Robust optimal stopping

This paper studies the optimal stopping problem in the presence of model uncertainty (ambiguity). We develop a method to practically solve this problem in a general setting, allowing for general time-consistent ambiguity averse preferences and general payoff processes driven by jump-diffusions. Our method consists of three steps. First, we construct a suitable Doob martingale associated with the solution to the optimal stopping problem represented by the Snell envelope using backward stochastic calculus. Second, we employ this martingale to construct an approximated upper bound to the solution using duality. Third, we introduce backward-forward simulation to obtain a genuine upper bound to the solution, which converges to the true solution asymptotically. We analyze the asymptotic behavior and convergence properties of our method. We illustrate the generality and applicability of our method and the potentially significant impact of ambiguity to optimal stopping in a few examples

Three DNA polymerases, recruited by different mechanisms, carry out NER repair synthesis in human cells

Nucleotide excision repair (NER) is the most versatile DNA repair system that deals with the major UV photoproducts in DNA, as well as many other DNA adducts. The early steps of NER are well understood, whereas the later steps of repair synthesis and ligation are not. In particular, which polymerases are definitely involved in repair synthesis and how they are recruited to the damaged sites has not yet been established. We report that, in human fibroblasts, approximately half of the repair synthesis requires both polκ and polδ, and both polymerases can be recovered in the same repair complexes. Polκ is recruited to repair sites by ubiquitinated PCNA and XRCC1 and polδ by the classical replication factor complex RFC1-RFC, together with a polymerase accessory factor, p66, and unmodified PCNA. The remaining repair synthesis is dependent on polɛ, recruitment of which is dependent on the alternative clamp loader CTF18-RFC

Replication protein A safeguards genome integrity by controlling NER incision events

Continued association of RPA with sites of incomplete nucleotide excision repair averts further incision events until repair is completed

Xeroderma pigmentosum group A protein loads as a separate factor onto DNA lesions

Nucleotide excision repair (NER) is the main DNA repair pathway in mammals for removal of UV-induced lesions. NER involves the concerted action of more than 25 polypeptides in a coordinated fashion. The xeroderma pigmentosum group A protein (XPA) has been suggested to function as a central organizer and damage verifier in NER. How XPA reaches DNA lesions and how the protein is distributed in time and space in living cells are unknown. Here we studied XPA in vivo by using a cell line stably expressing physiological levels of functional XPA fused to green fluorescent protein and by applying quantitative fluorescence microscopy. The majority of XPA moves rapidly through the nucleoplasm with a diffusion rate different from those of other NER factors tested, arguing against a preassembled XPA-containing NER complex. DNA damage induced a transient ( approximately 5-min) immobilization of maximally 30% of XPA. Immobilization depends on XPC, indicating that XPA is not the initial lesion recognition protein in vivo. Moreover, loading of replication protein A on NER lesions was not dependent on XPA. Thus, XPA participates in NER by incorporation of free diffusing molecules in XPC-dependent NER-DNA complexes. This study supports a model for a rapid consecutive assembly of free NER factors, and a relatively slow simultaneous disassembly, after repair

SARS-CoV-2 Proteome-Wide Analysis Revealed Significant Epitope Signatures in COVID-19 Patients

The WHO declared the COVID-19 outbreak a public health emergency of international concern. The causative agent of this acute respiratory disease is a newly emerged coronavirus, named SARS-CoV-2, which originated in China in late 2019. Exposure to SARS-CoV-2 leads to multifaceted disease outcomes from asymptomatic infection to severe pneumonia, acute respiratory distress and potentially death. Understanding the host immune response is crucial for the development of interventional strategies. Humoral responses play an important role in defending viral infections and are therefore of particular interest. With the aim to resolve SARS-CoV-2-specific humoral immune responses at the epitope level, we screened clinically well-characterized sera from COVID-19 patients with mild and severe disease outcome using high-density peptide microarrays covering the entire proteome of SARS-CoV-2. Moreover, we determined the longevity of epitope-specific antibody responses in a longitudinal approach. Here we present IgG and IgA-specific epitope signatures from COVID-19 patients, which may serve as discriminating prognostic or predictive markers for disease outcome and/or could be relevant for intervention strategies

Fractional flow reserve versus angiography for guidance of PCI in patients with multivessel coronary artery disease (FAME): 5-year follow-up of a randomised controlled trial

In the Fractional Flow Reserve Versus Angiography for Multivessel Evaluation (FAME) study, fractional flow reserve (FFR)-guided percutaneous coronary intervention (PCI) improved outcome compared with angiography-guided PCI for up to 2 years of follow-up. The aim in this study was to investigate whether the favourable clinical outcome with the FFR-guided PCI in the FAME study persisted over a 5-year follow-up

Second-generation molecular subgrouping of medulloblastoma: an international meta-analysis of Group 3 and Group 4 subtypes

In 2012, an international consensus paper reported that medulloblastoma comprises four molecular subgroups (WNT, SHH, Group 3, and Group 4), each associated with distinct genomic features and clinical behavior. Independently, multiple recent reports have defined further intra-subgroup heterogeneity in the form of biologically and clinically relevant subtypes. However, owing to differences in patient cohorts and analytical methods, estimates of subtype number and definition have been inconsistent, especially within Group 3 and Group 4. Herein, we aimed to reconcile the definition of Group 3/Group 4 MB subtypes through the analysis of a series of 1501 medulloblastomas with DNA-methylation profiling data, including 852 with matched transcriptome data. Using multiple complementary bioinformatic approaches, we compared the concordance of subtype calls between published cohorts and analytical methods, including assessments of class-definition confidence and reproducibility. While the lowest complexity solutions continued to support the original consensus subgroups of Group 3 and Group 4, our analysis most strongly supported a definition comprising eight robust Group 3/Group 4 subtypes (types I–VIII). Subtype II was consistently identified across all component studies, while all others were supported by multiple class-definition methods. Regardless of analytical technique, increasing cohort size did not further increase the number of identified Group 3/Group 4 subtypes. Summarizing the molecular and clinico-pathological features of these eight subtypes indicated enrichment of specific driver gene alterations and cytogenetic events amongst subtypes, and identified highly disparate survival outcomes, further supporting their biological and clinical relevance. Collectively, this study provides continued support for consensus Groups 3 and 4 while enabling robust derivation of, and categorical accounting for, the extensive intertumoral heterogeneity within Groups 3 and 4, revealed by recent high-resolution subclassification approaches. Furthermore, these findings provide a basis for application of emerging methods (e.g., proteomics/single-cell approaches) which may additionally inform medulloblastoma subclassification. Outputs from this study will help shape definition of the next generation of medulloblastoma clinical protocols and facilitate the application of enhanced molecularly guided risk stratification to improve outcomes and quality of life for patients and their families

Haloes gone MAD: The Halo-Finder Comparison Project

[abridged] We present a detailed comparison of fundamental dark matter halo properties retrieved by a substantial number of different halo finders. These codes span a wide range of techniques including friends-of-friends (FOF), spherical-overdensity (SO) and phase-space based algorithms. We further introduce a robust (and publicly available) suite of test scenarios that allows halo finder developers to compare the performance of their codes against those presented here. This set includes mock haloes containing various levels and distributions of substructure at a range of resolutions as well as a cosmological simulation of the large-scale structure of the universe. All the halo finding codes tested could successfully recover the spatial location of our mock haloes. They further returned lists of particles (potentially) belonging to the object that led to coinciding values for the maximum of the circular velocity profile and the radius where it is reached. All the finders based in configuration space struggled to recover substructure that was located close to the centre of the host halo and the radial dependence of the mass recovered varies from finder to finder. Those finders based in phase space could resolve central substructure although they found difficulties in accurately recovering its properties. Via a resolution study we found that most of the finders could not reliably recover substructure containing fewer than 30-40 particles. However, also here the phase space finders excelled by resolving substructure down to 10-20 particles. By comparing the halo finders using a high resolution cosmological volume we found that they agree remarkably well on fundamental properties of astrophysical significance (e.g. mass, position, velocity, and peak of the rotation curve).Comment: 27 interesting pages, 20 beautiful figures, and 4 informative tables accepted for publication in MNRAS. The high-resolution version of the paper as well as all the test cases and analysis can be found at the web site http://popia.ft.uam.es/HaloesGoingMA

DNA methylation-based classification of central nervous system tumours.

Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging-with substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology

Haloes gone MAD: The Halo-Finder Comparison Project

We present a detailed comparison of fundamental dark matter halo properties retrieved by a substantial number of different halo finders. These codes span a wide range of techniques including friends-of-friends, spherical-overdensity and phase-space-based algorithms. We further introduce a robust (and publicly available) suite of test scenarios that allow halo finder developers to compare the performance of their codes against those presented here. This set includes mock haloes containing various levels and distributions of substructure at a range of resolutions as well as a cosmological simulation of the large-scale structure of the universe. All the halo-finding codes tested could successfully recover the spatial location of our mock haloes. They further returned lists of particles (potentially) belonging to the object that led to coinciding values for the maximum of the circular velocity profile and the radius where it is reached. All the finders based in configuration space struggled to recover substructure that was located close to the centre of the host halo, and the radial dependence of the mass recovered varies from finder to finder. Those finders based in phase space could resolve central substructure although they found difficulties in accurately recovering its properties. Through a resolution study we found that most of the finders could not reliably recover substructure containing fewer than 30-40 particles. However, also here the phase-space finders excelled by resolving substructure down to 10-20 particles. By comparing the halo finders using a high-resolution cosmological volume, we found that they agree remarkably well on fundamental properties of astrophysical significance (e.g. mass, position, velocity and peak of the rotation curve). We further suggest to utilize the peak of the rotation curve, vmax, as a proxy for mass, given the arbitrariness in defining a proper halo edg