Phosphodiesterase 7 as a therapeutic target – Where are we now?

Cyclic nucleotide phosphodiesterases (PDEs) are a superfamily of enzymes that hydrolyse the intracellular second messengers cAMP and cGMP to their inactive forms 5’AMP and 5’GMP. Some members of the PDE family display specificity towards a single cyclic nucleotide messenger, and PDE4, PDE7, and PDE8 specifically hydrolyse cAMP. While the role of PDE4 and its use as a therapeutic target have been well studied, less is known about PDE7 and PDE8. This review aims to collate the present knowledge on human PDE7 and outline its potential use as a therapeutic target. Human PDE7 exists as two isoforms PDE7A and PDE7B that display different expression patterns but are predominantly found in the central nervous system, immune cells, and lymphoid tissue. As a result, PDE7 is thought to play a role in T cell activation and proliferation, inflammation, and regulate several physiological processes in the central nervous system, such as neurogenesis, synaptogenesis, and long-term memory formation. Increased expression and activity of PDE7 has been detected in several disease states, including neurodegenerative diseases such as Parkinson's, Alzheimer's and Huntington's disease, autoimmune diseases such as multiple sclerosis and COPD, and several types of cancer. Early studies have shown that administration of PDE7 inhibitors may ameliorate the clinical state of these diseases. Targeting PDE7 may therefore provide a novel therapeutic strategy for targeting a broad range of disease and possibly provide a complementary alternative to inhibitors of other cAMP-selective PDEs, such as PDE4, which are severely limited by their side-effects

Editorial

Denver, Theological Comments Will the Decision on Fellowship at Denver Make a Difference? Fellowship and the Younger Sister Churches Synodical Conventions: A Theological Perspectiv

Secondary prevention following coronary artery bypass surgery: a pilot study for improved patient education

This is an Open Access article distributed under the terms of the Open Access Policy

Tyrphostin AG126 exerts neuroprotection in CNS inflammation by a dual mechanism

© 2015 Wiley Periodicals, Inc. Acknowledgement Grant sponsor: State of Lower Saxony-Israel Research Cooperation; Grant number: ZN2035; Grant sponsor:German Research Council; Grant number: SFB/TRR43 and FOR1336; Grant sponsor: Parkinson UK; Grant number: K-1001; Grant sponsor: ProFutura Program (University of Gottingen); Grant sponsor: Else Kroner Fresenius Stiftung;Grant number: A69/2010; Grant sponsor: DFG; Grant number: WE 3547/4–1; Grant sponsor: US National Multiple Sclerosis Society; Grant numbers: NMSS; PP 1660. The authors thank Elke Pralle, Susanne Kiecke and Caroline Jaß (University of Gottingen) for excellent technical assistance.Peer reviewedPostprin

PRH/Hex: an oligomeric transcription factor and ,ultifunctional regulator of cell fate.

The PRH (proline-rich homeodomain) [also known as Hex (haematopoietically expressed homeobox)] protein is a critical regulator of vertebrate development. PRH is able to regulate cell proliferation and differentiation and is required for the formation of the vertebrate body axis, the haematopoietic and vascular systems and the formation of many vital organs. PRH is a DNAbinding protein that can repress and activate the transcription of its target genes using multiple mechanisms. In addition, PRH can regulate the nuclear transport of specific mRNAs making PRH a member of a select group of proteins that control gene expression at the transcriptional and translational levels. Recent biophysical analysis of the PRH protein has shown that it forms homo-oligomeric complexes in vivo and in vitro and that the proline-rich region of PRH forms a novel dimerization interface. Here we will review the current literature on PRH and discuss the complex web of interactions centred on this multifunctional protein

Finding Our Way through Phenotypes

Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US

This article contains supporting information online at http://www.pnas.org/lookup/suppl/doi:10.1073/pnas.2113561119/-/DCSupplemental.Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multi-model ensemble forecast that combined predictions from dozens of different research groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-week horizon 3-5 times larger than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.Integrative Biolog

PI3K/Akt1 signalling specifies foregut precursors by generating regionalized extra-cellular matrix.

During embryonic development signalling pathways act repeatedly in different contexts to pattern the emerging germ layers. Understanding how these different responses are regulated is a central question for developmental biology. In this study, we used mouse embryonic stem cell (mESC) differentiation to uncover a new mechanism for PI3K signalling that is required for endoderm specification. We found that PI3K signalling promotes the transition from naïve endoderm precursors into committed anterior endoderm. PI3K promoted commitment via an atypical activity that delimited epithelial-to-mesenchymal transition (EMT). Akt1 transduced this activity via modifications to the extracellular matrix (ECM) and appropriate ECM could itself induce anterior endodermal identity in the absence of PI3K signalling. PI3K/Akt1-modified ECM contained low levels of Fibronectin (Fn1) and we found that Fn1 dose was key to specifying anterior endodermal identity in vivo and in vitro. Thus, localized PI3K activity affects ECM composition and ECM in turn patterns the endoderm. DOI: http://dx.doi.org/10.7554/eLife.00806.00