Duality and Serre functor in homotopy categories

For a (right and left) coherent ring $A$, we show that there exists a duality between homotopy categories {\mathbb{K}}^{{\rm{b}}}({\rm mod}{\mbox{-}}A^{{\rm op}}) and {\mathbb{K}}^{{\rm{b}}}({\rm mod}{\mbox{-}}A). If $A=\Lambda$ is an artin algebra of finite global dimension, this duality restricts to a duality between their subcategories of acyclic complexes, {\mathbb{K}}^{{\rm{b}}}_{\rm ac}({\rm mod}{\mbox{-}}\Lambda^{\rm op}) and {\mathbb{K}}^{{\rm{b}}}_{\rm ac}({\rm mod}{\mbox{-}}\Lambda). As a result, it will be shown that, in this case, {\mathbb{K}}_{\rm ac}^{{\rm{b}}}({\rm mod}{\mbox{-}}\Lambda) admits a Serre functor and hence has Auslander-Reiten triangles.Comment: arXiv admin note: text overlap with arXiv:1605.0474

Derived equivalences of functor categories

Let \Mod \CS denote the category of \CS-modules, where \CS is a small category. Using the notion of relative derived categories of functor categories, we generalize Rickard's theorem on derived equivalences of module categories over rings to \Mod \CS. Several interesting applications will be provided. In particular, it will be shown that derived equivalence of two coherent rings not only implies the equivalence of their homotopy categories of projective modules, but also implies that they are Gorenstein derived equivalent. As another application, it is shown that a good tilting module produces an equivalence between the unbounded derived category of the module category of the ring and the relative derived category of the module category of the endomorphism ring of it

Auslander's Formula for contravariantly finite subcategories

A relative version of Auslander's formula with respect to a contravariantly finite subcategory will be given. Dual version will be treated. Several examples and applications will be provided. In particular, we show that under certain circumstances, if relative Auslander algebras of artin algebras $\Lambda$ and $\Lambda'$ are Morita equivalent, then $\Lambda$ and $\Lambda'$ are also Morita equivalent

Whole genome sequencing of Saccharomyces cerevisiae: from genotype to phenotype for improved metabolic engineering applications

<p>Abstract</p> <p>Background</p> <p>The need for rapid and efficient microbial cell factory design and construction are possible through the enabling technology, metabolic engineering, which is now being facilitated by systems biology approaches. Metabolic engineering is often complimented by directed evolution, where selective pressure is applied to a partially genetically engineered strain to confer a desirable phenotype. The exact genetic modification or resulting genotype that leads to the improved phenotype is often not identified or understood to enable further metabolic engineering.</p> <p>Results</p> <p>In this work we performed whole genome high-throughput sequencing and annotation can be used to identify single nucleotide polymorphisms (SNPs) between <it>Saccharomyces cerevisiae </it>strains S288c and CEN.PK113-7D. The yeast strain S288c was the first eukaryote sequenced, serving as the reference genome for the <it>Saccharomyces </it>Genome Database, while CEN.PK113-7D is a preferred laboratory strain for industrial biotechnology research. A total of 13,787 high-quality SNPs were detected between both strains (reference strain: S288c). Considering only metabolic genes (782 of 5,596 annotated genes), a total of 219 metabolism specific SNPs are distributed across 158 metabolic genes, with 85 of the SNPs being nonsynonymous (e.g., encoding amino acid modifications). Amongst metabolic SNPs detected, there was pathway enrichment in the galactose uptake pathway (<it>GAL1</it>, <it>GAL10</it>) and ergosterol biosynthetic pathway (<it>ERG8</it>, <it>ERG9</it>). Physiological characterization confirmed a strong deficiency in galactose uptake and metabolism in S288c compared to CEN.PK113-7D, and similarly, ergosterol content in CEN.PK113-7D was significantly higher in both glucose and galactose supplemented cultivations compared to S288c. Furthermore, DNA microarray profiling of S288c and CEN.PK113-7D in both glucose and galactose batch cultures did not provide a clear hypothesis for major phenotypes observed, suggesting that genotype to phenotype correlations are manifested post-transcriptionally or post-translationally either through protein concentration and/or function.</p> <p>Conclusions</p> <p>With an intensifying need for microbial cell factories that produce a wide array of target compounds, whole genome high-throughput sequencing and annotation for SNP detection can aid in better reducing and defining the metabolic landscape. This work demonstrates direct correlations between genotype and phenotype that provides clear and high-probability of success metabolic engineering targets. The genome sequence, annotation, and a SNP viewer of CEN.PK113-7D are deposited at <url>http://www.sysbio.se/cenpk</url>.</p

Hyponatremia and hospital outcomes among patients with pneumonia: a retrospective cohort study

<p>Abstract</p> <p>Background</p> <p>Community-acquired (CAP) and nosocomial pneumonias contribute substantially to morbidity and hospital resource utilization. Hyponatremia, occurring in >1/4 of patients with CAP, is associated with greater disease severity and worsened outcomes.</p> <p>Methods</p> <p>To explore how hyponatremia is associated with outcomes in hospitalized patients with pneumonia, we analyzed a large administrative database with laboratory component from January 2004 to December 2005. Hyponatremia was defined as at least two [Na⁺] < 135 mEq/L within 24 hours of admission value.</p> <p>Results</p> <p>Of 7,965 patients with pneumonia, 649 (8.1%) with hyponatremia were older (72.4 ± 15.7 vs. 68.0 ± 22.0, p < 0.01), had a higher mean Deyo-Charlson Comorbidity Index Score (1.7 ± 1.7 vs. 1.6 ± 1.6, p = 0.02), and higher rates of ICU (10.0% vs. 6.3%, p < 0.001) and MV (3.9% vs. 2.3%, p = 0.01) in the first 48 hours of hospitalization than patients with normal sodium. Hyponatremia was associated with an increased ICU (6.3 ± 5.6 vs. 5.3 ± 5.1 days, p = 0.07) and hospital lengths of stay (LOS, 7.6 ± 5.3 vs. 7.0 ± 5.2 days, p < 0.001) and a trend toward increased hospital mortality (5.4% vs. 4.0%, p = 0.1). After adjusting for confounders, hyponatremia was associated with an increased risk of ICU (OR 1.58, 95% CI 1.20–2.08), MV (OR 1.75 95% CI 1.13–2.69), and hospital death (OR 1.3, 95% CI 0.90–1.87) and with increases of 0.8 day to ICU and 0.3 day to hospital LOS, and over $1,300 to total hospital costs.</p> <p>Conclusion</p> <p>Hyponatremia is common among hospitalized patients with pneumonia and is associated with worsened clinical and economic outcomes. Studies in this large population are needed to explore whether prompt correction of [Na⁺] may impact these outcomes.</p

Impact of stoichiometry representation on simulation of genotype-phenotype relationships in metabolic networks.

<div><p>Genome-scale metabolic networks provide a comprehensive structural framework for modeling genotype-phenotype relationships through flux simulations. The solution space for the metabolic flux state of the cell is typically very large and optimization-based approaches are often necessary for predicting the active metabolic state under specific environmental conditions. The objective function to be used in such optimization algorithms is directly linked with the biological hypothesis underlying the model and therefore it is one of the most relevant parameters for successful modeling. Although linear combination of selected fluxes is widely used for formulating metabolic objective functions, we show that the resulting optimization problem is sensitive towards stoichiometry representation of the metabolic network. This undesirable sensitivity leads to different simulation results when using numerically different but biochemically equivalent stoichiometry representations and thereby makes biological interpretation intrinsically subjective and ambiguous. We hereby propose a new method, Minimization of Metabolites Balance (MiMBl), which decouples the artifacts of stoichiometry representation from the formulation of the desired objective functions, by casting objective functions using metabolite turnovers rather than fluxes. By simulating perturbed metabolic networks, we demonstrate that the use of stoichiometry representation independent algorithms is fundamental for unambiguously linking modeling results with biological interpretation. For example, MiMBl allowed us to expand the scope of metabolic modeling in elucidating the mechanistic basis of several genetic interactions in <em>Saccharomyces cerevisiae</em>.</p> </div