| 1. |
- Conti, David, V, et al.
(författare)
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Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction
- 2021
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Ingår i: Nature Genetics. - : Springer Nature. - 1061-4036 .- 1546-1718. ; 53:1, s. 65-75
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Tidskriftsartikel (refereegranskat)abstract
- Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction. A meta-analysis of genome-wide association studies across different populations highlights new risk loci and provides a genetic risk score that can stratify prostate cancer risk across ancestries.
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| 2. |
- Adomas, Aleksandra, et al.
(författare)
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Identification and analysis of differentially expressed cDNAs during nonself-competitive interaction between Phlebiopsis gigantea and Heterobasidion parviporum
- 2006
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Ingår i: FEMS Microbiology Ecology. - : Blackwell Publishing. - 0168-6496 .- 1574-6941. ; 57:1, s. 26-39
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Tidskriftsartikel (refereegranskat)abstract
- The molecular factors regulating interspecific interaction between the saprotrophic biocontrol fungus Phlebiopsis gigantea and the conifer pathogen Heterobasidion parviporum were investigated. We constructed cDNA libraries and used expressed sequence tag analysis for the identification and characterization of genes expressed during the self and nonself-hyphal interaction. cDNA clones from either the pathogen or biocontrol agent were arrayed on nylon membrane filters and differentially screened with cDNA probes made from mycelia forming the barrage zone during nonself-interactions, mycelia growing outside the barrage zones or monocultures. BlastX analysis of the differentially expressed clones led to the identification of genes with diverse functions, including those with potential as virulence factors, such as hydrophobins. Because of the high sequence conservation (r2 = 0.81) between P. gigantea and H. parviporum, a selected number of genes from either fungus were used to monitor the expression profile under varying interaction conditions by virtual northern blot. The results are discussed with respect to the potential role of the induced genes during the nonself-competitive interaction for space and nutrients between P. gigantea and H. parviporum.
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| 3. |
- Barreflod, Olle, et al.
(författare)
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Studying the ability to use sport watches when running - insights from a small pilot study
- 2022
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Ingår i: ECIS 2022 Research-in-Progress Papers.
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Konferensbidrag (refereegranskat)abstract
- Digitalization is a phenomenon that seems to affect all aspects of contemporary society. The sports domain is by no means excluded from this development. In sports, the sport watch might be one of the most iconic symbols in how digitalization has enhanced, changed and developed how physical activities are experienced and measured. Despite the massive adoption of sport watches among runners and other athletes, few studies have explored how sports watches are used in the specific activity they are designed for. The study presented in this research in progress paper is small and should be viewed as a small attempt to outline an approach to study digital technology use in sports activities.
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| 4. |
- Christensen, Martin, 1982-, et al.
(författare)
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Sculpting with SARA (Spatial Augmented Reality Assistance)
- 2023
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- We explored how spatial augmented reality can assist sculpting in the physicalspace based on a digital 3D-model. As a result of our findings we propose asetup of software and hardware as well as methods to use these (SARA), thatcan visually guide an artist in the work of manual transfer of digital to physicalthree-dimensional form. As a tool SARA could be used much more loosely; therelationship between a digital 3D sketch and a finished sculpture canconceptually be thought of as similar to a rough underdrawing and a finished oilpainting. In this case, the 3d sketch is there as an initial idea and a guide, but notas a ground truth. Beyond the scope of this project, SARA could be furtherexplored in relation to artistic questions. In practical terms, SARA works in thefollowing way: The colors projected during sculpting indicate how much thedistance deviates from the digital sketch in relation to the projector. The colorsare updated in real-time, as a 3D depth camera is continuously scanning theworking space.
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| 5. |
- Wang, Anqi, et al.
(författare)
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Characterizing prostate cancer risk through multi-ancestry genome-wide discovery of 187 novel risk variants
- 2023
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Ingår i: Nature Genetics. - : Springer Nature. - 1061-4036 .- 1546-1718. ; 55:12, s. 2065-2074
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Tidskriftsartikel (refereegranskat)abstract
- The transferability and clinical value of genetic risk scores (GRSs) across populations remain limited due to an imbalance in genetic studies across ancestrally diverse populations. Here we conducted a multi-ancestry genome-wide association study of 156,319 prostate cancer cases and 788,443 controls of European, African, Asian and Hispanic men, reflecting a 57% increase in the number of non-European cases over previous prostate cancer genome-wide association studies. We identified 187 novel risk variants for prostate cancer, increasing the total number of risk variants to 451. An externally replicated multi-ancestry GRS was associated with risk that ranged from 1.8 (per standard deviation) in African ancestry men to 2.2 in European ancestry men. The GRS was associated with a greater risk of aggressive versus non-aggressive disease in men of African ancestry (P = 0.03). Our study presents novel prostate cancer susceptibility loci and a GRS with effective risk stratification across ancestry groups.
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| 6. |
- Alvarsson, Jonathan, et al.
(författare)
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Benchmarking Study of Parameter Variation When Using Signature Fingerprints Together with Support Vector Machines
- 2014
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Ingår i: Journal of Chemical Information and Modeling. - : American Chemical Society (ACS). - 1549-9596 .- 1549-960X. ; 54:11, s. 3211-3217
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Tidskriftsartikel (refereegranskat)abstract
- QSAR modeling using molecular signatures and support vector machines with a radial basis function is increasingly used for virtual screening in the drug discovery field. This method has three free parameters: C, ?, and signature height. C is a penalty parameter that limits overfitting, ? controls the width of the radial basis function kernel, and the signature height determines how much of the molecule is described by each atom signature. Determination of optimal values for these parameters is time-consuming. Good default values could therefore save considerable computational cost. The goal of this project was to investigate whether such default values could be found by using seven public QSAR data sets spanning a wide range of end points and using both a bit version and a count version of the molecular signatures. On the basis of the experiments performed, we recommend a parameter set of heights 0 to 2 for the count version of the signature fingerprints and heights 0 to 3 for the bit version. These are in combination with a support vector machine using C in the range of 1 to 100 and gamma in the range of 0.001 to 0.1. When data sets are small or longer run times are not a problem, then there is reason to consider the addition of height 3 to the count fingerprint and a wider grid search. However, marked improvements should not be expected.
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| 7. |
- Alvarsson, Jonathan, 1981-
(författare)
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Ligand-based Methods for Data Management and Modelling
- 2015
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Drug discovery is a complicated and expensive process in the billion dollar range. One way of making the drug development process more efficient is better information handling, modelling and visualisation. The majority of todays drugs are small molecules, which interact with drug targets to cause an effect. Since the 1980s large amounts of compounds have been systematically tested by robots in so called high-throughput screening. Ligand-based drug discovery is based on modelling drug molecules. In the field known as Quantitative Structure–Activity Relationship (QSAR) molecules are described by molecular descriptors which are used for building mathematical models. Based on these models molecular properties can be predicted and using the molecular descriptors molecules can be compared for, e.g., similarity. Bioclipse is a workbench for the life sciences which provides ligand-based tools through a point and click interface. The aims of this thesis were to research, and develop new or improved ligand-based methods and open source software, and to work towards making these tools available for users through the Bioclipse workbench. To this end, a series of molecular signature studies was done and various Bioclipse plugins were developed.An introduction to the field is provided in the thesis summary which is followed by five research papers. Paper I describes the Bioclipse 2 software and the Bioclipse scripting language. In Paper II the laboratory information system Brunn for supporting work with dose-response studies on microtiter plates is described. In Paper III the creation of a molecular fingerprint based on the molecular signature descriptor is presented and the new fingerprints are evaluated for target prediction and found to perform on par with industrial standard commercial molecular fingerprints. In Paper IV the effect of different parameter choices when using the signature fingerprint together with support vector machines (SVM) using the radial basis function (RBF) kernel is explored and reasonable default values are found. In Paper V the performance of SVM based QSAR using large datasets with the molecular signature descriptor is studied, and a QSAR model based on 1.2 million substances is created and made available from the Bioclipse workbench.
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| 8. |
- Alvarsson, Jonathan, et al.
(författare)
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Ligand-Based Target Prediction with Signature Fingerprints
- 2014
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Ingår i: Journal of Chemical Information and Modeling. - : American Chemical Society (ACS). - 1549-9596 .- 1549-960X. ; 54:10, s. 2647-2653
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Tidskriftsartikel (refereegranskat)abstract
- When evaluating a potential drug candidate it is desirable to predict target interactions in silico prior to synthesis in order to assess, e.g., secondary pharmacology. This can be done by looking at known target binding profiles of similar compounds using chemical similarity searching. The purpose of this study was to construct and evaluate the performance of chemical fingerprints based on the molecular signature descriptor for performing target binding predictions. For the comparison we used the area under the receiver operating characteristics curve (AUC) complemented with net reclassification improvement (NRI). We created two open source signature fingerprints, a bit and a count version, and evaluated their performance compared to a set of established fingerprints with regards to predictions of binding targets using Tanimoto-based similarity searching on publicly available data sets extracted from ChEMBL. The results showed that the count version of the signature fingerprint performed on par with well-established fingerprints such as ECFP. The count version outperformed the bit version slightly; however, the count version is more complex and takes more computing time and memory to run so its usage should probably be evaluated on a case-by-case basis. The NRI based tests complemented the AUC based ones and showed signs of higher power.
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| 9. |
- Bonde, Tiago M., et al.
(författare)
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Time to castration-resistant prostate cancer and prostate cancer death according to PSA response in men with non-metastatic prostate cancer treated with gonadotropin releasing hormone agonists
- 2022
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Ingår i: Scandinavian journal of urology. - : Taylor & Francis Group. - 2168-1805 .- 2168-1813. ; 56:3, s. 169-175
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Tidskriftsartikel (refereegranskat)abstract
- Objectives: To predict castration-resistant prostate cancer (CRPC) and prostate cancer (Pca) death by use of clinical variables at Pca diagnosis and PSA levels after start of gonadotropin-releasing hormone agonists (GnRH) in men with non-metastatic castration sensitive prostate cancer (nmCSPC).Materials and Methods: PSA values for 1603 men with nmCSPC in the National Prostate Cancer Register of Sweden who received GnRH as primary treatment were retrieved from Uppsala-Örebro PSA Cohort and Stockholm PSA and Biopsy Register. All men had measured PSA before (pre-GnRH PSA) and 3–6 months after (post-GnRH PSA) date of start of GnRH. Unadjusted and adjusted Cox models were used to predict CRPC by PSA levels. PSA levels and ISUP grade were used to construct a risk score to stratify men by tertiles according to risk of CRPC and Pca death.Results: 788 (49%) men reached CRPC and 456 (28%) died of Pca during follow-up. Post-GnRH PSA predicted CRPC regardless of pre-GnRH PSA. CRPC risk increased with higher post-GnRH PSA, HR 4.7 (95% CI: 3.4–6.7) for PSA > 16 ng/mL vs 0–0.25 ng/mL and with ISUP grade, HR 3.7 (95%: 2.5–5.4) for ISUP 5 vs ISUP 1. Risk of Pca death in men above top vs bellow bottom tertile of post-GnRH PSA and ISUP grade was HR 4.1 (95% CI: 3.0–5.5).Conclusion: A risk score based on post-GnRH PSA and ISUP grade could be used for early identification of a target group for future clinical trials on additional therapy to GnRH.
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| 10. |
- Bulten, Wouter, et al.
(författare)
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Artificial intelligence assistance significantly improves Gleason grading of prostate biopsies by pathologists
- 2021
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Ingår i: Modern Pathology. - : NATURE PUBLISHING GROUP. - 0893-3952 .- 1530-0285. ; 34, s. 660-671
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Tidskriftsartikel (refereegranskat)abstract
- The Gleason score is the most important prognostic marker for prostate cancer patients, but it suffers from significant observer variability. Artificial intelligence (AI) systems based on deep learning can achieve pathologist-level performance at Gleason grading. However, the performance of such systems can degrade in the presence of artifacts, foreign tissue, or other anomalies. Pathologists integrating their expertise with feedback from an AI system could result in a synergy that outperforms both the individual pathologist and the system. Despite the hype around AI assistance, existing literature on this topic within the pathology domain is limited. We investigated the value of AI assistance for grading prostate biopsies. A panel of 14 observers graded 160 biopsies with and without AI assistance. Using AI, the agreement of the panel with an expert reference standard increased significantly (quadratically weighted Cohens kappa, 0.799 vs. 0.872;p = 0.019). On an external validation set of 87 cases, the panel showed a significant increase in agreement with a panel of international experts in prostate pathology (quadratically weighted Cohens kappa, 0.733 vs. 0.786;p = 0.003). In both experiments, on a group-level, AI-assisted pathologists outperformed the unassisted pathologists and the standalone AI system. Our results show the potential of AI systems for Gleason grading, but more importantly, show the benefits of pathologist-AI synergy.
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