| 1. |
|
|
| 2. |
|
|
| 3. |
|
|
| 4. |
- 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.
|
|
| 5. |
|
|
| 6. |
|
|
| 7. |
|
|
| 8. |
|
|
| 9. |
- Van Hemelrijck, Mieke, et al.
(författare)
-
Reasons for Discontinuing Active Surveillance : Assessment of 21 Centres in 12 Countries in the Movember GAP3 Consortium
- 2019
-
Ingår i: European Urology. - : Elsevier BV. - 0302-2838. ; 75:3, s. 523-531
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Careful assessment of the reasons for discontinuation of active surveillance (AS) is required for men with prostate cancer (PCa). Objective: Using Movember's Global Action Plan Prostate Cancer Active Surveillance initiative (GAP3) database, we report on reasons for AS discontinuation. Design, setting, and participants: We compared data from 10 296 men on AS from 21 centres across 12 countries. Outcome measurements and statistical analysis: Cumulative incidence methods were used to estimate the cumulative incidence rates of AS discontinuation. Results and limitations: During 5-yr follow-up, 27.5% (95% confidence interval [CI]: 26.4–28.6%) men showed signs of disease progression, 12.8% (95% CI: 12.0–13.6%) converted to active treatment without evidence of progression, 1.7% (95% CI: 1.5–2.0%) continued to watchful waiting, and 1.7% (95% CI: 1.4–2.1%) died from other causes. Of the 7049 men who remained on AS, 2339 had follow-up for >5 yr, 4561 had follow-up for <5 yr, and 149 were lost to follow-up. Cumulative incidence of progression was 27.5% (95% CI: 26.4–28.6%) at 5 yr and 38.2% (95% CI: 36.7–39.9%) at 10 yr. A limitation is that not all centres were included due to limited information on the reason for discontinuation and limited follow-up. Conclusions: Our descriptive analyses of current AS practices worldwide showed that 43.6% of men drop out of AS during 5-yr follow-up, mainly due to signs of disease progression. Improvements in selection tools for AS are thus needed to correctly allocate men with PCa to AS, which will also reduce discontinuation due to conversion to active treatment without evidence of disease progression. Patient summary: Our assessment of a worldwide database of men with prostate cancer (PCa) on active surveillance (AS) shows that 43.6% drop out of AS within 5 yr, mainly due to signs of disease progression. Better tools are needed to select and monitor men with PCa as part of AS.
|
|
| 10. |
- Breznau, Nate, et al.
(författare)
-
Observing many researchers using the same data and hypothesis reveals a hidden universe of uncertainty
- 2022
-
Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 119:44
-
Tidskriftsartikel (refereegranskat)abstract
- This study explores how researchers analytical choices affect the reliability of scientific findings. Most discussions of reliability problems in science focus on systematic biases. We broaden the lens to emphasize the idiosyncrasy of conscious and unconscious decisions that researchers make during data analysis. We coordinated 161 researchers in 73 research teams and observed their research decisions as they used the same data to independently test the same prominent social science hypothesis: that greater immigration reduces support for social policies among the public. In this typical case of social science research, research teams reported both widely diverging numerical findings and substantive conclusions despite identical start conditions. Researchers expertise, prior beliefs, and expectations barely predict the wide variation in research outcomes. More than 95% of the total variance in numerical results remains unexplained even after qualitative coding of all identifiable decisions in each teams workflow. This reveals a universe of uncertainty that remains hidden when considering a single study in isolation. The idiosyncratic nature of how researchers results and conclusions varied is a previously underappreciated explanation for why many scientific hypotheses remain contested. These results call for greater epistemic humility and clarity in reporting scientific findings.
|
|
