Background: Pesticide residue and its poor utilization remains problematic in agricultural development. To address the issue, a nano-pesticide has been developed by incorporating pesticide acetamiprid in porous silica nanoparticles. Results: This nano-pesticide had an acetamiprid loading content of 354.01 mg g⁻¹. Testing LC₅₀ value against tea aphids of the commercial preparation was three times that of the nano-pesticide. In tea seedlings (Camellia sinensis L.), acetamiprid was transported upward from the stem to the young leaves. On day 30, the average retained concentrations in tea leaves treated with the commercial preparation were about 1.3 times of that in the nano-pesticide preparation. The residual concentrations of dimethyl-acetamiprid in leaves for plants treated with the commercial preparation were about 1.1 times of that in the nano-pesticide preparation. Untargeted metabolomics of by LC–MS on the young leaves of tea seedlings under nano-pesticide and commercial pesticide treatments showed significant numbers of differentially expressed metabolites (P < 0.05 and VIP > 1). Between the nano-pesticide treatment group and the commercial preparation treatment group there were 196 differentially expressed metabolites 2 h after treatment, 200 (7^th day), 207 (21^st day), and 201 (30^th day) in negative ion mode, and 294 (2^nd h), 356 (7^th day), and 286 (30^th day) in positive ion mode. Preliminary identification showed that the major differentially expressed metabolites were glutamic acid, salicylic acid, p-coumaric acid, ribonic acid, glutamine, naringenin diglucoside, sanguiin H4, PG (34:2) and epiafzelechin. Conclusions: This work demonstrated that our nano-pesticide outperformed the conventional pesticide acetamiprid in terms of insecticidal activity and pesticide residue, and the absorption, transportation and metabolism of nano-pesticide in tea plant were different, which pave a new pathway for pest control in agricultural sector. Graphical

4,4′-dinitrocarbanilide (DNC) is a key component and marker residue of nicarbazin, which forms residues in edible tissue and then causes nephrotoxicity and hepatotoxicity in humans if used excessively. To simplify sample preparation and monitor the DNC rapidly and accurately, a comparable icELISA and lateral flow immunoassay (LFIA) was developed in this study. Briefly, the reaction parameters were explored for improving the sensitivity of icELISA and LFIA. Under the optimal conditions, methanol was selected as the extracting solvent for DNC in chicken, and 20- and 10-fold dilutions of sample extraction eliminated the matrix effect for icELISA and LFIA, separately. After sample pretreatment, the analysis properties of icELISA and LFIA were compared. The limit of detection of icELISA for DNC was 0.8 μg/kg, and the visual and quantitative limits of detection of LFIA were 8 and 2.5 μg/kg. Compared with icELISA, LFIA showed lower sensitivity but obvious advantages in terms of matrix tolerance and detection time (within 15 min). The sensitivity, specificity, and accuracy of the developed assays satisfied the detection requirement even if using simple sample pretreatment. This comparable icELISA and LFIA provided mutual verifiability methods for the accurate detection of DNC in chicken.

Objective: An optimized quick, easy, cheap, effective, rugged, and safe (QuEChERS) technique was investigated and compared with the conventional QuEChERS technique for the simultaneous analysis of fifty-three pesticide residues in safflower using ultra-high performance liquid chromatography–tandem mass spectrometry (UHPLC–MS/MS). Method: Graphitic carbon nitride (g-C₃N₄) consisting of a major amount of carbon and nitrogen with a large surface area was used as a QuEChERS adsorbent instead of graphitized carbon black (GCB) for safflower extraction purification. Validation experiments were performed using spiked pesticide samples, and real samples were analyzed. Results: The linearity of the modified QuEChERS technique was evaluated with high coefficients of determination (R-2) being higher than 0.99. The limits of detection were <10 μg/kg. The spiked recoveries ranged from 70.4% to 97.6% with a relative standard deviation of less than 10.0%. The fifty-three pesticides exhibited negligible matrix effects (<20%). Thiamethoxam, acetamiprid, metolachlor, and difenoconazole were detected in real samples using an established method. Conclusion: This work provides a new g-C₃N₄-based modified QuEChERS technique for multi-pesticide residue analysis in complex food matrices.

The simultaneous control of toxic cyanobacterial blooms and degradation of microcystins (MCs) remains a critical challenge for environmental risk reduction. Herein, we demonstrate the novel application of erythrosine (ERY), an Food and Drug Administration (FDA)-certified food additive, as a potent photoactive agent for concurrent control of cyanobacterial blooms and removal of microcystin-LR (MC-LR) contaminants. ERY treatment achieved effective growth inhibition of Microcystis aeruginosa. Mechanistic studies, including reactive oxygen species (ROS) quenching experiments, revealed that ERY-generated ROS caused comprehensive damage to cellular structures and photosynthesis systems. Notably, the ERY-treated samples showed a significantly greater reduction in extracellular MC-LR content compared to conventional H2O2 treatment, confirming its superior microcystin degradation efficiency. The degradation pathways of MC-LR were elucidated through LC-MS/MS analysis, with reactive sites confirmed by electrostatic potential (ESP) mapping and Fukui function calculations. Furthermore, ecotoxicological evaluation using Lemna minor and ERY decomposition kinetics (95.6% within 4 days) confirmed its minimal phytotoxicity and reduced secondary pollution risk. These findings position ERY as a promising and environmentally benign photosensitizer for harmful algal bloom mitigation.

Background: Short-chain organic acids (SCOAs) may have paradoxical effects on neurocognition, acting as either neuroprotective bioenergetic substrates or potential neurotoxicants. However, the joint effects of SCOA mixtures on cognitive impairment and the mechanisms underlying their divergent associations remain unclear. Objective: To investigate the joint effects of serum SCOAs mixtures on cognitive impairment and elucidate underlying mechanisms. Methods: Serum levels of 11 SCOAs were quantified in 4192 older adults. Logistic regression and Bayesian kernel machine regression (BKMR) were used to assess individual and mixture associations with cognitive impairment. Potential targets were screened from public databases, intersected with cognitive impairment-related genes, and mapped to protein-protein interaction networks. Core targets were validated using four machine learning algorithms. Functional enrichment and molecular docking analyses were performed to explore potential mechanisms. Results: In adjusted models, β-hydroxybutyric, butyric, and propionic acids were inversely associated with cognitive impairment, whereas isobutyric and crotonic acids were positively associated. BKMR revealed a non-linear joint effect, with the overall association shifting from positive to negative when the mixture quantile exceeded 0.5; butyric acid showed an inverted U-shaped relationship. Network analysis identified two functional groups: the inverse group centered on GAPDH, AKT1, CASP3, NFKB1, and STAT3 and was enriched in PI3K-Akt and insulin signaling, whereas the positive group centered on ribosomal proteins and HSP90AA1, implicating ribosomal stress and NOD-like receptor signaling. Conclusions: Serum SCOAs showed divergent associations with cognitive impairment. Bioenergetic metabolites were linked to putative neuroprotective signaling, whereas risk-associated metabolites were linked to ribosomal stress signatures.