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We investigate methods and tools for analysing translations between programming languages with respect to observational semantics. The behaviour of programs is observed in terms of may- and mustconvergence in arbitrary contexts, and adequacy of translations, i.e., the reflection of program equivalence, is taken to be the fundamental correctness condition. For compositional translations we propose a notion of convergence equivalence as a means for proving adequacy. This technique avoids explicit reasoning about contexts, and is able to deal with the subtle role of typing in implementations of language extensions.
We investigate methods and tools for analysing translations between programming languages with respect to observational semantics. The behaviour of programs is observed in terms of may- and mustconvergence in arbitrary contexts, and adequacy of translations, i.e., the reflection of program equivalence, is taken to be the fundamental correctness condition. For compositional translations we propose a notion of convergence equivalence as a means for proving adequacy. This technique avoids explicit reasoning about contexts, and is able to deal with the subtle role of typing in implementations of language extensions.
Motivated by the question of correctness of a specific implementation of concurrent buffers in the lambda calculus with futures underlying Alice ML, we prove that concurrent buffers and handled futures can correctly encode each other. Correctness means that our encodings preserve and reflect the observations of may- and must-convergence, and as a consequence also yields soundness of the encodings with respect to a contextually defined notion of program equivalence. While these translations encode blocking into queuing and waiting, we also describe an adequate encoding of buffers in a calculus without handles, which is more low-level and uses busy-waiting instead of blocking. Furthermore we demonstrate that our correctness concept applies to the whole compilation process from high-level to low-level concurrent languages, by translating the calculus with buffers, handled futures and data constructors into a small core language without those constructs.
Background: Eukaryotic gene expression is controlled by cis-regulatory elements (CREs), including promoters and enhancers, which are bound by transcription factors (TFs). Differential expression of TFs and their binding affinity at putative CREs determine tissue- and developmental-specific transcriptional activity. Consolidating genomic data sets can offer further insights into the accessibility of CREs, TF activity, and, thus, gene regulation. However, the integration and analysis of multi-modal data sets are hampered by considerable technical challenges. While methods for highlighting differential TF activity from combined chromatin state data (e.g., ChIP-seq, ATAC-seq, or DNase-seq) and RNA-seq data exist, they do not offer convenient usability, have limited support for large-scale data processing, and provide only minimal functionality for visually interpreting results.
Results: We developed TF-Prioritizer, an automated pipeline that prioritizes condition-specific TFs from multi-modal data and generates an interactive web report. We demonstrated its potential by identifying known TFs along with their target genes, as well as previously unreported TFs active in lactating mouse mammary glands. Additionally, we studied a variety of ENCODE data sets for cell lines K562 and MCF-7, including twelve histone modification ChIP-seq as well as ATAC-seq and DNase-seq datasets, where we observe and discuss assay-specific differences.
Conclusion: TF-Prioritizer accepts ATAC-seq, DNase-seq, or ChIP-seq and RNA-seq data as input and identifies TFs with differential activity, thus offering an understanding of genome-wide gene regulation, potential pathogenesis, and therapeutic targets in biomedical research.
Background Eukaryotic gene expression is controlled by cis-regulatory elements (CREs) including promoters and enhancers which are bound by transcription factors (TFs). Differential expression of TFs and their putative binding sites on CREs cause tissue and developmental-specific transcriptional activity. Consolidating genomic data sets can offer further insights into the accessibility of CREs, TF activity, and thus gene regulation. However, the integration and analysis of multi-modal data sets are hampered by considerable technical challenges. While methods for highlighting differential TF activity from combined ChIP-seq and RNA-seq data exist, they do not offer good usability, have limited support for large-scale data processing, and provide only minimal functionality for visual result interpretation.
Results We developed TF-Prioritizer, an automated java pipeline to prioritize condition-specific TFs derived from multi-modal data. TF-Prioritizer creates an interactive, feature-rich, and user-friendly web report of its results. To showcase the potential of TF-Prioritizer, we identified known active TFs (e.g., Stat5, Elf5, Nfib, Esr1), their target genes (e.g., milk proteins and cell-cycle genes), and newly classified lactating mammary gland TFs (e.g., Creb1, Arnt).
Conclusion TF-Prioritizer accepts ChIP-seq and RNA-seq data, as input and suggests TFs with differential activity, thus offering an understanding of genome-wide gene regulation, potential pathogenesis, and therapeutic targets in biomedical research.
In vivo inducible reverse genetics in patients' tumors to identify individual therapeutic targets
(2021)
High-throughput sequencing describes multiple alterations in individual tumors, but their functional relevance is often unclear. Clinic-close, individualized molecular model systems are required for functional validation and to identify therapeutic targets of high significance for each patient. Here, we establish a Cre-ERT2-loxP (causes recombination, estrogen receptor mutant T2, locus of X-over P1) based inducible RNAi- (ribonucleic acid interference) mediated gene silencing system in patient-derived xenograft (PDX) models of acute leukemias in vivo. Mimicking anti-cancer therapy in patients, gene inhibition is initiated in mice harboring orthotopic tumors. In fluorochrome guided, competitive in vivo trials, silencing of the apoptosis regulator MCL1 (myeloid cell leukemia sequence 1) correlates to pharmacological MCL1 inhibition in patients´ tumors, demonstrating the ability of the method to detect therapeutic vulnerabilities. The technique identifies a major tumor-maintaining potency of the MLL-AF4 (mixed lineage leukemia, ALL1-fused gene from chromosome 4) fusion, restricted to samples carrying the translocation. DUX4 (double homeobox 4) plays an essential role in patients’ leukemias carrying the recently described DUX4-IGH (immunoglobulin heavy chain) translocation, while the downstream mediator DDIT4L (DNA-damage-inducible transcript 4 like) is identified as therapeutic vulnerability. By individualizing functional genomics in established tumors in vivo, our technique decisively complements the value chain of precision oncology. Being broadly applicable to tumors of all kinds, it will considerably reinforce personalizing anti-cancer treatment in the future.
High precision measurement of the radiative capture cross section of 238U at the n_TOF CERN facility
(2017)
The importance of improving the accuracy on the capture cross-section of 238U has been addressed by the Nuclear Energy Agency, since its uncertainty significantly affects the uncertainties of key design parameters for both fast and thermal nuclear reactors. Within the 7th framework programme ANDES of the European Commission three different measurements have been carried out with the aim of providing the 238U(n,γ) cross-section with an accuracy which varies from 1 to 5%, depending on the energy range. Hereby the final results of the measurement performed at the n_TOF CERN facility in a wide energy range from 1 eV to 700 keV will be presented.
The 236U isotope plays an important role in nuclear systems, both for future and currently operating ones. The actual knowledge of the capture reaction of this isotope is satisfactory in the thermal region, but it is considered insufficient for Fast Reactor and ADS applications. For this reason the 236U(n, γ) reaction cross-section has been measured for the first time in the whole energy region from thermal energy up to 1 MeV at the n_TOF facility with two different detection systems: an array of C6D6 detectors, employing the total energy deposited method, and a FX1 total absorption calorimeter (TAC), made of 40 BaF2 crystals. The two n_TOF data sets agree with each other within the statistical uncertainty in the Resolved Resonance Region up to 800 eV, while sizable differences (up to ≃ 20%) are found relative to the current evaluated data libraries. Moreover two new resonances have been found in the n_TOF data. In the Unresolved Resonance Region up to 200 keV, the n_TOF results show a reasonable agreement with previous measurements and evaluated data.
The 33S(n,α)30Si cross section measurement, using 10B(n,α) as reference, at the n_TOF Experimental Area 2 (EAR2) facility at CERN is presented. Data from 0.01 eV to 100 keV are provided and, for the first time, the cross section is measured in the range from 0.01 eV to 10 keV. These data may be used for a future evaluation of the cross section because present evaluations exhibit large discrepancies. The 33S(n,α)30Si reaction is of interest in medical physics because of its possible use as a cooperative target to boron in Neutron Capture Therapy (NCT).
The Cosmological Lithium Problem refers to the large discrepancy between the abundance of primordial 7Li predicted by the standard theory of Big Bang Nucleosynthesis and the value inferred from the so-called “Spite plateau” in halo stars. A possible explanation for this longstanding puzzle in Nuclear Astrophysics is related to the incorrect estimation of the destruction rate of 7Be, which is responsible for the production of 95% of primordial Lithium. While charged-particle induced reactions have mostly been ruled out, data on the 7Be(n,α) and 7Be(n,p) reactions are scarce or completely missing, so that a large uncertainty still affects the abundance of 7Li predicted by the standard theory of Big Bang Nucleosynthesis. Both reactions have been measured at the n_TOF facility at CERN, providing for the first time data in a wide neutron energy range.