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- Lankester, Arjan C, et al.
(författare)
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Hematopoietic cell transplantation in severe combined immunodeficiency: The SCETIDE 2006-2014 European cohort.
- 2022
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Ingår i: The Journal of allergy and clinical immunology. - : Elsevier BV. - 1097-6825 .- 0091-6749. ; 149:5
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Tidskriftsartikel (refereegranskat)abstract
- Hematopoietic stem cell transplantation (HSCT) represents a curative treatment for patients with severe combined immunodeficiency (SCID), a group of monogenic immune disorders with an otherwise fatal outcome.We performed a comprehensive multicenter analysis of genotype-specific HSCT outcome, including detailed analysis of immune reconstitution (IR) and the predictive value for clinical outcome.HSCT outcome was studied in 338 patients with genetically confirmed SCID who underwent transplantation in 2006-2014 and who were registered in the SCETIDE registry. In a representative subgroup of 152 patients, data on IR and long-term clinical outcome were analyzed.Two-year OS was similar with matched family and unrelated donors and better than mismatched donor HSCT (P<.001). The 2-year event-free survival (EFS) was similar in matched and mismatched unrelated donor and less favorable in mismatched related donor (MMRD) HSCT (P< .001). Genetic subgroups did not differ in 2-year OS (P= .1) and EFS (P=.073). In multivariate analysis, pretransplantation infections and use of MMRDs were associated with less favorable OS and EFS. With a median follow-up of 6.2 years (range, 2.0-11.8 years), 73 of 152 patients in the IR cohort were alive and well without Ig dependency. IL-2 receptor gamma chain/Janus kinase 3/IL-7 receptor-deficient SCID, myeloablative conditioning, matched donor HSCT, and naive CD4 T lymphocytes >0.5×10e3/μL at+1 year were identified as independent predictors of favorable clinical and immunologic outcome.Recent advances in HSCT in SCID patients have resulted in improved OS and EFS in all genotypes and donor types. To achieve a favorable long-term outcome, treatment strategies should aim for optimal naive CD4 T lymphocyte regeneration.
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| 2. |
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| 3. |
- Jenkins, Andrew J., et al.
(författare)
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The Ehrenfest method with fully quantum nuclear motion (Qu-Eh) : Application to charge migration in radical cations
- 2018
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Ingår i: Journal of Chemical Physics. - : AIP Publishing. - 0021-9606 .- 1089-7690. ; 149:9
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Tidskriftsartikel (refereegranskat)abstract
- An algorithm is described for quantum dynamics where an Ehrenfest potential is combined with fully quantum nuclear motion (Quantum-Ehrenfest, Qu-Eh). The method is related to the single-set variational multi-configuration Gaussian approach (vMCG) but has the advantage that only a single quantum chemistry computation is required at each time step since there is only a single time-dependent potential surface. Also shown is the close relationship to the “exact factorization method.” The quantum Ehrenfest method is compared with vMCG for study of electron dynamics in a modified bismethylene-adamantane cation system. Illustrative examples of electron-nuclear dynamics are presented for a distorted allene system and for HCCI+ where one has a degenerate Π system.
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| 4. |
- Mansouri, Kamel, et al.
(författare)
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CERAPP : Collaborative Estrogen Receptor Activity Prediction Project
- 2016
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Ingår i: Journal of Environmental Health Perspectives. - : Environmental Health Perspectives. - 0091-6765 .- 1552-9924. ; 124:7, s. 1023-1033
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Humans are exposed to thousands of man-made chemicals in the environment. Some chemicals mimic natural endocrine hormones and, thus, have the potential to be endocrine disruptors. Most of these chemicals have never been tested for their ability to interact with the estrogen receptor (ER). Risk assessors need tools to prioritize chemicals for evaluation in costly in vivo tests, for instance, within the U.S. EPA Endocrine Disruptor Screening Program. OBJECTIVES: We describe a large-scale modeling project called CERAPP (Collaborative Estrogen Receptor Activity Prediction Project) and demonstrate the efficacy of using predictive computational models trained on high-throughput screening data to evaluate thousands of chemicals for ER-related activity and prioritize them for further testing. METHODS: CERAPP combined multiple models developed in collaboration with 17 groups in the United States and Europe to predict ER activity of a common set of 32,464 chemical structures. Quantitative structure-activity relationship models and docking approaches were employed, mostly using a common training set of 1,677 chemical structures provided by the U.S. EPA, to build a total of 40 categorical and 8 continuous models for binding, agonist, and antagonist ER activity. All predictions were evaluated on a set of 7,522 chemicals curated from the literature. To overcome the limitations of single models, a consensus was built by weighting models on scores based on their evaluated accuracies. RESULTS: Individual model scores ranged from 0.69 to 0.85, showing high prediction reliabilities. Out of the 32,464 chemicals, the consensus model predicted 4,001 chemicals (12.3%) as high priority actives and 6,742 potential actives (20.8%) to be considered for further testing.CONCLUSION: This project demonstrated the possibility to screen large libraries of chemicals using a consensus of different in silico approaches. This concept will be applied in future projects related to other end points.
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