Randomised trial of personalised computer based information for cancer patients

ObjectiveTo compare the use and effect of a computer based information system for cancer patients that is personalised using each patient''s medical record with a system providing only general information and with information provided in booklets.DesignRandomised trial with three groups. Data collected at start of radiotherapy, one week later (when information provided), three weeks later, and three months later.Participants525 patients started radical radiotherapy; 438 completed follow up.InterventionsTwo groups were offered information via computer (personalised or general information, or both) with open access to computer thereafter; the third group was offered a selection of information booklets.OutcomesPatients'' views and preferences, use of computer and information, and psychological status; doctors'' perceptions; cost of interventions.ResultsMore patients offered the personalised information said that they had learnt something new, thought the information was relevant, used the computer again, and showed their computer printouts to others. There were no major differences in doctors'' perceptions of patients. More of the general computer group were anxious at three months. With an electronic patient record system, in the long run the personalised information system would cost no more than the general system. Full access to booklets cost twice as much as the general system.ConclusionsPatients preferred computer systems that provided information from their medical records to systems that just provided general information. This has implications for the design and implementation of electronic patient record systems and reliance on general sources of patient information.     

Processing, Disulfide Pattern, and Biological Activity of a Sugar Beet Defensin, AX2, Expressed in Pichia pastoris

AX2 is a 46-amino-acid cysteine-rich peptide isolated from sugar beet leaves infected with the fungus Cercospora beticola (Sacc.). AX2 strongly inhibits the growth of C. beticola and other filamentous fungi, but has little or no effect against bacteria. AX2 is produced in very low amounts in sugar beet leaves, and to study the protein in greater detail with respect to biological function and protein structural analysis, the methylotrophic yeast Pichia pastoris was used for large-scale production. The amino acid sequence, processing of the signal peptide, disulfide bridges, and biological activity of the recombinant protein were determined and compared with that of the authentic AX2. In P. pastoris, the protein was expressed with an additional N-terminal arginine. The disulfide bonding was found to be identical to that of the authentic AX2. However, when tested in in vitro bioassay, the biological activity of the recombinant protein was slightly lower than that measured for the authentic protein. Furthermore, the recombinant protein was significantly more sensitive to Ca²⁺ than the authentic protein. This is most probably due to the extra arginine, since no other differences between the two proteins have been found.     

Decomposition rates and nutrient dynamics of Picea abies needles,twigs and fine roots after stem-only harvesting in eastern and western Norway

Objectives

Afforestation changes soil chemical properties over several decades. In contrast, microbial community structure can be shifted within the first decade and so, the direct effects of tree species can be revealed. The aim of this study was to determine the alteration of soil microbial community composition 10 years after afforestation by trees with contrasting functional traits.

Methods

The study was conducted at the BangorDIVERSE temperate forest experiment. Soil samples were collected under single, two and three species mixtures of alder and birch, beech and oak - early and secondary successional species, respectively, and contiguous agricultural field. Soil was analysed for total carbon (C) and nitrogen (N) contents, and microbial community structure (phospholipid fatty acids (PLFAs) analysis).

Results and conclusions

The total PLFAs content (370–640 nmol g^?1 soil) in forest plots increased for 30 to 110 % compared to the agricultural soil (290 nmol g^?1 soil). In contrast, soil C, N and C/N ratios were altered over 10 years much less - increased only up to 20 % or even decreased (for beech forest).

Afforestation increased bacterial PLFAs by 20–120 %, whereas it had stronger impact on the development of fungal communities (increased by 50–200 %). These effects were proved for all forests, but were more pronounced under the monocultures compared to mixtures. This indicates that species identity has a stronger effect than species diversity. Principal component analysis of PLFAs revealed that under mono and three species mixtures similar microbial communities were formed. In contrast, gram-positive PLFAs and actinomycete PLFAs contributed mainly to differentiation of two species mixtures from other forests. Thus, at the early afforestation stage: i) soil biological properties are altered more than chemical, and ii) tree species identity affects more than species amount on both processes.

     

Local environment and connectivity are the main drivers of diatom species composition and trait variation in a set of tropical reservoirs

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Discrimination of pancreatic cancer and pancreatitis by LC-MS metabolomics

Introduction

Pancreatic ductal adenocarcinoma (PDAC) is the fifth most common cause of cancer-related death in Europe with a 5-year survival rate of <5%. Chronic pancreatitis (CP) is a risk factor for PDAC development, but in the majority of cases malignancy is discovered too late for curative treatment. There is at present no reliable diagnostic marker for PDAC available.

Objectives

The aim of the study was to identify single blood-based metabolites or a panel of metabolites discriminating PDAC and CP using liquid chromatography-mass spectrometry (LC-MS).

Methods

A discovery cohort comprising PDAC (n?=?44) and CP (n?=?23) samples was analyzed by LC-MS followed by univariate (Student’s t test) and multivariate (orthogonal partial least squares-discriminant analysis (OPLS-DA)) statistics. Discriminative metabolite features were subject to raw data examination and identification to ensure high feature quality. Their discriminatory power was then confirmed in an independent validation cohort including PDAC (n?=?20) and CP (n?=?31) samples.

Results

Glycocholic acid, N-palmitoyl glutamic acid and hexanoylcarnitine were identified as single markers discriminating PDAC and CP by univariate analysis. OPLS-DA resulted in a panel of five metabolites including the aforementioned three metabolites as well as phenylacetylglutamine (PAGN) and chenodeoxyglycocholate.

Conclusion

Using LC-MS-based metabolomics we identified three single metabolites and a five-metabolite panel discriminating PDAC and CP in two independent cohorts. Although further study is needed in larger cohorts, the metabolites identified are potentially of use in PDAC diagnostics.

     

Proteomic data analysis workflow for discovery of candidate biomarker peaks predictive of clinical outcome for patients with acute myeloid leukemia

Our goal in this paper is to show an analytical workflow for selecting protein biomarker candidates from SELDI-MS data. The clinical question at issue is to enable prediction of the complete remission (CR) duration for acute myeloid leukemia (AML) patients. This would facilitate disease prognosis and make individual therapy possible. SELDI-mass spectrometry proteomics analyses were performed on blast cell samples collected from AML patients pre-chemotherapy. Although the biobank available included approximately 200 samples, only 58 were available for analysis. The presented workflow includes sample selection, experimental optimization, repeatability estimation, data preprocessing, data fusion, and feature selection. Specific difficulties have been the small number of samples and the skew distribution of the CR duration among the patients. Further, we had to deal with both noisy SELDI-MS data and a diverse patient cohort. This has been handled by sample selection and several methods for data preprocessing and feature detection in the analysis workflow. Four conceptually different methods for peak detection and alignment were considered, as well as two diverse methods for feature selection. The peak detection and alignment methods included the recently developed annotated regions of significance (ARS) method, the SELDI-MS software Ciphergen Express which was regarded as the standard method, segment-wise spectral alignment by a genetic algorithm (PAGA) followed by binning, and, finally, binning of raw data. In the feature selection, the "standard" Mann-Whitney t test was compared with a hierarchical orthogonal partial least-squares (O-PLS) analysis approach. The combined information from all these analyses gave a collection of 21 protein peaks. These were regarded as the most potential and robust biomarker candidates since they were picked out as significant features in several of the models. The chosen peaks will now be our first choice for the continuing work on protein identification and biological validation. The identification will be performed by chromatographic purification and MALDI MS/MS. Thus, we have shown that the use of several data handling methods can improve a protein profiling workflow from experimental optimization to a predictive model. The framework of this methodology should be seen as general and could be used with other one-dimensional spectral omics data than SELDI MS including an adequate number of samples.     

Diatoms: unicellular surrogates for macroalgal community structure in streams?

As wholesale biodiversity assessment is often impractical, the use of surrogates that reflect the assemblage structure and diversity of other taxa has attracted increased attention. We sampled 47 boreal streams for diatoms and macroalgae and examined their assemblage patterns along major environmental gradients. Our main intention was to examine whether diatoms might be useful surrogates for macroalgae in boreal streams. We also assessed whether taxon richness and community composition provided similar insights into the patterns of cross-taxon concordance. According to canonical correspondence analysis, diatom distribution was most strongly related to water pH, conductivity, latitude and longitude, and macroalgal distribution to water pH and iron content, latitude and bed instability. In Mantel’s test, diatoms and macroalgae showed significant cross-taxon concordance. However, there was no significant correlation between taxon richness of the two algal groups, likely reflecting their differing responses to environmental variables. We found evidence that although diatoms and macroalgae are partly controlled by different environmental factors, they are segregated rather similarly along latitude and a few environmental gradients such as water pH and iron content. We conclude that, at least at broad geographical extents and in small streams, diatoms reflect the structure of the macroalgal community and are therefore useful surrogates for cost-effective biomonitoring of algal communities in streams.     

Interactions between mountain birch seedlings from differentiated populations in contrasting environments of subarctic Russia

So far very few experiments have accounted for the combined effect of two phenomena co-occurring in stress gradients: local adaptation to stress and the increase in facilitation with increasing stress (predicted by the stress-gradient hypothesis, SGH). Mountain birch (Betula pubescens subsp. czerepanovii) facilitates conspecific seedlings in subarctic high stress sites and is capable of rapid evolutionary adaptation, being therefore a good model species for a study combining local ecotypes and SGH. A within-species experiment was conducted to test SGH in three stress gradients, detect potential local adaptations between low and high stress populations, and assess their effects on seedling-seedling interactions. Although no evidence for local adaptation was detected, high and low stress populations showed some differentiation, possibly explained by decreasing phenotypic plasticity in high stress conditions and/or neutral evolutionary mechanisms. Weak support for SGH was detected. While facilitation was unaffected by seedling origin, low stress populations showed better competitive ability.     

Full Likelihood Analysis of Genetic Risk with Variable Age at Onset Disease—Combining Population-Based Registry Data and Demographic Information

Background

In genetic studies of rare complex diseases it is common to ascertain familial data from population based registries through all incident cases diagnosed during a pre-defined enrollment period. Such an ascertainment procedure is typically taken into account in the statistical analysis of the familial data by constructing either a retrospective or prospective likelihood expression, which conditions on the ascertainment event. Both of these approaches lead to a substantial loss of valuable data.

Methodology and Findings

Here we consider instead the possibilities provided by a Bayesian approach to risk analysis, which also incorporates the ascertainment procedure and reference information concerning the genetic composition of the target population to the considered statistical model. Furthermore, the proposed Bayesian hierarchical survival model does not require the considered genotype or haplotype effects be expressed as functions of corresponding allelic effects. Our modeling strategy is illustrated by a risk analysis of type 1 diabetes mellitus (T1D) in the Finnish population-based on the HLA-A, HLA-B and DRB1 human leucocyte antigen (HLA) information available for both ascertained sibships and a large number of unrelated individuals from the Finnish bone marrow donor registry. The heterozygous genotype DR3/DR4 at the DRB1 locus was associated with the lowest predictive probability of T1D free survival to the age of 15, the estimate being 0.936 (0.926; 0.945 95% credible interval) compared to the average population T1D free survival probability of 0.995.

Significance

The proposed statistical method can be modified to other population-based family data ascertained from a disease registry provided that the ascertainment process is well documented, and that external information concerning the sizes of birth cohorts and a suitable reference sample are available. We confirm the earlier findings from the same data concerning the HLA-DR3/4 related risks for T1D, and also provide here estimated predictive probabilities of disease free survival as a function of age.