Attachment styles and personal growth following romantic breakups: The mediating roles of distress, rumination, and tendency to rebound

© 2013 Marshall et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.This article has been made available through the Brunel Open Access Publishing Fund.The purpose of this research was to examine the associations of attachment anxiety and avoidance with personal growth following relationship dissolution, and to test breakup distress, rumination, and tendency to rebound with new partners as mediators of these associations. Study 1 (N = 411) and Study 2 (N = 465) measured attachment style, breakup distress, and personal growth; Study 2 additionally measured ruminative reflection, brooding, and proclivity to rebound with new partners. Structural equation modelling revealed in both studies that anxiety was indirectly associated with greater personal growth through heightened breakup distress, whereas avoidance was indirectly associated with lower personal growth through inhibited breakup distress. Study 2 further showed that the positive association of breakup distress with personal growth was accounted for by enhanced reflection and brooding, and that anxious individuals’ greater personal growth was also explained by their proclivity to rebound. These findings suggest that anxious individuals’ hyperactivated breakup distress may act as a catalyst for personal growth by promoting the cognitive processing of breakup-related thoughts and emotions, whereas avoidant individuals’ deactivated distress may inhibit personal growth by suppressing this cognitive work

Using twins to better understand sibling relationships

We compared the nature of the sibling relationship in dyads of varying genetic relatedness, employing a behavioural genetic design to estimate the contribution that genes and the environment have on this familial bond. Two samples were used—the Sisters and Brothers Study consisted of 173 families with two target non-twin children (mean ages = 7.42 and 5.22 years respectively); and the Twins, Family and Behaviour study included 234 families with two target twin children (mean age = 4.70 years). Mothers and fathers reported on their children’s relationship with each other, via a postal questionnaire (the Sisters and Brothers Study) or a telephone interview (the Twins, Family and Behaviour study). Contrary to expectations, no mean level differences emerged when monozygotic twin pairs, dizygotic twin pairs, and non-twin pairs were compared on their sibling relationship quality. Behavioural genetic analyses also revealed that the sibling bond was modestly to moderately influenced by the genetic propensities of the children within the dyad, and moderately to substantially influenced by the shared environment common to both siblings. In addition, for sibling negativity, we found evidence of twin-specific environmental influence—dizygotic twins showed more reciprocity than did non-twins. Our findings have repercussions for the broader application of results from future twin-based investigations

Attachment, infidelity, and loneliness in college students involved in a romantic relationship: the role of relationship satisfaction, morbidity and prayer for partner

This study examined the mediating effects of relationship satisfaction, prayer for a partner, and morbidity in the relationship between attachment and loneliness, infidelity and loneliness, and psychological morbidity and loneliness, in college students involved in a romantic relationship. Participants were students in an introductory course on family development. This study examined only students (n = 345) who were involved in a romantic relationship. The average age of participants was 19.46 (SD = 1.92) and 25 % were males. Short-form UCLA Loneliness Scale (ULS-8), (Hays and DiMatteo in J Pers Assess 51:69–81, doi:10.1207/s15327752jpa5101_6, 1987); Relationship Satisfaction Scale (Funk and Rogge in J Fam Psychol 21:572–583, doi:10.1037/0893-3200.21.4.572, 2007); Rotterdam Symptom Checklist (De Haes et al. in Measuring the quality of life of cancer patients with the Rotterdam Symptom Checklist (RSCL): a manual, Northern Centre for Healthcare Research, Groningen, 1996); Prayer for Partner Scale, (Fincham et al. in J Pers Soc Psychol 99:649–659, doi:10.1037/a0019628, 2010); Infidelity Scale, (Drigotas et al. in J Pers Soc Psychol 77:509–524, doi:10.1037/0022-3514.77.3.509, 1999); and the Experiences in Close Relationship Scale-short form (Wei et al. in J Couns Psychol 52(4):602–614, doi:10.1037/0022-0167.52.4.602, 2005). Results showed that relationship satisfaction mediated the relationship between avoidance attachment and loneliness and between infidelity and loneliness. Physical morbidity mediated the relationship between anxious attachment and psychological morbidity. Psychological morbidity mediated the relationship between anxious attachment and physical morbidity. The present results expand the literature on attachment by presenting evidence that anxious and avoidant partners experience loneliness differently. Implications for couple’s therapy are addressed. Future research should replicate these results with older samples and married couples.Acknowledgments This research was supported by Grant Number 90FE0022 from the United States Department of Health and Human Services awarded to the last author

Gene encoder: a feature selection technique through unsupervised deep learning-based clustering for large gene expression data

© 2020, Springer-Verlag London Ltd., part of Springer Nature. Cancer is a severe condition of uncontrolled cell division that results in a tumor formation that spreads to other tissues of the body. Therefore, the development of new medication and treatment methods for this is in demand. Classification of microarray data plays a vital role in handling such situations. The relevant gene selection is an important step for the classification of microarray data. This work presents gene encoder, an unsupervised two-stage feature selection technique for the cancer samples’ classification. The first stage aggregates three filter methods, namely principal component analysis, correlation, and spectral-based feature selection techniques. Next, the genetic algorithm is used, which evaluates the chromosome utilizing the autoencoder-based clustering. The resultant feature subset is used for the classification task. Three classifiers, namely support vector machine, k-nearest neighbors, and random forest, are used in this work to avoid the dependency on any one classifier. Six benchmark gene expression datasets are used for the performance evaluation, and a comparison is made with four state-of-the-art related algorithms. Three sets of experiments are carried out to evaluate the proposed method. These experiments are for the evaluation of the selected features based on sample-based clustering, adjusting optimal parameters, and for selecting better performing classifier. The comparison is based on accuracy, recall, false positive rate, precision, F-measure, and entropy. The obtained results suggest better performance of the current proposal

A New Method to Address Unmet Needs for Extracting Individual Cell Migration Features from a Large Number of Cells Embedded in 3D Volumes

Background: In vitro cell observation has been widely used by biologists and pharmacologists for screening molecule-induced effects on cancer cells. Computer-assisted time-lapse microscopy enables automated live cell imaging in vitro, enabling cell behavior characterization through image analysis, in particular regarding cell migration. In this context, 3D cell assays in transparent matrix gels have been developed to provide more realistic in vitro 3D environments for monitoring cell migration (fundamentally different from cell motility behavior observed in 2D), which is related to the spread of cancer and metastases. Methodology/Principal Findings: In this paper we propose an improved automated tracking method that is designed to robustly and individually follow a large number of unlabeled cells observed under phase-contrast microscopy in 3D gels. The method automatically detects and tracks individual cells across a sequence of acquired volumes, using a template matching filtering method that in turn allows for robust detection and mean-shift tracking. The robustness of the method results from detecting and managing the cases where two cell (mean-shift) trackers converge to the same point. The resulting trajectories quantify cell migration through statistical analysis of 3D trajectory descriptors. We manually validated the method and observed efficient cell detection and a low tracking error rate (6%). We also applied the method in a real biological experiment where the pro-migratory effects of hyaluronic acid (HA) were analyzed on brain cancer cells. Using collagen gels with increased HA proportions, we were able to evidence a dose-response effect on cell migration abilities. Conclusions/Significance: The developed method enables biomedical researchers to automatically and robustly quantify the pro- or anti-migratory effects of different experimental conditions on unlabeled cell cultures in a 3D environment. © 2011 Adanja et al.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Calibrating ADL-IADL scales to improve measurement accuracy and to extend the disability construct into the preclinical range: a systematic review

<p>Abstract</p> <p>Background</p> <p>Interest in measuring functional status among nondisabled older adults has increased in recent years. This is, in part, due to the notion that adults identified as 'high risk' for functional decline portray a state that is potentially easier to reverse than overt disability. Assessing relatively healthy older adults with traditional self-report measures (activities of daily living) has proven difficult because these instruments were initially developed for institutionalised older adults. Perhaps less evident, are problems associated with change scores and the potential for 'construct under-representation', which reflects the exclusion of important features of the construct (e.g., disability). Furthermore, establishing a formal hierarchy of functional status tells more than the typical simple summation of functional loss, and may have predictive value to the clinician monitoring older adults: if the sequence task difficulty is accelerated or out of order it may indicate the need for interventions.</p> <p>Methods</p> <p>This review identified studies that employed item response theory (IRT) to examine or revise functional status scales. IRT can be used to transform the ordinal nature of functional status scales to interval level data, which serves to increase diagnostic precision and sensitivity to clinical change. Furthermore, IRT can be used to rank items unequivocally along a hierarchy based on difficulty. It should be noted that this review is not concerned with contrasting IRT with more traditional classical test theory methodology.</p> <p>Results</p> <p>A systematic search of four databases (PubMed, Embase, CINAHL, and PsychInfo) resulted in the review of 2,192 manuscripts. Of these manuscripts, twelve met our inclusion/exclusion requirements and thus were targeted for further inspection.</p> <p>Conclusions</p> <p>Manuscripts presented in this review appear to summarise gerontology's best efforts to improve construct validity and content validity (i.e., ceiling effects) for scales measuring the early stages of activity restriction in community-dwelling older adults. Several scales in this review were exceptional at reducing ceiling effects, reducing gaps in coverage along the construct, as well as establishing a formal hierarchy of functional decline. These instrument modifications make it plausible to detect minor changes in difficulty for IADL items positioned at the edge of the disability continuum, which can be used to signal the onset of progressive type disability in older adults.</p

Codominant scoring of AFLP in association panels

A study on the codominant scoring of AFLP markers in association panels without prior knowledge on genotype probabilities is described. Bands are scored codominantly by fitting normal mixture models to band intensities, illustrating and optimizing existing methodology, which employs the EM-algorithm. We study features that improve the performance of the algorithm, and the unmixing in general, like parameter initialization, restrictions on parameters, data transformation, and outlier removal. Parameter restrictions include equal component variances, equal or nearly equal distances between component means, and mixing probabilities according to Hardy–Weinberg Equilibrium. Histogram visualization of band intensities with superimposed normal densities, and optional classification scores and other grouping information, assists further in the codominant scoring. We find empirical evidence favoring the square root transformation of the band intensity, as was found in segregating populations. Our approach provides posterior genotype probabilities for marker loci. These probabilities can form the basis for association mapping and are more useful than the standard scoring categories A, H, B, C, D. They can also be used to calculate predictors for additive and dominance effects. Diagnostics for data quality of AFLP markers are described: preference for three-component mixture model, good separation between component means, and lack of singletons for the component with highest mean. Software has been developed in R, containing the models for normal mixtures with facilitating features, and visualizations. The methods are applied to an association panel in tomato, comprising 1,175 polymorphic markers on 94 tomato hybrids, as part of a larger study within the Dutch Centre for BioSystems Genomics

Cocoa, Hazelnuts, Sterols and Soluble Fiber Cream Reduces Lipids and Inflammation Biomarkers in Hypertensive Patients: A Randomized Controlled Trial

Cocoa, mixed with other food ingredients, intake can have beneficial effects on cardiovascular disease (CVD) biomarkers. We compared the effects of 4 cocoa cream products on some of these biomarkers.In this multi-centered, randomized, controlled, double-blind, parallel trial, volunteers (n = 113; age range: 43-65 years) who were pre-hypertensive, stage-1 hypertensive and hypercholesterolemic received one of 4 cocoa cream products (13 g/unit; 1 g cocoa/unit, 6 units/d; 465 Kcal/d) added to a low saturated fat diet for 4 weeks. The groups were: A) (n = 28), cocoa cream considered as control; B) (n = 28), cocoa+hazelnut cream (30 g/d hazelnuts); C) (n = 30), cocoa+hazelnuts+phytosterols (2 g/d); and D) (n = 27), cocoa+hazelnuts+phytosterols+soluble fiber (20 g/d) the patented "LMN product". Primary outcome measures were BP, LDL-c, apolipoprotein B-100 (Apo B), ApoB/ApoA ratio, oxidized LDL (oxLDL) and high-sensitive C-reactive protein (hsCRP) determined at baseline and post-cocoa cream product intake. Statistical analysis used was ANCOVA or mixed models (in case of repeated measurements), with baseline observation included as a covariate. After 4 weeks, compared to product A, product C reduced LDL-c by 11.2%, Apo B by 8.1% and ApoB/ApoA ratio by 7.8% (P = 0.01). LMN decreased LDL-c by 9.2%, Apo B-100 by 8.5%, ApoB/ApoA ratio by 10.5%, hsCRP by 33.4% and oxLDL by 5.9% (P = 0.01). Surprisingly, even "control" product A reduced systolic BP (-7.89 mmHg; 95%CI: -11.45 to -4.3) and diastolic BP (-5.54 mmHg; 95%CI: -7.79 to -3.29). The BP reductions were similar with the other 3 products. Limitations of the study are that the trial period was relatively short and that a better "BP control" product would have been preferable.The creams (particularly the LMN) have anti-inflammatory and antioxidant effects in addition to lowering LDL-c, Apo B and ApoB/ApoA ratio. Thus, the soluble fiber effects amplified with sterols (as contained in the cocoa creams) provide new dietary therapeutic perspectives.Clinicaltrials.gov NCT00511420

The relationships between self-compassion, attachment and interpersonal problems in clinical patients with mixed anxiety and depression and emotional distress

Self-compassion has been consistently linked to psychological well-being. The ability to be self-compassionate may be shaped by early attachment experiences and associated with interpersonal difficulties. However, evidence has yet to be extended to clinical populations. This study examined the role of self-compassion and its relationship with attachment and interpersonal problems in clinical patients with anxiety and depression. Participants (N = 74; 60% female, mean age 40 years) were recruited from a primary care psychological therapies service in Scotland, UK. Participants completed four self-report questionnaires assessing self-compassion, attachment, interpersonal problems and emotional distress (including depression and anxiety). Low self-compassion, attachment-related avoidance (but not attachment-related anxiety) and high interpersonal problems were all associated with higher levels of emotional distress and anxiety. Low self-compassion and high interpersonal problems were predicted by attachment-related avoidance. Self-compassion mediated the relationship between attachment-related avoidance and emotional distress and anxiety. This was a cross-sectional design and therefore a definitive conclusion cannot be drawn regarding causal relationships between these variables. Self-reported questionnaires were subject to response bias. This study has extended the evidence base regarding the role of self-compassion in patients with clinical levels of depression and anxiety. Notably, our findings indicated that self-compassion may be a particularly important construct, both theoretically and clinically, in understanding psychological distress amongst those with higher levels of attachment avoidance. This study supports the development and practice of psychotherapeutic approaches, such as compassion-focused therapy for which there is a growing evidence base

Cell Membrane Modification for Rapid Display of Bi-Functional Peptides: A Novel Approach to Reduce Complement Activation

Ischemia and reperfusion of organs is an unavoidable consequence of transplantation. Inflammatory events associated with reperfusion injury are in part attributed to excessive complement activation. Systemic administration of complement inhibitors reduces reperfusion injury but leaves patients vulnerable to infection. Here, we report a novel therapeutic strategy that decorates cells with an anti-complement peptide. An analog of the C3 convertase inhibitor Compstatin (C) was synthesized with a hexahistidine (His6) tag to create C-His6. To decorate cell membranes with C-His6, fusogenic lipid vesicles (FLVs) were used to incorporate lipids with nickel (Ni2+) tethers into cell membranes, and these could then couple with C-His6. Ni2+ tether levels to display C-His6 were modulated by changing FLV formulation, FLV incubation time and FLV levels. SKOV-3 cells decorated with C-His6 effectively reduced complement deposition in a classical complement activation assay. We conclude that our therapeutic approach appears promising for local ex vivo treatment of transplanted organs to reduce complement-mediated reperfusion injury