Limited sampling strategies for monitoring tacrolimus in paediatric liver transplant recipients

Ce travail de recherche a été réalisé dans le laboratoire de pharmacologie clinique, au Centre Hospitalier Universitaire Sainte-Justine, à Montréal. C'est une étude rétrospective basée sur le suivi thérapeutique du Tacrolimus prescrit chez les enfants après transplantation hépatique. Ce suivi est nécessaire car le Tacrolimus possède une importante variabilité pharmacocinétique inter et intra-individuelle ainsi qu'un index thérapeutique très étroit. Actuellement, l'individualisation des doses prescrites est basée sur la mesure de la concentration de base - du médicament dans le sang (C0), mais des études récentes montrent que cette mesure ne reflète pas précisément l'exposition du Tacrolimus dans l'organisme chez les enfants. Le meilleur reflet de cette exposition est la mesure de l'aire sous la courbe (AUC). Cependant, cette dernière implique la mesure de multiples concentrations tout au long de l'intervalle entre 2 doses de médicament (Tacrolimus: 12 heures) ce qui est long, cher et impraticable en ambulatoire. De nouvelles méthodes utilisant un nombre limité de prélèvements ont donc été développées pour prédire au mieux cette AUC. Ce sont les "Limited sampling strategies" ou LSS. La plupart de ces LSS pour le Tacrolimus ont été développées et validées chez des patients transplantés adultes et leur application directe chez les transplantés pédiatriques n'est pas possible en raison de différences importantes au niveau des paramètres pharmacocinétiques du médicament entre ces deux populations. Aussi, le but de ce travail était de développer et valider, pour la première fois, des LSS chez les enfants transplantés hépatiques. Pour cela, une analyse de 36 profils pharmacocinétiques de 28 patients transplantés hépatiques âgés de 0.4- 18.5 ans a été effectuée. Tous les profils ont été réalisés au Centre Hospitalier Universitaire Sainte-Justine entre janvier 2007 et janvier 2009. Les LSS comportant au maximum 4 mesures de concentration ont été développées en utilisant une analyse de régression multiple. Parmi tous les modèles obtenus, cinq ont été sélectionnés sur la base de critères précis puis validés selon la méthode décrite par Sheiner et Beal.¦Les résultats montrent que ces cinq modèles peuvent prédire l'AUC du Tacrolimus avec une précision cliniquement acceptable de ± 15% alors que la C0 présente la plus faible corrélation avec l'AUC.¦En conclusion, cette étude confirme que la C0 ne permet pas de prédire de manière efficace l'exposition du Tacrolimus dans l'organisme dans notre population de patients pédiatriques contrairement aux LSS analysées qui offrent une méthode pratique et fiable. Par ailleurs, en permettant d'obtenir une estimation précise et simplifiée de l'AUC complète du Tacrolimus chez les patients, ces LSS ouvrent la porte à de futures études prospectives visant à mieux définir l'AUC cible du médicament et à déterminer si le suivi basé sur la mesure de l'AUC est plus efficace et plus sûr que celui basé sur la mesure de la C0.

Interpolating and sampling sequences in finite Riemann surfaces

We provide a description of the interpolating and sampling sequences on a space of holomorphic functions on a finite Riemann surface, where a uniform growth restriction is imposed on the holomorphic functions.

Gesture sampling for instrumental sound synthesis: violin bowing as a case study

This paper presents a framework in which samples of bowing gesture parameters are retrieved and concatenated from a database of violin performances by attending to an annotated input score. Resulting bowing parameter signals are then used to synthesize sound by means of both a digital waveguide violin physical model, and an spectral-domainadditive synthesizer.

Long-distance wolf recolonization of France and Switzerland inferred from non-invasive genetic sampling over a period of 10 years

In the early 1900s, the wolf (Canis lupus) was extirpated from France and Switzerland. There is growing evidence that the species is presently recolonizing these countries in the western Alps. By sequencing the mitochondrial DNA (mtDNA) control region of various samples mainly collected in the field (scats, hairs, regurgitates, blood or tissue; n = 292), we could (1) develop a non-invasive method enabling the unambiguous attribution of these samples to wolf, fox (Vulpes vulpes) or dog (Canis familiaris), among others; (2) demonstrate that Italian, French and Swiss wolves share the same mtDNA haplotype, a haplotype that has never been found in any other wolf population world-wide. Combined together, field and genetic data collected over 10 years corroborate the scenario of a natural expansion of wolves from the Italian source population. Furthermore, such a genetic approach is of conservation significance, since it has important consequences for management decisions. This first long-term report using non-invasive sampling demonstrates that long-distance dispersers are common, supporting the hypothesis that individuals may often attempt to colonize far from their native pack, even in the absence of suitable corridors across habitats characterized by intense human activities.

Using niche-based models to improve the sampling of rare species

Because data on rare species usually are sparse, it is important to have efficient ways to sample additional data. Traditional sampling approaches are of limited value for rare species because a very large proportion of randomly chosen sampling sites are unlikely to shelter the species. For these species, spatial predictions from niche-based distribution models can be used to stratify the sampling and increase sampling efficiency. New data sampled are then used to improve the initial model. Applying this approach repeatedly is an adaptive process that may allow increasing the number of new occurrences found. We illustrate the approach with a case study of a rare and endangered plant species in Switzerland and a simulation experiment. Our field survey confirmed that the method helps in the discovery of new populations of the target species in remote areas where the predicted habitat suitability is high. In our simulations the model-based approach provided a significant improvement (by a factor of 1.8 to 4 times, depending on the measure) over simple random sampling. In terms of cost this approach may save up to 70% of the time spent in the field.

The underestimation of compliance to direct help requests explained by adaptive sampling

Helping behavior is any intentional behavior that benefits another living being or group (Hogg & Vaughan, 2010). People tend to underestimate the probability that others will comply with their direct requests for help (Flynn & Lake, 2008). This implies that when they need help, they will assess the probability of getting it (De Paulo, 1982, cited in Flynn & Lake, 2008) and then they will tend to estimate one that is actually lower than the real chance, so they may not even consider worth asking for it. Existing explanations for this phenomenon attribute it to a mistaken cost computation by the help seeker, who will emphasize the instrumental cost of “saying yes”, ignoring that the potential helper also needs to take into account the social cost of saying “no”. And the truth is that, especially in face-to-face interactions, the discomfort caused by refusing to help can be very high. In short, help seekers tend to fail to realize that it might be more costly to refuse to comply with a help request rather than accepting. A similar effect has been observed when estimating trustworthiness of people. Fetchenhauer and Dunning (2010) showed that people also tend to underestimate it. This bias is reduced when, instead of asymmetric feedback (getting feedback only when deciding to trust the other person), symmetric feedback (always given) was provided. This cause could as well be applicable to help seeking as people only receive feedback when they actually make their request but not otherwise. Fazio, Shook, and Eiser (2004) studied something that could be reinforcing these outcomes: Learning asymmetries. By means of a computer game called BeanFest, they showed that people learn better about negatively valenced objects (beans in this case) than about positively valenced ones. This learning asymmetry esteemed from “information gain being contingent on approach behavior” (p. 293), which could be identified with what Fetchenhauer and Dunning mention as ‘asymmetric feedback’, and hence also with help requests. Fazio et al. also found a generalization asymmetry in favor of negative attitudes versus positive ones. They attributed it to a negativity bias that “weights resemblance to a known negative more heavily than resemblance to a positive” (p. 300). Applied to help seeking scenarios, this would mean that when facing an unknown situation, people would tend to generalize and infer that is more likely that they get a negative rather than a positive outcome from it, so, along with what it was said before, people will be more inclined to think that they will get a “no” when requesting help. Denrell and Le Mens (2011) present a different perspective when trying to explain judgment biases in general. They deviate from the classical inappropriate information processing (depicted among other by Fiske & Taylor, 2007, and Tversky & Kahneman, 1974) and explain this in terms of ‘adaptive sampling’. Adaptive sampling is a sampling mechanism in which the selection of sample items is conditioned by the values of the variable of interest previously observed (Thompson, 2011). Sampling adaptively allows individuals to safeguard themselves from experiences they went through once and turned out to lay negative outcomes. However, it also prevents them from giving a second chance to those experiences to get an updated outcome that could maybe turn into a positive one, a more positive one, or just one that regresses to the mean, whatever direction that implies. That, as Denrell and Le Mens (2011) explained, makes sense: If you go to a restaurant, and you did not like the food, you do not choose that restaurant again. This is what we think could be happening when asking for help: When we get a “no”, we stop asking. And here, we want to provide a complementary explanation for the underestimation of the probability that others comply with our direct help requests based on adaptive sampling. First, we will develop and explain a model that represents the theory. Later on, we will test it empirically by means of experiments, and will elaborate on the analysis of its results.

Biological Sampling and Physical Habitat Assessment Standard Operating Procedure for Iowa Wadeable Streams and Rivers, July 24, 2015

The Iowa Department of Natural Resources uses benthic macroinvertebrate and fish sampling data to assess stream biological condition and the support status of designated aquatic life uses (Wilton 2004; IDNR 2013). Stream physical habitat data assist with the interpretation of biological sampling results by quantifying important physical characteristics that influence a stream’s ability to support a healthy aquatic community (Heitke et al., 2006; Rowe et al. 2009; Sindt et al., 2012). This document describes aquatic community sampling and physical habitat assessment procedures currently followed in the Iowa stream biological assessment program. Standardized biological sampling and physical habitat assessment procedures were first established following a pilot sampling study in 1994 (IDNR 1994a, 1994b). The procedure documents were last updated in 2001 (IDNR 2001a; 2001b). The biological sampling and physical habitat assessment procedures described below are evaluated on a continual basis. Revision of this working document will occur periodically to reflect additional changes.

Community Water Sampling Event

Summary of water monitoring conducted by the City of Bondurant and Bondurant-Farrar school students of sites in and around Bondurant.

Towards a universal sampling protocol for soil biotas in the humid tropics

This paper reviews the methods for the inventory of below-ground biotas in the humid tropics, to document the (hypothesized) loss of soil biodiversity associated with deforestation and agricultural intensification at forest margins. The biotas were grouped into eight categories, each of which corresponded to a major functional group considered important or essential to soil function. An accurate inventory of soil organisms can assist in ecosystem management and help sustain agricultural production. The advantages and disadvantages of transect-based and grid-based sampling methods are discussed, illustrated by published protocols ranging from the original "TSBF transect", through versions developed for the alternatives to Slash-and-Burn Project (ASB) to the final schemes (with variants) adopted by the Conservation and Sustainable Management of Below-ground Biodiversity Project (CSM-BGBD). Consideration is given to the place and importance of replication in below-ground biological sampling and it is argued that the new sampling protocols are inclusive, i.e. designed to sample all eight biotic groups in the same field exercise; spatially scaled, i.e. provide biodiversity data at site, locality, landscape and regional levels, and link the data to land use and land cover; and statistically robust, as shown by a partial randomization of plot locations for sampling.

Health consultation : Sub-Slab Gas and Air Sampling Data Alcoa – Davenport Works CERCLIS No. IAD005270160 Riverdale, Scott County, Iowa (2005)

The U.S. Environmental Protection Agency (EPA), the Alcoa – Davenport Works Facility (Alcoa), and concerned citizens and community leaders of Riverdale, Iowa requested the Iowa Department of Public Health (IDPH) Hazardous Waste Site Health Assessment Program to evaluate the health impacts of exposures to volatile organic vapors detected within residences located immediately to the west of the Alcoa property. This health consultation addresses inhalation exposure to individuals that may have occupied the currently vacant residences in which the air sampling was completed.

Evolutionary and dispersal history of Eurasian house mice Mus musculus clarified by more extensive geographic sampling of mitochondrial DNA.

We examined the sequence variation of mitochondrial DNA control region and cytochrome b gene of the house mouse (Mus musculus sensu lato) drawn from ca. 200 localities, with 286 new samples drawn primarily from previously unsampled portions of their Eurasian distribution and with the objective of further clarifying evolutionary episodes of this species before and after the onset of human-mediated long-distance dispersals. Phylogenetic analysis of the expanded data detected five equally distinct clades, with geographic ranges of northern Eurasia (musculus, MUS), India and Southeast Asia (castaneus, CAS), Nepal (unspecified, NEP), western Europe (domesticus, DOM) and Yemen (gentilulus). Our results confirm previous suggestions of Southwestern Asia as the likely place of origin of M. musculus and the region of Iran, Afghanistan, Pakistan, and northern India, specifically as the ancestral homeland of CAS. The divergence of the subspecies lineages and of internal sublineage differentiation within CAS were estimated to be 0.37-0.47 and 0.14-0.23 million years ago (mya), respectively, assuming a split of M. musculus and Mus spretus at 1.7 mya. Of the four CAS sublineages detected, only one extends to eastern parts of India, Southeast Asia, Indonesia, Philippines, South China, Northeast China, Primorye, Sakhalin and Japan, implying a dramatic range expansion of CAS out of its homeland during an evolutionary short time, perhaps associated with the spread of agricultural practices. Multiple and non-coincident eastward dispersal events of MUS sublineages to distant geographic areas, such as northern China, Russia and Korea, are inferred, with the possibility of several different routes.

Inventory of sparse forest populations using adaptive cluster sampling

Abstract

Prediction of soil orders with high spatial resolution: response of different classifiers to sampling density

The objective of this work was to evaluate sampling density on the prediction accuracy of soil orders, with high spatial resolution, in a viticultural zone of Serra Gaúcha, Southern Brazil. A digital elevation model (DEM), a cartographic base, a conventional soil map, and the Idrisi software were used. Seven predictor variables were calculated and read along with soil classes in randomly distributed points, with sampling densities of 0.5, 1, 1.5, 2, and 4 points per hectare. Data were used to train a decision tree (Gini) and three artificial neural networks: adaptive resonance theory, fuzzy ARTMap; self‑organizing map, SOM; and multi‑layer perceptron, MLP. Estimated maps were compared with the conventional soil map to calculate omission and commission errors, overall accuracy, and quantity and allocation disagreement. The decision tree was less sensitive to sampling density and had the highest accuracy and consistence. The SOM was the less sensitive and most consistent network. The MLP had a critical minimum and showed high inconsistency, whereas fuzzy ARTMap was more sensitive and less accurate. Results indicate that sampling densities used in conventional soil surveys can serve as a reference to predict soil orders in Serra Gaúcha.

Comparison of randomized branch sampling with and without replacement at the first stage

Abstract