241 research outputs found

    Potential use of ecotoxicological biomarkers in Serratella ignita (Ephemeroptera) larvae for Alcantara river (Sicily, Italy) water quality assessment

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    Benthic macroinvertebrates are important components of aquatic river ecosystems. These organisms are often used for biological monitoring since they are good indicators of the aquatic freshwater environment health status which can be negatively affected by human, agricultural and industrial activities. Many studies focused on the use of observed changes in macroinvertebrate communities or populations, but studies using biochemical biomarkers in these species are almost absent. The aim of this paper was to test the employment of ecotoxicological biomarkers in Ephemeroptera larvae to assess the water quality of the Alcantara river (Sicily) from its headwater to its mouth. This river represents the main source of potable water for all the counties situated in the Alcantara valley and for the city of Messina, and is the primary irrigation source for the large surrounding agricultural lands. Acetylcholinesterase activity (AChE) and Benzo(a)pyrene monooxygenase (BPMO) activity were evaluated in Serratella ignita (Ephemerellidae) larvae from different sampling sites along the river to show the potential presence of xenobiotic substances. Environmental parameters, such as temperature, dissolved oxygen, pH, conductivity and flow velocity, were also measured at different sampling sites. The biomarker approach in invertebrates represents an early warning signal of ecotoxicological alterations, providing information on which contaminants exert toxic effects on different biota. The results showed that the highest inhibition of AChE activity in S. ignita larvae was in Randazzo and Castiglione di Sicilia villages (i.e. high and medium level of the river). Here, agricultural activities are intense, with high production of fruit, olives, citrus and the heaviest usage of fertilizers, pesticides, and neurotoxic substances like organophosphate insecticides and carbammates in all the Alcantara valley. Regarding BPMO activity, the highest value was recovered in S. ignita larvae from the river mouth, which was characterised by the highest entry of water run off of streets and loaded with xenobiotic lipophilic compounds. Both AChE and BPMO were not linked to water temperature values. The data reported in the present work represent the first attempt to monitor levels of two widely recognised enzymatic biomarkers in benthic macroinvertebrates. Results indicate the possible use of this approach in macroinvertebrate larvae to study the health status of Alcantara river. The river appears to be impacted by contamination mainly from waste discharges and, upstream, from large pasture areas. Considering the world-wide distribution of S. ignita, the biomarker approach used to assess water quality may be applicable not only to Alcantara river, but also to other lotic ecosystems

    THE STRAIT OF MESSINA: A KEY AREA FOR PELAGIA NOCTILUCA (CNIDARIA, SCYPHOZOA)

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    The Strait of Messina is certainly a focal area for the biological cycle of the jellyfish Pelagia noctiluca in the Western Mediterranean Sea. By means of both original and literature data, a conceptual model outlining the biological cycle of this species is proposed. P. noctiluca reproduces from late winter to late spring in the Aeolian Island Archipelago. From late spring to early summer, currents transport newly produced young individuals (20-30 mm bell diameter) eastwards, towards the Strait. The Strait of Messina ecosystem is not a suitable reproduction area for its intense hydrodynamism that would surely lead to a very low reproductive success due to gamete dispersion. This area, however, represents an optimal site for growth, due to its intensive primary and secondary production, but also for an optimal temperature range, lower in summer and higher in winter in respect to the surrounding basins. Pelagia remains all the summer inside the Strait, increasing in bell diameter (50-70 mm) and biomass. Subsequently, in late summer-early autumn, the mature specimens, taking advantage of a typical autumnal downwelling transport, move to deep Tyrrhenian waters where overwinter, to upwell in the Aeolian Archipelago by late winter to start a new cycle

    The progressive loss of brain network fingerprints in Amyotrophic Lateral Sclerosis predicts clinical impairment

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    Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterised by functional connectivity alterations in both motor and extra-motor brain regions. Within the framework of network analysis, fingerprinting represents a reliable approach to assess subject-specific connectivity features within a given population (healthy or diseased). Here, we applied the Clinical Connectome Fingerprint (CCF) analysis to source-reconstructed magnetoencephalography (MEG) signals in a cohort of seventy-eight subjects: thirty-nine ALS patients and thirty-nine healthy controls. We set out to develop an identifiability matrix to assess the extent to which each patient was recognisable based on his/her connectome, as compared to healthy controls. The analysis was performed in the five canonical frequency bands. Then, we built a multilinear regression model to test the ability of the “clinical fingerprint” to predict the clinical evolution of the disease, as assessed by the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-r), the King’s disease staging system, and the Milano-Torino Staging (MiToS) disease staging system. We found a drop in the identifiability of patients in the alpha band compared to the healthy controls. Furthermore, the “clinical fingerprint” was predictive of the ALSFRS-r (p = 0.0397; ÎČ = 32.8), the King’s (p = 0.0001; ÎČ = − 7.40), and the MiToS (p = 0.0025; ÎČ = − 4.9) scores. Accordingly, it negatively correlated with the King’s (Spearman’s rho = -0.6041, p = 0.0003) and MiToS scales (Spearman’s rho = − 0.4953, p = 0.0040). Our results demonstrated the ability of the CCF approach to predict the individual motor impairment in patients affected by ALS. Given the subject-specificity of our approach, we hope to further exploit it to improve disease management

    A night of sleep deprivation alters brain connectivity and affects specific executive functions

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    : Sleep is a fundamental physiological process necessary for efficient cognitive functioning especially in relation to memory consolidation and executive functions, such as attentional and switching abilities. The lack of sleep strongly alters the connectivity of some resting-state networks, such as default mode network and attentional network. In this study, by means of magnetoencephalography (MEG) and specific cognitive tasks, we investigated how brain topology and cognitive functioning are affected by 24 h of sleep deprivation (SD). Thirty-two young men underwent resting-state MEG recording and evaluated in letter cancellation task (LCT) and task switching (TS) before and after SD. Results showed a worsening in the accuracy and speed of execution in the LCT and a reduction of reaction times in the TS, evidencing thus a worsening of attentional but not of switching abilities. Moreover, we observed that 24 h of SD induced large-scale rearrangements in the functional network. These findings evidence that 24 h of SD is able to alter brain connectivity and selectively affects cognitive domains which are under the control of different brain networks

    Radiomic and Artificial Intelligence Analysis with Textural Metrics, Morphological and Dynamic Perfusion Features Extracted by Dynamic Contrast-Enhanced Magnetic Resonance Imaging in the Classification of Breast Lesions

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    The aim of the study was to estimate the diagnostic accuracy of textural, morpho- logical and dynamic features, extracted by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) images, by carrying out univariate and multivariate statistical analyses including artificial intelligence approaches. Methods: In total, 85 patients with known breast lesion were enrolled in this retrospective study according to regulations issued by the local Institutional Review Board. All patients underwent DCE-MRI examination. The reference standard was pathology from a surgical specimen for malignant lesions and pathology from a surgical specimen or fine needle aspiration cytology, core or Tru-Cut needle biopsy for benign lesions. In total, 91 samples of 85 patients were ana- lyzed. Furthermore, 48 textural metrics, 15 morphological and 81 dynamic parameters were extracted by manually segmenting regions of interest. Statistical analyses including univariate and multivari- ate approaches were performed: non-parametric Wilcoxon–Mann–Whitney test; receiver operating characteristic (ROC), linear classifier (LDA), decision tree (DT), k-nearest neighbors (KNN), and support vector machine (SVM) were utilized. A balancing approach and feature selection methods were used. Results: The univariate analysis showed low accuracy and area under the curve (AUC) for all considered features. Instead, in the multivariate textural analysis, the best performance (accuracy (ACC) = 0.78; AUC = 0.78) was reached with all 48 metrics and an LDA trained with balanced data. The best performance (ACC = 0.75; AUC = 0.80) using morphological features was reached with an SVM trained with 10-fold cross-variation (CV) and balanced data (with adaptive synthetic (ADASYN) function) and a subset of five robust morphological features (circularity, rectangularity, sphericity, gleaning and surface). The best performance (ACC = 0.82; AUC = 0.83) using dynamic features was reached with a trained SVM and balanced data (with ADASYN function). Conclusion: Multivariate analyses using pattern recognition approaches, including all morphological, textural and dynamic features, optimized by adaptive synthetic sampling and feature selection operations obtained the best results and showed the best performance in the discrimination of benign and malignant lesions

    Practical recommendations for performing ultrasound scanning in the urological and andrological fields

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    Aim: US scanning has been defined as the urologist's stethoscope. These recommendations have been drawn up with the aim of ensuring minimum standards of excellence for ultrasound imaging in urological and andrological practice. A series of essential recommendations are made, to be followed during ultrasound investigations in kidney, prostate, bladder, scrotal and penile diseases. Methods: Members of the Imaging Working Group of the Italian Society of Urology (SIU) in collaboration with the Italian Society of Ultrasound in Urology, Andrology and Nephrology (SIEUN) identified expert Urologists, Andrologists, Nephrologists and Radiologists. The recommendations are based on review of the literature, previously published recommendations, books and the opinions of the experts. The final document was reviewed by national experts, including members of the Italian Society of Radiology. Results: Recommendations are listed in 5 chapters, focused on: kidney, bladder, prostate and seminal vesicles, scrotum and testis, penis, including penile echo-doppler. In each chapter clear definitions are made of: indications, technological standards of the devices, the method of performance of the investigation. The findings to be reported are described and discussed, and examples of final reports for each organ are included. In the tables, the ultrasound features of the principal male uro-genital diseases are summarized. Diagnostic accuracy and second level investigations are considered. Conclusions: Ultrasound is an integral part of the diagnosis and follow-up of diseases of the urinary system and male genitals in patients of all ages, in both the hospital and outpatient setting. These recommendations are dedicated to enhancing communication and evidence-based medicine in an inter- and multi-disciplinary approach. The ability to perform and interpret ultrasound imaging correctly has become an integral part of clinical practice in uro-andrology, but intra and inter-observer variability is a well known limitation. These recommendations will help to improve reliability and reproducibility in uro-andrological ultrasound scanning

    Digital breast tomosynthesis and contrast-enhanced dual-energy digital mammography alone and in combination compared to 2D digital synthetized mammography and MR imaging in breast cancer detection and classification.

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    To compare diagnostic performance of contrast-enhanced dual-energy digital mammography (CEDM) and digital breast tomosynthesis (DBT) alone and in combination compared to 2D digital mammography (MX) and dynamic contrast-enhanced MRI (DCE-MRI) in women with breast lesions. We enrolled 100 consecutive patients with breast lesions (BIRADS 3-5 at imaging or clinically suspicious). CEDM, DBT, and DCE-MRI 2D were acquired. Synthetized MX was obtained by DBT. A total of 134 lesions were investigated on 111 breasts of 100 enrolled patients: 53 were histopathologically proven as benign and 81 as malignant. Nonparametric statistics and receiver operating characteristic (ROC) curve were performed. Two-dimensional synthetized MX showed an area under ROC curve (AUC) of 0.764 (sensitivity 65%, specificity 80%), while AUC was of 0.845 (sensitivity 80%, specificity 82%) for DBT, of 0.879 (sensitivity 82%, specificity 80%) for CEDM, and of 0.892 (sensitivity 91%, specificity 84%) for CE-MRI. DCE-MRI determined an AUC of 0.934 (sensitivity 96%, specificity 88%). Combined CEDM with DBT findings, we obtained an AUC of 0.890 (sensitivity 89%, specificity 74%). A difference statistically significant was observed only between DCE-MRI and CEDM (P = .03). DBT, CEDM, CEDM combined to tomosynthesis, and DCE-MRI had a high ability to identify multifocal and bilateral lesions with a detection rate of 77%, 85%, 91%, and 95% respectively, while 2D synthetized MX had a detection rate for multifocal lesions of 56%. DBT and CEDM have superior diagnostic accuracy of 2D synthetized MX to identify and classify breast lesions, and CEDM combined with DBT has better diagnostic performance compared with DBT alone. The best results in terms of diagnostic performance were obtained by DCE-MRI. Dynamic information obtained by time-intensity curve including entire phase of contrast agent uptake allows a better detection and classification of breast lesions

    Computed Tomography Structured Reporting in the Staging of Lymphoma: A Delphi Consensus Proposal

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    Abstract Structured reporting (SR) in radiology is becoming increasingly necessary and has been recognized recently by major scientific societies. This study aims to build structured CT-based reports for lymphoma patients during the staging phase to improve communication between radiologists, members of multidisciplinary teams, and patients. A panel of expert radiologists, members of the Italian Society of Medical and Interventional Radiology (SIRM), was established. A modified Delphi process was used to develop the SR and to assess a level of agreement for all report sections. The Cronbach's alpha (Cα) correlation coefficient was used to assess internal consistency for each section and to measure quality analysis according to the average inter-item correlation. The final SR version was divided into four sections: (a) Patient Clinical Data, (b) Clinical Evaluation, (c) Imaging Protocol, and (d) Report, including n = 13 items in the "Patient Clinical Data" section, n = 8 items in the "Clinical Evaluation" section, n = 9 items in the "Imaging Protocol" section, and n = 32 items in the "Report" section. Overall, 62 items were included in the final version of the SR. A dedicated section of significant images was added as part of the report. In the first Delphi round, all sections received more than a good rating (≄3). The overall mean score of the experts and the sum of score for structured report were 4.4 (range 1-5) and 1524 (mean value of 101.6 and standard deviation of 11.8). The Cα correlation coefficient was 0.89 in the first round. In the second Delphi round, all sections received more than an excellent rating (≄4). The overall mean score of the experts and the sum of scores for structured report were 4.9 (range 3-5) and 1694 (mean value of 112.9 and standard deviation of 4.0). The Cα correlation coefficient was 0.87 in this round. The highest overall means value, highest sum of scores of the panelists, and smallest standard deviation values of the evaluations in this round reflect the increase of the internal consistency and agreement among experts in the second round compared to first round. The accurate statement of imaging data given to referring physicians is critical for patient care; the information contained affects both the decision-making process and the subsequent treatment. The radiology report is the most important source of clinical imaging information. It conveys critical information about the patient's health and the radiologist's interpretation of medical findings. It also communicates information to the referring physicians and records this information for future clinical and research use. The present SR was generated based on a multi-round consensus-building Delphi exercise and uses standardized terminology and structures, in order to adhere to diagnostic/therapeutic recommendations and facilitate enrolment in clinical trials, to reduce any ambiguity that may arise from non-conventional language, and to enable better communication between radiologists and clinicians
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