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At least 775 records · Page 43Linked to original sources
PubMed2004

Evaluation of atlas selection strategies for atlas-based image segmentation with application to confocal microscopy images of bee brains.

This paper evaluates strategies for atlas selection in atlas-based segmentation of three-dimensional biomedical images. Segmentation by intensity-based nonrigid registration to atlas images is applied to confocal microscopy images acquired from the brains of 20 bees. This paper evaluates and compares four different approaches for atlas image selection: registration to an individual atlas image (IND), registration to an average-shape atlas image (AVG), registration to the most similar image from a database of individual atlas images (SIM), and registration to all images from a database of individual atlas images with subsequent multi-classifier decision fusion (MUL). The MUL strategy is a novel application of multi-classifier techniques, which are common in pattern recognition, to atlas-based segmentation. For each atlas selection strategy, the segmentation performance of the algorithm was quantified by the similarity index (SI) between the automatic segmentation result and a manually generated gold standard. The best segmentation accuracy was achieved using the MUL paradigm, which resulted in a mean similarity index value between manual and automatic segmentation of 0.86 (AVG, 0.84; SIM, 0.82; IND, 0.81). The superiority of the MUL strategy over the other three methods is statistically significant (two-sided paired t test, P < 0.001). Both the MUL and AVG strategies performed better than the best possible SIM and IND strategies with optimal a posteriori atlas selection (mean similarity index for optimal SIM, 0.83; for optimal IND, 0.81). Our findings show that atlas selection is an important issue in atlas-based segmentation and that, in particular, multi-classifier techniques can substantially increase the segmentation accuracy.

Algorithms↗
PubMed2006

The functional neuroanatomy of autobiographical memory: a meta-analysis.

Autobiographical memory (AM) entails a complex set of operations, including episodic memory, self-reflection, emotion, visual imagery, attention, executive functions, and semantic processes. The heterogeneous nature of AM poses significant challenges in capturing its behavioral and neuroanatomical correlates. Investigators have recently turned their attention to the functional neuroanatomy of AM. We used the effect-location method of meta-analysis to analyze data from 24 functional imaging studies of AM. The results indicated a core neural network of left-lateralized regions, including the medial and ventrolateral prefrontal, medial and lateral temporal and retrosplenial/posterior cingulate cortices, the temporoparietal junction and the cerebellum. Secondary and tertiary regions, less frequently reported in imaging studies of AM, are also identified. We examined the neural correlates of putative component processes in AM, including, executive functions, self-reflection, episodic remembering and visuospatial processing. We also separately analyzed the effect of select variables on the AM network across individual studies, including memory age, qualitative factors (personal significance, level of detail and vividness), semantic and emotional content, and the effect of reference conditions. We found that memory age effects on medial temporal lobe structures may be modulated by qualitative aspects of memory. Studies using rest as a control task masked process-specific components of the AM neural network. Our findings support a neural distinction between episodic and semantic memory in AM. Finally, emotional events produced a shift in lateralization of the AM network with activation observed in emotion-centered regions and deactivation (or lack of activation) observed in regions associated with cognitive processes.

Autobiographies as Topic↗
PubMed2006

Remembering the past and imagining the future: common and distinct neural substrates during event construction and elaboration.

People can consciously re-experience past events and pre-experience possible future events. This fMRI study examined the neural regions mediating the construction and elaboration of past and future events. Participants were cued with a noun for 20s and instructed to construct a past or future event within a specified time period (week, year, 5-20 years). Once participants had the event in mind, they made a button press and for the remainder of the 20s elaborated on the event. Importantly, all events generated were episodic and did not differ on a number of phenomenological qualities (detail, emotionality, personal significance, field/observer perspective). Conjunction analyses indicated the left hippocampus was commonly engaged by past and future event construction, along with posterior visuospatial regions, but considerable neural differentiation was also observed during the construction phase. Future events recruited regions involved in prospective thinking and generation processes, specifically right frontopolar cortex and left ventrolateral prefrontal cortex, respectively. Furthermore, future event construction uniquely engaged the right hippocampus, possibly as a response to the novelty of these events. In contrast to the construction phase, elaboration was characterized by remarkable overlap in regions comprising the autobiographical memory retrieval network, attributable to the common processes engaged during elaboration, including self-referential processing, contextual and episodic imagery. This striking neural overlap is consistent with findings that amnesic patients exhibit deficits in both past and future thinking, and confirms that the episodic system contributes importantly to imagining the future.

Adolescent↗
PubMed2005

Database and tools for analysis of topographic organization and map transformations in major projection systems of the brain.

Integration of dispersed and complicated information collected from the brain is needed to build new knowledge. But integration may be hampered by rigid presentation formats, diversity of data formats among laboratories, and lack of access to lower level data. We have addressed some of the fundamental issues related to this challenge at the level of anatomical data, by producing a coordinate based digital atlas and database application for a major projection system in the rat brain: the cerebro-ponto-cerebellar system. This application, Functional Anatomy of the Cerebro-Cerebellar System in rat (FACCS), is available via the Rodent Brain WorkBench (http://www.rbwb.org). The data included are x,y,z-coordinate lists describing exact distributions of tissue elements (axonal terminal fields of axons, or cell bodies) that are labeled with axonal tracing techniques. All data are translated to a common local coordinate system to facilitate across animal comparison. A search capability allows queries based on, e.g. location of tracer injection sites, tracer category, size of the injection sites, and contributing author. A graphic search tool allows the user to move a volume cursor inside a coordinate system to detect particular injection sites having connections to a specific tissue volume at chosen density levels. Tools for visualization and analysis of selected data are included, as well as an option to download individual data sets for further analysis. With this application, data and metadata from different experiments are mapped into the same information structure and made available for re-use and re-analysis in novel combinations. The application is prepared for future handling of data from other projection systems as well as other data categories.

Anatomy, Artistic↗
PubMed2005

Searching for hypothetical proteins: theory and practice based upon original data and literature.

A large part of mammalian proteomes is represented by hypothetical proteins (HP), i.e. proteins predicted from nucleic acid sequences only and protein sequences with unknown function. Databases are far from being complete and errors are expected. The legion of HP is awaiting experiments to show their existence at the protein level and subsequent bioinformatic handling in order to assign proteins a tentative function is mandatory. Two-dimensional gel-electrophoresis with subsequent mass spectrometrical identification of protein spots is an appropriate tool to search for HP in the high-throughput mode. Spots are identified by MS or by MS/MS measurements (MALDI-TOF, MALDI-TOF-TOF) and subsequent software as e.g. Mascot or ProFound. In many cases proteins can thus be unambiguously identified and characterised; if this is not the case, de novo sequencing or Q-TOF analysis is warranted. If the protein is not identified, the sequence is being sent to databases for BLAST searches to determine identities/similarities or homologies to known proteins. If no significant identity to known structures is observed, the protein sequence is examined for the presence of functional domains (databases PROSITE, PRINTS, InterPro, ProDom, Pfam and SMART), subjected to searches for motifs (ELM) and finally protein-protein interaction databases (InterWeaver, STRING) are consulted or predictions from conformations are performed. We here provide information about hypothetical proteins in terms of protein chemical analysis, independent of antibody availability and specificity and bioinformatic handling to contribute to the extension/completion of protein databases and include original work on HP in the brain to illustrate the processes of HP identification and functional assignment.

Amino Acid Sequence↗
PubMed2000

Reading the mind in cartoons and stories: an fMRI study of 'theory of mind' in verbal and nonverbal tasks.

Previous functional imaging studies have explored the brain regions activated by tasks requiring 'theory of mind'--the attribution of mental states. Tasks used have been primarily verbal, and it has been unclear to what extent different results have reflected different tasks, scanning techniques, or genuinely distinct regions of activation. Here we report results from a functional magnetic resonance imaging study (fMRI) involving two rather different tasks both designed to tap theory of mind. Brain activation during the theory of mind condition of a story task and a cartoon task showed considerable overlap, specifically in the medial prefrontal cortex (paracingulate cortex). These results are discussed in relation to the cognitive mechanisms underpinning our everyday ability to 'mind-read'.

Adult↗
PubMed2000

Combining independent component analysis and correlation analysis to probe interregional connectivity in fMRI task activation datasets.

A new approach in studying interregional functional connectivity using functional magnetic resonance imaging (fMRI) is presented. Functional connectivity may be detected by means of cross correlating time course data from functionally related brain regions. These data exhibit high temporal coherence of low frequency fluctuations due to synchronized blood flow changes. In the past, this fMRI technique for studying functional connectivity has been applied to subjects that performed no prescribed task ("resting" state). This paper presents the results of applying the same method to task-related activation datasets. Functional connectivity analysis is first performed in areas not involved with the task. Then a method is devised to remove the effects of activation from the data using independent component analysis (ICA) and functional connectivity analysis is repeated. Functional connectivity, which is demonstrated in the "resting brain," is not affected by tasks which activate unrelated brain regions. In addition, ICA effectively removes activation from the data and may allow us to study functional connectivity even in the activated regions.

Adult↗
PubMed2003

Humor modulates the mesolimbic reward centers.

Humor plays an essential role in many facets of human life including psychological, social, and somatic functioning. Recently, neuroimaging has been applied to this critical human attribute, shedding light on the affective, cognitive, and motor networks involved in humor processing. To date, however, researchers have failed to demonstrate the subcortical correlates of the most fundamental feature of humor-reward. In an effort to elucidate the neurobiological substrate that subserves the reward components of humor, we undertook a high-field (3 Tesla) event-related functional MRI study. Here we demonstrate that humor modulates activity in several cortical regions, and we present new evidence that humor engages a network of subcortical regions including the nucleus accumbens, a key component of the mesolimbic dopaminergic reward system. Further, the degree of humor intensity was positively correlated with BOLD signal intensity in these regions. Together, these findings offer new insight into the neural basis of salutary aspects of humor.

Adult↗
PubMed2002

Learning anchor verbs for biological interaction patterns from published text articles.

Much of knowledge modeling in the molecular biology domain involves interactions between proteins, genes, various forms of RNA, small molecules, etc. Interactions between these substances are typically extracted and codified manually, increasing the cost and time for modeling and substantially limiting the coverage of the resulting knowledge base. In this paper, we describe an automatic system that learns from text interaction verbs; these verbs can then form the core of automatically retrieved patterns which model classes of biological interactions. We investigate text features relating verbs with genes and proteins, and apply statistical tests and a logistic regression statistical model to determine whether a given verb belongs to the class of interaction verbs. Our system, AVAD, achieves over 87% precision and 82% recall when tested on an 11 million word corpus of journal articles. In addition, we compare the automatically obtained results with a manually constructed database of interaction verbs and show that the automatic approach can significantly enrich the manual list by detecting rarer interaction verbs that were omitted from the database.

Artificial Intelligence↗
PubMed2003

Cell cycle-dependent protein fingerprint from a single cancer cell: image cytometry coupled with single-cell capillary sieving electrophoresis.

Study of cell cycle-dependent protein expression is important in oncology, stem cell research, and developmental biology. In this paper, we report the first protein fingerprint from a single cell with known phase in the cell cycle. To determine that phase, we treated HT-29 colon cancer cells with Hoescht 33342, a vital nuclear stain. A microscope was used to measure the fluorescence intensity from one treated cell; in this form of image cytometry, the fluorescence intensity is proportional to the cell's DNA content, which varies in a predictable fashion during the cell cycle. To generate the protein fingerprint, the cell was aspirated into the separation capillary and lysed. Proteins were fluorescently labeled with 3-(2-furoylquinoline-2-carboxaldehyde, separated by capillary sieving electrophoresis, and detected by laser-induced fluorescence. This form of electrophoresis is the capillary version of SDS-PAGE. The single-cell electropherogram partially resolved approximately 25 components in a 30-min separation, and the dynamic range of the detector exceeded 5000. There was a large cell-to-cell variation in protein expression, averaging 40% relative standard deviation across the electropherogram. The dominant source of variation was the phase of the cell in the cell cycle; on average, approximately 60% of the cell-to-cell variance in protein expression was associated with the cell cycle. Cells in the G1 and G2/M phases of the cell cycle had 27 and 21% relative standard deviations in protein expression, respectively. Cells in the G2/M phase generated signals that were twice the amplitude of the signals generated by G1 phase cells, as expected for cells that are soon to divide into two daughter cells. When electropherograms were normalized to total protein content, the expression of only one component was dependent on cell cycle at the 99% confidence limit. That protein is tentatively identified as cytokeratin 18 in a companion paper.

Algorithms↗
PubMed2002

Integration of genomic datasets to predict protein complexes in yeast.

The ultimate goal of functional genomics is to define the function of all the genes in the genome of an organism. A large body of information of the biological roles of genes has been accumulated and aggregated in the past decades of research, both from traditional experiments detailing the role of individual genes and proteins, and from newer experimental strategies that aim to characterize gene function on a genomic scale. It is clear that the goal of functional genomics can only be achieved by integrating information and data sources from the variety of these different experiments. Integration of different data is thus an important challenge for bioinformatics. The integration of different data sources often helps to uncover non-obvious relationships between genes, but there are also two further benefits. First, it is likely that whenever information from multiple independent sources agrees, it should be more valid and reliable. Secondly, by looking at the union of multiple sources, one can cover larger parts of the genome. This is obvious for integrating results from multiple single gene or protein experiments, but also necessary for many of the results from genome-wide experiments since they are often confined to certain (although sizable) subsets of the genome. In this paper, we explore an example of such a data integration procedure. We focus on the prediction of membership in protein complexes for individual genes. For this, we recruit six different data sources that include expression profiles, interaction data, essentiality and localization information. Each of these data sources individually contains some weakly predictive information with respect to protein complexes, but we show how this prediction can be improved by combining all of them. Supplementary information is available at http:// bioinfo.mbb.yale.edu/integrate/interactions/.

Cell Cycle↗
PubMed2004

Novel PEEK-WC membranes with low plasma protein affinity related to surface free energy parameters.

There has been growing interest in innovative materials with specific physico-chemical properties that provide an improved blood/cell compatibility. In this paper we evaluated the performance of new membranes prepared from a modified polyetheretherketone (PEEK-WC) contacting human plasma proteins. These membranes were prepared by using the phase inversion technique. Membrane wettability and affinity to proteins were evaluated by means of contact angle experiments, roughness measurements, and quantitative UV analysis. The energy parameters of membrane surfaces were determined according to Good, van Oss and Chaudhury's theory. The extent of human albumin, fibrinogen and immunoglobulin G adsorption was related to quantitative expressions of the membrane surface hydrophilicity: the base parameter of surface free energy and the free energy of interfacial interaction. The performance of PEEK-WC membranes was compared to that of commercial membranes, which conventionally are used in biomedical applications. The experimental results showed a reduction of protein adsorption on PEEK-WC membranes with respect to other commercial membranes. The low protein affinity of PEEK-WC membranes is due to the intrinsic physico-chemical characteristics of the polymeric material which makes these membranes interesting for potential use in biomedical applications.

Adsorption↗
PubMed2003

Quality and completeness of SNP databases.

To address the quality and completeness of single-nucleotide polymorphism (SNP) databases, we resequenced 173 kb (spanning 17 loci) in 150 chromosomes of west African and European ancestry. Over 88% of SNPs in the public (TSC and BAC overlap) and Celera databases were confirmed in independent resequencing. Approximately 45% of all human heterozygosity is attributable to SNPs already available from the two databases, and of SNPs with minor-allele frequencies >10%, more than half are represented.

Alleles↗