| 1. |
- Larsson, Karin, et al.
(författare)
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Increased levels of the cardiovascular disease risk biomarkers GDF15 and myostatin in patients with chronic lymphocytic leukemia
- 2021
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Ingår i: Growth Factors. - : Informa UK Limited. - 0897-7194 .- 1029-2292. ; 38:3-4, s. 189-196
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Tidskriftsartikel (refereegranskat)abstract
- Individuals suffering from cancer, including hematological malignancies, are at increased risk of cardiovascular disease (CVD). Elevated levels of several biomarkers in blood are associated with an increased risk of CVD. The aim of this study was to investigate whether a subset of such CVD risk biomarkers was elevated in patients with untreated chronic lymphocytic leukemia (CLL). Blood plasma and serum from 139 CLL patients and 71 healthy age-matched controls were analyzed for 11 proposed CVD risk biomarkers. The CLL cohort displayed a more heterogeneous pattern of biomarker expression compared to controls. The majority, eight out of 11, analyzed CVD risk biomarkers differed significantly in concentrations between CLL patients and controls. Increased levels of the biomarkers GDF15 and myostatin have not previously been reported in CLL. Further prospective studies are warranted to investigate whether these biomarkers predict future cardiovascular events in patients with CLL.
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| 2. |
- Zamora, Juan Carlos, et al.
(författare)
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Considerations and consequences of allowing DNA sequence data as types of fungal taxa
- 2018
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Ingår i: IMA Fungus. - : INT MYCOLOGICAL ASSOC. - 2210-6340 .- 2210-6359. ; 9:1, s. 167-185
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Tidskriftsartikel (refereegranskat)abstract
- Nomenclatural type definitions are one of the most important concepts in biological nomenclature. Being physical objects that can be re-studied by other researchers, types permanently link taxonomy (an artificial agreement to classify biological diversity) with nomenclature (an artificial agreement to name biological diversity). Two proposals to amend the International Code of Nomenclature for algae, fungi, and plants (ICN), allowing DNA sequences alone (of any region and extent) to serve as types of taxon names for voucherless fungi (mainly putative taxa from environmental DNA sequences), have been submitted to be voted on at the 11th International Mycological Congress (Puerto Rico, July 2018). We consider various genetic processes affecting the distribution of alleles among taxa and find that alleles may not consistently and uniquely represent the species within which they are contained. Should the proposals be accepted, the meaning of nomenclatural types would change in a fundamental way from physical objects as sources of data to the data themselves. Such changes are conducive to irreproducible science, the potential typification on artefactual data, and massive creation of names with low information content, ultimately causing nomenclatural instability and unnecessary work for future researchers that would stall future explorations of fungal diversity. We conclude that the acceptance of DNA sequences alone as types of names of taxa, under the terms used in the current proposals, is unnecessary and would not solve the problem of naming putative taxa known only from DNA sequences in a scientifically defensible way. As an alternative, we highlight the use of formulas for naming putative taxa (candidate taxa) that do not require any modification of the ICN.
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| 3. |
- Akbar, Muhammad Usman, 1990-, et al.
(författare)
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Brain tumor segmentation using synthetic MR images - A comparison of GANs and diffusion models
- 2024
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Ingår i: Scientific Data. - : Nature Publishing Group. - 2052-4463. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- Large annotated datasets are required for training deep learning models, but in medical imaging data sharing is often complicated due to ethics, anonymization and data protection legislation. Generative AI models, such as generative adversarial networks (GANs) and diffusion models, can today produce very realistic synthetic images, and can potentially facilitate data sharing. However, in order to share synthetic medical images it must first be demonstrated that they can be used for training different networks with acceptable performance. Here, we therefore comprehensively evaluate four GANs (progressive GAN, StyleGAN 1–3) and a diffusion model for the task of brain tumor segmentation (using two segmentation networks, U-Net and a Swin transformer). Our results show that segmentation networks trained on synthetic images reach Dice scores that are 80%–90% of Dice scores when training with real images, but that memorization of the training images can be a problem for diffusion models if the original dataset is too small. Our conclusion is that sharing synthetic medical images is a viable option to sharing real images, but that further work is required. The trained generative models and the generated synthetic images are shared on AIDA data hub.
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| 4. |
- Andersson, Sarah, et al.
(författare)
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Malmbanan Diaries
- 2010
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This booklet is a report for a case study visit during four day field trip, a group of nine PhD students and their supervisors – all part of the National Research School for Architecture and Planning in the Urban Landscape, APULA – set out to explore what may be considered the outback of Western Europe’s conurbations, the transnational region of Kiruna -Narvik.Both “remote” and “resourceful”, “threatened” and “thriving” (equally relative notions), this region seemed to offer possibilities to reflect upon many of the current tendencies influencing contemporary planning practice and research.
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| 5. |
- Arnab, Anurag, et al.
(författare)
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Conditional Random Fields Meet Deep Neural Networks for Semantic Segmentation: Combining Probabilistic Graphical Models with Deep Learning for Structured Prediction
- 2018
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Ingår i: IEEE Signal Processing Magazine. - 1558-0792 .- 1053-5888. ; 35:1, s. 37-52
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Tidskriftsartikel (refereegranskat)abstract
- Semantic segmentation is the task of labeling every pixel in an image with a predefined object category. It has numerous applications in scenarios where the detailed understanding of an image is required, such as in autonomous vehicles and medical diagnosis. This problem has traditionally been solved with probabilistic models known as conditional random fields (CRFs) due to their ability to model the relationships between the pixels being predicted. However, deep neural networks (DNNs) recently have been shown to excel at a wide range of computer vision problems due to their ability to automatically learn rich feature representations from data, as opposed to traditional handcrafted features. The idea of combining CRFs and DNNs have achieved state-of-the-art results in a number of domains. We review the literature on combining the modeling power of CRFs with the representation-learning ability of DNNs, ranging from early work that combines these two techniques as independent stages of a common pipeline to recent approaches that embed inference of probabilistic models directly in the neural network itself. Finally, we summarize future research directions.
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| 6. |
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| 7. |
- Borrelli, Pablo, et al.
(författare)
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Artificial intelligence-based detection of lymph node metastases by PET/CT predicts prostate cancer-specific survival
- 2021
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Ingår i: Clinical Physiology and Functional Imaging. - : Wiley. - 1475-0961 .- 1475-097X. ; 41:1, s. 62-67
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Tidskriftsartikel (refereegranskat)abstract
- Introduction Lymph node metastases are a key prognostic factor in prostate cancer (PCa), but detecting lymph node lesions from PET/CT images is a subjective process resulting in inter-reader variability. Artificial intelligence (AI)-based methods can provide an objective image analysis. We aimed at developing and validating an AI-based tool for detection of lymph node lesions. Methods A group of 399 patients with biopsy-proven PCa who had undergone(18)F-choline PET/CT for staging prior to treatment were used to train (n = 319) and test (n = 80) the AI-based tool. The tool consisted of convolutional neural networks using complete PET/CT scans as inputs. In the test set, the AI-based lymph node detections were compared to those of two independent readers. The association with PCa-specific survival was investigated. Results The AI-based tool detected more lymph node lesions than Reader B (98 vs. 87/117;p = .045) using Reader A as reference. AI-based tool and Reader A showed similar performance (90 vs. 87/111;p = .63) using Reader B as reference. The number of lymph node lesions detected by the AI-based tool, PSA, and curative treatment was significantly associated with PCa-specific survival. Conclusion This study shows the feasibility of using an AI-based tool for automated and objective interpretation of PET/CT images that can provide assessments of lymph node lesions comparable with that of experienced readers and prognostic information in PCa patients.
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| 8. |
- Bäckryd, Emmanuel, et al.
(författare)
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High levels of cerebrospinal fluid chemokines point to the presence of neuroinflammation in peripheral neuropathic pain : a cross-sectional study of 2 cohorts of patients compared with healthy controls
- 2017
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Ingår i: Pain. - : Ovid Technologies (Wolters Kluwer Health). - 0304-3959 .- 1872-6623. ; 158:12, s. 2487-2495
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Tidskriftsartikel (refereegranskat)abstract
- Animal models suggest that chemokines are important mediators in the pathophysiology of neuropathic pain. Indeed, these substances have been called “gliotransmitters,” a term that illustrates the close interplay between glial cells and neurons in the context of neuroinflammation and pain. However, evidence in humans is scarce. The aim of the study was to determine a comprehensive cerebrospinal fluid (CSF) inflammatory profile of patients with neuropathic pain. Our hypothesis was that we would thereby find indications of a postulated on-going process of central neuroinflammation. Samples of CSF were collected from 2 cohorts of patients with neuropathic pain (n = 11 and n = 16, respectively) and healthy control subjects (n = 11). The samples were analyzed with a multiplex proximity extension assay in which 92 inflammation-related proteins were measured simultaneously (Proseek Multiplex Inflammation I; Olink Bioscience, Uppsala, Sweden). Univariate testing with control of false discovery rate, as well as orthogonal partial least squares discriminant analysis, were used for statistical analyses. Levels of chemokines CXCL6, CXCL10, CCL8, CCL11, CCL23 in CSF, as well as protein LAPTGF-beta-1, were significantly higher in both neuropathic pain cohorts compared with healthy controls, pointing to neuroinflammation in patients. These 6 proteins were also major results in a recent similar study in patients with fibromyalgia. The findings need to be confirmed in larger cohorts, and the question of causality remains to be settled. Because it has been suggested that prevalent comorbidities to chronic pain (eg, depression, anxiety, poor sleep, and tiredness) also are associated with neuroinflammation, it will be important to determine whether neuroinflammation is a common mediator.
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| 9. |
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| 10. |
- De Kaminski, Marcin, et al.
(författare)
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Studying Norms and Social Change in a Digital Age: Identifying and Understanding a Multidimensional Gap Problem
- 2013
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Ingår i: Social and Legal Norms: Towards a Socio-legal Understanding of Normativity. - 9781409453437 ; , s. 309-330
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Bokkapitel (refereegranskat)abstract
- The fact that the debate concerning copyright in a digital society has been both intense and filled with polemic conflicts ever since the late 1990s makes it clear that it is a most complicated issue to solve, or even grasp. Basically, both the legal and societal discussion and development are explicitly dependent on a greater understanding of the on-going processes surrounding copyright. This presents a well-suited point of departure for research such as the one conducted within the Cybernorms research group – both in terms of providing valuable insights into the field of sociology of law when it comes to understanding how to relate to the framework provided by digitalization in general and the Internet in particular, and in terms of providing more accurate knowledge and toolsets to legislators in related fields.
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