Rectal temperature,distal sweat rate,and forearm blood flow following mild exercise at two phases of the circadian cycle

Changes in rectal temperature during mild exercise in the middle of the rising (11:00 h) and falling (23:00 h) phases of the circadian rhythm of resting core temperature have been compared. Seven healthy males were studied at rest, while exercising on a cycle ergometer (60 min at 80 W), and during the first 30 min of recovery. Rectal temperature, forearm blood flow, and forearm sweat rate were measured at 1 min intervals throughout. During exercise, there were significant time‐of‐day differences in the profiles of all three variables, and in the thresholds for increases in forearm blood flow and sweating. Forearm blood flow and sweat rate were recruited more rapidly and to a greater extent with evening exercise, and rectal temperature rose less. Analysis of covariance, with rectal temperature as the covariate, indicated the associations between it and forearm blood flow or sweating were significantly different (p<0.05) between the two times of day. There were also significant (p<0.05) time‐of‐day effects for forearm blood flow and sweating that were independent of rectal temperature. During recovery, rectal temperature fell more quickly in the late evening than late morning. Forearm blood flow and sweating also showed time‐of‐day differences, but these did not co‐vary with rectal temperature. Control of rectal temperature during exercise and recovery appears to be more effective in the late evening than late morning, and differences in forearm blood flow and sweating, as well as factors independent of these two variables, contribute to this difference. The results support our “heat‐gain/heat‐loss modes” hypothesis.     

Fractional Plans to Estimate Main Effects and Two Factor Interactions Inclusive of a Specific Factor

Balanced incomplete block designs are used to construct non‐geometric 2ⁿ fractional factorial plans to estimate all n main effects and n – 1, 2 factor interactions with a specific factor included in each interaction. When the balanced incomplete block design is of Family (A), the resulting fractional factorial plan has the same number of runs as a fold‐over Hadamard matrix giving same variances for the estimates; however, some new designs are shown to be non‐isomorphic to the fold‐over Hadamard matrix plans.     

Linear Contrasts in Experimental Design with Non‐Identical Error Distributions

Estimation of linear contrasts in experimental design, and testing their assumed values, is considered when the error distributions from block to block are not necessarily identical. The normal‐theory solutions are shown to have low efficiencies as compared to the solutions presented here.     

Reduced rank hazard regression with fixed and time‐varying effects of the covariates

Modelling survival data from long‐term follow‐up studies presents challenges. The commonly used proportional hazards model should be extended to account for dynamic behaviour of the effects of fixed covariates. This work illustrates the use of reduced rank models in survival data, where some of the covariate effects are allowed to behave dynamically in time and some as fixed. Time‐varying effects of the covariates can be fitted by using interactions of the fixed covariates with flexible transformations of time based on b‐splines. To avoid overfitting, a reduced rank model will restrict the number of parameters, resulting in a more sensible fit to the data. This work presents the basic theory and the algorithm to fit such models. An application to breast cancer data is used for illustration of the suggested methods.     

PCR of Immobilized DNA Molecules Isolated from Human Blood Cells by a Non‐Enzymatic Method

Abstract

DNA molecules suitable for amplification by Polymerase Chain Reaction were obtained by immobilizing whole blood or isolated leukocytes and incubating the immobilized cells for one hour with the known non‐enzymatic solution described for preparing intact DNA molecules for PFGE. Cell immobilization was done in agarose gels and punches of 1.2 mm of diameter had the amount of DNA needed for amplifying chromosomal and mitochondrial sequences, many times. The approach was successfully used in preparing DNA molecules from multiple samples in flat‐bottom 96‐well ELISA plates. The procedure is simple and does not demand special conditions for sample transportation or conservation; thus, it should be useful to collect and process samples under field conditions in epidemiological studies.     

Using proteomics to discover novel biomarkers for fatty liver development and response to CB1R antagonist treatment in an obese mouse model

Over activity of cannabinoid receptor type 1 (CB1R) plays a key role in increasing the incidence of obesity‐induced non‐alcoholic fatty liver disease. Tissue proteome analysis has been applied to investigate the bioinformatics regarding the mode of action and therapeutic mechanism. The aim of this study was to explore the potential pathways altered with CB1R in obesity‐induced fatty liver. Male C57BL/6 mice were fed either a standard chow diet (STD) or a high‐fat diet (HFD) with or without 1‐week treatment of CB1R inverse agonist AM251 at 5 mg/kg. Then, liver tissues were harvested for 2DE analysis and protein profiles were identified by using MALDI‐MS. Results showed that eight of significantly altered protein spots at the level of changes > twofold were overlapped among the three groups, naming major urinary protein 1, ATP synthase subunit β, glucosamine‐fructose‐6‐phosphate aminotransferase 1, zine finger protein 2, s‐adenosylmethionine synthase isoform type‐1, isocitrate dehydrogenase subunit α, epoxide hydrolase 2 and 60S acidic ribosomal protein P0. These identified proteins were involved in glucose/lipid metabolic process, xenobiotic metabolic system, and ATP synthesized process in mitochondria. Based on the findings, we speculated that CB1R blockade might exert its anti‐metabolic disorder effect via improvement of mitochondrial function in hepatic steatosis in HFD condition.     

Progress in plasmodial differentiation improves regularity of oscillating contractions in Physarum polycephalum

Based on the knowledge about subcellular morphogenetic processes in the acellular slime mold Physarum polycephalum, we hypothesized that during differentiation of undifferentiated endoplasm to the highly differentiated complex structure of the contractile apparatus of this organism, the regularity of oscillating contractions must improve. We measured the endogenous contraction automaticity starting from the de novo generation within minutes after sampling small portions of undifferentiated endoplasm. The standard deviation of the normalized period duration of these samples was compared to the respective values of radial contractions of differentiated protoplasmic plasmodial strands. The mean normalized standard deviation in endoplasmic drops was 28.3+/-12.2%. Respective values in protoplasmic strands were 10.0+/-3.7%. The difference between the experimental groups was highly significant (p<0.0001). We interpret the verification of our hypothesis as an indication that the very regular oscillating contractions in fully differentiated stages of Physarum require the complex structure of the sophisticated contractile apparatus, represented by the circular plasmalemma invagination system of protoplasmic strands, while the regularity is lower in stages, where the differentiation is still in progress. We believe that this is due to deficits in coordination capabilities, which need a directional and spatially oriented protoplasmic streaming as a precondition.     

An 'unconditional-like' structure for the conditional estimator of odds ratio from 2 x 2 tables

In the estimation of the odds ratio (OR), the conditional maximum-likelihood estimate (cMLE) is preferred to the more readily computed unconditional one (uMLE). However, the exact cMLE does not have a closed form to help divine it from the uMLE or to understand in what circumstances the difference between the two is appreciable. Here, the cMLE is shown to have the same 'ratio of cross-products' structure as its unconditional counterpart, but with two of the cell frequencies augmented, so as to shrink the unconditional estimator towards unity. The augmentation involves a factor, similar to the finite population correction, derived from the minimum of the marginal totals.     

miR‐149 controls non‐alcoholic fatty liver by targeting FGF‐21

Non‐alcoholic fatty liver disease (NAFLD), a lipid metabolism disorder characterized by the accumulation of intrahepatic fat, has emerged as a global public health problem. However, its underlying molecular mechanism remains unclear. We previously have found that miR‐149 was elevated in NAFLD induced by high‐fat diet mice model, whereas decreased by a 16‐week running programme. Here, we reported that miR‐149 was increased in HepG2 cells treated with long‐chain fatty acid (FFA). In addition, miR‐149 was able to promote lipogenesis in HepG2 cells in the absence of FFA treatment. Moreover, inhibition of miR‐149 was capable of inhibiting lipogenesis in HepG2 cells in the presence of FFA treatment. Meanwhile, fibroblast growth factor‐21 (FGF‐21) was identified as a target gene of miR‐149, which was demonstrated by the fact that miR‐149 could negatively regulate the protein expression level of FGF‐21, and FGF‐21 was also responsible for the effect of miR‐149 inhibitor in decreasing lipogenesis in HepG2 cells in the presence of FFA treatment. These data implicate that miR‐149 might be a novel therapeutic target for NAFLD.     

Non-homogeneous Markov process models with informative observations with an application to Alzheimer's disease

Identifying risk factors for transition rates among normal cognition, mildly cognitive impairment, dementia and death in an Alzheimer's disease study is very important. It is known that transition rates among these states are strongly time dependent. While Markov process models are often used to describe these disease progressions, the literature mainly focuses on time homogeneous processes, and limited tools are available for dealing with non-homogeneity. Further, patients may choose when they want to visit the clinics, which creates informative observations. In this paper, we develop methods to deal with non-homogeneous Markov processes through time scale transformation when observation times are pre-planned with some observations missing. Maximum likelihood estimation via the EM algorithm is derived for parameter estimation. Simulation studies demonstrate that the proposed method works well under a variety of situations. An application to the Alzheimer's disease study identifies that there is a significant increase in transition rates as a function of time. Furthermore, our models reveal that the non-ignorable missing mechanism is perhaps reasonable.     

Estimation of distribution function in bivariate competing risk models

We consider lifetime data involving pairs of study individuals with more than one possible cause of failure for each individual. Non-parametric estimation of cause-specific distribution functions is considered under independent censoring. Properties of the estimators are discussed and an illustration of their application is given.     

Identification of metastasis-associated proteins by proteomic analysis and functional exploration of interleukin-18 in metastasis

Very little is currently known about mechanisms underlying cancer metastasis. In the present study, metastasis-associated proteomes were separated and identified by comparative proteomic analysis, and the metastasis-related function of candidate protein interleukin-18 (IL-18) was further elucidated. First, a pair of highly and poorly metastatic sublines (termed PLA801D and PLA801C, respectively), originating from the same parental PLA801 cell line, was identified by spontaneous tumorigenicity and metastasis in vivo and characterized by metastatic phenotypes analysis in vitro. Subsequently, a proteomic approach was used to compare the protein expression profiles between PLA801C and PLA801D sublines. Eleven proteins were identified and further verified by one-dimensional Western blotting, Northern blot and/or semiquantitative reverse transciptase polymerase chain reaction analysis. Compared with those in poorly metastatic PLA801C subline, cytokeratin 18, tissue transglutaminase, Rho GDP-dissociation inhibitor 1, tropomyosin, fibroblast type, IL-18 and annexin I were significantly up-regulated, while protein disulfide isomerase, heat shock protein 60, peroxiredoxin 1, chlorine intracellular channel protein 1 (CLI1) and creatine kinase, B chain were significantly down-regulated in the highly metastatic PLA801D subline. Intriguingly, all the identified candidate proteins except for CLI1 have been shown to be somehow associated with distinct aspects of tumor metastasis such as cell growth, motility, invasion, adhesion, apoptosis and tumor immunity, etc. Considering that IL-18 was present in highly metastatic PLA801D but absent in poorly metastatic PLA801C, the association of IL-18 with metastasis was further elucidated by introducing IL-18 sense/IL-18 antisense into PLA801C/PLA801D sublines simultaneously. The results demonstrated that ectopically expressed IL-18 promoted cell motility in vitro and down-regulated E-cadherin expression of PLA801C transfectants, while IL-18 antisense remarkably decreased cell invasion potency in vitro and notably increased E-cadherin expression of PLA801D transfectants, indicating that IL-18 might play a role in metastasis by inhibiting E-cadherin expression.     

Trace fossils of animal‐plant interactions and “pseudointeractions” from maletín (Bohemian cretaceous basin,Czech Republic)

Old collections of the Upper Cretaceous flora at Maletín yield examples of trace fossils of plant‐arthropod interactions, comparable with recent insect galls. Grooves and ridges, often preserved on leaves at this locality, are (in contradiction to several previous authors) interpreted as traces of burrowing organisms, which originated in soft sediment adjacent to the plant remains lying on a lake floor or buried in the substrate. The leaves functioned in the sediment at the time of burrowing and/or during compaction of the substrate as distinctive laminar bodies with specific physical characteristics and therefore they enabled the preservation of some aspects of ichnofabric otherwise invisible in the surrounding strata.     

A chromaticity‐based technique for estimation of above‐ground plant biomass

Abstract. This paper presents a new and simple technique to derive quantitative estimates of green or dry biomass using colour information from digital pictures. This pixel‐counting technique is based on the association of particular plant material with a representative region on a two‐dimensional colour space, and applies to cases of non‐overlapping canopies. The efficacy of the method is demonstrated using sets of samples obtained from both field and laboratory studies. It is shown that application of the proposed approach results in a highly linear relationship between pixel count and foliar area for both green and non‐green material [r= 0.99 (p < 0.001)]. Analysis of images from a short‐grass steppe shows a high correlation between pixel count and measured values of green biomass [r= 0.95 (p < 0.001)]. The method outlined here allows for a substantial improvement in the speed of sample evaluation to estimate biomass both in the field and in the laboratory. It also provides a non‐destructive alternative to monitor plant cover and biomass in open canopies.     

Estimation of the ROC Curve under Verification Bias

The ROC (receiver operating characteristic) curve is the most commonly used statistical tool for describing the discriminatory accuracy of a diagnostic test. Classical estimation of the ROC curve relies on data from a simple random sample from the target population. In practice, estimation is often complicated due to not all subjects undergoing a definitive assessment of disease status (verification). Estimation of the ROC curve based on data only from subjects with verified disease status may be badly biased. In this work we investigate the properties of the doubly robust (DR) method for estimating the ROC curve under verification bias originally developed by Rotnitzky, Faraggi and Schisterman (2006) for estimating the area under the ROC curve. The DR method can be applied for continuous scaled tests and allows for a non‐ignorable process of selection to verification. We develop the estimator's asymptotic distribution and examine its finite sample properties via a simulation study. We exemplify the DR procedure for estimation of ROC curves with data collected on patients undergoing electron beam computer tomography, a diagnostic test for calcification of the arteries.     

Depletion of abundant proteins from non-human primate serum for biomarker studies

Non-human primates are an important biomedical research model organism and offer great promise for serum biomarker proteomic studies. However, potential obstacles to these studies include affinity serum depletion methods based on human antigens, depletion methods altering quantitation, and incomplete non-human primate genome sequences for protein identification. In the present study, high-abundance protein removal from monkey serum using a human multiple affinity removal system (MARS) was shown to be specific and did not alter quantitation. Depleted serum also demonstrated greater sensitivity for previously masked, lower-abundance proteins.     

Statistical surveillance of epidemics: peak detection of influenza in Sweden

A statistical surveillance system gives a signal as soon as data give enough evidence of an important event. We consider on-line surveillance systems for detecting changes in influenza incidence. One important feature of the influenza cycle is the start of the influenza season, and another one is the change to a decline (the peak). In this report we discuss statistical methods for on-line peak detection. One motive for doing this is the need for health resource planning. Surveillance systems were adapted for Swedish data on laboratory verified diagnoses of influenza. In Sweden, the parameters of the influenza cycles vary too much from year to year for parametric methods to be useful. We suggest a non-parametric method based on the monotonicity properties of the increase and decline around a peak. A Monte Carlo study indicated that this method has useful stochastic properties. The method was applied to Swedish data on laboratory verified diagnoses of influenza for seven periods.