1,867 research outputs found
Hypertriglyceridemic Pancreatitis: Conventional Treatment Versus Therapeutic Plasma Exchange
Introdução:A pancreatite aguda (PA) por hipertrigliceridemia (HTG) pode ser tratada com troca plasmĂĄtica terapĂȘutica (TPT), com redução rĂĄpida dos valores de triglicerĂdeos. Contudo, nĂŁo existem estudos comparativos definitivos que comprovem o real benefĂcio desta terapĂȘutica. Objetivo: Comparação dos mĂ©todos de tratamento (troca plasmĂĄtica terapĂȘutica versus convencional) em doentes com PA HTG, durante um perĂodo de 12 anos (2000-2012). MĂ©todos: Estudo retrospetivo descritivo e inferencial de 37 doentes, avaliando: sexo, idade, antecedentes pessoais, gravidade, valores de TG e evolução consoante o tratamento (âTPTâ ou terapĂȘutica convencional âCâ). Resultados: Os dois grupos TPT e C mostraram-se homogĂ©neos quanto ao sexo (p = 0,647), idade (43,5 ± 9,74 anos TPT versus 45,30 ± 9,90 anos C; p = 0.320), pancreatite prĂ©via (40% TPT vs 40,7% C; p = 1,0) alcoolismo crĂłnico (50% TPT vs 70,4% C; p = 0,275) e gravidade pelo score de APACHE II (p = 0,054) e Ranson Ă s 48 horas (p = 0,258). Dos doentes 45,95% apresentava mais de um fator de risco secundĂĄrio para HTG. O grupo TPT apresentou maiores valores de TG Ă admissĂŁo: 4850 ± 2802 mg/dL vs 1845 ± 1858 mg/dL (p = 0,001). NĂŁo se verificaram diferenças na duração do internamento 14,2 ± 6,8 dias vs 13,5 ± 9,0 dias (p = 0,56) ou na taxa de mortalidade (p = 0,47). Ă data de alta a redução dos TG foi superior no grupo TPT: 4433,70 ± 2896,08 mg/dL - 91,41% vs 1582,95 ± 2051,06 mg/dL â 83,92% (p = 0,002). De referir seis intercorrĂȘncias minor durante a troca plasmĂĄtica terapĂȘutica. DiscussĂŁo/ConclusĂ”es: Apesar do viĂ©s de seleção (estudo retrospetivo), foi constatada uma maior redução dos TG por esta tĂ©cnica. As intercorrĂȘncias inerentes Ă tĂ©cnica de troca plasmĂĄtica terapĂȘutica foram de simples resolução.info:eu-repo/semantics/publishedVersio
Pancreatite HipertrigliceridĂ©mica: Tratamento Convencional Versus Troca PlasmĂĄtica TerapĂȘutica
Introduction: Acute pancreatitis (AP) induced by hypertriglyceridemia
(HTG) can be treated with therapeutic plasma exchange
(TPE), resulting in rapid reduction of triglyceride level.
However, there are no definitive comparative studies that
prove the real benefits of this therapy.
Objectives: Comparison of treatment methods (TPE versus
conventional) in patients with HTG AP during a period of 12
years (2000-2012).
Methods: Retrospective, descriptive and inferential analysis of
37 patients, evaluating: gender, age, personal pathologic history,
severity of disease, HTG values and evolution depending
on treatment with therapeutic plasma exchange (âTPEâ) or
with conventional therapy (âCâ).
Results: Both groups TPE and C demonstrated homogeneity
considering gender (p = 0.647), age (43.5 ± 9.74 years TPE vs
45.30 ± 9.90 years C; p = 0.320), prior AP episode (40% TPE
vs 40.7% C; p = 1.0), chronic alcohol consumption (50% TPE
vs 70.4% C; p = 0.275) and severity disease scores: APACHE
II (p = 0.054) and Ranson (p = 0.258). More than one secondary
HTG risk factor was presented in 45.95% of patients
. TPE group presented higher TG levels at admission: 4850
± 2802 mg/dL vs 1845 ± 1858 mg/dL (p = 0.001). No significant
statistical differences were observed considering length
of hospital stay [14.2 ± 6.8 days vs 13.5 ± 9.0 days (p = 0.56)]
or mortality rate (p = 0.47). At discharge, TG reduction was
greater in TPE group: 4433.70 ± 2896.08 mg/dL â 91.41% vs
1582.95 ± 2051.06 mg/dL â 83,92% (p = 0.002). Six minor
complications associated to TPE occurred.
Discussion/Conclusion: Despite the selection bias (retrospective
study), a greater TG reduction was observed with TPE
technique. Complications associated with the technique were
simple to resolveinfo:eu-repo/semantics/publishedVersio
Noncommutative cosmological models coupled to a perfect fluid and a cosmological constant
In this work we carry out a noncommutative analysis of several
Friedmann-Robert-Walker models, coupled to different types of perfect fluids
and in the presence of a cosmological constant. The classical field equations
are modified, by the introduction of a shift operator, in order to introduce
noncommutativity in these models. We notice that the noncommutative versions of
these models show several relevant differences with respect to the
correspondent commutative ones.Comment: 27 pages. 7 figures. JHEP style.arXiv admin note: substantial text
overlap with arXiv:1104.481
Federated Ensemble Regression Using Classification
Ensemble learning has been shown to significantly improve predictive accuracy in a variety of machine learning problems. For a given predictive task, the goal of ensemble learning is to improve predictive accuracy by combining the predictive power of multiple models. In this paper, we present an ensemble learning algorithm for regression problems which leverages the distribution of the samples in a learning set to achieve improved performance. We apply the proposed algorithm to a problem in precision medicine where the goal is to predict drug perturbation effects on genes in cancer cell lines. The proposed approach significantly outperforms the base case
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Grazing exclusion-induced changes in soil fungal communities in a highly desertified Brazilian dryland
Soil desertification poses a critical ecological challenge in arid and semiarid climates worldwide, leading to decreased soil productivity due to the disruption of essential microbial community processes. Fungi, as one of the most important soil microbial communities, play a crucial role in enhancing nutrient and water uptake by plants through mycorrhizal associations. However, the impact of overgrazing-induced desertification on fungal community structure, particularly in the Caatinga biome of semiarid regions, remains unclear. In this study, we assessed the changes in both the total fungal community and the arbuscular mycorrhizal fungal community (AMF) across 1. Natural vegetation (native), 2. Grazing exclusion (20 years) (restored), and 3. affected by overgrazing-induced degradation (degraded) scenarios. Our assessment, conducted during both the dry and rainy seasons in Irauçuba, CearĂĄ, utilized Internal Transcribed Spacer (ITS) gene sequencing via IlluminaÂź platform. Our findings highlighted the significant roles of the AMF families Glomeraceae (âŒ71% of the total sequences) and Acaulosporaceae (âŒ14% of the total sequences) as potential key taxa in mitigating climate change within dryland areas. Moreover, we identified the orders Pleosporales (âŒ35% of the total sequences) and Capnodiales (âŒ21% of the total sequences) as the most abundant soil fungal communities in the Caatinga biome. The structure of the total fungal community differed when comparing native and restored areas to degraded areas. Total fungal communities from native and restored areas clustered together, suggesting that grazing exclusion has the potential to improve soil properties and recover fungal community structure amid global climate change challenges
Using a logical model to predict the growth of yeast
<p>Abstract</p> <p>Background</p> <p>A logical model of the known metabolic processes in <it>S. cerevisiae </it>was constructed from iFF708, an existing Flux Balance Analysis (FBA) model, and augmented with information from the KEGG online pathway database. The use of predicate logic as the knowledge representation for modelling enables an explicit representation of the structure of the metabolic network, and enables logical inference techniques to be used for model identification/improvement.</p> <p>Results</p> <p>Compared to the FBA model, the logical model has information on an additional 263 putative genes and 247 additional reactions. The correctness of this model was evaluated by comparison with iND750 (an updated FBA model closely related to iFF708) by evaluating the performance of both models on predicting empirical minimal medium growth data/essential gene listings.</p> <p>Conclusion</p> <p>ROC analysis and other statistical studies revealed that use of the simpler logical form and larger coverage results in no significant degradation of performance compared to iND750.</p
Comparative transcriptomic analysis reveals similarities and dissimilarities in saccharomyces cerevisiae wine strains response to nitrogen availability
Nitrogen levels in grape-juices are of major importance in winemaking ensuring adequate yeast growth and fermentation performance. Here we used a comparative transcriptome analysis to uncover wine yeasts responses to nitrogen availability during fermentation. Gene expression was assessed in three genetically and phenotypically divergent commercial wine strains (CEG, VL1 and QA23), under low (67 mg/L) and high nitrogen (670 mg/L) regimes, at three time points during fermentation (12h, 24h and 96h). Two-way ANOVA analysis of each fermentation condition led to the identification of genes whose expression was dependent on strain, fermentation stage and on the interaction of both factors. The high fermenter yeast strain QA23 was more clearly distinct from the other two strains, by differential expression of genes involved in flocculation, mitochondrial functions, energy generation and protein folding and stabilization. For all strains, higher transcriptional variability due to fermentation stage was seen in the high nitrogen fermentations. A positive correlation between maximum fermentation rate and the expression of genes involved in stress response was observed. The finding of common genes correlated with both fermentation activity and nitrogen up-take underlies the role of nitrogen on yeast fermentative fitness. The comparative analysis of genes differentially expressed between both fermentation conditions at 12h, where the main difference was the level of nitrogen available, showed the highest variability amongst strains revealing strain-specific responses. Nevertheless, we were able to identify a small set of genes whose expression profiles can quantitatively assess the common response of the yeast strains to varying nitrogen conditions. The use of three contrasting yeast strains in gene expression analysis prompts the identification of more reliable, accurate and reproducible biomarkers that will facilitate the diagnosis of deficiency of this nutrient in the grape-musts and the development of strategies to optimize yeast performance in industrial fermentations
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