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| 2. |
- Liu, Kui, et al.
(författare)
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Kallikrein genes are associated with lupus and glomerular basement membrane-specific antibody-induced nephritis in mice and humans
- 2009
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Ingår i: Journal of Clinical Investigation. - 0021-9738 .- 1558-8238. ; 119:4, s. 911-923
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Tidskriftsartikel (refereegranskat)abstract
- Immune-mediated nephritis contributes to disease in systemic lupus erythematosus, Goodpasture syndrome (caused by antibodies specific for glomerular basement membrane [anti-GBM antibodies]), and spontaneous lupus nephritis. Inbred mouse strains differ in susceptibility to anti-GBM antibody-induced and spontaneous lupus nephritis. This study sought to clarify the genetic and molecular factors that maybe responsible for enhanced immune-mediated renal disease in these models. When the kidneys of 3 mouse strains sensitive to anti-GBM antibody-induced nephritis were compared with those of 2 control strains using microarray analysis, one-fifth of the underexpressed genes belonged to the kallikrein gene family,which encodes serine esterases. Mouse strains that upregulated renal and urinary kallikreins exhibited less evidence of disease. Antagonizing the kallikrein pathway augmented disease, while agonists dampened the severity of anti-GBM antibody-induced nephritis. In addition, nephritis-sensitive mouse strains had kallikrein haplotypes that were distinct from those of control strains, including several regulatory polymorphisms,some of which were associated with functional consequences. Indeed, increased susceptibility to anti-GBM antibody-induced nephritis and spontaneous lupus nephritis was achieved by breeding mice with a genetic interval harboring the kallikrein genes onto a disease-resistant background. Finally, both human SLE and spontaneous lupus nephritis were found to be associated with kallikrein genes, particularly KLK1 and the KLK3 promoter, when DNA SNPs from independent cohorts of SLE patients and controls were compared. Collectively, these studies suggest that kallikreins are protective disease-associated genes in anti-GBM antibody-induced nephritis and lupus.
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| 6. |
- Garte, S, et al.
(författare)
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Metabolic gene polymorphism frequencies in control populations
- 2001
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Ingår i: Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology. - 1055-9965. ; 10:12, s. 1239-1248
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Tidskriftsartikel (refereegranskat)
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| 7. |
- Manni, Giovanni Li, et al.
(författare)
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The OpenMolcas Web : A Community-Driven Approach to Advancing Computational Chemistry
- 2023
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Ingår i: Journal of Chemical Theory and Computation. - : American Chemical Society (ACS). - 1549-9618 .- 1549-9626. ; 19:20, s. 6933-6991
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Tidskriftsartikel (refereegranskat)abstract
- The developments of the open-source OpenMolcas chemistry software environment since spring 2020 are described, with a focus on novel functionalities accessible in the stable branch of the package or via interfaces with other packages. These developments span a wide range of topics in computational chemistry and are presented in thematic sections: electronic structure theory, electronic spectroscopy simulations, analytic gradients and molecular structure optimizations, ab initio molecular dynamics, and other new features. This report offers an overview of the chemical phenomena and processes OpenMolcas can address, while showing that OpenMolcas is an attractive platform for state-of-the-art atomistic computer simulations.
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| 8. |
- Smits, KM, et al.
(författare)
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Association of metabolic gene polymorphisms with tobacco consumption in healthy controls
- 2004
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Ingår i: International Journal of Cancer. - : Wiley. - 0020-7136 .- 1097-0215. ; 110:2, s. 266-270
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Tidskriftsartikel (refereegranskat)abstract
- Polymorphisms in genes that encode for metabolic enzymes have been associated with variations in enzyme activity between individuals. Such variations could be associated with differences in individual exposure to carcinogens that are metabolized by these genes. In this study, we examine the association between polymorphisms in several metabolic genes and the consumption of tobacco in a large sample of healthy individuals. The database of the International Collaborative Study on Genetic Susceptibility to Environmental Carcinogens was used. All the individuals who were controls from the case-control studies included in the data set with information on smoking habits and on genetic polymorphisms were selected (n = 20,938). Sufficient information was available on the following genes that are involved in the metabolism of tobacco smoke constituents: CYPIAI, GSTMI, GSTTI, NAT2 and GSTPI. None of the tested genes was clearly associated with smoking behavior. Information on smoking dose, available for a subset of subjects, showed no effect of metabolic gene polymorphisms on the amount of smoking. No association between polymorphisms in the genes studied and tobacco consumption was observed; therefore, no effect of these genes on smoking behavior should be expected.
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| 10. |
- Manni, F, et al.
(författare)
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Hyperspectral Imaging for Glioblastoma Surgery: Improving Tumor Identification Using a Deep Spectral-Spatial Approach
- 2020
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Ingår i: Sensors (Basel, Switzerland). - : MDPI AG. - 1424-8220. ; 20:23
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Tidskriftsartikel (refereegranskat)abstract
- The primary treatment for malignant brain tumors is surgical resection. While gross total resection improves the prognosis, a supratotal resection may result in neurological deficits. On the other hand, accurate intraoperative identification of the tumor boundaries may be very difficult, resulting in subtotal resections. Histological examination of biopsies can be used repeatedly to help achieve gross total resection but this is not practically feasible due to the turn-around time of the tissue analysis. Therefore, intraoperative techniques to recognize tissue types are investigated to expedite the clinical workflow for tumor resection and improve outcome by aiding in the identification and removal of the malignant lesion. Hyperspectral imaging (HSI) is an optical imaging technique with the power of extracting additional information from the imaged tissue. Because HSI images cannot be visually assessed by human observers, we instead exploit artificial intelligence techniques and leverage a Convolutional Neural Network (CNN) to investigate the potential of HSI in twelve in vivo specimens. The proposed framework consists of a 3D–2D hybrid CNN-based approach to create a joint extraction of spectral and spatial information from hyperspectral images. A comparison study was conducted exploiting a 2D CNN, a 1D DNN and two conventional classification methods (SVM, and the SVM classifier combined with the 3D–2D hybrid CNN) to validate the proposed network. An overall accuracy of 80% was found when tumor, healthy tissue and blood vessels were classified, clearly outperforming the state-of-the-art approaches. These results can serve as a basis for brain tumor classification using HSI, and may open future avenues for image-guided neurosurgical applications.
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