Determining a healthy reference range and factors potentially influencing PRO-C3 – A biomarker of liver fibrosis

Background & AimsProgressive fibrosis has been identified as the major predictor of mortality in patients with non-alcoholic fatty liver disease (NAFLD). Several biomarkers are currently being evaluated for their ability to substitute the liver biopsy as the reference standard. Recent clinical studies in NAFLD/NASH patients support the utility of PRO-C3, a marker of type III collagen formation, as a marker for the degree of fibrosis, disease activity, and effect of treatment. Here we establish the healthy reference range, optimal sample handling conditions for both short- and long-term serum storage, and robustness for the PRO-C3 assay.MethodsPRO-C3 was measured in 269 healthy volunteers and in 222 NAFLD patients. Robustness of the PRO-C3 assay was measured according to Clinical and Laboratory Standards Institute standards and included validation of interference, precision, and reagent stability, whilst sample stability was defined for storage at different temperatures and for 3 freeze-thaw cycles. Fibrosis scoring was based on histological assessments and used as a reference for the diagnostic ability of PRO-C3 to discriminate between patients with different levels of fibrosis.ResultsRobustness of the PRO-C3 analysis validated by interference, precision, and reagent stability was found to be within the predefined acceptance criteria. The healthy reference range was determined to be 6.1–14.7 ng/ml. Levels of PRO-C3 were not affected by sex, age, BMI, or ethnicity. Levels of PRO-C3 were able to identify patients with clinically significant fibrosis and advanced fibrosis (AUC = 0.83 (95% CI [0.77–0.88], p <0.0001), and AUC = 0.79 (95% CI [0.73–0.85], p <0.0001), respectively).ConclusionsThe assay proved to be robust and sample stability was found to comply with hospital sample handling requirements. PRO-C3 measured in samples from patients with NAFLD/NASH was diagnostic for significant and advanced liver fibrosis

Mathematical Modelling as a Proof of Concept for MPNs as a Human Inflammation Model for Cancer Development

<p><b>Left:</b> Typical development in stem cells (top panel A) and mature cells (bottom panel B). Healthy hematopoietic cells (full blue curves) dominate in the early phase where the number of malignant cells (stipulated red curves) are few. The total number of cells is also shown (dotted green curves). When a stem cell mutates without repairing mechanisms, a slowly increasing exponential growth starts. At a certain stage, the malignant cells become dominant, and the healthy hematopoietic cells begin to show a visible decline. Finally, the composition between the cell types results in a takeover by the malignant cells, leading to an exponential decline in hematopoietic cells and ultimately their extinction. The development is driven by an approximately exponential increase in the MPN stem cells, and the development is closely followed by the mature MPN cells. <b>Right:</b> B)The corresponding allele burden (7%, 33% and 67% corresponding to ET, PV, and PMF, respectively) defined as the ratio of MPN mature cells to the total number of mature cells.</p

Towards developing thresholds for waterbirds that take into account turnover

To attain international importance and thus protection as a Ramsar site or as a Special Protection Area (SPA) a wetland site must either “regularly” support at least 20,000 waterbirds or seabirds, or 1% of the individuals of a population of a species or subspecies of waterbird. In most cases, sites have been designated by using the maxima of individual counts. These counts will underestimate volume (i.e. total number) of birds passing through the site if turnover of birds occurs. Using count data, observations of individually marked birds and survival and recruitment mark-recapture models, we present three different methods (V1, V2 & V3) implemented in the StopOver Duration Analysis or SODA program (Choquet & Pradel 2007) for estimating the total volume of birds passing through a site. We use simulated data to determine their performance using both biased and unbiased data. Specifically, we tested whether the estimates of volume were biased where the following parameters varied: proportion of birds marked, daily resighting rate, timing of arrival, proportion of transients in the population, heterogeneity in the resighting rates (i.e. some individuals with a high or low resighting rate), variation in arrival and stopover time and count error. With a relatively simple dataset (single arrival, no biases), the proportion of individuals marked had little effect on the reliability of the resulting volume estimates for both V1 and V3. Estimates of volume from V2 were always overestimated. The major factor that caused a small positive bias in V1 and V3 was the resighting probability. Lower resighting probabilities caused a small positive bias in the volume estimates. Resighting heterogeneity (i.e. some birds more likely to be seen than others) caused a substantial positive bias for all estimators. Transience (i.e. some birds stopping over for shorter time than others) caused no bias in V1 and V3, but a strong negative bias in V2.Transience seemed to reduce the positive bias due to heterogeneity in V1 and V3 when both were present. The use of trap-dependent models (i.e. those that allow individuals to have differential recapture rates) showed some promise for V3 as little bias in the volume estimate was observed when there was a moderate amount of variation in individuals’ resighting rates. V1 & V3 performed well under scenarios of varying arrival and stopover duration as well as where error in the counts was introduced. V2 was consistently biased (see Table 4.1) The V3 method performed well and consistently had the highest precision; it is the method we recommend to use to estimate volume. It is important that goodness of fit tests are used to determine biases in the data and appropriate models are used in Program SODA. Although some biases in the data have little effect on the resulting volume estimates, care must be taken when setting up a study to reduce bias. We present eight different ways of ensuring that bias is reduced during the collection of data. Practical ways to deal with biases are discussed. Recommendations (see section 4.2 for further details) are to: (i) Count at the same time as reading colour rings; (ii) Count at approximately one-third of the length of stay interval, e.g. if the species is thought to stay ten days on a site during passage then count every 5 days; (iii) aim to resight > 30 individuals during every count period, although preferably more; obtain as far as is possible representative samples of the population being studied; (iv) the timing of marking of the study species, the number of sites included, and the timing of counts is discussed

Sulfide invasion in the seagrass Posidonia oceanica at Mediterranean fish farms: Assessment using stable sulfur isotopes

The effect of organic enrichment of sediments on the composition of stable sulfur isotopes (δ34S), sulfide invasion (Fsulfide) and concentrations of total sulfur (TS) and elemental sulfur (S0) in the seagrass Posidonia oceanica was investigated along transects from 3 Mediterranean fish farms in Spain, Italy and Greece. The δ34S decreased and Fsulfide, TS and S0 decreased with distance from the fish farms indicating a higher invasion of sulfide in seagrasses close to the farms. Changes in plant sulfur parameters were linked to sedimentation of organic carbon, sediment organic matter pools and sediment sulfide production (sulfate reduction rates), but relationships were not statistically significant. The most significant changes in seagrass sulfur parameters took place in the roots and rhizomes, whereas leaves showed minor or no changes along the transects and among farms. Roots had the lowest δ34S, indicating that sulfide entered the plants here and moved to the other plant compartments. Significant correlations between S0 and F sulfide suggested that sulfide derivatives were accumulating inside the plant and isotopic analysis confirmed that the δ34S signal of S0 extracted from the plants was similar to the δ34S of sediment sulfide. The mortality of P. oceanica was negatively correlated to δ34S in the plant, indicating higher plant mortality with increasing sulfide invasion. The usability of stable sulfur isotopes as indicators of seagrass sulfide exposure is good, except in situations with high variation in δ34S of the sulfur sources, as observed at the fish farm in Spain. This variation may be adjusted for by calculating Fsulfide. © Inter-Research 2007.Peer Reviewe

Environmental forcing on life history strategies: evidence for multi-trophic level responses at ocean basin scales

Variation in life history traits of organisms is thought to reflect adaptations to environmental forcing occurring from bottom-up and top-down processes. Such variation occurs not only among, but also within species, indicating demographic plasticity in response to environmental conditions. From a broad literature review, we present evidence for ocean basin- and large marine ecosystem-scale variation in intra-specific life history traits, with similar responses occurring among trophic levels from relatively short-lived secondary producers to very long-lived apex predators. Between North Atlantic and North Pacific Ocean basins, for example, species in the Eastern Pacific exhibited either later maturation, lower fecundity, and/or greater annual survival than conspecifics in the Western Atlantic. Parallel variations in life histories among trophic levels also occur in adjacent seas and between eastern vs. western ocean boundaries. For example, zooplankton and seabird species in cooler Barents Sea waters exhibit lower fecundity or greater annual survival than conspecifics in the Northeast Atlantic. Sea turtles exhibit a larger size and a greater reproductive output in the Western Pacific vs. Eastern Pacific. These examples provide evidence for food-web-wide modifications in life history strategies in response to environmental forcing. We hypothesize that such dichotomies result from frequency and amplitude shifts in resource availability over varying temporal and spatial scales. We review data that supports three primary mechanisms by which environmental forcing affects life history strategies: (1) food-web structure; (2) climate variability affecting the quantity and seasonality of primary productivity; (3) bottom-up vs. top-down forcing. These proposed mechanisms provide a framework for comparisons of ecosystem function among oceanic regions (or regimes) and are essential in modeling ecosystem response to climate change, as well as for creating dynamic ecosystem-based marine conservation strategies

Effect of increased sediment sulfide concentrations on the composition of stable sulfur isotopes (d34S) and sulfur accumulation in the seagrasses Zostera marina and Posidonia oceanica

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