The PhanSST global database of Phanerozoic sea surface temperature proxy data

Paleotemperature proxy data form the cornerstone of paleoclimate research and are integral to understanding the evolution of the Earth system across the Phanerozoic Eon. Here, we present PhanSST, a database containing over 150,000 data points from five proxy systems that can be used to estimate past sea surface temperature. The geochemical data have a near-global spatial distribution and temporally span most of the Phanerozoic. Each proxy value is associated with consistent and queryable metadata fields, including information about the location, age, and taxonomy of the organism from which the data derive. To promote transparency and reproducibility, we include all available published data, regardless of interpreted preservation state or vital effects. However, we also provide expert-assigned diagenetic assessments, ecological and environmental flags, and other proxy-specific fields, which facilitate informed and responsible reuse of the database. The data are quality control checked and the foraminiferal taxonomy has been updated. PhanSST will serve as a valuable resource to the paleoclimate community and has myriad applications, including evolutionary, geochemical, diagenetic, and proxy calibration studies

Briefing Book for the Zeuthen Workshop

On Jun 18th 2004, the CERN Council, upon the initiative of its President, Prof. Enzo Iarocci, established an ad hoc scientific advisory group (the Strategy Group), to produce a draft strategy for European particle physics, which is to be considered by a special meeting of the CERN Council, to be held in Lisbon on Jul 14th 2006. There are three volumes to the Briefing Book. This first volume contains an introductory essay on particle physics, a summary of the issues discussed at the Open Symposium, and discussions of the other themes that the Strategy should address. The introductory essay on particle physics and the other themes were commissioned by the Preparatory Group. The summary of the issues discussed in the Symposium was prepared by the chairs of the sessions, the session speakers and the scientific secretaries. We acknowledge that this has been a difficult task, again on a very tight timescale, and we would like to thank all of those who have contributed to this volume

Coordinating Tissue Regeneration Through Transforming Growth Factorâ β Activated Kinase 1 Inactivation and Reactivation

Aberrant wound healing presents as inappropriate or insufficient tissue formation. Using a model of musculoskeletal injury, we demonstrate that loss of transforming growth factorâ β activated kinase 1 (TAK1) signaling reduces inappropriate tissue formation (heterotopic ossification) through reduced cellular differentiation. Upon identifying increased proliferation with loss of TAK1 signaling, we considered a regenerative approach to address insufficient tissue production through coordinated inactivation of TAK1 to promote cellular proliferation, followed by reactivation to elicit differentiation and extracellular matrix production. Although the current regenerative medicine paradigm is centered on the effects of drug treatment (â drug onâ ), the impact of drug withdrawal (â drug offâ ) implicit in these regimens is unknown. Because current TAK1 inhibitors are unable to phenocopy genetic Tak1 loss, we introduce the dualâ inducible COmbinational Sequential Inversion ENgineering (COSIEN) mouse model. The COSIEN mouse model, which allows us to study the response to targeted drug treatment (â drug onâ ) and subsequent withdrawal (â drug offâ ) through genetic modification, was used here to inactivate and reactivate Tak1 with the purpose of augmenting tissue regeneration in a calvarial defect model. Our study reveals the importance of both the â drug onâ (Creâ mediated inactivation) and â drug offâ (Flpâ mediated reactivation) states during regenerative therapy using a mouse model with broad utility to study targeted therapies for disease. Stem Cells 2019;37:766â 778Manipulating transforming growth factor βâ activated kinase 1 for cell and scaffold free tissue regeneration using a dualâ inducible Combinational Sequential Inversion Engineering mouse model.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149573/1/stem2991_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149573/2/stem2991.pd

Characterization of Notch1 Antibodies That Inhibit Signaling of Both Normal and Mutated Notch1 Receptors

Notch receptors normally play a key role in guiding a variety of cell fate decisions during development and differentiation of metazoan organisms. On the other hand, dysregulation of Notch1 signaling is associated with many different types of cancer as well as tumor angiogenesis, making Notch1 a potential therapeutic target.Here we report the in vitro activities of inhibitory Notch1 monoclonal antibodies derived from cell-based and solid-phase screening of a phage display library. Two classes of antibodies were found, one directed against the EGF-repeat region that encompasses the ligand-binding domain (LBD), and the second directed against the activation switch of the receptor, the Notch negative regulatory region (NRR). The antibodies are selective for Notch1, inhibiting Jag2-dependent signaling by Notch1 but not by Notch 2 and 3 in reporter gene assays, with EC(50) values as low as 5+/-3 nM and 0.13+/-0.09 nM for the LBD and NRR antibodies, respectively, and fail to recognize Notch4. While more potent, NRR antibodies are incomplete antagonists of Notch1 signaling. The antagonistic activity of LBD, but not NRR, antibodies is strongly dependent on the activating ligand. Both LBD and NRR antibodies bind to Notch1 on human tumor cell lines and inhibit the expression of sentinel Notch target genes, including HES1, HES5, and DTX1. NRR antibodies also strongly inhibit ligand-independent signaling in heterologous cells transiently expressing Notch1 receptors with diverse NRR "class I" point mutations, the most common type of mutation found in human T-cell acute lymphoblastic leukemia (T-ALL). In contrast, NRR antibodies failed to antagonize Notch1 receptors bearing rare "class II" or "class III" mutations, in which amino acid insertions generate a duplicated or constitutively sensitive metalloprotease cleavage site. Signaling in T-ALL cell lines bearing class I mutations is partially refractory to inhibitory antibodies as compared to cell-penetrating gamma-secretase inhibitors.Antibodies that compete with Notch1 ligand binding or that bind to the negative regulatory region can act as potent inhibitors of Notch1 signaling. These antibodies may have clinical utility for conditions in which inhibition of signaling by wild-type Notch1 is desired, but are likely to be of limited value for treatment of T-ALLs associated with aberrant Notch1 activation

Uncovering the Genetic Landscape for Multiple Sleep-Wake Traits

Despite decades of research in defining sleep-wake properties in mammals, little is known about the nature or identity of genes that regulate sleep, a fundamental behaviour that in humans occupies about one-third of the entire lifespan. While genome-wide association studies in humans and quantitative trait loci (QTL) analyses in mice have identified candidate genes for an increasing number of complex traits and genetic diseases, the resources and time-consuming process necessary for obtaining detailed quantitative data have made sleep seemingly intractable to similar large-scale genomic approaches. Here we describe analysis of 20 sleep-wake traits from 269 mice from a genetically segregating population that reveals 52 significant QTL representing a minimum of 20 genomic loci. While many (28) QTL affected a particular sleep-wake trait (e.g., amount of wake) across the full 24-hr day, other loci only affected a trait in the light or dark period while some loci had opposite effects on the trait during the light vs. dark. Analysis of a dataset for multiple sleep-wake traits led to previously undetected interactions (including the differential genetic control of number and duration of REM bouts), as well as possible shared genetic regulatory mechanisms for seemingly different unrelated sleep-wake traits (e.g., number of arousals and REM latency). Construction of a Bayesian network for sleep-wake traits and loci led to the identification of sub-networks of linkage not detectable in smaller data sets or limited single-trait analyses. For example, the network analyses revealed a novel chain of causal relationships between the chromosome 17@29cM QTL, total amount of wake, and duration of wake bouts in both light and dark periods that implies a mechanism whereby overall sleep need, mediated by this locus, in turn determines the length of each wake bout. Taken together, the present results reveal a complex genetic landscape underlying multiple sleep-wake traits and emphasize the need for a systems biology approach for elucidating the full extent of the genetic regulatory mechanisms of this complex and universal behavior

Adjusting Choice Models to Better Predict Market Behavior

The emergence of Bayesian methodology has facilitated respondent-level conjoint models, and deriving utilities from choice experiments has become very popular among those modeling product line decisions or new product introductions. This review begins with a paradox of why experimental choices should mirror market behavior despite clear differences in content, structure and motivation. It then addresses ways to design the choice tasks so that they are more likely to reflect market choices. Finally, it examines ways to model the results of the choice experiments to better mirror both underlying decision processes and potential market choices.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47012/1/11002_2005_Article_5885.pd