Effects of culture media and suspension expansion technologies in mesenchymal stem cell manufacturing - A computational bioprocess and bioeconomics study

Mesenchymal stem cell (MSC) based therapies are promising for a large spectrum of unmet medical needs. Despite this promise, the scaling-up of production of clinical grade MSCs is hindered by the use of planar technologies that require intensive labor and are not enough to meet market demands, as well as due to high product and process variability introduced by the use of xenogeneic materials. This work presents a new bioprocess and bioeconomics model of stem cell expansion to support informed decisions for stem cells process scaling up at reduced annual costs. The intrinsic equations and parameters that capture the cell biological features, according with their source and media used, are embedded in the model. A target number of cells per dose of 140 million and a GMP facility of 400 sq mt with 4 BSCs and 8 incubators will be used as the baseline for expansion of both bone marrow MSCs (BM-MSCs) and adipose stem cells (ASCs) using planar expansion technologies. The current standard medium for MSC culture containing fetal bovine serum (FBS) will be compared with the xeno-free alternative of human platelet lysate (hPL). The use of hPL for both cell sources results in an increase of the number of doses produced and a decrease of the cost of goods (CoG) per dose (Table 1). In order to improve the production capacity, 8 bioreactors with capacity up to 50L were input in the model, using xeno-free plastic microcarriers for cell adhesion and hPL as the culture medium. The model results indicate that the investment in the use of suspension cultures is valuable due to a considerable increase in the production and a decrease of CoG/dose. As the number of doses produced per year increases, the reagent costs dominate relatively to the facility costs (Fig. 1). Sensitivity analysis was performed by varying 11 model variables by +/- 33%. The main factors that influence annual capacity and CoGs are related to harvesting density and yield, growth rates and microcarrier area and concentration (Table 2). These findings may be used to improve the design of expansion methods with fully xeno-free materials and highlight the relevance of the optimization of harvesting and downstream processing protocols. Please click Additional Files below to see the full abstract

Magnetic fluctuations in 2D metals close to the Stoner instability

We consider the effect of potential disorder on magnetic properties of a two-dimensional metallic system (with conductance $g\gg 1$) when interaction in the triplet channel is so strong that the system is close to the threshold of the Stoner instability. We show, that under these conditions there is an exponentially small probability for the system to form local spin droplets which are local regions with non zero spin density. Using a non-local version of the optimal fluctuation method we find analytically the probability distribution and the typical spin of a local spin droplet (LSD). In particular, we show that both the probability to form a LSD and its typical spin are independent of the size of the droplet (within the exponential accuracy). The LSDs manifest themselves in temperature dependence of observable quantities. We show, that below certain cross-over temperature the paramagnetic susceptibility acquires the Curie-like temperature dependence, while the dephasing time (extracted from magneto-resistance measurements) saturates.Comment: 15 pages, 4 figure

A unifying framework for seed sensitivity and its application to subset seeds

We propose a general approach to compute the seed sensitivity, that can be applied to different definitions of seeds. It treats separately three components of the seed sensitivity problem -- a set of target alignments, an associated probability distribution, and a seed model -- that are specified by distinct finite automata. The approach is then applied to a new concept of subset seeds for which we propose an efficient automaton construction. Experimental results confirm that sensitive subset seeds can be efficiently designed using our approach, and can then be used in similarity search producing better results than ordinary spaced seeds

Schwinger-Keldysh Approach to Disordered and Interacting Electron Systems: Derivation of Finkelstein's Renormalization Group Equations

We develop a dynamical approach based on the Schwinger-Keldysh formalism to derive a field-theoretic description of disordered and interacting electron systems. We calculate within this formalism the perturbative RG equations for interacting electrons expanded around a diffusive Fermi liquid fixed point, as obtained originally by Finkelstein using replicas. The major simplifying feature of this approach, as compared to Finkelstein's is that instead of $N \to 0$ replicas, we only need to consider N=2 species. We compare the dynamical Schwinger-Keldysh approach and the replica methods, and we present a simple and pedagogical RG procedure to obtain Finkelstein's RG equations.Comment: 22 pages, 14 figure

Electrons in an annealed environment: A special case of the interacting electron problem

The problem of noninteracting electrons in the presence of annealed magnetic disorder, in addition to nonmagnetic quenched disorder, is considered. It is shown that the proper physical interpretation of this model is one of electrons interacting via a potential that is long-ranged in time, and that its technical analysis by means of renormalization group techniques must also be done in analogy to the interacting problem. As a result, and contrary to previous claims, the model does not simply describe a metal-insulator transition in $d=2+\epsilon$ ($\epsilon\ll 1$) dimensions. Rather, it describes a transition to a ferromagnetic state that, as a function of the disorder, precedes the metal-insulator transition close to $d=2$. In $d=3$, a transition from a paramagnetic metal to a paramagnetic insulator is possible.Comment: 13 pp., LaTeX, 2 eps figs; final version as publishe

Interplay of quantum magnetic and potential scattering around Zn or Ni impurity ions in superconducting cuprates

To describe the scattering of superconducting quasiparticles from non-magnetic (Zn) or magnetic (Ni) impurities in optimally doped high T$_c$ cuprates, we propose an effective Anderson model Hamiltonian of a localized electron hybridizing with $d_{x^2-y^2}$-wave BCS type superconducting quasiparticles with an attractive scalar potential at the impurity site. Due to the strong local antiferromagnetic couplings between the original Cu ions and their nearest neighbors, the localized electron in the Ni-doped materials is assumed to be on the impurity sites, while in the Zn-doped materials the localized electron is distributed over the four nearest neighbor sites of the impurities with a dominant $d_{x^2-y^2}$ symmetric form of the wave function. With Ni impurities, two resonant states are formed above the Fermi level in the local density of states at the impurity site, while for Zn impurities a sharp resonant peak below the Fermi level dominates in the local density of states at the Zn site, accompanied by a small and broad resonant state above the Fermi level mainly induced by the potential scattering. In both cases, there are no Kondo screening effects. The local density of states and their spatial distribution at the dominant resonant energy around the substituted impurities are calculated for both cases, and they are in good agreement with the experimental results of scanning tunneling microscopy in Bi$_2$Sr$_2$CaCu$_2$O$_{8+\delta}$ with Zn or Ni impurities, respectively.Comment: 24 pages, Revtex, 8 figures, submitted to Physical Review B for publication. Sub-ject Class: Superconductivity; Strongly Correlated Electron

Protein sequence and structure: Is one more fundamental than the other?

We argue that protein native state structures reside in a novel "phase" of matter which confers on proteins their many amazing characteristics. This phase arises from the common features of all globular proteins and is characterized by a sequence-independent free energy landscape with relatively few low energy minima with funnel-like character. The choice of a sequence that fits well into one of these predetermined structures facilitates rapid and cooperative folding. Our model calculations show that this novel phase facilitates the formation of an efficient route for sequence design starting from random peptides.Comment: 7 pages, 4 figures, to appear in J. Stat. Phy

Thermostatistics of deformed bosons and fermions

Based on the q-deformed oscillator algebra, we study the behavior of the mean occupation number and its analogies with intermediate statistics and we obtain an expression in terms of an infinite continued fraction, thus clarifying successive approximations. In this framework, we study the thermostatistics of q-deformed bosons and fermions and show that thermodynamics can be built on the formalism of q-calculus. The entire structure of thermodynamics is preserved if ordinary derivatives are replaced by the use of an appropriate Jackson derivative and q-integral. Moreover, we derive the most important thermodynamic functions and we study the q-boson and q-fermion ideal gas in the thermodynamic limit.Comment: 14 pages, 2 figure

Knowledge-based energy functions for computational studies of proteins

This chapter discusses theoretical framework and methods for developing knowledge-based potential functions essential for protein structure prediction, protein-protein interaction, and protein sequence design. We discuss in some details about the Miyazawa-Jernigan contact statistical potential, distance-dependent statistical potentials, as well as geometric statistical potentials. We also describe a geometric model for developing both linear and non-linear potential functions by optimization. Applications of knowledge-based potential functions in protein-decoy discrimination, in protein-protein interactions, and in protein design are then described. Several issues of knowledge-based potential functions are finally discussed.Comment: 57 pages, 6 figures. To be published in a book by Springe

A Combinatorial Framework for Designing (Pseudoknotted) RNA Algorithms

We extend an hypergraph representation, introduced by Finkelstein and Roytberg, to unify dynamic programming algorithms in the context of RNA folding with pseudoknots. Classic applications of RNA dynamic programming energy minimization, partition function, base-pair probabilities...) are reformulated within this framework, giving rise to very simple algorithms. This reformulation allows one to conceptually detach the conformation space/energy model -- captured by the hypergraph model -- from the specific application, assuming unambiguity of the decomposition. To ensure the latter property, we propose a new combinatorial methodology based on generating functions. We extend the set of generic applications by proposing an exact algorithm for extracting generalized moments in weighted distribution, generalizing a prior contribution by Miklos and al. Finally, we illustrate our full-fledged programme on three exemplary conformation spaces (secondary structures, Akutsu's simple type pseudoknots and kissing hairpins). This readily gives sets of algorithms that are either novel or have complexity comparable to classic implementations for minimization and Boltzmann ensemble applications of dynamic programming