Green Coffee Extract ( Coffea canephora ) as an Antioxidant in Mayonnaise in Replacement of Synthetic Agents

ABSTRACT Mayonnaise is very susceptible to oxidation, due to the high lipid content. The synthetic antioxidants are commonly used in the preparation of this sauce. The green coffee bean is one of the largest natural sources of phenolic compounds with antioxidant activity. This study aimed to assess the feasibility of using an aqueous green coffee extract (GCE) as an antioxidant in mayonnaise. Three concentrations of GCE were tested (0.5%, 1.0%, and 1.5%). About 1.5% GCE did not affect the emulsion formation, pH, and textural parameters ( p  > 0.05). GCE demonstrated a greater delay in peroxide value during 28 days of storage when compared with synthetic agents ( p  < 0.05). GCE increased the phenolic compounds proportionally to the added concentration, enhancing their antioxidant activity compared to the synthetic agents ( p  < 0.05). About 0.5%–1.5% of GCE did not affect sensory acceptance ( p  > 0.05). GCE as an antioxidant for mayonnaise, replacing synthetic antioxidants, proved viable, especially at a concentration of 1.5%. Practical Applications : Lipid‐rich products, such as mayonnaise, require antioxidants. Synthetic antioxidants are widely used; however, due to high consumer demand for natural products, green coffee extract becomes a viable alternative as it acts as an antioxidant and adds nutritional value to the products. This technology is a novel option for the industry, providing new natural antioxidant agents.

A New Methodology for Preparing Benzylated Aminopyridines Yields Previously Inaccessible Organocatalysts

p ‐Dialkylaminopyridines represent a key class of nucleophilic organocatalysts, widely used in alcohol‐modifying reactions, among other applications. However, access to certain variants of these catalysts, particularly those with sterically congested secondary sphere, remains challenging or even unfeasible using previously established synthetic routes. Lewis acid‐promoted benzylation or cyclative dibenzylation of simple aminopyridines with corresponding alcohols effectively overcomes these shortcomings. This innovative approach enables the synthesis of previously inaccessible (2,5‐diarylpyrrolidino)pyridines and novel ( N ‐benzyl‐ N ‐methylamino)pyridines bearing extended ortho ‐alkoxy tails on the aryl substituents. The new catalysts, characterized by their bulky secondary sphere, exhibit outstanding activity and high site‐selectivity in the phosphorylation of a model diol amphiphile.

Self‐Calibrating Copper‐Based Metal Organic Frameworks for Ratiometric Electrochemical Sensing of Creatinine

Abstract Nanostructures that can undergo redox reactions have significant potential for electrochemical analysis. They can act as signal amplifiers to determine concentrations of targets in biological samples. In this work, a rational combination of electroactive copper‐based metal‐organic frameworks (Cu‐MOFs) and ferrocene carboxylic acid (Fc) was designed for ratiometric electrochemical detection of creatinine. The synthesized Fc@Cu‐MOFs exhibited two redox signals from the Cu 2+ /Cu + and Fe 3+ /Fe 2+ systems in the skeleton of Cu‐MOFs and Fc, respectively. In the presence of chloride (Cl − ), the oxidation current of Cu + increased due to formation of solid‐state cuprous chloride (CuCl). Adding strong Cu + chelators, e. g. creatinine, coordinated with Cu + and caused the current output of solid‐state CuCl to decrease significantly. The anodic current of Fc did not appreciably change, serving as an internal reference signal. The ratiometric responses (I Cu(I) /I Fc ) changed with increasing concentrations of creatinine from 0.017–130 μM with a detection limit (S/N=3) of 0.005 μM. The main advantages of Fc@Cu‐MOFs are the low LOD, high selectivity, and reliability, making it a suitable platform for determining creatinine in human serum and urine samples. The as‐fabricated sensor is a reliable approach for determining (bio) molecules that can form stable complexes with Cu + ions.

An ICH Q14‐Guided AQbD Framework for the Development of an HPLC Method: Analysis of Siponimod Fumarate and Its Impurities

ABSTRACT Siponimod fumarate (SIP), a potent selective S1P receptor modulator, has emerged as a critical therapeutic agent in the treatment of multiple sclerosis. Recognizing the increasing regulatory demands for robust impurity profiling and method reliability, this study reports the development and optimization of an HPLC method for the simultaneous determination of SIP and its related impurities in both bulk drug substance and tablet dosage forms. The method was developed within an Analytical Quality by Design (AQbD) framework, guided by ICH Q14 principles, ensuring a systematic and risk‐based approach throughout the analytical lifecycle. Chromatographic separation necessary for resolving critical impurities was achieved on an XSelect HSS T3 column (150 mm × 4.6 mm, 3.5 µm) using a stepped gradient elution program with 0.1% perchloric acid in water and acetonitrile as the mobile phases. Optimal separation conditions, identified through the AQbD process to meet stringent performance criteria, were determined at a column temperature of 42.5°C, a flow rate of 1.4 mL min −1 , and UV detection at 212 nm. The method performance was rigorously evaluated through accuracy profiles, confirming both its precision and trueness across the targeted concentration range. In parallel, as part of a holistic method characterization, environmental sustainability was assessed using comprehensive greenness metrics, whereas its practical applicability was further substantiated using the Blue Applicability Grade Index (BAGI) and the Red–Green–Blue 12 (RGB12) algorithms. This approach not only bridges the gap created by the absence of an official pharmacopoeial monograph for SIP but also offers a robust, well‐characterized, and sustainable platform for pharmaceutical quality control, aligning method development with both regulatory performance needs and environmental awareness.

Rapid Separation and Analysis of Exosomes in Milk Sample by on‐Line Nano‐Liquid Chromatography

ABSTRACT Exosomes are very small vesicles of 30–150 nm average particle size and hold great potential in new therapeutic applications. The aim of this study is to develop a new method for the isolation and analysis of exosomes in milk via hydrophobic interaction chromatography (HIC), including salting‐out process in nano‐liquid chromatography (nano‐LC). On the basis of this approach, a trap column combined with graphene oxide (GO)‐based monolithic nano‐column was used for on‐line analysis of exosomes in nano‐LC. The monolith was prepared by an in situ polymerization of butyl methacrylate (BMA), ethylene glycol dimethacrylate (EDMA), and methacryloyl graphene oxide nanoparticles (MGONPs). The final solution was introduced into a fused silica capillary with a 50 µm i.d. for polymerization. After preparation, the column was further modified with dimethyloctadecylchlorosilane (DODCS) to increase its hydrophobicity. The characterization of monolith was performed using scanning electron microscopy (SEM) and chromatographic examination. The final monolith was applied for the isolation and analysis of exosomes in milk via HIC‐nano‐LC. Nanoparticle tracking analysis (NTA), SEM, and Fourier transform‐infrared (FT‐IR) for the tandem characterization of milk exosomes were used, whereas step gradient elution was employed for HIC. The results demonstrated good ability to isolate exosomes from milk with three dilution factors, and a loading capacity of 7.3 ± 02 × 10 11 exosomes could be obtained using the on‐line nano‐LC system. The developed method holds many advantages and may be adapted for the isolation of exosomes from a diverse range of media.

Enhancing the Diffusion Channels of Silica‐Alginate Capsules for Microbial Encapsulation

ABSTRACT Silica‐alginate capsule (G‐0) has recently been used in fermentation processes to encapsulate microbial cells for several benefits, including facilitating continuous flow processes and simplifying cell recovery and reuse. However, these conventional silica‐coated alginate capsules suffer from poor diffusion channels, which are critical for efficiently transporting substrates and products. This study aimed to develop a novel method for producing silica‐coated alginate capsules with improved diffusion channels (G‐3). The Ca‐alginate capsule was fabricated via a simple dripping method, where a solution of calcium chloride (CaCl 2 ) and carboxymethylcellulose (CMC) was dripped into an alginate solution. For the traditional silica coating (G‐0), the alginate capsule was mixed with a silica source (hydrolyzed 3‐aminopropyl triethoxysilane) under specific conditions. In the modified method, glucose was introduced as a pore‐forming agent (PFA), with varying amounts (0.75, 1.5, and 3 g) resulting in capsules labeled G‐0.75, G‐1.5, and G‐3, respectively. The diffusion coefficient for G‐3 was found to be the highest, for example, at 313.15 K, it was calculated as( 7.77 ± 0.57 ) × 10 − 3m m 2 / min 7.77 \pm 0.57 10}^{ - 3 2 }$ compared to( 3.04 ± 0.09 ) × 10 − 3 m m 2 / min $( {3.04 \pm 0.09 10}^{ - 3 2 }$ for G‐0. This finding highlights the effectiveness of PFA in enhancing membrane porosity and diffusivity, which is promising for microbial cell immobilization where mass transfer is a significant concern.

Overproduction and Characterization of Recombinant Soluble Trypanosoma brucei Phospholipase A2

Improved Conjugate Gradient Methods for Unconstrained Minimization Problems and Training Recurrent Neural Network

ABSTRACT This research introduces two conjugate gradient methods, BIV1 and BIV2, designed to enhance the efficiency and performance of unconstrained optimization problems with only first derivative vectors. The study explores the derivation of new conjugate gradient parameters and investigates their practical performance. The proposed BIV1 and BIV2 methods are compared with the traditional Hestenes‐Stiefel (HS) method through a series of numerical experiments. These experiments evaluate the methods on various test problems sourced from the CUTE library and other unconstrained problem collections. Key performance metrics, including the number of iterations, function evaluations, and CPU time, demonstrate that both BIV1 and BIV2 methods offer superior efficiency and effectiveness compared to the HS method. Furthermore, the effectiveness of these methods is illustrated in the context of training artificial neural networks. Experimental results show that the new methods achieve competitive performance in terms of convergence rate and accuracy.

A Comparative Study of One‐Step and Multi‐Step Numerical Methods for Solving Ordinary Differential Equations in Water Tank Drainage Systems

Hydrothermal Liquefaction of Jatropha curcas ( J. curcas ) Under Subcritical Water Conditions: Water and Palm Oil Mill Effluent as Solvents

ABSTRACT In this study, palm oil mill effluent (POME) and water were used as the medium or hydrogen donor solvent in the hydrothermal liquefaction (HTL) of Jatropha curcas . POME, with its high organic compound content, is seen as a promising solvent to be investigated. The POME analysis using GC–MS showed the existence of palmitic and oleic acids. The HTL was performed for both solvents using a batch reactor, and three parameters were varied (biomass‐to‐solvent ratio, temperature, and reaction time). The results showed that POME could be used as a medium for the HTL of J. curcas . It was found that the HTL of J. curcas with POME produced a higher oil yield (63.4%) than the one using water (43.2%) with a lower biomass‐to‐solvent ratio (1:2) and lower temperature (300°C) with an optimum reaction time (60 min), and with 30.8% of solid and 5.8% of gas recorded. The results of gas chromatography–mass spectrometry (GC–MS) showed that high ester content and the lowest acid content were obtained at 350°C for both solvents. As for POME, the ester content increased at 350°C while the acid content decreased at the same temperature. High hydrocarbon content was obtained for the experiment at 300°C for both solvents. The highest oil yield under POME conditions recorded a good HHV value of 39.07 MJ/kg with an oxygen content of ~11%, with 81% carbon recovered, indicating high energy recovery. The extra hydrogen generated through the reforming of POME in the liquefaction of J. curcas leads to stabilizing the free radicals and producing high oil yields.