Spatial snow water equivalent estimation for mountainous areas using wireless-sensor networks and remote-sensing products

We developed an approach to estimate snow water equivalent (SWE) through interpolation of spatially representative point measurements using a k-nearest neighbors (k-NN) algorithm and historical spatial SWE data. It accurately reproduced measured SWE, using different data sources for training and evaluation. In the central-Sierra American River basin, we used a k-NN algorithm to interpolate data from continuous snow-depth measurements in 10 sensor clusters by fusing them with 14 years of daily 500-m resolution SWE-reconstruction maps. Accurate SWE estimation over the melt season shows the potential for providing daily, near real-time distributed snowmelt estimates. Further south, in the Merced-Tuolumne basins, we evaluated the potential of k-NN approach to improve real-time SWE estimates. Lacking dense ground-measurement networks, we simulated k-NN interpolation of sensor data using selected pixels of a bi-weekly Lidar-derived snow water equivalent product. k-NN extrapolations underestimate the Lidar-derived SWE, with a maximum bias of −10 cm at elevations below 3000 m and +15 cm above 3000 m. This bias was reduced by using a Gaussian-process regression model to spatially distribute residuals. Using as few as 10 scenes of Lidar-derived SWE from 2014 as training data in the k-NN to estimate the 2016 spatial SWE, both RMSEs and MAEs were reduced from around 20–25 cm to 10–15 cm comparing to using SWE reconstructions as training data. We found that the spatial accuracy of the historical data is more important for learning the spatial distribution of SWE than the number of historical scenes available. Blending continuous spatially representative ground-based sensors with a historical library of SWE reconstructions over the same basin can provide real-time spatial SWE maps that accurately represents Lidar-measured snow depth; and the estimates can be improved by using historical Lidar scans instead of SWE reconstructions

Information content of spatially distributed ground-based measurements for hydrologic-parameter calibration in mixed rain-snow mountain headwaters

Parameters in hydrologic models used in mixed rain-snow regions are often uncertain to calibrate and overfitted on streamflow. To contribute addressing these challenges, we used an algorithm that assesses modeling performances through time (Dynamic Identifiability Analysis) to quantify the information content of spatially distributed ground-based measurements for identifying optimal parameter values in the Precipitation Runoff Modeling System (PRMS) model. Including spatially distributed ground-based measurements in Identifiability Analysis allowed us to unambiguously estimate more parameter values than only using streamflow (seven parameters instead of two out of a pool of thirty-three). Peaks in information gain were obtained when using dew-point temperature to identify precipitation phase-partitioning parameters. Multi-attribute identifiability analysis also yielded optimal parameter values that were temporally less variable than those estimated using streamflow alone. Overall, identifying parameter values using ground-based measurements improved the simulation of key drivers of the surface-water budget, such as air temperature and precipitation-phase partitioning. However, parameters simulating surface-to-subsurface mass fluxes like snow accumulation and melt or evapotranspiration were poorly identified by any attribute and so emerged as key sources of predictive uncertainty for this distributed-parameter hydrologic model. This work demonstrates the value of expanded ground-based measurements for identifying parameters in distributed-parameter hydrologic models and so diagnosing their conceptual uncertainty across the water budget

Jejunogastric intussusception presented with hematemesis: a case presentation and review of the literature

BACKGROUND: Jejunogastric intussusception (JGI) is a rare but potentially very serious complication of gastrectomy or gastrojejunostomy. To avoid mortality early diagnosis and prompt surgical intervention is mandatory. CASE PRESENTATION: A young man presented with epigastric pain and bilous vomiting followed by hematemesis,10 years after vagotomy and gastrojejunostomy for a bleeding duodenal ulcer. Emergency endoscopy showed JGI and the CT scan of the abdomen was compatible with this diagnosis. At laparotomy a retrograde type II, JGI was confirmed and managed by reduction of JGI without intestinal resection. Postoperative recovery was uneventful. CONCLUSIONS: JGI is a rare condition and less than 200 cases have been published since its first description in 1914. The clinical picture is almost diagnostic. Endoscopy performed by someone familiar with this rare entity is certainly diagnostic and CT-Scan of the abdomen could also help. There is no medical treatment for acute JGI and the correct treatment is surgical intervention as soon as possible

Lung glutathione adaptive responses to cigarette smoke exposure

<p>Abstract</p> <p>Background</p> <p>Smoking tobacco is a leading cause of chronic obstructive pulmonary disease (COPD), but although the majority of COPD cases can be directly related to smoking, only a quarter of smokers actually develop the disease. A potential reason for the disparity between smoking and COPD may involve an individual's ability to mount a protective adaptive response to cigarette smoke (CS). Glutathione (GSH) is highly concentrated in the lung epithelial lining fluid (ELF) and protects against many inhaled oxidants. The changes in GSH that occur with CS are not well investigated; therefore the GSH adaptive response that occurs with a commonly utilized CS exposure was examined in mice.</p> <p>Methods</p> <p>Mice were exposed to CS for 5 h after which they were rested in filtered air for up to 16 h. GSH levels were measured in the ELF, bronchoalveolar lavage cells, plasma, and tissues. GSH synthesis was assessed by measuring γ-glutamylcysteine ligase (GCL) activity in lung and liver tissue.</p> <p>Results</p> <p>GSH levels in the ELF, plasma, and liver were decreased by as much as 50% during the 5 h CS exposure period whereas the lung GSH levels were unchanged. Next, the time course of rebound in GSH levels after the CS exposure was examined. CS exposure initially decreased ELF GSH levels by 50% but within 2 h GSH levels rebound to about 3 times basal levels and peaked at 16 h with a 6-fold increase and over repeat exposures were maintained at a 3-fold elevation for up to 2 months. Similar changes were observed in tissue GCL activity which is the rate limiting step in GSH synthesis. Furthermore, elevation in ELF GSH levels was not arbitrary since the CS induced GSH adaptive response after a 3d exposure period prevented GSH levels from dropping below basal levels.</p> <p>Conclusions</p> <p>CS exposures evoke a powerful GSH adaptive response in the lung and systemically. These data suggests there may be a sensor that sets the ELF GSH adaptive response to prevent GSH levels from dipping below basal levels. Factors that disrupt GSH adaptive responses may contribute to the pathophysiology of COPD.</p

Microscale characterization of prostate biopsies tissues using optical coherence elastography and second harmonic generation imaging

© 2018 USCAP, Inc All rights reserved. Photonics, especially optical coherence elastography (OCE) and second harmonic generation (SHG) imaging are novel high-resolution imaging modalities for characterization of biological tissues. Following our preliminary experience, we hypothesized that OCE and SHG imaging would delineate the microstructure of prostate tissue and aid in distinguishing cancer from the normal benign prostatic tissue. Furthermore, these approaches may assist in characterization of the grade of cancer, as well. In this study, we confirmed a high diagnostic accuracy of OCE and SHG imaging in the detection and characterization of prostate cancer for a large set of biopsy tissues obtained from men suspected to have prostate cancer using transrectal ultrasound (TRUS). The two techniques and methods described here are complementary, one depicts the stiffness of tissues and the other illustrates the orientation of collagen structure around the cancerous lesions. The results showed that stiffness of cancer tissue was ∼57.63% higher than that of benign tissue (Young's modulus of 698.43±125.29 kPa for cancerous tissue vs 443.07±88.95 kPa for benign tissue with OCE. Using histology as a reference standard and 600 kPa as a cut-off threshold, the data analysis showed sensitivity and specificity of 89.6 and 99.8%, respectively. Corresponding positive and negative predictive values were 99.5 and 94.6%, respectively. There was a significant difference noticed in terms of Young's modulus for different Gleason scores estimated by OCE (P-value<0.05). For SHG, distinct patterns of collagen distribution were seen for different Gleason grade disease with computed quantification employing a ratio of anisotropic to isotropic (A:I ratio) and this correlated with disease aggressiveness

Shifting boundaries between the normal and the pathological:the case of mild intellectual disability

When disorders fade into normality, how can the threshold between normality and disorder be determined? In considering mild intellectual disability, I argue that economic factors partly determine thresholds. We tend to assume that the relationship between disorder, need and services is such that: first, a cut-off point between the disordered and the normal is determined; second, a needy population is identified; and third, resources are found (or at least should be found) to meet this need. However, the changing definitions of intellectual disability can best be understood if we think of this happening in reverse. That is, first, certain resources are thought obtainable, and then a cut-off point for disorder is selected which supplies an appropriately sized ‘needy population’

Structural and functional evolution of the P2Y12-like receptor group

Metabotropic pyrimidine and purine nucleotide receptors (P2Y receptors) belong to the superfamily of G protein-coupled receptors (GPCR). They are distinguishable from adenosine receptors (P1) as they bind adenine and/or uracil nucleotide triphosphates or diphosphates depending on the subtype. Over the past decade, P2Y receptors have been cloned from a variety of tissues and species, and as many as eight functional subtypes have been characterized. Most recently, several members of the P2Y12-like receptor group, which includes the clopidogrel-sensitive ADP receptor P2Y12, have been deorphanized. The P2Y12-like receptor group comprises several structurally related GPCR which, however, display heterogeneous agonist specificity including nucleotides, their derivatives, and lipids. Besides the established function of P2Y12 in platelet activation, expression in macrophages, neuronal and glial cells as well as recent results from functional studies implicate that several members of this group may have specific functions in neurotransmission, inflammation, chemotaxis, and response to tissue injury. This review focuses specifically on the structure-function relation and shortly summarizes some aspects of the physiological relevance of P2Y12-like receptor members

Adolescent Brain Development and the Risk for Alcohol and Other Drug Problems

Dynamic changes in neurochemistry, fiber architecture, and tissue composition occur in the adolescent brain. The course of these maturational processes is being charted with greater specificity, owing to advances in neuroimaging and indicate grey matter volume reductions and protracted development of white matter in regions known to support complex cognition and behavior. Though fronto-subcortical circuitry development is notable during adolescence, asynchronous maturation of prefrontal and limbic systems may render youth more vulnerable to risky behaviors such as substance use. Indeed, binge-pattern alcohol consumption and comorbid marijuana use are common among adolescents, and are associated with neural consequences. This review summarizes the unique characteristics of adolescent brain development, particularly aspects that predispose individuals to reward seeking and risky choices during this phase of life, and discusses the influence of substance use on neuromaturation. Together, findings in this arena underscore the importance of refined research and programming efforts in adolescent health and interventional needs