868 resultados para selectivity bias


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Cold-water corals form prominent reef ecosystems along ocean margins that depend on suspended resources produced in surface waters. In this study, we investigated food processing of 13C and 15N labelled bacteria and algae by the cold-water coral Lophelia pertusa. Coral respiration, tissue incorporation of C and N and metabolic-derived C incorporation into the skeleton were traced following the additions of different food concentrations (100, 300, 1300 µg C/l) and two ratios of suspended bacterial and algal biomass (1:1, 3:1). Respiration and tissue incorporation by L. pertusa increased markedly following exposure to higher food concentrations. The net growth efficiency of L. pertusa was low (0.08±0.03), which is consistent with their slow growth rates. The contribution of algae and bacteria to total coral assimilation was proportional to the food mixture in the two lowest food concentrations, but algae were preferred over bacteria as food source at the highest food concentration. Similarly, the stoichiometric uptake of C and N was coupled in the low and medium food treatment, but was uncoupled in the high food treatment and indicated a comparatively higher uptake or retention of bacterial carbon as compared to algal nitrogen. We argue that behavioural responses for these small-sized food particles, such as tentacle behaviour, mucus trapping and physiological processing, are more likely to explain the observed food selectivity as compared to physical-mechanical considerations. A comparison of the experimental food conditions to natural organic carbon concentrations above CWC reefs suggests that L. pertusa is well adapted to exploit temporal pulses of high organic matter concentrations in the bottom water caused by internal waves and down-welling events.

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Harmful algal blooms (HABs) are becoming more frequent as climate changes, with tropical species moving northward. Monitoring programs detecting the presence of toxic algae before they bloom are of paramount importance to protect aquatic ecosystems, aquaculture, human health and local economies. Rapid and reliable species identification methods using molecular barcodes coupled to biosensor detection tools have received increasing attention over the past decade as an alternative to the impractical standard microscopic counting-based techniques. This work reports on a PCR amplification-free electrochemical genosensor for the enhanced selective and sensitive detection of RNA from multiple Mediterranean toxic algal species. For a sandwich hybridization (SHA), we designed longer capture and signal probes for more specific target discrimination against a single base-pair mismatch from closely related species and for reproducible signals. We optimized experimental conditions, viz., minimal probe concentration in the SHA on a screen-printed gold electrode and selected the best electrochemical mediator. Probes from 13 Mediterranean dinoflagellate species were tested under optimized conditions and the format further tested for quantification of RNA from environmental samples. We not only enhanced the selectivity and sensitivity of the state-of-the-art toxic algal genosensors but also increased the repertoire of toxic algal biosensors in the Mediterranean, towards an integral and automatic monitoring system.

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Harmful algal blooms (HABs) are becoming more frequent as climate changes, with tropical species moving northward. Monitoring programs detecting the presence of toxic algae before they bloom are of paramount importance to protect aquatic ecosystems, aquaculture, human health and local economies. Rapid and reliable species identification methods using molecular barcodes coupled to biosensor detection tools have received increasing attention over the past decade as an alternative to the impractical standard microscopic counting-based techniques. This work reports on a PCR amplification-free electrochemical genosensor for the enhanced selective and sensitive detection of RNA from multiple Mediterranean toxic algal species. For a sandwich hybridization (SHA), we designed longer capture and signal probes for more specific target discrimination against a single base-pair mismatch from closely related species and for reproducible signals. We optimized experimental conditions, viz., minimal probe concentration in the SHA on a screen-printed gold electrode and selected the best electrochemical mediator. Probes from 13 Mediterranean dinoflagellate species were tested under optimized conditions and the format further tested for quantification of RNA from environmental samples. We not only enhanced the selectivity and sensitivity of the state-of-the-art toxic algal genosensors but also increased the repertoire of toxic algal biosensors in the Mediterranean, towards an integral and automatic monitoring system.

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The measurement of fast changing temperature fluctuations is a challenging problem due to the inherent limited bandwidth of temperature sensors. This results in a measured signal that is a lagged and attenuated version of the input. Compensation can be performed provided an accurate, parameterised sensor model is available. However, to account for the in influence of the measurement environment and changing conditions such as gas velocity, the model must be estimated in-situ. The cross-relation method of blind deconvolution is one approach for in-situ characterisation of sensors. However, a drawback with the method is that it becomes positively biased and unstable at high noise levels. In this paper, the cross-relation method is cast in the discrete-time domain and a bias compensation approach is developed. It is shown that the proposed compensation scheme is robust and yields unbiased estimates with lower estimation variance than the uncompensated version. All results are verified using Monte-Carlo simulations.

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BACKGROUND:
Evidence regarding the association of the built environment with physical activity is influencing policy recommendations that advocate changing the built environment to increase population-level physical activity. However, to date there has been no rigorous appraisal of the quality of the evidence on the effects of changing the built environment. The aim of this review was to conduct a thorough quantitative appraisal of the risk of bias present in those natural experiments with the strongest experimental designs for assessing the causal effects of the built environment on physical activity.

METHODS:
Eligible studies had to evaluate the effects of changing the built environment on physical activity, include at least one measurement before and one measurement of physical activity after changes in the environment, and have at least one intervention site and non-intervention comparison site. Given the large number of systematic reviews in this area, studies were identified from three exemplar systematic reviews; these were published in the past five years and were selected to provide a range of different built environment interventions. The risk of bias in these studies was analysed using the Cochrane Risk of Bias Assessment Tool: for Non-Randomized Studies of Interventions (ACROBAT-NRSI).

RESULTS:
Twelve eligible natural experiments were identified. Risk of bias assessments were conducted for each physical activity outcome from all studies, resulting in a total of fifteen outcomes being analysed. Intervention sites included parks, urban greenways/trails, bicycle lanes, paths, vacant lots, and a senior citizen's centre. All outcomes had an overall critical (n = 12) or serious (n = 3) risk of bias. Domains with the highest risk of bias were confounding (due to inadequate control sites and poor control of confounding variables), measurement of outcomes, and selection of the reported result.

CONCLUSIONS:
The present review focused on the strongest natural experiments conducted to date. Given this, the failure of existing studies to adequately control for potential sources of bias highlights the need for more rigorous research to underpin policy recommendations for changing the built environment to increase physical activity. Suggestions are proposed for how future natural experiments in this area can be improved.

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The measurement of fast changing temperature fluctuations is a challenging problem due to the inherent limited bandwidth of temperature sensors. This results in a measured signal that is a lagged and attenuated version of the input. Compensation can be performed provided an accurate, parameterised sensor model is available. However, to account for the influence of the measurement environment and changing conditions such as gas velocity, the model must be estimated in-situ. The cross-relation method of blind deconvolution is one approach for in-situ characterisation of sensors. However, a drawback with the method is that it becomes positively biased and unstable at high noise levels. In this paper, the cross-relation method is cast in the discrete-time domain and a bias compensation approach is developed. It is shown that the proposed compensation scheme is robust and yields unbiased estimates with lower estimation variance than the uncompensated version. All results are verified using Monte-Carlo simulations.

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In dieser Arbeit werden Exchange-Bias-Dünnschichtsysteme untersucht. Ein Fokus der Arbeit liegt auf der magnetooptischen Aktivität dieser Systeme und im speziellen wie sich diese optimieren lässt. Der zweite Fokus der Arbeit ist die Modellierung dieser Systeme. Aufbauend auf einem polykristallinen Ansatz wird eine neue rotierbare magnetische Anisotropie eingeführt, welche die Relaxationszeiten thermisch instabiler Körner im AF berücksichtigt.

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The current thesis examines memory bias for state anxiety prior to academic achievement situations like writing an exam and giving a speech. The thesis relies on the reconstruction principle, which assumes that memories for past emotions are reconstructed rather than stored permanently and accurately. This makes them prone to memory bias, which is af-fected by several influencing factors. A major aim is to include four important influencing factors simultaneously. Early research on mood and emotional autobiographical memory found evidence for the existence of a propositional associative network (Bower, 1981; Col-lins & Loftus, 1975), leading to mood congruent recall. But empirical findings gave also strong evidence for the existence of mood incongruent recall for one’s own emotions, which was for example linked to mood regulation via mood repair (e.g. Clark & Isen, 1982), which seems to be associated to the personality traits extraversion and neuroticism (Lischetzke & Eid, 2006; Ng & Diener, 2009). Moreover, neuroticism and trait anxiety are related to rumination, which is seen as negative post-event-processing (e.g. Wells & Clark, 1997). Overall, the elapsed time since the emotional event happened should have an impact on recall of emotions. Following the affect infusion model by Robinson and Clore (2002a), the influence of personality on memory bias should increase over time. Therefore, three longitudinal studies were realized, using naturally occurring as well as laboratory settings. The used paradigm was equivalent in all studies. Subjects were asked about their actual state anxiety prior to an academic achievement situation. Directly after the situation, cur-rent mood and recall of former anxiety were assessed. The same procedure was repeated a few weeks later. Personality traits and post-event-processing were also assessed. The results suggest a need to have a differentiated view on predicting memory bias. Study 1 (N = 131) as well as study 3 (N = 53) found evidence for mood incongruent memory in the sense of mood repair and downward regulation as a function of personality. Rumination was found to cause stable overestimation of pre-event anxiety in study 2 (N = 141) as well as in study 3. Although the relevance of the influencing factors changed over time, an increasing relevance of personality could not consistently be observed. The tremendously different effects of the laboratory study 2 indicated that such settings are not appropriate to study current issues. Theoretical and psychotherapeutically relevant conclusions are drawn and several limitations are discussed.

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In late 2014, a series of highly publicized police killings of unarmed Black male civilians in the United States prompted large-scale social turmoil. In the current review, we dissect the psychological antecedents of these killings and explain how the nature of police work may attract officers with distinct characteristics that may make them especially well-primed for negative interactions with Black male civilians. We use media reports to contextualize the precipitating events of the social unrest as we ground our explanations in theory and empirical research from social psychology and industrial and organizational (I/O) psychology. To isolate some of the key mechanisms at play, we disentangle racial bias (e.g., stereotyping processes) from common characteristics of law enforcement agents (e.g., social dominance orientation), while also addressing the interaction between racial bias and policing. By separating the moving parts of the phenomenon, we provide a more fine-grained analysis of the factors that may have contributed to the killings. In doing so, we endeavor to more effectively identify and develop solutions to eradicate excessive use of force during interactions between “Black” (unarmed Black male civilians) and “Blue” (law enforcement).

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Thesis (Master's)--University of Washington, 2016-08

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According to the Declaration of Helsinki, as well as the Statement on Public Disclosure of Clinical Trial Results of the World Health Organization, every researcher has the ethical obligation to publish research results on all trials with human participants in a complete and accurate way within 12 months after the end of the trial.1,2 Nevertheless, for several reasons, not all research results are published in an accurate way in case they are released at all. This phenomenon of publication bias may not only create a false impression on the reliability of clinical research business, but it may also affect the evidence of clinical conclusions about the best treatments, which are mostly based on published data and results.

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Catch effort data on which fisheries management regulations are sometimes based are not available for most lakes in Uganda. However, failure to regulate fishing gears and methods has been a major cause of collapse of fisheries in the country. Fisheries have been damaged by destructive and non-selective fishing gears and methods such as trawling and beach seining, by use of gill nets of mesh size which crop immature fish and by introduction of mechanised fishing. Selectivity of gears used to crop Lates niloticus L.(Nile perch), Oreochromis niloticus L. (Nile tilapia) and Rastrineobola argentea Pellegrin (Mukene) which are currently the most important commercial species in Uganda were examined in order to recommend the most suitable types, sizes and methods that should be used in exploiting these fisheries. Gill nets of less than 127 mm mainly cropped immature Nile tilapia and Nile perch. To protect these fisheries, the minimum mesh size of gill nets should be set at 127 mm. Seine nets of 5 mm caught high proportions in immature Mukene while those of 10 mm caught mainly mature Mukene. When operated inshore, both sizes caught immature Nile perch and Nile tilapia as by-catch. To protect the Mukene fishery and avoid catching immature bye-catch, a minimum mesh size of the Mukene net should be 10 mm operated as Lampara type net offshore, but since most fishermen have been using 5 mm seine nets for over five years the minimum size should not be allowed to drop below 5 mm pending further thorough investigations. Beach seining and trawling are destructive to fisheries and should be prohibited until data that may justify their use is available.

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Recent evidences indicate that tRNA modifications and tRNA modifying enzymes may play important roles in complex human diseases such as cancer, neurological disorders and mitochondrial-linked diseases. We postulate that expression deregulation of tRNA modifying enzymes affects the level of tRNA modifications and, consequently, their function and the translation efficiency of their tRNA corresponding codons. Due to the degeneracy of the genetic code, most amino acids are encoded by two to six synonymous codons. This degeneracy and the biased usage of synonymous codons cause alterations that can span from protein folding to enhanced translation efficiency of a select gene group. In this work, we focused on cancer and performed a meta-analysis study to compare microarray gene expression profiles, reported by previous studies and evaluate the codon usage of different types of cancer where tRNA modifying enzymes were found de-regulated. A total of 36 different tRNA modifying enzymes were found de-regulated in most cancer datasets analyzed. The codon usage analysis revealed a preference for codons ending in AU for the up-regulated genes, while the down-regulated genes show a preference for GC ending codons. Furthermore, a PCA biplot analysis showed this same tendency. We also analyzed the codon usage of the datasets where the CTU2 tRNA modifying enzyme was found deregulated as this enzyme affects the wobble position (position 34) of specific tRNAs. Our data points to a distinct codon usage pattern between up and downregulated genes in cancer, which might be caused by the deregulation of specific tRNA modifying enzymes. This codon usage bias may augment the transcription and translation efficiency of some genes that otherwise, in a normal situation, would be translated less efficiently.

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Several recent offsite recreational fishing surveys have used public landline telephone directories as a sampling frame. Sampling biases inherent in this method are recognised, but are assumed to be corrected through demographic data expansion. However, the rising prevalence of mobile-only households has potentially increased these biases by skewing raw samples towards households that maintain relatively high levels of coverage in telephone directories. For biases to be corrected through demographic expansion, both the fishing participation rate and fishing activity must be similar among listed and unlisted fishers within each demographic group. In this study, we tested for a difference in the fishing activity of listed and unlisted fishers within demographic groups by comparing their avidity (number of fishing trips per year), as well as the platform used (boat or shore) and species targeted on their most recent fishing trip. 3062 recreational fishers were interviewed at 34 tackle stores across 12 residential regions of Queensland, Australia. For each fisher, data collected included their fishing avidity, the platform used and species targeted on their most recent trip, their gender, age, residential region, and whether their household had a listed telephone number. Although the most avid fishers were younger and less likely to have a listed phone number, cumulative link models revealed that avidity was not affected by an interaction of phone listing status, age group and residential region (p > 0.05). Likewise, binomial generalized linear models revealed that there was no interaction between phone listing, age group and avidity acting on platform (p > 0.05), and platform was not affected by an interaction of phone listing status, age group, and residential region (p > 0.05). Ordination of target species using Bray-Curtis dissimilarity indices found a significant but irrelevant difference (i.e. small effect size) between listed and unlisted fishers (ANOSIM R < 0.05, p < 0.05). These results suggest that, at this time, the fishing activity of listed and unlisted fishers in Queensland is similar within demographic groups. Future research seeking to validate the assumptions of recreational fishing telephone surveys should investigate fishing participation rates of listed and unlisted fishers within demographic groups.

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The informational properties of biological systems are the subject of much debate and research. I present a general argument in favor of the existence and central importance of information in organisms, followed by a case study of the genetic code (specifically, codon bias) and the translation system from the perspective of information. The codon biases of 831 Bacteria and Archeae are analyzed and modeled as points in a 64-dimensional statistical space. The major results are that (1) codon bias evolution does not follow canonical patterns, and (2) the use of coding space in organsims is a subset of the total possible coding space. These findings imply that codon bias is a unique adaptive mechanism that owes its existence to organisms' use of information in representing genes, and that there is a particularly biological character to the resulting biased coding and information use.