Expression of the inducible NO synthase in human monocytic U937 cells allows high output nitric oxide production.

Nitric oxide (NO) produced by inducible NO synthase (iNOS, NOS-2) is an important component of the macrophage-mediated immune defense toward numerous pathogens. Murine macrophages produce NO after cytokine activation, whereas, under similar conditions, human macrophages produce low levels or no NO at all. Although human macrophages can express iNOS mRNA and protein on activation, whether they possess the complete machinery necessary for NO synthesis remains controversial. To define the conditions necessary for human monocytes/macrophages to synthesize NO when expressing a functional iNOS, the human monocytic U937 cell line was engineered to synthesize this enzyme, following infection with a retroviral expression vector containing human hepatic iNOS (DFGiNOS). Northern blot and Western blot analysis confirmed the expression of iNOS in transfected U937 cells both at the RNA and protein levels. NOS enzymatic activity was demonstrated in cell lysates by the conversion of L-[3H]arginine into L-[3H]citrulline and the production of NO by intact cells was measured by nitrite and nitrate accumulation in culture supernatants. When expressing functional iNOS, U937 cells were capable of releasing high levels of NO. NO production was strictly dependent on supplementation of the culture medium with tetrahydrobiopterin (BH4) and was not modified by stimulation of the cells with different cytokines. These observations suggest that (1) human monocytic U937 cells contain all the cofactors necessary for NO synthesis, except BH4 and (2) the failure to detect NO in cytokine-stimulated untransfected U937 cells is not due to the presence of a NO-scavenging molecule within these cells nor to the destabilization of iNOS protein. DFGiNOS U937 cells represent a valuable human model to study the role of NO in immunity toward tumors and pathogens.

Viihteen laatu nykytietokonepeleissä

Tässä pro gradu tutkielmassa tarkastellaan viihteen laadun tekijöitä nykyaikaisissa tietokonepeleissä ja niiden vaikutusta pelin viihdytysarvoon. Tutkielmassa on analysoitukeskeisiä pelialan artikkeleita, jotka käsittelevät pelaajien vaatimuksia hyvältä peliltä. Artikkeleita analysoimalla on löydetty 14 erilaista tietokonepelin viihdearvon osatekijää: osallistuminen, palaute, säännöt, pelaamaan oppiminen, mielekäs tekeminen, kilpailu, immersio, yhtenäinen ja ymmärrettävä pelimaailma, tarinan luominen, turvalliset kokemukset, sosiaalinen pääoma, ennakko-odotukset, tekniset vaatimukset ja markkinoiden odotukset. Löydettyjä viihteen laadun osatekijöitä etsitään pelityypin mukaan valittuista 12 nykypelistä, ja tulokset paljastavat, että tietyt tekijät ovat yhtenäisiä hyviksi koetuilla peleillä. Hyvät pelit näyttäisivät omaavan toimivat kontrollit, selkeät palautteet, tasapainoiset säännöt, mielenkiintoista tekemistä, palkintoja etenemisestä ja mahdollisuuksia vaikuttaa pelin tapahtumiin koko pelaamisen ajan. Hyväksi peliksi on määritelty peli, joka sai keskiarvokseen 90% tai enemmän peliarvosteluissa jaetuista pisteistä. Lisäksi hyvän pelin ei näyttäisi tarvitsevan toteuttaa täydellisesti kaikkia viihteellisen laadun osatekijöitä.

A novel approach to analysing the regimes of temporary streams in relation to their controls on the composition and structure of aquatic biota

Temporary streams are those water courses that undergo the recurrent cessation of flow or the complete drying of their channel. The structure and composition of biological communities in temporary stream reaches are strongly dependent on the temporal changes of the aquatic habitats determined by the hydrological conditions. Therefore, the structural and functional characteristics of aquatic fauna to assess the ecological quality of a temporary stream reach cannot be used without taking into account the controls imposed by the hydrological regime. This paper develops methods for analysing temporary streams' aquatic regimes, based on the definition of six aquatic states that summarize the transient sets of mesohabitats occurring on a given reach at a particular moment, depending on the hydrological conditions: Hyperrheic, Eurheic, Oligorheic, Arheic, Hyporheic and Edaphic. When the hydrological conditions lead to a change in the aquatic state, the structure and composition of the aquatic community changes according to the new set of available habitats. We used the water discharge records from gauging stations or simulations with rainfall-runoff models to infer the temporal patterns of occurrence of these states in the Aquatic States Frequency Graph we developed. The visual analysis of this graph is complemented by the development of two metrics which describe the permanence of flow and the seasonal predictability of zero flow periods. Finally, a classification of temporary streams in four aquatic regimes in terms of their influence over the development of aquatic life is updated from the existing classifications, with stream aquatic regimes defined as Permanent, Temporary-pools, Temporary-dry and Episodic. While aquatic regimes describe the long-term overall variability of the hydrological conditions of the river section and have been used for many years by hydrologists and ecologists, aquatic states describe the availability of mesohabitats in given periods that determine the presence of different biotic assemblages. This novel concept links hydrological and ecological conditions in a unique way. All these methods were implemented with data from eight temporary streams around the Mediterranean within the MIRAGE project. Their application was a precondition to assessing the ecological quality of these streams.

Feedback i oportunitats de millora: una avaluació orientada a l"aprenentatge actiu

This paper analyzes an innovative experience of formative assessment aimed at improving the teaching of Statistics, which could be easily extrapolated to other studies. We detail the implementation of the double correction, consisting of correcting students' work twice. With the first correction, carried out by classmates according to a rubric developed by the academic, possible errors or deficiencies are discovered, and students are provided with a feedback that allows them to correct and improve their work before being graded by the teacher; whereas in the second correction of the work, once upgraded, the professor evaluates and grades the work. As a result, there is a significant improvement in the quality of students" works, and an active learning from their own mistakes. Both contents and competencies are reinforced by the experience.

Comparison of acute non-visual bright light responses in patients with optic nerve disease, glaucoma and healthy controls.

This study examined the effect of optic nerve disease, hence retinal ganglion cell loss, on non-visual functions related to melanopsin signalling. Test subjects were patients with bilateral visual loss and optic atrophy from either hereditary optic neuropathy (n = 11) or glaucoma (n = 11). We measured melatonin suppression, subjective sleepiness and cognitive functions in response to bright light exposure in the evening. We also quantified the post-illumination pupil response to a blue light stimulus. All results were compared to age-matched controls (n = 22). Both groups of patients showed similar melatonin suppression when compared to their controls. Greater melatonin suppression was intra-individually correlated to larger post-illumination pupil response in patients and controls. Only the glaucoma patients demonstrated a relative attenuation of their pupil response. In addition, they were sleepier with slower reaction times during nocturnal light exposure. In conclusion, glaucomatous, but not hereditary, optic neuropathy is associated with reduced acute light effects. At mild to moderate stages of disease, this is detected only in the pupil function and not in responses conveyed via the retinohypothalamic tract such as melatonin suppression.

JNK controls the onset of mitosis of planarian stem cells and triggers apoptotic cell death required for regeneration and remodeling

Regeneration of lost tissues depends on the precise interpretation of molecular signals that control and coordinate the onset of proliferation, cellular differentiation and cell death. However, the nature of those molecular signals and the mechanisms that integrate the cellular responses remain largely unknown. The planarian flatworm is a unique model in which regeneration and tissue renewal can be comprehensively studied in vivo. The presence of a population of adult pluripotent stem cells combined with the ability to decode signaling after wounding enable planarians to regenerate a complete, correctly proportioned animal within a few days after any kind of amputation, and to adapt their size to nutritional changes without compromising functionality. Here, we demonstrate that the stress-activated c-jun-NH2-kinase (JNK) links wound-induced apoptosis to the stem cell response during planarian regeneration. We show that JNK modulates the expression of wound-related genes, triggers apoptosis and attenuates the onset of mitosis in stem cells specifically after tissue loss. Furthermore, in pre-existing body regions, JNK activity is required to establish a positive balance between cell death and stem cell proliferation to enable tissue renewal, remodeling and the maintenance of proportionality. During homeostatic degrowth, JNK RNAi blocks apoptosis, resulting in impaired organ remodeling and rescaling. Our findings indicate that JNK-dependent apoptotic cell death is crucial to coordinate tissue renewal and remodeling required to regenerate and to maintain a correctly proportioned animal. Hence, JNK might act as a hub, translating wound signals into apoptotic cell death, controlled stem cell proliferation and differentiation, all of which are required to coordinate regeneration and tissue renewal.

Mammalian Target of Rapamycin Complex 2 Controls CD8 T Cell Memory Differentiation in a Foxo1-Dependent Manner.

Upon infection, antigen-specific naive CD8 T cells are activated and differentiate into short-lived effector cells (SLECs) and memory precursor cells (MPECs). The underlying signaling pathways remain largely unresolved. We show that Rictor, the core component of mammalian target of rapamycin complex 2 (mTORC2), regulates SLEC and MPEC commitment. Rictor deficiency favors memory formation and increases IL-2 secretion capacity without dampening effector functions. Moreover, mTORC2-deficient memory T cells mount more potent recall responses. Enhanced memory formation in the absence of mTORC2 was associated with Eomes and Tcf-1 upregulation, repression of T-bet, enhanced mitochondrial spare respiratory capacity, and fatty acid oxidation. This transcriptional and metabolic reprogramming is mainly driven by nuclear stabilization of Foxo1. Silencing of Foxo1 reversed the increased MPEC differentiation and IL-2 production and led to an impaired recall response of Rictor KO memory T cells. Therefore, mTORC2 is a critical regulator of CD8 T cell differentiation and may be an important target for immunotherapy interventions.

MALT1 activity controls Kaposi's sarcoma-associated herpesvirus latency and growth of primary effusion lymphoma

The identification of cancer-specific enzymatic activities that can be therapeutically targeted is key to the development of suitable anti-cancer drugs. Primary effusion lymphoma (PEL) is a rare and incurable malignancy that can occur in immunodeficient patients as a consequence of latent infection of B-cells with Kaposi's sarcoma-associated herpesvirus, KSHV (also known as human herpesvirus-8, HHV8). Malignant growth of KSHV-infected B cells requires the constitutive activity of the transcription factor NF-KB, which controls expression of viral genes required for maintenance of viral latency and suppression of the viral lytic program. Here we identify the protease mucosa-associated lymphoid tissue transformation protein 1 (MALTI), a key driver of NF-KB activation in lymphocytes, as an essential component in KSHV-dependent NF-KB activation and growth of latently infected PEL cell lines. Inhibition of the MALTI protease activity induced a switch from the latent to the lytic stage of viral infection, and led to reduced growth and survival of PEL cell lines in vitro and in a xenograft model. These results demonstrate a key role for the proteolytic activity of MALTI in PEL, and provide a rationale for the pharmacological targeting of MALTI in PEL therapy. -- L'identification d'activités enzymatiques propre au cancer est clé dans le développement des nouvaux médicaments anti-cancer. Le lymphome primitif des séreuses est un lymphome rare et incurable qui peut se developer chez les patients immunodéficients. Il est la conséquence d'une infection latente des cellules B, dûe à l'herpes virus 8, plus connu comme herpes virus associé au sarcome de Kaposi (KSHV). La croissance maligne des cellules B infecteés par KSHV requière l'activité constitutive du facteur de transcription NF-KB qui contrôle l'expression des genes viraux requis pour la maintenance latente et la suppression du programme de lyse du virus. Avec cette étude, nous avons identifié la protease MALTI comme un composant essentiel dans l'activation de NF-KB dans les cellules B du lymphome primitif des séreuses. L'inhibition de l'activité de la protéase MALTI induit un virement de la phase latente à la phase lytique du KSHV et conduit à une reduction de la viabilité des cellules tumorales in vitro et dans un modèle de xénogreffe. Ces résultats démontrent un rôle clé pour l'activité protéolytique de MALTI dans le développement du lymphome primitif des séreuses et soutiennent l'idée que MALTI pourrait être une cible pharmacologique dans la thérapie de cette forme rare du lymphome.

Neuronal activity controls the antagonistic between PGC-1α and SMRT in regulating antioxidant defences

Transcriptional coactivators and corepressors often have multiple targets and can have opposing actions on transcription and downstream physiological events. The coactivator peroxisome proliferator-activated receptor-γ coactivator (PGC)-1α is under-expressed in Huntington's disease and is a regulator of antioxidant defenses and mitochondrial biogenesis. We show that in primary cortical neurons, expression of PGC-1α strongly promotes resistance to excitotoxic and oxidative stress in a cell autonomous manner, whereas knockdown increases sensitivity. In contrast, the transcriptional corepressor silencing mediator of retinoic acid and thyroid hormone receptors (SMRT) specifically antagonizes PGC-1α-mediated antioxidant effects. The antagonistic balance between PGC-1α and SMRT is upset in favor of PGC-1α by synaptic activity. Synaptic activity triggers nuclear export of SMRT reliant on multiple regions of the protein. Concommitantly, synaptic activity post-translationally enhances the transactivating potential of PGC-1α in a p38-dependent manner, as well as upregulating cyclic-AMP response element binding protein-dependent PGC-1α transcription. Activity-dependent targeting of PGC-1α results in enhanced gene expression mediated by the thyroid hormone receptor, a prototypical transcription factor coactivated by PGC-1α and repressed by SMRT. As a consequence of these events, SMRT is unable to antagonize PGC-1α-mediated resistance to oxidative stress in synaptically active neurons. Thus, PGC-1α and SMRT are antagonistic regulators of neuronal vulnerability to oxidative stress. Further, this coactivatorcorepressor antagonism is regulated by the activity status of the cell, with implications for neuronal viability.

Negative feedback regulation of calcineurin-dependent Prz1 transcription factor by the CaMKK-CaMK1 axis in fission yeast

Calcium signals trigger the translocation of the Prz1 transcription factor from the cytoplasm to the nucleus. The process is regulated by the calciumactivated phosphatase calcineurin, which activates Prz1 thereby maintaining active transcription during calcium signalling. When calcium signalling ceases, Prz1 is inactivated by phosphorylation and exported to the cytoplasm. In budding yeast and mammalian cells, different kinases have been reported to counter calcineurin activity and regulate nuclear export. Here, we show that the Ca2+/calmodulin-dependent kinase Cmk1 is first phosphorylated and activated by the newly identified kinase CaMKK2 homologue, Ckk2, in response to Ca2+. Then, active Cmk1 binds, phosphorylates and inactivates Prz1 transcription activity whilst at the same time cmk1 expression is enhanced by Prz1 in response to Ca2+. Furthermore, Cdc25 phosphatase is also phosphorylated by Cmk1, inducing cell cycle arrest in response to an increase in Ca2+. Moreover, cmk1 deletion shows a high tolerance to chronic exposure to Ca2+, due to the lack of cell cycle inhibition and elevated Prz1 activity. This work reveals that Cmk1 kinase activated by the newly identified Ckk2 counteracts calcineurin function by negatively regulating Prz1 activity which in turn is involved in activating cmk1 gene transcription. These results are the first insights into Cmk1 and Ckk2 function in Schizosaccharomyces pombe.

Identifying strategies for mitigating the global warming impact of the EU-25 economy using a multi-objective input-output approach

Global warming mitigation has recently become a priority worldwide. A large body of literature dealing with energy related problems has focused on reducing greenhouse gases emissions at an engineering scale. In contrast, the minimization of climate change at a wider macroeconomic level has so far received much less attention. We investigate here the issue of how to mitigate global warming by performing changes in an economy. To this end, we make use of a systematic tool that combines three methods: linear programming, environmentally extended input output models, and life cycle assessment principles. The problem of identifying key economic sectors that contribute significantly to global warming is posed in mathematical terms as a bi criteria linear program that seeks to optimize simultaneously the total economic output and the total life cycle CO2 emissions. We have applied this approach to the European Union economy, finding that significant reductions in global warming potential can be attained by regulating specific economic sectors. Our tool is intended to aid policymakers in the design of more effective public policies for achieving the environmental and economic targets sought.

Mutual feedback in e-portfolio assessment : an approach to the netfolio system

Peer-reviewed

Learning Preferences with Kernel-Based Methods

Learning of preference relations has recently received significant attention in machine learning community. It is closely related to the classification and regression analysis and can be reduced to these tasks. However, preference learning involves prediction of ordering of the data points rather than prediction of a single numerical value as in case of regression or a class label as in case of classification. Therefore, studying preference relations within a separate framework facilitates not only better theoretical understanding of the problem, but also motivates development of the efficient algorithms for the task. Preference learning has many applications in domains such as information retrieval, bioinformatics, natural language processing, etc. For example, algorithms that learn to rank are frequently used in search engines for ordering documents retrieved by the query. Preference learning methods have been also applied to collaborative filtering problems for predicting individual customer choices from the vast amount of user generated feedback. In this thesis we propose several algorithms for learning preference relations. These algorithms stem from well founded and robust class of regularized least-squares methods and have many attractive computational properties. In order to improve the performance of our methods, we introduce several non-linear kernel functions. Thus, contribution of this thesis is twofold: kernel functions for structured data that are used to take advantage of various non-vectorial data representations and the preference learning algorithms that are suitable for different tasks, namely efficient learning of preference relations, learning with large amount of training data, and semi-supervised preference learning. Proposed kernel-based algorithms and kernels are applied to the parse ranking task in natural language processing, document ranking in information retrieval, and remote homology detection in bioinformatics domain. Training of kernel-based ranking algorithms can be infeasible when the size of the training set is large. This problem is addressed by proposing a preference learning algorithm whose computation complexity scales linearly with the number of training data points. We also introduce sparse approximation of the algorithm that can be efficiently trained with large amount of data. For situations when small amount of labeled data but a large amount of unlabeled data is available, we propose a co-regularized preference learning algorithm. To conclude, the methods presented in this thesis address not only the problem of the efficient training of the algorithms but also fast regularization parameter selection, multiple output prediction, and cross-validation. Furthermore, proposed algorithms lead to notably better performance in many preference learning tasks considered.

Improved understanding of drought controls on seasonal variation in Mediterranean forest canopy CO2 and water fluxes through combined in situ measurements and ecosystem modelling

Water stress is a defining characteristic of Mediterranean ecosystems, and is likely to become more severe in the coming decades. Simulation models are key tools for making predictions, but our current understanding of how soil moisture controls ecosystem functioning is not sufficient to adequately constrain parameterisations. Canopy-scale flux data from four forest ecosystems with Mediterranean-type climates were used in order to analyse the physiological controls on carbon and water flues through the year. Significant non-stomatal limitations on photosynthesis were detected, along with lesser changes in the conductance-assimilation relationship. New model parameterisations were derived and implemented in two contrasting modelling approaches. The effectiveness of two models, one a dynamic global vegetation model ('ORCHIDEE'), and the other a forest growth model particularly developed for Mediterranean simulations ('GOTILWA+'), was assessed and modelled canopy responses to seasonal changes in soil moisture were analysed in comparison with in situ flux measurements. In contrast to commonly held assumptions, we find that changing the ratio of conductance to assimilation under natural, seasonally-developing, soil moisture stress is not sufficient to reproduce forest canopy CO2 and water fluxes. However, accurate predictions of both CO2 and water fluxes under all soil moisture levels encountered in the field are obtained if photosynthetic capacity is assumed to vary with soil moisture. This new parameterisation has important consequences for simulated responses of carbon and water fluxes to seasonal soil moisture stress, and should greatly improve our ability to anticipate future impacts of climate changes on the functioning of ecosystems in Mediterranean-type climates.