| 1. |
- Neidlin, Michael, et al.
(författare)
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An ex vivo tissue model of cartilage degradation suggests that cartilage state can be determined from secreted key protein patterns
- 2019
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 14:10
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Tidskriftsartikel (refereegranskat)abstract
- The pathophysiology of osteoarthritis (OA) involves dysregulation of anabolic and catabolic processes associated with a broad panel of proteins that ultimately lead to cartilage degradation. An increased understanding about these protein interactions with systematic in vitro analyses may give new ideas regarding candidates for treatment of OA related cartilage degradation. Therefore, an ex vivo tissue model of cartilage degradation was established by culturing tissue explants with bacterial collagenase II. Responses of healthy and degrading cartilage were analyzed through protein abundance in tissue supernatant with a 26-multiplex protein profiling assay, after exposing the samples to a panel of 55 protein stimulations present in synovial joints of OA patients. Multivariate data analysis including exhaustive pairwise variable subset selection identified the most outstanding changes in measured protein secretions. MMP9 response to stimulation was outstandingly low in degrading cartilage and there were several protein pairs like IFNG and MMP9 that can be used for successful discrimination between degrading and healthy samples. The discovered changes in protein responses seem promising for accurate detection of degrading cartilage. The ex vivo model seems interesting for drug discovery projects related to cartilage degradation, for example when trying to uncover the unknown interactions between secreted proteins in healthy and degrading tissues.
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| 2. |
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| 3. |
- Nordlund, Jessica, et al.
(författare)
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DNA methylation-based subtype prediction for pediatric acute lymphoblastic leukemia
- 2015
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Ingår i: Clinical Epigenetics. - : Springer Science and Business Media LLC. - 1868-7083 .- 1868-7075. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- Background: We present a method that utilizes DNA methylation profiling for prediction of the cytogenetic subtypes of acute lymphoblastic leukemia (ALL) cells from pediatric ALL patients. The primary aim of our study was to improve risk stratification of ALL patients into treatment groups using DNA methylation as a complement to current diagnostic methods. A secondary aim was to gain insight into the functional role of DNA methylation in ALL. Results: We used the methylation status of similar to 450,000 CpG sites in 546 well-characterized patients with T-ALL or seven recurrent B-cell precursor ALL subtypes to design and validate sensitive and accurate DNA methylation classifiers. After repeated cross-validation, a final classifier was derived that consisted of only 246 CpG sites. The mean sensitivity and specificity of the classifier across the known subtypes was 0.90 and 0.99, respectively. We then used DNA methylation classification to screen for subtype membership of 210 patients with undefined karyotype (normal or no result) or non-recurrent cytogenetic aberrations('other' subtype). Nearly half (n = 106) of the patients lacking cytogenetic subgrouping displayed highly similar methylation profiles as the patients in the known recurrent groups. We verified the subtype of 20% of the newly classified patients by examination of diagnostic karyotypes, array-based copy number analysis, and detection of fusion genes by quantitative polymerase chain reaction (PCR) and RNA-sequencing (RNA-seq). Using RNA-seq data from ALL patients where cytogenetic subtype and DNA methylation classification did not agree, we discovered several novel fusion genes involving ETV6, RUNX1, and PAX5. Conclusions: Our findings indicate that DNA methylation profiling contributes to the clarification of the heterogeneity in cytogenetically undefined ALL patient groups and could be implemented as a complementary method for diagnosis of ALL. The results of our study provide clues to the origin and development of leukemic transformation. The methylation status of the CpG sites constituting the classifiers also highlight relevant biological characteristics in otherwise unclassified ALL patients.
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| 4. |
- Abarenkov, Kessy, et al.
(författare)
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Annotating public fungal ITS sequences from the built environment according to the MIxS-Built Environment standard – a report from a May 23-24, 2016 workshop (Gothenburg, Sweden)
- 2016
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Ingår i: MycoKeys. - : Pensoft Publishers. - 1314-4057 .- 1314-4049. ; 16, s. 1-15
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Tidskriftsartikel (refereegranskat)abstract
- Recent molecular studies have identified substantial fungal diversity in indoor environments. Fungi and fungal particles have been linked to a range of potentially unwanted effects in the built environment, including asthma, decay of building materials, and food spoilage. The study of the built mycobiome is hampered by a number of constraints, one of which is the poor state of the metadata annotation of fungal DNA sequences from the built environment in public databases. In order to enable precise interrogation of such data – for example, “retrieve all fungal sequences recovered from bathrooms” – a workshop was organized at the University of Gothenburg (May 23-24, 2016) to annotate public fungal barcode (ITS) sequences according to the MIxS-Built Environment annotation standard (http://gensc.org/mixs/). The 36 participants assembled a total of 45,488 data points from the published literature, including the addition of 8,430 instances of countries of collection from a total of 83 countries, 5,801 instances of building types, and 3,876 instances of surface-air contaminants. The results were implemented in the UNITE database for molecular identification of fungi (http://unite.ut.ee) and were shared with other online resources. Data obtained from human/animal pathogenic fungi will furthermore be verified on culture based metadata for subsequent inclusion in the ISHAM-ITS database (http://its.mycologylab.org).
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| 5. |
- Bäcklin, Christofer L., 1983-, et al.
(författare)
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Developer-Friendly and Computationally Efficient Predictive Modeling without Information Leakage : The emil Package for R
- 2018
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Ingår i: Journal of Statistical Software. - : JOURNAL STATISTICAL SOFTWARE. - 1548-7660. ; 85:13, s. 1-30
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Tidskriftsartikel (refereegranskat)abstract
- Data driven machine learning for predictive modeling problems (classification, regression, or survival analysis) typically involves a number of steps beginning with data preprocessing and ending with performance evaluation. A large number of packages providing tools for the individual steps are available for R, but there is a lack of tools for facilitating rigorous performance evaluation of the complete procedures assembled from them by means of cross-validation, bootstrap, or similar methods. Such a tool should strictly prevent test set observations from influencing model training and meta- parameter tuning, so- called information leakage, in order to not produce overly optimistic performance estimates. Here we present a new package for R denoted emil (evaluation of modeling without information leakage) that offers this form of performance evaluation. It provides a transparent and highly customizable framework for facilitating the assembly, execution, performance evaluation, and interpretation of complete procedures for classification, regression, and survival analysis. The components of package emil have been designed to be as modular and general as possible to allow users to combine, replace, and extend them if needed. Package emil was also developed with scalability in mind and has a small computational overhead, which is a key requirement for analyzing the very big data sets now available in fields like medicine, physics, and finance. First package emil's functionality and usage is explained. Then three specific application examples are presented to show its potential in terms of parallelization, customization for survival analysis, and development of ensemble models. Finally a brief comparison to similar software is provided.
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| 6. |
- Bäcklin, Christofer, 1983-, et al.
(författare)
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Self-tuning density estimation based on Bayesian averaging of adaptive kernel density estimations yields state-of-the-art performance
- 2018
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Ingår i: Pattern Recognition. - : ELSEVIER SCI LTD. - 0031-3203 .- 1873-5142. ; 78, s. 133-143
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Tidskriftsartikel (refereegranskat)abstract
- Non-parametric probability density function (pdf) estimation is a general problem encountered in many fields. A promising alternative to the dominating solutions, kernel density estimation (KDE) and Gaussian mixture modeling, is adaptive KDE where kernels are given individual bandwidths adjusted to the local data density. Traditionally the bandwidths are selected by a non-linear transformation of a pilot pdf estimate, containing parameters controlling the scaling, but identifying parameters values yielding competitive performance has turned out to be non-trivial. We present a new self-tuning (parameter free) pdf estimation method called adaptive density estimation by Bayesian averaging (ADEBA) that approximates pdf estimates in the form of weighted model averages across all possible parameter values, weighted by their Bayesian posterior calculated from the data. ADEBA is shown to be simple, robust, competitive in comparison to the current practice, and easily generalize to multivariate distributions. An implementation of the method for R is publicly available.
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| 7. |
- Capek, Miloslav, et al.
(författare)
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Optimal Planar Electric Dipole Antennas Searching for antennas reaching the fundamental bounds on selected metrics.
- 2019
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Ingår i: IEEE Antennas & Propagation Magazine. - : Institute of Electrical and Electronics Engineers (IEEE). - 1045-9243 .- 1558-4143. ; 61:4, s. 19-29
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Tidskriftsartikel (refereegranskat)abstract
- Considerable time is often spent optimizing antennas to meet specific design metrics. Rarely, however, are the resulting antenna designs compared to rigorous physical bounds on those metrics. Here, we study the performance of optimized planar meander line antennas with respect to such bounds. Results show that these simple structures meet the lower bound on the radiation quality factor (Q-factor) (maximizing single-resonance fractional bandwidth) but are far from reaching the associated physical bounds for efficiency. The relative performance of other canonical antenna designs is comparable in similar ways, and the quantitative results are connected to intuitions from small antenna design, physical bounds, and matching network design.
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| 8. |
- Chantzi, Efthymia, et al.
(författare)
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COMBImage : a modular parallel processing framework for pairwise drug combination analysis that quantifies temporal changes in label-free video microscopy movies
- 2018
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Ingår i: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 19
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Tidskriftsartikel (refereegranskat)abstract
- Background: Large-scale pairwise drug combination analysis has lately gained momentum in drug discovery and development projects, mainly due to the employment of advanced experimental-computational pipelines. This is fortunate as drug combinations are often required for successful treatment of complex diseases. Furthermore, most new drugs cannot totally replace the current standard-of-care medication, but rather have to enter clinical use as add-on treatment. However, there is a clear deficiency of computational tools for label-free and temporal image-based drug combination analysis that go beyond the conventional but relatively uninformative end point measurements.Results: COMBImage is a fast, modular and instrument independent computational framework for in vitro pairwise drug combination analysis that quantifies temporal changes in label-free video microscopy movies. Jointly with automated analyses of temporal changes in cell morphology and confluence, it performs and displays conventional cell viability and synergy end point analyses. The image processing algorithms are parallelized using Google's MapReduce programming model and optimized with respect to method-specific tuning parameters. COMBImage is shown to process time-lapse microscopy movies from 384-well plates within minutes on a single quad core personal computer.This framework was employed in the context of an ongoing drug discovery and development project focused on glioblastoma multiforme; the most deadly form of brain cancer. Interesting add-on effects of two investigational cytotoxic compounds when combined with vorinostat were revealed on recently established clonal cultures of glioma-initiating cells from patient tumor samples. Therapeutic synergies, when normal astrocytes were used as a toxicity cell model, reinforced the pharmacological interest regarding their potential clinical use.Conclusions: COMBImage enables, for the first time, fast and optimized pairwise drug combination analyses of temporal changes in label-free video microscopy movies. Providing this jointly with conventional cell viability based end point analyses, it could help accelerating and guiding any drug discovery and development project, without use of cell labeling and the need to employ a particular live cell imaging instrument.
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| 9. |
- Chantzi, Efthymia, et al.
(författare)
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COMBImage2 : a parallel computational framework for higher-order drug combination analysis that includes automated plate design, matched filter based object counting and temporal data mining
- 2019
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Ingår i: BMC Bioinformatics. - : BMC. - 1471-2105. ; 20
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Tidskriftsartikel (refereegranskat)abstract
- Background: Pharmacological treatment of complex diseases using more than two drugs is commonplace in the clinic due to better efficacy, decreased toxicity and reduced risk for developing resistance. However, many of these higher-order treatments have not undergone any detailed preceding in vitro evaluation that could support their therapeutic potential and reveal disease related insights. Despite the increased medical need for discovery and development of higher-order drug combinations, very few reports from systematic large-scale studies along this direction exist. A major reason is lack of computational tools that enable automated design and analysis of exhaustive drug combination experiments, where all possible subsets among a panel of pre-selected drugs have to be evaluated.Results: Motivated by this, we developed COMBImage2, a parallel computational framework for higher-order drug combination analysis. COMBImage2 goes far beyond its predecessor COMBImage in many different ways. In particular, it offers automated 384-well plate design, as well as quality control that involves resampling statistics and inter-plate analyses. Moreover, it is equipped with a generic matched filter based object counting method that is currently designed for apoptotic-like cells. Furthermore, apart from higher-order synergy analyses, COMBImage2 introduces a novel data mining approach for identifying interesting temporal response patterns and disentangling higher- from lower- and single-drug effects.COMBImage2 was employed in the context of a small pilot study focused on the CUSP9v4 protocol, which is currently used in the clinic for treatment of recurrent glioblastoma. For the first time, all 246 possible combinations of order 4 or lower of the 9 single drugs consisting the CUSP9v4 cocktail, were evaluated on an in vitro clonal culture of glioma initiating cells.Conclusions: COMBImage2 is able to automatically design and robustly analyze exhaustive and in general higher-order drug combination experiments. Such a versatile video microscopy oriented framework is likely to enable, guide and accelerate systematic large-scale drug combination studies not only for cancer but also other diseases.
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| 10. |
- Eriksson, Anna, 1977-, et al.
(författare)
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Towards repositioning of quinacrine for treatment of acute myeloid leukemia - Promising synergies and in vivo effects.
- 2017
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Ingår i: Leukemia Research. - : Elsevier BV. - 0145-2126 .- 1873-5835. ; 63, s. 41-46
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Tidskriftsartikel (refereegranskat)abstract
- We previously reported that the anti-malarial drug quinacrine has potential to be repositioned for treatment of acute myeloid leukemia (AML). As a next step towards clinical use, we assessed the efficacy of quinacrine in an AML-PS mouse model and investigated possible synergistic effects when combining quinacrine with nine other antileukemic compounds in two AML cell lines. Furthermore, we explored the in vivo activity of quinacrine in combination with the widely used AML agent cytarabine. The in vivo use of quinacrine (100mg/kg three times per week for two consecutive weeks) significantly suppressed circulating blast cells at days 30/31 and increased the median survival time (MST). The in vitro drug combination analysis yielded promising synergistic interactions when combining quinacrine with cytarabine, azacitidine and geldanamycin. Finally, combining quinacrine with cytarabine in vivo showed a significant decrease in circulating leukemic blast cells and increased MST compared to the effect of either drug used alone, thus supporting the findings from the in vitro combination experiments. Taken together, the repositioning potential of quinacrine for treatment of AML is reinforced by demonstrating significant in vivo activity and promising synergies when quinacrine is combined with different agents, including cytarabine, the hypomethylating agent azacitidine and HSP-90 inhibitor geldanamycin.
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