Combined Chondroitinase and KLF7 Expression Reduce Net Retraction of Sensory and CST Axons from Sites of Spinal Injury

Axon regeneration in the central nervous system is limited both by inhibitory extracellular cues and by an intrinsically low capacity for axon growth in some CNS populations. Chondroitin sulfate proteoglycans (CSPGs) are well-studied inhibitors of axon growth in the CNS, and degradation of CSPGs by chondroitinase has been shown to improve the extension of injured axons. Alternatively, axon growth can be improved by targeting the neuron-intrinsic growth capacity through forced expression of regeneration-associated transcription factors. For example, a transcriptionally active chimera of Krüppel-like Factor 7 (KLF7) and a VP16 domain improves axon growth when expressed in corticospinal tract neurons. Here we tested the hypothesis that combined expression of chondroitinase and VP16-KLF7 would lead to further improvements in axon growth after spinal injury. Chondroitinase was expressed by viral transduction of cells in the spinal cord, while VP16-KLF7 was virally expressed in sensory neurons of the dorsal root ganglia or corticospinal tract (CST) neurons. After transection of the dorsal columns, both chondroitinase and VP16-KLF7 increased the proximity of severed sensory axons to the injury site. Similarly, after complete crush injuries, VP16-KLF7 expression increased the approach of CST axons to the injury site. In neither paradigm however, did single or combined treatment with chondroitinase or VP16-KLF7 enable regenerative growth distal to the injury. These results substantiate a role for CSPG inhibition and low KLF7 activity in determining the net retraction of axons from sites of spinal injury, while suggesting that additional factors act to limit a full regenerative response

Network Visualization of a Retracted Article: Repeated Proliferation of Error through Citation Networks

Retraction is used as an optimum tool to uphold and safe-guide the integrity of scholarly literature. However, knowingly or unknowingly the authors build the work on these false claims by citing the retracted articles. Such dependencies on retracted articles may become implicit and indirect causing profound and long-lasting threat to the credibility of the literature. Consequently, it is important to detect and analyze such threats. The article aims to demonstrate dependency of citing articles on retracted article with reference to the rest of the literature. A case study of highly cited (as reported by retraction watch) retracted article ”Spontaneous human adult stem cell transformation” published in Cancer Research in 2005 by Rubio, D as lead author is visualized in terms of bibliographic coupling of citing journals and network and density visualizations of co-citations of authors. The study concludes that there is high-order citation dependency of scientific literature on retracted article

The Ripple Effect of Retraction on an Author's Collaboration Network

Scientists involved in scientific misconduct may face social stigmatization, leading to isolation and limited opportunities for collaboration. The reputation of every individual is reflected on the team, as the fraud attempted by any member will be reflected on the team. Earlier studies pointed out the impact of citation penalty on the prior work of coauthors, the effect of retraction on a co-author's research career, and stigmatization through mere association. This paper explores the formation and dynamics of the networks of authors who faced retractions and their "innocent coauthors" who never faced retractions in their careers. Leveraging a dataset of 5972 retracted papers involving 24209 authors, we investigate whether scientific misconduct reduces collaborative ties of misconducting authors as opposed to those who never faced allegations of academic misconduct. We observe that the network structure of authors involved in retractions does not change significantly over the years compared to that of the "innocent coauthors". Our results suggest that stigmatization rarely affects the collaboration network of stigmatized authors. Our findings have implications for institutions adopting stringent measures and fostering ethical practices research

The Dynamics of Retraction in Epistemic Networks

Sometimes retracted or thoroughly refuted scientific information is used and propagated long after it is understood to be misleading. Likewise, sometimes retracted news items spread and persist, even after it has been publicly established that they are false. In this paper, we use agent-based models of epistemic networks to explore the dynamics of retraction.In particular, we focus on why false beliefs might persist, even in the face of retraction.Surprisingly, we find that in some cases delaying retraction may increase its impact. We also find that retractions are most successful when issued by the original source of misinformation rather than a separate source

Retraction: the “other face” of research collaboration?

The last two decades have witnessed the rising prevalence of both co-publishing and retraction. Focusing on research collaboration, this paper utilizes a unique dataset to investigate factors contributing to retraction probability and elapsed time between publication and retraction. Data analysis reveals that the majority of retracted papers are multi-authored and that repeat offenders are collaboration prone. Yet, all things being equal, collaboration, in and of itself, does not increase the likelihood of producing flawed or fraudulent research, at least in the form of retraction. That holds for all retractions and also retractions due to falsification, fabrication, and plagiarism (FFP). The research also finds that publications with authors from elite universities are less likely to be retracted, which is particularly true for retractions due to FFP. China stands out with the fastest retracting speed compared to other countries. Possible explanations, limitations, and policy implications are also discussed

The Dynamics of Retraction in Epistemic Networks

Sometimes retracted or thoroughly refuted scientific information is used and propagated long after it is understood to be misleading. Likewise, sometimes retracted news items spread and persist, even after it has been publicly established that they are false. In this paper, we use agent-based models of epistemic networks to explore the dynamics of retraction.In particular, we focus on why false beliefs might persist, even in the face of retraction.Surprisingly, we find that in some cases delaying retraction may increase its impact. We also find that retractions are most successful when issued by the original source of misinformation rather than a separate source