Hypovitaminosis D in an hospitalized old population of Western Friuli.

Objectives Hypovitaminosis D is very common in the elderly in Italy and generally in the world, contributing to bone fractures and muscle weakness. The aim of the study was to evaluate bone metabolism in an old population of patients hospitalized not for musculo-skeletal complaints. Methods The clinical records of 175 patients, 98 female and 77 male, aged >65 years, hospitalized in a Department of Internal Medicine (Sacile, Western Friuli) were retrospectively reviewed. Serum levels of calcium, phosphorous, alkaline phosphatase, parathyroid hormone (PTH) and 25-OH vitamin D were evaluated. Correlations between these parameters were investigate. Results Abnormalities of bone metabolism parameters were frequently founded, particularly hypocalcemia, increased PTH and reduced 25-OH vitamin D. Hypovitaminosis D were detected in 88% of patients, low levels in 30.28% and very low levels in 57.72%. Hypovitaminosis D was related to female sex, old age of patients and high levels of PTH. Conclusions Our data confirm that hypovitaminosis D is very common in elderly population. The study has been performed in an Italian Region where the supplementation of vitamin D in the elderly is not performed, suggesting that a awareness campaign of the doctors could be very useful to prevent bone metabolism abnormalities.Objectives: Hypovitaminosis D is very common in the elderly in Italy and generally in the world, contributing to bone fractures and muscle weakness. The aim of the study was to evaluate bone metabolism in an old population of patients hospitalized not for musculo-skeletal complaints. Methods: The clinical records of 175 patients, 98 female and 77 male, aged >65 years, hospitalized in a Department of Internal Medicine (Sacile, Western Friuli) were retrospectively reviewed. Serum levels of calcium, phosphorus, alkaline phosphatase, parathyroid hormone (PTH) and 25-OH vitamin D were evaluated. Correlations between these parameters were investigate. Results: Abnormalities of bone metabolism parameters were frequently founded, particularly hypocalcemia, increased PTH and reduced 25-OH vitamin D. Hypovitaminosis D were detected in 88% of patients, low levels in 30.28% and very low levels in 57.72%. Hypovitaminosis D was related to female sex, old age of patients and high levels of PTH. Conclusions: Our data confirm that hypovitaminosis D is very common in elderly population. The study has been performed in an Italian Region where the supplementation of vitamin D in the elderly is not performed, suggesting that a awareness campaign of the doctors could be very useful to prevent bone metabolism abnormalities

Toward coherent space-time mapping of seagrass cover from satellite data: An example of a Mediterranean lagoon

Seagrass meadows are a highly productive and economically important shallow coastal habitat. Their sensitivity to natural and anthropogenic disturbances, combined with their importance for local biodiversity, carbon stocks, and sediment dynamics, motivate a frequent monitoring of their distribution. However, generating time series of seagrass cover from field observations is costly, and mapping methods based on remote sensing require restrictive conditions on seabed visibility, limiting the frequency of observations. In this contribution, we examine the effect of accounting for environmental factors, such as the bathymetry and median grain size (D50) of the substrate as well as the coordinates of known seagrass patches, on the performance of a random forest (RF) classifier used to determine seagrass cover. Using 148 Landsat images of the Venice Lagoon (Italy) between 1999 and 2020, we trained an RF classifier with only spectral features from Landsat images and seagrass surveys from 2002 and 2017. Then, by adding the features above and applying a time-based correction to predictions, we created multiple RF models with different feature combinations. We tested the quality of the resulting seagrass cover predictions from each model against field surveys, showing that bathymetry, D50, and coordinates of known patches exert an influence that is dependent on the training Landsat image and seagrass survey chosen. In models trained on a survey from 2017, where using only spectral features causes predictions to overestimate seagrass surface area, no significant change in model performance was observed. Conversely, in models trained on a survey from 2002, the addition of the out-of-image features and particularly coordinates of known vegetated patches greatly improves the predictive capacity of the model, while still allowing the detection of seagrass beds absent in the reference field survey. Applying a time-based correction eliminates small temporal variations in predictions, improving predictions that performed well before correction. We conclude that accounting for the coordinates of known seagrass patches, together with applying a time-based correction, has the most potential to produce reliable frequent predictions of seagrass cover. While this case study alone is insufficient to explain how geographic location information influences the classification process, we suggest that it is linked to the inherent spatial auto-correlation of seagrass meadow distribution. In the interest of improving remote-sensing classification and particularly to develop our capacity to map vegetation across time, we identify this phenomenon as warranting further research

Remote sensing for optimal estimation of water temperature dynamics in shallow tidal environments

Given the increasing anthropogenic pressures on lagoons, estuaries, and lakes and considering the highly dynamic behavior of these systems, methods for the continuous and spatially distributed retrieval of water quality are becoming vital for their correct monitoring and management. Water temperature is certainly one of the most important drivers that influence the overall state of coastal systems. Traditionally, lake, estuarine, and lagoon temperatures are observed through point measurements carried out during field campaigns or through a network of sensors. However, sporadic measuring campaigns or probe networks rarely attain a density sufficient for process understanding, model development/validation, or integrated assessment. Here, we develop and apply an integrated approach for water temperature monitoring in a shallow lagoon which incorporates satellite and in-situ data into a mathematical model. Specifically, we use remote sensing information to constrain large-scale patterns of water temperature and high-frequency in situ observations to provide proper time constraints. A coupled hydrodynamic circulation-heat transport model is then used to propagate the state of the system forward in time between subsequent remote sensing observations. Exploiting the satellite data high spatial resolution and the in situ measurements high temporal resolution, the model may act a physical interpolator filling the gap intrinsically characterizing the two monitoring techniques

Lobular Carcinomas In Situ Display Intralesion Genetic Heterogeneity and Clonal Evolution in the Progression to Invasive Lobular Carcinoma

Purpose:; Lobular carcinoma; in situ; (LCIS) is a preinvasive lesion of the breast. We sought to define its genomic landscape, whether intralesion genetic heterogeneity is present in LCIS, and the clonal relatedness between LCIS and invasive breast cancers.; Experimental Design:; We reanalyzed whole-exome sequencing (WES) data and performed a targeted amplicon sequencing validation of mutations identified in 43 LCIS and 27 synchronous more clinically advanced lesions from 24 patients [9 ductal carcinomas; in situ; (DCIS), 13 invasive lobular carcinomas (ILC), and 5 invasive ductal carcinomas (IDC)]. Somatic genetic alterations, mutational signatures, clonal composition, and phylogenetic trees were defined using validated computational methods.; Results:; WES of 43 LCIS lesions revealed a genomic profile similar to that previously reported for ILCs, with; CDH1; mutations present in 81% of the lesions. Forty-two percent (18/43) of LCIS were found to be clonally related to synchronous DCIS and/or ILCs, with clonal evolutionary patterns indicative of clonal selection and/or parallel/branched progression. Intralesion genetic heterogeneity was higher among LCIS clonally related to DCIS/ILC than in those nonclonally related to DCIS/ILC. A shift from aging to APOBEC-related mutational processes was observed in the progression from LCIS to DCIS and/or ILC in a subset of cases.; Conclusions:; Our findings support the contention that LCIS has a repertoire of somatic genetic alterations similar to that of ILCs, and likely constitutes a nonobligate precursor of breast cancer. Intralesion genetic heterogeneity is observed in LCIS and should be considered in studies aiming to develop biomarkers of progression from LCIS to more advanced lesions

Dynamic response of marshes to perturbations in suspended sediment concentrations and rates of relative sea level rise

We have developed an analytical model of salt marsh evolution that captures the dynamic response of marshes to perturbations in suspended sediment concentrations, plant productivity, and the rate of relative sea level rise (RSLR). Sediment\u2010rich and highly productive marshes will approach a new equilibrium state in response to a step change in the rate of RSLR faster than sediment\u2010poor or less productive marshes. Microtidal marshes will respond more quickly to a step change in the rate of RSLR than mesotidal or macrotidal marshes. Marshes are more resilient to a decrease rather than to an increase in the rate of RSLR, and they are more resilient to a decrease rather than to an increase in sediment availability. Moreover, macrotidal marshes are more resilient to changes in the rate of RSLR than their microtidal counterparts. Finally, we find that a marsh\u2019s ability to record sea level fluctuations in its stratigraphy is fundamentally related to a timescale we call TFT, or filling timescale, which is equal to the tidal amplitude divided by the maximum possible accretion rate on the marsh (a function of plant productivity, sediment properties, and availability). Marshes with a short\u2010filling timescale (i.e., marshes with rapid sedimentation or small tidal amplitudes) are best suited to recording high\u2010frequency fluctuations in RSLR, but our model suggests it is unlikely that marshes will be able to record fluctuations occurring over timescales that are shorter than decadal

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Fluxes of water, sediments, and biogeochemical compounds in salt marshes

Tidal oscillations systematically flood salt marshes, transporting water, sediments, organic matter, and biogeochemical elements such as silica. Here we present a review of recent studies on these fluxes and their effects on both ecosystem functioning and morphological evolution of salt marshes. We reexamine a simplified model for the computation of water fluxes in salt marshes that captures the asymmetry in discharge between flood and ebb. We discuss the role of storm conditions on sediment fluxes both in tidal channels and on the marsh platform. We present recent methods and field instruments for the measurement of fluxes of organic matter. These methods will provide long-term data sets with fine temporal resolution that will help scientists to close the carbon budget in salt marshes. Finally, the main processes controlling fluxes of biogenic and dissolved silica in salt marshes are explained, with particular emphasis on the uptake by marsh macrophytes and diatoms