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Chemical engineering is an engineering branch that deals with the chemical production and manufacture of products that undergo chemical processes. This includes equipment design, creating systems and processes to refine raw material, as well as mixing, compounding, and processing chemicals to create products.
Chemistry and Chemical Engineering
Abstract
Aflatoxins (AFs) and deoxynivalenol (DON), common mycotoxins in cereals, pose contamination risks in beer production, often persisting from raw barley into final products. This study investigates the transfer and decomposition of AFs and DON during the barley steeping stage of malting. Barley spiked with AFs and DON was steeped, and mycotoxin concentrations were analyzed in both the barley residue and the resulting wastewater. Results indicated that AF and DON transfer into wastewater was influenced by water solubility, though concentrations remained below solubility limits. AFs and DON residues were also detected in the steeped barley. Decomposition studies showed that while AFs were partially degraded by UV light, DON required photocatalysis for effective degradation. However, matrix components in wastewater decreased the efficiency of DON decomposition, suggesting that preliminary removal of organic components from wastewater could enhance photocatalytic detoxification. These findings provide insight into mycotoxin management strategies for brewing wastewater, emphasizing the need for targeted pretreatment to improve degradation efficiency.
Abstract
The aim of the current investigation to estimate the amount of theobromine (THEOB), theophylline (THEOP) and caffeine (CAF) concurrently using ultra performance liquid chromatography with photo diode array detector (UPLC-PDA) in ultrasound assisted extract of commercially available food products. The commercially available products are categorized in three different groups including teas, coffees and chocolates. The UPLC approach is rapid, precise, highly sensitive and cost effective for the concurrent assessment of THEOB, THEOP and CAF in ultrasound assisted extract of commercially available food products. The mobile phase comprises a mixture of water and ACN (90:10, v/v) for the concurrent assessment of THEOB, THEOP and CAF in ultrasound assisted extract of commercially available food products. The current approach operated on a linear scale range of 6.66–33.3 ng mL−1, 3.33–33.3 ng mL−1 and 3.33 – 33.3 ng mL−1, respectively, for THEOB, THEOP and CAF at 272.5 nm wavelength. The LOD for THEOB, THEOP and CAF were assessed to be 1.10 ± 0.001, 0.75 ± 0.000 and 0.48 ± 0.002 ng mL−1, respectively by applying the present approach. The LOQ for THEOB, THEOP and CAF were assessed to be 3.35 ± 0.009, 2.29 ± 0.001 and 1.47 ± 0.001 ng mL−1, respectively by applying the present approach. These findings confirmed that the current UPLC approach is highly sensitive, accurate, precise and robust for the concurrent assessment of THEOB, THEOP and CAF in ultrasound assisted extract of commercially available food products. Antioxidant activity of different teas, coffees, chocolates as well as standard THEOB, THEO and CAF were determined by DPPH method.
Abstract
Osimertinib (Tagrisso, AstraZeneca Pharmaceuticals) is the inaugural third-generation irreversible EGFR-TKI that specifically targets both the EGFR T790M resistant mutation and EGFR-TKI-sensitizing mutations. On September 25, 2024, the Food and Drug Administration authorized osimertinib (OSM) for adult patients with locally advanced, unresectable (stage III) non-small cell lung cancer (NSCLC). The target of this work was to establish a fast, accurate, environmentally friendly, and highly sensitive UPLC-MS/MS methodology for detecting OSM levels in human liver microsomes (HLMs). The separation of OSM and zanubrutinib (ZNB) was accomplished utilizing a C8 column and an isocratic mobile phase. The linearity of the OSM calibration curve spanned from 1 to 3,000 ng mL−1. The AGREE score of 0.76 validates the efficacy of the current approach. The brief in vitro half-life (23.72 min) and moderate intrinsic clearance (34.18 mL min−1 kg−1) of OSM indicate that it resembles drugs with a moderate extraction ratio. The present LC-MS/MS technique is regarded as the primary analytical methodology for quantifying OSM in HLM matrices. The characterization of OSM metabolic stability and in silico ADME features are crucial for progressing the discovery of novel drugs with improved metabolic stability.
Abstract
Apples are among the most common fruits, produced on the territory of North Macedonia. Before they reach the market, it is essential to be tested for pesticide residues, which are used for protection against pests for this culture, and in order to ensure the customer safety. For this reason, a novel and simple method for simultaneous determination of captan, folpet, difenoconazole and chlorpyrifos in apple samples has been developed and validated. Acetone is used for extraction of the pesticide residues, followed by liquid-liquid (LLE) and solid–phase extraction (SPE). Separation and quantification of analytes is achieved on reversed-phase high performance liquid chromatography (RP-HPLC) with UV diode array detector (UV-DAD). The best results are obtained using analytical column LiChrospher 60 RP-select B (250 mm × 4 mm, 5 µm), with isocratic elution and acetonitrile/0.1 % acetic acid in water (70:30, V/V) as a mobile phase. The flow rate is 1 mL min−1, and UV detection is performed at 220 and 230 nm. The linearity of the method is tested in the range of 1.50–3.60 mg kg−1 for captan and folpet, and 0.35 – 0.60 mg kg−1 for difenoconazole and chlorpyrifos. The obtained values for recovery and RSD ranged from 94.94 to 114.63 %, and 0.09–9.25 %, respectively. The validated method is successfully applied to apple samples for the determination of the investigated pesticide residues.
Abstract
Aflatoxins, potent carcinogenic mycotoxins produced by Aspergillus species, persist in various foods, posing significant health risks upon consumption. This study assesses dietary aflatoxin B1 (AFB1) exposure in Vietnam using Margin of Exposure (MOE) and Hazard Index (HI) to evaluate risk levels in peanuts, chili powder, corn, and raisins. AFB1 levels were quantified by UPLC-FLD. AFB1 was detected in 71.5% of chili powder, 29.3% of peanuts, and 26.0% of corn samples, with no detectable levels in raisins. Peanuts and corn kernels were classified as high-risk, with MOE values below 10,000 (peanuts: 25.8–56.6; corn: 42.3–92.6) and HI values exceeding 1, potentially contributing to 20.4–44.7 and 12.5–27.3 liver cancer cases per 100,000 adults, respectively. In contrast, chili powder had MOE values between 3,208 and 7,021 and HI below 1, indicating a low public health risk. Raisins were deemed safe with MOE over 200,000 and HI at 0.01. Results also indicated higher cancer risk for women and lean individuals consuming the same AFB1 levels. These findings underscore the need for focused risk management strategies to mitigate AFB1 exposure and protect public health in Vietnam.
Abstract
In the field of pharmaceutical analysis, high-performance liquid chromatography (HPLC) is considered to be the key technique, which is one of the most efficient, quick, and easy methods for the simultaneous determination of two are more drugs. The purpose of the current study is to develop and validate the reversed-phase high-performance liquid chromatographic (RP-HPLC) method for the simultaneous determination of Paracetamol and Fexofenadine HCl. This approach was validated by the standards and The International Conference on Harmonization (ICH), and United States Pharmacopeia (USP) were followed in the development and validation of the method. The chromatographic conditions including a mobile phase comprised of a 35:65 buffer mix and acetonitrile with a 1.0 mL min−1 flow rate were used. A thorough investigation was performed, including linearity and range, specificity, robustness, accuracy, precision, solution stability, and system suitability. The outcomes of the studies have shown that, both Active Pharmaceutical ingredients i.e., Paracetamol and Fexofenadine HCl were separated in about 7.5 min. The variation coefficient for Paracetamol and fexofenadine HCl varied between 0.9992 R 2 and 0.9983 R 2, respectively. The devised method was proved accurate, as API recoveries in both cases of Paracetamol and Fexofenadine ranged from (99.79%, 100.72%, and 98.64%) to (99.96%, 100.64%, and 99.00%). The method's accuracy was further demonstrated by the solution stability which was 99.84% for Paracetamol, and 100.53% for Fexofenadine HCl. The suggested method for simultaneously measuring Paracetamol and Fexofenadine HCl was established, validated, and there was no evidence of any excipient interaction was observed.
Abstract
The need to develop environmentally friendly analytical approaches has driven the pharmaceutical industry to seek greener alternatives. Ultra-Performance Liquid Chromatography (UPLC) is known for its efficiency but traditionally relies on toxic solvents. Integrating Green Analytical Chemistry (GAC) principles aims to address environmental concerns while maintaining analytical performance. This work aims to advance and authenticate a green, efficient UPLC method for the concurrent quantification of Metformin (MET) and Empagliflozin (EPI) in tablet formulations, adhering to green chemistry principles and ensuring high analytical accuracy. The method was optimized using a UPLC-PDA system with a phenyl column and a mobile phase of ethanol and perchloric acid. Analytical Quality by Design (AQbD) was employed to optimize critical method parameters. Environmental impact was assessed using metrics such as GAPI, AMGS, and AGREE. Degradation studies under various stress conditions were performed to test method robustness. The method achieved high recovery rates for MET and EPI, with minimal interference from excipients. The environmental evaluation showed a high Analytical Eco-Score (AES) of 97, indicating low environmental impact. The AGREE score of 0.89 confirmed excellent alignment with green chemistry principles. Degradation studies confirmed the method's stability and reliability under stress conditions. The developed UPLC method demonstrates a significant advancement in analytical sustainability, offering an eco-friendly, efficient, and precise approach to drug analysis. The method's high alignment with green chemistry principles and its effectiveness in quantifying MET and EPI highlight its potential as a model for sustainable analytical practices in pharmaceutical analysis.
Abstract
Tea's beneficial effects have long been attributed to its abundance of natural bioactive compounds; however, the influence of variations in these compounds on taste and aroma remains poorly understood. To investigate the relationship between metabolomic profiles and tea processing adaptability, this study employed sensory evaluation and untargeted metabolomics to compare four tea cultivars from Guangxi—Ying Hong No.9 (YH), Gui Hong No.3 (GH), Gui Cha No.2 (GC), and Mei Zhan (MZ)—cultivated under the same conditions. Sensory evaluation revealed that GH and MZ exhibited the highest quality in green tea and black tea, respectively, while GC showed moderate quality, and YH performed less favorably than the other three cultivars. Metabolomics analysis uncovered significant differences in the metabolic profiles among the four tea cultivars, with MZ and YH displaying higher levels of flavonol glycosides, and GC and GH showing elevated levels of organic acids and fatty acids. Pathway analyses of GH and MZ indicated that the differentially enriched pathways were primarily related to linoleic acid metabolism and flavonoid and flavanol synthesis. Correlation analyses further revealed that the sensory quality of green tea was closely linked to fatty acids and organic acids in fresh leaves, whereas the sensory quality of black tea was strongly associated with flavonol glycoside levels. This study provides a comprehensive understanding of the complex relationship between metabolite characteristics and processing suitability in different tea cultivars, offering valuable insights into the development of tea germplasm resources in the Guangxi region.
Abstract
This research dealing with salting out TLC technique for simultaneous determination of two antihistaminic drugs Loratadine and its active metabolite desloratadine in pure, tablets and rabbit spiked plasma. Separation was performed on silica gel 60 F254 plates using aqueous ammonium sulfate and acetonitrile (6:4, v/v) as a mobile phase. The R f values were 0.51 ± 0.02 and 0.70 ± 0.004 for Loratadine and desloratadine, respectively in pure or dosage form while in spiked plasma R f values were 0.39 ± 0.004 and 0.61 ± 0.004 for both drugs respectively using levocetirizine as internal standard (R f 0.74 ± 0.004). The separated bands were scanned under UV light at λ 254 nm and the TLC chromatograms were captured by camera and treated with Image J software. Method validation was according to ICH and complied with USP31- NF26 guidelines. The correlation coefficients of calibration curves were 0.997 and 0.998 for Loratadine and desloratadine in pure and dosage form while in rabbit spiked plasma were 0.996 and 0.995 for both drugs respectively in the range 100–2,000 μg mL−1. limits of detection LOD and limits of quantitation LOQ for Loratadine and desloratadine were 7.84, 30.06 and 23.52, 91.18 μg mL−1 respectively as pure or as dosage form while LOD and LOQ in rabbit spiked plasma were 17.46, 14.03 and 52.38 and 42.09 μg mL−1 respectively.
Abstract
The automated system for enhancing plant growth presents an innovative approach to optimize quality of sugarcane cultivation for four main sugarcane growing zones. It includes issues like recommendation of crops based on soil nutrients, diagnosis of disease in the leaf and stem images of sugarcane, weed detection and harvesting time prediction. The research work proposed in the article presents an innovative two-stage approach for object detection and classification in agricultural imagery. Initially, YOLOv8 (You Only Look Once) is employed to accurately detect objects within images, delineating them with precise boundary boxes. Subsequently, the focus of hybrid model integrating Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks, known as Contextual Long Short-Term Memory (CLSTM), is employed. This dual-stage methodology harnesses the speed and accuracy of YOLOv8 for robust object localization, while the CLSTM model ensures nuanced classification, contributing to comprehensive and accurate approach for object detection and crop-weed differentiation in agricultural scenarios. The proposed approach is compared with the four DL algorithms for identifying weeds in sugarcane crops and subsequently assessed their accuracy and F1 score performance. At a learning rate of 0.002, the findings of CLSTM showcase superior precision at 98.5%, recall at 97.8%, F1 score at 98.1%, and an overall accuracy of 97.7%. The subsequent task is harvesting time prediction, which entails identifying the best time to harvest sugarcane based on the planting period, weather predictions, and sugarcane brix value. The implementation of this automated system not only enhances the productivity of sugarcane cultivation but also serves as a model for sustainable and resource-efficient agriculture.
