Abstract: The hydrogenation of levulinic acid (LA) is an important route to prepare high-value biomass-based platform compound γ-valerolactone (GVL). Herein, a highly efficient RuIr alloy bimetallic catalyst supported on SiC for the aqueous hydrogenation of levulinic acid (LA) into γ-valerolactone (GVL) under mild conditions. The RuIr/SiC catalyst exhibited a high LA conversion and GVL selectivity (both >99%) in water under 0.2 MPa H2 pressure at 25 oC. The excellent performance is due to the synergistic effect of Ru and Ir nanoparticles on the semiconducting SiC. Moreover, the activity of RuIr/SiC alloy catalyst did not change significantly after 5 cycles, indicating that the bimetallic alloy catalyst has high stability.

Abstract:

Cationic gemini surfactants are used due to their broad spectrum of activity, especially surface, anticorrosive and antimicrobial properties. Mixtures of cationic and anionic surfactants are also increasingly described. In order to investigate the effect of anionic additive on antimicrobial activity, experimental studies were carried out to obtain MIC (minimal inhibitory concentration) against E. coli and S. aureus bacteria. Two gemini surfactants (12-6-12 and 12-O-12) and two single quaternary ammonium salts (DTAB and DDAC) were analyzed. The most commonly used commercial compounds of this class, i.e. SDS and SL, were used as anionic additives. In addition, computer quantum-mechanical studies were also carried out to confirm the relationship between the structure of the mixture and the activity.

Abstract:

Fluorescence is a remarkable property exhibited by many chemical compounds and biomolecules. Fluorescence has revolutionized analytical and biomedical sciences due to its wide-ranging applications in analytical and diagnostic tools of biological and environmental importance. Fluorescent molecules are frequently employed in drug delivery, optical sensing, cellular imaging and biomarker discovery. Cancer is a global challenge and fluorescence agents can function as diagnostic as well as monitoring tools both during early tumor progression and treatment monitoring. Many fluorescent compounds can be found in their natural form but recent developments in synthetic chemistry and molecular biology have allowed us to synthesize and tune fluorescents molecules which otherwise wouldn’t exist in the nature. Naturally derived fluorescent compounds are generally more biocompatible and environmentally friendly. They can also be modified in cost-effective and target-specific ways with the help of synthetic tools. Understanding their unique chemical structures and photophysical properties is key to harnessing their full potential in biomedical and analytical research. As drug discovery efforts require rigorous characterization of pharmacokinetics and pharmacodynamics, fluorescence-based detection accelerates the understanding of drug interactions via in vitro and in vivo assays. Herein, we provide a review of natural products and synthetic analogs that exhibit fluorescence properties and can be used as probes, detailing their photophysical properties. We have also provided some insights into the relationships between chemical structures and fluorescent properties. Finally, we have discussed the applications of fluorescent compounds in biomedical science; mainly in the study of tumor and cancer cells and analytical research, highlighting their pivotal role in advancing drug delivery, biomarkers, cell imaging, biosensing technologies, and as targeting ligands in the diagnosis of tumors.

Abstract:

Heterocyclic compounds are cornerstone for active pharmaceutical ingredients. Among heterocycles, isoindoline core occupies special place as ten commercial bioactive compounds/drugs contain this skeleton decorated with several functional groups required for optimal receptor binding. These drugs are employed for indications such as multiple myeloma, leukemia, inflammation, hypertension, edema, obesity, and insect control. This review presents pharmacological activities, mechanisms of action and chemical syntheses of these commercial bioactive molecules/drugs.

Abstract:

Determining the values of various properties for new bioinks for 3D printing is a very important task in the design of new materials. For this purpose, a large number of experimental works have been consulted and a database with >1200 bioprinting tests has been created. These tests cover different combinations of conditions in terms of print pressure, temperature, and needle values, for example. These data are difficult to deal with in terms of determining combinations of conditions to optimize the tests and to analyze new options. The best model presented has values of specificity = Sp (%) = 88.4, sensitivity = Sn (%) = 86.2 in training series and Sp (%) = 85.9, Sn (%) = 80.3 in external validation series. This model uses operators based on perturbation theory in order to analyze the complexity of the data. The performance of the model has been compared with neural networks with very similar results. This tool could be easily applied to predict the properties of in silico bioprinting assays.

Abstract: As an appealing approach for discovering novel leads, the key advantage of de novo drug design lies in its ability to explore a much broader dimension of chemical space, without being confined to the knowledge of existing compounds. So far many generative models have been described in the literature, which have completely redefined the concept of de novo drug design. However, many of them lack practical value for real-world drug discovery. In this work, we have developed a graph-based generative model within a reinforcement learning framework, namely METEOR (Molecular Exploration Through multiplE-Objective Reinforcement). The backend agent of METEOR is based on the well-established GCPN model. To ensure the overall quality of the generated molecular graphs, we implemented a set of rules to identify and exclude undesired substructures. Importantly, METEOR is designed to conduct multi-objective optimization, i.e. simultaneously optimizing binding affinity, drug-likeness, and synthetic accessibility of the generated molecules under the guidance of a special reward function. We demonstrate in a specific test case that, without prior knowledge of true binders to the chosen target protein, METERO generated molecules with superior properties compared to those in the ZINC 250k data set. In conclusion, we have demonstrated the potential of METERO as a practical tool for generating rational drug-like molecules in the early phase of drug discovery.

Abstract: This study evaluated the stability and reusability of amino-functionalized nanocellulose aero-gels as CO₂ adsorbent materials. The modified aerogels, synthesized via a controlled silylation using N-[3-(trimethoxysilyl) propyl] ethylenediamine (DAMO), demonstrated excellent thermal stability up to 250°C (TGA) and efficient CO₂ adsorption through chemisorption, which was the main adsorption mechanism. The performance of the aerogels was assessed using both, adsorp-tion isotherms and the decay pressure technique, revealing that CO₂ adsorption capacity in-creased with higher amino group loading (4.62, 9.24, and 13.87 mmol of DAMO). At 298 K and 4 bar, CO₂ adsorption capacity increased proportionally with the amino group concentration, reaching values of 3.17, 5.98, and 7.86 mmol of CO₂ g-1 polymer, respectively. Furthermore, over 20 adsorption/desorption cycles, the aerogels maintained 95% CO₂ desorption at ambient tem-perature, indicating their potential for industrial use. These findings highlight the aerogels suitability as stable, reusable materials for large scale CO₂ capture and storage technologies.

Abstract:

Porous organic polymers (POPs), based on polysulfone (PSU) and covalently linked zirconium-organic moieties have been applied for the first time to Arsenic removal in wastewater. The synthesis involved anchoring a synthon molecule onto PSU, followed by MOF assembly and subsequent quaternization (QA) with trimethylamine (TMA). Two samples Zr-POP and Zr-POP-QA are characterized by NMR, FTIR, and titration. The efficiency of As uptake is revealed by ICP. The study is carried out at different pH (3, 7, and 12) to vary the charge of Zr-organic moieties and the charge of arsenite and arsenate species. Two concentrations (0.5 and 1 mM) of As (III) and As (V) are used. The results show that Zr-POP at pH 3 has a removal efficiency (RE%) of 77% for As (V), in agreement with the positive charge present in the Zr-framework at this pH. At neutral pH the As (III) sorption is also relevant. Zr-POP-QA at pH 12 shows, thanks to the positive charge on the ammonium moieties, a RE% of As (III) equal to 35%. The kinetic of processes, performed on the most promising system, i.e. Zr-POP at pH 3 for As(V), shows a plateau already after 8 hours with a second-order law. The regeneration of the material is also evaluated. According to the results, these materials are serious candidates in the removal of heavy metals in wastewater.

Abstract: Hybrid nanocomposites incorporating multiple fillers are gaining significant attention due to their ability to enhance material performance, offering superior properties compared to traditional monophase systems. This study investigates hybrid epoxy-based nanocomposites reinforced with multi-walled carbon nanotubes (MWCNTs) and graphene nanosheets (GNs), introduced at two different weight concentrations of the mixed filler, i.e. 0.1 wt% and 0.5 wt%, which are, respectively, below and above the Electrical Percolation Threshold (EPT) for the two binary polymer composites that solely include one of the two nanofillers, with varying MWCNTs:GNs ratios. Mechanical properties, such as contact depth, hardness, and reduced modulus, were experimentally assessed via nanoindentation, while morphological analysis supported the mechanical results. A Design of Experiments (DoE) approach was utilized to evaluate the influence of filler concentrations on the composite's mechanical performance, and Response Surface Methodology (RSM) was applied to derive a mathematical model correlating the filler ratios with key mechanical properties. The best and worst-performing formulations, based on hardness and contact depth results, were further investigated through detailed numerical simulations using a multiphysics software. After validation considering experimental data, the simulations provided additional insights into the mechanical behavior of the hybrid composites. This work aims to contribute to the knowledge base on hybrid composites and promote the use of computational modeling techniques for optimizing the design and mechanical performance of advanced materials.

Abstract: This research explores the synthesis and application of carbon-based adsorbents derived from olive stones and almond shells as low-cost biomass precursors through carbonization at 600°C combined with chemical activation using KOH, H3PO4 and ZnCl2 with carbon/activating agent (C/A) ratios of 1:2 and 1:4 (w/w) at 850°C for the removal of Cu2+ and Pb2+ ions from aqueous solutions. The carbons produced were characterized using different techniques including SEM-EDX, FTIR, XRD, BET analysis, CHNS elemental analysis and point of zero charge determination. Batch-mode adsorption experiments were carried out at adsorbent doses of 2 and 5 g L-1, initial metal concentrations of 100 and 500 mg L-1 and natural pH (around 5) with agitation at 350 rpm and 25°C for 24 h. KOH-activated carbons, especially at a 1:4 (w/w) ratio, exhibited superior adsorption performance mainly due to their favorable surface characteristics and functionalities. The greatest adsorption efficiency reached 100% (101.41-101.68 mg g-1) for Pb2+ at 500 mg L-1 and 5 g L-1 dosage, and 84.63-86.29% (41.69-42.52 mg g-1) for Cu2+ at 100 mg L-1 and 2 g L-1 dosage. The results of this study will help advance knowledge in the design and optimization of adsorption processes for heavy metal removal, benefiting industries seeking green technologies to mitigate environmental pollution.