Robustness - a challenge also for the 21st century: A review of robustness phenomena in technical, biological and social systems as well as robust approaches in engineering, computer science, operations research and decision aiding

Notions on robustness exist in many facets. They come from different disciplines and reflect different worldviews. Consequently, they contradict each other very often, which makes the term less applicable in a general context. Robustness approaches are often limited to specific problems for which they have been developed. This means, notions and definitions might reveal to be wrong if put into another domain of validity, i.e. context. A definition might be correct in a specific context but need not hold in another. Therefore, in order to be able to speak of robustness we need to specify the domain of validity, i.e. system, property and uncertainty of interest. As proofed by Ho et al. in an optimization context with finite and discrete domains, without prior knowledge about the problem there exists no solution what so ever which is more robust than any other. Similar to the results of the No Free Lunch Theorems of Optimization (NLFTs) we have to exploit the problem structure in order to make a solution more robust. This optimization problem is directly linked to a robustness/fragility tradeoff which has been observed in many contexts, e.g. 'robust, yet fragile' property of HOT (Highly Optimized Tolerance) systems. Another issue is that robustness is tightly bounded to other phenomena like complexity for which themselves exist no clear definition or theoretical framework. Consequently, this review rather tries to find common aspects within many different approaches and phenomena than to build a general theorem for robustness, which anyhow might not exist because complex phenomena often need to be described from a pluralistic view to address as many aspects of a phenomenon as possible. First, many different robustness problems have been reviewed from many different disciplines. Second, different common aspects will be discussed, in particular the relationship of functional and structural properties. This paper argues that robustness phenomena are also a challenge for the 21st century. It is a useful quality of a model or system in terms of the 'maintenance of some desired system characteristics despite fluctuations in the behaviour of its component parts or its environment' (s. [Carlson and Doyle, 2002], p. 2). We define robustness phenomena as solution with balanced tradeoffs and robust design principles and robustness measures as means to balance tradeoffs. --

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The transcriptional regulator SsuR activates expression of the Corynebacterium glutamicum sulphonate utilization genes in the absence of sulphate

Koch DJ, Rückert C, Albersmeier A, et al. The transcriptional regulator SsuR activates expression of the Corynebacterium glutamicum sulphonate utilization genes in the absence of sulphate. Mol Microbiol. 2005;58(2):480-494.In a recent study, the putative regulatory gene cg0012 was shown to belong to the regulon of McbR, a global transcriptional regulator of sulphur metabolism in Corynebacterium glutamicum ATCC 13032. A deletion of cg0012, now designated ssuR (sulphonate sulphur utilization regulator), led to the mutant strain C. glutamicum DK100, which was shown to be blocked in the utilization of sulphonates as sulphur sources. According to DNA microarray hybridizations, transcription of the ssu and seu genes, encoding the sulphonate utilization system of C. glutamicum, was considerably decreased in C. glutamicum DK100 when compared with the wild-type strain. Electrophoretic mobility shift assays with purified SsuR protein demonstrated that the upstream regions of ssuI, seuABC, ssuD2 and ssuD1CBA contain SsuR binding sites. A nucleotide sequence alignment of the four DNA fragments containing the SsuR binding sites revealed a common 21 bp motif consisting of T-, GC- and A-rich domains. Mapping of the transcriptional start sites in front of ssuI, seuABC, ssuD2 and ssuD1CBA indicated that the SsuR binding sites are located directly upstream of identified promoter sequences and that the ssu genes are expressed by leaderless transcripts. Binding of the SsuR protein to its operator was shown to be diminished in vitro by the effector substance sulphate and its direct assimilation products adenosine 5'-phosphosulphate, sulphite and sulphide. Real-time reverse transcription polymerase chain reaction experiments verified that the expression of the ssu and seu genes was also repressed in vivo by the presence of sulphate or sulphite. Therefore, the regulatory protein SsuR activates the expression of the ssu and seu genes in C. glutamicum in the absence of the preferred sulphur source sulphate

Novel Risk Classification Based on Pyroptosis-Related Genes Defines Immune Microenvironment and Pharmaceutical Landscape for Hepatocellular Carcinoma

Growing evidence has indicated that pyroptosis functions in the development of cancer. Nonetheless, specific roles of pyroptosis-related genes in tumor progression, immune response, prognosis, and immunotherapy have not been thoroughly elucidated. After a comprehensive evaluation of pyroptosis genes, unsupervised clustering was performed to generate three distinct clusters from hepatocellular carcinoma (HCC) samples. Three distinct pyroptosis-related molecular subtypes comprising three gene clusters that had differential prognostic effects on patient survival were then identified. Immune characteristics analyses revealed diversified immune cell infiltration among the subtypes. Two clusters served as immune-hot phenotypes associated with significantly poorer survival compared to a remaining third immune-cold cluster. Among these, the immune-hot clusters were characterized by abundant adaptive immune cell infiltration, active CD4+ and CD8+ T cells, high total leukocyte counts and tumor growth status, and lower Th17 cell and M2 macrophage densities. Then, risk scores indicated that low-risk patients were more sensitive to anti-tumor therapy. Subsequently, we found a significant correlation between pyroptosis and prognosis in HCC and that pyroptosis genes drive the heterogeneity of the tumor microenvironment. The risk scoring system, based on pyroptosis-related differentially expressed genes, was established to evaluate the individual outcomes and contribute to new insights into the molecular characterization of pyroptosis-related subtypes

RamA and RamB are global transcriptional regulators in Corynebacterium glutamicum and control genes for enzymes of the central metabolism

Auchter M, Cramer A, Hüser A, et al. RamA and RamB are global transcriptional regulators in Corynebacterium glutamicum and control genes for enzymes of the central metabolism. J Biotechnol. 2011;154(2-3):126-139.Expression profiling of Corynebacterium glutamicum in comparison to a derivative deficient in the transcriptional regulator AtlR (previously known as SucR or MtlR) revealed eight genes showing more than 4-fold higher mRNA levels in the mutant. Four of these genes are located in the direct vicinity of the atlR gene, i.e., xylB, rbtT, mtlD, and sixA, annotated as encoding xylulokinase, the ribitol transporter, mannitol 2-dehydrogenase, and phosphohistidine phosphatase, respectively. Transcriptional analysis indicated that atlR and the four genes are organized as atlR-xylB and rbtT-mtlD-sixA operons. Growth experiments with C. glutamicum and C. glutamicum ΔatlR, ΔxylB, ΔrbtT, ΔmtlD, and ΔsixA derivatives with sugar alcohols revealed that (i) wild-type C. glutamicum grows on D-arabitol but not on other sugar alcohols, (ii) growth in the presence of D-arabitol allows subsequent growth on D-mannitol, (iii) D-arabitol is cometabolized with glucose and preferentially utilized over D-mannitol, (iv) RbtT and XylB are involved in D-arabitol but not in D-mannitol metabolism, (v) MtlD is required for D-arabitol and D-mannitol metabolism, and (vi) SixA is not required for growth on any of the substrates tested. Furthermore, we show that MtlD confers D-arabitol and D-mannitol dehydrogenase activities, that the levels of these and also xylulokinase activities are generally high in the C. glutamicum ΔatlR mutant, whereas in the parental strain, they were high when cells were grown in the presence of D-arabitol and very low when cells were grown in its absence. Our results show that the XylB, RbtT, and MtlD proteins allow the growth of C. glutamicum on D-arabitol and that D-arabitol metabolism is subject to arabitol-dependent derepression by AtlR

Bioinformatics support for high-throughput proteomics

Wilke A, Rückert C, Bartels D, et al. Bioinformatics support for high-throughput proteomics. JOURNAL OF BIOTECHNOLOGY. 2003;106(2-3):147-156.In the "post-genome" era, mass spectrometry (MS) has become an important method for the analysis of proteome data. The rapid advancement of this technique in combination with other methods used in proteomics results in an increasing number of high-throughput projects. This leads to an increasing amount of data that needs to be archived and analyzed. To cope with the need for automated data conversion, storage, and analysis in the field of proteomics, the open source system ProDB was developed. The system handles data conversion from different mass spectrometer software, automates data analysis, and allows the annotation of MS spectra (e.g. assign gene names, store data on protein modifications). The system is based on an extensible relational database to store the mass spectra together with the experimental setup. It also provides a graphical user interface (GUI) for managing the experimental steps which led to the MS data. Furthermore, it allows the integration of genome and proteome data. Data from an ongoing experiment was used to compare manual and automated analysis. First tests showed that the automation resulted in a significant saving of time. Furthermore, the quality and interpretability of the results was improved in all cases. (C) 2003 Elsevier B.V. All rights reserved

Early prediction of circulatory failure in the intensive care unit using machine learning.

Intensive-care clinicians are presented with large quantities of measurements from multiple monitoring systems. The limited ability of humans to process complex information hinders early recognition of patient deterioration, and high numbers of monitoring alarms lead to alarm fatigue. We used machine learning to develop an early-warning system that integrates measurements from multiple organ systems using a high-resolution database with 240 patient-years of data. It predicts 90% of circulatory-failure events in the test set, with 82% identified more than 2 h in advance, resulting in an area under the receiver operating characteristic curve of 0.94 and an area under the precision-recall curve of 0.63. On average, the system raises 0.05 alarms per patient and hour. The model was externally validated in an independent patient cohort. Our model provides early identification of patients at risk for circulatory failure with a much lower false-alarm rate than conventional threshold-based systems

Early prediction of circulatory failure in the intensive care unit using machine learning

ISSN:1078-8956ISSN:1546-170