Extremely low frequency-magnetic fields (ELF-EMF) occupational exposure and natural killer activity in peripheral blood lymphocytes

Extremely Low Frequency-Magnetic Fields (ELF-MF) are possible carcinogens to humans and some data suggest that they can act as promoters or progressors. Since NK cells play a major role in the control of cancer development, an adverse effect on ELF-MF on NK function has been hypothesized. We examined NK activity in 52 workers exposed to different levels of ELF-MF in various activities. Individual exposure was monitored during 3 complete work-shifts using personal dosimeters. Environmental exposure was also monitored. ELF-MF levels in the workers were expressed as Time-Weighted Average (TWA) values. NK activity was measured in peripheral blood lymphocytes (PBL). In the whole group the median occupational TWA was 0.21 microT. According to the TWA levels, workers were classified as low exposed (26 subjects, TWA < or =0.2 microT) and higher exposed workers (26 subjects; TWA >0.2 microT). In higher exposed workers, we observed a trend to reduce NK activity compared to low exposed, but the difference was not significant. Then we selected a subgroup of highest exposed workers (12 subjects; TWA >1 microT); no difference was observed between low and highest exposed subjects in the main personal variables. Considering both E:T ratios from 12:1 to 50:1 and Lytic Units, a significant reduction in NK activity was observed in the highest exposed workers compared to the low exposed. Multivariate analysis showed a significant negative correlation between exposure and LU, while no correlation was evidenced with other personal characteristics. ELF-MF are considered possible carcinogens, and existing data suggest that they can act as promoters. Due to the role of NK activity in host defence against cancer, the results obtained in this study in workers exposed to ELF-MF levels exceeding 1 microT are in agreement with this hypothesis, and support the need for further investigation in this field.     

Results of Measuring the Influence of Casimir Energy on Superconducting Phase Transitions

The ALADIN experiment aims at observing how the critical magnetic field of a superconducting aluminum film is modified, when it constitutes one of the reflecting surfaces of a Casimir cavity. If successful, such an observation would reveal the influence of vacuum energy on the superconducting phase transition. In this paper, a rigorous analysis of experimental data is reported, the results are discussed and compared with theoretical predictions based on Lifshitz theory of dispersion forces, and the BCS formula for the optical conductivity of superconductors. Thanks to this rigorous analysis, it can now be asserted that in the region of energy where it is expected that Casimir energy is comparable with condensation energy and the deviations of critical field from BCS formula to be not negligible, an anomalous behavior is found.     

Evidence of the CH···O HydrogenBonding in Imidazolium-Based Ionic Liquids from Far-Infrared Spectroscopy Measurements and DFT Calculations

Knowledge of all the intermolecular forces occurring in ionic liquids (ILs) is essential to master their properties. Aiming at investigating the weaker hydrogen bonding in aprotic liquids, the present work combined computational study and far-infrared spectroscopy on four imidazolium-based ILs with different anions. The DFT calculations of the ionic couples, using the ωB97X-D functional and considering both the empirical dispersion corrections and the presence of a polar solvent, show that, for all samples, the lowest energy configurations of the ion pair present H atoms, directly bound to C atoms of the cation and close to O atoms of the anion, capable of creating moderate to weak hydrogen bonding with anions. For the liquids containing anions of higher bonding ability, the absorption curves generated from the calculated vibrational frequencies and intensities show absorption bands between 100 and 125 cm⁻¹ corresponding to the stretching of the hydrogen bond. These indications are in complete agreement with the presently reported temperature dependence of the far-infrared spectrum, where the stretching modes of the hydrogen bonding are detected only for samples presenting a moderate interaction and become particularly prominent at low temperatures. Moreover, from the analysis of the infrared spectra, the occurrence of various phase transitions as a function of temperature was detected, and the difference in the average energy between the H-bonded and the dispersion-governed molecular configurations was evaluated.     

Incremental template updating for face recognition in home environments

The extreme variability of faces in smart environment applications, due to continuous changes in terms of pose, illumination and subject appearance (hairstyle, make-up, etc.), requires the relevant mode of variations of the subject's faces to be encoded in the templates and to be continuously updated based on new inputs. This work proposes a new video-based template updating approach suitable for home environments where the image acquisition process is totally unconstrained but a large amount of face data is available for continuous learning. A small set of labeled images is initially used to create the templates and the updating is then totally unsupervised. Although the method is here presented in conjunction with a subspace-based face recognition approach, it can be easily adapted to deal with different kinds of face representations. A thorough performance evaluation is carried out to show the efficacy and reliability of the proposed technique.     

Application of proteomic techniques to the study of urine and renal tissue

The increasing application of proteomic methods to biomedical research is providing us with important new information; it holds particular promise in advancing basic and clinical renal research, but whether proteomics can ever become a routine diagnostic tool in nephrology is still uncertain. Currently, proteomic techniques are used by many groups in the search for "biomarkers" of disease, especially kidney disease, because of the ready availability of urine as an "end-product" of renal function. However, the question as to whether any disease-specific biomarkers exist or can be identified by proteomics is also uncertain. A growing application of proteomics in biomedical research is to understand the mechanism(s) of disease. This brief review is selective; in it we consider examples of proteomic studies of human urine for biomarkers, others that have explored renal physiology, and still others that have begun to probe the proteome of organelles. No single approach is sufficiently comprehensive, and the pooled application of proteomics to renal research will undoubtedly improve our understanding of renal function and enable us to explore in more detail subcellular structures, and to characterize cellular processes at the molecular level. When combined with other techniques in renal research, proteomics, and related analytical methods could prove indispensable in modeling renal function, and perhaps also in diagnosis and management of renal disease.     

2D face recognition based on supervised subspace learning from 3D models

One of the main challenges in face recognition is represented by pose and illumination variations that drastically affect the recognition performance, as confirmed by the results of recent face recognition large-scale evaluations. This paper presents a new technique for face recognition, based on the joint use of 3D models and 2D images, specifically conceived to be robust with respect to pose and illumination changes. A 3D model of each user is exploited in the training stage (i.e. enrollment) to generate a large number of 2D images representing virtual views of the face with varying pose and illumination. Such images are then used to learn in a supervised manner a set of subspaces constituting the user's template. Recognition occurs by matching 2D images with the templates and no 3D information (neither images nor face models) is required. The experiments carried out confirm the efficacy of the proposed technique.     

The role of settling velocity formulation in the determination of gully pot trapping efficiency: comparison between analytical and experimental data

Roadside gully pots are the connecting points between surface runoff and the underground drainage network; therefore they can be considered as the most superficial component of urban drainage systems. Gully pots are supposed to trap particulate matter washed off the catchment surface, but also to collect and convey stormwater into the network. The continuous accumulation of particulate matter results in a progressive loss of the gully pot hydraulic conveyance, thereby increasing the probability of urban flooding during rainstorm events. This study has therefore the objective to determine which variables influence the gully pot capability of retaining solids (efficiency), both experimentally and analytically. Several laboratory tests have been performed on a simple plastic gully pot, with different inflow rates and using both mono and hetero-disperse particle samples. Particular attention has been given to the influence exerted by the way particle settling velocity is expressed: efficiency has been analytically determined by means of multiple settling velocity formulas proposed by various authors and eventually compared to experimental data. Results deriving from the adoption of each single settling velocity formula have been extensively analysed, showing fairly different outcomes.     

Exosomal MicroRNAs as Potential Biomarkers of Hepatic Injury and Kidney Disease in Glycogen Storage Disease Type Ia Patients

Glycogen storage disease type Ia (GSDIa) is an inherited metabolic disorder caused by mutations in the enzyme glucose-6-phosphatase-α (G6Pase-α). Affected individuals develop renal and liver complications, including the development of hepatocellular adenoma/carcinoma and kidney failure. The purpose of this study was to identify potential biomarkers of the evolution of the disease in GSDIa patients. To this end, we analyzed the expression of exosomal microRNAs (Exo-miRs) in the plasma exosomes of 45 patients aged 6 to 63 years. Plasma from age-matched normal individuals were used as controls. We found that the altered expression of several Exo-miRs correlates with the pathologic state of the patients and might help to monitor the progression of the disease and the development of late GSDIa-associated complications.