A human neural crest model reveals the developmental impact of neuroblastoma-associated chromosomal aberrations

Early childhood tumours arise from transformed embryonic cells, which often carry large copy number alterations (CNA). However, it remains unclear how CNAs contribute to embryonic tumourigenesis due to a lack of suitable models. Here we employ female human embryonic stem cell (hESC) differentiation and single-cell transcriptome and epigenome analysis to assess the effects of chromosome 17q/1q gains, which are prevalent in the embryonal tumour neuroblastoma (NB). We show that CNAs impair the specification of trunk neural crest (NC) cells and their sympathoadrenal derivatives, the putative cells-of-origin of NB. This effect is exacerbated upon overexpression of MYCN, whose amplification co-occurs with CNAs in NB. Moreover, CNAs potentiate the pro-tumourigenic effects of MYCN and mutant NC cells resemble NB cells in tumours. These changes correlate with a stepwise aberration of developmental transcription factor networks. Together, our results sketch a mechanistic framework for the CNA-driven initiation of embryonal tumours

Inferring causal molecular networks: empirical assessment through a community-based effort

Inferring molecular networks is a central challenge in computational biology. However, it has remained unclear whether causal, rather than merely correlational, relationships can be effectively inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge that focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results constitute the most comprehensive assessment of causal network inference in a mammalian setting carried out to date and suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess the causal validity of inferred molecular networks

Inferring causal molecular networks: empirical assessment through a community-based effort

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess inferred molecular networks in a causal sense

Large increase of magnetic hyperfine fields of 5sp-shell impurities in ferromagnets after vacancy trapping

Vacancy trapping by 119Sb impurities implanted in Ni, Co, and Fe gives rise to large changes of the magnetic hyperfine fields Bhf of the 119Sn daughter nuclei. We have measured the following values for the normal substitutional and the vacancy-associated impurity hyperfine fields (in T): In all cases, the vacancies associated with the impurities could be "frozen in" up to high temperatures by decoration with post-implanted helium atoms. The substantial increase of the fields can be understood in terms of the conduction-electron polarization model of Blandin and Campbell

The Current Energy Situation: Summary Points

Energy problems are now being largely ignored, despite their continuing importance. The near-disappearance of energy from the U.S. public agenda is apparent in the scant attention given to energy topics by the media and by public figures. Some suggestions for governmental action were stimulated by the rise in gasoline prices in the Spring of 1996, but the matter was treated as a short-term anomaly -- not as a harbinger of more severe difficulties to come. This lack of long term concern is perhaps natural, because fuel supplies are generally ample and prices are still relatively low, with the real cost of gasoline in 1994 only one half the cost in 1981. However, we believe that neglect of potential future difficulties is highly imprudent. We summarize below the considerations that lead us to this conclusion. (This Background Paper was prepared by members of the Panel on Public Affairs of the American Physical Society. It is meant to reflect the considerations that underlie the Statement on Energy: the Forgotten Crisis issued by the American Physical Society. This paper has not been reviewed by the Society.