The two-bucket problem of unproven stem cell interventions

The two-bucket problem of unproven stem cell interventions (SCIs) continues to bifurcate good (ethical) from bad (unethical) practices in the translation of stem cell medicine in ways that divert attention from other salient and challenging questions. It causes scholars to focus narrowly on reprimanding bad actors through legal and regulatory approaches and distracts from other important considerations such as how best to balance evidence with unmet patient needs and address misinformation about unproven stem cell interventions potentially changing patient behavior. The stem cell science community needs to consider a range of ethical practices and aim to address important questions that have yet not received sufficient consideration.

[Research Progress on Individual Identification Using Forensic Imaging Data under the Influence of Evidence Rule]

With the progress and development of the DNA test and imaging technique, and the evolution of evidence rule which bring the discussions about whether the individual identification using imaging data is outdated, and other disputes such as whether radiologic evidence could be suitable for contemporary evidence and be used to solve the posture difference of imaging test. This article summaries the domestic and foreign researches of individual identification using imaging data in the past 20 years and reviews the problems above.

Use of Anecdotal Occurrence Data in Species Distribution Models: An Example Based on the White-Nosed Coati (Nasua narica) in the American Southwest

Simple Summary

We evaluated the influence of occurrence records with different reliability on predicted distribution of a unique, rare mammal in the American Southwest, the white-nosed coati (Nasua narica). We concluded that occurrence datasets that include anecdotal records can be used to infer species distributions, providing such data are used only for easily-identifiable species and based on robust modeling methods such as maximum entropy. Use of a reliability rating system is critical for using anecdotal data.

Abstract

Species distributions are usually inferred from occurrence records. However, these records are prone to errors in spatial precision and reliability. Although influence of spatial errors has been fairly well studied, there is little information on impacts of poor reliability. Reliability of an occurrence record can be influenced by characteristics of the species, conditions during the observation, and observer’s knowledge. Some studies have advocated use of anecdotal data, while others have advocated more stringent evidentiary standards such as only accepting records verified by physical evidence, at least for rare or elusive species. Our goal was to evaluate the influence of occurrence records with different reliability on species distribution models (SDMs) of a unique mammal, the white-nosed coati (Nasua narica) in the American Southwest. We compared SDMs developed using maximum entropy analysis of combined bioclimatic and biophysical variables and based on seven subsets of occurrence records that varied in reliability and spatial precision. We found that the predicted distribution of the coati based on datasets that included anecdotal occurrence records were similar to those based on datasets that only included physical evidence. Coati distribution in the American Southwest was predicted to occur in southwestern New Mexico and southeastern Arizona and was defined primarily by evenness of climate and Madrean woodland and chaparral land-cover types. Coati distribution patterns in this region suggest a good model for understanding the biogeographic structure of range margins. We concluded that occurrence datasets that include anecdotal records can be used to infer species distributions, providing such data are used only for easily-identifiable species and based on robust modeling methods such as maximum entropy. Use of a reliability rating system is critical for using anecdotal data.