ACS Omega最新文献

A novel organic–inorganic material (C₃H₈N₆)₂ZnCl₄·2Cl was synthesized via a slow evaporation approach and subjected to extensive characterization. Techniques involving X-ray diffraction, SEM/EDX, Hirshfeld surface examination, IR/Raman spectroscopy, thermal behavior (TG/DTG/SDTA and DSC), and electric and dielectric studies were applied. Examination of the crystal structure reveals that the synthesized material adopts a monoclinic system, particularly belonging to the P2₁/c space group with unit cell parameters a = 11.7274(3) Å, b = 6.2155(2) Å, c = 25.7877(8) Å, β = 94.27(1)°, V = 1874.50(4) ų, and Z = 4. Purity confirmation was established via powder X-ray diffraction analysis. Composition verification was conducted using semiquantitative EDXS analysis. The asymmetric unit comprises isolated tetrachlorozincate [ZnCl₄]^2– anions, two (C₃H₈N₆)²⁺ organic cations, and two free chlorine atoms, forming a 0D anionic network. N–H···Cl and N–H···N hydrogen bonding combined to form a 2D hydrogen-bonded network, maintaining crystal stability. Hirshfeld surface analysis elucidated intermolecular interactions, supported by 2D fingerprint plots. IR and Raman spectra analysis corroborated compound characteristics at room temperature. Thermal analysis revealed two phase transitions at 343 and 358 K, consistent with dielectric studies. Impedance spectroscopy highlighted the compound’s electrical properties, confirming thermal transitions. Conductivity studies exhibited an Arrhenius behavior. Frequency-dependent dielectric constant variations and modulus studies underscored grain and grain boundary effects, confirming the effective protonic conduction in the material.

Ammonium (NH₄⁺) concentration is critical to both nutrient availability and nitrogen (N) loss in soil ecosystems but can be highly variable across spatial and temporal scales. For this reason, effectively informing agricultural practices such as fertilizer management and understanding of mechanisms of soil N loss require sensor technologies to monitor ammonium concentrations in real time. Our work investigates the performance of fully printed ammonium ion-selective sensors used in diverse soil environments. Ammonium sensors consisting of a printed ammonium ion-selective electrode and a printed Ag/AgCl reference were fabricated and characterized in aqueous solutions and three different soil types (sand, peat, and clay) under the range of ion concentrations likely to be present in soil (0.01–100 mM). The response of ammonium sensors was further evaluated under variable gravimetric moisture content in the soil to reflect their reliability under field conditions. Ammonium sensors demonstrated a sensitivity of 53.6 ± 5.1 mV/decade when tested in aqueous solution, and a sensitivity of 55.7 ± 11 mV/dec, 57.5 ± 4.1 mV/dec, and 43.7 ± 4 mV/dec was measured in sand, clay, and peat soils, respectively.

In this study, the performance of the cell-penetrating and fusogenic peptide, TAT-HA2, which consists of a cell-permeable HIV trans-activator of transcription (TAT) protein transduction domain and a pH-responsive influenza A virus hemagglutinin protein (HA2) domain, was comparatively evaluated for the first time in peptideplex, multicomponent, and conjugate siRNA delivery systems. TAT-HA2 in all three systems protected siRNA from degradation, except in the conjugate system with a low Peptide/siRNA ratio. The synergistic effect of different peptide domains enhanced the transfection efficiency of multicomponent and conjugate systems compared to that of peptideplexes, which was attributed to the surface configuration of TAT-HA2 peptides depending on the nature of attachment. Particularly, the multicomponent system showed better cellular uptake and endosomal escape than the peptideplexes, resulting in enhanced siRNA delivery in the cytoplasm. In addition, the presence of cleavable disulfide bonds in multicomponent and conjugate systems promoted the effective siRNA delivery in the cytoplasm, resulting in improved gene silencing activity. The multicomponent system reduced the level of luciferase expression in SKOV3 cells to 45% (±4). In contrast, the conjugate system and the commercially available siRNA transfection agent, Lipofectamine RNAiMax, caused luciferase suppression down to 55% (±2) at a siRNA dose of 100 nM. For the same dose, the peptideplex system could only reduce the luciferase expression to 65% (±5). None of the developed systems showed significant toxicity at any dose. Overall, the TAT-HA2 peptide is promising as a siRNA delivery vector; however, its performance depends on the nature of attachment and, as a result, its surface configuration on the developed delivery system.

Interfacial regulation is crucial for the enhancement of the specific surface area and supercapacitive performance in porous carbon materials. However, traditional porous carbon obtained through potassium hydroxide activation is confronted with a complicated preparation process. Herein, hierarchical porous biocarbons (HPBC) were facilely prepared by using the multiscale template method and wheat flour as a precursor without any activation. A spherical SiO₂ template and wheat flour can be closely combined by gelatinization so as to effectively confine and spatially orient carbon materials. Benefiting from the hierarchical porous structure achieved through the use of templates at different sizes, HPBC-3 has the best electrochemical performance of 223.6 F·g^–1 at 1 A·g^–1. Moreover, the assembled HPBC-3//HPBC-3 symmetrical supercapacitor demonstrates a remarkable energy density of 15.6 W h·kg^–1 and exhibits exceptional cycling performance with a capacitance retention rate of 106% after 5000 cycles. The results fully demonstrate the promising application of the obtained hierarchical porous carbon in supercapacitors.

Periodontitis, the chronic inflammation of the periodontal tissues caused by bacteria in plaque, is the leading cause of tooth loss in adults in the world. Currently, periodontitis is effectively treated with mechanical cleaning and the use of antibiotics. However, these treatments only temporarily remove plaque, which can rapidly proliferate and multiply in periodontal pockets over time. Although antibiotics have positive antimicrobial effects, their long-term use increases the risk of the emergence of drug-resistant strains. The emergence of resistant strains reduces the effectiveness of periodontitis treatment and makes the disease more difficult to control. Herein, this paper reports the development of an injectable self-oxygenating composite hydrogel for periodontal therapy, which was produced by loading CaO₂ nanoparticles and ascorbic acid into an injectable alginate hydrogel. CaO₂ can improve the periodontal pocket microenvironment by reacting with water to generate oxygen, calcium ions can be used as a bone regeneration material, and ascorbic acid protects cells. The authors further showed that the composite hydrogel inhibited growth and colonization of anaerobic bacteria, reduced the degree of inflammation, and promoted alveolar bone regeneration. In conclusion, these findings suggest that the composite hydrogel can be used as a biocompatible, convenient, and effective method for periodontitis treatment.

An interesting platform for the construction of novel N,N′-bis(2-(arylazo)-2-(aroyl)vinyl)ethane-1,2-diamines is reported in this work. These bis-arylazo compounds were assembled based on the reaction of ethylenediamine with various 2-arylhydrazono-3-oxopropanals in aqueous conditions under both conventional stirring and microwave conditions at ambient temperature. The factors affecting the optimization conditions were intensively practiced. The structures of the new products were established from their spectroscopic analyses and X-ray single crystals. The photophysical behavior of the bis-arylazo derivatives was examined. The UV–vis spectra showed maximum absorption band in the range of 348–383 nm with molar extinction coefficients ranging from 0.89 × 10⁴ to 4.02 × 10⁴ M^–1 cm^–1. The highest molar absorptivity coefficient (∼45 × 10³ M^–1 cm^–1) was observed in CHCl₃ solvent. The fluorescence properties showed that some compounds were interesting fluorophore materials with high Stokes shifts. The photoluminescence study of some compounds was promising, with maximal emission peaks ranging between 417–436 nm.

Rapid detection of NO₃^–-N is critical to address the challenges of food security, environmental degradation, and climate change. Conventional methods for sensing NO₃^–-N in water demand pretreatments and chemical reagents, which are time- and cost-consuming. Consequently, Fourier transform infrared attenuated total reflectance (FTIR-ATR) spectroscopy has been well applied for the determination of NO₃^–-N. However, the conventional ATR crystals, i.e., zinc selenide (ZnSe) and diamond, showed a weakness in duration or cost since the ZnSe material was relatively soft and diamond was relatively expensive. In this study, comparing with ZnSe-ATR and diamond-ATR, a silicon-based ATR (Si-ATR) accessory was developed and used to explore the applicability and stability for sensing NO₃^–-N combining mathematic algorithms. It was found that partial least-squares regression (PLSR) showed a good performance comparing with the algorithms of principal component analysis (PCA) and linear regression (LR), and it was recommended for quantifying NO₃^–-N. For ZnSe-ATR, the residual prediction deviation (RPD) was more than 1.80, the determination coefficient (R²) was more than 0.7725, and the root-mean-square error (RMSE) was less than 2.73 mg L^–1. For diamond-ATR, the RPD was more than 1.76, the R² was more than 0.7309, and the RMSE was less than 8.22 mg L^–1. For Si-ATR, the RPD was more than 1.42, the R² was 0.5198, and the RMSE was less than 11.02 mg L^–1. It was confirmed that all three types of ATR could be applied in the quantification of NO₃^–-N in water for high nitrate concentrations. However, for the quantification of low nitrate concentrations (0–1 mg L^–1 NO₃^–-N), ZnSe-ATR and diamond-ATR acquired the same accuracy, while Si-ATR had a lower accuracy. The pretreatment of Si-ATR-based spectra using the deconvolution algorithm could improve the prediction accuracy compared to water deduction for predicting low NO₃^–-N. Furthermore, a Si-ATR accessory was developed using Si-ATR, which was reliable for NO₃^–-N concentration quantification in water with the advantage of its low cost and long durability. Totally, samples with high nitrate concentrations implied a more reliable prediction for all crystals, and comprehensively, ZnSe-ATR was recommended for sensing low nitrate concentrations; diamond-ATR was recommended for samples with strong acid or base corrosion; and for sensing relatively high nitrate concentrations, such as in natural water bodies, Si-ATR was more economical because of its low cost and relatively long use life.

Zinc oxide (ZnO) nanoparticles (NPs) are extensively utilized in the commercial and biomedical sectors, posing heightened risks of potential cytotoxicity through various mechanisms. Nonetheless, the regulatory framework governing the gestational toxicity of ZnO NPs and the corresponding intervention strategies remain largely obscure. In this study, using the Drosophila model, we observed that gestational exposure to ZnO NPs led to growth and developmental anomalies in a dose-dependent manner when compared with the control (no ZnO NP exposure). Subsequent dietary administration of Quercetin and Astragaloside IV resulted in effective mitigation of the developmental toxicity induced by exposure to ZnO NPs. Moreover, the latter also triggered activation of the ferroptosis pathway. The associated parameters were successfully ameliorated by the administration of Quercetin and Astragaloside IV. Notably, treatment with Ferrostatin-1 also alleviated developmental disorders arising from exposure to ZnO NPs. In conclusion, our investigation demonstrated that exposure to ZnO NPs during gestation interfered with growth and development via the ferroptosis pathway, underscoring the significance of dietary supplementation with Quercetin and Astragaloside IV for protection against developmental toxicity.

In our study, we aimed to use olive pomace, food industry waste, as biomass to produce biochar nanoparticles. The surface of the biochar was functionalized with the l-histidine ligand, and then cupric acetate was added to prepare Cu-l-histidine@biochar as a final catalyst for the chemo- and homoselective synthesis of amide and aniline derivatives. To characterize the novel catalyst, we employed various techniques. Another notable feature of this catalyst is its reusability, which maintained significant efficiency even after multiple uses in reactions.

Because of their high affinity, specificity, and environmental stability, nanobodies (Nbs) have continuously received attention from the field of biological research. However, it is tough work to obtain high-affinity Nbs using experimental methods. In the current study, 12 machine learning algorithms were compared in parallel to explore the potential patterns between Nb–ligand affinity and eight noncovalent interactions. After model comparison and optimization, four optimized models (SVMrB, RotFB, RFB, and C50B) and two stacked models (StackKNN and StackRF) based on nine uncorrelated (correlation coefficient <0.65) optimized models were selected. All the models showed an accuracy of around 0.70 and high specificity. Compared to the other models, RotFB and RFB were not capable of predicting nonaffinitive Nbs with lower precision (<0.44) but showed higher sensitivity at 0.6761 and 0.3521 and good model robustness (F1 score and MCC values). On the contrary, SVMrB, C50B, and StackKNN were able to effectively predict the future nonaffinitive Nbs (specificity >0.92) and reduce the number of true affinitive Nbs (precision >0.5). On the other hand, StackRF showed intermediate model performance. Furthermore, an in-depth feature analysis indicated that hydrogen bonding and aromatic-associated interactions were the key noncovalent interactions in determining Nb–ligand binding affinity. In summary, the current study provides, for the first time, a tool that can effectively predict whether there is an affinity between nanobodies and their intended ligands and explores the key factors that influence their affinity, which could improve the screening and design process of Nbs and accelerate the development of Nb drugs and applications.