| 1. |
-
- 2019
-
Tidskriftsartikel (refereegranskat)
|
|
| 2. |
|
|
| 3. |
- Klionsky, Daniel J., et al.
(författare)
-
Guidelines for the use and interpretation of assays for monitoring autophagy
- 2012
-
Ingår i: Autophagy. - : Informa UK Limited. - 1554-8635 .- 1554-8627. ; 8:4, s. 445-544
-
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.
|
|
| 4. |
|
|
| 5. |
|
|
| 6. |
- Lange, Leslie A, et al.
(författare)
-
Whole-Exome Sequencing Identifies Rare and Low-Frequency Coding Variants Associated with LDL Cholesterol.
- 2014
-
Ingår i: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297. ; 94:2, s. 233-245
-
Tidskriftsartikel (refereegranskat)abstract
- Elevated low-density lipoprotein cholesterol (LDL-C) is a treatable, heritable risk factor for cardiovascular disease. Genome-wide association studies (GWASs) have identified 157 variants associated with lipid levels but are not well suited to assess the impact of rare and low-frequency variants. To determine whether rare or low-frequency coding variants are associated with LDL-C, we exome sequenced 2,005 individuals, including 554 individuals selected for extreme LDL-C (>98(th) or <2(nd) percentile). Follow-up analyses included sequencing of 1,302 additional individuals and genotype-based analysis of 52,221 individuals. We observed significant evidence of association between LDL-C and the burden of rare or low-frequency variants in PNPLA5, encoding a phospholipase-domain-containing protein, and both known and previously unidentified variants in PCSK9, LDLR and APOB, three known lipid-related genes. The effect sizes for the burden of rare variants for each associated gene were substantially higher than those observed for individual SNPs identified from GWASs. We replicated the PNPLA5 signal in an independent large-scale sequencing study of 2,084 individuals. In conclusion, this large whole-exome-sequencing study for LDL-C identified a gene not known to be implicated in LDL-C and provides unique insight into the design and analysis of similar experiments.
|
|
| 7. |
- Ding, Yun Mei, et al.
(författare)
-
Effect of social support on illness perception in patients with atrial fibrillation during “Blanking Period” : Mediating role of sense of mastery
- 2023
-
Ingår i: Nursing Open. - : Wiley. - 2054-1058. ; 10:1, s. 115-122
-
Tidskriftsartikel (refereegranskat)abstract
- Aim: To explore whether sense of mastery can mediate the relationship between social support and illness perception in patients with atrial fibrillation (AF) who were at the “Blanking Period.”. Design: A cross-sectional design. Methods: 405 patients with AF who were at the “Blanking Period” in the Affiliated Hospital of Qingdao University were recruited; they completed a set of questionnaires, including the Perceived Social Support Scale, the Personal Mastery Scale and the Brief Illness Perception Questionnaire. Results: Social support and sense of mastery were both adversely connected to illness perception. The indirect effect of social support on illness perception through sense of mastery was negative, accounting for 86.04% of the total effect. Conclusion: During the “Blanking Period,” better social support and sense of mastery contribute to a positive illness perception of AF patients. Social support also can influence patients' illness perception indirectly via the mediator of sense of mastery.
|
|
| 8. |
- Mahajan, Anubha, et al.
(författare)
-
Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation
- 2022
-
Ingår i: Nature Genetics. - : Springer Nature. - 1061-4036 .- 1546-1718. ; 54:5, s. 560-572
-
Tidskriftsartikel (refereegranskat)abstract
- We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 x 10(-9)), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background. Genome-wide association and fine-mapping analyses in ancestrally diverse populations implicate candidate causal genes and mechanisms underlying type 2 diabetes. Trans-ancestry genetic risk scores enhance transferability across populations.
|
|
| 9. |
- Wei, Jiang, et al.
(författare)
-
17β-estradiol regulates the expression of apolipoprotein M through estrogen receptor α-specific binding motif in its promoter
- 2017
-
Ingår i: Lipids in Health and Disease. - : Springer Science and Business Media LLC. - 1476-511X. ; 16:1, s. 1-8
-
Tidskriftsartikel (refereegranskat)abstract
- Background: We have previously demonstrated that estrogen could significantly enhance expression of apolipoprotein M (apoM), whereas the molecular basis of its mechanism is not fully elucidated yet. To further investigate the mechanism behind the estrogen induced up-regulation of apoM expression. Results: Our results demonstrated either free 17β-estradiol (E2) or membrane-impermeable bovine serum albumin-conjugated E2 (E2-BSA) could modulate human apoM gene expression via the estrogen receptor alpha (ER-α) pathway in the HepG2 cells. Moreover, experiments with the luciferase activity analysis of truncated apoM promoters could demonstrate that a regulatory region (from-1580 to −1575 bp (−GGTCA-)) upstream of the transcriptional start site of apoM gene was essential for the basal transcriptional activity that regulated by the ER-α. With the applications of an electrophoresis mobility shift assay and a chromatin immunoprecipitation assay, we could successfully identify a specific ER-α binding element in the apoM promoter region. Conculsion: In summary, the present study indicates that 17β-estradiol induced up-regulation of apoM in HepG2 cells is through an ER-α-dependent pathway involving ER-α binding element in the promoter of the apoM gene.
|
|
| 10. |
- Wu, Chuanyan, et al.
(författare)
-
PEPRF : Identification of Essential Proteins by Integrating Topological Features of PPI Network and Sequence-based Features via Random Forest
- 2021
-
Ingår i: Current Bioinformatics. - : Bentham Science Publishers Ltd.. - 1574-8936. ; 16:9, s. 1161-1168
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Essential proteins play an important role in the process of life, which can be identified by experimental methods and computational approaches. Experimental approaches to identify essential proteins are of high accuracy but with the limitation of time and resource-consuming. Objective: Herein, we present a computational model (PEPRF) to identify essential proteins based on machine learning. Methods: Different features of proteins were extracted. Topological features of Protein-Protein Interaction (PPI) network-based are extracted. Based on the protein sequence, graph theory-based features, in-formation-based features, composition and physichemical features, etc., were extracted. Finally, 282 features are constructed. In order to select the features that contributed most to the identification, Re-liefF-based feature selection method was adopted to measure the weights of these features. Results: As a result, 212 features were curated to train random forest classifiers. Finally, PEPRF get the AUC of 0.71 and an accuracy of 0.742. Conclusion: Our results show that PEPRF may be applied as an efficient tool to identify essential pro-teins.
|
|
