Haut PDF Practices in the Squale Quality Model (Squale Deliverable 1.3)

Practices in the Squale Quality Model (Squale Deliverable 1.3)

Practices in the Squale Quality Model (Squale Deliverable 1.3)

This model is complete but very difficult to apply because of the 300 metrics needed to compute it. It is implemented in several commercial tools but the correspondence between metrics and criteria is not clearly defined as already reported by Marinescu and Ratiu [MR04]. An important weakness is the lack of connexion between a criterium and the potential problem it reflects. When a criterium has a poor mark we don’t know exactly what is the cause of the problem. Even if the criterium is computed with a single metric, it does not give the solution to improve the quality. And when the criterium is computed with several metrics, it becomes very difficult to determine how to remedy to the problem. The Squale model, inspired by the ISO 9126 and the McCall models, keep the advantage of the overall view of the quality but brings a new dimension to this kind of model which allows to keep all the details: practices give information on the quality of the project that can be interpreted in order to improve this quality.
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EvoEvo Deliverable 2.2 : Genome-network model

EvoEvo Deliverable 2.2 : Genome-network model

1. Introduction The deliverable D2.2 (genome-network model) is available on the EvoEvo project website ( http://www.evoevo.eu/genome-network-model/ ). 1 This software follows the choices presented in deliverable 2.1 ( http://www.evoevo.eu/deliverable-2- 1-specifications-of-the-genome-network-model/ ). Some new features, that have not been specified in the deliverable are also included in the code in order to prepare the development of the following models of the project (e.g. membrane permeability or transcriptional noise). Installation instructions are detailed in section 2 and in the file INSTALL, in the root of the project. A demonstration parameters file is available in the folder examples. The file README describes the steps for a first usage of the software (also in section 3). Parameters usage is detailed in doc/parameters_description.html. During the simulation, one can have a closer look to the evolution of the system by opening the viewer (/experiment_path/viewer/viewer.html) in an internet browser.
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EvoEvo Deliverable 2.3: Specifications of the population model

EvoEvo Deliverable 2.3: Specifications of the population model

In order to vary the strength of spatial structure, a random fraction 𝑚𝑖𝑔 of organisms and free metabolites can be swapped at each time step. To do so, pairs of lattice cells are randomly chosen and their contents are swapped. Depending on the 𝑚𝑖𝑔 value, one can vary the population structure from well-mixed (𝑚𝑖𝑔 = 1) to perfectly local (𝑚𝑖𝑔 = 0). Moreover, some metabolites can also be artificially maintained at a constant concentration, be regularly provided locally or globally in the environment or, on the opposite, be regularly washed-out from the environment. Thus, various real experimental setups can be mimicked, including serial plates or chemostat (Mozhayskiy & Tagkopoulos, 2012). Similarly, some individuals can be regularly picked up in the environment to seed a new colony, thus mimicking a mutation accumulation experiment. All these optional features will be useful for further experiments in WP3 as mutation accumulation is often used in experimental evolution (figure 3). In order for the simulation to be computationally tractable, a concentration threshold may be defined above which a given metabolite could be considered absent from the local environment.
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EvoEvo Deliverable 2.1: Specifications of the genome-network model

EvoEvo Deliverable 2.1: Specifications of the genome-network model

5. Conclusion Merging INRIA and UU know-how allowed us to specify a genome-network model that will permit us to investigate the feasibility of integrating realistic genome structure and metabolic network. To date, a runnable prototype has been implemented and has provided some preliminary results. However, developing a biological model for research purpose is just not the same as developing an application for a customer. Specifications can change over time, owing to experimental results, to parametric exploration, interaction with biologists and new insights in the model. Thus, the overview presented above may change slightly during model development and test. For example, we are currently working on a more complex artificial chemistry, allowing for chemical bonds and the existence of macromolecules. As presented in section 2.3, we should explore the feasibility of the different artificial chemistry paradigms, and this will possibly modify some of the model specifications. In such a case, new versions of the present deliverable will be written.
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EvoEvo Deliverable 2.5 : Specifications of the realistic network model

EvoEvo Deliverable 2.5 : Specifications of the realistic network model

The fitness of each individual is then computed depending on which genes are on or off. Figure 1 - Overview of Pearls-on-a-String model (from Crombach & Hogeweg, 2008). (A) Simulations are run on a 150x50 lattice for 6.10 5 time steps. The lattice harbors a population of genomes, where a genome is a linear chromosome of genes with binding sites. A Boolean threshold network is built from each genome. During each time step the network may update the expression level of the genes for 11 propagation steps. (B) The impact of several gene and binding site mutations is shown. The change in the genome and network topology is signaled by a red star. In a typical simulation the parameters are (per gene, binding site): gene duplication (dup) 2.10 -4 , deletion 3.10 -4 , threshold 5.10 -6 , binding site (bsite) duplication 2.10 -5 , innovation 1.10 -5 , deletion (del) 3.10 -5 , preference (pref) 2.10 -5 and weight 2.10 -5 . (C) Typically the environment changes over time with a probability of λ = 3.10 -4 . The two evolutionary targets A and B determine which genes should be expressed (on) or inhibited (off). The result is four categories of genes; some should be always on, some should toggle their expression state and some should never be expressed. In a typical simulation, the target expression states are, from gene 0 to 19, A: 00011 11000 00000 11111 and B: 11010 01001 01100 01011.
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Understanding the Impact of Release Processes and Practices on Software Quality

Understanding the Impact of Release Processes and Practices on Software Quality

The advent of continuous delivery and rapid release practices have significantly reduced the amount of stabilization time available for new features, forcing companies to resort to inno- vative techniques to ensure that important features are released to the public, in a timely manner and with a good quality. To cope with short release cycles, Mozilla has re-organized its release process around four channels: a development channel named Nightly, two stabi- lization channels (Aurora and Beta), and a main Release channel. Features corresponding to a new release are developed on the Nightly channel over a period of six weeks. After that, the code is transferred to Aurora, where it is tested by Mozilla developers and contributors, for a period of six weeks, and then to Beta where it is tested by a selected group of external users. Finally, mature Beta features are imported into the main Release channel and delivered to end users. This pipelined process allows Mozilla to avoid mixing the development of new features with the stabilization process, which is particularly important given that integration operations are unpredictable [75], and can significantly delay a release process, if not enough time is allowed for stabilization. However, this well organized release process is frequently subverted by urgent patches, implementing high-value features or critical fixes, that cannot wait for the next release train. These features and fixes are directly promoted from the development channel to stable channels (i.e., Aurora, Beta, and main Release), a practice called patch uplift. Patch uplift is risky because the time allowed for the stabilization of uplifted patches is reduced by six weeks for each skipped channel. Therefore, it is important to carefully pick the patches that are uplifted and ensure that developers scrutinize them properly, to reduce the risk of regressions. There are a set of rules in place at Mozilla to govern this uplift process. One of these rules is that patches uplifted to the Beta channel should be (1) ideally reproducible by the QA team, so that they can be verified; (2) should have been verified on Aurora/Nightly first; and (3) should not contain string changes (i.e., changes in the text which is visible to users). However, despite these rules, multiple uplifted patches still introduce regressions in the code. Hence, it is unclear if–and–how the rules are ∗ Part of the content of this chapter is published in “An Empirical Study of Patch Uplift in Rapid Release
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The PILOTE-N model for improving water and nitrogen management practices: Application in a Mediterranean context

The PILOTE-N model for improving water and nitrogen management practices: Application in a Mediterranean context

drainage period from DOY 250 (2013) to DOY 90 (2014) due to the absence of heavy rainfall, confirms the ability of the model to properly simulate mineralization during the inter-season, the N soil storages being correctly predicted as shown by Fig.5. LIC of 2007, 2011, 2012 and 2013 highlighted the pertinence of a reduction in N application for water-scarce conditions attesting that nitrogen savings are possible when the initial N soil storage before sowing is known. A case that deserves dedicated attention is the rain-fed treatment of 2008. This cropping season with corn, was not selected because N in the plant was not measured. But it was sufficiently rainy (235 mm on the cropping cycle) to point out the effect of a reduction in N inputs (37 kg N ha -1 only at sowing) responsible for the low final grain yield, unlike other rain-fed treatments analyzed in this article. The fact that PILOTE substantially overestimates the corn yield (7.3 vs. 4.0 Mg ha -1 ) compared with PILOTE-N (4.3 vs. 4.0 Mg.ha -1 ) highlights the difficulty to manage efficiently both water and nitrogen, since the rainfall forecast is not possible for a farmer. For the durum wheat case, the application of PILOTE-N allowed noticing that the low yield value for the 2008-2009 cropping season was due to N leaching, whereas PILOTE substantially overestimated the yields. This statement pleads in favor of the identification of an efficient N management strategy using a modeling approach such as that proposed by PILOTE-N.
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Deliverable D4.20, Part 1 - Summary report on WP4 Task 2, Activities a) b) c) d)

Deliverable D4.20, Part 1 - Summary report on WP4 Task 2, Activities a) b) c) d)

4.5 Role of the CAP  4.5.1 Description of CAP measures  In the RDP, Axis 3 and 4 focus on the rural development through leader groups and local businesses  and communities. The first two objectives of axis 3 aims at the valorisation of landscape services: the  diversification  of  the  rural  economy  and  improving  the  quality  of  rural  life  both  refer  to  the  valorisation of cultural landscape services, i.e. promoting the demand for services enhances regional  economic  performance.  For  instance,  almost  one  third  (32%)  of  the  funds  in  axis  3  are  spent  on  measure  313,  which  aims  at  the  encouragement  tourism  activities.  The  measures  in  axis  3  are  targeted  at  both  farmers  (for  diversification  of  businesses)  and  non‐farmer  actors.  The  measures  adopted  in  both  axis  3  and  axis  4  do  not  address  landscape  management  and  only  affect  the  valorisation  of  landscape  services  by  encouraging  societal  demand.  Quantifying  the  contribution  of  axis  3  and  4  measures  to  regional  economic  performance  is  complicated,  but  the  aggregated  class  “trade,  hotels,  restaurants  and  repair”  (in  table  5)  indicates  the  importance  of  the  recreational/tourism  sector  for  the  regional  economy.  Moreover,  an  economic  valuation  study  of  cultural  landscape  services  shows  that  tourists  and  recreants  are  willing  to  pay  for  conservation  of  the coulisse landscape (van Berkel & Verburg, 2014). 
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EvoEvo Deliverable 2.4 : Population model

EvoEvo Deliverable 2.4 : Population model

1. Introduction The deliverable D2.4 (population model) is available on the EvoEvo project website ( http://www.evoevo.eu/population-model/ ). 1 This software follows the choices presented in deliverable 2.3 ( http://www.evoevo.eu/deliverable-2- 3-specifications-of-the-population-model/ ). Some new features, that have not been specified in the deliverable are also included in the code in order to prepare the development of the following models of the project (e.g. membrane permeability or transcriptional noise). Installation instructions are detailed in section 2 and in the file INSTALL, in the root of the project. A demonstration parameters file is available in the folder examples. The file README describes the steps for a first usage of the software (also in section 3). Parameters usage is detailed in doc/parameters_description.html. During the simulation, one can have a closer look to the evolution of the system by opening the viewer (/experiment_path/viewer/viewer.html) in an internet browser.
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Sulfone Based-Electrolytes for Lithium-Ion Batteries: Cycling Performances and Passivation Layer Quality of Graphite and LiNi 1/3 Mn 1/3 Co 1/3 O 2 Electrodes

Sulfone Based-Electrolytes for Lithium-Ion Batteries: Cycling Performances and Passivation Layer Quality of Graphite and LiNi 1/3 Mn 1/3 Co 1/3 O 2 Electrodes

Recently, our group published a review that gathers many data on the physicochemical and electrochemical properties of electrolytes for lithium-ion batteries. 4 This paper showed that seven families of dipolar aprotic organic solvent beside ionic liquids can be used in LiBs: carbonates, esters, ethers, acetals, sulfoxides, sulfites and sulfones. Each family presents advantages and disadvantages in terms of viscosity, ionic conductivity, thermal properties or anodic stability. Among these solvents, sulfones are an interesting in terms of thermal and oxidation stability except of viscosity, which remains too high and their ionic conductivities in the presence of lithium salt are usually very low. This review also showed that there is a great interest to extend the investigation of electrochemical and physicochemical properties to other sulfones in order to identify less viscous sulfones exhibiting higher ionic conductivities in the presence of lithium salts. Within this framework, a QSPR model was developed to find relationships between chemical structure and physicochemical properties of electrolytes. 21 For the first
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Ice monitoring of Deception Bay: Deliverable no.1 to no. 4

Ice monitoring of Deception Bay: Deliverable no.1 to no. 4

29 Figure 12 : Supporting structure for the network camera For sites #2 and #3, hunting type cameras were selected. Less expensive than the network camera, they have a low power consumption and internal data storage capacity. To optimally cover the Bay while staying within budget, four cameras will be installed. First, a Reconyx PC800 model will be installed at each site. We have already used this model in other projects in Nunavik and it has performed very well in extreme conditions. Examples of these pictures can be viewed at: http://www.krg.ca/en/ice-movement . Then, since the objective of the project is to assess the complementarity of different monitoring techniques, we will test two other hunting type models: the Strike Force HD from Browning and the Tiny-Plus from SpyPoint (Table 5). They are also less expensive than the Reconyx while providing a much better resolution.
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EvoEvo Deliverable 1.4 :  Analysis of phenotypic innovation (part 1)

EvoEvo Deliverable 1.4 : Analysis of phenotypic innovation (part 1)

Page 12 of 15 3. Phenotypic innovation at the regulatory network level in the E. coli experimental model During a long-term evolution experiment (LTEE), twelve populations are propagated by daily transfers from a common Escherichia coli ancestor for more than 60,000 generations in a constant glucose-limited environment. Adaptation of E. coli during the LTEE has been shown to involve the rewiring of global regulatory networks [Hindré et al., 2012]. In particular, the CRP-controlled regulon has been shown to be increasingly important during evolution [Cooper et al., 2008]. Deletions of the global regulatory crp gene have been introduced in both the ancestor of the LTEE and two independently evolved clones, one sampled from each of two of the twelve populations after 20,000 generations [Cooper et al., 2008]. Deleting crp had a much more dramatic effect on both the growth in the evolution environment and the global transcription profile of the two evolved clones than of the ancestor. Because the sequence of the crp gene was unchanged after 20,000 generations during evolution, these differences indicated epistatic interactions between crp and mutations at other loci that accumulated during evolution [Cooper et al., 2008]. Therefore, epistasis has been important in the adaptive evolution of these bacterial populations. However, the nature of these changes in epistatic interactions is unknown. Identification of the types of genetic changes that epistatically interact with the crp deletion would give new insights into the mechanisms through which epistasis can evolve. Moreover, phenotypic investigation of these changes in the global regulatory network will allow us to address whether these modifications of the interactions between global regulators within the regulatory network affected the robustness and evolvability of the evolved clones.
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EvoEvo Deliverable 2.8: Integrated evolutionary model

EvoEvo Deliverable 2.8: Integrated evolutionary model

1. Introduction The deliverable D2.8 (integrated evolutionary model) is available on the EvoEvo project website ( http://www.evoevo.eu/integrated-evolutionary-model/ ). 1 This software follows the choices presented in deliverable 2.7 ( http://www.evoevo.eu/deliverable-2- 7-specifications-of-the-integrated-evolutionary-model/ ). Some new features, that have not been specified in the deliverable are also included in the code in order to prepare the development of the following models of the project (e.g. membrane permeability or transcriptional noise). Installation instructions are detailed in section 2 and in the file INSTALL, in the root of the project. A demonstration parameters file is available in the folder examples. The file README describes the steps for a first usage of the software (also in section 3). Parameters usage is detailed in doc/parameters_description.html. During the simulation, one can have a closer look to the evolution of the system by opening the viewer (/experiment_path/viewer/viewer.html) in an internet browser.
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Modelling management practices in viticulture while considering resource limitations: the Dhivine model

Modelling management practices in viticulture while considering resource limitations: the Dhivine model

5.1 Case study and simulation experiments The simulation study focuses on the MG11 vineyard. (See Table 3 and Fig 4 for description of the vineyard, Tables 1 and 2 and Fig 3 for description of the equipment and labour require- ments and management strategy). MG11 is located in the Peyne river valley in the Languedoc- Roussillon region of southern France, which is one of the largest wine-producing regions in the world. The region's climate is sub-humid Mediterranean. Annual rainfall is about 700 mm, but varies widely from year to year. There are sharp seasonal contrasts, with rainy autumns and springs, and hot, dry summers. In terms of physical characteristics, the Peyne river valley is part of the main vineyard landscape of southern Languedoc-Roussillon, which developed on top of Miocene marine and lacustrine sediments partially overlain by alluvial deposits [ 45 ]. Most of the valley has gentler landforms and is covered by vineyards. The soil pattern of the valley includes a great range of soil types that present contrasting characteristics in terms of soil texture. As shown in Table 3 , the MG11 vineyard comprises 20 vines plots distributed between five types of soil [ 46 ]. Altitudes range from 60 m to 120 m. Most of the plots have a mean slope under 10%. In the case of steeper slope (plots P03, P16 and P18), terraces have been formed to facilitate machinery use. The diversity of the vine plots characteristics also con- cerns the varieties (12 different varieties), the vine density (from 3333 to 4444 vines/ha) and the pruning system (cane-trained or cordon-trained).
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The Squale Model - A Practice-based Industrial Quality Model

The Squale Model - A Practice-based Industrial Quality Model

The Squale model allows one to determine the quality of a project and control its evolution during the maintenance of a project, preventing deterioration. Moreover, using this model during the development of a project allows one to improve its quality. The Squale model stresses bad quality instead of averaging the quality in order to quickly focus on the wrong parts. It uses a set of measures combined into practices, formulae and weights to take into account the standards of the company and the technical specificity of a project. Practices and weights are customized with respect to these overall constraints. Air France-KLM and PSA Peugeot-Citroën have validated their own instances of the Squale model to monitor different information systems. Since 2008, the Squale project assembles the Qualixo company, the Paqtigo company, Air France-KLM, PSA Peugeot-Citroen, INRIA and the University of Paris 8 3 . It aims to formalize new practices and a Squale metamodel which would decrease the time spent while customizing the 3 This project is supported and labelled by the "Systematic - PARIS
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Going Wide with the 1-2-3 Conjecture

Going Wide with the 1-2-3 Conjecture

component isomorphic to K 2 , the main question is on determining its irregularity strength s(G), which is the smallest k such that irregular k-labellings of G exist. Note that the previous notions and definitions rely strongly on distances between some elements in the graph, as they are involved, in irregular labellings, both in the computation of the vertices’ sums, and in the set of vertices which must get distinct sums. That is, the vertices’ sums are computed from the labels assigned to the incident edges (thus at distance 1), while any two vertices (thus at distance less than the graph’s order) must get distinct sums. From this observation, playing with these distance parameters, we can already gather several variants of irregular labellings through a similar terminology. Namely, for any two r, d ≥ 1, we can define an (r, d)-irregular labelling of a graph G as a labelling such that we have c r ` (u) 6= c r ` (v) for any two distinct vertices u and v of G at distance at most d, where, for a vertex w, we define c r
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Combined impacts of oregano extract and vacuum packaging on the  quality changes of frigate tuna muscles stored at 3±1°C

Combined impacts of oregano extract and vacuum packaging on the quality changes of frigate tuna muscles stored at 3±1°C

The shelf life of fish can be extended noticeably by modifying the environment of the product [4]. Rapid cooling or storage in crushed ice is common methods that are traditionally used to extend the shelf life of seafood products. However, in the presence of ordi- nary atmosphere where the growth of aerobic bacteria is stimulated, atmospheric oxygen causes undesirable intense lipid rancidity due to the high proportion of polyunsaturated fatty acids in fish flesh [5]. For this reason, lower temperatures are combined with vacuum packaging (VP) and become an increasingly wide- spread preservation method involving the modification of atmosphere inside the pack [4]. VP prolongs the shelf life of fish products by removing air from a low oxygen permeability pack thereby reducing the availability of O 2 that is essential for the growth of aerobic bacteria, preventing lipid rancidity in fillets [6], ensuring correct assembly, and protection against external aggressions such as dehydration observed during the refrigeration. However, VP conditions have no important inhibiting effect on microbial growth leading to off-odors and slimy appearance of fish. Thus, its required to combine such techniques with the application of plant extract (antimicrobial) to guarantee the safety and high quality of vacuum packed products. Dipping in a natural pre- servative from oregano extract with vacuum packaging might provide an effective preserving system and lead to seafood with better sensory and microbiological qual- ity than those of common packaged seafood products.
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ESN-1-2-3

ESN-1-2-3

• On pourrait cependant dire que le poids idéal d’un individu est, dans le cadre d’un bilan clinique, son poids de forme habituel. Examen clinique.[r]

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TP 1 2 3

TP 1 2 3

 Les autres organes sont suspendus dans de l’eau physiologique ; après agitation vigoureuse l’eau est récupérée pour une observation sous la loupe binoculaire..  Une solution d’éth[r]

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TH1579, MTH1 inhibitor, delays tumour growth and inhibits metastases 1 development in osteosarcoma model 2 3

TH1579, MTH1 inhibitor, delays tumour growth and inhibits metastases 1 development in osteosarcoma model 2 3

Recently, there has been a growing interest for antitumour capa- bilities of the reactive oxygen species (ROS), notably through their ability to induce DNA damage [10] . ROS can indeed interact with the pool of free nucleotides, creating oxidized nucleotides. These oxonu- cleotides can be integrated into the DNA double helix by a DNA poly- merase, during replication, and disturb cellular processes [11] . Base Excision Repair (BER) mechanism then lead to excision of oxonucleo- tides from DNA by glycosylases such as the 8-oxoguanineglycosylase 1 (OGG1). However, this repair mechanism can be overwhelmed, leading to cell death. The Mutt homolog 1 (MTH1) or Nudix-Type 1 (NUDT1) protein is part of the nudix family of hydrolases. MTH1 acts as a nucleotide pool sanitation enzyme by hydrolysing oxonucleoti- des triphosphates such as 8-oxo-dGTP, 2-OH-dATP or 8-oxo-dATP, into their monophosphates counterparts. Its activity prevents the integration of oxidized nucleotides into DNA, since monophosphate nucleotides cannot be used by the DNA polymerase [ 12 , 13 ]. Thus, MTH1 protects cells against ROS effects on DNA integrity. Therefore, targeting MTH1 could imply impairing the genome integrity, i.e. through the targeting of DNA building blocks, nucleotides. Free nucleotides are also more likely to be oxidized by ROS than DNA mac- romolecules [12] . Furthermore, ROS are by-products of cell metabo- lism [14] , and it has been shown that tumour cells produce high quantity of ROS compared to normal cells, due to their fast metabo- lism, their environment and mutations [15 17] . Consequently, tumour cells could strongly depend on MTH1 activity to protect their genome integrity, and thus increase its expression compared to nor- mal cells. MTH1 has indeed been found to be overexpressed in sev- eral types of cancer such as breast and colorectal cancer [ 18 , 19 ], while MTH1-de ficient mice developed spontaneous tumours 18 months after birth [20] . Since 2014, several studies have tested the effects of MTH1 inhibition in different cancer types including osteo- sarcoma, melanoma, breast, cervical or colorectal cancer. MTH1 inhi- bition reduced cell viability and colony formation, increased oxidized
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