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Arsenic (As) is an element with important environmental and human health implications due to its toxic properties. It is naturally occurring since it is contained in minerals, but it can also be enriched and distributed in the environment by anthropogenic activities. This paper reports on the historic As contamination of agricultural soils in one of the most important national relevance site for contamination in Italy, the so-called SIN Brescia-Caffaro, in the city of Brescia, northern Italy. These agricultural areas received As through the use of irrigation waters from wastewater coming from a factory of As-based pesticides (lead and calcium arsenates, sodium arsenite). Pesticide production started in 1920 and ended in the '70. Concentrations in the areas are generally beyond the legal threshold values for different soil uses and are up to >200 mg/kg. Arsenic contamination was studied to assess the long-time trend and the dynamics related to the vertical movement of As down to 1 m depth and its horizontal diffusion with surface irrigation in the entire field. Arsenic fractionation analysis (solid phase speciation by sequential extraction procedure) was also performed on samples collected from these areas and employed in greenhouse experiments with several plant species to evaluate the long-term contamination and the role of plant species in modifying As availability in soil. The results of this work can help in the evaluation of the conditions controlling the vertical transfer of As towards surface aquifers, the bioaccumulation likelihood in the agricultural food chain and the selection of sustainable remediation techniques such as phytoextraction., 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 © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Microwave imaging is a safe and promising new technology in breast radiology, avoiding discomfort of breast compression and usage of ionizing radiation. This paper presents the first prospective microwave breast imaging study during which both symptomatic and asymptomatic subjects were recruited. Specifically, a prospective multicentre international clinical trial was performed in 2020-2021, to investigate the capability of a microwave imaging device (MammoWave) in allowing distinction between breasts with no radiological finding (NF) and breasts with radiological findings (WF), i.e., with benign or malignant lesions. Each breast scan was performed with the volunteers lying on a dedicated examination table in a comfortable prone position. MammoWave output was compared to reference standard (i.e., radiologic study obtained within the last month and integrated with histological one if available and deemed necessary by responsible investigator) to classify breasts into NF/WF categories. MammoWave output consists of a selection of microwave images' features (determined prior to trials' start), which allow distinction between NF and WF breasts (using statistical significance p<0.05). 353 women were enrolled in the study (mean age 51 years ± 12 [SD], minimum age 19, maximum age 78); MammoWave data from the first 15 women of each site, all with NF breasts, were used for calibration. Following central assessor evaluation, 111 NF (48 dense) and 272 WF (136 dense) breasts were used for comparison with MammoWave output. 272 WF comprised 182 benign findings and 90 malignant histology-confirmed cancer. A sensitivity of 82.3% was achieved (95%CI: 0.78-0.87); sensitivity is maintained when limiting the investigation to histology-confirmed breasts cancer only (90 histology-confirmed breasts cancer have been included in this analysis, having sizes ranging from 3 mm to 60 mm). Specificity value of approximately 50% was achieved as expected, since thresholds were calculated (for each feature) using median value obtained after recruiting the first 15 women (of each site), all NF. This prospective trial may represent another step for introducing microwave imaging into clinical practice, for helping in breast lesion identification in asymptomatic women., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: Navid Ghavami, Gianluigi Tiberi, Lorenzo Sani, Alessandro Vispa, Alessandra Bigotti, Giovanni Raspa and Mario Badia, are employed by UBT - Umbria Bioengineering Technologies Srl. Navid Ghavami, Gianluigi Tiberi and Lorenzo Sani are shareholders of UBT - Umbria Bioengineering Technologies. Please NOTE that the authors listed had no access to "reference standard" (only the Local Investigators and the C.R.O. had access to "reference standard"). UBT manufactured the microwave imaging device known as MammoWave. This does not alter our adherence to PLOS ONE policies on sharing data and materials., (Copyright: © 2023 Sánchez-Bayuela et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Novel techniques, such as microwave imaging, have been implemented in different prototypes and are under clinical validation, especially for breast cancer detection, due to their harmless technology and possible clinical advantages over conventional imaging techniques. In the prospective study presented in this work, we aim to investigate through a multicentric European clinical trial (ClinicalTrials.gov Identifier NCT05300464) the effectiveness of the MammoWave microwave imaging device, which uses a Huygens-principle-based radar algorithm for image reconstruction and comprises dedicated image analysis software. A detailed clinical protocol has been prepared outlining all aspects of this study, which will involve adult females having a radiologist study output obtained using conventional exams (mammography and/or ultrasound and/or magnetic resonance imaging) within the previous month. A maximum number of 600 volunteers will be recruited at three centres in Italy and Spain, where they will be asked to sign an informed consent form prior to the MammoWave scan. Conductivity weighted microwave images, representing the homogeneity of the tissues' dielectric properties, will be created for each breast, using a conductivity = 0.3 S/m. Subsequently, several microwave image parameters (features) will be used to quantify the images' non-homogenous behaviour. A selection of these features is expected to allow for distinction between breasts with lesions (either benign or malignant) and those without radiological findings. For all the selected features, we will use Welch's t -test to verify the statistical significance, using the gold standard output of the radiological study review.

The aim of work is to contribute to the development of methodologies concerning the selection and characterisation of radon priority areas. The selection of areas was based on risk from indoor radon exposure, expressed in terms of number of expected deaths per year. Radon data come from a survey carried out in the Lazio Region (Italy) and consist of 5297 indoor concentration measurements. Population data were also used. Data showed that dwellings with concentrations above 300 Bq/m 3 , taken as reference level (RL), are not confined to specific areas, but rather spread out over the territory. An absolute risk model has been chosen to predict annual deaths on a regular grid of cells 2kmx2km sized. The analysis showed that 21.7% of the territory is completely uninhabited and that another 13.9% presents a marginal risk, quantifiable in total as less than one expected death per year. The remaining territory is of interest to identify the areas where dwellings with a concentration higher than the RL would be located. It was found that: such dwellings occur with different percentage in all the cells; exposed people varies from a few to almost 2000 per cell; indoor radon risk from exposure above RL is dominated by the number of exposed people and amounts to 106 deaths per year; the number of cells where a such risk is low is far greater than where the risk is high. These findings led to restrict RPA to the smallest set of cells that retained 85% of risk, i.e. 90 expected deaths per year. This percentage has been subjectively set because the technical and economic information required for its optimal calculation was not available. Based on this assumption, the RPA were identified by applying a threshold of 43 to the number of exposed people in each cell, in order to reach 85% of risk. The other main characteristics, also expressed as percentages of the corresponding totals within the area of interest, were found to be: extension 31.5% and exposed people 84%., 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 © 2023 Elsevier Ltd. All rights reserved.)

In 1996 high dichlorodiphenyltrichloroethane (DDT) concentrations were found in Lake Maggiore (Italy) fish and sediments. DDT was produced by a chemical company located in a subalpine valley (Ossola valley, Piedmont Region, Italy), and ended up in the Toce River, a tributary of Lake Maggiore. In the area surrounding the chemical plant, high DDT concentrations in soil and vegetation were found after subsequent investigations. The quantification of the release from contaminated soil and the following migration toward downwind areas, deposition to the soil, and further evaporation plays an important role in understanding future DDT trends in soil and the atmosphere. To study this phenomenon, soil, and vegetation from Ossola Valley were monitored in 2001 and 2011. The concentration values obtained (soils: 0.05 to 1 μg/g; vegetation 2-100 ng/g), allowed to reconstruct the contamination gradient in the valley and were used to develop and calibrate a spatially resolved multimedia fugacity model. The model accounts for spatial and temporal dynamicity of environmental characteristics such as wind speed and direction, variable air compartment height etc., and simulates the fate and transport of chemicals on a local scale. The dynamic emission of DDT (about 13,000 kg for the 50 y production time) to the air was estimated and utilized for a 100-year simulation (from 1948 to 2048). The results obtained allowed to understand the temporal and spatial pattern of DDT contamination for a long period at a local scale as well as the potential contribution as a source potentially affecting sites at larger distances., 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 © 2022 Elsevier B.V. All rights reserved.)

Studies about biodegradation potential in soils often refer to artificially contaminated and simplified systems, overlooking the complexity associated with contaminated sites in a real context. This work aims to provide a holistic view on microbiome assembly and functional diversity in the model site SIN Brescia-Caffaro (Italy), characterized by historical and uneven contamination by organic and inorganic compounds. Here, physical and chemical analyses and microbiota characterization were applied on one-hundred-twenty-seven soil samples to unravel the environmental factors driving bacterial community assembly and biodegradation potential in three former agricultural fields. Chemical analyses showed a patchy distribution of metals, metalloids and polychlorinated biphenyls (PCB) and allowed soil categorization according to depth and area of collections. Likewise, the bacterial community structure, described by molecular fingerprinting and 16S rRNA gene analyses, was significantly different according to collection site and depth. Pollutant concentrations (i.e., hexachloro-biphenyls, arsenic and mercury), nitrogen content and parameters related to soil texture were identified as main drivers of microbiota assembly, being significantly correlated to bacterial community composition. Moreover, bacteria putatively involved in the aerobic degradation of PCBs were enriched over the total bacterial community in topsoils, where the highest activity was recorded using fluorescein hydrolysis as proxy. Metataxonomic analyses revealed the presence of bacteria having metabolic pathways related to PCB degradation and tolerance to heavy metals and metalloids in the topsoil samples collected in all areas. Overall, the provided dissection of soil microbiota structure and its degradation potential in the SIN Brescia-Caffaro can contribute to target specific areas for rhizoremediation implementation. Metagenomics studies could be implemented in the future to understand if specific degradative pathways are present in historically polluted sites characterized by the co-occurrence of multiple classes of contaminants., (Copyright © 2022 Elsevier GmbH. All rights reserved.)

MammoWave is a microwave imaging device for breast lesion detection, employing two antennas which rotate azimuthally (horizontally) around the breast. The antennas operate in the 1-9 GHz band and are set in free space, i.e., pivotally, no matching liquid is required. Microwave images, subsequently obtained through the application of Huygens Principle, are intensity maps, representing the homogeneity of the dielectric properties of the breast tissues under test. In this paper, MammoWave is used to realise tissues dielectric differences and localise lesions by segmenting microwave images adaptively employing pulse coupled neural network (PCNN). Subsequently, a non-parametric thresholding technique is modelled to differentiate between breasts having no radiological finding (NF) or benign (BF) and breasts with malignant finding (MF). Resultant findings verify that automated breast lesion localization with microwave imaging matches the gold standard achieving 81.82% sensitivity in MF detection. The proposed method is tested on microwave images acquired from a feasibility study performed in Foligno Hospital, Italy. This study is based on 61 breasts from 35 patients; performance may vary with larger number of datasets and will be subsequently investigated., Competing Interests: Lorenzo Sani, Alessandro Vispa and Giovanni Raspa are employed by UBT - Umbria Bioengineering Technologies. Gianluigi Tiberi and Lorenzo Sani are shareholders of UBT - Umbria Bioengineering Technologies. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Plant roots can accumulate organic chemicals, including PCBs, and this could be relevant in spreading chemicals through the food chain. To estimate such uptake, several equations are available in the literature, mostly developed in lab conditions, to obtain the root concentration factor (RCF). Here, a long-term (18 months) greenhouse experiment, using an aged, contaminated soil, was performed to reproduce root uptake in field-like conditions and to account for the ecological variability of exposure during the entire life cycle. Specific growth strategies (i.e., annual vs. perennial), root development (e.g., timing of root production and decaying), and soil parameters (e.g., dissolved organic carbon (DOC), and the particulate organic carbon (POC)) may interfere with the uptake of contaminants into the roots of plants. In this study, we investigate the effects of these factors on the RCF, obtained for 79 PCBs. New predictive equations were calculated for 5 different plants species at four different growth times (from few months to 1.5 years) and stages (growing vs maturity). The relationships highlighted a species-specific and time-dependent accumulation of PCB in plants roots, with higher RCFs in summer than in fall for some species, and the relevant influence of DOC and POC in affecting root uptake., (Copyright © 2021 Elsevier B.V. All rights reserved.)