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Estimating long-term modifications of the sea surface temperature (SST) is crucial for evaluating the current state of the oceans and to correctly assess the impact of climate change at regional scales. In this work, we analyze SST variations within the Mediterranean Sea and the adjacent Northeastern Atlantic box (west of the Strait of Gibraltar) over the last 37 years, by using a satellite-based dataset from the Copernicus Marine Environment Monitoring Service (CMEMS). We found a mean warming trend of 0.041 ± 0.006 ∘ C/year over the whole Mediterranean Sea from 1982 to 2018. The trend has an uneven spatial pattern, with values increasing from 0.036 ± 0.006 ∘ C/year in the western basin to 0.048 ± 0.006 ∘ C/year in the Levantine–Aegean basin. The Northeastern Atlantic box and the Mediterranean show a similar trend until the late 1990s. Afterwards, the Mediterranean SST continues to increase, whereas the Northeastern Atlantic box shows no significant trend, until ~2015. The observed change in the Mediterranean Sea affects not only the mean trend but also the amplitude of the Mediterranean seasonal signal, with consistent relative increase and decrease of summer and winter mean values, respectively, over the period considered. The analysis of SST changes occurred during the “satellite era” is further complemented by reconstructions also based on direct in situ SST measurements, i.e., the Extended Reconstructed SST (ERSST) and the Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST), which go back to the 19th century. The analysis of these longer time series, covering the last 165 years, indicates that the increasing Mediterranean trend, observed during the CMEMS operational period, is consistent with the Atlantic Multidecadal Oscillation (AMO), as it closely follows the last increasing period of AMO. This coincidence occurs at least until 2007, when the apparent onset of the decreasing phase of AMO is not seen in the Mediterranean SST evolution.

A joint effort between the Copernicus Climate Change Service (C3S) and the Group for High Resolution Sea Surface Temperature (GHRSST) has been dedicated to an intercomparison study of eight global gap-free sea surface temperature (SST) products to assess their accurate representation of the SST relevant to climate analysis. In general, all SST products show consistent spatial patterns and temporal variability during the overlapping time period (2003–18). The main differences between each product are located in the western boundary current and Antarctic Circumpolar Current regions. Linear trends display consistent SST spatial patterns among all products and exhibit a strong warming trend from 2012 to 2018 with the Pacific Ocean basin as the main contributor. The SST discrepancy between all SST products is very small compared to the significant warming trend. Spatial power spectral density shows that the interpolation into 1° spatial resolution has negligible impacts on our results. The global mean SST time series reveals larger differences among all SST products during the early period of the satellite era (1982–2002) when there were fewer observations, indicating that the observation frequency is the main constraint of the SST climatology. The maturity matrix scores, which present the maturity of each product in terms of documentation, storage, and dissemination but not the scientific quality, demonstrate that ESA-CCI and OSTIA SST are well documented for users’ convenience. Improvements could be made for MGDSST and BoM SST. Finally, we have recommended that these SST products can be used for fundamental climate applications and climate studies (e.g., El Niño).

Marine heatwaves (MHWs) represent anomalously warm temperature conditions of seawater that may affect marine life and ocean biogeochemistry. Under such conditions, phytoplankton communities may modify their structure and functions, and their resilience is not assured. This study characterizes the impact of MHWs on the phytoplankton spring bloom in the North‐Western Mediterranean Sea. Here, we synergistically combine autonomous observations from BioGeoChemical‐Argo floats, satellite‐based and marine ecosystem model data, and show that MHW events occurring during winter drastically inhibit phytoplankton carbon biomass in spring by up to 70%. Such reduction is related to the enhanced stratification of the water column under MHWs which hinders the renewal of nutrients from deep‐ocean reservoirs, thus preventing surface phytoplankton from blooming. This process negatively impacts particulate organic carbon stocks within the mixed layer, while severe events cause an earlier shift of phytoplankton phenology that provokes changes in zooplankton biomass distribution. Plain Language Summary Marine heatwaves (MHWs) are described as an abnormal and prolonged increase of ocean temperatures. These events may occur in all the oceans, and are becoming more frequent than before. Such increase in water temperature might not be tolerated by organisms, which must need to adapt themselves to the new environmental conditions. Consequently, marine ecosystem health is endangered. Here, we analyze the effect that MHWs have on the growth of small algae called phytoplankton. Phytoplankton are vital microscopic organisms for ecosystems that use sunlight to produce organic carbon through photosynthesis. At middle and high latitudes, phytoplankton massively grows (i.e., blooms) once a year at the sea surface, and introduces a major carbon flux into the ecosystem that sustains larger animals. Through combining observations acquired by different platforms (satellites, autonomous in situ BioGeoChemical‐Argo robots, and ecosystem models), we comprehensively study how MHWs affect phytoplankton carbon production during spring blooms and trophic chains at mid‐latitudes. Results show that MHW events occurring in winter lead to a large decrease in phytoplankton carbon biomass (up to 70%) in spring. Winter MHW events, driven by local atmospheric conditions, intensify water column stratification thus hindering the deep‐ocean nutrient transport to the surface, which is essential for phytoplankton to bloom. Key Points Marine heatwaves (MHWs) intensify water stratification leading to reduction in nutrient supply which inhibits surface phytoplankton spring bloom MHWs lead to a phytoplankton community shift toward smaller cells, while increasing the transparency of surface waters MHWs decrease carbon stocks within the mixed layer, while intense ones shift phytoplankton phenology and affect zooplankton

Since May 2022, the Mediterranean Sea has been experiencing an exceptionally long marine heatwave event. Warm anomalies, mainly occurring in the Western basin, have persisted until boreal spring 2023, making this event the longest Mediterranean marine heat wave of the last four decades. In this work, the 2022/2023 anomaly is characterized, using in-situ and satellite measurements, together with state of the art reanalysis products. The role of atmospheric forcing is also investigated; the onset and growth of sea surface temperature anomalies is found to be related to the prevalence of anticyclonic conditions in the atmosphere, which have also caused severe droughts in the Mediterranean region over the same period. Analysis of in-situ observations from the Lampedusa station and of ocean reanalyzes reveals that wind-driven vertical mixing led to the penetration of the warm anomalies below the sea surface, where they have persisted for several months, particularly in the central part of the basin. The evolution of the 2022/23 event is compared with the severe 2003 event, to put recent conditions in the context of climate change.

Anomalous warming of the upper ocean is increasingly being observed in the Mediterranean Sea. Extreme events, known as marine heatwaves (MHWs), can have a profound impact on marine ecosystems, and their correct detection and characterization are crucial to define future impact scenarios. Here, we analyze MHWs observed over the last 41 years (1982–2022) in the Mediterranean sea surface temperatures (SSTs). We show that the intensification in frequency, intensity, and duration of Mediterranean MHWs in recent years is mainly due to a shift in SST mean that occurred in the last two decades and largely reduced when analyzing detrended SST data. Detrending thus allows the use of a fixed climatology without overestimating MHW properties over time and distinguishes long-term warming (i.e., trend) from transient and abrupt SST changes. Analogous results are also found over a shorter temporal period, by analyzing 13 years (2007–2020) of in situ data collected at different depths (5 to 40 m) at Columbretes Islands. Additionally, the in situ analysis reveals that atmospheric summer heatwaves could affect a layer of 10 m in depth. Lastly, a catalogue of the major Mediterranean MHWs that have occurred since 1982 is presented. This catalogue evidences an exceptionally long-lasting and intense MHW, starting in May 2022 and persisting, at least, until the end of the year, resulting in the event with the highest cumulative intensity just after the well-known 2003 MHW event.

We present a methodology to detect oil spills using MODIS near-infrared sun glittered radiance imagery. The methodology was developed by using a set of seven MODIS images (training dataset) and validated using four other images (validation dataset). The method is based on the ratio image R = L'GN/LGN, where L'GN is the MODIS-retrieved normalized sun glint radiance image and LGN the same quantity, but obtained from the Cox and Munk isotropic (independent of wind direction) sun glint model. We show that in the R image, while clean water pixel values tend to one, oil spills stand out as anomalies. Moreover, we provide a criterion to distinguish between positive and negative oil-water contrast. A pixel in an R image is classified as a potential oil spill or water via a variable threshold Rs as a function of L'GN, where the threshold values are obtained from the slicks of our training dataset. Two different fitting curves are provided for Rs, according to the contrast sign. The selection of the correct fitting curve is based on the contrast type, resulting from the criterion above. Results indicate that the thresholding is able to isolate the spills and that the spills of the validation dataset are successfully detected. Spurious look-alike features, such as clouds, and other non-spill features, e.g., large areas at the glint region border, are also detected as oil spills and must be eliminated. We believe that our methodology represents a novel and promising, though preliminary, approach towards automatic oil spill detection in optical satellite images.

This study evaluates the potential impact of the Copernicus Imaging Microwave Radiometer (CIMR) mission on the sea surface temperature (SST) products of the Mediterranean Sea. Currently, infrared (IR) radiometers provide accurate, high-resolution SST measurements, but they are limited by their inability to see through clouds. Passive microwave (PMW) radiometers, on the other hand, offer monitoring capabilities in almost all weather conditions but typically at lower spatial resolutions. The CIMR mission represents a notable advance in microwave remote sensing of SSTs, as it will ensure a ≤15 km spatial resolution in the recovered SST field. Using an observing system simulation experiment (OSSE), this study evaluates the effect of inserting synthetic CIMR observations into the Copernicus Mediterranean SST analysis system, which is based on an optimal interpolation (OI) algorithm. The OSSE was conducted using data for the year 2017, including daily SST and salinity outputs from a Mediterranean Sea model, hourly precipitation rates from the IMERG, and wind and cloud cover data from ERA5. The results suggest that the improved spatial resolution and accuracy of the CIMR could potentially improve SST retrievals in the Mediterranean Sea, offering better insights for climate and environmental monitoring in semi-closed basins. Including CIMR data in the OI algorithm reduced the mean error and root mean square error (RMSE) of the SST analysis, especially under conditions of low IR coverage. The greatest improvements were found to occur in July, corresponding to coastal upwelling and Atlantic inflow into the Alboran Sea. Improvements ranged from 16% to 29%, with an overall improvement of 26% for the full year of 2017. In conclusion, this preliminary study indicates that Copernicus Mediterranean Sea HR SST products could benefit from the inclusion of the CIMR in the current IR sensor constellation.

Background Pancreatic ductal adenocarcinoma (PDAC) poses a significant challenge due to late-stage diagnoses resulting from nonspecific early symptoms and the absence of early diagnostic biomarkers. MicroRNAs (miRNAs) play a crucial role in regulating diverse biological processes, and their abnormal expression is observed in various diseases, including cancer. Cancer stem cells (CSCs) are thought to act as a driving force in PDAC spread and recurrence. In pursuing the goal of unravelling the complexities of PDAC and its underlying molecular mechanisms, our study aimed to identify PDAC-associated miRNAs and relate them to disease progression, focusing on their involvement in various PDAC stages in patients and in reliable in vitro models, including pancreatic CSC (PaCSC) models. Methods The miRNA profiling datasets of serum and solid biopsies of PDAC patients deposited in GEO DataSets were analyzed by REML-based meta-analysis. The panel was then investigated by Real Time PCR in serum and solid biopsies of 37 PDAC patients enrolled in the study, as well as on BxPC-3 and AsPC-1 PDAC cell lines. We extended our focus towards a possible role of PDAC-associated miRNAs in the CSC phenotype, by inducing CSC-enriched pancreatospheres from BxPC-3 and AsPC-1 PDAC cell lines and performed differential miRNA expression analysis between PaCSCs and monolayer-grown PDAC cell lines. Results Meta-analysis showed differentially expressed miRNAs in blood samples and cancerous tissues of PDAC patients, allowing the identification of a panel of 9 PDAC-associated miRNAs. The results emerging from our patients fully confirmed the meta-analysis for the majority of miRNAs under investigation. In vitro tasks confirmed the aberrant expression of the panel of PDAC-associated miRNAs, with a dramatic dysregulation in PaCSC models. Notably, PaCSCs have shown significant overexpression of miR-4486, miR-216a-5p, and miR-216b-5p compared to PDAC cell lines, suggesting the recruitment of such miRNAs in stemness-related molecular mechanisms. Globally, our results showed a dual behaviour of miR-216a-5p and miR-216b-5p in PDAC while miR-4486, miR-361-3p, miR-125a-5p, miR-320d expression changes during the disease suggest they could promote PDAC initiation and progression. Conclusions This study contributed to an enhanced comprehension of the role of miRNAs in the development and progression of PDAC, shedding new light on the miRNA landscape in PDAC and its intricate interplay with CSCs, and providing specific insights useful in the development of miRNA-based diagnostic biomarkers and therapeutic targets.

Background: Trace elements and heavy metals can provide valuable forensic information for individual identification, lifestyle reconstruction, and association with the scene or time of death and may also assist in linking objects to criminal activities. However, the lack of standardized guidelines and post-mortem reference values represents a significant limitation in forensic investigations. Methods: This review was conducted in accordance with the PRISMA statement. We performed a comprehensive literature study over the last ten years focusing on the analysis of trace elements and heavy metals in post-mortem tissues. Results: The search results from the databases yielded 247 records. The screening, according to PRISMA criteria, allowed us to select and include 19 articles. The results showed the need for standardized guidelines and reference values. Although post-mortem trace element analysis shows high potential for forensic applications, substantial methodological heterogeneity persists. Some studies have proposed preliminary reference values for cadmium (Cd) in kidneys and mercury (Hg) in hair but validated post-mortem reference ranges remain largely unavailable. Conclusions: The current literature demonstrates the forensic potential of trace element and heavy metals analysis including Cd, Hg, lead (Pb), Manganese (Mn), Aluminum (Al), Copper (Cu), Zinc (Zn), Iron (Fe), Thallium (Tl), Polonium (210Po) but also underlines the urgent need for standardized protocols and validated post-mortem reference values to improve interpretability and reliability in forensic contexts.

Background: Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive lethal neoplasm, and it has an average 5-year survival rate of less than 10%. Although the factors that influence PDAC development remain unclear, exposure to toxic metals or the imbalance in essential elements may have a role in PDAC-associated metabolic pathways. Methods: This study determined the concentrations of Cd, Cr, Cu, Fe, Mn, Ni, Pb, Se and Zn in whole blood, cancer and non-cancer tissues of patients affected by PDAC, and compared them with levels in healthy controls using inductively coupled plasma mass spectrometry. Results: Results of the whole blood showed significantly higher levels of Cr, Cu and Cu/Zn ratio in PDAC patients compared to the controls. In addition, the concentrations of Cu, Se, Fe and Zn significantly increased in cancer tissue compared to the healthy counterparts. Conclusions: This study revealed evidence of altered metal levels in the blood and pancreatic tissues of PDAC patients with respect to healthy controls. These changes may contribute to multiple mechanisms involved in metal-induced carcinogenesis, including oxidative stress, DNA damage, genetic alteration, decreased antioxidant barriers and inflammatory responses. Thus, the analysis of metals can be used in the diagnosis and monitoring of PDAC neoplasms.