Browsing by Subject "Cluster analysis"

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Open Access
Adjuvant autologous melanoma vaccine for macroscopic stage III disease: survival, biomarkers, and improved response to CTLA-4 blockade
(Hindawi Limited, 2016) Lotem, M.; Merims, S.; Frank, S.; Hamburger, T.; Nissan, A.; Kadouri, L.; Cohen, J.; Straussman, R.; Eisenberg, G.; Frankenburg, S.; Carmon, E.; Alaiyan, B.; Shneibaum, S.; Ayyildiz, Z. O.; Isbilen, M.; Senses, K. M.; Ron, I.; Steinberg, H.; Smith, Y.; Shiloni, E.; Gure, A. O.; Peretz, T.
Background. There is not yet an agreed adjuvant treatment for melanoma patients with American Joint Committee on Cancer stages III B and C. We report administration of an autologous melanoma vaccine to prevent disease recurrence. Patients and Methods. 126 patients received eight doses of irradiated autologous melanoma cells conjugated to dinitrophenyl and mixed with BCG. Delayed type hypersensitivity (DTH) response to unmodified melanoma cells was determined on the vaccine days 5 and 8. Gene expression analysis was performed on 35 tumors from patients with good or poor survival. Results. Median overall survival was 88 months with a 5-year survival of 54%. Patients attaining a strong DTH response had a significantly better (p = 0.0001) 5-year overall survival of 75% compared with 44% in patients without a strong response. Gene expression array linked a 50-gene signature to prognosis, including a cluster of four cancer testis antigens: CTAG2 (NY-ESO-2), MAGEA1, SSX1, and SSX4. Thirty-five patients, who received an autologous vaccine, followed by ipilimumab for progressive disease, had a significantly improved 3-year survival of 46% compared with 19% in nonvaccinated patients treated with ipilimumab alone (p = 0.007). Conclusion. Improved survival in patients attaining a strong DTH and increased response rate with subsequent ipilimumab suggests that the autologous vaccine confers protective immunity.
Open Access
BRAPH: A graph theory software for the analysis of brain connectivity
(Public Library of Science, 2017) Mijalkov, M.; Kakaei, E.; Pereira, J. B.; Westman, E.; Volpe, G.
The brain is a large-scale complex network whose workings rely on the interaction between its various regions. In the past few years, the organization of the human brain network has been studied extensively using concepts from graph theory, where the brain is represented as a set of nodes connected by edges. This representation of the brain as a connectome can be used to assess important measures that reflect its topological architecture. We have developed a freeware MatLab-based software (BRAPH–BRain Analysis using graPH theory) for connectivity analysis of brain networks derived from structural magnetic resonance imaging (MRI), functional MRI (fMRI), positron emission tomography (PET) and electroencephalogram (EEG) data. BRAPH allows building connectivity matrices, calculating global and local network measures, performing non-parametric permutations for group comparisons, assessing the modules in the network, and comparing the results to random networks. By contrast to other toolboxes, it allows performing longitudinal comparisons of the same patients across different points in time. Furthermore, even though a user-friendly interface is provided, the architecture of the program is modular (object-oriented) so that it can be easily expanded and customized. To demonstrate the abilities of BRAPH, we performed structural and functional graph theory analyses in two separate studies. In the first study, using MRI data, we assessed the differences in global and nodal network topology in healthy controls, patients with amnestic mild cognitive impairment, and patients with Alzheimer’s disease. In the second study, using resting-state fMRI data, we compared healthy controls and Parkinson’s patients with mild cognitive impairment. © 2017 Mijalkov et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Open Access
Cortical networks of dynamic scene category representation in the human brain
(Elsevier, 2021-07-24) Keleş, Ümit; Kiremitçi, İbrahim; Gallant, J. L.; Çukur, Tolga; Çelik, Emin
Humans have an impressive ability to rapidly process global information in natural scenes to infer their category. Yet, it remains unclear whether and how scene categories observed dynamically in the natural world are represented in cerebral cortex beyond few canonical scene-selective areas. To address this question, here we examined the representation of dynamic visual scenes by recording whole-brain blood oxygenation level-dependent (BOLD) responses while subjects viewed natural movies. We fit voxelwise encoding models to estimate tuning for scene categories that reflect statistical ensembles of objects and actions in the natural world. We find that this scene-category model explains a significant portion of the response variance broadly across cerebral cortex. Cluster analysis of scene-category tuning profiles across cortex reveals nine spatially-segregated networks of brain regions consistently across subjects. These networks show heterogeneous tuning for a diverse set of dynamic scene categories related to navigation, human activity, social interaction, civilization, natural environment, non-human animals, motion-energy, and texture, suggesting that the organization of scene category representation is quite complex.
Open Access
Differences in the accumulation and distribution profile of heavy metals and metalloid between male and female crayfish (Astacus leptodactylus)
(2013) Tunca, E.; Ucuncu, E.; Ozkan, A.D.; Ulger, Z.E.; Cansizoǧlu, A.E.; Tekinay, T.
Concentrations of selected heavy metals and a metalloid were measured by ICP-MS in crayfish (Astacus leptodactylus) collected from Lake Hirfanli, Turkey. Aluminum (Al), chromium (52Cr, 53Cr), copper ( 63Cu, 65Cu), manganese (Mn), nickel (Ni) and arsenic (As) were measured in the exoskeleton, gills, hepatopancreas and abdominal muscle tissues of 60 crayfish of both genders. With the exception of Al, differences were determined between male and female cohorts for the accumulation trends of the above-mentioned elements in the four tissues. It was also noted that the accumulation rates of Ni and As were significantly lower in gill tissue of females compared to males and no significant difference was observed for Cu isotopes in female crayfish. Cluster Analysis (CA) recovered similar results for both genders, with links between accumulations of Ni and As being notable. Accumulation models were described separately for male and female crayfish using regression analysis, and are presented for models where R2 > 0.85. © 2013 Springer Science+Business Media New York.
Open Access
Distinct regulation of tonsillar immune response in virus infection
(Wiley-Blackwell Publishing Ltd., 2014) Jartti, T.; Palomares, O.; Waris, M.; Tastan, O.; Nieminen, R.; Puhakka, T.; Rückert, B.; Aab, A.; Vuorinen, T.; Allander, T.; Vahlberg, T.; Ruuskanen, O.; Akdis, M.; Akdis, C. A.
Background: The relationships between tonsillar immune responses, and viral infection and allergy are incompletely known. Objective To study intratonsillar/nasopharyngeal virus detections and in vivo expressions of T-cell- and innate immune response-specific cytokines, transcription factors, and type I/II/III interferons in human tonsils. Methods: Palatine tonsil samples were obtained from 143 elective tonsillectomy patients. Adenovirus, bocavirus-1, coronavirus, enteroviruses, influenza virus, metapneumovirus, parainfluenza virus, rhinovirus, and respiratory syncytial virus were detected using PCR. The mRNA expression levels of IFN-α, IFN-β, IFN-γ, IL-10, IL-13, IL-17, IL-28, IL-29, IL-37, TGF-β, FOXP3, GATA3, RORC2, and Tbet were directly analyzed by quantitative RT-PCR. Results Fifty percentage of subjects reported allergy, 59% had ≥1 nasopharyngeal viruses, and 24% had ≥1 intratonsillar viruses. Tonsillar virus detection showed a strong negative association with age; especially rhinovirus or parainfluenza virus detection showed positive association with IFN-γ and Tbet expressions. IL-37 expression was positively associated with atopic dermatitis, whereas IFN-α, IL-13, IL-28, and Tbet expressions were negatively associated with allergic diseases. Network analyses demonstrated strongly polarized clusters of immune regulatory (IL-10, IL-17, TGF-β, FOXP3, GATA3, RORC2, Tbet) and antiviral (IFN-α, IFN-β, IL-28, IL-29) genes. These two clusters became more distinctive in the presence of viral infection or allergy. A negative correlation between antiviral cytokines and IL-10, IL-17, IL-37, FOXP3, and RORC2 was observed only in the presence of viruses, and interestingly, IL-13 strongly correlated with antiviral cytokines. Conclusions: Tonsillar cytokine expression is closely related to existing viral infections, age, and allergic illnesses and shows distinct clusters between antiviral and immune regulatory genes. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Open Access
Efficient processing of category-restricted queries for web directories
(Springer, 2008-03-04) Altıngövde, İsmail Şengör; Can, Fazlı; Ulusoy, Özgür
We show that a cluster-skipping inverted index (CS-IIS) is a practical and efficient file structure to support category-restricted queries for searching Web directories. The query processing strategy with CS-IIS improves CPU time efficiency without imposing any limitations on the directory size. © 2008 Springer-Verlag Berlin Heidelberg.
Open Access
Large-scale cluster-based retrieval experiments on Turkish texts
(ACM, 2007) Altıngövde, İsmail Şengör; Özcan, Rıfat; Öcalan Hüseyin C.; Can, Fazlı; Ulusoy, Özgür
We present cluster-based retrieval (CBR) experiments on the largest available Turkish document collection. Our experiments evaluate retrieval effectiveness and efficiency on both an automatically generated clustering structure and a manual classification of documents. In particular, we compare CBR effectiveness with full-text search (FS) and evaluate several implementation alternatives for CBR. Our findings reveal that CBR yields comparable effectiveness figures with FS. Furthermore, by using a specifically tailored cluster-skipping inverted index we significantly improve in-memory query processing efficiency of CBR in comparison to other traditional CBR techniques and even FS.
Open Access
A novel model-based method for feature extraction from protein sequences for classification
(IEEE, 2006) Saraç, Ö. S.; Atalay, V.; Çetin-Atalay, Rengül
Representation of amino-acid sequences constitutes the key point in classification of proteins into functional or structural classes. The representation should contain the biologically meaningful information hidden in the primary sequence of the protein. Conserved or similar subsequences are strong indicators of functional and structural similarity. In this study we present a feature mapping that takes into account the models of the subsequences of protein sequences. An expectation-maximization algorithm along with an HMM mixture model is used to cluster and learn the models of subsequences of a given set of proteins.
Open Access
Online bicriteria load balancing for distributed file servers
(IEEE, 2008-08) Tse, Savio
We study the online bicriteria load balancing problem in a system of M distributed homogeneous file servers located in a cluster. The load and storage space are assumed to be independent. We propose two online approximate algorithms for balancing the load and required storage space of each server during document placement. Our first algorithm combines the first result In [10] and the upper bound result In [1]. With applying document reallocation, we further obtain improvement and give a smoother tradeoff curve of the upper bounds of load and storage space. This result improves the best existing solutions. The second algorithm Is for theoretical purpose. Its existence proves that the bounds for the load and the required storage space of each server, respectively, are strictly better when document reallocation Is allowed. It enhances the research In applying document reallocation. The time complexities of both algorithms are O(log M); and the cost of document reallocation should be taken into account.
Open Access
PATIKAmad: putting microarray data into pathway context
(Wiley - V C H Verlag GmbH & Co. KGaA, 2008-06) Babur, Özgün; Colak, Recep; Demir, Emek; Doğrusöz, Uğur
High-throughput experiments, most significantly DNA microarrays, provide us with system-scale profiles. Connecting these data with existing biological networks poses a formidable challenge to uncover facts about a cell's proteome. Studies and tools with this purpose are limited to networks with simple structure, such as protein-protein interaction graphs, or do not go much beyond than simply displaying values on the network. We have built a microarray data analysis tool, named PATIKAmad, which can be used to associate microarray data with the pathway models in mechanistic detail, and provides facilities for visualization, clustering, querying, and navigation of biological graphs related with loaded microarray experiments. PATIKAmad is freely available to noncommercial users as a new module of PATIKAweb at http://web.patika.org. © 2008 Wiley-VCH Verlag GmbH & Co. KGaA.
Open Access
Quantification of SLIT-ROBO transcripts in hepatocellular carcinoma reveals two groups of genes with coordinate expression
(BioMed Central, 2008) Avci, M. E.; Konu, O.; Yagci, T.
Background: SLIT-ROBO families of proteins mediate axon pathfinding and their expression is not solely confined to nervous system. Aberrant expression of SLIT-ROBO genes was repeatedly shown in a wide variety of cancers, yet data about their collective behavior in hepatocellular carcinoma (HCC) is missing. Hence, we quantified SLIT-ROBO transcripts in HCC cell lines, and in normal and tumor tissues from liver. Methods: Expression of SLIT-ROBO family members was quantified by real-time qRT-PCR in 14 HCC cell lines, 8 normal and 35 tumor tissues from the liver. ANOVA and Pearson's correlation analyses were performed in R environment, and different clinicopathological subgroups were pairwise compared in Minitab. Gene expression matrices of cell lines and tissues were analyzed by Mantel's association test. Results: Genewise hierarchical clustering revealed two subgroups with coordinate expression pattern in both the HCC cell lines and tissues: ROBO1, ROBO2, SLIT1 in one cluster, and ROBO4, SLIT2, SLIT3 in the other, respectively. Moreover, SLIT-ROBO expression predicted AFP-dependent subgrouping of HCC cell lines, but not that of liver tissues. ROBO1 and ROBO2 were significantly up-regulated, whereas SLIT3 was significantly down-regulated in cell lines with high-AFP background. When compared to normal liver tissue, ROBO1 was found to be significantly overexpressed, while ROBO4 was down-regulated in HCC. We also observed that ROBO1 and SLIT2 differentiated histopathological subgroups of liver tissues depending on both tumor staging and differentiation status. However, ROBO4 could discriminate poorly differentiated HCC from other subgroups. Conclusion: The present study is the first in comprehensive and quantitative evaluation of SLIT-ROBO family gene expression in HCC, and suggests that the expression of SLIT-ROBO genes is regulated in hepatocarcinogenesis. Our results implicate that SLIT-ROBO transcription profile is bi-modular in nature, and that each module shows intrinsic variability. We also provide quantitative evidence for potential use of ROBO1, ROBO4 and SLIT2 for prediction of tumor stage and differentiation status.