The Treatment of Peritoneal Carcinomatosis in Advanced Gastric Cancer: State of the Art

Gastric cancer (GC) is the fourth most common cancer and the second leading cause of cancer death in the world; 53–60% of patients show disease progression and die of peritoneal carcinomatosis (PC). PC of gastric origin has an extremely inauspicious prognosis with a median survival estimate at 1–3 months. Different studies presented contrasting data about survival rates; however, all agreed with the necessity of a complete cytoreduction to improve survival. Hyperthermic intraperitoneal chemotherapy (HIPEC) has an adjuvant role in preventing peritoneal recurrences. A multidisciplinary approach should be empowered: the association of neoadjuvant intraperitoneal and systemic chemotherapy (NIPS), cytoreductive surgery (CRS), HIPEC, and early postoperative intraperitoneal chemotherapy (EPIC) could increase the rate of completeness of cytoreduction (CC) and consequently survival rates, especially in patients with Peritoneal Cancer Index (PCI) ≤6. Neoadjuvant chemotherapy may improve survival also in PC from GC and adjuvant chemotherapy could prevent recurrence. In the last decade an interesting new drug, called Catumaxomab, has been developed in Germany. Two studies showed that this drug seems to improve progression-free survival in patients with GC; however, final results for both studies have still to be published

How can numerical weather prediction support the ATM activity during severe weather events?

Climate change is intensifying the water cycle, bringing more intense precipitation and flooding in some regions, as well as longer and stronger droughts in others. The number of short-term and highly localized phenomena, such as thunderstorms, hailstorms, wind gusts or tornadoes, is expected to grow in the coming years, with important repercussions in air traffic management activities (ATM). One of the challenges for meteorologists is to improve the location and timing of such events that develop on small spatial and temporal scales. In this regard, the H2020 Satellite-borne and IN-situ Observations to Predict The Initiation of Convection for ATM (SINOPTICA) project aims to demonstrate that numerical weather forecasts with high spatial and temporal resolution, benefiting from the assimilation of radar data, in situ weather stations, GNSS and lightning data, could improve the prediction of severe weather events for the benefit of air traffic control (ATC) and air traffic management (ATM). As part of the project, three severe weather events were identified on the Italian territory which resulted in the closure of the airport with heavy delays on arrivals and departures as well as numerous diversions. The data of the numerical simulations, carried out with the Weather Research and Forecasting (WRF) model and the 3D-VAR assimilation technique, will be integrated into air traffic control and management systems (Arrival Manager) in order to generate and optimize 4D trajectories avoiding areas affected by adverse phenomena with the objectives of increasing flight safety and predictability and reducing controllers' workload. In addition to the numerical simulations, a nowcasting technique called PHAse- diffusion model for STochastic nowcasting (PhaSt) has been investigated to further improve ATC supporting systems during severe weather. This work presents the results of the WRF and PhaSt experiments, for the Milan Malpensa case study of 11 May 2019, demonstrating that it is possible to improve the prediction of such events in line with expectations and ATM needs

Data assimilation and nowcasting for air traffic management purposes: First results from the SINOPTICA H2020 project

One of the main challenges for meteorologists is to improve the prediction of severe weather events that develop on small spatial and temporal scales and that have important repercussions in air traffic management activities (ATM). In this regard, the H2020 project "Satellite-borne and IN-situ Observations to Predict The Initiation of Convection for ATM" (SINOPTICA) aims to demonstrate that numerical weather prediction with high spatial and temporal resolution, benefiting from the assimilation of non-conventional observations, GNSS, weather radar, and lightning data, could improve the prediction of severe weather events for the benefit of air traffic control (ATC) and air traffic management (ATM) in the vicinity of airports. In addition to the numerical simulations, a nowcasting technique called PHAse- diffusion model for STochastic nowcasting (PHAST) has been developed to predict the highly localized convective events triggering in the vicinity of airports and to further support the ATM activities. As part of the project, three severe weather events were identified on the Italian territory which caused the closure of some airport, huge delays on arrivals and departures and numerous diversions. The data of the numerical simulations, carried out with the Weather Research and Forecasting (WRF) and nowcasting technique, performed with PHAST, were integrated into the Arrival Manager 4D-CARMA (4-Dimensional Cooperative Arrival Manager), an adaptive air traffic sequencing and management system for controllers. As part of the project, 4D-CARMA was extended to now generate and optimize 4D trajectories avoiding areas affected by adverse phenomena with the objectives of increasing flight safety and predictability and, under certain circumstances, reducing controllers' and pilots' workload. This work presents the first outcomes of the SINOPTICA project, demonstrating that it is possible to improve the prediction of the above-mentioned events in line with expectations and ATM needs

Innovative integration of severe weather forecasts into an extended arrival manager

The impact of extreme weather on air traffic is a global challenge that results in varying delays to flights depending on climate zone, traffic, and available infrastructure. Due to an observed increase in severe weather events, this impact on air traffic is expected to grow in intensity in the coming years, making it increasingly important to organize airspaces safely and efficiently even under severe weather conditions. In the EU H2020 project "Satellite-borne and INsitu Observations to Predict The Initiation of Convection for ATM" (SINOPTICA), three new meteorological forecasting techniques - PhaSt, RaNDeVIL and WRF-RUC - were developed and tested to better nowcast severe weather events affecting tactical air traffic management operations. The nowcasts are used to organize the approaching traffic by an Extended Arrival Manager (E-AMAN) generating 4D trajectories to efficient detour around severe weather areas in the vicinity of airports. For this purpose, short-range severe weather forecasts with very high spatial resolution were elaborated starting from radar images, through an application of nowcasting techniques combined with Numerical Weather Prediction (NWP) models and data assimilation. This compact nowcast information were integrated into an E-AMAN to support Air Traffic Controllers (ATCO) when sequencing and guiding approaching aircraft even in adverse weather situations. The combination of fast and reliable weather nowcasts with a guidance-support system enables on the one hand the 4D trajectory calculation for diversion coordination around severe weather areas, and on the other hand the visualization of dynamic weather information on the radar displays of controllers. A previous evaluation of the concept by ATCOs showed that the presentation of meteorological information must be compact and concise to not interfere with relevant traffic information on the display. Two severe weather events impacting different Italian airports were selected for validation of the E-AMAN. Combining the Vertical Integrated Liquid and the Echo Top Maximum products, hazard thresholds were defined for domains around the airports. The Weather Research and Forecasting model has been used to simulate the formation and development of the aforementioned convective events. In order to produce a more accurate very short-term weather forecast (nowcasting), remote sensing data (e.g. radar, GNSS) and conventional observations were assimilated by using a cycling three-dimensional variational technique. The validation of E-AMAN system in SINOPTICA project focused on the aspects of feasibility and efficiency and contained two phases. In the first phase, recorded weather data and realistic air traffic were combined and run in a traffic simulation, where the E-AMAN has to organize and to plan the aircraft depending on the measured and forecasted weather. For the evaluation, flight time, track miles and fuel consumption estimation KPIs were applied. In the second phase, various E-AMAN simulation runs were demonstrated to an international controller team for evaluation. The predictions of the three considered forecast models were surprisingly heterogeneous for the same period and area, so that a comparative statement regarding the support quality of the considered E-AMAN within the project is only possible to a limited extent. However, it is indicated that an E-AMAN is very helpful if there is a possibility for large-scale fly-around planning. For this purpose, longer-term and highly precise forecasts that are precisely tailored to Air Traffic Control requirements are essential. The forecast model must correspond to the safety perception of the air traffic controllers and pilots on site, so that they can manage the traffic as efficiently and safely as possible. However, with the help of sophisticated nowcast models and the E-AMAN, SINOPTICA was able to show that it is possible to support controllers and pilots in challenging meteorological situations to guide air traffic safely and efficiently, and thus to make planning more reliable and predictable for all stakeholders on ground and in the air. This contribution presents an overview of the final results of the SINOPTICA project

Characterization of ADSC and ADSCK cell cultures.

<p>(A) Growth curve of two representative ADSC and ADSCK primary cultures. Values were expressed as cumulative population doublings calculated with the formula reported by Avanzini et al. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0112746#pone.0112746-Avanzini1" target="_blank">[26]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0112746#pone.0112746-Kotaja1" target="_blank">[44]</a>. (B) Cell viability after freezing and thawing evaluated by trypan blue dye exclusion assay comparing the number of viable cells after thawing to the number of cells previously frozen. Data are expressed as mean±SEM (n = 9 per group; three independent experiments for each cell culture; *P<0.05 vs ADSCs). (C) FACs analysis performed at passage 3 on ADSC (black bar) and on ADSCK (grey bar) to evaluate immunophenotypically mesenchymal markers. Data are expressed as mean±SD (n = 3 per group).</p

Biochemical behaviour of AR in ADSCs and ADSCKs.

<p>(A) High resolution fluorescence microscopy analysis (63X magnification) performed on ADSCs and ADSCKs in absence (–T) or in presence (+T) of 10 nM of testosterone for 48 hours in basal condition or after treatment with 10 µM of MG132 for 24 hours. Nuclei were stained with DAPI. Scale bar 10 µm. (B) High resolution fluorescence microscopy analysis (63X magnification) performed on ADSCKs in the presence (+T) of 10 nM of testosterone for 48 hours after treatment with 10 µM of MG132 for 24 hours. Fluorescence microscopy localization of AR (green) and Hsp70 (red). Nuclei were stained with DAPI. (C) High resolution fluorescence microscopy analysis (63X magnification) performed on ADSCKs in presence (+T) of 10 nM of testosterone for 48 hours after treatment with 10 µM of MG132 for 24 hours. Fluorescence microscopy localization of AR (green) and ubiquitin (red). Nuclei were stained with DAPI. Panel B and C represent only the nuclear area of the cells where the aggregates were observed. The arrows indicate the ARpolyQ inclusions co-stained with Hsp70 and ubiquitin, respectively.</p

Characterization of AR expression in ADSCs and ADSCKs.

<p>(A) AR mRNA levels in ADSCs and ADSCKs were determined by real time quantitative PCR. SHSY-5Y cells were used as negative control. (n = 3 per group; *P<0.05, **P<0.01 <i>vs</i> negative control; °P<0.05 <i>vs</i> ADSCs). (B) Western Blot on ADSCs and ADSCKs in absence (–T) or in presence (+T) of 10 nM of testosterone for 48 hours. Alpha-tubulin was used to normalize for protein loading.</p

Multipotency characterization of ADSCs and ADSCKs.

<p>(A–E) Representative images of normal morphology in absence of differentiation stimuli. (B–F) Adipogenic differentiation was confirmed by Oil Red O Staining. (C–G) Osteogenic differentiation was displayed by Alizarin Red staining. (D–H) Chondrogenic differentiation was visualized by Aggrecan immunofluorescence (red); nuclei were stained with DAPI (blue). (20X magnification).</p