Preface to the special issue on harnessing personal tracking data for personalization and sense-making

Increasingly, people are making use of diverse digital services that create many types of personal data. The most recent addition to such services are self-tracking devices that are capable of creating very detailed personal activity records. The focus of this special issue is to explore how such activity records can be exploited to provide user-centric personalization services

Fyn Mediates Leptin Actions in the Thymus of Rodents

BACKGROUND:Several effects of leptin in the immune system rely on its capacity to modulate cytokine expression and apoptosis in the thymus. Surprisingly, some of these effects are dependent on signal transduction through the IRS1/PI3-kinase, but not on the activation of JAK2. Since all the well known effects of leptin in different cell types and tissues seem to be dependent on JAK2 activation, we hypothesized that, at least for the control of thymic function, another, unknown kinase could mediate the transduction of the leptin signal from the ObR towards the IRS1/PI3-kinase signaling cascade. METHODOLOGY/PRINCIPAL FINDINGS:Here, by employing immunoblot, real-time PCR and flow citometry we show that the tyrosine kinase, Fyn, is constitutively associated with the ObR in thymic cells. Following a leptin stimulus, Fyn undergoes an activating tyrosine phosphorylation and a transient association with IRS1. All these effects are independent of JAK2 activation and, upon Fyn inhibition, the signal transduction towards IRS1/PI3-kinase is abolished. In addition, the inhibition of Fyn significantly modifies the effects of leptin on thymic cytokine expression. CONCLUSION/SIGNIFICANCE:Therefore, in the thymus, Fyn acts as a tyrosine kinase that transduces the leptin signal independently of JAK2 activation, and mediates some of the immunomodulatory effects of leptin in this tissue

DAF-16 and Δ9 Desaturase Genes Promote Cold Tolerance in Long-Lived Caenorhabditis elegans age-1 Mutants

In Caenorhabditis elegans, mutants of the conserved insulin/IGF-1 signalling (IIS) pathway are long-lived and stress resistant due to the altered expression of DAF-16 target genes such as those involved in cellular defence and metabolism. The three Δ9 desaturase genes, fat-5, fat-6 and fat-7, are included amongst these DAF-16 targets, and it is well established that Δ9 desaturase enzymes play an important role in survival at low temperatures. However, no assessment of cold tolerance has previously been reported for IIS mutants. We demonstrate that long-lived age-1(hx546) mutants are remarkably resilient to low temperature stress relative to wild type worms, and that this is dependent upon daf-16. We also show that cold tolerance following direct transfer to low temperatures is increased in wild type worms during the facultative, daf-16 dependent, dauer stage. Although the cold tolerant phenotype of age-1(hx546) mutants is predominantly due to the Δ9 desaturase genes, additional transcriptional targets of DAF-16 are also involved. Surprisingly, survival of wild type adults following a rapid temperature decline is not dependent upon functional daf-16, and cellular distributions of a DAF-16::GFP fusion protein indicate that DAF-16 is not activated during low temperature stress. This suggests that cold-induced physiological defences are not specifically regulated by the IIS pathway and DAF-16, but expression of DAF-16 target genes in IIS mutants and dauers is sufficient to promote cross tolerance to low temperatures in addition to other forms of stress

Correlation of gene expression and protein production rate - a system wide study

<p>Abstract</p> <p>Background</p> <p>Growth rate is a major determinant of intracellular function. However its effects can only be properly dissected with technically demanding chemostat cultivations in which it can be controlled. Recent work on <it>Saccharomyces cerevisiae </it>chemostat cultivations provided the first analysis on genome wide effects of growth rate. In this work we study the filamentous fungus <it>Trichoderma reesei </it>(<it>Hypocrea jecorina</it>) that is an industrial protein production host known for its exceptional protein secretion capability. Interestingly, it exhibits a low growth rate protein production phenotype.</p> <p>Results</p> <p>We have used transcriptomics and proteomics to study the effect of growth rate and cell density on protein production in chemostat cultivations of <it>T. reesei</it>. Use of chemostat allowed control of growth rate and exact estimation of the extracellular specific protein production rate (SPPR). We find that major biosynthetic activities are all negatively correlated with SPPR. We also find that expression of many genes of secreted proteins and secondary metabolism, as well as various lineage specific, mostly unknown genes are positively correlated with SPPR. Finally, we enumerate possible regulators and regulatory mechanisms, arising from the data, for this response.</p> <p>Conclusions</p> <p>Based on these results it appears that in low growth rate protein production energy is very efficiently used primarly for protein production. Also, we propose that flux through early glycolysis or the TCA cycle is a more fundamental determining factor than growth rate for low growth rate protein production and we propose a novel eukaryotic response to this i.e. the lineage specific response (LSR).</p

Personalization in Virtual Enterprises

Each business company collects, produces and exploits for its activities and goals large amounts of infor-mation. Most of the times this knowledge makes the intellectual capital for creating value and innovation. Knowledge management (KM) systems aim at manipulating knowledge by storing and redistributing corporate information that are acquired from the organizations members. In this context, Virtual Enterprises (VE) plays a crucial role as not permanent alliances of enterprises joined together to share resources and skills in order to better respond to business opportunities. The representation and retrieval of distributed knowledge is an important feature that information systems must provide in order to obtain advantages from this kind of enterprises. PVE (Personalized Virtual Enterprise) is an ongoing research project for developing a system able to extract and let different business companies access to collective knowledge required to achieve particular shared goals. In this paper, we report the most important features of this system,especially in the context of distributed knowledge representation and retrieval

Intelligent Search on the Internet

The Web has grown from a simple hypertext system for research labs to an ubiquitous information system including virtually all human knowledge, e.g., movies, images, music, documents, etc. The traditional browsing activity seems to be often inadequate to locate information satisfying the user needs. Even search engines, based on the Information Retrieval approach, with their huge indexes show many drawbacks, which force users to sift through long lists of results or reformulate queries several times. Recently, an important research activity effort has been focusing on this vast amount of machine-accessible knowledge and on how it can be exploited in order to match the user needs. The personalization and adaptation of the human-computer interaction in information seeking by means of machine learning techniques and in AI-based representations of the information help users to address the overload problem. This chapter illustrates the most important approaches proposed to personalize the access to information, in terms of gathering resources related to given topics of interest and ranking them as a function of the current user needs and activities, as well as examples of prototypes and Web systems

Mining prerequisite relationships among learning objects

The process of carefully choosing and sequencing a set of Learning Objects (LOs) to build a course may reveal to be quite a challenging task. In this work we focus on an aspect of such challenge, related to the verification and respect of the relationships of pedagogical dependence that holds between two LOs added to a course (meaning that if a given LO has another one as “pre-requisite”, then any sequencing of the LOs in the course will need to have the latter LO taken by the learners before of the former). An innovative Machine learning-based approach for the identification of these kinds of relationships is proposed