| 1. |
- Chen, Zhishan, et al.
(författare)
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Fine-mapping analysis including over 254 000 East Asian and European descendants identifies 136 putative colorectal cancer susceptibility genes
- 2024
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Ingår i: Nature Communications. - : Springer Nature. - 2041-1723. ; 15:1
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Tidskriftsartikel (refereegranskat)abstract
- Genome-wide association studies (GWAS) have identified more than 200 common genetic variants independently associated with colorectal cancer (CRC) risk, but the causal variants and target genes are mostly unknown. We sought to fine-map all known CRC risk loci using GWAS data from 100,204 cases and 154,587 controls of East Asian and European ancestry. Our stepwise conditional analyses revealed 238 independent association signals of CRC risk, each with a set of credible causal variants (CCVs), of which 28 signals had a single CCV. Our cis-eQTL/mQTL and colocalization analyses using colorectal tissue-specific transcriptome and methylome data separately from 1299 and 321 individuals, along with functional genomic investigation, uncovered 136 putative CRC susceptibility genes, including 56 genes not previously reported. Analyses of single-cell RNA-seq data from colorectal tissues revealed 17 putative CRC susceptibility genes with distinct expression patterns in specific cell types. Analyses of whole exome sequencing data provided additional support for several target genes identified in this study as CRC susceptibility genes. Enrichment analyses of the 136 genes uncover pathways not previously linked to CRC risk. Our study substantially expanded association signals for CRC and provided additional insight into the biological mechanisms underlying CRC development.
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| 2. |
- Edlund, Christoffer, et al.
(författare)
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LIVECell : a large-scale dataset for label-free live cell segmentation
- 2021
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Ingår i: Nature Methods. - : Nature Publishing Group. - 1548-7091 .- 1548-7105. ; 18:9, s. 1038-1045
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Light microscopy combined with well-established protocols of two-dimensional cell culture facilitates high-throughput quantitative imaging to study biological phenomena. Accurate segmentation of individual cells in images enables exploration of complex biological questions, but can require sophisticated imaging processing pipelines in cases of low contrast and high object density. Deep learning-based methods are considered state-of-the-art for image segmentation but typically require vast amounts of annotated data, for which there is no suitable resource available in the field of label-free cellular imaging. Here, we present LIVECell, a large, high-quality, manually annotated and expert-validated dataset of phase-contrast images, consisting of over 1.6 million cells from a diverse set of cell morphologies and culture densities. To further demonstrate its use, we train convolutional neural network-based models using LIVECell and evaluate model segmentation accuracy with a proposed a suite of benchmarks.
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| 3. |
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| 4. |
- Edlund, Sara, 1983-, et al.
(författare)
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Facing negative emotions : Evaluation of a brief training in validating communication for contact nurses in cancer care
- 2023
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Ingår i: European Journal of Oncology Nursing. - : Elsevier. - 1462-3889 .- 1532-2122. ; 66
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Tidskriftsartikel (refereegranskat)abstract
- Background: Contact nurses in cancer care (CNCC) often face challenges when communicating with patients and their families. The overall aim was to evaluate a brief digital validation training for CNCC, to test whether it was associated with increased validation and decreased invalidation. Associations between communication skills in validation and markers of work-related stress were also investigated. Methods: This intervention study investigated associations between the training and validation skills using a within-group design with repeated measures (at pre, post, and eight-week follow-up). Additionally, associations between the training and occupational self-efficacy, self-validation, and exhaustion symptoms were explored. Results: Seventeen CNCCs (all female with relatively long work experience) completed a five-week digital training program. Results indicated a statistically significant increase in validation and a statistically significant decrease in invalidation, showing that the nurses improved their communication skills following the training. No changes were found in markers of work-related stress. Conclusion: The results indicate that digital validation training for CNCCs is potentially beneficial by means of improving communication skills. This study further demonstrates that a brief digital training in validating communication to CNCC is associated with improved person-centered communication regarding strong negative emotions.
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| 5. |
- Fernandez-Rozadilla, Ceres, et al.
(författare)
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Deciphering colorectal cancer genetics through multi-omic analysis of 100,204 cases and 154,587 controls of European and east Asian ancestries
- 2023
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Ingår i: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 55, s. 89-99
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Tidskriftsartikel (refereegranskat)abstract
- Colorectal cancer (CRC) is a leading cause of mortality worldwide. We conducted a genome-wide association study meta-analysis of 100,204 CRC cases and 154,587 controls of European and east Asian ancestry, identifying 205 independent risk associations, of which 50 were unreported. We performed integrative genomic, transcriptomic and methylomic analyses across large bowel mucosa and other tissues. Transcriptome- and methylome-wide association studies revealed an additional 53 risk associations. We identified 155 high-confidence effector genes functionally linked to CRC risk, many of which had no previously established role in CRC. These have multiple different functions and specifically indicate that variation in normal colorectal homeostasis, proliferation, cell adhesion, migration, immunity and microbial interactions determines CRC risk. Crosstissue analyses indicated that over a third of effector genes most probably act outside the colonic mucosa. Our findings provide insights into colorectal oncogenesis and highlight potential targets across tissues for new CRC treatment and chemoprevention strategies.
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| 6. |
- Hassan, Jasmin, et al.
(författare)
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Reference standards for follicular density in ovarian cortex from birth to sexual maturity
- 2023
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Ingår i: Reproductive BioMedicine Online. - : Elsevier. - 1472-6483 .- 1472-6491. ; 47:4
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Tidskriftsartikel (refereegranskat)abstract
- Research question: Are age-normalized reference values for human ovarian cortical follicular density adequate for tissue quality control in fertility preservation?Design: Published quantitative data on the number of follicles in samples without known ovarian pathology were converted into cortical densities to create reference values. Next, a sample cohort of 126 girls (age 1-24 years, mean +/- SD 11 +/- 6) with cancer, severe haematological disease or Turner syndrome were used to calculate Z-scores for cortical follicular density based on the reference values.Results: No difference was observed between Z-scores in samples from untreated patients (0.3 +/- 3.5, n = 30) and patients treated with (0.5 +/- 2.9, n = 48) and without (0.1 +/- 1.3, n = 6) alkylating chemotherapy. Z-scores were not correlated with increasing cumulative exposure to cytostatics. Nevertheless, Z-scores in young treated patients (0-2 years -2.1 +/- 3.1, n = 10, P = 0.04) were significantly lower than Z-scores in older treated patients (11-19 years, 2 +/- 1.9, n = 15). Samples from patients with Turner syndrome differed significantly from samples from untreated patients (-5.2 +/- 5.1, n = 24, P = 0.003), and a Z-score of -1.7 was identified as a cut-off showing good diagnostic value for identification of patients with Turner syndrome with reduced ovarian reserve. When this cut-off was applied to other patients, analysis showed that those with indications for reduced ovarian reserve (n = 15) were significantly younger (5.9 +/- 4.2 versus 10.7 +/- 5.9 years, P = 0.004) and, when untreated, more often had non-malignant haematologic diseases compared with those with normal ovarian reserve (n = 24, 100% versus 19%, P = 0.009).Conclusion: Z-scores allow the estimation of genetic- and treatment-related effects on follicular density in cortical tissue from young patients stored for fertility preservation. Understanding the quality of cryopreserved tissue facilitates its use during patient counselling. More research is needed regarding the cytostatic effects found in this study.
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| 7. |
- Holopainen, Riikka, et al.
(författare)
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Physiotherapists’ validating and invalidating communication before and after participating in brief cognitive functional therapy training : Test of concept study
- 2023
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Ingår i: European Journal of Physiotherapy. - : Taylor & Francis. - 2167-9169 .- 2167-9177. ; 25:2, s. 73-79
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Tidskriftsartikel (refereegranskat)abstract
- Objective: The aim of this study was to investigate physiotherapists' validating and invalidating communication, before and after brief Cognitive Functional Therapy (CFT) training that included a session on validation skills. Associations between validation/invalidation and the characteristics of the interviews and physiotherapists were also explored.Methods: Eighteen physiotherapists treating patients with low back pain participated in the study. The study had a within-group design in which validation and invalidation for physiotherapists were rated before and after training using a reliable observational scale. We also collected data on interview length and physiotherapists' and patients' speech percentages.Results: The physiotherapists' validating responses increased and invalidating responses decreased from pre- to post-training. The within-group effect size was large for validating responses and medium for invalidating responses. The interview length increased from pre- to post-training (large effect size). However, the reason for this was related to factors other than validation and invalidation. The results indicate that increased validation is associated with an increase in physiotherapists' speech percentage.Conclusions: The results of this study show changes invalidating and invalidating communication among physiotherapists from pre- to post-CFT training. The study also found associations between specific interview characteristics and validating communication. Future studies with larger samples and control groups are needed.
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| 8. |
- Khalid, Nabeel, et al.
(författare)
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DeepCeNS : An end-to-end Pipeline for Cell and Nucleus Segmentation in Microscopic Images
- 2021
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Ingår i: Proceedings of the International Joint Conference on Neural Networks. - : IEEE. - 9780738133669 - 9781665439008 - 9781665445979
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Konferensbidrag (refereegranskat)abstract
- With the evolution of deep learning in the past decade, more biomedical related problems that seemed strenuous, are now feasible. The introduction of U-net and Mask R-CNN architectures has paved a way for many object detection and segmentation tasks in numerous applications ranging from security to biomedical applications. In the cell biology domain, light microscopy imaging provides a cheap and accessible source of raw data to study biological phenomena. By leveraging such data and deep learning techniques, human diseases can be easily diagnosed and the process of treatment development can be greatly expedited. In microscopic imaging, accurate segmentation of individual cells is a crucial step to allow better insight into cellular heterogeneity. To address the aforementioned challenges, DeepCeNS is proposed in this paper to detect and segment cells and nucleus in microscopic images. We have used EVICAN2 dataset which contains microscopic images from a variety of microscopes having numerous cell cultures, to evaluate the proposed pipeline. DeepCeNS outperforms EVICAN-MRCNN by a significant margin on the EVICAN2 dataset.
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| 9. |
- Khalid, Nabeel, et al.
(författare)
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DeepCIS : An end-to-end Pipeline for Cell-type aware Instance Segmentation in Microscopic Images
- 2021
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Ingår i: 2021 IEEE EMBS International Conference on Biomedical and Health Informatics, Proceedings. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781665403580
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Konferensbidrag (refereegranskat)abstract
- Accurate cell segmentation in microscopic images is a useful tool to analyze individual cell behavior, which helps to diagnose human diseases and development of new treatments. Cell segmentation of individual cells in a microscopic image with many cells in view allows quantification of single cellular features, such as shape or movement patterns, providing rich insight into cellular heterogeneity. Most of the cell segmentation algorithms up till now focus on segmenting cells in the images without classifying the culture of the cell in the images. Discrimination among cell types in microscopic images can lead to a new era of high-throughput cell microscopy. Multiple cell types in co-culture can be easily identified and studying the changes in cell morphology can lead to many applications such as drug treatment. To address this gap, DeepCIS is proposed to detect, segment, and classify the culture of the cells and nucleus in the microscopic images. We have used the EVICAN60 dataset which contains microscopic images from a variety of microscopes having numerous cell cultures, to evaluate the proposed pipeline. To further demonstrate the utility of the DeepCIS, we have designed various experimental settings to uncover its learning potential. We have achieved a mean average precision score of 24.37% for the segmentation task averaged over 30 classes for cell and nucleus.
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| 10. |
- Khalid, Nabeel, et al.
(författare)
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DeepMuCS: A framework for co-culture microscopic image analysis : from generation to segmentation
- 2022
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Ingår i: 2022 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI). - : IEEE. - 9781665487917 ; , s. 1-4
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Konferensbidrag (refereegranskat)abstract
- Discrimination between cell types in the co-culture environment with multiple cell lines can assist in examining the interaction between different cell populations. Identifying different cell cultures in addition to cell segmentation in co-culture is essential for understanding the cellular mechanisms associated with disease states. In drug development, biologists are more interested in co-culture models because they replicate the tumor environment in vivo better than the monoculture models. Additionally, they have a measurable effect on cancer cell response to treatment. Co-culture models are critical for designing a drug with maximum efficacy on cancer while minimizing harm to the rest of the body. In the past, there existed minimal progress related to cell-type aware segmentation in the monoculture and no development whatsoever for the co-culture. The introduction of the LIVECell dataset has allowed us to perform experiments for cell-type-aware segmentation. However, it is composed of microscopic images in a monoculture environment. This paper presents a framework for co-culture microscopic image data generation, where each image can contain multiple cell cultures. The framework also presents a pipeline for culture-dependent cell segmentation in co-culture microscopic images. The extensive evaluation revealed that it is possible to achieve cell-type aware segmentation in co-culture microscopic images with good precision.
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