REELIN ameliorates Alzheimer's disease, but how?

Alzheimer's disease (AD) is the most prevalent type of dementia; therefore, there is a high demand for therapeutic medication targeting it. In this context, extensive research has been conducted to identify molecular targets for drugs. AD manifests through two primary pathological signs: senile plaques and neurofibrillary tangles, caused by accumulations of amyloid-beta (Aß) and phosphorylated tau, respectively. Thus, studies concerning the molecular mechanisms underlying AD etiology have primarily focused on Aß generation and tau phosphorylation, with the anticipation of uncovering a signaling pathway impacting these molecular processes. Over the past two decades, studies using not only experimental model systems but also examining human brains have accumulated fragmentary evidences suggesting that REELIN signaling pathway is deeply involved in AD. Here, we explore REELIN signaling pathway and its involvement in memory function within the brain and review studies investigating molecular connections between REELIN signaling pathway and AD etiology. This review aims to understand how the manipulation (activation) of this pathway might ameliorate the disease's etiology.

Non-coding RNAs as key regulators of Gasdermin-D mediated pyroptosis in cancer therapy.

Pyroptosis is an inflammatory programed cell death process that plays a crucial role in cancer therapeutic, while Gasdermin-D is a critical effector protein for pyroptosis execution. This review discusses the intricate interactions between Gasdermin-D and some non-coding RNAs (lncRNA, miRNA, siRNA) and their potential application in the regulation of pyroptosis as an anticancer therapy. Correspondingly, these ncRNAs significantly implicate in Gasdermin-D expression and function regarding the pyroptosis pathway. Functioning as competing endogenous RNAs (ceRNAs), these ncRNAs might regulate Gasdermin-D at the molecular level, underlying fatal cell death caused by cancer and tumor propagation. Therefore, these interactions appeal to therapeutics, offering new avenues for cancer treatment. It address this research gap by discussing the possible roles of ncRNAs as mediators of gasdermin-D regulation. It suggest therapeutic strategies based on the current research findings to ensure the interchange between the ideal pyroptosis and cancer cell death.

A Review on the Driving Forces in the Formation of Bioactive Molecules-Loaded Prolamin-Based Particles.

Prolamin-based particles loaded with bioactive molecules have attracted widespread attention from scientists due to their novel properties in chemistry, physics, and biology. In the self-assembly process of biopolymer-based nanocapsules, noncovalent interactions are the main driving forces for reducing bulk materials to the nanoscale and controlling the release of bioactive molecules. This article reviews the types of interaction forces, binding strength, binding active sites, molecular orientation, and binding affinity that affect the release profile of bioactive molecules during the preparation of protein stabilizer particles. Different preparation formulations, the use of different biopolymers, the inherent nature of the loaded bioactive molecules, and external factors (including pH, biopolymer concentration, temperature, salt, ultrasonication, and atmospheric cold plasma treatment) lead to different types and strengths of intra- and intermolecular interactions. Strategies, such as pH, ultrasonication, and atmospheric cold plasma, to change the protein conformation are key to improving the binding strength between proteins and bioactive substances or stabilizers. This review provides some guidance for scientists and technicians dedicated to improving loading efficiency, delaying release, enhancing colloidal stability, and exploring the binding behavior among proteins, stabilizers, and bioactive molecules.

Unconventional Luminescence Polymer with Color-Tunability based on Solvent-induced Electrostatic Potential Distribution of Fluorophore.

Tuning the full-color emission of polymers holds significant promise. However, preparing unconventional luminescence polymers with color-tunability in dilute solution and understanding the relationship between non-covalent interactions and luminescent behavior remains a great challenge. We report two emitters (P1 and P2) incorporating tetracoordinate boron. The P1 with non-conjugated D-π-A structure, exhibited red delayed fluorescence at 645 nm with quantum yield of 9.15% in aggregates. Notably, the emission wavelength of P1 can be tuned from 418 to 588 nm at different solvent. Similarly, the emission wavelength of P2 can also be adjusted by manipulating the interactions between the solvent and fluorophore. Experimental characterization and theoretical calculations indicate that the B←N bond and electronic interactions between solvent and fluorophore significantly regulate the equilibrium the electrostatic potential (ESP) and the intramolecular O···O interactions of P1, thereby modulating its emission wavelength. Additionally, these polymers showed excellent potential in fluoride ions detection. This work provides new insights into the complex effects of intermolecular interactions on luminescent properties.

Effects of probiotics fermentation on physicochemical properties of plum (Pruni domesticae semen) seed protein-based gel.

The plum seed protein isolates (PSPI) were used to prepare a gel by probiotics fermentation. The effects of fermentation time (from 0 to 12 h) on the physicochemical properties of PSPI gel were evaluated. The results showed that PSPI started to form a gel after 6 h of fermentation, as evidenced by a decrease in pH from 6.6 to 5.2, an increase in particle size from 10 µm to 40 µm, appearance of a new peak with retention time of 10 min in gel filtration high-performance liquid chromatography, and formation of aggregation and porous structure observed by fluorescence and scanning electron microscope. The PSPI gel from 9 h of fermentation exhibited the highest viscosity (318 Pa.s), storage modulus (18,000 Pa), water holding capacity (37 %), and gel strength (21.5 g) due to stronger molecular interactions such as hydrogen bond, electrostatic, hydrophobic interaction and disulfide bond. However, increasing fermentation time over 9 h led to disrupture of PSPI gel. Furthermore, the subunit around 15 kDa of PSPI disappeared after fermentation, indicating that the formation of PSPI gel was induced by both acidification and partial hydrolysis. Our results suggest that PSPI can provide an alternative for developing plant-based gel products.

Tuning Ferulic Acid Solubility in Choline-Chloride- and Betaine-Based Deep Eutectic Solvents: Experimental Determination and Machine Learning Modeling.

Deep eutectic solvents (DES) represent a promising class of green solvents, offering particular utility in the extraction and development of new formulations of natural compounds such as ferulic acid (FA). The experimental phase of the study undertook a systematic investigation of the solubility of FA in DES, comprising choline chloride or betaine as hydrogen bond acceptors and six different polyols as hydrogen bond donors. The results demonstrated that solvents based on choline chloride were more effective than those based on betaine. The optimal ratio of hydrogen bond acceptors to donors was found to be 1:2 molar. The addition of water to the DES resulted in a notable enhancement in the solubility of FA. Among the polyols tested, triethylene glycol was the most effective. Hence, DES composed of choline chloride and triethylene glycol (TEG) (1:2) with added water in a 0.3 molar ration is suggested as an efficient alternative to traditional organic solvents like DMSO. In the second part of this report, the affinities of FA in saturated solutions were computed for solute-solute and all solute-solvent pairs. It was found that self-association of FA leads to a cyclic structure of the C28 type, common among carboxylic acids, which is the strongest type of FA affinity. On the other hand, among all hetero-molecular bi-complexes, the most stable is the FA-TEG pair, which is an interesting congruency with the high solubility of FA in TEG containing liquids. Finally, this work combined COSMO-RS modeling with machine learning for the development of a model predicting ferulic acid solubility in a wide range of solvents, including not only DES but also classical neat and binary mixtures. A machine learning protocol developed a highly accurate model for predicting FA solubility, significantly outperforming the COSMO-RS approach. Based on the obtained results, it is recommended to use the support vector regressor (SVR) for screening new dissolution media as it is not only accurate but also has sound generalization to new systems.

An Insight into the Molecular Electronic Structure of Graphene Oxides and Their Interactions with Molecules of Different Polarities Using Quantum Chemical and COSMO-RS Calculations.

A systematic theoretical study on the molecular electronic structure of graphene and its oxides, including their interactions with molecular species of different polarity, was carried out. The influence of the O/C atomic ratio in the graphene oxides was also evaluated. Quantum chemical and COSMO-based statistical-thermodynamic calculations were performed. Geometry optimizations demonstrated that graphene sheets are structurally distorted by oxygen substitution, although they show high resistance to deformation. Furthermore, under axial O-C bonding, proton-donor and proton-acceptor centers are created on the graphene oxide surface, which could acquire an amphoteric character. In low-oxidized graphene oxides, H-bonding centers coexist with neutral highly polarizable π electron clouds. Deep graphene oxidation is also related to the formation of a quasi-two-dimensional H-bond network. These two phenomena are responsible for the exceptional adsorption and catalytic properties and the potential proton conductivity of graphene oxides. The current calculations demonstrated that the interactions of polar molecular species with deep-oxidized graphene derivatives are thermodynamically favorable, but not with low-oxidized ones. The capacity of the quantum chemical and COSMO-RS calculations to model all these issues opens the possibility of selecting or designing graphene-based materials with optimized properties for specific applications. Also, they are valuable in selecting/designing solvents with good exfoliant properties with respect to certain graphene derivatives.

Design and Optimization of Molecularly Imprinted Polymer Targeting Epinephrine Molecule: A Theoretical Approach.

Molecularly imprinted polymers (MIPs) are a growing highlight in polymer chemistry. They are chemically and thermally stable, may be used in a variety of environments, and fulfill a wide range of applications. Computer-aided studies of MIPs often involve the use of computational techniques to design, analyze, and optimize the production of MIPs. Limited information is available on the computational study of interactions between the epinephrine (EPI) MIP and its target molecule. A rational design for EPI-MIP preparation was performed in this study. First, density functional theory (DFT) and molecular dynamic (MD) simulation were used for the screening of functional monomers suitable for the design of MIPs of EPI in the presence of a crosslinker and a solvent environment. Among the tested functional monomers, acrylic acid (AA) was the most appropriate monomer for EPI-MIP formulation. The trends observed for five out of six DFT functionals assessed confirmed AA as the suitable monomer. The theoretical optimal molar ratio was 1:4 EPI:AA in the presence of ethylene glycol dimethacrylate (EGDMA) and acetonitrile. The effect of temperature was analyzed at this ratio of EPI:AA on mean square displacement, X-ray diffraction, density distribution, specific volume, radius of gyration, and equilibrium energies. The stability observed for all these parameters is much better, ranging from 338 to 353 K. This temperature may determine the processing and operating temperature range of EPI-MIP development using AA as a functional monomer. For cost-effectiveness and to reduce time used to prepare MIPs in the laboratory, these results could serve as a useful template for designing and developing EPI-MIPs.

Molecular Interaction Mechanisms Between Lubricant-Infused Slippery Surfaces and Mussel-Inspired Polydopamine Adhesive and DOPA Moiety.

Lubricant-infused slippery surfaces have recently emerged as promising antifouling coatings, showing potential against proteins, cells, and marine mussels. However, a comprehensive understanding of the molecular binding behaviors and interaction strength of foulants to these surfaces is lacking. In this work, mussel-inspired chemistry based on catechol-containing chemicals including 3,4-dihydroxyphenylalanine (DOPA) and polydopamine (PDA) is employed to investigate the antifouling performance and repellence mechanisms of fluorinated-based slippery surface, and the correlated interaction mechanisms are probed using atomic force microscopy (AFM). Intermolecular force measurements and deposition experiments between PDA and the surface reveal the ability of lubricant film to inhibit the contact of PDA particles with the substrate. Moreover, the binding mechanisms and bond dissociation energy between a single DOPA moiety and the lubricant-infused slippery surface are quantitatively investigated employing single-molecule force spectroscopy based on AFM (SM-AFM), which reveal that the infused lubricant layer can remarkably influence the dissociation forces and weaken the binding strength between DOPA and underneath per-fluorinated monolayer surface. This work provides new nanomechanical insights into the fundamental antifouling mechanisms of the lubricant-infused slippery surfaces against mussel-derived adhesive chemicals, with important implications for the design of lubricant-infused materials and other novel antifouling platforms for various bioengineering and engineering applications.

Design of deep eutectic solvents for multiple perfluoroalkyl substances removal: Energy-based screening and mechanism elucidation.

The current landscape of perfluoroalkyl substances (PFAS) extraction methodologies presents significant challenges, particularly for multiple PFAS with different carbon chain lengths. This study introduced an energy-driven strategic approach for screening deep eutectic solvents (DESs) to effectively remove a diverse range of PFAS, including perfluoroalkylcarboxylic acids (PFCAs), perfluoroalkanesulfonic acids (PFSAs), and perfluoroalkyl amides (FAAs), from contaminated environments (total 13 target compounds). Utilizing energy-based screening, we identified DES candidates with high affinity for a spectrum of PFAS compounds from 1234 potential starting materials of eutectic systems. Key findings revealed the superior removal efficiency of tributylphosphineoxide/2-methylpiperazine system, exceeding 99 % for various PFAS with different carbon chain lengths in real environmental water samples. Additionally, we elucidated the molecular interactions between DESs and PFAS through ab initio molecular dynamics (AIMD) simulations, providing valuable insights into the mechanisms governing the removal process. The mechanism of extraction involves hydrogen bond network topology and structural organization, with DESs capable of extracting PFAS while maintaining a weakly aggregated state of target molecules and minimizing the impact on the intrinsic structures of DES. The proposed system forms a dynamic, complementary, and flexible non-covalent interaction network structure with PFAS. The study advances the understanding of DES as a designable, effective, and sustainable alternative to conventional solvents for PFAS remediation, offering a significant contribution to environmental chemistry and green technology.

Transcriptome-Wide Association Study Reveals New Molecular Interactions Associated with Melanoma Pathogenesis.

A transcriptome-wide association study (TWAS) was conducted on genome-wide association study (GWAS) summary statistics of malignant melanoma of skin (UK Biobank dataset) and The Cancer Genome Atlas-Skin Cutaneous Melanoma (TCGA-SKCM) gene expression weights to identify melanoma susceptibility genes. The GWAS included 2465 cases and 449,799 controls, while the gene expression testing was conducted on 103 cases. Afterward, a gene enrichment analysis was applied to identify significant TWAS associations. The melanoma's gene-microRNA (miRNA) regulatory network was constructed from the TWAS genes and their corresponding miRNAs. At last, a disease enrichment analysis was conducted on the corresponding miRNAs. The TWAS detected 27 genes associated with melanoma with p-values less than 0.05 (the top three genes are LOC389458 (RBAK), C16orf73 (MEIOB), and EIF3CL). After the joint/conditional test, one gene (AMIGO1) was dropped, resulting in 26 significant genes. The Gene Ontology (GO) biological process associated the extended gene set (76 genes) with protein K11-linked ubiquitination and regulation of cell cycle phase transition. K11-linked ubiquitin chains regulate cell division. Interestingly, the extended gene set was related to different skin cancer subtypes. Moreover, the enriched pathways were nsp1 from SARS-CoV-2 that inhibit translation initiation in the host cell, cell cycle, translation factors, and DNA repair pathways full network. The gene-miRNA regulatory network identified 10 hotspot genes with the top three: TP53, BRCA1, and MDM2; and four hotspot miRNAs: mir-16, mir-15a, mir-125b, and mir-146a. Melanoma was among the top ten diseases associated with the corresponding (106) miRNAs. Our results shed light on melanoma pathogenesis and biologically significant molecular interactions.

Advancing molecular understanding in high moisture extrusion for plant-based meat analogs: Challenges and perspectives.

In recent years, meat analogs based on plant proteins have received increasing attention. However, the process of high moisture extrusion (HME), the method for their preparation, has not been thoroughly explored, particularly in terms of elucidating the complex interactions that occur during extrusion, which remain challenging. These interactions arise from the various ingredients added during HME, including proteins, starches, edible gums, dietary fibers, lipids, and enzymes. These ingredients undergo intricate conformational changes and interactions under extreme conditions of high temperature, pressure, and shear, ultimately forming the fibrous structure of meat analogs. This review offers a overview of these ingredients and the molecular interaction changes they undergo during the extrusion process. Additionally, it delves into the major molecular interactions such as disulfide bonding, hydrogen bonding, and hydrophobic interactions, providing detailed insights into each.

Enhancing optimal molecular interactions during food processing to design starch key structures for regulating quality and nutrition of starch-based foods: an overview from a synergistic regulatory perspective.

Charting out personalized and/or optimized diets offers new opportunities in the field of food science, although with inherent challenges. Starch-based foods are a major component of daily energy intake in humans. In addition to being rich in starch, starchy foods also contain a multitude of bioactive substances (e.g., polyphenols, lipids). Food processing including storage affects the consistency and interactions between starch and other food components, which can affect the quality and nutritional characteristics of starch-based foods. This review describes the effects of interactions between starch and other components on the structural evolution of starch during food processing. We ponder upon how the evolution of starch molecular structure affects the quality and nutritional characteristics of starch-based foods vis-a-vis the structure-property relationship. Furthermore, we formulate best practices in processing starchy food to retain the quality and nutritional value by rationally designing starch structural domains. Interestingly, we found that inhibiting the formation of a crystalline structures while promoting the formation of short-range ordered structures and nano-aggregates can synchronously slow down its digestion and retrogradation properties, thus improving the quality and nutritional characteristics of starch-based food. This review provides theoretical guidelines for new researchers and food innovators of starch-based foods.

On the Structure, Stability, and Cell Uptake of Nanostructured Lipid Carriers for Drug Delivery.

The efficacy of nanostructured lipid carriers (NLC) for drug delivery strongly depends on their stability and cell uptake. Both properties are governed by their compositions and internal structure. To test the effect of the lipid composition of NLC on cell uptake and stability, three kinds of liquid lipids with different degrees of unsaturation are employed. After ensuring homogeneous size distributions, the thermodynamic characteristics, stability, and mixing properties of NLC are characterized. Then the rates and predominant pathways of cell uptake are determined. Although the same surfactant is used in all cases, different uptake rates are observed. This finding contradicts the view that the surface properties of NLC are dominated by the surfactant. Instead, the uptake rates are explained by the structure of the nanocarrier. Depending on the mixing properties, some liquid lipids remain inside the nanocarrier, while other liquid lipids are present on the surface. Nanocarriers with liquid lipids on the surface are taken up more readily by the cells. This shows that the engineering of efficient lipid nanocarriers requires a delicate balance of interactions between all components of the nanocarrier on the molecular level.

Design and Characterization of a Novel Core-Shell Nano Delivery System Based on Zein and Carboxymethylated Short-Chain Amylose for Encapsulation of Curcumin.

Curcumin is a naturally occurring hydrophobic polyphenolic compound with a rapid metabolism, poor absorption, and low stability, which severely limits its bioavailability. Here, we employed a starch-protein-based nanoparticle approach to improve the curcumin bioavailability. This study focused on synthesizing nanoparticles with a zein "core" and a carboxymethylated short-chain amylose (CSA) "shell" through anti-solvent precipitation for delivering curcumin. The zein@CSA core-shell nanoparticles were extensively characterized for physicochemical properties, structural integrity, ionic stability, in vitro digestibility, and antioxidant activity. Fourier-transform infrared (FTIR) spectroscopy indicates nanoparticle formation through hydrogen-bonding, hydrophobic, and electrostatic interactions between zein and CSA. Zein@CSA core-shell nanoparticles exhibited enhanced stability in NaCl solution. At a zein-to-CSA ratio of 1:1.25, only 15.7% curcumin was released after 90 min of gastric digestion, and 66% was released in the intestine after 240 min, demonstrating a notable sustained release effect. Furthermore, these nanoparticles increased the scavenging capacity of the 1,1-diphenyl-2-picrylhydrazyl (DPPH•) free radical compared to those composed solely of zein and were essentially nontoxic to Caco-2 cells. This research offers valuable insights into curcumin encapsulation and delivery using zein@CSA core-shell nanoparticles.

Understanding regulating effects of protein-anionic octenyl succinic anhydride-modified starch interactions on the structural, rheological, digestibility and release properties of starch.

BACKGROUND: Proteins and anionic octenyl succinic anhydride (OSA)-modified starch (OSA-starch) are common ingredients in food systems. The interactions between OSA-starch and protein are found to alter the structural and functional properties of the protein-OSA-starch complexes. In this regard, the close understanding of the relationship among the molecular interactions between whey protein isolate (WPI) and OSA-high amylose corn starch (HAS), structure changes and rheological, digestibility and release properties of WPI-OSA-HAS was investigated. RESULTS: The molecular interactions of WPI-OSA-HAS were significant for increasing the surface rough, solubility, storage modulus and loss modulus, but decreasing the R1047/1022 values. For the nutritional evaluation, the anti-digestibility of WPI-OSA-HAS was enhanced with increased resistant starch + slowly digestible starch contents and decreased equilibrium hydrolysis percentage and kinetic constant. During the digestion, part of the starch granule, OSA groups and WPI were lost, but the loss was lower than for OSA-HAS. Furthermore, the results of curcumin-loaded WPI-OSA-HAS in simulated gastrointestinal fluids demonstrated that curcumin could be gradually released to simulate colonic fluid. Notably, the interaction between WPI and OSA-HAS depended on the WPI concentration with the stronger molecular interactions obtained at 35% concentration. CONCLUSION: These results provided important information concerning how to adjust the rheological, anti-digestibility and release properties of WPI-OSA-HAS through altering the electrostatic interactions and hydrophobic interactions of WPI-OSA-HAS. © 2024 Society of Chemical Industry.

Effects of inulin with different polymerization degrees on the structural and gelation properties of potato protein.

This study investigated the effect of inulin with different polymerization degrees (DP), including L-inulin (DP 2-6), M-inulin (DP 10-23) and H-inulin (DP 23-46), on the structural and gelation properties of potato protein isolate (PPI). Results revealed that textural properties (hardness, cohesiveness, springiness and chewiness) and water-holding capacity (WHC) of PPI-inulin composite gels were positively correlated with the inulin DP and addition content at 0-1.5% (w/v), but deteriorated at 2% due to phase separation. The addition of 1.5% H-inulin showed the most significant increment effects on the WHC (18.65%) and hardness (2.84 N) of PPI gel. Furthermore, M-/H-inulin were more effective in increasing the whiteness and surface hydrophobicity, as well as in strengthening hydrogen bonds and hydrophobic interactions than L-inulin. Fourier transform infrared spectroscopy analysis and microstructural observation indicated that inulin with higher DP promoted more generation of ß-sheet structures, and leading to the formation of stronger and finer network structures.

Neighborhood based computational approaches for the prediction of lncRNA-disease associations.

MOTIVATION: Long non-coding RNAs (lncRNAs) are a class of molecules involved in important biological processes. Extensive efforts have been provided to get deeper understanding of disease mechanisms at the lncRNA level, guiding towards the detection of biomarkers for disease diagnosis, treatment, prognosis and prevention. Unfortunately, due to costs and time complexity, the number of possible disease-related lncRNAs verified by traditional biological experiments is very limited. Computational approaches for the prediction of disease-lncRNA associations allow to identify the most promising candidates to be verified in laboratory, reducing costs and time consuming. RESULTS: We propose novel approaches for the prediction of lncRNA-disease associations, all sharing the idea of exploring associations among lncRNAs, other intermediate molecules (e.g., miRNAs) and diseases, suitably represented by tripartite graphs. Indeed, while only a few lncRNA-disease associations are still known, plenty of interactions between lncRNAs and other molecules, as well as associations of the latters with diseases, are available. A first approach presented here, NGH, relies on neighborhood analysis performed on a tripartite graph, built upon lncRNAs, miRNAs and diseases. A second approach (CF) relies on collaborative filtering; a third approach (NGH-CF) is obtained boosting NGH by collaborative filtering. The proposed approaches have been validated on both synthetic and real data, and compared against other methods from the literature. It results that neighborhood analysis allows to outperform competitors, and when it is combined with collaborative filtering the prediction accuracy further improves, scoring a value of AUC equal to 0966. AVAILABILITY: Source code and sample datasets are available at: https://github.com/marybonomo/LDAsPredictionApproaches.git.

Temperature effects and molecular insights towards the optimization of polyvinyl alcohol as adsorbent of organic pollutants from aqueous solution.

One of the easier methods of wastewater treatment is adsorption due to its simplicity in implementation, environmental friendliness, and economic feasibility. Polyvinyl alcohol (PVA) looks promising as an adsorbent due to its biocompatible, non-toxic, water-soluble and eco-friendly nature. The investigation of PVA for its potential in the adsorption of pollutants has been reported in many studies but the mechanistic understanding of the adsorption is poor. The present study used a theoretical approach through density functional theory and Monte Carlo with molecular dynamics simulations to investigate the adsorption mechanism behaviors of model organic molecules (bromothymol blue (BTB), methylene blue (MB), metronidazole (MNZ) and tetracycline (TC)) on PVA surface. The quantum chemical calculations result showed that with the increase in PVA chains (2, 4, 8, 16, and 32 units), the zero-point energy decreases (from -308.79 to -4922.93 kcal/mol) while the dipole moment increases (from 4.37 to 87.52 Debye). Temperature effect on the PVA chain structures showed the same trends for all the chain units and with the increase in temperature (50-600 K), there are no appreciable changes in zero-point energy, enthalpy energy increases while Gibbs free energy decreases. Considering PVA-pollutant complexes, the effects of temperature on the structures showed that there are no appreciable changes in the zero-point energy, Gibbs free and thermal energies increase with an increase in temperature while the kinetic rate of reactions decreases with an increase in temperature. The enthalpy of the reaction showed different trends with antibiotic and dye complexes. In all the thermodynamic properties investigated and the rate of reaction, the order of affinity of the pollutants with PVA followed TC > MNZ > MB > BTB. Monte Carlo simulation was used to investigate the adsorption behavior of the pollutants on the surface of PVA. The negative adsorption energies (-366.56 to -2266.81 kcal/mol) in terms of affinity towards the pollutants on the surface of PVA followed the sequence TC > MNZ > BTB > MB and the molecular dynamic simulation results followed the same order. The obtained results give valuable insights into the mechanism and performance of PVA as an adsorbent. Most of these computational observations are in good agreement with the available experimental results.

Effects of OSA-starch-fatty acid interactions on the structural, digestibility and release characteristics of high amylose corn starch.

This study investigated the effects of octenyl succinic anhydride (OSA)-starch-fatty acid (FA) interactions on the structural, digestibility and release characteristics of high amylose corn starch (HAS). FTIR and XRD analysis showed that the hydrophobic interaction between HAS and FA promoted the covalent binding between OSA and HAS. With the increasing of the FA chain length, the complex index, degree of substitution, R1047/1022 and relative crystallinity of OSA-HAS-FA increased first and then decreased, whereas the first-order rate coefficient and percentage of digested in infinite time showed an opposite trend. Structural changes and the molecular interactions of OSA-HAS-FA with 12­carbon FA resulted in highest resistant starch content (45.43%) and encapsulation efficiency of curcumin (Cur) (47.98%). In vitro release test revealed that Cur could be gradually released from OSA-HAS-FA in simulated gastric, intestinal and colonic fluids. Results provided novel insights into HAS-FA complex grafted with OSA as carrier for colon-specific of functional materials.