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The authors used 1H-MRS to investigate hypothalamic metabolism in 26 patients with cluster headache (CH) and 12 healthy subjects. Hypothalamic N-acetylaspartate/creatine was reduced in patients with CH vs controls (p < 0.01). Dividing the patients into episodic CH outside- and in-cluster periods and chronic CH, the hypothalamic N-acetylaspartate/creatine in all three subgroups of patients was reduced. The reduction of the neuronal marker N-acetylaspartate is consistent with hypothalamic neuronal dysfunction in patients with CH.

A hierarchical formulation is presented for the large displacement modal and transient analysis of rotating plates having different thicknesses, sizes, and settings angle with respect to the spinning axis. After derivation of the governing equations of motion by the Principle of Virtual Displacements, the finite element discretization yields a set of nonlinear ordinary-differential equations for the generalized coordinates including gyroscopic terms, centrifugal/Euler accelerations and spin-softening effects. A Total Lagrangian approach is adopted. The modal analysis is performed by a two-step procedure. The static shape of the structure deformed by the centrifugal force is first defined. Subsequently, eigenfrequencies and mode shapes are computed by a classical eigenvalue problem past the static configuration previously computed. The transient analysis of the plates subject to a varying angular velocity is tackled by solving the nonlinear equations of motion by the Generalized- $$\alpha $$ method coupled to the Newmark’s approximation for the velocity and acceleration fields. It has been numerically proven that accurate results can be obtained by the use of Murakami’s Zig-Zag Function which a-priori enforces the interlaminar discontinuity of the displacements’slopes in the Equivalent Single Layer axiomatic model, thus avoiding higher-order polynomial representations for the displacement fields, or the use of Layer-Wise theories.

SEXTANT LOCALIZATION OF PROSTATE CANCER WITH 11C-CHOLINE PET/CT: COMPARISON WITH THREE-DIMENSIONAL PROTON MR SPECTROSCOPIC IMAGING USING STEP SECTION HISTOPATHOLOGY AS STANDARD OF REFERENCES

Aims Functional mitral regurgitation (MR) (FMR) is common in heart failure with reduced ejection fraction and worsens morbidity and mortality, even when mild. The CARILLON (R) mitral contour system (Cardiac Dimensions, Kirkland, WA, USA), a mitral annuloplasty device delivered percutaneously to the coronary sinus, is designed to reduce the mitral annular dimension by virtue of the close anatomic relationship between the coronary sinus and the posterior mitral annulus. We performed a comprehensive individual patient data meta-analysis of all studies that used CARILLON (R) device vs. control that have measured mitral regurgitation severity, left ventricular (LV) remodelling, functional status, and heart failure-related outcomes in heart failure with reduced ejection fraction patients. Methods and results The Cochrane Central Register of Controlled Trials, MEDLINE, and EMBASE were searched in July 2020. Primary outcomes of interest were measures of MR severity, LV remodelling, New York Heart Association functional class and heart failure-related outcomes [mortality and heart failure hospitalization (HFH) during follow up]. All data were received as individual patient and individual time point data-points. Mean differences and 95% confidence intervals (CIs) were calculated for continuous data using a fixed-effects model. Three studies (REDUCE FMR, TITAN and TITAN II) enrolling 209 participants were identified and included. Pooled analysis showed that, compared with control, CARILLON (R) device significantly improved both MR volume (mean difference MD -9.20, 95% C.I. -16.11 to -2.29 mL, P = 0.009) and MR grade (MD -1.12, 95% CI -1.36 to -0.88, P < 0.00001) and this was associated with a significant reduction in LA volume, MD -7.54 mL, 95% CI -14.90 to - 0.18, P = 0.04. Significant LV reverse remodelling was also seen in terms of EDV (MD -16.53, 95% CI -28.61 to -44.4 mL, P = 0.007), and a trend in ESV (MD -8.68, 95% CI -18.69 to -1.34 mL, P = 0.09) but no significant effect on LVEF (MD 0.88, 95% CI -1.52% to 2.38%, P = 0.47), due presumably to the greater residual MR in the control patients falsely elevating the LVEF. In addition, the CARILLON (R) device significantly improved New York Heart Association functional Class (MD -0.22, 95% CI -0.24 to -0.16, P < 0.00001), associated with a lower rate of HFH compared with controls (45.3% vs. 64%, respectively, P = 0.04). As a sensitivity analysis we also restricted the analyses to those patients with Class 3+/4+ MR at baseline. In this cohort, the echocardiographic results were similar, and the reduction in HFH rates was even more marked (43.9% vs. 82.9%, respectively, P = 0.04). Conclusions This comprehensive meta-analysis of individual patient data has shown that CARILLON (R) device provides statistically significant and clinically meaningful benefits on MR severity, LA and LV volumes, and remodelling and rates of subsequent heart failure hospitalization

Simple Summary Prostate Cancer is one of the main threats to men’s health. Its accurate diagnosis is crucial to properly treat patients depending on the cancer’s level of aggressiveness. Tumor risk-stratification is still a challenging task due to the difficulties met during the reading of multi-parametric Magnetic Resonance Images. Artificial Intelligence models may help radiologists in staging the aggressiveness of the equivocal lesions, reducing inter-observer variability and evaluation time. However, these algorithms need many high-quality images to work efficiently, bringing up overfitting and lack of standardization and reproducibility as emerging issues to be addressed. This study attempts to illustrate the state of the art of current research of Artificial Intelligence methods to stratify prostate cancer for its clinical significance suggesting how widespread use of public databases could be a possible solution to these issues. Abstract Many efforts have been carried out for the standardization of multiparametric Magnetic Resonance (mp-MR) images evaluation to detect Prostate Cancer (PCa), and specifically to differentiate levels of aggressiveness, a crucial aspect for clinical decision-making. Prostate Imaging—Reporting and Data System (PI-RADS) has contributed noteworthily to this aim. Nevertheless, as pointed out by the European Association of Urology (EAU 2020), the PI-RADS still has limitations mainly due to the moderate inter-reader reproducibility of mp-MRI. In recent years, many aspects in the diagnosis of cancer have taken advantage of the use of Artificial Intelligence (AI) such as detection, segmentation of organs and/or lesions, and characterization. Here a focus on AI as a potentially important tool for the aim of standardization and reproducibility in the characterization of PCa by mp-MRI is reported. AI includes methods such as Machine Learning and Deep learning techniques that have shown to be successful in classifying mp-MR images, with similar performances obtained by radiologists. Nevertheless, they perform differently depending on the acquisition system and protocol used. Besides, these methods need a large number of samples that cover most of the variability of the lesion aspect and zone to avoid overfitting. The use of publicly available datasets could improve AI performance to achieve a higher level of generalizability, exploiting large numbers of cases and a big range of variability in the images. Here we explore the promise and the advantages, as well as emphasizing the pitfall and the warnings, outlined in some recent studies that attempted to classify clinically significant PCa and indolent lesions using AI methods. Specifically, we focus on the overfitting issue due to the scarcity of data and the lack of standardization and reproducibility in every step of the mp-MR image acquisition and the classifier implementation. In the end, we point out that a solution can be found in the use of publicly available datasets, whose usage has already been promoted by some important initiatives. Our future perspective is that AI models may become reliable tools for clinicians in PCa diagnosis, reducing inter-observer variability and evaluation time.

Introduction: The mitochondrial DNA (mtDNA) m.3243A > G mutation in the MT-TL1 gene results in a multi-systemic disease, that is commonly associated with neurodegenerative changes in the brain. Methods: Seventeen patients harboring the m3243A > G mutation were enrolled (age 43.1 ± 11.4 years, 10 M/7F). A panel of plasma biomarkers including lactate acid, alanine, L-arginine, fibroblast growth factor 21 (FGF-21), growth/differentiation factor 15 (GDF-15) and circulating cell free -mtDNA (ccf-mtDNA), as well as blood, urine and muscle mtDNA heteroplasmy were evaluated. Patients also underwent a brain standardized MR protocol that included volumetric T1-weighted images and diffusion-weighted MRI. Twenty sex- and age-matched healthy controls were included. Voxel-wise analysis was performed on T1-weighted and diffusion imaging, respectively with VBM (voxel-based morphometry) and TBSS (Tract-based Spatial Statistics). Ventricular lactate was also evaluated by 1H-MR spectroscopy. Results: A widespread cortical gray matter (GM) loss was observed, more severe (p < 0.001) in the bilateral calcarine, insular, frontal and parietal cortex, along with infratentorial cerebellar cortex. High urine mtDNA mutation load, high levels of plasma lactate and alanine, low levels of plasma arginine, high levels of serum FGF-21 and ventricular lactate accumulation significantly (p < 0.05) correlated with the reduced brain GM density. Widespread microstructural alterations were highlighted in the white matter, significantly (p < 0.05) correlated with plasma alanine and arginine levels, with mtDNA mutation load in urine, with high level of serum GDF-15 and with high content of plasma ccf-mtDNA. Conclusions: Our results suggest that the synergy of two pathogenic mechanisms, mtDNA-related mitochondrial respiratory deficiency and defective nitric oxide metabolism, contributes to the brain neurodegeneration in m.3243A > G patients.

Differential diagnosis between primary progressive aphasia (PPA) and Alzheimer’s disease (AD) could be difficult if based on clinical grounds alone. We evaluated the combination of proton MR spectroscopy of posterior cingulate cortex (PCC) and quantitative structural imaging asymmetries to differentiate PPA from AD patients. A greater left-lateralized temporo-parietal atrophy (higher accuracy for the PCC, 81.4%) and metabolic neurodegenerative changes in PCC (accuracy 76.8%) was demonstrated in PPA versus AD. The combined multiparametric approach increased the accuracy to 94%in the differential diagnosis between these two neurodegenerative diseases.

Nuclear Magnetic Resonance (NMR) is a well-suited methodology to study bone composition and structural properties. This is because the NMR parameters, such as the T2 relaxation time, are sensitive to the chemical and physical environment of the 1H nuclei. Although magnetic resonance imaging (MRI) allows bone structure assessment in vivo, its cost limits the suitability of conventional MRI for routine bone screening. With difficulty accessing clinically suitable exams, the diagnosis of bone diseases, such as osteoporosis, and the associated fracture risk estimation is based on the assessment of bone mineral density (BMD), obtained by the dual-energy X-ray absorptiometry (DXA). However, integrating the information about the structure of the bone with the bone mineral density has been shown to improve fracture risk estimation related to osteoporosis. Portable NMR, based on low-field single-sided NMR devices, is a promising and appealing approach to assess NMR properties of biological tissues with the aim of medical applications. Since these scanners detect the signal from a sensitive volume external to the magnet, they can be used to perform NMR measurement without the need to fit a sample inside a bore of a magnet, allowing, in principle, in vivo application. Techniques based on NMR single-sided devices have the potential to provide a high impact on the clinical routine because of low purchasing and running costs and low maintenance of such scanners. In this review, the development of new methodologies to investigate structural properties of trabecular bone exploiting single-sided NMR devices is reviewed, and current limitations and future perspectives are discussed.

MR fingerprinting (MRF) is an innovative approach to quantitative MRI. A typical disadvantage of dictionary-based MRF is the explosive growth of the dictionary as a function of the number of reconstructed parameters, an instance of the curse of dimensionality, which determines an explosion of resource requirements. In this work, we describe a deep learning approach for MRF parameter map reconstruction using a fully connected architecture. Employing simulations, we have investigated how the performance of the Neural Networks (NN) approach scales with the number of parameters to be retrieved, compared to the standard dictionary approach. We have also studied optimal training procedures by comparing different strategies for noise addition and parameter space sampling, to achieve better accuracy and robustness to noise. Four MRF sequences were considered: IR-FISP, bSSFP, IR-FISP- B 1 , and IR-bSSFP- B 1 . A comparison between NN and the dictionary approaches in reconstructing parameter maps as a function of the number of parameters to be retrieved was performed using a numerical brain phantom. Results demonstrated that training with random sampling and different levels of noise variance yielded the best performance. NN performance was at least as good as the dictionary-based approach in reconstructing parameter maps using Gaussian noise as a source of artifacts: the difference in performance increased with the number of estimated parameters because the dictionary method suffers from the coarse resolution of the parameter space sampling. The NN proved to be more efficient in memory usage and computational burden, and has great potential for solving large-scale MRF problems.

Atherosclerosis is a dynamic process driven by all cardiovascular risk factors that can be briefly divided into an early and a late phase. Inflammation is one of the fundamental substrates that initiates the atherosclerotic process in the early stages and promotes and maintains it in the final stages. In the last decades, clinical and experimental data have shown that inflammation is supported by mediators that respond to physical activity. The present review aims at investigating the effect of physical exercise on inflammatory mediators, both the positive ones that therefore have a pro-inflammatory effect (interleukin 6, c-reactive protein and tumor necrosis factor alpha, interferon gamma, high-mobility group box-1), and the negative ones which have an anti-inflammatory effect (interleukin 10). Pooled data support the evidence that physical exercise is able to directly modulate the activity of inflammatory cytokines slowing down or preventing the formation of the atherosclerotic stage.

This paper deals with the theoretical–numerical study of integral formulations for the prediction of noise scattered by moving bodies, through the velocity-potential description of flow disturbance. Specifically, three potential-flow acoustic scattering integral formulations are examined: A linearized boundary-field integral formulation, recently introduced by the authors, is compared with two widely applied boundary integral approaches based on Taylor and Taylor–Lorentz transformations. The objective of this work is to provide a detailed analysis of the theoretical differences among these formulations and corresponding limits of applicability, followed by the assessment of their capability of capturing the influence of nonuniform mean flow around moving sound scatterers. This is accomplished by a numerical investigation that concerns a rigid, rectangular, non-lifting wing in uniform rectilinear translation impinged by sound waves emitted by a comoving pulsating point source.

Objective: Friedreich ataxia (FRDA) is an inherited neurological disease defined by progressive movement incoordination. We undertook a comprehensive characterization of the spatial profile and progressive evolution of structural brain abnormalities in people with FRDA. Methods: A coordinated international analysis of regional brain volume using magnetic resonance imaging data charted the whole-brain profile, interindividual variability, and temporal staging of structural brain differences in 248 individuals with FRDA and 262 healthy controls. Results: The brainstem, dentate nucleus region, and superior and inferior cerebellar peduncles showed the greatest reductions in volume relative to controls (Cohen d= 1.5–2.6). Cerebellar gray matter alterations were most pronounced in lobules I–VI (d= 0.8), whereas cerebral differences occurred most prominently in precentral gyri (d= 0.6) and corticospinal tracts (d= 1.4). Earlier onset age predicted less volume in the motor cerebellum (rmax= 0.35) and peduncles (rmax= 0.36). Disease duration and severity correlated with volume deficits in the dentate nucleus region, brainstem, and superior/inferior cerebellar peduncles (rmax= −0.49); subgrouping showed these to be robust and early features of FRDA, and strong candidates for further biomarker validation. Cerebral white matter abnormalities, particularly in corticospinal pathways, emerge as intermediate disease features. Cerebellar and cerebral gray matter loss, principally targeting motor and sensory systems, preferentially manifests later in the disease course. Interpretation: FRDA is defined by an evolving spatial profile of neuroanatomical changes beyond primary pathology in the cerebellum and spinal cord, in line with its progressive clinical course. The design, interpretation, and generalization of research studies and clinical trials must consider neuroanatomical staging and associated interindividual variability in brain measures. ANN NEUROL 2021;90:570–583.

Background To date, research assessing discrimination has employed primarily explicit measures (i.e., self-reports), which can be subject to intentional and social desirability processes. Only a few studies, focusing on sex and race/ethnicity discrimination, have relied on implicit measures (i.e., Implicit Association Test, IAT), which permit assessing mental representations that are outside of conscious control. This study aims to advance measurement of discrimination by extending the application of implicit measures to multiple types of discrimination and optimizing the time required for the administration of these instruments. Methods Between September 27th 2019 and February 9th 2020, we conducted six experiments (984 participants) to assess implicit and explicit discrimination based on race/ethnicity, sex, gender identity, sexual orientation, weight, and age. Implicit discrimination was measured by using the Brief-Implicit Association Test (B-IAT), a new validated version of the IAT developed to shorten the time needed (from ≈15 to ≈2 min) to assess implicit mental representations, while explicit discrimination was assessed using self-reported items. Results Among participants (mean age = 37.8), 68.6% were White Non-Hispanic; 69% were females; 76.1% were heterosexual; 90.7% were gender conforming; 52.8% were medium weight; and 41.5% had an advanced level of education. Overall, we found implicit and explicit recognition of discrimination towards all the target groups (stronger for members of the target than dominant groups). Some exceptions emerged in experiments investigating race/ethnicity and weight discrimination. In the racism experiment, only people of Color showed an implicit recognition of discrimination towards the target group, while White people were neutral. In the fatphobia experiment, participants who were not heavy showed a slight implicit recognition of discrimination towards the dominant group, while heavy participants were neutral. Conclusions This study provides evidence that the B-IAT is a valuable tool for quickly assessing multiple types of implicit discrimination. It shows also that implicit and explicit measures can display diverging results, thus indicating that research would benefit from the use of both these instruments. These results have important implications for the assessment of discrimination in health research as well as in social and psychological science.

This paper presents a boundary-field integral formulation suitable for the prediction of noise scattered by moving bodies. Although based on the same flow modeling assumptions, linear formulations derived from velocity potential or pressure disturbance wave equations provide different predictions when the scatterer is not at rest. Indeed, the discrepancies reside in the different influence of the neglected nonlinear terms. Here, a velocity potential-based approach is developed by extracting the first-order contributions from the nonlinear terms. This yields a linearized boundary-field, frequency-domain formulation for the scattered potential that, extending the standard linear boundary integral approach, takes into account the effects of mean flow nonuniformity. The influence of the additional field contributions is examined for different scatterer velocities, with the aim of assessing the domain of validity of the fully linear formulation and the rate of growth of the field contributions with increase of velocity. Specifically, the numerical investigation concerns the noise scattered by a moving, nonlifting wing, when impinged by an acoustic disturbance generated by a co-moving point source.

BACKGROUND AND PURPOSE: Mitochondrial neurogastrointestinal encephalopathy is a rare disorder due to recessive mutations in the thymidine phosphorylase gene, encoding thymidine phosphorylase protein required for mitochondrial DNA replication. Clinical manifestations include gastrointestinal dysmotility and diffuse asymptomatic leukoencephalopathy. This study aimed to elucidate the mechanisms underlying brain leukoencephalopathy in patients with mitochondrial neurogastrointestinal encephalopathy by correlating multimodal neuroradiologic features to postmortem pathology. MATERIALS AND METHODS: Seven patients underwent brain MR imaging, including single-voxel proton MR spectroscopy and diffusion imaging. Absolute concentrations of metabolites calculated by acquiring unsuppressed water spectra at multiple TEs, along with diffusion metrics based on the tensor model, were compared with those of healthy controls using unpaired t tests in multiple white matters regions. Brain postmortem histologic, immunohistochemical, and molecular analyses were performed in 1 patient. RESULTS: All patients showed bilateral and nearly symmetric cerebral white matter hyperintensities on T2-weighted images, extending to the cerebellar white matter and brain stem in 4. White matter, N -acetylaspartate, creatine, and choline concentrations were significantly reduced compared with those in controls, with a prominent increase in the radial water diffusivity component. At postmortem examination, severe fibrosis of brain vessel smooth muscle was evident, along with mitochondrial DNA replication depletion in brain and vascular smooth-muscle and endothelial cells, without neuronal loss, myelin damage, or gliosis. Prominent periependymal cytochrome C oxidase deficiency was also observed. CONCLUSIONS: Vascular functional and histologic alterations account for leukoencephalopathy in mitochondrial neurogastrointestinal encephalopathy. Thymidine toxicity and mitochondrial DNA replication depletion may induce microangiopathy and blood-brain-barrier dysfunction, leading to increased water content in the white matter. Periependymal cytochrome C oxidase deficiency could explain prominent periventricular impairment.

This paper investigates the use of the permeable surface integral formulation based on the Ffowcs Williams–Hawkings Equation to predict the noise field generated by marine propellers. After derivation of the integral formulation, first, in the framework of potential flows, its main features are discussed for case-studies that allow a straightforward interpretation of the results achieved. Then, issues related to the use of pseudo-compressible, performance-oriented CFD solvers to detect the sources of sound over the permeable surface of integration are carefully examined. Among them, the occurrence of undesired boundary reflection effects and the strategies for their mitigation are discussed. The end-cap problem, open v s closed surface strategies, placement/sizing of the permeable surface and CFD grid topology suitability for hydroacoustic purposes are further topics considered in the paper. In order to provide guidelines and best practices for FWH permeable-surface hydroacoustics, the strategic choices made in determining the numerical predictions are discussed in detail. As one of the most interesting outcomes of the numerical investigation, it has been proven that accurate noise predictions are achievable through tailored CFD grid stretching capable of avoiding boundary reflections, an issue affecting hydroacoustics more than hydrodynamics.

Melanopsin retinal ganglion cells (mRGCs) are intrinsically photosensitive photoreceptors contributing both to image and non-image-forming (NIF) functions of the eye. They convey light signal to the brain to modulate circadian entrainment, sleep, alertness, cognition, brightness perception and coarse vision. Given that rods and cones also contribute to all these impacts of light, isolating mRGC visual and NIF roles in humans is challenging so that mRGC functions remains to be fully characterized. Here, we evaluated light-driven visual and cognitive brain responses in Leber’s Hereditary Optic Neuropathy (LHON), an inherited optic neuropathy that is characterized by a selective relative sparing of the melanopsin-expressing retinal ganglion cells (mRGCs). Twelve patients and twelve matched healthy controls (HC) were enrolled in a functional brain magnetic resonance imaging (fMRI) protocol including visual and visual-cognitive paradigms under blue (480 nm) and red (620 nm) light exposures. Primary visual cortex activation was detected in LHON patients; in particular higher occipital activation was found in response to sustained blue vs. red stimulation in LHON vs. HC. Similarly, brain responses to the executive task were larger under blue vs. red light in LHON over lateral prefrontal cortex. These findings are in line with the relative mRGC sparing demonstrated in LHON and support the mRGC contribution to both non-visual and visual brain functions, with potential implication for visual rehabilitation in hereditary optic neuropathy patients.

Objectives To evaluate white matter and cortical changes in patients with parkinsonisms and healthy controls (HC), applying both hypothesis-free and regions of interest (ROI)-based advanced brain MR analyses. Methods Twenty-five patients with Progressive Supranuclear Palsy - Richardson's Syndrome (PSP-RS), nine with cerebellar and nine with parkinsonian Multiple System Atrophy variants (MSA-C and MSA-P), forty-seven with Parkinson's Disease (PD) and twenty-seven HC underwent a 1.5 T brain-MR protocol including high-resolution 3D T1-weighted and 25-direction diffusion tensor imaging sequences. We performed cortical and white matter analysis by using vertex-based cortical thickness evaluation and Tract Based Spatial Statistics (TBSS), followed by a ROI-based cortical thickness analysis and probabilistic tractography of cortico-spinal tract (CST), and middle and superior cerebellar peduncles (MCP and SCP). Results In PSP-RS, both ROIs-based and voxel-wise analyses demonstrated significant thinning of the pre-central cortices and diffuse white matter alterations involving supra- and infratentorial compartments. Along-tract tractography analysis of CST showed a significantly higher MD in PSP-RS vs PD and HC limited to the portion of the tract within the corona radiata. In MSA-C, a predominant involvement of MCPs was evident, while alterations in MCPs in MSA–P and in SCPs in PSP-RS and MSA-C were also present. Conclusion Specific patterns of cortical and white matter changes in atypical parkinsonism patients reflect the neuropathological and clinical features of these disorders. This study shows that quantitative brain MR techniques can detect significant changes that help to elucidate the physiopathology of movement disorders and support their differential diagnosis.

This paper deals with theoretical-numerical comparisons among integral formulations for the prediction of noise scattered by moving bodies. Three acoustic scattering integral formulations for the solution of the velocity potential wave equation are examined: a recently proposed linearized boundary-field integral formulation, and two widely applied boundary integral approaches based on Taylor and Taylor-Lorentz transformations. Aim of the work is to highlight their theoretical differences and limits of applicability, while examining their capability of capturing the influence of body motion and corresponding nonuniform mean flow around it on the scattered noise field. Numerical results concern a rigid rectangular non-lifting wing in uniform rectilinear translation impinged by sound waves emitted by a co-moving pulsating point-source.

The presence of the insecticide Fipronil and its main products of toxicological relevance, namely Sulfone and Desulfinyl, was assessed in 161 residential house dust samples in the absence (N = 101) and presence (N = 60) of cats and dogs in Italy. High-resolution mass spectrometry analysis revealed a significant difference (p < 0.001) in the dust contamination in the presence of pets (median: 467 vs. 24 ng/g dry weight), even if the highest value was found in the absence of pets (82,069 vs. 67,799 ng/g dry weight). Fipronil intake estimates from dust in toddlers, computed according to US-EPA and EU-ECHA guidelines, ranged from 333 to 556 and from 20 to 34 ng/kg per day for acute and chronic scenario, respectively. Dust seemed not able itself to lead to Fipronil overexposure with respect to acute and chronic toxicity health-based guidance values. Kittens were potentially overexposed to Fipronil under both acute (26,076 ng/kg per day) and chronic (1,633 ng/kg per day) scenarios. The mild symptomatology associated with acute intoxication could possibly determine case underreporting within pharmacosurveillance schemes. Its administration was estimated in 7.3–9.7 tons per year. Such a range suggests its prudent use under strict veterinary control to prevent pest resistance and ecotoxicological outcomes.

This paper presents two novel integral formulations for the prediction of sound scattered by moving bodies, derived from the Lighthill and the Ffowcs Williams and Hawkings equations for the pressure field. These are expressed in the frequency-domain, over a permeable (fictitious) surface surrounding the scatterer(s), and are numerically evaluated through application of a boundary element technique. The aims of the paper are the assessment of the influence of the nonlinear terms of Lighthill and Ffowcs Williams and Hawkings equations on sound scattering prediction in the presence of nonuniform mean-flow due to scatterer motion, the assessment of the corresponding limits of applicability of the widely-used linear formulations for solid-wall boundaries, and the development of integral formulations capable to predict accurately and efficiently the noise scattered in the far field by moving bodies. The numerical investigation concerns a non-lifting wing in uniform translation impinged by an acoustic disturbance generated by a co-moving source, and includes the comparison of the results obtained through the proposed scattering formulations with those provided by a boundary-field velocity-potential approach recently validated for moving-body problems. Its main outcomes reveal that, when the proposed pressure-field formulations include the nonlinear terms through application of a suitable permeable-surface, their predictions match those provided by the boundary-field velocity-potential solver, whereas the fully linear versions of both pressure-field approaches yield underestimated scattered noise predictions, significantly less accurate than those given by the linear version of the velocity-potential formulation.