| 1. |
|
|
| 2. |
|
|
| 3. |
|
|
| 4. |
|
|
| 5. |
- Beckham, Gregg T., et al.
(författare)
-
The O-Glycosylated Linker from the Trichoderma reesei Family 7 Cellulase Is a Flexible, Disordered Protein
- 2010
-
Ingår i: Biophysical Journal. - : Elsevier BV. - 0006-3495 .- 1542-0086. ; 99:11, s. 3773-3781
-
Tidskriftsartikel (refereegranskat)abstract
- Fungi and bacteria secrete glycoprotein cocktails to deconstruct cellulose Cellulose degrading enzymes (cellulases) are often modular with catalytic domains for cellulose hydrolysis and carbohydrate binding modules connected by linkers rich in serine and threonine with O-glycosylation Few studies have probed the role that the linker and O-glycans play in catalysis Since different expression and growth conditions produce different glycosylation patterns that affect enzyme activity the structure function relationships that glycosylation imparts to linkers are relevant for understanding cellulase mechanisms Here the linker of the Trichoderma reesei Family 7 cellobiohydrolase (Cel7A) is examined by simulation Our results suggest that the Cel7A linker is an intrinsically disordered protein with and without glycosylation Contrary to the predominant view the O-glycosylation does not change the stiffness of the linker as measured by the relative fluctuations in the end to end distance rather it provides a 16 A extension thus expanding the operating range of Cel7A We explain observations from previous biochemical experiments in the light of results obtained here and compare the Cel7A linker with linkers from other cellulases with sequence based tools to predict disorder This preliminary screen indicates that linkers from Family 7 enzymes from other genera and other cellulases within T reesei may not be as disordered warranting further study
|
|
| 6. |
- Bloecker, K., et al.
(författare)
-
Tibial coverage, meniscus position, size and damage in knees discordant for joint space narrowing - data from the Osteoarthritis Initiative
- 2013
-
Ingår i: Osteoarthritis and Cartilage. - : Elsevier BV. - 1063-4584. ; 21:3, s. 419-427
-
Tidskriftsartikel (refereegranskat)abstract
- Introduction: Meniscal extrusion is thought to be associated with less meniscus coverage of the tibial surface, but the association of radiographic disease stage with quantitative measures of tibial plateau coverage is unknown. We therefore compared quantitative and semi-quantitative measures of meniscus position and morphology in individuals with bilateral painful knees discordant on medial joint space narrowing (mJSN). Methods: A sample of 60 participants from the first half (2,678 cases) of the Osteoarthritis Initiative cohort fulfilled the inclusion criteria: bilateral frequent pain, Osteoarthritis Research Society International (OARSI) mJSN grades 1-3 in one, no-JSN in the contra-lateral (CL), and no lateral JSN in either knee (43 unilateral mJSN1; 17 mJSN2/3; 22 men, 38 women, body mass index (BMI) 31.3 +/- 3.9 kg/m(2)). Segmentation and three-dimensional quantitative analysis of the tibial plateau and meniscus, and semiquantitative evaluation of meniscus damage (magnetic resonance imaging (MRI) osteoarthritis knee score = MOAKS) was performed using coronal 3T MR images (MPR DESSwe and intermediate-weighted turbo spin echo (IW-TSE) images). CL knees were compared using paired t-tests (between-knee, within-person design). Results: Medial tibial plateau coverage was 36 +/- 9% in mJSN1 vs 45 +/- 8% in CL no-JSN knees, and was 31 +/- 9% in mJSN2/3 vs 46 +/- 6% in no-JSN knees (both P < 0.001). mJSN knees showed greater meniscus extrusion and damage (MOAKS), but no significant difference in meniscus volume. No significant differences in lateral tibial coverage, lateral meniscus morphology or position were observed. Conclusions: Knees with medial JSN showed substantially less medial tibial plateau coverage by the meniscus. We suggest that the less meniscal coverage, i.e., less mechanical protection may be a reason for greater rates of cartilage loss observed in JSN knees. (C) 2012 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.
|
|
| 7. |
- Dore, Riccardo, et al.
(författare)
-
Resistance to thyroid hormone induced tachycardia in RTHα syndrome
- 2023
-
Ingår i: Nature Communications. - 2041-1723. ; 14:1
-
Tidskriftsartikel (refereegranskat)abstract
- Mutations in thyroid hormone receptor α1 (TRα1) cause Resistance to Thyroid Hormone α (RTHα), a disorder characterized by hypothyroidism in TRα1-expressing tissues including the heart. Surprisingly, we report that treatment of RTHα patients with thyroxine to overcome tissue hormone resistance does not elevate their heart rate. Cardiac telemetry in male, TRα1 mutant, mice indicates that such persistent bradycardia is caused by an intrinsic cardiac defect and not due to altered autonomic control. Transcriptomic analyses show preserved, thyroid hormone (T3)-dependent upregulation of pacemaker channels (Hcn2, Hcn4), but irreversibly reduced expression of several ion channel genes controlling heart rate. Exposure of TRα1 mutant male mice to higher maternal T3 concentrations in utero, restores altered expression and DNA methylation of ion channels, including Ryr2. Our findings indicate that target genes other than Hcn2 and Hcn4 mediate T3-induced tachycardia and suggest that treatment of RTHα patients with thyroxine in high dosage without concomitant tachycardia, is possible.
|
|
| 8. |
|
|
| 9. |
- Kovacs-Gyoeri, Anna, et al.
(författare)
-
Opportunities and Challenges of Geospatial Analysis for Promoting Urban Livability in the Era of Big Data and Machine Learning
- 2020
-
Ingår i: ISPRS International Journal of Geo-Information. - : MDPI AG. - 2220-9964. ; 9:12
-
Tidskriftsartikel (refereegranskat)abstract
- Urban systems involve a multitude of closely intertwined components, which are more measurable than before due to new sensors, data collection, and spatio-temporal analysis methods. Turning these data into knowledge to facilitate planning efforts in addressing current challenges of urban complex systems requires advanced interdisciplinary analysis methods, such as urban informatics or urban data science. Yet, by applying a purely data-driven approach, it is too easy to get lost in the 'forest' of data, and to miss the 'trees' of successful, livable cities that are the ultimate aim of urban planning. This paper assesses how geospatial data, and urban analysis, using a mixed methods approach, can help to better understand urban dynamics and human behavior, and how it can assist planning efforts to improve livability. Based on reviewing state-of-the-art research the paper goes one step further and also addresses the potential as well as limitations of new data sources in urban analytics to get a better overview of the whole 'forest' of these new data sources and analysis methods. The main discussion revolves around the reliability of using big data from social media platforms or sensors, and how information can be extracted from massive amounts of data through novel analysis methods, such as machine learning, for better-informed decision making aiming at urban livability improvement.
|
|
| 10. |
- Kovacs-Györi, A., et al.
(författare)
-
Assessing and representing livability through the analysis of residential preference
- 2019
-
Ingår i: Sustainability. - : MDPI AG. - 2071-1050. ; 11:18
-
Tidskriftsartikel (refereegranskat)abstract
- Livability reflects the quality of the person-environment relationship, namely how well the built environment or the available services in a city fulfill the residents' needs and expectations. We argue that livability assessment can aid the implementation of certain New Urban Agenda (NUA) goals by providing a flexible way to assess urban environments and their quality. However, a reliable and transferable assessment framework requires the key elements of livability to be defined in such a way that measurable factors adequately represent the person-environment relationship. As an innovative approach, we determined key livability elements accordingly and asked over 400 residents worldwide to evaluate their urban environments using these parameters. Thereby, we could calibrate the livability assessment workflow by including personal aspects and identifying the most relevant livability factors through an ordinal regression analysis. Next, we performed relational-statistical learning in order to define the individual and combined contribution of these statistically significant factors to the overall livability of a place. We found that urban form and mobility-related factors tend to have the highest influence on residential satisfaction. Finally, we tested the robustness of the assessment by using geospatial analysis to model the livability for the city of Vienna, Austria. We concluded that the workflow allows for a reliable livability assessment and for further utilization in urban planning, improving urban quality by going beyond simple city rankings.
|
|
