| 1. |
- Andersson, Henrik, et al.
(författare)
-
T A microarray analysis of the murine macrophage response to infection with Francisella tularensis LVS
- 2006
-
Ingår i: Journal of Medical Microbiology. - : Microbiology Society. - 0022-2615 .- 1473-5644. ; 55:8, s. 1023-1033
-
Tidskriftsartikel (refereegranskat)abstract
- The response of cells of the mouse macrophage cell line J774 to infection with Francisella tularensis LVS was analysed by means of a DNA microarray representing approximately 18 500 genes (20 600 clones). The adaptive response was modest at all time points, and at most, 81 clones were differentially regulated from the time point of uptake of bacteria (0 min) up to 240 min later. For all five time points, 229 clones fulfilled the criteria of being differentially regulated, i.e. the ratio between infected versus non-infected cells was at least 1.7-fold up- or down-regulated and P <0.05. It was found that many of the differentially regulated genes are known to respond to stress in general and to oxidative stress specifically. However, at 120 min it was observed that genes that lead to depletion of glutathione were upregulated. Possibly, this was a result of mechanisms induced by F. tularensis. Generally, there was a conspicuous lack of inflammatory responses and, for example, although tumour necrosis factor alpha (TNF-α) was upregulated at 0 min, a significant down-regulation was noted at all subsequent time points. When cells were treated with an inhibitor of inducible nitric oxide synthase (iNOS) or the antioxidant N-acetylcysteine (NAC), the infection-induced cytopathogenic effect was significantly inhibited. Together, the results suggest that F. tularensis LVS infection confers an oxidative stress upon the target cells and that many of the host-defence mechanisms appear to be intended to counteract this stress. The infection is characterized by a very modest inflammatory response.
|
|
| 2. |
- Dracheva, Elena, et al.
(författare)
-
In Silico Identification of Potential Thyroid Hormone System Disruptors among Chemicals in Human Serum and Chemicals with a High Exposure Index
- 2022
-
Ingår i: Environmental Science and Technology. - : American Chemical Society (ACS). - 0013-936X .- 1520-5851. ; 56:12, s. 8363-8372
-
Tidskriftsartikel (refereegranskat)abstract
- Data on toxic effects are at large missing the prevailing understanding of the risks of industrial chemicals. Thyroid hormone (TH) system disruption includes interferences of the life cycle of the thyroid hormones and may occur in various organs. In the current study, high-throughput screening data available for 14 putative molecular initiating events of adverse outcome pathways, related to disruption of the TH system, were used to develop 19 in silico models for identification of potential thyroid hormone system-disrupting chemicals. The conformal prediction framework with the underlying Random Forest was used as a wrapper for the models allowing for setting the desired confidence level and controlling the error rate of predictions. The trained models were then applied to two different databases: (i) an in-house database comprising xenobiotics identified in human blood and ii) currently used chemicals registered in the Swedish Product Register, which have been predicted to have a high exposure index to consumers. The application of these models showed that among currently used chemicals, fewer were overall predicted as active compared to chemicals identified in human blood. Chemicals of specific concern for TH disruption were identified from both databases based on their predicted activity.
|
|
| 3. |
- Golosovskaia, Elena, 1993-
(författare)
-
Development of in silico methods to aid chemical risk assessment : focusing on kinetic interactions in mixtures
- 2024
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The environment and biota are constantly exposed to numerous chemicals through contaminated food, soil, water, and air. These chemicals can be taken up and distributed to reach sensitive tissues where they may cause various effects. Many of these chemicals lack data on their environmental and human health effects. Traditional toxicological tests relying on animal experiments are today being phased out in favor of cell-based and computational methods for early hazard detection and exposure assessment. This thesis focuses on developing computational tools for various stages of chemical risk assessment with a particular focus on bisphenols and per- and polyfluoroalkyl substances (PFAS). In Paper I, quantitative structure-activity relationship (QSAR) models covering molecular targets of the thyroid hormone (TH) system were developed and applied to two data sets to prioritize chemicals of concern for detailed toxicological studies. In Papers II and III, experimental and computational approaches were combined to study toxicokinetics and maternal transfer in zebrafish. Our main focus was to study potential mixture effects on administration, distribution, metabolism, and elimination (ADME) processes, i.e., to reveal if co-exposed chemicals impact each other’s ADME. Physiologically based kinetic (PBK) mixture models were developed to allow translation of external exposure concentrations into tissue concentrations and modelling plausible mechanisms of chemical interactions in a mixture.Main findings of this thesis are summarized as follows:• Application of QSAR models (Paper I) to two chemical inventories revealed that chemicals found in human blood could induce a large iirange of pathways in the TH system whereas chemicals used in Sweden with predicted high exposure index to consumers showed a lower likelihood to induce TH pathways.• Two zebrafish experiments (Paper II and Paper III) did not reveal statistically significant mixture effects on ADME of chemicals.• In Paper II, a PBK mixture model for PFAS accounting for competitive plasma protein binding was developed. The model demonstrated good predictive performance. Competitive plasma protein binding did not affect the predicted internal concentrations.• In Paper III we developed a binary PBK model parametrized for two bisphenols and PFOS showing that competitive plasma protein binding has an effect on ADME of bisphenols at PFOS concentrations at μg/L levels. At these levels internal concentrations of bisphenols were shown to decrease, implying that PFOS outcompeted bisphenols from studied plasma proteins resulting in higher excretion rates.Developed QSAR models showed good predictive power and the ability to identify and prioritize chemicals of concern with confidence. Additionally, PBK models aid in hypotheses testing and predicting exposure concentrations at which co-exposed chemicals could potentially influence each other’s ADME properties. These tools will provide overall early tier data on exposure and effects using non-testing methods in assessment of risks of chemicals.
|
|
| 4. |
|
|
| 5. |
- Andersson-Evelönn, Emma, 1983-, et al.
(författare)
-
Combining epigenetic and clinicopathological variables improves specificity in prognostic prediction in clear cell renal cell carcinoma
- 2020
-
Ingår i: Journal of Translational Medicine. - : Springer Science and Business Media LLC. - 1479-5876. ; 18:1
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Metastasized clear cell renal cell carcinoma (ccRCC) is associated with a poor prognosis. Almost one-third of patients with non-metastatic tumors at diagnosis will later progress with metastatic disease. These patients need to be identified already at diagnosis, to undertake closer follow up and/or adjuvant treatment. Today, clinicopathological variables are used to risk classify patients, but molecular biomarkers are needed to improve risk classification to identify the high-risk patients which will benefit most from modern adjuvant therapies. Interestingly, DNA methylation profiling has emerged as a promising prognostic biomarker in ccRCC. This study aimed to derive a model for prediction of tumor progression after nephrectomy in non-metastatic ccRCC by combining DNA methylation profiling with clinicopathological variables.Methods: A novel cluster analysis approach (Directed Cluster Analysis) was used to identify molecular biomarkers from genome-wide methylation array data. These novel DNA methylation biomarkers, together with previously identified CpG-site biomarkers and clinicopathological variables, were used to derive predictive classifiers for tumor progression.Results: The “triple classifier” which included both novel and previously identified DNA methylation biomarkers together with clinicopathological variables predicted tumor progression more accurately than the currently used Mayo scoring system, by increasing the specificity from 50% in Mayo to 64% in our triple classifier at 85% fixed sensitivity. The cumulative incidence of progress (pCIP5yr) was 7.5% in low-risk vs 44.7% in high-risk in M0 patients classified by the triple classifier at diagnosis.Conclusions: The triple classifier panel that combines clinicopathological variables with genome-wide methylation data has the potential to improve specificity in prognosis prediction for patients with non-metastatic ccRCC.
|
|
| 6. |
|
|
| 7. |
|
|
| 8. |
|
|
| 9. |
- Andersson, H., et al.
(författare)
-
Transcriptional profiling of the peripheral blood response during tularemia
- 2006
-
Ingår i: Genes and Immunity. - : Springer Science and Business Media LLC. - 1466-4879 .- 1476-5470. ; 7:6, s. 503-513
-
Tidskriftsartikel (refereegranskat)abstract
- Tularemia is a febrile disease caused by the highly contagious bacterium Francisella tularensis. We undertook an analysis of the transcriptional response in peripheral blood during the course of ulceroglandular tularemia by use of Affymetrix microarrays comprising 14,500 genes. Samples were obtained from seven individuals at five occasions during 2 weeks after the first hospital visit and convalescent samples 3 months later. In total, 265 genes were differentially expressed, 95 of which at more than one time point. The differential expression was verified with real-time quantitative polymerase chain reaction for 36 genes (R(2)=0.590). The most prominent changes were noted in samples drawn on days 2-3 and a considerable proportion of the upregulated genes appeared to represent an interferon-gamma-induced response and also a proapoptotic response. Genes involved in the generation of innate and acquired immune responses were found to be downregulated, presumably a pathogen-induced event. A logistic regression analysis revealed that seven genes were good predictors of the early phase of tularemia. This is the first description of the transcriptional host response to ulceroglandular tularemia and the study has identified gene subsets relevant to the pathogenesis of the disease and subsets that may serve as early diagnostic biomarkers.
|
|
| 10. |
|
|
