993 resultados para specific load


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Background: Although combination antiretroviral therapy (cART) dramatically reduces rates of AIDS and death, a minority of patients experience clinical disease progression during treatment. <p>Objective: To investigate whether detection of CXCR4(X4)-specific strains or quantification of X4-specific HIV-1 load predict clinical outcome. Methods: From the Swiss HIV Cohort Study, 96 participants who initiated cART yet subsequently progressed to AIDS or death were compared with 84 contemporaneous, treated nonprogressors. A sensitive heteroduplex tracking assay was developed to quantify plasma X4 and CCR5 variants and resolve HIV-1 load into coreceptor-specific components. Measurements were analyzed as cofactors of progression in multivariable Cox models adjusted for concurrent CD4 cell count and total viral load, applying inverse probability weights to adjust for sampling bias. Results: Patients with X4 variants at baseline displayed reduced CD4 cell responses compared with those without X4 strains (40 versus 82 cells/mu l; P= 0.012). The adjusted multivariable hazard ratio (HR) for clinical progression was 4.8 [95% confidence interval (Cl) 2.3-10.0] for those demonstrating X4 strains at baseline. The X4-specific HIV-1 load was a similarly independent predictor, with HR values of 3.7(95%Cl, 1.2-11.3) and 5.9 (95% Cl, 2.2-15.0) for baseline loads of 2.2-4.3 and > 4.3 log(10)copies/ml, respectively, compared with < 2.2 log(10)copies/ml. Conclusions: HIV-1 coreceptor usage and X4-specific viral loads strongly predicted disease progression during cART, independent of and in addition to CD4 cell count or total viral load. Detection and quantification of X4 strains promise to be clinically useful biomarkers to guide patient management and study HIV-1 pathogenesis.

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The factors responsible for the phenotypic heterogeneity of memory CD4 T cells are unclear. In the present study, we have identified a third population of memory CD4 T cells characterized as CD45RA(+)CCR7(-) that, based on its replication history and the homeostatic proliferative capacity, was at an advanced stage of differentiation. Three different phenotypic patterns of memory CD4 T cell responses were delineated under different conditions of antigen (Ag) persistence and load using CD45RA and CCR7 as markers of memory T cells. Mono-phenotypic CD45RA(-)CCR7(+) or CD45RA(-)CCR7(-) CD4 T cell responses were associated with conditions of Ag clearance (tetanus toxoid-specific CD4 T cell response) or Ag persistence and high load (chronic HIV-1 and primary CMV infections), respectively. Multi-phenotypic CD45RA(-)CCR7(+), CD45RA(-)CCR7(-) and CD45RA(+)CCR7(-) CD4 T cell responses were associated with protracted Ag exposure and low load (chronic CMV, EBV and HSV infections and HIV-1 infection in long-term nonprogressors). The mono-phenotypic CD45RA(-)CCR7(+) response was typical of central memory (T(CM)) IL-2-secreting CD4 T cells, the mono-phenotypic CD45RA(-)CCR7(-) response of effector memory (T(EM)) IFN-gamma-secreting CD4 T cells and the multi-phenotypic response of both IL-2- and IFN-gamma-secreting cells. The present results indicate that the heterogeneity of different Ag-specific CD4 T cell responses is regulated by Ag exposure and Ag load.

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BACKGROUND: Although combination antiretroviral therapy (cART) dramatically reduces rates of AIDS and death, a minority of patients experience clinical disease progression during treatment. OBJECTIVE: To investigate whether detection of CXCR4(X4)-specific strains or quantification of X4-specific HIV-1 load predict clinical outcome. METHODS: From the Swiss HIV Cohort Study, 96 participants who initiated cART yet subsequently progressed to AIDS or death were compared with 84 contemporaneous, treated nonprogressors. A sensitive heteroduplex tracking assay was developed to quantify plasma X4 and CCR5 variants and resolve HIV-1 load into coreceptor-specific components. Measurements were analyzed as cofactors of progression in multivariable Cox models adjusted for concurrent CD4 cell count and total viral load, applying inverse probability weights to adjust for sampling bias. RESULTS: Patients with X4 variants at baseline displayed reduced CD4 cell responses compared with those without X4 strains (40 versus 82 cells/microl; P = 0.012). The adjusted multivariable hazard ratio (HR) for clinical progression was 4.8 [95% confidence interval (CI) 2.3-10.0] for those demonstrating X4 strains at baseline. The X4-specific HIV-1 load was a similarly independent predictor, with HR values of 3.7 (95% CI, 1.2-11.3) and 5.9 (95% CI, 2.2-15.0) for baseline loads of 2.2-4.3 and > 4.3 log10 copies/ml, respectively, compared with < 2.2 log10 copies/ml. CONCLUSIONS: HIV-1 coreceptor usage and X4-specific viral loads strongly predicted disease progression during cART, independent of and in addition to CD4 cell count or total viral load. Detection and quantification of X4 strains promise to be clinically useful biomarkers to guide patient management and study HIV-1 pathogenesis.

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Background: CD4(+)CD25(high) regulatory T (T(Reg)) cells modulate antigen-specific T cell responses, and can suppress anti-viral immunity. In HTLV-1 infection, a selective decrease in the function of T(Reg) cell mediated HTLV-1-tax inhibition of FOXP3 expression has been described. The purpose of this study was to assess the frequency and phenotype of T(Reg) cells in HTLV-1 asymptomatic carriers and in HTLV-1-associated neurological disease (HAM/TSP) patients, and to correlate with measures of T cell activation. Results: We were able to confirm that HTLV-1 drives activation, spontaneous IFN gamma production, and proliferation of CD4+ T cells. We also observed a significantly lower proportion of CTLA-4(+) T(Reg) cells (CD4(+)CD25(high) T cells) in subjects with HAM/TSP patients compared to healthy controls. Ki-67 expression was negatively correlated to the frequency of CTLA-4(+) T(Reg) cells in HAM/TSP only, although Ki-67 expression was inversely correlated with the percentage of CD127(low) T(Reg) cells in healthy control subjects. Finally, the proportion of CD127(low) T(Reg) cells correlated inversely with HTLV-1 proviral load. Conclusion: Taken together, the results suggest that T(Reg) cells may be subverted in HAM/TSP patients, which could explain the marked cellular activation, spontaneous cytokine production, and proliferation of CD4(+) T cells, in particular those expressing the CD25(high)CD127(low) phenotype. T(Reg) cells represent a potential target for therapeutic intervention for patients with HTLV-1-related neurological diseases.

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The T cell immunoglobulin mucin 3 (Tim-3) receptor is highly expressed on HIV-1-specific T cells, rendering them partially ""exhausted'' and unable to contribute to the effective immune mediated control of viral replication. To elucidate novel mechanisms contributing to the HTLV-1 neurological complex and its classic neurological presentation called HAM/TSP (HTLV-1 associated myelopathy/tropical spastic paraparesis), we investigated the expression of the Tim-3 receptor on CD8(+) T cells from a cohort of HTLV-1 seropositive asymptomatic and symptomatic patients. Patients diagnosed with HAM/TSP down-regulated Tim-3 expression on both CD8(+) and CD4(+) T cells compared to asymptomatic patients and HTLV-1 seronegative controls. HTLV-1 Tax-specific, HLA-A*02 restricted CD8(+) T cells among HAM/TSP individuals expressed markedly lower levels of Tim-3. We observed Tax expressing cells in both Tim-3(+) and Tim-3(-) fractions. Taken together, these data indicate that there is a systematic downregulation of Tim-3 levels on T cells in HTLV-1 infection, sustaining a profoundly highly active population of potentially pathogenic T cells that may allow for the development of HTLV-1 complications.

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We examined the effect of age-specific fecundity, mated status, and egg load on host-plant selection, by Helicoverpa armigera under laboratory conditions. The physiological state of a female moth (number of mature eggs produced) greatly influences her host-plant specificity and propensity to oviposit (oviposition motivation). Female moths were less discriminating against cowpea (a low-ranked host) relative to maize (a high-ranked host) as egg load increased. Similarly, increased egg load led to a greater propensity to oviposit on both cowpea and maize. Distribution of oviposition with age of mated females peaked shortly after mating and declined steadily thereafter until death. Most mated females (88%) carried only a single spermatophore, a few females (12%) contained two. The significance of these findings in relation to host-plant selection by H. armigera, and its management, are discussed.

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A definition of medium voltage (MV) load diagrams was made, based on the data base knowledge discovery process. Clustering techniques were used as support for the agents of the electric power retail markets to obtain specific knowledge of their customers’ consumption habits. Each customer class resulting from the clustering operation is represented by its load diagram. The Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) were applied to an electricity consumption data from a utility client’s database in order to form the customer’s classes and to find a set of representative consumption patterns. The WEACS approach is a clustering ensemble combination approach that uses subsampling and that weights differently the partitions in the co-association matrix. As a complementary step to the WEACS approach, all the final data partitions produced by the different variations of the method are combined and the Ward Link algorithm is used to obtain the final data partition. Experiment results showed that WEACS approach led to better accuracy than many other clustering approaches. In this paper the WEACS approach separates better the customer’s population than Two-step clustering algorithm.

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With the electricity market liberalization, the distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity consumers. A fair insight on the consumers’ behavior will permit the definition of specific contract aspects based on the different consumption patterns. In order to form the different consumers’ classes, and find a set of representative consumption patterns we use electricity consumption data from a utility client’s database and two approaches: Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) for combining partitions in a clustering ensemble. While EAC uses a voting mechanism to produce a co-association matrix based on the pairwise associations obtained from N partitions and where each partition has equal weight in the combination process, the WEACS approach uses subsampling and weights differently the partitions. As a complementary step to the WEACS approach, we combine the partitions obtained in the WEACS approach with the ALL clustering ensemble construction method and we use the Ward Link algorithm to obtain the final data partition. The characterization of the obtained consumers’ clusters was performed using the C5.0 classification algorithm. Experiment results showed that the WEACS approach leads to better results than many other clustering approaches.

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The present research paper presents five different clustering methods to identify typical load profiles of medium voltage (MV) electricity consumers. These methods are intended to be used in a smart grid environment to extract useful knowledge about customer’s behaviour. The obtained knowledge can be used to support a decision tool, not only for utilities but also for consumers. Load profiles can be used by the utilities to identify the aspects that cause system load peaks and enable the development of specific contracts with their customers. The framework presented throughout the paper consists in several steps, namely the pre-processing data phase, clustering algorithms application and the evaluation of the quality of the partition, which is supported by cluster validity indices. The process ends with the analysis of the discovered knowledge. To validate the proposed framework, a case study with a real database of 208 MV consumers is used.

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With the electricity market liberalization, distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity customers. In this environment all consumers are free to choose their electricity supplier. A fair insight on the customer´s behaviour will permit the definition of specific contract aspects based on the different consumption patterns. In this paper Data Mining (DM) techniques are applied to electricity consumption data from a utility client’s database. To form the different customer´s classes, and find a set of representative consumption patterns, we have used the Two-Step algorithm which is a hierarchical clustering algorithm. Each consumer class will be represented by its load profile resulting from the clustering operation. Next, to characterize each consumer class a classification model will be constructed with the C5.0 classification algorithm.

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Recent data suggest that the clinical course of reactional states in leprosy is closely related to the cytokine profile released locally or systemically by the patients. In the present study, patients with erythema nodosum leprosum (ENL) were grouped according to the intensity of their clinical symptoms. Clinical and immunological aspects of ENL and the impact of these parameters on bacterial load were assessed in conjunction with patients' in vitro immune response to mycobacterial antigens. In 10 out of the 17 patients tested, BI (bacterial index) was reduced by at least 1 log from leprosy diagnosis to the onset of their first reactional episode (ENL), as compared to an expected 0.3 log reduction in the unreactional group for the same MDT (multidrug therapy) period. However, no difference in the rate of BI reduction was noted at the end of MDT among ENL and unreactional lepromatous patients. Accordingly, although TNF-alpha (tumor necrosis factor) levels were enhanced in the sera of 70.6% of the ENL patients tested, no relationship was noted between circulating TNF-alpha levels and the decrease in BI detected at the onset of the reactional episode. Evaluation of bacterial viability of M. leprae isolated from the reactional lesions showed no growth in the mouse footpads. Only 20% of the patients demonstrated specific immune response to M. leprae during ENL. Moreover, high levels of soluble IL-2R (interleukin-2 receptor) were present in 78% of the patients. Circulating anti-neural (anti-ceramide and anti-galactocerebroside antibodies) and anti-mycobacterial antibodies were detected in ENL patients' sera as well, which were not related to the clinical course of disease. Our data suggest that bacterial killing is enhanced during reactions. Emergence of specific immune response to M. leprae and the effective role of TNF-alpha in mediating fragmentation of bacteria still need to be clarified.

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The analysis of 58 patients with chronic hepatitis C without cirrhosis and treated with interferon-alpha demonstrated that hepatitis C viral (HCV) load does not correlate with the histological evolution of the disease (p = 0.6559 for architectural alterations and p = 0.6271 for the histological activity index). Therefore, the use of viral RNA quantification as an evolutive predictor or determinant of the severity of hepatitis C is incorrect and of relative value. A review of the literature provided fundamental and interdependent HCV (genotype, heterogeneity and mutants, specific proteins), host (sex, age, weight, etc) and treatment variables (dosage, time of treatment, type of interferon) within the broader context of viral kinetics, interferon-mediated immunological response (in addition to natural immunity against HCV) and the role of interferon as a modulator of fibrogenesis. Therefore, viral load implies much more than numbers and the correct interpretation of these data should consider a broader context depending on multiple factors that are more complex than the simple value obtained upon quantification.

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Ergonomic interventions such as increased scheduled breaks or job rotation have been proposed to reduce upper limb muscle fatigue in repetitive low-load work. This review was performed to summarize and analyze the studies investigating the effect of job rotation and work-rest schemes, as well as, work pace, cycle time and duty cycle, on upper limb muscle fatigue. The effects of these work organization factors on subjective fatigue or discomfort were also analyzed. This review was based on relevant articles published in PubMed, Scopus and Web of Science. The studies included in this review were performed in humans and assessed muscle fatigue in upper limbs. 14 articles were included in the systematic review. Few studies were performed in a real work environment and the most common methods used to assess muscle fatigue were surface electromyography (EMG). No consistent results were found related to the effects of job rotation on muscle activity and subjective measurements of fatigue. Rest breaks had some positive effects, particularly in perceived discomfort. The increase in work pace reveals a higher muscular load in specific muscles. The duration of experiments and characteristics of participants appear to be the factors that most have influenced the results. Future research should be focused on the improvement of the experimental protocols and instrumentation, in order to the outcomes represent adequately the actual working conditions. Relevance to industry: Introducing more physical workload variation in low-load repetitive work is considered an effective ergonomic intervention against muscle fatigue and musculoskeletal disorders in industry. Results will be useful to identify the need of future research, which will eventually lead to the adoption of best industrial work practices according to the workers capabilities.

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The method used by YAGYU et al. for the subtype-specific polymerase chain reaction (PCR) amplification of the gp41 transmembrane region of the human immunodeficiency virus type-1 (HIV-1) env gene, was tested. HIV-1 proviral DNA from 100 infected individuals in Itajaí, South Brazil was used to analyze this method. Seventy individuals were determined according to this method as having PCR products at the expected size for subtypes B, C, D and F. Of these individuals, 26 (37.1%) were observed as having the expected amplification for subtype C, and 42 (60%) were observed as having the expected products for subtypes B and D. Of the subtype B and D amplicons, 16 (22.9%) were classified as subtype D, and 26 (37.1%) were classified as subtype B. Two individuals (2.9%) had amplicons that were observed after subtype F-specific amplification was performed. Sequencing and comparing the patient sequences to reference sequences confirmed the classification of sequences of subtypes C and B. However, sequences that were falsely determined as being D and F in the PCR assay were determined as being subtypes C and B, respectively, by sequence analysis. For those individuals from whom no amplified products were obtained, a low viral load that was indicated in their patient history may explain the difficulty in subtyping by PCR methods. This issue was demonstrated by the results of ANOVA when testing the effect of viral load on the success of PCR amplification. The alignment of the obtained sequences with HIV-1 reference sequences demonstrated that there is high intra-subtype diversity. This indicates that the subtype-specific primer binding sites were not conserved or representative of the subtypes that are observed in the Brazilian populations, and that they did not allow the correct classification of HIV-1 subtypes. Therefore, the proposed method by YAGYU et al. is not applicable for the classification of Brazilian HIV-1 subtypes.