Series Of Descriptors Research Articles

Prejudice Toward Asian American Women: Clothing Influences Stereotypes

Clothing type can have a significant impact on the way people are perceived. In this study, we were interested in the effect of business versus casual clothing on the perception of Asian American women, given various stereotypes about them. We used a between-subjects design with a sample of college students from a university in the United States. Participants saw 3 Asian American women (and 1 European American woman to distract from the nature of the study) in either business attire or casual outfits, and rated each woman on a series of descriptors based off various stereotypes of Asian American women. We used the Scale of Anti-Asian American Stereotypes to measure internal prejudice toward Asian Americans and the Ambivalent Sexism Inventory to measure sexism. The Scale of Anti-Asian American stereotypes was a significant covariate, F(4, 233) = 6.09, p < .001, ηp2 = .10. Participants rated models in business attire as less stereotypically Asian, F(1, 239) = 46.56, p < .001, ηp2 = .17, less sexualized, F(1, 239) = 12.91, p < .001, ηp2 = .05, and less invisible, F(1, 239) = 42.01, p < .001, ηp2 = .15. Our results show that stereotypes can indeed be influenced by business attire. It is important to note that future research may be oriented toward changing the attitudes of those who hold harmful stereotypes, rather than the actions (i.e., clothing choices) of the subjects of prejudice.

Theoretical study of the structural and energetic properties of platinum clusters with up to 60 atoms

Applying a theoretical approach that combines an efficient and fast global optimization based on genetic algorithms (GA) to search in structure space and the parameterized density-functional tight-binding (DFTB) method for the calculation of the energy for a given structure, the structures of neutral and isolated Ptn clusters are determined with size n from 4 up to 60 atoms. For the analysis of the structural, energetic, and electronic properties of Ptn as a function of n, a series of descriptors are employed, including a stability function, the HOMO-LUMO energy gap, and atomic radial distances of the atoms, as well as a similarity function. The results demonstrate that the structural motifs change from planar to shell-like structures with low-symmetry. In addition, the growth patterns of Ptn clusters also are analyzed using these descriptors, suggesting that meta-stable isomers also play a role in the growth process. Studying the impact of zero-point vibration and of temperature on the energetic properties of the different isomers, we found only very small effects, implying that properties found for T = 0 are relevant also at elevated temperatures. On the other hand, even though Pt is the neighbor to Au in the periodic table, the properties of Ptn clusters differ markedly from those of Aun clusters, and it can therefore be expected that the properties of AuPt nanoalloys will not resemble those of the pure clusters.

High-throughput phenotyping of brachiaria grass seeds using free access tool for analyzing X-ray images.

New approaches based on image analysis can assist in phenotyping of biological characteristics, serving as support for decision-making in modern agribusiness. The aim of this study was to propose a method of high-throughput phenotyping of free access for processing of 2D X-ray images of brachiaria grass (Brachiaria ruziziensis cv. Ruziziensis) seeds, as well as correlate the parameters linked to the physiological potential of the seeds. The study was carried out by means of automated analysis of X-ray images of seeds in which a macro, called PhenoXray, was developed, responsible for digital image processing, for which a series of descriptors were obtained. After the X-ray analysis, a germination test was performed on the seeds and, from this, variables related to the physiological quality of the seeds were obtained. The use of the macro PhenoXray allowed large-scale phenotyping of seed X-rays in a simple, rapid, robust, and totally free manner. This study confirmed that the methodology is efficient for obtaining morphometric data and tissue integrity data in Brachiaria ruziziensis seeds and that parameters such as relative density, integrated density, and seed filling are closely related to the physiological attributes of seed quality.

Antimicrobial activity of natural compounds against listeria spp. and their effects on sensory attributes in salmon (Salmo salar) and cod (Gadus morhua)

The application of natural preservatives on fresh fish has potential to extend shelf-life. In the present study, 8 essential oils (EOs) (lemon, lemongrass, lime, garlic, onion, oregano, thyme and rosemary) and 3 organic acids (OAs) (ascorbic, citric and lactic) were evaluated. The antimicrobial activity of these compounds was tested in-vitro against four confirmed Listeria spp. isolated from retail skin-packed salmon and cod. The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) were established for each compound. Then, a sensory evaluation was performed by a panel of ‘expert assessors’ on cooked fish treated with all of the OAs and any 4 EOs with a MIC <0.8%. A series of descriptors were assigned to characterize the combination of each compound with cooked salmon or cod.The highest antimicrobial effect against all Listeria spp. was observed for lactic acid (0.31–2.5%), but treatment with this compound resulted in the development of organoleptically unacceptable changes in salmon or cod. The most acceptable OAs for salmon and cod were ascorbic acid (1.25%) and citric acid (0.63%) respectively, which were shown to enhance certain organoleptic characteristics.The most effective EO against all Listeria strains evaluated was oregano oil (0.2%) and it was considered suitable as a treatment for salmon. In contrast, none of the EOs tested was organoleptically acceptable in combination with cod because of their strong odours and flavours that masked the fresh attributes associated with this fish.

Estimation of the breadth of CD4bs targeting HIV antibodies by molecular modeling and machine learning.

HIV is a highly mutable virus for which all attempts to develop a vaccine have been unsuccessful. Nevertheless, few long-infected patients develop antibodies, called broadly neutralizing antibodies (bnAbs), that have a high breadth and can neutralize multiple variants of the virus. This suggests that a universal HIV vaccine should be possible. A measure of the efficacy of a HIV vaccine is the neutralization breadth of the antibodies it generates. The breadth is defined as the fraction of viruses in the Seaman panel that are neutralized by the antibody. Experimentally the neutralization ability is measured as the half maximal inhibitory concentration of the antibody (IC50). To avoid such time-consuming experimental measurements, we developed a computational approach to estimate the IC50 and use it to determine the antibody breadth. Given that no direct method exists for calculating IC50 values, we resort to a combination of atomistic modeling and machine learning. For each antibody/virus complex, an all-atoms model is built using the amino acid sequence and a known structure of a related complex. Then a series of descriptors are derived from the atomistic models, and these are used to train a Multi-Layer Perceptron (an Artificial Neural Network) to predict the value of the IC50 (by regression), or if the antibody binds or not to the virus (by classification). The neural networks are trained by use of experimental IC50 values collected in the CATNAP database. The computed breadths obtained by regression and classification are reported and the importance of having some related information in the data set for obtaining accurate predictions is analyzed. This approach is expected to prove useful for the design of HIV bnAbs, where the computation of the potency must be accompanied by a computation of the breadth, and for evaluating the efficiency of potential vaccination schemes developed through modeling and simulation.

A Conceptual DFT Study of the Chemical Reactivity of Magnesium Octaethylporphyrin (MgOEP) as Predicted by the Minnesota Family of Density Functionals

The Minnesota family of density functionals has been assessed for the calculation of the molecular structure and electronic properties of a Mg(II)-porphyrin, namely Magnesium Octaethylporphyrin (MgOEP). Several global descriptors arising from Conceptual have been calculated through a ΔSCF procedure, and by means of the HOMO and LUMO frontier orbitals. On the basis of the obtained Conceptual indices, a series of descriptors have been devised in order to verify the fulfillment of the Koopmans' theorem in DFT procedure. It is shown that the density functionals that verify this approximation with a certain degree of accuracy are only those denoted as range-separated hybrids (RSH), while the usual GGA-hybrids and the local density functionals fail completely.

Validation of the Koopman's Theorem in DFT by Means of the Calculation of the Conceptual DFT Descriptors of Three Fluorescent DNA Staining Dyes

The fulfillment of the "Koopmans' theorem in DFT" is verified by means of the calculation of several global descriptors arising from Conceptual DFT. They have been calculated through a ΔSCF procedure, and by means of the HOMO and LUMO frontier orbitals. The latest Minnesota family of density functionals has been considered and three fluorescent DNA staining dyes have been studied: Hoechst 33258, Hoechst 33342 and Hoechst 34580. On the basis of the obtained Conceptual DFT indices, a series of descriptors have been devised in order to determine the accuracy of each model chemistry considered here in the verification of the mentioned theorem. It is shown that the only density functionals that fulfill this task are those denoted as range-separated hybrids (RSH), while the local density functionals are not useful at all.

QSAR and Structure Based Molecular Docking of Angelicin Compounds: an Attempt to Drug Design against Swine Influenza

There has been a great challenge of research and discovery of novel medicinal leads against swine influenza since 2009. Rational drug design utilizing pharmacoinformatics tools has been augmented now-a-days for in-silico screening of lead compounds prior to experimental synthesis, structural elucidation, biological evaluation and finally clinical trials to make the cost efficient drug design and discovery research. There is hardly any specific chemotherapeutics for the treatment against deadly swine influenza viral infection. Therefore, it is an urgent need to design and develop new anti-viral lead compounds active against swine influenza. Quantitative structure activity relationship (QSAR) has been used to develop models that correlate biological activity of angelicin compounds derived from published literature and their computed structural properties. The approach started by generation of a series of descriptors including topological, three dimensional, constitutional, functional groups and atom fragment indices respectively solely calculated from the compounds in the data set. In this study, data set consists of 53 angelicin compounds along with their inhibitory concentration 50% (IC50, μM) against H1N1 swine influenza virus. Genetic algorithm-multiple linear regression (GA-MLR) analysis technique has been to generate a number of QSAR models. The models were validated statistically incorporating training and test set approaches. Finally, structure-based molecular docking study has been performed for interpretation of the mode of binding of the angelicin compounds toward H1N1 target. QSAR and molecular docking analysis of these congeners have not yet been reported. Therefore, this study has significant impact for designing of the highly active compounds in this series that are useful for the treatment of swine influenza. In-silico structure based docking model could be helpful for design and screening of congeneric compounds having mode of binding similarity.

Quantitative structure-activity relationship for antimalarial activity of artemisinin

The increase in resistance to older drugs and the emergence of new types of infection have created an urgent need for discovery and development of new compounds with antimalarial activity. Quantitative-Structure Activity Relationship (QSAR) methodology has been performed to develop models that correlate antimalarial activity of artemisinin analogs and their molecular structures. In this study, the data set consisted of 197 compounds with their activities expressed as log RA (relative activity). These compounds were randomly divided into training set (n=157) and test set (n=40). The initial stage of the study was the generation of a series of descriptors from three-dimensional representations of the compounds in the data set. Several types of descriptors which include topological, connectivity indices, geometrical, physical properties and charge descriptors have been generated. The number of descriptors was then reduced to a set of relevant descriptors by performing a systematic variable selection procedure which includes zero test, pairwisecorrelation analysis and genetic algorithm (GA). Several models were developed using different combinations of modelling techniques such as multiple linear regression (MLR) and partial least square (PLS) regression. Statistical significance of the final model was characterized by correlation coefficient, r2 and root-mean-square error calibration, RMSEC. The results obtained were comparable to those from previous study on the same data set with r2 values greater than 0.8. Both internal and external validations were carried out to verify that the models have good stability, robustness and predictive ability. The cross-validated regression coefficient (r2cv) and prediction regression coefficient (r2 test) for the external test set were consistently greater than 0.7. The QSAR models developed in this study should facilitate the search for new compounds with antimalarial activity.

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.

Retail Concentration and Shopping Center Rents-A Comparison of Two Cities

This study aims primarily at testing whether, and to what extent, retail concentration within regional and super-regional shopping centers affect rent levels, as well as the differential impact it may exert for various goods categories and sub-categories and in different urban contexts. In this paper, 1,499 leases distributed among eleven regional and super-regional shopping centers in Montreal and Quebec City, Canada, and negotiated over the 2000-2003 period are considered. Unit base rents (base rent per sq. ft.) are regressed on a series of descriptors that include percentage rent rate, retail unit size (GLA), lease duration, shopping center age, as well as 31 retail categories while the Herfindahl index is used as a measure of intra-category retail concentration. Findings suggest that while, overall, intracategory retail concentration affects base rent negatively, the magnitude and, eventually, direction of the impact varies depending on the nature of the activity and the market dynamics that prevail for the category considered.

Retail Concentration and Shopping Center Rents—A Comparison of Two Cities

This study aims primarily at testing whether, and to what extent,retail concentration within regional and super-regional shoppingcenters affect rent levels, as well as the differential impact it mayexert for various goods categories and sub-categories and indifferent urban contexts. In this paper, 1,499 leases distributedamong eleven regional and super-regional shopping centers inMontreal and Quebec City, Canada, and negotiated over the2000–2003 period are considered. Unit base rents (base rent persq. ft.) are regressed on a series of descriptors that includepercentage rent rate, retail unit size (GLA), lease duration,shopping center age, as well as 31 retail categories while theHerfindahl index is used as a measure of intra-category retailconcentration. Findings suggest that while, overall, intra-categoryretail concentration affects base rent negatively, themagnitude and, eventually, direction of the impact variesdepending on the nature of the activity and the market dynamicsthat prevail for the category considered.

Soccer penalty takers' uniform colour and pre-penalty kick gaze affect the impressions formed of them by opposing goalkeepers

In this study, we examined the impact of soccer players' uniform colour and gaze behaviour on the impressions that are formed of them by opposing goalkeepers. Twelve soccer goalkeepers observed video footage, filmed from between the goalposts to simulate their usual viewpoint, of four players preparing to take a penalty kick. Each of the four players displayed a different combination of gaze (either 90% or 10% with gaze operationalized as looking directly at the camera) and uniform colour (red or white). Goalkeepers rated each player on a series of descriptors (e.g. confidence, composure, assertiveness) and rated their expectancies for successfully saving penalty kicks from that player. Analysis revealed that those penalty takers displaying 90% gaze were perceived to possess positive characteristics to a greater extent than penalty takers displaying 10% gaze. Results also revealed penalty takers wearing red were perceived to possess positive characteristics to a greater extent than those wearing white. Goalkeepers reported higher expectancies of saving penalties from penalty takers displaying 10% gaze and wearing white uniforms than any of the other combinations. Our results therefore support the potential importance of gaze and uniform colour in the formation of impressions and expectancies in sport.

How the Parts Organize in the Whole? A Top-Down View of Molecular Descriptors and Properties for QSAR and Drug Design

Sometimes the complexity of a system, or the properties derived from it, do depend neither on the individual characteristics of the components of the system nor on the nature of the physical forces that hold them together. In such cases the properties derived from the "organization" of the system given by the connectivity of its elements can be determinant for explaining the structure of such systems. Here we explore the necessity of accounting for these structural characteristics in the molecular descriptors. We show that graph theory is the most appropriate mathematical theory to account for such molecular features. We review a method (TOPS-MODE) that is able to transform simple molecular descriptors, such as logP, polar surface area, molar refraction, charges, etc., into series of descriptors that account for the distribution of these characteristics (hydrophobicity, polarity, steric effects, etc) across the molecule. We explain the mathematical and physical principles of the TOPS-MODE method and develop three examples covering the description and interpretation of skin sensitisation of chemicals, chromosome aberration produced by organic molecules and drug binding to human serum albumin.

Evaluation of descriptors and classification schemes to predict cytochrome substrates in terms of chemical information

Using a small database of defined substrates in humans for cytochrome P450 mixed function oxidases, a series of descriptors and classification methods were evaluated with respect to how well they correctly classified substrates. The descriptors ranged from structural keys to topological to electronic. A variety of classification schemes were examined in terms of their ability to point out which descriptors are important for predicting the cytochrome P450 specificity for a substrate. Results illustrate the relative effectiveness of the various kinds of descriptors and classification methods, as well as the value of using as well-defined data set as possible.

Quantitative analysis and classification of AFM images of human hair.

The surface topography of human hair, as defined by the outer layer of cellular sheets, termed cuticles, largely determines the cosmetic properties of the hair. The condition of the cuticles is of great cosmetic importance, but also has the potential to aid diagnosis in the medical and forensic sciences. Atomic force microscopy (AFM) has been demonstrated to offer unique advantages for analysis of the hair surface, mainly due to the high image resolution and the ease of sample preparation. This article presents an algorithm for the automatic analysis of AFM images of human hair. The cuticular structure is characterized using a series of descriptors, such as step height, tilt angle and cuticle density, allowing quantitative analysis and comparison of different images. The usefulness of this approach is demonstrated by a classification study. Thirty-eight AFM images were measured, consisting of hair samples from (a) untreated and bleached hair samples, and (b) the root and distal ends of the hair fibre. The multivariate classification technique partial least squares discriminant analysis is used to test the ability of the algorithm to characterize the images according to the properties of the hair samples. Most of the images (86%) were found to be classified correctly.

Connectivity polynomial and long-range contributions in the molecular connectivity model

A novel molecular polynomial, P χ ( G, x), representing the connectivity between all pairs of atoms in a molecule is introduced. The connectivity index χ is obtained directly from the first derivative of this polynomial, P χ ′( G, x=0). A series of descriptors containing contributions coming from non-bonded atoms in the molecule is derived by variation of x in the polynomial, P χ ′( G, x≠0). Significant improvements compared to the χ index are obtained when the novel descriptors are used in QSPR studies. The physicochemical and structural interpretations of these indices are also advanced.

Intraobserver agreement in interpretation of digital epiluminescence microscopy

Background: Although a major problem with the classification of epiluminescence microscopy (ELM) findings is the lack of standard definitions, reproducibility of the criteria proposed has never been investigated. Objectives: Our purposes were (1) to perform a review of four major published classifications to obtain a set of apparently well-defined ELM variables and descriptors and (2) to evaluate the ability of one of us to report consistently ELM findings in melanocytic lesions according to these criteria. Methods: Intraobserver agreememt (with a set of 44 selected descriptors) between two readings of 150 digital ELM images was evaluated with the kappa (ϰ) statistic. Subgroups of descriptors were compared for ϰ value distribution. Results: The median ϰ value for the whole series of descriptors was 0.66. Median ϰ did not vary significantly among the four classification systems (ϰ = 0.61 to 0.67). Agreement was significantly better as to the presence or absence of ELM findings (ϰ range, 0.39 to 1.00; median ϰ, 0.77) compared with agreement as to their distribution (ϰ range, 0.10 to 0.79; median ϰ, 0.47; p = 0.0007) and their width, thickness, and size (ϰ range, 0.06 to 0.83; median ϰ, 0.39; p = 0.0075). Conclusion: Although nothing can be inferred from a single study, descriptors associated with low intraobserver agreement are likely to be inadequately defined.

Acceptance and perception of percutaneous endoscopic gastrostomy by patients with upper aerodigestive tract cancer

Surgeons have identified a role for percutaneous endoscopic gastrostomy (PEG) in selected patients with upper aerodigestive tract cancer, but little is known about the patient's acceptance and perception of PEG. Nineteen patients with upper aerodigestive tract cancer had placement of a PEG and were asked about their perceptions via a series of descriptors and associated questions. The 13 patients who had PEG placement under local anaesthesia and intravenous midazolam were questioned 12–16 h later and reported that the procedure was comfortable and not as bad as expected. These patients together with a further 6 patients who had placement under general anaesthesia were questioned about their acceptance of the PEG tube after 10 days. Comfort, ease of use and maintenance, and coverage by clothing confirms that PEG is an acceptable delivery system for enteral nutrition in patients with upper aerodigestive tract cancer.

Evaluation of Chemoreception by Penaeus vannamei under Experimental Conditions

Abstract A series of descriptors (perception, orientation, displacement or movement, arrival at feed, and feeding intensity) was developed to characterize the responses of Pacific white shrimp (Penaeus vannamei) to chemical feeding stimuli. Controlled laboratory trials established both requisite experimental system design and reproducible responses by shrimp, permitting quantification of behavioral patterns and feed preferences. Responses to pelleted feed with and without a coating of commercial chemoattractant demonstrated that the chemoattractant improved perception of the feed and shortened response times (by as much as 50%). The strength of shrimp feeding responses was positively correlated with the degree of prior starvation.