Exploiting physico-chemical properties in string kernels

<p>Abstract</p> <p>Background</p> <p>String kernels are commonly used for the classification of biological sequences, nucleotide as well as amino acid sequences. Although string kernels are already very powerful, when it comes to amino acids they have a major short coming. They ignore an important piece of information when comparing amino acids: the physico-chemical properties such as size, hydrophobicity, or charge. This information is very valuable, especially when training data is less abundant. There have been only very few approaches so far that aim at combining these two ideas.</p> <p>Results</p> <p>We propose new string kernels that combine the benefits of physico-chemical descriptors for amino acids with the ones of string kernels. The benefits of the proposed kernels are assessed on two problems: MHC-peptide binding classification using position specific kernels and protein classification based on the substring spectrum of the sequences. Our experiments demonstrate that the incorporation of amino acid properties in string kernels yields improved performances compared to standard string kernels and to previously proposed non-substring kernels.</p> <p>Conclusions</p> <p>In summary, the proposed modifications, in particular the combination with the RBF substring kernel, consistently yield improvements without affecting the computational complexity. The proposed kernels therefore appear to be the kernels of choice for any protein sequence-based inference.</p> <p>Availability</p> <p>Data sets, code and additional information are available from <url>http://www.fml.tuebingen.mpg.de/raetsch/suppl/aask</url>. Implementations of the developed kernels are available as part of the Shogun toolbox.</p

MultiMetEval: comparative and multi-objective analysis of genome-scale metabolic models

Comparative metabolic modelling is emerging as a novel field, supported by the development of reliable and standardized approaches for constructing genome-scale metabolic models in high throughput. New software solutions are needed to allow efficient comparative analysis of multiple models in the context of multiple cellular objectives. Here, we present the user-friendly software framework Multi-Metabolic Evaluator (MultiMetEval), built upon SurreyFBA, which allows the user to compose collections of metabolic models that together can be subjected to flux balance analysis. Additionally, MultiMetEval implements functionalities for multi-objective analysis by calculating the Pareto front between two cellular objectives. Using a previously generated dataset of 38 actinobacterial genome-scale metabolic models, we show how these approaches can lead to exciting novel insights. Firstly, after incorporating several pathways for the biosynthesis of natural products into each of these models, comparative flux balance analysis predicted that species like Streptomyces that harbour the highest diversity of secondary metabolite biosynthetic gene clusters in their genomes do not necessarily have the metabolic network topology most suitable for compound overproduction. Secondly, multi-objective analysis of biomass production and natural product biosynthesis in these actinobacteria shows that the well-studied occurrence of discrete metabolic switches during the change of cellular objectives is inherent to their metabolic network architecture. Comparative and multi-objective modelling can lead to insights that could not be obtained by normal flux balance analyses. MultiMetEval provides a powerful platform that makes these analyses straightforward for biologists. Sources and binaries of MultiMetEval are freely available from https://github.com/PiotrZakrzewski/MetEv​al/downloads

Characterization of Parameters Required for Effective Use of Tamoxifen-Regulated Recombination

Conditional gene targeting using the Cre-loxp system is a well established technique in numerous in vitro and in vivo systems. Ligand regulated forms of Cre have been increasingly used in these applications in order to gain temporal and spatial control over conditional targeting. The tamoxifen-regulated Cre variant mer-Cre-mer (mCrem) is widely utilized because of its reputation for tight regulation in the absence of its tamoxifen ligand. In the DT40 chicken B cell line, we generated an mCrem-based reversible switch for conditional regulation of a transgene, and in contrast with previous work, observed significant constitutive activity of mCrem. This prompted us to use our system for analysis of the parameters governing tamoxifen-regulated mCrem recombination of a genomic target. We find that robust mCrem expression correlates with a high level of tamoxifen-independent Cre activity, while clones expressing mCrem at the limit of western blot detection exhibit extremely tight regulation. We also observe time and dose-dependent effects on mCrem activity which suggest limitations on the use of conditional targeting approaches for applications which require tight temporal coordination of Cre action within a cell population

Missed injuries in trauma patients: A literature review

<p>Abstract</p> <p>Background</p> <p>Overlooked injuries and delayed diagnoses are still common problems in the treatment of polytrauma patients. Therefore, ongoing documentation describing the incidence rates of missed injuries, clinically significant missed injuries, contributing factors and outcome is necessary to improve the quality of trauma care. This review summarizes the available literature on missed injuries, focusing on overlooked muscoloskeletal injuries.</p> <p>Methods</p> <p>Manuscripts dealing with missed injuries after trauma were reviewed. The following search modules were selected in PubMed: Missed injuries, Delayed diagnoses, Trauma, Musculoskeletal injuires. Three time periods were differentiated: (n = 2, 1980–1990), (n = 6, 1990–2000), and (n = 9, 2000-Present).</p> <p>Results</p> <p>We found a wide spread distribution of missed injuries and delayed diagnoses incidence rates (1.3% to 39%). Approximately 15 to 22.3% of patients with missed injuries had clinically significant missed injuries. Furthermore, we observed a decrease of missed pelvic and hip injuries within the last decade.</p> <p>Conclusion</p> <p>The lack of standardized studies using comparable definitions for missed injuries and clinically significant missed injuries call for further investigations, which are necessary to produce more reliable data. Furthermore, improvements in diagnostic techniques (e.g. the use of multi-slice CT) may lead to a decreased incidence of missed pelvic injuries. Finally, the standardized tertiary trauma survey is vitally important in the detection of clinically significant missed injuries and should be included in trauma care.</p

Asymmetric Strand Segregation: Epigenetic Costs of Genetic Fidelity?

Asymmetric strand segregation has been proposed as a mechanism to minimize effective mutation rates in epithelial tissues. Under asymmetric strand segregation, the double-stranded molecule that contains the oldest DNA strand is preferentially targeted to the somatic stem cell after each round of DNA replication. This oldest DNA strand is expected to have fewer errors than younger strands because some of the errors that arise on daughter strands during their synthesis fail to be repaired. Empirical findings suggest the possibility of asymmetric strand segregation in a subset of mammalian cell lineages, indicating that it may indeed function to increase genetic fidelity. However, the implications of asymmetric strand segregation for the fidelity of epigenetic information remain unexplored. Here, I explore the impact of strand-segregation dynamics on epigenetic fidelity using a mathematical-modelling approach that draws on the known molecular mechanisms of DNA methylation and existing rate estimates from empirical methylation data. I find that, for a wide range of starting methylation densities, asymmetric—but not symmetric—strand segregation leads to systematic increases in methylation levels if parent strands are subject to de novo methylation events. I found that epigenetic fidelity can be compromised when enhanced genetic fidelity is achieved through asymmetric strand segregation. Strand segregation dynamics could thus explain the increased DNA methylation densities that are observed in structured cellular populations during aging and in disease

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration

Quantitative Comparison of Constitutive Promoters in Human ES cells

BACKGROUND: Constitutive promoters that ensure sustained and high level gene expression are basic research tools that have a wide range of applications, including studies of human embryology and drug discovery in human embryonic stem cells (hESCs). Numerous cellular/viral promoters that ensure sustained gene expression in various cell types have been identified but systematic comparison of their activities in hESCs is still lacking. METHODOLOGY/PRINCIPAL FINDINGS: We have quantitatively compared promoter activities of five commonly used constitutive promoters, including the human β-actin promoter (ACTB), cytomegalovirus (CMV), elongation factor-1α, (EF1α), phosphoglycerate kinase (PGK) and ubiquitinC (UbC) in hESCs. Lentiviral gene transfer was used to ensure stable integration of promoter-eGFP constructs into the hESCs genome. Promoter activities were quantitatively compared in long term culture of undifferentiated hESCs and in their differentiated progenies. CONCLUSION/SIGNIFICANCE: The ACTB, EF1α and PGK promoters showed stable activities during long term culture of undifferentiated hESCs. The ACTB promoter was superior by maintaining expression in 75-80% of the cells after 50 days in culture. During embryoid body (EB) differentiation, promoter activities of all five promoters decreased. Although the EF1α promoter was downregulated in approximately 50% of the cells, it was the most stable promoter during differentiation. Gene expression analysis of differentiated eGFP+ and eGFP- cells indicate that promoter activities might be restricted to specific cell lineages, suggesting the need to carefully select optimal promoters for constitutive gene expression in differentiated hESCs

Functional interplay between p63 and p53 controls RUNX1 function in the transition from proliferation to differentiation in human keratinocytes

The interfollicular epidermis is continuously renewed, thanks to a regulated balance between proliferation and differentiation. The ΔNp63 transcription factor has a key role in the control of this process. It has been shown that ΔNp63 directly regulates Runt-related transcription factor 1 (RUNX1) transcription factor expression in mouse keratinocytes. The present study showed for the first time that RUNX1 is expressed in normal human interfollicular epidermis and that its expression is tightly regulated during the transition from proliferation to differentiation. It demonstrated that ΔNp63 directly binds two different RUNX1 regulatory DNA sequences and modulates RUNX1 expression differentially in proliferative or differentiated human keratinocytes. It also showed that the regulation of RUNX1 expression by ΔNp63 is dependent on p53 and that this coregulation relies on differential binding and activation of RUNX1 regulatory sequences by ΔNp63 and p53. We also found that RUNX1 inhibits keratinocyte proliferation and activates directly the expression of KRT1, a critical actor in early keratinocyte differentiation. Finally, we described that RUNX1 expression, similar to ΔNp63 and p53, was strongly expressed and downregulated in basal cell carcinomas and squamous cell carcinomas respectively. Taken together, these data shed light on the importance of tight control of the functional interplay between ΔNp63 and p53 in regulating RUNX1 transcription factor expression for proper regulation of interfollicular epidermal homeostasis

Signatures of mutational processes in human cancer.

All cancers are caused by somatic mutations; however, understanding of the biological processes generating these mutations is limited. The catalogue of somatic mutations from a cancer genome bears the signatures of the mutational processes that have been operative. Here we analysed 4,938,362 mutations from 7,042 cancers and extracted more than 20 distinct mutational signatures. Some are present in many cancer types, notably a signature attributed to the APOBEC family of cytidine deaminases, whereas others are confined to a single cancer class. Certain signatures are associated with age of the patient at cancer diagnosis, known mutagenic exposures or defects in DNA maintenance, but many are of cryptic origin. In addition to these genome-wide mutational signatures, hypermutation localized to small genomic regions, 'kataegis', is found in many cancer types. The results reveal the diversity of mutational processes underlying the development of cancer, with potential implications for understanding of cancer aetiology, prevention and therapy