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

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)

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

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; β = 32.8), the King’s (p = 0.0001; β = − 7.40), and the MiToS (p = 0.0025; β = − 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

: 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

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

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

Scientific Status Quo of Small Renal Lesions: Diagnostic Assessment and Radiomics

Background: Small renal masses (SRMs) are defined as contrast-enhanced renal lesions less than or equal to 4 cm in maximal diameter, which can be compatible with stage T1a renal cell carcinomas (RCCs). Currently, 50-61% of all renal tumors are found incidentally. Methods: The characteristics of the lesion influence the choice of the type of management, which include several methods SRM of management, including nephrectomy, partial nephrectomy, ablation, observation, and also stereotactic body radiotherapy. Typical imaging methods available for differentiating benign from malignant renal lesions include ultrasound (US), contrast-enhanced ultrasound (CEUS), computed tomography (CT), and magnetic resonance imaging (MRI). Results: Although ultrasound is the first imaging technique used to detect small renal lesions, it has several limitations. CT is the main and most widely used imaging technique for SRM characterization. The main advantages of MRI compared to CT are the better contrast resolution and tissue characterization, the use of functional imaging sequences, the possibility of performing the examination in patients allergic to iodine-containing contrast medium, and the absence of exposure to ionizing radiation. For a correct evaluation during imaging follow-up, it is necessary to use a reliable method for the assessment of renal lesions, represented by the Bosniak classification system. This classification was initially developed based on contrast-enhanced CT imaging findings, and the 2019 revision proposed the inclusion of MRI features; however, the latest classification has not yet received widespread validation. Conclusions: The use of radiomics in the evaluation of renal masses is an emerging and increasingly central field with several applications such as characterizing renal masses, distinguishing RCC subtypes, monitoring response to targeted therapeutic agents, and prognosis in a metastatic context

Orthostatic Hypotension in Parkinson's Disease: Do Height and Weight Matter?

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