N-methyl-d-aspartate (NMDA) receptor-dependent signaling, which is known to be involved in neuronal plasticity, in mouse primary visual cortex (V1) during visuomotor development. We used a local knockout of NMDA receptors and a photoactivatable inhibition of CaMKII in V1 during the first visual experience to probe for changes in neuronal activity in V1 as well as the influence on performance in a visuomotor task. We found that a knockout of NMDA receptors before, but not after, first visuomotor experience reduced responses to unpredictable stimuli, diminished the suppression of predictable feedback in V1, and impaired visuomotor skill learning later in life. Our results demonstrate that NMDA receptor-dependent signaling in V1 is critical during the first visuomotor experience for shaping visuomotor integration and enabling visuomotor skill learning.The experience of coupling between motor output and visual feedback is necessary for the development of visuomotor skills and shapes visuomotor integration in visual cortex. Whether these experience-dependent changes of responses in V1 depend on modifications of the local circuit or are the consequence of circuit changes outside of V1 remains unclear. Here, we probed the role of  Movement results in predictable sensory consequences. Through experience, the brain learns this transformation from motor output to sensory feedback. These transformations between different coding coordinate systems are referred to as internal models and are essential for the capacity of using sensory input to guide movements . When raGiven that V1 receives both the bottom-up visual input and signals consistent with a top-down prediction of visual feedback given movement  necessarN-methyl-d-aspartate (NMDA) receptors in V1 prior to first visuomotor experience. NMDA receptors are involved in a wide variety of different forms of plasticity  that can be rendered inactive by Cre recombination  or Flp (control) AAV vectors, both also driving expression of an mCherry fluorophore. Mice were sacrificed between P42 and P45, and V1 tissue was extracted and processed for single-nuclei RNA sequencing on the 10X Genomics platform . In both conditions, our sequencing data covered all of the major neuronal groups , 9 days prior to the start of the training sessions  that did not receive a Grin1 knockout but were dark-reared from birth. The ΔGrin1juv and Controljuv groups were dark-reared until P32. All three groups were initially exposed to closed-loop experience in a virtual reality setup (as described above) and subsequently trained to perform a virtual navigation task  promoter, the strongest changes were in mismatch and visual responses, while running onset responses were less affected , midazolam , and medetomidine . Analgesics were applied perioperatively  and postoperatively . Eyes were covered with ophthalmic gel (Virbac Schweiz AG). At P21, we injected approximately 100 nl of AAV2/1-Ef1α-Cre-T2A-mCherry vector at a titer of between 3.2 × 1010 GC/ml —5; AAV2/13 GC/ml  through For window implantations at P30, we performed a cranial window surgery by implanting a circular 4 mm glass coverslip bilaterally, following injections of approximately 200 nl of AAV vectors (AAV2/1-EF1α-GCaMP6f-WPRE or AAV2/1-EF1α-NES-jRGECO1a-WPRE) into V1, 2.5 mm lateral from lambda.In all experiments involving the virtual reality system, mice were head-fixed and mounted on a spherical treadmill, as described previously . In brieFirst visual and visuomotor exposure of the mice occurred in this virtual reality environment in the 12 days prior to imaging experiments. Mice were trained for 2 hr every other day  with closed-loop feedback between forward locomotion and backward visual flow in a virtual corridor with walls textured with vertical sinusoidal gratings . All twoFor the virtual navigation experiments , rotatiowhere θ(t) is the direction of running relative to the target, and v(t) is the running speed of the mouse. The intuition behind this index is to quantify performance as the fraction of distance traveled in the direction of the target, normalized by the total distance traveled. The second factor is added to reduce variability driven by a short time spent running, as is typical in early training sessions.Two-photon imaging of L2/3 neurons in V1 was performed as described previously . In brietm2StlGrin1 mouse line . We followed a standardized formaldehyde-fixed paraffin-embedding protocol. In brief, mice were transcardially perfused with phosphate buffered saline (PBS), followed by perfusion with a solution of 4% paraformaldehyde (PFA) in PBS. Brains were isolated, post-fixed overnight in 4% PFA, paraffinized for 24 hr, and cut at 5 µm using a microtome (Thermo Fisher). Slices were stained using hematoxylin to mark cell bodies, and Mm-Grin1-O1  to label Grin1 mRNA. To ease identification of the knockout area in two-photon calcium imaging, a vector co-expressing a red fluorophore (mCherry) and Cre was used to induce the Grin1 knockout in most experiments. Due to a shortage of the correct vector, a subset (6 of 14) of the ΔGrin1adult experiments were performed without the mCherry fluorophore. For pharmacological NMDA receptor inhibition experiments   to inhibh tissue , we preptm2StlGrin1 mice (P21) were anesthetized, as described above, and injected with either AAV2/1- EF1α-Cre-T2A-mCherry or AAV2/1-EF1α-mCherry-IRES-Flpo at P21. Two injections, ~250 nl each, were made in V1 bilaterally. Mice were sacrificed for single-nuclei RNA sequencing between P41 and P45. Prior to nuclei isolation, mice were again anesthetized and perfused with carbogenated, ice-cold choline ACSF . After perfusion, mice were decapitated, and the brain was removed and placed into a Petri dish containing ice-cold choline solution. The neocortex was separated from the rest of the brain, and using an epifluorescent microscope, an area corresponding to V1 with visible mCherry expression was dissected and placed into a 1.5 ml RNase-free Eppendorf tube. The tube was then flash frozen in liquid nitrogen and stored at –80°C prior to nuclei isolation.Two 2, 20 mm Tricine-KOH, 1 mM DTT, 0.5 mM spermidine, 0.15 mM spermine, 1 protease inhibitor tablet  per 50 ml, 0.07% RNAse inhibitor [Promega], 0.4% bovine serum albumin [BSA]). The solution was then dounce homogenized 10 times with a loose pestle, 50 µl of 6% IGEPAL-630 was added to each sample, followed by homogenization with a tight pestle 5 times. The homogenized solution was passed through a 40 µm filter (Flowmi cell strainer) and combined with an equal volume of 50% iodixanol in diluent buffer . Samples were each transferred to a 13.2 ml Ultra-clear centrifuge tube (Beckman Coulter) and underlayered with 30% and then 40% iodixanol. Samples were centrifuged at 10,000 × g for 18 min at 4°C in a prechilled swinging bucket rotor. The interface between the 30 and 40% iodixanol solutions was collected. Then DAPI (1:1000) and DRAQ5 (Thermo Fisher) (1:200) were added to the sample fractions, and each sample was passed through a 30 µm filter (CellTrics).Nuclei isolation proceeded as previously described , with thIsolated fractions were immediately sorted with an MA900 cell sorter (Sony) using a 100 µm chip. To exclude debris, particles were selected by shape (back and forward scatter) to enrich the nuclei population. DRAQ5 and DAPI stains were also used during sorting to ensure purity and exclude doublets. Typically, between 70 and 90% of all events were nuclei. At the early stages of experiment development, samples were stained with DAPI and DRAQ5 and examined using fluorescence microscopy to confirm that sorted samples were enriched for nuclei. Samples were sorted directly into a PBS and BSA solution, and the final concentration of the BSA was 0.04%. In all instances, 14,000 nuclei were sorted. Samples were processed with the Chromium Single Cell Gene Expression kit. Gel bead-in-emulsion generation, reverse transcription, barcoding, cDNA amplification and purification were all in accordance with the manufacturer’s recommendations. Finalized libraries were sequenced on a NextSeq machine using the High-out 75-cycle paired-end protocol, to a read depth of approximately 15,000–20,000 reads per nucleus.Grin1 gene that is flanked by loxP sites in the tm2StlGrin1 mice. Features on the minus strand of this region were removed from the analysis.Initial processing was performed with the Cell Ranger software package (version 6.1.2). Mapping was performed against a custom genome and included intronic reads. The custom genome was constructed from the Genome Reference Consortium Mouse Build 39 with a version 104 GTF file. For mapping viral expression, an mCherry sequence (Addgene 237633) was amended as a separate chromosome. The GTF file was edited to include features corresponding to viral expression, as well as a portion of chromosome 2 , which corresponds to the part of the Raw feature barcode matrices were imported into R using the Scater package . Cells wCalcium imaging data were processed as described previously . In brie−2 cm/s. For analysis of average activity levels in closed-loop sessions . For all population onset responses, data were first averaged over onsets for each neuron and then averaged over neurons. Unless stated otherwise, shading and error bars indicate the standard error of the mean (SEM) across neurons. We did not test for normality of distributions. For analysis of onset responses , recordisessions , we calcsessions , we calcsessions , we calc This study demonstrates that the development of visuomotor mismatch signals in V1 as well as behavioral reactions to mismatches depend on NMDA receptors in V1 during early visual experience, suggesting a critical role of NMDA receptor-dependent plasticity within V1 in forming internal models that transform self-movement to visual experiences. The result will be of great interest to the neuroscience community. public reviews designed to be posted alongside the preprint for the benefit of readers; ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.Our editorial process produces two outputs: i) Decision letter after peer review:eLife. Your article has been reviewed by 2 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Andrew King as the Senior Editor. The reviewers have opted to remain anonymous.Thank you for submitting your article "Developmental plasticity in visual cortex is necessary for normal visuomotor integration and visuomotor skill learning" for consideration by The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.Essential revisions:This study examined the mechanism underlying the development of prediction-error related responses of neurons in the primary visual cortex evoked by mismatch between self-generated locomotor movement and visual feedback. The reviewers found that this study contains important results, in particular, a local mechanism involving NMDA receptors and CaMKII. The manuscript is written clearly and discusses various limitations of the study carefully. However, the reviewers have made various points that need to be clarified or discussed in more detail, and made several suggestions that will likely improve this work. We do not expect that addressing these issues will necessarily require additional experiments, although some points may benefit from them.In the following, we list a few essential points that the reviewers have identified. The detailed comments associated with these points are further described in the individual reviewers' comments below.1) Both reviewers raised the issue of the uncertainty of the site of action of NMDA receptors and CaMKII. The reviewers suggest some clarifications of which cell types or layers express Cre-recombinase used for conditional knockouts and some verification of gene knockouts. Are there any relationships between cellular responses and these factors? We recognize that these analyses can be difficult, but if the authors can include some data or discussion that addresses these points, it would be great to present them.2) The mismatch signals vary across "control" groups in different experiments. It is worrisome that this might be leading to inaccurate characterizations of the effects of particular manipulations. See Reviewer 1's comment for more details.3) From the presented data, it is difficult to know whether the altered neuronal responses and behaviors are due to a deficit in plasticity. While this is not an unreasonable argument, given the difficulty of excluding other mechanisms (e.g. bottom-up activation), it would be good to tone down the claim of plasticity (particularly as it is in the title).Reviewer #1 (Recommendations for the authors):This is a really nice set of experiments that help us understand where in the brain plasticity is happening as mice learn the sensory consequences of their actions. I think the question is very important and that the particular perturbations that were performed and the analyses are all appropriate. I also commend the authors on their recognition of the limits of their study in the Discussion – the limits are all reasonable. I don't have any new experiments that I would recommend, but see a suggested analysis (next paragraph) and a few other smaller points.do not need to do this analysis for me to recommend acceptance of this paper. I simply bring it up because I think it is a potential analysis that could help solidify the importance of NMDARs.Presumably not all V1 neurons expressed Cre-recombinase (which was necessary to interfere with NMDAR function). What did the distribution of mismatch signals look like in V1 of Grin1 mice? Do some neurons show perfectly normal mismatch signals? Taking that just a bit further, is there enough statistical power to analyze whether there is any correspondence between the magnitude of mismatch signals and the active/inactive status of NMDARs at the single-cell level? I recognize that this might be a difficult analysis to do with low N's of trials. Also, it's quite possible that what we're observing here is network-level learning, and that you may not see cell-to-cell changes in mismatch signals that correspond with NMDAR suppression . However, given the findings of excitatory-cell-specific CaMKII inactivation, it's plausible that the function of NMDARs within single L2/3 cells might allow for the continued single-cell computation of mismatch signals to persist, even in the absence of functional NMDARs in neighboring cells. Therefore, if there was a correspondence between NMDAR function and mismatch at the single cell level, this would be quite strong evidence pointing toward the importance of functional NMDARs in single cells. The authors The mismatch signals across different "control" groups in this paper are quite different, and I worry that perhaps this is leading to inaccurate characterizations of the effects of particular manipulations. In particular, the mismatch signal in the control group from the paAIP2-PV experiments  is almost non-existent. These data are used to show that blocking CaMKII in PV cells leads to an increased mismatch responses and is therefore different from blocking CaMKII in SST cells . But if these mice were compared against a different control group, there could be either no effect or the exact opposite effect. I would find it helpful if the authors spoke to the variability in results from distinct control groups in the results or the discussion. Alternatively, the authors could show that their findings hold up to some other analysis in which a more consistent control condition is used (if possible).Line 109 describes correlations between neural activity and optic flow and locomotion. These findings make sense to me if they were analyzed in the open-loop variant, but I did not see in either the Methods or the Results whether we switched to a new experiment at this point (the previous data were presumably about closed loop).Line 205 begins to describe the optical strategy for suppression of NMDAR function. When I got to line 314 I learned that the blue illumination was delivered during all motor-sensory experience, but line 205 led me to believe that brief blue light led to a permanent shift. This was particularly confusing when I got to line 257, which told me that we could study the same mice without CaMKII inhibition. The authors should do a bit more methodological hand holding in the results and in the Methods.Line 138, did the adult Grin1 mice still have their NMDARs silenced when the VR acclimation/training started? It's unclear from the paper. (I think this is the case but would be great to have it spelled out).In Figure 4E, I can't figure out what each dot represents. At first I thought each dot was a mouse, but it seems like too many dots for the number of mice included in the study groups. Once I know what the dots represent, I will be interested in the overlap across populations. For example, many of the Grin1-Juv dots are above the Grin1-adult dots and are on par with the Control-Juv dots. Is there an explanation for this? Was the NMDAR perturbation more quantifiably efficacious for some mice than for others?Reviewer #2 (Recommendations for the authors):Major issues1) Presented data do not convincingly support the direct role of NMDAR or CamK2 dependent plasticity for visuomotor integration associated with first visual experience. As grating onset response was reduced by juvenile V1 NMDAR knock-out or CaMK2 manipulations in addition to mismatch onset response, it is totally possible that diminished mismatch response is secondary to diminished visual response due to plasticity deficits of bottom-up visual input connectivity only without requiring plasticity in bottom-up/top-down integration. This possibility needs to be discussed, and title of the paper and overall interpretation of the data should be revised accordingly.2) Manipulations of Grin and CaMK2 led to very different V1 responses for grating onset response . One possibility not discussed was that manipulation in single cell type  vs multiple cell types  might lead to different outcomes. Ideally, it would be informative to manipulate Grin and CaMK2 in same cell types to make better comparisons of the two mechanisms. At least, it would be informative to check if Grin KO is happening in both pyramidal and SST cells in Figure 1.3) At the level of activity correlation visual flow, results shown in Fig6 are consistent with the unique role of SST in contributing to the mismatch response deficits. To increase the coherence of the data among different experiments, I suggest showing data in Fig6A as in Fig1I and Fig2E. Similarly, Fig1I and Fig2E can include bar graphs similar to Fig6A.Other points4) Quantification of Grin knock-down is missing for both juvenile  and adult  knock out studies. While one representative image is shown in Figure 1, knock down level is not quantified. Quantification in the adult mice is also important as Grin1 is likely less expressed compared to young mice. It is also not described at what age AAV was injected and at what age animals were sacrificed for in situ hybridization. It would be important to match the age to the experimental conditions to ensure timely knock-down.5) Comparison between dark rearing+Juvenile Grin knock out condition  vs normal rearing+adult Grin KO  is not straight forward without another control condition . This limitation should be discussed.6) Dark rearing of mice from birth is known to delay the timecouse of V1 critical period by keeping V1 circuits immature. It is unclear how such changes induced by dark rearing confound the findings reported in this study. Without dark rearing, it is likely that the physiological experience-dependent sensory-motor integration happens earlier during development. I suggest to discuss these points in Discussion section.7) Animal number information should be provided for each experiments instead of grouping together in Table S2 to ensure that data is not biased from limited number of mice. Essential revisions:This study examined the mechanism underlying the development of prediction-error related responses of neurons in the primary visual cortex evoked by mismatch between self-generated locomotor movement and visual feedback. The reviewers found that this study contains important results, in particular, a local mechanism involving NMDA receptors and CaMKII. The manuscript is written clearly and discusses various limitations of the study carefully. However, the reviewers have made various points that need to be clarified or discussed in more detail, and made several suggestions that will likely improve this work. We do not expect that addressing these issues will necessarily require additional experiments, although some points may benefit from them.In the following, we list a few essential points that the reviewers have identified. The detailed comments associated with these points are further described in the individual reviewers' comments below.1) Both reviewers raised the issue of the uncertainty of the site of action of NMDA receptors and CaMKII. The reviewers suggest some clarifications of which cell types or layers express Cre-recombinase used for conditional knockouts and some verification of gene knockouts. Are there any relationships between cellular responses and these factors? We recognize that these analyses can be difficult, but if the authors can include some data or discussion that addresses these points, it would be great to present them.This is an excellent question and we had previously attempted to address this by looking for a relationship between mCherry expression and functional effects in the knockout data (the vector used to induce the knockout was an AAV2/1-EF1α-Cre-T2A-mCherry). However, we failed to detect any systematic relationship. We speculated that this might be the consequence of the fact that the knockout is non-linearly related to Cre expression , while the mCherry measurement is linear in expression level. Thus, it is possible that even in cells in which we did not detect any mCherry, there was a complete knockout. On top of this, there is a correlation between mCherry and GCaMP responses that is driven by differences in imaging quality that interferes with this analysis .Grin1 mRNA (using an in-situ hybridization probe that targets a region of mRNA that is within the region of the Grin1 gene that is knocked out). Even with a very low threshold for what we counted as “Grin1-positive”  for what we define as a punctum), we found that less than 1% of the cells at an injection site were still Grin1 positive.To determine the strength of the knockout, we first quantified the in-situ hybridization data. We selected a random set of 500 µm by 500 µm regions either at injection sites or away from injection sites and counted the number of cells that stained positive for Grin1 expression in all neuron types. Please note, we found some remaining Grin1 reads also in the knockout samples, but we suspect this is mainly the consequence of the dissected tissue also containing cells that were outside the region of knockout.To confirm this result, and to test whether the knockout spared certain neuron types, we performed a single nuclei sequencing experiment . Mice received an injection of either Cre (knockout) or Flp (control) AAV vectors at P21, before being sacrificed between P41 and P45 for single nuclei sequencing. We were able to identify all major cortical neuron types in both knockout and control data  and found that the knockout reduced 2) The mismatch signals vary across "control" groups in different experiments. It is worrisome that this might be leading to inaccurate characterizations of the effects of particular manipulations. See Reviewer 1's comment for more details.There are likely two things that contributed to this variability across control groups. First, population average mismatch responses by imaging site are quite variable see . We werejuvΔGrin1 mice and the adultΔGrin1 mice and refer to these as “juvenile control” and “adult control” in the following passage. The overall effects in the ΔGrin1 data were much smaller than in the paAIP2 data, and consequently any putative interhemispheric compensation is also likely smaller. A few findings may stand out. First, mismatch responses were larger in the adult mice than in juvenile mice, but this is perhaps not surprising as mismatch responses increased with experience . Second, in the group of juvenile mice that received CaMKII inhibition in excitatory neurons, all responses appeared to be much faster in rise time (in both inhibited and control hemispheres). Why this is, we do not know, however, the key finding here is that mismatch responses in the inhibited hemisphere were smaller than those in the control hemisphere. While only just, this was also true if we compared peak amplitude against juvenile control. However, given that the control hemisphere responses were clearly also influenced by the inhibition of paAIP2 in the contralateral hemisphere, we suspect the better comparison is the within mouse control. Third, in mice that received CaMKII inhibition in PV interneurons, the control hemisphere mismatch responses were substantially reduced compared to those in the juvenile control. But again, the paAIP2 inhibited mismatch response was larger than both that in the control hemisphere as well as that in the juvenile control. Thus, while there are many aspects of these effects we do not fully understand yet, we don’t think we are inaccurately characterizing the mismatch response changes by using the within animal controls. We have expanded on the discussion of these problems in the manuscript.In 3) From the presented data, it is difficult to know whether the altered neuronal responses and behaviors are due to a deficit in plasticity. While this is not an unreasonable argument, given the difficulty of excluding other mechanisms (e.g. bottom-up activation), it would be good to tone down the claim of plasticity (particularly as it is in the title).We have changed the title and abstract of the manuscript as suggested and now discuss alternative mechanisms more thoroughly.Reviewer #1 (Recommendations for the authors):This is a really nice set of experiments that help us understand where in the brain plasticity is happening as mice learn the sensory consequences of their actions. I think the question is very important and that the particular perturbations that were performed and the analyses are all appropriate. I also commend the authors on their recognition of the limits of their study in the Discussion – the limits are all reasonable. I don't have any new experiments that I would recommend, but see a suggested analysis (next paragraph) and a few other smaller points.We thank the reviewer for the help in improving the manuscript. Please note, to ease reference, we have added numbering to the following points.Presumably not all V1 neurons expressed Cre-recombinase (which was necessary to interfere with NMDAR function). What did the distribution of mismatch signals look like in V1 of Grin1 mice? Do some neurons show perfectly normal mismatch signals? Taking that just a bit further, is there enough statistical power to analyze whether there is any correspondence between the magnitude of mismatch signals and the active/inactive status of NMDARs at the single-cell level? I recognize that this might be a difficult analysis to do with low N's of trials. Also, it's quite possible that what we're observing here is network-level learning, and that you may not see cell-to-cell changes in mismatch signals that correspond with NMDAR suppression . However, given the findings of excitatory-cell-specific CaMKII inactivation, it's plausible that the function of NMDARs within single L2/3 cells might allow for the continued single-cell computation of mismatch signals to persist, even in the absence of functional NMDARs in neighboring cells. Therefore, if there was a correspondence between NMDAR function and mismatch at the single cell level, this would be quite strong evidence pointing toward the importance of functional NMDARs in single cells. The authors do not need to do this analysis for me to recommend acceptance of this paper. I simply bring it up because I think it is a potential analysis that could help solidify the importance of NMDARs.This is an interesting point and we had previously attempted to perform an analysis along the lines of what the reviewer is suggesting. We split the neurons based on the expression levels of mCherry (the Cre vector we used co-expressed mCherry) to test whether neurons with high levels of mCherry exhibited larger effects than those with low or no detectable expression of mCherry. The argument being – as the reviewer suggests – that neurons that expressed mCherry have a knockout of NMDA receptors while those that did not, had no knockout. The issue we encountered was that there was a positive correlation between mCherry expression and GCaMP signal strength that dominated the effect . We could not find a way to disentangle this effect with a potential cell specific effect of the knockout. In addition, given that the Cre effect is non-linear , we thought it conceivable that the knockout may be complete in that it affected all neurons at the injection site of the Cre vector.Grin1 exon targeted by the knockout in the injection site was below 1%. To confirm that all neuron types were affected equally by this manipulation, we then performed single nuclei sequencing on knockout tissue and found that Grin1 mRNA levels were reduced homogeneously across all major cortical neuron types .What we then proceeded to do, was estimate the fraction of neurons in an injection site that were affected by the knockout. We first quantified this in our in-situ hybridization data  and found that the number of cells positive for the While we do think that the effect is likely a mixture of network and neuron specific effects, we refrained from speculating one way or the other given that the knockout appeared to be quite complete.The mismatch signals across different "control" groups in this paper are quite different, and I worry that perhaps this is leading to inaccurate characterizations of the effects of particular manipulations. In particular, the mismatch signal in the control group from the paAIP2-PV experiments  is almost non-existent. These data are used to show that blocking CaMKII in PV cells leads to an increased mismatch responses and is therefore different from blocking CaMKII in SST cells . But if these mice were compared against a different control group, there could be either no effect or the exact opposite effect. I would find it helpful if the authors spoke to the variability in results from distinct control groups in the results or the discussion. Alternatively, the authors could show that their findings hold up to some other analysis in which a more consistent control condition is used (if possible).We have expanded on the discussion of variability in the control groups as suggested. Please also see response to essential review comment 2 above related to this point.Line 109 describes correlations between neural activity and optic flow and locomotion. These findings make sense to me if they were analyzed in the open-loop variant, but I did not see in either the Methods or the Results whether we switched to a new experiment at this point (the previous data were presumably about closed loop).Please excuse the inaccuracy – the reviewer is absolutely correct. These analyses were done on the open-loop data. We have rephrased the corresponding passage to correct this.Line 205 begins to describe the optical strategy for suppression of NMDAR function. When I got to line 314 I learned that the blue illumination was delivered during all motor-sensory experience, but line 205 led me to believe that brief blue light led to a permanent shift. This was particularly confusing when I got to line 257, which told me that we could study the same mice without CaMKII inhibition. The authors should do a bit more methodological hand holding in the results and in the Methods.We have rephrased and expanded as suggested.Line 138, did the adult Grin1 mice still have their NMDARs silenced when the VR acclimation/training started? It's unclear from the paper. (I think this is the case but would be great to have it spelled out).Grin1 KO mice had received a Grin1 knockout prior to the start of training on the VR setup . We have changed the passage to make this clearer as suggested.This is correct – the adult group of In Figure 4E, I can't figure out what each dot represents. At first I thought each dot was a mouse, but it seems like too many dots for the number of mice included in the study groups. Once I know what the dots represent, I will be interested in the overlap across populations. For example, many of the Grin1-Juv dots are above the Grin1-adult dots and are on par with the Control-Juv dots. Is there an explanation for this? Was the NMDAR perturbation more quantifiably efficacious for some mice than for others?This is a very good catch – each dot should indeed have been one mouse. As a result of a bug in our analysis code, most mice were included twice. “Early” and “late” timepoints are days 1 and 2, and days 6 and 7, respectively. For most of the mice the two time points were not combined but plotted separately. Please excuse the mistake.juv mice was similar to that in juvΔGrin1 mice. Thus, even without any variability in the effect size of the knockout, we would expect to have roughly this level of variability in juvΔGrin1 mice. To quantify the relationship between knockout efficacy and effect size would require substantially larger cohorts (or an assay with less mouse-to-mouse variability).Regarding the variability – this is likely driven predominantly by mouse-to-mouse variability in this metric. The variability in ControlReviewer #2 (Recommendations for the authors):Major issues1) Presented data do not convincingly support the direct role of NMDAR or CamK2 dependent plasticity for visuomotor integration associated with first visual experience. As grating onset response was reduced by juvenile V1 NMDAR knock-out or CaMK2 manipulations in addition to mismatch onset response, it is totally possible that diminished mismatch response is secondary to diminished visual response due to plasticity deficits of bottom-up visual input connectivity only without requiring plasticity in bottom-up/top-down integration. This possibility needs to be discussed, and title of the paper and overall interpretation of the data should be revised accordingly.This is absolutely correct, however, there are a few things we would like to note. First, to avoid a potential misunderstanding, we are working under the assumption that all layer 2/3 neurons establish an opposing balance between top-down and bottom-up input . Second, we used the concept of plasticity in the integration of bottom-up and top-down input to mean plasticity in either top-down input or bottom-up input, or both. The system needs to match opposing bottom-up and top-down inputs in L2/3 neurons to compute prediction error responses, but this can happen either by matching bottom-up input to a fixed top-down input, or vice versa, or by changing both. Thus, a deficit in bottom-up input connectivity onto L2/3 neuron would be consistent with our interpretation. An alternative, possibly along the lines of what the reviewer was suggesting, is that the NMDA knockout mediates its effects by virtue of reducing feed-forward input onto layer 4 neurons. We think this is unlikely as a knockout of NMDA receptors in L4 neurons does not alter visually evoked potentials in visual cortex, nor does it impair visual acuity of the mice, regardless of whether the knockout is congenital or postadolescent . We have rephrased and revised the manuscript to make this clearer.2) Manipulations of Grin and CaMK2 led to very different V1 responses for grating onset response . One possibility not discussed was that manipulation in single cell type  vs multiple cell types  might lead to different outcomes. Ideally, it would be informative to manipulate Grin and CaMK2 in same cell types to make better comparisons of the two mechanisms. At least, it would be informative to check if Grin KO is happening in both pyramidal and SST cells in Figure 1.Grin1 knockout, we have added the experiments and analyses shown in Figures 1F and 1G. In brief, the knockout seems to indeed affect all cell types similarly. This is likely due to the fact that the Cre effect is highly non-linear (i.e. one Cre protein suffices for a complete knockout), and that Ef1α promoter drives expression also in interneurons, albeit at low levels. The 1.3kb version of the CaMKII promoter we used to express the paAIP2 in excitatory neurons also drives expression in low levels in inhibitory neurons, similar to Ef1α. However, the effect of CaMKII inhibition is probably linear in the number of paAIP2 molecules, and hence indeed biased towards excitatory neurons. We expanded on this point in the discussion.To address the question of which cell types are targeted by the 3) At the level of activity correlation visual flow, results shown in Fig6 are consistent with the unique role of SST in contributing to the mismatch response deficits. To increase the coherence of the data among different experiments, I suggest showing data in Fig6A as in Fig1I and Fig2E. Similarly, Fig1I and Fig2E can include bar graphs similar to Fig6A.We chose not to present the data this way as we feel it distracts from the main points. The average visual flow correlation differences  are barely visible in the correlation scatter plots shown in Figures 2E and 3E . Conversely, the visual flow correlations of the NMDA knockout data only become relevant in the comparison to the correlations of the paAIP2 SST data, and this is all in Figure 7A . We have added the scatter plots to Other points4) Quantification of Grin knock-down is missing for both juvenile  and adult  knock out studies. While one representative image is shown in Figure 1, knock down level is not quantified. Quantification in the adult mice is also important as Grin1 is likely less expressed compared to young mice. It is also not described at what age AAV was injected and at what age animals were sacrificed for in situ hybridization. It would be important to match the age to the experimental conditions to ensure timely knock-down.We have added the information as requested and have added a more detailed quantification of the knockout using both in situ hybridization data and single nuclei sequencing data. See response to essential review point 1 in the summary above. With respect to the age matching of the knockout quantification, in the in situ analysis we have data from 2 mice, one was age matched to the juvenile experiments and one was age matched to the adult. The analysis shown in Figure 1F, split by the juvenile and adult, is shown in 5) Comparison between dark rearing+Juvenile Grin knock out condition  vs normal rearing+adult Grin KO  is not straight forward without another control condition . This limitation should be discussed.We have added this point to the discussion as suggested.6) Dark rearing of mice from birth is known to delay the timecouse of V1 critical period by keeping V1 circuits immature. It is unclear how such changes induced by dark rearing confound the findings reported in this study. Without dark rearing, it is likely that the physiological experience-dependent sensory-motor integration happens earlier during development. I suggest to discuss these points in Discussion section.This is correct, the dark rearing in our paradigm likely influences the timing of critical windows for plasticity. However, please note that the paradigm used in the current study was the same as that used in a previous study . There we show that this paradigm  resulted in increased prediction error responses in V1 . Thus, while there likely are changes in critical window timing, this should not change our conclusions we draw based on the data. We have added this point to the discussion as suggested.7) Animal number information should be provided for each experiments instead of grouping together in Table S2 to ensure that data is not biased from limited number of mice.1 and N2).We have added information on the number of mice for all experiments to Supplementary Table 1 . Visuomotor Coupling Shapes the Functional Development of Mouse Visual Cortex. Cell 30, 2555–2572.Fong, M.F., Finnie, P.S., Kim, T., Thomazeau, A., Kaplan, E.S., Cooke, S.F., and Bear, M.F. (2020). Distinct Laminar Requirements for NMDA Receptors in Experience-Dependent Visual Cortical Plasticity. Cerebral Cortex  108, 1194-1206.e5.Jordan, R., and Keller, G.B. (2020). Opposing Influence of Top-down and Bottom-up Input on Excitatory Layer 2/3 Neurons in Mouse Primary Visual Cortex. Neuron 38, 977–985.Sawtell, N.B., Frenkel, M.Y., Philpot, B.D., Nakazawa, K., Tonegawa, S., and Bear, M.F. (2003). NMDA receptor-dependent ocular dominance plasticity in adult visual cortex. Neuron 523, 2019–2042.Scheyltjens, I., Laramée, M.-E., Van den Haute, C., Gijsbers, R., Debyser, Z., Baekelandt, V., Vreysen, S., and Arckens, L. (2015). Evaluation of the expression pattern of rAAV2/1, 2/5, 2/7, 2/8, and 2/9 serotypes with different promoters in the mouse visual cortex. Journal of Comparative Neurology


Background: Breast cancer is the most common cancer in women worldwide and is the leading cause of death amongst women with cancer. One novel therapy used for breast cancer treatment constitutes non-contact electric fields and is called electro-capacitive cancer therapy (ECCT) with intermediate frequency and low intensity. The objective of this study was to examine the effect of ECCT on mammary tumors growth in rats and observing the immune responses that play a role in fighting the tumor.Methods: Female SD rats were used and divided into four groups, namely control (NINT), placebo (NIT), non- therapy (INT), and therapy (IT) groups with 6 biological replicates in each group. Rats in INT and IT groups were treated with 7,12-dimethylbenz[a]anthracene for mammary tumor induction. Only rats in NIT and IT groups were exposed to ECCT individually for 10 hours per day for 21 days. The size of all tumors was measured with a digital caliper. The distributions of PCNA, ErbB2, caspase-3, CD68, CD4, and CD8-positive cells were observed with immunohistochemistry and scoring with ImageJ.Results: The growth rate of mammary tumors in IT group was significantly lower (p<0.05) than that in INT group. The number of mitotic figures and the percentage of PCNA, caspase-3, and CD68-positive cells in IT group were significantly lower (p<0.05) than those in INT group. Conversely, the percentage of CD8-positive T cells in IT group was significantly higher (p<0.05) than that in INT group. Moreover, the CD4/CD8 ratio in IT group was found to have decreased. Some tumor tissues were blackened and detached from the surrounding tissue, resulting in an open wound which then healed upon exposure.Conclusions: Non-contact electric fields exposure showed inhibition on mammary tumor growth in rats while inducing CD8+ T cells, leading to tumor cell death and potentially helping wounds heal. Furthermore, of 18.1 million new cancer cases in 2018, around 2.1 million were breast cancer cases. This type of cancer is also the leading cause of death in women with cancer2. Commonly, the treatment of breast cancer is carried out in two ways. The first, termed local therapy, controls or removes the tumor in specific areas, such as through breast-conserving therapy and mastectomy that may be followed by radiotherapy. The second, called systemic therapy, uses the circulatory system in the body to inhibit cancerous cell growth, which spread in the afflicted parts of the body. This type of treatment includes chemotherapy, targeted therapy, and endocrine therapy3. However, breast cancer therapy applied so far often causes negative effects, such as the presence of pathophysiological mechanisms that cause chronic pain4 or the mechanism of multidrug resistance (MDR) in breast cancer cells as a reaction to chemotherapy6. Moreover, breast cancer therapies may attack certain normal cells or tissues, which result in toxicity symptoms7. A novel cancer therapy based on electric field exposure with intermediate frequency and low intensity called Tumor Treating Fields (TTFields) has been developed to prevent such negative effects of cancer therapy and still inhibit cancer growth. No toxic side effects or adverse events were found on animal tumor models nor patients under the exposure to this electric field-based cancer therapy, except for skin toxicity or dermatitis of low severity9.Breast cancer is the most common cancer among women in the world, with one in eight women being at risk of developing it10. As such, we have developed a type of non-contact electric field therapy using capacitive modality to avoid such injuries. In our previous study in a preclinical setting, cancer therapy, namely electro-capacitive cancer therapy (ECCT), using the non-contact electric fields with intermediate frequency (100 kHz) and low intensity (18 peak-to-peak Voltage/Vpp) was found to reduce the size of breast tumors in mice significantly without causing histological damage to mammary and skin tissues. In addition, lymphocyte and macrophage infiltration was found around the tumor area through the blood vessels11. Thus, one of the mechanisms of tumor cells death can be carried out with the act of anti-tumor mechanisms of various immune cells, including helper and cytotoxic T cells of lymphocytes, as well as macrophages12. Cytotoxic CD8+ T cells, which are activated by helper CD4+ T cells, may enter the tumor microenvironment and induce apoptosis, resulting in shrinkage of the tumor lesions13. Macrophages with the M1 phenotype play an important role in the recognition and destruction of cancer cells and their presence usually indicates a favorable prognosis. On the other hand, macrophages with the M2 phenotype are involved in anti-inflammation, helping the angiogenesis process and the expression of scavenger receptors, and have a significant role in tumor development and metastasis13, including breast tumor15. One of the marker proteins to observe the infiltration of macrophages in tissues, including mammary tumor tissue, is the CD68 protein16.Skin toxicity or dermatitis arises in electric field therapy due to prolonged direct contact between the electrodes and the skin17. Petriet al.18 reported that static electric fields increase the immune response in mice. Moreover, electric fields modulate the activation and polarization of some immune cells, including T cells19 and macrophages20. Voloshinet al.21 reported that TTFields exposure combined with anti-PD-1 therapy induced immunogenic cell death in lung and colon tumors. In addition, Pratiwiet al.22 reported the increased expression of CD68 and caspase-3 in rat breast tumor tissues under the exposure to 150 kHz non-contact electric fields while reducing the expression of PCNA and ErbB2 proteins. However, the study by Pratiwiet al.22 showed an increase of the tumor size during therapy. Using a different intermediate frequency (100 kHz), we examined the effect of non-contact electric fields exposure on tumor growth in mammary tumors-induced rats and observed the activation of immune cells in fighting the tumor cells. We hypothesized that the increase in the size of mammary tumors would not occur under exposure to such non-contact electric fields with the induction of immune cells, especially lymphocytes and macrophages.Cancer therapy that can re-induce immune response to destroy and clean up tumor cells is a therapy that is being developed because of its positive effects. By activating immune cells, the immune cells may reach the tumor-specific areas, including the metastatic area, and specifically attack only tumor cells, not the normal cells in the vicinity22. Experimental protocol in this study was performed following approval by the Ethical Clearance Committee of LPPT UGM with ethical clearance number: 00015/4/LPPT/IV/2017. The Ethical Clearance Committee stated that this study met the ethical requirements for research on experimental animals, and that the Ethical Clearance Committee has the right to conduct monitoring during the research.This study was conducted at the Integrated Research and Testing Laboratory (LPPT) of Universitas Gadjah Mada (UGM) and at the Animal Structure and Development Laboratory of Faculty of Biology, UGM. LPPT UGM has been awarded ISO/IEC 17025:2000 accreditation for competence in testing and calibrationRattus norvegicus, Berkenhout 1769) weighing 50−80 grams were used for this study. SD rats have been used as animal tumor models to study human breast cancer with various induction agents, as well as with 7,12-dimethylbenz[a]anthracene (DMBA) administration24, since rats have a 98% genetic homology with humans25. The rats were supplied by the LPPT UGM laboratory, Yogyakarta, Indonesia, and never used for any other experiment. Rats showing any symptoms of illness or abnormalities were excluded from the experiment. The rats were acclimated for 1 week in polypropylene cages serving as communal home cages, each of the size of 50 × 40 cm2 and covered with rice hulls bedding at the bottom. One communal cage consisted of 5 rats. The temperature of the animal room was maintained at 23–26°C with 81.09% average relative humidity to avoid dehydration during electric fields exposure. Lighting condition was light from lamps during the day and total darkness during the night (12L:12D photoperiod). The rats were fed an AD2 pellet animal diet and tap waterad libitum. However, during treatment, cucumber slices were given as a substitute for water to avoid the animals being shocked with electricity, since the tips of the drink bottle are metal and can permit electric fields. Cage cleaning was carried out every day by cleaning the animal waste from the cage and changing food and water. Individual marking was conducted by giving picric acid to rat fur, while group marking was conducted by labelling the cage with a paint marker to avoid potential confounders.A total of 40 five-week-old healthy female Sprague Dawley (SD) rats , administered two times per week for five weeks. The DMBA compound is a neuroendocrine disruptor that commonly used for carcinogenesis in specific organs, including breast tumors in rats27. The first six rats to develop tumors were assigned to the IT group, and then six more rats were assigned to the INT group. We did this because it was technically easier to carry out the research and avoided mistakes in operating the ECCT device, since we had to turn the device on and off twice daily in the IT group, while not in the INT group. Not all rats grew tumors after DMBA administration. All healthy, normal rats in the placebo (NIT) group were given corn oil as the solvent for DMBA. All administrations were performed by the same researcher (AGF). Furthermore, each researcher in the team had different task. Besides the researcher who administered DMBA, other researchers measured the size of the nodules, recorded the morphology of mammary tumors, dissected the euthanized rats and analyzed the data statistically. One researcher (FA) controlled and monitored all the different steps in the experiment.The SD rats were divided into four groups, namely control (non-induction and non-therapy or NINT), placebo (non-induction and therapy or NIT), DMBA-induced mammary tumors without therapy (induction and non-therapy or INT), and DMBA-induced mammary tumors with therapy (induction and therapy or IT) groups. The sample size in each group was calculated according to Federer’s formula, where six biological replicates were used for each group2 in size or the last day of therapy had been reached. All rats in the placebo (NIT) group were also exposed to non-contact electric fields in the same period, three weeks after the last corn oil administration. The duration of electric fields exposure of 10 hours per day was shorter than the previous exposure in our preliminary study11 to minimize any possible side effects due to exposure to electric fields10. After treatment, all animals were returned to their communal cages.Following the development of mammary tumors up to 1.5 cm in length, all rats in the IT group were exposed to intermediate frequency (100 kHz) and low intensity (18 Vpp) non-contact electric fields generated between pairs of capacitive electrodes embedded in individual cages that had been modified to an ECCT device . The dev2) was measured with a digital caliper and tabulated. All nodule measurements were conducted by the same researcher (NF). In this study, we did not measure nodule size in volume due to tool limitations. The tumor size data were used to calculate the tumor surface area (TSA) using the formula for circle and ellipse areas, and subsequently, the TSA data were used to calculate the tumor growth rates (TGR) of mammary tumors. The TGR was calculated by using the specific growth rates (SGR) formula28 with modification as follows: SGR (%/day) =ln (A2/A1)/(t2 –t1), where A1 and A2 are the tumor surface area before (t1) and after therapy (t2), respectively. Besides tumor size, the morphology of mammary tumors was also recorded by the same researcher (JIMP).During therapy, all tumors were palpated once every two days and their size  for deep anesthesia using intramuscular injection. The rats were pinned ventral side up on a dissected box and dissected by the same surgeon (AGF). Nodules and normal breast tissues were taken and washed using physiological saline. All tissues were fixed using neutral buffered formalin (NBF). Three nodules from three different rats were collected from the INT and IT groups each, while one normal breast tissue was collected from the NINT and NIT groups each. These six nodules were used for histological examination with immunohistochemical staining (IHC) of the target antigens, while the normal breast tissues were used for comparison of the overall histological structure without IHC. The number of samples used for histopathological examination with IHC staining was quite representative.29 using Starr Trek Universal HRP Detection Kit Biocare. Observations and counting were performed on the mitotic figures on H&E preparations. Six antibodies purchased from Abcam Cambridge, United Kingdom, were used for IHC, namely anti-PCNA polyclonal antibody , anti-ErbB2 monoclonal antibody (Cat# ab16901), anti-caspase-3 polyclonal antibody (Cat# ab13847), anti-CD68 monoclonal antibody (Cat# ab201340), anti-CD4 polyclonal antibody (Cat# ab203034), and anti-CD8 alpha monoclonal antibody . The dilution for anti-CD4 and anti-CD8 antibodies was 1:750, where 1 µl of antibody was diluted with 750 µl of BSA-PBST solution . On the other hand, the dilution for anti-PCNA, anti-ErbB2, anti-caspase-3, and anti-CD68 antibodies was 1:500. As much as 100 µl diluted primary antibody was applied on the appropriate slide covered with a parafilm and placed in a humidity chamber. Then, the slide was removed to a refrigerator (4°C) overnight. One to two drops (50 to 100 µl) of biotinylated secondary antibody Trekkie Universal  were applied on the slides covered with a parafilm and incubated for 30 minutes at room temperature. The concentration of antibodies given was as per the manufacturer’s instructions.Histological examination was performed by using paraffin-embedded Hematoxylin and Eosin (H&E)-stained histology slides followed by IHC22. The comparison between positive area of stained cells and total area showed the distributions of the targeted antigens and cells30. Scoring was carried out in 50 fields per group (INT and IT groups), in which 17–18 random fields were examined in one slide. In addition, CD68+ macrophages counting was performed using 60 fields per group with 20 random fields examined in a slide. In total, three slides from three different nodules were examined from each group.All measured data were analyzed with appropriate methods and without any exclusion. Semi-quantitative IHC scoring was performed using the percentage of positive area of stained cells  and the number of stained cells (CD68-positive macrophages). IHC scoring was performed in ImageJ ver.1.51, a freely available software22 for Windows by the same researcher (NF). Qualitative data (morphology of mammary tumors) were analyzed descriptively.All data were tested for normality . The data of mammary tumors growth rate from 12 animals (six rats from the IT and INT groups each) and the number of mitotic figures were analyzed using a t-test (α=0.05) to find statistical significance. The data of PCNA, ErbB2, caspase-3, CD68, CD4, and CD8-positive cells and CD4/CD8 ratio were analyzed quantitatively using non-parametric Mann-Whitney test, since the data were not normally distributed. All data were analyzed statistically using GraphPad Prism ver.8.4.3 softwareThe outcome of this study was the growth rate of mammary tumors under exposure to non-contact electric fields. The comparison of histological characteristics between breast tissue and breast cancer in the animal tumor model, the distribution of molecular markers that described the proliferation and the mechanism of cell death, and the response of immune cells under exposure will be explained coherently in the sections below.et al.22, and appear bruised  was significantly lower (p<0.05) than that in the INT group (0.108 ± 0.078) and showed a negative tumor growth rate as depicted inbruised  due to tackened . The blaackened  and shraackened .32. Conversely,34. The necrotic areas with inflammatory environment in the INT group were larger than those in the IT group.The characteristics of normal breast tissue and the pathogenesis of actively dividing cells in DMBA-induced breast cancer in rats can be seen through H&E staining .Figures36. In addition, the expression of caspase-3 in the IT group was also found at hollow regions in the mammary tumors  as compared to that in the IT group (5.43±1.81), as shown in+ macrophages, CD4+, and CD8+ T cells, respectively, in rat mammary tumors. The expression of CD68, CD4, and CD8 were detected on the cell membrane and in cytoplasm  than that in the IT group  of CD6811. In addition, the development of mammary tumors exposed to 100 kHz non-contact electricfields of ECCT was decreased, unlike in the study of Pratiwiet al.22 that used a different frequency of 150 kHz. This may suggest that differences in the frequency of the electric fields can give different therapeutic results in cancer treatment38 and that the 100 kHz was the appropriate frequency of non-contact electric fields in inhibiting the proliferation of mammary tumor cells. These results are consistent with the results of ourin vitro studies using various frequencies  and intensities  to inhibit breast cancer cell proliferation, and it was found that a frequency of 100 kHz and an intensity of 18 Vpp were the optimum electric fields exposure to inhibit breast cancer cell proliferation11.In the present study, the significantly lower growth rate of rat mammary tumors in the IT group with a negative mean value of SGR as compared to the INT group with a positive mean value of SGR  showed t40. In addition, different levels of stress due to therapy in individual cages could affect differences in the development of mammary tumors in individual rat42.There are several deviation values that are quite large in some data that show quite different responses from each individual rat to the electric field exposure. For example, in the SGR data , there i11. The safety of electric field exposure in normal tissue is determined not only by the frequency and intensity used37, but also by the membrane potential of the normal cell, which is higher than cancer cell44. External electric field exposure cannot penetrate normal cell membranes due to the higher membrane potential44 and only causes rotational motion of the cell37. On the other hand, external electric field exposure can penetrate cancer cell membranes with lower membrane potential, thereby interfering with mitosis44. However, not all normal cells have a higher membrane potential than cancer cells. For example, liver cell has the same membrane potential as MCF-7 breast cancer cell44. Even so, we found that liver structure and function were not impaired under exposure to ECCT’s electric fields based on histological examination, and alanine transferase activity and bilirubin levels in blood plasma, respectively. The data of the safety of ECCT exposure in rat, particularly in the structure and function of liver and kidney, and haematological profiles, will be published separately.The absence of tumors in the placebo (NIT) group  demonstr46. Instead, it helped wound healing after cancer treatment in rats of the IT group, indicated by the drying wound and the reduction of wound size  infiltration in mammary tumors would be accompanied by an increase in tumor size64, as shown in the INT group  exposure in our study may also inhibit the amplification of M2 macrophage polarization, resulting in the negative mammary tumor growth rate in rats of the IT group  and intermediate frequency (100 kHz) non-contact electric fields exposure showed inhibition of mammary tumor growth in rats by inducing CD8https://doi.org/10.17605/OSF.IO/3P79480 (registered on 11 December 2020:https://osf.io/b6d4m).Open Science Framework: Cytotoxic T cells response with decreased CD4/CD8 ratio during mammary tumors inhibition in rats induced by non-contact electric fields,This project contains the following underlying data:- Ethical clearance document- Growth rate of mammary tumors and wound healing data- IHC scoring data- Raw images for IHC and hematoxylin figures- Statistical analysis with GraphPad Prism ver.8.4.3Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public Domain Dedication).Data are available under the terms of the The authors responded to my concerns well. I do not have any further questions. I strongly recommend indexing.Is the work clearly and accurately presented and does it cite the current literature?YesIf applicable, is the statistical analysis and its interpretation appropriate?YesAre all the source data underlying the results available to ensure full reproducibility?YesIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?YesAre sufficient details of methods and analysis provided to allow replication by others?YesReviewer Expertise:Medical imaging, cancer therapy, MRI, image guided therapiesI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Some data presented in the results showed a quite big deviation, are there any outliers in the 6 replicates data which contributed for this deviation? If it’s possible that the authors could explain this clearly, it would then strengthen the paper.Although the electrical field is not contacted with the animal models, it is placed in the closed chamber. Could the authors explain in scientific view whether there are no side effects of the electric field?The condition parameter of electric field used in this study is only point. Is it an optimum condition? If yes, the proven study for the optimalization should be included.If there is toxicity data of the instrument published, it would be better if included.The article consists a quite good scientific background and methodology and has an innovation to be contributed in the treatment of cancer, however other clinical studies should be conducted. The quality of works and article is suitable for indexing, however, some comments should be addressed by author for the statement or question as follow:Is the work clearly and accurately presented and does it cite the current literature?YesIf applicable, is the statistical analysis and its interpretation appropriate?YesAre all the source data underlying the results available to ensure full reproducibility?YesIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?YesAre sufficient details of methods and analysis provided to allow replication by others?YesReviewer Expertise:NAI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. 1. The deviation value that is quite large in some data shows a quite different response from each individual rat to the electric field exposure. For example, in the SGR data , there is indeed 1 outlier data in each of the IN and INT groups. This may occur because the estrous cycle that stimulates prolactin can be different in each individual mouse which can affect differences in the growth rate of mammary tumors in rat . In addition, different levels of stress due to therapy in individual cages could affect differences in the development of mammary tumors in individual rat . We have added this argument in the revision of our article. 2. We have explained the safety of electric field of ECCT to mammry and skin tissues of animal models in the second paragraph of the Introduction as reported in our previous publication. In addition, ECCT has passed the phase I clinical trials for healthy volunteers as stated in the last sentence of the Discussion. The safety of ECCT in normal tissue is determined by the membrane potential of the tissue which is higher than that in cancer cells . External electric field exposure cannot penetrate normal cell membranes due to the higher membrane potential  and only causes rotational motion of the cell organelles . On the other hand, external electric field exposure can penetrate cancer cell membranes with lower cell membrane potential, thereby interfering with mitosis . However, not all normal cells have a higher membrane potential than cancer cells. For example, liver cell has the same membrane potential as MCF-7 cancer cell .  Even so, we found that liver function was not impaired based on alanine transferase activity and bilirubin levels in blood plasma. The data of the safety of ECCT exposure in rat and healthy volunteers will be published separately this year. 3. We have tried various frequencies  and intensities  of the ECCT electric field in preclinical studies and found that a frequency of 100 kHz and an intensity of 18 Vpp are the optimum electric field exposure for breast cancer therapy. 4. ECCT toxicity data on the liver, kidney and hematological profiles will be published separately this year. Even though the study results are quite impressive, I have some additional issues to be considered/corrected before this paper is indexed. First, the manuscript needs serious language editing. I strongly advise them to get a professional editing service when revising.  Second, the below concerns must be answered and explained well in the manuscript before being indexed: "The first 6 rats to develop tumors were assigned to IT group, and then 6 more rats were assigned to INT group. Not all rats grew tumors after DMBA administration. All healthy, normal rats in the placebo (NIT) group were given corn oil as DMBA  solvent." On page 4 it says,Questions:What does this mean? How many rats developed tumors in the IT and INT groups? Why were all the rats that developed the tumor first included in the IT group rather than equally distributed to INT and IT?Were the rats in the NIT group taken from the non tumor growing induced group after being given corn oil? On page 5 it says, "Three nodules from three different rats were collected from each INT and IT groups, while one normal breast tissue was collected from each NINT and NIT groups."Question:Why not all? How are the rats chosen? On page 7 it says,INT group .""In addition, the percentage of positively stained areas of PCNA in INT group (36.16 ± 5.16%) was significantly higher than that inComment:'INT' in bold above is supposed to be 'IT' group. Please correct it.Is the work clearly and accurately presented and does it cite the current literature?YesIf applicable, is the statistical analysis and its interpretation appropriate?YesAre all the source data underlying the results available to ensure full reproducibility?YesIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?YesAre sufficient details of methods and analysis provided to allow replication by others?YesReviewer Expertise:Medical imaging, cancer therapy, MRI, image guided therapiesI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. 1. We will consider getting a professional language editing service to revise our manuscript. 2. The rats were randomly selected for mammary tumor induction with DMBA administration. One month after DMBA administration, the tumors began to grow with a different time of appearance which was between 38-63 days. Since we used 6 biological replicates for each group based on Federer formula, 12 rats were used for IT and INT groups. Then, we selected the first 6 rats that developed tumors to be assigned to the IT group, so that it was technically easier to carry out the research and avoided mistakes in operating the ECCT device. We did not equally distribute the induced rats to both groups to avoid human errors in operating the ECCT, since we had to turn on and off the device twice every day for the IT group, while not for the INT group. 3. The rats in the NIT group were normal rats with corn oil administration. They did not experience any DMBA administration. 4. We used 3 nodules from 3 rats for each IT and INT group, since this sample size was sufficiently representative for the IHC method. We randomly selected the rats with nodules for histopathological analysis. 5. Yes, we made a mistake for that sentence. We will correct it.