Unexpected Metastasis of High Grade Serous Ovarian Cancer to Breast: Case Report and Literature Review

Introduction: Metastasis of ovarian serous carcinoma to breast and/or axillary lymph nodes represents an unusual event. Nevertheless, their detection and distinction from mammary carcinoma are of huge clinical importance because the treatment and prognosis diverge significantly. Case presentation: We report a case of a 47 year-old Caucasian female patient with unforeseen metastasis to the breast and to axillary lymph nodes due to ovarian serous carcinoma. Conclusion: In patients with history of OSC who present with axillary or breast mass, an accurate histological diagnosis should be obtained since this has a great impact on treatment outcomes

Monitoring urban heat island through google earth engine. Potentialities and difficulties in different cities of the United States

The aim of this work is to exploit the large-scale analysis capabilities of the innovative Google Earth Engine platform in order to investigate the temporal variations of the Urban Heat Island phenomenon as a whole. A intuitive methodology implementing a large-scale correlation analysis between the Land Surface Temperature and Land Cover alterations was thus developed. The results obtained for the Phoenix MA are promising and show how the urbanization heavily affects the magnitude of the UHI effects with significant increases in LST. The proposed methodology is therefore able to efficiently monitor the UHI phenomenon

Multistep, sequential control of the trafficking and function of the multiple sulfatase deficiency gene product, SUMF1 by PDI, ERGIC-53 and ERp44.

Sulfatase modifying factor 1 (SUMF1) encodes for the formylglicine generating enzyme, which activates sulfatases by modifying a key cysteine residue within their catalytic domains. SUMF1 is mutated in patients affected by multiple sulfatase deficiency, a rare recessive disorder in which all sulfatase activities are impaired. Despite the absence of canonical retention/retrieval signals, SUMF1 is largely retained in the endoplasmic reticulum (ER), where it exerts its enzymatic activity on nascent sulfatases. Part of SUMF1 is secreted and paracrinally taken up by distant cells. Here we show that SUMF1 interacts with protein disulfide isomerase (PDI) and ERp44, two thioredoxin family members residing in the early secretory pathway, and with ERGIC-53, a lectin that shuttles between the ER and the Golgi. Functional assays reveal that these interactions are crucial for controlling SUMF1 traffic and function. PDI couples SUMF1 retention and activation in the ER. ERGIC-53 and ERp44 act downstream, favoring SUMF1 export from and retrieval to the ER, respectively. Silencing ERGIC-53 causes proteasomal degradation of SUMF1, while down-regulating ERp44 promotes its secretion. When over-expressed, each of three interactors favors intracellular accumulation. Our results reveal a multistep control of SUMF1 trafficking, with sequential interactions dynamically determining ER localization, activity and secretion

Raveguard: A noise monitoring platform using low-end microphones and machine learning

Urban noise is one of the most serious and underestimated environmental problems. According to the World Health Organization, noise pollution from traffic and other human activities, negatively impact the population health and life quality. Monitoring noise usually requires the use of professional and expensive instruments, called phonometers, able to accurately measure sound pressure levels. In many cases, phonometers are human-operated; therefore, periodic fine-granularity city-wide measurements are expensive. Recent advances in the Internet of Things (IoT) offer a window of opportunities for low-cost autonomous sound pressure meters. Such devices and platforms could enable fine time\u2013space noise measurements throughout a city. Unfortunately, low-cost sound pressure sensors are inaccurate when compared with phonometers, experiencing a high variability in the measurements. In this paper, we present RaveGuard, an unmanned noise monitoring platform that exploits artificial intelligence strategies to improve the accuracy of low-cost devices. RaveGuard was initially deployed together with a professional phonometer for over two months in downtown Bologna, Italy, with the aim of collecting a large amount of precise noise pollution samples. The resulting datasets have been instrumental in designing InspectNoise, a library that can be exploited by IoT platforms, without the need of expensive phonometers, but obtaining a similar precision. In particular, we have applied supervised learning algorithms (adequately trained with our datasets) to reduce the accuracy gap between the professional phonometer and an IoT platform equipped with low-end devices and sensors. Results show that RaveGuard, combined with the InspectNoise library, achieves a 2.24% relative error compared to professional instruments, thus enabling low-cost unmanned city-wide noise monitoring

Coherent Change Detection for repeated-pass interferometric SAR images: An application to earthquake damage assessment on buildings

During disaster response, the availability of relevant information, delivered in a proper format enabling its use among the different actors involved in response efforts, is key to lessen the impact of the disaster itself. Focusing on the contribution of geospatial information, meaningful advances have been achieved through the adoption of satellite earth observations within emergency management practices. Among these technologies, the Synthetic Aperture Radar (SAR) imaging has been extensively employed for large-scale applications such as flood areas delineation and terrain deformation analysis after earthquakes. However, the emerging availability of higher spatial and temporal resolution data has uncovered the potential contribution of SAR to applications at a finer scale. This paper proposes an approach to enable pixel-wise earthquake damage assessments based on Coherent Change Detection methods applied to a stack of repeated-pass interferometric SAR images. A preliminary performance assessment of the procedure is provided by processing Sentinel-1 data stack related to the 2016 central Italy earthquake for the towns of Amatrice and Accumoli. Damage assessment maps from photo-interpretation of high-resolution airborne imagery, produced in the framework of Copernicus EMS (Emergency Management Service - European Commission) and cross-checked with field survey, is used as ground truth for the performance assessment. Results show the ability of the proposed approach to automatically identify changes at an almost individual building level, thus enabling the possibility to empower traditional damage assessment procedures from optical imagery with the centimetric change detection sensitivity characterizing SAR. The possibility of disseminating outputs in a GIS-like format represents an asset for an effective and cross-cutting information sharing among decision makers and analysts

Eddy diffusivity derived from drifter data for dispersion model applications

Ocean transport and dispersion processes are at the present time simulated using Lagrangian stochastic models coupled with Eulerian circulation models that are supplying analyses and forecasts of the ocean currents at unprecedented time and space resolution. Using the Lagrangian approach, each particle displacement is described by an average motion and a fluctuating part. The first one represents the advection associated with the Eulerian current field of the circulation models while the second one describes the sub-grid scale diffusion. The focus of this study is to quantify the sub-grid scale diffusion of the Lagrangian models written in terms of a horizontal eddy diffusivity. Using a large database of drifters released in different regions of the Mediterranean Sea, the Lagrangian sub-grid scale diffusion has been computed, by considering different regimes when averaging statistical quantities. In addition, the real drifters have been simulated using a trajectory model forced by OGCM currents, focusing on how the Lagrangian properties are reproduced by the simulated trajectories

Fluorimetric methods for the measurement of intermediate metabolites (lactate, pyruvate, alanine, β-hydroxybutyrate, glycerol) using a COBAS FARA centrifugal analyser

Intermediate products of the metabolism of glucose, fat and amino-acid are important in the evaluation of such metabolic disorders as diabetes mellitus, liver disease and metabolic acidosis. In the present study, methods for the measurement of intermediate metabolites (lactate, pyruvate, alanine, β-hydroxybutyrate and glycerol) have been adapted to a fast centrifugal analyzer: the COBAS FARA. Correlation coeffcients rangedfrom 0.90 to 0.99, compared to established manual spectrophotometric methods. Within-run coeffcients of variation (CVs) ranged between 2.9 and 8.8% at low levels, between 1.5 and 5.7% at medium levels and between 1.2 and 5.6% at high levels. Between-run CVs were between 4.0 and 15.0% at low levels, between 1.7 and 7.0% at medium levels and between 1.3 and 2.7% at high levels. These fluorimetric assays for the determination of intermediate metabolites on COBAS FARA (Roche) have a good sensitivity and precision, are less costly than manual methods and can be used on a routine basis

High-resolution marine magnetic surveys for searching underwater cultural resources

Recently two marine magnetic surveys, combined with the use of a multi-beam sonar (Kongsberg Marittime EM 300 multibeam: 30 KHz frequency echosounder for hydrographic purposes; acoustic lobe composed of 128 beams able to cover a 150° sector) a side-scan sonar (Simrad MS 992 dual-frequency sidescan sonar with echo sounder transducers 150 Hz and 330 KHz) and a Remote Operated Vehicle (ROV – a mobile tools used in environments which are too dangerous for humans), were executed in two sites respectively in the Ligurian Sea and the Asinara Gulf. The aim of these investigations was to test modern instrumentations and set new working procedures for searching underwater cultural resources. The collected and processed magnetic data yielded very satisfactory results: we detected submerged and buried features of cultural interest at both sites, at depths of 40 m and 400 m respectively