Dietetic study of pregnant women of Santa Maria Cauqué, Guatemala. I. Variability of protein indicators and analysis by the time of meals

The distribution of the protein energy ratio indicators (Pe%), amino acid score and protein value (NDpCal%) in the three daily meals (breakfast, lunch and dinner) of the diet of pregnant women from Santa María Cauqué, Guatemala, was studied. The results were compared with those obtained for the total daily food intake. The differences observed were not significant, confirming the validity of the determination of amino acid score, Pe% and NDpCal% in the foods consumed during the whole day in this type of populations. It also reflects the nutritional benefit of the food pattern, since protein utilization would not be decreased by a different distribution of protein quality and concentration throughout the three daily meals. The variability among individuals of Pe% intake, amino acid score and NDpCal% gave the following values: 16.0, 9.3 and 15.6, respectively. It is noteworthy to add that the variability of Pe% observed is similar to that reported for populations of developed countries.     

Learning Structure from Data and Its Application to Ozone Prediction

In this paper we propose an algorithm for structure learning in predictive expert systems based on a probabilistic network representation. The idea is to have the simplest structure (minimum number of links) with acceptable predictive capability. The algorithm starts by building a tree structure based on measuring mutual information between pairs of variables, and then it adds links as necessary to obtain certain predictive performance. We have applied this method for ozone prediction in México City, where the ozone level is used as a global indicator for the air quality in different parts of the city. It is important to predict the ozone level a day, or at least several hours in advance, to reduce the health hazards and industrial losses that occur when the ozone reaches emergency levels. We obtained as a first approximation a tree-structured dependency model for predicting ozone in one part of the city. We observe that even with only three parameters, its estimations are acceptable.A causal network representation and the structure learning techniques produced some very interesting results for the ozone prediction problem. Firstly, we got some insight into the dependence structure of the phenomena. Secondly, we got an indication of which are the important and not so important variables for ozone forecasting. Taking this into account, the measurement and computational costs for ozone prediction could be reduced. And thirdly, we have obtained satisfactory short term ozone predictions based on a small set of the most important parameters.     

Norovirus Intestinal Infection and Lewy Body Disease in an Older Patient with Acute Cognitive Impairment

We present a case report on an older woman with unspecific symptoms and predominant long-term gastrointestinal disturbances, acute overall health deterioration with loss of autonomy for daily activities, and cognitive impairment. Autopsy revealed the presence of alpha-synuclein deposits spread into intestinal mucosa lesions, enteric plexuses, pelvic and retroperitoneal nerves and ganglia, and other organs as well as Lewy pathology in the central nervous system (CNS). Moreover, we isolated norovirus from the patient, indicating active infection in the colon and detected colocalization of norovirus and alpha-synuclein in different regions of the patient’s brain. In view of this, we report a concomitant norovirus infection with synthesis of alpha-synuclein in the gastrointestinal mucosa and Lewy pathology in the CNS, which might support Braak’s hypothesis about the pathogenic mechanisms underlying synucleinopathies.     

LncRNA H19 Impairs Chemo and Radiotherapy in Tumorigenesis

Various treatments based on drug administration and radiotherapy have been devoted to preventing, palliating, and defeating cancer, showing high efficiency against the progression of this disease. Recently, in this process, malignant cells have been found which are capable of triggering specific molecular mechanisms against current treatments, with negative consequences in the prognosis of the disease. It is therefore fundamental to understand the underlying mechanisms, including the genes—and their signaling pathway regulators—involved in the process, in order to fight tumor cells. Long non-coding RNAs, H19 in particular, have been revealed as powerful protective factors in various types of cancer. However, they have also evidenced their oncogenic role in multiple carcinomas, enhancing tumor cell proliferation, migration, and invasion. In this review, we analyze the role of lncRNA H19 impairing chemo and radiotherapy in tumorigenesis, including breast cancer, lung adenocarcinoma, glioma, and colorectal carcinoma.     

Anatomical Laser Microdissection of the Ileum Reveals mtDNA Depletion Recovery in A Mitochondrial Neuro-Gastrointestinal Encephalomyopathy (MNGIE) Patient Receiving Liver Transplant

mitochondrial neuro-gastrointestinal encephalomyopathy (MNGIE) is a rare genetic disorder characterized by thymidine phosphorylase (TP) enzyme defect. The absence of TP activity induces the imbalance of mitochondrial nucleotide pool, leading to impaired mitochondrial DNA (mtDNA) replication and depletion. Since mtDNA is required to ensure oxidative phosphorylation, metabolically active tissues may not achieve sufficient energy production. The only effective life-saving approach in MNGIE has been the permanent replacement of TP via allogeneic hematopoietic stem cell or liver transplantation. However, the follow-up of transplanted patients showed that gut tissue changes do not revert and fatal complications, such as massive gastrointestinal bleeding, can occur. The purpose of this study was to clarify whether the reintroduction of TP after transplant can recover mtDNA copy number in a normal range. Using laser capture microdissection and droplet-digital-PCR, we assessed the mtDNA copy number in each layer of full-thickness ileal samples of a naive MNGIE cohort vs. controls and in a patient pre- and post-TP replacement. The treatment led to a significant recovery of gut tissue mtDNA amount, thus showing its efficacy. Our results indicate that a timely TP replacement is needed to maximize therapeutic success before irreversible degenerative tissue changes occur in MNGIE.     

Effective edge node configuration for video transport over Optical Burst Switched networks

This paper considers digital video transport over Optical Burst Switched networks where burst losses cause data loss from one or more adjacent video frames. Analytical approximations for the frame losses and video playback interruptions are derived and validated using simulations. Both parameters require a very limited and static amount of data about the video on the user side and some quality of service metrics about the network to quantify the quality of the received video. The results take into account the strong dependency in the video traffic structure due to the coding mechanisms. The critical effect of video coding parameters is also revealed. The paper also presents a Traffic Engineering procedure to select the best parameters for the edge node and the video codec to meet a given video quality level on the user side.     

Probing the electromagnetic field distribution within a metallic nanodisk

A Co nanolayer is used as a local probe to evaluate the vertical inhomogeneous distribution of the electromagnetic (EM) field within a resonant metallic nanodisk. Taking advantage of the direct relation between the magneto-optical activity and the electromagnetic field intensity in the Co layer, it is shown that the nonuniform EM distribution within the nanodisk under plasmon resonant conditions has maximum values close to the upper and lower flat faces, and a minimum value in the middle.     

Pixel selection for near-infrared chemical imaging (NIR-CI) discrimination between fish and terrestrial animal species in animal protein by-product meals

This paper proposes a method based on near-infrared hyperspectral imaging for discriminating between terrestrial and fish species in animal protein by-products used in livestock feed. Four algorithms (Mahalanobis distance, Kennard-Stone, spatial interpolation, and binning) were compared in order to select an appropriate subset of pixels for further partial least squares discriminant analysis (PLS-DA). The method was applied to a set of 50 terrestrial and 40 fish meals analyzed in the 1000-1700 nm range. Models were then tested using an external validation set comprising 45 samples (25 fish and 20 terrestrial). The PLS-DA models obtained using the four subset-selection algorithms yielded a classification accuracy of 99.80%, 99.79%, 99.85%, and 99.61%, respectively. The results represent a first step for the analysis of mixtures of species and suggest that NIR-CI, providing valuable information on the origin of animal components in processed animal proteins, is a promising method that could be used as part of the EU feed control program aimed at eradicating and preventing bovine spongiform encephalopathy (BSE) and related diseases.     

Multimode polarization degree of mixture optical states in integrated directional couplers

Mixture multimode optical field classical states propagating in N?×?N integrated directional couplers are analyzed by using the density matrix formalism in a N-dimensional optical space. These mutimode optical fields present a kind of generalized polarization and accordingly a definition of a multimode polarization degree is proposed. It is based on the distance measure between a mixture state and an unpolarized state in a N-dimensional optical space so that in the case N=2 the standard polarization degree is recovered. It is shown that directional couplers can reduce or increase remarkably the multimode polarization degree of a mixture state. Likewise a simple measurement technique, based on Y junctions, of this multimode polarization degree is proposed. Finally all the results can be formally extended to the special case of multimode single photon quantum states.     

Characterization and Physical Explanation of Energetic Particles on Planck HFI Instrument

The Planck High Frequency Instrument (HFI) has been surveying the sky continuously from the second Lagrangian point (L2) between August 2009 and January 2012. It operates with 52 high impedance bolometers cooled at 100 mK in a range of frequency between 100 GHz and 1 THz with unprecedented sensitivity, but strong coupling with cosmic radiation. At L2, the particle flux is about 5 \(\hbox {cm}^{-2}\,\hbox {s}^{-1}\) and is dominated by protons incident on the spacecraft. Protons with an energy above 40 MeV can penetrate the focal plane unit box causing two different effects: glitches in the raw data from direct interaction of cosmic rays with detectors (producing a data loss of about 15 % at the end of the mission) and thermal drifts in the bolometer plate at 100 mK adding non-Gaussian noise at frequencies below 0.1 Hz. The HFI consortium has made strong efforts in order to correct for this effect on the time ordered data and final Planck maps. This work intends to give a view of the physical explanation of the glitches observed in the HFI instrument in-flight. To reach this goal, we performed several ground-based experiments using protons and \(\alpha \) particles to test the impact of particles on the HFI spare bolometers with a better control of the environmental conditions with respect to the in-flight data. We have shown that the dominant part of glitches observed in the data comes from the impact of cosmic rays in the silicon die frame supporting the micro-machined bolometric detectors propagating energy mainly by ballistic phonons and by thermal diffusion. The implications of these results for future satellite missions will be discussed.