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Measures of observation impact in non-Gaussian data assimilation
ABSTRACT
Non-Gaussian/non-linear data assimilation is becoming an increasingly important area of research in the
Geosciences as the resolution and non-linearity of models are increased and more and more non-linear
observation operators are being used. In this study, we look at the effect of relaxing the assumption of a
Gaussian prior on the impact of observations within the data assimilation system. Three different measures of
observation impact are studied: the sensitivity of the posterior mean to the observations, mutual information
and relative entropy. The sensitivity of the posterior mean is derived analytically when the prior is modelled
by a simplified Gaussian mixture and the observation errors are Gaussian. It is found that the sensitivity
is a strong function of the value of the observation and proportional to the posterior variance. Similarly,
relative entropy is found to be a strong function of the value of the observation. However, the errors
in estimating these two measures using a Gaussian approximation to the prior can differ significantly. This
hampers conclusions about the effect of the non-Gaussian prior on observation impact. Mutual information
does not depend on the value of the observation and is seen to be close to its Gaussian approximation. These
findings are illustrated with the particle filter applied to the Lorenz ’63 system. This article is concluded with a
discussion of the appropriateness of these measures of observation impact for different situations
Anti-cancer drug validation: the contribution of tissue engineered models
Abstract Drug toxicity frequently goes concealed until clinical trials stage, which is the most challenging, dangerous and expensive stage of drug development. Both the cultures of cancer cells in traditional 2D assays and animal studies have limitations that cannot ever be unraveled by improvements in drug-testing protocols. A new generation of bioengineered tumors is now emerging in response to these limitations, with potential to transform drug screening by providing predictive models of tumors within their tissue context, for studies of drug safety and efficacy. Considering the NCI60, a panel of 60 cancer cell lines representative of 9 different cancer types: leukemia, lung, colorectal, central nervous system (CNS), melanoma, ovarian, renal, prostate and breast, we propose to review current Bstate of art^ on the 9 cancer types specifically addressing the 3D tissue models that have been developed and used in drug discovery processes as an alternative to complement their studyThis article is a result of the project FROnTHERA (NORTE-01-0145-FEDER-000023), supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). This article was also supported by the EU Framework Programme for Research and Innovation HORIZON 2020 (H2020) under grant agreement n° 668983 — FoReCaST. FCT distinction attributed to Joaquim M. Oliveira (IF/00423/2012) and Vitor M. Correlo (IF/01214/2014) under the Investigator FCT program is also greatly acknowledged.info:eu-repo/semantics/publishedVersio
DNA Sequence Profiles of the Colorectal Cancer Critical Gene Set KRAS-BRAF-PIK3CA-PTEN-TP53 Related to Age at Disease Onset
The incidence of colorectal cancer (CRC) increases with age and early onset indicates an increased likelihood for genetic predisposition for this disease. The somatic genetics of tumor development in relation to patient age remains mostly unknown. We have examined the mutation status of five known cancer critical genes in relation to age at diagnosis, and compared the genomic complexity of tumors from young patients without known CRC syndromes with those from elderly patients. Among 181 CRC patients, stratified by microsatellite instability status, DNA sequence changes were identified in KRAS (32%), BRAF (16%), PIK3CA (4%), PTEN (14%) and TP53 (51%). In patients younger than 50 years (n = 45), PIK3CA mutations were not observed and TP53 mutations were more frequent than in the older age groups. The total gene mutation index was lowest in tumors from the youngest patients. In contrast, the genome complexity, assessed as copy number aberrations, was highest in tumors from the youngest patients. A comparable number of tumors from young (<50 years) and old patients (>70 years) was quadruple negative for the four predictive gene markers (KRAS-BRAF-PIK3CA-PTEN); however, 16% of young versus only 1% of the old patients had tumor mutations in PTEN/PIK3CA exclusively. This implies that mutation testing for prediction of EGFR treatment response may be restricted to KRAS and BRAF in elderly (>70 years) patients. Distinct genetic differences found in tumors from young and elderly patients, whom are comparable for known clinical and pathological variables, indicate that young patients have a different genetic risk profile for CRC development than older patients
Hierarchical Models in the Brain
This paper describes a general model that subsumes many parametric models for
continuous data. The model comprises hidden layers of state-space or dynamic
causal models, arranged so that the output of one provides input to another. The
ensuing hierarchy furnishes a model for many types of data, of arbitrary
complexity. Special cases range from the general linear model for static data to
generalised convolution models, with system noise, for nonlinear time-series
analysis. Crucially, all of these models can be inverted using exactly the same
scheme, namely, dynamic expectation maximization. This means that a single model
and optimisation scheme can be used to invert a wide range of models. We present
the model and a brief review of its inversion to disclose the relationships
among, apparently, diverse generative models of empirical data. We then show
that this inversion can be formulated as a simple neural network and may provide
a useful metaphor for inference and learning in the brain
Biophilic architecture: a review of the rationale and outcomes
Contemporary cities have high stress levels, mental health issues, high crime levels and ill health, while the built environment shows increasing problems with urban heat island effects and air and water pollution. Emerging from these concerns is a new set of design principles and practices where nature needs to play a bigger part called “biophilic architecture”. This design approach asserts that humans have an innate connection with nature that can assist to make buildings and cities more effective human abodes. This paper examines the evidence for this innate human psychological and physiological link to nature and then assesses the emerging research supporting the multiple social, environmental and economic benefits of biophilic architecture
Molecular detection of tilapia lake virus (TiLV) genome in Nile tilapia (Oreochromis niloticus) from Lake Victoria
Proceedings of the 35 scientific conference of the Tanzania Veterinary Association held at AICC, Arusha, December 2017.ilapia lake virus (TiLV) is an emerging pathogen of Tilapiines associated with high mortalities of wild and farmed
tilapia posing great threat to the fishery industry worldwide. The virus has been reported in Israel, Ecuador, Colombia,
Thailand, Egypt, Taiwan, India and Malaysia. In this study, a reverse transcription polymerase chain reaction (RT-PCR)
assay was developed and used to detect TiLV genome in Nile tilapia from Lake Victoria. Nile tilapia samples were
collected from the Tanzanian (108 fish) and Ugandan (83 fish) parts of Lake Victoria in 2015 and 2016, respectively.
Samples were screened for TiLV by using RT-PCR and the PCR products were sequenced. The findings show that out of
the 191 fish examined, 28 had PCR products showing the presence of TiLV genome. The TiLV nucleic acids were
detected in the spleen (10.99%, N=191), head kidney (7.69%, N=65), heart (3.45%, N=29) and liver (0.71%, N=140)
samples while no PCR amplification was detected in the brain by the developed RT-PCR method. Generally, the findings
show that the lymphoid organs, mainly comprising of the head kidney and spleen had the highest number of samples with
positive nucleic acids for TiLV followed by heart samples. On the contrary, the liver and brain that have previously been
shown to be target organs during acute infection either did not have or had the lowest level of TiLV nucleic acids
detected in the present study. All the 28 sequences retrieved had an average length of 768 bp. A blast analysis on NCBI
showed that all sequences obtained were homologous to TiLV segment-2 sequences obtained from previous outbreaks in
Israel and Thailand. To our knowledge, this is the first detection of TiLV subclinical infections in Nile tilapia in Lake
Victoria, a none-outbreak area
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