Dataset Information

Diabetes Enhances the Proliferation of Adult Pancreatic Multipotent Progenitor Cells and Biases Their Differentiation to More Beta-Cell Production

ABSTRACT: Endogenous pancreatic multipotent progenitors (PMPs) are ideal candidates for regenerative approaches to compensate for b-cell loss since their b-cell–producing capacities as well as strategic location would eliminate unnecessary invasive manipulations. However, little is known about the status and potentials of PMPs under diabetic conditions. Here we show that b-cell metabolic stress and hyperglycemia enhance the proliferation capacities of adult PMP cells and bias their production of progeny toward b-cells in mouse and human. These effects are dynamic and correlate with functional b-cell regeneration when conditions allow.

ORGANISM(S): Mus musculus

PROVIDER: GSE66817 | GEO | 2015/03/13

SECONDARY ACCESSION(S): PRJNA278022

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:In real life, we often have to make judgements under uncertainty. One such judgement task is estimating the probability of a given event based on uncertain evidence for the event, such as estimating the chances of actual fire when the fire alarm goes off. On the one hand, previous studies have shown that human subjects often significantly misestimate the probability in such cases. On the other hand, these studies have offered divergent explanations as to the exact causes of these judgment errors (or, synonymously, biases). For instance, different studies have attributed the errors to the neglect (or underweighting) of the prevalence (or base rate) of the given event, or the overweighting of the evidence for the individual event (‘individuating information’), etc. However, whether or to what extent any such explanation can fully account for the observed errors remains unclear. To help fill this gap, we studied the probability estimation performance of non-professional subjects under four different real-world problem scenarios: (i) Estimating the probability of cancer in a mammogram given the relevant evidence from a computer-aided cancer detection system, (ii) estimating the probability of drunkenness based on breathalyzer evidence, and (iii & iv) estimating the probability of an enemy sniper based on two different sets of evidence from a drone reconnaissance system. In each case, we quantitatively characterized the contributions of the various potential explanatory variables to the subjects’ probability judgements. We found that while the various explanatory variables together accounted for about 30 to 45% of the overall variance of the subjects’ responses depending on the problem scenario, no single factor was sufficient to account for more than 53% of the explainable variance (or about 16 to 24% of the overall variance), let alone all of it. Further analyses of the explained variance revealed the surprising fact that no single factor accounted for significantly more than its ‘fair share’ of the variance. Taken together, our results demonstrate quantitatively that it is statistically untenable to attribute the errors of probabilistic judgement to any single cause, including base rate neglect. A more nuanced and unifying explanation would be that the actual biases reflect a weighted combination of multiple contributing factors, the exact mix of which depends on the particular problem scenario.

Dataset Information

Diabetes Enhances the Proliferation of Adult Pancreatic Multipotent Progenitor Cells and Biases Their Differentiation to More Beta-Cell Production

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets