A microfluidic setup for quantifying single-cell transcription regulatory dynamics

Bacteria are exposed to fluctuations in their environment and can respond to such changes by regulating gene expression, often at the level of transcription. Since gene expression is an inherently stochastic process, identical cells within a single environment display heterogeneous expression levels. To understand how the stochastic processes in gene expression affect the dynamics of single-cell gene regulation it is necessary to observe gene expression in single cells in changing environments. Recently developed microfluidic devices combined with quantitative fluorescence time-lapse microscopy allow lineages of single cells to be followed over long timescales and to measure their growth and gene expression phenotypes simultaneously. However these devices are missing the environmental control needed to study gene regulation. Therefore we set out to find a way to combine the longterm observation of single cells with precise environmental control in a single microfluidic chip. As a basis we chose a device called the Mother Machine in which single files of cells are growing in small dead end growth channels. These growth channels are connected to a main channel with a constant flow of medium for nutrient diffusion into the growth channels. The cells at the dead end of the growth channels are trapped and when dividing push their progeny into the main channel where they are removed by the flow. Therefore the trapped cell can be monitored essentially for its whole lifetime, while its progeny can only be observed for a short timeframe before they leave the growth channel. By combining the Mother Machine design with a specialized dual input junction and mixing serpentines for environmental control we developed a device that offers new prospects in studying gene regulation. Together with the device we developed an easy to use software solution to analyze data from Mother Machine like devices together with our collaboration partners. This integrated experimental and computational setup will be an important tool to understand the genetic basis for differences in single-cell expression distributions, and to understand how natural selection has shaped single-cell gene regulation. As a first example we show how single cells differ in the regulation of the expression of the lac operon when exposed to alternating changes in the available carbon source switching between glucose and lactose every 4h

Erhöhtes Risiko für Stentthrombosen bei DES?

Zusammenfassung: Im Vergleich zu unbeschichteten Stents ("bare-metal stents" [BMS]) verhindern medikamentenbeschichtete Stents ("drug-eluting stents" [DES]) mit großer Effektivität die Entstehung von Restenosen und damit die Notwendigkeit von Wiedereingriffen am behandelten Gefäß. Die Langzeitmortalität wird durch DES im Vergleich zu BMS weder im positiven noch im negativen Sinne beeinflusst. Späte Stentthrombosen nach Implantation von DES sind selten, aber dennoch häufiger als nach Implantation von BMS. Die einzige heute zur Verfügung stehende Maßnahme, das Auftreten später Stentthrombosen einzudämmen, ist die Verlängerung der dualen plättchenhemmenden Therapie über 12 Monate. In Zukunft müssen einerseits durch weitere Studien speziell von DES profitierende Patientensubgruppen identifiziert und andererseits verbesserte Stents mit geringerem Risiko zur Entwicklung einer späten Stentthrombose entwickelt werde

Models and numbers: Representing the world or imposing order?

We argue for a foundational epistemic claim and a hypothesis about the production and uses of mathematical epidemiological models, exploring the consequences for our political and socio-economic lives. First, in order to make the best use of scientific models, we need to understand why models are not truly representational of our world, but are already pitched towards various uses. Second, we need to understand the implicit power relations in numbers and models in public policy, and, thus, the implications for good governance if numbers and models are used as the exclusive drivers of decision making.acceptedVersio

Rainbow bases in matroids

Recently, it was proved by B\'erczi and Schwarcz that the problem of factorizing a matroid into rainbow bases with respect to a given partition of its ground set is algorithmically intractable. On the other hand, many special cases were left open. We first show that the problem remains hard if the matroid is graphic, answering a question of B\'erczi and Schwarcz. As another special case, we consider the problem of deciding whether a given digraph can be factorized into subgraphs which are spanning trees in the underlying sense and respect upper bounds on the indegree of every vertex. We prove that this problem is also hard. This answers a question of Frank. In the second part of the article, we deal with the relaxed problem of covering the ground set of a matroid by rainbow bases. Among other results, we show that there is a linear function $f$ such that every matroid that can be factorized into $k$ bases for some $k \geq 3$ can be covered by $f(k)$ rainbow bases if every partition class contains at most 2 elements

Brokerage at the science–policy interface: from conceptual framework to practical guidance

This article analyses the conceptual framework of brokerage at the science–policy interface as an important boundary function to support trusted and transparent government decision-making. Policymaking involves a broad range of considerations, but science advice and evidence is critical to help inform decisions. However, mechanisms for requesting and receiving advice from the scientific community are not straightforward, considering that the knowledge needed generally spans multiple disciplines of the natural and social sciences. Once evidence has been appropriately synthesized, there remains the need to ensure an effective and unbiased translation to the policy and political community. The concept of knowledge brokerage revolves around an understanding of the ontologies, cultures and languages of both the policy community and the science community, in order to effectively link the two bidirectionally. In practical terms, this means ensuring that the information needs of the former are understood, and that the type and form of information offered by the latter aligns with those needs. Ideally, knowledge brokers act at the interface between researchers/experts and decision-makers to present evidence in a way that informs policy options but does not determine policy development. Conceptually, negotiating this interface involves acknowledging that values are embedded in the scientific process and evidentiary synthesis, and in particular, in considering the inferential risks inherent in making evidence claims. Brokers are faced with navigating complex policy dynamics and balancing information asymmetries between research providers and users. Building on the conceptual analysis and examination of the nuances of brokerage observed in practice, we propose a set of guidelines to translate the concepts of brokerage to practical application.publishedVersio