Model-based analysis of the Tower of London task

The planning process is central to goal-directed behaviour in any task that requires the organization of a series of actions aimed at achieving a goal. Although the planning process has been investigated thoroughly, relatively little is known about how this process emerges and evolves during childhood. In this paper we describe three reinforcement learning models of planning, in the Tower of London (ToL) task, and use Bayesian analysis to fit each model to pre-existing data from 3-4 year-old and 5-6 year-old children performing the task. The models all capture the increased organisation seen in the older children’s performance. It is also shown that, at least for this dataset, the most complex model – that with discounting of future rewards and pruning of highly aversive states – provides no additional explanatory power beyond a simpler discounting-only model. Insights into developmental aspects of the planning process are discussed

Short Communication. Comparing flammability traits among fire-stricken (low elevation) and non fire-stricken (high elevation) conifer forest species of Europe: A test of the Mutch hypothesis

Aim of study. The flammability of the main coniferous forest species of Europe, divided into two groups according to their fire regime and altitudinal distribution, was tested in an effort to detect species-specific differences that may have an influence on community-wide fire regimes.Area of study. Conifer species comprising low- and high-elevation forests in Europe.Materials and Methods. The following conifer species were tested: low elevation; Pinus halepensis (Aleppo pine), Pinus brutia (Turkish pine), Pinus pinaster (maritime pine), Pinus pinea (stone pine) and Cupressus sempervirens (cypress), high elevation (i.e., above 600 m a.s.l.); Pinus sylvestris (Scots pine), Abies alba (white fir), Picea excelsa (Norway spruce), Abies borissii regis (Macedonian fir) and Pinus nigra (black pine). Flammability assessment (time-to-ignition and ignition temperature) was conducted by an innovative ignition apparatus, heat content was measured with an IKA Adiabatic Bomb Calorimeter and ash content by heating 5 g of plant material in a muffle furnace at 650ºC for 1 h. Differences among species was statistically analysed by Duncan’s multiple comparison test.Main results. The results did not distinguish separate groups among traits between fire- and non-fire-stricken communities at the individual species level.Research highlights. Differences in fire regimes among low and high elevation conifer forests could be attributed either to differences in flammability of the plant communities as a whole (i.e., fuelbed or canopy properties vs. individual fuel properties) or to other factors (climatic or anthropogenic).Key words: flammability; ignitability; heat content; ash content; conifer species; Mutch hypothesis

canSAR: an updated cancer research and drug discovery knowledgebase.

canSAR (http://cansar.icr.ac.uk) is a publicly available, multidisciplinary, cancer-focused knowledgebase developed to support cancer translational research and drug discovery. canSAR integrates genomic, protein, pharmacological, drug and chemical data with structural biology, protein networks and druggability data. canSAR is widely used to rapidly access information and help interpret experimental data in a translational and drug discovery context. Here we describe major enhancements to canSAR including new data, improved search and browsing capabilities, new disease and cancer cell line summaries and new and enhanced batch analysis tools

Greece's Sudden Faltering Economy: From Boom to Bust With special reference to the debt problem

In this paper, we deal with theoretical propositions and empirical evidence that are needed to explain the paradox of rapid GDP growth in the face of the dismal competitiveness of the Greek economy during 1995-2008. We show how Greece’s economy structural weaknesses have hit the domestic economy and we investigate their impact on the current turmoil of the economy. We show that the previous favourable global economic environment acted as a locomotive to domestic growth, and now that it is gone, structural problems of poor governance, low competitiveness and a ballooning public deficit and debt, have come to the surface. Also, in the context of debt sustainability we look at the recent actions to reduce debt that are taken by the Growth and Stability Program. We construct five scenarios regarding the level of public debt at the end of the 2011-2015 period that is commonly accepted that Greece will return to global financial markets to finance its debt. We find that only under a very optimistic scenario of robust growth of the economy based on structural and institutional reforms that boost productivity, significantly improve competitiveness, and boost the financial sector as described in the Growth and Stability Program along with a successful privatization of 50 billion euros the public debt to gdp ratio can reach the 60% threshold that the financial markets find comfortable. We offer a specific explanation of the current unfortunate state of the economy and we briefly suggest avenues of necessary progressive reforms to overcome it

canSAR: update to the cancer translational research and drug discovery knowledgebase.

canSAR (https://cansar.ai) is the largest public cancer drug discovery and translational research knowledgebase. Now hosted in its new home at MD Anderson Cancer Center, canSAR integrates billions of experimental measurements from across molecular profiling, pharmacology, chemistry, structural and systems biology. Moreover, canSAR applies a unique suite of machine learning algorithms designed to inform drug discovery. Here, we describe the latest updates to the knowledgebase, including a focus on significant novel data. These include canSAR's ligandability assessment of AlphaFold; mapping of fragment-based screening data; and new chemical bioactivity data for novel targets. We also describe enhancements to the data and interface

A Modified Method for Whole Exome Resequencing from Minimal Amounts of Starting DNA

Next generation DNA sequencing (NGS) technologies have revolutionized the pace at which whole genome and exome sequences can be generated. However, despite these advances, many of the methods for targeted resequencing, such as the generation of high-depth exome sequences, are somewhat limited by the relatively large amounts of starting DNA that are normally required. In the case of tumour analysis this is particularly pertinent as many tumour biopsies often return submicrogram quantities of DNA, especially when tumours are microdissected prior to analysis. Here, we present a method for exome capture and resequencing using as little as 50 ng of starting DNA. The sequencing libraries generated by this minimal starting amount (MSA-Cap) method generate datasets that are comparable to standard amount (SA) whole exome libraries that use three micrograms of starting DNA. This method, which can be performed in most laboratories using commonly available reagents, has the potential to enhance large scale profiling efforts such as the resequencing of tumour exomes

Proposing a Governance model for environmental crises

During August 2021, a wildfire outbreak in Evia, Greece's second largest island, resulted in a major environmental and economic crisis. Apart from biodiversity and habitat loss, the disaster triggered a financial crisis because it wiped out wood-productive forests and outdoor areas that attract visitors. This crisis highlighted the need for a new governance model in order to respond to environmental crises more effectively. The aim of this study was to investigate the acceptance and attitudes of relevant stakeholders towards establishing a Hub a proposed governance model responsible for monitoring and restoring the natural capital and biodiversity after environmental crises. Results based on quantitative data collected via questionnaires showed that most respondents were positive to the Hub and perceived that its main functions should be to recommend measures after environmental crises and to facilitate cooperation among involved stakeholders. Moreover, results pointed to preferred funding sources, stakeholder groups that should participate in the Hub and key performance indicators (KPIs) for monitoring Hub's performance. The applied methodology could guide the establishment of governance models both in the study area and other countries facing environmental crises

Deriving a mutation index of carcinogenicity using protein structure and protein interfaces

With the advent of Next Generation Sequencing the identification of mutations in the genomes of healthy and diseased tissues has become commonplace. While much progress has been made to elucidate the aetiology of disease processes in cancer, the contributions to disease that many individual mutations make remain to be characterised and their downstream consequences on cancer phenotypes remain to be understood. Missense mutations commonly occur in cancers and their consequences remain challenging to predict. However, this knowledge is becoming more vital, for both assessing disease progression and for stratifying drug treatment regimes. Coupled with structural data, comprehensive genomic databases of mutations such as the 1000 Genomes project and COSMIC give an opportunity to investigate general principles of how cancer mutations disrupt proteins and their interactions at the molecular and network level. We describe a comprehensive comparison of cancer and neutral missense mutations; by combining features derived from structural and interface properties we have developed a carcinogenicity predictor, InCa (Index of Carcinogenicity). Upon comparison with other methods, we observe that InCa can predict mutations that might not be detected by other methods. We also discuss general limitations shared by all predictors that attempt to predict driver mutations and discuss how this could impact high-throughput predictions. A web interface to a server implementation is publicly available at http://inca.icr.ac.uk/

canSAR: update to the cancer translational research and drug discovery knowledgebase.

canSAR (http://cansar.icr.ac.uk) is a public, freely available, integrative translational research and drug discovery knowlegebase. canSAR informs researchers to help solve key bottlenecks in cancer translation and drug discovery. It integrates genomic, protein, pharmacological, drug and chemical data with structural biology, protein networks and unique, comprehensive and orthogonal 'druggability' assessments. canSAR is widely used internationally by academia and industry. Here we describe major enhancements to canSAR including new and expanded data. We also describe the first components of canSARblack-an advanced, responsive, multi-device compatible redesign of canSAR with a question-led interface

Characterization of the genomic features and expressed fusion genes in micropapillary carcinomas of the breast

Micropapillary carcinoma ( MPC ) is a rare histological special type of breast cancer, characterized by an aggressive clinical behaviour and a pattern of copy number aberrations ( CNAs ) distinct from that of grade‐ and oestrogen receptor ( ER )‐matched invasive carcinomas of no special type ( IC‐NSTs ). The aims of this study were to determine whether MPCs are underpinned by a recurrent fusion gene(s) or mutations in 273 genes recurrently mutated in breast cancer. Sixteen MPCs were subjected to microarray‐based comparative genomic hybridization ( aCGH ) analysis and Sequenom OncoCarta mutation analysis. Eight and five MPCs were subjected to targeted capture and RNA sequencing, respectively. aCGH analysis confirmed our previous observations about the repertoire of CNAs of MPCs . Sequencing analysis revealed a spectrum of mutations similar to those of luminal B IC‐NSTs , and recurrent mutations affecting mitogen‐activated protein kinase family genes and NBPF10 . RNA ‐sequencing analysis identified 17 high‐confidence fusion genes, eight of which were validated and two of which were in‐frame. No recurrent fusions were identified in an independent series of MPCs and IC‐NSTs . Forced expression of in‐frame fusion genes ( SLC2A1–FAF1 and BCAS4–AURKA ) resulted in increased viability of breast cancer cells. In addition, genomic disruption of CDK12 caused by out‐of‐frame rearrangements was found in one MPC and in 13% of HER2 ‐positive breast cancers, identified through a re‐analysis of publicly available massively parallel sequencing data. In vitro analyses revealed that CDK12 gene disruption results in sensitivity to PARP inhibition, and forced expression of wild‐type CDK12 in a CDK12 ‐null cell line model resulted in relative resistance to PARP inhibition. Our findings demonstrate that MPCs are neither defined by highly recurrent mutations in the 273 genes tested, nor underpinned by a recurrent fusion gene. Although seemingly private genetic events, some of the fusion transcripts found in MPCs may play a role in maintenance of a malignant phenotype and potentially offer therapeutic opportunities. © 2014 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106752/1/path4325.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/106752/2/path4325-sup-0001-AppendixS1.pd