Adequate Descriptors Research Articles

Breast cancer: A fractal approach, scaling analysis and quantum cluster algorithm

Tumor growth in the breast is a complex process, understanding this type of phenomenon is important in order to establish adequate strategies at diagnostic and therapeutic levels, beginning with the evaluation morphology, through adequate descriptors. Scaling analysis is used to extract parameters such as exponents of local roughness and fractal dimension, which characterize tumor growth. The results show that invasive lobular and ductal tumors in situ behave as proposed by Family-Vicsek (Family and Vicsek, 1991), while benign tumors behave differently.

Big Gods and Big Rituals

This short article reviews recent claims made about large-scale rituals and moralizing gods for the formation of large-scale societies. It starts from a reconstruction of the actual contents of the claims made in very different forms and wording and points to the very vague suggestions about causal relationships or chronological coincidence. Against these claims, three main arguments are advanced. First, it is difficult to formulate a model of trans-locally standardized rituals that would be able to keep together trans-local societies without the existence of secondary media, above all writing, which would be an even more important factor in processes of homogenization. Secondly, historically religion can be shown to serve as frequently for stabilizing distinction and dissent as for producing unity. Thirdly and finally, the very possibility of an exhaustive and stable classificatory grid across cultures and epochs is questioned. In a brief final case study, the lack of adequate descriptors in the database under review is demonstrated for ancient Rome.

Navigating Concepts in the Human Mind Unravels the Latent Geometry of Its Semantic Space

Mechanisms for retrieving basic knowledge in the human mind are still unknown. Exploration is usually represented by cognitive units, i.e., concepts, linked together by associative relationships forming semantic networks. However, understanding how humans navigate such networks remains elusive, because the underlying topology of concepts cannot be observed directly, and only functional representations are accessible. Here, we overcome those limitations and show that the hypothesis of an underlying, latent geometry characterizing the human mind is plausible. We characterize this geometry by means of adequate descriptors for exploring and navigating dynamics, demonstrating that they can capture the differences between healthy subjects and patients at different stages of dementia. Our results provide the first fundamental step to develop a new unifying conceptual and computational framework that can be used to support the assessment of neurodegenerative diseases from language and semantic memory retrieval tasks, as well as helping develop targeted nonpharmacological therapies to maintain residual cognitive capacity.

Statistical mitigation of COVID-19 pandemic disruptions to growth data collection in clinical studies

Rationale: Conducting clinical trials during the pandemic is fraught with challenges like missed visits/ procedures, visits out of window, and subject discontinuation. We seek to show that predictive growth models are adequate descriptors of infant weight (wt), length (ln), and head circumference (hc) under various patterns of missing and visits outside protocol windows.

Network structure and the optimization of proximity‐based association criteria

Abstract Animal social network analysis (SNA) often uses proximity data obtained from automated tracking of individuals. Identifying associations based on proximity requires deciding on quantitative criteria such as the maximum distance or the longest time interval between visits of different individuals to still consider them associated. These quantitative criteria are not easily chosen based on a priori biological arguments alone. Here we propose a procedure for optimizing proximity‐based association criteria in SNA, whereby different spatial and temporal criteria are screened to determine which combination detects more network structure. If we assume that biologically relevant associations among individuals are non‐random, and that proximity data are mostly influenced by those associations, then it is logical to select criteria that minimise random associations and show the underlying network structure more clearly. We first used simulations to evaluate which of four simple descriptors of network structure remain unbiased (i.e. do not change directionally) when reducing the number of observations, since unbiased descriptors are necessary for comparing the structure of networks using different association criteria. Then, using two of those descriptors (coefficient of variation of the strength of associations and network entropy) and empirical proximity data from automated tracking of common waxbills Estrilda astrild in a mesocosm environment, we found that the structure‐based optimization procedure selected the most biologically relevant combination of spatial and temporal proximity criteria, in the sense that those criteria were also the best at distinguishing between previously known social subgroups of individuals. These results indicate that, provided that the assumptions for structure‐based optimization are met, this procedure can find the most biologically relevant association criteria. Thus, under the condition that proximity data are shaped by non‐random social associations, and if using adequate descriptors of network structure, structure‐based optimization may be a useful tool for SNA, particularly when a priori biological arguments are insufficient to inform the choice of proximity‐based association criteria.

Origin Authentication of Pork Fat via Elemental Composition, Isotope Ratios, and Multivariate Chemometric Analyses

Globalization has resulted in the availability of food products from other countries, and therefore today consumers are concerned to know the origin of their food. Efficient analytical techniques are required to guarantee accurate labeling and the authentication of the food origin. This study was designed to analyze pork belly fat from USA, Spain, Canada, Germany, Mexico, Chile and South Korea for elemental composition and isotope ratios and multivariate chemometric analyses were employed to authenticate the geographical origins of the samples. The concentrations of macroelements were in the order of potassium > phosphorus > sodium > sulfur > calcium > aluminum > zinc > iron while the trace elements were below the safe limits. The isotope ratios for 87Sr/84Sr, 52Cr/50Cr, and 71Ga/69Ga were comparatively high. Linear discriminant analysis and principal component analysis distinguished the samples to 98.2%. Lithium, strontium, arsenic, chromium, vanadium, manganese, nickel, and cadmium were considered to be adequate descriptors for pork origin authentication.

An efficient similarity search using a combination between descriptors: a case of study in human face recognition

Face recognition is one of the important fields of search in computer vision. Its principle consists to look for images that represent the similar faces to a given face image the image request. This process is done by extracting a set of features of the request image then making comparison between features generated by the request one and the others extracted from whole face image database. Recently, numerous face representation and classification methods have been proposed in the literature. Nevertheless, many issues related to indexing, combination of adequate descriptors and time computing have not yet been solved. In this paper, we deal with problems related to features combination and this, by conceiving a preformat content-based image retrieval that is mainly oriented to handle face authentication challenges. Its convivial interface allows to user the selection of appropriate weighting coefficient values associate to each feature based on human judgment in order to enhance the retrieval performance. We have tested our proposed method on ORL database by using a set of known features. The obtained results show the performance of our proposed method.

Sexual dimorphism in the catfish Genidens genidens (Siluriformes: Ariidae) based on otolith morphometry and relative growth

ABSTRACT Genidens genidens is a species susceptible to population declines in view of their reproductive biology peculiarities. Morphometric differences between sexes are observed in the literature, and these differences should also be evident in otolith development. Growth patterns are one of the most important biological characteristics regarding population dynamics and management. In this context, the aim of the present study is to describe this species relative growth and identify differences between sex life cycles. Somatic growth-otolith growth relationships and somatic length-weight relationships were estimated based on two methodologies; the Huxley and the polyphasic allometric models. Both models demonstrated different growth patterns between sexes. The three axes of otolith growth were adequate descriptors of growth, and the results of the Huxley model demonstrated distinct growth patterns between sexes, with male otoliths larger in all three measured axes. In the polyphase model, male otoliths were thicker, while female otoliths were longer and higher. Both sexes presented similar length-weight relationships, which may indicate that oocyte production and parental care lead to similar costs for this species.

Binding and Release between Polymeric Carrier and Protein Drug: pH-Mediated Interplay of Coulomb Forces, Hydrogen Bonding, van der Waals Interactions, and Entropy.

The accelerating search for new types of drugs and delivery strategies poses challenge to understanding the mechanism of delivery. To this end, a detailed atomistic picture of binding between the drug and carrier is quintessential. Although many studies focus on the electrostatics of drug-vector interactions, it has also been pointed out that entropic factors relating to water and counterions can play an important role. By carrying out extensive molecular dynamics simulations and subsequently validating with experiments, we shed light herein on the binding in aqueous solution between a protein drug and polymeric carrier. We examined the complexation between the polymer poly(ethylene glycol) methyl ether acrylate-b-poly(carboxyethyl acrylate (PEGMEA-b-PCEA) and the protein egg white lysozyme, a system that acts as a model for polymer-vector/protein-drug delivery systems. The complexation has been visualized and characterized using contact maps and hydrogen bonding analyses for five independent simulations of the complex, each running over 100 ns. Binding at physiological pH is, as expected, mediated by Coulombic attraction between the positively charged protein and negatively charged carboxylate groups on the polymer. However, we find that consideration of electrostatics alone is insufficient to explain the complexation behavior at low pH. Intracomplex hydrogen bonds, van der Waals interactions, as well as water-water interactions dictate that the polymer does not release the protein at pH 4.8 or indeed at pH 3.2 even though the Coulombic attractions are largely removed as carboxylate groups on the polymer become titrated. Experiments in aqueous solution carried out at pH 7.0, 4.5, and 3.0 confirm the veracity of the computed binding behavior. Overall, these combined simulation and experimental results illustrate that coulomb interactions need to be complemented with consideration of other entropic forces, mediated by van der Waals interactions and hydrogen bonding, to search for adequate descriptors to predict binding and release properties of polymer-protein complexes. Advances in computational power over the past decade make atomistic molecular dynamics simulations such as implemented here one of the few avenues currently available to elucidate the complexity of these interactions and provide insights toward finding adequate descriptors. Thus, there remains much room for improvement of design principles for efficient capture and release delivery systems.

On the formation of multiple local peaks in breakthrough curves

AbstractThe analysis of breakthrough curves (BTCs) is of interest in hydrogeology as a way to parameterize and explain processes related to anomalous transport. Classical BTCs assume the presence of a single peak in the curve, where the location and size of the peak and the slope of the receding limb has been of particular interest. As more information is incorporated into BTCs (for example, with high‐frequency data collection, supercomputing efforts), it is likely that classical definitions of BTC shapes will no longer be adequate descriptors for contaminant transport problems. We contend that individual BTCs may display multiple local peaks depending on the hydrogeologic conditions and the solute travel distance. In such cases, classical definitions should be reconsidered. In this work, the presence of local peaks in BTCs is quantified from high‐resolution numerical simulations in synthetic fields with a particle tracking technique and a kernel density estimator to avoid either overly jagged or smoothed curves that could mask the results. Individual BTCs from three‐dimensional heterogeneous hydraulic conductivity fields with varying combinations of statistical anisotropy, heterogeneity models, and local dispersivity are assessed as a function of travel distance. The number of local peaks, their corresponding slopes, and a transport connectivity index are shown to strongly depend on statistical anisotropy and travel distance. Results show that the choice of heterogeneity model also affects the frequency of local peaks, but the slope is less sensitive to model selection. We also discuss how solute shearing and rerouting can be determined from local peak quantification.

Pharmacokinetics of plasma-derived and recombinant factor IX - implications for prophylaxis and on-demand therapy

Plasma-derived (pd) and recombinant (r) factor IX (FIX) differ in pharmacokinetic (PK) properties. These differences and their clinical implications have been debated since the introduction of rFIX. The aim of this review was to describe the comparative disposition of pdFIX and rFIX and will for this purpose begin with an overview of population PK modelling. In contrast to the model-independent method, a population PK model can analyse sparse data sets obtained in various settings, provide parameter values that can be used to predict coagulation factor levels with any kind of single or multiple dosing and include statistical analysis of variation between individuals. Population modelling has also clearly demonstrated the difference in PK between pdFIX and rFIX. Their distribution characteristics influence the FIX coagulant activity (FIX:C) level vs. time curve during the early hours after infusion. In vivo recovery and elimination half-life are consequently not adequate descriptors of the effective PK of FIX, and for new analogues with modified PK, differences in distribution might be clinically important. Calculated doses to maintain 1% trough levels during twice-weekly prophylactic treatment are considerably higher with rFIX than with pdFIX and roughly correspond to dosing in clinical studies. However, the putative relationship between FIX:C trough level and therapeutic outcome has never been confirmed in a clinical trial. Comparative studies on prophylaxis with different types of FIX are needed.

On analysis of circle moments and texture features for cartridge images recognition

Even though rapid advances in intelligent firearm identification have been made in recently years, the major practical and theoretical problems are still unsolved. From the practical point of view, capturing high quality images from ballistics specimen is a difficult task. From the theoretical point of view, extracting the descriptive features from projectile and cartridge images is an open research question in firearm identification. The aim of this paper is to address the research issues with respect to feature extraction and intelligent ballistics recognition. In this paper, different image processing techniques are employed for digitizing the ballistics images. Due to some segments in an image systematically distributed by the image’s geometrical circular center, the existing moment invariants however cannot extract the required pattern features for intelligent recognition. This paper presents the novel feature set called circle moment invariants to overcome the shortcoming of existing moment invariants. In addition, an intelligent system is designed for classifying and evaluating the extracted features of ballistics images. The experimental results indicate that the proposed approach and feature criteria are capable of classifying the cartridge images very efficiently and effectively. Consequently, the circle moment invariants are proved to be the adequate descriptors for describing the pattern features in cartridge images.

ASYMMETRY OF GENETIC VARIATION IN FITNESS-RELATED TRAITS: APPARENT STABILIZING SELECTION ONgmax

The maintenance of genetic variation in traits closely associated with fitness remains a key unresolved issue in evolutionary genetics. One important qualification on the observation of genetic variation in fitness-related traits is that such traits respond asymmetrically to selection, evolving to a greater extent in the direction of lower fitness. Here we test the hypothesis that standing genetic variation in fitness-related traits is principally maintained for unfit phenotypes. Male Drosophila bunnanda vary in mating success (the primary determinant of male fitness) due to female mate choice. We used competitive mating success to partitioning males into two groups: successful (high fitness) and unsuccessful (low fitness). Relative to successful males, unsuccessful males harbored considerably greater levels of additive genetic variation for sexual signaling traits. This genetic asymmetry was detected for a multivariate trait that we demonstrated was not directly under stabilizing sexual selection, leading us to conclude the trait was under apparent stabilizing selection. Consequently, our results suggest genetic variance might be biased toward low fitness even for traits that are not themselves the direct targets of selection. Simple metrics of genetic variance are unlikely to be adequate descriptors of the complex nature of the genetic basis of traits under selection.

Validity of the Walking Scale for Spinal Cord Injury and Other Domains of Function in a Multicenter Clinical Trial

Objective. To demonstrate criterion (concurrent and predictive) and construct validity of the Walking Index for Spinal Cord Injury (WISCI) scale and other walking measures in the Spinal Cord Injury Locomotor Trial (SCILT). Design. Prospective multicenter clinical trial of a walking intervention for patients with acute traumatic spinal cord injury (SCI). Participants/Methods. Body weight−supported treadmill training was compared to overground mobility training in 146 patients with incomplete SCI (C4 to L3) enrolled within 8 weeks of onset and treated for 12 weeks. Primary outcome measures were the Functional Independence Measure (FIM), 50-foot walking speed (50FW-S), and 6-minute walking distance (6MW-D), tested 3, 6, and 12 months after entry. Secondary measures were the Lower Extremity Motor Score (LEMS), Berg Balance Scale (BBS), WISCI, and FIM locomotor score (LFIM), assessed at 6 centers by blinded observers. Data for the 2 arms were combined since no significant differences in outcomes had been found. Results. Correlations with WISCI at 6 months were significant with BBS (r = .90), LEMS (r = .85), LFIM (r = .89), FIM (r = .77), 50FW-S (r = .85), and 6MW-D ( r = .79); similar correlations occurred at 3 and 12 months. Correlations of change scores from baseline WISCI were significant for change scores from baseline of LEMS/BBS/LFIM. Correlation of baseline LEMS and WISCI at 12 months were most significant (r = .73). The R 2 of baseline LEMS explained 57% of variability of WISCI levels at 3 months. Conclusion. Concurrent validity of the WISCI scale was supported by significant correlations with all measures at 3, 6, and 12 months. Correlation of change scores supports predictive validity. The LEMS at baseline was the best predictor of the WISCI score at 12 months and explained most of the variance, which supported both predictive and construct validity. The combination of the LEMS, BBS, WISCI, 50FW-S, and LFIM appears to encompass adequate descriptors for outcomes of walking trials for incomplete SCI.

Phenolysis and benzenethiolysis reactions of carbonyl and thiocarbonyl compounds from the perspective of the HSAB principle

Global and local DFT-based reactivity descriptors are used to characterize phenolysis and benzenethiolysis reactions of methyl 2,4-dinitrophenyl carbonate, O-ethyl 2,4-dinitrophenyl thiolcarbonate, methyl 2,4-dinitrophenyl thionocarbonate and O-ethyl 2,4-dinitrophenyl dithiocarbonate. The conceptual framework to rationalize the trends observed in reaction rate constants and to explain the main reaction product encountered experimentally is provided by the Pearson’s HSAB principle. Molecular hardness of the reactant molecules indicate that the reactions are favored when hard–hard or soft–soft interactions are present. Local softness are found to be the most adequate descriptors to characterize local interactions that might be driving the phenolysis and benzenethiolysis reactions.

Content-based retrieval of 3D models

In the past few years, there has been an increasing availability of technologies for the acquisition of digital 3D models of real objects and the consequent use of these models in a variety of applications, in medicine, engineering, and cultural heritage. In this framework, content-based retrieval of 3D objects is becoming an important subject of research, and finding adequate descriptors to capture global or local characteristics of the shape has become one of the main investigation goals. In this article, we present a comparative analysis of a few different solutions for description and retrieval by similarity of 3D models that are representative of the principal classes of approaches proposed. We have developed an experimental analysis by comparing these methods according to their robustness to deformations, the ability to capture an object's structural complexity, and the resolution at which models are considered.

Physical and biochemical averaged vertical profiles in the Mediterranean regions: an important tool to trace the climatology of water masses and to validate incoming data from operational oceanography

Seasonally and spatially averaged vertical profiles of temperature, salinity, dissolved oxygen, nutrients and chlorophyll- a have been computed from in situ observations in different regions of the Mediterranean Sea using the recently released EU/MEDAR/MEDATLAS II and EU/MTPII/MATER databases. The regions have been defined according to known dynamics important in the formation, transformation and spreading of the main water masses that circulate in the upper, intermediate and deep layers. The climatological characteristics of temperature and salinity reflect the water mass structures and the general thermohaline circulation patterns. Spatial and temporal variations on a seasonal basis of nutrients and principal biological parameters are described along with some aspects of the trophic conditions of the Mediterranean Sea. The strongest signal of variability is along the vertical; however, horizontal inhomogeneities are mostly associated with the internal dynamics. The distribution of the biochemical elements, in conjunction with hydrographic measurements of temperature and salinity, may serve as appropriate tracers for the characterisation of the main water masses (Atlantic Water, Levantine Intermediate Water and Bottom Water in the eastern and eastern basins) throughout the Mediterranean Sea. In a first approach, adequate descriptors of water properties have been obtained, useful for the quality control of incoming data in large databases and in setting-up documented procedures to improve future data management practices. Secondly, the biochemical climatological characteristics addressed in this paper are verified to be consistent with the physics of the Mediterranean Sea and are conceived useful to initialise coupled physical–biological models. The full set of spatially averaged vertical profiles can be found and downloaded from the World Wide Web data server established at OGS ( http://doga.ogs.trieste.it/medar/climatologies/).

Larval development of the New Zealand geoduck Panopea zelandica (Bivalvia: Hiatellidae)

The larval development of the New Zealand geoduck, Panopea zelandica, grown under culture conditions, was described through measurements of shell morphometry using video image analysis, photomicrographs, and scanning electron microscopy (SEM). Gametes were stripped from ripe broodstock and eggs fertilised with a dilute sperm solution. Developing larvae were maintained at 17 ± 1°C. Fertilised eggs developed into trochophores within 12 h and to D‐stage larvae (105.3 μm shell length) within 24 h. Larvae spontaneously settled after c. 16 days at c. 247 μm shell length. Measurements of shell morphology, including total length, total height, hinge length, length of anterior end, and umbo length and height were adequate descriptors of larval development. SEM indicated that the provinculum of D‐stage and developing veliger larvae lacked any teeth, although there was some development of a small lamelliform tooth on the hinge structure of newly settled post‐larvae. Prominent spines common on dissoconch shells of other hiatellid clams were absent in newly settled post‐larvae of P. zelandica. The data presented here are the first description of the larval development and larval biology of P. zelandica. The relative ease of spawning and rearing of P. zelandica suggests that the development of commercial hatchery technology for this species warrants further investigation.

VSMP: a novel variable selection and modeling method based on the prediction.

The use of numerous descriptors that are indicative of molecular structure and topology is becoming more common in quantitative structure-activity relationship (QSAR). How to choose the adequate descriptors for QSAR studies is important but difficult because there are no absolute rules to govern this choice. A variety of variable selection techniques including stepwise, partial least squares/principal component analysis (PLS/PCA), neural network, and evolutionary algorithm such as genetic algorithm have been applied to this common problem. All-subsets regression (ASR) is capable of finding out the best variable subset from among a large pool. In this paper, a novel variable selection and modeling method based on the prediction, for short VSMP, has been developed. Here two controllable parameters, the interrelation coefficient between the pairs of the independent variables (r(int)) and the correlation coefficient (q(2)) obtained using the leave-one-out (LOO) cross-validation technique, are introduced into the ASR to improve its performances. This technique differs from the other variable selection procedures related to the ASR by two main features: (1) The search of various optimal subset search is controlled by the statistic q(2) or root-mean-square error (RMSEP) in the LOO cross-validation step rather than the correlation coefficient obtained in the modeling step (r(2)). (2) The searching speed of all optimal subsets is expedited by the statistic r(int) together with q(2). A comparison of the results of the VSMP applied to the Selwood data set (n = 31 compounds, m = 53 descriptors) with those obtained from alternative algorithms shows the good performance of the technique.

Liposome-water and octanol-water partitioning of alcohol ethoxylates.

Liposome-water partitioning coefficients, (Klipw s), were determined for eight pure alcohol ethoxylates using equilibrium dialysis and ultracentrifugation. Both methods yielded statistically indistinguishable results. The experimentally determined log Klipw s were compared with log Kow values estimated with the fragment method using different literature sources for the fragment constants. Fragments of log Klipw were calculated for the ethoxy group (EO) and the -CH2 - units from the experimentally determined data. An additional -CH2 - unit causes an average increase of log Klipw by 0.45, and an additional EO causes an average decrease of log Klipw by -0.12. With these fragments, the quality of log Klipw estimations can be improved significantly as compared to simple linear regression of log Klipw versus log Kow . The Klipw values calculated according to the new fragment method for pure compounds and for commercial mixtures are shown to be adequate descriptors for quantitative structure-activity relationships of bioaccumulation, toxicity, and sorption to natural organic material.