Mechanism of Dye Degradation during Electrochemical Treatment

Studies were conducted for understanding the electrochemical (EC) degradation mechanism of a triphenylmethane dye, namely, basic green 4 (BG), commonly known as malachite green with aluminum electrode. At the optimum conditions (current density = 117.64 A m^–2, initial dye concentration = 125 mg L^–1, pH = 6.5, electrode gap = 1 cm, and NaCl concentration = 1.5 g L^–1), more than 85% BG degradation was observed within 50 min of treatment. UV–visible and Fourier transform infrared (FTIR) spectroscopy, high performance liquid chromatography (HPLC), gas chromatography–mass spectroscopy (GCMS), and high-resolution mass spectroscopy (HRMS) analysis showed that the degradation occurred via the cleavage of conjugated structure and N-demethylation. The intermediate products identified included hydroxymethylated intermediates during the N-demethylation of the dye; and <i>N</i>,<i>N</i>,<i>N</i>′,<i>N</i>′-tetramethyl-4,4′-diaminobenzophenone, 4,4′-bisaminobenzophenone and <i>N</i>-methyl-para-aminophenol after cleavage of the conjugated triphenylmethane ring. Zeta potential study indicated a hard acid–base interaction between aluminum ions and hydroxides generated in situ during the EC treatment process and the −N­(CH₃)₂ group of dye molecules. Generation of active species such as hydrogen peroxide, ozone, and chlorinated oxidizing compounds was observed during the EC treatment process and that the BG degradation occurred via a ^•OH radical attack

Electrochemical Treatment of Dye Bearing Effluent with Different Anode–Cathode Combinations: Mechanistic Study and Sludge Analysis

The present study investigates the electrochemical (EC) treatment of actual dye bearing effluent (DBE) with different combinations of aluminum (Al) and stainless steel (SS) electrodes as anode and cathode. Effects of the current density (<i>j</i>) and pH with different anode–cathode combinations (Al–Al, Al–SS, SS–SS, and SS–Al) were studied. The change in zeta (ζ) potential with current density at different times, and the change in colloid particle diameters at different pH, gave information regarding the potential stability of the colloidal suspension. In addition, specific energy consumption and current efficiency have also been calculated. Maximum color, COD, TOC, and turbidity removal efficiencies were found to be 99.90%, 82.50%, 68.8%, and 98.8%, respectively, at <i>j</i> = 117.64 A/m² and pH 8.5 with the SS–SS electrode combination. Solid residue obtained during EC treatment of DBE was characterized by scanning electron microscopy, energy dispersive X-ray spectroscopy, thermogravimetric analysis, and pore distribution analysis to propose reutilization of the sludge

N‑Heterocyclic Carbene Promoted Decarboxylation of Lignin-Derived Aromatic Acids

Decarboxylation is an important reaction in organic synthesis and drug discovery, which is typically catalyzed by strong bases or metal-based catalysts bearing low yield and selectivity. For the first time, we demonstrated a new strategy of decarboxylation of hydroxyl cinnamic acids such as <i>p</i>-coumaric acid, ferulic acid, sinapinic acid, and caffeic acid in the presence of N-heterocyclic carbene (NHC) precursors (i.e., 1-ethyl-3-methyl imidazolium acetate [C₂C₁Im]­[OAc]), achieving high yields and selectivities up to 100% under relatively mild conditions. [C₂C₁Im]­[OAc] showed excellent recyclability as organocatalysis during three times of recycling using biphasic reaction system. A mechanistic study revealed that the decarboxylation was catalyzed by NHCs that were in-situ generated by self-deprotonation of [C₂C₁Im]­[OAc]. Our demonstrated route is especially appealing for the production of lignin-derived renewable aromatics

MOESM1 of Impact of lignin polymer backbone esters on ionic liquid pretreatment of poplar

Additional file 1: Figure S1. Mass balances during three different IL pretreatments followed by enzymatic hydrolysis

MOESM1 of Hybrid phenolic-inducible promoters towards construction of self-inducible systems for microbial lignin valorization

Additional file 1: Table S1. Oligonucleotides used in this study. Table S2. Nucleotide sequence of promoters used in this study. Table S3. Vanillin induced sub-population of cells with high fluorescence and forward scattering. Table S4. Coumaric acid induced sub-population of cells with high fluorescence and forward scattering. Figure S1. Vector map of the construct utilized to interrogate the strength of the promoters in this study. Based upon the promoter present in the construct, pRIFXX can be pRIF01, pRIF02, pRIF03, or pRIF04. Figure S2. Optical density of the E. coli strains under varying concentrations of vanillic acid and coumaric acid. Figure S3. Flow cytometric analysis of vanillin induced cultures. Figure S4. Flow cytometric analysis of coumaric acid induced cultures

Honokiol causes G₁ phase cell cycle arrest in human pancreatic cancer cells.

<p>MiaPaCa and Panc1cells (1×10⁶ cells/well) were synchronized by culturing in serum free media for 72 h, followed by incubation in serum-containing media for 24 h and subsequent treatment with either honokiol (20, 40 or 60 µM) or DMSO (control) for 24 h. Distribution of cells in different phases of cell cycle was analyzed by propidium iodide (PI) staining followed by flow cytometry. Enhanced accumulation of MiaPaCa and Panc1 cells in the G₁ phase of the cell cycle was observed after treatment with honokiol in a dose-dependent manner (as indicated by flow histograms) with a concomitant decrease in S-phase cells.</p

Physics-Based Machine Learning Models Predict Carbon Dioxide Solubility in Chemically Reactive Deep Eutectic Solvents

Carbon dioxide (CO2) is a detrimental greenhouse gas and is the main contributor to global warming. In addressing this environmental challenge, a promising approach emerges through the utilization of deep eutectic solvents (DESs) as an ecofriendly and sustainable medium for effective CO2 capture. Chemically reactive DESs, which form chemical bonds with the CO2, are superior to nonreactive, physically based DESs for CO2 absorption. However, there are no accurate computational models that provide accurate predictions of the CO2 solubility in chemically reactive DESs. Here, we develop machine learning (ML) models to predict the solubility of CO2 in chemically reactive DESs. As training data, we collected 214 data points for the CO2 solubility in 149 different chemically reactive DESs at different temperatures, pressures, and DES molar ratios from published work. The physics-driven input features for the ML models include σ-profile descriptors that quantify the relative probability of a molecular surface segment having a certain screening charge density and were calculated with the first-principle quantum chemical method COSMO-RS. We show here that, although COSMO-RS does not explicitly calculate chemical reaction profiles, the COSMO-RS-derived σ-profile features can be used to predict bond formation. Of the models trained, an artificial neural network (ANN) provides the most accurate CO2 solubility prediction with an average absolute relative deviation of 2.94% on the testing sets. Overall, this work provides ML models that can predict CO2 solubility precisely and thus accelerate the design and application of chemically reactive DESs

Honokiol suppresses growth of human pancreatic cancer cells.

<p>(<b>A</b>) MiaPaCa and Panc1 cells were seeded in 6 well plate (1×10⁵ cells/well) and allowed to attain 70–80% confluence prior to honokiol (10–60 µM) treatment for 48 h. Following treatment, significant change in cell morphology was observed of both the cell types as examined under phase-contrast microscope. Cells became round, shrunken and detached from cell surface in a dose-dependent manner. Representative micrographs are from one of the random fields of view (magnification 200X) of cells treated with 20, 40 or 60 µM honokiol. (<b>B</b>) MiaPaCa and Panc1 cells were grown in 96 well microtitre plates (1×10⁴ cells /well) and treated with honokiol (10–60 µM) at 70–80% confluence. Percent viability of cells was measured by WST-1 assay after 24, 48 and 72 h. An OD value of control cells (treated with an equal volume of DMSO, final concentration, <0.1%) was taken as 100% viability. Honokiol inhibited cell viability in a dose- and time- dependent manner for both the cell types suggesting anti-tumor effect of honokiol. Data are expressed as mean± SD; (n = 3).</p

Honokiol attenuates constitutive NF-κB activation by inhibiting nuclear translocation of NF-κB/p65 in human pancreatic cancer cells.

<p>(A) MiaPaCa and Panc1cells (0.5×10⁶ cells/well) were seeded in 12-well plate. Next day at 60% confluence, cells were co-transfected with NF-κB luciferase reporter and TK-Renilla luciferase (control) plasmids. Twenty-four hours post-transfection, cells were treated with honokiol (20, 40, or 60 µM) for next 24 h. Protein lysates were made and luciferase (Fire-fly; test and Renilla, transfection efficiency control) activity assessed using a dual-luciferase assay system. Data is presented as normalized fold-change in luciferase activity (mean± SD; n = 3, * p<0.05). (B) Total, nuclear and cytoplasmic extracts were prepared from cells treated with honokiol (20, 40, or 60 µM) for 6 h and expression of NF-κB/p65, p-IκB-α (S32/36) and IκB-α was determined by Western blot analysis. β-actin was used as a loading control. Intensities of the immunoreactive bands were quantified by densitometry. Normalized densitometry values are indicated at the top of the bands indicating a decreased localization of NF-κB/p65 in nucleus with a concomitant increase in cytoplasm. In contrast, expression of p-IκB-α was decreased leading to increased levels of IκB-α. Altogether, these data clearly suggest that honokiol inhibits NF-κB activity through stabilization of IκB-α.</p

Honokiol induces apoptosis in human pancreatic cancer cells.

<p>MiaPaCa and Panc1 cells were grown in 6-well plates (1×10⁶ cells /well) and allowed to attain 70–80% confluence. Cells were treated with either honokiol (20, 40 or 60 µM) or DMSO (control) for 24 h and subsequently stained with 7-AAD and PE Annexin V followed by flow cytometry. The lower left quadrants of each panels show the viable cells (negative for both, PE Annexin V and 7-AAD). The upper right quadrants contain necrotic or late apoptotic cells (positive for both, PE Annexin V and 7-AAD). The lower right quadrants represent the early apoptotic cells (PE Annexin V positive and 7-AAD negative). Data show a dose-dependent increase in the number of apoptotic cells in both MiaPaCa and Panc1 cells after treatment with honokiol as compared to control cells, indicating apoptotis inducing potential of honokiol.</p