138 research outputs found

    Are Steroids Still Useful in Immunosuppressed Patients With Inflammatory Bowel Disease? A Retrospective, Population-Based Study

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    Background: Effectiveness of corticosteroids in immunosuppressed patients with inflammatory bowel disease (IBD) has not been completely elucidated. Aims: To assess the effectiveness and examine the long-term follow-up of systemic or low-bioavailability oral steroid treatment for moderate flare-ups in patients treated with immunosuppressive drugs. Methods: Immunosuppressed patients with inflammatory bowel disease (IBD) from our population-data registry were analyzed. For statistical analysis, the chi-square test, Mann-Whitney U test, and Kaplan-Meier survival analysis were used as appropriate. Results: A total of 392 patients with IBD and a median of 82 (range, 6–271) months of immunosuppressive (IMM) treatment were identified. The mean follow-up was 87 months (range, 6–239 months). A total of 89 patients (23%) needed at least one steroid course during their follow-up. Average time from IMM to steroid treatment was 26 (range, 6–207) months. In patients with CD, fibrostenotic (B2) and fistulizing (B3) behaviors [p = 0.005; odds ratio (OR): 2.284] were risk factors for using steroids after IMM treatment. In patients with UC, no statistically significant variables were identified. Of the 89 patients who received one first steroid course, 49 (55%) stepped up to biological treatment or surgery after a median of 13 months (range, 0–178), 19 (21%) were treated with repeated steroid courses, and 31 (35%) required no further treatment. Patients with CD had a higher risk (p = 0.007; OR: 3.529) of receiving biological treatment or surgery than patients with UC. The longer the patients with UC (more months) spent using steroids, the greater the risk of requiring treatment with biological drugs or surgery (p = 0.009). Conclusion: A total of 23% of the immunosuppressed patients with IBD received at least one course of steroid treatment. In patients under immunosuppression treated with at least a course of steroids, CD patients were more likely stepped up to biologics and/or surgery than UC patients. In patients with CD, B2/B3 behavior pattern were significant risk factors. After one course of steroids only 35% of immunosuppressed IBD patients remained in remission without needing treatment scalation. © Copyright © 2021 Sicilia, Arias, Hontoria, García, Badia and Gomollón

    Herramienta de apoyo a la docencia de la energía solar fotovoltaica

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    Con el siguiente trabajo se pretende colaborar en la formación y difusión de la energía solar fotovoltaica; energía alternativa, para la obtención de electricidad, que ocupa un apartado especial en las acciones clave de la Unión Europea. La Universidad de Jaén cuenta con dos asignaturas optativas, como herramientas para contribuir a estos fines. Estas asignaturas pertenecen al plan de estudios correspondiente a Ingeniero Técnico Industrial. Dichas materias, “Electricidad Fotovoltaica” e “Instalaciones fotovoltaicas” se ofertan a las especialidades de: Mecánica, Electricidad y las Electrónica Industrial. El Curso de Energía SolarFotovoltaica para Internet forma parte de la formación en estas materias contribuyendo a cambiar el método de enseñanza empleado hasta ahora. Permite favorecer el grado de implicación por parte del alumno en el proceso de enseñanza – aprendizaje, además de proporcionar información con la que los alumnos puedan construir su conocimiento

    Herramienta software para el cálculo de la radiación solar en superficies con distinta inclinación: ORIENTSOL

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    Este documento pretende presentar una herramienta software de carácter didáctico que hace más sencillo tanto la enseñanza como el aprendizaje del cálculo de la radiación solar sobre superficies inclinadas. Este concepto forma parte de los contenidos de la asignatura optativa, “Instalaciones fotovoltaicas”. Ésta es ofertada por la Universidad de Jaén en el plan de estudios correspondiente a Ingeniero Técnico Industrial en las especialidades de: Mecánica, Electricidad y Electrónica Industrial

    Lipoic acid inhibits leptin secretion and Sp1 activity in adipocytes

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    Lipoic acid (LA) is an antioxidant with therapeutic potential on several diseases such as diabetes and obesity. Hyperleptinemia and oxidative stress play a major role in the development of obesity-linked diseases. The aim of this study was to examine in vivo and in vitro the effects of LA on leptin production, as well as to elucidate the mechanisms and signalling pathways involved in LA actions. Methods and results: Dietary supplementation with LA decreased both circulating leptin, and adipose tissue leptin mRNA in rats. Treatment of 3T3-L1 adipocytes with LA caused a concentration-dependent inhibition of leptin secretion and gene expression. Moreover, LA stimulated the anaerobic utilization of glucose to lactate, which negatively correlated with leptin secretion. Furthermore, LA enhanced phosphorylation of Sp1 and inhibited Sp1 transcriptional activity in 3T3-L1 adipocytes. Moreover, LA inhibited Akt phosphorylation, a downstream target of phosphatidylinositol 3-kinase (PI3K). Treatment with the PI3K inhibitor LY294002 mimicked LA actions, dramatically inhibiting both leptin secretion and gene expression and stimulating Sp1 phosphorylation. Conclusion: All of these data suggest that the phosphorylation of Sp1 and the accompanying reduced DNA-binding activity are likely to be involved in the inhibition of leptin induced by LA, which could be mediated in part by the abrogation of the PI3K/Akt pathway

    Examination of gammarid transcriptomes reveals a widespread occurrence of key metabolic genes from epibiont bdelloid rotifers in freshwater species

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    Previous data revealed the unexpected presence of genes encoding for long-chain polyunsaturated fatty acid (LC-PUFA) biosynthetic enzymes in transcriptomes from freshwater gammarids but not in marine species, even though closely related species were compared. This study aimed to clarify the origin and occurrence of selected LC-PUFA biosynthesis gene markers across all published gammarid transcriptomes. Through systematic searches, we confirmed the widespread occurrence of sequences from seven elongases and desaturases involved in LC-PUFA biosynthesis, in transcriptomes from freshwater gammarids but not marine species, and clarified that such occurrence is independent from the gammarid species and geographical origin. The phylogenetic analysis established that the retrieved elongase and desaturase sequences were closely related to bdelloid rotifers, confirming that multiple transcriptomes from freshwater gammarids contain contaminating rotifers’ genetic material. Using the Adineta steineri genome, we investigated the genomic location and exon–intron organization of the elongase and desaturase genes, establishing they are all genome-anchored and, importantly, identifying instances of horizontal gene transfer. Finally, we provide compelling evidence demonstrating Bdelloidea desaturases and elongases enable these organisms to perform all the reactions for de novo biosynthesis of PUFA and, from them, LC-PUFA, an advantageous trait when considering the low abundance of these essential nutrients in freshwater environments

    Herramienta docente en la asignatura de instalaciones fotovoltaicas (Design SFA v1.0). Adaptación a los créditos ECTS

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    Este documento pretende presentar una herramienta software de carácter docente orientada al aprendizaje del diseño de  Sistemas Fotovoltaicos Autónomos (SFA). Este último forma parte de los contenidos de las asignaturas optativas, “Instalaciones fotovoltaicas” y “Electricidad Fotovoltaica”, ofertadas por la Universidad de Jaén en el plan de estudios correspondiente a Ingeniero Técnico Industrial en las especialidades de: Mecánica, Electricidad y Electrónica Industrial. Así mismo, el diseño de los SFA también conforma un módulo del Máster de Energías Renovables impartido en esta misma Universidad

    Cover crop identity determines root fungal community and arbuscular mycorrhiza colonization in following main crops

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    Cover crops (CC) can promote nutrient retention and recycling for main crops yet may also promote soilborne pathogens or suppress beneficial root symbionts such as arbuscular mycorrhizal fungi (AMF). We investigated how root fungal communities of main crop are affected by preceding CC monocultures and mixtures and by main crop identity. We expected that AMF abundance and diversity in main crops are promoted by AM-host CC, and suppressed by non-AM-host CC, and that mixtures of CC species can promote beneficial and suppress pathogenic root fungi. Our full-factorial field experiment comprised crop rotation in sand soil with different CC treatments (monocultures of radish [AM non-host], ryegrass, clover, vetch [AM hosts], mixtures of radish + vetch, ryegrass + clover and fallow) and two main crops (oat and endive). At peak crop growth, we investigated the root fungal communities in the main crops using microscopy and high throughput sequencing (Illumina MiSeq). Cover crop identity was of prime importance and CC legacy overruled main crop identity in determining root fungal communities in main crops. Compared with fallow, CC with ryegrass increased AMF colonization and richness in both main crops and of non-AMF in oat. Legacies of ryegrass, ryegrass + clover and vetch resulted in distinct root fungal communities in the main crops, while the legacy of CC with radish were similar to the legacy of fallow. Root fungal community in crops after clover had highest abundance of representative fungal pathogens in contrast with the other CC treatments that resulted in fungal communities where pathogens were scarce. Oppositely to expected, CC mixtures did not enhance fungal symbionts or suppressed pathogens. Overall, fungal communities in roots of the main crops in our field experiment were determined by the preceding CC species in monoculture, rather than by the CC AMF preference or functional group. This research highlights that the choice of CC determines the root fungal community in main crop which may influence crop quality

    Effects of alpha-lipoic acid and eicosapentaenoic acid in overweight and obese women during weight loss

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    Objective: To evaluate the potential body weight lowering effects of dietary supplementation with eicosapentaenoic acid (EPA) and α-lipoic acid separately or combined, in healthy overweight/obese women following a hypocaloric diet. Design and Methods: This is a short-term double-blind placebo-controlled lasted 10-weeks study with parallel design. Of the randomized participants, 97 women received the allocated treatment (Control, EPA (1.3 g/d of EPA), α-lipoic acid (0.3 g/d) and EPA+ α-lipoic acid (1.3 g/d + 0.3 g/d)), finishing 77 volunteers. All groups followed an energy-restricted diet of 30% from the total energy expenditure. Body weight, anthropometric measurements, body composition, resting energy expenditure, blood pressure, serum glucose, insulin and lipid profile, as well as leptin and ghrelin levels, were assessed at baseline and after nutritional intervention. Results: Body weight loss was significantly higher (P < 0.05) in those groups supplemented with α-lipoic acid. EPA supplementation significantly attenuated (P < 0.001) the decrease in leptin levels that occurs during weight loss. Body weight loss improved lipid and glucose metabolism parameters, but without significant differences between groups. Conclusion: The intervention suggests that α-lipoic acid supplementation alone or in combination with EPA may help to promote body weight loss in healthy overweight/obese women following energy-restricted diets

    PPARGC1A gene promoter methylation as a biomarker of insulin secretion and sensitivity in response to glucose challenges

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    Methylation in CpG sites of the PPARGC1A gene (encoding PGC1-α) has been associated with adiposity, insulin secretion/sensitivity indexes and type 2 diabetes. We assessed the association between the methylation profile of the PPARGC1A gene promoter gene in leukocytes with insulin secretion/sensitivity indexes in normoglycemic women. A standard oral glucose tolerance test (OGTT) and an abbreviated version of the intravenous glucose tolerance test (IVGTT) were carried out in n = 57 Chilean nondiabetic women with measurements of plasma glucose, insulin, and C-peptide. Bisulfite-treated DNA from leukocytes was evaluated for methylation levels in six CpG sites of the proximal promoter of the PPARGC1A gene by pyrosequencing (positions -816, -783, -652, -617, -521 and -515). A strong correlation between the DNA methylation percentage of different CpG sites of the PPARGC1A promoter in leukocytes was found, suggesting an integrated epigenetic control of this region. We found a positive association between the methylation levels of the CpG site -783 with the insulin sensitivity Matsuda composite index (rho = 0.31; p = 0.02) derived from the OGTT. The CpG hypomethylation in the promoter position -783 of the PPARGC1A gene in leukocytes may represent a biomarker of reduced insulin sensitivity after the ingestion of glucose

    Artificial intelligence for photovoltaic systems

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    Photovoltaic systems have gained an extraordinary popularity in the energy generation industry. Despite the benefits, photovoltaic systems still suffer from four main drawbacks, which include low conversion efficiency, intermittent power supply, high fabrication costs and the nonlinearity of the PV system output power. To overcome these issues, various optimization and control techniques have been proposed. However, many authors relied on classical techniques, which were based on intuitive, numerical or analytical methods. More efficient optimization strategies would enhance the performance of the PV systems and decrease the cost of the energy generated. In this chapter, we provide an overview of how Artificial Intelligence (AI) techniques can provide value to photovoltaic systems. Particular attention is devoted to three main areas: (1) Forecasting and modelling of meteorological data, (2) Basic modelling of solar cells and (3) Sizing of photovoltaic systems. This chapter will aim to provide a comparison between conventional techniques and the added benefits of using machine learning methods
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