436 research outputs found
A Neural network based observation operator for coupled ocean acoustic variational data assimilation
Variational data assimilation requires implementing the tangent-linear and adjoint (TA/AD) version of any operator. This intrinsically hampers the use of complicated observations.Here, we assess a new data-driven approach to assimilate acoustic underwater propagation measurements [transmission loss (TL)] into a regional ocean forecasting system. TL measurements depend on the underlying sound speed fields, mostly temperature, and their inversion would require heavy coding of the TA/AD of an acoustic underwater propagation model. In this study, the nonlinear version of the acoustic model is applied to an ensemble of perturbed oceanic conditions. TL outputs are used to formulate both a statistical linear operator based on canonical correlation analysis (CCA), and a neural network based (NN) operator. For the latter, two linearization strategies are compared, the best-performing one relying on reverse-mode automatic differentiation. The new observation operator is applied in data assimilation experiments over the Ligurian Sea (Mediterranean Sea), using the observing system simulation experiments (OSSE) methodology to assess the impact of TL observations onto oceanic fields. TL observations are extracted from a nature run with perturbed surface boundary conditions and stochastic ocean physics. Sensitivity analyses indicate that theNNreconstruction of TL is significantly better than CCA. BothCCAandNNare able to improve the upper-ocean skill scores in forecast experiments, with NN outperforming CCA on the average. The use of the NN observation operator is computationally affordable, and its general formulation appears promising for the adjoint-free assimilation of any remote sensing observing network. SIGNIFICANCE STATEMENT: Deep learning algorithms are now widely spread in a diverse range of fields to help with solving automatic classification and regression problems. Here, we present and assess a strategy aimed at introducing an observation operator based on neural networks in data assimilation. Linearization of such an operator, required by variational schemes, is also discussed and implemented. The methodology is applied to the coupled oceanic acoustic data assimilation problem, and provides promising results. Our approach may be extended in the future to assimilate any remotely sensed type of observations
Assessing the Impact of Different Ocean Analysis Schemes on Oceanic and Underwater Acoustic Predictions
Assimilating oceanic observations into prediction systems is an advantageous approach for real-time ocean environment characterization. However, its benefits to underwater acoustic predictions are not trivial due to the nonlinearity and sensitivity of underwater acoustic propagation to small-scale oceanic features. In order to assess the potential of oceanic data assimilation, integrated ocean-acoustic Observing System Simulation Experiments are conducted. Synthetic altimetry and in situ data were assimilated through a variational oceanographic data assimilation system. The predicted sound speed fields are then ingested in a range-dependent acoustic model for transmission loss (TL) predictions. The predicted TLs are analyzed for the purpose of (i) evaluating the contributions of different sources to the uncertainties of oceanic and acoustic forecasts and (ii) comparing the impact of different oceanic analysis schemes on the TL prediction accuracy. Using ensemble member clustering techniques, the contributions of boundary conditions, ocean parameterizations, and geoacoustic characterization to acoustic prediction uncertainties are addressed. Subsequently, the impact of three-dimensional variational (3DVAR), 4DVAR, and hybrid ensemble-3DVAR data assimilation on acoustic TL prediction at two signal frequencies (75 and 2,500 Hz) and different ranges (30 and 60 km) are compared. 3DVAR significantly improves the predicted TL accuracy compared to the control run. Promisingly, 4DVAR and hybrid data assimilation further improve the TL forecasts, the hybrid scheme achieving the highest skill scores for all cases, while being the most computationally intensive scheme. The optimal scheme choice thus depends on requirements on the accuracy and computational constraints. These findings foster developments of coupled data assimilation for operational underwater acoustic propagation
Internal tides in the central Mediterranean Sea: observational evidence and numerical studies
Internal tides are studied in the central Mediterranean Sea using observational data and numerical experiments. Both numerical results and observations indicate that the baroclinic variability in this area is dominated by the K1 diurnal tide. In agreement with previous studies, the diurnal internal tides have the characteristics of Kelvin-like bottom trapped waves. They are mainly generated by the interaction of the induced barotropic tidal flow with the steep bathymetric gradient connecting the Ionian Sea with the shallow Sicily Channel. The bathymetric gradient appears to be the major forcing shaping the propagation paths of the internal tides. The most energetic internal tides follow the steep bathymetric gradient, propagating southward and tending to dissipate rapidly. Other waves cross the continental shelf south of Malta and then split with one branch moving toward the southern coast of Sicily and the other moving toward the west. Internal tides propagate with a variable phase velocity of about 1 ms(-1) and a wavelength of the order of 100 km. During their journey, the internal waves appear to be subject to local processes that can modify their characteristics. The induced vertical shear strongly dominates the vertical turbulence and generates vertical mixing that alters the properties of the water masses traversing the area. Barotropic and internal tides remove heat from the ocean surface, increasing atmospheric heating, and redistributing energy through increased lateral heat fluxes. Lateral heat fluxes are significantly greater in the presence of internal tides due to the simultaneous increase in volume fluxes and water temperatures
In vivo effect of an immunostimulating bacterial lysate on human B lymphocytes.
The aim of the present study is to investigate in humans the mechanism by which the oral vaccine Polyvalent Mechanical Bacterial Lysate (PMBL) can rapidly mobilize specific immune response and evaluate the efficacy of its immunostimulating activity in preventing recurrent infections of the upper respiratory tract (URTIs) in a group of patients with a medical history of URTI recurrence. Patients received, by sublingual route, PBML, an immunostimulating lysate obtained by mechanical lysis of the most common bacteria responsible for upper respiratory tract infections. The treatment was administered for 10 consecutive days/month for 3 consecutive months. After the end of the treatment period the patients were followed up for an additional 3 months. The frequency of IgM memory B cells and the expression of the activation marker CD25 in peripheral blood lymphocytes were measured using the flow cytometric method before the start and at days 30 and 90 of the treatment cycle. To correlate clinical results to immunological parameters, the patients were monitored at different time-points during the treatment and at the end of follow-up period. The results showed that PMBL exerts a therapeutic and preventing effect in acute and recurrent infections of the upper respiratory tract and that this effect correlated with the activation and enhancement of both IgM memory B lymphocytes (CD24+/CD27+ cells) and IL2 receptor-expressing lymphocytes (CD25+ cells) involved either in humoral or cellular immunity
Energy metabolism and ketogenic diets: What about the skeletal health? a narrative review and a prospective vision for planning clinical trials on this issue
The existence of a common mesenchymal cell progenitor shared by bone, skeletal muscle, and adipocytes cell progenitors, makes the role of the skeleton in energy metabolism no longer surprising. Thus, bone fragility could also be seen as a consequence of a “poor” quality in nutrition. Ketogenic diet was originally proven to be effective in epilepsy, and long-term follow-up studies on epileptic children undergoing a ketogenic diet reported an increased incidence of bone fractures and decreased bone mineral density. However, the causes of such negative impacts on bone health have to be better defined. In these subjects, the concomitant use of antiepileptic drugs and the reduced mobilization may partly explain the negative effects on bone health, but little is known about the effects of diet itself, and/or generic alterations in vitamin D and/or impaired growth factor production. Despite these remarks, clinical studies were adequately designed to investigate bone health are scarce and bone health related aspects are not included among the various metabolic pathologies positively influenced by ketogenic diets. Here, we provide not only a narrative review on this issue, but also practical advice to design and implement clinical studies on ketogenic nutritional regimens and bone health outcomes. Perspectives on ketogenic regimens, microbiota, microRNAs, and bone health are also included
Patterns of genomic instability in gastric cancer: clinical implications and perspectives
In gastric cancer (GC) the loss of genomic stability represents a key molecular step that occurs early in the carcinogenesis process and creates a permissive environment for the accumulation of genetic and epigenetic alterations in tumor suppressor genes and oncogenes. It is widely accepted that GC can follow at least two major genomic instability pathways, microsatellite instability (MSI) and chromosome instability (CIN). MSI is responsible for a well-defined subset of GCs. CIN represents a more common pathway comprising heterogeneous subsets of GC. In addition to MSI and CIN, the CpG islands methylator phenotype (CIMP) plays an important role in gastric carcinogenesis. CIMP may lead to the transcriptional silencing of various genes in gastric carcinogenesis. Intriguingly, more recently in addition to CpG island hypermethylation, a global DNA demethylation, that precedes genomic damage, has been observed in GC. Thus, epigenetic alterations may play a relevant role in gastric carcinogenesis as alternative mechanisms. Evidence suggests that although MSI, CIN and CIMP phenotypes can be distinguished from one another, there might be some degree of overlap. This review describes our current knowledge of the instability pathways in gastric carcinogenesis and the potential clinical applications for different forms of genomic instability in G
Pathophysiology of Mild Hypercortisolism: From the Bench to the Bedside
Mild hypercortisolism is defined as biochemical evidence of abnormal cortisol secretion without the classical detectable manifestations of overt Cushing’s syndrome and, above all, lacking catabolic characteristics such as central muscle weakness, adipose tissue redistribution, skin fragility and unusual infections. Mild hypercortisolism is frequently discovered in patients with adrenal incidentalomas, with a prevalence ranging between 5 and 50%. This high variability is mainly due to the different criteria used for defining this condition. This subtle cortisol excess has also been described in patients with incidentally discovered pituitary tumors with an estimated prevalence of 5%. To date, the mechanisms responsible for the pathogenesis of mild hypercortisolism of pituitary origin are still not well clarified. At variance, recent advances have been made in understanding the genetic background of bilateral and unilateral adrenal adenomas causing mild hypercortisolism. Some recent data suggest that the clinical effects of glucocorticoid (GC) exposure on peripheral tissues are determined not only by the amount of the adrenal GC production but also by the peripheral GC metabolism and by the GC sensitivity. Indeed, in subjects with normal cortisol secretion, the combined estimate of cortisol secretion, cortisone-to-cortisol peripheral activation by the 11 beta-hydroxysteroid dehydrogenase enzyme and GC receptor sensitizing variants have been suggested to be associated with the presence of hypertension, diabetes and bone fragility, which are three well-known consequences of hypercortisolism. This review focuses on the pathophysiologic mechanism underlying both the different sources of mild hypercortisolism and their clinical consequences (bone fragility, arterial hypertension, subclinical atherosclerosis, cardiovascular remodeling, dyslipidemia, glucose metabolism impairment, visceral adiposity, infections, muscle damage, mood disorders and coagulation). © 2022 by the authors. Licensee MDPI, Basel, Switzerland
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