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Evolutionary conservation of domain-domain interactions
Genome Biology volume 7, Article number: R125 (2006)
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Recently, there has been much interest in relating domain-domain interactions (DDIs) to protein-protein interactions (PPIs) and vice versa, in an attempt to understand the molecular basis of PPIs.
Here we map structurally derived DDIs onto the cellular PPI networks of different organisms and demonstrate that there is a catalog of domain pairs that is used to mediate various interactions in the cell. We show that these DDIs occur frequently in protein complexes and that homotypic interactions (of a domain with itself) are abundant. A comparison of the repertoires of DDIs in the networks of Escherichia coli, Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster, and Homo sapiens shows that many DDIs are evolutionarily conserved.
Our results indicate that different organisms use the same 'building blocks' for PPIs, suggesting that the functionality of many domain pairs in mediating protein interactions is maintained in evolution.
Many proteins are constructed of domains, which are their main functional and structural units. A specific domain can be found in different proteins, and several different domains can be found within a given protein. Proteins can thus be viewed as being built of a finite set of domains, which are joined together in diverse combinations. Domains are often related to particular functions; for example, they may be responsible for catalytic activity or they may mediate the interactions of proteins with other molecules [1–3]. They are believed to play a crucial role in protein-protein interactions (PPIs), by binding either short peptide motifs or other domains. The former are usually associated with transient interactions, whereas the latter are assumed to mediate more stable interactions and assemblies of proteins into complexes [2]. Domain-domain interactions (DDIs) can be either heterotypic, when the interaction involves two different domains, or homotypic, when it involves two identical domains. Homotypic interactions do not necessarily imply the formation of homodimers but may also involve binding of two different proteins or intraprotein interactions mediated by two identical domains. Heterotypic interactions refer to interactions between two different domains either within a protein or between proteins (different or identical).
The domain modularity of proteins on the one hand and the fact that PPIs are mediated via DDIs on the other hand raise the question of PPI modularity; can the PPIs be attributed to a limited set of DDIs? Two lines of evidence support this idea. The first comes from the work of several groups who found statistically significant over-representation of domain pairs in large datasets of experimentally determined PPIs [4–11]. The inferred domain pairs can be considered as putative interacting domain pairs that are shared by multiple PPIs. In some cases these putative DDIs could indeed be supported by available experimental data (for example, see the report by Sprinzak and Margalit [4]) and/or confirmed by structural information from solved protein complexes (for example, see the report by Riley and coworkers [11]). However, in most cases experimental verification in support of the DDI-PPI correspondence is still missing. The second line of evidence comes from structurally based DDI databases that were recently published [12, 13] and list the actual domains that are involved in the interactions, based on solved structures from the Protein Data Bank [14]. These databases include many DDIs that are shared between different PPIs, corroborating the modularity of PPIs. However, because the dataset of crystallograpically solved PPIs is relatively small, it is not clear whether we can conjecture from it to the cellular PPI networks.
In the present study we combined the structurally derived information with the PPI network information based on small-scale and large-scale experiments, in order to study further the modularity of the PPIs. It is well known that domains often exhibit evolutionary conservation in sequence and three-dimensional structure [15], and therefore it might be expected that the same domain pairs mediate PPIs in different organisms. It is intriguing, therefore, to examine whether there are common DDIs that can be identified in the PPI networks of the various organisms. To this end we mapped the structurally determined DDIs onto the PPI networks of five organisms (Escherichia coli, Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster, and Homo sapiens) and compared the occurrence of these interacting domain pairs in the studied networks to that expected at random. This analysis provides a proteome-wide view on the involvement of these interacting domain pairs in protein interactions in the cell. Next, we compared the DDI repertoires of the five organisms and showed that there are DDIs that are unique to a specific organism; DDIs that are shared by two, three, or four organisms; and DDIs that are conserved in all five organisms. Many of the highly conserved DDIs involve domains known to function in basic processes, such as DNA metabolism and nucleotide binding. In summary, our results suggest that different organisms use the same 'building blocks' for PPIs and that the functionality of many domain pairs as mediating protein interactions is maintained in evolution.
Database of DDIs
Recently, two databases of DDIs based on high-resolution three-dimensional structures were published, namely the database of 3D Interacting Domains (3DID) [12] and the iPfam database [13], both derived from the Protein Data Bank [14]. These databases contain information from a variety of organisms, ranging from bacteria to human. The DDIs in these databases are based on two types of interactions: interprotein DDIs (interactions between domains in two different proteins) and intraprotein DDIs (interacting domains within multidomain proteins). The 3DID and iPfam databases differ slightly in their DDI definitions and therefore they overlap in only about 70% of the DDIs. We combined the DDI data from both databases and filtered it as described in the Materials and methods section (below), resulting in a database that contained 2,983 DDIs. Of these DDIs, 74% were derived from interprotein interactions, 13% were derived from intraprotein interactions, and 13% DDIs were found in both interprotein and intraprotein interactions (Additional data file 1 [Supplementary Figure 1a]). Some DDIs occurred only once whereas others appeared repeatedly (up to hundreds of times). The median number of DDI occurrences was nine. This already suggests that there are domain pairs that are used repeatedly in different interactions.
DDIs as the building blocks of cellular PPI networks
Next, we asked whether the DDIs can be identified in the cellular PPI networks of various organisms (E. coli, S. cerevisiae, C. elegans, D. melanogaster, and H. sapiens) in a frequency that exceeds random expectations. We mapped the DDIs onto the PPI networks, as described in Figure 1. This mapping allowed us to focus on the PPIs that may be mediated by the DDIs in each of the organisms (Figure 1e) and to study the repertoire of DDIs in each organism (Figure 1f). Interestingly, DDIs derived solely from intraprotein interactions could be mapped onto only a very small fraction of PPIs. Most PPI-DDI mappings involved DDIs from interprotein interactions, and some mappings involved DDIs derived from both interprotein and intraprotein interactions (Additional data file 1 [Supplementary Figure 1b]).
The fractions of the organisms' PPIs with domain assignments to which DDIs could be mapped ranged from 6% to 20% (Table 1). To evaluate whether the number of interactions attributed to DDIs is statistically significantly greater than expected at random, we generated 1000 same size, same topology, organism-specific random PPI networks (see Materials and methods). For each of these networks we counted the number of PPIs to which structurally based DDIs could be mapped. The fraction of random networks in which the number of interactions attributed to DDIs was equal to or exceeded the number in the studied network provided a measure of statistical significance. Our analysis revealed that for each of the five organisms the number of PPIs attributed to DDIs was statistically significantly greater than expected at random (Table 1).
Both the 3DID and iPfam databases are based on a variety of organisms, and there is some overlap between the PPIs in the organisms' networks and those used to derive the structurally based DDIs. To rule out a potential bias in the results due to this overlap, we repeated the analysis for each organism disregarding PPI-DDI mappings caused by overlap between the structural database and the PPI data of that organism. As expected, there was a slight decrease in the number of PPIs attributed to DDIs in the various organisms, but these numbers remained highly statistically significant (Table 1).
Our statistical evaluation strongly supports the conjecture that PPIs in the cellular networks may use the structurally based interacting domain pairs to mediate their interactions. Still, without explicit structural information, there is always the possibility that in multidomain proteins the mapped DDIs are not actually the domains that mediate the interaction for particular interacting protein pairs. We therefore turned to examine a subset of the PPIs, namely those involving only single domain proteins. We first verified that the domains constitute most of the sequences of these single domain proteins, and therefore it is conceivable that these PPIs are mediated by residues within the domains. As shown in Table 2, the number of single domain PPIs that could be attributed to the DDIs highly exceeded random expectation. This further supports our previous conclusion that there are domain pairs that are used preferentially for PPIs.
Our analyses defined for each organism a set of interacting domain pairs that can be considered as mediating the PPIs, as illustrated in Figure 1f (and detailed in Additional data file 2). The counts of DDIs that were mapped onto the PPI network of each organism are summarized in Table 3. These counts greatly exceeded the corresponding numbers in random networks (P < 0.001). Figure 2 describes the distribution of these DDIs among the organisms' PPIs. Although in each organism there are DDIs that are mapped only to one PPI, most DDIs are mapped to two or more PPIs. Notably in human, at least 20% of the PPI-DDI mappings were attributed to a relatively small number of DDIs. Each of these DDIs was mapped to more than 90 PPIs. Because there is always the concern that certain DDIs are over-represented due to paralogs that carry out paralogous interactions, we also carried out the analysis after excluding paralogous interactions. The exclusion of paralogous interactions resulted in a significant decrease in the number of repeatedly used DDIs in E. coli to 81 DDIs (approximately 10% of E. coli DDIs), but had a much smaller effect on the other organisms (Additional data file 1 [Supplementary Table 1]). For the eukaryotes, the fractions of PPI-DDI mappings attributed to repeatedly used DDIs were still very high, and ranged between about 72% to 96% when paralogous PPIs were excluded (Additional data file 1 [Supplementary Figure 2]). These findings support the conjecture of Dueber and coworkers [16] on the higher functional flexibility that proteins in eukaryotes may achieve by using the same domains for interactions in different contexts. This is also exemplified in Figure 3a, in which the use of the same DDI to mediate PPIs in different processes within the same organism is demonstrated. Our findings support previous reports based on S. cerevisiae data [4, 5], and imply that at the organism level there are pairs of domains that can be considered the 'building blocks' of the PPI networks, and these are used in different protein contexts to mediate the interactions.
DDIs are evolutionarily conserved
Are these 'building blocks' conserved in evolution? To address this question we compared the repertoires of DDIs of the different organisms, and examined how many of the DDIs are common to two, three, four, or all of the five organisms. The results are described in Table 3 and Figure 4 (also see Additional data file 1 [Supplementary Table 2]). For each such comparison, the number of common DDIs was compared with their number in the intersection of 1000 random DDI networks of the compared organisms, to obtain a measure of statistical significance (see Materials and methods, below). Because many of the structurally derived DDIs were determined from human and E. coli, it is not surprising that the number of unique DDIs is high for these organisms and low for the other organisms (Table 3). It is important to emphasize that most of the organisms' unique DDIs are not due to organism-specific domains. These domains occur in the proteins of other organisms, but PPIs that contain these DDIs were not determined yet. Table 3 shows the common DDIs between all pairs of organisms. Again, most of the DDIs of yeast, worm, and fly are shared with either E. coli or human, because many of the DDIs were taken from structures of these two organisms. However, it is instructive that other organism-organism comparisons revealed high numbers of common DDIs, which were all statistically significant. It is clear from Table 3 and Figure 4 that the similarity in DDI repertoires is much higher among the eukaryotes than between E. coli and the eukaryotes. Figure 3 demonstrates two examples of the use of the same DDIs in human and either yeast (Figure 3b) or fly (Figure 3c). As seen in the figure, the same DDIs are used in the various organisms in different cellular processes.
The intersections of three, four, or five DDI sets were even more revealing. As demonstrated in Figure 4, when E. coli was included in the comparisons the number of common DDIs was rather small. However, when comparing three or four eukaryotes the number of common DDIs ranged between 84 and 147 (P < 0.001). Exclusion of interologs (see Materials and methods, below) hardly affected these numbers (Additional data file 1 [Supplementary Table 2 and Supplementary Figure 3]). Many of these DDIs are homotypic (involving identical domains in the interactions). This is already evident in the structural database of DDIs and is reinforced when one examines the conserved DDIs. On average, the repertoire of DDIs of each organism included 56% homotypic DDIs. This fraction increased to 62%, 70%, 77% and 85% among the DDIs that were conserved in two, three, four and five organisms, respectively. These homotypic DDIs are found in both homodimers and heterodimers.
There are 27 DDIs that were found to be conserved among all five organisms and are thus conserved from prokaryotes to eukaryotes (Additional data file 1 [Supplementary Table 2] and Additional data file 3). A close look at these DDIs reveals that they are involved in basic functions such as ATP and nucleic acid binding. Some of the domains involved in these DDIs were documented originally as either prokaryotic or eukaryotic domains, but they occur also in eukaryotic and prokaryotic organisms, respectively, participating in the same or similar functions. In addition to these 27 DDIs, an additional 57 DDIs were found to be shared by the four eukaryotes in our study, mostly involving domains that are characteristic of nuclear proteins and domains that function in protein modification and signal transduction. Looking at DDIs shared by three eukaryotes shows additional common functions, such as intracellular protein transport, which is common to yeast, worm, and human. Focusing on those DDIs conserved in two eukaryotes reveals advanced processes, such as domains involved in dynamics of cytoskeletal elements that are conserved between fly and human.
DDIs are over-represented in protein complexes
It is commonly acknowledged that transient interactions involve short motifs whereas more stable interactions, such as the ones found in protein complexes, are mediated by DDIs [2]. Accordingly, we would expect that the fraction of PPIs attributed to DDIs within stable complexes will be higher than in the whole PPI network. To test this, we examined two datasets that contain information on protein complexes in S. cerevisiae [17, 18]. The first database, MIPS, is manually curated and is considered to be highly reliable [17]. The second database is based on a highly sensitive large-scale study conducted by Gavin and coworkers [18], in which the proteins involved in complexes were classified into cores, modules, and attachments. Based on the work of Gavin and coworkers, cores contain the most reliable members of the complex, attachments contain less reliable participants, and modules are attachments that recur in several complexes. We marked the PPIs that reside in these complexes, and examined the DDI-PPI mapping for these interactions. Figure 5 shows the fractions of PPIs onto which DDIs could be mapped in the various datasets of complexes, in comparison with the whole yeast interactome. It is clearly seen that in every dataset there is enrichment in PPIs attributed to DDIs compared with their fraction in the entire PPI network (P values range between 3.4 × e-77 to 2.8 × e-45 by χ2 test). It is remarkable that the MIPS data and the core data reported by Gavin and coworkers exhibited the greatest enrichment, and as we added more remote components of the complexes (modules and attachments) the fractions of PPIs attributed to DDIs decreased. This supports the involvement of DDIs in more stable interactions.
Using a compilation of structurally derived interacting domain pairs [12, 13], we show that experimentally determined interacting protein pairs are statistically significantly enriched in these domain pairs. This suggests that there is a limited catalog of domain pairs that is used to mediate various interactions in the cell and that this catalog is shared to various degrees by different organisms. The fact that the domain regions cover large fractions of the sequences in our study (see Materials and methods, below) further strengthens this finding. Nevertheless, it should be noted that our conclusions are based on putative mappings of the DDIs onto the PPI networks. Until these complexes are solved crystallographically, there is no certainty that these are indeed the domains that mediate the interactions. However, several considerations corroborate our conclusions. First, in the structural databases we also find repeated use of the same DDIs in different PPIs or complexes and in different organisms. Second, our results are highly statistically significant; the counts of PPIs attributed to DDIs in 1000 random networks are always substantially smaller than their counts in the actual networks. Third, we show that PPIs that involve only single-domain proteins are also statistically significantly enriched in the structurally derived DDIs. Fourth, we find the structurally derived DDIs in the PPI networks of various organisms and show that their conservation is statistically significant. Finally, we show that protein complexes that are believed to involve DDIs are enriched in the structurally derived DDIs. All of these findings support the identified DDI-PPI correspondence. Previous studies carried out statistical analyses of all possible domain combinations in a dataset of PPIs and identified over-represented pairs that were suggested as the domain pairs responsible for the interaction [4, 7, 9]. Demonstrating this phenomenon based on structurally derived DDIs further supports this conjecture, and is important both for understanding the molecular basis of the interactions and as a basis for the identification of new interactions.
Although our results are highly statistically significant, the fractions of PPIs with annotated domains that have been attributed to the structurally derived DDIs are relatively small, ranging from 6% in D. melanogaster to 20% in human. This may be due to the lack of information for many DDIs that probably play a role in mediating the interactions, but have not yet been found in solved structures and therefore were not included in this analysis. It is conceivable that with the increase in the number of solved structures, the number of DDIs will increase, followed by an increase in the PPIs that can be attributed to DDIs. A first clue in this direction can be obtained by the expansion of the catalog of DDIs by additional DDIs derived from interactions between single-domain proteins. For single-domain interacting proteins there is almost no doubt as to the domains that may be involved in the interactions, and therefore they provide information that is almost equivalent to domain-level information from solved structures. In our data, some of the single-domain PPIs could be attributed to the structurally derived DDIs, but there were many others that were not classified by the DDIs (Table 2, row iii). These can be used to expand the dataset of DDIs. Indeed, inclusion of the single-domain interacting pairs extended the database of DDIs from 2,983 to 8,228 DDIs. Repeating the same analysis, using this extended DDI database, resulted in the mapping of 20% to 32% of the known PPIs with annotated domains by these defined DDIs (Table 4). These highly statistically significant results (P < 0.001) add further support to the suggestion that there is a finite set of interacting domain pairs mediating the PPIs, and that these domain pairs could be considered as the 'building blocks' of the interaction networks.
Assuming that the DDIs mediate more stable interactions, can we evaluate the fractions of stable and transient interactions in the interaction networks from the fractions of PPIs attributed to DDIs? Clearly, our analyses provide an overestimate of the transient interactions and an underestimate of the stable interactions, because not all proteins could be annotated by their domains and because there are probably more DDIs but they have not yet been identified in solved structures. In addition, we used in the analysis interactions based on both large-scale and small-scale experiments. It is possible that a fraction of the interactions that were not attributed to the DDIs do not necessarily represent transient interactions but include false-positive interactions based on large-scale experiments. Indeed, when we repeated the analysis for yeast, including only interactions based on small-scale experiments as reported in the DIP database [19], we obtained a fraction of 20% PPIs attributed to DDIs (versus 9% for PPIs based on both small-scale and large-scale experiments). Thus, in this regard our analysis can be considered as providing a rough estimate of the minimal fraction of stable PPIs in the cellular networks.
Of the DDIs in the structural databases, 399 (13%) were derived from both DDIs within a protein ('intraprotein interactions') and interactions between proteins ('interprotein interactions'). This finding has two implications. First, it provides reassurance for use of DDIs derived from either interprotein or intraprotein interactions for analyzing the domain pairs in PPIs. Second, it lends structural support to the inference of PPIs or functional relationships in cases where domains A and B are found in two different proteins in one organism whereas they are fused into a single protein in a different organism, as suggested by Marcotte and coworkers [20] and Enright and colleagues [21]. The mapping of DDIs onto PPIs further strengthens this conjecture, as 23% to 32% of the PPIs attributed to DDIs in the aforementioned organisms are based on this subset of DDIs (Additional data file 1 [Supplementary Figure 1b]). As already pointed out by Tsoka and Ouzounis [22], we find that many of these DDIs are involved in metabolic processes. Interestingly, although in the structural databases and in our mapping, many of the DDIs are homotypic; this phenomenon is not observed here. Of the DDIs derived from both intraprotein and interprotein interactions, 62.4% are heterotypic interactions and only 37.6% are homotypic interactions. This is in accord with the recent report by Wright and coworkers [23], who suggested that homologous domains in proteins accumulate mutations in order to avoid aggregation. Avoidance of homotypic interactions within proteins should have even a stronger influence toward preventing aggregation. Surprisingly, we found that a very small fraction of the PPIs (2% to 4%) were attributed to DDIs derived solely from intraprotein interactions. The analysis of Littler and coworkers [24] may provide an explanation for this finding. This study pointed out that most of the adjacent domains within a single polypeptide chain (separated by a short loop) tend to interact with one another. This may suggest that some of the intraprotein DDIs may occur merely because of the vicinity of the two domains in the sequence, and would not necessarily occur between two proteins.
Our finding that homotypic DDIs constitute, on average, more than 50% of the DDIs used by an organism, and even higher fractions of the DDIs conserved between organisms, is consistent with previous publications that reported the relatively high abundance of homodimers in PPI networks [25–27]. Ispolatov and coworkers [25] reported that both homodimers and dimers formed by paralogs are very abundant. This strengthens the notion that PPIs are more inclined to be mediated by similar elements. Our analysis brings this notion one step further, because we found homotypic interactions mediating interactions between different proteins, and not just homodimerization, both in the structural database and by our mapping. Several attempts have been made to explain the source of homodimer abundance, from improved stability, through functional suitability (for example, binding of a homodimer transcription factor to a symmetric binding site), to reduction in genome size [25–27]. However, for homotypic DDIs in different proteins these explanations do not hold, and there must be a biophysical explanation for their advantage [28]. Such an advantage may be reflected in stabilizing mutations, which will have a double effect in homotypic interactions. It is possible that such considerations played a role early in evolution, leading to self-interaction of certain single-domain proteins. Such domains may have been joined later by other domains to create multidomain proteins whose interactions are mediated through the homotypic interactions [15].
Comparisons of the DDI catalogs of the five organisms in our study confirm that the 'building blocks' of the interactions are conserved in evolution. Previously, the PPI networks themselves were compared, revealing subnetworks that were conserved in evolution [29, 30]. Here we show similar findings at the domain level. Among the 1637 DDIs, which we mapped onto the PPI networks of the various organisms, 665 DDIs were mapped to PPIs of at least two organisms. The number of DDIs common to four organisms ranged from 29 to 84, where the low numbers regard DDIs common to E. coli and three eukaryotes. These numbers are remarkable in view of the very small overlap that was recently documented for the PPI networks of human, yeast, fly, and worm [31], when sequence similarity per se was used for comparison of pairs of interacting partners between species. When comparing the PPIs in the four networks only 16 common interactions were found [31], whereas we find 84 common DDIs used by these four organisms. The differences in the repertoires of shared DDIs between the E. coli PPI network and the networks of the three other eukaryotes, and the differences observed between the four eukaryotes are also remarkable. Although some DDIs appear to be ancient and are shared by all organisms, other DDIs have probably evolved more recently. It is possible that the source of the DDI-PPI correspondence is in interactions between pairs of single-domain proteins that occurred in various organisms at different evolutionary stages, defining the 'seeds' of the DDI catalogs. These single-domain proteins recruited additional domains, but they maintained their ability to interact through these domain pairs. Conceivably, there are such DDI seeds that evolved early in evolution and they are found in many organisms, and others that are related to more specialized processes and evolved in certain species and not others. This may explain the recurrence of the DDIs in various organisms and in various cellular contexts.
By computationally mapping structurally derived pairs of interacting domains onto the PPI networks of five organisms (from E. coli to human), insights into the roles of these domain pairs in the interactome networks were gained. The over-representation of these interacting domain pairs in experimentally determined protein complexes corroborates the suggestion that more stable interactions in the cell are mediated by interactions between domains rather than short motifs. There are interacting domain pairs that are used repeatedly in each of the networks, and many of them are evolutionary conserved from prokaryotes to eukaryotes. In fact, there are domain pairs that are conserved in all five organisms. This latter finding is very interesting in view of recent reports that showed that the conservation of the PPIs themselves among several organisms is very low. It seems that there are interacting domain pairs that are used as the building blocks of the interactome networks and they are conserved more than the interactions themselves.
Materials and methods
Compiling the structural database of DDIs
We used two sources to compile a nonredundant structural database of DDIs: the 3DID [12] and iPfam [13]. These two databases (September 2005 versions) were filtered and unified as follows. For each pair of interacting domains A-B documented in each of these databases, we calculated three measures: the number of interacting amino acids in A, the number of interacting amino acids in B, and the number of amino acid-amino acid interactions between the two domains. Two domains reported in either iPfam or 3DID as interacting were included in our database if each exhibited at least three amino acids involved in the interactions and if there were at least three interactions between them. In addition, only entries with explicit amino acids were considered (entries with ambiguous names were filtered out). Also, we manually examined DDIs based on PDB structures consisting of at least two interacting molecules, in order to avoid false-positive DDIs resulting from crystal packing. At the end of the various processing steps, our database contained 2983 structurally derived DDIs.
Compiling species-specific PPI databases
We used three public databases as sources of the PPIs: INTACT [32], DIP [19], and BIOGRID [33]. These databases consist of both literature-curated PPIs from small-scale experiments and PPIs based on high-throughput experiments. For each of the five organisms, E. coli, S. cerevisiae, C. elegans, D. melanogaster, and H. sapiens, we generated a nonredundant dataset of documented PPIs. Because some of the interacting proteins in human were published by their gene name, there was a concern that we may assign DDIs involving domains that actually were not included in the mature proteins because of alternative splicing. Therefore, human proteins encoded by alternatively spliced genes were excluded from the study.
Domain assignment
We used the domain definitions of the InterPro database [34] for the assignment of domains to each of the proteins in our study. A protein may be labeled by one or several different domains. We examined what fraction of the protein sequences in our data are covered by the domains (based on the InterPro annotations), and found that on average the domains cover 91.3% of a protein's residues. In case a specific domain occurred more than once in a protein, it was assigned only once. In order to characterize the interacting domains, we used the domains' Gene Ontology (GO) annotations from the InterPro database.
Statistical evaluations of the results
The first question we addressed was to what extent the organism's PPIs could be attributed to the structure-based DDIs. To this end, we counted the number of PPIs to which DDIs could be mapped. To evaluate the statistical significance of our findings, we generated 1000 random PPI networks for each of the five organisms, preserving the number of nodes and the degree of each node. The random networks were generated from all the proteins of an organism. For a given organism, we counted for each random network the number of PPIs to which DDIs could be mapped. The fraction of random networks where this count was equal to or exceeded the count in the actual network provided the statistical significance. Our statistical analysis guarantees that any over-representation of DDIs found in the PPI networks is not due to large families of proteins that contain these domains, because these large families were also taken into account in the generation of the random networks.
We next studied the evolutionary conservation of DDIs by comparing the DDI repertoires of the organisms. To evaluate the statistical significance, we generated 1000 random DDI networks for each of the five organisms. The random networks were generated from all the InterPro domains assigned to the organism's proteins, while preserving the number of nodes and the degree of each node in the original DDI network. We then performed 1000 comparisons between the random DDI repertoires of two or more organisms. The statistical significance of the conserved DDIs was evaluated by comparing the number of conserved DDIs between two or more organisms to the equivalent counts in the random networks, and computing the fraction of random networks in which the conserved DDI count was equal to or exceeded the actual count.
Exclusion of interologs
Two pairs of interacting proteins in two organisms are defined as interologs if each pair-mate is an ortholog of its corresponding pair-mate in the other organism [35, 36]. Such interologs might contain the same domains correspondingly and therefore may lead to a conclusion that their DDIs are conserved, whereas it is the orthology per se that is the basis of this finding. In order to avoid such misleading conclusions we repeated the analysis after exclusion of interologs. We determined orthlogous proteins based on three resources: The COGs database [37, 38]; the Metagenes database [39], which consists of sets of genes across multiple organisms whose protein sequences are one another's best BLAST [40] hits; and the String database [41]. Interologs were omitted based on the orthology relationships and our databases of PPIs.
Exclusion of paralogs
An additional bias in the results may be caused by paralogs. Two pairs of interacting proteins within the same organism that exhibit paralogy relationships correspondingly may lead to false conclusions about repeatedly used DDIs within an organism due to paralogy per se. To rule out conclusions due to such a bias, we repeated the analysis after exclusion of interacting paralogous pairs. Paralogs were determined by BLAST [40], using a strict E value threshold (10 × e-35), in order to avoid exclusion of two unrelated proteins that only share a domain.
Additional data files
The following additional data are available with the online version of this paper. Additional data file 1 contains a series of supplementary figures and tables. Additional data file 2 contains lists of DDIs for E. coli, S. cerevisiae, C. elegans, D. melanogaster, and H. sapiens. Additional data file 3 contains lists of DDIs that are shared by two or more organisms (E. coli, S. cerevisiae, C. elegans. D. melanogaster, and H. sapiens).
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We thank Ruth Hershberg, Ora Schueler-Furman, and Ariel Jaimovich for their useful comments on the manuscript, and Shmuel Sattath for his help with the analysis. We are grateful to all our group members for useful discussions. This study was supported by the EU grant 3D-repertoire, contract number LSHG-CT-2005-512028.
Electronic supplementary material
Additional data file 2: Lists of DDIs for E. coli, S. cerevisiae, C. elegans, D. melanogaster, and H. sapiens; each domain pair record contains InterPro accessions, domain names, number of occurrences, and GO annotations. (XLS 511 KB)
Additional data file 3: Lists of DDIs that are shared by two or more organisms (E. coli, S. cerevisiae, C. elegans. D. melanogaster, and H. sapiens); each domain pair record contains InterPro accessions, domain names, number of occurrences, and GO annotations. (XLS 438 KB)
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Itzhaki, Z., Akiva, E., Altuvia, Y. et al. Evolutionary conservation of domain-domain interactions. Genome Biol 7, R125 (2006). https://doi.org/10.1186/gb-2006-7-12-r125
DOI: https://doi.org/10.1186/gb-2006-7-12-r125


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The city of Myrtle Beach is ready to go to the dogs for the week of Oct. 25-31 for the Great Dane Club of America's annual meeting and convention at the Myrtle Beach Convention Center. Hundreds of the jumbo-sized dogs and their proud owners will converge on the town to share their passion for the popular dog breed.
Held at the Myrtle Beach Convention Center, the event is only two blocks away from the pet-friendly Breakers Resort on the downtown oceanfront. Convention guests can find great accommodations for their dogs and themselves at the spacious Breakers Resort, including easy access to the beach for the dogs to run. Guests can make the short stroll to and from the convention from their luxurious room at the Breakers.
A full week of festivities are on the agenda, including organizational meetings, committee meetings, vendor booths featuring veterinarians, educational seminars for breeders, judges, trainers, and handlers. Owners and their dogs can also find plenty of fun things to do with their four-legged friends, including meet and greet opportunities at The Breakers and other dog-friendly venues around Myrtle Beach.
In addition to all the great events scheduled for Great Danes throughout the week, visitors for the GDCA event can find lots of fun things to do around town with their dogs. Myrtle Beach is home to two Bark Parks, where dogs can legally roam free, fetch, swim and make new friends. The Coastal Grand Mall area is home to a Petsmart outlet for all of your animal's needs, and there are hiking trails and other areas where you can mix and mingle with other lovers of the breed. Of course, the beach is the best place to take your dog for a walk, and the Breakers Resort property and adjoining beach provide the perfect place to unwind during your down time from the convention.
The festivities get under way Sunday night with a board meeting and a Welcome party, followed by the first full day of activities Monday, which include Fertility Day and the opening of Obedience and Rally Trials. The second round of Rally Trials will be held Monday night, including a formal dinner at the Myrtle Beach Convention Center. Fertility Day continues Tuesday with the second round of Obedience Trials, a general membership meeting and the Top 20 Dinner & Competition to round out the preliminary events and festivities.
Wednesday's schedule sees the start of the regular program, including Agility, Health Training and a Guided Bus Tour to Charleston for those interested in seeing the historic city to the south. The evening's highlights are a Pajama Dinner & Party for both the two-legged and four-legged participants. Guests and their Great Danes are invited to take part in the slumber party by dressing up in their best nightwear, with prizes awarded for Best Puppy, Adult, Veteran, Brace and Human-and-Dog Team. Everyone who dressed up for the occasion is entered into a drawing for a special prize, and raffles are held throughout the week.
Day 1 of Judging is held all day Thursday, followed by the second GDCA Board Meeting, Dinner & Auction. Friday sees the second day of Judging, a Juniors Party, Ringside Cocktails and an Evening Parade that allows handlers and their dogs to strut their stuff before the main event on the weekend. The highlight of the week is Saturday's Showmanship and Breed Judging with the winners' award banquet at the MBCC. For those who can stick around the Grand Strand for Sunday, the week concludes with the Independent Specialty Show, hosted by The Great Dane Club of Central North Carolina.
For a great time for you and your Great Dane, stay and play at the Breakers Resort in Myrtle Beach.
(Posted: 10/12/15)

subset: commoncrawl


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With such history it is no wonder that it is the second oldest city in Kyoto Prefecture, and with just 80,000 people the lifestyle is more relaxed compared to Kyoto. If you wander around the Shimoyanagimachi and Teramachi areas, you can still see traces of its history, with many old buildings and shops that date back to the 19th Century.
In April 9 and 10 each year there is a Fukuchiyama Castle Festival, while in fall come and see the beautiful autumn leaves at Choanji Temple, which is also called Momiji (maple) temple.
Nearby is the Sandanike Park Recreation Area, which also houses a science museum, planetarium, as well as a beautiful lake and gardens.
There is also a zoo which is famous for Miwa, the piggyback riding macaque and Uribo, the boar who is the other half of the famous couple. The Zoo is also resident to Grey Kangaroos, Penguins, Orang-utans and Raccoons.
The zoo is open from 9am to 5pm all year, except Wednesdays. If Wednesday is a public holiday, then it would close on Thursday instead. Admission is very budget friendly at 210 yen for adults and high school students, and 100 yen for children.
Fukuchiyama is also the southern terminal for the Kita Kinki Railway which takes you to Amanohashidate, one of the three most scenic spots in Japan. From there you can head to Ine Bay, which is famous for boathouses that line the water and is the scene of many movies and TV dramas.
While Fukuchiyama is considered off the beaten track for most travellers to Kyoto Prefecture, it is actually easier to get to than I thought. It is about 1 hour 20 minutes away from JR Kyoto on the Hashidate Limited Express, and 1 hour and 30 minutes north of Osaka on the Tango Explorer or Monju/ Kitakinki Limited Express. JR Pass holders can use these trains for free.More
R Inn has majestic views over Fukuchiyama station on one side and the distant mountains on the other. In a city that doesn't h..
Long before the advent of Shinkansen or bullet trains, steam locomotives such as the C 58 series ferried passengers and freight..
Fukuchiyama City Zoo is the only zoo in Northern Kansai, featuring family friendly facilities where you can interact and feed animals...
Thank you


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Gone are the days when "fashion" was just a thing for "women"; many men are now breaking away from the "traditional", "conformist" and dare I say "boring" styles and embracing new clothes in new colours.
Look at the former One Direction member Harry Styles for example, who is upping his fashion game as the days go by (by no means are we taking the credit away from his talent, we love his new single album). But come on just look at him, he proves that pink suits are a thing can be ever so manly.
If you are someone who loves to play around with clothes and experiment with them from time to time, great. However, if you are not comfortable in coming out of the comfort of your shades of black, white, and brown, we would suggest that you take baby steps; for example maybe order some crazy coloured mens pyjamas online and start wearing them inside your house. You never know you might even start taking fashion risks outside the comfort of your house.
Well, whatever above mentioned categories you belong to, you should be aware of the fashion experiments we are about to tell you. These are some risks that you should certainly take; needless to say that you will attract those ladies as they love a man who can take these risks.
1.) Say yes to colours: This is the most essential thing if you want to experiment with fashion. We agree that many men are opening up to the idea of playing around with colours. We also agree that the men's section now has more colours than earlier. However the fact remains that many men are still not comfortable in wearing anything else than blue, black, grey, white and brown. So, boys/men, we need to see more colours on you.
2.) Try the combination of brown and black: Sounds odd, right? We know that this combination is majorly frowned upon and is thought of as a hideous pair. But believe us, if done right, this can do wonders for you. It is important that before you decide to give it a short, you search the internet for inspiration.
3.) Include coloured socks in your formal attire: Again, it might sound odd as it breaks away from the serious tone of formal dressing. Adding a dash of colour to your formal clothes with a funky pair of socks is a wonderful idea. The best thing is that it does the trick by breaking the monotony at the same time not being too distracting.
4.) Including two different prints at the same time: Yes we know, we might be asking for too much here, but believe us it is worth a try. Of course we are not asking you to go ahead and wear just any two prints, we are asking you to create a well thought out attire around it. If you are willing to try it, internet will be of great help.
5.) Experiment by mixing vintage pieces with the modern ones: Mixing vintage clothes with modern ones is indeed is a risk worth taking. They go really well together. So, go ahead experiment around it and we are sure that you will come up with something that will make the ladies swoon.
These were the 5 fashion risks that you must give shot to. Do not hesitate to go ahead with them. We are sure that you would not regret the decision of being bold in this case.
Don't forget to loop us in when you try them.


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This 2019-2030 Regeneration Strategy for the Isle of Wight was adopted in June 2019. The strategy aims to set out how the council is leading the agenda to ensure the economic future of the Island and create the Island that is a great place to grow up, live, work and visit. The strategy sets out where we are today and the actions and activities we believe will enable the vision for the future to be realised.
Inspiration Island: Our vision is for the Isle of Wight to be an inspiring place to grow up, live, work and visit.
Following a year of conversations and discussions, and the publication of the draft strategy, this document aims to capture the challenges the Island faces and set out the ways in which these challenges might be overcome during the next 10 to 12 years. The strategy is split into six key themes. This executive summary is designed to allow the reader to get a snapshot of the document and set out what we mean by each theme and some of the key activities and actions that are planned.
What's already been done
The consultation for the regeneration strategy ran from 19 July 2018 to 12 October 2018, but if you have comments or queries about any aspect of regeneration, you can email them to us at any time.
Newport Place Plan: Shaping Newport
Between November 2017 and April 2018, the Shaping Newport project, a collaboration between the Isle of Wight Council, Newport Parish Council and Newport Business Association, set out to ask the people of the county town for their experiences and opinions of the place, its positives and negatives. See the report here.
2017 initial consultation
We invited Islanders to complete a survey over summer 2017 and held a series of workshops across the Island to reflect back the results of the survey and further understand what makes parts of the Island more or less successful.
The results from the first surveys are available to download and read Area Workshop feedback analysis (PDF 28 Pages, 7mb). Or view below:


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Fashion in Russia 2018: which are the best shirts of the World Cup?
What inspired designers of brands such as Adidas and Nike to create these uniforms?
The uniforms of the national teams are one of the favorite themes of the World Cup. This year, which is the most beautiful shirt? What inspired designers of brands such as Adidas and Nike to create these uniforms?
Leer en español: La moda de Rusia 2018: ¿cuáles son las mejores camisetas de la Copa del Mundo?
Colombia: the most beautiful
By March of this year, only 19 teams had made public the shirts they would use for the Russian championship. However, the British tabloid 'Mirror' made a top with these 19 garments, in which the best was that of Nigeria.
Insert picture 'Nigeria'.
"It's amazing, frankly, and will make us all Super Eagles during the summer," wrote the English media, hinting at the nickname with which the African team is known.
However, in the second place was Colombia, being the best Latin American shirt in the ranks, followed by Argentina, in the tenth place; Brazil in 11; Uruguay in 14 and Mexico in 15.
However, the surprise for Colombia was greater, when climbing a position in the last ranking exposed by The Telegraph, last May. In the top of the London newspaper, the yellow shirt of the national team was the most beautiful of the 64 that will take place in the World Cup in Russia, counting the local and visitor of each team.
"The first impression was that the yellow did not shine as much as in the previous World Cup (...) Without the winter and with the sunrise, we can see what this Colombian equipment really has: it borders on perfection; is our winner ", was The Telegraph's analysis of the Colombian garment.
Insert picture 'Colombia 1'.
In second place was the shirt of Germany (local), followed by the one of Brazil (visitor). While the "less beautiful" was the holder of the selection of Switzerland.
The 'retro' takes the World
Of the 32 football teams participating in the FIFA World Cup, 12 of them are equipped by Adidas.
The German sportswear brand outperforms the American, Nike, which makes the uniforms of ten national combos.
Therefore, the retro fashion that Adidas chose for their respective teams will be the one that most prevails in the next world championship.
Based on the shirts of the 80s and 90s, the designers of this multinational decided to remember in Russia 2018 great moments lived by the teams they wear during these decades.
Among the shirts of the Latin American teams, those from Argentina and Colombia stand out.
The jacket that Argentina will wear is inspired by the garment worn by the 'gauchos' in the 1993 Copa América; the last great glory achieved by the football team of this country.
"The laurels run in a modern pixel optic to offer a contemporary look and you can find two gold stars above the badge, in celebration of the two World Cups harvested," said Adidas.
Insert picture 'Argentina'.
For its part, the shirt of the Colombian team evokes the one used by the 'coffee' cast in the 1990 World Cup, in which they made it to the knockout stages of the competition. This had been the best participation of Colombia in the history of the World Cups, before reaching the quarterfinals in the last World Cup in Brazil 2014.
Insert picture 'Colombia 2'.
Also, European teams such as Germany, Spain, Belgium, and Russia will carry the memory of old achieved glory or teams that, even without winning anything, deserve to be in the memory of their fans.
Latin American Post | Christopher Ramírez Hernández
Copy edited by Laura Rocha Rueda
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Light Symposium Wismar 2016 (LSW 2016), held from October 12 through Friday, October 14, 2016, is a 3-day light forum that will bring together recent insights into the effects of healthy light and lighting in daily life. All with respect to research, theory, technologies, design and applications.
Following the popular symposia in 2008, 2010, 2012 and 2015 in Wismar and Stockholm, it aims to deliver a state-of-the-art outline of how natural and artificial light affects human beings' physical and mental health, efficiency, and performance. The symposium offers an outstanding occasion for researchers, students, and practitioners to keep up-to-date with recent findings.
The Light Symposium Wismar 2016 will close with a PLDC 2017 warm-up on the Friday evening. All Light Symposium attendees are welcome to attend this professional lighting design community networking event.


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While you can't endorse a presidential candidate as a church, you are allowed to learn from them. And there's plenty to learn from the communications practices of candidates. Let's start with their web sites (I've blogged about these issues elsewhere, but let's apply them to the church):
Web 2.0 Friendly
Both John McCain and Barack Obama are embracing the web 2.0 wave. They've got MySpace profiles, Facebook friends, YouTube videos and Twitter tweets (they also both have their own social networking sites, my.BarackObama.com and McCainSpace). The real question is if they'll make the most out of them. More channels can just be more noise unless you take advantage of the unique strengths of each new channel. And if you ignore the rules like John McCain did last year, you'll end up looking ridiculous.
For Churches: Twitter, YouTube and Facebook can be great tools, but know how to use them. Don't just jump on the latest bandwagon.
Barack Obama Has No Search Box
If you visit Barack Obama's web site you'll be hard pressed to find a search box. His site is huge and crammed with information, but there's no search functionality. What? It doesn't matter how great your content is, it's worthless if people can't find it.
For Churches: Make sure your web site has a search box. Google can hook you up for free if you're technically inept .
Answer Questions
I contacted both candidates last week with a simple question and received widely different responses. Barack Obama's campaign added me to their e-mail newsletter without asking and has sent me eight e-mails in a week, none of which answered my question. On the other hand John McCain's campaign hasn't sent me so much as an auto-response. One candidate gives me the cold shoulder, the other won't leave me alone. And neither one answers my question.
For Churches: Answer questions as they come up. And if you don't know the answer it's OK to say so. Just communicate with people. That's what most of our marketing work is trying to get people to do, so don't turn someone off by failing to answer a question.


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The Atlantic recently published a column about fact checking by Alesh Houdek. Houdek asks a question and by the end he gives us an answer. The answer reveals the key problem with modern fact checking, though Houdek apparently doesn't completely see it.
The question (from the story's deck):
Seen from the right angle with the right squint, the claim that PolitiFact named 2012's lie of the year looks like the truth. What does that mean?
Houdek makes some appropriate observations, such as the subjectivity of the various rating scales mainstream fact checkers use, but he reaches an incredible conclusion.
The answer:
It's not the rating that matters, but the deep dive into the facts behind a statement and the vigorous debate that it engenders.
Put another way, the ends justify the means.
It's hypocritical thinking.
If it's okay for some of the most popular fact checkers to use misleading and subjective ratings systems to make judgments on partisan political speech, then why can't the politicians claim a share of that credit?
It's not the accuracy of the political claim that matters, it's the vigorous debate that it engenders.
It's not the accuracy of the political claim that matters, it's the effect it has on the electorate.
Houdek leaves out a key component of the Romney/Jeep controversy: PolitiFact fact checkers misled in their judgments of the ad just as surely as the ad misled viewers in the first place–if not more so. Romney's ad, after all, did not make the explicit claim that fact checkers used as their pretext for condemning it. In comparison, fact checkers deliberately conflated the ad with a speech in which Romney mischaracterized a news article he had seen. Annenberg Fact Check did it. The Washington Post Fact Checker did it. PolitiFact did it.
To get readers to understand the misleading message of the ad, the fact checkers had to introduce readers to a statement from Romney with which they would probably otherwise be unfamiliar. The fact checkers took an ad featuring true statements and an overall ambiguous message and presented it as a deliberate deception pushing a very clear message. The hidden context was the key to understanding Romney's supposedly dishonest strategy.
"It's not the rating that matters."
Of course the rating matters. The rating is the blaring mainstream media message that just happens to fit, more often than not, with the Republicans/Romney liar meme. That's why, for example, fact checkers at PolitiFact in 2008 gave then-candidate Barack Obama a "Mostly True" rating for saying Biden wrote the Violence Against Women Act after which domestic violence "dropped dramatically." PolitiFact admitted Obama was sending a false message with his statement. But they don't nominate "Mostly True" statements for "Lie of the Year," do they?
Claiming the rating doesn't matter gives fact checkers tacit permission to present their subjective opinions as though they are facts.
The ratings matter because they are imprecise summaries used primarily to help pique reader interest. Their imprecision and subjectivity regularly mislead readers, especially those who do not bother giving the accompanying stories a thorough read. And having the summary makes it easier to skip the details.
Annenberg Fact Check is right to avoid using such flawed gimmicks. We can either excuse fact checkers for engaging in deception with such devices or else demand that they change what they're doing.
Let's not pretend it doesn't matter.
Correction Feb 25, 2013: Thanks to reader J.D., who pointed out that I had referred to "objective opinions" in the third-to-last paragraph. Make that "subjective opinions" despite the redundancy.


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- Material covering: sintered
- Material support plate: steel
- Compatibility: Formula Cura 4
- Weight: 25g pair
Brakes & Brake Pads
Formula Cura 4 Brake Pads Sintered – Bulk Packaging
In stock
The coverings are made of sintered materials and bound with synthetic resin. In order to improve the braking properties and reduce abrasion, the coating contains small amounts of metal particles. Nevertheless, the coverings are mostly sintered, you could say they are semi-metallic. This mixture gives optimum dry and wet braking values and also keeps the wear of the disc low.
In stockCompare


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Kilted Kamikaze2013-09-06
- 1 oz Japanese Whisky
- 2 oz Pomegranate Juice
- ¼ oz Canton Ginger Liqueur
- ¼ oz Campari
- ¼ oz Créme de Cassis
- ¼ oz Lemon Juice
- Shake the whisky, pomegranate juice, Canton ginger liqueur, Campari, crème de cassis, and lemon juice with ice in a Cocktail Shaker. Strain into a Coupe Glass.
- Garnish with a Lemon Twist.
The Scottish influence in Japanese whisky is undeniable. This smoky, sweet, and bitter concoction showcases Japanese whisky in a flavor-packed cocktail bomb! This complex and delicious drink is a great sipper or the perfect accompaniment to a juicy steak or a greasy hamburger. Named after the "divine wind" which saved the Japanese homeland from an invading army in the 13th century, this cocktail will hit every sense and stimulate every taste bud. Enjoy!
VN:F [1.9.22_1171]Kilted Kamikaze, Add to favorites
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From firstname.lastname@example.com Sun May 13 08:16:46 1990 From: firstname.lastname@example.com (Jeff W. Hyche) Subject: ModPail
A while back, one of our users started a discussion about all the different types of users that show up on a BBS. This inspired us to challange everyone on The Stargate BBS to make up a Garbage Pail Kid type name and a short summery of the Kid's character. If you are under the age of 20, or have school aged kids at home, you know what we are talking about….if you fall between the carcks, Garbage Pail Kids are tasteless little cards that can be collected that feature unfortunates such as Acne Andy. Well, Stargate never pretended to be a tasteful board and therefore we are proud to present our collection of….
Modem Pail Kids
Anxious Albert- This user leaves a message to a fellow user on the BBS. Trouble is, he's so anxious to see if he received a response, he calls back ever 15 minutes to check, thus preventing his buddy (or anyone else) from logging on and answering him.
Baud-Rate Bert- This user trys to call a 300 baud BBS at 1200 baud and waits for the SysOp to pick up the phone after it rings….then he HANGS UP!
Buffer Bob- This user leaves his buffer open constantly in case somthing important comes ome the screen. Of course when somthing important does appear, they belatedly realize that the buffer filled up a long time ago.
BBS Bill- This is a SysOp who logs onto a BBS for the sole purpose of advertising his own BBS.
Big-Brother Brent- This SysOp gets his kicks by watching users quietly while they go about their business on the board. Suddenly, while the user least expects it, he suddenly makes his presence known, and scares the user to death.
Blank Betty- A user who leaves a message like this: …………………………………………and then wonders why she never gets any responses.
Cautious Charlie- To keep his password secure, this user changes his password frequently. Unfortunatly, he has a hard time logging on and doing anything because he can never remember what his current password is supposed to be.
Chatting Carl- This user insists on trying to chat, even when a message announces that the SysOp isn't around.
Chatty Patty- This user calls the SysOp to chat just to see if he is a Big Brother Brent and has been watching her session.
Cheap Curtis- This user looks through every computer magazine to find the cheapest price for his hardware. He eventually finds out that when it arrives, it needs so many additional parts that by the time he gets it all together, he's spent far more than he would of if he had bought it retail in the first place.
Depressed Dan- This user has spent $150 calling long distance to an out of state BBS to download a program he has been searching everywhere for. Thoughts of suicide arise, when upon trying the program, he finds that it doesn't work at all.
Depressed Dan Jr.- Follows in his fathers footsteps, but gets upset when he spends 90 minutes uploading a complicated file, and the SysOp wipes it. These people are always considered to have suicidal tendencies.
Dippy David- This user logs on but doesn't bother to learn the system or read any directions and subsequently leaves a lot of /s and .s at the end of his messages.
Downloading Derek- One of those users who keep downloading files from a board that doesn't support his computer because he wants the file to work so bad.
Eggbert Excuse- This user spends plenty of time explaining why he never leaves any messages on the board, but explainations are the only things he ever manages to leave.
Feedback Freddy- A user who leaves several rambling messages in feedback on different subjects and wonders why the SysOp never answers him.
Frantic Fred- A user who constantly checks his time left on the board so he won't be suddenly logged off, but never stays more than 5 minutes at a time anyway.
Fryin' Brian- This user is so impatient to get his computer, modem or whatever hooked up so that he can being to use it that he doesn't bother reading the directions cause it takes up too much time. Of course they end up shorting out everything with a resultant 2-6 wait to get whatever they fried fixed.
Game Freak Gus- This user doesn't do anything but dial BBSs to get games, and has no use at all for boards like TFC.
Gullible Gilligan- A user that buys a $8000 dollar computer only to find that the company that makes the software for it went out of business 6 months ago.
Hacker Harry- A hacker who breaks into places like a library computer system and acts like its the greatest accomplishment in the world.
Idiot Irv- A user who posts the smae message twice because they wanna be sure that everyone has seen it.
Late-Night Lenny- A user who likes to call boards very late (yawn) at night, starts to download somthing and then decides that they are too tired to wait and just hangs up leaving the board tied up the rest of the night. These people usually use 250 baud or less.
Log Off Larry- A user who thinks logging off a BBS means to hang up whenever they have had enough.
Many Board Mike- A users who is a member of so many boards that he leaves a message to a user on a local board who in actually uses a board in Florida.
Mess-Up Morris- A user who maks manis mestaks whil typying mussages und blams it on littl creatchers sucking data out of fone linez.
Message Manny- A (sometimes) new user who calls a BBS and leaves pitiful messages begging people to leave him mail.
Never Call Norman- A user who calls a BBS just often enough to discover that he's been deleted for lack of participation.
New User Ned- Someone that doesn't know anything about running a BBS yet tries to start one of his own. Most of the time he runs it with one floppy disk and calls it the best board around.
Nonsense Nick- A user who writes tons of long complicated messages that no one can figure out.
Novice Nancy- This user selects expert mode and then always lists the menu anyway.
Once-in-a-While Willy- This user calls a bit more often than Never Call Norman, but only calls to make sure he is still listed on the user log.
Pain-in-the-Ass Pete- This user reads the messages on the board and takes the Devil's Advocate side to whatever is current on the board, being generally obnoxious and boring.
Paranoid Polly- This SysOp wants a copy of your birth certificate and driver's license before she will let you on the board.
Paul Promise- The one who leaves messages everywhere about his intentions about putting up a MAJOR BBS, then never gets around to it because his parents never bought him a modem for Christmas.
Password Pete- The user who changes his password every time he logs onto a board because he is afraid that his little brother will use it to log on and ruin his reputation so he'll never be accepted on another board for the rest of his life.
Perfect Paul- this user insists on leaving messages without any mistakes al all, and when he does happen to make one, he just aborts it rather than bother with the editor.
Phantom Phred- A user who calls every day, but never posts anything.
Phoney Phil- Not a real name, just a handle of a user trying to increase his daily time allotment on a BBS by calling back as different users. He often wonders why no one else calls the board except him.
Phreaking Phreddie- This modem hacker who breaks into a banks computer system…and then wonders why the FBI is concerned.
Purging Paul- When asked by the system is he wishes to delete or kill a message after he's read it, this user is quick to answer YES, only to get a sinking feeling moments later that the message contained important information that he thought he had memorized, but hadn't.
RBBS Rob- A person who logs onto a board and goes to expert mode right away using RBBS commands, even on non RBBSs. He often leaves mail to the SysOp complaining that the commands don't seem to be working.
Re-register Ralph- Like Never Call Norman, this user registers on a BBS, but after a while is deleted because he never calls back. Then he finally gets around to calling the board, finds he's been deleted, and re-registers on the board, and once again drops out of sight.
Responding Ronald- This idiot posts responses to messages he saw on another board.
RETURNing Randy- This user constantly hits RETURN while the board is loading a program and wthen wonders why they keep seeing
Screamin' Sam- THIS USER NEVER USES LOWER CASE SO IT ALWAYS SEEMS HE'S SHOUTING AT YOU.
Slowpoke Sally- This user types so slowly that the board gets no input long enough to trigger the time out option and logs the user off.
SysOp Stan- This guy is in LOVE with new BBS programs, and constantly trys out new ones on his unsuspecting users. However he never bothers to transfer the user log or passwords which means that by the time you have re-registered and have waited the 24 hour hold, he has already taken it down and put yet another one up in its place
Testing-the-waters Ted- Lonesome for some company, this user presses the chat page cautiously, cause he doesn't want to bother the SysOp if he's busy…when the SysOp answers he then claims that "I hit the chat by accident." Depending on how the SysOp responds, the user then has a nice chat, or if he Is busy, the user has a valid excuse for paging the SysOp in the first place.
Time Bomb Tom- A user that stays on line for half an hour going from menu to menu, but not doing anything….when he finally gets up the courage to actually do somthing, he manages to mess up the board.
Uploading Oscar- This user keeps uploading the same file over and over using different names in order to take advantage of the 3 for 1 time ratio and get enough time to download the 1500 block program he's been hoping to get.
Voice Synthesizer Victor- This user will go to ANY lengths to hear his computer talk, even though you can't understand a word it says.
Whoops Wilbur- This person logs onto Stargate BBS, writes a wonderful message full of wit and wisdom, hits a to abort the message, and then logs off the BBS without ever Posting the little gem…sending it to the same place where the socks in the dryer go, never to be seen again.
William Writers-Block- This users sees "Use <CR> for new paragraph and left justify ONLY, "/*" to end."…..and every word of English he ever learned leaves his head.
Worn Out Wally- This user calls so many boards that the letters on his keyboard disappear from excessive wear.
Wondering Wally- What Worn Out Wally turns into after the letters on the keys are gone. The blankness usually comes to them after they "wake up" from their state of computer hypnosis, caused by not being able to type. They then start to wonder what happened to the keys.
Words Waldo- No matter how long the message was that was left him, this users manages to reply in only one word sentences.
With thanks to all the users of the Stargate BBS and Jean from The French Connection who provided the incentive for something like this. e
After reading the first Modpal kid text file. The users of NEB put together there own version:
Bulletin bill - the users who will sit a the bulletin menu for quite awhile and not even read the bulletin.
Amiga An-the sysop who tries to run the biggest Amiga board in the state on an IBM or and Apple.
Xmodem Andrew -This is the user who has Zmodem or Y-modem Batch and will download one file at a time using Xmodem- checksum
Virus Val-will go on every BBS in town and only download virus and Trojan checkers.
BBS Bill - Calls local and long distance just t o download bbs programs he will never use.
Hoarding Harald - A user who downloads everything new to check to see if it is the new version the Archives it never to use it again or delete it for that manner.
Jumping Jon -A sysop who tight security on his board then goes on other boards and brags about it.
Misfire Mike - A new user to board who logs on and read part of and ongoing discussion and feels obliged to leave a reply with out reading th e rest of the discussion leave the other users wonder what he is talk about.
Download Darren - The user who seams to only no one key on a board D for download
HotKey Harold - A user who sets the board on hotkey. Then types a head of himself filling up the buffer on the board and then propromply forget where he is going and what to do when he gets there.
Sleeping Sam - After using a batch download this user falls asleep at the switch to wake up the next morning with the keys to his computer firmly imbedded in his face and a slightly annoyed Sysop wonder why his board was tied up for over a hour while the user inspected one menu.
Patent Paula-this user will batch download a whole boat load of files, and sit and watch the bytes tick of afraid she is goanna miss something wonderful. Even though a few hours will go by.
Uploading Eunice- Spends 5 hours on a board uploading worthless files and then uses the extra upload credit to download like a fiend for another 4 hours!
Scriptfile Sally-A user who has to use a scriptfile on every board
Hangup Henry-He calls the boards and hangs up in the middle without logging off, or hangs up in the middle of a u/load or d/load and hangs up the board.
Call-Waiting Colby- A user that just happens to know your phone number and the fact that you have call-waiting. To knock you off of his favorite bbs, he gives you a friendly phone call, and then call the board himself.
Xmodem Xenious-Will log on to a bbs that supports zmodem and this person will be using a comm program with zmodem and will immediately start downloading with xmodem checksum
Commodore Candy- A user that owns a Commodore 64 with one disk drive and will go on every board in town bad mouthing amigas,ibms and apples and will claim her's is the best in the world
IBM Indy-Same as Commodore Candy except this user will have one 5 1/4 inch drive and no hard drive and will be on at 2400 baud
Amiga Audrey-Same as IBM Indy and Commodore Candy except this Amiga user will be using a borrowed Amiga from a friend and will really own a Radio Shack Color Computer
Time Limit Terry-A person who comes on a board with a open time limit and downloads and downloads and forgets that there are other people who want to come on
One more to add: Textfile Tex: A sysop who encourages text files like this to be put together by users on his bbs


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A federal judge in Texas has thrown out the Affordable Care Act – every single word of the sprawling law. As Michigan law professor Nick Bagley tweeted, even the calorie counts on restaurant menus are now at risk.
The Dec. 14 Texas decision, if upheld (a big if) threatens the coverage of roughly 20 million people covered in the ACA exchanges and through Medicaid expansion. (More on the numbers at the end of this post).
It affects tens of millions of other Americans either in the individual market (outside the exchanges) or who get insurance through an employer. Much has been said about the protections for people with pre-existing conditions. But that's by no means all that's at stake. There are many provisions that are very popular that people don't necessarily think of as "Obamacare" – covering adult children until age 26, the ban on annual and lifetime insurance limits, the cap on how much more older people pay for insurance than younger ones, free preventive care service, etc. Some Medicare patients would face higher drug costs. And CMMI – the Medicare and Medicaid Innovation Center and all the work it's doing on health care delivery – was also created by the ACA and is thus subject to extinction. And on and on.
Right now, nothing changes. The court ruled that without the individual mandate penalty – eliminated by Congress in last year's tax law – the law cannot stand. But the judge didn't issue an injunction. Unless the Trump administration steps in to immediately stop the ACA, nothing happens while this wends its way through the courts. The White House issued a statement on the night of the Texas decision:
"We expect this ruling will be appealed to the Supreme Court. Pending the appeal process, the law remains in place."
Of course, there is no guarantee that President Donald Trump won't change his mind. But the chaos would be considerable, and the political risk great (given that we already seem to be well into the 2020 campaign cycle and the Democrats just won the House in no small part because of voter concern about protecting people with pre-existing conditions). CMS Administrator Seema Verma has hinted about a "backup" plan but nothing has been made public. And since most observers expected a far narrower ruling, affecting patient protections but not the entire law, any "backup" might have been a far narrower fix for that more limited scenario.
So for now, premium subsidies will still be made. Protections for pre-existing conditions continue. Medicaid expansion doesn't stop (although the uncertainty may affect the states that are just now considering expansion, either because they had a referendum in November approving it or they've elected Democratic governors as in Wisconsin, Maine and Kansas). Doctors and hospitals will get paid.
But the uncertainty for both consumers and politics is not insignificant. This thrusts the ACA right back onto center stage in both Congress and the courts. People will be confused – we may never know how many people didn't sign up for coverage on the last day of open enrollment, which was the day after the court ruling, because they didn't think they still could. Democrats will be in the majority in the House and they can easily pass some ACA repair plans – but the Republican-led Senate will remain an obstacle.
So it's up to the courts. California and the other liberal states that had challenged the Texas case, itself brought by 20 more conservative states, have already said they will appeal. The conventional wisdom is that it will end up in the Supreme Court, and that will probably take until 2020. Two very prominent health law experts, Nick Bagley (pro-ACA) and Jonathan Adler (anti-ACA), have both (on Twitter) made the somewhat contrarian case that the legal argument the Texas judge made is so absurd that the Fifth Circuit (a very conservative court with five Trump appointees) will put it quickly out of its misery and it will never get to the Supreme Court. Time will tell.
There's been a ton of good reporting and analysis on this (more remarkable since the ruling popped on a Friday night when half of Washington seemed to be at holiday parties). But if you are going to read just one analyses, I'd recommend this NYT op-ed from Adler and Abbe Gluck.
NOTE: A word on how many people would lose their coverage if the law were thrown out (without other legislation put in place). Estimates vary. I've seen some news reports citing the 17 million people losing insurance estimate from the Urban Institute (but that's not how many are covered under ACA exchanges or Medicaid expansion – it's Urban's estimate of how many of those who are covered would not be insured, it assumes some of them would get insurance on the individual market post-exchange). A Kaiser Family Foundation report estimated about 15 million were covered by Medicaid expansion –12 million of whom were newly eligible. Plus there were about 10 million people covered in the exchanges last year – though that looks like it's dropping this year. And some could get insurance off exchange…On the other hand, some states are poised to expand Medicaid in 2019, boosting the number directly affected. Plus there's the under 26 population – it's hard to know how many of them would lose coverage…. And people who would have trouble getting covered in the individual market because of pre-existing conditions… A CBO estimate in 2017 found that repeal of most – not all, but most – of the law would lead to 32 million people being uninsured in a decade.


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Perhaps this question is asked so often due to the history of conquests of the island. Here is a brief history of the Mediterranean Island that became part of Italy during the unification in 1861 and today is one of Italy's five autonomous regions.
For a relatively small island, Sicily boasts maybe an unparalleled history with stories of conquest and invasion. While the following article is not meant to give you a detailed account of the island's history, its aim is to give you a snapshot of the events that have formed the land and the people that are Sicily today.
Since the beginning of time, Sicily has been fought over by all the powers of the Mediterranean. Standing at the gateway between the east & the west, it has been conquered by different people groups wanting to gain Sicily's geographical strategic advantage. Sicily stands strong today as the largest island of the Mediterranean with its unique identity & culture that has been forged as a result of the continual tidal wave of people. As a visitor to the island you'll see those legacies that have been left behind and are still embedded in the architecture, culture & language. Find out about the people that you'll encounter and the wealth of history that the island has to offer.
In prehistoric times three different indigenous tribes dwelt on the island, one of which gave Sicily its name. As time progressed and Greece sought to expand its power in the Mediterranean, settlers arrived in the eastern port of Naxos ready to make the island their home. Like many civilizations that would later arrive, the Greeks built altars across the island as an act of worship to their gods, thus changing the landscape. It is thanks to the Greeks who brought with them vines and olives, that the island is so rich in these products today.
As the Greeks arrived on the eastern side of Sicily in 735 BC, on the west coast Phoenicians arrived from modern day Lebanon & Syria to set up a trading base on the island. Not so concerned with establishing their identity on Sicily, the Phoenicians often took wives from the local population and integrated with the prevailing Greek culture. It may have been the Phoenicians who first built the salt flats in Trapani, the beginnings of a salt harvesting tradition that still lives on today.
The Carthaginians were the next to arrive from modern day Tunisia, before an important battle was fought at Himera between the Carthaginians and the Greeks. The outcome of the battle confirmed Sicily as a Greek island and the Greek culture dominated the terrain. From the Temple of Athena at Syracuse that was built to celebrate the victory in 480 BC, to the open air theaters that were built in every city. This was the golden age for Sicily who raised up important scientists during this time. One of these was Archimedes; and Plato was a frequent visitor to the island, who surmised that Sicily would be a place to put into practice his model of Utopia.
Toward 200 BC the Greek rule was coming to an end and Rome was establishing itself as the new power in the Mediterranean. During their 600 year rule of Sicily the landscape was to change again as the Romans used the fields to plant grain and build their rich, extravagant villas. Although it seems that the Romans took more from the Sicilians than they gave, their greatest legacy was to be of a spiritual nature as Christianity spread throughout the island during their time in power.
After the fall of Rome at the end of the 5th Century, Sicily was conquered by the Barbarians and then captured by the Byzantines in the Middle Ages, who ruled from Constantinople or modern day Istanbul.
At less than 100 miles from North Africa, it was only a matter of time before the Arabs arrived in Sicily and this was to happen in the 9th Century. After arriving at Mazara del Vallo, it took the Arabs 50 years until they finally took control of the whole island and the changes they brought with them would be great. For the first time, Sicily became a multi ethnic island, with Christians, Jews & Muslims all residing together. The Arabic influence was huge, moving the capital from Syracuse to Palermo, they lavishly decorated their new seat of power with gardens, parks, mosques and palaces. Although the material remnants of their reign are scarce on the island today, their influence upon Sicilian cuisine has never been renounced. Citrus trees, date palms, pistachios, almonds, sugar, eggplant were all ingredients brought over from North Africa and have flavored the local dishes ever since.
The Normans were the next group of people to conquer Sicily. The term 'Norman' meant 'men from the north' & was applied to this new group of men descending from Scandinavian, Germanic, Roman & Celtic origins who made their home in Northern France and spoke a kind of French dialect. The Normans were Christians and their society was highly evolved in its government, law, architecture and literature which would profoundly affect Sicily. In 1061 AD on a Christian mission sponsored by the Pope, the Normans invaded Sicily, led by 2 brothers from the De Hauteville family.
Sicily was to come under Norman rule and saw the introduction of a royal family as Roger II was crowned as the first king of Sicily. During his reign King Roger championed the arts in Sicily, with one of his greatest feats being the Palatine Chapel, located in the Palazzo del Normanni in Palermo with its convergence of architectural influences, one of the wonders of Sicily and inscribed on Unesco's world heritage list. Other Norman sites to be visited include the 'duomos' or cathedrals at Monreale & Cefalu.
As Norman rule came to an end, it was the Spanish who took over for the next 500 years during which time the island became more isolated and the cultural movements sweeping across Europe during the 14th & 15th century never made it to Sicily. The Spanish brought with them some products from the new world but also the Inquisition of 1478 with its aim to eliminate potential heretics from society by torturous means. The seat of the inquisition in Sicily was at the Palazzo Steri (now Piazza Marina) in Palermo where inscriptions from the prisoners can still be seen.
In 1693 a huge earthquake devastated the island killing over 60,000 people and whole cities had to be rebuilt. This was the time for Baroque architecture to flourish with lavish churches & palaces erected with colored marble, mosaic inlay and ornate decorations. The Sicilian Baroque style was unique in that it added cherubs and balconies to adorn the dramatic buildings. There are some notable examples of this delightful style that can only be found in Sicily; be sure to visit Catania, Noto or Ragusa among other cities whose architectural style is now protected.
The last dynasty to rule Sicily as a sovereign kingdom were the Bourbons, a branch of the royal houses of France and Spain. The Bourbon Kings officially resided in Naples, and Naples and Sicily were officially merged to form the Kingdom of 2 Sicilies by Ferdinand I. The Sicilians dreamed of autonomy and freedom from poverty and maladministration and being full of disillusionment, the Sicilians were ready for a revolution.
After a tumultuous history, liberation was coming for Sicily as part of a revolt led by Guiseppe Garibaldi in 1860 which would lead to a unified Italy. In 1946 Sicily became an autonomous region of Italy, the position that it enjoys today. With such a colorful history, Sicilians will always be Sicilians, with an identity that comes from the land and is felt in the soul.
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