Systematic analysis of multigene predictors in gastric cancer exploiting gene expression signature

Gastric cancer (GC) is the second most common cause of cancer death worldwide but could be more curable if diagnosed at an earlier stage. At present, the capability to predict the efficaciousness of molecular diagnosis for GC for each patient remains elusive. The purpose of this study was to identify tumor biomarkers through systems analysis of multigene predictors exploiting the available data resource. In this study, we investigated the top 10% overexpressed genes in GC from five data sets of the Oncomine platform, with 265 GC samples versus 174 normal gastric mucosa samples. Sixteen candidate genes were identified as predictors of GC, of which 14 genes were verified through the comparison of expression levels in specimens from normal (chronic gastritis, 21 samples) and GC groups (38 samples). In addition, unique molecular portraits of diffuse adenocarcinoma (DA), intestinal adenocarcinoma (IA), and mixed adenocarcinoma (MA) were studied through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, where DA showed higher extracellular matrix alteration while IA and MA showed higher cell-cycle alteration than other types. We also found that the elevated expressions of genes during GC progression were independent of gene mutations, and high core-binding factor subunit β expression is correlated with a high overall survival rate in GC patients. Our research may provide an efficient clinical diagnosis of GC at an early stage with high accuracy and thus help improve the overall survival rate through early therapeutic interventions.     

Effect of long-term NPK application on secondary and micro nutrient contents ofCoffea canephora Pierre

Summary The Ca, Mg, S, Mn and Cu contents in leaves ofCoffea canephora trees selected in 64 plots under a 4×4×2 NPK trial were determined after seven years of fertilizer application. It was observed that NPK applications increased Mn uptake, P application increased the uptake of Cu, Ca and S while application of N and K did not enhance the uptake of Cu, Mg, Ca and S. It was shown that as a result of NPK applications, Ca and Mg had become deficient in coffee leaves, which corroborates earlier findings based on soil analysis.     

Serum metabonomics study of pregnant women with gestational diabetes mellitus based on LC-MS

ObjectiveThrough metabolomics method, the objective of the paper is to differentially screen serum metabolites of GDM patients and healthy pregnant women, to explore potential biomarkers of GDM and analyze related pathways, and to explain the potential mechanism and biological significance of GDM.MethodsThe serum samples from 30 GDM patients and 30 healthy pregnant women were selected to conduct non-targeted metabolomics study by liquid chromatography-mass spectrometry. The differential metabolites between the two groups were searched and the metabolic pathway was analyzed by KEGG database.ResultsMultivariate statistical analysis found that serum metabolism in GDM patients was different significantly from healthy pregnant women, 36 differential metabolites and corresponding metabolic pathways were identified in serum, which involved several metabolic ways like, fatty acid metabolism, butyric acid metabolism, bile secretion, and amino acid metabolism.ConclusionThe discovery of these biomarkers provided a new theoretical basis and experimental basis for further study of the early diagnosis and pathogenesis of GDM. At the same time, LC-MS-based serum metabolomics methods also showed great application values in disease diagnosis and mechanism research.     

Validation of density–elasticity relationships for finite element modeling of human pelvic bone by modal analysis

In total hip arthroplasty and particularly in revision surgery, computer assisted pre-operative prediction of the best possible anchorage strategy for implant fixation would be a great help to the surgeon. Computer simulation relies on validated numerical models. In the current study, three density–elasticity relationships (No. 1–3) from the literature for inhomogeneous material parameter assignment from CT data in automated finite element (FE) modeling of long bones were evaluated for their suitability for FE modeling of human pelvic bone. Numerical modal analysis was conducted on 10 FE models of hemipelvic bone specimens and compared to the gold standard provided by experimental modal analysis results from a previous in-vitro study on the same specimens. Overall, calculated resonance frequencies came out lower than measured values. Magnitude of mean relative deviation of numerical resonance frequencies with regard to measured values is lowest for the density–elasticity relationship No. 3 (−15.9%) and considerably higher for both density–elasticity relationships No. 1 (−41.1%) and No. 2 (−45.0%). Mean MAC values over all specimens amount to 77.8% (No. 1), 78.5% (No. 2), and 83.0% (No. 3). MAC results show, that mode shapes are only slightly influenced by material distribution. Calculated resonance frequencies are generally lower than measured values, which indicates, that numerical models lack stiffness. Even when using the best suited (No. 3) out of three investigated density–elasticity relationships, in FE modeling of pelvic bone a considerable underestimation of model stiffness has to be taken into account.     

Quantifying light-dependent circadian disruption in humans and animal models

Although circadian disruption is an accepted term, little has been done to develop methods to quantify the degree of disruption or entrainment individual organisms actually exhibit in the field. A variety of behavioral, physiological and hormonal responses vary in amplitude over a 24-h period and the degree to which these circadian rhythms are synchronized to the daily light–dark cycle can be quantified with a technique known as phasor analysis. Several studies have been carried out using phasor analysis in an attempt to measure circadian disruption exhibited by animals and by humans. To perform these studies, species-specific light measurement and light delivery technologies had to be developed based upon a fundamental understanding of circadian phototransduction mechanisms in the different species. When both nocturnal rodents and diurnal humans, experienced different species-specific light–dark shift schedules, they showed, based upon phasor analysis of the light–dark and activity–rest patterns, similar levels of light-dependent circadian disruption. Indeed, both rodents and humans show monotonically increasing and quantitatively similar levels of light-dependent circadian disruption with increasing shift-nights per week. Thus, phasor analysis provides a method for quantifying circadian disruption in the field and in the laboratory as well as a bridge between ecological measurements of circadian entrainment in humans and parametric studies of circadian disruption in animal models, including nocturnal rodents.     

On the Information Matrix of Exponential Mixture Models with Long-term Survivors

The aim of this paper is to study the properties of the asymptotic variances of the maximum likelihood estimators of the parameters of the exponential mixture model with long-term survivors for randomly censored data. In addition, we study the asymptotic relative efficiency of these estimators versus those which would be obtained with complete follow-up. It is shown that fixed censoring at time T produces higher precision as well as higher asymptotic relative efficiency than those obtainable under uniform and uniform-exponential censoring distributions over (0, T). The results are useful in planning the size and duration of survival experiments with long-term survivors under random censoring schemes.     

Disorders of the Menstrual Cycle in Elite Female Ice Hockey Players and Figure Skaters

The purpose of this study was to assess and compare the incidence of delayed menarche and menstrual dysfunction among elite ice hockey players and figure skaters. Forty-three ice hockey players (23.5 ± 4.8 years, 68.2 ± 1.2 kg, 1.68 ± 0.01 m) and 39 figure skaters (17.5 ± 3.4 years, 53.7 ± 5.8 kg, 1.64 ± 0.05 m) completed a self-administered questionnaire on their menstrual status and history, training regimens and lifestyle. Age at menarche did not differ significantly between ice hockey players (13.3 ± 1.3 years) and figure skaters (13.7 ± 1.4 years). Menarche was unrelated to nationality, vigorous training premenarche or age at which the athlete began her sport, but was correlated with the age at menarche of the athletes’ mothers (r = 0.39, p < 0.05). Hormonal contraceptives were used by 35% of ice hockey players and 15% of the figure skaters. Amenorrhea and oligomenorrhea were experienced by 7.1% and 38.7% of postmenarcheal, ice hockey players and figure skaters respectively not using hormonal contraceptives. Menstrual dysfunction was associated with both age and age at menarche in the ice hockey players only. Training factors, and psychological pressure were perceived by the athletes to contribute to menstrual dysfunction. A greater training volume, younger age at commencing sport, lower body mass, greater subjective body image pressure and younger biological and gynaecological age were reported among the figure skaters, and were proposed to explain the higher incidence of menstrual dysfunction among the figure skaters compared with the ice hockey players. Figure skaters appear at increased risk of amenorrhea and oligomenorrhea compared with ice hockey players, which may be linked to training and physical characteristics of the sports.     

Differentiation of subspecies and sexes of Beringian Dunlins using morphometric measures

Five subspecies of Dunlins (Calidris alpina) that breed in Beringia are potentially sympatric during the non‐breeding season. Studying their ecology during this period requires techniques to distinguish individuals by subspecies. Our objectives were to determine (1) if five morphometric measures (body mass, culmen, head, tarsus, and wing chord) differed between sexes and among subspecies (C. a. actites, arcticola, kistchinski, pacifica, and sakhalina), and (2) if these differences were sufficient to allow for correct classification of individuals using equations derived from discriminant function analyses. We conducted analyses using morphometric data from 10 Dunlin populations breeding in northern Russia and Alaska, USA. Univariate tests revealed significant differences between sexes in most morphometric traits of all subspecies, and discriminant function equations predicted the sex of individuals with an accuracy of 83–100% for each subspecies. We provide equations to determine sex and subspecies of individuals in mixed subspecies groups, including the (1) Western Alaska group of arcticola and pacifica (known to stage together in western Alaska) and (2) East Asia group of arcticola, actites, kistchinski, and sakhalina (known to winter together in East Asia). Equations that predict the sex of individuals in mixed groups had classification accuracies between 75% and 87%, yielding reliable classification equations. We also provide equations that predict the subspecies of individuals with an accuracy of 22–96% for different mixed subspecies groups. When the sex of individuals can be predetermined, the accuracy of these equations is increased substantially. Investigators are cautioned to consider limitations due to age and feather wear when using these equations during the non‐breeding season. These equations will allow determination of sexual and subspecies segregation in non‐breeding areas, allowing implementation of taxonomic‐specific conservation actions.