Causal Mechanistic Regulatory Network for Glioblastoma Deciphered Using Systems Genetics Network Analysis.

Cell Syst. 2016 Jul 14;

Authors: Plaisier CL, O'Brien S, Bernard B, Reynolds S, Simon Z, Toledo CM, Ding Y, Reiss DJ, Paddison PJ, Baliga NS

Abstract
We developed the transcription factor (TF)-target gene database and the Systems Genetics Network Analysis (SYGNAL) pipeline to decipher transcriptional regulatory networks from multi-omic and clinical patient data, and we applied these tools to 422 patients with glioblastoma multiforme (GBM). The resulting gbmSYGNAL network predicted 112 somatically mutated genes or pathways that act through 74 TFs and 37 microRNAs (miRNAs) (67 not previously associated with GBM) to dysregulate 237 distinct co-regulated gene modules associated with patient survival or oncogenic processes. The regulatory predictions were associated to cancer phenotypes using CRISPR-Cas9 and small RNA perturbation studies and also demonstrated GBM specificity. Two pairwise combinations (ETV6-NFKB1 and romidepsin-miR-486-3p) predicted by the gbmSYGNAL network had synergistic anti-proliferative effects. Finally, the network revealed that mutations in NF1 and PIK3CA modulate IRF1-mediated regulation of MHC class I antigen processing and presentation genes to increase tumor lymphocyte infiltration and worsen prognosis. Importantly, SYGNAL is widely applicable for integrating genomic and transcriptomic measurements from other human cohorts.

PMID: 27426982 [PubMed - as supplied by publisher]

Systems Glycobiology: Integrating glycogenomics, glycoproteomics, glycomics and other 'omics data sets to characterize cellular glycosylation processes.

J Mol Biol. 2016 Jul 13;

Authors: Bennun SV, Hizal DB, Heffner K, Can O, Zhang H, Betenbaugh MJ

Abstract
The number of proteins encoded in the human genome has been estimated at between 20,000 and 25,000 despite estimates that the entire proteome contains more than a million proteins. One reason for this difference is due to the many protein post-translational modifications that contribute to proteome complexity. Among them, glycosylation is of particular relevance because it serves to modify a large number of cellular proteins. Glycogenomics, glycoproteomics, glycomics and glycoinformatics are helping to accelerate our understanding of the cellular events involved in generating the glycoproteome, the variety of glycan structures possible, and the importance glycans play in therapeutics and disease. Indeed, interest in glycosylation has expanded rapidly over the past decade as large amounts of experimental 'omics data relevant to glycosylation processing has accumulated. Furthermore, new and more sophisticated glycoinformatics tools and databases are now available for glycan and glycosylation pathway analysis. Here, we summarize some of the recent advances in both experimental profiling and analytical methods involving N- and O-linked glycosylation processing for biotechnological and medically-relevant cells together with the unique opportunities and challenges associated with interrogating and assimilating multiple disparate high-throughput glycosylation data sets. This emerging era of advanced glycomics will lead to the discovery of key glycan biomarkers linked to diseases and help establish a better understanding of physiology and improved control of glycosylation processing in diverse cells and tissues important to disease and production of recombinant therapeutics. Furthermore, methodologies that facilitate the integration of glycomics measurements together with other 'omics data sets will lead to a deeper understanding and greater insights into the nature of glycosylation as a complex cellular process.

PMID: 27423401 [PubMed - as supplied by publisher]

Comparative proteomic and metabolomic analysis reveal the antiosteoporotic molecular mechanism of icariin from Epimedium brevicornu Maxim.

J Ethnopharmacol. 2016 Jul 12;

Authors: Xue L, Jiang Y, Han T, Zhang N, Qin L, Xin H, Zhang Q

Abstract
ETHNOPHARMACOLOGICAL RELEVANCE: Icariin, a principal flavonoid glycoside of Epimedium brevicornu Maxim, has been widely proved to possess antiosteoporotic activity with promoting bone frormation and decreasing bone resorption. However, the involving mechanisms remain unclear.
AIM OF THE STUDY: To clear a global insight of signal pathways involved in anti-osteoporotic mechanism of icariin at proteins and metabolites level by integrating the proteomics and NMR metabonomics, in a systems biology approach.
MATERIAL AND METHODS: Mice were divided into sham, OVX model and icariin-treated OVX group, after 90 days treatment, difference gel electrophoresis combined with MALDI-TOF/TOF proteomics analysis on bone femur and serum metabolomics were carried out for monitor intracellular processes and elucidate anti-osteoporotic mechanism of icariin. Osteoblast and osteoclast were applied to evaluate the potential signal pathways.
RESULTS: 23 proteins in bone femur, and 8 metabolites in serum, were significantly altered and identified, involving in bone remodeling, energy metabolism, cytoskeleton, lipid metabolism, MAPK signaling, Ca(2+) signaling et, al. Furthermore, animal experiment show icariin could enhance the BMD and BMC, decrease CTX-I level in ovariectomized mice. The mitochondrial membrane potential and the intracellular ATP levels were increased significantly, and the cytoskeleton were improved in icariin-treatment osteoblast and osteoclast. Icariin also increased mRNA expression of Runx2 and osterix of OB, decreased CTR and CAII mRNA expression and protein expression of P38 and JNK. However, icariin did not reveal any inhibition of the collagenolytic activity of cathepsin K, mRNA expression of MMP-9 and protein expression of ERK in osteoclast.
CONCLUSION: we consider icariin as multi-targeting compounds for treating with osteoporosis, involve intiating osteoblastogenesis, inhibiting adipogenesis, and preventing osteoclast differentiation.

PMID: 27422162 [PubMed - as supplied by publisher]

Mesoscopic Model of Neuronal System Deficits in Multiple Sclerosis.

J Theor Biol. 2016 Jul 12;

Authors: Safarbali B, Hadaeghi F, Gharibzadeh S

Abstract
Multiple Sclerosis (MS) is a devastating autoimmune disease which deteriorates the connections in central nervous system (CNS) through the attacks to oligodendrocytes. Studying its origin and progression, in addition to clinical developments such as MRI brain images, cerebrospinal fluid (CSF) variation and quantitative measures of disability (EDSS), which sought to early diagnosis and efficient therapy, there is an increasing interest in developing computational models using the experimental data obtained from MS patients. From the perspective of mathematical modelling, although the origin of systemic symptoms might be attributed to cellular phenomena in microscopic level such as axonal demyelination, symptoms mainly are observed in macroscopic levels. How to fill the gap between these two levels of system modelling, however, remains as a challenge in systems biology studies. Trying to provide a conceptual framework to bridge between these two levels of modelling in systems biology, we have suggested a mesoscopic model composed of interacting neuronal population, which successfully replicates the changes in neuronal population synchrony due to MS progression.

PMID: 27422137 [PubMed - as supplied by publisher]

When communities collide.

Elife. 2016;5

Authors: Merritt J, Kuehn S

Abstract
A new model demonstrates how microbial communities can survive encounters with other communities as a cohesive group, even in the complete absence of cooperation.

PMID: 27420812 [PubMed - as supplied by publisher]

Optimizing cyanobacterial product synthesis: Meeting the challenges.

Bioengineered. 2016 Jul 15;:0

Authors: Zavřel T, Červený J, Knoop H, Steuer R

Abstract
The synthesis of renewable bioproducts using photosynthetic microorganisms holds great promise. Sustainable industrial applications, however, are still scarce and the true limits of phototrophic production remain unknown. One of the limitations of further progress is our insufficient understanding of the quantitative changes in photoautotrophic metabolism that occur during growth in dynamic environments. We argue that a proper evaluation of the intra- and extracellular factors that limit phototrophic production requires the use of highly-controlled cultivation in photobioreactors, coupled to real-time analysis of production parameters and their evaluation by predictive computational models. In this addendum, we discuss the importance and challenges of systems biology approaches for the optimization of renewable biofuels production. As a case study, we present the utilization of a state-of-the-art experimental setup together with a stoichiometric computational model of cyanobacterial metabolism for quantitative evaluation of ethylene production by a recombinant cyanobacterium Synechocystis sp. PCC 6803.

PMID: 27420605 [PubMed - as supplied by publisher]

Developmentally regulated long non-coding RNAs in Xenopus tropicalis.

Dev Biol. 2016 Jul 11;

Authors: Forouzmand E, Owens ND, Blitz IL, Paraiso KD, Khokha MK, Gilchrist MJ, Xie X, Cho KW

Abstract
Advances in RNA sequencing technologies have led to the surprising discovery that a vast number of transcripts emanate from regions of the genome that are not part of coding genes. Although some of the smaller ncRNAs such as microRNAs have well-characterized functions, the majority of long ncRNA (lncRNA) functions remain poorly understood. Understanding the significance of lncRNAs is an important challenge facing biology today. A powerful approach to uncovering the function of lncRNAs is to explore temporal and spatial expression profiling. This may be particularly useful for classes of lncRNAs that have developmentally important roles as the expression of such lncRNAs will be expected to be both spatially and temporally regulated during development. Here, we take advantage of our ultra-high frequency (temporal) sampling of Xenopus embryos to analyze gene expression trajectories of lncRNA transcripts over the first 3 days of development. We computationally identify 5689 potential single- and multi-exon lncRNAs. These lncRNAs demonstrate clear dynamic expression patterns. A subset of them displays highly correlative temporal expression profiles with respect to those of the neighboring genes. We also identified spatially localized lncRNAs in the gastrula stage embryo. These results suggest that lncRNAs have regulatory roles during early embryonic development.

PMID: 27418388 [PubMed - as supplied by publisher]

A roadmap for biocatalysis - functional and spatial orchestration of enzyme cascades.

Microb Biotechnol. 2016 Jul 15;

Authors: Schmidt-Dannert C, Lopez-Gallego F

Abstract
Advances in biological engineering and systems biology have provided new approaches and tools for the industrialization of biology. In the next decade, advanced biocatalytic systems will increasingly be used for the production of chemicals that cannot be made by current processes and/or where the use of enzyme catalysts is more resource efficient with a much reduced environmental impact. We expect that in the future, manufacture of chemicals and materials will utilize both biocatalytic and chemical synthesis synergistically. The realization of such advanced biomanufacturing processes currently faces a number of major challenges. Ready-to-deploy portfolios of biocatalysts for design to production must be created from biological diverse sources and through protein engineering. Robust and efficient multi-step enzymatic reaction cascades must be developed that can operate simultaneously in one-pot. For this to happen, bio-orthogonal strategies for spatial and temporal control of biocatalyst activities must be developed. Promising approaches and technologies are emerging that will eventually lead to the design of in vitro biocatalytic systems that mimic the metabolic pathways and networks of cellular systems which will be discussed in this roadmap.

PMID: 27418373 [PubMed - as supplied by publisher]

Topological Small-World Organization of the Fibroblastic Reticular Cell Network Determines Lymph Node Functionality.

PLoS Biol. 2016 Jul;14(7):e1002515

Authors: Novkovic M, Onder L, Cupovic J, Abe J, Bomze D, Cremasco V, Scandella E, Stein JV, Bocharov G, Turley SJ, Ludewig B

Abstract
Fibroblastic reticular cells (FRCs) form the cellular scaffold of lymph nodes (LNs) and establish distinct microenvironmental niches to provide key molecules that drive innate and adaptive immune responses and control immune regulatory processes. Here, we have used a graph theory-based systems biology approach to determine topological properties and robustness of the LN FRC network in mice. We found that the FRC network exhibits an imprinted small-world topology that is fully regenerated within 4 wk after complete FRC ablation. Moreover, in silico perturbation analysis and in vivo validation revealed that LNs can tolerate a loss of approximately 50% of their FRCs without substantial impairment of immune cell recruitment, intranodal T cell migration, and dendritic cell-mediated activation of antiviral CD8+ T cells. Overall, our study reveals the high topological robustness of the FRC network and the critical role of the network integrity for the activation of adaptive immune responses.

PMID: 27415420 [PubMed - as supplied by publisher]

Network analysis and juvenile idiopathic arthritis (JIA): a new horizon for the understanding of disease pathogenesis and therapeutic target identification.

Pediatr Rheumatol Online J. 2016;14(1):40

Authors: Donn R, De Leonibus C, Meyer S, Stevens A

Abstract
Juvenile idiopathic arthritis (JIA) is a clinically diverse and genetically complex autoimmune disease. Currently, there is very limited understanding of the potential underlying mechanisms that result in the range of phenotypes which constitute JIA.The elucidation of the functional relevance of genetic associations with phenotypic traits is a fundamental problem that hampers the translation of genetic observations to plausible medical interventions. Genome wide association studies, and subsequent fine-mapping studies in JIA patients, have identified many genetic variants associated with disease. Such approaches rely on 'tag' single nucleotide polymorphisms (SNPs). The associated SNPs are rarely functional variants, so the extrapolation of genetic association data to the identification of biologically meaningful findings can be a protracted undertaking. Integrative genomics aims to bridge the gap between genotype and phenotype.Systems biology, principally through network analysis, is emerging as a valuable way to identify biological pathways of relevance to complex genetic diseases. This review aims to highlight recent findings in systems biology related to JIA in an attempt to assist in the understanding of JIA pathogenesis and therapeutic target identification.

PMID: 27411317 [PubMed - in process]

MicroRNA gene expression signatures in long-surviving malignant pleural mesothelioma patients.

Genom Data. 2016 Sep;9:44-9

Authors: Lin RC, Kirschner MB, Cheng YY, van Zandwijk N, Reid G

Abstract
Malignant pleural mesothelioma (MPM) is a tumor originating in the mesothelium, the membrane lining the thoracic cavities, and is induced by exposure to asbestos. Australia suffers one of the world's highest rates of MPM and the incidence is yet to peak. The prognosis for patients with MPM is poor and median survival following diagnosis is 4-18 months. Currently, no or few effective therapies exist for MPM. Trials of targeted agents such as antiangiogenic agents (VEGF, EGFR) or ribonuclease inhibitors (ranpirnase) largely failed to show efficacy in MPM Tsao et al. (2009) [1]. A recent study, however, showed that cisplatin/pemetrexed + bevacizumab (a recombinant humanized monoclonal antibody that inhibit VEGF) treatment has a survival benefit of 2.7 months Zalcman et al. (2016) [2]. It remains to be seen if this targeted therapy will be accepted as a new standard for MPM. Thus the unmet needs of MPM patients remain very pronounced and almost every patient will be confronted with drug resistance and recurrence of disease. We have identified unique gene signatures associated with prolonged survival in mesothelioma patients undergoing radical surgery (EPP, extrapleural pneumonectomy), as well as patients who underwent palliative surgery (pleurectomy/decortication). In addition to data published in Molecular Oncology, 2015;9:715-26 (GSE59180) Kirschner et al. (2015) , we describe here additional data using a system-based approach that support our previous observations. This data provides a resource to further explore microRNA dynamics in MPM.

PMID: 27408810 [PubMed]

A Systems-Level Analysis of the Peripheral Nerve Intrinsic Axonal Growth Program.

Neuron. 2016 Mar 2;89(5):956-70

Authors: Chandran V, Coppola G, Nawabi H, Omura T, Versano R, Huebner EA, Zhang A, Costigan M, Yekkirala A, Barrett L, Blesch A, Michaelevski I, Davis-Turak J, Gao F, Langfelder P, Horvath S, He Z, Benowitz L, Fainzilber M, Tuszynski M, Woolf CJ, Geschwind DH

Abstract
The regenerative capacity of the injured CNS in adult mammals is severely limited, yet axons in the peripheral nervous system (PNS) regrow, albeit to a limited extent, after injury. We reasoned that coordinate regulation of gene expression in injured neurons involving multiple pathways was central to PNS regenerative capacity. To provide a framework for revealing pathways involved in PNS axon regrowth after injury, we applied a comprehensive systems biology approach, starting with gene expression profiling of dorsal root ganglia (DRGs) combined with multi-level bioinformatic analyses and experimental validation of network predictions. We used this rubric to identify a drug that accelerates DRG neurite outgrowth in vitro and optic nerve outgrowth in vivo by inducing elements of the identified network. The work provides a functional genomics foundation for understanding neural repair and proof of the power of such approaches in tackling complex problems in nervous system biology.

PMID: 26898779 [PubMed - indexed for MEDLINE]

BiGG Models: A platform for integrating, standardizing and sharing genome-scale models.

Nucleic Acids Res. 2016 Jan 4;44(D1):D515-22

Authors: King ZA, Lu J, Dräger A, Miller P, Federowicz S, Lerman JA, Ebrahim A, Palsson BO, Lewis NE

Abstract
Genome-scale metabolic models are mathematically-structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repositories of high-quality models must be established, models must adhere to established standards and model components must be linked to relevant databases. Tools for model visualization further enhance their utility. To meet these needs, we present BiGG Models (http://bigg.ucsd.edu), a completely redesigned Biochemical, Genetic and Genomic knowledge base. BiGG Models contains more than 75 high-quality, manually-curated genome-scale metabolic models. On the website, users can browse, search and visualize models. BiGG Models connects genome-scale models to genome annotations and external databases. Reaction and metabolite identifiers have been standardized across models to conform to community standards and enable rapid comparison across models. Furthermore, BiGG Models provides a comprehensive application programming interface for accessing BiGG Models with modeling and analysis tools. As a resource for highly curated, standardized and accessible models of metabolism, BiGG Models will facilitate diverse systems biology studies and support knowledge-based analysis of diverse experimental data.

PMID: 26476456 [PubMed - indexed for MEDLINE]

Renal systems biology of patients with systemic inflammatory response syndrome.

Kidney Int. 2015 Oct;88(4):804-14

Authors: Tsalik EL, Willig LK, Rice BJ, van Velkinburgh JC, Mohney RP, McDunn JE, Dinwiddie DL, Miller NA, Mayer ES, Glickman SW, Jaehne AK, Glew RH, Sopori ML, Otero RM, Harrod KS, Cairns CB, Fowler VG, Rivers EP, Woods CW, Kingsmore SF, Langley RJ

Abstract
A systems biology approach was used to comprehensively examine the impact of renal disease and hemodialysis (HD) on patient response during critical illness. To achieve this, we examined the metabolome, proteome, and transcriptome of 150 patients with critical illness, stratified by renal function. Quantification of plasma metabolites indicated greater change as renal function declined, with the greatest derangements in patients receiving chronic HD. Specifically, 6 uremic retention molecules, 17 other protein catabolites, 7 modified nucleosides, and 7 pentose phosphate sugars increased as renal function declined, consistent with decreased excretion or increased catabolism of amino acids and ribonucleotides. Similarly, the proteome showed increased levels of low-molecular-weight proteins and acute-phase reactants. The transcriptome revealed a broad-based decrease in mRNA levels among patients on HD. Systems integration revealed an unrecognized association between plasma RNASE1 and several RNA catabolites and modified nucleosides. Further, allantoin, N1-methyl-4-pyridone-3-carboxamide, and N-acetylaspartate were inversely correlated with the majority of significantly downregulated genes. Thus, renal function broadly affected the plasma metabolome, proteome, and peripheral blood transcriptome during critical illness; changes were not effectively mitigated by hemodialysis. These studies allude to several novel mechanisms whereby renal dysfunction contributes to critical illness.

PMID: 25993322 [PubMed - indexed for MEDLINE]

Integrating Transcriptomic and Proteomic Data Using Predictive Regulatory Network Models of Host Response to Pathogens.

PLoS Comput Biol. 2016 Jul;12(7):e1005013

Authors: Chasman D, Walters KB, Lopes TJ, Eisfeld AJ, Kawaoka Y, Roy S

Abstract
Mammalian host response to pathogenic infections is controlled by a complex regulatory network connecting regulatory proteins such as transcription factors and signaling proteins to target genes. An important challenge in infectious disease research is to understand molecular similarities and differences in mammalian host response to diverse sets of pathogens. Recently, systems biology studies have produced rich collections of omic profiles measuring host response to infectious agents such as influenza viruses at multiple levels. To gain a comprehensive understanding of the regulatory network driving host response to multiple infectious agents, we integrated host transcriptomes and proteomes using a network-based approach. Our approach combines expression-based regulatory network inference, structured-sparsity based regression, and network information flow to infer putative physical regulatory programs for expression modules. We applied our approach to identify regulatory networks, modules and subnetworks that drive host response to multiple influenza infections. The inferred regulatory network and modules are significantly enriched for known pathways of immune response and implicate apoptosis, splicing, and interferon signaling processes in the differential response of viral infections of different pathogenicities. We used the learned network to prioritize regulators and study virus and time-point specific networks. RNAi-based knockdown of predicted regulators had significant impact on viral replication and include several previously unknown regulators. Taken together, our integrated analysis identified novel module level patterns that capture strain and pathogenicity-specific patterns of expression and helped identify important regulators of host response to influenza infection.

PMID: 27403523 [PubMed - as supplied by publisher]

Multi-OMICs and Genome Editing Perspectives on Liver Cancer Signaling Networks.

Biomed Res Int. 2016;2016:6186281

Authors: Lin S, Yin YA, Jiang X, Sahni N, Yi S

Abstract
The advent of the human genome sequence and the resulting ~20,000 genes provide a crucial framework for a transition from traditional biology to an integrative "OMICs" arena (Lander et al., 2001; Venter et al., 2001; Kitano, 2002). This brings in a revolution for cancer research, which now enters a big data era. In the past decade, with the facilitation by next-generation sequencing, there have been a huge number of large-scale sequencing efforts, such as The Cancer Genome Atlas (TCGA), the HapMap, and the 1000 genomes project. As a result, a deluge of genomic information becomes available from patients stricken by a variety of cancer types. The list of cancer-associated genes is ever expanding. New discoveries are made on how frequent and highly penetrant mutations, such as those in the telomerase reverse transcriptase (TERT) and TP53, function in cancer initiation, progression, and metastasis. Most genes with relatively frequent but weakly penetrant cancer mutations still remain to be characterized. In addition, genes that harbor rare but highly penetrant cancer-associated mutations continue to emerge. Here, we review recent advances related to cancer genomics, proteomics, and systems biology and suggest new perspectives in targeted therapy and precision medicine.

PMID: 27403431 [PubMed - in process]

Graphics processing units in bioinformatics, computational biology and systems biology.

Brief Bioinform. 2016 Jul 8;

Authors: Nobile MS, Cazzaniga P, Tangherloni A, Besozzi D

Abstract
Several studies in Bioinformatics, Computational Biology and Systems Biology rely on the definition of physico-chemical or mathematical models of biological systems at different scales and levels of complexity, ranging from the interaction of atoms in single molecules up to genome-wide interaction networks. Traditional computational methods and software tools developed in these research fields share a common trait: they can be computationally demanding on Central Processing Units (CPUs), therefore limiting their applicability in many circumstances. To overcome this issue, general-purpose Graphics Processing Units (GPUs) are gaining an increasing attention by the scientific community, as they can considerably reduce the running time required by standard CPU-based software, and allow more intensive investigations of biological systems. In this review, we present a collection of GPU tools recently developed to perform computational analyses in life science disciplines, emphasizing the advantages and the drawbacks in the use of these parallel architectures. The complete list of GPU-powered tools here reviewed is available at http://bit.ly/gputools.

PMID: 27402792 [PubMed - as supplied by publisher]

PetriScape - A plugin for discrete Petri net simulations in Cytoscape.

J Integr Bioinform. 2016;13(1):284

Authors: Almeida D, Azevedo V, Silva A, Baumbach J

Abstract
Systems biology plays a central role for biological network analysis in the post-genomic era. Cytoscape is the standard bioinformatics tool offering the community an extensible platform for computational analysis of the emerging cellular network together with experimental omics data sets. However, only few apps/plugins/tools are available for simulating network dynamics in Cytoscape 3. Many approaches of varying complexity exist but none of them have been integrated into Cytoscape as app/plugin yet. Here, we introduce PetriScape, the first Petri net simulator for Cytoscape. Although discrete Petri nets are quite simplistic models, they are capable of modeling global network properties and simulating their behaviour. In addition, they are easily understood and well visualizable. PetriScape comes with the following main functionalities: (1) import of biological networks in SBML format, (2) conversion into a Petri net, (3) visualization as Petri net, and (4) simulation and visualization of the token flow in Cytoscape. PetriScape is the first Cytoscape plugin for Petri nets. It allows a straightforward Petri net model creation, simulation and visualization with Cytoscape, providing clues about the activity of key components in biological networks.

PMID: 27402693 [PubMed - in process]

The Notch meeting: an odyssey from structure to function.

Development. 2016 Feb 15;143(4):547-53

Authors: Chitnis A, Balle-Cuif L

Abstract
The Notch signaling pathway plays fundamental roles in diverse developmental processes. Studies of the basic biology of Notch function have provided insights into how its dysfunction contributes to multi-systemic diseases and cancer. In addition, our understanding of Notch signaling in maintaining stem/progenitor cell populations is revealing new avenues for rekindling regeneration. The Notch IX meeting, which was held in Athens, Greece in October 2015, brought together scientists working on different model systems and studying Notch signaling in various contexts. Here, we provide a summary of the key points that were presented at the meeting. Although we focus on the molecular mechanisms that determine Notch signaling and its role in development, we also cover talks describing roles for Notch in adulthood. Together, the talks revealed how interactions between adjacent cells mediated by Notch regulate development and physiology at multiple levels.

PMID: 26884393 [PubMed - indexed for MEDLINE]

Slowing Down of Recovery as Generic Risk Marker for Acute Severity Transitions in Chronic Diseases.

Crit Care Med. 2016 Mar;44(3):601-6

Authors: Olde Rikkert MG, Dakos V, Buchman TG, Boer Rd, Glass L, Cramer AO, Levin S, van Nes E, Sugihara G, Ferrari MD, Tolner EA, van de Leemput I, Lagro J, Melis R, Scheffer M

Abstract
OBJECTIVE: We propose a novel paradigm to predict acute attacks and exacerbations in chronic episodic disorders such as asthma, cardiac arrhythmias, migraine, epilepsy, and depression. A better generic understanding of acute transitions in chronic dynamic diseases is increasingly important in critical care medicine because of the higher prevalence and incidence of these chronic diseases in our aging societies.
DATA SOURCES: PubMed, Medline, and Web of Science.
STUDY SELECTION: We selected studies from biology and medicine providing evidence of slowing down after a perturbation as a warning signal for critical transitions.
DATA EXTRACTION: Recent work in ecology, climate, and systems biology has shown that slowing down of recovery upon perturbations can indicate loss of resilience across complex, nonlinear biologic systems that are approaching a tipping point. This observation is supported by the empiric studies in pathophysiology and controlled laboratory experiments with other living systems, which can flip from one state of clinical balance to a contrasting one. We discuss examples of such evidence in bodily functions such as blood pressure, heart rate, mood, and respiratory regulation when a tipping point for a transition is near.
CONCLUSIONS: We hypothesize that in a range of chronic episodic diseases, indicators of critical slowing down, such as rising variance and temporal correlation, may be used to assess the risk of attacks, exacerbations, and even mortality. Identification of such early warning signals over a range of diseases will enhance the understanding of why, how, and when attacks and exacerbations will strike and may thus improve disease management in critical care medicine.

PMID: 26765499 [PubMed - indexed for MEDLINE]