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In artisanal small-scale gold mines (ASGM), mercury (Hg) is known to pollute nearby river waters and sediments where it can be methylated to the highly bioavailable methylmercury (MeHg). The assessment of Hg speciation in water samples has been challenging for many years, with recommended procedures often not adequately allowing for analysis of samples in a suitable timeframe. Using a novel solid-phase extraction (SPE) method for sampling and preservation of Hg species, representative speciation data can be safely and easily collected and retained for up to 4-weeks (MeHg = 115 ± 8% refrigerated and 109 ± 13% unrefrigerated storage; Hg 2+  = 100 ± 14% refrigerated and 94 ± 12% unrefrigerated storage). Concentrations of MeHg in environmental water samples and drinking water were below detection limit across two ASGM sites in western Kenya and concentrations of Hg 2+ were below drinking water guidelines; however, drinking water sources contribute 20-30% of the tolerable weekly intake of Hg, indicating a need to minimise exposure of Hg from dietary sources to prevent Hg poisoning. Sediments from receiving rivers at ASGM sites showed total Hg concentrations above guideline limits (0.08-1.84 mg kg -1 total Hg) along the length of the river; however, MeHg concentrations fluctuated dependent on the stagnation of the river due to damns and ponds (5.9 ± 14.3 µg kg -1 MeHg). The findings show that SPE can be used as a robust sample collection and preservation approach for Hg speciation, which can better inform mitigation measures, understand ecological and human health implications, and improve environmental monitoring., (© 2024. British Geological Survey (UKRI), Nottingham Trent University, Odipo Osano, Robert Mortimer.)

Background: The role of vitamin D in human physiology is a topic of great interest for the scientific community in the last decades. The common target for all clinicians is to improve its status in order to prevent several pathological conditions., Methods: The aim of our study was to evaluate the safety and the efficacy of both calcifediol and cholecalciferol in combination with alendronate in osteoporotic women. A homogeneous population of 300 postmenopausal osteoporotic women was selected for this study. 150 women were administered with alendronate 70 mg combined with clacifediol 0.266 mg soft capsules monthly. The other half (other 150 women) were administered with alendronate 70 mg combined with cholecalciferol 25000 IU monthly. First follow-up was after 4 months and second follow-up after 12 months., Results: No case of toxicity was detected throughout the study in any patient. In regards to increase of vitamin D serum level, after four months supplementation calcifediol is 1.29 fold more effective than cholecalciferol while after 12 months of supplementation calcifediol is 2.32 fold more effective compared to cholecalciferol., Conclusions: In our study calcifediol showed to be as safe as cholecalciferol and more effective than cholecalciferol in order to increase vitamin D serum level after four and 12 months of supplementation when supplementation is combined with alendronate 70 mg in osteoporotic women.

Analysis of mercury (Hg) in natural water samples has routinely been impractical in many environments, for example, artisanal and small-scale gold mines (ASGM), where difficult conditions make monitoring of harmful elements and chemicals used in the processes highly challenging. Current sampling methods require the use of hazardous or expensive materials, and so difficulties in sample collection and transport are elevated. To solve this problem, a solid-phase extraction-based method was developed for the sampling and preservation of dissolved Hg in natural water samples, particularly those found around ASGM sites. Recoveries of 85% ± 10% total Hg were obtained during 4 weeks of storage in refrigerated (4 °C, dark) and unrefrigerated (16 °C, dark) conditions, and from a representative river water spiked to 1 μg L -1 Hg 2+ , 94% ± 1% Hg recovery was obtained. Solid-phase extraction loading flow rates were tested at 2, 5, and 10 mL min -1 with no breakthrough of Hg, and sorbent stability showed no breakthrough of Hg up to 2 weeks after functionalisation. The method was deployed across five artisanal gold mines in Kakamega gold belt, Kenya, to assess Hg concentrations in mine shaft water, ore washing ponds, and river and stream water, including drinking water sources. In all waters, Hg concentrations were below the WHO guideline limit value of 6 μg L -1 , but drinking water sources contained trace concentrations of up to 0.35 μg L -1 total Hg, which may result in negative health effects from long-term exposure. The SPE method developed and deployed here is a robust sampling method that can therefore be applied in future Hg monitoring, toxicology, and environmental work to provide improved data that is representative of total dissolved Hg in water samples.

Nuclear receptors (NRs) are transcriptional regulators involved in different aspects of normal cell physiology. Their deregulation is associated with aberrant expression, gene mutations and/or epigenetic alterations that can be related to the pathogenesis of various human diseases, and especially in cancer. In particular, a complex genomic network involved in the development and progression of NR‑mediated cancer has been highlighted. Advanced genomic technologies have made it possible to understand that the expression of any particular NR in a given cancer subtype is only one component of a larger transcriptional machinery that is controlled by multiple associated NRs and transcription factors. Additionally, their ability to regulate and to be regulated by molecules of non‑coding RNAs, microRNAs as well as long non‑coding RNAs, is opening new scenarios for understanding the role of NRs in cancer initiation and progression. In the present review, the authors aimed to outline the reciprocal interactions that exist between the main NRs and long non‑coding RNAs in different tumor diseases, to suggest new diagnostic biomarkers as well as therapeutic strategies for these tumors.

Autosomal recessive mutation of HOXB1 and Hoxb1 causes sensorineural hearing loss in patients and mice, respectively, characterized by the presence of higher auditory thresholds; however, the origin of the defects along the auditory pathway is still unknown. In this study, we assessed whether the abnormal auditory threshold and malformation of the sensory auditory cells, the outer hair cells, described in Hoxb1null mutants depend on the absence of efferent motor innervation, or alternatively, is due to altered sensory auditory components. By using a whole series of conditional mutant mice, which inactivate Hoxb1 in either rhombomere 4-derived sensory cochlear neurons or efferent motor neurons, we found that the hearing phenotype is mainly reproduced when efferent motor neurons are specifically affected. Our data strongly suggest that the interactions between olivocochlear motor neurons and outer hair cells during a critical postnatal period are crucial for both hair cell survival and the establishment of the cochlear amplification of sound., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Di Bonito 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.)

Gold mining activities are undertaken both at large and artisanal scale, often resulting in serious 'collateral' environmental issues, including environmental pollution and hazard to human and ecosystem health. Furthermore, some of these activities are poorly regulated, which can produce long-lasting damage to the environment and local livelihoods. The aim of this study was to identify a new workflow model to discriminate anthropogenic versus geogenic enrichment in soils of gold mining regions. The Kedougou region (Senegal, West Africa) was used as a case study. Ninety-four soil samples (76 topsoils and 18 bottom soils) were collected over an area of 6,742 km 2 and analysed for 53 chemical elements. Robust spatial mapping, compositional and geostatistical models were employed to evaluate sources and elemental footprint associated with geology and mining activities. Multivariate approaches highlighted anomalies in arsenic (As) and mercury (Hg) distribution in several areas. However, further interpretation with enrichment factor (EFs) and index of geoaccumulation (IGeo) emphasised high contamination levels in areas approximately coinciding with the ones where artisanal and small scale mining (ASGM) activities occur, and robust compositional contamination index (RCCI) isolated potentially harmful elements (PHE) contamination levels in very specific areas of the Kedougou mining region. The study underlined the importance of complementary approaches to identify anomalies and, more significantly, contamination by hazardous material. In particular, the analyses helped to identify discrete areas that would require to be surveyed in more detail to allow a comprehensive and thorough risk assessment, to investigate potential impacts to both human and ecosystem health., (© 2023. The Author(s).)

Mercury is considered to be one of the most toxic elements to humans. Due to pollution from industry and artisanal gold mining, mercury species are present globally in waters used for agriculture, aquaculture, and drinking water. This review summarises methods reported for preserving mercury species in water samples and highlights the associated hazards and issues with each. This includes the handling of acids in an uncontrolled environment, breakage of sample containers, and the collection and transport of sample volumes in excess of 1 L, all of which pose difficulties for both in situ collection and transportation. Literature related to aqueous mercury preservation from 2000-2021 was reviewed, as well as any commonly cited and relevant references. Amongst others, solid-phase extraction techniques were explored for preservation and preconcentration of total and speciated mercury in water samples. Additionally, the potential as a safe, in situ preservation and storage method for mercury species were summarised. The review highlighted that the stability of mercury is increased when adsorbed on a solid-phase and therefore the metal and its species can be preserved without the need for hazardous reagents or materials in the field. The mercury species can then be eluted upon return to a laboratory, where sensitive analytical detection and speciation methods can be better applied. Developments in solid phase extraction as a preservation method for unstable metals such as mercury will improve the quality of representative environmental data, and further improve toxicology and environmental monitoring studies.

Background/aim: Breast angiosarcoma is a rare and aggressive disease with a poor prognosis. Two subtypes have been identified: primary angiosarcoma (PBA) and secondary breast angiosarcoma (SBA). In this retrospective analysis, we describe and compare our institute experience with the data existing in the literature., Materials and Methods: We included in our analysis 29 patients who received a diagnosis of PBA or SBA between 2006 and 2019., Results: All patients received surgery as frontline treatment, but only 6 patients underwent to adjuvant treatment. Neoadjuvant chemotherapy was administered 2 patients. The preferred chemotherapeutic regimen was taxanes with or without gemcitabine and associated with anthracyclines. A lower median RFS and OS were reported in patients with PBA compared to those with SBA, but the difference observed was not statistically significant. Patients with PBA had a lower median age at the diagnosis (38 vs. 75)., Conclusion: In our analysis, we have shown a lower median RFS and OS in patients with PBA compared with those with SBA, and a significantly younger age at diagnosis in patients affected by PBA., (© 2022 S. Karger AG, Basel.)

Breast cancer is the most commonly diagnosed cancer and registers the highest number of deaths for women. Advances in diagnostic activities combined with large-scale screening policies have significantly lowered the mortality rates for breast cancer patients. However, the manual inspection of tissue slides by pathologists is cumbersome, time-consuming and is subject to significant inter- and intra-observer variability. Recently, the advent of whole-slide scanning systems has empowered the rapid digitization of pathology slides and enabled the development of Artificial Intelligence (AI)-assisted digital workflows. However, AI techniques, especially Deep Learning, require a large amount of high-quality annotated data to learn from. Constructing such task-specific datasets poses several challenges, such as data-acquisition level constraints, time-consuming and expensive annotations and anonymization of patient information. In this paper, we introduce the BReAst Carcinoma Subtyping (BRACS) dataset, a large cohort of annotated Hematoxylin and Eosin (H&E)-stained images to advance AI development in the automatic characterization of breast lesions. BRACS contains 547 Whole-Slide Images (WSIs) and 4539 Regions Of Interest (ROIs) extracted from the WSIs. Each WSI and respective ROIs are annotated by the consensus of three board-certified pathologists into different lesion categories. Specifically, BRACS includes three lesion types, i.e., benign, malignant and atypical, which are further subtyped into seven categories. It is, to the best of our knowledge, the largest annotated dataset for breast cancer subtyping both at WSI and ROI levels. Furthermore, by including the understudied atypical lesions, BRACS offers a unique opportunity for leveraging AI to better understand their characteristics. We encourage AI practitioners to develop and evaluate novel algorithms on the BRACS dataset to further breast cancer diagnosis and patient care. Database URL: https://www.bracs.icar.cnr.it/., (© The Author(s) 2022. Published by Oxford University Press.)

Background: We retrospectively evaluated safety and performance of magnetic seed localisation of nonpalpable breast lesions., Methods: We reviewed records of patients with nonpalpable breast lesions preoperative localised by placing magnetic Magseed® marker between February 2019 and December 2020. During surgery, Sentimag® magnetic probe was used to localise the marker and guide surgery. Safety, lesion identification and excision with tumour with free margins and re-excision rate were assessed., Results: A total of 77 Magseed® devices were placed into the breasts of 73 patients, 44 under ultrasound and 33 under stereotactic guidance (4 bilateral). All devices were retrieved as were the target lesions. Magnetic marker placement was successful in all cases without any adverse event. Intraoperative identification and excision of the localised lesion were successful in 77 of 77 of cases (100%). In three cases (all of them calcifications with the seed placed under stereotactic guidance), the seed did not reach the exact target position of the biopsy clip; thus, larger excision was needed, with localisation failure attributed to incorrect clip insertion (n = 1) or to clip dislocation (n = 2). Migration of the marker was negligible in all patients. Complete excision after the initial procedure with at least 1-mm disease-free margins was obtained in 74 out of 77 (96.1%) lesions. The re-excision rate was 3 out of 77 (4%)., Conclusions: Magnetic marker localisation for nonpalpable breast lesions was safe, reliable, and effective in terms of lesion identification, excision with tumour-free margins and re-excision rate., (© 2022. The Author(s) under exclusive licence to European Society of Radiology.)

Purpose: To evaluate radiomics features in order to: differentiate malignant versus benign lesions; predict low versus moderate and high grading; identify positive or negative hormone receptors; and discriminate positive versus negative human epidermal growth factor receptor 2 related to breast cancer., Methods: A total of 182 patients with known breast lesions and that underwent Contrast-Enhanced Mammography were enrolled in this retrospective study. The reference standard was pathology (118 malignant lesions and 64 benign lesions). A total of 837 textural metrics were extracted by manually segmenting the region of interest from both craniocaudally (CC) and mediolateral oblique (MLO) views. Non-parametric Wilcoxon-Mann-Whitney test, receiver operating characteristic, logistic regression and tree-based machine learning algorithms were used. The Adaptive Synthetic Sampling balancing approach was used and a feature selection process was implemented., Results: In univariate analysis, the classification of malignant versus benign lesions achieved the best performance when considering the original_gldm_DependenceNonUniformity feature extracted on CC view (accuracy of 88.98%). An accuracy of 83.65% was reached in the classification of grading, whereas a slightly lower value of accuracy (81.65%) was found in the classification of the presence of the hormone receptor; the features extracted were the original_glrlm_RunEntropy and the original_gldm_DependenceNonUniformity, respectively. The results of multivariate analysis achieved the best performances when using two or more features as predictors for classifying malignant versus benign lesions from CC view images (max test accuracy of 95.83% with a non-regularized logistic regression). Considering the features extracted from MLO view images, the best test accuracy (91.67%) was obtained when predicting the grading using a classification-tree algorithm. Combinations of only two features, extracted from both CC and MLO views, always showed test accuracy values greater than or equal to 90.00%, with the only exception being the prediction of the human epidermal growth factor receptor 2, where the best performance (test accuracy of 89.29%) was obtained with the random forest algorithm., Conclusions: The results confirm that the identification of malignant breast lesions and the differentiation of histological outcomes and some molecular subtypes of tumors (mainly positive hormone receptor tumors) can be obtained with satisfactory accuracy through both univariate and multivariate analysis of textural features extracted from Contrast-Enhanced Mammography images.

Purpose :The purpose of this study was to discriminate between benign and malignant breast lesions through several classifiers using, as predictors, radiomic metrics extracted from CEM and DCE-MRI images. In order to optimize the analysis, balancing and feature selection procedures were performed. Methods : Fifty-four patients with 79 histo-pathologically proven breast lesions (48 malignant lesions and 31 benign lesions) underwent both CEM and DCE-MRI. The lesions were retrospectively analyzed with radiomic and artificial intelligence approaches. Forty-eight textural metrics were extracted, and univariate and multivariate analyses were performed: non-parametric statistical test, receiver operating characteristic (ROC) and machine learning classifiers. Results : Considering the single metrics extracted from CEM, the best predictors were KURTOSIS (area under ROC curve (AUC) = 0.71) and SKEWNESS (AUC = 0.71) calculated on late MLO view. Considering the features calculated from DCE-MRI, the best predictors were RANGE (AUC = 0.72), ENERGY (AUC = 0.72), ENTROPY (AUC = 0.70) and GLN (gray-level nonuniformity) of the gray-level run-length matrix (AUC = 0.72). Considering the analysis with classifiers and an unbalanced dataset, no significant results were obtained. After the balancing and feature selection procedures, higher values of accuracy, specificity and AUC were reached. The best performance was obtained considering 18 robust features among all metrics derived from CEM and DCE-MRI, using a linear discriminant analysis (accuracy of 0.84 and AUC = 0.88). Conclusions: Classifiers, adjusted with adaptive synthetic sampling and feature selection, allowed for increased diagnostic performance of CEM and DCE-MRI in the differentiation between benign and malignant lesions.

Cancer diagnosis, prognosis, and therapy response predictions from tissue specimens highly depend on the phenotype and topological distribution of constituting histological entities. Thus, adequate tissue representations for encoding histological entities is imperative for computer aided cancer patient care. To this end, several approaches have leveraged cell-graphs, capturing the cell-microenvironment, to depict the tissue. These allow for utilizing graph theory and machine learning to map the tissue representation to tissue functionality, and quantify their relationship. Though cellular information is crucial, it is incomplete alone to comprehensively characterize complex tissue structure. We herein treat the tissue as a hierarchical composition of multiple types of histological entities from fine to coarse level, capturing multivariate tissue information at multiple levels. We propose a novel multi-level hierarchical entity-graph representation of tissue specimens to model the hierarchical compositions that encode histological entities as well as their intra- and inter-entity level interactions. Subsequently, a hierarchical graph neural network is proposed to operate on the hierarchical entity-graph and map the tissue structure to tissue functionality. Specifically, for input histology images, we utilize well-defined cells and tissue regions to build HierArchical Cell-to-Tissue (HACT) graph representations, and devise HACT-Net, a message passing graph neural network, to classify the HACT representations. As part of this work, we introduce the BReAst Carcinoma Subtyping (BRACS) dataset, a large cohort of Haematoxylin & Eosin stained breast tumor regions-of-interest, to evaluate and benchmark our proposed methodology against pathologists and state-of-the-art computer-aided diagnostic approaches. Through comparative assessment and ablation studies, our proposed method is demonstrated to yield superior classification results compared to alternative methods as well as individual pathologists. The code, data, and models can be accessed at https://github.com/histocartography/hact-net., 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 © 2021. Published by Elsevier B.V.)