5,619 research outputs found
Physics-based analysis of Affymetrix microarray data
We analyze publicly available data on Affymetrix microarrays spike-in
experiments on the human HGU133 chipset in which sequences are added in
solution at known concentrations. The spike-in set contains sequences of
bacterial, human and artificial origin. Our analysis is based on a recently
introduced molecular-based model [E. Carlon and T. Heim, Physica A 362, 433
(2006)] which takes into account both probe-target hybridization and
target-target partial hybridization in solution. The hybridization free
energies are obtained from the nearest-neighbor model with experimentally
determined parameters. The molecular-based model suggests a rescaling that
should result in a "collapse" of the data at different concentrations into a
single universal curve. We indeed find such a collapse, with the same
parameters as obtained before for the older HGU95 chip set. The quality of the
collapse varies according to the probe set considered. Artificial sequences,
chosen by Affymetrix to be as different as possible from any other human genome
sequence, generally show a much better collapse and thus a better agreement
with the model than all other sequences. This suggests that the observed
deviations from the predicted collapse are related to the choice of probes or
have a biological origin, rather than being a problem with the proposed model.Comment: 11 pages, 10 figure
Efficacy of internet-based interventions for common mental disorder symptoms and psychosocial problems in older adults: A systematic review and meta-analysis.
Although a high proportion of older adults suffer from common mental disorder symptoms and psychosocial problems, only a small number of older individuals seek psychological treatment. Internet-based interventions have the potential to bridge this treatment gap. However, while there is extensive literature on internet-based treatments in younger to middle-aged adults, research on older individuals is lacking.
We aimed to summarize narratively and empirically the existing literature on the efficacy of internet-based interventions for the treatment of common mental disorder symptoms and psychosocial problems (loneliness, stress) in older individuals.
This systematic review and meta-analysis was registered in PROSPERO (registration number: CRD42021235129). Systematic literature searches were conducted in PsycInfo, Ageline, Medline, CINHAL, and Psyndex. Studies were eligible for inclusion if they a) focused on older adults, b) assessed the efficacy of an internet-delivered psychological intervention, c) included a control condition and d) assessed common mental disorder symptoms or psychosocial problems as outcomes. Meta-analyses were conducted based on studies that included a passive, minimally active or placebo control condition to estimate pooled effects on overall symptom severity as well as on specific psychological outcomes.
11 Studies met inclusion criteria, with the majority of interventions focusing on depression or anxiety symptoms and being based on CBT principles. Significant large effect of internet-based interventions for older adults were found for overall symptom severity (depression, anxiety, PTSD, stress) as well as for depression symptom severity. No significant effects were found for anxiety symptom severity.
Our findings provide preliminary support that internet-based interventions might be a feasible and effective intervention method for the treatment of common mental disorder symptoms and stress in older adults. However, research in this area is still at an early stage. More studies are needed to shed light on the role of various treatment and patient characteristics in the efficacy of internet-delivered treatments
Lost in translation: data integration tools meet the Semantic Web (experiences from the Ondex project)
More information is now being published in machine processable form on the
web and, as de-facto distributed knowledge bases are materializing, partly
encouraged by the vision of the Semantic Web, the focus is shifting from the
publication of this information to its consumption. Platforms for data
integration, visualization and analysis that are based on a graph
representation of information appear first candidates to be consumers of
web-based information that is readily expressible as graphs. The question is
whether the adoption of these platforms to information available on the
Semantic Web requires some adaptation of their data structures and semantics.
Ondex is a network-based data integration, analysis and visualization platform
which has been developed in a Life Sciences context. A number of features,
including semantic annotation via ontologies and an attention to provenance and
evidence, make this an ideal candidate to consume Semantic Web information, as
well as a prototype for the application of network analysis tools in this
context. By analyzing the Ondex data structure and its usage, we have found a
set of discrepancies and errors arising from the semantic mismatch between a
procedural approach to network analysis and the implications of a web-based
representation of information. We report in the paper on the simple methodology
that we have adopted to conduct such analysis, and on issues that we have found
which may be relevant for a range of similar platformsComment: Presented at DEIT, Data Engineering and Internet Technology, 2011
IEEE: CFP1113L-CD
Dynamics of the Pionium with the Density Matrix Formalism
The evolution of pionium, the hydrogen-like atom, while passing
through matter is solved within the density matrix formalism in the first Born
approximation. We compare the influence on the pionium break-up probability
between the standard probabilistic calculations and the more precise picture of
the density matrix formalism accounting for interference effects. We focus our
general result in the particular conditions of the DIRAC experiment at CERN.Comment: 14 pages, 2 figures, submitted to J. Phys. B: At. Mol. Phy
Effective affinities in microarray data
In the past couple of years several studies have shown that hybridization in
Affymetrix DNA microarrays can be rather well understood on the basis of simple
models of physical chemistry. In the majority of the cases a Langmuir isotherm
was used to fit experimental data. Although there is a general consensus about
this approach, some discrepancies between different studies are evident. For
instance, some authors have fitted the hybridization affinities from the
microarray fluorescent intensities, while others used affinities obtained from
melting experiments in solution. The former approach yields fitted affinities
that at first sight are only partially consistent with solution values. In this
paper we show that this discrepancy exists only superficially: a sufficiently
complete model provides effective affinities which are fully consistent with
those fitted to experimental data. This link provides new insight on the
relevant processes underlying the functioning of DNA microarrays.Comment: 8 pages, 6 figure
Investigating the timecourse of accessing conversational implicatures during incremental sentence interpretation
Many contextual inferences in utterance interpretation are explained as following from the nature of conversation and the assumption that participants are rational. Recent psycholinguistic research has focussed on certain of these ‘Gricean’ inferences and have revealed that comprehenders can access them in online interpretation. However there have been mixed results as to the time-course of access. Some results show that Gricean inferences can be accessed very rapidly, as rapidly as any other contextually specified information (Sedivy, 2003; Grodner, Klein, Carbery, & Tanenhaus, 2010); while other studies looking at the same kind of inference suggest that access to Gricean inferences are delayed relative to other aspects of semantic interpretation (Huang & Snedeker, 2009; in press). While previous timecourse research has focussed on Gricean inferences that support the online assignment of reference to definite expressions, the study reported here examines the timecourse of access to scalar implicatures, which enrich the meaning of an utterance beyond the semantic interpretation. Even if access to Gricean inference in support of reference assignment may be rapid, it is still unknown whether genuinely enriching scalar implicatures are delayed. Our results indicate that scalar implicatures are accessed as rapidly as other contextual inferences. The implications of our results are discussed in reference to the architecture of language comprehension
Stable longitudinal associations of family income with children's hippocampal volume and memory persist after controlling for polygenic scores of educational attainment
Despite common notion that the correlation of socioeconomic status with child cognitive performance may be driven by both environmentally- and genetically-mediated transactional pathways, there is a lack of longitudinal and genetically informed research that examines these postulated associations. The present study addresses whether family income predicts associative memory growth and hippocampal development in middle childhood and tests whether these associations persist when controlling for DNA-based polygenic scores of educational attainment. Participants were 142 6-to-7-year-old children, of which 127 returned when they were 8-to-9 years old. Longitudinal analyses indicated that the association of family income with children's memory performance and hippocampal volume remained stable over this age range and did not predict change. On average, children from economically disadvantaged background showed lower memory performance and had a smaller hippocampal volume. There was no evidence to suggest that differences in memory performance were mediated by differences in hippocampal volume. Further exploratory results suggested that the relationship of income with hippocampal volume and memory in middle childhood is not primarily driven by genetic variance captured by polygenic scores of educational attainment, despite the fact that polygenic scores significantly predicted family income
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