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- Klionsky, Daniel J., et al.
(författare)
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Guidelines for the use and interpretation of assays for monitoring autophagy
- 2012
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Ingår i: Autophagy. - : Informa UK Limited. - 1554-8635 .- 1554-8627. ; 8:4, s. 445-544
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Forskningsöversikt (refereegranskat)abstract
- In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field.
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- Romagnoni, A, et al.
(författare)
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Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data
- 2019
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Ingår i: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9:1, s. 10351-
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Tidskriftsartikel (refereegranskat)abstract
- Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers.
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- Elhai, M, et al.
(författare)
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Outcomes of patients with systemic sclerosis treated with rituximab in contemporary practice: a prospective cohort study
- 2019
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Ingår i: Annals of the rheumatic diseases. - : BMJ. - 1468-2060 .- 0003-4967. ; 78:7, s. 979-987
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Tidskriftsartikel (refereegranskat)abstract
- To assess the safety and efficacy of rituximab in systemic sclerosis (SSc) in clinical practice.MethodsWe performed a prospective study including patients with SSc from the European Scleroderma Trials and Research (EUSTAR) network treated with rituximab and matched with untreated patients with SSc. The main outcomes measures were adverse events, skin fibrosis improvement, lung fibrosis worsening and steroids use among propensity score-matched patients treated or not with rituximab.Results254 patients were treated with rituximab, in 58% for lung and in 32% for skin involvement. After a median follow-up of 2 years, about 70% of the patients had no side effect. Comparison of treated patients with 9575 propensity-score matched patients showed that patients treated with rituximab were more likely to have skin fibrosis improvement (22.7 vs 14.03 events per 100 person-years; OR: 2.79 [1.47–5.32]; p=0.002). Treated patients did not have significantly different rates of decrease in forced vital capacity (FVC)>10% (OR: 1.03 [0.55–1.94]; p=0.93) nor in carbon monoxide diffusing capacity (DLCO) decrease. Patients having received rituximab were more prone to stop or decrease steroids (OR: 2.34 [1.56–3.53], p<0.0001). Patients treated concomitantly with mycophenolate mofetil had a trend for better outcomes as compared with patients receiving rituximab alone (delta FVC: 5.22 [0.83–9.62]; p=0.019 as compared with controls vs 3 [0.66–5.35]; p=0.012).ConclusionRituximab use was associated with a good safety profile in this large SSc-cohort. Significant change was observed on skin fibrosis, but not on lung. However, the limitation is the observational design. The potential stabilisation of lung fibrosis by rituximab has to be addressed by a randomised trial.
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