Multiresidue extraction of current-use pesticides from complex solid matrices using energized dispersive guided extraction with analysis by gas and liquid chromatography tandem mass spectroscopy.

The development of sample processing techniques that recover a broad suite of pesticides from solid matrices, while mitigating coextracted matrix interferences, and reducing processing time is beneficial for high throughput analyses. The objective of this study was to evaluate the effectiveness of an automated extraction system for pesticide analyses in solid environmental samples. An Energized Dispersive Guided Extraction (EDGE) system was used to evaluate two different extraction solvents in optimizing the extraction of 210 pesticides and pesticide transformation products. A graphitized carbon cleanup step was implemented, and three elution solvents were evaluated separately for analyte recoveries. Recoveries between 70 and 130% were achieved for 167 compounds in a test soil using acetonitrile as an extraction solvent and carbon cleanup with acetonitrile and dichloromethane elutions. Nine field samples (soil, sediment, and biosolids) were extracted using the newly developed method and were compared with a previously validated pressurized liquid extraction (PLE) method using an Accelerated Solvent Extraction (ASE) system. Concentrations obtained from the two methods were comparable (linear R2 > 0.999), suggesting similar performance between the EDGE and PLE extractions in complex matrices. The new method provided slightly better sensitivities in comparison to the PLE method, ranging from 0.09 to 2.56 ng g-1. The method presented here significantly reduces extraction setup and runtimes while also minimizing the volume of carcinogenic solvents (e.g., dichloromethane) used in the laboratory and presents a sensitive multiresidue method for a wide range of pesticides in solid matrices.

Measured efficacy, bioaccumulation, and leaching of a transfluthrin-based insecticidal paint: a case study with a nuisance, nonbiting aquatic insect.

BACKGROUND: Pest management professionals will require a diverse, adaptive abatement toolbox to combat advanced challenges from disease vector and nuisance insect populations. Designed for post-application longevity, insecticidal paints offer extended residual effects on targeted insect pest populations; a measured understanding of active ingredient bioavailability over time is valuable to fully assess treatment efficacy and potential environmental risks. This study was initiated because a nuisance net-spinning caddisfly, Smicridea fasciatella, is lowering the quality of life for riverfront residents at the type locality. RESULTS: We tested the efficacy and potential mobility of a transfluthrin-based paint (a.i. 0.50%), comparing the impacts of UV exposure and substrate texture over time. Direct UV exposure decreased efficacy (ß ± S.E. = 0.008 ± 0.001, P < 0.001) and a coarse texture maintained greater efficacy (ß ± S.E. = -3.7 ± 1.3, P = 0.004) over time. Notably, the coarse texture + indirect UV treatment maintained 100% mortality after 240 days. UV exposure and substrate texture did not have a significant impact on leachate concentrations over time, and successive immersion tests indicated a two-phase emission pattern. Bioaccumulation increased with time on the cuticle of dead adult S. fasciatella; after 24 h of direct exposure the concentration of transfluthrin was 25.3 ± 0.9 ng/caddisfly with a maximum concentration of 345 ng/caddisfly after 7 days. CONCLUSION: Our predictions were validated with measured, time-dependent impacts on efficacy, leachability, and bioaccumulation. Because of the mobility of active ingredient in the environment, insecticidal paints merit low-impact protocols to improve public health outcomes and environmental safety. © 2022 Society of Chemical Industry.

Artificial Intelligence Clinical Evidence Engine for Automatic Identification, Prioritization, and Extraction of Relevant Clinical Oncology Research.

PURPOSE: We developed a system to automate analysis of the clinical oncology scientific literature from bibliographic databases and match articles to specific patient cohorts to answer specific questions regarding the efficacy of a treatment. The approach attempts to replicate a clinician's mental processes when reviewing published literature in the context of a patient case. We describe the system and evaluate its performance. METHODS: We developed separate ground truth data sets for each of the tasks described in the paper. The first ground truth was used to measure the natural language processing (NLP) accuracy from approximately 1,300 papers covering approximately 3,100 statements and approximately 25 concepts; performance was evaluated using a standard F1 score. The ground truth for the expert classifier model was generated by dividing papers cited in clinical guidelines into a training set and a test set in an 80:20 ratio, and performance was evaluated for accuracy, sensitivity, and specificity. RESULTS: The NLP models were able to identify individual attributes with a 0.7-0.9 F1 score, depending on the attribute of interest. The expert classifier machine learning model was able to classify the individual records with a 0.93 accuracy (95% CI, 0.9 to 0.96, P < .0001), and sensitivity and specificity of 0.95 and 0.91, respectively. Using a decision boundary of 0.5 for the positive (expert) label, the classifier demonstrated an F1 score of 0.92. CONCLUSION: The system identified and extracted evidence from the oncology literature with a high degree of accuracy, sensitivity, and specificity. This tool enables timely access to the most relevant biomedical literature, providing critical support to evidence-based practice in areas of rapidly evolving science.

Leaching and sorption of neonicotinoid insecticides and fungicides from seed coatings.

Seed coatings are a treatment used on a variety of crops to improve production and offer protection against pests and fungal outbreaks. The leaching of the active ingredients associated with the seed coatings and the sorption to soil was evaluated under laboratory conditions using commercially available corn and soybean seeds to study the fate and transport of these pesticides under controlled conditions. The active ingredients (AI) included one neonicotinoid insecticide (thiamethoxam) and five fungicides (azoxystrobin, fludioxonil, metalaxyl, sedaxane thiabendazole). An aqueous leaching experiment was conducted with treated corn and soybean seeds. Leaching potential was a function of solubility and seed type. The leaching of fludioxonil, was dependent on seed type with a shorter time to equilibrium on the corn compared to the soybean seeds. Sorption experiments with the treated seeds and a solution of the AIs were conducted using three different soil types. Sorption behavior was a function of soil organic matter as well as seed type. For most AIs, a negative relationship was observed between the aqueous concentration and the log Koc. Sorption to all soils tested was limited for the hydrophilic pesticides thiamethoxam and metalaxyl. However, partitioning for the more hydrophobic fungicides was dependent on both seed type and soil properties. The mobility of fludioxonil in the sorption experiment varied by seed type indicating that the adjuvants associated with the seed coating could potentially play a role in the environmental fate of fludioxonil. This is the first study to assess, under laboratory conditions, the fate of pesticides associated with seed coatings using commercially available treated seeds. This information can be used to understand how alterations in agricultural practices (e.g., increasing use of seed treatments) can impact the exposure (concentration and duration) and potential effects of these chemicals to aquatic and terrestrial organisms.