Project description:With the development and application of nanomaterials, their impact on the environment and organisms has attracted attention. As a common nanomaterial, nano-titanium dioxide (nano-TiO2) has adsorption properties to heavy metals in the environment. Quantitative structure-activity relationship (QSAR) is often used to predict the cytotoxicity of a single substance. However, there is little research on the toxicity of interaction between nanomaterials and other substances. In this study, we exposed human renal cortex proximal tubule epithelial (HK-2) cells to mixtures of eight heavy metals with nano-TiO2, measured absorbance values by CCK-8, and calculated cell viability. PLS and two ensemble learning algorithms are used to build multiple QSAR models for data sets, and the test set R2 is increased from 0.38 to 0.78 and 0.85, and RMSE is decreased from 0.18 to 0.12 and 0.10. After selecting the better random forest algorithm, the K-means clustering algorithm is used to continue to optimize the model, increasing the test set R2 to 0.95 and decreasing the RMSE to 0.08 and 0.06. As a reliable machine algorithm, random forest can be used to predict the toxicity of the mixture of nano-metal oxides and heavy metals. The cluster analysis can effectively improve the stability and predictability of the model, and provide a new idea for the prediction of cytotoxicity model in the future.
Project description:Metal oxide nanoparticles (MONPs) are widely used in medicine and environmental remediation because of their unique properties. However, their size, surface area, and reactivity can cause toxicity, potentially leading to oxidative stress, inflammation, and cellular or DNA damage. In this study, a nano-quantitative structure-toxicity relationship (nano-QSTR) model was initially developed to assess zebrafish toxicity for 24 MONPs. Previously established 23 first- and second-generation periodic table descriptors, along with five newly proposed third-generation descriptors derived from the periodic table, were employed. Subsequently, to enhance the quality and predictive capability of the nano-QSTR model, a nano-quantitative read across structure-toxicity relationship (nano-qRASTR) model was created. This model integrated read-across descriptors with modeled descriptors from the nano-QSTR approach. The nano-qRASTR model, featuring three attributes, outperformed the previously reported simple QSTR model, despite having one less MONP. This study highlights the effective utilization of the nano-qRASTR algorithm in situations with limited data for modeling, demonstrating superior goodness-of-fit, robustness, and predictability (R 2 = 0.81, Q 2 LOO = 0.70, Q 2 F1/R 2 PRED = 0.76) compared to simple QSTR models. Finally, the developed nano-qRASTR model was applied to predict toxicity data for an external dataset comprising 35 MONPs, addressing gaps in zebrafish toxicity assessment.
Project description:Soil contamination with heavy metals presents a substantial environmental peril, necessitating the exploration of innovative remediation approaches. This research aimed to investigate the efficiency of nano-silica in stabilizing heavy metals in a calcareous heavy metal-contaminated soil. The soil was treated with five nano-silica levels of 0, 100, 200, 500, and 1000 mg/kg and incubated for two months. The results showed that nano-silica had a specific surface area of 179.68 m2/g . At 1000 mg/kg, the DTPA-extractable concentrations of Pb, Zn, Cu, Ni, and Cr decreased by 12%, 11%, 11.6%, 10%, and 9.5% compared to the controls, respectively. Additionally, as the nano-silica application rate increased, both soil pH and specific surface area increased. The augmentation of nano-silica adsorbent in the soil led to a decline in the exchangeable (EX) and carbonate-bound fractions of Pb, Cu, Zn, Ni, and Cr, while the distribution of heavy metals in fractions bonded with Fe-Mn oxides, organic matter, and residue increased. The use of 1000 mg/kg nano-silica resulted in an 8.0% reduction in EX Pb, 4.5% in EX Cu, 7.3% in EX Zn, 7.1% in EX Ni, and 7.9% in EX Cr compared to the control treatment. Overall, our study highlights the potential of nano silica as a promising remediation strategy for addressing heavy metal pollution in contaminated soils, offering sustainable solutions for environmental restoration and ecosystem protection.
Project description:In this study, Bi2WO6/mesoporous TiO2 nanotube composites (BWO/TNTs) were successfully synthesized to remove the heavy metal Cr(vi) and refractory organic compound dibutyl phthalate (DBP) from contaminated water under visible light. Coupling TNTs with BWO can greatly improve the photocatalytic activity of the catalyst for treating Cr(vi)-DBP mixed pollutants because of synergetic effects from Cr(vi) and DBP. Specifically, the visible-light photocatalytic activities of 3% BWO/TNTs for removing DBP and Cr(vi) from mixed pollutant solutions were 10.8 and 3.8 times higher than those of BWO. Firstly, this system can take full advantage of charge carriers and can spatially separate reduction sites and oxidation sites in the photocatalyst. Secondly, TNTs has a unique multiscale channel structure that can enhance mass transfer and light utilization. These characteristics lead to very obvious photocatalytic activity improvements. In addition, the BWO/TNTs composite photocatalysts exhibited excellent stability and durability under visible and UV light irradiation. This work demonstrated a feasible method for fabricating composite photocatalysts and applied them to the simultaneous removal of heavy metal and refractory organic pollutants from contaminated water.
Project description:Overall photocatalytic water splitting is one of the most sought after processes for sustainable solar-to-chemical energy conversion. The efficiency of this process strongly depends on charge carrier recombination and interaction with surface adsorbates at different time scales. Here, we investigated how hydration of TiO2 P25 affects dynamics of photogenerated electrons at the millisecond to minute time scale characteristic for chemical reactions. We used rapid scan diffuse-reflectance infrared Fourier transform spectroscopy (DRIFTS). The decay of photogenerated electron absorption was substantially slower in the presence of associated water. For hydrated samples, the charge carrier recombination rates followed an Arrhenius-type behavior in the temperature range of 273-423 K; these became temperature-independent when the material was dehydrated at temperatures above 423 K or cooled below 273 K. A DFT+U analysis revealed that hydrogen bonding with adsorbed water stabilizes surface-trapped holes at anatase TiO2(101) facet and lowers the barriers for hole migration. Hence, hole mobility should be higher in the hydrated material than in the dehydrated system. This demonstrates that adsorbed associated water can efficiently stabilize photogenerated charge carriers in nanocrystalline TiO2 and suppress their recombination at the time scale up to minutes.
Project description:Hybrid poly(ether sulfones) (PES)-TiO2 electrospun mats are used as selective filters to remove lead and zinc ions from water. Presence of TiO2 is functional to trigger fiber's surface charge that allows for better performances in terms of ionic adsorption with respect to bare PES mats. Temperature increase promotes a speed up of ion removal. Ability of electrospun mats to retain adsorbed ions is proven by washing procedures, which confirm the lack of released Pb2+ in solution, even after sonication. To detect presence of metal ions in aqueous solutions, water-soluble porphyrins are used as chemosensors, which are able to provide fast, in-field, and real-time analysis. In particular, cationic H2T4 metalation, occurring both in solution or at transparent glass surface, allows for a straightforward spectrophotometric (UV-vis) detection of metal ions in solution.
Project description:It is important to recognize the great diversity of monosaccharides commonly encountered in animals, plants, and microbes, as well as to organize them in a visually interesting style that also emphasizes their similarities and relatedness. This article discusses the nature of building blocks, monosaccharides, and monosaccharide derivatives-terms commonly used in discussing "glycomolecules" found in nature. To aid in awareness of monosaccharide diversity, here is presented a Periodic Table of Monosaccharides. The rationale is given for construction of the Table and the selection of 103 monosaccharides, which is largely based on those presented in the KEGG and SNFG websites of monosaccharides, and includes room to enlarge as new discoveries are made. The Table should have educational value and is intended to capture the attention and foster imagination of those not very familiar with glycosciences, and encourage researchers to delve deeper into this fascinating area.
Project description:A comprehensive knowledge of the physical and chemical properties of nanomaterials (NMs) is necessary to design them effectively for regulated use. Although NMs are utilized in therapeutics, their cytotoxicity has attracted great attention. Nanoscale quantitative structure-property relationship (nano-QSPR) models can help in understanding the relationship between NMs and the biological environment and provide new ways for modeling the structural properties and bio-toxic effects of NMs. The goal of the study is to construct fully validated property-based models to extract relevant features for estimating and influencing the zeta potential and obtaining the toxicity profile regarding cell damage in the treatment of cancer cells. To achieve this, QSPR modeling was first performed with 18 metal oxide (MeOx) NMs to measure their materials properties using periodic table-based descriptors. The features obtained were later applied for zeta potential calculation (imputation for sparse data) for MeOx NMs that lack such information. To further clarify the influence of the zeta potential on cell damage, a QSPR model was developed with 132 MeOx NMs to understand the possible mechanisms of cell damage. The results showed that zeta potential, along with seven other descriptors, had the potential to influence oxidative damage through free radical accumulation, which could lead to changes in the survival rate of cancerous cells. The developed QSPR and quantitative structure-activity relationship models also give hints regarding safer design and toxicity assessment of MeOx NMs.
Project description:Drawing parallels to the symmetry breaking of atomic orbitals used to explain the periodic table of chemical elements; here we introduce a periodic table of droplet motions, also based on symmetry breaking but guided by a recent droplet spectral theory. By this theory, higher droplet mode shapes are discovered and a wettability spectrometer is invented. Motions of a partially wetting liquid on a support have natural mode shapes, motions ordered by kinetic energy into the periodic table, each table characteristic of the spherical-cap drop volume and material parameters. For water on a support having a contact angle of about 60°, the first 35 predicted elements of the periodic table are discovered. Periodic tables are related one to another through symmetry breaking into a two-parameter family tree.
Project description:In most organisms, transition metal ions are necessary cofactors of ribonucleotide reductase (RNR), the enzyme responsible for biosynthesis of the 2'-deoxynucleotide building blocks of DNA. The metal ion generates an oxidant for an active site cysteine (Cys), yielding a thiyl radical that is necessary for initiation of catalysis in all RNRs. Class I enzymes, widespread in eukaryotes and aerobic microbes, share a common requirement for dioxygen in assembly of the active Cys oxidant and a unique quaternary structure, in which the metallo- or radical-cofactor is found in a separate subunit, β, from the catalytic α subunit. The first class I RNRs, the class Ia enzymes, discovered and characterized more than 30 years ago, were found to use a diiron(III)-tyrosyl-radical Cys oxidant. Although class Ia RNRs have historically served as the model for understanding enzyme mechanism and function, more recently, remarkably diverse bioinorganic and radical cofactors have been discovered in class I RNRs from pathogenic microbes. These enzymes use alternative transition metal ions, such as manganese, or posttranslationally installed tyrosyl radicals for initiation of ribonucleotide reduction. Here we summarize the recent progress in discovery and characterization of novel class I RNR radical-initiating cofactors, their mechanisms of assembly, and how they might function in the context of the active class I holoenzyme complex.