6 research outputs found

    Multi-Regression Factors Influencing Textile Dye Adsorption on Activated Carbon

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    Waste from textile plants contains high concentrations of textile dyes, which may be harmful to the environment. Activated carbon can be used to remove the dyes from such wastewater. Dyes can adsorb onto the activated carbon, making the wastewater safer for the environment and health of those drinking it. This experiment researched the factors affecting adsorbance onto activated carbon and what conditions work best in eliminating the dye. The aim for this experiment is to develop a mathematical model to predict the adsorbance of dye onto activated carbon. The factors studied affecting this include types of dye, salinity, pH, type of carbon, and time the mixture is in contact with the carbon. Using factorial analysis, two different dyes, two salinities, three pH’s, and three different types of carbon were tested under three different time spans

    Application of Factorial Design in the Analysis of Factors Influencing Textile Dye Adsorption on Activated Carbon

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    In this study, the use of factorial design software is applied to evaluate efficiently factors influencing the adsorption capacity of activated carbon in treating textile dyes. Activated carbon is usually used to treat wastewater effluents from textile industries in order to remove textile dyes before discharge into the environment. Most treatment facilities, particularly large industrial or wastewater treatment facilities use continuous flow reactors or packed columns to treat the dye. Due to the limited residence time in these types of reactors, adsorption equilibrium is not necessarily reached, and the absorption rate becomes an important factor in this treatment process. Other factors influencing the capacity of activated carbon used in this study included pH, ionic strength, the type of the dye and the type of carbon. In this study, we use Minitab software to design an experiment to evaluate collectively these factors, each under various levels (33 × 22 factorial design). The novelty of this study is the utilization of factorial design in the experimental approach

    Cognitive decline in Huntington's disease expansion gene carriers

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    Clinical manifestations of intermediate allele carriers in Huntington disease

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    Objective: There is controversy about the clinical consequences of intermediate alleles (IAs) in Huntington disease (HD). The main objective of this study was to establish the clinical manifestations of IA carriers for a prospective, international, European HD registry. Methods: We assessed a cohort of participants at risk with <36 CAG repeats of the huntingtin (HTT) gene. Outcome measures were the Unified Huntington's Disease Rating Scale (UHDRS) motor, cognitive, and behavior domains, Total Functional Capacity (TFC), and quality of life (Short Form-36 [SF-36]). This cohort was subdivided into IA carriers (27-35 CAG) and controls (<27 CAG) and younger vs older participants. IA carriers and controls were compared for sociodemographic, environmental, and outcome measures. We used regression analysis to estimate the association of age and CAG repeats on the UHDRS scores. Results: Of 12,190 participants, 657 (5.38%) with <36 CAG repeats were identified: 76 IA carriers (11.56%) and 581 controls (88.44%). After correcting for multiple comparisons, at baseline, we found no significant differences between IA carriers and controls for total UHDRS motor, SF-36, behavioral, cognitive, or TFC scores. However, older participants with IAs had higher chorea scores compared to controls (p 0.001). Linear regression analysis showed that aging was the most contributing factor to increased UHDRS motor scores (p 0.002). On the other hand, 1-year follow-up data analysis showed IA carriers had greater cognitive decline compared to controls (p 0.002). Conclusions: Although aging worsened the UHDRS scores independently of the genetic status, IAs might confer a late-onset abnormal motor and cognitive phenotype. These results might have important implications for genetic counseling. ClinicalTrials.gov identifier: NCT01590589

    Clinical and genetic characteristics of late-onset Huntington's disease

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    Background: The frequency of late-onset Huntington's disease (&gt;59 years) is assumed to be low and the clinical course milder. However, previous literature on late-onset disease is scarce and inconclusive. Objective: Our aim is to study clinical characteristics of late-onset compared to common-onset HD patients in a large cohort of HD patients from the Registry database. Methods: Participants with late- and common-onset (30–50 years)were compared for first clinical symptoms, disease progression, CAG repeat size and family history. Participants with a missing CAG repeat size, a repeat size of ≤35 or a UHDRS motor score of ≤5 were excluded. Results: Of 6007 eligible participants, 687 had late-onset (11.4%) and 3216 (53.5%) common-onset HD. Late-onset (n = 577) had significantly more gait and balance problems as first symptom compared to common-onset (n = 2408) (P &lt;.001). Overall motor and cognitive performance (P &lt;.001) were worse, however only disease motor progression was slower (coefficient, −0.58; SE 0.16; P &lt;.001) compared to the common-onset group. Repeat size was significantly lower in the late-onset (n = 40.8; SD 1.6) compared to common-onset (n = 44.4; SD 2.8) (P &lt;.001). Fewer late-onset patients (n = 451) had a positive family history compared to common-onset (n = 2940) (P &lt;.001). Conclusions: Late-onset patients present more frequently with gait and balance problems as first symptom, and disease progression is not milder compared to common-onset HD patients apart from motor progression. The family history is likely to be negative, which might make diagnosing HD more difficult in this population. However, the balance and gait problems might be helpful in diagnosing HD in elderly patients
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