MNSFß promotes LPS-induced TNFα expression by increasing the localization of RC3H1 to stress granules, and the interfering peptide HEPN2 reduces TNFα production by disrupting the MNSFß-RC3H1 interaction in macrophages.

Abnormally elevated tumor necrosis factor-α (TNFα) levels at the maternal-fetal interface can lead to adverse pregnancy outcomes, including recurrent miscarriage (RM), but the mechanism underlying upregulated TNFα expression is not fully understood. We previously reported that the interaction between monoclonal nonspecific suppressor factor-ß (MNSFß) and RC3H1 upregulates TNFα expression, but the precise mechanisms are unknown. In this study, we found that MNSFß stimulated the LPS-induced TNFα expression by inactivating the promoting effect of RC3H1 on TNFα mRNA degradation rather than directly inhibiting the expression of RC3H1 in THP1-Mϕs. Mechanistically, the 81-326 aa region of the RC3H1 protein binds to the 101-133 aa region of the MNSFß protein, and MNSFß facilitated stress granules (SGs) formation and the translocation of RC3H1 to SGs by interacting with RC3H1 and fragile X mental retardation 1 (FMR1) in response to LPS-induced stress. The SGs-localization of RC3H1 reduced its inhibitory effect on TNFα expression in LPS-treated THP1-Mϕs. The designed HEPN2 peptide effectively reduced the LPS-induced expression of TNFα in THP1-Mϕs by interfering with the MNSFß-RC3H1 interaction. Treatment with the HEPN2 peptide significantly improved adverse pregnancy outcomes, including early pregnancy loss (EPL) and lower fetal weight (LFW), which are induced by LPS in mice. These data indicated that MNSFß promoted TNFα expression at least partially by increasing the localization of RC3H1 to SGs under inflammatory stimulation and that the HEPN2 peptide improved the adverse pregnancy outcomes induced by LPS in mice, suggesting that MNSFß is a potential pharmacological target for adverse pregnancy outcomes caused by abnormally increased inflammation at early pregnancy.

DECNet: Left Atrial Pulmonary Vein Class Imbalance Classification Network.

In clinical practice, the anatomical classification of pulmonary veins plays a crucial role in the preoperative assessment of atrial fibrillation radiofrequency ablation surgery. Accurate classification of pulmonary vein anatomy assists physicians in selecting appropriate mapping electrodes and avoids causing pulmonary arterial hypertension. Due to the diverse and subtly different anatomical classifications of pulmonary veins, as well as the imbalance in data distribution, deep learning models often exhibit poor expression capability in extracting deep features, leading to misjudgments and affecting classification accuracy. Therefore, in order to solve the problem of unbalanced classification of left atrial pulmonary veins, this paper proposes a network integrating multi-scale feature-enhanced attention and dual-feature extraction classifiers, called DECNet. The multi-scale feature-enhanced attention utilizes multi-scale information to guide the reinforcement of deep features, generating channel weights and spatial weights to enhance the expression capability of deep features. The dual-feature extraction classifier assigns a fixed number of channels to each category, equally evaluating all categories, thus alleviating the learning bias and overfitting caused by data imbalance. By combining the two, the expression capability of deep features is strengthened, achieving accurate classification of left atrial pulmonary vein morphology and providing support for subsequent clinical treatment. The proposed method is evaluated on datasets provided by the People's Hospital of Liaoning Province and the publicly available DermaMNIST dataset, achieving average accuracies of 78.81% and 83.44%, respectively, demonstrating the effectiveness of the proposed approach.

TransDiffSeg: Transformer-Based Conditional Diffusion Segmentation Model for Abdominal Multi-Objective.

In the domain of medical image segmentation, traditional diffusion probabilistic models are hindered by local inductive biases stemming from convolutional operations, constraining their ability to model long-term dependencies and leading to inaccurate mask generation. Conversely, Transformer offers a remedy by obviating the local inductive biases inherent in convolutional operations, thereby enhancing segmentation precision. Currently, the integration of Transformer and convolution operations mainly occurs in two forms: nesting and stacking. However, both methods address the bias elimination at a relatively large granularity, failing to fully leverage the advantages of both approaches. To address this, this paper proposes a conditional diffusion segmentation model named TransDiffSeg, which combines Transformer with convolution operations from traditional diffusion models in a parallel manner. This approach eliminates the accumulated local inductive bias of convolution operations at a finer granularity within each layer. Additionally, an adaptive feature fusion block is employed to merge conditional semantic features and noise features, enhancing global semantic information and reducing the Transformer's sensitivity to noise features. To validate the impact of granularity in bias elimination on performance and the impact of Transformer in alleviating the accumulated local inductive biases of convolutional operations in diffusion probabilistic models, experiments are conducted on the AMOS22 dataset and BTCV dataset. Experimental results demonstrate that eliminating local inductive bias at a finer granularity significantly improves the segmentation performance of diffusion probabilistic models. Furthermore, the results confirm that the finer the granularity of bias elimination, the better the segmentation performance.

MiR-3074-5p suppresses non-small cell lung cancer progression by targeting the YWHAZ/Hsp27 axis.

Non-small cell lung cancer (NSCLC) accounts for more than 80% of lung cancer cases, and the 5-year survival rate of patients remains unsatisfactory. MicroRNAs (miRNAs) are small endogenous noncoding RNAs that are considered essential posttranscriptional regulators of tumorigenesis, including NSCLC. In this study, we aimed to investigate the biological role of miR-3074-5p in NSCLC cells and the underlying molecular mechanisms. We showed that miR-3074-5p expression was decreased in human NSCLC specimens and cell lines. Moreover, miR-3074-5p overexpression inhibited cell proliferation, migration and invasion and induced apoptosis and cell cycle arrest. In addition, miR-3074-5p overexpression not only suppressed tumor growth but also enhanced the antitumor effect of paclitaxel (PTX) on NSCLC cells in vitro and in vivo. A transcriptome sequencing assay revealed genes that were differentially expressed after miR-3074-5p overexpression, and among the genes whose expression levels were most significantly decreased, tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein zeta (YWHAZ) was a target of miR-3074-5p. The regulatory effect of miR-3074-5p on YWHAZ expression was verified by Western blotting and dual-luciferase reporter assays. The inhibition of A549 cell growth, migration and invasion was reversed by YWHAZ overexpression. Furthermore, we showed that PTX stimulated the expression of the YWHAZ and Hsp27 proteins and promoted the phosphorylation of Hsp27 (at S15 and S78). YWHAZ was confirmed to interact with Hsp27 in A549 cells, and downregulating YWHAZ expression promoted the degradation of the Hsp27 protein. Taken together, these results suggest that the miR-3074-5p/YWHAZ/Hsp27 axis may be a novel therapeutic target for NSCLC treatment.

Increased miR-3074-5p expression promotes M1 polarization and pyroptosis of macrophages via ERα/NLRP3 pathway and induces adverse pregnancy outcomes in mice.

Decidual macrophages (dMϕs) play critical roles in regulation of immune-microhomeostasis at maternal-fetal interface during pregnancy, but the underlying molecular mechanisms are still unclear. In this study, it was found that litter size and fetal weight were significantly reduced, whereas the rate of embryo resorption was increased in miR-3074-5p knock-in (3074-KI) pregnant mice, compared to that of wild-type (WT) pregnant mice. Plasma levels of pro-inflammatory cytokines in 3074-KI pregnant mice were also significantly elevated compared to WT pregnant mice at GD7.5. The quantity of M1-Mϕs in uterine tissues of 3074-KI pregnant mice was significantly increased compared to WT pregnant mice at GD13.5. Estrogen receptor-α (ERα) was validated to be a target of miR-3074-5p. Either miR-3074-5p overexpression or ERα knockdown promoted transcriptional activity of NF-κB/p65, induced M1-polarization and pyroptosis of THP1-derived Mϕs, accompanied with increased intracellular levels of cleaved Caspase-1, cleaved IL-1ß, NLRP3, cleaved GSDMD and ASC aggregation. Furthermore, ERα could not only bind to NLRP3 or ASC directly, but also inhibit the interaction between NLRP3 and ASC. The endometrial miR-3074-5p expression level at the middle secretory stage of repeated implantation failure (RIF) patients was significantly decreased compared to that of control fertile women. These data indicated that miR-3074-5p could promote M1 polarization and pyroptosis of Mϕs via activation of NLRP3 inflammasome by targeting ERα, and the dysregulation of miR-3074-5p expression in dMϕs might damage the embryo implantation and placentation by interfering with inflammatory microenvironment at the maternal-fetal interface during early pregnancy.

MOTC: Abdominal Multi-objective Segmentation Model with Parallel Fusion of Global and Local Information.

Convolutional Neural Networks have been widely applied in medical image segmentation. However, the existence of local inductive bias in convolutional operations restricts the modeling of long-term dependencies. The introduction of Transformer enables the modeling of long-term dependencies and partially eliminates the local inductive bias in convolutional operations, thereby improving the accuracy of tasks such as segmentation and classification. Researchers have proposed various hybrid structures combining Transformer and Convolutional Neural Networks. One strategy is to stack Transformer blocks and convolutional blocks to concentrate on eliminating the accumulated local bias of convolutional operations. Another strategy is to nest convolutional blocks and Transformer blocks to eliminate bias within each nested block. However, due to the granularity of bias elimination operations, these two strategies cannot fully exploit the potential of Transformer. In this paper, a parallel hybrid model is proposed for segmentation, which includes a Transformer branch and a Convolutional Neural Network branch in encoder. After parallel feature extraction, inter-layer information fusion and exchange of complementary information are performed between the two branches, simultaneously extracting local and global features while eliminating the local bias generated by convolutional operations within the current layer. A pure convolutional operation is used in decoder to obtain final segmentation results. To validate the impact of the granularity of bias elimination operations on the effectiveness of local bias elimination, the experiments in this paper were conducted on Flare21 dataset and Amos22 dataset. The average Dice coefficient reached 92.65% on Flare21 dataset, and 91.61% on Amos22 dataset, surpassing comparative methods. The experimental results demonstrate that smaller granularity of bias elimination operations leads to better performance.

MiR-3074-5p Regulates Trophoblasts Function via EIF2S1/GDF15 Pathway in Recurrent Miscarriage.

Dysfunction of extravillous trophoblasts (EVTs) might cause early pregnancy failure by interfering with embryo implantation and/or placentation. We previously reported that the villus miR-3074-5p expression level was increased, whereas the peripheral level of GDF15, a predict target gene of miR-3074-5p, was decreased in recurrent miscarriages (RM) patients, and miR-3074-5p could enhance apoptosis but reduce invasion of human extravillous trophoblast cells (EVTs). The aim of this study was to further explore roles of miR-3074-5p/GDF15 pathway in regulation of EVTs function. It was validated that GDF15 was not the direct target of miR-3074-5p, whereas EIF2S1, an upstream regulator of GDF15 maturation and secretion, was the direct target of miR-3074-5p. The villus expression levels of GDF15 and EIF2S1 were significantly decreased in RM patients. Knockdown of GDF15 expression presented inhibitory effects on proliferation, migration, and invasion of HTR8/SVneo cells. Up-regulated miR-3074-5p expression led to the significant decreased GDF15 expression in HTR8/SVneo cells, and this effect could be efficiently reversed by the overexpression of EIF2S1. Meanwhile, the suppressive effects of miR-3074-5p on proliferation, migration, and invasion of HTR8/SVneo cells could be intercepted by the treatment of recombinant human GDF15 protein. Collectively, these data suggested that miR-3074-5p could reduce GDF15 production via targeting inhibition of EIF2S1 expression, and the deficiency in GDF15 function might lead to the early pregnancy loss by attenuating proliferation and invasion of EVTs.

Synthesis of environmentally friendly neonicotinoid insecticide with proper functional properties by theoretical methodologies.

Modern insecticide substitutes using acetylcholine receptors (nAChR) as biochemical targets, such as neonicotinoid insecticides (NNIs), have been extensively researched. Only 12 compounds have been experimentally realized since the initial discovery of imidacloprid. Increasingly, the bottleneck in this field is to rapidly determine the synthesizability of NNI substitutes. Here, we designed a coupled evaluation system for synthesis prediction and validation, including the synthesis probability, reaction path difficulty, and electron transfer characteristics of NNIs and their substitutes. Firstly, a total of 1475 eigenvalues were generated and 52 critical eigenvalues were screened out through the Pearson's correlation coefficient. The positive and unlabeled (PU) machine learning was constructed using the critical eigenvalues NNIs, including 12 experimentally synthesized NNIs (positive samples) and 73 unsynthesized NNI substitutes (unlabeled samples). Results identified 3 NNI substitutes that were highly promising candidates for synthesis (synthesis probability > 0.5). The results of density functional theory demonstrated the ranking of their reaction ease was UN-1 (31.4 kcal/mol) > UN-2 (81.6 kcal/mol) > UN-3 (3.35 ×103 kcal/mol). Time-dependent density functional theory revealed that changes in the electron distribution and electron excitation type were critical factors affecting their synthesizability, and the local excitation type was more favorable for the synthesizability of NNI substituents. The findings provide significant guidance for NNIs synthesis, reducing the possible space of unlabeled samples to 95.89% of their original size, while also minimizing the cost of research on subsequent NNI substitutes.

Acceptance of influenza vaccination and associated factors among teachers in China: A cross-sectional study based on health belief model.

Teachers played an important role on the transmission of influenza in schools and communities. The study aims to investigate the influenza vaccination coverage and the factors determining flu vaccination acceptance among teachers in Hangzhou, China. A total of 1039 junior high school teachers in Hangzhou were recruited. The self-made questionnaire was used to investigate the influenza vaccine coverage among teachers and the influencing factors of influenza vaccination acceptance. Univariate analysis using the chi-square test and multivariable analysis using binary logistic regression were conducted to determine the relative predictors. The Influenza vaccine coverage among teachers was 5.9% (62/1039). 52.9% of teachers had the intention to receive influenza vaccine, 25.3% (247/977)/21.8% (213/977) of participants was hesitant/did not have the intention to get influenza vaccine. The top three sources for teachers to gain knowledge about influenza were website (72%), TV/radio (66.1%) and social media (58%). Whether get influenza vaccination before, knowledge about influenza and influenza vaccine, the beliefs for the likelihood of catching flu, the severity of getting flu, the effectiveness of influenza vaccine, the possibility of side effects after vaccination, and the troublesome of vaccination, doctors' recommendation, as well as the situation of vaccination among other teachers were the associated factors of influenza vaccination acceptance. The influenza vaccination coverage was low but the intentions were relatively high among junior high school teachers. Future research should focus on the relationship between vaccination acceptance and behavior to increase influenza vaccination rates.

Do adolescents need a rubella vaccination campaign? Rubella serosurvey among healthy children in Hangzhou, China.

The aim of this study was to evaluate the seroprevalence of rubella antibodies and factors associated with antibody seropositivity after vaccination among healthy children aged 14 and below. A multi-stage stratified random sampling method was employed to recruit participants for the rubella serological test. An enzyme-linked immunosorbent assay method was used to detect human IgG antibodies with avidity for rubella virus in the sera of participants. Univariate and multivariate analyses were used to analyze associations between variables. A total of 778 subjects were included in the subsequent analysis. The overall positive rate of rubella antibody was 83.0% (95%CI: 80.2-85.5%), and the overall geometric mean concentration (GMC) was 58.05 IU/ml. In multivariate analysis, gender, residence, birth year group, and time since the last rubella-containing vaccines (RCV) vaccination were significantly associated with the seroprevalence of rubella antibodies. Our study showed a decreasing trend in rubella antibody positivity and GMC in the population aged five to 14 years. Therefore, we recommend a catch-up dose of RCV for adolescents and young people aged over 14 years not yet vaccinated.

Multi-process regulation of novel brominated flame retardants: Environmentally friendly substitute design, screening and environmental risk regulation.

Novel brominated flame retardants (NBFRs), one of the most widely used synthetic flame-retardant materials, have been considered as a new group of pollutants that potentially affect human health. To overcome the adverse effects of NBFRs, a systematic approach for molecular design, screening, and performance evaluation was developed to generate environmentally friendly NBFR derivatives with unaltered functionality. In the present study, the features of NBFRs (long-distance migration, biotoxicity, bioenrichment, and environmental persistence) were determined and characterized by the multifactor comprehensive characterization method with equal weight addition, and the similarity index analysis (CoMSIA) model was constructed. Based on the three-dimensional equipotential diagram of the target molecule 2-ethylhexyl tetrabromobenzoic acid (TBB), 23 TBB derivatives were designed. Of these, 22 derivatives with decreased environmental impact and unaltered functional properties (i.e., flame retardancy and stability) were selected using 3D-QSAR models and density functional theory methods. The health risks of these derivatives to humans were assessed by toxicokinetic analysis; the results narrowed down the number of candidates to three (Derivative-7, Derivative-10, and Derivative-15). The environmental impact of these candidates was further evaluated and regulated in the real-world environment by using molecular dynamics simulation assisted by the Taguchi experimental design method. The relationship between the binding effects and the nonbonding interaction resultant force (TBB derivatives-receptor proteins) was also studied, and it was found that the larger the modulus of the binding force, the stronger the binding ability of the two. This finding indicated that the environmental impact of the designed NBFR derivatives was decreased. The present study aimed to provide a new idea and method for designing NBFR substitutes and to provide theoretical support for restraining the potential environmental risks of NBFRs.

Analysis of 13-valent pneumococcal polysaccharide conjugate vaccine among children born in Hangzhou from 2017 to 2021.

Background: 13-valent pneumococcal polysaccharide conjugate vaccine (PCV13) has been introduced in Hangzhou since 2017, whereas its current immunization state in children is not clear. Therefore, this study aims to describe the PCV13 vaccination distribution among children born in Hangzhou from 2017 to 2021 to provide data for reducing vaccination differences among different populations. Methods: Descriptive epidemiology was used for data analysis and PCV13 vaccination related information of children was collected from children vaccination management system of Zhejiang Province (ZJCVMS). Results: Among the 649,949 children born in Hangzhou from 2017 to 2021, 169,230 were vaccinated with an average full course vaccination rate of 26.0%. The full course vaccination rates in 5 years were different (P = 0.000) with an increasing trend (P fortrend < 0.01). The first dose vaccination rates were different in 5 years (P = 0.000) with an increasing trend (P fortrend < 0.01). The distribution of age when first dose PCV13 was administered varied, most people at 2 months and least people at 5 months. The full course vaccination rate varied by areas, highest in central urban areas and lowest in remote areas respectively (all P-value < 0.05). Overall, the full course vaccination rate of PCV13 was higher in the registered residence population than the non-registered residence population, which was 136,693 (31.4%) and 32,537 (15.1%) respectively (P = 0.000). The full course vaccination rates were the same between men and women (P = 0.502), which was 87,844 for men (26.0%) and 81,386 for women (26.1%). Conclusion: Although the number of people who received PCV13 full course vaccination and received the first dose vaccination showed yearly increasing trends in Hangzhou, the full course vaccination rate for the whole population was relatively low. In addition, the PCV13 vaccination rates also differed by geography and household registration status. Measures such as expanding vaccination publicity or including national immunization should be taken to increase vaccination rates and reduce the differences in vaccination among groups with different characteristics.

Associated factors of burnout among Chinese vaccination staff during COVID-19 epidemic: A cross-sectional study.

Objective: During the COVID-19 epidemic, vaccination staff had three main aspects of work: routine vaccination for children and adults, COVID-19 vaccination and COVID-19 prevention and control. All these works significantly increased the workload of vaccination staff. This study aimed to investigate the prevalence and influencing factors of burnout among vaccination staff in Hangzhou, China. Methods: A total of 501 vaccination staff from 201 community/township healthcare centers in Hangzhou were recruited using a cross-sectional survey through WeChat social platform. The Maslach Burnout Inventory-General Scale (MBI-GS) was used to assess the level of burnout. Descriptive statistics were made on the characteristics of participants. Univariate analysis using the chi-square test and multivariable analysis using binary logistic regression were conducted to determine the relative predictors of burnout. Univariate analysis and multiple linear regression were used to determine the relative predictors of exhaustive emotion, cynicism, and personal accomplishment. Results: During the COVID-19 pandemic, 20.8% of the vaccination staff experienced burnout. Educational level above undergraduate education level, medium professional title, and more working time in COVID-19 vaccination work reported a higher degree of job burnout. The vaccination staff was experiencing a high degree of exhaustive emotion, cynicism, and low personal accomplishment. Professional title, working place, and working time for COVID-19 vaccination were associated with exhaustive emotion and cynicism. Professional title and participation time for COVID-19 prevention and control were associated with personal accomplishment. Conclusions: Our findings suggest that the prevalence rate of burnout is high among vaccination staff during the COVID-19 pandemic, especially with a low level of personal accomplishment. Psychological intervention for vaccination staff is urgently needed.

Variations in Breast Milk Iodine Concentration over 24 h among Lactating Women in Northern China.

BACKGROUND: Adequate breast milk iodine concentration (BMIC) is essential for the growth and cognitive development of exclusively breastfed infants; however, data on variations in BMIC over 24 h are limited. OBJECTIVE: We aimed to explore in lactating women the variation in 24-h BMIC. METHODS: Thirty pairs of mothers and breastfed infants aged 0-6 mo were recruited from the cities of Tianjin and Luoyang, China. A 3-d 24-h dietary record, including salt intake, was performed to assess the dietary iodine intake of lactating women. Breast milk samples before and after each feeding for 24 h and 24-h urine samples were collected from the women for 3 d to estimate iodine excretion. A multivariate linear regression model was used to analyze the factors influencing BMIC. A total of 2658 breast milk samples and 90 24-h urine samples were collected. RESULTS: The median BMIC and 24-h urine iodine concentration (UIC) of lactating women for a mean of 3.6 ± 1.48 mo were 158 µg/L and 137 µg/L, respectively. The interindividual variability of BMIC (35.1%) was higher than that observed within individuals (11.8%). The variation in BMIC showed a "V" shaped curve over 24 h. The median BMIC at 08:00-12:00 (137 µg/L) was significantly lower than that at 20:00-24:00 (163 µg/L) and 00:00-04:00 (164 µg/L). A progressively increasing curve was obtained for BMIC until it peaked at 20:00 and plateaued at a higher concentration from 20:00 to 04:00 than at 08:00-12:00 (all P < 0.05). BMIC was associated with dietary iodine intake (ß: 0.366; 95% CI: 0.004, 0.018) and infant age (ß: -0.432; 95% CI: -1.07, -0.322). CONCLUSIONS: Our study shows that the BMIC presents a "V" shaped curve over 24 h. We recommend that breast milk samples be collected between 08:00 and 12:00 for evaluation of the iodine status of lactating women.

In-silico analysis of atmospheric diffusion, crop planting degrading scheme, and health risk of dioxins from a domestic waste incineration plant.

Based on a domestic waste incineration power generation project, the dioxin emission from the waste incineration plant (WIP), phytoextraction and microbial degradation of dioxins, and dioxins human health risks reduction were investigated through in-silico methods. Based on the dioxins concentrations in soil (9.97 × 10-9-7.00 × 10-5ng/g) predicted by atmospheric dispersion model system and the Level-III fugacity model, planting schemes under different wind directions were designed considering the dioxin absorption capacity and the economic benefits for crops (i.e., barley, peanut, pea, maize and wheat). The dioxins in soils can be further degraded by five crops' rhizosphere microorganisms and fertilizers, simulated through molecular dynamic simulations. The enhanced degradation rates of dioxin by rhizosphere microorganisms of five crops reached 15.70 %-28.66 %. Finally, healthy dietary plans were developed to reduce the risk of dioxin exposure to the sensitive populations living around WIP. Results showed that the consumption of maize, fungus, mushroom and bamboo fungus could effectively reduce dioxins toxicity to humans by 58.13 %. The systematic approach developed in this study provided theoretical support for soil remediation and human health risk control of dioxins-contaminated sites.

Investigating the electrochemical advanced oxidation mechanism of N-doped graphene aerogel: Molecular dynamics simulation combined with DFT method.

Nitrogen-doped graphene as a perfectly-efficient and environmentally compatible electrocatalyst won widespread attention in electrochemical advanced oxidation processes (EAOP). However, the relationship between surface structure regulation and activity of catalysts is still lacking in systematic scientific guidance. Herein, nitrogen-doped graphene aerogel (NGA) was conveniently prepared through hydrothermal treatment, and then utilized to fabricate the gas diffusion electrode (GDE) as the cathode for tetracycline (TC) removal. High free radical yield (81.2 µM) and fast reaction rate (0.1469 min-1) were found in NGA system. The molecular dynamics simulation (MD) results showed that the interaction energy of NGA was greater than the raw graphene aerogel (GA). The adsorption activation of H2O2 and the degradation of TC occurred in the first adsorption layer of catalysts, and both processes turned more orderly after nitrogen doping. Moreover, the van der Waals interaction was stronger than the electrostatic interaction. Density function theory (DFT) revealed that the adsorption energy of H2O2 at graphitic N, pyridinic N, and pyrrolic N sites was -0.03 eV, -0.39 eV, and -0.30 eV, respectively. Pyridinic N sites were inferred as the main functional regions of in-situ activation •OH, there were more likely to occur ectopic reaction in pyrrolic N, and graphitic N were responsible for improving H2O2 production. By revealing the microstructure and activation characteristics of NGA, an experiment-simulation complementary strategy is provided in the EAOP to discover or to optimize new catalysts.

New insights into enhanced electrochemical advanced oxidation mechanism of B-doped graphene aerogel: Experiments, molecular dynamics simulations and DFT.

B-doped graphene, as an efficient and environmental-friendly metal-free catalyst, has aroused much attention in the electrochemical advanced oxidation process (EAOP), but the bottleneck in this field is to determine the relationship between the surface structure regulation and activity of catalysts. Herein, the B-doped graphene aerogel (BGA) fabricated gas diffusion electrode was prepared and used as a cathode for EAOP to remove tetracycline (TC). Higher free radical yield (169.59 µM), faster reaction speed (0.35 min-1) and higher TC removal rate (99.93%) were found in the BGA system. Molecular dynamics simulation unveiled the interaction energy of BGA was greater than the raw graphene aerogel (GA). The adsorption-activation process of H2O2 and the degradation process of TC occurred in the first adsorption layer of catalysts. And both processes turned more orderly after B doping, which accelerated the reaction efficiency. Results of density functional theory displayed the contribution of three B-doped structures to improve the binding strength between H2O2 and BGA was: - BCO2 (-0.23 eV) > - BC2O (-0.16 eV) > - BC3 (-0.09 eV). -BCO2 was inferred to be the main functional region of H2O2 in-situ activation to hydroxyl radical (•OH), while -BC2O and -BC3 were responsible for improving H2O2 production.

A critical review on the interaction of polymer particles and co-existing contaminants: Adsorption mechanism, exposure factors, effects on plankton species.

This review considers the interaction of microplastics (MPs)/nanoplastics (NPs) and co-existing contaminants, including organic contaminants, potentially toxic elements (PTEs), and metal/metal-oxide nanoparticles. Stronger adsorption between plastic particles and co-existing contaminants can either facilitate or prevent more contaminants to enter plankton. The characteristics of MPs/NPs, such as polymer type, size, functional groups, and weathering, affect combined effects. Mixture toxicity is affected by those factors simultaneously and also affected by the type of co-existing contaminants, their concentrations, exposure time, dissolved organic matter, and surfactant. For co-exposure involving organics and metal nanoparticles, marine Skeletonema costatum generally had antagonistic effects, while marine Chlorella pyrenoidosa, Platymonas subcordiformis, and Tetraselmis chuii, showed synergistic effects. For co-exposure involving organics and PTEs, both Chlorella sp. and Microcystis aeruginosa generally demonstrated antagonistic effects. Freshwater Chlorella reinhardtii and Scenedesmus obliquus had synergistic effects for co-exposure involving metal/metal oxide nanoparticles. Zooplankton shows more unpredicted sensitivity towards the complex system. Different co-existing contaminants have different metabolism pathways. Organic contaminants could be biodegraded, which may enhance or alleviate mixture toxicity. PTEs could be adsorbed and desorbed under changing environments, and further affect the combined effects. The presence of metal/metal-oxide nanoparticles is more complicated, since some may release ion metals, increasing contaminant composition.