Analysis by structural equation modeling of the questionnaire about the risk and its preventive measures in a pharmacy

Pharmacists are now facing a problem of developing measures for dispensing mistakes, because there recently is increasing social awareness on medical accidents and a tendency to increase medical accidents in pharmacies due to popularizing separation of dispensing and prescribing functions. In this study, questionnaire survey was conducted to investigate pharmacist's views on human error measures and the relationship between mistakes and the preventive measures. To clarify relationship between human error measures and preventive measures for avoiding mistakes, questionnaire result was analyzed based on structural equation modeling (SEM). Questionnaire survey was sent to community pharmacies in Hokkaido. The result was analyzed by SEM. The recovery rate of the questionnaire was 71.0%. Human error measures were classified into The measures against deficient knowledge and insufficient experiences. Attention problem measures and The measures against a cognitive error. While attention problem was strongly related to the cognitive error, there was no relationship between Attention problem measures and The measures against a cognitive error. Moreover, it were clarified that to develop human error measures for deficient knowledge and insufficient experiences was effective for the preventive against the mismatch of the cognitive mechanism and the intentional mistake and for bridging the gap between knowledge and experiences. This study showed that SEM was effective for adopting efficient preventive measures for medical accident and analyzing risk management in pharmacies. Applying these results to the medical accident preventive measures contribute to improvement of the risk management.     

Core reporting practices in structural equation modeling

BackgroundStructural equation modeling (SEM) is a popular analysis technique because of the wide range of questions that it can help answer. There are several pieces of information specific to SEM that should be reported when this technique is used.ObjectivesTo demonstrate a basic framework for reporting SEM analyses, to provide definitions of key terms readers will encounter, and to illustrate 2 examples for reporting SEM results.MethodsData from 650 participants who completed 3 self-report surveys were used to test a confirmatory factor analysis and a structural model as examples of information to be reported.ResultsThe results displayed are requisite information for any SEM analysis.ConclusionsIt is important for investigators to provide this information so that readers can properly evaluate the results and conclusions based on the analyses.     

Structural features of guinea pig aldehyde oxidase inhibitory activities of flavonoids explored using QSAR and molecular modeling studies

In this study, guinea pig aldehyde oxidase inhibitory activities of flavonoids were investigated using in silico, quantitative structure–activity relationships, molecular modeling, and experimental techniques, in order to understand more about their mode of interactions. The aldehyde oxidase inhibitory activity values determined experimentally in this work or collected from our previous report were used to derive mathematical models for the prediction purposes employing combined genetic algorithm and partial least square method, as well as multiple linear regression analysis. The statistical parameters for the developed models and the results of leave-one-out internal cross-validation were indicative of the validity of the models. To further investigate the mechanism of interaction between flavonoid inhibitors and guinea pig aldehyde oxidase enzyme, the structural model of the enzyme was built and the inhibitors were docked manually into the binding site. The model for quercetin-aldehyde oxidase complex was validated based on its appropriate stability during 10?ns molecular dynamics simulation, and hence the positioning procedure for the rest of flavonoids was guided based on the manually docked position of quercetin. The identified interactions were compared with those of flavonoids previously reported for rat aldehyde oxidase and the results showed a substantial commonality between the modes of interactions predicted for flavonoids positioned into the binding site of aldehyde oxidase from guinea pig and rat. This commonality is also reflected by the quantitative structure–activity relationships models. The results presented in this work may provide useful information where the structural requirements for aldehyde oxidase inhibition are sought, such as designing novel aldehyde oxidase inhibitors or investigating drug interaction involving aldehyde oxidase mediated biotransformation.     

运用PDCA循环法管理药房的效果分析

目的探讨运用PDCA循环法管理药房的效果。方法依据采用的管理方法,药房不同分为对照组和观察组。对照组采用传统方法管理,观察组运用PDCA循环法管理。结果观察组有效使用药品、不合格药品报损及去向明确率情况优于对照组,差异具有显著性（P〈0.05）,有统计学意义。结论运用PDCA循环法管理药房,能促使医院药房的管理工作向科学管理发展,提高临床用药的质量,减少药物造成的医疗问题。     

Investigation on patient satisfaction at community pharmacies: analyzing questionnaire survey by structural equation modeling and multiple regression analysis

Separation of the dispensing function and the prescribing function, Iyaku Bungyo, has been progressing in Japan. We are now witnessing the advent of a new society where patients select pharmacists and their satisfaction is recognized as one of the healthcare outcome indicators. It is necessary to clarify which factors affect patients' satisfaction with the services provided at community pharmacies and how they do so. A survey was conducted among 104 community pharmacies and their patients around the Tokyo metropolitan area in Japan. The questionnaire comprised 11 items (observed variables), each with a five-grade scale. With the transformed data-oriented pharmacy, the percentage of being not unsatisfactory was examined in two multivariate analyses of the relation and structure of patient satisfaction with a community pharmacy. Structural equation modeling (SEM) with factor analysis (FA) was performed using the observed variables and latent factors. Multiple regression analysis was performed with comprehensive satisfaction as an independent variable, examining the factors that affect comprehensive satisfaction with the pharmacy. The result of the FA indicated three latent factors of instruction on the use of drugs, quality of staff, and environment, based on which SEM model was constructed with a relatively high goodness of fit index. The result of multiple regression analyses indicated almost all variables such as satisfaction with reception by the pharmacist affected the comprehensive satisfaction, but privacy did not show a significant effect. These results, notably the relationship between each variables and latent factors, suggested the importance of higher skills of pharmacists, service qualities at pharmacies, and their functions adjusted to the community.     

Beyond path diagrams: Enhancing applied structural equation modeling research through data visualization

IntroductionStructural equation modeling (SEM) is a multivariate data analytic technique used in many domains of addictive behaviors research. SEM results are usually summarized and communicated through statistical tables and path diagrams, which emphasize path coefficients and global fit without showing specific quantitative values of data points that underlie the model results. Data visualization methods are often absent in SEM research, which may limit the quality and impact of SEM research by reducing data transparency, obscuring unexpected data anomalies and unmodeled heterogeneity, and inhibiting the communication of SEM research findings to research stakeholders who do not have advanced statistical training in SEM.Methods and resultsIn this report, we show how data visualization methods can address these limitations and improve the quality of SEM-based addictive behaviors research. We first introduce SEM and data visualization methodologies and differentiate data visualizations from model visualizations that are commonly used in SEM, such as path diagrams. We then discuss ways researchers may utilize data visualization in SEM research, including by obtaining estimates of latent variables and by visualizing multivariate relations in two-dimensional figures. R syntax is provided to help others generate data visualizations for several types of effects commonly modeled in SEM, including correlation, regression, moderation, and simple mediation.DiscussionThe techniques outlined here may help spur the use of data visualization in SEM-based addictive behaviors research. Using data visualization in SEM may enhance methodological transparency and improve communication of research findings.     

Structural features of GABAA receptor antagonists: pharmacophore modeling and 3D-QSAR studies

Pharmacophore modeling, comparative molecular field analysis (CoMFA), and comparative molecular similarity indices analysis (CoMSIA) studies have been carried out on 5-(4-piperidyl)-3-isoxazolol (4-PIOL) analogs as GABA_A receptor antagonists in this study. The best pharmacophore hypothesis generated by PHASE was ADHPR.6, which comprised a hydrogen bond acceptor (A), a hydrogen bond donor (D), a hydrophobic group (H), a positively charged group (P), and an aromatic ring (R). The pharmacophore model provided a good alignment for the further 3D-QSAR analyses, which presented a good R ² value of 0.943, 0.930, and 0.916 for atom-based QSAR model, CoMFA model, and CoMSIA model, respectively. All QSAR models presented good statistical significance and predictivity, the corresponding Q ² values for each 3D-QSAR model are 0.794, 0.569, and 0.637, respectively. Both pharmacophore and CoMSIA results showed that the hydrophobic sites are the key structural feature for GABA_A receptor antagonists with high activities.     

Classification of spider neurotoxins using structural motifs by primary structure features. Single residue distribution analysis and pattern analysis techniques.

In recent years the data on the novel structures of spider toxins have been greatly increasing. The sequence data should be classified. We introduced two primary structure analysis techniques-single residue distribution analysis (SRDA) and pattern analysis for classifying spider polypeptide toxins with molecular weight less than 10kDa. For multiple sequence alignment, we also introduced three novel sequence representation formats named as a simple record, motif record and a pattern record, which can be useful for large-scale analysis of structures. About 300 sequences of spider toxins were analyzed and nine primary structure motifs were identified. New classification of spider toxins was proposed on the basis of previously described principal structural motif (PSM) and extra structural motif (ESM) [Kozlov, S.A., Malyavka, A.A., McCutchen, B., Lu, A., Schepers, E., Herrmann, R., Grishin, E.V., 2005. A novel strategy for the identification of toxin-like structures in spider venom. Proteins 59 (1), 131-140]. Five main structural classes were revealed, and for putative ion channel inhibitors from the most numerous classes 1, 2, and 3, five-digital personal ID numbers were introduced. A reference table with simple, motif and pattern representation sequence formats was created for all analyzed structures.     

Stakeholder analysis of clinical trials in China: a structural equation model

Stakeholder analysis was conducted to define stakeholders and their role inclinical trials;a conceptual model and hypotheses regarding the relationship of each stakeholder were then constructed based on pharmaceutical regulations in China andinterviews with experts; Amos 17.0 was utilized to test the model and path analysis. We found that government and hospital are the most powerful stakeholders, while the public and sponsor have little impact on clinical trials. Further measures should be taken by sponsors to promote the development of clinical trials, and the public should be more involved in clinical research.     

Pharmacophoric features of biguanide derivatives: an electronic and structural analysis

The structure and electronic structure of drugs determine their mechanism of action. Correct structural representation of drugs helps in the proper identification of pharmacophoric features. Biguanide derivatives are a very important class of drugs, but their electronic structure was not clearly understood. Ab initio MO and density functional studies revealed the structure of the most stable tautomer of biguanide. (i) Electron delocalization, (ii) 1,3-H shift, (iii) 1,5-H shift, (iv) protonation, and (v) deprotonation processes, etc., have been investigated for biguanide. The molecular electrostatic potential (MESP) surfaces of neutral, protonated, and deprotonated biguanide have been shown to be similar in their most stable arrangements. The electrostatic potential of the complementary surface where these systems may bind also could be identified. Finally, the most stable structure of the important biguanide derivatives has been given after performing a conformational search.     

Descriptive analysis of pharmacy services provided after community pharmacy screening

Background Community pharmacies are promising locations for opportunistic screening due to pharmacist accessibility and ability to perform various health and medication management services. Little is known as to the provision of pharmacy services following screening initiatives. Objective To describe provision of pharmacy services for participants following a community pharmacy stroke screening initiative. Setting The Program for the Identification of “Actionable Atrial” Fibrillation Pharmacy initiative took place in 30 pharmacies in Alberta and Ontario, Canada. 1149 participants?≥?65 were screened for atrial fibrillation, type 2 diabetes, and hypertension. Method Retrospective, secondary analysis of data using participant case-report forms, pharmacy data, and pharmacy claims to describe pharmacy services received by participants post-screening. Main Outcome Measure Number and types of remunerated pharmacy services received by participants post-screening. Results A total of 535/1149 (46.6%) participants screened at their regular pharmacy were included in this analysis. Of these, 165 (30.8%) participants received 229 pharmacy services within 3 months post-screening, including 146 medication reviews, 57 influenza vaccinations, and 21 pharmaceutical opinions. A median (interquartile range, IQR) of 6 (2–11) pharmacy services were delivered, and median (IQR) reimbursement was $187.50 ($67.50–$342.50). Conclusions Approximately one-third of participants received a pharmacy service within 3 months post-screening. Relatively large numbers of annual and follow-up medication reviews were delivered despite low eligibility for annual-only reviews and despite many missed opportunities for pharmacy service provision in at-risk patients. In-pharmacy screening may facilitate provision of some services, namely medication reviews, by providing opportunities to identify patients at-risk.     

Reducing the peptidyl features of caspase-3 inhibitors: a structural analysis

Caspases are cysteine proteases that specifically cleave Asp-Xxx bonds. They are key agents in inflammation and apoptosis and are attractive targets for therapy against inflammation, neurodegeneration, ischemia, and cancer. Many caspase structures are known, but most involve either peptide or protein inhibitors, unattractive candidates for drug development. We present seven crystal structures of inhibited caspase-3 that illustrate several approaches to reducing the peptidyl characteristics of the inhibitors while maintaining their potency and selectivity. The inhibitors reduce the peptidyl nature of inhibitors while preserving binding potency by (1). exploiting a hydrophobic binding site C-terminal to the cleavage site, (2). replacing the negatively charged aspartyl residue at P4 with neutral groups, and (3). using a peptidomimetic 5,6,7-tricyclic system or a pyrazinone at P2-P3. In addition, we have found that two nicotinic acid aldehydes induce a significant conformational change in the S2 and S3 subsites of caspase-3, revealing an unexpected binding mode. These results advance the search for caspase-directed drugs by revealing how unacceptable molecular features can be removed without loss of potency.     

Exploring structural requirement,pharmacophore modeling,and de novo design of LRRK2 inhibitors using homology modeling approach

A mutation in the gene, encoding leucine rich repeat kinase 2 (LRRK2), is a genetic cause of Parkinson’s disease (PD). LRRK2 is a dimeric multidomain protein, largely regulates guanosine triphosphate (GTP). G2019S and I2020T, the mutation encodes in the kinase domain of LRRK2 increase the GTPase activity, are the important regulators in pathogenesis of PD. To design potent LRRK2 inhibitors, pharmacophore modeling approach was employed with a wide chemical diversity of compound’s database. The best hypothesis consists of hydrogen-bond acceptor and donor as well as hydrophobic aliphatic and ring aromatic features. The model was validated by the test and decoy sets followed by Fischer’s randomization test. The validated model was used to screen the database of compounds, which were designed through de novo approach. Homology model of the kinase domain of LRRK2 was built initially using the crystal structure of Janus kinase 3. The designed molecules were further screened for ADMET properties, and ligand–receptor interaction of top hits was analyzed by molecular docking studies to explore potent LRRK2 inhibitors.     

In vitro and ex vivo bioadhesivity analysis of polymeric intravaginal caplets using physicomechanics and computational structural modeling

The in vitro and ex vivo bioadhesivity of polyacrylic acid (PAA)-based intravaginal caplets was explored from a physicomechanical and chemometrical structural modeling viewpoint. An Extreme Vertices Mixture Design was constructed for analyzing the bioadhesivity of 11 matrices that were optimized. Two sets of crosslinked PAA-based matrices comprising either allyl-sucrose (AS-PAA) or allyl-penta-erythritol (APE-PAA) were explored. Powders were compressed into caplet-shaped matrices and rotational rheological analysis was performed on hydrated polymeric blends. Caplets were evaluated for bioadhesiveness using a simulated vaginal membrane (SVM) with optimized caplets further tested using freshly excised rabbit vaginal tissue. The SVM and caplets were hydrated in simulated vaginal fluid before bioadhesivity testing using a texture analyzer to determine the rupture force between the membranous substrates and hydrated caplets. Computational and molecular structural modeling deduced transient sol–gel mechanisms, chemical interactions and inter-polymeric interfacing during caplet-substrate bioadhesion. Peak adhesive force (PAF) and work of adhesion (AUC_FD) values for the APE-PAA caplets (1.671 ± 0.232 N; 0.0010 ± 0.0002 J) were higher than the AS-PAA caplets (1.168 ± 0.093 N; 0.00030 ± 0.0001 J) revealing superior bioadhesiveness. Similarly, rheological analysis revealed APE-PAA blends with higher viscosity and shear stress values (9 × 10⁵ mPa/180 Pa). The optimized APE-PAA matrices adhered appreciably to rabbit vaginal tissue (PAF = 0.883 ± 0.083 N; AUC_FD = (0.0003 ± 3.5355) × 10⁻⁵ J). Results strongly suggest that the approach may be useful for assessing the bioadhesivity of intravaginal matrices on ex vivo rabbit vaginal tissue with data further supported by molecular structural analysis and energy-dependant bioadhesivity modeling.     

Effects of environmental levels of cadmium,lead and mercury on human renal function evaluated by structural equation modeling

A relationship between exposure to heavy metals, including lead and cadmium, and renal dysfunction has long been suggested. However, modeling of the potential additive, or synergistic, impact of metals on renal dysfunction has proven to be challenging. In these studies, we used structural equation modeling (SEM), to investigate the relationship between heavy metal burden (serum and urine levels of lead, cadmium and mercury) and renal function using data from the NHANES database. We were able to generate a model with goodness of fit indices consistent with a well-fitting model. This model demonstrated that lead and cadmium had a negative relationship with renal function, while mercury did not contribute to renal dysfunction. Interestingly, a linear relationship between lead and loss of renal function was observed, while the maximal impact of cadmium occurred at or above serum cadmium levels of 0.8 μg/L. The interaction of lead and cadmium in loss of renal function was also observed in the model. These data highlight the use of SEM to model interaction between environmental contaminants and pathophysiology, which has important implications in mechanistic and regulatory toxicology.