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Electrolysis that reduces carbon dioxide (CO2) to useful chemicals can, in principle, contribute to a more sustainable and carbon-neutral future1-6. However, it remains challenging to develop this into a robust process because efficient conversion typically requires alkaline conditions in which CO2 precipitates as carbonate, and this limits carbon utilization and the stability of the system7-12. Strategies such as physical washing, pulsed operation and the use of dipolar membranes can partially alleviate these problems but do not fully resolve them11,13-15. CO2 electrolysis in acid electrolyte, where carbonate does not form, has therefore been explored as an ultimately more workable solution16-18. Herein we develop a proton-exchange membrane system that reduces CO2 to formic acid at a catalyst that is derived from waste lead-acid batteries and in which a lattice carbon activation mechanism contributes. When coupling CO2 reduction with hydrogen oxidation, formic acid is produced with over 93% Faradaic efficiency. The system is compatible with start-up/shut-down processes, achieves nearly 91% single-pass conversion efficiency for CO2 at a current density of 600 mA cm-2 and cell voltage of 2.2 V and is shown to operate continuously for more than 5,200 h. We expect that this exceptional performance, enabled by the use of a robust and efficient catalyst, stable three-phase interface and durable membrane, will help advance the development of carbon-neutral technologies.
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Herein, we report a high-density dual-structure single-atom catalyst (SAC) by creating a large number of vacancies of O and Ti in two-dimensional (2D) Ti3C2 to immobilize Pt atoms (SA Pt-Ti3C2). The SA Pt-Ti3C2 showed excellent performance toward the pH-universal electrochemical hydrogen evolution reaction (HER) and multimodal sensing. For HER catalysis, compared to the commercial 20 wt % Pt/C, the Pt mass activities of SA Pt-Ti3C2 at the overpotentials of â¼30 and 110 mV in acid and alkaline media are 45 and 34 times higher, respectively. More importantly, during the alkaline HER process, an interesting synergetic effect between Pt-C and Pt-Ti sites that dominated the Volmer and Heyrovsky steps, respectively, was revealed. Moreover, the SA Pt-Ti3C2 catalyst exhibited high sensitivity (0.62-2.65 µA µM-1) and fast response properties for the multimodal identifications of ascorbic acid, dopamine, uric acid, and nitric oxide under the assistance of machine learning.
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Photocatalytic hydrogen peroxide production from water and oxygen offers a clean and sustainable alternative to the conventional energy-intensive anthraquinone oxidation method. Compared to powdered covalent triazine frameworks (CTFs), the film morphology of CTFs provides better connectivity in 2D, yielding several advantages: more efficient connections between active sites, reduced electron-hole pair recombination, increased resistance to superoxide radical induced corrosion, and decreased light scattering. Leveraging these benefits, it has incorporated dual active sites for both the oxygen reduction reaction (ORR) and the water oxidation reaction (WOR) into a CTF film system. This dual-active CTF film demonstrated an exceptional hydrogen peroxide production rate of 19 460 µmol h⻹ mâ»2 after 1 h and 17 830 µmol h⻹ mâ»2 after 5 h under visible light irradiation (≥420 nm) without the need for sacrificial agents.
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The interlayer strategy has emerged as an effective approach for modulating the interfacial polymerization process and improving the permeability and selectivity of polyamide membranes. However, the underlying mechanisms by which charged interlayers influence the interfacial polymerization process remain inadequately understood. In this study, we utilized two distinct charged cellulose nanofibers, namely, carboxylated cellulose (â-CNF) and quaternized cellulose ([Formula: see text]-CNF), as interlayers to regulate the interfacial polymerization process. Through simulation results, isothermal titration calorimetry (ITC) and UV tests, we demonstrated that the [Formula: see text]-CNF interlayer, which possesses stronger hydration capability and better piperazine affinity, enhanced the diffusion of piperazine across the reaction interface compared with the â-CNF interlayer. This led to an acceleration of the interfacial polymerization process and the formation of a denser membrane structure. Further investigation revealed that the charged interlayers significantly influenced the surface charging properties of the resulting nanofiltration membranes within a 30 nm range of electrostatic effects. Specifically, the â-CNF interlayer conferred a higher negative charge to the membrane surface, while the [Formula: see text]-CNF interlayer endowed the membranes with a lower surface negative charge. Leveraging these differences, the â-i-TFC membranes exhibited exceptional separation performance for divalent anions, achieving a SO42-/Cl- selectivity of 136. Conversely, the [Formula: see text]-i-TFC membrane demonstrated an enhanced separation of divalent cations, displaying a Mg2+/Na+ selectivity of 3.5. This study lays the groundwork for regulating the surface charging properties of polyamide membranes, offering potential advancements in nanofiltration applications.
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This study investigated the regulatory impact of Toll-like receptor 4 (TLR4) gene on glioma cell proliferation and apoptosis, elucidating the molecular mechanisms underlying TLR4-induced growth inhibition in vivo. U-87MG-Sh and U-87MG-NC cells, with silenced TLR4 and negative control plasmid respectively, were established. Eighteen nude mice, divided into transfection, negative control, and blank control groups, were inoculated with corresponding cells. Over four weeks, the transfection group exhibited significantly reduced tumor growth rates, smaller mass and volume, and lower growth activity compared to controls. Histological analysis revealed sparse tumor cells, increased fibrous connective tissue, and slower angiogenesis in the transfection group. Flow cytometry demonstrated a lower proliferation index and increased G0/1 cell count in the transfection group. mRNA levels of TLR4, NF-κB, and CyclinD1 were significantly lower in the transfection group. TLR4 silencing correlated with U-87MG cell proliferation regulation, growth inhibition, NF-κB and CyclinD1 modulation, and induction of cell cycle arrest and apoptosis. These findings suggest TLR4 as a potential gene therapy target for glioma.
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Apoptose , Proliferação de Células , Ciclina D1 , Inativação Gênica , Glioma , Camundongos Nus , NF-kappa B , Receptor 4 Toll-Like , Animais , Receptor 4 Toll-Like/metabolismo , Receptor 4 Toll-Like/genética , Glioma/patologia , Glioma/genética , Glioma/metabolismo , Proliferação de Células/genética , Linhagem Celular Tumoral , Apoptose/genética , Humanos , NF-kappa B/metabolismo , Ciclina D1/metabolismo , Ciclina D1/genética , Camundongos , Pontos de Checagem do Ciclo Celular/genética , RNA Interferente Pequeno/genética , RNA Interferente Pequeno/metabolismo , Regulação Neoplásica da Expressão Gênica , Camundongos Endogâmicos BALB CRESUMO
BACKGROUND: Emerging evidence suggests that alterations in BCAA metabolism may contribute to the pathogenesis of sarcopenia. However, the relationship between branched-chain amino acids (BCAAs) and sarcopenia is incompletely understood, and existing literature presents conflicting results. In this study, we conducted a community-based study involving > 100,000 United Kingdom adults to comprehensively explore the association between BCAAs and sarcopenia, and assess the potential role of muscle mass in mediating the relationship between BCAAs and muscle strength. METHODS: Multivariable linear regression analysis examined the relationship between circulating BCAAs and muscle mass/strength. Logistic regression analysis assessed the impact of circulating BCAAs and quartiles of BCAAs on sarcopenia risk. Subgroup analyses explored the variations in associations across age, and gender. Mediation analysis investigated the potential mediating effect of muscle mass on the BCAA-muscle strength relationship. RESULTS: Among 108,017 participants (mean age: 56.40 ± 8.09 years; 46.23% men), positive associations were observed between total BCAA, isoleucine, leucine, valine, and muscle mass (beta, 0.56-2.53; p < 0.05) and between total BCAA, leucine, valine, and muscle strength (beta, 0.91-3.44; p < 0.05). Logistic regression analysis revealed that increased circulating valine was associated with a 47% reduced sarcopenia risk (odds ratio = 0.53; 95% confidence interval = 0.3-0.94; p = 0.029). Subgroup analyses demonstrated strong associations between circulating BCAAs and muscle mass/strength in men and individuals aged ≥ 60 years. Mediation analysis suggested that muscle mass completely mediated the relationship between total BCAA, and valine levels and muscle strength, partially mediated the relationship between leucine levels and muscle strength, obscuring the true effect of isoleucine on muscle strength. CONCLUSION: This study suggested the potential benefits of BCAAs in preserving muscle mass/strength and highlighted muscle mass might be mediator of BCAA-muscle strength association. Our findings contribute new evidence for the clinical prevention and treatment of sarcopenia and related conditions involving muscle mass/strength loss.
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Aminoácidos de Cadeia Ramificada , Força Muscular , Sarcopenia , Humanos , Sarcopenia/sangue , Sarcopenia/epidemiologia , Masculino , Feminino , Estudos Transversais , Aminoácidos de Cadeia Ramificada/sangue , Pessoa de Meia-Idade , Força Muscular/fisiologia , Idoso , Reino Unido/epidemiologia , Músculo Esquelético/metabolismo , AdultoRESUMO
Background- Postoperative delirium is a common complication associated with the elderly, causing increased morbidity and prolonged hospital stay. However, its risk factors in chronic subdural hematoma patients have not been well studied. Methods- A total of 202 consecutive patients with chronic subdural hematoma at Peking University Third Hospital between January 2018 and January 2023 were enrolled. Various clinical indicators were analyzed to identify independent risk factors for postoperative delirium using univariate and multivariate regression analyses. Delirium risk prediction models were developed as a nomogram and a Markov chain. Results- Out of the 202 patients (age, 71 (IQR, 18); female-to-male ratio, 1:2.7) studied, 63 (31.2%) experienced postoperative delirium. Univariate analysis identified age (p < 0.001), gender (p = 0.014), restraint belt use (p < 0.001), electrolyte imbalance (p < 0.001), visual analog scale score (p < 0.001), hematoma thickness (p < 0.001), midline shift (p < 0.001), hematoma side (p = 0.013), hematoma location (p = 0.018), and urinal catheterization (p = 0.028) as significant factors. Multivariate regression analysis confirmed the significance of restraint belt use (B = 7.657, p < 0.001), electrolyte imbalance (B = -3.993, p = 0.001), visual analog scale score (B = 2.331, p = 0.016), and midline shift (B = 0.335, p = 0.007). Hematoma thickness and age had no significant impact. Conclusion- Increased midline shift and visual analog scale scores, alongside restraint belt use and electrolyte imbalance elevate delirium risk in chronic subdural hematoma surgery. Our prediction models may offer reference value in this context.
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Delírio do Despertar , Hematoma Subdural Crônico , Humanos , Masculino , Feminino , Idoso , Hematoma Subdural Crônico/complicações , Delírio do Despertar/complicações , Estudos Retrospectivos , Fatores de Risco , Medição de Risco , EletrólitosRESUMO
INTRODUCTION: The cognitive impairment patterns and the association with Alzheimer's disease (AD) in mental disorders remain poorly understood. METHODS: We analyzed data from 486,297 UK Biobank participants, categorizing them by mental disorder history to identify the risk of AD and the cognitive impairment characteristics. Causation was further assessed using Mendelian randomization (MR). RESULTS: AD risk was higher in individuals with bipolar disorder (BD; hazard ratio [HR] = 2.37, P < 0.01) and major depressive disorder (MDD; HR = 1.63, P < 0.001). MR confirmed a causal link between BD and AD (ORIVW = 1.098), as well as obsessive-compulsive disorder (OCD) and AD (ORIVW = 1.050). Cognitive impairments varied, with BD and schizophrenia showing widespread deficits, and OCD affecting complex task performance. DISCUSSION: Observational study and MR provide consistent evidence that mental disorders are independent risk factors for AD. Mental disorders exhibit distinct cognitive impairment prior to dementia, indicating the potential different mechanisms in AD pathogenesis. Early detection of these impairments in mental disorders is crucial for AD prevention. HIGHLIGHTS: This is the most comprehensive study that investigates the risk and causal relationships between a history of mental disorders and the development of Alzheimer's disease (AD), alongside exploring the cognitive impairment characteristics associated with different mental disorders. Individuals with bipolar disorder (BD) exhibited the highest risk of developing AD (hazard ratio [HR] = 2.37, P < 0.01), followed by those with major depressive disorder (MDD; HR = 1.63, P < 0.001). Individuals with schizophrenia (SCZ) showed a borderline higher risk of AD (HR = 2.36, P = 0.056). Two-sample Mendelian randomization (MR) confirmed a causal association between BD and AD (ORIVW = 1.098, P < 0.05), as well as AD family history (proxy-AD, ORIVW = 1.098, P < 0.001), and kept significant after false discovery rate correction. MR also identified a nominal significant causal relationship between the obsessive-compulsive disorder (OCD) spectrum and AD (ORIVW = 1.050, P < 0.05). Individuals with SCZ, BD, and MDD exhibited impairments in multiple cognitive domains with distinct patterns, whereas those with OCD showed only slight declines in complex tasks.
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Doença de Alzheimer , Bancos de Espécimes Biológicos , Disfunção Cognitiva , Análise da Randomização Mendeliana , Humanos , Doença de Alzheimer/genética , Doença de Alzheimer/epidemiologia , Reino Unido/epidemiologia , Feminino , Masculino , Disfunção Cognitiva/genética , Disfunção Cognitiva/epidemiologia , Fatores de Risco , Pessoa de Meia-Idade , Idoso , Transtornos Mentais/epidemiologia , Transtornos Mentais/genética , Transtorno Depressivo Maior/genética , Transtorno Depressivo Maior/epidemiologia , Transtorno Bipolar/genética , Transtorno Bipolar/epidemiologia , Esquizofrenia/genética , Esquizofrenia/epidemiologia , Biobanco do Reino UnidoRESUMO
BACKGROUND: The influences of abscisic acid (ABA) applications on precursors and gene expression in 3-alkyl-2-methoxypyrazines (MPs) biosynthetic pathway, MPs concentration and sensory evaluation of its derived peculiar odors in Cabernet Sauvignon grapes and wines were investigated. At the vineyard, ABA solution with 25, 100 and 400 mg L-1 (AT1, AT2 and AT3, respectively) and an aqueous solution (control) were sprayed three times from veraison to pre-harvest. RESULTS: Higher concentration ABA applications (AT2 and AT3) in grapes could significantly reduce MPs concentration and its derived peculiar odors in grapes and wines compared to a lower concentration ABA application (AT1) and control, with AT2 application having the strongest effect. The changes in MPs were mainly a result of the downregulated expression of VvOMTs genes at higher concentration ABA applications, independent of the levels of their potential precursors. CONCLUSION: The present study reveals that ABA application had the potential to decrease production of MPs in Cabernet Sauvignon grapes and wines, and this result provides reference values for the removal of unpleasant vegetable odors from Cabernet Sauvignon wines in production. © 2024 Society of Chemical Industry.
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Ácido Abscísico , Frutas , Odorantes , Pirazinas , Vitis , Vinho , Vitis/química , Vitis/metabolismo , Vinho/análise , Ácido Abscísico/metabolismo , Odorantes/análise , Frutas/química , Frutas/metabolismo , Pirazinas/análise , Pirazinas/metabolismo , Humanos , Proteínas de Plantas/metabolismo , Proteínas de Plantas/genética , Aromatizantes/química , Aromatizantes/metabolismo , Reguladores de Crescimento de Plantas/farmacologiaRESUMO
BACKGROUND: Algae oil has garnered widespread acclaim due as a result of its high purity of docosahexaenoic acid (DHA) and excellent safety profile. The present study aimed to develop stable nanoemulsions (NEs) systems containing DHA from algae oil through thermal sterilization by combining modified whey protein concentrate (WPC) with low methoxyl pectin (LMP), as well as to investigate the impact of LMP concentration on the thermal stability and the gastrointestinal delivery efficiency of DHA NEs. RESULTS: The addition of LMP enhanced the stability of the emulsion after sterilization, at the same time as improving the protective and sustained release effects of DHA in the gastrointestinal tract. Optimal effect was achieved at a LMP concentration of 1% (10 g kg-1 sample), the stability of the emulsion after centrifugation increased by 17.21 ± 5.65% compared to the group without LMP, and the loss of DHA after sterilization decreased by only 0.92 ± 0.09%. Furthermore, the addition of 1% LMP resulted in a substantial reduction in the release of fatty acids from the NEs after gastrointestinal digestion simulation, achieving the desired sustained-release effect. However, excessive addition of 2% (20 g kg-1 sample) LMP negatively impacted all aspects of the NEs system, primarily because of the occurrence of depletion effects. CONCLUSION: The construction of the LMP/WPC-NEs system is conducive to the protection of DHA in algae oil and its sustained-release in the gastrointestinal tract. The results of the present study can provide reference guidance for the application of algae oil NEs in the food field. © 2024 Society of Chemical Industry.
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The solar-driven photocatalytic production of hydrogen peroxide (H2O2) from water and oxygen using semiconductor catalysts offers a promising approach for converting solar energy into storable chemical energy. However, the efficiency of photocatalytic H2O2 production is often restricted by the low photo-generated charge separation, slow surface reactions and inadequate stability. Here, we developed a mixed-linker strategy to build a donor-acceptor-acceptor (D-A-A) type covalent organic framework (COF) photocatalyst, FS-OHOMe-COF. The FS-OHOMe-COF structure features extended π-π conjugation that improves charge mobility, while the introduction of sulfone units not only as active sites facilitates surface reactions with water but also bolsters stability through increased interlayer forces. The resulting FS-OHOMe-COF has a low exciton binding energy, long excited-state lifetime and high photo-stability that leads to high performance for photocatalytic H2O2 production (up to 1.0â mM h-1) with an H2O2 output of 19â mM after 72â hours of irradiation. Furthermore, the catalyst demonstrates high stability, which sustained activity over 192â hours of photocatalytic experiment.
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Electrochemical CO2 reduction reaction (CO2RR) offers a sustainable strategy for producing fuels and chemicals. However, it suffers from sluggish CO2 activation and slow water dissociation. In this work, we construct a (P-O)δ- modified In catalyst that exhibits high activity and selectivity in electrochemical CO2 reduction to formate. A combination of in situ characterizations and kinetic analyses indicate that (P-O)δ- has a strong interaction with K+(H2O)n, which effectively accelerates water dissociation to provide protons. In situ attenuated total reflectance surface-enhanced infrared absorption spectroscopy (ATR-SEIRAS) measurements together with density functional theory (DFT) calculations disclose that (P-O)δ- modification leads to a higher valence state of In active site, thus promoting CO2 activation and HCOO* formation, while inhibiting competitive hydrogen evolution reaction (HER). As a result, the (P-O)δ- modified oxide-derived In catalyst exhibits excellent formate selectivity across a broad potential window with a formate Faradaic efficiency as high as 92.1 % at a partial current density of ~200â mA cm-2 and a cathodic potential of -1.2â V vs. RHE in an alkaline electrolyte.
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The identification of colored steel buildings in images is crucial for managing the construction sector, environmental protection, and sustainable urban development. Current deep learning methods for optical remote sensing images often encounter challenges such as confusion between the roof color or shape of regular buildings and colored steel structures. Additionally, common semantic segmentation networks exhibit poor generalization and inadequate boundary regularization when extracting colored steel buildings. To overcome these limitations, we utilized the metal detection and differentiation capabilities inherent in synthetic aperture radar (SAR) data to develop a network that integrates optical and SAR data. This network, employing a triple-input structure, effectively captures the unique features of colored steel buildings. We designed a multimodal hybrid attention module in the network that discerns the varying importance of each data source depending on the context. Additionally, a boundary refinement (BR) module was introduced to extract the boundaries of the colored steel buildings in a more regular manner, and a deep supervision strategy was implemented to improve the performance of the network in the colored steel building extraction task. A BR module and deep supervision strategy were also implemented to sharpen the extraction of building boundaries, thereby enhancing the network's accuracy and adaptability. The results indicate that, compared to mainstream semantic segmentation, this method effectively enhances the precision of colored steel building detection, achieving an accuracy rate of 83.19%. This improvement marks a significant advancement in monitoring illegal constructions and supporting the sustainable development of the Beijing-Tianjin-Hebei metropolitan region.
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The Internet of Medical Things (IoMT) is being incorporated into current healthcare systems. This technology intends to connect patients, IoMT devices, and hospitals over mobile networks, allowing for more secure, quick, and convenient health monitoring and intelligent healthcare services. However, existing intelligent healthcare applications typically rely on large-scale AI models, and standard IoMT devices have significant resource constraints. To alleviate this paradox, in this paper, we propose a Knowledge Distillation (KD)-based IoMT end-edge-cloud orchestrated architecture for medical image segmentation tasks, called Light-M, aiming to deploy a lightweight medical model in resource-constrained IoMT devices. Specifically, Light-M trains a large teacher model in the cloud server and employs computation in local nodes through imitation of the performance of the teacher model using knowledge distillation. Light-M contains two KD strategies: (1) active exploration and passive transfer (AEPT) and (2) self-attention-based inter-class feature variation (AIFV) distillation for the medical image segmentation task. The AEPT encourages the student model to learn undiscovered knowledge/features of the teacher model without additional feature layers, aiming to explore new features and outperform the teacher. To improve the distinguishability of the student for different classes, the student learns the self-attention-based feature variation (AIFV) between classes. Since the proposed AEPT and AIFV only appear in the training process, our framework does not involve any additional computation burden for a student model during the segmentation task deployment. Extensive experiments on cardiac images and public real-scene datasets demonstrate that our approach improves student model learning representations and outperforms state-of-the-art methods by combining two knowledge distillation strategies. Moreover, when deployed on the IoT device, the distilled student model takes only 29.6 ms for one sample at the inference step.
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Instalações de Saúde , Coração , Humanos , Hospitais , AprendizagemRESUMO
Variational Autoencoders (VAEs) are an efficient variational inference technique coupled with the generated network. Due to the uncertainty provided by variational inference, VAEs have been applied in medical image registration. However, a critical problem in VAEs is that the simple prior cannot provide suitable regularization, which leads to the mismatch between the variational posterior and prior. An optimal prior can close the gap between the evidence's real and variational posterior. In this paper, we propose a multi-stage VAE to learn the optimal prior, which is the aggregated posterior. A lightweight VAE is used to generate the aggregated posterior as a whole. It is an effective way to estimate the distribution of the high-dimensional aggregated posterior that commonly exists in medical image registration based on VAEs. A factorized telescoping classifier is trained to estimate the density ratio of a simple given prior and aggregated posterior, aiming to calculate the KL divergence between the variational and aggregated posterior more accurately. We analyze the KL divergence and find that the finer the factorization, the smaller the KL divergence is. However, too fine a partition is not conducive to registration accuracy. Moreover, the diagonal hypothesis of the variational posterior's covariance ignores the relationship between latent variables in image registration. To address this issue, we learn a covariance matrix with low-rank information to enable correlations with each dimension of the variational posterior. The covariance matrix is further used as a measure to reduce the uncertainty of deformation fields. Experimental results on four public medical image datasets demonstrate that our proposed method outperforms other methods in negative log-likelihood (NLL) and achieves better registration accuracy.
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Processamento de Imagem Assistida por Computador , Humanos , Processamento de Imagem Assistida por Computador/métodos , AlgoritmosRESUMO
Microplastics (MPs) and polycyclic aromatic hydrocarbons (PAHs) are toxic contaminants that have been found in marine ecosystems. This review aims to explore the sources and mechanisms of PAHs and MPs mixed contamination in marine environments. Understanding the released sources of PAHs and MPs is crucial for proposing appropriate regulations on the release of these contaminants. Additionally, the mechanisms of co-occurrence and the role of MPs in distributing PAHs in marine ecosystems were investigated in detail. Moreover, the chemical affinity between PAHs and MPs was proposed, highlighting the potential mechanisms that lead to their persistence in marine ecosystems. Moreover, we delve into the various factors influencing the co-occurrence, chemical affinity, and distribution of mixed contaminants in marine ecosystems. These factors, including environmental characteristics, MPs properties, PAHs molecular weight and hydrophobicity, and microbial interactions, were critically examined. The co-contamination raises concerns about the potential synergistic effects on their degradation and toxicity. Interesting, few studies have reported the enhanced photodegradation and biodegradation of contaminants under mixed contamination compared to their individual remediation. However, currently, the remediation strategies reported for PAHs and MPs mixed contamination are scarce and limited. While there have been some initiatives to remove PAHs and MPs individually, there is a lack of research specifically targeting the removal of mixed contaminants. This deficiency highlights the need for further investigation and the development of effective remediation approaches for the efficient remediation of PAHs and MPs from marine ecosystems.
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Ecossistema , Monitoramento Ambiental , Microplásticos , Hidrocarbonetos Policíclicos Aromáticos , Poluentes Químicos da Água , Água do Mar/químicaRESUMO
Citri Reticulatae Pericarpium is a traditional Chinese medicine with extremely high health benefits as well as clinical value. In vivo and in vitro tests have proved that its main active secondary metabolites are flavonoids. However, they have not been comprehensively analyzed up to now mainly due to lack of suitable analysis method. To solve this problem, a novel strategy based on precursor ions locked and targeted MS/MS analysis was proposed. Firstly, the database of the flavonoids previously isolated from Citri Reticulatae Pericarpium was established to obtain the characteristics of their precursor ions. Secondly, after performing the full MS scan of the extract, all compounds in the total ion chromatogram were extracted by Compound Discoverer software. Thirdly, the precursor ions of the flavonoids were locked from the extracted compounds according to their characteristics, forming a precursor ions list. Finally, the precursor ions in the constructed list were performed targeted MS/MS analysis for structures characterization. As a result, total 187 flavonoids were successfully identified, and except for flavones, flavonols as well as dihydroflavones, some chalcones were also characterized from Citri Reticulatae Pericarpium for the first time.