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Topic review
Updated time: 01 Sep 2021
Submitted by: Kamel Mhalhel
Definition: Acid-sensing ion channels (ASICs) are Na+channels gated by extracellular H+and are widely expressed in the mammalian central and peripheral nervous systems. ASICs are part of the degenerin/epithelial sodium (Na) channel (DEG/ENaC) superfamily whose feature is high permeability to Na that could be blocked by amiloride. Structurally, ASICs consist of two hydrophobic transmembrane domains (TMD) of 20 amino acids approximately, TMD1 and TMD2, a large domain of around 370 amino acids forming an extracellular loop of 14 conserved cysteines, and a kind of short cytoplasmic amino and carboxyl termini of 35–90 amino acids.
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Topic review
Updated time: 03 Sep 2020
Submitted by: Stan Moaraf
Definition: Despite growing evidence that demonstrate adverse effects of artificial light at night (ALAN) on many species, relatively little is known regarding its effects on brain plasticity in birds. We recently showed that although ALAN increases cell proliferation in brains of birds, neuronal densities in two brain regions decreased, indicating neuronal death, which might be due to mortality of newly produced neurons or of existing ones. Therefore, in the present study we studied the effect of long-term ALAN on the recruitment of newborn neurons into their target regions in the brain. Accordingly, we exposed zebra finches (Taeniopygia guttata) to 5 lux ALAN, and analysed new neuronal recruitment and total neuronal densities in several brain regions. We found that ALAN increased neuronal recruitment, possibly as a compensatory response to ALAN-induced neuronal death, and/or due to increased nocturnal locomotor activity caused by sleep disruption. Moreover, ALAN also had a differential temporal effect on neuronal densities, because hippocampus was more sensitive to ALAN and its neuronal densities were more affected than in other brain regions. Nocturnal melatonin levels under ALAN were significantly lower compared to controls, indicating that very low ALAN intensities suppress melatonin not only in nocturnal, but also in diurnal species.
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Topic review
Updated time: 13 Apr 2021
Submitted by: Yunmin Wei
Definition: Aluminum (Al) toxicity is a major environmental stress that inhibits plant growth and development in acidic soils.
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Topic review
Updated time: 28 Jul 2020
Submitted by: Francesca Pistollato
Definition: Noncommunicable diseases, such as Alzheimer’s disease, breast and prostate cancer, are becoming increasingly prevalent in Western countries. To better elucidate the onset and evolution of these pathologies and ultimately design new preventive and therapeutic strategies, research activities focused on these biomedical areas have been supported by the European Union in the last two decades. While research has globally contributed increasing our understanding of the pathological mechanisms underlying these diseases, the failure rate in drug development still remains very high. Nowadays, it is important to monitor contribution to innovation and impact of funded research by means of defined indicators.
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Topic review
Updated time: 13 Oct 2020
Submitted by: Jadwiga Topczewska
Definition: The neural classification system in form of a multi-layered artificial neural network suggested in this paper was implemented in the programming environment MATLAB. MATLAB is a useful tool focused mainly on scientific and technical calculations. It boasts of a wide spectrum of software solutions/libraries, the so-called Toolboxes that can be used, for example to create and optimize neural networks. It is fully compatible with other programming environments. Matlab is a tool for rapid prototyping that enables a wide range of learning algorithms, the selection of optimal neural network architecture, the selection of the most efficient neuron activation functions as well as optimal learning parameters. The design of the network is of key significance both for the learning process, and the quality of its operation in later stages. The set of input data, purpose, and results do have significant impact on the they configuration. A key assumption is taking cognizance of factual links between the set of explanatory variables (input) and the output. The artificial neural networks enable the capture of relationships and dependencies between the data in circumstances where the application of traditional analytical methods would not have yielded satisfactory solutions. The use of ANN enables objective assessments of individual animals by taking into account only factors essential for determining horses’ performance and breeding values. Preliminary results of the application of artificial neural networks in predicting the utility value of Hucul horses, relying on a specific set of features seem rather promising. It offers potential possibilities of evaluation, relying on available information about the animals.
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Topic review
Updated time: 02 Sep 2020
Submitted by: Alec Michael
Definition: In response to the threat presented by AMR, it is critically important to find methods for effectively interpreting minimum inhibitory concentration (MIC) tests. A wide array of techniques for analysis of MIC data exist, which require different ways of modifying the MIC data for use as the dependent variable in regression and analysis. For use as the outcome in logistic regression, MIC data is categorized using clinical breakpoints and epidemiological cutoff values (ECOFF). Clinical breakpoints classify isolates as susceptible (S), resistant (R), or an intermediate category based on expected clinical outcomes of treatment with a specific antimicrobial. The ECOFF classifies organisms as wild type (WT) or non-wild type (non-WT) based on the absence or presence of phenotypically-detectable acquired resistance mechanisms to the specific antimicrobial. Dichotomization of MIC data results in information loss, as only changes in the proportions of WT/non-WT or S/R are observed in dichotomized data. As a result, changes in MIC distributions that do not cross the threshold may be unobserved using approaches with dichotomized outcomes. Other modeling approaches for MIC data may attempt to avoid information loss by not dichotomizing the outcome when using regression to analyze MIC data.
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Biography
Updated time: 28 Oct 2020
Submitted by: Andrew Knight
Abstract: Biography for Prof. Andrew Knight
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Topic review
Updated time: 08 Jan 2021
Submitted by: Gabriella Guelfi
Definition: Resilience is conceived as a dynamic developmental process involving the achievement of positive adaptation within the context of significant adversity. Resilience is not a unique ability but rather a set of capacities of a system put in place to absorb a disturbance and to reorganize while trying to retain the same function, structure, and identity. This study describes the characteristics and the molecular mechanisms of resilience to understand the core elements of resilience and its indicators.
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Topic review
Updated time: 31 Jul 2020
Submitted by: Guilherme Ferreira
Definition: Reports of a reproducibility crisis combined with a high attrition rate in the pharmaceutical industry have put animal research increasingly under scrutiny in the past decade. Many researchers and the general public now question whether there is still a justification for conducting animal studies. While criticism of the current modus operandi in preclinical research is certainly warranted, the data on which these discussions are based are often unreliable. Several initiatives to address the internal validity and reporting quality of animal studies (e.g., Animals in Research: Reporting In Vivo Experiments (ARRIVE) and Planning Research and Experimental Procedures on Animals: Recommendations for Excellence (PREPARE) guidelines) have been introduced but seldom implemented. As for external validity, progress has been virtually absent. Nonetheless, the selection of optimal animal models of disease may prevent the conducting of clinical trials, based on unreliable preclinical data. Here, we discuss three contributions to tackle the evaluation of the predictive value of animal models of disease themselves. First, we developed the Framework to Identify Models of Disease (FIMD), the first step to standardise the assessment, validation and comparison of disease models. FIMD allows the identification of which aspects of the human disease are replicated in the animals, facilitating the selection of disease models more likely to predict human response. Second, we show an example of how systematic reviews and meta-analyses can provide another strategy to discriminate between disease models quantitatively. Third, we explore whether external validity is a factor in animal model selection in the Investigator’s Brochure (IB), and we use the IB-derisk tool to integrate preclinical pharmacokinetic and pharmacodynamic data in early clinical development. Through these contributions, we show how we can address external validity to evaluate the translatability and scientific value of animal models in drug development. However, while these methods have potential, it is the extent of their adoption by the scientific community that will define their impact. By promoting and adopting high-quality study design and reporting, as well as a thorough assessment of the translatability of drug efficacy of animal models of disease, we will have robust data to challenge and improve the current animal research paradigm.
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Topic review
Updated time: 16 Dec 2020
Definition: Nematodes of the Anisakidae family have a cosmopolitan distribution, due to their ability to infest a wide variety of aquatic hosts during the development of their larval stages, mainly marine mammals and aquatic birds, such as pelicans; being the hosts where the life cycle is completed. The participation of intermediate hosts such as cephalopods, shrimp, crustaceans and marine fish, are an important part to complete this cycle. However, its importance in human health is due to its zoonotic capacity, which causes the clinical presentation in humans, known as Anisakiasis or Anisakidosis, depending on the species of the infecting parasite.
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