Body fluids and salt metabolism - Part II

There is a high frequency of diarrhea and vomiting in childhood. As a consequence the focus of the present review is to recognize the different body fluid compartments, to clinically assess the degree of dehydration, to know how the equilibrium between extracellular fluid and intracellular fluid is maintained, to calculate the effective blood osmolality and discuss both parenteral fluid maintenance and replacement

Impaired Mitochondrial ATP Production Downregulates Wnt Signaling via ER Stress Induction.

Wnt signaling affects fundamental development pathways and, if aberrantly activated, promotes the development of cancers. Wnt signaling is modulated by different factors, but whether the mitochondrial energetic state affects Wnt signaling is unknown. Here, we show that sublethal concentrations of different compounds that decrease mitochondrial ATP production specifically downregulate Wnt/β-catenin signaling in vitro in colon cancer cells and in vivo in zebrafish reporter lines. Accordingly, fibroblasts from a GRACILE syndrome patient and a generated zebrafish model lead to reduced Wnt signaling. We identify a mitochondria-Wnt signaling axis whereby a decrease in mitochondrial ATP reduces calcium uptake into the endoplasmic reticulum (ER), leading to endoplasmic reticulum stress and to impaired Wnt signaling. In turn, the recovery of the ATP level or the inhibition of endoplasmic reticulum stress restores Wnt activity. These findings reveal a mechanism that links mitochondrial energetic metabolism to the control of the Wnt pathway that may be beneficial against several pathologies

Differential diagnosis of neurodegenerative dementias with the explainable MRI based machine learning algorithm MUQUBIA

Biomarker-based differential diagnosis of the most common forms of dementia is becoming increasingly important. Machine learning (ML) may be able to address this challenge. The aim of this study was to develop and interpret a ML algorithm capable of differentiating Alzheimer's dementia, frontotemporal dementia, dementia with Lewy bodies and cognitively normal control subjects based on sociodemographic, clinical, and magnetic resonance imaging (MRI) variables. 506 subjects from 5 databases were included. MRI images were processed with FreeSurfer, LPA, and TRACULA to obtain brain volumes and thicknesses, white matter lesions and diffusion metrics. MRI metrics were used in conjunction with clinical and demographic data to perform differential diagnosis based on a Support Vector Machine model called MUQUBIA (Multimodal Quantification of Brain whIte matter biomArkers). Age, gender, Clinical Dementia Rating (CDR) Dementia Staging Instrument, and 19 imaging features formed the best set of discriminative features. The predictive model performed with an overall Area Under the Curve of 98%, high overall precision (88%), recall (88%), and F1 scores (88%) in the test group, and good Label Ranking Average Precision score (0.95) in a subset of neuropathologically assessed patients. The results of MUQUBIA were explained by the SHapley Additive exPlanations (SHAP) method. The MUQUBIA algorithm successfully classified various dementias with good performance using cost-effective clinical and MRI information, and with independent validation, has the potential to assist physicians in their clinical diagnosis

Seismic reservoir characterization in offshore Nile Delta. Part I: comparing different methods to derive a reliable rock-physics model.

Seismic-reflection data are used in reservoir characterization not only for obtaining a geometric description of the main subsurface structures but also for estimating properties like lithologies and fluid contents of the target levels of interest. To this end, a rock-physics model (RPM) is incorporated into a seismic inversion scheme, such as amplitude versus angle (AVA) inversion (Grana and Della Rossa, 2011) or full-waveform inversion (Bacharach, 2006), to directly derive petrophysical rock properties from pre-stack seismic data. The outcomes of petrophysical-seismic inversion provide reservoir property maps to reservoir engineers for field appraisal, selection of optimal well location, and production enhancement (Bosh et al. 2010). A rock-physics model is a generic transformation (fRPM) that can be expressed as follow: The RPM relates rock properties (which typically are porosity - φ -, water saturation - Sw - , shale content - Sh -) and the depth (z), that can be easily related to the pressure conditions, to elastic attributes (such as P-wave and S-wave velocities - Vp, Vs - and density). A rock-physics model can be based on theoretical equations (Avseth et al. 2005), or on empirical set of equations derived from available information (e.g. well-log or core measurements) for the specific case of interest (Mazzotti and Zamboni, 2003). In the last case, either a linear or a non-linear model can be considered (Eberhart-Phillips et al. 1989). In case of a non-linear approach many methods can be used to derive such rock-physics model. Among the non-linear approaches neural networks (Saggaf et al. 2003) and stochastic optimizations (Aleardi, 2015) have received great attention. Anyway, independently from the method used, there is no doubt that the quality and the reliability of available well-log data and/or core measurements play an essential role in defining a solid RPM. The aim of this work is derive a reliable RPM to be used in conjunction with an AVA inversion for the characterization of a clastic reservoir located in offshore Nile delta. To derive the RPM both theoretical and empirical approaches are employed. For what concerns the empirical approaches we use both a linear and two non-linear methods to define different rock-physics models. The linear model is obtained by applying a multilinear stepwise regression, whereas neural networks and genetic algorithms are used to derive non-linear transformations from petrophysical to elastic properties. The main difference among neural networks and genetic algorithms is that the former is a gradient-based method while the latter is a global, stochastic, optimization method. We start by introducing the different methods used to derive the theoretical and the empirical rock-physics models. Then, the RPMs resulting from theoretical and empirical approaches are analyzed in detail to define the benefits and the limits of each method. Moreover, in the empirical approaches we focus our attention on discussing the differences between linear and non-linear methods for the specific case under examination and on analyzing the drawbacks that characterize the neural network technique. The simplicity and the reliability of the empirical rock-physics model derived by applying multilinear stepwise regression and the optimal prediction capability of the theoretical rock-physics model enable us to consider these two RPMs in the petrophysical AVA inversion that is discussed in the companion paper titled “Seismic reservoir characterization in offshore Nile Delta. Part II: Probabilistic petrophysical-seismic inversion”

BAYESIAN PETROPHYSICAL-SEISMIC INVERSION TECHNIQUES FOR KEY RESERVOIR PARAMETER ESTIMATION: A CASE STUDY FROM THE OFFSHORE ABU QIR FIELD

Recent advances in seismic-constrained reservoir characterization combine statistical rock-physics and amplitude versus offset/angle (AVO/AVA) inversion in order to directly estimate petrophysical properties such as porosity, shaliness and water saturation from pre-stack seismic data. By exploiting the Bayesian inversion formalism, it is possible to propagate uncertainty from seismic to petrophysical properties, including the effect of noise on seismic data and the approximation of physical models. The results of such petrophysical-seismic inversion are spatial probability density distributions of rock and fluid properties that can be effectively integrated in the reservoir modeling workflows. This paper discusses two target-oriented Bayesian petrophysical-AVA inversion techniques: a two-stage approach and a single-stage approach, developed as part of a collaborative research project between Edison and the Earth Sciences Department of the University of Pisa. The two approaches are evaluated on the gas-bearing sands of the Pliocene interval in the Northern area of the offshore Abu Qir field where a 3D seismic survey was acquired using long-offset cables and well-control is available to validate the inversion results. The two-stage approach, is performed over the whole target-interval and is based on two cascade steps: first, seismic angle-gathers are inverted into acoustic and shear impedances using the convolutional model and a narrow-angle, time-continuous approximation of the Zoeppritz equations; then, a rock-physics model is used to transform the elastic parameters into petrophysical properties. Differently, the single-stage approach uses the rock-physics model to re-parameterize the exact Zoeppritz equations in terms of petrophysical variables; the derived equations are used to directly estimate the petrophysical property along the top-horizon of target interval by taking into account wide-angle seismic reflections. Independently from the inversion approach considered, the rock-physics model plays a crucial role in petrophysical-AVA inversion as it provides the link between elastic and petrophysical properties. In the Abu Qir field, borehole data acquired at the target-depths were exploited to derive a single rock-physics model, valid for different lithologies and for the full-ranges of shaliness and water saturation values. Despite the differences in the forward-model parameterization, the results of the two inversions are comparable and consistent with borehole data. In particular, the described inversion approaches were both able to identify the increase of porosity and the decreases of shaliness and water saturation in the target sands. It results that porosity is well resolved by both two-stage (narrow-angle) and single-stage (wide-angle) inversions. The water saturation remains poorly resolvable in both inversions due to its limited influence in determining the AVA response. Finally, wide-angle reflection inversion has demonstrated to be particularly effective in better constrain the shaliness estimations

Strategies to reduce stress and burnout in healthcare workers. An RCT research protocol

Aim The coronavirus (COVID-19), discovered in early 2020, has spread very rapidly around the world. Since of the numerous modifications made in hospitals to better cope with this infection, COVID-19 has harshly affected the mental and physical health of all labourers involved. Stress and burnout were the issues most commonly faced by healthcare workers (HCWs). To cut work-related stress and work-related burnout in HCWs directly tangled in the COVID-19 pandemic with different strategies. Several studies in the literature demonstrate the efficiency of Yoga, Mindfulness-Based Intervention (MBI), Visual Thinking Strategies (VTS) and Forest Bathing (FB) in improving the mental health of HCWs. Methods The study will be a randomized clinical trial (RCT), to assess the efficacy of four different interventions based on four types of techniques for improving mental health in HCWs. Results At the end of the study, thanks to the different strategies and deliveries, the participants, in the four groups, will be able to work on the different psychological aspects with improving life skills, and will be less likely to develop work-related stress and burnout. Conclusion Opening an easy-to-access and remote training program, steered by specialists in the field, through the creation of an application where the lessons will be uploaded, will allow an increase in the psychological health of the staff tangled, with the purpose of reducing medical faults and increasing standards of care for patients

Measurement of the K+→π+γγK^+\to\pi^+\gamma\gamma decay

International audienceA sample of 3984 candidates of the $K^+\to\pi^+\gamma\gamma$ decay, with an estimated background of $291\pm14$ events, was collected by the NA62 experiment at CERN during 2017-2018. In order to describe the observed di-photon mass spectrum, the next-to-leading order contribution in chiral perturbation theory was found to be necessary. The decay branching ratio in the full kinematic range is measured to be $(9.61\pm0.17)\times10^{-7}$. The first search for production and prompt decay of an axion-like particle with gluon coupling in the process $K^+\to\pi^+a$, $a\to\gamma\gamma$ is also reported

Measurement of the K+→π+γγK^+\to\pi^+\gamma\gamma decay

International audienceA sample of 3984 candidates of the $K^+\to\pi^+\gamma\gamma$ decay, with an estimated background of $291\pm14$ events, was collected by the NA62 experiment at CERN during 2017-2018. In order to describe the observed di-photon mass spectrum, the next-to-leading order contribution in chiral perturbation theory was found to be necessary. The decay branching ratio in the full kinematic range is measured to be $(9.61\pm0.17)\times10^{-7}$. The first search for production and prompt decay of an axion-like particle with gluon coupling in the process $K^+\to\pi^+a$, $a\to\gamma\gamma$ is also reported

Search for K+K^+ decays into the π+e+e−e+e−\pi^+e^+e^-e^+e^- final state

International audienceThe first search for ultra-rare $K^+$ decays into the $\pi^+e^+e^-e^+e^-$ final state is reported, using a dataset collected by the NA62 experiment at CERN in 2017-2018. An upper limit of $1.4\times 10^{-8}$ at 90% CL is obtained for the branching ratio of the $K^+\to\pi^+e^+e^-e^+e^-$ decay, predicted in the Standard Model to be $(7.2\pm0.7)\times 10^{-11}$. Upper limits at 90% CL are obtained at the level of $10^{-9}$ for the branching ratios of two prompt decay chains involving pair-production of hidden-sector mediators: $K^+\to\pi^+aa$, $a\to e^+e^-$ and $K^+\to\pi^+S$, $S\to A^\prime A^\prime$, $A^\prime\to e^+e^-$. The QCD axion is excluded as a possible explanation of the "17 MeV anomaly"

Measurement of the K+→π+γγK^+ \to \pi^+ \gamma \gamma decay

A sample of 3984 candidates of the $K^+ \to \pi^+ \gamma \gamma$ decay, with an estimated background of $291 \pm 14$ events, was collected by the NA62 experiment at CERN during 2017–2018. In order to describe the observed di-photon mass spectrum, the next-to-leading order contribution in chiral perturbation theory was found to be necessary. The decay branching ratio in the full kinematic range is measured to be ($9.61 \pm 0.17) \times 10^{−7}$. The first search for production and prompt decay of an axion-like particle with gluon coupling in the process $K^+ \to \pi^+ a, a \to \gamma \gamma$ is also reported.A sample of 3984 candidates of the $K^+\to\pi^+\gamma\gamma$ decay, with an estimated background of $291\pm14$ events, was collected by the NA62 experiment at CERN during 2017-2018. In order to describe the observed di-photon mass spectrum, the next-to-leading order contribution in chiral perturbation theory was found to be necessary. The decay branching ratio in the full kinematic range is measured to be $(9.61\pm0.17)\times10^{-7}$. The first search for production and prompt decay of an axion-like particle with gluon coupling in the process $K^+\to\pi^+a$, $a\to\gamma\gamma$ is also reported