A gradient tree boosting and network propagation derived pan-cancer survival network of the tumor microenvironment

Predicting cancer survival from molecular data is an important aspect of biomedical research because it allows quantifying patient risks and thus individualizing therapy. We introduce XGBoost tree ensemble learning to predict survival from transcriptome data of 8,024 patients from 25 different cancer types and show highly competitive performance with state-of-the-art methods. To further improve plausibility of the machine learning approach we conducted two additional steps. In the first step, we applied pan-cancer training and showed that it substantially improves prognosis compared with cancer subtype-specific training. In the second step, we applied network propagation and inferred a pan-cancer survival network consisting of 103 genes. This network highlights cross-cohort features and is predictive for the tumor microenvironment and immune status of the patients. Our work demonstrates that pan-cancer learning combined with network propagation generalizes over multiple cancer types and identifies biologically plausible features that can serve as biomarkers for monitoring cancer survival

Gradient tree boosting and network propagation for the identification of pan-cancer survival networks

Cancer survival prediction is typically done with uninterpretable machine learning techniques, e.g., gradient tree boosting. Therefore, additional steps are needed to infer biological plausibility of the predictions. Here, we describe a protocol that combines pan-cancer survival prediction with XGBoost tree- ensemble learning and subsequent propagation of the learned feature weights on protein interaction networks. This protocol is based on TCGA transcriptome data of 8,024 patients from 25 cancer types but can easily be adapted to cancer patient data from other sources. For complete details on the use and execution of this protocol, please refer to Thedinga and Herwig (2022)

The Cellular Architecture of the Larval Zebrafish Tectum, as Revealed by Gal4 Enhancer Trap Lines

We have carried out a Gal4 enhancer trap screen in zebrafish, and have generated 184 stable transgenic lines with interesting expression patterns throughout the nervous system. Of these, three display clear expression in the tectum, each with a distinguishable and stereotyped distribution of Gal4 expressing cells. Detailed morphological analysis of single cells, using a genetic “Golgi-like” labelling method, revealed four common cell types (superficial, periventricular, shallow periventricular, and radial glial), along with a range of other less common neurons. The shallow periventricular (PV) and a subset of the PV neurons are tectal efferent neurons that target various parts of the reticular formation. We find that it is specifically PV neurons with dendrites in the deep tectal neuropil that target the reticular formation. This indicates that these neurons receive the tectum's highly processed visual information (which is fed from the superficial retinorecipient layers), and relay it to premotor regions. Our results show that the larval tectum, both broadly and at the single cell level, strongly resembles a miniature version of its adult counterpart, and that it has all of the necessary anatomical characteristics to inform motor responses based on sensory input. We also demonstrate that mosaic expression of GFP in Gal4 enhancer trap lines can be used to describe the types and abundance of cells in an expression pattern, including the architectures of individual neurons. Such detailed anatomical descriptions will be an important part of future efforts to describe the functions of discrete tectal circuits in the generation of behavior

User's manual for the Shuttle Electric Power System analysis computer program (SEPS), volume 2 of program documentation

The Shuttle Electric Power System Analysis SEPS computer program which performs detailed load analysis including predicting energy demands and consumables requirements of the shuttle electric power system along with parameteric and special case studies on the shuttle electric power system is described. The functional flow diagram of the SEPS program is presented along with data base requirements and formats, procedure and activity definitions, and mission timeline input formats. Distribution circuit input and fixed data requirements are included. Run procedures and deck setups are described

The Core Composition of a White Dwarf in a Close Double Degenerate System

We report the identification of the double degenerate system NLTT 16249 that comprises a normal, hydrogen-rich (DA) white dwarf and a peculiar, carbon-polluted white dwarf (DQ) showing photospheric traces of nitrogen. We disentangled the observed spectra and constrained the properties of both stellar components. In the evolutionary scenario commonly applied to the sequence of DQ white dwarfs, both carbon and nitrogen would be dredged up from the core. The C/N abundance ratio (~ 50) in the atmosphere of this unique DQ white dwarf suggests the presence of unprocessed material (14N) in the core or in the envelope. Helium burning in the DQ progenitor may have terminated early on the red-giant branch after a mass-ejection event leaving unprocessed material in the core although current mass estimates do not favor the presence of a low-mass helium core. Alternatively, some nitrogen in the envelope may have survived an abridged helium-core burning phase prior to climbing the asymptotic giant-branch. Based on available data, we estimate a relatively short orbital period (P <~ 13 hrs) and on-going spectroscopic observations will help determine precise orbital parameters.Comment: Accepted for publication in ApJ Letter

Modeling He-rich subdwarfs through the hot-flasher Scenario

We present 1D numerical simulations aimed at studying the hot-flasher scenario for the formation of He-rich subdwarf stars. Sequences were calculated for a wide range of metallicities and physical assumptions, such as the stellar mass at the moment of the helium core flash. This allows us to study the two previously proposed flavors of the hot-flasher scenario ("deep" and "shallow" mixing cases) and to identify a third transition type. Our sequences are calculated by solving simultaneously the mixing and burning equations within a diffusive convection picture, and in the context of standard mixing length theory. We are able to follow chemical evolution during deep-mixing events in which hydrogen is burned violently, and therefore able to present a homogeneous set of abundances for different metallicities and varieties of hot-flashers. We extend the scope of our work by analyzing the effects of non-standard assumptions, such as the effect of chemical gradients, extra-mixing at convective boundaries, possible reduction in convective velocities, or the interplay between difussion and mass loss. Particular emphasis is placed on the predicted surface properties of the models. We find that the hot-flasher scenario is a viable explanation for the formation and surface properties of He-sdO stars. Our results also show that, during the early He-core burning stage, element diffusion may produce the transformation of (post hot-flasher) He-rich atmospheres into He-deficient ones. If this is so, then we find that He-sdO stars should be the progenitors of some of the hottest sdB stars.Comment: 13 pages, including 8 figures and 6 tables. Accepted for publication in A&A. Replaced to match the final version, including a note added in proof regarding PG 1544+48

Element Abundance Determination in Hot Evolved Stars

The hydrogen-deficiency in extremely hot post-AGB stars of spectral class PG1159 is probably caused by a (very) late helium-shell flash or a AGB final thermal pulse that consumes the hydrogen envelope, exposing the usually-hidden intershell region. Thus, the photospheric element abundances of these stars allow us to draw conclusions about details of nuclear burning and mixing processes in the precursor AGB stars. We compare predicted element abundances to those determined by quantitative spectral analyses performed with advanced non-LTE model atmospheres. A good qualitative and quantitative agreement is found for many species (He, C, N, O, Ne, F, Si, Ar) but discrepancies for others (P, S, Fe) point at shortcomings in stellar evolution models for AGB stars. Almost all of the chemical trace elements in these hot stars can only be identified in the UV spectral range. The Far Ultraviolet Spectroscopic Explorer and the Hubble Space Telescope played a crucial role for this research.Comment: To appear in: Recent Advances in Spectroscopy: Theoretical, Astrophysical, and Experimental Perspectives, Proceedings, Jan 28 - 31, 2009, Kodaikanal, India (Springer