Is cognition integral to psychopathology? A population-based cohort study

BACKGROUND

Lower cognitive functioning has been documented across psychiatric disorders and hypothesized to be a core deficit of mental disorders. Situating psychopathology and cognition as part of a unitary construct is therefore important to understanding the etiology of psychiatric disorders. The current study aims to test competing structural models of psychopathology and cognition in a large national cohort of adolescents.

METHODS

The analytic sample consisted of 1189 participants aged 16-17 years, screened by the Israeli Draft Board. Psychopathology was assessed using a modified version of the Brief Symptom Inventory, and cognition was assessed based on four standardized test scores ((1) mathematical reasoning, concentration, and concept manipulation; (2) visual-spatial problem-solving skills and nonverbal abstract reasoning; (3) verbal understanding; (4) categorization and verbal abstraction). Confirmatory factor analysis was implemented to compare competing structural models of psychopathology with and without cognition. Sensitivity analyses examined the models in different subpopulations.

RESULTS

Confirmatory factor analysis indicated a better model fit of psychopathological symptoms without cognition (RMSEA = 0.037; TLI = 0.991; CFI = 0.992) than with cognition (RMSEA = 0.04-0.042; TLI = 0.987-0.988; CFI = 0.988-0.989). Sensitivity analyses supported the robustness of these results with a single exception. Among participants with low cognitive abilities (N = 139), models that integrated psychopathological symptoms with cognition had a better fit compared to models of psychopathology without cognition.

CONCLUSIONS

The current study suggests that cognition and psychopathology are, generally, independent constructs. However, within low cognitive abilities, cognition was integral to the structure of psychopathology. Our results point toward an increased vulnerability to psychopathology in individuals with low cognitive abilities and may provide valuable information for clinicians.

[Automatic determination of mandibular landmarks based on three-dimensional mandibular average model]

OBJECTIVE

To explore an efficient and automatic method for determining the anatomical landmarks of three-dimensional(3D) mandibular data, and to preliminarily evaluate the performance of the method.

METHODS

The CT data of 40 patients with normal craniofacial morphology were collected (among them, 30 cases were used to establish the 3D mandibular average model, and 10 cases were used as test datasets to validate the performance of this method in determining the mandibular landmarks), and the 3D mandibular data were reconstructed in Mimics software. Among the 40 cases of mandibular data after the 3D reconstruction, 30 cases that were more similar to the mean value of Chinese mandibular features were selected, and the size of the mandibular data of 30 cases was normalized based on the Procrustes analysis algorithm in MATLAB software. Then, in the Geomagic Wrap software, the 3D mandibular average shape model of the above 30 mandibular data was constructed. Through symmetry processing, curvature sampling, index marking and other processing procedures, a 3D mandible structured template with 18 996 semi-landmarks and 19 indexed mandibular anatomical landmarks were constructed. The open source non-rigid registration algorithm program Meshmonk was used to match the 3D mandible template constructed above with the tested patient's 3D mandible data through non-rigid deformation, and 19 anatomical landmark positions of the patient's 3D mandible data were obtained. The accuracy of the research method was evaluated by comparing the distance error of the landmarks manually marked by stomatological experts with the landmarks marked by the method of this research.

RESULTS

The method of this study was applied to the data of 10 patients with normal mandibular morphology. The average distance error of 19 landmarks was 1.42 mm, of which the minimum errors were the apex of the coracoid process [right: (1.01±0.44) mm; left: (0.56±0.14) mm] and maximum errors were the anterior edge of the lowest point of anterior ramus [right: (2.52±0.95) mm; left: (2.57±1.10) mm], the average distance error of the midline landmarks was (1.15±0.60) mm, and the average distance error of the bilateral landmarks was (1.51±0.67) mm.

CONCLUSION

The automatic determination method of 3D mandibular anatomical landmarks based on 3D mandibular average shape model and non-rigid registration algorithm established in this study can effectively improve the efficiency of automatic labeling of 3D mandibular data features. The automatic determination of anatomical landmarks can basically meet the needs of oral clinical applications, and the labeling effect of deformed mandible data needs to be further tested.

Analysing tax-benefit reforms in the Netherlands using structural models and natural experiments

We combine the strengths of structural models and natural experiments in an analysis of tax-benefit reforms in the Netherlands. We first estimate structural discrete-choice models for labour supply. Next, we simulate key past reforms and compare the predictions of the structural model with the outcomes of quasi-experimental studies. The structural model predicts the treatment effects well. The structural model then allows us to conduct counterfactual policy analysis. Policies targeted at working mothers with young children generate the largest labour supply responses but generate little additional government revenue. Introducing a flat tax, basic income or joint taxation is not effective.

Differences in encounters, likeability and desirability of wildlife species among residents of a Greek city

Urbanization is ever-increasing worldwide and urban green spaces and their associated wildlife are becoming critically important for human well-being. Understanding public preferences for urban wildlife would allow urban planners and managers for designing successful management plans. 600 Greek urban residents were asked to rate their frequency of encounters, likeability and desirability to encounter more often 30 urban wildlife taxa. Factor analysis identified three groups varying in degree of encounters, likeability and desirability. The most likeable species were also the most desirable (butterfly, songbird, duck, tortoise, squirrel, feral pigeon, hedgehog, heron, little owl). Structural models revealed that likeability was the most significant and positive predictor of desirability, in all identified species desirability groups: desirable, undesirable and indifferent. Participation in environmental lifestyle and conservation actions and support of animal welfare were generally positive predictors of encounters, likeability and desirability in all identified groups. Age was a significant negative predictor of encounters in the desirable and undesirable groups, of likeability in the desirable group and of desirability in the indifferent group. Females liked more than males the desirable species, and less than males the undesirable and indifferent species, encountered more often than males the undesirable and indifferent species, and wished to encounter less often the undesirable species. More educated participants liked the indifferent species more than those less educated, while the former also wished to encounter the undesirable species more often than the latter. Pet owners encountered all species more often than non-pet owners, liked more the indifferent species and wished to encounter more often the desirable species than non-pet owners. Our findings revealed public preferences for wildlife species in urban green spaces. This information would be valuable for managing urban wildlife for the benefit of both people and wildlife, in the study area and elsewhere, especially in areas where similar species occur.

Cognitive behavioral therapy reduces illness perceptions and anxiety symptoms in patients with unruptured intracranial aneurysm

The main purpose of this study was to assess the relation between cognitive behavioral therapy and possible changes in illness perceptions and anxiety in patients diagnosed with unruptured intracranial aneurysm. An observational study of an intervention with 67 patients with an unruptured intracranial aneurysm from two medical centers in a Colombian city (n = 35 on the intervention group) was carried out. To assess changes, measurements were taken at baseline and at one-year follow-up with the Beck Anxiety Inventory and the Illness Perception Questionnaire, brief version, taking into account the importance of perceptions in the process of adjusting to illness and acquiring healthy life habits. Hypotheses were tested by a structural model. The results obtained from this study showed that illness perceptions were related to anxiety levels at both time points; however, the relations were stronger before cognitive behavioral therapy (βt0 = 0.61, p < 0.01; βt1 = 0.37, p < 0.01). Cognitive behavioral therapy was found to be a moderator of changes in both illness perceptions and anxiety at the time of follow-up (β = -0.31, p < 0.01; β = -0.26, p < 0.01). The structural model suggests that cognitive behavioral therapy is associated with less anxiety (β = -0.17, p < 0.05) and better illness perceptions (β = -0.35, p < 0.01) in patients diagnosed with unruptured intracranial aneurysms.

[Testing a Model to Predict Problem Gambling in Speculative Game Users]

PURPOSE

The purpose of the study was to develop and test a model for predicting problem gambling in speculative game users based on Blaszczynski and Nower's pathways model of problem and pathological gambling.

METHODS

The participants were 262 speculative game users recruited from seven speculative gambling places located in Seoul, Gangwon, and Gyeonggi, Korea. They completed a structured self-report questionnaire comprising measures of problem gambling, negative emotions, attentional impulsivity, motor impulsivity, non-planning impulsivity, gambler's fallacy, and gambling self-efficacy. Structural Equation Modeling was used to test the hypothesized model and to examine the direct and indirect effects on problem gambling in speculative game users using SPSS 22.0 and AMOS 20.0 programs.

RESULTS

The hypothetical research model provided a reasonable fit to the data. Negative emotions, motor impulsivity, gambler's fallacy, and gambling self-efficacy had direct effects on problem gambling in speculative game users, while indirect effects were reported for negative emotions, motor impulsivity, and gambler's fallacy. These predictors explained 75.2% problem gambling in speculative game users.

CONCLUSION

The findings suggest that developing intervention programs to reduce negative emotions, motor impulsivity, and gambler's fallacy, and to increase gambling self-efficacy in speculative game users are needed to prevent their problem gambling.

Computational Biochemistry-Enzyme Mechanisms Explored

Understanding enzyme mechanisms is a major task to achieve in order to comprehend how living cells work. Recent advances in biomolecular research provide huge amount of data on enzyme kinetics and structure. The analysis of diverse experimental results and their combination into an overall picture is, however, often challenging. Microscopic details of the enzymatic processes are often anticipated based on several hints from macroscopic experimental data. Computational biochemistry aims at creation of a computational model of an enzyme in order to explain microscopic details of the catalytic process and reproduce or predict macroscopic experimental findings. Results of such computations are in part complementary to experimental data and provide an explanation of a biochemical process at the microscopic level. In order to evaluate the mechanism of an enzyme, a structural model is constructed which can be analyzed by several theoretical approaches. Several simulation methods can and should be combined to get a reliable picture of the process of interest. Furthermore, abstract models of biological systems can be constructed combining computational and experimental data. In this review, we discuss structural computational models of enzymatic systems. We first discuss various models to simulate enzyme catalysis. Furthermore, we review various approaches how to characterize the enzyme mechanism both qualitatively and quantitatively using different modeling approaches.

[A Structural Model for Premenstrual Coping in University Students: Based on Biopsychosocial Model]

PURPOSE

The aims of this study were to construct a hypothetical structural model which explains premenstrual coping in university students and to test the fitness with collected data.

METHODS

Participants were 206 unmarried women university students from 3 universities in A and B cities. Data were collected from March 29 until April 30, 2016 using self-report structured questionnaires and were analyzed using IBM SPSS 23.0 and AMOS 18.0.

RESULTS

Physiological factor was identified as a significant predictor of premenstrual syndrome (t=6.45, p<.001). This model explained 22.1% of the variance in premenstrual syndrome. Psychological factors (t=-2.49, p=.013) and premenstrual syndrome (t=8.17, p<.001) were identified as significant predictors of premenstrual coping. Also this model explained 30.9% of the variance in premenstrual coping in university students. A physiological factors directly influenced premenstrual syndrome (β=.41, p=.012). Premenstrual syndrome (β=.55, p=.005) and physiological factor (β=.23, p=.015) had significant total effects on premenstrual coping. Physiological factor did not have a direct influence on premenstrual coping, but indirectly affected it (β=.22, p=.007). Psychological factors did not have an indirect or total effect on premenstrual coping, but directly affected it (β=-.17, p=.036).

CONCLUSION

These findings suggest that strategies to control physiological factors such as menstrual pain should be helpful to improve premenstrual syndrome symptoms. When developing a program to improve premenstrual coping ability and quality of menstrual related health, it is important to consider psychological factors including perceived stress and menstrual attitude and premenstrual syndrome.

Genetic and structural study of DNA-directed RNA polymerase II of Trypanosoma brucei, towards the designing of novel antiparasitic agents

Trypanosoma brucei brucei (TBB) belongs to the unicellular parasitic protozoa organisms, specifically to the Trypanosoma genus of the Trypanosomatidae class. A variety of different vertebrate species can be infected by TBB, including humans and animals. Under particular conditions, the TBB can be hosted by wild and domestic animals; therefore, an important reservoir of infection always remains available to transmit through tsetse flies. Although the TBB parasite is one of the leading causes of death in the most underdeveloped countries, to date there is neither vaccination available nor any drug against TBB infection. The subunit RPB1 of the TBB DNA-directed RNA polymerase II (DdRpII) constitutes an ideal target for the design of novel inhibitors, since it is instrumental role is vital for the parasite’s survival, proliferation, and transmission. A major goal of the described study is to provide insights for novel anti-TBB agents via a state-of-the-art drug discovery approach of the TBB DdRpII RPB1. In an attempt to understand the function and action mechanisms of this parasite enzyme related to its molecular structure, an in-depth evolutionary study has been conducted in parallel to the in silico molecular designing of the 3D enzyme model, based on state-of-the-art comparative modelling and molecular dynamics techniques. Based on the evolutionary studies results nine new invariant, first-time reported, highly conserved regions have been identified within the DdRpII family enzymes. Consequently, those patches have been examined both at the sequence and structural level and have been evaluated in regard to their pharmacological targeting appropriateness. Finally, the pharmacophore elucidation study enabled us to virtually in silico screen hundreds of compounds and evaluate their interaction capabilities with the enzyme. It was found that a series of chlorine-rich set of compounds were the optimal inhibitors for the TBB DdRpII RPB1 enzyme. All-in-all, herein we present a series of new sites on the TBB DdRpII RPB1 of high pharmacological interest, alongside the construction of the 3D model of the enzyme and the suggestion of a new in silico pharmacophore model for fast screening of potential inhibiting agents.

[A structural model for primiparas' breastfeeding behavior]

PURPOSE

The study was done to construct and test a structural model to explain primipara breastfeeding behavior.

METHODS

The participants were 213 primiparas on postpartum wards. Data were analyzed using the PASW 18.0 and AMOS 19.0 programs.

RESULTS

Fitness statistics for the hypothetical model were appropriate (χ² =38.50, p=.070, GFI=.96, RMSEA=.05, AGFI=.93, NFI=.95, TLI=.97, CFI=.98, PNFI=.57, χ²/df=1.43). Breastfeeding behaviors were directly influenced by intention to breastfeed, perceived effectiveness of breastfeeding, and the amount of supplementary feeding. The amount of supplementary feeding had the largest direct impact on breastfeeding behavior. The largest total effect on breastfeeding behavior was intention to breastfeed. The environment of the maternity hospital indirectly influenced breastfeeding behavior. These factors explained 18.9% of variance in the primipara breastfeeding behavior.

CONCLUSION

The results of the study indicate that in order to promote primipara breastfeeding the amount of supplementary feeding immediately after the birth should be limited and an environment that encourages exclusive breastfeeding in the hospital should be provided. The results also suggest it is necessary to provide nursing interventions that increase the intention to breastfeed and the perceived effectiveness of breastfeeding.