| 1. |
- Andersson, Tobias, et al.
(författare)
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3D-Simulation of Heat Flow in Indexable Drilling
- 2023
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Ingår i: Key Engineering Materials. - : Scientific.Net. - 1013-9826 .- 1662-9795. ; 955, s. 53-62
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Tidskriftsartikel (refereegranskat)abstract
- In machining, the heat flow into the workpiece during the cutting process is often a major concern. The temperature rise can lead to substantial residual stresses or elastic in-process deformations which may result in the dimensional tolerance requirements being violated. In the present study a modelling strategy is developed for determination of the heat load during indexable drilling. The heat load on the workpiece is determined from 3D thermomechanical Coupled Eulerian Lagrangian analyses of orthogonal turning for various chip thicknesses and cutting speeds. The determined heat load is then transferred to a 3D transient heat transfer analysis of the indexable drilling process for the determination of the temperature field. Thereby, this modelling technique avoids the complex cutting process that is performed in real cutting simulations and thereby reducing the computational complexity of the problem considerably. The simulated temperatures are compared with experimentally measured temperatures and some conclusions are drawn regarding the modelling approach.
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| 2. |
- Gustavsson, Carolina, et al.
(författare)
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Cerebrospinal fluid levels of insulin, leptin, and agouti-related protein in relation to BMI in pregnant women
- 2016
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Ingår i: Obesity. - : Wiley. - 1930-7381. ; 24:6, s. 1299-1304
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Tidskriftsartikel (refereegranskat)abstract
- ObjectiveDuring pregnancy, metabolic interactions must be adapted, though neuroendocrine mechanisms for increased food intake are poorly understood. The objective of this study was to characterize differences in insulin, leptin, and agouti-related protein (AgRP) levels in serum and cerebrospinal fluid (CSF) in pregnant women with normal weight (NW) and pregnant women with overweight (OW) or obesity (OB). Placenta as a source for increased peripheral AgRP levels during pregnancy was also investigated. MethodsWomen were recruited at admission for elective cesarean section. Insulin, AgRP, and leptin were measured in serum and CSF from 30 NW, 25 OW, and 21 OB at term. Serum during pregnancy and placenta at term were collected for further AgRP analysis. ResultsImmunohistology showed placental production of AgRP and serum AgRP levels increased throughout pregnancy. CSF AgRP, leptin, and insulin levels were higher in OW and OB than NW. Serum leptin and insulin levels were higher and AgRP lower in OB than NW. ConclusionsHigh serum AgRP levels might protect from the suppressive effects of leptin during pregnancy. Pregnant women with OB and OW might further be protected from the suppressive effect of leptin by high CSF AgRP levels. Evidence was found, for the first time, of human placental AgRP production mirrored by levels in the circulation.
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| 3. |
- Muszynska, Carolina, et al.
(författare)
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A risk score model to predict incidental gallbladder cancer in patients scheduled for cholecystectomy
- 2020
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Ingår i: American Journal of Surgery. - : Elsevier BV. - 0002-9610 .- 1879-1883. ; 220:3, s. 741-744
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Tidskriftsartikel (refereegranskat)abstract
- Background: Gallbladder cancer (GBC) has a poor prognosis. The aim was to develop and validate a preoperative risk score for incidental gallbladder cancer (IGBC) in patients scheduled for cholecystectomy. Methods: Data registered in the nationwide Swedish Registry for Gallstone Surgery (GallRiks) was analyzed, including the derivation cohort (n = 28915, 2007–2014) and the validation cohort (n = 7851, 2014–2016). An additive risk score model based on odds ratio was created. Results: The scoring model to predict IGBC includes age, female gender, previous cholecystitis, and either jaundice or acute cholecystitis. The calibration by HL test and discrimination by AUROC was 8.27 (P = 0.291) and 0.76 in the derivation cohort (214 IGBC) and 14.28 (P = 0.027) and 0.79 in the validation cohort (35 IGBC). The scoring system was applied to three risk-groups, based on the risk of having IGBC, eg. the high-risk group (>8 points) included 7878 patients, with 154 observed and 148 expected IGBC cases. Conclusion: We present the first risk score model to predict IGBC. The model estimates the expected risk for the individual patient and may help to optimize treatment strategies.
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| 4. |
- Muszynska, Carolina, et al.
(författare)
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Incidental metastases and lymphoma of the gallbladder–an analysis of ten rare cases identified from a large national database
- 2019
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Ingår i: Scandinavian Journal of Gastroenterology. - : Informa UK Limited. - 0036-5521 .- 1502-7708. ; 54, s. 350-358
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Tidskriftsartikel (refereegranskat)abstract
- Background: The aim was to identify and characterize rare malignancies of the gallbladder, incidentally found at cholecystectomy, and describe the diagnostic work-up, treatment and outcome. Methods: Data from cholecystectomies during 2007–2014 registered in the Swedish Register for Gallstone Surgery (GallRiks) were analyzed for incidental cancer. For completion of the pathology report, data were linked with the Swedish Registry for Cancer in the liver and biliary tract (SweLiv) and/or the Swedish Cancer Registry. Results: From 36,355 patients that underwent cholecystectomy on a benign indication 215 cases of incidental gallbladder cancer (IGBC) were identified. In total seven patients with metastases to the gallbladder from different primary tumors (breast cancer, malignant melanoma, gastric cancer, renal cell carcinoma, upper gastrointestinal cancer, colon cancer and pancreatic cancer) and three patients with lymphoma involvement of the gallbladder were found. Most patients were female with no difference between the groups (8/10 versus 171/215). The median age for the metastasis and lymphoma (MOL) group was equal to the IGBC group, 70 (64–72) years versus 70 (63–78) years. All patients in the MOL group underwent preoperative imaging with ultrasound or computed tomography, on which no metastases were identified. In only two patients a tumor was seen by the surgeon during the perioperative examination of the gallbladder. The median survival was 5.8 months for MOL patients and 23 months for IGBC patients. Conclusion: Metastases and lymphoma of the gallbladder are rare. Traditional imaging methods prior to cholecystectomy may miss gallbladder malignancies. A liberal approach of histopathological analysis of the gallbladder should be applied.
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| 5. |
- Muszynska, Carolina, et al.
(författare)
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Predictors of incidental gallbladder cancer in patients undergoing cholecystectomy for benign gallbladder disease : Results from a population-based gallstone surgery registry
- 2017
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Ingår i: Surgery. - : Elsevier BV. - 0039-6060 .- 1532-7361. ; 162:2, s. 256-263
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Tidskriftsartikel (refereegranskat)abstract
- Background: Gallbladder cancer is a rare neoplasm with a poor prognosis. Early diagnosis and correct treatment strategy is important. The aim of this study was to identify predictors for incidental gallbladder cancer. Methods: Data from cholecystectomies registered in the nationwide Swedish Register for Gallstone Surgery between 2007 and 2014 were analyzed for incidental gallbladder cancer. Exclusion criteria were patients with a gallbladder not sent for histopathology, preoperative suspicion of polyps/gallbladder cancer, and indication for operation for other reasons than gallstone disease. Predictive factors for incidental gallbladder cancer were identified using multivariable logistic regression. Results: A total of 86,154 procedures were registered in the Swedish Register for Gallstone Surgery. Of these, 36,355 patients were included in the analysis, and 215 of the included patients had incidental gallbladder cancer (0.59%). Mean age was 70 ± 11 years for index cases and 54 ± 16 years for the control group, and 80% of cases and 60% of controls were female. Predictors for incidental gallbladder cancer were older age (odds ratio = 1.08; P < .001), female sex (odds ratio = 3.58; P < .001), previous cholecystitis (odds ratio = 1.37; P = .045), and the combination of acute cholecystitis without jaundice (odds ratio = 1.39; P = .041) and jaundice without acute cholecystitis (odds ratio = 2.02; P = .009). A preoperative risk model including these factors gave an area under receiver operating characteristic curve of 0.82. By adding macroscopic evaluation of the gallbladder by the surgeon, the area under receiver operating characteristic curve increased to 0.87. Intraoperatively suspected gallbladder cancer was confirmed as cancer in 31% of the cases. Conclusion: Incidental gallbladder cancer is more likely to be diagnosed in older patients, women, and after previous cholecystitis. Jaundice and acute cholecystitis were also shown to be important risk factors. Intraoperative inspection of the gallbladder improved the risk model.
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| 6. |
- Aguilar, Mónica García, et al.
(författare)
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Governance challenges and opportunities for implementing resource recovery from organic waste streams in urban areas of Latin America: insights from Chía, Colombia
- 2022
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Ingår i: Sustainable Production and Consumption. - : Elsevier. - 2352-5509. ; 30, s. 53-63
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Tidskriftsartikel (refereegranskat)abstract
- Across the globe, there is increasing interest in implementing circular approaches to urban sanitation and waste management to mitigate environmental challenges and promote sustainable business opportunities. In Latin America where 80% of the population live in urban areas, there is limited investigation into the enabling factors and governance barriers that are critical to implementing circular economy strategies in urban areas. This paper aims at assessing the governance capacity to implement resource recovery from organic waste streams in the municipality of Chía, Colombia, through applying the Governance Capacity Framework in a participatory process with local stakeholders. The findings highlight the importance of local initiatives for resource recovery that allow experimentation, raise awareness and foster collaboration, as well as mechanisms available for public participation in decision-making processes as enabling factors. Meanwhile, the inadequate monitoring and assessment of environmental strategies and policies, inadequate sharing of information among stakeholders and the relative low awareness of potential benefits of recovering resources from organic waste streams, especially among public sector actors, emerge as key barriers. Beyond Chía, the results provide insights on crucial factors for ensuring sufficient governance capacity in other urban areas in low- and middle-income countries which are considering circular approaches to urban sanitation and waste management. The findings also provide an empirical basis to advance the understanding of the governance conditions necessary for implementing resource recovery from organic waste streams, upon which further applications of the governance capacity framework along with participatory aspects in other similar urban contexts could build.
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| 7. |
- Andersson, Axel, et al.
(författare)
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Cell Segmentation of in situ Transcriptomics Data using Signed Graph Partitioning
- 2023
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Ingår i: Graph-Based Representations in Pattern Recognition. - Cham : Springer. - 9783031427947 - 9783031427954 ; , s. 139-148
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Konferensbidrag (refereegranskat)abstract
- The locations of different mRNA molecules can be revealed by multiplexed in situ RNA detection. By assigning detected mRNA molecules to individual cells, it is possible to identify many different cell types in parallel. This in turn enables investigation of the spatial cellular architecture in tissue, which is crucial for furthering our understanding of biological processes and diseases. However, cell typing typically depends on the segmentation of cell nuclei, which is often done based on images of a DNA stain, such as DAPI. Limiting cell definition to a nuclear stain makes it fundamentally difficult to determine accurate cell borders, and thereby also difficult to assign mRNA molecules to the correct cell. As such, we have developed a computational tool that segments cells solely based on the local composition of mRNA molecules. First, a small neural network is trained to compute attractive and repulsive edges between pairs of mRNA molecules. The signed graph is then partitioned by a mutex watershed into components corresponding to different cells. We evaluated our method on two publicly available datasets and compared it against the current state-of-the-art and older baselines. We conclude that combining neural networks with combinatorial optimization is a promising approach for cell segmentation of in situ transcriptomics data. The tool is open-source and publicly available for use at https://github.com/wahlby-lab/IS3G.
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| 8. |
- Andersson, Axel
(författare)
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Computational Methods for Image-Based Spatial Transcriptomics
- 2024
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Why does cancer develop, spread, grow, and lead to mortality? To answer these questions, one must study the fundamental building blocks of all living organisms — cells. Like a well-calibrated manufacturing unit, cells follow precise instructions by gene expression to initiate the synthesis of proteins, the workforces that drive all living biochemical processes.Recently, researchers have developed techniques for imaging the expression of hundreds of unique genes within tissue samples. This information is extremely valuable for understanding the cellular activities behind cancer-related diseases. These methods, collectively known as image-based spatial transcriptomics (IST) techniques, use fluorescence microscopy to combinatorically label mRNA species (corresponding to expressed genes) in tissue samples. Here, automatic image analysis is required to locate fluorescence signals and decode the combinatorial code. This process results in large quantities of points, marking the location of expressed genes. These new data formats pose several challenges regarding visualization and automated analysis.This thesis presents several computational methods and applications related to data generated from IST methods. Key contributions include: (i) A decoding method that jointly optimizes the detection and decoding of signals, particularly beneficial in scenarios with low signal-to-noise ratios or densely packed signals; (ii) a computational method for automatically delineating regions with similar gene compositions — efficient, interactive, and scalable for exploring patterns across different scales; (iii) a software enabling interactive visualization of millions of gene markers atop Terapixel-sized images (TissUUmaps); (iv) a tool utilizing signed-graph partitioning for the automatic identification of cells, independent of the complementary nuclear stain; (v) A fast and analytical expression for a score that quantifies co-localization between spatial points (such as located genes); (vi) a demonstration that gene expression markers can train deep-learning models to classify tissue morphology.In the final contribution (vii), an IST technique features in a clinical study to spatially map the molecular diversity within tumors from patients with colorectal liver metastases, specifically those exhibiting a desmoplastic growth pattern. The study unveils novel molecular patterns characterizing cellular diversity in the transitional region between healthy liver tissue and the tumor. While a direct answer to the initial questions remains elusive, this study sheds illuminating insights into the growth dynamics of colorectal cancer liver metastases, bringing us closer to understanding the journey from development to mortality in cancer.
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| 9. |
- Andersson, Axel, et al.
(författare)
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ISTDECO : In Situ Transcriptomics Decoding by Deconvolution
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- In Situ Transcriptomics (IST) is a set of image-based transcriptomics approaches that enables localisation of gene expression directly in tissue samples. IST techniques produce multiplexed image series in which fluorescent spots are either present or absent across imaging rounds and colour channels. A spot’spresence and absence form a type of barcoded pattern that labels a particular type of mRNA. Therefore, the expression of agene can be determined by localising the fluorescent spots and decode the barcode that they form. Existing IST algorithms usually do this in two separate steps: spot localisation and barcode decoding. Although these algorithms are efficient, they are limited by strictly separating the localisation and decoding steps. This limitation becomes apparent in regions with low signal-to-noise ratio or high spot densities. We argue that an improved gene expression decoding can be obtained by combining these two steps into a single algorithm. This allows for an efficient decoding that is less sensitive to noise and optical crowding. We present IST Decoding by Deconvolution (ISTDECO), a principled decoding approach combining spectral and spatial deconvolution into a single algorithm. We evaluate ISTDECOon simulated data, as well as on two real IST datasets, and compare with state-of-the-art. ISTDECO achieves state-of-the-art performance despite high spot densities and low signal-to-noise ratios. It is easily implemented and runs efficiently using a GPU.ISTDECO implementation, datasets and demos are available online at: github.com/axanderssonuu/istdeco
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| 10. |
- Andersson, Axel, et al.
(författare)
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Points2Regions : Fast, interactive clustering of imaging-based spatial transcriptomics data
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Imaging-based spatial transcriptomics techniques generate image data that, once processed, results in a set of spatial points with categorical labels for different mRNA species. A crucial part of analyzing downstream data involves the analysis of these point patterns. Here, biologically interesting patterns can be explored at different spatial scales. Molecular patterns on a cellular level would correspond to cell types, whereas patterns on a millimeter scale would correspond to tissue-level structures. Often, clustering methods are employed to identify and segment regions with distinct point-patterns. Traditional clustering techniques for such data are constrained by reliance on complementary data or extensive machine learning, limiting their applicability to tasks on a particular scale. This paper introduces 'Points2Regions', a practical tool for clustering spatial points with categorical labels. Its flexible and computationally efficient clustering approach enables pattern discovery across multiple scales, making it a powerful tool for exploratory analysis. Points2Regions has demonstrated efficient performance in various datasets, adeptly defining biologically relevant regions similar to those found by scale-specific methods. As a Python package integrated into TissUUmaps and a Napari plugin, it offers interactive clustering and visualization, significantly enhancing user experience in data exploration. In essence, Points2Regions presents a user-friendly and simple tool for exploratory analysis of spatial points with categorical labels.
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