Metastability of non-reversible mean-field Potts model with three spins

We examine a non-reversible, mean-field Potts model with three spins on a set with $N\uparrow\infty$ points. Without an external field, there are three critical temperatures and five different metastable regimes. The analysis can be extended by a perturbative argument to the case of small external fields. We illustrate the case of large external fields with some phenomena which are not present in the absence of external field.Comment: 34 pages, 12 figure

Tunneling and Metastability of continuous time Markov chains

We propose a new definition of metastability of Markov processes on countable state spaces. We obtain sufficient conditions for a sequence of processes to be metastable. In the reversible case these conditions are expressed in terms of the capacity and of the stationary measure of the metastable states

Local mutations:On the tentative beginnings of molecular oncology in Britain 1980–2000

Popular and scientific accounts of the molecularisation of cancer typically attribute it to advances in laboratory science, particularly molecular geneticists. However, historical research has indicated that clinical expertise input was often vital for advancing such work. The present paper reinforces that view. Looking in detail at British research into the molecular genetics of familial cancers during the 1980s and 1990s, it shows that that research, too, depended on crucial input from family cancer clinics. Moreover, the development of clinical services for familial cancers was in turn shaped by the demands of contributing to molecular genetic research. The paper concludes that accounts of the molecularisation of cancer that suppose a one-way transfer of knowledge and practice from laboratory to clinic misrepresent the complex interactions that were involved in molecularising familial cancers, and that were informed by the particular local and national circumstances in which they took shape

Bigger, Faster, Better? Rhetorics and Practices of Large-Scale Research in Contemporary Bioscience

publication-status: Publishedtypes: ArticleEditorial for Special Issu

Integrated trajectories of the maternal metabolome, proteome, and immunome predict labor onset

Estimating the time of delivery is of high clinical importance because pre- and postterm deviations are associated with complications for the mother and her offspring. However, current estimations are inaccurate. As pregnancy progresses toward labor, major transitions occur in fetomaternal immune, metabolic, and endocrine systems that culminate in birth. The comprehensive characterization of maternal biology that precedes labor is key to understanding these physiological transitions and identifying predictive biomarkers of delivery. Here, a longitudinal study was conducted in 63 women who went into labor spontaneously. More than 7000 plasma analytes and peripheral immune cell responses were analyzed using untargeted mass spectrometry, aptamer-based proteomic technology, and single-cell mass cytometry in serial blood samples collected during the last 100 days of pregnancy. The high-dimensional dataset was integrated into a multiomic model that predicted the time to spontaneous labor [R = 0.85, 95% confidence interval (CI) [0.79 to 0.89], P = 1.2 × 10−40, N = 53, training set; R = 0.81, 95% CI [0.61 to 0.91], P = 3.9 × 10−7, N = 10, independent test set]. Coordinated alterations in maternal metabolome, proteome, and immunome marked a molecular shift from pregnancy maintenance to prelabor biology 2 to 4 weeks before delivery. A surge in steroid hormone metabolites and interleukin-1 receptor type 4 that preceded labor coincided with a switch from immune activation to regulation of inflammatory responses. Our study lays the groundwork for developing blood-based methods for predicting the day of labor, anchored in mechanisms shared in preterm and term pregnancies

Molecular Genetic Features of Polyploidization and Aneuploidization Reveal Unique Patterns for Genome Duplication in Diploid Malus

Polyploidization results in genome duplication and is an important step in evolution and speciation. The Malus genome confirmed that this genus was derived through auto-polyploidization, yet the genetic and meiotic mechanisms for polyploidization, particularly for aneuploidization, are unclear in this genus or other woody perennials. In fact the contribution of aneuploidization remains poorly understood throughout Plantae. We add to this knowledge by characterization of eupolyploidization and aneuploidization in 27,542 F1 seedlings from seven diploid Malus populations using cytology and microsatellite markers. We provide the first evidence that aneuploidy exceeds eupolyploidy in the diploid crosses, suggesting aneuploidization is a leading cause of genome duplication. Gametes from diploid Malus had a unique combinational pattern; ova preserved euploidy exclusively, while spermatozoa presented both euploidy and aneuploidy. All non-reduced gametes were genetically heterozygous, indicating first-division restitution was the exclusive mode for Malus eupolyploidization and aneuploidization. Chromosome segregation pattern among aneuploids was non-uniform, however, certain chromosomes were associated for aneuploidization. This study is the first to provide molecular evidence for the contribution of heterozygous non-reduced gametes to fitness in polyploids and aneuploids. Aneuploidization can increase, while eupolyploidization may decrease genetic diversity in their newly established populations. Auto-triploidization is important for speciation in the extant Malus. The features of Malus polyploidization confer genetic stability and diversity, and present heterozygosity, heterosis and adaptability for evolutionary selection. A protocol using co-dominant markers was proposed for accelerating apple triploid breeding program. A path was postulated for evolution of numerically odd basic chromosomes. The model for Malus derivation was considerably revised. Impacts of aneuploidization on speciation and evolution, and potential applications of aneuploids and polyploids in breeding and genetics for other species were evaluated in depth. This study greatly improves our understanding of evolution, speciation, and adaptation of the Malus genus, and provides strategies to exploit polyploidization in other species

Deregulation of CREB Signaling Pathway Induced by Chronic Hyperglycemia Downregulates NeuroD Transcription

CREB mediates the transcriptional effects of glucose and incretin hormones in insulin-target cells and insulin-producing β-cells. Although the inhibition of CREB activity is known to decrease the β-cell mass, it is still unknown what factors inversely alter the CREB signaling pathway in β-cells. Here, we show that β-cell dysfunctions occurring in chronic hyperglycemia are not caused by simple inhibition of CREB activity but rather by the persistent activation of CREB due to decreases in protein phophatase PP2A. When freshly isolated rat pancreatic islets were chronically exposed to 25 mM (high) glucose, the PP2A activity was reduced with a concomitant increase in active pCREB. Brief challenges with 15 mM glucose or 30 µM forskolin after 2 hour fasting further increased the level of pCREB and consequently induced the persistent expression of ICER. The excessively produced ICER was sufficient to repress the transcription of NeuroD, insulin, and SUR1 genes. In contrast, when islets were grown in 5 mM (low) glucose, CREB was transiently activated in response to glucose or forskolin stimuli. Thus, ICER expression was transient and insufficient to repress those target genes. Importantly, overexpression of PP2A reversed the adverse effects of chronic hyperglycemia and successfully restored the transient activation of CREB and ICER. Conversely, depletion of PP2A with siRNA was sufficient to disrupt the negative feedback regulation of CREB and induce hyperglycemic phenotypes even under low glucose conditions. Our findings suggest that the failure of the negative feedback regulation of CREB is the primary cause for β-cell dysfunctions under conditions of pathogenic hyperglycemia, and PP2A can be a novel target for future therapies aiming to protect β-cells mass in the late transitional phase of non-insulin dependent type 2 diabetes (NIDDM)

Chemical genetics strategies for identification of molecular targets

Chemical genetics is an emerging field that can be used to study the interactions of chemical compounds, including natural products, with proteins. Usually, the identification of molecular targets is the starting point for studying a drug’s mechanism of action and this has been a crucial step in understanding many biological processes. While a great variety of target identification methods have been developed over the last several years, there are still many bioactive compounds whose target proteins have not yet been revealed because no routine protocols can be adopted. This review contains information concerning the most relevant principles of chemical genetics with special emphasis on the different genomic and proteomic approaches used in forward chemical genetics to identify the molecular targets of the bioactive compounds, the advantages and disadvantages of each and a detailed list of successful examples of molecular targets identified with these approaches

The babel of drugs: On the consequences of evidential pluralism in pharmaceutical regulation and regulatory data journeys

This is the final version. Available on open access from Springer via the DOI in this recordThroughout the last century, pharmaceutical regulators all over the world have used various methods to test medical treatments. From 1962 until 2016, the Randomized Clinical Trial (RCT) was the reference test for most regulatory agencies. Today, the standards are about to change, and in this chapter we draw on the idea of the data journey to illuminate the trade-offs involved. The 21st Century Cures Act (21CCA) allows for the use of Electronic Health Records (EHRs) for the assessment of different treatment indications for already approved drugs. This might arguably shorten the testing period, bringing treatments to patients faster. Yet, EHR are not generated for testing purposes and no amount of standardization and curation can fully make up for their potential flaws as evidence of safety and efficacy. The more noise in the data, the more mistakes regulators are likely to make in granting market access to new drugs. In this paper we will discuss the different dimensions of this journey: the different sources and levels of curation involved, the speed at which they can travel, and the level of risk of regulatory error involved as compared with the RCT standard. We are going to defend that what counts as evidence, at the end of the journey, depends on the risk definition and threshold regulators work with.European Research Council (ERC)Engineering and Physical Sciences Research Council (EPSRC