Effect of PPARγ Inhibition during Pregnancy on Posterior Cerebral Artery Function and Structure

Peroxisome proliferator-activated receptor-γ (PPARγ), a ligand-activated transcription factor, has protective roles in the cerebral circulation and is highly activated during pregnancy. Thus, we hypothesized that PPARγ is involved in the adaptation of cerebral vasculature to pregnancy. Non-pregnant (NP) and late-pregnant (LP) rats were treated with a specific PPARγ inhibitor GW9662 (10 ]mg/kg/day, in food) or vehicle for 10 days and vascular function and structural remodeling were determined in isolated and pressurized posterior cerebral arteries (PCA). Expression of PPARγ and angiotensin type 1 receptor (AT1R) in cerebral (pial) vessels was determined by real-time RT-PCR. PPARγ inhibition decreased blood pressure and increased blood glucose in NP rats, but not in LP rats. PPARγ inhibition reduced dilation to acetylcholine and sodium nitroprusside in PCA from NP (p < 0.05 vs. LP-GW), but not LP rats. PPARγ inhibition tended to increase basal tone and myogenic activity in PCA from NP rats, but not LP rats. Structurally, PPARγ inhibition increased wall thickness in PCA from both NP and LP rats (p < 0.05), but increased distensibility only in PCA from NP rats. Pregnancy decreased expression of PPARγ and AT1R (p < 0.05) in cerebral arteries that was not affected by GW9662 treatment. These results suggest that PPARγ inhibition had significant effects on the function and structure of PCA in the NP state, but appeared to have less influence during pregnancy. Down-regulation of PPARγ and AT1R in cerebral arteries may be responsible for the lack of effect of PPARγ in cerebral vasculature and may be part of the vascular adaptation to pregnancy

Rainfall depth-duration-frequency curves for short-duration precipitation events in Sicily (Italy)

The design criteria of the hydraulic infrastructures, including, for instance, those for flood defense, urban drainage systems, reservoirs spillways and bridges, are based on the coupled analysis of the magnitude of rainfall events for a fixed duration and their estimated annual exceedance probability. The well-known rainfall depth-duration-frequency (DDF) curves, typically derived from the analysis of long historical annual maxima data series, synthesize the relationships between rainfall depth, duration and exceedance probability which is usually expressed as a return period. The time-resolution of rainfall data typically available for the construction of DDF curves and provided by gauges having large sample size, is hourly or coarser; this has allowed the definition of statistically consistent and reliable curves, suitable for rainfall duration hourly or longer, while, for shorter duration, empirical relationships with a high degree of approximation are generally used. Small river basins and plot-size areas with short response time, as well as urban drainage systems, are expected to be particularly vulnerable to sub-hourly intense rainfall events. Many practical applications, design procedures and mathematical models indeed require a finer time-resolution (i.e. sub - hourly). Moreover, in many regions of the world, such as the Sicily (Italy), an intensification of short-duration rainfall events is observed probably in response to the ongoing climate changes. This work proposes an approach for estimating the distribution of sub-hourly extreme rainfalls and extending depth–duration–frequency (DDF) curves derived for duration over the hourly also to sub-hourly durations. The approach is applied in Sicily starting from the coupled analysis of two different databases. The former (OA-ARRA database) contains long series of annual maxima for the fixed duration of 1, 3, 6, 12 and 24 hours for about 250 gauges, while the latter (SIAS database), include 10-minutes rainfall data series for about 100 gauges collected during the last 15 years (from 2003 to now), form which annual maxima time-series for fixed sub-hourly duration are derived. The approach includes a procedure for pairing raingauges, provided from the two databases, according to a distance- and elevation-based criterion and consolidated inference statistical techniques for the coupled analysis of the data-series from the two gauges

Detecting precipitation trend using a multiscale approach based on quantile regression over a Mediterranean area

One of the most relevant and debated topics related to the effects of the climate change is whether intense rainfall events have become more frequent over the last decades. It is a crucial aspect, since an increase in the magnitude and frequency of occurrence of heavy rainfall events could result in a dramatic growth of floods and, in turn, human lives losses and economic damages. Because of its central position in the Mediterranean area, Sicily has been often screened with the aim to capture some trends in precipitation, potentially related to climate change. While Mann-Kendall test has been largely used for the rainfall trend detection, in this work a different procedure is considered. Precipitation trends are here investigated by processing the whole rainfall time-series, provided by the regional agency SIAS at a 10-min resolution, through the quantile regression method by aggregating precipitation across a wide spectrum of durations and considering different quantiles. Results show that many rain gauges are characterized by an increasing trend in sub-hourly precipitation intensity, especially at the highest quantiles, thus suggesting that, from 2002 to 2019, sub-hourly events have become more intense in most of the island. Moreover, by analysing some spatial patterns, it has been revealed that the south and the east of Sicily are more interested in significant increasing rainfall trends, especially at the 10-min duration. Finally, the comparison between the two procedures revealed a stronger reliability of the quantile regression in the trend analysis detection, mainly due to the possibility of investigating the temporal variation of the tails of precipitation distribution

TTF-1/p63-positive poorly differentiated NSCLC: A histogenetic hypothesis from the basal reserve cell of the terminal respiratory unit

TTF-1 is expressed in the alveolar epithelium and in the basal cells of distal terminal bronchioles. It is considered the most sensitive and specific marker to define the adenocarcinoma arising from the terminal respiratory unit (TRU). TTF-1, CK7, CK5/6, p63 and p40 are useful for typifying the majority of non-small-cell lung cancers, with TTF and CK7 being typically expressed in adenocarcinomas and the latter three being expressed in squamous cell carcinoma. As tumors with coexpression of both TTF-1 and p63 in the same cells are rare, we describe different cases that coexpress them, suggesting a histogenetic hypothesis of their origin. We report 10 cases of poorly differentiated non-small-cell lung carcinoma (PD-NSCLC). Immunohistochemistry was performed by using TTF-1, p63, p40 (∆Np63), CK5/6 and CK7. EGFR and BRAF gene mutational analysis was performed by using real-time PCR. All the cases showed coexpression of p63 and TTF-1. Six of them showing CK7+ and CK5/6− immunostaining were diagnosed as “TTF-1+ p63+ adenocarcinoma”. The other cases of PD-NSCLC, despite the positivity for CK5/6, were diagnosed as “adenocarcinoma, solid variant”, in keeping with the presence of TTF-1 expression and p40 negativity. A “wild type” genotype of EGFR was evidenced in all cases. TTF1 stained positively the alveolar epithelium and the basal reserve cells of TRU, with the latter also being positive for p63. The coexpression of p63 and TTF-1 could suggest the origin from the basal reserve cells of TRU and represent the capability to differentiate towards different histogenetic lines. More aggressive clinical and morphological features could characterize these “basal-type tumors” like those in the better known “basal-like” cancer of the breast

Using very high resolution (VHR) imagery within a GEOBIA framework for gully mapping: An application to the Calhoun Critical Zone Observatory

Gully erosion is a form of accelerated erosion that may affect soil productivity, restrict land use, and lead to an increase of risk to infrastructure. Accurate mapping of these landforms can be difficult because of the presence of dense canopy and/or the wide spatial extent of some gullies. Even where possible, mapping of gullies through conventional field surveying can be an intensive and expensive activity. The recent widespread availability of very high resolution (VHR) imagery has led to remarkable growth in the availability of terrain information, thus providing a basis for the development of new methodologies for analyzing Earth’s surfaces. This work aims to develop a geographic object-based image analysis to detect and map gullies based on VHR imagery. A 1-meter resolution LIDAR DEM is used to identify gullies. The tool has been calibrated for two relatively large gullies surveyed in the Calhoun Critical Zone Observatory (CCZO) area in the southeastern United States. The developed procedure has been applied and tested on a greater area, corresponding to the Holcombe’s Branch watershed within the CCZO. Results have been compared to previous works conducted over the same area, demonstrating the consistency of the developed procedure

Spiral trajectories induced by radial thrust with applications to generalized sails

In this study, new analytical solutions to the equations of motion of a propelled spacecraft are investigated using a shape-based approach. There is an assumption that the spacecraft travels a two-dimensional spiral trajectory in which the orbital radius is proportional to an assigned power of the spacecraft angular coordinate. The exact solution to the equations of motion is obtained as a function of time in the case of a purely radial thrust, and the propulsive acceleration magnitude necessary for the spacecraft to track the prescribed spiral trajectory is found in a closed form. The analytical results are then specialized to the case of a generalized sail, that is, a propulsion system capable of providing an outward radial propulsive acceleration, the magnitude of which depends on a given power of the Sun-spacecraft distance. In particular, the conditions for an outward radial thrust and the required sail performance are quantified and thoroughly discussed. It is worth noting that these propulsion systems provide a purely radial thrust when their orientation is Sun-facing. This is an important advantage from an engineering point of view because, depending on the particular propulsion system, a Sun-facing attitude can be stable or obtainable in a passive way. A case study is finally presented, where the generalized sail is assumed to start the spiral trajectory from the Earth’s heliocentric orbit. The main outcome is that the required sail performance is in principle achievable on the basis of many results available in the literature

Face recognition with image sets using manifold density divergence

In many automatic face recognition applications, a set of a person\u27s face images is available rather than a single image. In this paper, we describe a novel method for face recognition using image sets. We propose a flexible, semi-parametric model for learning probability densities confined to highly non-linear but intrinsically low-dimensional manifolds. The model leads to a statistical formulation of the recognition problem in terms of minimizing the divergence between densities estimated on these manifolds. The proposed method is evaluated on a large data set, acquired in realistic imaging conditions with severe illumination variation. Our algorithm is shown to match the best and outperform other state-of-the-art algorithms in the literature, achieving 94% recognition rate on average

A Surface Evolution Approach to Probabilistic Space Carving

We present a 3D photography method that generates a texture-mapped three-dimensional model of a scene computed from multi-view calibrated two-dimensional photographs. Our approach first performs probabilistic space carving, which results in a 3D grid of voxel probabilities that describe the likelihood of a voxel existing in the model. We then employ a three-dimensional geodesic active surface to extract a most likely conformally-weighted minimal surface from the voxel probabilities. This surface is then polygonalized and texture-mapped, yielding in a 3D model easily rendered with standard graphics hardware