High-Throughput Quantitative Biochemical Characterization of Algal Biomass by NIR Spectroscopy; Multiple Linear Regression and Multivariate Linear Regression Analysis

2013 ◽  
Vol 61 (50) ◽  
pp. 12307-12314 ◽  
Author(s):  
L. M. L. Laurens ◽  
E. J. Wolfrum
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
High Throughput ◽  
Algal Biomass ◽  
Biochemical Characterization ◽  
Linear Regression Analysis ◽  
Nir Spectroscopy ◽  
Multivariate Linear Regression Analysis

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

Correlation between FA and ADC, number and length of the periprostatic neurovascular fibers

2021 ◽  
pp. 039156032110637
Author(s):  
Valerio Di Paola ◽  
Angelo Totaro ◽  
Giacomo Avesani ◽  
Benedetta Gui ◽  
Andrea Boni ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Negative Correlation ◽  
Multivariate Regression ◽  
Linear Regression Analysis ◽  
Multivariate Linear Regression ◽  
Multivariate Linear Regression Analysis ◽  
Independent Variables ◽  
Fiber Tracts ◽  
Good Agreement

Purpose: Our aim was to explore the relation between FA and ADC, number and length of the periprostatic neurovascular fibers (PNF) by means of 1.5 T Diffusion Tensor Imaging (DTI) imaging through a multivariate linear regression analysis model. Methods: For this retrospective study, 56 patients (mean age 63.5 years), who underwent 1.5-T prostate MRI, including DTI, were enrolled between October 2014 and December 2018. Multivariate regression analysis was performed to evaluate the statistically significant correlation between FA values (dependent variable) and ADC, the number and the length of PNF (independent variables), if p-value <0.05. A value of 0.5 indicated poor agreement; 0.5–0.75, moderate agreement; 0.75–0.9, good agreement; 0.61–0.80, good agreement; and 0.9–1.00, excellent agreement. Results: The overall fit of the multivariate regression model was excellent, with R2 value of 0.9445 ( R2 adjusted 0.9412; p < 0.0001). Multivariate linear regression analysis showed a statistically significant correlation ( p < 0.05) for all the three independent variables. The r partial value was −0.9612 for ADC values ( p < 0.0001), suggesting a strong negative correlation, 0.4317 for the number of fiber tracts ( p < 0.001), suggesting a moderate positive correlation, and −0.306 for the length of the fiber tracts ( p < 0.05), suggesting a weak negative correlation. Conclusions: Our multivariate linear regression model has demonstrated a statistically significant correlation between FA values of PNF with other DTI parameters, in particular with ADC.

QSAR Docking on Azoles as inhibitors of Notum carboxylesterase

2021 ◽  
Vol 15 ◽  
Author(s):  
Amuthalakshmi Sivaperuman ◽  
Ramalakshmi Natarajan ◽  
Manimegalai P ◽  
Arunkumar Subramani ◽  
Puratchikody Ayarivan
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Wnt Signaling ◽  
Multiple Linear Regression ◽  
Inhibitory Activity ◽  
Linear Regression Analysis ◽  
External Validation ◽  
Negative Regulator ◽  
Qsar Analysis ◽  
Wnt Proteins

Background: Carboxylesterase Notum is a negative regulator of Wnt signaling. Notum carboxylesterase is a carboxylic ester hydrolase enzyme that functions as a negative feedback regulator of Wnt proteins by depalmitoylation reaction. It is of great importance to understand the pathway of Wnt regulation because, conversely, misregulation of Wnt signaling is a telltale sign of cancer and other degenerative diseases. The Wnt inhibition is important in the control of colorectal cancer. Objective: In the present study, we carried out a QSAR analysis of a series of reported compounds with carboxylesterase Notum inhibitory activity using multiple regression analysis. A series of 83 compound datasets of pyrrole derivatives with carboxy Notum inhibitory values were taken from the reported literature. Methods: The study was performed by conducting multiple linear regression analysis followed by validation of the model. The multiple linear regression (MLR) models with the highest coefficients of correlation (R2) and explained variance in leave-one-out (Q2 LOO) prediction and leave-many-out (Q2 LMO) were selected for the whole dataset. The developed models were subjected to internal and external validation. The reliability of the predicted model was checked by plotting the Williams plot. The docking methodology was performed using Autodock 4 for the designed compounds to study the interaction between the ligand and the receptor. Results: The best model generated exhibited an r2 value of 0.7413, Q2LOO =0.6379, Q2LMO =0.6368. Novel compounds of phenyl pyrrolidine were designed based on generated QSAR equations. The carboxylesterase Notum inhibitory activity was predicted using the QSAR equations. The docking studies were carried out for designed compounds using Autodock against Carboxylesterase Notum esterase. Conclusion: From the results, the designed compounds were found to inhibit Notum Carboxylase. Thus, the study led to the development of a novel lead compound for Carboxylesterase Notum.

scholarly journals The Association of Circulating MiR-29b and Interleukin-6 with Subclinical Atherosclerosis

2017 ◽  
Vol 44 (4) ◽  
pp. 1537-1544 ◽  
Author(s):  
Yu-qing Huang ◽  
Jie Li ◽  
Ji-yan Chen ◽  
Ying-ling Zhou ◽  
An-ping Cai ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Interleukin 6 ◽  
Subclinical Atherosclerosis ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Control Group ◽  
Study Group ◽  
Circulating Levels

Background/Aims: Although it is widely acknowledged that atherosclerosis is mainly a chronic inflammatory process, in which both miR-29b and interleukin-6 (IL-6) play multifaceted roles, the association between miR-29b and IL-6 remains unknown. The aim of the present study was to explore the relationship between miR-29b and IL-6 and to test whether circulating levels of miR-29b and IL-6 could predict atherosclerosis. Methods: A total of 170 participants were divided into two groups according to carotid intima-media thickness (CIMT): study group (CIMT ≥ 0.9mm) and control group (CIMT < 0.9mm). Levels of circulating miR-29b and IL-6 were measured by quantitative real-time polymerase chain reaction (qRT-PCR) and enzyme-linked immunosorbent assay (ELISA), respectively. The association of miR-29b and IL-6 levels with CIMT was assessed using Spearman correlation analysis and multiple linear regression analysis. Results: The study group showed higher miR-29b levels (31.61 ± 3.05 vs. 27.91 ± 1.71 Ct, p < 0.001) and IL-6 levels (3.40 ± 0.67 vs. 2.99 ± 0.37 pg/ml, p < 0.001), compared with the control group. CIMT was positively correlated with miR-29b (r = 0.587, p < 0.001) and IL-6 (r = 0.410, p < 0.001), and miR-29b levels were also correlated with IL-6 (r = 0.242, p = 0.001). Multiple linear regression analysis also showed that CIMT was positively correlated with miR-29b and IL-6. After adjustment for age, body mass index, systolic blood pressure, total cholesterol and C-reactive protein, CIMT was still closely correlated with miR-29b and IL-6. The combination of miR-29b and IL-6 (AUC = 0.901, p < 0.001) offered a better predictive index for atherosclerosis than either miR-29b (AUC = 0.867, p < 0.001) or IL-6 (AUC = 0.747, p < 0.001) alone. Conclusion: Circulating levels of miR-29b and IL-6 may be independently correlated with subclinical atherosclerosis, and may serve as novel biomarkers for the identification of atherosclerosis.

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