Partial Least Squares Method Research Articles

NIR spectra processing for developing efficient protein prediction Model in mungbean

Mung bean is considered one of the significant protein sources with high digestibility; a wide range is observed for protein content in germplasm collections. Near-infrared reflectance spectroscopy (NIRS) is a rapid and non-destructive analytical technique widely used for predicting protein and other nutrients. One hundred and fifty germplasm with a wide range of protein contents (19.7–29.1 %) were selected to build the model. A set of 100 accessions was used for training and validated on the remaining 50 accessions. A systematic comparison of modified partial least squares (mPLS) and partial least squares (PLS) regression techniques with different pre-processing methods (SNV-DT and MSC) and mathematical treatments were carried out. Validation of the calibration equation returned the highest R2 value of 0.940 with mathematical treatment 2882 using mPLS regression, and 0.934 with mathematical treatment 2442 for PLS regression, having ratio prediction deviations (RPD) of 3.84 and 3.59, respectively. Based on the external validation results, the mPLS regression method was found to be superior to the PLS method.

An Empirical Analysis of Cashless Payment Systems for Business Transactions

This paper examines the antecedents of cashless payment systems among businesses in Malaysia. The adoption of cashless payment systems by businesses has the potential to reduce the costs related to handling huge amounts of cash in the market and enhance transaction speed. Unfortunately, its current adoption in Malaysia is still small and very little is known about the factors. A seven-factor model based on the TOE framework was developed and tested. The partial least square (PLS) statistical approach was employed to analyze data collected from 200 business entities in Malaysia. The results reveal that compatibility and technology competence have higher significant relationships with the adoption of cashless payment systems. Management support, firm critical mass, competitive pressure, and information intensity are significantly related to the adoption of cashless payment systems, while firm size is not associated with it. The findings of this study provide significant practical implications for Malaysian stakeholders and technology vendors to recognize factors that affect a firm’s adoption of cashless payment systems to support business transactions. By investigating the phenomenon through the TOE framework, this study presents an integrated model of cashless payment systems by businesses. Our findings also offer guidance for future application of the PLS method in cashless payment and related research. The paper provides a more holistic understanding of the factors influencing cashless payment systems among businesses.

Univariate and Multivariate Determination of Dapagliflozin and Saxagliptin in Bulk and Dosage Form.

Dapagliflozin is a sodium glucose cotransporter-II inhibitor while saxagliptin is a dipeptidyl peptidase-4 inhibitor. Both are used to manage type 2 diabetes mellitus. The aim of this work is to develop four simple, accurate, and precise UV-spectrophotometric methods, three univariate and one multivariate, for the estimation of dapagliflozin and saxagliptin in their pure and marketed dosage forms. Method (A) is based on the ratio difference method; Method (B) is ratio subtraction with constant multiplication; while Method (C) is a second derivative method and Method (D) is a partial least-squares method. The calibration curves for dapagliflozin and saxagliptin were linear within the concentration range of 2.50-50.0 μg/mL and 5.0-60.0 μg/mL, respectively. The specificity of the proposed methods was studied by analyzing different laboratory-prepared mixtures and their combined pharmaceutical dosage form. According to the International Council for Harmonisation guidelines, the three proposed methods were validated regarding the accuracy, precision, and specificity. Method (D), partial least-squares, was employed for the determination of the same mixture over a wavelength range of 205-300 nm. A statistical comparison was performed between the results of the proposed methods and those of a reported spectrophotometric method and no statistically significant difference was detected at 95% confidence limit regarding both precision and accuracy. Four accurate, specific, and precise UV-spectrophotometric methods for dapagliflozin and saxagliptin testing and estimation were successfully utilized and validated. The examined methods are simple and do not involve sophisticated and expensive instruments. They could be effectively employed in quality control laboratories for routine examination of the investigated drugs in their pure powdered or combined pharmaceutical formulations.

An improved method for predicting soluble solids content in apples by heterogeneous transfer learning and near-infrared spectroscopy

Predicting fruit soluble solids content (SSC) is a hot topic in non-destructive detection. Biological variability of fruit decreases the accuracy of the prediction model. Therefore, modeling methods that can reduce the negative effect of biological variability are necessary. In this paper, an improved modeling method based on the partial least squares (PLS) regression was proposed, using convolutional autoencoder and heterogeneous transfer learning for feature extraction. The dataset used for calibration and prediction contains spectra and corresponding SSC values of apples collected from 2012 to 2018. In comparison with the traditional PLS method, the proposed method performed better for long-term SSC prediction of apples with biological variability. The correlation coefficients calculated on validation set were 0.934, 0.940, 0.915, 0.899, 0.901, respectively. The root mean square errors calculated on validation set were 0.736 °Brix, 0.694 °Brix, 0.674 °Brix, 0.571 °Brix, 0.620 °Brix, respectively. Besides, the proposed method could still achieve relatively satisfactory results when the quantity of calibration samples was less.

The Determinants of Purchase Intention on Agricultural Products via Public-Interest Live Streaming for Farmers during COVID-19 Pandemic

In order to sell unmarketable products and alleviate farmers’ economic difficulties caused by the COVID-19 pandemic, public-interest livestreaming for farmers with the property of altruism has been emerging as a new way of mobile commerce and has attracted a huge amount of attention among Chinese consumers. In this paper, based on the theory of reasoned action, we intend to explore the influencing factors from the levels of the platform, product, and consumer that affect consumers’ attitudes and purchase intentions towards agricultural products via public-interest livestreaming. We have collected 475 valid responses from Chinese consumers (especially from youth) who experienced the public-interest livestreaming for farmers and then constructed a structural equation model using the partial least-squares method. The results show that consumers’ attitudes towards agricultural products have a significant positive impact on their purchase intentions with respect to livestreaming. Perceived interactivity, perceived endorsement, product familiarity, subjective norms, altruistic value, and the livestream shopping experience all significantly positively affected consumers’ attitudes toward the agricultural products in the mobile livestreaming. Moreover, subjective norms can also directly impact consumers’ purchase intentions. We can see that the proposed influencing factors from the platform, product, and consumer levels provide a better explanation of the attitudes and purchase intentions, respectively. This paper aims to expand the empirical research on the purchase intentions of agricultural products and then to provide insights into the phenomenon of public-interest livestreaming during COVID-19, which can assist farmers in addressing the dilemma caused by the epidemic and promote rural economic development by mobile commerce. Additionally, the insights from this case study in China can also be extended to other countries where farmers have suffered from the impact of COVID-19.

Economic Development of Indigenous Communities In North Toraja Regency To Face The Digital Marketing Era, Through The Use of Fintech-Based Epayments And Payments

Promotions done by an endorser through social media like Instagram doesn't only use by companies big in activity marketing them, but also can use to promote a product from local MSME brands for increased sale product online. Based on the amount variables and indicators used in research _, the approach sample representative used in the withdrawal sample, so that amount is as many as 80 to 160 respondents. The purposive sampling technique that became part of the non-probability sampling technique will be used for determining the respondents who become the sample. During the research, a set of questionnaires with choice 5 Likert scale answers will be given to the target respondent as the primary data source. After the research data is obtained, the data then will analyze for the validity and reliability test. After the data is found to be valid and reliable, the method of partial least squares (PLS) analysis will use to test the proposed hypothesis. Analysis performed statistics _ includes evaluation of the outer and inner models. The expected results and outcomes of the research produce a reference for the perpetrators MSME business in To do activity businesses that use endorsers as one of the methods for strengthening brand attitude when consumers To do decision online purchases. Research results this is at TKT 2. Results obtained from the study will be published in Accredited National Journal: Journal of Business Economics, State University of Malang Accredited Sinta 4 with p-ISSN: 0853-7283 and e-ISSN: 2528-0503 as outside Mandatory accepted and Journal Management Marketing of Petra Christian University Accredited Sinta 3 with p-ISSN: 1907235X and e-ISSN: 1907235X as outside additions submitted. And the 2021 National Seminar on Management and Business Economics (SNMEB) as an outside Additional.

Reaction Analysis and Process Optimization with Online Infrared Data Based on Kinetic Modeling and Partial Least Squares Quantitation.

In-situ Fourier transform infrared (FT-IR) spectroscopy has been recognized as an important technology for online monitoring of chemical reactions. However, analysis of the real-time IR data for identification and quantification of uncertain reactants or intermediates is often ambiguous and difficult. Here, we propose an analysis algorithm based on reaction kinetic modeling and the chemometric method of partial least squares (PLS) to comprehensively and quantitatively study reaction processes. Concentration profiles and apparent kinetic parameters can be simultaneously calculated from the spectral data, without the demand of complicated analysis on characteristic absorbance peaks or tedious sampling efforts for multivariate modeling. Paal-Knorr reactions and glyoxylic acid synthesis reactions were selected as typical reactions to validate the algorithm. A lack of fit of the Paal-Knorr reaction spectra was less than 2.5% at various conditions, and the absolute errors between the predicted values and HPLC measurement of glyoxylic acid synthesis were less than 6% during the reaction process. Moreover, the reaction kinetic models extracted from FT-IR data were used to simulate reaction processes and optimize the conditions in order to maximize product yields, which proved that this analysis method could be used for process optimization.

Peranan Sumber Daya terhadap Pengembangan Usaha Kemitraan Domba

Regulation of the Minister of Agriculture of the Republic of Indonesia Number 13 of 2017 concerning Animal Husbandry Business Partnerships states that livestock farming business partnerships are cooperation between livestock farming businesses on the basis of the principles of mutual need, strengthening, benefiting, respect, responsibility, and dependence. The purpose of this study was to examine the influence of economical, environmental, and social resources on the development of sheep partnership farming business. The novelty of this research is to review the development of resource-based sheep partnership farming business. The research was conducted on a sheep partnership farming business at Gumukmas Multi Farm (GMF) Jember district. The data collection method was carried out by survey, Focus Group Discussion (FGD), and observation. Research variables include livestock farming business development (Y), economical resources (X1), environmental resources (X2), and social resources (X3). Analysis of research data using the Partial Least Square (PLS) method with the help of SmartPLS 2.0 software. The PLS method generally consists of 2 (two) kinds of test models, namely the outer model and the inner model. The results obtained from the indicator test and declared valid are economical resources consisting of 4 (four) indicators, environmental resources consisting of 2 (two) indicators, and social resources consisting of 6 (six) indicators. The conclusion shows that economical resources, environmental resources, and social resources are quite influential on the development of sheep farming partnerships with an R2 value of 45.1%

The Effect Of Work Environment On Employee Performance Through Motivation And Job Satisfaction As Intervening Variables On Permanent Employees

The issue is that employees' expectations of the organization in terms of rewards in the form of pay, benefits, and development to keep up with the flow of progress are still insufficient, and employees have a longer extension time. The purpose of this study is to investigate the impact of the work environment on employee performance using motivation and job satisfaction as intervening variables. The Partial Least Square (PLS) method will be used to analyze the data used to test this research. Previous research which has similarities with this study in terms of the number of variables and the presence of intervening variables is one of the basic references. Researchers chose to use the PLS method that the work environment has significant effect on motivation and the hypothesis is accepted, the work environment has a significant effect on job satisfaction and the hypothesis is accepted, motivation has a significant effect on employee performance and the hypothesis is rejected, job satisfaction has not significant effect on employee performance and the hypothesis is rejected, and the work environment has a significant effect on employee performance and the acceptance hypothesis, and through research indirectly results that the work environment has not significant effect on employee performance through motivation and the hypothesis is rejected, and the work environment has not significant effect on employee performance through employee satisfaction and the hypothesis is rejected, is expected to have a dominant influence so that every employee has the awareness to cultivate a good attitude in the work environment. According to the research, substantial motivation is required, such as providing staff promotions, to boost employee happiness and performance in the organization.

The Effect Of Work Environment On Employee Performance Through Motivation And Job Satisfaction As Intervening Variables On Permanent Employees

The issue is that employees' expectations of the organization in terms of rewards in the form of pay, benefits, and development to keep up with the flow of progress are still insufficient, and employees have a longer extension time. The purpose of this study is to investigate the impact of the work environment on employee performance using motivation and job satisfaction as intervening variables. The Partial Least Square (PLS) method will be used to analyze the data used to test this research. Previous research which has similarities with this study in terms of the number of variables and the presence of intervening variables is one of the basic references. Researchers chose to use the PLS method that the work environment has significant effect on motivation and the hypothesis is accepted, the work environment has a significant effect on job satisfaction and the hypothesis is accepted, motivation has a significant effect on employee performance and the hypothesis is rejected, job satisfaction has not significant effect on employee performance and the hypothesis is rejected, and the work environment has a significant effect on employee performance and the acceptance hypothesis, and through research indirectly results that the work environment has not significant effect on employee performance through motivation and the hypothesis is rejected, and the work environment has not significant effect on employee performance through employee satisfaction and the hypothesis is rejected, is expected to have a dominant influence so that every employee has the awareness to cultivate a good attitude in the work environment. According to the research, substantial motivation is required, such as providing staff promotions, to boost employee happiness and performance in the organization.

The Multidimensional Vaccine Hesitancy Scale: A Validation Study.

Vaccination hesitancy (VH) is a phenomenon which increases the occurrence of vaccine-preventable diseases. The study tests the validity of the Multidimensional Vaccine Hesitancy Scale (MVHS) in the case of a sample of Romanian adults (n = 528; Meanage = 30.57). The latter filled in an online cross-sectional survey. The construct validity of MVHS was assessed by using confirmatory factor analysis (CFA), the reliability was calculated by using the internal consistency, and the convergent and discriminant validity was assessed by using the composite reliability (CR), and average variance extracted (AVE). The obtained model was invariant across gender. The structural equation model was designed for predictive validity by using the partial least square method (PLS-SEM) which analyses the relation between the MVHS dimensions and the vaccination willingness. The results show support for the 8-factor structure of the scale (χ2/df = 2.48; CFI = 0.95; RMSEA = 0.053). The Cronbach’s coefficients α > 0.70; McDonald’s ω > 0.70 and CR > 0.80 have very good values. The structural equation model shows that there are more dimensions of the scale which predict vaccination hesitancy in various types of vaccines—the main predictors remain the dimensions of health risk and healthy condition. The study’s conclusion led to the idea that the MVHS is suitable for medical practice and for research on the analysis of vaccination behaviours and intentions.

Applications of mobile learning on college students' water leisure sports in the post-pandemic era.

This study explored the relationship and influence of college students’ participation in water leisure sports, as well as the technology acceptance model (TAM). With the rapid development of the economy, the government is promoting various water leisure sports centered on the concept and policy of a maritime- and ocean-based nation. Based on the TAM, this study investigated the relationships among its ease of use, usefulness, water leisure involvement, benefits, barriers, and intentions to participate in water activities in connection with college students participating in water leisure sports. A total of 420 college students who participated in water leisure activities were sampled. There were 370 valid questionnaires, and the recovery rate of valid questionnaires was 82.2%. The data were analyzed by the structural equation modeling of the partial least squares method (PLS-SEM). The results show that the ease of use of water facilities had a positive effect on the usefulness, involvement, and participation in water activities; the usefulness of water facilities had a positive and significant impact on the intention to participate in water activities; water leisure involvement had a positive and significant impact on the benefits and the intention to participate in water activities; the intention to participate in water activities had a positive and significant impact on the benefits of water leisure activities. Furthermore, the study found that the intention to participate in water activities had a mediating effect between water leisure involvement and water leisure benefits; water leisure involvement had a mediating effect between the ease of use of water facilities and the intention to participate in water activities; the usefulness of water facilities had a mediating effect between the ease of use of water facilities and the intention to participate in water activities. In addition, the interaction between water leisure involvement and water leisure constraints had an interfering effect on water leisure benefits. Accordingly, recommendations for promotion and implementation are provided. Based on the TAM, the study provided suggestions for implementing water leisure sports to promote college students’ participation behavior in water leisure sports.

Hyperspectral Inversion of Soil Carbon and Nutrient Contents in the Yellow River Delta Wetland

Hyperspectral inversion techniques can facilitate soil quality monitoring and evaluation. In this study, the Yellow River Delta Wetland Nature Reserve was used as the study area. By measuring and analyzing soil samples under different vegetation types and collecting soil reflectance spectra, the relationships between vegetation types, soil depth, and the changes in soil total carbon (TC), total nitrogen (TN), and total phosphorus (TP) contents were assessed. The spectral data set was changed by spectral first derivative processing and division of the sample set according to vegetation type. The correlation between soil carbon, nitrogen, and phosphorus contents, and soil spectra was also analyzed, sensitive bands were selected, and the partial least-squares (PLS) method, support vector machine (SVM) method, and random forest (RF) model were used to establish the inversion model based on the characteristic bands. The optimal combination of spectral transformation, sample set partitioning, and inversion model was explored. The results showed significant differences (p < 0.05) in soil TC, TN, and TP contents under reed and saline alkali poncho vegetation, but not between soil element contents under different stratifications of the same plant species. The first derivative reflectance had higher correlation coefficients with soil TC, TN, and TP contents compared with the original reflectance, while the sensitive bands and quantities of the three elements differed. The division of the sample sets according to vegetation type and the first derivative treatment can improve the prediction accuracy of the model. The best combination of sample set plus FD plus RF for TC, TN, and TP in reed soil and sample set plus FD plus SVM for TC, TN, and TP in saline alkali pine soil provides technical support to further improve the prediction accuracy of TC, TN, and TP in wetland soil.

Gender Differences in Oral Health: Self-Reported Attitudes, Values, Behaviours and Literacy among Romanian Adults.

A topic that has been less researched on, especially in Romania, is the identification of gender differences in oral health. The present scientific research used an online survey to assess the attitudes (dental beliefs survey-R/R-DBS), the values (oral health values scale/OHVS), the behaviours (dental neglect scale/DNS), and the literacy (oral health literacy scale/OHLS) related to oral health and to dental professional services in the case of a sample of 600 Romanian adults (Meanage = 30.84). The relation between the level of knowledge as a predictor of attitudes and values related to oral health was analysed by the means of a structural equation based on the partial least square method (PLS-SEM). The results show that women have more positive attitudes towards dental medical services, higher oral health values, better self-care behaviours, and higher oral health literacy than men. In the case of men, attitudes and behaviours related to self-care are influenced by their oral health literacy and level of education; in the case of women, the latter are influenced only by their level of oral health literacy. The impact that knowledge in oral health has on attitudes, values, and behaviours was highlighted. The differences in attitudes and values related to oral health between the two genders can be accounted for by the differences in formal and informal education (studies and oral health literacy, respectively).

592. CLINICAL EVALUATION OF A HYPERSPECTRAL IMAGING SYSTEM FOR MINIMALLY INVASIVE SURGERY (HSI-MIS)

Abstract Hyperspectral Imaging (HSI) provides surgeons intraoperative colored images of abdominal organgs detecting the perfusion and oxygenation. Limiting factors such as missing colour video, camera size, and long acquisition times have been overcome in the first CE-certified HSI-System for Minimally-Invasive Surgery (HSI-MIS; TIVITA® Mini Endoscopy Edition, Diaspective Vision GmbH, Am Salzhaff, Germany). This system was evaluated in-vivo during surgery and compared with an HSI-System for Open Surgery (TIVITA® Tissue, Diaspective Vision GmbH, Am Salzhaff, Germany). Hyperspectral imaging was performed with both the HSI-MIS and the HSI-System for Open Surgery at the Region of Interest. 19 patients undergoing gastroenterologic resections were included in the study. The images acquired with the HSI-MIS were registered onto the images from the open HSI system, and spectra, as well as parameter images, were pixel-wise compared. Violin plots were created for Tissue Oxygen Saturation (StO2), Near-Infrared Perfusion Index (NIR PI), Tissue Water Index (TWI) and Organ Hemoglobin Index (OHI). The raw data was analyzed using a partial least squares (PLS) and compared with the parameters as calculated by the original software The MAE results for the in-vivo evaluation were: StO2: 17.4% ± 7.6%, NIR PI: 16.3 ± 9.4, OHI: 14.3 ± 4.5, and TWI: 18.3 ± 7.8. The results obtained by PLS were StO2: 11.1% ± 3.9% (improved by 36%), NIR PI: 9.5 ± 5.8 (improved by 42%), OHI: 10.7 ± 2.7 (improved by 25%) and TWI: 9.6 ± 4.3 (improved by 48%) Laparoscopic hyperspectral imaging during minimally invasive procedures shows promising results. Parameter deviations might be attributable to technical differences and on how the parameters are calculated. The PLS method has shown significant improvement compared to the original calculation.

Critical factors to improve customer satisfaction and reduce operating costs in large and medium-sized manufacturing companies in Nuevo León and the impact caused by the COVID pandemic

<p>The objective of this document is to determine how transportation, trained personnel, customs procedures, preventive maintenance and inventory reliability impact customer satisfaction and operating costs in large and medium-sized companies in the State of Nuevo Leon, Mexico; Likewise, how they were affected by the pandemic caused by COVID. To carry out this research, a measurement instrument was developed, being of a non-experimental, descriptive and longitudinal type, where the results are first evaluated before the pandemic and after the presence of COVID. To analyze the collected information, the structural equation model was used with the method of partial least squares with the SmartPLS3 software. The results are initially presented globally, and later two groups were formed by type of company, those with Mexican and foreign capital; In this way, the approaches of each group and the impact of the factors on the response variables can be evaluated. The results presented in this article are expected to guide companies to improve customer satisfaction and reduce operating costs with and without a pandemic.</p>

Estimation of rock copper content based on Fractional-order derivative and visible Near-infrared–Shortwave infrared spectroscopy

Rock geochemistry can accurately and effectively delineate geological anomalies, providing clear instructions for geological prospecting and playing a crucial role in mineral resource exploration. However, traditional geochemical exploration methods are based on ground sampling and laboratory chemical analysis, which are time-consuming, laborious, and inefficient. This study collected 191 rock samples, and the Cu content and spectral data were obtained using chemical analysis and an analytical spectral device (fieldspec3, portable spectrometer) in the laboratory. However, spectral preprocessing and estimation models are critical for estimation accuracy. Therefore, this study discusses the potential of fractional derivative spectroscopy and a model method for estimating rock Cu content. The results show the following. (1) Compared with the original spectrum and the integer-order derivative spectrum (first and second derivative), the fractional-order derivatives (FODs) can better highlight the spectral details. With the increased order of derivatives, the characteristic band becomes more obvious. (2) The combined FOD and random forest (RF) model performs best for the full sample data. The coefficient of determination (R2) is as high as 0.766, the mean absolute error (MAE), and the ratio of the performance to deviation (RPD) are 9.09 and 2.067, respectively, significantly better than partial least squares (PLS) models (R2 = 0.598, MAE = 13.389, RPD = 1.577) and the K-nearest neighbor (KNN) algorithm (R2 = 0.686, MAE = 10.905, RPD = 1.786). (3) For the samples with Cu content less than 45 mg/kg, using the PLS method and samples with Cu content greater than 45 mg/kg and the RF method to build the estimation model achieved better overall results (R2 = 0.881, MAE = 6.697, RPD = 2.899). Therefore, combining FOD technology and the segmental modeling method can effectively and quickly estimate the Cu content in rocks, providing technical support for estimating Cu content in rocks from aerial imaging hyperspectral images.

A new predictive model for the concurrent risk of diabetic retinopathy in type 2 diabetes patients and the effect of metformin on amino acids.

This study established a model to predict the risk of diabetic retinopathy (DR) with amino acids selected by partial least squares (PLS) method, and evaluated the effect of metformin on the effect of amino acids on DR in the model. In Jinzhou, Liaoning Province, China, we retrieved 1031 patients with type 2 diabetes (T2D) from the First Affiliated Hospital of Liaoning Medical University. After sorting the amino acids using the PLS method, the top 10 amino acids were included in the model. Multivariate logistic regression was used to analyze the relationship between different amino acids and DR. And then the effects of metformin on amino acids were explored through interaction. Finally, Spearman's rank correlation analysis was used to analyze the correlation between different amino acids. After sorting by PLS, Gly, Pro, Leu, Lyr, Glu, Phe, Tyr, His, Val and Ser were finally included in the DR risk prediction model. The predictive model after adding amino acids was statistically different from the model that only included traditional risk factors (p=0.001). Metformin had a significant effect on the relationship between DR and 7 amino acids (Gly, Glu, Phe, Tyr, His, Val, Ser, p<0.05), and the population who are not using metformin and have high levels of Glu (OR: 0.44, 95%CI: 0.27-0.71) had an additive protection effect for the occurrence of DR. And the similar results can be seen in high levels of Gly (OR: 0.46, 95%CI: 0.29-0.75), Leu (OR: 0.48, 95%CI: 0.29-0.8), His (OR: 0.46, 95%CI: 0.29-0.75), Phe (OR: 0.24, 95%CI: 0.14-0.42) and Tyr (OR: 0.41, 95%CI: 0.24 -0.68) in population who are not using metformin. We established a prediction model of DR by amino acids and found that the use of metformin reduced the protective effect of amino acids on DR developing, suggesting that amino acids as biomarkers for predicting DR would be affected by metformin use.

Walking exercise alters pedunculopontine nucleus connectivity in Parkinson’s disease in a dose-dependent manner

BackgroundGait disturbances are critical motor symptoms in Parkinson’s disease (PD). The mechanisms of gait impairment in PD are not entirely understood but likely involve changes in the Pedunculopontine Nucleus (PPN), a critical locomotion center, and its associated connections. Exercise is universally accepted as helpful in PD, but the extent and intensity of exercise required for plastic changes are unclear.MethodsTwenty-seven PD subjects participated in a 3-month gait training intervention. Clinical assessments and resting-state functional magnetic resonance imaging were performed at baseline and 3 months after exercise. Functional connectivity of PPN was assessed by combining the methods of partial least squares, conditional dependence and partial correlation. In addition, paired t-tests were used to examine the effect of exercise on PPN functional connectivity and clinical measures, and Pearson’s correlation was used to assess the association between altered PPN functional connectivity and clinical measures.ResultsExercise significantly improved Unified Parkinson’s Disease Rating Scale-III (UPDRS-III). A significant increase in right PPN functional connectivity was observed after exercise, which did not correlate with motor improvement. However, the decrease in left PPN functional connectivity significantly correlated with the improvement in UPDRS-III and was linearly related to both number of walks and the duration of walks. In addition, exercise induced a significant increase in the laterality of PPN connectivity strength, which correlated with motor improvement.ConclusionPPN functional connectivity is modifiable by walking exercise in both a dose-independent (right PPN and laterality of PPN connectivity strength) and dose-dependent (left PPN) manner. The PPN may contribute to pathological and compensatory processes in PD gait control. The observed gait improvement by walking exercise is most likely due to the reversal of the maladaptive compensatory mechanism. Altered PPN functional connectivity can be a marker for exercise-induced motor improvement in PD.

Spectrum effect correlation of yangyin tongnao granules on cerebral ischemia-reperfusion injury rats.

Yangyin Tongnao Granules (YYTNG), as traditional Chinese medicine (TCM) compound preparation, have a good curative effect on cerebral ischemia-reperfusion injury. This study aimed to investigate the relationship between the active components of YYTNG in the plasma and the inflammatory response in cerebral ischemia-reperfusion injury rats. High-performance liquid chromatography (HPLC) was conducted to determine the fingerprints at different time points of middle cerebral artery occlusion (MCAO) rats after the administration of YYTNG at different times points. Enzyme-linked immunosorbent assay (ELISA) was performed to detect the levels of interleukin-18 (IL-18) and tumor necrosis factor-α (TNF-α) in the plasma of MCAO rats at different time points. The spectral-effect relationship between the YYTNG fingerprints and inflammatory indexes in vivo was established by combining three different mathematical models, grey correlation, multiple linear regression, and partial least-square method. The results revealed that each chromatographic peak in the HPLC of the plasma exhibited a certain correlation with the inflammatory index, in the following order: P2 >P6 >P5 >P1 >P3 >P4. Therefore, this study successfully established the spectrum-effect correlation of YYTNG on cerebral ischemia-reperfusion injury rats. The results provide a certain guiding ideology for the analyses of the relationship between fingerprints and the pharmacodynamics of TCM prescriptions.