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An expanded genome-scale metabolic model of E. coli (iJR904 GSM/GPR) has been reconstructed which includes 904 genes and 931 unique biochemical reactions. The reactions in the expanded model are both elementally and charge balanced. Network gap analysis led to putative assignments for 55 open reading frames (ORFs). Gene to protein to reaction associations (GPR) are now directly included in the model. Comparisons between predictions made by iJR904 and iJE660a models show that they are generally similar but differ under certain circumstances. Analysis of genome-scale proton balancing shows how the flux of protons into and out of the medium is important for maximizing cellular growth.


The constraint-based modeling approach has been used to study E. coli metabolism for over ten years; the history of such model building efforts has recently been reviewed [7]. The first genome-scale metabolic (GSM) model accounting for 660 gene products (iJE660 GSM) was reconstructed using genomic information, biochemical data and physiological data [8]. This genome-scale model has been used to perform in silico gene deletion studies [8] and to predict both optimal growth behavior [9] and the outcome of adaptive evolution [10].




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This paper reports an expansion of iJE660a GSM, which itself is a slight modification of the original genome-scale metabolic model (iJE660 GSM) [8]. Gene to protein to reaction (GPR) associations are included directly in the new model (iJR904 GSM/GPR). These associations describe the dependence of reactions on proteins and proteins on genes (Figure 2). The metabolic network described by iJR904 has also changed; individual reactions are now elementally and charge balanced, and a significant number of new genes and novel reactions have been added to the model. iJR904 GSM/GPR accounts for over 904 genes and the 931 unique biochemical reactions the encoded proteins carry out. This paper discusses the effects that these additional reactions have on the predictive capabilities of the model and identifies putative ORFs in the genome which could resolve gaps in the metabolic network.


Since computational models of E. coli will continue to grow in size and scope [7] it will become important to be able to distinguish between the different models - a naming convention will aid in this effort. The naming convention we chose to use mirrors the one already established for plasmids. The general form of the names of in silico strains used is iXXxxxa YYY. The 'i' in the name refers to an in silico model (that is, a computer model). This 'i' is followed by the initials (XX) of the person who developed the model and then the number of genes (xxx) included in the model. Any letters (a) after the number of genes indicates that slight modifications were made to the model, for instance iJE660a is derived from iJE660. Further designation of the content and scope of a model are found in YYY; here the acronyms GSM and GPR stand for genome-scale model and gene-protein-reaction associations, respectively. The contents of iJE660a and iJR904 can be found on our website [11], and iJR904 is also detailed in the additional data files.


The metabolic network described by E. coli iJE660a has expanded in size from 627 unique reactions and 438 metabolites to 931 unique reactions and 625 metabolites in iJR904. Complete maps containing all the reactions in the metabolic network are available in the additional data files and can also be downloaded from [11]. The molecular formulae and charges for the metabolites in the model were determined assuming a pH of 7.2. Fifty-eight of the reactions in iJR904 currently do not have associated genes. A complete list of the reactions can be found in the additional data files. Putative functional gene assignments account for 23 of the added reactions, with the majority of these being putative transporters.


This paper reports the curation and expansion of a previous genome-scale constraint-based model of E. coli metabolism (iJE660a GSM) that is now used in multiple laboratories (A.L. Barabasi, personal communication; Church and colleagues [23]; H. Greenberg, personal communication and C. Maranas, personal communication). This expanded model, iJR904 GSM/GPR, includes 37% more metabolic genes and 47% more metabolic reactions. Each reaction in the network is now both elementally and charge balanced with the exception of the six reactions listed in Table 1. While the new reactions added to the network do not change many of the predicted optimal phenotypes, there are instances in which the expanded model makes significantly different predictions, examples of which occur when glycerol, glucose, malate, acetate and αKG are used as the carbon sources under oxygen-limited conditions.


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Explanation: This criterion influences external validity, but not the internal or statistical validity of the trial. It has been included in the PEDro scale so that all items of the Delphi scale are represented on the PEDro scale. This item is not used to calculate the PEDro score.


The Spanish versions of the long (26-item) and short (12-item) forms of the SCS are valid and reliable instruments for the evaluation of self-compassion among the general population. These results substantiate the use of this scale in research and clinical practice.


Self-compassion is assessed using the Self-Compassion Scale [10]. The original SCS contains 26 items, measuring six components of self-compassion: Self-Kindness, Self-Judgment, Common Humanity, Isolation, Mindfulness and Over-Identification [10]. Adequate psychometric properties are also reported [10]. The items are rated on a five-point response scale ranging from 1 (almost never) to 5 (almost always). Recently, a shorter version (12 items) of the SCS has been developed [14]. The aim of this study was to validate and assess the psychometric properties of the Spanish versions of both questionnaires (long and short forms). The reason for validating both questionnaires simultaneously was that none of them had previously been validated in Spanish. The validation of the short form required the calculation of the correlation with the validated long form, and therefore it seemed logical to validate both at the same time. On the other hand, the simultaneous validation of both instruments allowed them to be compared and the usefulness of each one to be identified. This facilitates the work of researchers by allowing them to obtain all the information in a single manuscript.


The SCS [11] is a 26-item questionnaire designed to assess overall self-compassion (total score) and components of self-compassions across three conceptually distinct, but theoretically related, facets: common humanity (SCS-CH), mindfulness (SCS-M), and self-kindness (SCS-SK). Although the construct was defined using these three facets [10], the factor analysis suggested six subscales, representing positive and negative aspects of each facet [11]. These items were designed to assess how respondents perceive their actions toward themselves in difficult times and are rated using a Likert-type scale anchored from 1 (almost never) to 5 (almost always). The SCS has adequate reliability and validity [11], even in different cultures [16].


Regarding the correlation between the 26 and 12-item forms of the SCS, the following correlations between the corresponding subscales were observed: r =0.89 for Self-Kindness, r =0.90 for Self-Judgement, r =0.81 for Common Humanity, r =0.81 for Isolation, r =0.83 for Mindfulness and r =0.90 for Over-Identification. The correlation between the total score of the long and short forms was high (r =0.92).


The main purpose of the present study was to validate the Spanish versions of the long and short forms of the SCS in university students (long form) and health workers (short form). To our knowledge, despite the importance of the self-compassion construct, no validation of any of the two forms in any other language had been previously performed, apart from the original English version of both scales [11, 14] and a Dutch version of the 26 [38] and 12-item forms [14].


In our samples, both forms of the SCS showed high internal consistency, high test-retest reliability and expected and significant correlations with associated psychological variables, such as depression, trait anxiety, perceived stress (negative correlation) and mindfulness (positive correlation). In addition, the results observed using CFA were largely consistent with those reported in previous studies [11, 14, 38]: the six-factor model of both scales showed adequate fit and all items loaded strongly onto the expected latent factor. This factor structure is maintained cross-culturally [16], thus these results could be expected. Moreover, according to the criteria of Stöber & Joormann [39] for creating short forms of longer self-report measures, the 12-item form of the SCS fulfils both criteria: (a) high correlations with the long SCS and (b) high correlations of the short version subscales with their intended subscales of long form of the SCS. 2ff7e9595c


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