Relationship between leptin receptor and polycystic ovary syndrome

Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders, which is involved in the multi-system disease, and its etiology is still not clearly understood. It is currently considered that not only the genetic factors but also the environment factors play a crucial role in the pathogenesis of PCOS. Obesity plays an important role through the insulin, leptin and endocannabinoid system in the pathological process of PCOS, leading to more severe clinical manifestations. The aim of our present study is to investigate whether there is association between single nucleotide polymorphisms (SNPs) of Gln223Arg and Pro1019Pro in the leptin receptor gene (LEPR) and PCOS in a Korean population. Interestingly, a significant association was found between the Pro1019Pro in LEPR gene and PCOS, and a highly significant association was found between the Gln223Arg in LEPR gene and PCOS (P = 0.033, OR = 1.523, 95% confidence interval and P < 0.0001, OR = 0.446, 95% confidence interval). Moreover, genotype combination and haplotype analyses indicate that Gln223Arg and Pro1019Pro polymorphisms of LEPR are significantly associated with the risk of PCOS.     

Rule extraction in gene–disease relationship discovery

Background

Biomedical data available to researchers and clinicians have increased dramatically over the past years because of the exponential growth of knowledge in medical biology. It is difficult for curators to go through all of the unstructured documents so as to curate the information to the database. Associating genes with diseases is important because it is a fundamental challenge in human health with applications to understanding disease properties and developing new techniques for prevention, diagnosis and therapy.

Methods

Our study uses the automatic rule-learning approach to gene–disease relationship extraction. We first prepare the experimental corpus from MEDLINE and OMIM. A parser is applied to produce some grammatical information. We then learn all possible rules that discriminate relevant from irrelevant sentences. After that, we compute the scores of the learned rules in order to select rules of interest. As a result, a set of rules is generated.

Results

We produce the learned rules automatically from the 1000 positive and 1000 negative sentences. The test set includes 400 sentences composed of 200 positives and 200 negatives. Precision, recall and F-score served as our evaluation metrics. The results reveal that the maximal precision rate is 77.8% and the maximal recall rate is 63.5%. The maximal F-score is 66.9% where the precision rate is 70.6% and the recall rate is 63.5%.

Conclusions

We employ the rule-learning approach to extract gene–disease relationships. Our main contributions are to build rules automatically and to support a more complete set of rules than a manually generated one. The experiments show exhilarating results and some improving efforts will be made in the future.     

Quantum chemical insight on vibration spectra of silica systems

A set of silicate ions and corresponding lithium salts have been quantum chemically (QC) simulated in a “free molecule” approach. The infrared (IR), inelastic neutron scattering (INS), and Raman spectra have been simulated and fitted to the experimentally registered ones. The complete assignment of the vibrational bands along with the intensities and potential energy distribution has been performed. The applicability of the traditionally used quasimolecule Si–O–Si model to the interpretation of bands near 440–480 cm^? 1 and so-called “Boson” peak near 50 cm^? 1 has been critically discussed.     

Long-Term Heart Rate Fluctuations in Postoperative and Brain-Dead Patients

Long-term heart rate fluctuations in postoperative and brain-dead patients were investigated. Heart rates were monitored continuously, and the data were stored, edited, and interpolated to allow for data lost during calibration and disconnection of the sensors for various treatments. Heart rate power spectra were calculated using the fast Fourier transform method. The power spectra of the patients who recovered showed that the heart rate fluctuated and produced a 1/f relationship, termed 1/f fluctuations, whereas those of patients who died in the intensive care unit (ICU) consisted of white-noise-like signals. The power spectra in brain-dead patients showed a 1/f relationship under steady-state conditions, while the power density and variation of the frequency distribution were lower than those in a normal subject. Therefore, 1/f fluctuations appear to be universal and occur independent of the central nervous system. (Chronobiology International, 15(6), 633-646, 1998)     

Quantification of Sleepiness Through Principal Component Analysis of the Electroencephalographic Spectrum

Although circadian and sleep research has made extraordinary progress in the recent years, one remaining challenge is the objective quantification of sleepiness in individuals suffering from sleep deprivation, sleep restriction, and excessive somnolence. The major goal of the present study was to apply principal component analysis to the wake electroencephalographic (EEG) spectrum in order to establish an objective measure of sleepiness. The present analysis was led by the hypothesis that in sleep-deprived individuals, the time course of self-rated sleepiness correlates with the time course score on the 2nd principal component of the EEG spectrum. The resting EEG of 15 young subjects was recorded at 2-h intervals for 32–50?h. Principal component analysis was performed on the sets of 16 single-Hz log-transformed EEG powers (1–16?Hz frequency range). The time course of self-perceived sleepiness correlated strongly with the time course of the 2nd principal component score, irrespective of derivation (frontal or occipital) and of analyzed section of the 7-min EEG record (2-min section with eyes open or any of the five 1-min sections with eyes closed). This result indicates the possibility of deriving an objective index of physiological sleepiness by applying principal component analysis to the wake EEG spectrum. (Author correspondence: putilov@ngs.ru)     

Using a dry electrode EEG device during balance tasks in healthy young-adult males: Test–retest reliability analysis

Abstract

Background: The analysis of brain activity during balance is an important topic in different fields of science. Given that all measurements involve an error that is caused by different agents, like the instrument, the researcher, or the natural human variability, a test–retest reliability evaluation of the electroencephalographic assessment is a needed starting point. However, there is a lack of information about the reliability of electroencephalographic measurements, especially in a new wireless device with dry electrodes.

Objective: The current study aims to analyze the reliability of electroencephalographic measurements from a wireless device using dry electrodes during two different balance tests.

Method: Seventeen healthy male volunteers performed two different static balance tasks on a Biodex Balance Platform: (a) with two feet on the platform and (b) with one foot on the platform. Electroencephalographic data was recorded using Enobio (Neuroelectrics). The mean power spectrum of the alpha band of the central and frontal channels was calculated. Relative and absolute indices of reliability were also calculated.

Results: In general terms, the intraclass correlation coefficient (ICC) values of all the assessed channels can be classified as excellent (>0.90). The percentage standard error of measurement oscillated from 0.54% to 1.02% and the percentage smallest real difference ranged from 1.50% to 2.82%.

Conclusion: Electroencephalographic assessment through an Enobio device during balance tasks has an excellent reliability. However, its utility was not demonstrated because responsiveness was not assessed.     

Structure of native oligomeric Sprouty2 by electron microscopy and its property of electroconductivity

Receptor tyrosine kinases (RTKs) regulate many cellular processes, and Sprouty2 (Spry2) is known as an important regulator of RTK signaling pathways. Therefore, it is worth investigating the properties of Spry2 in more detail. In this study, we found that Spry2 is able to self-assemble into oligomers with a high-affinity KD value of approximately 16 nM, as determined through BIAcore surface plasmon resonance analysis. The three-dimensional (3D) structure of Spry2 was resolved using an electron microscopy (EM) single-particle reconstruction approach, which revealed that Spry2 is donut-shaped with two lip-cover domains. Furthermore, the method of energy dispersive spectrum obtained through EM was analyzed to determine the elements carried by Spry2, and the results demonstrated that Spry2 is a silicon- and iron-containing protein. The silicon may contribute to the electroconductivity of Spry2, and this property exhibits a concentration-dependent feature. This study provides the first report of a silicon- and iron-containing protein, and its 3D structure may allow us (1) to study the potential mechanism through the signal transduction is controlled by switching the electronic transfer on or off and (2) to develop a new type of conductor or even semiconductor using biological or half-biological hybrid materials in the future.     

Botanical affinity of pollen harvested by Apis mellifera L. in a semi-arid area from Bahia,Brazil

We analysed the botanical composition of pollen harvested by Apis mellifera L. in the Canudos Biological Station, Bahia, Brazil, and the influence of climatic factors on pollen sample composition was assessed. Forty-six pollen types were identified belonging to species occurring in the study area. The family Leguminosae was of significant importance amongst the samples, represented by ten pollen types. Diodia radula, Rhaphiodon echinus, and Mimosa misera pollen types occurred most constantly among the samples. We observed that isolated pollen class characterises samples analysed. It was also observed that pollen type richness is directly linked to rainfall, reflecting the strong influence of this climatic parameter on flowering intensity, and thus on the ability of the bees to obtain food resources.     

Air and surface soil samples – two different pairs of shoes? Comparing the pollen spectrum on different days of the pollen season

The pollen spectra of air and surface soil samples from a rooftop (at 14 m) and from ground level (at 1.6 m) in the suburbs of Vienna (Austria) were compared. Two soil samples and two air samples were taken on four different days to account for possible differences: in winter when no pollination occurred (reference day), in spring during the main flowering of Betula (birch day), in spring/summer during the main flowering of Poaceae (grass day), and in autumn during the main flowering of Ambrosia (ragweed day). Thirty-five different pollen types were used to describe the pollen spectra. Frequencies of certain pollen types reflect a seasonal impact on both the surface soil and air samples and show a similarity between air and soil samples on most of the days. However, the seasonal impact is higher in the air samples and shows a high consistency for ground and rooftop level. Kendall’s tau correlation coefficients further substantiate the similarities of the samples especially for the pollen season days. Exceptions include the winter day when pollination was low and the air samples recorded nearly no pollen at all, and the ragweed day when Ambrosia pollen was abundant in three of four samples but not in the ground surface soil sample. Thus, (1) air and surface pollen samples record similar signals during the pollen season but not during the ragweed and winter season and (2) air and surface pollen samples show the impact of local vegetation also in pollen traps located at different heights.