A new solid phase extraction sorbent developed based on cyanopropyl functionalized silica nanoparticles for organophosphorus pesticides determination

Rational design of mixed-ligand metal-organic framework with dual emission signals for real-time visual detection and efficient adsorption of glyphosate in water

Glyphosate residues have raised significant concerns owing to their detrimental effects on public health and ecosystems. The development of adsorbents capable of simultaneous visual detection and removal of glyphosate remains challenging. In this study, a fluorescent zirconium-based metal-organic framework (BDC/TCPP-MOF) with dual emission signals was synthesized through a mixed-ligand strategy. The BDC/TCPP-MOF demonstrated remarkable selectivity and sensitivity for ratiometric fluorescence detection of glyphosate, achieving a limit of detection as low as 70 nmol/L (11.8 μg/L). Notably, the BDC/TCPP-MOF-based fluorescence sensor exhibited a distinct color transition from pink to blue during glyphosate detection. Furthermore, a portable hydrogel-based detection platform integrated with smartphone was developed, enabling rapid, real-time quantitative detection of glyphosate across a wide concentration range. The BDC/TCPP-MOF also demonstrated excellent glyphosate adsorption capacity (up to 116.85 mg/g) from water. Extensive characterisations demonstrate that visual recognition and efficient adsorption are primarily attributed to glyphosate-Zr-OH interactions, hydrogen bonding, and electrostatic interactions. This study not only provides valuable insights for the design of multifunctional MOF materials but also establishes a novel dual-functional material for visual detection and adsorption of glyphosate in water, demonstrating substantial potential for environmental pollution monitoring applications.

Synthesis of flower-like polyamine/C18 dual-functional magnetic titanium dioxide-based oligopolymer microspheres and their application for the purification, detection and dietary exposure assessment of 52 pesticides in bayberry samples

Novel core-shell flower-like polyamine/C18 dual-functional magnetic titanium dioxide-based oligopolymer (Fe3O4@fTiO2-PAPMA/C18) microspheres were synthesized and used as a magnetic solid-phase extraction (MSPE) adsorbent to purify 52 pesticides in bayberry samples. The Fe3O4@fTiO2-PAPMA/C18 microspheres were fully characterized and it can obviously improve the purification ability of 52 pesticides in bayberry samples. Coupled to LC-MS/MS, the developed method indicated low limits of detection (LODs) and limits of quantification (LOQs) of 0.1-1.0 μg/kg and 0.3-3.0 μg/kg, respectively. Recoveries in bayberry samples ranged from 71.1 % to 108 %, with relative standard deviations (RSDs) of 1.5 % ∼ 9.6 % at four spiking levels. The established MSPE-LC-MS/MS method was employed to analyze 52 pesticide residues in 374 bayberry samples, and the top five pesticides with the highest detection rate were phenylether metronidazole, pyraclostrobin, carbendazim, imidacloprid and tebuconazole. Furthermore, the risk assessment to the 30 pesticides showed that the levels of pesticides found in bayberry samples do not pose a health risk.

MXene-based materials for enhanced water quality: Advances in remediation strategies

Two-dimensional MXenes are promising candidates for water treatment because of their large surface area (e.g., exceeding 1000 m²/g for certain structures), high electrical conductivity (e.g., >1000 S/m), hydrophilicity, and chemical stability. Their strong sorption selectivity and effective reduction capacity, exemplified by heavy metal adsorption efficiencies exceeding 95 % in several studies, coupled with facile surface modification, make them suitable for removing diverse contaminants. Applications include the removal of heavy metals (e.g., achieving >90 % removal of Pb(II)), dye removal (e.g., demonstrating >80 % removal of methylene blue), and radioactive waste elimination. Furthermore, 3D MXene architecture exhibit enhanced performance in antibacterial activities (e.g., against bacteria), desalination rejection percentage, and photocatalytic degradation of organic contaminants. However, several challenges have remained, which necessitate further investigation into toxicity (e.g., assessing effects on aquatic organisms), scalability, and cost-effectiveness of large-scale production. This review summarizes recent advancements in 3D MXene-based functional materials for wastewater treatment and water remediation, critically analyzing their both potential and limitations.

Removal of chlorpyrifos from aqueous medium using Ca-CuO@clay nanoflakes coated with deep eutectic solvent

Availability of fresh water for domestic, industrial, and agricultural use has become a huge challenge in different parts of the world due to continuous contamination. The leaching of different pesticides in agricultural lands is one of the major sources of water contamination that needs to be monitored and countered. The current study was designed to synthesize specific material for the removal of pesticides from aqueous medium. Facile two-step synthesis of Ca-CuO bimetallic nanoparticles (NPs) with kaolinite core (Ca-CuO@clay) was achieved via the co-precipitation method. These NPs were then coated with deep eutectic solvent (DES) and characterization of coated and non-coated NPs was done by SEM, EDX, XRD method, and FTIR analytical techniques. These analyses confirmed the formation of Ca-CuO@clay NPs and coated NPs were found having dual layer structure; an inner layer composed of Ca-CuO@clay nanoparticles, and an outer layer of DES. Both the coated and non-coated nanoparticles were tested for pesticide removal potential and degradation of the pesticide was confirmed by GCMS analysis. Degradation of Chlorpyrifos up to 62% and 89% was achieved using the coated and non-coated nanoparticles respectively. The results revealed that coating of nanomaterial with DES will be helpful in controlling the surface properties, shelf-life, and stability of the NPs that will surely modify their efficiency for different applications. The authors suggest that Ca-CuO@clay NPs can be an excellent choice towards improving wastewater treatment technologies for the removal of pesticides from water medium.

Easy and fast synthesis of MnCo-LDH yolk-shell spheres porous composites applied electrospinning nanofibers highly effective for extracting triazole fungicides

Today, the wide utilization of triazole fungicides due to environmental damage and its side effects has raised global concern. Thus, in this investigation, polyacrylonitrile/MnCo-layered double hydroxides nanofiber was synthesized and applied as an effective and novel adsorbent at thin-film solid-phase micro-extraction technique for the quick and concurrent extraction of five triazole fungicides in fruit and vegetable samples before quantitative analysis by high-performance liquid chromatography-ultraviolet. The incorporation of MnCo-layered double hydroxides with porous structure and abundant functional groups in a polymer medium improves the extraction efficiency of nanofibers owing to hydrogen bonding and π-π interactions formed between analytes and synthesized nano-adsorbent. Various important elements that affect the extraction efficiency of the intended analytes were optimized using a time-variable approach. Under the optimum conditions, the limit of detection and quantification range from 0.1 to 0.15 and 0.3-0.5 ng mL-1, respectively.

Sustainable approach for the expulsion of metaldehyde: risk, interactions, and mitigation: a review

All pests can be eliminated with the help of pesticides, which can be either natural or synthetic. Because of the excessive use of pesticides, it is harmful to both ecology and people's health. Pesticides are categorised according to several criteria: their chemical composition, method of action, effects, timing of use, source of manufacture, and formulations. Many aquatic animals, birds, and critters live in danger owing to hazardous pesticides. Metaldehyde is available in various forms and causes significant impact even when small amounts are ingested. Metaldehyde can harm wildlife, including dogs, cats, and birds. This review discusses pesticides, their types and potential environmental issues, and metaldehyde's long-term effects. In addition, it examines ways to eliminate metaldehyde from the aquatic ecosystem before concluding by anticipating how pesticides may affect society. The metal-organic framework and other biosorbents have been appropriately synthesized and subsequently represent the amazing removal of pesticides from effluent as an enhanced adsorbent, such as magnetic nano adsorbents. A revision of the risk assessment for metaldehyde residuals in aqueous sources is also attempted.

Utilizing nanotechnology and advanced machine learning for early detection of gastric cancer surgery

Nanotechnology has emerged as a promising frontier in revolutionizing the early diagnosis and surgical management of gastric cancers. The primary factors influencing curative efficacy in GIC patients are drug inefficacy and high surgical and pharmacological therapy recurrence rates. Due to its unique optical features, good biocompatibility, surface effects, and small size effects, nanotechnology is a developing and advanced area of study for detecting and treating cancer. Considering the limitations of GIC MRI and endoscopy and the complexity of gastric surgery, the early diagnosis and prompt treatment of gastric illnesses by nanotechnology has been a promising development. Nanoparticles directly target tumor cells, allowing their detection and removal. It also can be engineered to carry specific payloads, such as drugs or contrast agents, and enhance the efficacy and precision of cancer treatment. In this research, the boosting technique of machine learning was utilized to capture nonlinear interactions between a large number of input variables and outputs by using XGBoost and RNN-CNN as a classification method. The research sample included 350 patients, comprising 200 males and 150 females. The patients' mean ± SD was 50.34 ± 13.04 with a mean age of 50.34 ± 13.04. High-risk behaviors (P = 0.070), age at diagnosis (P = 0.034), distant metastasis (P = 0.004), and tumor stage (P = 0.014) were shown to have a statistically significant link with GC patient survival. AUC was 93.54%, Accuracy 93.54%, F1-score 93.57%, Precision 93.65%, and Recall 93.87% when analyzing stomach pictures. Integrating nanotechnology with advanced machine learning techniques holds promise for improving the diagnosis and treatment of gastric cancer, providing new avenues for precision medicine and better patient outcomes.