| 1. |
- Kattge, Jens, et al.
(författare)
-
TRY plant trait database - enhanced coverage and open access
- 2020
-
Ingår i: Global Change Biology. - : Wiley-Blackwell. - 1354-1013 .- 1365-2486. ; 26:1, s. 119-188
-
Tidskriftsartikel (refereegranskat)abstract
- Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.
|
|
| 2. |
- Zamora, Juan Carlos, et al.
(författare)
-
Considerations and consequences of allowing DNA sequence data as types of fungal taxa
- 2018
-
Ingår i: IMA Fungus. - : INT MYCOLOGICAL ASSOC. - 2210-6340 .- 2210-6359. ; 9:1, s. 167-185
-
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.
|
|
| 3. |
- Hop, Paul J., et al.
(författare)
-
Genome-wide study of DNA methylation shows alterations in metabolic, inflammatory, and cholesterol pathways in ALS
- 2022
-
Ingår i: Science Translational Medicine. - : American Association for the Advancement of Science. - 1946-6234 .- 1946-6242. ; 14:633
-
Tidskriftsartikel (refereegranskat)abstract
- Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with an estimated heritability between 40 and 50%. DNA methylation patterns can serve as proxies of (past) exposures and disease progression, as well as providing a potential mechanism that mediates genetic or environmental risk. Here, we present a blood-based epigenome-wide association study meta-analysis in 9706 samples passing stringent quality control (6763 patients, 2943 controls). We identified a total of 45 differentially methylated positions (DMPs) annotated to 42 genes, which are enriched for pathways and traits related to metabolism, cholesterol biosynthesis, and immunity. We then tested 39 DNA methylation-based proxies of putative ALS risk factors and found that high-density lipoprotein cholesterol, body mass index, white blood cell proportions, and alcohol intake were independently associated with ALS. Integration of these results with our latest genome-wide association study showed that cholesterol biosynthesis was potentially causally related to ALS. Last, DNA methylation at several DMPs and blood cell proportion estimates derived from DNA methylation data were associated with survival rate in patients, suggesting that they might represent indicators of underlying disease processes potentially amenable to therapeutic interventions.
|
|
| 4. |
- Dalili, Danoob, et al.
(författare)
-
Interventional Techniques for Bone and Musculoskeletal Soft Tissue Tumors : Current Practices and Future Directions - Part I. Ablation
- 2020
-
Ingår i: Seminars in Musculoskeletal Radiology. - : Georg Thieme Verlag KG. - 1089-7860 .- 1098-898X. ; 24:06, s. 692-709
-
Forskningsöversikt (refereegranskat)abstract
- Musculoskeletal (MSK) image-guided oncologic intervention is an established field within radiology. Numerous studies have described its clinical benefits, safety, cost effectiveness, patient satisfaction, and improved quality of life, thereby establishing image-guided oncologic intervention as a preferred pathway in treating patients presenting with specific benign MSK tumors. But there is a paradigm shift on the horizon because these techniques may also support established pillars (surgery, systemic treatment, radiotherapy) in the treatment of malignant MSK tumors. Unlike benign tumors, where they are used as primary therapy lines with curative intent, such interventions can be selected for malignant tumors as adjuvant treatment in painful or unstable bone or soft tissue lesions or as more palliative therapy strategies. Using examples from our clinical practices, we elaborate on the benefits of applying a multidisciplinary approach (traditionally involving MSK radiologists, oncologists, orthopaedic surgeons, microbiologists, pathologists, physiotherapists, and pain management experts), ideally within a sarcoma treatment center to deliver a patient-specific therapy plan and illustrate methods to assess the benefits of this model of care. In this article, we review the current repertoire of ablation techniques, demonstrate why such procedures offer value-based alternatives to conventional treatments of specific tumors, and reflect on future directions. Additionally, we review the advantages and limitations of each technique and offer guidance to improve outcomes.
|
|
| 5. |
- Dalili, Danoob, et al.
(författare)
-
Interventional Techniques for Bone and Musculoskeletal Soft Tissue Tumors : Current Practices and Future Directions - Part II. Stabilization
- 2020
-
Ingår i: Seminars in Musculoskeletal Radiology. - : Georg Thieme Verlag KG. - 1089-7860 .- 1098-898X. ; 24:06, s. 710-725
-
Tidskriftsartikel (refereegranskat)abstract
- Percutaneous image-guided oncologic interventions have rapidly evolved over the last two decades as an independent strategy or used within a first-, second-, or even third-line strategy in the treatment of musculoskeletal (MSK) tumors. Abundant mostly nonrandomized publications have described the safety, efficacy, and reproducibility of implementing percutaneous therapies both with curative and palliative intent. In this article, we continue to share our experience in bone and MSK soft tissue interventions focusing on stabilization and combined ablation and stabilization. We propose a pathway and explore future directions of image-guided interventional oncology related to skeletal disease. We reflect on the advantages and limitations of each technique and offer guidance and pearls to improve outcomes. Representing patterns from our practices, we demonstrate the role of collaborative working within a multidisciplinary team, ideally within a dedicated tumor treatment center, to deliver patient-specific therapy plans that are value based and favored by patients when given the choice.
|
|
| 6. |
- Jimenez-del-Toro, Oscar, et al.
(författare)
-
Cloud-Based Evaluation of Anatomical Structure Segmentation and Landmark Detection Algorithms : VISCERAL Anatomy Benchmarks
- 2016
-
Ingår i: IEEE Transactions on Medical Imaging. - : Institute of Electrical and Electronics Engineers (IEEE). - 0278-0062 .- 1558-254X. ; 35:11, s. 2459-2475
-
Tidskriftsartikel (refereegranskat)abstract
- Variations in the shape and appearance of anatomical structures in medical images are often relevant radiological signs of disease. Automatic tools can help automate parts of this manual process. A cloud-based evaluation framework is presented in this paper including results of benchmarking current state-of-the-art medical imaging algorithms for anatomical structure segmentation and landmark detection: the VISCERAL Anatomy benchmarks. The algorithms are implemented in virtual machines in the cloud where participants can only access the training data and can be run privately by the benchmark administrators to objectively compare their performance in an unseen common test set. Overall, 120 computed tomography and magnetic resonance patient volumes were manually annotated to create a standard Gold Corpus containing a total of 1295 structures and 1760 landmarks. Ten participants contributed with automatic algorithms for the organ segmentation task, and three for the landmark localization task. Different algorithms obtained the best scores in the four available imaging modalities and for subsets of anatomical structures. The annotation framework, resulting data set, evaluation setup, results and performance analysis from the three VISCERAL Anatomy benchmarks are presented in this article. Both the VISCERAL data set and Silver Corpus generated with the fusion of the participant algorithms on a larger set of non-manually-annotated medical images are available to the research community.
|
|
| 7. |
- Lalam, Radhesh, et al.
(författare)
-
ESSR Consensus Document for Detection, Characterization, and Referral Pathway for Tumors and Tumorlike Lesions of Bone
- 2017
-
Ingår i: Seminars in Musculoskeletal Radiology. - : Georg Thieme Verlag KG. - 1089-7860 .- 1098-898X. ; 21:5, s. 630-647
-
Forskningsöversikt (refereegranskat)abstract
- Benign bone tumors are rare but are more common than primary malignant bone tumors. The early accurate diagnosis and reliable differentiation of these rare benign tumors and tumor mimickers from the even rarer malignant tumors with subsequent appropriate treatment or watchful waiting is crucial for the clinical outcome. Bone tumors are often a source of diagnostic and therapeutic uncertainty. Thus this European Society of Musculoskeletal Radiology consensus document is intended to help radiologists in their decision making and support discussion among clinicians who deal with patients with suspected or proven bone tumors. Evaluating these tumors starts with a patient history and physical examination. Radiography is the principal imaging modality and often can reliably diagnose a benign bone tumor by providing information about localization, matrix, aggressiveness, size, and (potential) multiplicity. In a significant number of cases, additional imaging is not necessary. Potentially malignant entities recognized by radiography should be referred for magnetic resonance imaging, which also serves as a preoperative local staging modality, with specific technical requirements. Indeterminate tumors, or tumors in which therapy depends on histology results, should be biopsied. For biopsy, we strongly recommend referral to a specialist regional sarcoma treatment center (RSTC), where a multidisciplinary tumor team, including a specialist pathologist, radiologist, and sarcoma surgeon, are involved. Additional staging modalities are entity specific and should be performed according to the recommendations of the RSTC.
|
|
| 8. |
- Mehta, Raghav, et al.
(författare)
-
QU-BraTS : MICCAI BraTS 2020 Challenge on QuantifyingUncertainty in Brain Tumor Segmentation - Analysis of Ranking Scores and Benchmarking Results
- 2022
-
Ingår i: Journal of Machine Learning for Biomedical Imaging. - 2766-905X. ; , s. 1-54
-
Tidskriftsartikel (refereegranskat)abstract
- Deep learning (DL) models have provided the state-of-the-art performance in a wide variety of medical imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) challenges. However, the task of focal pathology multi-compartment segmentation (e.g., tumor and lesion sub-regions) is particularly challenging, and potential errors hinder the translation of DL models into clinical workflows. Quantifying the reliability of DL model predictions in the form of uncertainties, could enable clinical review of the most uncertain regions, thereby building trust and paving the way towards clinical translation. Recently, a number of uncertainty estimation methods have been introduced for DL medical image segmentation tasks. Developing scores to evaluate and compare the performance of uncertainty measures will assist the end-user in making more informed decisions. In this study, we explore and evaluate a score developed during the BraTS 2019-2020 task on uncertainty quantification (QU-BraTS), and designed to assess and rank uncertainty estimates for brain tumor multi-compartment segmentation. This score (1) rewards uncertainty estimates that produce high confidence in correct assertions, and those that assign low confidence levels at incorrect assertions, and (2) penalizes uncertainty measures that lead to a higher percentages of under-confident correct assertions. We further benchmark the segmentation uncertainties generated by 14 independent participating teams of QU-BraTS 2020, all of which also participated in the main BraTS segmentation task. Overall, our findings confirm the importance and complementary value that uncertainty estimates provide to segmentation algorithms, and hence highlight the need for uncertainty quantification in medical image analyses. Our evaluation code is made publicly available at https://github.com/RagMeh11/QU-BraTS
|
|
