Iron hydroxides are important scavengers for dissolved chromium (Cr) via coprecipitation processes; however, the influences of organic matter (OM) on Cr sequestration in Fe/Cr-OM ternary systems and the stability of the coprecipitates are not well understood. Here, Fe/Cr-OM coprecipitation was conducted at pH 3, and Cr hydroxide was undersaturated. Acetic acid (HAc), poly(acrylic acid) (PAA), and Suwannee River natural organic matter (SRNOM) were selected as model OMs, which showed different complexation capabilities with Fe/Cr ions and Fe/Cr hydroxide particles. HAc had no significant effect on the coprecipitation, as the monodentate carboxyl ligand in HAc did not favor complexation with dissolved Fe/Cr ions or Fe/Cr hydroxide nanoparticles. Contrarily, PAA and SRNOM with polydentate carboxyl ligand had strong complexation with Fe/Cr ions and Fe/Cr hydroxide nanoparticles, leading to significant amounts of PAA/SRNOM sequestered in the coprecipitates, which caused the structural disorder and fast aggregation of the coprecipitates. In comparison with that of PAA, preferential complexation of Cr ions with SRNOM resulted in higher Cr/Fe ratios in the coprecipitates. This study advances the fundamental understanding of Fe/Cr-OM coprecipitation and mechanisms controlling the composition and stability of the coprecipitates, which is essential for successful Cr remediation and removal in both natural and engineered settings.
Despite the increasing usage of porphyrinic metal-organic frameworks (MOFs) for combination therapy, the controlled encapsulation of inorganic nanoparticle-based therapeutics into such MOFs with specific structures has remained a major obstacle for improved tumor therapy. Here, we report the synthesis of a mesoporous MOF shell on the surface of gold nanorods (AuNRs), wherein a single AuNR is captured individually in single-crystalline MOFs with a controlled crystallographic orientation, for combinational phototherapy against solid tumors. The core-shell heterostructures have the benefits of a mesoporous structure and photoinduced singlet oxygen generation behavior characterized by the porphyrinic MOF shell, together with the plasmonic photothermal conversion characteristic of AuNRs. We demonstrated that the AuNR@MOF nanoplatform enables an efficient tumor treatment strategy by combining photodynamic therapy and photothermal therapy. We should emphasize that such systems could have applications beyond the field of cancer therapy, like plasmonic harvesting of light energy to induce and accelerate catalytic reactions within MOFs and multifunctional nanocarriers for agricultural formulations.
Peroxymonosulfate (PMS)-based advanced oxidation processes (PMS-AOPs) as an efficient strategy for organic degradation are highly dependent on catalyst design and structured active sites. However, the identification of the active sites and their relationship with reaction mechanisms for organic degradation are not fully understood for a composite catalyst due to the complex structure. Herein, we developed a family of Co encapsulated in N-doped carbons (Co-PCN) with tailored types and contents of active sites via manipulated pyrolysis for PMS activation and ciprofloxacin (CIP) degradation, focusing on the correlation of active sites to generated reactive species and degradation routes of organics. The structure–function relationships between the different active sites in Co-PCN catalysts and reactive oxygen species (ROS), as well as bond breaking position of CIP, were revealed through regression analysis and density functional theory calculation. Co–Nx, O–C═O, C═O, graphitic N, and defects in Co-PCN stimulate the generation of 1O2 for oxidizing the C–C bond in the piperazine ring of CIP into C═O. The substitution of F by OH and hydroxylation of the piperazine ring might be induced by SO4•– and •OH, whose formation was affected by C–O, Co(0), Co–Nx, graphitic N, and defects. The findings provided new insights into reaction mechanisms in PMS-AOP systems and rational design of catalysts for ROS-oriented degradation of pollutants.
The purpose of this study was to examine the daily social pressure and socioeconomic factors related to women’s alcohol consumption in China. Cross-sectional data were obtained from the 2012 China Family Panel Studies. A multivariate logistic regression analysis of a sample of 16 339 female adults with the mean age of 45.3 years was used to examine the relationships between dependent and independent variables. According to the results, first, the greater the daily social pressure, the more likely women were to engage in general alcohol consumption (odds ratio = 1.061) and risk drinking (odds ratio = 1.057). Second, while there is a positive relationship between the general level of social pressure and women’s alcohol consumption, the relationship between the severe level of social pressure and women’s alcohol consumption was not significant. Finally, women in the Central region were less likely to engage in risk drinking than women in the Western region; women with secondary school education were more likely to engage in risk drinking than women with primary school education or below; and age was significantly positively associated with both general and risk drinking. In conclusion, increasing alcohol consumption among women may be due to increased social pressure.
AIMS: To establish an automated method for identifying referable diabetic retinopathy (DR), defined as moderate nonproliferative DR and above, using deep learning-based lesion detection and stage grading. MATERIALS AND METHODS: A set of 12,252 eligible fundus images of diabetic patients were manually annotated by 45 licenced ophthalmologists and were randomly split into training, validation, and internal test sets (ratio of 7:1:2). Another set of 565 eligible consecutive clinical fundus images was established as an external test set. For automated referable DR identification, four deep learning models were programmed based on whether two factors were included: DR-related lesions and DR stages. Sensitivity, specificity and the area under the receiver operating characteristic curve (AUC) were reported for referable DR identification, while precision and recall were reported for lesion detection. RESULTS: Adding lesion information to the five-stage grading model improved the AUC (0.943 vs. 0.938), sensitivity (90.6% vs. 90.5%) and specificity (80.7% vs. 78.5%) of the model for identifying referable DR in the internal test set. Adding stage information to the lesion-based model increased the AUC (0.943 vs. 0.936) and sensitivity (90.6% vs. 76.7%) of the model for identifying referable DR in the internal test set. Similar trends were also seen in the external test set. DR lesion types with high precision results were preretinal haemorrhage, hard exudate, vitreous haemorrhage, neovascularisation, cotton wool spots and fibrous proliferation. CONCLUSIONS: The herein described automated model employed DR lesions and stage information to identify referable DR and displayed better diagnostic value than models built without this information.
