PubMed

For clarification of this abstract, it may be worth noting that K-Lysine acetyltransferase 2a (Kat2a) is more widely known by its former name General control of amino-acid synthesis 5 (Gcn5) or General control of amino-acid synthesis 5 like 2 (Gcn5l2). http://www.ncbi.nlm.nih.gov/gene/14534

I am very happy to see more published information about this topic. I have been speaking professionally abut this topic for 10 years and it is becoming increasingly recognized as to it's importance in the management of MS patients. This article confirms the often unrecognized frequency of this issue. When MS patients say they "are tired all the time," we need to think about the details. Physical fatigue, cognitive fatigue, psychological fatigue (depression) and sleepiness may all be part of this complaint.

Your spatial-temporal correlation is especially suggestive for the pathophysiology expected in multiple neuropsychiatric diagnostic categories. Further work in animal models on measures of action potential speed/velocity are expected to reveal abnormalities in such neuropsychiatric categories. Best wishes, Joe Ray Newton

Readers should note that the whole genome-profiling in this study used outbred mice, with a sample size of n=4 per group. In my opinion, this is a very serious limitation, as it will result in the identification of many differences between groups that are simply due to the underlying genetic variation of the mice being tested, and are unrelated to nutrition status.

The authors cite our paper (Buehler E, 2012) as evidence that “…pools of siRNA targeting different mRNAs, such as those used in libraries, results in increased off-target effects”. Unfortunately, that sentence is not supported by our paper. The method demonstrated in our paper was applied to an arrayed screen of individual siRNAs in which there were no pools, and no conclusions about pooling of siRNAs can be reached from that manuscript. Furthermore, the authors state that “The use of this siRNA pool allows avoiding too high concentration of each single siRNA and thus prevents off-target effects” and cite Jackson AL, 2010 to support this. Again, this assertion is not supported by the cited reference. Jackson AL, 2010 states that “Pooling of multiple siRNAs to the same target may help to reduce off-target silencing, due to competition among the siRNAs in the pool” (emphasis added). No evidence exists to support the claim that pools 3 or 4 siRNAs will prevent off-target effects. To the contrary, we have demonstrated previously that pooling siRNAs does not generate more reproducible phenotypes than single siRNAs (see Marine S, 2012, Figure 1, B and C) and that pools of siRNAs can and do generate many off-target phenotypes, which can then be confirmed by deconvolution of those pools (see Marine S, 2012, Figure 2). Unfortunately, the authors base most of their conclusions on experiments using a single reagent (a pool of four different siRNAs targeting CDT2) and a single non-silencing control. This means that many or all of the phenotypes they observed experimentally may be due to siRNA off-target effects (see Chung HY, 2014 for a case study in how off-target effects can result in false positives). This is not to say that their conclusions are incorrect, only that I believe that RNAi experiments require multiple independently tested reagents and/or matched controls to guard against the false positives due to off-target effects that are so frequent in these experiments.

This study strongly endorses the hypothesis that counteracting neurohormonal hyperactivation represents a cornerstone for the treatment of heart failure. Remarkably, the Authors did not provide any data on the smoking status of the patients nor on catecholamine levels, which I believe would contribute compelling pathophysiological insights about the modulation of autonomic nervous system by neprilysin/angiotensin receptor inhibition. Indeed, cigarette smoking has been shown to increase catecholamine release, generating important effects on cardiovascular regulation essentially via sympathetic nervous system activation (1). Supporting this view, when examining the diabetic population (one third of the enrolled patients) no significant difference was found in the specific outcome ‘death from cardiovascular causes’. This finding could be at least in part ascribable to the autonomic neuropathy and neurovascular dysfunction described in diabetes mellitus (2). In this sense, an analysis that takes into account the duration of diabetes and therapy [i.e. insulin vs oral hypoglycemics (3)] in this population would also be interesting to the Reader.

References 1. Grassi G, Seravalle G, Calhoun DA, et al. Mechanisms responsible for sympathetic activation by cigarette smoking in humans. Circulation 1994;90:248-53. 2. Vinik AI, Maser RE, Mitchell BD, Freeman R. Diabetic autonomic neuropathy. Diabetes care 2003;26:1553-79. 3. Sardu C, Marfella R, Santulli G. Impact of diabetes mellitus on the clinical response to cardiac resynchronization therapy in elderly people. J Cardiovasc Transl Res. 2014 Apr;7(3):362-8.

Gaetano Santulli, MD, PhD Columbia University Medical Center, New York, NY, USA

To Whom It May Concern:

We have reviewed the concerns regarding some of the images presented in our study brought up by Paul Brookes on PubMed and Derek Lowe on his blog. In the wake of numerous controversial studies in the stem cell field, we appreciate the scrutiny of our results as skepticism plays a critical role in the progression of scientific research.

We have addressed all of the concerns raised on the internet regarding duplication of images and cropping of western blots and detail these responses separately.

First, regarding the similar radial contrast patterns in Figure 1C and 2D when black images are overexposed, we now provide high magnification versions of these images showing that while the radial contrast is similar between images (as would be expected when taking images from an essentially blank field on the same microscope with the same detector), there are clear differences observable upon higher magnification, demonstrating that these blank images were acquired independently.

Also, we have now provided all of the original western blots to the Journal that can be published in an erratum if the Journal deems this necessary. There were no sign of splicing or cropping of these original western data in Figure 4C, and we cut out the unnecessary part of images for the display on the limited area of paper in Figure 4F.

Finally, with regard to the image duplication of the brightfield micrograph of proliferating fibroblasts in Figure 2b: Yes, these are the same image, because this is the Time 0 timepoint of the experiment, prior to induction of EMF and factor infection. This began as a single culture at Time 0, after which half of the culture was exposed to EMF and the other half (control) was not (all in the presence of the Yamanaka factors). It is unclear to us why this is a concern for Paul Brookes, as he asserts this image was used to ‘represent different conditions’, however at Time 0, prior to the induction of EMF, these are in fact the same condition.

We are more than happy to provide all original images and discussion regarding these points in an erratum to the manuscript if the Journal deems it to be necessary.

On another note, we would like to point out significant errors made by Paul Brookes and Derek Lowe in their respective blogs in their interpretation of our study. Brookes states “in the wake of the STAP stem cell controversy, a paper claiming that iPSCs can be made using magnetic fields deserves special scrutiny”, and Lowe states “Yep, this paper says that stem cells can be produced from ordinary somatic cells by exposure to electromagnetic fields”. To us this suggests that neither Brookes nor Lowe actually read our manuscript, and rather just began altering contrast of images in the paper to find what they perceive as discrepancies.

Nowhere in our manuscript do we claim “iPSCs can be made using magnetic fields”. This would be highly suspect indeed. Rather, we demonstrate that in the context of highly reproducible and well-established reprogramming to pluripotency with the Yamanaka factors (Oct4, Sox2, Klf4, and cMyc/or Oct4 alone), EMF influences the efficiency of this process. Such a result is, to us, not surprising given that EMF has long been noted to have effects on biological system(Adey 1993, Del Vecchio et al. 2009, Juutilainen 2005)(There are a thousand of papers for biological effects of EMF on Pubmed) and given that numerous other environmental parameters are well-known to influence reprogramming by the Yamanaka factors, including Oxygen tension (Yoshida et al. 2009), the presence of Vitamin C (Esteban et al. 2010), among countless other examples.

For individuals such as Brookes and Lowe to immediately discount the validity of the findings without actually attempting to reproduce the central experimental finding is not only non-scientific, but borders on slanderous. We suggest that these individuals take their skepticism to the laboratory bench so that something productive can result from the time they invest prior to their criticizing the work of others.

“Often those that criticize others reveal what he himself lacks.” ― Shannon L. Alder

http://i.imgur.com/XgKBX47.jpg?1

http://i.imgur.com/gvZdZAQ.jpg

http://i.imgur.com/ljqPnxU.jpg

http://i.imgur.com/dEB1aoX.jpg

JP Kim

JONGPIL KIM, Ph.D. Assistant Professor Dept of Biomedical Engineering Dongguk University Seoul, Korea Tel: 82-02-2260-3371 Fax: 82-02-2260-8726 Email: jpkim153@dongguk.edu, jk2316@gmail.com

The abstract uses 2 nearly identical rs#s, one of which is an error. rs1059111 appears to be correct, rs105911 appears to be a typo

The cell lines used here - HEp-2 and KB - are both known to be cross-contaminated. Unfortunately, that means that both of these models are actually HeLa, from cervical carcinoma.

HEp-2 and KB are widely used in the literature as models for head and neck SCC, even though they are not appropriate models for this tissue type. Always be careful to test cell lines to check that they are not cross-contaminated, using a consensus method such as short tandem repeat (STR) profiling.

For a list of known cross-contaminated or otherwise misidentified cell lines, see http://iclac.org/databases/cross-contaminations/.

The suggestion here that Tan IIA might be an anticancer agent for oral cancer relies on a single cell line - KB. Unfortunately, KB has been shown to be cross-contaminated by HeLa and so is a misidentified cell line. KB cells are actually from cervical cancer, not oral cancer.

For a list of known misidentified cell lines, see http://iclac.org/databases/cross-contaminations/.

KB is not an OSCC cell line - KB cells are actually HeLa, from cervical adenocarcinoma. Cross-contamination of KB was discovered by Stanley Gartler back in 1967. Unfortunately, KB is still widely used as a model for oral cancer. Cross-contaminated cell lines are extensively used in the scientific literature, with many scientists not aware of this important problem.

A list of cross-contaminated or otherwise misidentified cell lines can be found at http://iclac.org/databases/cross-contaminations/.

The skepticism of Dr. Berthelsen is well taken. However, contrary to his expectation, the results of our study with its primary endpoint troponin release have already been replicated, see Candilio L, 2014.

The authors quite correctly identify that making prior imaging available to the current institution and formally summarizing their findings as one of the greatest opportunity to provide value to the health care system in order to avoid unnecessary repeat examinations. When patients are transferred between providers the referring physician commonly summarizes the case and its course in discharge notes. In radiology, however, the chore of collecting and compiling the performed radiology is usually done at the receiving hospital. It stands to reason that if the equivalent of radiological discharge notes instead are created at the department performing the examinations, the quality of the summaries must be improved, as well as the content of the transferred information, to the benefit of both clinicians and radiologists at the receiving hospital.

I would like to point out that I and multiple coauthors published a paper on pooling mitochondrial genomes and shotgun sequencing them for biodiversity analysis in 2000. I believe our paper should have been cited and discussed in this paper. See A case for evolutionary genomics and the comprehensive examination of sequence biodiversity. Pollock DD, Eisen JA, Doggett NA, Cummings MP. Mol Biol Evol. 2000 Dec;17(12):1776-88..

Abstract is pasted below:

Comparative analysis is one of the most powerful methods available for understanding the diverse and complex systems found in biology, but it is often limited by a lack of comprehensive taxonomic sampling. Despite the recent development of powerful genome technologies capable of producing sequence data in large quantities (witness the recently completed first draft of the human genome), there has been relatively little change in how evolutionary studies are conducted. The application of genomic methods to evolutionary biology is a challenge, in part because gene segments from different organisms are manipulated separately, requiring individual purification, cloning, and sequencing. We suggest that a feasible approach to collecting genome-scale data sets for evolutionary biology (i.e., evolutionary genomics) may consist of combination of DNA samples prior to cloning and sequencing, followed by computational reconstruction of the original sequences. This approach will allow the full benefit of automated protocols developed by genome projects to be realized; taxon sampling levels can easily increase to thousands for targeted genomes and genomic regions. Sequence diversity at this level will dramatically improve the quality and accuracy of phylogenetic inference, as well as the accuracy and resolution of comparative evolutionary studies. In particular, it will be possible to make accurate estimates of normal evolution in the context of constant structural and functional constraints (i.e., site-specific substitution probabilities), along with accurate estimates of changes in evolutionary patterns, including pairwise coevolution between sites, adaptive bursts, and changes in selective constraints. These estimates can then be used to understand and predict the effects of protein structure and function on sequence evolution and to predict unknown details of protein structure, function, and functional divergence. In order to demonstrate the practicality of these ideas and the potential benefit for functional genomic analysis, we describe a pilot project we are conducting to simultaneously sequence large numbers of vertebrate mitochondrial genomes.

The paper that Dr. Carter comments on should have been retracted 9 years ago. The urinary oxytocin (and AVP) data that provide the foundation of the research are fundamentally flawed, with the reported values being approximately one million times higher than prior (and subsequent) reports (see Anderson GM. Report of altered urinary oxytocin and AVP excretion in neglected orphans should be reconsidered. Journal of Autism and Developmental Disorders, 36:829-30, 2006). This was NOT due to a simple error in calculation or a misplaced decimal points. Rather, the analytical method used was non-specific. At the time, the authors defended their results as accurate and even provided some mass spectral data purporting to show that they were indeed measuring correct amounts of urinary oxytocin. In more recent research they have used a more specific method and now obtain results consistent with all other published work. However, they continue to reference this paper without mentioning the huge discrepancy. The paper and any of its conclusions should be disregarded. Just as regretable as the continued presence in the literature and continued citing of this misleading research is the fact that the editiorial board of PNAS has not seen fit to perform the retraction which is a necessary part of self-correcting science. This latter fact reflects very poorly on all papers published in PNAS as there does not seem to be any standard or threshold for retraction; the low quality of review that the paper received in the first place is also not reassuring when considering how much credence to give PNAS papers.

This paper has been subjected to a significant correction for duplicate publication: http://retractionwatch.com/2014/10/09/u-illinois-chancellor-earns-mega-correction-for-duplicate-publication/