Hlf and Tef, are critical for constraining plasticity and for preventing life-threatening seizures. These data indicate that transcriptional activation is not only required for many forms of homeostatic plasticity but is also involved in restraint of the response to activity deprivation.Healthy neuronal networks rely on homeostatic plasticity to maintain stable firing rates despite changing synaptic drive. These mechanisms, however, can themselves be destabilizing if activated inappropriately or excessively. For example, prolonged activity deprivation can lead to rebound hyperactivity and seizures. While many forms of homeostasis have been described, whether and how the magnitude of homeostatic plasticity is constrained remains unknown. Here, we uncover negative regulation of cortical network homeostasis by the PARbZIP family of transcription factors. In cortical slice cultures made from knockout mice lacking all three of these factors, the network response to prolonged activity withdrawal measured with calcium imaging is much stronger, while baseline activity is unchanged. Whole-cell recordings reveal an exaggerated increase in the frequency of miniature excitatory synaptic currents reflecting enhanced upregulation of recurrent excitatory synaptic transmission. Genetic analyses reveal that two of the factors,  The human brain is made up of billions of nerve cells called neurons which receive and send signals to one another. To avoid being over- or under-stimulated, neurons can adjust the strength of the inputs they receive by altering how connected they are to other nerve cells.This process, known as homeostatic plasticity, is thought to be necessary for normal brain activity as it helps keep the outgoing signals of neurons relatively constant. However, homeostatic plasticity can lead to seizures if it becomes too strong and overcompensates for weak input signals. Regulating this process is therefore central to brain health, but scientists do not understand if or how it is controlled.To address this, Valakh et al. analyzed the genes activated in neurons lacking incoming signals to find proteins that regulate homeostatic plasticity. This revealed a class of molecules called transcription factors (which switch genes on or off) that constrain the process. In brain samples from mice without these regulatory proteins, neurons received twice as much input, leading to an increase in brain activity resembling that observed during seizures. Valakh et al. confirmed this finding using live mice, which developed seizures in the absence of these transcription factors.These findings suggest that this type of regulation to keep homeostatic plasticity from becoming too strong may be important. This could be especially vital as the brain develops, when the strength of connections between neurons changes rapidly. The discovery of the transcription factors involved provides a potential target for activating or restraining homeostatic plasticity. This control could help researchers better understand how the process stabilizes brain signaling. Neuronal networks are equipped with a set of homeostatic plasticity mechanisms that enable them to rebalance activity following perturbations during development, learning, or disease. Homeostatic plasticity can alter the intrinsic excitability of individual neurons, as well as the strength and number of both excitatory and inhibitory synapses . SynaptiDespite recognition of the significance of homeostatic plasticity, whether and how its strength is normally constrained has remained unknown. Downregulation of the strength of homeostatic plasticity could potentially provide protection against inappropriate or excessive activation of these mechanisms. However, such negative regulators of homeostatic plasticity have not been previously described.Here, we investigate the role of the proline and acidic amino acid-rich basic leucine zipper (PAR bZIP) family of transcription factors (TFs) in homeostatic plasticity. The family consists of hepatic leukemia factor (HLF), thyrotroph embryonic factor (TEF), and albumin D-site-binding protein (DBP) which are thought to act as transcriptional activators, as well as E4 Promoter-Binding Protein 4  that acts as a transcriptional repressor . All fouIn order to investigate the role that gene transcription plays in regulating the neuronal response to activity deprivation, we profiled changes in gene expression engaged during homeostatic plasticity and found that prolonged activity deprivation activates a robust transcriptional program involving the PARbZIP TF family members HLF and TEF. Both act to restrain the expression of homeostatic plasticity. While they have limited effects on network function at baseline, they strongly suppress the upregulation of homeostatic changes, mainly by regulating recurrent excitatory synaptic connections, although inhibition is also affected. Taken together, these results indicate that homeostatic plasticity is itself subject to activity-dependent regulation and is transcriptionally restrained by the PARbZIP TFs HLF and TEF.+ interneurons and performed RNA sequencing to look for transcripts that change following prolonged silencing. Inactivity activates a robust transcriptional program of both positively and negatively affected genes , suggesting that this family member may play a more limited role in the neocortex. Both Hlf and Tef are robustly upregulated after 5 days of activity deprivation in both excitatory  and inhibitory neurons , while Nfil3 and Dbp were not .Certain forms of homeostatic plasticity require transcription  and actied genes  consisteed genes . To idened genes . This suHlf and Tef transcript levels at various time points during activity deprivation using real-time quantitative PCR. We find that upregulation occurs soon after activity withdrawal, since by 4 hr of TTX application the level of both TFs is already substantially elevated . After 2 days of TTX treatment, the frequency of the upstates increases. While 2 days of TTX incubation increases the peak frequency 3.6-fold in wild-type (WT) slices (from 0.06 ± 0.01 to 0.22 ± 0.04 Hz), the same silencing duration produces a nearly sixfold increase in the TKO slices . Rather than attempt to statistically test individual differences between each of 27 potential genotypes , we fit a series of multivariate linear models to test the ability of genotype to predict calcium peak frequency. The same six models, described in Hlf and Tef, either independently, or summed together. The ability of each model to account for the data was estimated from the adjusted R2 which reflects the fraction of the variance in the data predicted by the model variables. Several key points were evident from this analysis:Expression of both  element , they ma2 of –0.01 to 0.063) to the control data, consistent with the hypothesis that baseline activity does not depend on genotype.All of the models produced poor fits (adjusted RHlf and/or Tef produced much better fits to the TTX data (adjusted R2 of 0.198–0.296) consistent with the hypothesis that rebound activity is influenced by genotype. In these models, the coefficients (effect size) for Hlf and Tef were similar and t tests revealed they were highly significantly different from 0.All of the models that included variables for Dbp (line 4) provided a poor fit to the TTX data (adjusted R2 = 0.073) and in the model that included both terms for Dbp and the other two factors (line 1), the Dbp coefficient was small and not significantly different from 0. These observations are consistent with the hypothesis that rebound activity does not depend on Dbp and that even in a significant model including Hlf and Tef, Dbp does not add additional explanatory power to the model.The model that only depended on Hlf and Tef (line 5) or for their sum (line 6) produced the best fits (adjusted R2 = 0.291 and 0.296); that is, better than those that depend on only one of these factors . This is consistent with the hypothesis that both genes contribute to constraining cortical homeostatic plasticity.The models that included terms for both 2 was that which depended only on the sum of the number of Hlf and Tef alleles (line 6), we used this model for further post hoc (Tukey) tests to determine the effect of different numbers of alleles on the TTX response. The results of this analysis are shown in Hlf + Tef) and WT  could be restored by a single allele, although there was a small but significant improvement between two and four alleles. The fact that this difference was significant, but the differences between 1 and 2 alleles, and 1 and 4 alleles were not, may reflect a real difference between these groups, or may reflect the imbalanced numbers of animals in each group. The group with two alleles included animals that were WT for Hlf but lacked Tef (N = 8), animals that were WT for Tef and lacked Hlf (N = 9), and trans-Het animals that were heterozygous for both Hlf and Tef (N = 7). A separate analysis of variance of these three subgroups revealed that the means  were not significantly different (p = 0.28), consistent with the hypothesis that alleles of Hlf and Tef can substitute for one another in their ability to regulate the homeostatic response to activity deprivation.Since the model with the highest adjusted RHlf or Tef restores the lifespan of the animals to levels not statistically different from WT. Mice with one Dbp allele have improved survival compared to TKO animals but still die at a statistically significant higher rate than WT mice  from that in WT. We also found, in agreement with prior findings , and conformed to the National Institutes of Health Guide for the Care and Use of Laboratory Animals. The initial RNAseq screen  was perf animals  which we2PO4, 25 mM dextrose, 2 mM CaCl2, and 2 mM MgCl2, 315–319 mOsm) with a ceramic blade and placed directly onto six-well Millipore Millicell cell culture inserts  over 1 mL warmed neuronal media (1× MEM (Millipore-Sigma), 1× GLUTAMAX (Gibco Thermo Fisher Scientific), 1 mM CaCl2, 2 mM MgSO4, 12.9 mM dextrose, 0.08% ascorbic acid, 18 mM NaHCO3, 35 mM 1 M HEPES (pH 7.5), 1 µg/mL insulin and 20% Horse Serum , pH 7.45 and 305 mOsm). Slices were placed in media containing 1× PenStrep (Gibco Thermo Fisher Scientific) and 50 µg/mL gentamicin (Millipore Sigma) for 24 hr and subsequent media changes were antibiotic-free. The slices were then grown at 35°C and 5% CO2. Media were changed every other day to 1 mL of fresh media. For TTX treatment, media containing 500 nM TTX was added during the media change at EP 12. For TTX washout experiments, two additional media changes with TTX-free media were performed 5 min apart.Organotypic slices were dissected from P6 to P8 pups. Animals were anesthetized with a ketamine (20 mg/mL), xylazine (2.5 mg/mL), and acepromazine (0.5 mg/mL) mixture , the brain was extracted, embedded in 2% agarose, and coronal slices containing primary somatosensory cortex were cut on a compresstome  to 300 μm in ice-chilled ACSF  5′-CACGGACGATCCTATTGTCA-3′, GAPDH (forward) 5′-TCAATGAAGGGGTCGTTGAT-3′ GAPDH (reverse) 5′-CGTCCCGTAGACAAAATGGT-3′, HLF (forward) 5′-CGGTCATGGATCTCAGCAG-3′, HLF (reverse) 5′-GTACCTGGATGGTGTCAGGG-3′, TEF (forward) 5′-GAGCATTCTTTGCCTTGGTC-3′, and TEF (reverse) 5′-GGATGGTCTTGTCCCAGATG-3′.RNA was extracted from neocortical regions of slice cultures using TRIzol reagent followed by RNA Clean and Concentrator Kit (Zymo Research R1014). cDNA was synthesized with 0.5 µg of RNA using the cDNA Synthesis Kit (Bio-Rad 170-8891) using random hexamers to generate cDNA from total RNA. Quantitative real-time PCR was performed using Corbett Research RG-6000 Real-Time PCR Thermocycler with SYBR Green Supermix (Bio-Rad). The following primer sequences were used: RPL10 (forward) Organotypic slice cultures were cut out of the cell culture inserts along with the membrane using a scalpel blade. Slices were transferred to a thermo-regulated recording chamber and continuously perfused with oxygenated ACSF. Neurons were visualized on an Olympus upright epifluorescence microscope with 10× air and 40× water immersion objectives. Visually guided whole-cell patch-clamp recordings were made using near-infrared differential interference contrast microscopy. Recording pipettes of 3–5 MΩ resistance contained internal solution with the following concentrations. For excitatory currents and intrinsic excitability: (in mM) 20 KCl, 100 K-gluconate, 10 HEPES, 4 Mg-ATP, 0.3 Na-GTP, 10 Na-phosphocreatine, and 0.1% biocytin. For inhibitory currents: (in mM) 120 KCl, 10 HEPES, 4 Mg-ATP, 0.3 Na-GTP, 10 Na-phosphocreatine, and 0.1% biocytin. Recordings were collected using an AxoPatch 200B amplifier , filtered at 10 kHz and were not corrected for liquid junction potentials. Data were collected on a Dell computer using custom software running on Igor Pro .Cells were selected at random from layer 5 in primary somatosensory cortex. Whole-cell recordings were performed with a K-Gluconate-based internal recording solution. Synaptic currents were blocked by adding picrotoxin (PTX) at 25 μM, 6,7-dinitroquinoxaline-2,3-dione (DNQX) 25 μM, and (2R)-amino-5-phosphonovaleric acid (APV) at 35 μM to standard ACSF to block γ-aminobutyric acid (GABA), α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA), and N-methyl-d-aspartate (NMDA) receptors, respectively. Cells were held at –65 mV by injecting a small current. 500 ms current injections ranging from –25 to 275 pA in 25 pA steps increments at random intensity were delivered every 10 s. Adaptation ratio was calculated using custom-written IGOR script as previously described . BrieflyTo isolated miniature excitatory AMPA-mediated currents 25 µM PTX, 35 µM APV, and 500 nM TTX were added to the extracellular recording solution. To isolate inhibitory currents, 20 µM DNQX, 35 µM APV, and 500 nM TTX were added to the extracellular solution. The slices were incubated in TTX only during active recording, which lasted no more than 30 min for each slice. Cells were clamped at –65 mV with a series resistance of below 20 MΩ with no compensation for the liquid junction potential. Ten 10-s traces were acquired for each cell. Threshold-based detection of mPSCs and action potentials was implemented using custom-written IGOR scripts equipped with routines for baseline subtraction, custom filtering, and measurements of intervals, amplitudes, and kinetic properties.To visualize calcium dynamics, 24 hr after slice preparation, 1 µL of pAAV.Syn.GCaMP6f.WPRE.SV40  was applied to the somatosensory cortex in each hemisphere. At day EP14, slices were cut out along with the membrane and placed into the perfusion chamber mounted on a spinning disc microscope , with an Andor CSU W1 spinning disc unit, using an Andor Neo sCMOS cameras and Andor IQ3 to run the system . Slices were allowed to acclimate while being perfused with 33°C oxygenated ACSF with no TTX for 10 min. Slices were imaged with a 10× objective centered over the primary somatosensory area. For each slice, 10 min of imaging from a 500-µm square per slice were acquired at 33 frames per second.http://github.com/VH-Lab/vhlab-TwoPhoton-matlab) (Cellular somatic ROIs were selected by hand from background using custom MATLAB code (-matlab)  based on Homeostatic plasticity helps to maintain the stability of neural network activity. This study shows that activation of PAR bZIP family of transcription factors restrains homeostatic upregulation of network activity in response to activity deprivation in mouse brain slice cultures. The identification of an endogenous transcriptional program that limits upward homeostatic response and helps prevent aberrant activity associated with epilepsy and brain disorders is important, and the findings will be of interest to a broad 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 3 peer reviewers, including Yukiko Goda as Reviewing Editor and Reviewer #1, and the evaluation has been overseen by Gary Westbrook as the Senior Editor.Thank you for submitting your article "A transcriptional constraint mechanism limits the homeostatic response to activity deprivation in mammalian neocortex" 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:All three reviewers acknowledge that the study provides novel insights into a long-standing question about the mechanisms that constrain homeostatic synaptic plasticity, and the findings are exciting and of broad interest. However, a couple of major concerns have been raised regarding (a) the interpretation of calcium imaging data and (b) data quantification, effect sizes and statistics in a number of experiments.(a) The main conclusion that PAR bZIP transcription factors constrain the network activity via regulating excitatory synapses should be further strengthened by addressing the following two points:(i) Ruling out the contribution of changes in inhibitory synaptic transmission in TKO neurons. If the authors cannot rule out the contribution, then calcium imaging experiments should be conducted also in excitatory or inhibitory neurons to clarify the relative contributions.(ii) In addition, calcium imaging, as the key physiology data, should be performed in WT and TKO cultures for two time points: after 2 days in TTX and after 5 days in TTX. Monitoring the kinetics will help in better relating the physiology data to the RNA-seq data and to clarify whether TKO cultures overshoots or if they show a faster compensation.(b) The authors should fully address the concerns regarding data quantification and statistics that are raised by Reviewers 2 and 3.Reviewer #1 (Recommendations for the authors):1. The initial RNA seq analysis in Figure 1A,B compares control vs. TTX in L5-6 pyramidal and PV+ neurons. How well does the observation of strong upregulation of HFL and TEF extend to pyramidal and PV+ cells for a 2-day TTX treatment that is used for much of the later experiments? Notably, calcium imaging based on synapsin promoter-driven GCaMP6f expression does not specify cortical layers being targeted nor discriminate between excitatory and inhibitory neurons.2. Figure 2. It would be informative to monitor calcium dynamics in a cell-type specific manner to decipher the differences in homeostatic response between WT and mutant neurons.3. Line 266-269. It seems premature to conclude that homeostatic plasticity of mIPSCs is not driving the TTX-dependent change in network activity based on the fact that the levels of mIPSC amplitude and frequency are indistinguishable between WT and mutant after TTX treatment. In particular, the striking reduction in mIPSC amplitude in the baseline in the mutant prep indicates that already some form of compensation for altered mIPSCs has taken place to keep the network activity level comparable between WT and mutant prior to TTX treatment. In addition, the observed lack of a further change in mIPSCs could be due to saturation of mIPSC-dependent mechanisms.Reviewer #2 (Recommendations for the authors):I have concerns, mainly revolving around statistics and effect sizes:1. Based on the RNA seq data shown in figure 1, it is unclear why the authors focused their analyses on Hlf, Tef and Dbp, because the data suggest more pronounced regulation of other genes. The authors should explain why these candidates were chosen for further analysis in the Results section.2. One of the central findings of this study is that Hlf-/-/Dbp-/-/Tef-/- triple knockout (TKO) slice cultures display a more pronounced increase in calcium peak frequency upon TTX treatment compared to WT controls. In the Results section, it is mentioned that TTX treatment induces a two-fold increase in calcium peak frequency in WT, and a four-fold increase in TKO cultures . However, based on the mean data plotted in figure 2D, the increase in WT is around 3-4-fold (15 peaks x s^-1/4 peaks x s^-1=3.5), whereas the one in TKO is around four-fold (30/7.5=4). Could the authors comment on the discrepancy between the text and the data? Furthermore, it is key to test for an interaction between treatment and genotype to support this major conclusion by statistics. Additionally, it would be helpful to plot the relative increase in calcium peak frequency upon TTX treatment in WT and TKO.3. On a similar note, although not statistically significant, the mean calcium peak frequency in TKO cultures is around two-fold higher than WT under baseline conditions . A similar trend can be seen in the data shown in figure 6A (top panel), whereas the baseline calcium peak frequency is similar between TKO and controls in the experiment shown in Figure 2B. Based on the scatter of the data, can the authors exclude that baseline calcium peak frequency is increased in TKO cultures? I suggest running a power analysis for these data to verify if the sample sizes are sufficient to support their conclusions. Otherwise, sample sizes would have to be increased, or the conclusions should be revised/toned down. Alternatively, could additional parameters, such as inter-burst interval, be read out to support the conclusions that baseline network excitability is unchanged in TKO cultures, and that TTX application leads to a more pronounced increase in calcium peak frequency? Another possibility may be to pool the data of the different experiments?4. Based on the data shown in figure 6, they conclude that one copy of Tef is sufficient to constrain homeostatic plasticity. Can they rule out that one copy of Hlf is sufficient as well? This would actually fit to the result that one copy of Tef or Hlf rescues lifespan in TKO. The peak frequencies of DKO;Tef +/- and DKO;Hlf +/- after TTX treatment actually look quite similar. Are these two groups statistically different from one another? Only comparing the absolute DKO;Tef +/- or DKO;Hlf +/- data to WT is not very informative. Again, I suggest normalizing the data of each genotype to the respective control, and to test for interactions between treatment and genotype.5. Sample sizes  should be clearly specified for each experiment. Are some data sets only based on two cultures ? Again, a power analysis may be helpful to determine sample sizes.6. The major (recorded) effect underlying the increase in network excitability is an increase in mEPSC frequency. Does this indicate that the mechanisms that constrain homeostatic plasticity mainly work on presynaptic mechanisms, or an increase in synapse number? These possibilities should be also discussed.7. TTX application increases mEPSC frequency by around two-fold and does not affect other recorded parameters, such as excitability. How could a two-fold increase in mEPSC frequency translate into a four-fold increase in calcium peak frequency? Is there any evidence for a supralinear increase in network activity with regard to miniature frequency? This issue should be discussed.8. What is the evidence for 'exaggerated' homeostatic plasticity in TKO cultures? Can they rule out that TKO neurons compensate better? This possibility should be discussed unless they can exclude the possibility that TKO cultures indeed do not retarget set-point activity.Other comments:1. It would be very helpful if the abstract could contain more specific information 2. The more pronounced increase in mEPSC frequency upon TTX treatment in TKO cultures compared to WT  appears more robust than the corresponding changes in calcium peak frequency . However, they should also test for an interaction between treatment and genotype to support their conclusion by statistics for the data shown in figure 3B, C.3. Similarly, although not statistically significant, the decrease in mIPSC frequency upon TTX treatment seems less pronounced in TKO cultures . Could they run a power analysis and test for treatment-group interaction as well?4. mIPSC amplitudes are decreased in TKO cultures, and there is no further decrease upon TTX application . First, the decrease in baseline mIPSC amplitude in TKO is interesting, and may represent a homeostatic response that counteracts a potential increase in excitability/ calcium peak frequency under baseline conditions . This possibility should be discussed in addition to previous work indicating reduced glutamate decarboxylase function in PLP KOs. Second, could the lack of a decrease in mIPSC amplitude after TTX in TKO neurons also oppose increased network excitability? This possibility should be also discussed.5. TTX treatment results in a rapid regulation of Hlf and Tef mRNA on the hour time scale . The mEPSC/IPSC recordings were carried out in the presence of TTX. It is thus crucial to mention the time window during which WT recordings were conducted with regard to the beginning of TTX incubation to assess whether Hlf or Tef transcripts could be increased in the control group.6. I suggest using the SI unit Hz instead of peaks/minute for the calcium imaging data.7. The figure labels "mutant" could be more specific .8. Some figures are not referenced in the text.9. It should be briefly described how miniature PSCs and APs were analyzed .Reviewer #3 (Recommendations for the authors):I have a few suggestions for the authors that may strengthen the manuscript:1. Quantification of the network activity homeostasis : The authors provided quantification of frequency of Ca events (probably associated with spike bursts). It is unclear why the amplitude was not taken into account. Mean firing rate should be better reflected by frequency x amplitude calculation.2. What is the mechanism that links spike silencing to activation of PAR-bZIP TFs by inactivity? Is it mediated by the previously described mechanisms related to T-type Ca channels  or L-type Ca channels and CaMK4 ? This should be at least discussed.3. I am not sure I agree with the interpretation of mIPSC results. The results show that both frequency and amplitude homeostatic down-regulation are disabled by TF deletion. This, in my view, may be a possible compensation to prevent a further increase in the E/I ratio (meaning that without it epilepsy would be even more severe).Statistics: I could not find cell numbers (n) in the legends / text for each experiment.line 179 – did the authors mean removal of silencing? Essential revisions:All three reviewers acknowledge that the study provides novel insights into a long-standing question about the mechanisms that constrain homeostatic synaptic plasticity, and the findings are exciting and of broad interest. However, a couple of major concerns have been raised regarding (a) the interpretation of calcium imaging data and (b) data quantification, effect sizes and statistics in a number of experiments.Please see detailed replies below.(a) The main conclusion that PAR bZIP transcription factors constrain the network activity via regulating excitatory synapses should be further strengthened by addressing the following two points:(i) Ruling out the contribution of changes in inhibitory synaptic transmission in TKO neurons. If the authors cannot rule out the contribution, then calcium imaging experiments should be conducted also in excitatory or inhibitory neurons to clarify the relative contributions.Previously we did some pilot experiments trying to attribute individual cellular firing to pyramids or subtypes of interneurons. We do not think this will be informative in the TTX condition (in either genotype) because the network activity is so intense and is shared across almost all cells in the network. Both interneurons and pyramids receive both excitation and inhibition, but the recurrent excitation is so powerful that all cells fire near simultaneously. Hence we do not believe we can clarify their relative contributions in this way. Therefore, we think that the more difficult experiment of manipulating HLF and TEF independently in pyramids and interneurons, and/or sparsely in individual cells will be much more informative, but this will take significant additional work.(ii) In addition, calcium imaging, as the key physiology data, should be performed in WT and TKO cultures for two time points: after 2 days in TTX and after 5 days in TTX. Monitoring the kinetics will help in better relating the physiology data to the RNA-seq data and to clarify whether TKO cultures overshoots or if they show a faster compensation.We performed additional experiments after 5 days in TTX as well as additional experiments to expand the sample size at 2 days in TTX. We report the data in Figure 2—Figure Supplement 1C-D. Response to TTX in 5 day-treated cultures is comparable to that at 2 days in TTX and the TKO phenotype is similar with the longer TTX incubation.(b) The authors should fully address the concerns regarding data quantification and statistics that are raised by Reviewers 2 and 3.We address these concerns and other concerns raised by each reviewer below.Reviewer #1 (Recommendations for the authors):1. The initial RNA seq analysis in Figure 1A,B compares control vs. TTX in L5-6 pyramidal and PV+ neurons. How well does the observation of strong upregulation of HFL and TEF extend to pyramidal and PV+ cells for a 2-day TTX treatment that is used for much of the later experiments? Notably, calcium imaging based on synapsin promoter-driven GCaMP6f expression does not specify cortical layers being targeted nor discriminate between excitatory and inhibitory neurons.Hlf and Tef at multiple time points following initiation of TTX treatment is shown in Figure 1C. Real-time PCR experiments from RNA extracted from whole cortical slice cultures were performed at 4 hours, 1 day, 3 days and 5 days. Due to the small number of replicates, the data were underpowered for full posthoc testing of all genes/time points. However, t-tests revealed significant upregulation of both Hlf and Tef relative to Rpl10 after 24 hours in TTX .Data showing upregulation of 2. Figure 2. It would be informative to monitor calcium dynamics in a cell-type specific manner to decipher the differences in homeostatic response between WT and mutant neurons.Hlf and Tef in excitatory vs. inhibitory neurons would be instructive, but unfortunately the knockout available to us is a germline deletion. We plan to address this issue with additional experiments in the future, but this is likely to require very significant additional work and so is outside of the scope of this study.We chose not to monitor calcium dynamics in a cell-type specific manner because, following TTX treatment, the activity of nearly all neurons in the slice are highly correlated in both genotypes (synchrony near 0.95) and are driven by strong recurrent connectivity. Hence, we do not believe there would be informative differences. We do believe that selectively manipulating 3. Line 266-269. It seems premature to conclude that homeostatic plasticity of mIPSCs is not driving the TTX-dependent change in network activity based on the fact that the levels of mIPSC amplitude and frequency are indistinguishable between WT and mutant after TTX treatment. In particular, the striking reduction in mIPSC amplitude in the baseline in the mutant prep indicates that already some form of compensation for altered mIPSCs has taken place to keep the network activity level comparable between WT and mutant prior to TTX treatment. In addition, the observed lack of a further change in mIPSCs could be due to saturation of mIPSC-dependent mechanisms.We acknowledge that the reviewer is correct and emended our statement:directly driving the changes in the network activity following TTX treatment. We cannot rule out the possibility that although baseline activity is normal, the baseline reduction in mIPSC amplitude contributes to subsequent network plasticity indirectly by contributing to induction of the changes in EPSCs observed, or by inducing some form of compensation other than the physiological parameters measured.”“Thus, both the amplitude and frequency of mIPSCs received by pyramidal neurons after activity deprivation are indistinguishable from the wild-type in the TKO slices, suggesting that homeostatic plasticity of mIPSCs is not Reviewer #2 (Recommendations for the authors):I have concerns, mainly revolving around statistics and effect sizes:1. Based on the RNA seq data shown in figure 1, it is unclear why the authors focused their analyses on Hlf, Tef and Dbp, because the data suggest more pronounced regulation of other genes. The authors should explain why these candidates were chosen for further analysis in the Results section.We added additional explanation to this section of the paper as follows:“To identify potential transcriptional regulators of homeostatic plasticity, we looked for transcription factors (TFs) upregulated in the TTX condition. TFs can be classified into families, and in some cases subfamilies, which share a DNA binding domain, and so are expected to bind the same target DNA sequences in the genome and therefore to regulate the same or similar target transcripts. We asked which families or subfamilies were most over-represented amongst the TFs differentially expressed during activity blockade. The most overrepresented subfamily was the PAR bZIP subfamily of TFs, a subtype of the CEBP-related family in the class of Basic leucine zipper factors . This subfamily includes 3 transcriptional activators Hlf, Tef, and Dbp, and a transcriptional repressor, Nfil3.”2. One of the central findings of this study is that Hlf-/-/Dbp-/-/Tef-/- triple knockout (TKO) slice cultures display a more pronounced increase in calcium peak frequency upon TTX treatment compared to WT controls. In the Results section, it is mentioned that TTX treatment induces a two-fold increase in calcium peak frequency in WT, and a four-fold increase in TKO cultures . However, based on the mean data plotted in figure 2D, the increase in WT is around 3-4-fold (15 peaks x s^-1/4 peaks x s^-1=3.5), whereas the one in TKO is around four-fold (30/7.5=4). Could the authors comment on the discrepancy between the text and the data? Furthermore, it is key to test for an interaction between treatment and genotype to support this major conclusion by statistics. Additionally, it would be helpful to plot the relative increase in calcium peak frequency upon TTX treatment in WT and TKO.We thank the reviewer for catching the discrepancy. We performed additional experiments and have re-analyzed the old and new data together. We have fixed the text to reflect the data and have plotted the peak frequency normalized to control  as well as non-normalized frequency in Hz. The combined data and analysis further strengthen our conclusion that there is no change in network activity level at baseline between WT and TKO cultures.We tested for interactions and found highly significant (<0.0001) interaction between treatment and genotype. We include the results in the text (line 141).“While 2 days of TTX incubation increases the peak frequency 3.6-fold in WT slices (from 0.06 +/- 0.01 to 0.22 +/- 0.04 Hz), the same silencing duration produces a nearly six-fold increase in the TKO slices . A two-way ANOVA revealed significant effects of treatment  and genotype (p<0.0001) and a significant interaction between the two (p<0.0001). Post hoc T-tests (with Tukey correction for multiple comparisons) revealed that TTX increases in activity were highly significant in both WT (p = 0.0007) and TKO (p<0.0001) slices and that TTX produced a significantly stronger increase in the TKO (p<0.0001), while the baseline activity of cells from slices derived from the TKO and WT do not differ significantly (p=0.92). Consistent with this, normalizing the TTX response to the control response revealed a larger relative increase in TKO than WT cultures .”3. On a similar note, although not statistically significant, the mean calcium peak frequency in TKO cultures is around two-fold higher than WT under baseline conditions . A similar trend can be seen in the data shown in figure 6A (top panel), whereas the baseline calcium peak frequency is similar between TKO and controls in the experiment shown in Figure 2B. Based on the scatter of the data, can the authors exclude that baseline calcium peak frequency is increased in TKO cultures? I suggest running a power analysis for these data to verify if the sample sizes are sufficient to support their conclusions. Otherwise, sample sizes would have to be increased, or the conclusions should be revised/toned down. Alternatively, could additional parameters, such as inter-burst interval, be read out to support the conclusions that baseline network excitability is unchanged in TKO cultures, and that TTX application leads to a more pronounced increase in calcium peak frequency? Another possibility may be to pool the data of the different experiments?We performed additional experiments, reanalyzed our existing data and replotted the figures including the additional experiments. A small subset of experiments were excluded because the calcium signal was too low to accurately measure changes in firing. We have made the exclusion criteria clear in the methods. The previous trend towards an increase at baseline is no longer present with the additional data . Additionally, we now report synchrony, a measure of the average cross-correlation at zero lag during network bursts (figure 2 supplement 1B). The synchrony metric saturates in the WT TTX condition, making it unsuitable for detecting further increases in network activity and so we use peak frequency for most of the rest of the manuscript. We also performed a power analysis. The synchrony results and power analysis are described in the following sentences (line 152):“The TTX condition also increased synchrony (from 0.76 +/- 0.03 to 0.95 +/- 0.01) in WT, and in the TKO . While the TTX effects were highly significant , there was no significant effect of genotype (p=0.43) and no interaction between treatment and genotype (p=0.65), presumably reflecting the fact that synchrony is already saturated by TTX treatment in the WT and cannot further increase in the TKO, but also indicating that baseline synchrony is not altered in the TKO. A power test revealed that with the effect size and variances observed, 95 slice cultures in each group would be needed to detect a significant difference between WT and TKO peak frequency, while for the synchrony measure, the required N would be 1609.”4. Based on the data shown in figure 6, they conclude that one copy of Tef is sufficient to constrain homeostatic plasticity. Can they rule out that one copy of Hlf is sufficient as well? This would actually fit to the result that one copy of Tef or Hlf rescues lifespan in TKO. The peak frequencies of DKO;Tef +/- and DKO;Hlf +/- after TTX treatment actually look quite similar. Are these two groups statistically different from one another? Only comparing the absolute DKO;Tef +/- or DKO;Hlf +/- data to WT is not very informative. Again, I suggest normalizing the data of each genotype to the respective control, and to test for interactions between treatment and genotype.We agree with the reviewer’s skepticism of our ability to distinguish the contributions of Hlf and Tef and wrestled with how best to perform this analysis. A key limitation is that there are 27 potential genotypes  for the three genes considered jointly and so even with a total of 185 experiments (87 Control and 98 TTX) we were almost definitely underpowered for most specific comparisons. Rather than attempt to make all possible pairwise comparisons, we chose to put all of the data together . We then fit these data with a series of linear regression models to determine the relationship between peak frequency and genotype. The same set of six models were used to separately fit the data from control slices and from TTX-treated slices.These analyses are described in the following section (line 258):2 which reflects the fraction of the variance in the data predicted by the model variables. Several key points were evident from this analysis:“To test whether Hlf, Tef, and Dbp work together to regulate homeostatic plasticity or if they have unequal contributions to restraining network response to activity deprivation, we measured the homeostatic response while varying gene copy number of each transcription factor. In addition to the WT and TKO data described in Figure 2 and Figure 2—Figure Supplement 1, we measured calcium transients in slice cultures treated with or without TTX from 97 additional animals with various combinations of 0, 1 or 2 alleles of Hlf, Tef and Dbp (full details of each experiment given in associated data file). Rather than attempt to statistically test individual differences between each of 27 potential genotypes , we fit a series of multivariate linear models to test the ability of genotype to predict calcium peak frequency. The same six models, described in Table 1, were fit separately to data from control and TTX-treated slices. The models, shown in Table 1, differ in how they depend on the number of alleles of each of the three genes. Model 1 depends on all three genes, models 2-4 depend only on one of the three genes (each in turn) and models 5 and 6 depend only on Hlf and Tef, either independently, or summed together. The ability of each model to account for the data was estimated from the adjusted R2 of -0.01 to 0.063) to the control data, consistent with the hypothesis that baseline activity does not depend on genotype.1) All of the models produced poor fits (adjusted R2 of 0.198 to 0.296) consistent with the hypothesis that rebound activity is influenced by genotype. In these models, the coefficients (effect size) for Hlf and Tef were similar and T-tests revealed they were highly significantly different from zero.2) All of the models that included variables for Hlf and/or Tef produced much better fits to the TTX data (adjusted R2 = 0.073) and in the model that included both terms for Dbp and the other two factors (line 1), the Dbp coefficient was small and not significantly different from zero. These observations are consistent with the hypothesis that rebound activity does not depend on Dbp and that even in a significant model including Hlf and Tef, Dbp does not add additional explanatory power to the model.3) The model that only depended on Dbp (line 4) provided a poor fit to the TTX data (adjusted R2 = 0.291 and 0.296); i.e. better than those that depend on only one of these factors . This is consistent with the hypothesis that both genes contribute to constraining cortical homeostatic plasticity.3) The models that included terms for both Hlf and Tef (line 5) or for their sum (line 6) produced the best fits , we used this model for further post hoc (Tukey) tests to determine the effect of different numbers of alleles on the TTX response. The results of this analysis are shown in Figure 6. The most significant differences were between TKO slices  and the other genotypes tested . Most of the other comparisons were not significant, with the exception of the difference between WT responses and those for animals with only two alleles (p=0.011). This indicates that most of the difference between TKO  and WT  could be restored by a single allele, although there was a small but significant improvement between 2 and 4 alleles. The fact that this difference was significant, but the differences between 1 and 2 alleles, and 1 and 4 alleles were not, may reflect a real difference between these groups, or may reflect the imbalanced numbers of animals in each group. The group with 2 alleles included animals that were WT for Hlf but lacked Tef (N=8), animals that were WT for Tef and lacked Hlf (N=9), and trans-Het animals that were heterozygous for both Hlf and Tef (N=7). A separate analysis of variance of these three subgroups revealed that the means  were not significantly different (p=0.28), consistent with the hypothesis that alleles of Hlf and Tef can substitute for one another in their ability to regulate the homeostatic response to activity deprivation.”Since the model with the highest adjusted R5. Sample sizes  should be clearly specified for each experiment. Are some data sets only based on two cultures ? Again, a power analysis may be helpful to determine sample sizes.We performed additional experiments and added additional data to figure 6. The N’s for each major group are stated in the legend (#cultures) and the precise genotypes for every experiment and the # neurons selected in each slice are provided in the accompanying supporting data file. We did not perform a power analysis for each model.6. The major (recorded) effect underlying the increase in network excitability is an increase in mEPSC frequency. Does this indicate that the mechanisms that constrain homeostatic plasticity mainly work on presynaptic mechanisms, or an increase in synapse number? These possibilities should be also discussed.We add a discussion of potential mechanism underlying this change to the Discussion section of the manuscript:“Although two days of activity blockade in dissociated cortical cultures were initially found to produce scaling up of EPSC amplitudes without accompanying changes in mEPSC frequency , multiple subsequent studies have found evidence for changes in both amplitude and frequency as found here . Changes in mini frequency are typically interpreted as reflecting increased presynaptic release, either via increases in the numbers of synapses or active release sites, or via changes in the rate at which spontaneous, action potential independent release occurs at each site.”7. TTX application increases mEPSC frequency by around two-fold and does not affect other recorded parameters, such as excitability. How could a two-fold increase in mEPSC frequency translate into a four-fold increase in calcium peak frequency? Is there any evidence for a supralinear increase in network activity with regard to miniature frequency? This issue should be discussed.With inclusion of additional data, the increase in mEPSC frequency following TTX was 1.7-fold larger in the TKO than in WT  at 2 days and 2.5-fold greater at 5 days. We added discussion of the relationship in the following paragraph:“Although the increase observed in mEPSC frequency (1.7-fold greater in TKO than WT), was lower than the relative increase in activity levels, measured from the frequency of calcium transients (2.5-fold greater in TKO than WT at 5 days), these two measures need not be linearly related. First, mini frequency can be distinct from action potential evoked release  and second, in a highly recurrent network, the relationship between firing and synaptic strength can be nonlinear .”8. What is the evidence for 'exaggerated' homeostatic plasticity in TKO cultures? Can they rule out that TKO neurons compensate better? This possibility should be discussed unless they can exclude the possibility that TKO cultures indeed do not retarget set-point activity.Although we are not positive we understand the point the reviewer is making, we think he/she is suggesting that we do not know whether the genetic manipulation changes rebound activity following activity deprivation because of a change in the vigor or speed with which the network attempts to restore activity (which we refer to as exaggerated homeostatic plasticity) or a change in the set point to which activity is trying to return, or both.We directly tested this possibility in the experiment shown in figure 2 supplement 2. We observe that in the TKO, rebound activity is indeed higher, but it returns to the same baseline level after two days of recovery in normal media lacking TTX. We realize that we did not adequately highlight the significance of this result and thank the reviewer for spurring us to make this clearer. We added the following sentences to the Results section of the manuscript (line 174):“In addition, changes in activity following rebound from deprivation could reflect either a change in the vigor of the circuit’s attempt to restore activity (i.e. enhanced homeostatic plasticity) or a persistent change in the setpoint to which activity is returned , or both. To test whether the transcriptional restraint of homeostasis is required for bidirectional flexibility and to assess whether the setpoint had changed, we asked whether the network is able to return back to baseline activity levels when the activity blockade is removed. We measured network activity immediately after the end of silencing with TTX as well as following two days of recovery in TTX-free media. In WT slices, activity deprivation causes hyperactivity, evident from a two-fold rise in the peak frequency of the calcium activity. However, this exuberant activity is restored back to baseline levels within two days following restoration of action potential firing. In the mutant, even though the initial response to TTX is exaggerated, the network is also able to return to baseline levels following two days of recovery, to levels indistinguishable from WT . These data suggest that the recovery from a high activity state is not diminished in the TKO and suggests that the mutation in fact produces exaggerated homeostatic plasticity rather than a change in activity setpoint.”Other comments:1. It would be very helpful if the abstract could contain more specific information We have reworked the abstract to be more descriptive and to include these details.2. The more pronounced increase in mEPSC frequency upon TTX treatment in TKO cultures compared to WT  appears more robust than the corresponding changes in calcium peak frequency . However, they should also test for an interaction between treatment and genotype to support their conclusion by statistics for the data shown in figure 3B, C.We now include these statistical analyses including the interaction between treatment and genotype in the figure legend.3. Similarly, although not statistically significant, the decrease in mIPSC frequency upon TTX treatment seems less pronounced in TKO cultures . Could they run a power analysis and test for treatment-group interaction as well?We now test for interactions between the treatment and the genotype and report the findings in the figure legend along with a power analysis of the sample size that would be required for the observed difference to be significant:“Two-way ANOVA revealed a significant main effect of TTX treatment (p<0.0001) but not genotype (p=0.54). There was no significant interaction between treatment and genotype (p=0.40), N=28 for WT control, N=37 for WT TTX, N=23 for TKO control, N=20 for TKO TTX. TTX treatment decreased mIPSC frequency in WT  but not in TKO cells . mIPSC frequency in TTX-treated cells is not different in TKO slices compared to WT (p=0.72). The normalized change in frequency  was 0.55 in WT and 0.70 in TKO. We performed a power analysis that revealed that for the observed effect size and variance a sample of 68 neurons per condition would be required for significance.”4. mIPSC amplitudes are decreased in TKO cultures, and there is no further decrease upon TTX application . First, the decrease in baseline mIPSC amplitude in TKO is interesting, and may represent a homeostatic response that counteracts a potential increase in excitability/ calcium peak frequency under baseline conditions . This possibility should be discussed in addition to previous work indicating reduced glutamate decarboxylase function in PLP KOs. Second, could the lack of a decrease in mIPSC amplitude after TTX in TKO neurons also oppose increased network excitability? This possibility should be also discussed.The decrease in mIPSC amplitude observed would not be expected to represent a homeostatic response counteracting increased excitability/ calcium peak frequency since it would exacerbate the resulting increase in network excitability. Furthermore, as noted above, additional experiments make it clearer that baseline frequency is not altered. The prior work on reduced glutamate decarboxylase function is discussed in the following paragraph:“Gachon et al.  first reported that deletion of the PARbZIP proteins TEF, HLF and DBP caused spontaneous and audiogenic seizures. They suggested that this may reflect effects on neurotransmitter metabolism caused by a reduction in pyridoxal phosphate (PLP) since pyridoxal kinase, which catalyzes the last step in the conversion of vitamin B6 into PLP is a target of the PAR bZIP proteins. PLP is a required cofactor for decarboxylases and other enzymes involved in the synthesis and metabolism of GABA, glutamate and the biogenic amine neurotransmitters including dopamine, serotonin and histamine. Using HPLC they found no changes in GABA or glutamate, but reduced levels of dopamine, serotonin and histamine in the knockout animals. Although changes in amine transmitters could potentially contribute to phenotypes in vivo, they are unlikely to contribute to plasticity in cortical slice cultures which do not include the brainstem nuclei from which these projections arise. Reduced glutamate decarboxylase action could potentially have contributed to the observed baseline reduction in mIPSCs since heterozygous  and homozygous  mutants of Gad1, the gene encoding the GAD67 isoform of glutamic acid decarboxylase, have reduced mIPSC amplitudes. However, this does not account for the enhanced homeostatic overshoot following activity blockade, since in the TKO animals, activity blockade did not produce any further reduction in inhibition but produced robust changes at excitatory synapses.”5. TTX treatment results in a rapid regulation of Hlf and Tef mRNA on the hour time scale . The mEPSC/IPSC recordings were carried out in the presence of TTX. It is thus crucial to mention the time window during which WT recordings were conducted with regard to the beginning of TTX incubation to assess whether Hlf or Tef transcripts could be increased in the control group.We added the following detail to the methods section of the manuscript.“The slices were incubated in TTX only during active recording, which lasted no more than 30 minutes for each slice.”6. I suggest using the SI unit Hz instead of peaks/minute for the calcium imaging data.We re-plotted all of our data in Hz.7. The figure labels "mutant" could be more specific .We relabeled our figures as suggested.8. Some figures are not referenced in the text.We have now included reference to all the figures in the text.9. It should be briefly described how miniature PSCs and APs were analyzed .:We added the following description to the methods“Threshold-based detection of mPSCs and action potentials were implemented using custom-written IGOR scripts equipped with routines for baseline subtraction, custom filtering and measurements of intervals, amplitudes and kinetic properties.”Reviewer #3 (Recommendations for the authors):I have a few suggestions for the authors that may strengthen the manuscript:1. Quantification of the network activity homeostasis : The authors provided quantification of frequency of Ca events (probably associated with spike bursts). It is unclear why the amplitude was not taken into account. Mean firing rate should be better reflected by frequency x amplitude calculation.Although in principle the amplitude of calcium transients may provide additional information about the magnitude of the firing underlying these events, we found that the distribution of event amplitudes were dependent upon other experimental factors such as the amount of calcium indicator expressed as well as optical factors such as the depth of the cell in the slice. Although it may be possible with further calibration experiments to control for some of these factors, we decided instead to simply use the calcium transients as indicative of periods of neuronal firing without attempting to ascertain the precise number of action potentials contributing. We added the following summary of this idea to the methods:“Since the distribution of event amplitudes across cells was potentially dependent on other experimental factors such as the amount of calcium indicator expressed as well as optical factors such as the depth of the cell in the slice, we decided not to try to infer the magnitude of firing from the amplitude of events, but only periods of elevated firing from the timing of events.”2. What is the mechanism that links spike silencing to activation of PAR-bZIP TFs by inactivity? Is it mediated by the previously described mechanisms related to T-type Ca channels  or L-type Ca channels and CaMK4 ? This should be at least discussed.We added the following speculative paragraph to the discussion:“The mechanisms linking activity deprivation to Tef and Hlf activation were not directly addressed in this work, but seem likely to depend on reduced calcium influx. Prior studies have suggested alternately that scaling up of mEPSC amplitudes depends upon calcium influx through either T-type  or L-type  calcium channels. The former pathway has also been found to depend on the activity-dependent transcription factors Elk1 and SRF. Activation of the constraining TFs Tef and Hlf could be secondary or delayed responses dependent on changes in the transcription and translation of other activity-dependent TFs, or may represent a primary response to activity deprivation, analogous to, but in the opposite direction of the well-studied immediate early genes such as Fos, Arc and others.”3. I am not sure I agree with the interpretation of mIPSC results. The results show that both frequency and amplitude homeostatic down-regulation are disabled by TF deletion. This, in my view, may be a possible compensation to prevent a further increase in the E/I ratio (meaning that without it epilepsy would be even more severe).We agree that we can’t exclude this possibility and add the following statement to the discussion:“We cannot rule out the possibility that although baseline activity is normal, the baseline reduction in mIPSC amplitude contributes to subsequent network plasticity indirectly by contributing to induction of the changes in EPSCs observed, or by inducing some form of compensation other than the physiological parameters measured”Statistics: I could not find cell numbers (n) in the legends / text for each experiment.We thank the reviewer for catching the error and now report N values for each experiment.line 179 – did the authors mean removal of silencing?We have corrected the wording and thank the reviewer for pointing it out. The statement now reads:“We measured network activity immediately after the end of silencing with TTX”ab


Response to pain therapy is currently by patient self-report. We demonstrate that by evaluating the neurochemistry of a patient, using two-dimensional Correlated SpectroscopY (2D COSY) in a 3T MRI scanner, response to therapy can be recorded. A chronic temporomandibular joint (TMJ) pain patient was evaluated by a pain physician specializing in temporomandibular disorders (TMD), and by 2D COSY, before, and 6 days after treatment with Botulinum Toxin A. Prior to treatment the self-reported pain score was 8/10 and reduced to 0/10 within 24 h of treatment. The neurochemistry of the patient prior to treatment was typical of chronic pain. In particular, the Fuc-α(1–2) glycans were affected. Following treatment, the substrates, α-L Fucose, were elevated and the Fuc-α(1–2) glycans repopulated. The depletion of the molecule assigned the glutathione cysteine moiety, with chronic pain, is indicative of a Glutathione redox imbalance linked to neurodegeneration. This new approach to monitor pain could help discriminate the relative contributions in the complex interplay of the sensory and affective  components of pain leading to appropriate individualized pharmaceutical drug regimens. The current “gold-standard” for pain assessment are self-report medical questionnaires. Necessarily, the response to the questionnaires are based on the patients' own perception of their pain and their ability to understand information and then communicate this individual experience  glycans have been shown in animal models, to be implicated in the mechanisms underlying neuronal development, learning, memory  disorders affect the masticatory muscles and temporomandibular joints causing pain and dysfunction  in a clinical 3T MR scanner.Here we evaluate the neurochemistry of a patient suffering from chronic TMJ before and after treatment with botulinum toxin A using Institutional ethics approval was received from Queensland Health Metro South Ethics Committee (HREC/17/QPAH/808). All components of this study were conducted in accord with approved guidelines and regulations from relevant governance and institutional bodies. All participants in the study provided written informed consent.n = 14 healthy controls . The patient had experienced a level of pain that made it difficult to concentrate and had a history of successful outcomes from treatment with Botulinum Toxin A, with a cessation of pain within 24 h.A 37-year-old woman with a six-year history of chronic TMJ was recruited for this study and examined by a clinician specializing in TMJ pain. The participant's data was statistically compared to The healthy controls were recruited from a number of sources including social media and local advertising. Participants were included if they were aged between 18 and 65 years. They were assessed by the Structured Clinical Interview for DSM V (SCID) 28 and included if they had had no current DSM-V Axis I disorder and no history of an anxiety or mood disorder, current or past history of neurological disease; major head injury; currently or possibly pregnant or had any contraindications to MRI scanning.Healthy controls were screened by a Clinical Psychologist using a combination of clinical interview and psychometric tests. These tests included a screen to assess symptoms of post-traumatic stress disorder (post-traumatic stress disorder checklist), mood disorders, anxiety disorders , alcohol-related disorders  and history of head injury (Ohio State University TBI checklist). Following the psychological assessment, neuroimaging was conducted.The TMJ participant was imaged prior to Botulinum Toxin A treatment and again 6 days after treatment. All scans were performed on a 3T Prisma scanner  with a 64-channel head and neck coil  at the Princess Alexandra Hospital .Magnetic resonance imaging including T1 and T2 weighted images were obtained for diagnostic reporting and anatomical localization. A 3D T1-weighted magnetization-prepared rapid gradient-echo (MPRAGE) was acquired , for accurate MRS voxel placement.On T1 and T2 weighted imaging an 11 cm sebaceous cyst on the left side of the skull vault was identified. This was considered an incidental finding that was present on T1 weighted imaging at each time point.3 voxel positioned in the posterior cingulate gyrus (PCG), 0 field mapping technique supplied by the vendor (Siemens AG). Each voxel was manually shimmed to ensure that FWHM was not >15 Hz as per the system reported results. All participant data obtained was acceptable for analysis.L-COSY data were acquired from a 3 × 3 × 3 cmData was processed and analyzed using MATLAB , and FelixNMR , a 2D NMR processing software. The post-processing parameters used in Felix were: F2domain , F1 domain   to see how much the pre- and post-deviated from the healthy cohort. We took the peaks in the pre- and post-treatment with z-score of >1.959, which is the equivalent of a p-value of <5%.The average chemical shift, in ppm, of each cross-peak position from the 14 healthy volunteers was then calculated and compared to the patient before and after treatment. The The patient was evaluated by a pain physician specializing in temporomandibular disorders (TMD), and recorded a pain score of 8/10 at the time of the first scan. The treatment for this subject with severe myofascial pain of the temporomandibular region used botulinum toxin injections, administered at another site 2 days after the first scan. There are extensive studies describing the efficacy and safety of botulinum toxin for TMD  in The 2D COSY spectra reporting on the neurochemistry of the patient before and after treatment is shown and compared with typical healthy control spectrum , and the unassigned resonance at , were significantly increased by 25 and 43%, respectively. The resonance at 1.37 ppm has been consistently reproducible, although there is a risk that it may be attributable to noise from the strong lipid signal at 1.2 ppm. Myo-Inositol was also significantly increased by 24%. The fucosylated glycans, Fuc 5 and Fuc 6 were reduced by 21 and 46%, respectively. The two crosspeaks assigned to the substrate free fucose were reduced by 39 and 18%. The other fucosylated glycans were increased as shown in 3 lipid increased significantly above healthy control levels. The α-L-fucose substrate 1, had almost reached equilibrium but α-L-fucose substrate 2 had increased from 18% below healthy controls to 80% above healthy controls albeit with a p-value of only 0.82. Fuc 4 increased significantly to 60% above the level of healthy controls. Fucosylated glycans Fuc 1 and 2 had almost returned to healthy control levels, 6 days after treatment. Fucosylated glycan Fuc 7 remained elevated while Fuc 3 and 6 increased. However, Fucosylated glycan Fuc 6 was still 23% below healthy controls. Fucosylated glycans Fuc 5 had increased from 21% below healthy controls to 16% above the healthy controls.Six days following the successful treatment, the glutathione cysteine moiety had increased by 27%, but was still 17% below that of the healthy controls. Glutathione (GSH) and Threonine decreased to levels significantly below healthy controls, while Lactate, Glx, myo-Inositol and the unassigned resonance were seen returning to healthy control levels. The CHThis is the first report of a detailed neurochemical response of the human brain, following successful treatment for pain. It provides an insight into the neurochemical pathways affected by the high level of pain and how the brain is attempting to readjust after the pain was treated. It is commonly reported that when a person has chronic pain, they have difficulties with cognitive functioning and are unable to concentrate  glycan denoted Fuc 2 is considered a marker of pain intensity (Manuscript under review). Thus, recording a return to normal of this glycan, when the pain level reduced from 8/10 to 0/10, is consistent with this finding. Glycans have important recognition roles in neuronal regulation and are important in the metabolic requirements of the peripheral and central systems  glycans currently assigned  and ableImportant is the large depletion of the diagonal resonance at 8.13 ppm of 44% in the chronic pain state . This diThe capacity to monitor the effect of pain on the human brain and how it responds to successful treatment, is the first step in a personalized approach to monitoring therapy objectively. It also provides strong clues as to the biochemical pathways affected by chronic pain, and how they recover. An objective measurement of pain could help in discriminating the relative contributions in the complex interplay of the sensory and affective  components of pain, leading to appropriate individualized pharmaceutical drug regimens.The data that support the findings of this study are available on request from the corresponding author CM. The data is not publicly available due to privacy and consent concerns raised by ethical boards.The studies involving human participants were reviewed and approved by Queensland Health Metro South Ethics Committee (HREC/17/QPAH/808). The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.CM, GG, and JW: study conception and design. JW and EV: acquisition of data. CM, DL, GG, and JW: analysis and interpretation of data. JW and CM: drafting of the manuscript. CM, DL, EV, GG, and JW: critical revision. All authors contributed to the article and approved the submitted version.CM has filed patent registrations in this area. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Tunga penetrans. Female fleas penetrate the skin, particularly at the feet, and cause severe inflammation. This study aimed to characterize disease burden in two highly affected regions in Kenya, to test the use of thermography to detect tungiasis-associated inflammation and to create a new two-level classification of disease severity suitable for mapping, targeting, and monitoring interventions.Tungiasis is a neglected tropical skin disease caused by the sand flea From February 2020 to April 2021, 3532 pupils age 8–14 years were quasi-randomly selected in 35 public primary schools and examined for tungiasis and associated symptoms. Of the infected pupils, 266 were quasi-randomly selected and their households visited, where an additional 1138 family members were examined. Inflammation was assessed using infra-red thermography. A Clinical score was created combining the number of locations on the feet with acute and chronic symptoms and infra-red hotspots.CI): 8.4–10.3]. Based on mixed effects logistic models, the odds of infection with tungiasis among school pupils was three times higher in Kwale  than in Siaya ; three times higher in males than in females  and three times lower among pupils sleeping in a house with a concrete floor . The odds of finding an infected person among the household population during surveys before the COVID-19 pandemic was a third  of that when schools were closed due to COVID-19 restrictions and approximately half  in surveys done after school re-opening (round 3). Infection intensity was positively correlated with inflammation as measured by thermography  and with the clinical score . Based on the two-level classification, severe cases were associated with a threefold higher level of pain  and itching  than mild cases.The overall prevalence of tungiasis among all the school pupils who were randomly selected during survey rounds 1 and 3 was 9.3% [95% confidence interval (Thermography was a valuable addition for assessing morbidity and the proposed two-level classification of disease severity clearly separated patients with mild and severe impacts. The burden of tungiasis was considerably higher in households surveyed during COVID-19 restrictions suggesting underlying risks are found in the home environment more than in school.The online version contains supplementary material available at 10.1186/s40249-023-01080-5. Tunga penetrans, which penetrate the skin, usually of the feet, of their mammalian hosts and stay embedded for their remaining life [Tungiasis is a highly neglected tropical skin disease (NTSD) caused by the female sand flea, ing life . The fleing life  and the ing life . The embTunga penetrans is endemic in the tropics of the Americas and in sub-Saharan Africa with an estimated 668 million people considered to be at risk of infection in sub-Saharan Africa alone [ca alone , 5. In eca alone  althoughca alone . Intensica alone .Sand fleas cause severe morbidity in humans, companion animals and livestock –13. MorbA study conducted in Brazil 20 years ago carefully documented the clinical features of tungiasis . Acute sOverall, the SSAT and SSCT have only rarely been used since they were published. One of the reasons may be that edema, erythema and warmness-to-touch, the signs of inflammation, are difficult to assess, particularly on a dark skin and by non-clinical staff. The SSAT also included scores for the number of sites with flea clusters, and the patient’s experience of pain, itching and sleep disturbance. It was demonstrated that those individuals with the highest infection rate (newly embedded live fleas over time) had the highest SSAT . A separNow that tungiasis has been added to the World Health Organization (WHO) list of NTDs (under scabies and other ectoparasites), governments and organizations will start to plan surveillance and intervention programs, and these will need carefully defined indicators and targets. As has been implemented for other NTDs, initially it will be appropriate to target those individuals with the highest morbidity. For instance, the WHO NTD Roadmap 2021–2030  recommenTo date, disease intensity for tungiasis has been classified in three-tiers, defined using embedded flea counts; mild cases being defined as having 1–5 fleas, moderate cases having 6–30 fleas and severe cases more than 30 fleas , 10, 22.Consequently, in the current study we set out to (i) describe the prevalence and intensity of infection in two regions of Kenya with suspected high disease burden; (ii) simplify the clinical scoring method; (iii) test the use of thermography to assess inflammation; (iv) evaluate the past disease severity classification with respect to symptoms in these populations in Kenya and develop a new classification with only two disease severity groups. The data reported here is part of a larger project aimed at characterizing the disease ecology of tungiasis in East Africa, including a better understanding of the parasite, risk factors for severe tungiasis and its impact on child development and well-being.A cross-sectional observation study of children in primary schools, their families, and homesteads in two regions of Kenya was carried out between February 2020 and April 2021. Primary school children between the age of 8 and 14 years were selected since this is the age group most affected by tungiasis in Kenya .Surveys, following the same procedures, were conducted in the sub-counties of Matuga and Msambweni of Kwale county on the south east coast of Kenya, and in Ugenya sub-county of Siaya county in western Kenya near the border with Uganda Fig. . These cAverage rainfall amount (mm) for each month of the study from October 2019 to April 2021 was retrieved from World Weather Online  for the th  pupil was then selected in each sex and age group until 17 from each was reached, to a total of 102. All selected pupils were examined for tungiasis, and a small questionnaire was administered asking about the floor of the house they sleep in and whether other people in the family are infected. The examinations and interview were conducted by field enumerators trained and supervised by the authors. Out of all tungiasis infected pupils identified in a school, a maximum of ten who reported living in a home with an unsealed soil or sand floor were randomly (paper lottery method) selected for household surveys. If only ten or less than ten were identified in a school, all were selected. We specifically targeted households with unsealed floors since this risk factor has been well-established for tungiasis [Within Kwale and Siaya counties, sub-counties were selected that were known by the county Department of Health to have a high tungiasis burden. Lists of all existing public primary schools in the sub-counties were provided by the county education departments and 35 schools randomly selected using a paper lottery approach. In each school, 51 boys and 51 girls between the age of 8 and 14 years  were quungiasis , 26 and COVID-19 restrictions forced the closure of schools from March to December 2020. Field research activities were however free to recommence from July 2020. Consequently, the survey strategy was adapted to recruit cases through a household-based survey only. In the catchment areas of 11 schools already selected randomly before COVID-19 closures, community health volunteers (CHVs) were asked to invite any children aged 8 to 14 years they considered to be infected, to a location where they could be screened by the study team. Out of all infected children seen through this approach, a maximum of ten were randomly selected for household surveys. This survey strategy was used between August and October 2020 (survey round 2) returning to school-based surveys in January to May 2021 (survey round 3). No school or household was visited more than once. Figure The clinical assessment procedures were the same for the pupils in schools and for the household members of the selected pupils.The feet of the 102 children in each school were washed and dried and systematically examined for the presence of tungiasis by observing nine zones on each foot in order from the largest toe to the smallest toe, the medial side, lateral side, the sole and the heel. Those pupils found to have sand fleas embedded in the feet, were assessed for intensity of infection by counting the number of fleas that were: alive (round white lesion with dark spot at center); dead ; manipulated (lesion from where a flea had clearly been removed) or large clusters of embedded fleas in which individual fleas could not be counted as they were too close together.Infected individuals were also assessed for acute and chronic symptoms by modifying the technique described by Kehr et al. . Both feInfected individuals were also asked to report the amount of pain and, separately, the amount of itching they felt in their feet associated with the embedded fleas using the options: “none at all”, “a little”, “some” or “a lot”.A low-resolution 220 × 160) infra-red camera detecting wavelengths of 8–14 µm  was used to observe the nine zones, both upper and lower surfaces of both feet. These cameras convert the different temperatures detected into a range of colors  were calculated for geographic regions, sexes, age groups and survey round. To test for associations between tungiasis infection status (infected and not infected) and geographic region, sex, age, survey round and rainfall (independent variables), multilevel mixed effects (MLME) logistic models were used with an exchangeable correlation matrix. The unique school ID was included as a random effect for the pupil population and the household unique ID for the household population. Initially, bivariable analyses were run for each independent variable and then multivariable analysis with all variables. Backward elimination was used to develop the final model using Akaike information criteria (AIC) to compare goodness of fit of the models. Bivariable outcomes are presented as odds ratios (OR) and multivariable outcomes as adjusted odds ratios (aOR) calculated as the exponential of the coefficient with 95% CI and P-values.All analyses were conducted in Stata IC version 15.1 . For the pupil and household populations surveyed in schools and homes, prevalence (proportion of examined participants) and 95% confidence intervals  on both feet, plus the number of flea clusters multiplied by 5 (as an estimate for an average number of fleas/cluster). Since infection intensities were not normally distributed, medians and interquartile ranges (IQR) were calculated for schools, regions, sexes, age groups and survey round. Since infection intensity was a positively skewed count variable for cases only, with no zeros, associations with region, sex, age, survey round and rainfall were tested using MLME linear regression models with zero-truncated negative binomial probability distributions and log link functions. The unique school ID was included as a random effect. Backward elimination was used to develop the final model using AIC to compare the goodness of fit of multivariable models. Bivariable outcomes are presented as incidence rate ratios (IRR) and multivariable outcomes and adjusted incidence rate ratios (AIRR) with 95% 2 and the P-value.The correlation of school level prevalence and median infection intensity was tested using linear regression setting the intercept at zero since median infection intensity can only be zero if prevalence is zero. The coefficient is presented as RAcute symptoms scores were calculated by summing the number of zones on the feet exhibiting each symptom, and then the scores for desquamation, fissures, ulcers and abscess were totaled, with a maximum possible score of 72 (9 zones × 2 feet × 4 pathologies). Chronic symptoms scores were calculated by summing the number of zones on the feet exhibiting each symptom and then the scores for hyperkeratosis, peri-ungual hypertrophy, deformed nails and lost nails totaled, with a maximum of 38 . This was different to the previously described method of Kehr et al.  who assiFor the thermography, the infra-red hotspots were considered as a symptom and the total number of zones on the feet with a hotspot was totaled for each patient, with a maximum possible value of 18. Correlations were explored between infra-red scores, the three symptoms scores  and intensity of infection using Spearman rank correlation coefficient since these variables were positively skewed and are presented as rho values in a correlation matrix. Once the infra-red scores were seen to correlate with the other variables, they were added to create a new clinical score.CI and P-values. To identify a possible new two-level classification for disease severity, a scatter plot was created of infection intensity by clinical score for all infected cases. The clinical scores were used as these were a measure of overall morbidity and reflect actual disease severity. The nonparametric Loess regression technique was used to fit a smooth curve through the scatter plot to help see the relationship between the two variables. The previous threshold levels for defining three levels of disease severity based on infection intensity alone [To evaluate the association of the old disease intensity groups based on flea counts with the new clinical score, bivariable MLME linear models were used with negative binomial probability distributions, log link functions and exchangeable correlations. The unique school ID was included as a random effect. Outcomes are presented as incidence rate ratios (IRR) with 95% ty alone , 22 are Children age 8–14 years were screened for tungiasis in 35 primary schools, 15 schools in Msambweni/Matuga  and 20 in Ugenya (Siaya), of which 8 were completed in 2020 (survey round 1) and the remainder in 2021 (survey round 3) when schools re-opened after the COVID-19 shut-down . In multivariable models, boys had a three-fold higher odds of infection than girls , even within the narrow age range of examined pupils, 8–14 years. Pupils in Siaya had a nearly three-fold lower odds of infection (aOR = 0.36) than those in Kwale, as did pupils who sleep in a house with an unsealed sand or mud floor compared to those with a concrete floor (aOR = 0.36). There was no association with rainfall. The maps in Fig. The overall prevalence of tungiasis among all the school pupils who were randomly selected during survey rounds 1 and 3 was 9.3% (95% CI: 47.4–53.2). As among the pupils, males had a higher odds of infection than females , but adults and children over 14 years had 50 to 100-fold lower odds of infection compared to the youngest age group.By selection criteria, all the 266 households selected had at least one child age 8–14 years infected and an unsealed sand or mud floor. The overall prevalence in these households was 50.2% (95% aOR = 0.44). The map in Fig. When adjusted for sex and age, households examined during round 1 had a three-fold lower odds (AOR 0.33) of being infected than those seen in round 2, and households seen in round 3 had a more than two-fold lower odds of infection to those in round 2 (n = 44), they were excluded from analyses. Of the remaining 633 individuals with full data sets, 406 (64.1%) were from Kwale, 430 (67.9%) were male and 503 (79.5%) were age 8–14 years.To investigate infection intensity and the symptoms caused by embedded fleas, data for all infected individuals were combined  which goes hand in hand with the overall lower prevalence in that region. Boys had a higher infection intensity than females (aIRR = 1.27) and those examined in survey round 1 (aIRR = 0.5) and 3 (aIRR = 0.63) had lower infection intensity than those in round 2. There was no association between infection intensity with age nor rainfall.The infection intensity for the 633 cases ranged from 1 to 154 fleas, with a median intensity of 13 fleas (IQR: 5–28) . However, the scatter plot in Fig. The school prevalence ranged from 0% in four schools to 26% in one school Fig. , with moP < 0.001), the strongest correlation being for infection intensity score with desquamation and deformed nails  were recorded to have at least one symptom. The most common was desquamation (88%), considered to be an acute symptom, followed by deformed nails (74%) and peri-ungual hyperkeratosis (58%) which are classified as chronic symptoms  of ten infected children from all infected children age 8 to 14 years identified during screening.Another explanation could be that the infected households visited during round 2 may always have had a higher household prevalence than those visited during round 1 and 3. Since the schools catchment areas targeted in round 2 are evenly distributed among those surveyed in round 1 and 3, and the schools and their catchment areas targeted in all rounds were all selected randomly, this is unlikely. Longitudinal cohort studies of schools and households may be one study design to avoid this, but the results of subsequent visits run the risk of being biased as the families become more aware of disease transmission and change behavior. In addition, research ethics compel researchers to provide access to treatment for cases which is likely to alter subsequent prevalence.Changes in weather patterns could have been responsible since low rainfall has been shown to be associated with higher prevalence previously . HoweverThe higher prevalence during school closure could also have been caused by the extended time at home and the different behaviors during that time. During school closures children were spending all day at home or at homes of friends and relatives, resulting in more exposure to transmission sites per unit of time compared to spending most of the day in school classrooms. This would corroborate our previous finding  that chiThe infection intensity among infected children was also significantly higher during school-closure. Since infection intensity was positively correlated with clinical scores and higher levels of pain and itching, this means that school closures due to COVID-19 resulted in more tungiasis-related suffering in children.Our study has confirmed previous findings of the heterogeneity of tungiasis distribution , 22 withThis study corroborates findings from past surveys from Brazil , CamerooAs might be expected, the intensity of infection in school pupils was positively correlated to the prevalence, albeit with some outlier schools. The more children are infected in a community, the more contamination of the environment with off-host stages and the higher the exposure of others to infection. Even if most transmission is happening within homes , childreWhile some past studies have described tungiasis as a highly aggregated disease where the majority of cases had an intensity of infection of 1–5 fleas and only a few cases had a high intensity of infection with more than 30 fleas , 22, 35,Our simplified symptoms score is appropriate since both the acute and chronic symptoms scores correlated significantly with the infection intensity, and with each other. The most commonly reported symptom in previous studies was deformed nails, being as high as 98% of cases in a study focusing only on severe cases  and was To further simplify the assessment of inflammation we adapted the methodology of Schuster et al.  who demoAs governments and organizations begin to map tungiasis in their countries and to implement intervention programs, it will be important to have clear definitions for identifying target populations and intervention goals. Previously the three-tier classification of disease severity has been used, based only on flea counts with no description of how this correlated with symptoms. Since WHO guidelines for the control of other NTDs use targets based on two-tier levels of morbidity caused by different infection intensities, we propose a two-tier classification for tungiasis based on the Clinical score of 10. As with other NTDs, assessment of symptoms is time consuming, and parasite counts quicker and simpler to conduct for large scale public health projects, so we recommend a total flea count of 10 is an appropriate threshold for severe disease.This study had three main limitations. While the pandemic accidentally afforded the opportunity to observe the impact of school closures, it also meant we could not continue the randomized sampling of pupils in all communities that was needed to obtain prevalence estimates across all sampling sites. Secondly, school-based sampling means the study would have missed children from the poorest families who cannot afford to send their children to school and given the association of tungiasis with poverty , possiblTungiasis is a highly heterogeneous disease with the prevalence in schools varying considerably. Prevalence of tungiasis was positively correlated with infection intensity and with morbidity. Simplified thermography is a valuable addition for assessing morbidity associated with tungiasis and will be useful to assess the efficacy of treatment in future clinical trials. Along with other pathologies, thermography helped to classify mild and severe disease which will be used in our future studies on the impact of tungiasis. Fortuitously, the survey spanned the COVID-19 school closures and demonstrated that when children spent an extended period out of school, the prevalence, intensity and morbidity of tungiasis increased significantly indicating prevention measures and education should target household level infrastructure and behavior.Additional file 1: Frequency of acute and chronic symptoms associated with tungiasis. The number and percent of patients with acute and chronic symptoms.Additional file 2: Spearman Correlation of individual flea counts and tungiasis associated acute symptoms. Description: a spearman correlation matrix with rho and p-value for each flea type count  and the number of sites on the feet with each of the acute symptoms .Additional file 3: Spearman Correlation of individual flea counts and tungiasis associated chronic. Description: a spearman correlation matrix with rho and p-value for each flea type count  and the number of sites on the feet with each of the chronic symptoms Additional file 4: Elson Pupil dataset.Additional file 5: Elson Households dataset.Additional file 6: Elson Child cases dataset.