| 1. |
- Nowicka, Paulina, 1974-, et al.
(författare)
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Self-esteem in a clinical sample of morbidly obese children and adolescents
- 2009
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Ingår i: Acta Paediatrica. - : Wiley. - 0803-5253 .- 1651-2227. ; 98:1, s. 153-158
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Tidskriftsartikel (refereegranskat)abstract
- Aim: To study self-esteem in clinical sample of obese children and adolescents.Methods: Obese children and adolescents aged 8–19 years (n = 107, mean age 13.2 years, mean BMI 32.5 [range 22.3–50.6], mean BMI z-score 3.22 [range 2.19–4.79]; 50 boys and 57 girls) were referred for treatment of primary obesity. Self-esteem was measured with a validated psychological test with five subscales: physical characteristics, talents and skills, psychological well-being, relations with the family and relations with others. A linear mixed effect model used the factors gender and adolescence group, and the continuous covariates: BMI z-scores, and BMI for the parents as fixed effects and subjects as random effects.Results: Age and gender, but neither the child’s BMI z-score nor the BMI of the parents were significant covariates. Self-esteem decreased (p < 0.01) with age on the global scale as well as on the subscales, and was below the normal level in higher ages in both genders. Girls had significantly lower self-esteem on the global scale (p = 0.04) and on the two subscales physical characteristics (p < 0.01) and psychological well-being (p < 0.01).Conclusion: Self-esteem is lower in girls and decreases with age. In treatment settings special attention should be paid to adolescent girls.
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| 2. |
- Aine, Mattias, et al.
(författare)
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Biological determinants of bladder cancer gene expression subtypes.
- 2015
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 5
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Tidskriftsartikel (refereegranskat)abstract
- Molecular stratification of tumors by gene expression profiling has been applied to a large number of human malignancies and holds great promise for personalized treatment. Comprehensive classification schemes for urothelial carcinoma have been proposed by three separate groups but have not previously been evaluated simultaneously in independent data. Here we map the interrelations between the proposed molecular subtypes onto the intrinsic structure of a rich independent dataset and show that subtype stratification within each scheme can be explained in terms of a set of common underlying biological processes. We highlight novel biological and genomic drivers of urothelial carcinoma molecular subtypes and show that tumors carrying genomic aberrations characteristic of distinct molecular pathways converge on a common top level phenotype corresponding to the two major molecular subtypes of non-muscle invasive disease.
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| 3. |
- Aine, Mattias, et al.
(författare)
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Integrative epigenomic analysis of differential DNA methylation in urothelial carcinoma.
- 2015
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Ingår i: Genome Medicine. - : Springer Science and Business Media LLC. - 1756-994X. ; 7:1
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Tidskriftsartikel (refereegranskat)abstract
- Urothelial carcinoma of the bladder (UC) is a common malignancy. Although extensive transcriptome analysis has provided insights into the gene expression patterns of this tumor type, the mechanistic underpinnings of differential methylation remain poorly understood. Multi-level genomic data may be used to profile the regulatory potential and landscape of differential methylation in cancer and gain understanding of the processes underlying epigenetic and phenotypic characteristics of tumors.
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| 4. |
- Aine, Mattias, et al.
(författare)
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On Molecular Classification of Bladder Cancer: Out of One, Many.
- 2015
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Ingår i: European Urology. - : Elsevier BV. - 1873-7560 .- 0302-2838. ; 68:6, s. 921-923
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Tidskriftsartikel (refereegranskat)abstract
- Comparative analysis showed that bladder cancer classification systems identify overlapping subtypes but at different levels. Muscle-invasive bladder cancer shows remarkable heterogeneity, and six subtypes were identified that differ in transcriptional networks, marker profiles, and expression of actionable targets.
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| 5. |
- Anckarsäter, Henrik, 1966, et al.
(författare)
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Mental disorder is a cause of crime: The cornerstone of forensic psychiatry
- 2009
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Ingår i: International Journal of Law and Psychiatry. - : Elsevier BV. - 0160-2527 .- 1873-6386. ; 32:6, s. 342-347
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Tidskriftsartikel (refereegranskat)abstract
- The assumption that mental disorder is a cause of crime is the foundation of forensic psychiatry, but conceptual. epistemological. and empirical analyses show that neither mental nor crime, or the causation implied, are clear-cut concepts. "Mental" denotes heterogeneous aspects of a per-son such as inner experiences. cognitive abilities, and behaviour patterns described in a non-physical vocabulary. In psychology and psychiatry, mental describes law-bound, caused aspects of human functioning that are predictable and generalizable. Problems defined as mental disorders are end-points of dimensional inter-individual differences rather than natural categories. Deficits in cognitive faculties, such as attention, verbal understanding, impulse control, and reality assessment, may be susceptibility factors that relate to behaviours (Such as crimes) by increasing the probability (risk) for a negative behaviour or constitute causes in the sense of INUS conditions (insufficient but Non-redundant parts of Unnecessary but Sufficient conditions). Attributing causes to complex behaviours such as crimes is not an unbiased process, and mental disorders will attract disproportionate attention when it comes to explanations of behaviours that we wish to distance ourselves from. Only by rigorous interpretation of what psychiatry actually can inform us about, using empirical analyses of quantified aggressive antisocial behaviours and their possible explanatory factors, can we gain a clearer notion of the relationship between mental disorder and crime. (C) 2009 Elsevier Ltd. All rights reserved.
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| 6. |
- Bahnan, Wael, et al.
(författare)
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Spike-Dependent Opsonization Indicates Both Dose-Dependent Inhibition of Phagocytosis and That Non-Neutralizing Antibodies Can Confer Protection to SARS-CoV-2
- 2022
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Ingår i: Frontiers in Immunology. - : Frontiers Media SA. - 1664-3224. ; 12
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Tidskriftsartikel (refereegranskat)abstract
- Spike-specific antibodies are central to effective COVID19 immunity. Research efforts have focused on antibodies that neutralize the ACE2-Spike interaction but not on non-neutralizing antibodies. Antibody-dependent phagocytosis is an immune mechanism enhanced by opsonization, where typically, more bound antibodies trigger a stronger phagocyte response. Here, we show that Spike-specific antibodies, dependent on concentration, can either enhance or reduce Spike-bead phagocytosis by monocytes independently of the antibody neutralization potential. Surprisingly, we find that both convalescent patient plasma and patient-derived monoclonal antibodies lead to maximum opsonization already at low levels of bound antibodies and is reduced as antibody binding to Spike protein increases. Moreover, we show that this Spike-dependent modulation of opsonization correlate with the outcome in an experimental SARS-CoV-2 infection model. These results suggest that the levels of anti-Spike antibodies could influence monocyte-mediated immune functions and propose that non-neutralizing antibodies could confer protection to SARS-CoV-2 infection by mediating phagocytosis.
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| 7. |
- Bernardo, Carina, et al.
(författare)
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Molecular pathology of the luminal class of urothelial tumors
- 2019
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Ingår i: Journal of Pathology. - : Wiley. - 0022-3417 .- 1096-9896. ; 249:3, s. 308-318
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Tidskriftsartikel (refereegranskat)abstract
- Molecular subtypes of urothelial carcinoma may be divided into luminal and nonluminal tumors. Nonluminal tumors are composed of cases with basal/squamous-like or small cell/neuroendocrine features, with a consensus on the molecular characteristics of the respective subtype. In contrast, luminal tumors are more disparate with three to five suggested subtypes and with definitions that do not always cohere. To resolve some of these disparities we assembled a cohort of 344 luminal tumors classified as urothelial-like (Uro), with the subtypes UroA, UroAp, UroB, and UroC, or genomically unstable (GU) according to the LundTax system. Cases were systematically analyzed by immunohistochemistry using antibodies for proteins representing important biological processes or cellular states: KRT5, EGFR, and CDH3 for the integrity of a basal cell layer; CCNB1, Ki67, and FOXM1 for proliferation; FGFR3 and ERBB2 for receptor tyrosine kinase status; CCND1, CDKN2A(p16), RB1, and E2F3 for cell cycle regulation; PPARG, GATA3, and TP63 for the differentiation regulatory system; and KRT20 and UPK3 for the differentiation readout. We show that Uro tumors form one, albeit heterogenous, group characterized by FGFR3, CCND1, and RB1 expression, but low or absence of CDKN2A(p16) and ERBB2 expression. The opposite expression pattern is observed in GU cases. Furthermore, Uro tumors are distinguished from GU tumors by showing a high RB1/p16 expression ratio. Class defining characteristics were independent of pathological stage and growth pattern, and thus intrinsic. In Uro tumors, proliferation was limited to a well-defined single layer of basal-like cells in UroA tumors but occurred throughout the tumor parenchyma, independent of the basal layer, in the more progressed UroAp and UroC tumors. A similar change in proliferation topology was not observed in GU. We conclude that luminal urothelial carcinomas consist, at the molecular pathology level, of two major subtypes, the larger heterogenous Uro and the biologically distinct GU subtype.
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| 8. |
- Bernardo, Carina, et al.
(författare)
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Molecular pathology of the non-luminal Ba/Sq-like and Sc/NE-like classes of urothelial tumours : An integrated immunohistochemical analysis
- 2022
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Ingår i: Human Pathology. - : Elsevier BV. - 0046-8177. ; 122, s. 11-24
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Tidskriftsartikel (refereegranskat)abstract
- Several groups have during past years produced molecular classification schemes for bladder cancer. Even though no consensus on how to define a subtype exists, one approach has been to base definitions on how tumours cluster according to their mRNA expression profiles. In many cases, obtained profiles, and thus class defining features, are affected by signals from non-tumour cells within the biopsy. To overcome this issue, we combined gene expression analyses with analyses of the actual tumour cells by extensive immunohistochemistry (IHC). By this approach we were able to define tumour cell phenotypes i.e., subtypes defined by features of the tumour cells only, and adjust mRNA-based algorithms accordingly. In the present investigation we address the non-luminal Basal/Squamous-like (Ba/Sq) and Small cell/Neuroendocrine-like (Sc/NE) categories of tumours defined by mRNA-based classification. We make use of IHC data for 15 proteins, all known to be instrumental for defining molecular subtypes of urothelial carcinoma. We show that the UroB type of tumours, frequently grouped together with Ba/Sq, are different from the Ba/Sq entity at several essential features and is a derivative of Urothelial-like tumours (Uro). We show that the Sc/NE tumours are similar to but represents extreme versions of Genomically Unstable (GU) tumours. We apply clustering to 423 cases representing all subtypes using IHC data for 14 proteins and show that the obtained grouping conforms well with the mRNA-based classification. This work describes in detail the molecular pathology of non-luminal RNA-based bladder cancer subtypes and highlight similarities/dissimilarities suggestive of origin.
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| 9. |
- Eriksson, Pontus, et al.
(författare)
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A comparison of rule-based and centroid single-sample multiclass predictors for transcriptomic classification
- 2022
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 38:4, s. 1022-1029
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Tidskriftsartikel (refereegranskat)abstract
- MOTIVATION: Gene expression-based multiclass prediction, such as tumor subtyping, is a non-trivial bioinformatic problem. Most classifier methods operate by comparing expression levels relative to other samples. Methods that base predictions on the expression pattern within a sample have been proposed as an alternative. As these methods are invariant to the cohort composition and can be applied to a sample in isolation, they can collectively be termed single sample predictors (SSP). Such predictors could potentially be used for preprocessing-free classification of new samples and be built to function across different expression platforms where proper batch and dataset normalization is challenging. Here we evaluate the behavior of several multiclass single sample predictors based on binary gene-pair rules (k-Top Scoring Pairs, Absolute Intrinsic Molecular Subtyping, and a new Random Forest approach) and compare them to centroids built with centered or raw expression values, with the criteria that an optimal predictor should have high accuracy, overcome differences in tumor purity, be robust across expression platforms, and provide an informative prediction output score.RESULTS: We found that gene-pair based SSPs showed excellent performance on many expression-based classification tasks. The three methods differed in prediction score output, handling of tied scores, and behavior in low purity samples. The k-Top Scoring Pairs and Random Forest approach both achieved high classification accuracy while providing an informative prediction score. Although gene-pair-based SSPs have been touted as being cross-platform compatible (through training on mixed platform data), out-of-the-box compatibility with a new dataset remains a potential issue that warrants cohort-to-cohort verification.AVAILABILITY: Our R package 'multiclassPairs' (https://cran.r-project.org/package=multiclassPairs) (https://doi.org/10.1093/bioinformatics/btab088) is freely available and enables easy training, prediction, and visualization using the gene-pair rule-based Random Forest SSP method and provides additional multiclass functionalities to the switchBox k-Top-Scoring Pairs package.SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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| 10. |
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