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Ecological risk assessments for potential pesticide impacts on species listed as threatened or endangered must ensure that decisions to grant registration or establish water quality standards will not jeopardize species or their critical habitats. Pesticides are designed to affect pest species via physiological pathways that may be shared by some nontarget species for which toxicity data are usually unavailable, creating a need for robust methods to estimate acute and chronic toxicity with minimal data. We used a unique probabilistic approach to estimate the risk of chronic effects of two organophosphate (OP) pesticides on the vernal pool fairy shrimp Branchinecta lynchi. Acute toxicity estimates were derived from Monte Carlo (MC) sampling of acute toxicity distributions developed from interspecies relationships using surrogate species. Within each MC draw, acute values were divided by an acute to chronic ratio (ACR) sampled from a distribution of ACRs for OP pesticides and invertebrates, producing a distribution of chronic effects concentrations. The estimated exposure concentrations (EECs) were sampled from distributions representing different environmental conditions. Risk was characterized using probability distributions of acute toxicity, ACRs, and EECs in a probabilistic analysis, as well as partial probabilistic variations that used only some distributions whereas some variables were used deterministically. A deterministic risk quotient (RQ) was compared with the results of probabilistic methods to compare the approaches. Risk varied across exposure scenarios and the number of variables that were handled probabilistically, increasing as the number of variables drawn from distributions increased. The magnitude of RQs was not correlated with the probability that EECs would exceed chronic thresholds, and comparison of the two approaches demonstrates the limited interpretability of RQs. Our novel probabilistic approach to estimating chronic risk with minimal data incorporates uncertainty underlying both exposure and effects assessments for listed species. Integr Environ Assess Manag 2024;20:1654-1666. Published 2024. This article is a U.S. Government work and is in the public domain in the USA., (Published 2024. This article is a U.S. Government work and is in the public domain in the USA.)

The set-coloring Ramsey number R r , s ( k ) is defined to be the minimum n such that if each edge of the complete graph K n is assigned a set of s colors from { 1 , … , r } , then one of the colors contains a monochromatic clique of size k . The case s = 1 is the usual r -color Ramsey number, and the case s = r - 1 was studied by Erdős, Hajnal and Rado in 1965, and by Erdős and Szemerédi in 1972. The first significant results for general s were obtained only recently, by Conlon, Fox, He, Mubayi, Suk and Verstraëte, who showed that R r , s ( k ) = 2 Θ ( k r ) if s / r is bounded away from 0 and 1. In the range s = r - o ( r ) , however, their upper and lower bounds diverge significantly. In this note we introduce a new (random) coloring, and use it to determine R r , s ( k ) up to polylogarithmic factors in the exponent for essentially all r , s , and k ., (© 2023 The Authors. Random Structures & Algorithms published by Wiley Periodicals LLC.)

The automatic segmentation of the abnormality region from the head MRI is a challenging task in the medical science domain. The abnormality in the form of the tumor comprises the uncontrolled growth of the cells. The automatic identification of the affected cells using computerized software systems is demanding in the past several years to provide a second opinion to radiologists. In this paper, a new clustering approach is introduced based on the machine learning aspect that clusters the tumor region from the input MRI using disjoint tree generation followed by tree merging. Further, the proposed algorithm is improved by introducing the theory of joint probabilities and nearest neighbors. Later, the proposed algorithm is automated to find the number of clusters required with its nearest neighbors to do semantic segmentation of the tumor cells. The proposed algorithm provides good semantic segmentation results having the DB index-0.11 and Dunn index-13.18 on the SMS dataset. While the experimentation with BRATS 2015 dataset yields Dice complete =80.5 %, Dice core =73.2 %, and Dice enhanced =62.8 %. The comparative analysis of the proposed approach with benchmark models and algorithms proves the model's significance and its applicability to do semantic segmentation of the tumor cells with the average increment in the accuracy of around ±2.5 % with machine learning algorithms., (© 2023 Walter de Gruyter GmbH, Berlin/Boston.)

Aflatoxin contamination can appear in various points of the food chain. If animals are fed with contaminated feed, AFB1 is transformed-among others-to aflatoxin M1 (AFM1) metabolite. AFM1 is less toxic than AFB1, but it is still genotoxic and carcinogenic and it is present in raw and processed milk and all kinds of milk products. In this article, the chronic exposure estimation and risk characterization of Hungarian consumers are presented, based on the AFM1 contamination of milk and dairy products, and calculated with a probabilistic method, the two-dimensional Monte-Carlo model. The calculations were performed using the R plugin (mc2d package) integrated into the KNIME (Konstanz Information Miner) software. The simulations were performed using data from the 2018-2020 food consumption survey. The AFM1 analytical data were derived from the Hungarian monitoring survey and 1,985 milk samples were analyzed within the framework of the joint project of the University of Debrecen and the National Food Chain Safety Office of Hungary (NÉBIH). Limited AFM1 concentrations were available for processed dairy products; therefore, a database of AFM1 processing factors for sour milk products and various cheeses was produced based on the latest literature data, and consumer exposure was calculated with the milk equivalent of the consumed quantities of these products. For risk characterization, the calculation of hazard index (HI), Margin of Exposure, and the hepatocellular carcinoma incidence were used. The results indicate that the group of toddlers that consume a large amount of milk and milk products are exposed to a certain level of health risk. The mean estimated daily intake of toddlers is in the range of 0.008-0.221 ng kg -1 bw day -1 ; the 97.5th percentile exposure of toddlers is between 0.013 ng kg -1 bw day -1 and 0.379 ng kg -1 bw day -1 , resulting in a HI above 1. According to our study, the exposure of older age groups does not pose an emergent health risk. Nevertheless, the presence of carcinogenic compounds should be kept to a minimum in the whole population., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Farkas, Kerekes, Ambrus, Süth, Peles, Pusztahelyi, Pócsi, Nagy, Sipos, Miklós, Lőrincz, Csorba and Jóźwiak.)

Extensive evidence of elevated arsenic (As) in the food-chain, mainly rice, wheat and vegetables exists. Nevertheless, the importance of exposure from food towards total As exposure and associated health risks in areas with natural occurring As in drinking water is still often neglected, and accordingly mitigations are largely focused on drinking water only. In this study, the contribution of food over drinking water to overall As exposure was estimated for As exposed populations in Bihar, India. Increased lifetime cancer risk was predicted using probabilistic methods with input parameters based on detailed dietary assessment and estimation of As in drinking water, cooked rice, wheat flour and potato collected from 91 households covering 19 villages. Median total exposure was 0.83 μg/kgBW/day (5th and 95th percentiles were 0.21 and 11.1 μg/kgBW/day) and contribution of food (median = 49%) to overall exposure was almost equal to that from drinking water (median = 51%). More importantly and contrary to previous studies, food was found to contribute more than drinking water to As exposure, even when drinking water As was above the WHO provisional guide value of 10 μg/L. Median and 95th percentile excess lifetime cancer risks from food intake were 1.89 × 10 -4 and 7.32 × 10 -4 respectively when drinking water As was below 10 μg/L and 4.00 × 10 -4 and 1.83 × 10 -3 respectively when drinking water As was above 10 μg/L. Our results emphasise the importance of food related exposure in As-endemic areas, and, perhaps surprisingly, particularly in areas with high As concentrations in drinking water - this being partly ascribed to increases in food As due to cooking in high As water. These findings are timely to stress the importance of removing As from the food chain and not just drinking water in endemic areas., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

In this study, we have screened the six most relevant forensic body fluids / tissues, namely blood, semen, saliva, vaginal secretion, menstrual blood and skin, for miRNAs using a whole miRNome massively parallel sequencing approach. We applied partial least squares (PLS) and linear discriminant analysis (LDA) to predict body fluids based on the expression of the miRNA markers. We estimated the prediction accuracy for models including different subsets of miRNA markers to identify the minimum number of markers needed for sufficient prediction performance. For one selected model consisting of 9 miRNA markers we calculated their importance for prediction of each of the six different body fluid categories., (Copyright © 2019 Elsevier B.V. All rights reserved.)

The potential catastrophic event of a landslide bringing contaminants to surface waters has been highlighted in public media, but there are still few scientific studies analyzing the risk of landslides with contaminated soil. The aim of this study is to present a method to estimate the risk of potential long-term ecological effects on water bodies due to contaminated soil released into a river through a landslide. The study constitutes further development of previous work focusing on the instantaneous (short-term) release of contaminants and associated effects. Risk is here defined as the probability of surface water failing to comply with environmental quality standards (EQS). The transport model formulation is kept simple enough to allow for a probabilistic analysis as a first assessment of the impact on the river water quality from a landslide runout deposit containing contaminated soil. The model is applied at a contaminated site located adjacent to the Göta Älv River that discharges into the Gothenburg estuary, in southwest Sweden. The results from the case study show that a contaminated runout deposit will likely cause contamination levels above EQSs in the near area for a long time and that it will take several years for the deposit to erode, with the greatest erosion at the beginning when water velocities are their highest above the deposit. A contaminated landslide runout deposit will thus act as a source of contamination to the downstream water system until all the contaminated deposit has been eroded away and the contaminants have been transported from the deposit to the river, and further to the river mouth - diluted but not necessarily negligible. Therefore, it is important to prevent landslides of contaminated soil or waste, and if such events were to occur, to remove the contaminated runout deposit as soon as possible., (Copyright © 2018. Published by Elsevier B.V.)

Based on the Hungarian pesticide residues monitoring data of the last five years and the consumption data collected within a 3-day dietary record survey in 2009 (more than 2 million pesticide residue results and almost 5000, 0-101-year-old consumers 3 non-consecutive-day personal fruit and vegetable consumption data), the cumulative acute exposure of organophosphorus pesticide residues was evaluated. The relative potency factor approach was applied, with acephate chosen as index compound. According to our conservative calculation method, applying the measured residues only, the 99.95% of the 99th percentiles of calculated daily intakes was at or below 87 μg/kgbwday, indicating that the cumulative acute exposure of the whole Hungarian population (including all age classes) to organophosphorus compounds was not a health concern., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Data validation plays an important role in ensuring the reliability and reproducibility of studies. NMR investigations of the functional properties, dynamics, chemical kinetics, and structures of proteins depend critically on the correctness of chemical shift assignments. We present a novel probabilistic method named ARECA for validating chemical shift assignments that relies on the nuclear Overhauser effect data . ARECA has been evaluated through its application to 26 case studies and has been shown to be complementary to, and usually more reliable than, approaches based on chemical shift databases. ARECA is available online at http://areca.nmrfam.wisc.edu/.

The aim of this study was to assess probabilistic exposure to nail cosmetics in French consumers. The exposure assessment was performed with base coat, polish, top coat and remover. This work was done for adult and child consumers. Dermal, inhalation and oral routes were taken into account for varnishes. Exposure evaluation was performed for the inhalation route with polish remover. The main route of exposure to varnishes was the ungual route. Inhalation was the secondary route of exposure, followed by dermal and oral routes. Polish contributed most to exposure, regardless of the route of exposure. For this nail product, P50 and P95 values by ungual route were respectively equal to 1.74 mg(kg bw week)(-1) and 8.55 mg(kg bw week)(-1) for women aged 18-34 years. Exposure to polish by inhalation route was equal to 0.70 mg(kg bw week)(-1) (P50) and 5.27 mg(kg bw week)(-1) (P95). P50 and P95 values by inhalation route were respectively equal to 0.08 mg(kg bw week)(-1) and 1.14 mg(kg bw week)(-1) for consumers aged 18-34 years exposed to polish remover. This work provided current exposure data for nail cosmetics, and a basis for future toxicological studies of the uptake of substances contained in nail cosmetics in order to assess systemic exposure., (Copyright © 2014 Elsevier Ltd. All rights reserved.)