| 1. |
- Bel Lassen, P., et al.
(författare)
-
Protein intake, metabolic status and the gut microbiota in different ethnicities: Results from two independent cohorts
- 2021
-
Ingår i: Nutrients. - : MDPI AG. - 2072-6643. ; 13:9
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Protein intake has been associated with the development of pre-diabetes (pre-T2D) and type 2 diabetes (T2D). The gut microbiota has the capacity to produce harmful metabolites derived from dietary protein. Furthermore, both the gut microbiota composition and metabolic status (e.g., insulin resistance) can be modulated by diet and ethnicity. However, to date most studies have predominantly focused on carbohydrate and fiber intake with regards to metabolic status and gut microbiota composition. Objectives: To determine the associations between dietary protein intake, gut microbiota composition, and metabolic status in different ethnicities. Methods: Separate cross-sectional analysis of two European cohorts (MetaCardis, n = 1759; HELIUS, n = 1528) including controls, patients with pre-T2D, and patients with T2D of Caucasian/non-Caucasian origin with nutritional data obtained from Food Frequency Questionnaires and gut microbiota composition. Results: In both cohorts, animal (but not plant) protein intake was associated with pre-T2D status and T2D status after adjustment for confounders. There was no significant association between protein intake (total, animal, or plant) with either gut microbiota alpha diversity or beta diversity, regardless of ethnicity. At the species level, we identified taxonomical signatures associated with animal protein intake that overlapped in both cohorts with different abundances according to metabolic status and ethnicity. Conclusions: Animal protein intake is associated with pre-T2D and T2D status but not with gut microbiota beta or alpha diversity, regardless of ethnicity. Gut microbial taxonomical signatures were identified, which could function as potential modulators in the association between dietary protein intake and metabolic status. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
|
|
| 2. |
- Krzywicka, K., et al.
(författare)
-
Age-Stratified Risk of Cerebral Venous Sinus Thrombosis After SARS-CoV-2 Vaccination
- 2022
-
Ingår i: Neurology. - : Ovid Technologies (Wolters Kluwer Health). - 0028-3878 .- 1526-632X. ; 98:7
-
Tidskriftsartikel (refereegranskat)abstract
- Background and Objectives Cerebral venous sinus thrombosis (CVST) as a part of the thrombosis and thrombocytopenia syndrome is a rare adverse drug reaction of severe acute respiratory syndrome coronavirus disease 2 (SARS-CoV-2) vaccination. Estimated background rate of CVST with thrombocytopenia is 0.1 per million per month. We assessed the age-stratified risk of CVST with and without thrombocytopenia after SARS-CoV-2 vaccination. Methods We estimated the absolute risk of CVST with and without thrombocytopenia within 28 days of a first dose of 4 SARS-CoV-2 vaccinations using data from the European Medicines Agency's EudraVigilance database (until June 13, 2021). As a denominator, we used data on vaccine delivery from 31 European countries. For 22.8 million adults from 25 countries, we estimated the absolute risk of CVST after the first dose of ChAdOx1 nCov-19 per age category. Results The absolute risk of CVST within 28 days of first-dose vaccination was 7.5 (95% confidence interval [CI] 6.9-8.3), 0.7 (95% CI 0.2-2.4), 0.6 (95% CI 0.5-0.7), and 0.6 (95% CI 0.3-1.1) per million of first doses of ChAdOx1 nCov-19, Ad26.COV2.S, BNT162b2, and mRNA-1273, respectively. The absolute risk of CVST with thrombocytopenia within 28 days of first dose vaccination was 4.4 (95% CI 3.9-4.9), 0.7 (95% CI 0.2-2.4), 0.0 (95% CI 0.0-0.1), and 0.0 (95% CI 0.0-0.2) per million of first doses of ChAdOx1 nCov-19, Ad26.COV2.S, BNT162b2, and mRNA-1273, respectively. In recipients of ChAdOx1 nCov-19, the absolute risk of CVST, both with and without thrombocytopenia, was the highest in the 18- to 24-year-old group (7.3 per million, 95% CI 2.8-18.8 and 3.7 per million, 95% CI 1.0-13.3, respectively). The risk of CVST with thrombocytopenia in ChAdOx1 nCov-19 recipients was the lowest in the age group >= 70 years (0.2, 95% CI 0.0-1.3). Age <60 years compared to >= 60 years was a predictor for CVST with thrombocytopenia (incidence rate ratio 5.79, 95% CI 2.98-11.24, p < 0.001). Discussion The risk of CVST with thrombocytopenia within 28 days of first-dose vaccination with ChAdOx1 nCov-19 was higher in younger age groups. The risk of CVST with thrombocytopenia was slightly increased in patients receiving Ad26.COV2.S compared with the estimated background risk. The risk of CVST with thrombocytopenia was not increased in recipients of SARS-CoV-2 mRNA vaccines.
|
|
| 3. |
- Bouget, D., et al.
(författare)
-
Preoperative Brain Tumor Imaging: Models and Software for Segmentation and Standardized Reporting
- 2022
-
Ingår i: Frontiers in Neurology. - : Frontiers Media SA. - 1664-2295. ; 13
-
Tidskriftsartikel (refereegranskat)abstract
- For patients suffering from brain tumor, prognosis estimation and treatment decisions are made by a multidisciplinary team based on a set of preoperative MR scans. Currently, the lack of standardized and automatic methods for tumor detection and generation of clinical reports, incorporating a wide range of tumor characteristics, represents a major hurdle. In this study, we investigate the most occurring brain tumor types: glioblastomas, lower grade gliomas, meningiomas, and metastases, through four cohorts of up to 4,000 patients. Tumor segmentation models were trained using the AGU-Net architecture with different preprocessing steps and protocols. Segmentation performances were assessed in-depth using a wide-range of voxel and patient-wise metrics covering volume, distance, and probabilistic aspects. Finally, two software solutions have been developed, enabling an easy use of the trained models and standardized generation of clinical reports: Raidionics and Raidionics-Slicer. Segmentation performances were quite homogeneous across the four different brain tumor types, with an average true positive Dice ranging between 80 and 90%, patient-wise recall between 88 and 98%, and patient-wise precision around 95%. In conjunction to Dice, the identified most relevant other metrics were the relative absolute volume difference, the variation of information, and the Hausdorff, Mahalanobis, and object average symmetric surface distances. With our Raidionics software, running on a desktop computer with CPU support, tumor segmentation can be performed in 16-54 s depending on the dimensions of the MRI volume. For the generation of a standardized clinical report, including the tumor segmentation and features computation, 5-15 min are necessary. All trained models have been made open-access together with the source code for both software solutions and validation metrics computation. In the future, a method to convert results from a set of metrics into a final single score would be highly desirable for easier ranking across trained models. In addition, an automatic classification of the brain tumor type would be necessary to replace manual user input. Finally, the inclusion of post-operative segmentation in both software solutions will be key for generating complete post-operative standardized clinical reports.
|
|
