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PubMed2025

Integrative multi-omics analysis proposes a metabolic classification of gliomas: distinct metabolic states, immune infiltration, and prognosis.

BACKGROUND: The tumor microenvironment (TME) of glioma harbors diverse cell types; however, cell metabolic heterogeneity remains to be explored. This study aims to characterize the metabolic features of different cell types in the TME by integrating multiple datasets, including genomics, bulk and single-cell transcriptomics, and metabolomics. METHODS: Unsupervised machine learning was used to construct an energy metabolic classifier based on the metabolic pathways identified from bulk RNA-seq of gliomas in the TCGA dataset. The classifier was externally validated using multiple datasets, including genomics, bulk RNA-seq, snRNA-seq, and the metabolomics data. Furthermore, metabolic heterogeneity associated with the classifier was further characterized at single-cell resolution. RESULTS: The energy metabolism-based classifier stratified patients into two prognostic clusters: patients in cluster 1 were characterized by high pathway activity of glycolysis, the pentose phosphate pathway (PPP), and fatty acid oxidation (FAO), whereas patients in cluster 2 exhibited higher activity in glutaminolysis. This metabolic classifier revealed both intratumoral and intertumoral metabolic heterogeneity, and the complexity was further validated by the metabolomics profiling and snRNA-seq data from the CPTAC dataset. Notably, OSMR, highly expressed in cluster 1, showed significant co-expression with key glycolytic enzyme genes. The OSM/OSMR/JAK1/STAT3 axis potently drives malignant progression of glioma cells, specially enhancing their invasive and migratory capabilities. Single-cell resolution analyses demonstrated that tumor metabolic heterogeneity is primarily driven by malignant cells rather than non-malignant components, while tumor microenvironment (TME) factors were also found to modulate malignant cell metabolism. Significantly, glycolytic activity in glioma cells increased during the phenotypic transition from PN (proneural) to MES (mesenchymal), with cluster 1 metabolic phenotypes predominating in the tumor core. Compared to cluster 2, cluster 1 patients exhibited higher mRNA expression of immunosuppressive checkpoint genes, which correlated with pronounced immunosuppression in the TME. Furthermore, various immune cells demonstrated distinct metabolic preferences at single-cell resolution. CONCLUSIONS: This study developed an energy metabolic-based classifier for gliomas with prognostic and therapeutic potential. Metabolic reprogramming was linked with the PN-to-MES transition of glioma cells and immunosuppression in the tumor microenvironment. Multi-omics data, especially snRNA-seq, offered insights into metabolism heterogeneity at single-cell resolution, enabling personalized treatment strategies.

Humans↗
PubMed2000

Recovery of global nonrigid motion: a model-based approach without point correspondences

We present a novel technique for the estimation of global nonrigid motion of an object's boundary without using point correspondences. A complete description of the motion of an object's boundary involves specifying a displacement vector at each point of the boundary. Such a description provides a large amount of information, which needs to be processed further for study of the global characteristics of the deformation. Nonrigid motion can be studied hierarchically in terms of global nonrigid motion and point-by-point local nonrigid motion. The technique presented gives a method for estimating a global affine or polynomial transformation between two object boundaries. The novelty of the technique lies in the fact that it does not use any point correspondences. Our method uses hyperquadric models to model the data and estimate the global deformation. We show that affine or polynomial transformation between two datasets can be recovered from the hyperquadric parameters. The usefulness of the technique is twofold. First, it paves the way for viewing nonrigid motion hierarchically in terms of global and local motion. Second, it can be used as a front end to other motion analysis techniques that assume small motion. For instance, most nonrigid motion analysis algorithms make some assumptions on the type of nonrigid motion (conformal motion, small motion, etc.) that are not always satisfied in practice. When the motion between two datasets is large, our algorithm can be used to estimate the affine transformation (which includes scale and shear) or a polynomial transformation between the two datasets, which can then be used to warp the first dataset closer to the second so as to satisfy the small-motion assumption. We present experimental results with real and synthetic two- and three-dimensional data.

Journal Article↗
PubMed2004

Relative significance of the terms in the CIEDE2000 and CIE94 color-difference formulas.

CIELAB-based color-difference formulas are used to improve the prediction of visually perceived color differences through the introduction of various corrections to CIELAB. In our study we analyze the relative importance of these corrections. From the combined dataset employed for the development of CIEDE2000, we found that the improvement of CIE94 over CIELAB was considerably greater than that of CIEDE2000 over CIE94. Chroma-difference correction was the most important correction in both CIE94 and CIEDE2000. With an arbitrary value of 100 assigned to this correction, the score of the hue-difference correction in CIE94 was 21, and the scores of the four remaining corrections in CIEDE2000 were as follows: hue difference, 29; rotation term, 8; lightness difference, 8; and gray correction, 6. At 95% confidence level each of the corrections introduced in CIEDE2000 or CIE94 was statistically significant for the whole combined dataset, in agreement with the results reported by CIE TC 1-47 and 1-29. For the combined dataset, the differences between CMC and CIEDE2000 were found to be statistically significant at 95% confidence level, but the differences between CMC and CIE94 were not. From subsets of the combined dataset it was concluded that further analyses of the lightness-difference and gray corrections proposed by CIEDE2000 would be desirable, using new experimental data.

Journal Article↗
PubMed2006

The G protein-coupled receptor subset of the chicken genome.

G protein-coupled receptors (GPCRs) are one of the largest families of proteins, and here we scan the recently sequenced chicken genome for GPCRs. We use a homology-based approach, utilizing comparisons with all human GPCRs, to detect and verify chicken GPCRs from translated genomic alignments and Genscan predictions. We present 557 manually curated sequences for GPCRs from the chicken genome, of which 455 were previously not annotated. More than 60% of the chicken Genscan gene predictions with a human ortholog needed curation, which drastically changed the average percentage identity between the human-chicken orthologous pairs (from 56.3% to 72.9%). Of the non-olfactory chicken GPCRs, 79% had a one-to-one orthologous relationship to a human GPCR. The Frizzled, Secretin, and subgroups of the Rhodopsin families have high proportions of orthologous pairs, although the percentage of amino acid identity varies. Other groups show large differences, such as the Adhesion family and GPCRs that bind exogenous ligands. The chicken has only three bitter Taste 2 receptors, and it also lacks an ortholog to human TAS1R2 (one of three GPCRs in the human genome in the Taste 1 receptor family [TAS1R]), implying that the chicken's ability and mode of detecting both bitter and sweet taste may differ from the human's. The chicken genome contains at least 229 olfactory receptors, and the majority of these (218) originate from a chicken-specific expansion. To our knowledge, this dataset of chicken GPCRs is the largest curated dataset from a single gene family from a non-mammalian vertebrate. Both the updated human GPCR dataset, as well the chicken GPCR dataset, are available for download.

Animals↗
PubMed2006

Meta-analysis of differentiating mouse embryonic stem cell gene expression kinetics reveals early change of a small gene set.

Stem cell differentiation involves critical changes in gene expression. Identification of these should provide endpoints useful for optimizing stem cell propagation as well as potential clues about mechanisms governing stem cell maintenance. Here we describe the results of a new meta-analysis methodology applied to multiple gene expression datasets from three mouse embryonic stem cell (ESC) lines obtained at specific time points during the course of their differentiation into various lineages. We developed methods to identify genes with expression changes that correlated with the altered frequency of functionally defined, undifferentiated ESC in culture. In each dataset, we computed a novel statistical confidence measure for every gene which captured the certainty that a particular gene exhibited an expression pattern of interest within that dataset. This permitted a joint analysis of the datasets, despite the different experimental designs. Using a ranking scheme that favored genes exhibiting patterns of interest, we focused on the top 88 genes whose expression was consistently changed when ESC were induced to differentiate. Seven of these (103728_at, 8430410A17Rik, Klf2, Nr0b1, Sox2, Tcl1, and Zfp42) showed a rapid decrease in expression concurrent with a decrease in frequency of undifferentiated cells and remained predictive when evaluated in additional maintenance and differentiating protocols. Through a novel meta-analysis, this study identifies a small set of genes whose expression is useful for identifying changes in stem cell frequencies in cultures of mouse ESC. The methods and findings have broader applicability to understanding the regulation of self-renewal of other stem cell types.

Adaptation, Physiological↗
PubMed2025

Trajectory inference from single-cell genomics data with a process time model.

Single-cell transcriptomics experiments provide gene expression snapshots of heterogeneous cell populations across cell states. These snapshots have been used to infer trajectories and dynamic information even without intensive, time-series data by ordering cells according to gene expression similarity. However, while single-cell snapshots sometimes offer valuable insights into dynamic processes, current methods for ordering cells are limited by descriptive notions of "pseudotime" that lack intrinsic physical meaning. Instead of pseudotime, we propose inference of "process time" via a principled modeling approach to formulating trajectories and inferring latent variables corresponding to timing of cells subject to a biophysical process. Our implementation of this approach, called Chronocell, provides a biophysical formulation of trajectories built on cell state transitions. The Chronocell model is identifiable, making parameter inference meaningful. Furthermore, Chronocell can interpolate between trajectory inference, when cell states lie on a continuum, and clustering, when cells cluster into discrete states. By using a variety of datasets ranging from cluster-like to continuous, we show that Chronocell enables us to assess the suitability of datasets and reveals distinct cellular distributions along process time that are consistent with biological process times. We also compare our parameter estimates of degradation rates to those derived from metabolic labeling datasets, thereby showcasing the biophysical utility of Chronocell. Nevertheless, based on performance characterization on simulations, we find that process time inference can be challenging, highlighting the importance of dataset quality and careful model assessment.

Single-Cell Analysis↗
PubMed2025

How does date-rounding affect phylodynamic inference for public health?

Phylodynamic analyses infer epidemiological parameters from pathogen genome sequences for enhanced genomic surveillance in public health. Pathogen genome sequences and their associated sampling dates are the essential data in every analysis. However, sampling dates are usually associated with hospitalisation or testing and can sometimes be used to identify individual patients, posing a threat to patient confidentiality. To lower this risk, sampling dates are often given with reduced date-resolution to the month or year, which can potentially bias inference. Here, we introduce a practical guideline on when date-rounding biases the inference of epidemiologically important parameters across a diverse range of empirical and simulated datasets. We show that the direction of bias varies for different parameters, datasets, and tree priors, while compounding with lower date-resolution and higher substitution rates. We also find that bias decreases for datasets with longer sampling intervals, implying that our guideline is most applicable to emerging datasets. We conclude by discussing future solutions that prioritise patient confidentiality and propose a method for safer sharing of sampling dates that translates them them uniformly by a random number.

Humans↗
PubMed2025

Sparse deconvolution of cell type medleys in spatial transcriptomics.

Mapping cell distributions across spatial locations with whole-genome coverage is essential for understanding cellular responses and signaling However, current deconvolution models aim to estimate the proportions of distinct cell types in each spatial transcriptomics spot by integrating reference single-cell data. These models often assume strong overlap between the reference and spatial datasets, neglecting biology-grounded constraints such as sparsity and cell-type variations, as well as technical sparsity. As a result, these methods rely on over-permissive algorithms that ignore given constraints leading to inaccurate predictions, particularly in heterogeneous or unmatched datasets. We introduce Weight-Induced Sparse Regression (WISpR), a machine learning algorithm that integrates spot-specific hyperparameters and sparsity-driven modeling. Unlike conventional approaches that neglect biology-grounded constraints, WISpR accurately predicts cell-type distributions while preserving biological coherence, i.e., spatially and functionally consistent cell-type localization, even in unmatched datasets. Benchmarking against five alternative methods across ten datasets, WISpR consistently outperformed competitors and predicted cellular landscapes in both normal and cancerous tissues. By leveraging sparse cell-type arrangements, WISpR provides biologically informed, high-resolution cellular maps. Its ability to decode tissue organization in both healthy and diseased states highlights WISpR's practical utility for spatial transcriptomics, particularly in challenging settings involving noise, sparsity, or reference mismatches.

Humans↗
PubMed2006

SPA: a probabilistic algorithm for spliced alignment.

Recent large-scale cDNA sequencing efforts show that elaborate patterns of splice variation are responsible for much of the proteome diversity in higher eukaryotes. To obtain an accurate account of the repertoire of splice variants, and to gain insight into the mechanisms of alternative splicing, it is essential that cDNAs are very accurately mapped to their respective genomes. Currently available algorithms for cDNA-to-genome alignment do not reach the necessary level of accuracy because they use ad hoc scoring models that cannot correctly trade off the likelihoods of various sequencing errors against the probabilities of different gene structures. Here we develop a Bayesian probabilistic approach to cDNA-to-genome alignment. Gene structures are assigned prior probabilities based on the lengths of their introns and exons, and based on the sequences at their splice boundaries. A likelihood model for sequencing errors takes into account the rates at which misincorporation, as well as insertions and deletions of different lengths, occurs during sequencing. The parameters of both the prior and likelihood model can be automatically estimated from a set of cDNAs, thus enabling our method to adapt itself to different organisms and experimental procedures. We implemented our method in a fast cDNA-to-genome alignment program, SPA, and applied it to the FANTOM3 dataset of over 100,000 full-length mouse cDNAs and a dataset of over 20,000 full-length human cDNAs. Comparison with the results of four other mapping programs shows that SPA produces alignments of significantly higher quality. In particular, the quality of the SPA alignments near splice boundaries and SPA's mapping of the 5' and 3' ends of the cDNAs are highly improved, allowing for more accurate identification of transcript starts and ends, and accurate identification of subtle splice variations. Finally, our splice boundary analysis on the human dataset suggests the existence of a novel non-canonical splice site that we also find in the mouse dataset. The SPA software package is available at http://www.biozentrum.unibas.ch/personal/nimwegen/cgi-bin/spa.cgi.

Algorithms↗
PubMed2006

A predictive model to identify women with injuries related to intimate partner violence.

PURPOSE: The diagnosis of intimate partner violence (IPV) is challenging. The authors conducted a cross-sectional study to develop a predictive model to identify IPV-related injuries and validate the model with an independent sample. MATERIALS AND METHODS: The authors enrolled women older than 18 years seeking treatment for injuries. They randomized the sample into index and validation datasets. They used the index dataset to develop a predictive model; the validation set served as an independent sample for assessing the predictive model's goodness of fit. Study variables included risk of self-report of an IPV-related injury and demographic and socioeconomic variables. The outcome variable was self-reported injury etiology (IPV or other). The authors used multiple logistic regression techniques to develop a predictive model that they then applied to the validation dataset, and they measured goodness of fit with the Hosmer-Lemeshow test. RESULTS: The sample was randomized into index (n = 201) and validation (n = 104) sets. For the index set, age, race and risk of IPV were associated with IPV-related injuries (P < .01). The accuracy of the model was 92 percent. Application of the model to the validation dataset resulted in excellent agreement between the observed and actual number of women with IPV-related injuries (accuracy: 93 percent). No statistically significant differences existed between the observed and predicted outcomes (P = .64). CONCLUSIONS: A predictive model composed of age, race and risk of experiencing IPV accurately characterizes women likely to report IPV-related injuries. CLINICAL IMPLICATIONS: Once the clinician diagnoses IPV-related injury, he or she can intervene to prevent future IPV-related injuries.

Adult↗
PubMed1999

Dose-dependent effect of folic acid on the prevention of orofacial clefts.

OBJECTIVE: In 1982, Tolarova(4) found a reduction in the recurrence rate of isolated cleft lip (CL) with or without cleft palate (CP; CL +/- CP) after periconceptional supplementation with a multivitamin including a very high dose (10 mg) of folic acid. The Hungarian randomized, double-blind, controlled trial of periconceptional supplementation with a multivitamin including a physiologic dose (.8 mg) of folic acid did not show any preventive effect on the first occurrence of isolated CL +/- CP and CP. However, the general evaluation of congenital abnormalities in the Hungarian Case-Control Surveillance of Congenital Abnormalities indicated, among others, a reduction of isolated CL +/- CP and CP after the use of high doses of folic acid in the critical period for the development of these congenital abnormalities in the 12-year dataset between 1980 and 1991. We hypothesized that the prevention of orofacial clefts by folic acid has a dose-dependent effect, and this hypothesis was tested in 2 recent Hungarian datasets. DESIGN: In a prospective cohort study, the occurrence of isolated CL +/- CP and CP was studied in the newborn infants born to mothers with or without periconceptional folic acid-containing (.8 mg) multivitamin supplementation. Supplemented women with confirmed pregnancy were recruited from the participants of the periconceptional service. Unsupplemented women were invited to take part in the study after the first visit between the 8th and 12th week of gestation in the antenatal care. Supplemented and unsupplemented women were matched based on age, socioeconomic status, and residence. In contrast, the occurrence of high-dose (in general daily 6 mg) folic acid supplementation was evaluated in the case-control pairs of CL +/- CP and CP, particularly during the critical period of these 2 types of orofacial clefts in the 17 years dataset of the Case-Control Surveillance of Congenital Abnormalities, between 1980 and 1996. Cases were selected from the population-based Hungarian Congenital Abnormality Registry, whereas population controls without congenital abnormality were ascertained from the national birth registry. Two population controls were matched to every case according to sex, week of birth, and district of parental residence. The drug uses, including pregnancy supplements as folic acid, were evaluated based on retrospective self-reported maternal questionnaire and prospective medically documented data of antenatal care logbook. RESULTS: In the prospective cohort study, of 3019 informative offspring (termination of pregnancies in the second and third trimesters because of fetal defect, stillborn fetuses, and liveborn infants) in the supplemented group, 3 had CL +/- CP and 1 was affected with CP, whereas of 3432 informative offspring in the unsupplemented group, 2 had CL +/- CP and 1 had CP. The lack of preventive effect was in agreement with the result of the previous Hungarian randomized double-blind controlled trial; thus, these 2 datasets were combined. The preventive effect of a folic acid containing multivitamin used in the periconceptional period for the first occurrence of isolated CL +/- CP and CP was estimated by the Mantel-Haenszel test. Of 5488 supplemented women, 6 had CL +/- CP, and of 5821 unsupplemented women, 4 had CL +/- CP. Of 5489 supplemented women, 1 had CP, and of 5823 unsupplemented pregnant women, 3 had CP. The Hungarian Case-Control Surveillance of Congenital Abnormalities, 1980-1996, included 38 151 population controls (1.8% of the Hungarian births) and 22 865 cases with congenital abnormalities. Within the latter group, 1368 had isolated CL +/- CP, and 596 had CP. A significantly more frequent use of high-dose folic acid (in general daily 6 mg) supplementation was found in controls than in cases of 1246 case-control pairs of CL +/- CP group and of 537 case-control pairs of CP group, respectively. (ABSTRACT TRUNCATED)

Adult↗
PubMed2004

Multidetector CT angiography of arterial inflow and runoff in the lower extremities: a challenge in data acquisition and evaluation.

PURPOSE: To show the feasibility of acquiring homogenous 3-dimensional datasets with high temporal and spatial resolution from computed tomographic angiographic (CTA) scans of the lower extremities and to assess automated vessel-tracking techniques for vascular evaluation. METHODS: Eighteen men (mean age 67.0 years, range 43-83) with aneurysmal or occlusive vascular diseases underwent contrast-enhanced CTA of the lower limb arteries utilizing a 16-row CT imager. Curved multiplanar reformations were generated by manual selection of vessel centerlines in the infrarenal aorta and the arterial vasculature in the pelvis, thigh, and calf based on volume-rendering techniques. For each vessel, opacification and depiction were quantitatively evaluated. The manually segmented images were compared to datasets processed with automated vessel-tracking strategies by 5 radiologists, who evaluated diagnostic reliability and image quality. A Differential Receiver Operating Characteristic (DROC) analysis was performed. RESULTS: An increase in the temporal and spatial resolution led to acquisition of high quality CTA datasets. Significant homogeneity of the vascular contrast-to-noise ratios was achieved in the pelvic (coefficient of variance 1.5% to 10.1%), thigh (0.1% to 9.4%), and calf (3.3% to 19.2%) vessels. The assessment of vascular delineation revealed full-width-at-half-maximum contrast values of 96.4%, 95.5%, and 111.3% in the pelvis, thigh, and calf, respectively. Observers were not able to distinguish between manual and automated vascular segmentation, as represented by a 0.56 value for the area under the DROC curve. CONCLUSIONS: High-resolution CTA lower extremity datasets were acquired successfully, presenting vascular signal intensities of high homogeneity suitable for automated vessel-tracking techniques. Automated 3D visualization tools produced reliable, reproducible, and time-efficient centerline extractions that were comparable to manually defined centerlines.

Adult↗
PubMed2005

Functional grouping of yeast genes via biclustering microarray data.

Biclustering algorithm on Gibbs sampling strategy is a recruit in the field of the analysis of gene expression data of microarray experiments. Its feasibility and validity still need to be researched not only for synthetic datasets but also for real datasets. Here we investigated a biclustering algorithm on a microarray dataset of Yeast genome through building a database for storing microarray datasets and MIPS data, and running the scripts on Matlab platform to discover gene patterns. In contrast with standard clusterings that reveal genes behaving similarly over all the conditions, biclustering groups genes over only a subset of conditions for which those genes have a sharp probability distribution. It has the key advantage of providing a transparent probabilistic interpretation of the biclusters. Its basic strategy of Gibbs sampling does not suffer from the problem of local minima that often characterizes expectation maximization, so that the patterns should be more global and accurate. Also we tested it with the known explanation of genes in MIPS, objectively to demonstrate the effectiveness and deficiencies of biclustering approach, and the functions of a few unknown ORFs in some bicluster can be deduced in the present research. In addition, the result of similarity searching in Blast-Search can be an assistant evidence for its effectivity.

Cluster Analysis↗
PubMed2001

Measles: how many hospitalised cases are we missing?

We aimed to determine whether the Victorian measles surveillance system had missed hospitalised cases of measles during an inter-epidemic period. We searched the Victorian Inpatient Minimum Dataset (VIMD) for the period 1 January 1997 to 30 June 1998 to identify patients with ICD-9 discharge codes for measles (055). The data were compared with that held in the Victorian measles surveillance dataset. The hospital case notes of patients identified in the VIMD but not in the measles surveillance dataset were reviewed systematically to determine whether the patients met case definitions for laboratory-confirmed or clinically compatible measles. Sixteen admissions (15 patients) were identified with a measles ICD-9 code. Eight patients were not identified in the measles surveillance dataset. Of these, one was a laboratory confirmed case of measles and two met a clinical case definition but all should have been notified to the Department of Human Services as suspected cases. While the small number of missed notifications is encouraging in terms of overall measles surveillance, it highlights important deficiencies in the awareness of hospital staff of their role in the control of measles, particularly as Australia moves towards the elimination of measles.

Adult↗
PubMed1999

A study in causal discovery from population-based infant birth and death records.

In the domain of medicine, identification of the causal factors of diseases and outcomes, helps us formulate better management, prevention and control strategies for the improvement of health care. With the goal of exploring, evaluating and refining techniques to learn causal relationships from observational data, such as data routinely collected in healthcare settings, we focused on investigating factors that may contribute causally to infant mortality in the United States. We used the U.S. Linked Birth/Infant Death dataset for 1991 with more than four million records and about 200 variables for each record. Our sample consisted of 41,155 records randomly selected from the whole dataset. Each record had maternal, paternal and child factors and the outcome at the end of the first year--whether the infant survived or not. For causal discovery we used a modified Local Causal Discovery (LCD2) algorithm, which uses the framework of causal Bayesian Networks to represent causal relationships among model variables. LCD2 takes as input a dataset and outputs causes of the form variable X causes variable Y. Using the infant birth and death dataset as input, LCD2 output nine purported causal relationships. Eight out of the nine relationships seem plausible. Even though we have not yet discovered a clinically novel causal link, we plan to look for novel causal pathways using the full sample after refining the algorithm and developing a more efficient implementation.

Algorithms↗
PubMed2000

Radiological tele-immersion for next generation networks.

Since the acquisition of high-resolution three-dimensional patient images has become widespread, medical volumetric datasets (CT or MR) larger than 100 MB and encompassing more than 250 slices are common. It is important to make this patient-specific data quickly available and usable to many specialists at different geographical sites. Web-based systems have been developed to provide volume or surface rendering of medical data over networks with low fidelity, but these cannot adequately handle stereoscopic visualization or huge datasets. State-of-the-art virtual reality techniques and high speed networks have made it possible to create an environment for clinicians geographically distributed to immersively share these massive datasets in real-time. An object-oriented method for instantaneously importing medical volumetric data into Tele-Immersive environments has been developed at the Virtual Reality in Medicine Laboratory (VRMedLab) at the University of Illinois at Chicago (UIC). This networked-VR setup is based on LIMBO, an application framework or template that provides the basic capabilities of Tele-Immersion. We have developed a modular general purpose Tele-Immersion program that automatically combines 3D medical data with the methods for handling the data. For this purpose a DICOM loader for IRIS Performer has been developed. The loader was designed for SGI machines as a shared object, which is executed at LIMBO's runtime. The loader loads not only the selected DICOM dataset, but also methods for rendering, handling, and interacting with the data, bringing networked, real-time, stereoscopic interaction with radiological data to reality. Collaborative, interactive methods currently implemented in the loader include cutting planes and windowing. The Tele-Immersive environment has been tested on the UIC campus over an ATM network. We tested the environment with 3 nodes; one ImmersaDesk at the VRMedLab, one CAVE at the Electronic Visualization Laboratory (EVL) on east campus, and a CT scan machine in UIC Hospital. CT data was pulled directly from the scan machine to the Tele-Immersion server in our Laboratory, and then the data was synchronously distributed by our Onyx2 Rack server to all the VR setups. Instead of permitting medical volume visualization at one VR device, by combining teleconferencing, tele-presence, and virtual reality, the Tele-Immersive environment will enable geographically distributed clinicians to intuitively interact with the same medical volumetric models, point, gesture, converse, and see each other. This environment will bring together clinicians at different geographic locations to participate in Tele-Immersive consultation and collaboration.

Humans↗
PubMed2001

Influence of OSEM and segmented attenuation correction in the calculation of standardised uptake values for [18F]FDG PET.

Standardised Uptake Values (SUVs) are widely used in positron emission tomography (PET) as a semi-quantitative index of fluorine-18 labelled fluorodeoxyglucose uptake. The objective of this study was to investigate any bias introduced in the calculation of SUVs as a result of employing ordered subsets-expectation maximisation (OSEM) image reconstruction and segmented attenuation correction (SAC). Variable emission and transmission time durations were investigated. Both a phantom and a clinical evaluation of the bias were carried out. The software implemented in the GE Advance PET scanner was used. Phantom studies simulating tumour imaging conditions were performed. Since a variable count rate may influence the results obtained using OSEM, similar acquisitions were performed at total count rates of 34 kcps and 12 kcps. Clinical data consisted of 100 patient studies. Emission datasets of 5 and 15 min duration were combined with 15-, 3-, 2- and 1-min transmission datasets for the reconstruction of both phantom and patient studies. Two SUVs were estimated using the average (SUVavg) and the maximum (SUVmax) count density from regions of interest placed well inside structures of interest. The percentage bias of these SUVs compared with the values obtained using a reference image was calculated. The reference image was considered to be the one produced by filtered back-projection (FBP) image reconstruction with measured attenuation correction using the 15-min emission and transmission datasets for each phantom and patient study. A bias of 5%-20% was found for the SUVavg and SUVmax in the case of FBP with SAC using variable transmission times. In the case of OSEM with SAC, the bias increased to 10%-30%. An overall increase of 5%-10% was observed with the use of SUVmax. The 5-min emission dataset led to an increase in the bias of 25%-100%, with the larger increase recorded for the SUVmax. The results suggest that OSEM and SAC with 3 and 2 min transmission may be reliably used to reduce the overall data acquisition time without compromising the accuracy of SUVs.

Fluorodeoxyglucose F18↗
PubMed2002

An overview on predicting the subcellular location of a protein.

The present paper overviews the issue on predicting the subcellular location of a protein. Five measures of extracting information from the global sequence based on the Bayes discriminant algorithm are reviewed. 1) The auto-correlation functions of amino acid indices along the sequence; 2) The quasi-sequence-order approach; 3) the pseudo-amino acid composition; 4) the unified attribute vector in Hilbert space, 5) Zp parameters extracted from the Zp curve. The actual performance of the predictive accuracy is closely related to the degree of similarity between the training and testing sets or to the average degree of pairwise similarity in dataset in a cross-validated study. Many scholars considered that the current higher predictive accuracy still cannot ensure that some available algorithms are effective in practice prediction for the higher pairwise sequence identity of the datasets, but some of them declared that construction of the dataset used for developing software should base on the reality determined by the Mother Nature that some subcellular locations really contain only a minor number of proteins of which some even have a high percentage of sequence similarity. Owing to the complexity of the problem itself, some very sophisticated and special programs are needed for both constructing dataset and improving the prediction. Anyhow finding the target information in mature protein sequence and properly cooperating it with sorting signals in prediction may further improve the overall predictive accuracy and make the prediction into practice.

Algorithms↗