Several Issues Concerning the Use of Bifactor Model in Understanding Dimensionality

The goals of the study are to investigate the use of bifactor models in understanding dimensionality and to demonstrate several issues that arise from its applications. The bifactor analysis is available for about 80 years, and it is lately argued that the bifactor model is superior to its competitors in many aspects of studying dimensionality. The bifactor model is currently widely applied to examine both old and new concepts against second-order factor model/multiple factor models in many fields. Despite its widespread use and many advantages, the bifactor analysis is not well understood, and the latest techniques developed for it are not endorsed by applied researchers. The misunderstandings had led to both methodological challenges and practical erroneousness which resulted in fallacious conclusions. The present study attempts to demonstrate several critical issues concerning bifactor favoring model fit bias, three exploratory bifactor analytics (S-L transformation, J-B analytics, and target rotation), and oblique versus orthogonal bifactor representations by using three real data. Substantively, the present study will potentially advance the understandings of the three constructs under review as well as their relations to external variables. Methodologically, the present research broadens the literature in clarifying the current issues regarding bifactor analysis, and hopefully, this study will enlighten the applied researchers on the latest techniques. Results from the current study showed that the confirmatory bifactor model has a better fit than its nested second-order factor model or multiple factor models across the three studies which conform with previous findings. Whether a bifactor model will always fit better is still under investigation. Several researchers have dedicated their work to identify the source of the bias, and a consolidated explanation is yet to find. However, it is warned that researchers shall not rely on model fit as the sole criterion in determining the champion between the two. Results from the first study also showed that the three exploratory bifactor analytics do not agree in the presence of cross-loadings. Specifically, unexpected patterns are observed with the orthogonal J-B solution and the oblique target rotation solution. The former has produced a distorted group factor with which three out of 6 of its loadings are smaller than .30, and two negative loadings cross-loaded. The latter has generated a weak and partially defined general factor with which seven out of 24 of its loadings are smaller than .40 and three of them lower than .30. The results might indicate that orthogonal J-B analytic and oblique target rotation methods are inadequate at recovering complexities (e.g., the presence of cross-loaded items). With the second study, a surprising factor pattern is observed, in which a second general factor runs through all the items but with half negative loadings. This unexpected pattern might represent a special case of the “group factor collapsing onto general factor” problem that is specific to the J-B analytic. The current findings also suggest that oblique solution tends to introduce a higher level general factor to account for the group factor intercorrelations which complicates the model and results in difficulties in interpretation. The bifactor model is found especially useful with two-dimensional data where a second-order model is not identifiable. The model-based indices such as omega hierarchical, ECV, FD, and H are helpful in assessing the strength of the general factor, and it is recommended to report them in applied researches. Worth mentioning is that they might be subject to model misspecifications. Besides, item cluster analysis seems to be useful in discovering departure from the perfect independent structure of multidimensional data. It is recommended to perform exploratory factor analysis as a preliminary exploration before conducting the exploratory bifactor analysis. Recommendations and insights for future studies follow discussions on the issues

Integration of Kinetic Analysis of Reaction Curve with a Proper Classical Approach for Enzymatic Analysis

For enzymatic analysis to quantify a substrate or enzyme, kinetic analysis of reaction curve can be integrated with a proper classical approach. For their integration, they should have consistent slopes and intercepts of linear response and an overlapped region of analyte quantities measurable under optimized conditions. To quantify a substrate after optimizations of tool enzyme activity and reaction duration, the equilibrium method works when the reaction is completed within the reaction duration; otherwise, kinetic analysis of reaction curve applies providing at least seven data with sufficient consumption of substrate. To quantify an enzyme after optimizations of initial substrate concentration and reaction duration, the classical initial rate method works when an estimated initial rate locates within the linear range; otherwise, kinetic analysis of reaction curve applies after the conversion of the quantification index with optimized parameters. This integration strategy has ideal linear ranges and practical efficiency for quantifying an enzyme at moderate substrate levels and for quantifying a substrate at moderate cost on tool enzyme; it has promise to simultaneous assays of multiple enzymes in one reaction vessel each time and ,thus, potential applications to concurrently quantify multiple serum enzymes, screen inhibitors against multiple enzyme targets, and detect multiple serum components by enzymeimmunoassay

Data for High-Throughput Estimation of Specific Activities of Enzyme/Mutants in Cell Lysates Through Immunoturbidimetric Assay of Proteins

Data in this article are associated with the research article “Highthroughput estimation of specific activities of enzyme/mutants in cell lysates through immunoturbidimetric assay of proteins” (Yang et al., 2017) [1]. This article provided data on how to develop an immunoturbidimetric assay (ITA) of enzyme/mutants as proteins in cell lysates in high-throughput (HTP) mode together with HTP assay of their activities to derive their specific activities in cell lysates for comparison, with Pseudomonas aeruginosa arylsulfatase (PAAS) and Bacillus fastidious uricase (BFU) plus their mutants as models. Data were made publicly available for further analyses

Estimation of affinities of ligands in mixtures via magnetic recovery of target-ligand complexes and chromatographic analyses: chemometrics and an experimental model

<p>Abstract</p> <p>Background</p> <p>The combinatorial library strategy of using multiple candidate ligands in mixtures as library members is ideal in terms of cost and efficiency, but needs special screening methods to estimate the affinities of candidate ligands in such mixtures. Herein, a new method to screen candidate ligands present in unknown molar quantities in mixtures was investigated.</p> <p>Results</p> <p>The proposed method involves preparing a processed-mixture-for-screening (PMFS) with each mixture sample and an exogenous reference ligand, initiating competitive binding among ligands from the PMFS to a target immobilized on magnetic particles, recovering target-ligand complexes in equilibrium by magnetic force, extracting and concentrating bound ligands, and analyzing ligands in the PMFS and the concentrated extract by chromatography. The relative affinity of each candidate ligand to its reference ligand is estimated <it>via </it>an approximation equation assuming (a) the candidate ligand and its reference ligand bind to the same site(s) on the target, (b) their chromatographic peak areas are over five times their intercepts of linear response but within their linear ranges, (c) their binding ratios are below 10%. These prerequisites are met by optimizing primarily the quantity of the target used and the PMFS composition ratio.</p> <p>The new method was tested using the competitive binding of biotin derivatives from mixtures to streptavidin immobilized on magnetic particles as a model. Each mixture sample containing a limited number of candidate biotin derivatives with moderate differences in their molar quantities were prepared <it>via </it>parallel-combinatorial-synthesis (PCS) without purification, or <it>via </it>the pooling of individual compounds. Some purified biotin derivatives were used as reference ligands. This method showed resistance to variations in chromatographic quantification sensitivity and concentration ratios; optimized conditions to validate the approximation equation could be applied to different mixture samples. Relative affinities of candidate biotin derivatives with unknown molar quantities in each mixture sample were consistent with those estimated by a homogenous method using their purified counterparts as samples.</p> <p>Conclusions</p> <p>This new method is robust and effective for each mixture possessing a limited number of candidate ligands whose molar quantities have moderate differences, and its integration with PCS has promise to routinely practice the mixture-based library strategy.</p

Modeling habitat suitability for Yunnan Snub-nosed monkeys in Laojun Mountain National Park

We provide new information on Yunnan snub-nosed monkey (Rhinopithecus bieti) behavioral ecology, contributing to future conservation efforts within the Laojun Mountain National Park. Habitat evaluation procedures are used to quantify the value of land as a habitat for a species. We analyzed environmental variables hypothesized to influence habitat suitability for Yunnan snub-nosed monkeys, and mapped the distribution of suitable habitats across the study area and adjacent areas. Spatial analysis with GPS data was conducted to investigate home-range change of these monkeys. Predictor variables were generated using ArcMap and R programming language. We prepared 34 environmental variables at 30-m spatial resolution. Maxent was used to analyze environmental variables that contributed to suitability. Using satellite remote sensing and GIS, we modeled the distribution of suitable habitat for Yunnan snub-nosed monkeys in the Jinsichang area of the Laojun Mountains in China. This study did not describe the frequency or intensity of habitat use. Habitat suitability was affected by several variables, the most influential, as determined by permutation importance, being mean diurnal temperature range (31.6%), precipitation during the wettest quarter of the year (30.4%), average annual precipitation (17%), normalized difference vegetation index (5%), wetness (4.6%), and aspect (4.5%). This habitat suitability model provides information about the current distribution of Yunnan snub-nosed monkeys, which is important for appropriate implementation of conservation actions

Persistent fifth aortic arch: a comprehensive literature review

Persistent fifth aortic arch (PFAA) is an extremely rare congenital cardiovascular anomaly resulting from the failure of the fifth aortic arch to degenerate during embryonic development; it is often associated with various other cardiovascular anomalies. Despite being first reported by Van Praagh in 1969, there have been only a few individual case reports. Owing to its rarity and lack of comprehensive understanding, PFAA is often misdiagnosed or missed diagnosed during clinical. Thus, this review aimed to summarise the embryonic development, pathological classification, imaging diagnosis, and clinical treatment of PFAA to improve its overall understanding, ultimately helping in accurate diagnosis and treatment

Extracorporeal Delivery of a Therapeutic Enzyme

To remove circulating harmful small biochemical(s)/substrates causing/deteriorating certain chronic disease, therapeutic enzyme(s) delivered via vein injection/infusion suffer(s) from immunoresponse after repeated administration at proper intervals for a long time and short half-lives since delivery. Accordingly, a novel, generally-applicable extracorporeal delivery of a therapeutic enzyme is proposed, by refitting a conventional hemodialysis device bearing a dialyzer, two pumps and connecting tubes, to build a routine extracorporeal blood circuit but a minimal dialysate circuit closed to circulate the therapeutic enzyme in dialysate. A special quantitative index was derived to reflect pharmacological action and thus pharmacodynamics of the delivered enzyme. With hyperuricemic blood in vitro and hyperuricemic geese, a native uricase via extracorporeal delivery was active in the dialysate for periods much longer than that in vivo through vein injection, and exhibited the expected pharmacodynamics to remove uric acid in hyperuricemic blood in vitro and multiple forms of uric acid in hyperuricemic geese. Therefore, the extracorporeal delivery approach of therapeutic enzymes was effective to remove unwanted circulating small biochemical(s)/substrates, and was expected to avoid immunogenicity problems of therapeutic enzymes after repeated administration at proper intervals for a long time due to no contacts with macromolecules and cells in the body

Gut microbiota alterations are associated with functional outcomes in patients of acute ischemic stroke with non-alcoholic fatty liver disease

IntroductionPatients with acute ischemic stroke (AIS) with non-alcoholic fatty liver disease (NAFLD) frequently have poor prognosis. Many evidences suggested that the changes in gut microbiota may play an important role in the occurrence and development of AIS patients with NAFLD. The purpose of this study was to explore microbial characteristics in patients of AIS with NAFLD, and the correlation between gut microbiota and functional outcomes.MethodsThe patients of AIS were recruited and divided into NAFLD group and non-NAFLD group. The stool samples and clinical information were collected. 16 s rRNA sequencing was used to analyze the characteristics of gut microbiota. The patients of AIS with NAFLD were followed-up to evaluate the functional outcomes of disease. The adverse outcomes were determined by modified Rankin scale (mRS) scores at 3 months after stroke. The diagnostic performance of microbial marker in predicting adverse outcomes was assessed by recipient operating characteristic (ROC) curves.ResultsOur results showed that the composition of gut microbiota between non-NAFLD group and NAFLD group were different. The characteristic bacteria in the patients of AIS with NAFLD was that the relative abundance of Dorea, Dialister, Intestinibacter and Flavonifractor were decreased, while the relative abundance of Enorma was increased. Moreover, the characteristic microbiota was correlated with many clinical parameters, such as mRS scores, mean arterial pressure and fasting blood glucose level. In addition, ROC models based on the characteristic microbiota or the combination of characteristic microbiota with independent risk factors could distinguish functional dependence patients and functional independence patients in AIS with NAFLD (area under curve is 0.765 and 0.882 respectively).ConclusionThese findings revealed the microbial characteristics in patients of AIS with NAFLD, and further demonstrated the predictive capability of characteristic microbiota for adverse outcomes in patients of AIS with NAFLD