scholarly journals The Correlation between Serum Selenium and Blood Selenium in Cattle

1992 ◽  
Vol 4 (1) ◽  
pp. 48-52 ◽  
Author(s):  
John Maas ◽  
Francis D. Galey ◽  
John R. Peauroi ◽  
James T. Case ◽  
E. Sue Littlefield ◽  
...  
Keyword(s):  
Linear Regression ◽  
Prediction Interval ◽  
Linear Regression Analysis ◽  
Hydride Generation ◽  
Argon Plasma ◽  
Prediction Intervals ◽  
Serum Selenium ◽  
Prediction Formula ◽  
Serum Samples ◽  
Inverse Prediction

The selenium (Se) concentration of paired blood and serum samples from cattle was determined by 2 methods: 1) atomic absorption spectroscopy using hydride generation (HG-AAS), and 2) inductively coupled argon plasma emission spectroscopy using hydride generation (ICP). Samples from 327 cattle were analyzed by HG-AAS, and samples from 344 cattle were analyzed by ICP. The data were examined by linear regression analysis, and the technique of inverse prediction was utilized to determine prediction intervals for estimating blood Se concentration from known serum Se concentration. The correlation coefficients, by simple linear regression of serum Se on blood Se, were 0.79 ( r2 = 0.62) and 0.88 ( r2 = 0.77) for the HG-AAS data and the ICP data, respectively. For the HG-AAS data, the inverse prediction formula for estimating blood Se when serum Se is known, at the 95% prediction interval, was For the ICP data, the inverse prediction formula for estimating blood Se when serum Se is known, at the 95% prediction interval, was The prediction intervals were quite wide, and the accuracy of estimating blood Se from a known serum Se was not useful for diagnostic purposes. The use of serum Se concentration to assess nutritional status of cattle with respect to Se does not appear to be appropriate.

The effect of prior cisplatin therapy on the pharmacokinetics of high-dose methotrexate.

1984 ◽  
Vol 2 (6) ◽  
pp. 655-661 ◽  
Author(s):  
W R Crom ◽  
C B Pratt ◽  
A A Green ◽  
J E Champion ◽  
D B Crom ◽  
...  
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Half Life ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Model ◽  
High Dose ◽  
Severe Toxicity ◽  
High Dose Methotrexate ◽  
Serum Samples ◽  
Dose Methotrexate

The pharmacokinetics of high-dose methotrexate (MTX, 5-15 g/m2) were evaluated in 11 children and adolescents who had previously received two to eight doses of cisplatin (90 mg/m2) in the treatment of malignant solid tumors. The half-life for disappearance of MTX from serum during the first 24 hours after infusion was determined from serum samples obtained at the end of a six-hour infusion and six, 12, and 24 hours after infusion. These values were compared to a mean half-life of 2.83 (+/- 0.34) hours following 489 courses administered to 71 patients who had not received cisplatin. Stepwise multiple linear regression analysis of patient variables revealed cumulative cisplatin dosage and time from last cisplatin dose as the best predictors of MTX half-life (r2 = 65.4%, p less than 0.001). The best predictors of 24-hour serum concentration were cumulative cisplatin dosage and MTX dosage (r2 = 54.2%, p less than 0.001) in the multiple linear regression model. Patients with delayed MTX clearance received additional leucovorin and experienced no severe toxicity. Patients receiving up to 270 mg/m2 of cisplatin appear to have minimal increases in MTX half-life, while the likelihood of delayed clearance increases in patients who have received 360 mg/m2 or more of cisplatin. All patients who have previously received cisplatin should be treated cautiously with high-dose MTX and prospective pharmacokinetic monitoring should be routinely performed.

scholarly journals Antiapolipoprotein A-1 Autoantibody Positivity Is Associated with Threatened Abortion

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Alessandra Vecchié ◽  
Aldo Bonaventura ◽  
Federico Carbone ◽  
Davide Maggi ◽  
Antonella Ferraiolo ◽  
...  
Keyword(s):  
Linear Regression ◽  
Pregnant Women ◽  
Inflammatory Diseases ◽  
Linear Regression Analysis ◽  
Linear Regression Models ◽  
Serum Samples ◽  
Uncomplicated Pregnancy ◽  
Threatened Abortion ◽  
Elisa Technique ◽  
Study Inclusion

Background. Autoantibodies against apolipoprotein A-1 (anti-ApoA-1 IgG) were demonstrated to be associated with cardiovascular outcomes in several inflammatory diseases. As balanced inflammation is critical for uncomplicated pregnancy, we aimed to investigate the prevalence of anti-ApoA-1 IgG and anti-c-terminal ApoA-1 autoantibodies (Ac-terAA1 IgG) in a cohort of pregnant women and their potential relationship with threatened abortion (TA). Methods. Between 2012 and 2014, 371 consecutive outpatient pregnant women were included in this study and followed until delivery. Anti-ApoA-1 and anti-Ac-terAA1 IgG were measured by ELISA technique on serum samples collected between the 24th and 26th week of pregnancy. Associations with TA were tested using linear regression analysis and C-statistics. Results. Median age was 34 with a prevalence of the Caucasian ethnicity (90.5%). TA occurred in 10 women (2.7%). C-statistics indicated that anti-ApoA-1 and anti-Ac-terAA1 IgG levels upon study inclusion were predictive of TA (0.73, 95% confidence interval [CI] 0.69-0.78, p<0.001 and 0.76, 95% CI 0.71-0.80, p=0.01, respectively). At the prespecified anti-ApoA-1 IgG cutoff, the negative predictive value (NPV) was 100%. For anti-Ac-terAA1 IgG, at the optimal cutoff, the NPV was 99%. Linear regression models indicated that risk associations were independent of age and the presence of autoimmune diseases for both autoantibodies (p<0.001). Anti-Ac-terAA1 IgG-positive individuals were more frequently non-Caucasians (p=0.009). Conclusion. Anti-ApoA-1 and anti-Ac-terAA1 IgG are independently associated with TA during pregnancy with an appealing NPV. The causal biological mechanisms underlying this association as well as the possible clinical relevance of these findings require further investigations.

scholarly journals Estimation of Motor Impairment and Usage of Upper Extremities during Daily Living Activities in Poststroke Hemiparesis Patients by Observation of Time Required to Accomplish Hand Dexterity Tasks

2019 ◽  
Vol 2019 ◽  
pp. 1-8
Author(s):  
Tomoko Tanaka ◽  
Toyohiro Hamaguchi ◽  
Makoto Suzuki ◽  
Daigo Sakamoto ◽  
Junpei Shikano ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Upper Extremity ◽  
Daily Living ◽  
Linear Regression Analysis ◽  
Motor Impairment ◽  
Prediction Formula ◽  
Item Score ◽  
Hand Dexterity ◽  
Time Required

Aim. This study evaluated whether specific actual performance could accurately predict body function levels and upper limb use in the real-life functioning of poststroke hemiparesis patients to aid in choosing the most appropriate rehabilitation exercises. Methods. We measured the time taken for poststroke patients to move small objects with the paralyzed hand and investigated how the measurement could estimate upper extremity motor impairment and hand usage during activities of daily living (ADL). We examined 86 stroke patients (age 66 ± 16 years) whose upper extremity motor paralysis was measured using the Fugl-Meyer assessment (FMA) and Southampton Hand Assessment Procedure (SHAP), and patient-reported ADL was investigated using the Jikei Assessment Scale for Motor Impairment in Daily Living (JASMID). To identify the time required to perform each SHAP item, we employed a linear regression analysis. The prediction formula was used in the linear regression analysis, and the coefficient of determination (R2) was applied to compare each component item score that was obtained with the predicted values derived from the linear regression analysis. Results. The most easily accomplished task was Heavy Power in the SHAP. The R2 between the SHAP Heavy Power item score and the FMA scores was moderate (R2 = 0.344, P<0.0001), whereas the R2 with the JASMID score was low (R2 = 0.126, P<0.001). Conclusions. By measuring the time it takes for poststroke hemiparesis patients to hold and move an object, we developed a prediction formula for upper extremity motor function and hand dexterity.

Multicomponent analysis for alkaline phosphatase isoenzyme determination by multiple linear regression

1994 ◽  
Vol 40 (5) ◽  
pp. 803-810 ◽  
Author(s):  
C R Tillyer ◽  
S Rakhorst ◽  
C M Colley
Keyword(s):  
Alkaline Phosphatase ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Linear Regression Analysis ◽  
Multicomponent System ◽  
Multiple Linear Regression Analysis ◽  
Serum Samples ◽  
Electrophoretic Method ◽  
Multicomponent Analysis ◽  
Alkaline Phosphatase Isoenzyme

Abstract Alkaline phosphatase (EC 3.1.3.1) isoenzymes in serum may be determined by multicomponent analysis of the enzyme activities in the presence of multiple inhibitors. To determine inhibition coefficients of the isoenzymes, we used multiple linear regression analysis to compare alkaline phosphatase activities in the presence of known inhibitors with electrophoretically determined isoenzyme activities in plasma and serum samples. All possible combinations of exactly determined and overdetermined linear systems of inhibitors were ranked according to their prediction error to select an optimum set. The best multicomponent system for prediction included the use of levamisole, phenylalanine, and heat inhibition at 56 degrees C and 65 degrees C to determine bone, hepatic, intestinal, and placental isoenzymes. Consideration of the hepatic isoenzyme as liver and macromolecular fractions resulted in significantly worse predictions. Error analysis involving repeat determinations and a simplex optimization of the inhibition coefficients indicated that the inaccuracy of the comparison electrophoretic method may have been a major factor affecting poor isoenzyme prediction in some samples.

scholarly journals Influence of lens position as detected by an anterior segment analysis system on postoperative refraction in cataract surgery

2021 ◽  
Vol 14 (7) ◽  
pp. 1006-1012
Author(s):  
Jia-Ju Zhang ◽  
◽  
Chen Li ◽  
Yi-Hong Cao ◽  
Pei-Rong Lu ◽  
...  
Keyword(s):  
Linear Regression ◽  
Prediction Error ◽  
Linear Regression Analysis ◽  
Anterior Segment ◽  
Final Analysis ◽  
Prediction Formula ◽  
Weak Correlation ◽  
Lens Position ◽  
Iol Power ◽  
Analysis System

AIM: To predict postoperative intraocular lens (IOL) position using the Sirius anterior segment analysis system and investigate the effect of lens position and IOL type on postoperative refraction. METHODS: A total of 97 patients (102 eyes) were enrolled in the final analysis. An anterior segment biometry measurement was performed preoperatively with Sirius and Lenstar. The results of predicted lens position (PLP) and IOL power were automatically calculated by the software used by the instruments. Effective lens position (ELP) was measured manually using Sirius 3mo postoperatively. Pearson’s correlation analysis and linear regression analysis were used to determine the correlation of lens position to other parameters. RESULTS: PLP and ELP were positively correlated to axial length (AL; r=0.42, P<0.0001 and r=0.49, P<0.0001, respectively). There was a weak correlation between the peLP (ELP-PLP) and the prediction error of spherical refraction (peSR; r=0.34, P<0.0001). The peLP of Softec HD IOL differed statistically from those of both the TECNIS ZCB00 and Sensor AR40E IOLs. Multiple linear regression was used to obtain the prediction formula: ELP=0.66+0.63× [aqueous depth (AQD)+0.6LT] (r=0.61, P<0.0001), and a new variable (AQD+0.6 LT) was found to have the strongest correlation with ELP. CONCLUSION: The Sirius anterior segment analysis system is helpful to predict ELP, which reduces postoperative refraction error.

Comparison of methods for calculating serum osmolality: multivariate linear regression analysis

2005 ◽  
Vol 43 (6) ◽  
Author(s):  
Mehdi Rasouli ◽  
Kiarash Rezaei Kalantari
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Serum Osmolality ◽  
Multivariate Linear Regression Analysis ◽  
Serum Samples ◽  
Sodium Potassium ◽  
The Subject ◽  
Spss Software

AbstractBackground: There are several methods for calculating serum osmolality, and their accordance with measured osmolality is the subject of controversy.Methods: The concentrations of sodium, potassium, glucose, blood urea nitrogen (BUN) and osmolalities of 210 serum samples were measured. Two empirical equations were deduced for the calculation of serum osmolality by regression analysis of the data. To choose the best equation, chemical concentrations were also used to calculate osmolalities according to our formulas and 16 different equations were taken from the literature and compared with the measured osmolalities. Correlation and linear regression analyses were performed using Excel and SPSS software.Results: Multiple linear regression analysis showed that serum concentrations of sodium (β=0.778, p≤0.000), BUN (β=0.315, p≤0.000), glucose (β=0.0.089, p≤0.007) and potassium (β=0.109, p≤0.008) are strong predictors of serum osmolality. The data were also analyzed by manual linear regression to yield the equations: osmolality=1.897[NaConclusions: Our data suggest use of the Worthley et al. formula Osm=2[Na

PENGARUH FAKTOR-FAKTOR INTERNAL PERBANKAN TERHADAP NON PERFORMING FINANCING PADA BANK UMUM SYARIAH

2019 ◽  
Vol 6 (2) ◽  
pp. 115-130
Author(s):  
Eka Ambara Harci Putranta ◽  
Lilik Ambarwati
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Capital Adequacy ◽  
Annual Reports ◽  
Regression Methods ◽  
Capital Adequacy Ratio ◽  
Negative Effect ◽  
Independent Variable

The study aims to analyze the influence of internal banking factors in the form of: Capital Adequency Ratio (CAR), Financing to Deposit Ratio (FDR) and Total Assets (TA) to Non Performing Financing at Sharia Banks. This research method used multiple linear regression analysis with the help of SPSS 16.00 software which is used to see the influence between the independent variables in the form of Capital Adequacy Ratio (CAR), Financing to Deposit Ratio (FDR) and Total Assets (TA) to Non Performing Financing. The sample of this study was 3 Islamic Commercial Banks, so there were 36 annual reports obtained through purposive sampling, then analyzed using multiple linear regression methods. The results showed that based on the F Test, the independent variable had an effect on the NPF, indicated by the F value of 17,016 and significance of 0,000, overall the independent variable was able to explain the effect of 69.60%. While based on the partial t test, showed that CAR has a significant negative effect, Total assets have a significant positive effect with a significance value below 0.05 (5%). Meanwhile FDR does not affect NPF.

ANALISIS PENGARUH INFLASI, KURS DAN IHSG TERHADAP RETURN REKSA DANA SAHAM PT NIKKO SECURITIES INDONESIA PERIODE 2014-2017

2019 ◽  
Vol 2 (2) ◽  
pp. 103
Author(s):  
Muhammad Rois Rois ◽  
Manarotul Fatati Fatati ◽  
Winda Ihda Magfiroh
Keyword(s):  
Regression Analysis ◽  
Exchange Rate ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Stock Price ◽  
Price Index ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Equity Fund ◽  
Stock Price Index

This study aims to determine the effect of Inflation, Exchange Rate and Composite Stock Price Index (IHSG) to Return of PT Nikko Securities Indonesia Stock Fund period 2014-2017. The study used secondary data obtained through documentation in the form of PT Nikko Securities Indonesia Monthly Net Asset (NAB) report. Data analysis is used with quantitative analysis, multiple linear regression analysis using eviews 9. Population and sample in this research are PT Nikko Securities Indonesia. The result of multiple linear regression analysis was the coefficient of determination (R2) showed the result of 0.123819 or 12%. This means that the Inflation, Exchange Rate and Composite Stock Price Index (IHSG) variables can influence the return of PT Nikko Securities Indonesia's equity fund of 12% and 88% is influenced by other variables. Based on the result of the research, the variables of inflation and exchange rate have a negative and significant effect toward the return of PT Nikko Securities Indonesia's equity fund. While the variable of Composite Stock Price Index (IHSG) has a negative but not significant effect toward Return of Equity Fund of PT Nikko Securities Indonesia

Sign in / Sign up

Export Citation Format

Share Document