Harmful Molecules Research Articles

Architectural dissection of adhesive bacterial cell surface appendages from a "molecular machines" viewpoint.

The ability of bacteria to interact with and respond to their environment is crucial to their lifestyle and survival. Bacterial cells routinely need to engage with extracellular target molecules, in locations spatially separated from their cell surface. Engagement with distant targets allows bacteria to adhere to abiotic surfaces and host cells, sense harmful or friendly molecules in their vicinity, as well as establish symbiotic interactions with neighboring cells in multicellular communities such as biofilms. Binding to extracellular molecules also facilitates transmission of information back to the originating cell, allowing the cell to respond appropriately to external stimuli, which is critical throughout the bacterial life cycle. This requirement of bacteria to bind to spatially separated targets is fulfilled by a myriad of specialized cell surface molecules, which often have an extended, filamentous arrangement. In this review, we compare and contrast such molecules from diverse bacteria, which fulfil a range of binding functions critical for the cell. Our comparison shows that even though these extended molecules have vastly different sequence, biochemical and functional characteristics, they share common architectural principles that underpin bacterial adhesion in a variety of contexts. In this light, we can consider different bacterial adhesins under one umbrella, specifically from the point of view of a modular molecular machine, with each part fulfilling a distinct architectural role. Such a treatise provides an opportunity to discover fundamental molecular principles governing surface sensing, bacterial adhesion, and biofilm formation.

Research Advances of Cellular Nanoparticles as Multiplex Countermeasures.

Cellular nanoparticles (CNPs), fabricated by coating natural cell membranes onto nanoparticle cores, have been widely used to replicate cellular functions for various therapeutic applications. Specifically, CNPs act as cell decoys, binding harmful molecules or infectious pathogens and neutralizing their bioactivity. This neutralization strategy leverages the target's functional properties rather than its structure, resulting in broad-spectrum efficacy. Since their inception, CNP platforms have undergone significant advancements to enhance their neutralizing capabilities and efficiency. This review traces the research advances of CNP technology as multiplex countermeasures across four categories with progressive functions: neutralization through cell membrane binding, simultaneous neutralization using both cell membrane and nanoparticle core, continuous neutralization via enzymatic degradation, and enhanced neutralization through membrane modification. The review highlights the structure-property relationship in CNP designs, showing the functional advances of each category of CNP. By providing an overview of CNPs in multiplex neutralization of a wide range of chemical and biological threat agents, this article aims to inspire the development of more advanced CNP nanoformulations and uncover innovative applications to address unresolved medical challenges.

Glycation Produces Topologically Different α-Synuclein Oligomeric Strains and Modulates Microglia Response via the NLRP3-Inflammasome Pathway.

α-Synuclein, a key player in Parkinson's disease and other synucleinopathies, possesses an inherently disordered structure that allows for versatile structural changes during aggregation. Microglia, the brain immune cells, respond differently to various α-synuclein strains, influencing their activation and release of harmful molecules, leading to neuronal death. Post-translational modifications, such as glycation in α-synuclein, add a layer of complexity to microglial activation. This study aimed to explore the impact of glycation on α-synuclein aggregation and microglial responses, which have not been studied before. Biophysical analyses revealed that glycated α-synuclein oligomers had distinct morphologies with a more negative and hydrophobic surface, preventing fibril formation and interfering with membrane interactions. Notably, there was increased cytosolic Ca2+ dysregulation, redox stress, and mitochondrial instability compared to cells exposed to unmodified α-synuclein oligomers. Additionally, glycated α-synuclein oligomers exhibited impaired binding to Toll-like receptor 2, compromising downstream signaling. Surprisingly, these oligomers promoted TLR4 endocytosis and degradation. In our experiments with oligomers, glycated α-synuclein oligomers preferred NLRP3 inflammasome-mediated neuroinflammation, contributing differently from unmodified α-synuclein oligomers. In summary, this study unveils the mechanism underlying the effect of glycation on α-synuclein oligomers and highlights the conformation-specific microglial responses toward extracellular α-synuclein.

Effects of mulch films with different thicknesses on the microbial community of tobacco rhizosphere soil in Yunnan laterite.

The mulch film (MF) management model of the agricultural field affects the physical and chemical properties of soil (PCPS) and the structure of the microorganism community; however, studies on the relationship between the rhizosphere microorganism community structure and the thickness of MF are still limited. To understand the interactions among the MF thickness, PCPS, and rhizosphere microorganism, a study was conducted by using an integrated metagenomic strategy, where tobacco rhizosphere soil was treated with four commonly representative and used thicknesses of MFs (0.004, 0.006, 0.008, and 0.010 mm) in Yunnan laterite. The results showed that agronomic traits such as the tobacco plant height (TPH), leaf number (LN), fresh leaf weight (FLW), and dry leaf weight (DLW) were significantly (p < 0.01) improved in the field mulched with the thickest film (0.010 mm) compared with the exposed field (CK), and there was a 6.81 and 5.54% increase in the FLW and TPH, separately. The correlation analyses revealed a significant positive correlation of the MF thickness with the soil water content (SWC), soil organic matter (SOM), total nitrogen (TN), available nitrogen (AN), total phosphorus (TP), and available phosphorus (AP; all p < 0.01), while the MF thickness was negatively correlated with the soil temperature (ST; p < 0.01). In addition, the community structure of the rhizosphere soil bacteria was significantly changed overall by the MF thickness, which also interfered with the function of the rhizosphere soil bacteria. The correlation analyses also showed that the abundance of Bradyrhizobium and Nitrospira was positively correlated with the MF thickness, while the abundance of Sphinsinomonas and Massilia was negatively correlated with it. This indicated that with the increase of the MF thickness, the ability of the rhizosphere soil to utilize N and remove harmful molecules was strengthened, while the capacity of the rhizosphere soil to degrade pollutants was greatly reduced. These findings provide additional insights into the potential risks of the application of different thicknesses of MFs, particularly concerning the PCPS and soil microbial communities.

The contribution of porins to enterobacterial drug resistance.

In Enterobacteriaceae, susceptibility to cephalosporins and carbapenems is often associated with membrane and enzymatic barrier resistance. For about 20 years, a large number of Klebsiella pneumoniae, Escherichia coli and Enterobacter cloacae presenting ß-lactam resistance have been isolated from medical clinics. In addition, some of the resistant isolates exhibited alterations in the outer membrane porin OmpC-OmpF orthologues, resulting in the complete absence of gene expression, replacement by another porin or mutations affecting channel properties. Interestingly, for mutations reported in OmpC-OmpF orthologues, major changes in pore function were found to be present in the gene encoding for OmpC. The alterations were located in the constriction region of the porin and the resulting amino acid substitutions were found to induce severe restriction of the lumen diameter and/or alteration of the electrostatic field that governs the diffusion of charged molecules. This functional adaptation through porins maintains the entry of solutes necessary for bacterial growth but critically controls the influx of harmful molecules such as β-lactams at a reduced cost. The data recently published show the importance of understanding the underlying parameters affecting the uptake of antibiotics by infectious bacteria. Furthermore, the development of reliable methods to measure the concentration of antibiotics within bacterial cells is key to combat impermeability-resistance mechanisms.

Hepatocyte-Specific Yap1 Knockout Maintained the Liver Homeostasis of Lipid Metabolism in Mice.

Yes-associated protein 1 (YAP1) is a crucial molecule in the Hippo pathway. The impact of hepatocyte-specific Yap1 knockout (Yap1 LKO) on hepatic lipid droplets (LD) and pePLIN2 in metabolic fatty liver has not been reported. This study aims to explore whether Yap1 LKO could offer a protective effect in a liver injury model. Three-week-old Yap1 LKO and Yap1 Flox mice were given aristolochic acid I (AAI) combined carbon tetrachloride (CCL4) establish liver injury model. Eight-week-old Yap1 LKO and Yap1 Flox mice were fed with a high-fat diet for 18 weeks to establish obesity-related liver injury model. Further biochemical, histomorphological, immunohistochemical, and lipidomic analyses were performed on serum and liver tissues of these mice to elucidate the effects of hepatocyte-specific Yap1 knockout on hepatic lipid metabolism. Yap1 LKO reduced triglyceride (TG) content and PLIN2 expression level in the liver during the intervention of AAI combined CCl4. Moreover, Yap1 LKO improved lipid metabolism homeostasis in the liver by increasing the beneficial lipid molecules and reducing the harmful lipid molecules through lipidomics. Finally, Yap1 LKO reduced TG content in the serum and liver, hepatic vacuolar degeneration, and hepatic PLIN2 expression level in mice fed with a high-fat diet (HFD). Yap1 LKO is protective in regulating liver and blood TG when induced with toxic substances AAI combined CCl4 and a high-fat diet.

Association of ultraprocessed food consumption with risk of microvascular complications among individuals with type 2 diabetes in the UK Biobank: a prospective cohort study

BackgroundThe poor nutritional characteristics and potentially harmful molecules in ultraprocessed foods (UPFs) are risk factors for diabetic microvascular complications. However, the evidence regarding UPFs and diabetic microvascular complications remains limited. ObjectivesWe aimed to evaluate the associations between UPF consumption and risk of diabetic microvascular complications, to examine the underlying biological pathways (e.g., inflammation and lipid profile), and to identify whether the associations differ by type of UPF dietary patterns. MethodsWe included a prospective cohort of UK Biobank participants with type 2 diabetes (T2D) having at least one 24-h dietary recall (N = 5685). UPFs were defined using the Nova classification. Principal component analysis was used to derive UPF consumption patterns. Associations of UPFs and their consumption patterns with microvascular complications were assessed using Cox proportional hazards regression models. Mediation analyses were used to estimate the mediating effects of 22 biomarkers. ResultsDuring a median of 12.7 y of follow-up, 1243 composite microvascular complications events occurred (599 diabetic retinopathy, 237 diabetic neuropathy, and 662 diabetic kidney disease events). Five consumption patterns were identified (spread and bread, cereal prepared with liquids, dairy-based products, sugary beverage and snack, and mixed beverage and savory snack patterns). A 10% increment in the proportion of UPF was associated with higher hazards of the composite microvascular complications (hazard ratio [HR]: 1.08; 95% confidence interval [CI]: 1.03, 1.13) and diabetic kidney disease (HR: 1.13; 95% CI: 1.06, 1.20). Triglycerides, C-reactive protein, and body mass index collectively explained 22.0% (9.6%–43.0%) of the association between UPF intake and composite microvascular complications. Pattern high in mixed beverage and savory snack was associated with a higher risk of composite microvascular complications. ConclusionsHigher UPF consumption was associated with higher risks of diabetic microvascular complications, and the association was partly mediated through multiple potential ways.

Adsorption performance of harmful gas molecules over copper decorated aluminene: a DFT study

Adsorption performance of harmful gas molecules over copper decorated aluminene: a DFT study

Feature Selection AI Technique for Predicting Chronic Kidney Disease

The kidney is a vital organ that plays a crucial role in eliminating waste and excess water from the bloodstream. When renal function is impaired, the filtration process also ceases. This leads to an elevation of harmful molecules in the body, a condition referred to as chronic kidney disease (CKD). Early-stage chronic kidney disease often lacks noticeable symptoms, making it challenging to detect in its early stages. Diagnosing chronic kidney disease (CKD) typically involves advanced blood and urine tests, but unfortunately, by the time these tests are conducted, the disease may already be life-threatening. Our research focuses on the early prediction of chronic kidney disease (CKD) using machine learning (ML) and deep learning (DL) techniques. Utilized a dataset from the machine learning repository at the University of California, Irvine (UCI) to train various machine learning algorithms in conjunction with a Convolutional Neural Network (CNN) model. The algorithms encompassed in this set are Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), and Gradient Boosting (GB). Based on the experimental results, the CNN model achieves a prediction accuracy of precisely 97% after feature selection, the highest among all models tested. Hence, the objective of this project is to develop a deep learning-based prediction model to aid healthcare professionals in the timely identification of chronic kidney disease (CKD), potentially leading to life-saving interventions for patients.

Adsorption configuration, electronic structure and spectra of the harmful NH3, NO, and NO2 molecules on a bilayer boron cluster

Density functional theory (DFT) calculations were performed to investigate the adsorption configuration, electronic structure and spectra of a bilayer B48 cluster with NH3, NO, and NO2 adsorptions. The B48 shows a high affinity for NH3 and NO2 molecules and a medium adsorption ability for NO. The high binding strength of the B48 cluster for these gases originates from the direct B–N bonds corresponding to partially covalent characters. The energy gap changes are in the order of NO2 > NH3 > NO. The recovery time of the B48 for different gases can be adjusted to a reasonable range by increasing the temperature. Infrared (IR) and ultraviolet–visible (UV–vis) spectra were in detail analyzed before and after gas adsorptions for the identification of the adsorption structures in further experiments. Along with gas adsorption, the B48 cluster exhibits vastly different spectral characteristics. Our results indicate that the B48 shows promising sensor performance for studied gases, in particular for NO molecules, and can be considered as potential gas sensor candidates.

A Biodegradable Fiber Calcium Ion Sensor by Covalently Bonding Ionophores on Bioinert Nanoparticles.

Implantable sensors, especially ion sensors, facilitate the progress of scientific research and personalized healthcare. However, the permanent retention of implants induces health risks after sensors fulfill their mission of chronic sensing. Biodegradation is highly anticipated; while; biodegradable chemical sensors are rare due to concerns about the leakage of harmful active molecules after degradation, such as ionophores. Here, a novel biodegradable fiber calcium ion sensor is introduced, wherein ionophores are covalently bonded with bioinert nanoparticles to replace the classical ion-selective membrane. The fiber sensor demonstrates comparable sensing performance to classical ion sensors and good flexibility. It can monitor the fluctuations of Ca2+ in a 4-day lifespan in vivo and biodegrade in 4 weeks. Benefiting from the stable bonding between ionophores and nanoparticles, the biodegradable sensor exhibits a good biocompatibility after degradation. Moreover, this approach of bonding active molecules on bioinert nanoparticles can serve as an effective methodology for minimizing health concerns about biodegradable chemical sensors.

Bio‐inspired hierarchical bamboo‐based air filters for efficient removal of particulate matter and toxic gases

AbstractAir pollution is caused by the perilous accumulation of particulate matter (PM) and harmful gas molecules of different sizes. There is an urgent need to develop highly efficient air filtration systems capable of removing particles with a wide size distribution. However, the efficiency of current air filters is compromised by controlling their hierarchical pore size. Inspired by the graded filtration mechanisms in the human respiratory system, microporous ZIF‐67 is in situ synthesized on a 3D interconnected network of bamboo cellulose fibers (BCFs) to fabricate a multiscale porous filter with a comprehensive pore size distribution. The macropores between the BCFs, mesopores formed by the BCF microfibers, and micropores within the ZIF‐67 synergistically facilitate the removal of particulates of different sizes. The filtration capabilities of PM2.5 and PM0.3 could reach 99.3% and 98.6%, respectively, whereas the adsorption of formaldehyde is 88.7% within 30 min. In addition, the filter exhibits excellent antibacterial properties (99.9%), biodegradability (80.1% degradation after 14 days), thermal stability, and skin‐friendly properties (0 irritation). This study may inspire the research of using natural features of renewable resources to design high‐performance air‐filtration materials for various applications.

A machine learning based prediction of reaction parameters on reaction kinetics for treatment of industrial wastewater

Industrial wastewater is a major cause of pollution of surface water bodies since it is often discharged into these water bodies without adequate treatment. Past attempts at treating industrial wastewater have led to the emergence of multiple approaches for the removal of impurities. These include conventional techniques like biological, physical, and chemical techniques, and recently advanced oxidation processes that have, under certain specific conditions, produced desired results through decomposing contaminating organic compounds into water, carbon dioxide, or less harmful molecules. This study examines the removal of phenol in industrial wastewater using a Photo-Fenton reagent on account of its cost-effectiveness and the possibility of rapid results. The effectiveness of the removal of contaminants was assessed based on the rate of reaction (k1). Data collected through laboratory experiments was then put through various Machine Learning classifiers including Neural Network, CHAID, Generalized Linear Model, Linear Classifier, and Random Trees using IBM SPSS Modeler and models trained. An accuracy of 97.2 % was observed for the Deep Neural Network. Further, it is observed that for a specific level of impurities in industrial water, the pH of solution, intensity of light, and amount of Hydrogen Peroxide (H2O2) are the most important factors in predicting the rate of reaction with concentration of [Fe3+] ions and catalyst TiO2 playing smaller roles.

Halogen-doped CQDs as a modulation of fractional function sensing in ZIF composites

This study draws inspiration from the partition-function sensing mechanism of plant cells for purifying harmful gas molecules. The size of the pore size of ZIF-8 sieving gas molecules was modulated by halogen-doped carbon quantum dots (CQDs) during the formation of ZIF-8. Notably, the difference in electronegativity of different halogens makes the sieving pore size of ZIF-8 tunable in the nanometer range, which greatly enhances the selectivity of the composite. In addition, the halogen-doped carbon quantum dots modulate the structure, band gap, and impedance of the composites, enabling the detection of specific gases on the order of ppb. Using X-ray photoelectron spectroscopy, simulation data and density-functional theory, we find that halogen-doped CQDs can fine-tune the pore size of ZIF-8 by influencing the chemical bond lengths by affecting the positions of atoms on the imidazole ring. Plants in nature are similarly characterized in that different components act as sensors for characteristic gas components and synergistically promote the adsorption and purification processes of gas molecules. This study provides an innovative means of modifying the structure and properties of ZIF materials and introduces the concept of plant-like gas multi-sensing in the field of gas sensing research.

Integrated insulin-iron nanoparticles: a multi-modal approach for receptor-specific bioimaging, reactive oxygen species scavenging, and wound healing

Metallic nanoparticles have emerged as a promising option for various biological applications, owing to their distinct characteristics such as small size, optical properties, and ability to exhibit luminescence. In this study, we have successfully employed a one-pot method to synthesize multifunctional insulin-protected iron [Fe(II)] nanoparticles denoted as [IFe(II)NPs]. The formation of IFe(II)NPs is confirmed by the presence of FTIR bonds at 447.47 and 798.28 cm−1, corresponding to Fe–O and Fe–N bonds, respectively. Detailed analysis of the HR-TEM-EDS-SAED data reveals that the particles are spherical in shape, partially amorphous in nature, and have a diameter of 28.6 ± 5.2 nm. Additionally, Metal Ion Binding (MIB) and Protein Data Bank (PDB) analyses affirm the binding of iron ions to the insulin hexamer. Our findings underscore the potential of IFe(II)NPs as a promising new platform for a variety of biomedical applications due to their high signal-to-noise ratio, and minimal background fluorescence. The particles are highly luminescent, biocompatible, and have a significant quantum yield (0.632). Exemplar applications covered in this paper include insulin receptor recognition and protection against reactive oxygen species (ROS), harmful molecules known to inflict damage on cells and DNA. The IFe(II)NPs effectively mitigate ROS-induced inflammation, which is a hinderance to wound recovery, thereby facilitating enhanced wound recovery.Graphical abstract

Uniform monolayer of branched silver nanoplates-assembled nanoparticles for sensitive and reproducible SERS detection of harmful molecules

Surface-enhanced Raman scattering (SERS) technique can offer the fingerprint information of trace substances, and thus has wide potential applications in many fields. There is still a requirement to develop new and effective methods to construct high-performance SERS substrates. Here, a facile electrodeposition method is presented for fabricating large-scale uniform films assembled by branched silver (Ag) nanoplates. The morphology and structure of such film are highly uniform over a large area, which can ensure good spectral uniformity and reproducibility. There are dense sub-10 nm gaps between neighboring Ag nanoplates and between neighboring branches, forming plenty of hot spots. Therefore, the Ag nanoparticle monolayer exhibits high SERS activity along with excellent spectral repeatability. It is found that the limits of detection (LODs) towards rhodamine 6G and 4-aminothiophenol can reach 0.387 pM and 49.0 pM, respectively, showing high sensitivity of the designed SERS substrate. The enhancement factor of the prepared roughened Ag nanoparticle monolayer is computed to be as large as 2.37 × 108. Then, the highly roughened nanoparticle monolayer is used to detect cationic dye and fungicide (methylene blue, MB) and a synthetic cytokinin (6-benzylaminopurine, 6-BAP), and the corresponding LODs are determined down to 1.1 nM and 28.8 pM, respectively. Such LODs are much lower than the tolerance for MB and 6-BAP residues established by some authoritative regulations. Sensitive monitoring of 6-BAP residue on vegetables and fruits can also be achieved using such SERS substrate, indicating its promising application in environment monitoring and food safety supervision.

Advancements and recent explorations of anti-cancer activity of chrysin: from molecular targets to therapeutic perspective.

In recent times, there have been notable advancements in comprehending the potential anti-cancer effects of chrysin (CH), a naturally occurring flavonoid compound found abundantly in various plant sources like honey, propolis, and certain fruits and vegetables. This active compound has garnered significant attention due to its promising therapeutic qualities and minimal toxicity. CH's ability to combat cancer arises from its multifaceted mechanisms of action, including the initiation of apoptosis and the inhibition of proliferation, angiogenesis, metastasis, and cell cycle progression. CH also displays potent antioxidant and anti-inflammatory properties, effectively counteracting the harmful molecules that contribute to DNA damage and the development of cancer. Furthermore, CH has exhibited the potential to sensitize cancer cells to traditional chemotherapy and radiotherapy, amplifying the effectiveness of these treatments while reducing their negative impact on healthy cells. Hence, in this current review, the composition, chemistry, mechanisms of action, safety concerns of CH, along with the feasibility of its nanoformulations. To conclude, the recent investigations into CH's anti-cancer effects present a compelling glimpse into the potential of this natural compound as a complementary therapeutic element in the array of anti-cancer approaches, providing a safer and more comprehensive method of combating this devastating ailment.

Regulation of immune responses to infection through interaction between stem cell-derived exosomes and toll-like receptors mediated by microRNA cargoes.

Infectious diseases are among the factors that account for a significant proportion of disease-related deaths worldwide. The primary treatment approach to combat microbial infections is the use of antibiotics. However, the widespread use of these drugs over the past two decades has led to the emergence of resistant microbial species, making the control of microbial infections a serious challenge. One of the most important solutions in the field of combating infectious diseases is the regulation of the host's defense system. Toll-like receptors (TLRs) play a crucial role in the first primary defense against pathogens by identifying harmful endogenous molecules released from dying cells and damaged tissues as well as invading microbial agents. Therefore, they play an important role in communicating and regulating innate and adaptive immunity. Of course, excessive activation of TLRs can lead to disruption of immune homeostasis and increase the risk of inflammatory reactions. Targeting TLR signaling pathways has emerged as a new therapeutic approach for infectious diseases based on host-directed therapy (HDT). In recent years, stem cell-derived exosomes have received significant attention as factors regulating the immune system. The regulation effects of exosomes on the immune system are based on the HDT strategy, which is due to their cargoes. In general, the mechanism of action of stem cell-derived exosomes in HDT is by regulating and modulating immunity, promoting tissue regeneration, and reducing host toxicity. One of their most important cargoes is microRNAs, which have been shown to play a significant role in regulating immunity through TLRs. This review investigates the therapeutic properties of stem cell-derived exosomes in combating infections through the interaction between exosomal microRNAs and Toll-like receptors.

Plasmon AgNPs/MoS2/ZnO nanorods array ternary heterojunctions enabling high-efficiency solar-light energy utilization for photocatalysis and recyclable SERS detection

BackgroundSurface-enhanced Raman scattering (SERS) has gained widespread use in molecule-level detection benefiting from its high sensitivity, nondestructive data acquisition, and capacity for providing molecular fingerprint information. However, the strong adhesion of target molecules to the substrate (known as the “memory effect”) inherently hinders the reusability of SERS substrates. Research has shown that self-cleaning SERS substrates based on versatile semiconductor materials with SERS enhancement capabilities and solar photocatalytic properties offer an effective platform for the sensitive detection and degradation of harmful molecules. ResultsIn this research, a resuable SERS-active substrate was facilely fabricated by anchoring silver nanoparticles (AgNPs) to the edges of MoS2 nanosheet decorated on ZnO nanorod arrays (NRAs). This innovative design exhibited a remarkable SERS enhancement factor (EF) of 4.6 × 107 and demonstrated significant solar photocatalytic efficiency. Such superior characteristics of ternary plasma heterojunction were ascribable to the synergistic effect of the “Schottky barrier” and “hot spots” between MoS2 and AgNPs, the inherent chemical enhancement proficiency of the MoS2/ZnO NRAs heterojunction, as well as the ultrafast electron transfer within the ternary heterojunction. SignificanceThe developed ternary heterojunction substrate enabled highly sensitive SERS detection of trace amounts of organic molecules. Moreover, this SERS substrate exhibited self-cleaning and recyclability via solar-light-driven photocatalysis. This bifunctional recyclable SERS substrate proved capable of meeting various requirements for routine monitoring of environmental organic pollutants and provided a robust avenue for advancing energy utilization materials that serve as high-performance SERS sensors and catalysts.

Synergistic effect between p-n heterojunction and oxygen vacancies of Co3O4-C/Fe-MOF for highly sensitive detection of trace atrazine

Atrazine is a type of herbicide widely used in agricultural production, and trace atrazine would cause human hormone disorders and even lead to cancer and cancer-related diseases. There are still significant challenges in the highly sensitive detection of trace atrazine. Herein, a Co3O4-C/Fe-MOF with p-n heterojunction and oxygen vacancies was theoretically predicted, and it had potential interactions with atrazine. Leaf-shaped Co3O4-C/Fe-MOF with p-n heterojunction and oxygen vacancies was in-suit constructed on the surface of foam nickel by self-assembly strategy. The electrochemical detection results showed that the Co3O4-C/Fe-MOF electrochemical sensor achieved ultra-low detection concentration (0.06 pM) and ultra-high detection sensitivity (60.32 μA/pMcm2) within an ultra-wide concentration range (1 pM-5 mM). The Co3O4-C/Fe-MOF electrochemical sensor was successfully applied for the detection of atrazine in real samples. In addition, theoretical calculations and experimental analysis systematically reveal the detection mechanism. The rich oxygen vacancies enhanced the adsorption of atrazine, and the p-n heterojunctions promoted electronic transitions to the material surface and react quickly with atrazine. The synergistic effect between p-n heterojunctions and oxygen vacancies promoted the electrochemical reaction kinetics of atrazine. This study provides a new strategy for designing active composite materials to achieve highly sensitive detection of harmful small molecules.