Categories Of Descriptors Research Articles

Predictive QSPR modelling for the olfactory threshold of a series of pyrazine derivatives

ABSTRACTNowadays, much interest is shown in the prediction of different organoleptic properties of molecules for their prominent use in a variety of formulations and food products. Against this background, cheminformatics modelling was done in the present work for the development of predictive models for the olfactory threshold (log T) of a series of 74 pyrazine derivatives employing in silico techniques such as genetic function algorithm (GFA) and genetic partial least squares algorithm (G/PLS). Different categories of descriptors were calculated for the work. After validating the models both internally and externally, a parabolic GFA‐spline model was selected as the best model which showed significant predictive quality [ = 0.822, = 0.641, = 0.019]. Interpretation of the descriptors concluded that increased hydrophobic surface area, along with an increase in the positive charge weighted solvent accessible surface area (as interpreted from the Jurs_DPSA_2 descriptor) in the molecules, provides a low value of log T. Again, the presence of an isopropyl group and electron richness of the molecules significantly influences the property profile (log T) of the molecules. Finally, 27 pyrazine derivatives were designed based on the present analysis and good in silico prediction values for odour threshold, i.e. low log T values were obtained from the developed model. Thus, use of this optimized quantitative structure–property relationship (QSPR) model may be used to screen molecule databases as well as modify the structures for selection of potent entities. Copyright © 2013 John Wiley & Sons, Ltd.

A simple electrotopological index for quantitative structure-activity relationship correlation of physical properties with biomolecular activities

Quantitative structure-activity relationship (QSAR) studies constitute a process by which the physicochemical properties of a set of chemical structures are quantitatively correlated with a measurable, such as the concentration of a substance required to give a certain therapeutic drug response. 2D-QSAR studies start with 10–20 analogues, ranging from biologically active to inactive; each analogue, regardless of bioactivity, is described by a series of descriptors. To further broaden the practical utility of these simple descriptors we have sought to identify hybrid indices which are trivial to calculate but which capture data from at least two categories of descriptors. An electrotopological descriptor, termed ET\(_\mathrm{Z}\), which combines electronic information and molecular topology, has been devised and validated against a set of 25 anticonvulsant hydantoin molecules. This ET\(_\mathrm{Z}\) is based solely on atomic connectivity information obtained from the graph without explicit input from molecular geometry.

Lower-Extremity Arterial Air Plethysmography Evaluation

Plethysmography is a noninvasive technique based on detecting small volume changes in the limb secondary to the cardiac cycle. These changes provide a methodology for qualitative assessment of arterial waveforms and are obtained in conjunction with the measurement of systolic blood pressures. The quality of the waveform is directly related to technical components of the study as well as physical components of the patient. Interpretation of the waveform includes the utilization of qualitative waveform descriptor categories, comparison of waveforms to adjacent ipsilateral levels, as well as contralateral waveforms at the same level. Examples of normal findings and various levels of arterial occlusive disease states will demonstrate the practical application of this testing technique. However, plethysmography does have a number of potential sources of error that must be recognized to ensure the study is of diagnostic quality. These potential pitfalls are described as well as some important considerations to provide the most accurate information. Although other studies may provide greater detail about the presence and location of arterial occlusive disease, plethysmography does provide an efficient and cost-effective method to assist in the diagnosis and management of the disease process.

Learning the shape manifold to improve object recognition

This paper presents an approach for object recognition and shape retrieval in binary images. Object description is accomplished by contour and region-based solutions. Fusion of two categories of shape descriptors causes a considerable performance improvement in retrieval. In order to improve the recognition rate, it is important to extract the intrinsic object feature vectors in such a way that the geometrical distance between two such vectors matches the semantic relation between the two objects from which they were extracted. The main contribution in this paper is learning how to map the samples in high-dimensional observation space into the new manifold space so that the geometrically closer vectors belong to near semantics. Feature extraction is done by Isomap that belongs to a non-linear feature extraction algorithm. In the proposed method, the shortest path in the dissimilarity graph leads to less value between the samples in the same category by denoising the edge values. Experiments show that the geometrical distance between the samples on the manifold space are more compatible to the semantic distance of them. The proposed method has been compared to some well-known approaches by a variety of shape databases which includes MPEG-7 Part B, Kimia silhouettes, and Fish. The results show the effectiveness and validity of the method.

Comparative QSARs for antimalarial endochins: Importance of descriptor-thinning and noise reduction prior to feature selection

The emergence of multidrug resistance of the currently available antimalarial drugs has led to the need of the discovery and development of new antimalarial compounds. In the present study, we have selected a series of 53 endochin analogs with antimalarial activity against the clinically relevant multidrug resistant malarial strain TM-90-C2B to develop robust QSAR models using different chemometric tools such as stepwise regression, factor analysis followed by multiple linear regression (FA-MLR), factor analysis followed by partial least squares (FA-PLS) analysis, genetic function approximation (GFA) and genetic partial least squares (G/PLS) techniques. We have tried to emphasize on importance of descriptor-thinning prior to feature selection step. For this purpose, we have partitioned the total pool of descriptors into three categories followed by running stepwise regression separately for all three categories of descriptors for selection of variables. Then we have applied genetic methods of model development on the selected pool of descriptors. We have validated the models using different validation parameters to check the statistical quality and reliability of the models. It has been found that models developed from variable selection by stepwise regression followed by GFA and G/PLS are the best two models. This study reflects the importance of descriptor-thinning and noise reduction prior to feature selection for the development of QSAR models. According to the best two models, we interpreted that substitutions with rotatable bond containing groups (e.g., long alkyl chains), limited volume of the molecules, absence of ▪ C—R group, presence of electronegative (like —Br) fragments, absence of cycles or rings in the molecules are important for the antimalarial activity. The developed models are believed to comply with the OECD guidelines for QSAR models. The results also confirmed that the QSAR models developed from the reduced pool of descriptors were better than those obtained from the entire pool of descriptors.

Pediatric Restless Legs Syndrome

The specific aims of this study were to collect and analyze detailed symptom descriptions from patients with pediatric restless legs syndrome, ages 6 to 17 years, as well as assess symptom impact and the usefulness of drawings. Trained qualitative interviewers conducted face-to-face audio-recorded interviews of children and adolescents who met criteria for definite restless legs syndrome. Thirty-three patients in 3 age groups used 16 different categories of descriptors for restless legs sensations, with a mean of 3 or more categories used per patient in each age group. "Need to move/kick," "pain/hurts," "uncomfortable/cannot get comfortable," and "like bugs or ants/crawling" were the most common descriptors. Two-thirds reported daytime sensations, and nearly half had arm involvement. They described impact on sleep, cognitive function, and affect. Drawings provided useful diagnostic information. These detailed empirical data will be useful in clinical practice, as well as in the development of formal diagnostic tools and severity measures.

Quantitative structure-activity relationships for cycloguanil analogs as PfDHFR inhibitors using mathematical molecular descriptors

Computed molecular descriptors were used to develop quantitative structure-activity relationships (QSARs) for binding affinities (Ki ) for a set of 58 cycloguanil (2,4-diamino-1,6-dihydro-1,3,5-triazine) analogues for dihydrofolate reductase (DHFR) enzyme extracted from wild and A16V+S108T mutant type (a double mutation) malaria parasite Plasmodium falciparum (Pf). High-quality models were obtained in both cases. The results of statistical analyses show that ridge regression (RR) outperformed the two other modelling methods, principal component regression (PCR) and partial least squares (PLS). For both enzymes, recognition of the inhibitors was based on four broad categories of descriptors encoding information on: (1) the electronic character of the various atoms in the molecule, (2) the size and shape of the structure, (3) the degree of branching in the molecular skeleton, and (4) two to five atom molecular fragments with aliphatic carbon at one end and aliphatic or aromatic carbon or nitrogen at the other end. The subsets of influential descriptors underlying the QSARs for the wild versus the mutant DHFR are quite non-overlapping. This indicates that the two enzymes recognize the inhibitor molecules on the basis of mutually distinct structural attributes. Such differential QSARs can be useful in the design of novel drugs active against malaria parasites which are growing in resistant to existing chemotherapeutic agents.

Applying Chemometrics Approaches to Model and Predict the Binding Affinities Between the Human Amphiphysin SH3 Domain and Its Peptide Ligands (Suplementary Material)

In this study, we used two categories of molecular descriptors as CODESSA and DPPS (divided physicochemical property scores of amino acids) to parameterize structural characteristics of 2015 human amphiphysin SH3 domain-binding decapeptides at atom and residue levels. Based upon that, several robust quantitative structure-affinity relationship (QSAR) models were then constructed using partial least squares regression (PLS) and least squares-support vector machine (LSSVM) coupled with genetic algorithm (GA)-variable selection. Results show that (1) GA is a powerful tool for variable selection by which the most informative variable combinations can be efficiently determined for PLS and LSSVM modeling, (2) regression models constructed using nonlinear LSSVM approach are more robust and predictable than those by linear PLS method, (3) the residue level descriptor (DPPS) performs better in capturing peptide structural characteristics, more amenable than those from the atom level descriptor (CODESSA). By investigating the optimal DPPS-based GA-LSSVM model, it is indicated that the core motif of SH3 domain-binding peptides contributes significantly to the binding affinity, whereas the two end residues, especially the N-terminal residue, have a little effect on the binding process.

Spouses use of social control to improve diabetic patients' dietary adherence.

We investigated two types of negative and positive social control strategies, warning and encouragement, used by spouses to urge patients with type II diabetes to improve adherence to the diabetic diet. Warning refers to things a spouse may say or do to caution the patient about the consequences of eating a poor diet, and encouragement refers to things a spouse may say or do to promote healthier food choices by the patient. Our dyadic design (n=109 couples) assessed spouses' use of warning and encouragement (reported by spouses and by patients), as well as patients' reports of dietary adherence. Spouses being actively involved in patients' dietary choices was the largest category of open-ended descriptors of both warning and encouragement. Both spousal warning and encouragement were associated with patients' adherence to the recommended diabetic diet, with warning associated with poorer adherence and encouragement associated with better adherence. Moreover, it was the spouses' perceptions of their own influence attempts, and not patients' reports, that were consequential for patients' adherence. Patients' dietary behavior, and ultimately disease management, appears to be best served when the spouse uses more positively toned and less coercive influence attempts.

Development of a Novel Location-Based Assessment of Sensory Symptoms in Cancer Patients: Preliminary Reliability and Validity Assessment

We report on the development of a novel location- based assessment of sensory symptoms in cancer (L-BASIC) instrument, and its initial estimates of reliability and validity. L-BASIC is structured so that patients provide a numeric score and an adjectival description for any sensory symptom, including both pain and neuropathic sensations, present in each of the 10 predefined body areas. Ninety-seven patients completed the baseline questionnaire; 39 completed the questionnaire on two occasions. A mean of 3.5 body parts was scored per patient. On average, 2.7 (of 11) descriptor categories were used per body part. There was good internal consistency (Cronbach's α = 0.74) for a four-item scale that combined location-specific metrics. Temporal stability was adequate (κ > 0.50 and r > 0.60 for categorical and continuous variables, respectively) among patients without observed or reported subjective change in clinical status between L-BASIC administrations. We compared our four-item scale against scores obtained from validated pain and quality-of-life (QOL) scales, and as expected, correlations were higher for pain-related items than for QOL-related items. We detected differences in L-BASIC responses among patients with cancer-related head or neck pain, chemotherapy-related neuropathy and breast cancer-related lymphedema. We conclude that L-BASIC provides internally consistent and temporally stable responses, while acknowledging that further refinement and testing of this novel instrument are necessary. We anticipate that future versions of L-BASIC will provide reliable and valid syndrome-specific measurement of defined clinical pain and symptom constructs in the cancer population, which may be of particular value in assessing treatment response in patients with such multiple complaints.

In Silico Screening of Chemicals for Genetic Toxicity Using MDL-QSAR, Nonparametric Discriminant Analysis, E-State, Connectivity, and Molecular Property Descriptors

ABSTRACTGenetic toxicity testing is a critical parameter in the safety assessment of pharmaceuticals, food constituents, and environmental and industrial chemicals. Quantitative structure-activity relationship (QSAR) software offers a rapid, cost-effective means of prioritizing the genotoxic potential of chemicals. Our goal is to develop and validate a complete battery of complementary QSAR models for genetic toxicity. We previously reported the development of MDL-QSAR models for the prediction of mutations in Salmonella typhimurium and Escherichia coli (); this report describes the development of eight additional models for mutagenicity, clastogenicity, and DNA damage. The models were created using MDL-QSAR atom-type E-state, simple connectivity and molecular property descriptor categories, and nonparametric discriminant analysis. In 10% leave-group-out internal validation studies, the specificity of the models ranged from 63% for the mouse lymphoma (L5178Y-tk) model to 88% for chromosome aberrations in vivo. Sensitivity ranged from a high of 74% for the mouse lymphoma model to a low of 39% for the unscheduled DNA synthesis model. The receiver operator characteristic (ROC) was ≥2.00, a value indicative of good predictive performance. The predictive performance of MDL-QSAR models was also shown to compare favorably to the results of MultiCase MC4PC () genotoxicity models prepared with the same training data sets. MDL-QSAR software models exhibit good specificity, sensitivity, and coverage and they can provide rapid and cost-effective large-scale screening of compounds for genotoxic potential by the chemical and pharmaceutical industry and for regulatory decision support applications.

Use of Microcalcification Descriptors in BI-RADS 4th Edition to Stratify Risk of Malignancy

To retrospectively evaluate whether microcalcification descriptors and the categorization of microcalcification descriptors in the Breast Imaging Reporting and Data System (BI-RADS) 4th edition help stratify the risk of malignancy, by using biopsy and clinical follow-up as reference standards. The institutional review board approved this HIPAA-compliant study and waived informed consent. The study included 115 women (age range, 26-82 years; mean age, 55.8 years +/- 10.5 [standard deviation]) who consecutively underwent image-guided biopsy of microcalcifications between November 2001 and October 2002. Screening and diagnostic mammograms (including magnification views) obtained before biopsy were analyzed in a blinded manner by a subspecialty-trained breast imager who recorded BI-RADS descriptors on a checklist. The proportion of malignant cases was used as the outcome variable to evaluate the ability of the descriptors to help capture the risk of malignancy. Fisher exact test was used to calculate the difference among the individual descriptors and descriptor categories. The positive predictive value of biopsy for malignancy was 21.7%. Each calcification morphologic descriptor was able to help stratify the probability of malignancy as follows: coarse heterogeneous, one (7%) of 14; amorphous, four (13%) of 30; fine pleomorphic, 10 (29%) of 34; and fine linear, 10 (53%) of 19. Fisher exact test results revealed a significant difference among these descriptor categories (P = .005). Significant differences among the risks suggested by microcalcification distribution descriptors (P = .004) and between that of stability descriptors (P = .001) were found. The microcalcification descriptors and categories in BI-RADS 4th edition help predict the risk of malignancy for suspicious microcalcifications.

Development of a Model to Predict Partition Coefficient of Organic Pollutants in Cloud Point Extraction Process

A quantitative structure property relationship (QSPR) study has been performed to establish a model to relate structural descriptors of 45 organic compounds to their partition coefficients in water-hexadecylpyridinium chloride (CPC) micelles at 298K using partial least squares (PLS). 510 of six different categories of structural descriptors were calculated by Dragon software. The descriptors with 0.9 mutually pair correlations and with less than 0.1 with dependent variables were excluded at the early stage of the preprocessing of the structural data matrix. The data set was randomly divided into two groups: training set (40 molecules) and test set (5 molecules). In the final model 50 of the most effective of the structural descriptors on the partition coefficient were remained to model building by PLS calibration method. The optimum number of latent variables 5, which spanned 80% of the original variations of data matrix, was selected using leave one out cross validation method. Prediction ability of the model was tested by prediction of the partition coefficients of five unknown compounds and the mean relative error of prediction was 3.6%. The outliers were treated using leverage and score plots of the first third principal components. The efficiency of the new model was compared with Abraham model and it was found that the proposed model has more prediction ability.

Taxonomy and structure of Croatian personality‐descriptive adjectives

This paper describes the development of a comprehensive taxonomy of Croatian personality‐descriptive terms, organized in three studies. In the first study three judges searched through a standard dictionary of the Croatian language for person‐descriptive terms. In the second study, personality‐descriptive adjectives were classified by seven judges into 13 different categories of descriptors. In the third study, the 483 adjectives that the majority of judges in the second study classified as dispositions were rated for self‐descriptions by 515 University of Zagreb students and for peer‐descriptions by 513 students' best acquaintances. Self‐ and peer ratings were factor analysed separately and the Croatian emic lexical factors from both data sets were interpreted to be similar to the Big‐Five factors: Agreeableness, Extraversion, Conscientiousness, Intellect, and Emotional Stability. The inspection of factor content of the Croatian emic factors and their relation to imported Big‐Five measures revealed high correspondences for all five Croatian factors although the relation between the Croatian and the imported factors of Emotional Stability and Agreeableness was somewhat more complex. Copyright © 2004 John Wiley & Sons, Ltd.

Correlation of change in visual analog scale with pain relief in the ED

Objectives To evaluate the validity of change in visual analog Scale (VAS) as a measure of pain relief using a verbal descriptor Scale (VDS) of change in pain. Methods A prospective observational study of emergency department patients measured pain with VAS and recorded verbal report of change in pain. Results One thousand four hundred ninety patients yielded 1999 comparisons between change in VAS and VDS. Correlation of change in VAS and VDS of change in pain was ρ = 0.667 ( P < .001). A wide range of change in VAS, large standard deviations for the mean change in VAS, and discordance in the direction of change in VAS were present within each verbal descriptor category. Conclusions Change in VAS is moderately correlated with a VDS of change in pain. Wide variability in change in VAS and discordance with a VDS demonstrate that change in VAS is not a valid indicator of pain relief for individual patients.

Changes in intensity, location, and quality of vaso-occlusive pain in children with sickle cell disease

A descriptive, longitudinal design was used to examine changes in current, worst, and least pain intensity during hospitalization for a vaso-occlusive episode in children with sickle cell disease. Other dimensions of the pain experience including location and quality were also evaluated. Children reported severe pain on the day of admission with 50% of the episodes showing a current pain intensity score of >70 and a worst pain intensity score of >80. Although both pain intensity scores demonstrated statistically significant decreases by approximately 5% over the course of the hospitalization, these decreases were not clinically significant based on the recommendations made in the American Pain Society's Guideline for the management of acute and chronic pain in sickle cell disease. In contrast to the pain intensity ratings, which did not decrease in 25% of the episodes, pain location surface area decreased in 100% of the episodes. Children described the quality of vaso-occlusive pain using all categories of word descriptors from the adolescent pediatric pain tool. These findings suggest that pain associated with a vaso-occlusive episode is inadequately assessed and managed during hospitalization.

Color naming by boys and girls.

The present study describes a field experiment conducted to test the hypothesis that color naming varies for 56 adolescent boys and 39 girls. No standard color chart such as Munsell, Pantone, or Crayola was used. Instead, subjects identified 15 computer-generated color samples assigned a score based on thescale devised by Rich in 1977 of four color descriptor categories. Findings differed from those of most previous studies, in which women aged over 16 years showed a more elaborate color vocabulary than men. Among the 14- to 16-yr.-old subjects, there was no significant difference in color naming.

COLOR NAMING BY BOYS AND GIRLS

The present study describes a field experiment conducted to test the hypothesis that color naming varies for 56 adolescent boys and 39 girls. No standard color chart such as Munsell, Pantone, or Crayola was used. Instead, subjects identified 15 computer-generated color samples assigned a score based on the scale devised by Rich in 1977 of four color descriptor categories. Findings differed from those of most previous studies, in which women aged over 16 years showed a more elaborate color vocabulary than men. Among the 14- to 16-yr.-old subjects, there was no significant difference in color naming.

Implicit anti-fat bias among health professionals: is anyone immune?

To investigate whether negative implicit attitudes and beliefs toward overweight persons exist among health professionals who specialize in obesity treatment, and to compare these findings to the implicit anti-fat bias evident in the general population. Health care professionals completed a series of implicit and explicit attitude and belief measures. Results were compared to measures obtained from a general population sample. A total of 84 health professionals who treat obesity (71% male, mean age 48 y, mean body mass index (BMI) 25.39). Participants completed an attitude- and a belief-based lmplicit Association Test. This reaction time measure of automatic memory-based associations asked participants to classify words into the following target category pair. 'fat people' vs 'thin people'. Simultaneously, the tasks required categorization of words into one of the following descriptor category pairs: good vs bad (attitude measure) or motivated vs lazy (stereotype measure). Participants also reported explicit attitudes and beliefs about fat and thin persons. Clear evidence for implicit anti-fat bias was found for both the attitude and stereotype measures. As expected, this bias was strong but was lower than bias in the general population. Also as predicted, only minimal evidence for an explicit anti-fat bias was found. Implicit and explicit measures of the lazy stereotype were positively related although the attitude measures were not. Even health care specialists have strong negative associations toward obese persons, indicating the pervasiveness of the stigma toward obesity. Notwithstanding, there appears to be a buffering factor, perhaps related to their experience in caring for obese patients, which reduces the bias.

A novel index for the description of molecular linearity.

To investigate the description of molecular shape, a heterogeneous data set of 200 compounds was designed. The compounds included many disparate molecular shapes, and a total of 64 descriptors was calculated including topological indices, surface areas, molecular volumes, measures of molecular dimensions, and ratios of moments of inertia. Cluster analysis on the variables indicated that there are four major categories of steric descriptors, those for molecular bulk, dimensions, and two clusters representing varying aspects of shape. To describe molecular shape more efficiently, a novel linearity index based upon ratios of moments of inertia and the molecular weight is proposed.