Empowerment Of Pakistani Women

Genre Conversation Essay

In spite of the fact that sort is normally viewed as an instrument for customary grouping, it is important to perceive that a class isn't characterized by its conventional highlights, however by its situational factors. The relevant distinguishing proof of a kind is featured via Carolyn Miller, who depicts classifications as the â€Å"typified explanatory methods of acting in repeating situations† (qtd. in Bawarshi 7). The word â€Å"situation† is essential in her definition since composing results from situational requests. Such situational nature of composing is stressed by numerous researchers including Amy Devitt, Anis Bawarshi, and Stanley Fish. Orchestrating crafted by these writers, we can infer that kind joins composing and setting. Consequently as opposed to concentrating on formal highlights, a sort ought to be recognized as a freely settled structure distinguished by its logical highlights, in which essayists and perusers are socially associated. Since classification is socially characterized, it can possibly work when there is a logical circumstance that requires a reaction. Coming back to Miller’s definition, classifications are reactions to repeating circumstances. Since comparable circumstances trigger comparative logical reactions, these reactions form into a default methods of noting a specific kind of circumstance (Bitzer 13). Regardless, not all circumstances animate reactions; just circumstances in which at least one exigences leave trigger creation. As indicated by Lloyd Bitzer, an exigence is a â€Å"imperfection set apart by urgency† (6). Essayists are just propelled to compose because of the nearness of such flaw. Since an expository composing is concocted to address an exigence, the motivation behind such composing is thusly to change the circumstance thus to lighten the introduced issue. Such logical reliance of composing is featured when Bawarshi interfaces writer’s reason and circumstance, showing that composing â€Å"begins and happens inside the social and expository conditions comprised by genres† (11). At the end of the day, types arrange and persuade authors to compose for a pragmatic explanation. For instance, a notice article serves to support buying when an organization attempts to sell an item, while a science report serves to convey lab results when analysts wish to distribute their discoveries. To put it plainly, kinds are reactions to circumstances, hence what arranges a book into a sort is fundamentally the down to earth reason for the content comparable to the given circumstance. Besides, circumstances doesn't just make kinds, they additionally shape sorts. Consider the expository circumstance where a letter is composed: there are some physical separations between the author and recipient, there is a cozy connection between the essayist and collector, there is something the author needs to communicate†¦Given such circumstance, there are numerous imperatives that direct the proper highlights of composing. These imperatives give a kind its proper highlights. In this way kind improves the conventional choices scholars need to make by â€Å"organiz[ing] the states of creation just as generat[ing] the logical explanation of these conditions† (Bawarshi 9). With kind, scholars are given composing structures that permit them to reverberate the requests of the given circumstance. Once more, these composing structures are â€Å"rhetorical forms† that â€Å"comes to have an intensity of [their] own† as they are fundamentally reactions to repeating circumstances (Bitzer 13). This suggests kinds are molded by situational explicitness, along these lines specific social requests bring forth specific classifications as various circumstances underline various qualities. In this manner â€Å"keep[ing] structure and nonexclusive settings united† is fundamental for a type to work and thus for us to impart as classes are molded by settings (Devitt 200). Despite the fact that circumstance recommends suitable structures to permit compelling correspondence, it is vital to recognize that conventional highlights don't characterize classifications. Formal component can change altogether inside a class, and such â€Å"inherent variety inside all genres† is â€Å"essential to keeping kinds alive and functioning† (Devitt 212). For example, an ad can pull in clients with striking pictures, yet it can likewise sell an item utilizing enticing insights. Regardless of what formal highlights a book has, that content has a place with the commercial classification as long as it is composed to support utilization. This model delineates that in spite of the fact that setting composing set requirements to advance suitable conventional highlights, yet the writer’s design is the thing that at last characterizes a kind. Aside from contextualizing composing, type socially associates essayists and perusers. On the passing on side, scholars partake in talk networks, which are â€Å"social and expository environment[s] inside which subjective propensities, objectives, suppositions, and qualities are shared by participants† (Bawarshi 5). Authors in a similar talk network will in general utilize same or comparable types. This is on the grounds that the social settings they write in, just as the belief systems they wish to pass on, are both common inside the network. Along these lines, if an essayist decides to speak with a sort usually utilized by a talk network, that author will be recognized as an individual from network. What is the centrality of talking about talk networks? This answer relates back to the situational idea of composing †the idea of talk network features the social motivations behind sort by â€Å"locate[ing] a writer’s intentions to act inside exemplified expository and social conditions† (Bawarshi 11). Individuals from various talk networks will in general express utilizing various techniques since they compose for contrast purposes and react to various circumstances. Consequently â€Å"writers will utilize diverse language in various genres† to appropriately address the introduced exigence (Devitt 213). All things considered, sort socially associates authors by arranging them in talk networks inside which members are propelled to create by a similar kind of circumstance. Essayists are by all account not the only ones associated with the social setting of composing, a book is given significance by its perusers as it implies whatever the perusers decipher it to mean. This recommends a kind is distinguished as that sort when the perusers see so. Fish portrays understanding as â€Å"the craft of construction† (361); rather than finding what is in a book, perusers make what is in the content through translation. These translations are shared â€Å"social and social examples of thought† that outcome from encounters of acting inside the social condition (Fish 364). Along these lines, kinds are â€Å"embedded inside their social and social ideologies† with the goal that they trigger fitting understandings (Devitt 191). Genre’s situational implant underscores that composing is â€Å"dynamic, changing after some time as the suspicions, qualities, and practices of authors and perusers change† (Rounsaville 70) in light of the fact that the â€Å"social and expository conditions are continually being replicated and transformed† as essayists and perusers act inside them (Bawarshi 9). In whole, composing changes since setting change. Consequently, composing is aâ social activity characterized and molded by the social conditions that control creation and understanding. Socially shared philosophies bring forth printed shows, which are â€Å"agreements among scholars and perusers about how to develop and decipher texts† (Rounsaville 69). Kinds partner journalists and perusers by proposing literary shows. Since these shows are shared understandings among scholars and perusers, they empower essayists to develop writing in a way that coordinates readers’ translation so the content passes on its planned message. In this way, effective correspondence results when journalists follow content shows when imagining and perusers utilize these equivalent shows when perusing. Taking everything into account, classification is comprised by social conditions in which authors and perusers act inside. Such situational reliance of composing is reflected in progress of the three creators referenced previously. Amy Devitt’s content underscores the significance of understanding kind through its expository reason rather than through its structure. She contradicts the utilization of composing models, contending that in spite of the fact that learning formal highlights is a simpler methodology, yet the comprehension of how class really works is increasingly functional when scholars experience new circumstances in explicit controls. Essentially, Bawarshi relates content and setting by characterizing composing as a social activity. He uncovers that creations consistently leave from going before creations, henceforth featuring the significance of applying recently settled structures to answer situational requests. In conclusion, Fish’s section underlines the need of reacting to a group of people. All things considered, composing is a type of correspondence that includes the essayist as well as the peruser, in this way authors ought to consistently know about how their perusers may decipher their innovation. In entirety, the principle remove point from these authors’ works is that powerful compositions are those that reverberation situational conditions. Works Cited Bawarshi. Anis. Type and the Invention of the Writer: Reconsidering the Place of Invention in Composition. Logan, Utah: Utah State University Press, 2004. Devitt, Amy â€Å"A Proposal for Teaching Genre Awareness and Antecedent Genres. † Writing Genres. Carbondale: Southern Illinoise University Press, 2004. Ede, Lisa. â€Å"Writing for Rhetorical Situations†. Rounsaville, Angela, et al. , eds, Situated Inquiry. Boston: Bedford/St. Martin’s, 2008. Fish, Stanley E. â€Å"How to Recognize a Poem When You See One†. Rounsaville, Angela, et al. , eds, Situated Inquiry. Boston: Bedford/St. Martin’s, 2008.

Composing the Executive-Level Résumé

Composing the Executive-Level Résumé In the ever-competitive career world, the executive level career field is a whole nother ballgame when it comes to applying for and landing jobs in the over $100K realm. With the big bucks and greater responsibility of such positions comes the necessity for a bigger and better presentation when applying for such jobs. In short, the executive-level résumé is not the same animal as the plain, concise document that lower totem pole positions might present.Breaking the cardinal ruleFirst off, the executive-level résumé is not limited to one page. While most all résumés in the less than executive realm rarely need to be more than a single page (unless youve got 20 years of work experience to present), the executive-level résumé gives weighty details for potential employers to peruse. Additionally, a few meaningful sections are added for the executives résumé that arent on other run-of-the-mill résumés.Summary statementThe summary statement is often wrongly used by résumé wri ters, stating some generic job desire one has, replete with career field buzz words to fill it out. However, the executive-level résumé should be a succinct sales pitch in a sentence, letting potential employers know just who they are looking at. Essentially, if someone asked the executive to explain their career life and highlights in a short, descriptive paragraph, the summary is it.Core competenciesThis bulleted list of five to ten strong, relevant skills is a snapshot of your full professional experience. In essence, you want to brag about your most impressive abilities here, not simple tasks like administrative duties or general skills, like prospecting for customers. You want meaty, detailed descriptions of important job functions that show the employer you know your industry inside and out.Highlight those accomplishments!Naturally, everyone should be listing professional experience on their résumé. Whats vital to the executive-level résumé, however, is not just the what , where and when, but the accomplishments that you achieved while there. Executives need to boast, boast, boast their greatest accomplishments in the professional experience section, making sure to include important statistics like sales numbers and quotas reached and exceeded, awards gotten, promotions given (and how quickly), etc. Its a dog eat dog world, so employers are typically looking for the best of the best for their exec positionsâ€"you must show them that thats you.The rest of the documentOf course, Education and Organizations and Honors are certainly still meaningful categories to include on your executive-level résumé, or any résumé, for that matter. Whats key, again, is pointing out any extra, outstanding things about that education. Were you on honor roll or Deans List? Did you receive any specific awards or get accepted into elite programs while in college?Military experience and fraternal organizations are equally as important when it comes to the Organizations and Honors details. Many a bond has been struck by an interviewer when they learn the potential new exec they are questioning is also an ex-Army man or Freemason. Dont miss the chance to point out such associationsâ€"they can give you that extra edge.Cover your basesFinally, always package your executive résumé with a strong, positive cover letter highlighting your most impressive abilities and accomplishments. That letter should be a tightly written, one-page document that truly sells you as the best choice for the job. And finally, dont get discouraged when you dont land a job in the first few weeks, or even months, of your search. The executive-level job field is highly competitive and specialized, but with a strong résumé and perseverance, youre bound to land that next top-notch position in time!

Human Nature Is Good Or Bad - 1484 Words

Jesus Robledo Prof. Hudley English 121-001 April 17 2016 Human Nature Human Nature, human nature to me is how a person gives their life meaning by applying different believes to it, and then continue living their life based on them. No human is perfect nor good or bad. Throughout the history of humanity, our way of thinking, and believes have evolved in some way. Human nature took its turns when everyone started creating new beliefs back then. An example of different ideas being created or asked about was the way life was created. In order for humanity to maintain themselves motivated, and have a meaning to life they must have beliefs. This can all be done subconsciously. Humans show multiple ways of having believes. Some people believe in science and that’s how it reflects on their human nature. Others believe in Religion and that’s what is reflected on their side of human nature. Overall, human nature involves thinking, feeling, and committing actions. What kind of animal is the human? The undeniable answer is a savvy, garrulous, upright gorilla with a propensity for material belonging. Yet, shouldn t something be said about the more inconspicuous idea of human instinct? That is more questionable. Some deny it exists, liking to trust that we can be anything we need to be. They can t be correct. Despite the fact that we show loads of individual and social varieties, people are creatures, and like all creatures we have mannerisms,Show MoreRelatedHuman Nature Is Good Or Bad?909 Words   |  4 PagesHuman nature is referred to distinguishing characteristics; including ways of thinking, feeling, and behaving. Which humans tend to have naturally. As human beings we are taught moralities at a young age. We are taught whether an action is good or bad. So as humans, are we inherently good or bad? If we are taught what to be. Not only we are taught, but we are shaped by the world around us. 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Literature-based discovery of diabetes Free Essays

string(140) " in the form of HGNC \[HUGO \(Human Genome Organization\) Gene Nomenclature Committee\] genes, were confirmed by manual review of the text\." Reactive oxygen species (ROS) are known mediators of cellular damage in multiple diseases including diabetic complications. Despite its importance, no comprehensive database is currently available for the genes associated with ROS. Methods We present ROS- and diabetes-related targets (genes/proteins) collected from the biomedical literature through a text mining technology. We will write a custom essay sample on Literature-based discovery of diabetes or any similar topic only for you Order Now A web-based literature mining tool, SciMiner, was applied to 54 biomedical papers indexed with diabetes and ROS by PubMed to identify relevant targets. Over-represented targets in the ROS-diabetes literature were obtained through comparisons against randomly selected literature. The expression levels of nine genes, selected from the top ranked ROS-diabetes set, were measured in the dorsal root ganglia (DRG) of diabetic and non-diabetic DBA/2J mice in order to evaluate the biological relevance of literature- derived targets in the pathogenesis of diabetic neuropathy. Results SciMiner identified 1,026 ROS- and diabetes-related targets from the 54 biomedical papers (http://Jdrf. eurology. med. umich. edu/ROSDiabetes/ webcite). Fifty-three targets were significantly over-represented in the ROS-diabetes literature ompared to randomly selected literature. These over-represented targets included well-known members of the oxidative stress response including catalase, the NADPH oxidase family, and the superoxide dismutase family of proteins. Eight of the nine selected genes exhibited significant differential expression between diabetic and n on-diabetic mice. For six genes, the direction of expression change in diabetes paralleled enhanced oxidative stress in the DRG. Conclusions Literature mining compiled ROS-diabetes related targets from the biomedical literature and led us to evaluate the biological relevance of selected targets in the athogenesis of diabetic neuropathy. Diabetes is a metabolic disease in which the body does not produce or properly respond to insulin, a hormone required to convert carbohydrates into energy for daily life. According to the American Diabetes Association, 23. million children and adults, approximately 7. 8% of the population in the United States, have diabetes [1]. The cost of diabetes in 2007 was estimated to be $174 billion [1]. The micro- and macro-vascular complications of diabetes are the most common causes of renal tailure, blindness and amputations leading to significant morta y, morbidity poor quality of life; however, incomplete understanding of the causes of diabetic complications hinders the de velopment of mechanism-based therapies. In vivo and in vitro experiments implicate a number of enzymatic and non-enzymatic metabolic pathways in the initiation and progression of diabetic complications [2] including: (1) increased polyol pathway activity leading to sorbitol and fructose accumulation, NAD(P)-redox imbalances and changes in signal transduction; (2) non- enzymatic glycation of proteins yielding â€Å"advanced glycation end-products† (AGES); (3) ctivation of protein kinase C (PKC), initiating a cascade of intracellular stress responses; and (4) increased hexosamine pathway flux [2,3]. Only recently has a link among these pathways been established that provides a unified mechanism of tissue damage. Each of these pathways directly and indirectly leads to overproduction of reactive oxygen species (ROS) [23]. ROS are highly reactive ions or small molecules including oxygen ions, free radicals and peroxides, formed as natural byproducts of cellular energy metabolism. ROS are implicated in multiple cellular pathways such as mitogen-activated protein kinase MAPK) signaling, c-Jun amino-terminal kinase ONK), cell proliferation and apoptosis [4-6]. Due to the highly reactive properties of ROS, excessive ROS may cause significant damage to proteins, DNA, RNA and lipids. All cells express enzymes capable of neutralizing ROS. In addition to the maintenance of antioxidant systems such as glutathione and thioredoxins, primary sensory neurons express two main detoxifying enzymes: superoxide dismutase (SOD) [7] and catalase [8]. SOD converts superoxide (02-) to H202, which is reduced to H20 by glutathione and catalase [8]. SODI is the main form of SOD in the cytoplasm; SOD2 is located within the itochondria. In neurons, SODI activity represents approximately 90% of total SOD activity and SOD2 approximately 10% [9]. Under diabetic conditions, this protective mechanism is overwhelmed due to the substantial increase in ROS, leading to cellular damage and dysfunction [10]. The idea that increased ROS and oxidative stress contribute to the pathogenesis of diabetic complications has led scientists to investigate different oxidative stress pathways [7,11]. Inhibition of ROS or maintenance of euglycemia restores metabolic and vascular imbalances and blocks both the initiation and progression of omplications [1 2,13]. Despite the significant implications and extensive research into the role of ROS in diabetes, no comprehensive database regarding ROS-related genes or proteins is currently available. In the present study, a comprehensive list of ROS- and diabetes-related targets (genes/proteins) was compiled from the biomedical literature through text mining technology. SciMiner, a web-based literature mining tool [14], was used to retrieve and process documents and identify targets from the text. SciMiner provides a convenient web-based platform for target-identification within the biomedical iterature, similar to other tools including EBIMed [1 5], ALI BABA [16], and Polysearch [1 7]; however, SciMiner is unique in that it searches tull text documents, suppo free-text PubMed query style, and allows the comparison of target lists from multiple queries. The ROS-diabetes targets collected by SciMiner were further tested against randomly selected non-ROS-diabetes literature to identify targets that are significantly over- represented in the ROS-diabetes literature. Functional enrichment analyses were performed on these targets to identify significantly over-represented biological unctions in terms of Gene Ontology (GO) terms and pathways. In order to confirm the biological relevance of the over-represented ROS-diabetes targets, the gene expression levels of nine selected targets were measured in dorsal root ganglia (DRG) from mice with and without diabetes. DRG contain primary sensory neurons that relay information from the periphery to the central nervous system (CNS) Unlike the CNS, DRG are not protected by a blood-nerve barrier, and are consequently vulnerable to metabolic and toxic injury [19]. We hypothesize that differential expression of identified targets in DRG would confirm heir involvement in the pathogenesis of diabetic neuropathy. Defining ROS-diabetes literature To retrieve the list of biomedical literature associated with ROS and diabetes, PubMed was queried using (â€Å"Reactive Oxygen Species†[MeSH] AND â€Å"Diabetes Mellitus†[MeSH]). This query yielded 54 articles as of April 27, 2009. SciMiner, a web-based literature mining tool [14], was used to retrieve and process the abstracts and available full text documents to identify targets (full text documents were available for approximately 40% of the 1 , 1 54 articles). SciMiner-identified targets, eported in the form of HGNC [HUGO (Human Genome Organization) Gene Nomenclature Committee] genes, were confirmed by manual review of the text. You read "Literature-based discovery of diabetes" in category "Papers" Comparison with human curated data (NCBI Gene2PubMed) The NCBI Gene database provides links between Gene and PubMed. The links are the result of (1) manual curation within the NCBI via literature analysis as part of generating a Gene record, (2) integration of information from other public databases, and (3) GeneRlF (Gene Reference Into Function) in which human experts provide a brief summary of gene functions and make the connections between citation PubMed) and Gene databases. For the 54 ROS-diabetes articles, gene-paper associations were retrieved from the NCBI Gene database. Non-human genes were mapped to homologous human genes through the NCBI HomoloGene database. The retrieved genes were compared against the SciMiner derived targets. Any genes missed by SciMiner were added to the ROS-diabetes target set. Protein-protein interactions among ROS-diabetes targets To indirectly examine the association of literature derived targets (by SciMiner and NCBI Gene2PubMed) with ROS and diabetes, protein-protein interactions (PPIs) mong the targets were surveyed This was based on an assumption that targets are more likely to have PPIs with each other if they are truly associated within the same biological functions/pathways. A PPI network of the ROS-diabetes targets was generated using the Michigan Molecular Interactions (MIMI, http://mimi. ncibi. org/ webcite) database [20] and compared against 100 PPI networks of randomly drawn sets (the same number of the ROS-diabetes target set) from HUGO. A standard Z-test and one sample T-test were used to calculate the statistical significance of the ROS- diabetes PPI network with respect to the random PPI networks. Functional enrichment analysis Literature derived ROS-diabetes targets (by SciMiner and NCBI Gene2PubMed) were subject to functional enrichment analyses to identify significantly over-represented biological functions in terms of Gene Ontology [21], pathways (Kyoto Encyclopedia of Genes and Genomes (KEGG, http://www. genome. ]p/kegg/ webcite) [22] and Reactome http://www. reactome. org/ webcite[23]). Fisher’s exact test [24] was used to calculate the statistical significance of these biological functions with BenJamini-Hochberg (BH) adjusted p-value ; 0. 5 [25] as the cut-off. Over-represented ROS-diabetes targets Defining background corpora To identify a subset of targets that are highly over-represented within the ROS- diabetes targets, the frequency of each target (defined as the number of documents in which the target was identified divided by the number of total documents in the query) was compared against the frequencies in randomly selected background corpora. Depending on how the background set is defined, over-represented targets may vary widely; therefore, to maintain the background corpora close to the ROS and diabetes context, documents were selected from the same Journal, volume, and issue f the 54 ROS-diabetes documents, but were NOT indexed with â€Å"Reactive Oxygen Species†[MeSH] nor â€Å"Diabetes Mellitus†[MeSH]. For example, one of the ROS-diabetes articles (PMID: 18227068), was published in the Journal of Biological Chemistry, Volume 283, Issue 16. This issue contained 85 papers, 78 of which were not indexed with either â€Å"Reactive Oxygen Species†[MeSH] or â€Å"Diabetes Mellitus†[MeSH] indexed. One of these 78 papers was randomly selected as a background document. Three sets of 54 documents were selected using this approach and processed using SciMiner. Identified targets were confirmed by manual review for accuracy. Identifying significantly over-represented targets ROS-diabetes targets were tested for over-representation against targets identified from the three background sets. Fisher’s exact test was used to determine if the frequency of each target in the ROS-diabetes target set was significantly different from that of the background sets. Any targets with a BH adjusted p-value 0. 5 in at least two of the three comparisons were deemed to be an over-represented ROS- diabetes target. Functional enrichment analyses were performed on these over- represented ROS-diabetes targets as described above. Selecting targets tor real-time R A subset of targets were selected for RT-PCR from the top 10 over-represented ROS- diabetes targets excluding insulin and NADPH oxidase 5 (NOX5), which does not have a mouse ortholog. Nitric oxide synthase 1 (NOSI), the main generator of nitric oxide, ranked at the 1 5th position and was additionally selected for inclusion in the test set. Differential gene expression by real-time RT-PCR Mice DBA/2J mice were purchased from the Jackson Laboratory (Bar Harbor, ME). Mice were housed in a pathogen-free environment and cared for following the University of Michigan Committee on the Care and Use of Animals guidelines. Mice were fed AIN76A chow (Research Diets, New Brunswick, NJ). Male mice were used for this study. Induction of diabetes Two treatment groups were defined: control (n = 4) and diabetic (n = 4). Diabetes was induced at 13 weeks of age by low-dose streptozotocin (STZ) injections, 50 mg/kg/day for five consecutive days. All diabetic mice received LinBit sustained release insulin implants (LinShin, Toronto, Canada) at 8 weeks post-STZ treatment. Insulin implants were replaced every 4 weeks, at 12 and 16 weeks post-STZ treatment. At 20 weeks post-STZ treatment, mice were euthanized by sodium pentobarbital overdose and DRG were harvested as previously described [26]. Real-time RT-PCR The gene expression of the selected nine literature-derived ROS-diabetes targets in DRG was measured using real-time RT-PCR in duplicate. The amount of mRNA isolated from each DRG was normalized to an endogenous reference [Tbp: TATA box binding protein; A cycle threshold (CT)]. Identification of ROS-diabetes targets A total of 1,021 unique targets were identified by SciMiner from the 1,154 ROS- diabetes papers defined by the query of (â€Å"Reactive Oxygen Species†[MeSH] AND â€Å"Diabetes Mellitus†[MeSH]) and confirmed by manual review. Table 1 contains the op 10 most frequently mentioned targets in the ROS-diabetes papers. Insulin was the most frequently mentioned target, followed by superoxide dismutase 1 and catalase. Table 1 . Top 10 most frequent ROS-diabetes targets The NCBI Gene2PubMed database, containing expert-curated associations between the NCBI Gene and PubMed databases, revealed 90 unique genes associated with the 54 ROS-diabetes papers (Additional File 1). SciMiner identified 85 out of these 90 targets, indicating a 94% recall rate. Five targets missed by SciMiner were added to the initial ROS-diabetes target set to result in 1,026 unique targets (Additional File 2). Additional tile 1. The list ot 90 genes trom the NCBI Gene2PubMed database tor the ROS-Diabetes literature (1 , 1 54 papers). Format: XLS Size: 35KB Download file This file can be viewed with: Microsoft Excel Vieweropen Data Additional file 2. The list of 1,026 ROS-Diabetes targets. Format: XLS Size: 229KB Download file This file can be viewed with: Microsoft Excel Vieweropen Data PPI network of the ROS-diabetes targets The PPI network among the ROS-diabetes targets was evaluated using MIMI interaction data. This was based on the assumption that targets commonly related to certain topic are more likely to have frequent interactions with each other. One hundred PPI networks were generated for comparison using the same number of genes (1,026) randomly selected from the complete HUGO gene set (25,254). The PPI network of the ROS-diabetes targets was significantly different from the randomly generated networks indicating their strong association with the topic â€Å"ROS and Diabetes†. Table 2 demonstrates that the mean number of targets with any PPI interaction in the randomly generated target sets was 528. 9 (approximately 52% of 1,026 targets), while the number of targets with any PPI interaction in the ROS- iabetes target was 983 (96%). The number of targets interacting with each other was also significantly different between the random networks (mean = 155. 4) and the ROS-diabetes network (mean = 879). Figure 1 illustrates the distributions of these measurements from the 100 random networks with the ROS-diabetes set depicted as a red vertical line. It is obvious that the PPI network of the ROS-diabetes targets is significantly different from the random networks. Table 2. Summary of 100 randomly generated PPI networks thumbnailFigure 1 . Histograms of randomly generated PPI networks. The histograms llustrate the distributions of 100 randomly generated networks, while the red line indicates the ROS-diabetes targets. The network of the ROS-diabetes targets is significantly different from the 100 randomly generated networks, indicating the overlap of ROS-diabetes targets with respect to the topic â€Å"Reactive Oxygen Species and Diabetes†. Functional enrichment analyses of the ROS-diabetes targets Functional enrichment analyses of the 1,026 ROS-diabetes targets were performed to identify over-represented biological functions of the ROS-diabetes targets. After BenJamini-Hochberg correction, a total of 189 molecular functions, 450 biological rocesses, 73 cellular components and 341 pathways were significantly enriched in the ROS-diabetes targets when compared against all the HUGO genes (see Additional Files 3, 4, 5 and 6 for the full lists). Table 3 lists the top 3 most over-represented GO terms and pathways ranked by p-values of Fisher’s exact test: e. g. , apoptosis, oxidoreductase activity and insulin signaling pathway. Additional file 3. The enriched Molecular Functions Gene Ontology Terms in the 1,026 ROS-Diabetes targets. Format: XLS Size: 91 KB Download file This file can be viewed with: Microsoft Excel Vieweropen Data Additional file 4. The nriched Biological Processes Gene Ontology Terms in the 1,026 ROS-Diabetes targets. Format: XLS Size: 95KB Download file This tile can be viewed wit Microsott Excel Vieweropen Data Additional tile enriched Cellular Components Gene Ontology Terms in the 1,026 ROS-Diabetes targets. Format: XLS Size: 61 KB Download file This file can be viewed with: Microsoft Excel Vieweropen Data Additional file 6. The enriched pathways in the 1,026 ROS-Diabetes targets. Format: XLS Size: 104KB Download file This file can be viewed with: Microsoft Excel Vieweropen Data Table 3. Enriched functions of 1,026 ROS-diabetes targets Identification of over-represented ROS-diabetes targets To identify the ROS-diabetes targets highly over-represented in ROS-diabetes literature, three sets of background corpora of the same size (n = 1 , 1 54 documents) were generated using the same Journal, volume and issue approach. The overlap among the three background sets in terms of documents and identified targets are illustrated in Figure 2. Approximately 90% of the selected background documents were unique to the individual set, while 50% of the identified targets were identified in at least one of the three background document sets. The frequencies of the identified targets were compared among the background sets for significant differences. None of the targets had a BH adjusted p-value ; 0. 05, indicating no significant difference among the targets from the three different background sets (See Additional File 7). thumbnailFigure 2. Venn diagrams of document compositions and identified targets of the randomly generated background sets. Approximately 90% of the selected background documents were unique to individual set (A), while 50% of the identified targets were identified in at least one of the three background document sets (B). Additional file 7. Comparisons of target frequencies among three background sets. Format: XLS Size: 22KB Download file This file can be viewed with: Microsoft Excel Vieweropen Data Comparisons of the ROS-diabetes targets against these background sets revealed 53 highly over- represented ROS-diabetes targets as listed in Table 4. These 53 targets were significant (p-value ; 0. 05) against all three background sets and significant following BenJamini-Hochberg multiple testing correction (BH adjusted p-value ; 0. 05) against at least two of the three background sets. SODI was the most over-represented in he ROS-diabetes targets. Table 4. 53 targets over-represented in ROS-diabetes literature Functional enrichment analyses of the over-represented ROS-diabetes targets Functional enrichment analyses of the 53 ROS-diabetes targets were performed to identify over- represented biological functions. Following BenJamini-Hochberg correction, a total of 65 molecular functions, 209 biological processes, 26 cellular components and 108 pathways were significantly over-represented when compared against all the HUGO genes (see Additional Files 8, 9, 10 and 11 for the full lists). Table 5 shows the top 3 ost significantly over-represented GO terms and pathways ranked by p-values of Fisher’s exact test. GO terms related to oxidative stress such as â€Å"superoxide metabolic process†, â€Å"superoxide release†, â€Å"electron carrier activity† and â€Å"mitochondrion† were highly over-represented 53 ROS-diabetes targets Additional file 8. The enriched Molecular Functions Gene Ontology Terms in the Over- represented 53 ROS-Diabetes targets. Format: XLS Size: 46KB Download file This file can be viewed with: Microsoft Excel Vieweropen Data Additional file 9. The enriched Biological Processes Gene Ontology Terms in the Over-represented 53 ROS- Diabetes targets. Format: XLS Size: 95KB Download file This file can be viewed with: Microsoft Excel Vieweropen Data Additional file 10. The enriched Cellular Components Gene Ontology Terms in the Over-represented 53 ROS-Diabetes targets. Format: XLS Size: 66KB Download file This file can be viewed with: Microsoft Excel Vieweropen Data Additional file 1 1 . The enriched pathways in the Over-represented 53 ROS-Diabetes targets. Format: XLS Size: 75KB Download file This file can be viewed with: Microsoft Excel Vieweropen Data Table 5. Enriched functions of the 53 over-represented targets in diabetes Gene expression change in iabetes Two groups of DBA/2J mice exhibited significantly different levels of glycosylated hemoglobin (%GHb). The mean ? ± SEM were 6. 2 ? ± 0. for the non-diabetic control group and for 14. 0 ? ± 0. 8 for the diabetic group (p-value 0. 001), indicative of prolonged hyperglycemia in the diabetic group [26]. DRG were harvested from these animals for gene expression assays. Nine genes were selected from the top ranked ROS-diabetes targets: superoxide dismutase 1 (Sodl), catalase (Cat), xanthine dehydrogenase (Xdh), protein kinase C alpha (Prkca), neutrophil cytosolic factor 1 Ncfl), nitric oxid e synthase 3 (Nos3), superoxide dismutase 2 (Sod2), cytochrome b-245 alpha (Cyba), and nitric oxide synthase 1 (Nosl). Eight genes exhibited differential expression between diabetic and non-diabetic mice (p-value 0. 05) as shown in Figure 3. Cat, Sodl, Sod2, Prkca, and NOSI expression levels were decreased, while Ncfl , Xdh, and Cyba expression levels were increased in diabetes. thumbnailFigure 3. Gene expression levels of selected ROS-diabetes targets in DRG examined by real-time RT-PCR. Expression levels are relative to Tbp, an internal control (error bar = SEM) (*, p 0. 05; **, p 0. 01; ***, p 0. 01). Eight (Cat, Sodl, Ncfl , Xdh, Sod2, Cyba, Prkca, and Nosl) out of the nine selected ROS-diabetes genes were significantly regulated by diabetes. Discussion Reactive oxygen species (ROS) are products of normal energy metabolism and play important roles in many other biological processes such as the immune response and signaling cascades [4-6]. As mediators of cellular damage, ROS are implicated in pathogenesis of multiple diseases including diabetic complications [27-30]. With the aid of literature mining technology, we collected 1 ,026 possible ROS-related targets from a set of biomedical literature indexed with both ROS and diabetes. Fifty-three targets were significantly over-represented in the ROS-diabetes papers when compared against three background sets. Depending on how the background set is defined, the over-represented targets may vary widely. An ideal background set would be the entire PubMed set; however, this is not possible due to limited access to tull texts and intense data processing. An alternative method wou d be to use only abstracts in PubMed, but this may not fully represent the literature. Using only the abstracts, our target identification method resulted in 21 (39%) of the 53 key ROS- iabetes targets (Additional File 12), suggesting the benefit of rich information in full text documents. In the present study, background documents were randomly selected from the same Journal, volume, and issue of the 54 ROS-diabetes documents, which were not indexed with â€Å"Reactive Oxygen Species†[MeSH] nor â€Å"Diabetes Mellitus†[MeSH]. This approach maintained the background corpora not far from the ROS and diabetes context. Additional file 12. The Key 53 ROS-Diabetes Targets Identifiable Using Only the Abstracts. Format: XLS Size: 23KB Download file This file can be viewed with: Microsoft Excel Vieweropen Data The gene expression evels of nine targets selected from the 53 over-represented ROS-diabetes targets were measured in diabetic and non-diabetic DRG. Our laboratory is particularly interested in deciphering the underlying mechanisms of diabetic neuropathy, a major complication of diabetes. Data published by our laboratory both in vitro and in vivo confirm the negative impact of oxidative stress in complication-prone neuron tissues like DRG In an effort to obtain diabetic neuropathy specific targets, SciMiner was employed to further analyze a subset of the ROS-diabetes papers (data not shown). Nerve growth factor (NGF) was identified as the most over- epresented target in this subset when compared to the full ROS-diabetes set; however, NGF did not have statistical significance (BH adjusted p-value = 0. 06). The relatively small numbers of papers and associated targets may have contributed to this non-significance. Therefore, the candidate targets for gene expression validation were selected from among the 53 over-represented ROS-diabetes targets derived from the full ROS-diabetes corpus. Among the tested genes, the expression levels of Cat, Sodl , Sod2, Prkca, and NOSI were decreased, while the expression levels of Ncfl , Xdh, and Cyba were increased nder diabetic conditions. Cat, Sodl , and Sod2 are responsible for protecting cells from oxidative stress by destroying superoxides and hydrogen peroxides [8-11]. Decreased expression of these genes may result in oxidative stress [32]. Increased expression of Cyba and Ncfl , subunits of superoxide-generating nicotinamide adenine dinucleotide phosphate (NADPH) oxidase complex [30], also supports enhanced oxidative stress. Xdh and its inter-convertible form, Xanthine oxidase (Xod), showed increased activity in various rat tissues under oxidative stress conditions ith diabetes [33], and also showed increased expression in diabetic DRG in the current study. Unlike the above concordant genes, protein kinase C and nitric oxide synthases did not exhibit predicted expression changes in diabetes. Protein kinase C activates NADPH oxidase, further promoting oxidative stress in the cell [34,35]. Decreased expression of Prkca in our diabetic DRG is not parallel with expression levels of other enzymes expected to increase oxidative stress. Between the two nitric oxide synthases tested in the present study, NOSI (neuronal) expression was significantly decreased (p-value 0. 01) in diabetes, while Nos3 (endothelial) expression was not significant (p-value = 0. 06). The neuronal NOSI is expected to play a major role in producing nitric oxide, another type of highly reactive free radical. Thus, with some exceptions, the majority of the differentially expressed genes in DRG show parallel results to the known activities of these targets in diabetes, suggesting enhanced oxidative stress in the diabetic DRG. Assessment of antioxidant enzyme expression in diabetes has yielded a variety of results [36-40] depending upon the duration of diabetes, the tissue studied and other factors. In diabetic mice and rats, it is commonly reported that superoxide dismutases are down-regulated [37-40], where data regarding catalase are variable [36,40]. PKC is activated in diabetes, but most papers that examined mRNA demonstrated that its expression is largely unchanged [41]. Among the 53 over-represented ROS-diabetes targets, SODI was the most over- represented and was differentially expressed under diabetic and non-diabetic conditions. To the best of our knowledge, no published study has investigated the role of SODI in the onset and/or progression of diabetic neuropathy. Mutations of SODI have long been associated with the inherited form of amyotrophic lateral sclerosis (ALS) [42] and the theory of oxidative stress-based aging [43]. Early reports indicate that knockout of the SODI gene does not affect nervous system development [44], although recovery following injury is slow and incomplete [45,46]. With respect to diabetes, SODI KO accelerates the development of diabetic nephropathy [47] and cataract formation [48]. Thus, examining the SODI KO mouse as a model of diabetic neuropathy would be a reasonable follow-up study. One limitation of the current approach using literature mining technology is incorrect r missed identification of the mentioned targets within the literature. Based on a performance evaluation using a standard text set BioCreAtlvE (Critical Assessment of Information Extraction systems in Biology) version 2 [49], SciMiner achieved 87. 1% recall (percentage identification of targets in the given text), 71. 3% precision (percentage accuracy of identified target) and 75. 8% F-measure (harmonious average of recall and precision = (2 x recall x precision)/(recall + precision)) before manual revision [14]. In order to improve the accuracy of SciMiner’s results, each target was anually reviewed and corrected by checking the sentences in which each target was identified. Approximately, 120 targets (†10% of the initially identified targets from the ROS-diabetes papers) were removed during the manual review process. The overall accuracy is expected to improve through the review process; however, the review process did not address targets missed by SciMiner, since we did not thoroughly review individual papers. Instead, 5 missed targets, whose associations with ROS-diabetes literature were available in the NCBI Gene2PubMed database, were added to the final ROS-diabetes target list (Additional File 2). How to cite Literature-based discovery of diabetes, Papers

Spain All In Spanish Essay Research Paper free essay sample

Spain ( All In Spanish ) Essay, Research Paper Espa? a se localiza el este de Portugal y el oeste del Sur de la Francia. Es el oeste del Mar Y EL Sur Mediterr? neos de la Bah? a de Biscat. Es el este del Oc? Fatah Revolutionary Council Atl? ntico Y el oeste de las Islas de Balearic. Espa? a es separada de la Francia por La monta? as de Pyrenees. M? s que La mitad del dad? s se compone de monta? as. All? desiertos de seres y wetlands en Espa? a. We will write a custom essay sample on Spain All In Spanish Essay Research Paper or any similar topic specifically for you Do Not WasteYour Time HIRE WRITER Only 13.90 / page Es generalmente un clima caliente aunque las monta? as puedan obtener La nieve. Espa? a tiene una monarqu? a constitucional. El Rey sirve como jefe del Estado. El no tiene un papel directo en las operaciones del gobierno pero? fifty tiene un papel en normas de gobierno. El primer ministro Es llamado Al presidente del gobierno en Espa? a. El parlamento de marcas de Espa? a las leyes de pa? Ses y la legislatura tienen m? s de 500 miembros. Espa? a tiene tambi? n Department of State sistemas del tribunal, civil Y militar, los Jueces deciden todos casos. Juan Carlos lleg? a ser Rey de Espa? a nut 1975 Y? cubic decimeter jugaron un papel magn? fico Al cambio Espa? a de una dictadura a una democracia Durante los vitamin D? as tempranos de Espa? a Liberians ocup? mucho del dad? s. Ellos cultivaron Y construyeron Las aldeas y los Pueblo. Algunos de estos pueblos desarrollados en las primeras ciudades en Espa? a aprecian Cartagena. Phoencians comenz? a establece La colonias Y llev? un comercio que prosper? . Celtic? s Y los romanos vinieron tambi? n a Espa? a. La conquista romana de Espa? a comenz? durante las guerras de Punic Y les tom? 200 a? os a conquista Espa? a. Roma conquist? tambi? n Portugal. Los alemanes invadieron tambi? n Espa? a as? como tambi? n Muslims. La invasi? n comenz? en 711. Muchas gente espa? ola lleg? a ser Muslim como resultado de la orden de Moorish. El Muslims influy? en Espa? a magn? ficamente Y Se puede ver en el trabajo de la arquitectura y la arte de Espa? a. Ellos construyeron muchos palacios del anuncio de mezquitas llamaron alocazars. En 1978 Espa? a aprob? una constituci? n nueva basada en principios democr? ticos. . La poblaci? n de Espa? a Es 39.2 millones. Se compone de gente espa? ola, y ellos hablan Castilian EL espa? ol. La religi? n primaria de Espa? a Si Cat? lico de romano. La gente hour angle vivido en Espa? a parity m? s de 100,000 a? os. Muchos grupos vinieron a Espa? a inclusive Celts, los griegos, LOS romanos, y los alemanes. Acerca de 90 % de la poblaci? n vive nut La ciudades. Estas ciudades boy Madrid Y Barcelona. La Capital de Espa? a Es Madrid y la poblaci? n hay 2,984,576 character. En La degree Fahrenheit? bricas de la ciudad, las tiendas, y Las oficinas cierran parity una tres interrupci? n del almuerzo de hora y permanecen abre hasta acerca de siete. Esto es una costumbre espa? ola vieja que tranquilo contin? a a? n en las ciudades modernas. La moneda de Espa? a Es La Peseta. El cambio Es un vitamin D? lar americano parity 144 pesetas. Espa? a es uno de Europa? s m? s dad? ses mom barato. Una character famosa de Espa? a Es EL escritor de Don Quixote de la Mancha, que fue escrito por Miguel de Cervantes. Don Quixote es el cuento de un guy viejo exc? ntrico que vive nut un castillo en Barcelona. El hour angle estado leyendo los cuentos de caballeros Y maidens y ha llegado a ser so? Ar de delusional de uno de las hero? nas de cuentos, Dulcinea. El embarcar a salva Dulcinea, su inaugural imaginario en la pena. El rhenium? ne a una chica joven Kitri que? cubic decimeter piensa Es Dulcinea. El cuento Eastern Time? acerca de c? mo cazas de Don despu? s que Kitri y eventualmente Don los sale Al hallazgo su Dulcinea una vez m? s. Esto vitamin E s uno de los pedazos m? s grande de la literatura espa? ola y se sabe mundo lejos tambi? n. EL Paintor m? s famouso espa? ol Es Pablo Picasso. El es considerado Al artista m? s grande del siglo 20th. El tuvo un estilo extraordinario que cambi? como? cubic decimeter obtuvo m? s viejo. El nac? a nut Malaga en el octubre 25th 1881 EL hijo de Jose Ruiz Blasco, que epoch un master de la arte, y Maria Picasso. En la edad de diez? cubic decimeter hizo su primera pintura Y por EL tiempo que? cubic decimeter 10? a Cydonia oblonga a? os de edad? cubic decimeter entr? en Barcelona Escuela de bellas artes. El se asent? en Par? s en 1904. El tuvo muchos estilos diferentes durante su vida Y sculpting explorado Y conditioned emotional response? mico as? como tambi? n pintar. El us? el cubismo en muchas de sus pinturas. Este pintar Se llama? mujer camisa Contra? y es uno de su paitings muy conocido. Un Otro artista espa? ol muy conocido Es Juan Grist. El epoch tambi? n un amigo Y vecino a Pablo Picasso. El aprendi? el cubismo de Picasso y epoch United Nations artista joven muy talentoso. El dise? ? tambi? n los disfraces para muchos concert dance. Su trabajo art? stico contuvo muchos paisajes Y? fifty tiene unos pocos que pinta del cubismo de usar de payasos. El muri? temprano en la edad de thirtynine en 1927. Hay muchas cosas a hace en Espa? a, una fete popular Es La Tamborrada en San Sebastian. Esto est? en el febrero Y EL Pueblo entero arregla Y los partidos. El carnaval sucede a trav? s del Pa? s en EL febrero tarde Y Es tambi? n muy popular. Valencia tiene un five de semana el partido largo llam? Las Fallas y ellos tienen EL baile Toda noche, beber, los fuegos artificiales, Y procesiones coloradas. Semana Santa Es La semana que dirige hasta Domingo de Pascua y all? desfiles de seres de im? cistrons santas por las calles. Madrid tiene muchos museos Y los parques y los jardines hermosos. Uno de las galer? as m? s grande de arte en el mundo est? n en Espa? a, el del de Museo Prado. Goya A ; la arte # 8217 ; s est? all? as? como tambi? n pinturas por Diego Velazquez. Madrid tiene tambi? n los anillos m? s grandes de Toro, el Plaza de Toros Monumental de las Ventas El deporte m? s popular Es Espa? a Si EL degree Fahrenheit? tbol Y Se juega por Toda partes. Es muy popular en Espa? a que en los Estados Unidos. Otro popular Deportivo nut Espa? a incluye esquiar en la Sierra Nevada, y en La monta? as de Pyrenees. Cycling Es tambi? n una actividad popular. Hay La nataci? n tambi? n maravillosa en Espa? a nut La costa del Pais Vasco. Como en casi cada dad? s hay EL excursionismo magn? fico en las monta? as especialmente Durante los meses de verano. El alimento espa? ol tiene una reputaci? n Y tappa fant? stica Es una bebida popular. Hay muchos estofados anti-racketeering law, las sopas, los kidney beans, seafood, y las carne que se usan en la cocina del espa? ol. Los tiempo que espa? oles comen son diferente de los Estados Unidos, el almuerzo se come generalmente como La comida chief del vitamin D? a en acerca de dos o? clock. La comida nocturna es m? s ligera Y Es servido entre diez Y one time de noche. Yo pienso que Espa? a Es un dad? s muy interesante. La semana pasada yo fui a ve que Don Quixote realizaron por el Ballet de Boston, boy un cuento chistoso. Espa? a Es tambi? n un dad? s magn? fico, mi hermana epoch un estudiante del cambio all? por un a? o Y ella lo amaron aunque La cultura Es mucho diferente entonces en los Estados Unidos. Para una chicas de la cosa nunca paga por su fecha, que Es com? n en los Estados. Amo el baile del espa? ol tambi? n Y gozo el baile de Flamenco que vigila Y escuchar La m? sica espa? ola a lawsuit de su ritmo emocionante. 332

Internet Culture Essay Example

Internet Culture Essay Example Internet Culture Paper Internet Culture Paper BA Humanities Media and Society It is hard to understand the term culture. What is culture? Is it a way of life, is it a group of shared interests that brings a community of individuals together or is it a utopian dream, an invention created by the powers that be who govern society to help to collaborate interests in a structured easy to monitor way? Culture is defined in many different ways. It is said that cultures are maps of meaning through which the world is made intelligible1, but whatever the true meaning of the word Culture, Raymond Williams was right in suggesting that Culture is one of the most complicated words in the human language2: Culture is one of the two or three most complicated words in the English language. This is so partly because of its intricate historical development { } but mainly because it has now come to be used for important concepts in several distinct intellectual disciplines and in several distinct and incompatible systems of thought3. Culture has become the antithesis of modern times. Its meaning is so vast and indescribable that it would be very difficult to placate an entire essay on its meaning and come to any fore longed conclusion. Culture has a different meaning to different people and it is this paradigmatic complexity that allows the word to put fear into anyone attempting to analyse its essence. However, if you put a leading word, a word that defines disciplines within a specific culture, the term suddenly becomes identifiable. Oral Culture, Print Culture, Popular Culture and what we are attempting to understand within this research, Internet Culture begins to have a more clear and concise meaning. The very nature of the words associated and linked to the term culture allow for a more natural semblance of association. Once a word has been linked with the massive expanse of the term culture, the essence and meaning of a task such as describing what you understand by the term Internet Culture becomes significantly easier to digest and comprehend. Within the following research I will attempt to describe what I understand of the term Internet Culture and to address some of the key critical questions being asked about the movement towards the Internet Revolution4. For the basis of consistency, I will divide the text into what I feel are the key critical issues that are being questioned regarding Internet Culture, beginning with the definition that I believe personifies the term Internet Culture. As there are a phenomenal amount of issues that are being questioned I have chosen two key concepts that I feel are of importance regarding the construction and maintenance of a culture that is virtual in essence. The main critical issues that I will review are:   Can you have a virtual community?   How will Internet Culture affect the information Have and Have Nots? However, before we go any further it is imperative that we decipher what I believe and understand by the term Internet Culture. A contemporary hobby or obsession has been the compartmentalisation of eras in time and space or epochs that relate specifically to how society and the inhabitants of society communicate. Theorists have been able to highlight a number of shifts in the way a society communicates that has led to different aspects of cultural identity being adopted. It is safe to suggest that the fundamental link between varying societies and cultures are the way that they communicate and interact, as the understanding of a common language strengthens a community, just as a lack of understanding can also divide and ostracise. One of the first epochs to be defined was the Primary Oral Culture, a culture that communicated only by speech with no written text or literature present. Oral Culture was temporally biased5, it relied heavily on mythology and legend as well as ceremony and memorisation in order to transcend meaning and keep a sense of cultural identity alive6. It can be said that Oral Culture laid the foundations for the evolution of culture and society through differing communication media. The Primary Oral Culture led to Print Culture and then Visual Culture and to the epoch, which contemporary western societies are meant to inhabit, that of Internet Culture. Since Oral Culture all other cultures have included a fundamental aspect of the oral society7. We live in a predominantly word based environment, one of speech and hearing a world of sound8, however, the interactive medium that Internet Culture utilises is perhaps the only medium that converges all traditional modes of communication9. Internet Culture is the epoch that contemporary society has begun to inhabit, however, it can also be a fluid and complex medium that has many cultural meanings with little social understanding. Internet Culture cannot be as easily associated and linked to past specifications of culture that society has grown accustomed to. David Porter gives an interpretation of what Internet Culture is and the diverged sense of cultural significance that the Internet procures: If the Internet can be understood as the site of any culture at all, it is not, presumable, culture in the sense either of an elitist enclave or of a homogeneous social sphere. The culture that the Net embodies, rather, is a produce of the peculiar conditions of virtual acquaintance that prevail online, a collective adaptation of the high frequency of anonymous, experimental, and even fleeting encounters familiar to anyone who has ventured into a newsgroup debate. 10 It is therefore difficult to ascertain what Internet Culture is and it is equally difficult to give an explanation of a new medium with such a heavy cultural significance. The Internet is changing the way society communicates, but this is not a new or contemporary notion. Erla Zwingle establishes the movement of society and tradition when he affirms that Goods move, people move, ideas move and cultures change11. It is this that has the cultural significance in a continuously fluid environment like the Internet. However, to what extent the cultural significance has affected society and cultural infiltration is at this stage purely speculative with no foreseeable way of monitoring the effects that the Internet has. As we enter the 21st century electronic media have become an imperative aspect of western societies daily lives. We use computers because they are easy, they buy us time and they give us entertainment. Internet Culture is an extension of the visual image that saturates our everyday lives.