Active Pharmaceutical Ingredients in Choline- and Betaine-Based Deep Eutectic Solvents: Machine Learning Modeling and Experimental Validation.

Deep eutectic solvents (DESs) are popular green media used for various industrial, pharmaceutical, and biomedical applications. However, the possible compositions of eutectic systems are so numerous that it is impossible to study all of them experimentally. To remedy this limitation, the solubility landscape of selected active pharmaceutical ingredients (APIs) in choline chloride- and betaine-based deep eutectic solvents was explored using theoretical models based on machine learning. The available solubility data for the selected APIs, comprising a total of 8014 data points, were collected for the available neat solvents, binary solvent mixtures, and DESs. This set was augmented with new measurements for the popular sulfa drugs in dry DESs. The descriptors used in the machine learning protocol were obtained from the σ-profiles of the considered molecules computed within the COSMO-RS framework. A combination of six sets of descriptors and 36 regressors were tested. Taking into account both accuracy and generalization, it was concluded that the best regressor is nuSVR regressor-based predictive models trained using the relative intermolecular interactions and a twelve-step averaged simplification of the relative σ-profiles.

Lewis acid‐promoted C–H Chalcogenation of Arenes and Heteroarenes

An efficient catalytic system employing TMS•OTf for the regioselective thiolation of electron‐rich arenes with sulfonyl hydrazides has been developed. The reaction occurs in a solvent mixture of dichloroethane and trifluoroethanol under mild conditions, with the addition of water. This method furnishes a range of para‐thio‐substituted arenes and 3‐sulfenyl‐indoles in good to excellent yields, marking a significant advancement in organic synthesis.

Review article on self emulsifying system

The solubility challenges faced by the pharmaceutical industry, particularly with orally administered drugs, are indeed significant. Low aqueous solubility often leads to poor dissolution and subsequently, low bioavailability, which can result in inconsistent drug effects among patients. Various methods have been explored to address this issue, including salt formation, solid dispersion, and complex formation.Among these approaches, Self-Emulsifying Drug Delivery Systems (SEDDS) have emerged as a promising solution for enhancing the solubility of lipophilic drugs. SEDDS consist of isotropic mixtures of hydrophilic solvents, co-solvents, and surfactants. They possess the unique ability to form fine oil-in-water micro emulsions upon mild agitation and dilution in aqueous media, such as gastrointestinal fluids.The advancement in SEDDS technology encompasses improvements in composition, evaluation methods, development of different dosage forms, and techniques for converting liquid SEDDS into solid forms. These advancements not only enhance solubility but also offer versatility in administration routes and dosage forms, thereby expanding the potential applications of SEDDS in pharmaceutical formulations.This comprehensive review provides valuable insights into the latest developments in SEDDS, offering a detailed account of its composition, evaluation parameters, diverse dosage forms, and innovative techniques for solidification. Moreover, it highlights the diverse applications of SEDDS across various therapeutic areas, underscoring its growing significance in modern pharmaceutical research and development.

Modular Point-of-Need Tropane Alkaloid Detection at Regulatory Levels: Combining Solid-Liquid Extraction from Buckwheat with a Paper-Immobilized Liquid-Phase Microextraction and Immuno-Detection in Interconnectable 3D-Printed Devices.

Contamination with tropane alkaloids in cereals is expected to increase globally. However, current identification tools (e.g., liquid chromatography-mass spectrometry) for tropane alkaloids are time-consuming and expensive. Furthermore, their miniaturized alternatives lack sensitivity and robustness. Therefore, there is a pressing need for inexpensive and effective screening methods. Here, an on-site applicable modular workflow for tropane alkaloid detection in buckwheat is presented. The modular workflow combines paper microfluidics and interconnectable 3D-printed sample preparation tools and was evaluated for different tropane alkaloids, including atropine and scopolamine. Furthermore, integration with an indirect competitive lateral flow immunoassay (icLFIA) for atropine detection at relevant levels was demonstrated. In the modular workflow, to minimize matrix coextraction, tropane alkaloids were extracted from the milled buckwheat cereals by a mixture of alkaline aqueous and immiscible organic solvents (extraction recoveries: 66-79%). The tropane alkaloids were subsequently concentrated with a newly developed paper-immobilized liquid-phase microextraction (PI-LPME, extraction recoveries: 34-60%, concentration factor to immobilized solution in paper: 60-108×). After the PI-LPME, with an integrated 3D-printed setup, the tropane alkaloids were directly eluted (elution recoveries: 83-93%) and detected with the icLFIA. Digital read-out of the icLFIA, by employing a hand-held reader, enabled semiquantification of atropine (IC50 = 0.56 ng mL-1 in standard solutions). The modular workflow was validated by analyzing 24 blank and spiked buckwheat cereal samples with 5 and 10 μg kg-1 atropine. A cutoff value was established with an estimated false negative rate of 1% and estimated false positive rate of 0.68%. Therefore, the modular workflow can aid in fast, inexpensive, and on-site atropine detection by nonexperts, and when integrated with a scopolamine-specific icLFIA expanded toward scopolamine detection. Moreover, the developed sample extraction and concentration method (PI-LPME) is suitable for the analysis of many other compounds with pH-dependent polarity.

Ultrasound-assisted process to improve proteins recovery from industrial canola and soybean byproducts

AbstractAn ultrasound-assisted process is proposed to obtain protein isolates from canola and soybean byproducts. A laboratory-scale probe system (24 kHz, 400W) was used for protein extraction and six levels of energy density were analyzed. Different mixtures of solvents (water, ethanol, methanol, acetone) and temperatures were tested for removing phenolic compounds, and the best results were obtained with ethanol-water (8:2 v/v) and energy density of 104 kJ/L, which minimize protein losses at that step. After extraction of phenolic compounds, samples were alkalinized (pH 12 or 9.5), subjected to ultrasound treatment and the protein precipitated at the isoelectric pH. The highest yield on protein extraction was obtained with 1:20 meal: NaOH solution ratio, applying 150 kJ/L at constant temperature (30 °C), increasing the protein recovery, 72.5% for canola meal and 37.5% for soybean meal, compared to the conventional method. The solubility of both isolates obtained with ultrasound improved ~ 50% at a pH close to neutral and basic, with an increase in free sulfhydryl groups, without significant effects of ultrasound treatment on the subunit fractions of the proteins. These results provide alternatives to develop protein isolates from an undervalued by-product, with better techno-functional properties that can be employed in the food industry.