A Path Algorithm for Constrained Estimation

Many least squares problems involve affine equality and inequality constraints. Although there are variety of methods for solving such problems, most statisticians find constrained estimation challenging. The current paper proposes a new path following algorithm for quadratic programming based on exact penalization. Similar penalties arise in $l_1$ regularization in model selection. Classical penalty methods solve a sequence of unconstrained problems that put greater and greater stress on meeting the constraints. In the limit as the penalty constant tends to $\infty$, one recovers the constrained solution. In the exact penalty method, squared penalties are replaced by absolute value penalties, and the solution is recovered for a finite value of the penalty constant. The exact path following method starts at the unconstrained solution and follows the solution path as the penalty constant increases. In the process, the solution path hits, slides along, and exits from the various constraints. Path following in lasso penalized regression, in contrast, starts with a large value of the penalty constant and works its way downward. In both settings, inspection of the entire solution path is revealing. Just as with the lasso and generalized lasso, it is possible to plot the effective degrees of freedom along the solution path. For a strictly convex quadratic program, the exact penalty algorithm can be framed entirely in terms of the sweep operator of regression analysis. A few well chosen examples illustrate the mechanics and potential of path following.Comment: 26 pages, 5 figure

Lysosomes in iron metabolism, ageing and apoptosis

The lysosomal compartment is essential for a variety of cellular functions, including the normal turnover of most long-lived proteins and all organelles. The compartment consists of numerous acidic vesicles (pH ∼4 to 5) that constantly fuse and divide. It receives a large number of hydrolases (∼50) from the trans-Golgi network, and substrates from both the cells’ outside (heterophagy) and inside (autophagy). Many macromolecules contain iron that gives rise to an iron-rich environment in lysosomes that recently have degraded such macromolecules. Iron-rich lysosomes are sensitive to oxidative stress, while ‘resting’ lysosomes, which have not recently participated in autophagic events, are not. The magnitude of oxidative stress determines the degree of lysosomal destabilization and, consequently, whether arrested growth, reparative autophagy, apoptosis, or necrosis will follow. Heterophagy is the first step in the process by which immunocompetent cells modify antigens and produce antibodies, while exocytosis of lysosomal enzymes may promote tumor invasion, angiogenesis, and metastasis. Apart from being an essential turnover process, autophagy is also a mechanism by which cells will be able to sustain temporary starvation and rid themselves of intracellular organisms that have invaded, although some pathogens have evolved mechanisms to prevent their destruction. Mutated lysosomal enzymes are the underlying cause of a number of lysosomal storage diseases involving the accumulation of materials that would be the substrate for the corresponding hydrolases, were they not defective. The normal, low-level diffusion of hydrogen peroxide into iron-rich lysosomes causes the slow formation of lipofuscin in long-lived postmitotic cells, where it occupies a substantial part of the lysosomal compartment at the end of the life span. This seems to result in the diversion of newly produced lysosomal enzymes away from autophagosomes, leading to the accumulation of malfunctioning mitochondria and proteins with consequent cellular dysfunction. If autophagy were a perfect turnover process, postmitotic ageing and several age-related neurodegenerative diseases would, perhaps, not take place

Ligand-Receptor Interactions

The formation and dissociation of specific noncovalent interactions between a variety of macromolecules play a crucial role in the function of biological systems. During the last few years, three main lines of research led to a dramatic improvement of our understanding of these important phenomena. First, combination of genetic engineering and X ray cristallography made available a simultaneous knowledg of the precise structure and affinity of series or related ligand-receptor systems differing by a few well-defined atoms. Second, improvement of computer power and simulation techniques allowed extended exploration of the interaction of realistic macromolecules. Third, simultaneous development of a variety of techniques based on atomic force microscopy, hydrodynamic flow, biomembrane probes, optical tweezers, magnetic fields or flexible transducers yielded direct experimental information of the behavior of single ligand receptor bonds. At the same time, investigation of well defined cellular models raised the interest of biologists to the kinetic and mechanical properties of cell membrane receptors. The aim of this review is to give a description of these advances that benefitted from a largely multidisciplinar approach

The mitochondrial genome sequence of the ciliate Paramecium caudatum reveals a shift in nucleotide composition and codon usage within the genus Paramecium

<p>Abstract</p> <p>Background</p> <p>Despite the fact that the organization of the ciliate mitochondrial genome is exceptional, only few ciliate mitochondrial genomes have been sequenced until today. All ciliate mitochondrial genomes are linear. They are 40 kb to 47 kb long and contain some 50 tightly packed genes without introns. Earlier studies documented that the mitochondrial guanine + cytosine contents are very different between <it>Paramecium tetraurelia </it>and all studied <it>Tetrahymena </it>species. This raises the question of whether the high mitochondrial G+C content observed in <it>P. tetraurelia </it>is a characteristic property of <it>Paramecium </it>mtDNA, or whether it is an exception of the ciliate mitochondrial genomes known so far. To test this question, we determined the mitochondrial genome sequence of <it>Paramecium caudatum </it>and compared the gene content and sequence properties to the closely related <it>P. tetraurelia</it>.</p> <p>Results</p> <p>The guanine + cytosine content of the <it>P. caudatum </it>mitochondrial genome was significantly lower than that of <it>P. tetraurelia </it>(22.4% vs. 41.2%). This difference in the mitochondrial nucleotide composition was accompanied by significantly different codon usage patterns in both species, i.e. within <it>P. caudatum </it>clearly A/T ending codons dominated, whereas for <it>P. tetraurelia </it>the synonymous codons were more balanced with a higher number of G/C ending codons. Further analyses indicated that the nucleotide composition of most members of the genus <it>Paramecium </it>resembles that of <it>P. caudatum </it>and that the shift observed in <it>P. tetraurelia </it>is restricted to the <it>P. aurelia </it>species complex.</p> <p>Conclusions</p> <p>Surprisingly, the codon usage bias in the <it>P. caudatum </it>mitochondrial genome, exemplified by the effective number of codons, is more similar to the distantly related <it>T. pyriformis </it>and other single-celled eukaryotes such as <it>Chlamydomonas</it>, than to the closely related <it>P. tetraurelia</it>. These differences in base composition and codon usage bias were, however, not reflected in the amino acid composition. Most probably, the observed picture is best explained by a hitherto unknown (neutral or adaptive) mechanism that increased the guanine + cytosine content in <it>P. tetraurelia </it>mtDNA on the one hand, and strong purifying selection on the ancestral amino acid composition on the other hand. These contradicting forces are counterbalanced by a considerably altered codon usage pattern.</p

Abnormal Intracellular Accumulation and Extracellular Aβ Deposition in Idiopathic and Dup15q11.2-q13 Autism Spectrum Disorders

<div><h3>Background</h3><p>It has been shown that amyloid ß (Aβ), a product of proteolytic cleavage of the amyloid β precursor protein (APP), accumulates in neuronal cytoplasm in non-affected individuals in a cell type–specific amount.</p> <h3>Methodology/Principal Findings</h3><p>In the present study, we found that the percentage of amyloid-positive neurons increases in subjects diagnosed with idiopathic autism and subjects diagnosed with duplication 15q11.2-q13 (dup15) and autism spectrum disorder (ASD). In spite of interindividual differences within each examined group, levels of intraneuronal Aβ load were significantly greater in the dup(15) autism group than in either the control or the idiopathic autism group in 11 of 12 examined regions (p<0.0001 for all comparisons; Kruskall-Wallis test). In eight regions, intraneuronal Aβ load differed significantly between idiopathic autism and control groups (p<0.0001). The intraneuronal Aβ was mainly N-terminally truncated. Increased intraneuronal accumulation of Aβ_17–40/42 in children and adults suggests a life-long enhancement of APP processing with α-secretase in autistic subjects. Aβ accumulation in neuronal endosomes, autophagic vacuoles, Lamp1-positive lysosomes and lipofuscin, as revealed by confocal microscopy, indicates that products of enhanced α-secretase processing accumulate in organelles involved in proteolysis and storage of metabolic remnants. Diffuse plaques containing Aβ_1–40/42 detected in three subjects with ASD, 39 to 52 years of age, suggest that there is an age-associated risk of alterations of APP processing with an intraneuronal accumulation of a short form of Aβ and an extracellular deposition of full-length Aβ in nonfibrillar plaques.</p> <h3>Conclusions/Significance</h3><p>The higher prevalence of excessive Aβ accumulation in neurons in individuals with early onset of intractable seizures, and with a high risk of sudden unexpected death in epilepsy in autistic subjects with dup(15) compared to subjects with idiopathic ASD, supports the concept of mechanistic and functional links between autism, epilepsy and alterations of APP processing leading to neuronal and astrocytic Aβ accumulation and diffuse plaque formation.</p> </div

Agent-Based Model of Therapeutic Adipose-Derived Stromal Cell Trafficking during Ischemia Predicts Ability To Roll on P-Selectin

Intravenous delivery of human adipose-derived stromal cells (hASCs) is a promising option for the treatment of ischemia. After delivery, hASCs that reside and persist in the injured extravascular space have been shown to aid recovery of tissue perfusion and function, although low rates of incorporation currently limit the safety and efficacy of these therapies. We submit that a better understanding of the trafficking of therapeutic hASCs through the microcirculation is needed to address this and that selective control over their homing (organ- and injury-specific) may be possible by targeting bottlenecks in the homing process. This process, however, is incredibly complex, which merited the use of computational techniques to speed the rate of discovery. We developed a multicell agent-based model (ABM) of hASC trafficking during acute skeletal muscle ischemia, based on over 150 literature-based rules instituted in Netlogo and MatLab software programs. In silico, trafficking phenomena within cell populations emerged as a result of the dynamic interactions between adhesion molecule expression, chemokine secretion, integrin affinity states, hemodynamics and microvascular network architectures. As verification, the model reasonably reproduced key aspects of ischemia and trafficking behavior including increases in wall shear stress, upregulation of key cellular adhesion molecules expressed on injured endothelium, increased secretion of inflammatory chemokines and cytokines, quantified levels of monocyte extravasation in selectin knockouts, and circulating monocyte rolling distances. Successful ABM verification prompted us to conduct a series of systematic knockouts in silico aimed at identifying the most critical parameters mediating hASC trafficking. Simulations predicted the necessity of an unknown selectin-binding molecule to achieve hASC extravasation, in addition to any rolling behavior mediated by hASC surface expression of CD15s, CD34, CD62e, CD62p, or CD65. In vitro experiments confirmed this prediction; a subpopulation of hASCs slowly rolled on immobilized P-selectin at speeds as low as 2 µm/s. Thus, our work led to a fundamentally new understanding of hASC biology, which may have important therapeutic implications

Mapping genetic variations to three- dimensional protein structures to enhance variant interpretation: a proposed framework

The translation of personal genomics to precision medicine depends on the accurate interpretation of the multitude of genetic variants observed for each individual. However, even when genetic variants are predicted to modify a protein, their functional implications may be unclear. Many diseases are caused by genetic variants affecting important protein features, such as enzyme active sites or interaction interfaces. The scientific community has catalogued millions of genetic variants in genomic databases and thousands of protein structures in the Protein Data Bank. Mapping mutations onto three-dimensional (3D) structures enables atomic-level analyses of protein positions that may be important for the stability or formation of interactions; these may explain the effect of mutations and in some cases even open a path for targeted drug development. To accelerate progress in the integration of these data types, we held a two-day Gene Variation to 3D (GVto3D) workshop to report on the latest advances and to discuss unmet needs. The overarching goal of the workshop was to address the question: what can be done together as a community to advance the integration of genetic variants and 3D protein structures that could not be done by a single investigator or laboratory? Here we describe the workshop outcomes, review the state of the field, and propose the development of a framework with which to promote progress in this arena. The framework will include a set of standard formats, common ontologies, a common application programming interface to enable interoperation of the resources, and a Tool Registry to make it easy to find and apply the tools to specific analysis problems. Interoperability will enable integration of diverse data sources and tools and collaborative development of variant effect prediction methods