A fixed combination of probiotics and herbal extracts attenuates intestinal barrier dysfunction from inflammatory stress in an in vitro model using Caco-2 cells.

Background: Inflammatory Bowel Diseases (IBD), are considered a growing global disease, with about ten million people being affected worldwide. Maintenance of intestinal barrier integrity is crucial for preventing IBD onset and exacerbations. Some recent patents regarding oily formulations containing probiotics (WO2010122107A1 and WO2010103374A9) and the use of probiotics for gastrointestinal complaints (US20110110905A1 and US9057112B2) exist, or are pending application. Objective: In this work, we studied the effect of a fixed combination of registered Lactobacillus reuteri and Lactobacillus acidophilus strains and herbal extracts in an in vitro inflammation experimental model. Methods: Caco-2 cell monolayer was exposed to INF-\u3b3+TNF-\u3b1 or to LPS; Trans Epithelial Electrical Resistance (TEER) and paracellular permeability were investigated. ZO-1 and occludin Tight Junctions (TJs) were also investigated by mean of immunofluorescence. Results: Pre-treatment with the fixed combination of probiotics and herbal extracts prevented the inflammation-induced TEER decrease, paracellular permeability increase and TJs translocation. Conclusions: In summary, the fixed combination of probiotics and herbal extracts investigated in this research was found to be an interesting candidate for targeting the re-establishment of intestinal barrier function in IBD conditions

Assessing radiative transfer models trained by numerical weather forecasts using sun-tracking radiometric measurements for satellite link characterization up to W band

Radio communications, and in particular Earth-to-satellite links, are worldwide used for delivering digital services. The bandwidth demand of such services is increasing accordingly to the advent of more advanced applications (e.g., multimedia services, deep-space explorations, etc.) thus pushing the scientific community toward the investigation of channel carriers at higher frequencies. When using carrier frequencies above X band, the main drawback is how to tackle the impact of tropospheric processes (i.e., rain, cloud, water vapor). This work assesses the joint use of weather forecast models, radiative transfer models and Sun-tracking radiometric measurements to explore their potential benefits in predicting path attenuation and sky noise temperature for slant paths at frequencies between K and W band, thus paving the way to the optimization of satellite link-budgets

The Eyjafjöll explosive volcanic eruption from a microwave weather radar perspective

Abstract. The sub-glacial Eyjafjöll explosive volcanic eruptions of April and May 2010 are analyzed and quantitatively interpreted by using ground-based weather radar data and the Volcanic Ash Radar Retrieval (VARR) technique. The Eyjafjöll eruptions have been continuously monitored by the Keflavík C-band weather radar, located at a distance of about 155 km from the volcano vent. Considering that the Eyjafjöll volcano is approximately 20 km from the Atlantic Ocean and that the northerly winds stretched the plume toward the mainland Europe, weather radars are the only means to provide an estimate of the total ejected tephra. The VARR methodology is summarized and applied to available radar time series to estimate the plume maximum height, ash particle category, ash volume, ash fallout and ash concentration every 5 min near the vent. Estimates of the discharge rate of eruption, based on the retrieved ash plume top height, are provided together with an evaluation of the total erupted mass and volume. Deposited ash at ground is also retrieved from radar data by empirically reconstructing the vertical profile of radar reflectivity and estimating the near-surface ash fallout. Radar-based retrieval results cannot be compared with ground measurements, due to the lack of the latter, but further demonstrate the unique contribution of these remote sensing products to the understating and modelling of explosive volcanic ash eruptions

Hydrometeor classification from dual-polarized weather radar: extending fuzzy logic from S-band to C-band data

International audienceA model-based fuzzy classification method for C-band polarimetric radar data, named Fuzzy Radar Algorithm for Hydrometeor Classification at C-band (FRAHCC), is presented. Membership functions are designed for best fitting simulation data at C-band, and they are derived for ten different hydrometeor classes by means of a scattering model, based on T-Matrix numerical method. The fuzzy logic classification technique uses a reduced set of polarimetric observables, i.e. copolar reflectivity and differential reflectivity, and it is finally applied to data coming from radar sites located in Gattatico and S. Pietro Capofiume in North Italy. The final purpose is to show qualitative accuracy improvements with respect to the use of a set of ten bidimensional MBFs, previously adopted and well suited to S-band data but not to C-band data

Interpretation of observed microwave signatures from ground dual polarization radar and space multi-frequency radiometer for the 2011 Grímsvötn volcanic eruption

Abstract. The important role played by ground-based microwave weather radars for the monitoring of volcanic ash clouds has been recently demonstrated. The potential of microwaves from satellite passive and ground-based active sensors to estimate near-source volcanic ash cloud parameters has been also proposed, though with little investigation of their synergy and the role of the radar polarimetry. The goal of this work is to show the potentiality and drawbacks of the X-band dual polarization (DPX) radar measurements through the data acquired during the latest Grímsvötn volcanic eruptions that took place in May 2011 in Iceland. The analysis is enriched by the comparison between DPX data and the observations from the satellite Special Sensor Microwave Imager/Sounder (SSMIS) and a C-band single polarization (SPC) radar. SPC, DPX, and SSMIS instruments cover a large range of the microwave spectrum, operating respectively at 5.4, 3.2, and 0.16–1.6 cm wavelengths

Influence of wind-induced effects on laser disdrometer measurements: Analysis and compensation strategies

Nowadays, laser disdrometers constitute a very appealing tool for measuring surface precipitation properties, by virtue of their capability to estimate not only the rainfall amount and intensity, but also the number, the size and the velocity of falling drops. However, disdrometric measures are affected by various sources of error being some of them related to environmental conditions. This work presents an assessment of Thies Clima laser disdrometer performance with a focus on the relationship between wind and the accuracy of the disdrometer output products. The 10-min average rainfall rate and total rainfall accumulation obtained by the disdrometer are systematically compared with the collocated measures of a standard tipping bucket rain gauge, the FAK010AA sensor, in terms of familiar statistical scores. A total of 42 rainy events, collected in a mountainous site of Southern Italy (Montevergine observatory), are used to support our analysis. The results show that the introduction of a new adaptive filtering in the disdrometric data processing can reduce the impact of sampling errors due to strong winds and heavy rain conditions. From a quantitative perspective, the novel filtering procedure improves by 8% the precipitation estimates with respect to the standard approach widely used in the literature. A deeper examination revealed that the signature of wind speed on raw velocity-diameter spectrographs gradually emerges with the rise of wind strength, thus causing a progressive increase of the wrongly allocated hydrometeors (which reaches 70% for wind speed greater than 8 m s−1). With the aid of reference rain-gauge rainfall data, we designed a second simple methodology that makes use of a correction factor to mitigate the wind-induced bias in disdrometric rainfall estimates. The resulting correction factor could be applied as an alternative to the adaptive filtering suggested by this study and may be of practical use when dealing with disdrometric data processing

Contribution of mitochondrial activity to doxorubicin-resistance in osteosarcoma cells

: Osteosarcoma is considered the most common bone tumor affecting children and young adults. The standard of care is chemotherapy; however, the onset of drug resistance still jeopardizes osteosarcoma patients, thus making it necessary to conduct a thorough investigation of the possible mechanisms behind this phenomenon. In the last decades, metabolic rewiring of cancer cells has been proposed as a cause of chemotherapy resistance. Our aim was to compare the mitochondrial phenotype of sensitive osteosarcoma cells (HOS and MG-63) versus their clones when continuously exposed to doxorubicin (resistant cells) and identify alterations exploitable for pharmacological approaches to overcome chemotherapy resistance. Compared with sensitive cells, doxorubicin-resistant clones showed sustained viability with less oxygen-dependent metabolisms, and significantly reduced mitochondrial membrane potential, mitochondrial mass, and ROS production. In addition, we found reduced expression of TFAM gene generally associated with mitochondrial biogenesis. Finally, combined treatment of resistant osteosarcoma cells with doxorubicin and quercetin, a known inducer of mitochondrial biogenesis, re-sensitizes the doxorubicin effect in resistant cells. Despite further investigations being needed, these results pave the way for the use of mitochondrial inducers as a promising strategy to re-sensitize doxorubicin cytotoxicity in patients who do not respond to therapy or reduce doxorubicin side effects

Potential of high-resolution detection and retrieval of precipitation fields from X-band spaceborne synthetic aperture radar over land

Abstract. X-band Synthetic Aperture Radars (X-SARs), able to image the Earth's surface at metric resolution, may provide a unique opportunity to measure rainfall over land with spatial resolution of about few hundred meters, due to the atmospheric moving-target degradation effects. This capability has become very appealing due to the recent launch of several X-SAR satellites, even though several remote sensing issues are still open. This work is devoted to: (i) explore the potential of X-band high-resolution detection and retrieval of rainfall fields from space using X-SAR signal backscattering amplitude and interferometric phase; (ii) evaluate the effects of spatial resolution degradation by precipitation and inhomogeneous beam filling when comparing to other satellite-based sensors. Our X-SAR analysis of precipitation effects has been carried out using both a TerraSAR-X (TSX) case study of Hurricane "Gustav" in 2008 over Mississippi (USA) and a COSMO-SkyMed (CSK) X-SAR case study of orographic rainfall over Central Italy in 2009. For the TSX case study the near-surface rain rate has been retrieved from the normalized radar cross section by means of a modified regression empirical algorithm (MREA). A relatively simple method to account for the geometric effect of X-SAR observation on estimated rainfall rate and first-order volumetric effects has been developed and applied. The TSX-retrieved rain fields have been compared to those estimated from the Next Generation Weather Radar (NEXRAD) in Mobile (AL, USA). The rainfall detection capability of X-SAR has been tested on the CSK case study using the repeat-pass coherence response and qualitatively comparing its signature with ground-based Mt. Midia C-band radar in central Italy. A numerical simulator to represent the effect of the spatial resolution and the antenna pattern of TRMM satellite Precipitation Radar (PR) and Microwave Imager (TMI), using high-resolution TSX-retrieved rain images, has been also set up in order to evaluate the rainfall beam filling phenomenon. As expected, the spatial average can modify the statistics of the high-resolution precipitation fields, strongly reducing its dynamics in a way non-linearly dependent on the rain rate local average value

Impact of radar data assimilation for the simulation of a heavy rainfall case in central Italy using WRF–3DVAR

Abstract. The aim of this study is to investigate the role of the assimilation of Doppler weather radar (DWR) data in a mesoscale model for the forecast of a heavy rainfall event that occurred in Italy in the urban area of Rome from 19 to 22 May 2008. For this purpose, radar reflectivity and radial velocity acquired from Monte Midia Doppler radar are assimilated into the Weather Research Forecasting (WRF) model, version 3.4.1. The general goal is to improve the quantitative precipitation forecasts (QPF): with this aim, several experiments are performed using the three-dimensional variational (3DVAR) technique. Moreover, sensitivity tests to outer loops are performed to include non-linearity in the observation operators. In order to identify the best initial conditions (ICs), statistical indicators such as forecast accuracy, frequency bias, false alarm rate and equitable threat score for the accumulated precipitation are used. The results show that the assimilation of DWR data has a large impact on both the position of convective cells and on the rainfall forecast of the analyzed event. A positive impact is also found if they are ingested together with conventional observations. Sensitivity to the use of two or three outer loops is also found if DWR data are assimilated together with conventional data

Potential of High-resolution Detection and Retrieval of Precipitation Fields from X-band Spaceborne Synthetic Aperture Radar over land

X-band Synthetic Aperture Radars (X-SARs), able to image the Earth’s surface at metric resolution, may provide a unique opportunity to measure rainfall over land with spatial resolution of about few hundred meters, due to the atmospheric moving-target degradation effects. This capability has become very appealing due to the recent launch of several X-SAR satellites, even though several remote sensing issues are still open. This work is devoted to: (i) explore the potential of X-band high-resolution detection and retrieval of rainfall fields from space using X-SAR signal backscattering amplitude and interferometric phase; (ii) evaluate the effects of spatial resolution degradation by precipitation and inhomogeneous beam filling when comparing to other satellite-based sensors. Our X-SAR analysis of precipitation effects has been carried out using both a TerraSAR-X (TSX) case study of Hurricane “Gustav” in 2008 over Mississippi (USA) and a COSMO-SkyMed (CSK) X-SAR case study of orographic rainfall over Central Italy in 2009. For the TSX case study the near-surface rain rate has been retrieved from the normalized radar cross section by means of a modified regression empirical algorithm (MREA). A relatively simple method to account for the geometric effect of X-SAR observation on estimated rainfall rate and firstorder volumetric effects has been developed and applied. The TSX-retrieved rain fields have been compared to those estimated from the Next Generation Weather Radar (NEXRAD) in Mobile (AL, USA). The rainfall detection capability of X-SAR has been tested on the CSK case study using the Correspondence to: F. S. Marzano ([email protected]) repeat-pass coherence response and qualitatively comparing its signature with ground-based Mt. Midia C-band radar in central Italy. A numerical simulator to represent the effect of the spatial resolution and the antenna pattern of TRMMsatellite Precipitation Radar (PR) and Microwave Imager (TMI), using high-resolution TSX-retrieved rain images, has been also set up in order to evaluate the rainfall beam filling phenomenon. As expected, the spatial average can modify the statistics of the high-resolution precipitation fields, strongly reducing its dynamics in a way non-linearly dependent on the rain rate local average value