96 research outputs found
The latent structure of the adult attachment interview: Large sample evidence from the collaboration on attachment transmission synthesis
The Adult Attachment Interview (AAI) is a widely used measure in developmental science that assesses adultsâ current states of mind regarding early attachment-related experiences with their primary caregivers. The standard system for coding the AAI recommends classifying individuals categorically as having an autonomous, dismissing, preoccupied, or unresolved attachment state of mind. However, previous factor and taxometric analyses suggest that: (a) adultsâ attachment states of mind are captured by two weakly correlated factors reflecting adultsâ dismissing and preoccupied states of mind and (b) individual differences on these factors are continuously rather than categorically distributed. The current study revisited these suggestions about the latent structure of AAI scales by leveraging individual participant data from 40 studies (N = 3,218), with a particular focus on the controversial observation from prior factor analytic work that indicators of preoccupied states of mind and indicators of unresolved states of mind about loss and trauma loaded on a common factor. Confirmatory factor analyses indicated that: (a) a 2-factor model with weakly correlated dismissing and preoccupied factors and (b) a 3-factor model that further distinguished unresolved from preoccupied states of mind were both compatible with the data. The preoccupied and unresolved factors in the 3-factor model were highly correlated. Taxometric analyses suggested that individual differences in dismissing, preoccupied, and unresolved states of mind were more consistent with a continuous than a categorical model. The importance of additional tests of predictive validity of the various models is emphasized
The I4U Mega Fusion and Collaboration for NIST Speaker Recognition Evaluation 2016
The 2016 speaker recognition evaluation (SRE'16) is the latest edition in the series of benchmarking events conducted by the National Institute of Standards and Technology (NIST). I4U is a joint entry to SRE'16 as the result from the collaboration and active exchange of information among researchers from sixteen Institutes and Universities across 4 continents. The joint submission and several of its 32 sub-systems were among top-performing systems. A lot of efforts have been devoted to two major challenges, namely, unlabeled training data and dataset shift from Switchboard-Mixer to the new Call My Net dataset. This paper summarizes the lessons learned, presents our shared view from the sixteen research groups on recent advances, major paradigm shift, and common tool chain used in speaker recognition as we have witnessed in SRE'16. More importantly, we look into the intriguing question of fusing a large ensemble of sub-systems and the potential benefit of large-scale collaboration.Peer reviewe
Hemap: An nteractive online resource for characterizing molecular phenotypes across hematologic malignancies
Large collections of genome-wide data can facilitate the characterization of disease states and subtypes, permitting pan-cancer analysis of molecular phenotypes and evaluation of disease contexts for new therapeutic approaches. We analyzed 9,544 transcriptomes from over 30 hematologic malignancies, normal blood cell types and cell lines, and show that the disease types can be stratified in a data-driven manner. We utilized the obtained molecular clustering for discovery of cluster-specific pathway activity, new biomarkers and in silico drug target prioritization through integration with drug target databases. Using known vulnerabilities and available drug screens in benchmarking, we highlight the importance of integrating the molecular phenotype context and drug target expression for in silico prediction of drug responsiveness. Our analysis implicates BCL2 expression level as
important indicator of venetoclax responsiveness and provides a rationale for its targeting in specific leukemia subtypes and multiple myeloma, links several polycomb group proteins that could be targeted by small molecules (SFMBT1, CBX7 and EZH1) with CLL, and supports CDK6 as disease-specific target in AML. Through integration with proteomics data, we characterized target protein expression for pre-B leukemia immunotherapy candidates, including DPEP1. These molecular data can be explored using our freely available interactive resource, Hemap, for expediting therapeutic innovations in hematologic malignancies
Common Inflammation-Related Candidate Gene Variants and Acute Kidney Injury in 2647 Critically Ill Finnish Patients
Acute kidney injury (AKI) is a syndrome with high incidence among the critically ill. Because the clinical variables and currently used biomarkers have failed to predict the individual susceptibility to AKI, candidate gene variants for the trait have been studied. Studies about genetic predisposition to AKI have been mainly underpowered and of moderate quality. We report the association study of 27 genetic variants in a cohort of Finnish critically ill patients, focusing on the replication of associations detected with variants in genes related to inflammation, cell survival, or circulation. In this prospective, observational Finnish Acute Kidney Injury (FINNAKI) study, 2647 patients without chronic kidney disease were genotyped. We defined AKI according to Kidney Disease: Improving Global Outcomes (KDIGO) criteria. We compared severe AKI (Stages 2 and 3, n = 625) to controls (Stage 0, n = 1582). For genotyping we used iPLEX(TM) Assay (Agena Bioscience). We performed the association analyses with PLINK software, using an additive genetic model in logistic regression. Despite the numerous, although contradictory, studies about association between polymorphisms rs1800629 in TNFA and rs1800896 in IL10 and AKI, we found no association (odds ratios 1.06 (95% CI 0.89-1.28, p = 0.51) and 0.92 (95% CI 0.80-1.05, p = 0.20), respectively). Adjusting for confounders did not change the results. To conclude, we could not confirm the associations reported in previous studies in a cohort of critically ill patients.Peer reviewe
Co-creation with Companies: A Means to Enhance Societal Impact of University Researchers?
In this chapter, we explore co-creation as a form of societal interaction of science. We approach co-creation as a goal-oriented form of dynamic interaction aiming at mutual benefit of all parties. As such, we exclude technology transfer and other linear societal interaction forms that follow a closed-model innovation format. We argue that focusing solely on tapping the needs of researchers and âpureâ science would lead to ignoring the broader context in which researchers work. An excessive focus on meeting the needs of external stakeholders could jeopardize the preconditions of science. Hence, this chapter explores how researcher-company co-creation can be nurtured in a heavily institutionalized setting, where established rules govern the process of knowledge production and protect research integrity. The co-creation process is analyzed by combining Nonakaâs SECI model and Stroberâs interdisciplinary interaction model for knowledge creation. We find that the core of this process lies facilitated dialogue, which is seen as open knowledge sharing between equal participants
Heme oxygenase-1 repeat polymorphism in septic acute kidney injury
Acute kidney injury (AKI) is a syndrome that frequently affects the critically ill. Recently, an increased number of dinucleotide repeats in the HMOX1 gene were reported to associate with development of AKI in cardiac surgery. We aimed to test the replicability of this finding in a Finnish cohort of critically ill septic patients. This multicenter study was part of the national FINNAKI study. We genotyped 300 patients with severe AKI (KDIGO 2 or 3) and 353 controls without AKI (KDIGO 0) for the guanine-thymine (GTn) repeat in the promoter region of the HMOX1 gene. The allele calling was based on the number of repeats, the cut off being 27 repeats in the S-L (short to long) classification, and 27 and 34 repeats for the S-M-L2 (short to medium to very long) classification. The plasma concentrations of heme oxygenase-1 (HO-1) enzyme were measured on admission. The allele distribution in our patients was similar to that published previously, with peaks at 23 and 30 repeats. The S-allele increases AKI risk. An adjusted OR was 1.30 for each S-allele in an additive genetic model (95% CI 1.01-1.66; p = 0.041). Alleles with a repeat number greater than 34 were significantly associated with lower HO-1 concentration (p<0.001). In septic patients, we report an association between a short repeat in HMOX1 and AKI risk
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