Formulations for delivery of therapeutic proteins

Advances in biotechnology have now created a capacity to produce therapeutically active proteins on a commercial scale, opening the potential for their application in an array of disease conditions. The process of translation of the variety of different therapeutic proteins into the medicines used in clinics is now occurring. To assist in this translation, new formulations to deliver proteins could play an important role. These new formulations need to more adequately address the pharmacological and therapeutic requirement for each particular protein/peptide and, in that way, either improve present therapies or extend with new entries the current list of protein based medicines used in clinic.

Leitlinien zur molekulargenetischen Diagnostik: Fragiles-X und Fragiles-X assoziiertes Tremor/Ataxie Syndrom

Ohne Zusammenfassung

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Corpus Interruptus: Biotech Drugs, Insurance Providers and the Treatment of Breast Cancer

In researching the biomedically-engineered drug Neulasta (filgrastim), a breast cancer patient becomes aware of the extent to which knowledge about the development and marketing of drugs influences her decisions with regard to treatment. Time spent on understanding the commercial interests of insurers and pharmaceutical companies initially thwarts but ultimately aids the healing process. This first-person narrative calls for physicians to recognize that the alignment of commercial interests transgresses the patient’s humanity.

Modeling brain dynamics using computational neurogenetic approach

The paper introduces a novel computational approach to brain dynamics modeling that integrates dynamic gene–protein regulatory networks with a neural network model. Interaction of genes and proteins in neurons affects the dynamics of the whole neural network. Through tuning the gene–protein interaction network and the initial gene/protein expression values, different states of the neural network dynamics can be achieved. A generic computational neurogenetic model is introduced that implements this approach. It is illustrated by means of a simple neurogenetic model of a spiking neural network of the generation of local field potential. Our approach allows for investigation of how deleted or mutated genes can alter the dynamics of a model neural network. We conclude with the proposal how to extend this approach to model cognitive neurodynamics.

Individual variability of behavioural responses by Wandering Albatrosses (Diomedea exulans) to human disturbance

Sub-Antarctic Marion Island has had a permanent research station for 50 years and the islands Wandering Albatrosses have been intensively studied for 20 years. The reactions of breeding birds to approaches by a human on foot were recorded. Three response variables were calculated: intensity of vocal reaction (IVR), intensity of non-vocal reaction (INR) and overall response index (ORI). At 5 m from the nest, twice as many birds stood and/or vocalised as at 15 m. Nearest neighbour distance, age and gender did not explain individual variability of responses. Study colony birds had higher IVR scores than non-study colony birds; birds at colonies closest to the station had the highest ORI scores. A better breeding record was associated with lower IVR and ORI scores, but a causative relationship remains to be demonstrated. A minimum viewing distance of 25 m is recommended for breeding Wandering Albatrosses.

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Why Folkbiology Matters: Resource Conflict Despite Shared Goals and Knowledge

There is a continuing controversy over Native American fishing and hunting rights. We show that Native American (Menominee) and European American fish experts have a common knowledge base and share values and attitudes associated with fishing practices (though organized around different ethical principles). Nonetheless, perceived group differences are dramatic (especially European American perceptions of Native Americans). Cultural differences in models of nature and associated inference processes appear to mediate these stereotypes and may hold the key to reducing intergroup conflict over resources.

Forty Years of ‘The Strategy’: Levins on Model Building and Idealization

This paper is an interpretation and defense of Richard Levins’ “The Strategy of Model Building in Population Biology,” which has been extremely influential among biologists since its publication 40 years ago. In this article, Levins confronted some of the deepest philosophical issues surrounding modeling and theory construction. By way of interpretation, I discuss each of Levins’ major philosophical themes: the problem of complexity, the brute-force approach, the existence and consequence of tradeoffs, and robustness analysis. I argue that Levins’ article is concerned, at its core, with justifying the use of multiple, idealized models in population biology.

Hierarchical analysis of piecewise affine models of gene regulatory networks

A key point in the analysis of dynamical models of biological systems is to handle systems of relatively high dimensions. In the present paper we propose a method to hierarchically organize a certain type of piecewise affine (PWA) differential systems. This specific class of systems has been extensively studied for the past few years, as it provides a good framework to model gene regulatory networks. The method, shown on several examples, allows a qualitative analysis of the asymptotic behavior of a PWA system, decomposing it into several smaller subsystems. This technique, based on the well-known strongly connected components decomposition, is not new. However, its adaptation to the non-smooth PWA differential equations turns out to be quite relevant because of the strong discrete structure underlying these equations. Its biological relevance is shown on a 7-dimensional PWA system modeling the gene network responsible for the carbon starvation response in Escherichia coli.

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Engineering-approach accelerates computational understanding of V1–V2 neural properties

We present two computational models (i) long-range horizontal connections and the nonlinear effect in V1 and (ii) the filling-in process at the blind spot. Both models are obtained deductively from standard regularization theory to show that physiological evidence of V1 and V2 neural properties is essential for efficient image processing. We stress that the engineering approach should be imported to understand visual systems computationally, even though this approach usually ignores physiological evidence and the target is neither neurons nor the brain.

Hennigian Phylogenetic Systematics and the ‘Groundplan’ vs. ‘Post-Groundplan’ Approaches: A Reply to Kukalová-Peck

The recent contribution by Jarmila Kukalová-Peck on Hennigian phylogenetics and hexapod limb evolution is critically evaluated.

Strategies of abstraction

Abstraction is seen as an active process which both enlightens and obscures. Abstractions are not true or false but relatively enlightening or obscuring according to the problem under study; different abstractions may grasp different aspects of a problem. Abstractions may be useless if they can answer questions only about themselves. A theoretical enterprise explores reality through acluster of abstractions that use different perspectives, temporal and horizontal scales, and assumes different givens.

Towards dynamical system models of language-related brain potentials

Event-related brain potentials (ERP) are important neural correlates of cognitive processes. In the domain of language processing, the N400 and P600 reflect lexical-semantic integration and syntactic processing problems, respectively. We suggest an interpretation of these markers in terms of dynamical system theory and present two nonlinear dynamical models for syntactic computations where different processing strategies correspond to functionally different regions in the system’s phase space.

Is it a revolution?

Jablonka and Lamb's claim that evolutionary biology is undergoing a ‘revolution’ is queried. But the very concept of revolutionary change has uncertain application to a field organized in the manner of contemporary biology. The explanatory primacy of sequence properties is also discussed.

Gridcast—a next generation broadcast infrastructure?

Gridcast is an R&D project investigating grid ideas and technologies in the broadcasting technical infrastructure. In this paper I discuss the business and technical issues in building infrastructures to support broadcasters and outline the structure of the Gridcast grid-based service oriented architecture for broadcasting playout support.

Individual optimization efforts and population dynamics: a mathematical model for the evolution of resource allocation strategies, with applications to reproductive and mating systems

We develop a formal framework for the optimal allocation of limited resources that includes and clarifies the interplay between individual optimization and the resulting effects at the population level. As an example, in regard to the evolution of sexual recombination, the paradox of the twofold cost of sex is avoided by distinguishing between the evolution of recombination and the subsequent emergence and stability of different mating types as a result of individual optimization within a population that benefits from recombination.

Autonomic power and performance management for computing systems

With the increased complexity of platforms, the growing demand of applications and data centers’ servers sprawl, power consumption is reaching unsustainable limits. The need to improved power management is becoming essential for many reasons including reduced power consumption & cooling, improved density, reliability & compliance with environmental standards. This paper presents a theoretical framework and methodology for autonomic power and performance management in e-business data centers. We optimize for power and performance (performance-per-watt) at each level of the hierarchy while maintaining scalability. We adopt mathematically-rigorous optimization approach to minimize power while meeting performance constraints. Our experimental results show around 72% savings in power while maintaining performance as compared to static power management techniques and 69.8% additional savings with both global and local optimizations.