Chemical Papers最新文献

Paper is an eco-friendly, flexible, porous, and adaptable substrate that can be used to quickly detect analytes of interest in low-cost devices and biosensors. Paper-based sensors offer inexpensive platforms for pathogen detection, food quality monitoring, environmental and sun exposure monitoring, and fast, easy, and accurate disease detection. While many significant biomarkers, such as proteins, enzymes, nucleic acids, antibodies, hormones, and so on, have already been identified using paper-based instruments, more study is required to increase sensitivity and identify a wider range of biomarkers. The performance of these sensors varies depending on the platform, manufacturing process, and sensing material employed. This review curtails the history of biosensors to their classification and application in various fields. In addition, we present different detection techniques that are employed in paper-based sensors such as colorimetric, electrochemical, and fluorescence detection. The functionality of a paper-based sensor adopting different approaches, particularly electrochemical and optical methods, is discussed. Here, we review the development (from 2010 to post-COVID) of paper-based sensors in the field of the detection and determination of biomolecules. Furthermore, their constraints and opportunities for future developments are also addressed.

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A-Amylase and α-glucosidase inhibition is a hopeful curative target against type II diabetes as it can downgrade fierce digestion and absorption of carbohydrates into absorbable monosaccharides. Medicinal plants have been used as blood sugar reducers; on the other hand, the inhibitory action of phytocompounds found in these plants on α-amylase is yet limited. Palmarosa essential oil (PRO) from Cymbopogon martinii is complementary and conventional medicine worldwide. The aim of the study presented is compositional profiling of PRO and in silico docking of main bioactive compounds: geraniol, geranial, linalool, fenchyl alcohol, 6-methyl-hept-5-en-2-one, borneol, elemol, δ-cadinol against alpha-amylase and alpha-glucosidase. GC-FID was used to find out bioactive components in PRO. For docking, Cb-dock2 tool was utilized. Ligand–protein 2-D interactions were also studied. In silico ADMET pharmacoinformatics viewpoint along with PASS prediction of all the ligands has prospected from the point of view of human health. Wet laboratory validation was performed by using Aspergillus oryzae-derived α-amylase and Saccharomyces cerevisiae-derived α-glucosidase. GC-FID exposed presence of 13 bioactive components. Docking investigation demonstrated the effective binding of all the ligands with the enzymes. The interaction results imply that the enzyme-ligand complexes form hydrogen, hydrophobic, and other interactions. Furthermore, molecular dynamics (MD) simulations were also carried out for the best-docked complexes from docking studies (α-amylase–elemol, α-glucosidase–elemol, and α-glucosidase–δ-cadinol) to clarify some information on their thermodynamic and dynamic properties and confirm the docking results as well. In silico ADMET examination disclosed that all the ligand molecules have no toxic effect and acceptable absorption as well. PRO retains inhibition in dose-dependent manner against α-amylase (IC50 = 194.78 μg/ml) and α-glucosidase (IC50 = 162.36 μg/ml). A kinetic study showed that PRO inhibited the α-amylase and α-glucosidase competitively. It could be inferred that the phytochemicals present in PRO might be responsible in α-amylase and α-glucosidase inhibition and thus have potential to be produced as an antidiabetic drug.

Textile wastewater, which often contains dye contamination and other pollutants, can harm and detrimental effects on the environment. In this research, the characteristics of circular disc-shaped ceramic membranes were investigated by fabricating them and studying the impact of sintering temperature. The sintering process of membranes was conducted at four different temperatures ranging 600–900 °C. The membranes were characterized using Fourier transform infrared spectroscopy, thermogravimetric analysis, field emission scanning electron microscopy, zeta potential, and X-ray diffraction. The constructed membranes displayed remarkable chemical stability in both acidic and basic solutions. They exhibited porosity ranging from 15.44 to 28.22% and an average pore size ranging from 0.416 to 4.32 µm. The membranes were sintered at 700 °C showed highest permeability, with a range of 0.04412 to 0.13628 L/h m² for transmembrane pressures of 0.5 to 4 bar, respectively. These membranes demonstrated potential for effective separation of dye methylene blue. The surface of membrane exhibited a negative charge between pH 3 and pH 11, indicating that adsorption was primary mechanism for removal of cationic dye. At a pressure of 0.5 bar, the efficiency of dye removal decreased from 99.61% at a feed concentration of 10 mg/L to 99.37% at 100 mg/L. The experiment design and analysis were examined and optimized transmembrane pressure, feed concentration, flux, and rejection using response surface methodology via central composite design. This study highlights the excellent potential of these membranes for textile dye treatment and various other membrane-based applications.

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The study aims to determine the live crude oil compositional feature’s effect on asphaltene precipitation as a function of temperature. In this study, we have applied different modern feature engineering techniques incorporated with machine learning to understand the importance of governing composition features affecting the asphaltene precipitation as a function of temperature during depressurization. To achieve this purpose, different feature selection techniques integrated with the famous random forest (RF) algorithm were applied to the high pressure high temperature (HPTP) experimental data of ten live crude oil samples available in the published literature having outcome as asphaltene precipitation increase or decrease as a result of temperature rise. All data were visualized by using different techniques. Since the data was scarce in the literature, therefore, to avoid overfitting issues the recursive feature elimination with a fourfold cross-validation technique was applied. Random forest algorithm was trained on 60% of the dataset, while testing was done on the remaining 40% dataset. An accuracy of 100% was achieved during the training phase, while it decreased to zero when applied to the testing dataset. The results were validated using a gradient boosting machine (GBM) and found to be in excellent agreement. However, the implementation of other advanced data science techniques aided in improving the accuracy of the testing phase but to very little margin, i.e., from 0 to 25%. Generally, Heavy ends, Light ends and API were found to be the important features in deciding the trend of asphaltene precipitation with temperature changes. Crude oils with higher Heavy ends or decreased API were found to increase asphaltene precipitation when temperature rises. Since, due to the complex relationship of asphaltene precipitation concerning temperature, the study will help in the prediction of the expected trend of asphaltene precipitation for different types of crude oil under field conditions when the temperature will change during production.

An innovative green synthesized carbon quantum dot was decorated with terbium as new fluorescent nanoprobes (Tb,N@CQDs) and developed as eco-friendliness, water-soluble, cost-effectiveness, and biocompatibility quantum dots for analysis of edoxaban (EDN). A microwave synthesis technique produced environmentally friendly (Tb,N@CQDs) in just 7 min, boasting a high quantum yield of 35.44%. The green synthesized quantum dots were then utilized in the development of a sensor for detecting trace amounts of edoxaban (EDN). EDN is a newly approved anticoagulant medication by the US-FDA for treating deep vein thrombosis (DVT) in patients initially treated with a parenteral anticoagulant for 5–10 days. The introduction of EDN resulted in a gradual decrease in the fluorescence intensity of Tb,N@CQDs at 436 nm within the calibration range 30.0 – 350.0 ng mL⁻¹. The creative method was validated for bio-analytical applications by FDA standards with a lower limit of quantitation (LOQ) 18.33 ng mL⁻¹, demonstrating simplicity, affordability, high sensitivity, and exceptional selectivity, making it suitable for clinical research. This established method proved effective in quantifying EDN in human plasma with percent of recovery (98.88 ± 2.74), pharmaceutical formulations, and pharmacokinetic studies, showcasing sustainability by incorporating recent evaluation criteria.

This study investigated the ultrasound-assisted adsorption of methylene blue (MB) onto vermicompost (VC) derived hydrochars prepared at different hydrothermal treatment temperatures (220, 250, and 280 °C). The effects of pH, time, and initial concentration on the adsorption process were evaluated. The kinetic and isotherm models were applied to fit the experimental data. The results showed that the VC hydrochars exhibited superior adsorption capacity for MB under alkaline conditions. The adsorption process was influenced by chemical interactions between the MB molecules and the surface of hydrochars, and the adsorption process was irreversible chemisorption. VC220 hydrochar demonstrated the highest adsorption capacity for MB, followed by VC250 and VC280 hydrochars. The Pseudo Second Order kinetic model and Langmuir isotherm model provided the best fits to the experimental data. This suggests that the adsorption of MB onto VC hydrochars follows a second-order reaction mechanism and monolayer adsorption process with high adsorption capacities.

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The main protease (M^pro), also called 3C-like protease, activates the initial step of Covid-19 replication by the proteolytic cleavage of viral polyprotein. The M^pro of Covid-19 is distinctly different from the proteases of the host cell (human), which makes M^pro an attractive therapeutic target for small molecule inhibitors. Herein, we have employed extensive computational approaches to identify a novel chemical scaffold against the M^pro enzyme of Covid-19. The pharmacophore model was developed and then validated by Gunner–Henry method. The validated model was then used for the virtual screening. The identified natural product compounds revealed good docking score and interactions with receptor. The final candidate hit established hydrogen bond interactions with essential binding pocket residues of the M^pro enzyme. Moreover, several hydrophobic interactions were also observed between the final candidate hit compound and the M^pro enzyme. Molecular dynamics simulation confirmed the stability of the identified hits in complex with M^pro enzyme. Finally, we argue that this study will potentially contribute to expand the chemical space of M^pro enzyme inhibition and could potentially develop new safe and efficient natural drugs against the Covid-19.

The extraction of phenolic compounds from natural sources is crucial for their utilization in various applications, including food, pharmaceuticals, and cosmetics. However, current extraction methods often suffer from drawbacks such as low yield, long extraction times, and the use of harsh chemicals. The present study aimed to assess in vitro the antioxidant activities of solvent extracts from different wild plants (green tea, al sidr, and sage), in addition to introducing a novel, environmentally friendly method for extracting phenolic compounds from different wild plants and finding the best solvent system for extraction of different phenolic compounds. In the present work, 15 solvent extracts from 3 plant samples were evaluated against 2, 2-diphenyl-1-picrylhydrazyl (DPPH) and potassium permanganate (KMnO₄) as non-radical reagents and compared with ascorbic acid as a natural standard antioxidant, in addition to the analysis of the chemical constituents of promising extracts from wild plants using HPLC. The obtained results revealed that both methods go in parallel, showing that the concentration of extract and incubation time are dependent and proportional to the concentration of phenolic compounds. Buffer-ethanol extract from green tea plant recorded the highest antioxidant activity when compared with other solvent extracts, with more than 95% against the DPPH radical method, but the activities decreased in the case of the KMnO₄ method. Thus, the HPLC analysis of aqueous extracts of promising buffer and buffer-ethanol solvent systems for the 3 plants showed a highly complex profile, containing approximately 14 and 18 different components. From these compounds, gallic acid recorded the highest concentration for green tea in both extracts at 982.06 and 275.06 µg/ml, respectively. While rosmarinic acid recorded the highest concentration for sage in buffer-ethanol extract at 395.93 µg/ml. From the obtained results, it could be concluded that the solvent extracts of plant samples are rich in different active ingredients, especially phenolic compounds and their derivatives. The extracts from green tea, especially with buffer solution, are more acceptable when compared with other extracts. Buffer, ethanol, and ethanol-buffer extracts (from al sidr, sage, and green tea) recorded high concentrations of phenolic compounds and their derivatives and exhibited antioxidant activity, respectively.

The global spread of the human immunodeficiency virus (HIV) constitutes a significant threat to human health, focusing the important task for today’s scientific community to explore anti-HIV drug design and address the urgent need for drug repurposing strategies given the challenge of HIV drug resistance. In this study, a library of 4099 marketed drugs was computationally evaluated using similarity search, e-pharmacophore, molecular docking, binding free energy, pharmacokinetic estimation, antiviral activity prediction analysis, hierarchical clustering, molecular electrostatic potential, and crystal structures of the HIV-1 reverse transcriptase (RT) enzyme. Reliable pharmacophore models were obtained with AUC values of 0.858 (± 0.015) for Pharm-1 and 0.864 (± 0.016) for Pharm-2. Similarly, the molecular docking showed AUC values of 0.835 (± 0.024) for SP glide and 0.819 (± 0.021) for XP glide. The multi-step computational process initially identified 120 drugs through similarity analysis, followed by 1489 drugs selected by Pharm-1 and 1945 displayed by Pharm-2. Finally, after molecular docking and binding free energy analysis four potential candidates (procaterol, pravastatin, pergolide, and ropinirole) with promising inhibitory effects on HIV-1 RT (pIC50 values of 5.714, 5.888, 6.269, and 6.383 and predicted inhibition of 46.58%, 51.87%, 51.70%, and 51.61%, respectively) were selected. This protocol seems to provide a viable solution for exploring marketed drugs and their potential repositioning for HIV-1 RT, and can be expanded to investigate different protein targets, thereby identifying novel candidates for experimental testing. Further validation through experimental studies can pinpoint the bioactivity of selected drugs, facilitating their potential application in the management of HIV disease.

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In this paper, we have developed a series of piperic acid (PA) derivatives to overcome the inherent constraints linked to PA for Alzheimer's disease (AD) management. We have carried out a comprehensive study to investigate the structure–activity relationship (SAR) of PAanalogs to enhance their inhibitory properties towards cholinesterase enzymes. Compound 3m exhibited notable inhibition against butyrylcholinesterase (BChE) and acetylcholinesterase (AChE) among all developed analogs (BChE (µM), 1.03 ± 0.011; AChE (µM), 4.26 ± 0.13 respectively) over PA (AChE% inhibition at 20 µM, 7.14 ± 0.98; BChE% inhibition at 20 µM, 5.87 ± 0.76). Compound 3m  was chosen for further biological investigations based on these encouraging outcomes. 3 m demonstrated a binding affinity for AChE’s peripheral anionic site, indicating its interaction with this specific enzyme region. Additionally, it also possesses favorable permeability across the blood–brain barrier, with a Pe (permeability coefficient) value of 5.79 ± 1.12. The molecular docking investigations unveiled the ability of 3mto intricately engage with AChE and BChE.In cell-based cytotoxicity tests, compound 3m displayed cell-friendly characteristics across different tested concentrations. Notably, 3m exhibited the ability to counteract scopolamine-induced memory impairmentin mice, enhancing both spatial and cognitive memories. These results strongly suggest that 3m can behave as a potential compound for AD management.

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