Dataset Information

Continuous high-frequency pesticide monitoring to observe the unexpected and the overlooked

ABSTRACT: Highlights • We produced a novel continuous, high-frequency, multi-species concentration dataset.• High-requency captured acute toxicity exceedance during large and small rainfalls.• We captured a large diversity of concentration patterns and peaks timing.• Few different species unexpectedly underwent similar dynamics over rainfall events.• Legacy pesticide dynamics indicated first-flush of pre-event water in the stream. Graphical abstract Image, graphical abstract Synthetic Plant Protection Products (PPPs) are a key element for a large part of today's global food systems. However, the transport of PPPs and their transformation products (TPs) to water bodies has serious negative effects on aquatic ecosystems. Small streams in agricultural catchments may experience pronounced concentration peaks given the proximity to fields and poor dilution capacity. Traditional sampling approaches often prevent a comprehensive understanding of PPPs and TPs concentration patterns being limited by trade-offs between temporal resolution and duration of the observation period. These limitations result in a knowledge gap for accurate ecotoxicological risk assessment and the achievement of optimal monitoring strategies for risk mitigation. We present here high-frequency PPPs and TPs concentration time-series measured with the autonomous MS2Field platform that combines continuous sampling and on-site measurements with a high-resolution mass spectrometer, which allows for overcoming temporal trade-offs. In a small agricultural catchment, we continuously measured 60 compounds at 20 minutes resolution for 41 days during the growing season. This observation period included 8 large and 15 small rain events and provided 2560 concentration values per compound. To identify similarities and differences among the compound-specific concentration time-series, we analysed the entire dataset with positive matrix factorisation. Six factors sufficiently captured the overall complexity in concentration dynamics. While one factor reflected dilution during rainfall, five factors identified PPPs groups that seemed to share a common history of recent applications. The investigation per event of the concentration time-series revealed a surprising complexity of dynamic patterns; physico-chemical properties of the compounds did not influence the (dis)similarity of chemographs. Some PPPs concentration peaks led while others lagged by several hours the water level peaks during large events. During small events, water level peaks always preceded concentration peaks, which were generally only observed when the water levels had almost receded to pre-event levels. Thus, monitoring schemes relying on rainfall or water level as proxies for triggering sampling may lead to systematic biases. The high temporal resolution revealed that the Swiss national monitoring integrating over 3.5 days underestimated critical concentration peaks by a factor of eight to more than 32, captured 3 out of 11 exceedances of legal acute quality standards (the relevant values in the Swiss Water Protection Law) and recorded 1 out of 9 exceedances of regulatory acceptable concentrations (the relevant values for the PPPs registration process). MS2Field allowed for observing unexpected and overlooked pesticide dynamics with consequences for further research but also for monitoring. The large variability in timing of concentration peaks relative to water level calls for more in-depth analyses regarding the respective transport mechanisms. To perform these analyses, spatially distributed sampling and time-series of geo-referenced PPPs application data are needed.

SUBMITTER: la Cecilia D

PROVIDER: S-EPMC8593654 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Suction of the left ventricle can lead to potentially life-threatening events in left ventricular assist device (LVAD) patients. With the resolution of currently available clinical LVAD monitoring healthcare professionals are unable to evaluate patients' suction occurrences in detail. This study investigates occurrences and durations of suction events and their associations with tachycardia in stable outpatients. Continuous high-resolution LVAD data from HVAD patients were analyzed in the early outpatient period for 15 days. A validated suction detection from LVAD signals was used. Suction events were evaluated as suction rates, bursts of consecutive suction beats, and clusters of suction beats. The occurrence of tachycardia was analyzed before, during, and after suction clusters. Furthermore, blood work, implant strategy, LVAD speed setting, inflow cannula position, left ventricular diameters, and adverse events were evaluated in these patients. LVAD data of 10 patients was analyzed starting at 78 ± 22 postoperative days. Individuals' highest suction rates per hour resulted in a median of 11% (range 3%-61%). Bursts categorized as consecutive suction beats with n = 2, n = 3-5, n = 6-15, and n > 15 beats were homogenously distributed with 10.3 ± 0.8% among all suction beats. Larger suction bursts were followed by shorter suction-free periods. Tachycardia during suction occurred in 12% of all suction clusters. Significant differences in clinical parameters between individuals with high and low suction rates were only observed in left ventricular end-diastolic and end-systolic diameters (P < .02). Continuous high-resolution LVAD monitoring sheds light on outpatient suction occurrences. Interindividual and intraindividual characteristics of longitudinal suction rates were observed. Longer suction clusters have higher probabilities of tachycardia within the cluster and more severe types of suction waveforms. This work shows the necessity of improved LVAD monitoring and the implementation of an LVAD speed control to reduce suction rates and their concomitant burden on the cardiovascular system.

Project description:ObjectiveWe evaluated the impact of monitoring indication, early electroencephalography (EEG), and clinical features on seizure risk in all neonates undergoing continuous EEG (cEEG) monitoring following a standardized monitoring protocol.MethodsAll cEEGs from unique neonates 34-48 weeks postmenstrual age monitored from 1/2011-10/2017 (n = 291) were included. We evaluated the impact of cEEG monitoring indication (acute neonatal encephalopathy [ANE], suspicious clinical events [SCEs], or other high-risk conditions [OHRs]), age, medication status, and early EEG abnormalities (including the presence of epileptiform discharges and abnormal background continuity, amplitude, asymmetry, asynchrony, excessive sharp transients, and burst suppression) on time to first seizure and overall seizure risk using Kaplan-Meier survival curves and multivariable Cox proportional hazards models.ResultsSeizures occurred in 28% of high-risk neonates. Discontinuation of monitoring after 24 hours of seizure-freedom would have missed 8.5% of neonates with seizures. Overall seizure risk was lower in neonates monitored for ANE compared to OHR (P = .004) and trended lower compared to SCE (P = .097). The time course of seizure presentation varied by group, where the probability of future seizure was less than 1% after 17 hours of seizure-free monitoring in the SCE group, but required 42 hours in the OHR group, and 73 hours in the ANE group. The presence of early epileptiform discharges increased seizure risk in each group (ANE: adjusted hazard ratio [aHR] 4.32, 95% confidence interval [CI] 1.23-15.13, P = .022; SCE: aHR 10.95, 95% CI 4.77-25.14, P < 1e-07; OHR: aHR 56.90, 95% CI 10.32-313.72, P < 1e-05).SignificanceNeonates who undergo cEEG are at high risk for seizures, and risk varies by monitoring indication and early EEG findings. Seizures are captured in nearly all neonates undergoing monitoring for SCE within 24 hours of cEEG monitoring. Neonates monitored for OHR and ANE can present with delayed seizures and require longer durations of monitoring. Early epileptiform discharges are the best early EEG feature to predict seizure risk.

Dataset Information

Continuous high-frequency pesticide monitoring to observe the unexpected and the overlooked

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets