Identifying the lights position in photometric stereo under unknown lighting

Reconstructing the 3D shape of an object from a set of images is a classical problem in Computer Vision. Photometric stereo is one of the possible approaches. It stands on the assumption that the object is observed from a fixed point of view under different lighting conditions. The traditional approach requires that the position of the light sources is accurately known. It has been proved that the lights position can be estimated directly from the data, when at least 6 images of the observed object are available. In this paper, we give a Matlab implementation of the algorithm for solving the photometric stereo problem under unknown lighting, and propose a simple shooting technique to solve the bas-relief ambiguity.Comment: new versio

ESA SENTINEL 2 IMAGERY AND GBGEOAPP: INTEGRATED TOOLS FOR THE DEOSAI NATIONAL PARK MANAGEMENT PLAN

Deosai plateau, in the Gilgit-Baltistan Province of Pakistan, for its average elevation of 4,114 meters, is the second highest plateau in the world after Changtang Tibetan Plateau. Two biogeographically important mountain ranges merge in Deosai: the Himalayan and Karakorum–Pamir highlands. The Deosai National Park, with its first recognition in 1993, encompasses an area of about 1620 km2, with the altitude ranging from 3500 to 5200 meters a.s.l. It is known and visited by tourists for the presence of brown bear, but a large number of species of fauna and flora leave, and can be seen during the summer season. This high-altitude ecosystem is particularly fragile and can be considered a sentinel for the effects of climate changes. Due to its geographic position and high altitude, the area of Deosai has never been studied in all its ecosystem components, producing high resolution maps. The first land cover map of Deosai with 10 meters of resolution is discussed in this study. This map has been obtained from Sentinel-2 imagery and improved through the new tool developed in this study: the GBGEOApp. This application for mobile has been done with three main ambitions: the validation of the new land cover map, its improvement with land use information, and the collection of new data in the field. On the basis of the results, the use of the GBGEOApp, as a tool for validation and increasing of environmental data collection, seems to be completely applicable involving the local technicians in a process of data sharing

Effect of storage conditions on seed germination of eigTyrrhenian endemic vascular plant species of conservation interest

The conservation of endemic and endangered plant species is of great interest to the scientific and research community. In this frame, seed banks play a crucial role when biodiversity preservation and climate change are considered. The study of seed viability and germination during storage conditions provides basic and useful information to ensure successful ex situ conservation. The aim of this study was to evaluate whether storage time and conditions (i.e., base collection at -25°C and active collection at +5°C) affect seed germination in the long term. For these purposes, eight Tyrrhenian endemic vascular plant species (mostly endangered) with orthodox seeds were studied: Brassica insularis, Centranthus amazonum, Dianthus morisianus, Digitalis purpurea var. gyspergerae, Ferula arrigonii, Helicodiceros muscivorus, Iberis integerrima and Verbascum plantagineum. These species were stored in the Sardinian Germplasm Bank (BG-SAR) at -25°C and at +5°C for a time ranging from 2 to 12 years. Germination tests were carried out following the optimal conditions reported in the literature for each species. The results showed, in general terms, the high seed germination capacity of all species stored at both conditions; regarding the time of seed storage, germination in some tested species (such as B. insularis and C. amazonum) slightly decreased over time. We argued that seed dehydration, low seed moisture content during storage and the use of hermetic glass containers can be considered key factors for long-term conservation of these orthodox seeds. In conclusion, this study showed that the conservation of these endemic species is ensured by seed bank storage, according to the general assumption that seed longevity depends on seed lot quality, on well-sealed storage containers and conditions before and during storage

Chronic treatment with statins increases the availability of selenium in the antioxidant defence systems of hemodialysis patients.

Project. Oxidative stress (OS) is enhanced in hemodialysis (HD) patients. Lipid peroxidation and oxidative damage to glycids, proteins and nucleic acids are main consequences of OS and are associated to increased cardiovascular risk. Vitamin E and Glutathione Peroxidase (GSH-Px) represent main antioxidant systems in human cells. Selenium (Se), bound to the active sites of GSH-Px, plays a critical role in this antioxidant defense system. Statins are widely used and extensively investigated in the prevention of cardiovascular disease, notably in high-risk subjects. Several studies suggest that statins show antioxidant effects, protecting low-density lipoproteins from oxidation. Aim of our study was to compare serum Se concentration in ESRD patients on maintenance HD and in homogeneous healthy subjects and to investigate whether chronic assumption of statins may interfere with serum Se concentration in HD patients. Procedure. A total of 103 HD patients and 69 healthy subjects were enrolled; HD patients were then divided into patients who were not treated with statins (group A) and patients who assumed statins since six months at least (group B). Serum Se was determined by atomic absorption spectrometry. Results. Serum Se was significantly lower in HD patients of group A compared to healthy subjects (81.65±19.66mcg/L Vs. 96.47±15.62mcg/L, p<0.0040). However, in HD patients who assumed statins serum Se was significantly higher than in HD patients who did not. (111.83±18.82mcg/L Vs. 81.65±19.66mcg/L, p<0.0001). Conclusions. our results suggest that in HD patients chronic assumption of statins is related to a higher availability of active antioxidant agents and to reduced oxidative stress

RNA analysis of consensus sequence splicing mutations: implications for thediagnosis of Wilson disease

Wilson disease (WD) is an autosomal recessive disorder caused by a defective function of the copper-transporting ATP7B protein. This results in progressive copper overload and consequent liver, brain, and kidney damage. Approximately 300 WD-causing mutations have been described to date. Missense mutations are largely prevalent, while splice-site mutations are rarer. Of these, only a minority are detected in splicing consensus sequences. Further, few splicing mutations have been studied at the RNA level. In this study we report the RNA molecular characterization of three consensus splice-site mutations identified by DNA analysis in WD patients. One of them, c.51 + 4 A --> T, resides in the consensus sequence of the donor splice site of intron 1; the second, c. 2121 + 3 A --> G, occurred in position + 3 of intron 7; and the c.2447 + 5 G --> A is localized in the consensus sequence of the donor splice site of intron 9. Analysis revealed predominantly abnormal splicing in the samples carrying mutations compared to the normal controls. These results strongly suggest that consensus sequence splice-site mutations result in disease by interfering with the production of the normal WD protein. Our data contribute to understanding the mutational spectrum that affect splicing and improve our capability in WD diagnosis

Delayed diagnosis of coeliac disease increases cancer risk

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Accumulation of neutral lipids in peripheral blood mononuclear cells as a distinctive trait of Alzheimer patients and asymptomatic subjects at risk of disease

<p>Abstract</p> <p>Background</p> <p>Alzheimer's disease is the most common progressive neurodegenerative disease. In recent years, numerous progresses in the discovery of novel Alzheimer's disease molecular biomarkers in brain as well as in biological fluids have been made. Among them, those involving lipid metabolism are emerging as potential candidates. In particular, an accumulation of neutral lipids was recently found by us in skin fibroblasts from Alzheimer's disease patients. Therefore, with the aim to assess whether peripheral alterations in cholesterol homeostasis might be relevant in Alzheimer's disease development and progression, in the present study we analyzed lipid metabolism in plasma and peripheral blood mononuclear cells from Alzheimer's disease patients and from their first-degree relatives.</p> <p>Methods</p> <p>Blood samples were obtained from 93 patients with probable Alzheimer's disease and from 91 of their first-degree relatives. As controls we utilized 57, cognitively normal, over-65 year-old volunteers and 113 blood donors aged 21-66 years, respectively. Data are reported as mean ± standard error. Statistical calculations were performed using the statistical analysis software Origin 8.0 version. Data analysis was done using the Student t-test and the Pearson test.</p> <p>Results</p> <p>Data reported here show high neutral lipid levels and increased ACAT-1 protein in about 85% of peripheral blood mononuclear cells freshly isolated (<it>ex vivo</it>) from patients with probable sporadic Alzheimer's disease compared to about 7% of cognitively normal age-matched controls. A significant reduction in high density lipoprotein-cholesterol levels in plasma from Alzheimer's disease blood samples was also observed. Additionally, correlation analyses reveal a negative correlation between high density lipoprotein-cholesterol and cognitive capacity, as determined by Mini Mental State Examination, as well as between high density lipoprotein-cholesterol and neutral lipid accumulation. We observed great variability in the neutral lipid-peripheral blood mononuclear cells data and in plasma lipid analysis of the subjects enrolled as Alzheimer's disease-first-degree relatives. However, about 30% of them tend to display a peripheral metabolic cholesterol pattern similar to that exhibited by Alzheimer's disease patients.</p> <p>Conclusion</p> <p>We suggest that neutral lipid-peripheral blood mononuclear cells and plasma high density lipoprotein-cholesterol determinations might be of interest to outline a distinctive metabolic profile applying to both Alzheimer's disease patients and asymptomatic subjects at higher risk of disease.</p

Predictive Power Estimation Algorithm (PPEA) - A New Algorithm to Reduce Overfitting for Genomic Biomarker Discovery

Toxicogenomics promises to aid in predicting adverse effects, understanding the mechanisms of drug action or toxicity, and uncovering unexpected or secondary pharmacology. However, modeling adverse effects using high dimensional and high noise genomic data is prone to over-fitting. Models constructed from such data sets often consist of a large number of genes with no obvious functional relevance to the biological effect the model intends to predict that can make it challenging to interpret the modeling results. To address these issues, we developed a novel algorithm, Predictive Power Estimation Algorithm (PPEA), which estimates the predictive power of each individual transcript through an iterative two-way bootstrapping procedure. By repeatedly enforcing that the sample number is larger than the transcript number, in each iteration of modeling and testing, PPEA reduces the potential risk of overfitting. We show with three different cases studies that: (1) PPEA can quickly derive a reliable rank order of predictive power of individual transcripts in a relatively small number of iterations, (2) the top ranked transcripts tend to be functionally related to the phenotype they are intended to predict, (3) using only the most predictive top ranked transcripts greatly facilitates development of multiplex assay such as qRT-PCR as a biomarker, and (4) more importantly, we were able to demonstrate that a small number of genes identified from the top-ranked transcripts are highly predictive of phenotype as their expression changes distinguished adverse from nonadverse effects of compounds in completely independent tests. Thus, we believe that the PPEA model effectively addresses the over-fitting problem and can be used to facilitate genomic biomarker discovery for predictive toxicology and drug responses