OSCR

Nociceptor circadian clock genes control excitability and pain perception in mice in a sex- and time-dependent manner.

Code ↔ Paper

7 matches between paragraphs of the paper and lines of its authors' code, computed by the harvester (lexical-v1). Click a colored paragraph or line to see its counterpart.

The 7 matches
  1. [1] § Methods › RNA sequencing ↔ Figure5a/0_helpers/OutlierDetect.R, lines 14–53 · score 0.64 · outlier detection, arrayQualityMetrics
  2. [2] § Methods › RNA sequencing ↔ Figure5a/0_helpers/VstTransform.R, lines 20–30 · score 0.62 · variance stabilizing transformed, DESeq2, genes
  3. [3] § Methods › Whole-cell recordings ↔ VoltageClamp_AK42.m, lines 1–65 · score 0.61 · voltage clamp, series resistance, Labs, baseline, cell
  4. [4] § Methods › Whole-cell recordings ↔ VoltageClamp_AK42.m, lines 1–65 · score 0.61 · Patch clamp, voltage clamp, resistance, capacitance, cells
  5. [5] § Methods › Whole-cell recordings ↔ VoltageClamp_AK42.m, lines 318–443 · score 0.56 · membrane resistance, series resistance, pulses, mM, clamp
  6. [6] § Methods › RNA sequencing ↔ Figure5a/3_naiveDrg/3_deseqCandidate/1.0_getKeggGenes.R, lines 1–56 · score 0.55 · ion channel, KEGG, br, mmu04040, candidate, genes
  7. [7] § Methods › Whole-cell recordings ↔ Axograph_to_Matlab.m, lines 1–77 · score 0.51 · Patch clamp, Axograph, resistance, capacitance, mice

Paper

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The authors' code

MATLAB · 592 lines · 37 KB · no license · 3 matches

  1. function AK42analysis
  4. Protocol=[0 80 0 114 -2 111 0 116 0 111 0 99 0 111 0 108 0 32 0 58];
  5. SeriesResistance=[0 83 0 101 0 114 0 105 0 101 0 115 0 32 0 82 0 101 0 115 0 105 0 115 0 116 0 97 0 110 0 99 0 101];
  6. MembraneCapacitance=[0 77 0 101 0 109 0 98 0 114 0 97 0 110 0 101 0 32 0 67 0 97 0 112 0 97 0 99 0 105 0 116 0 97 0 110 0 99 0 101 0 32 0 32 0 61 0 32 0 32];
  7. MembraneResistance=[0 77 0 101 0 109 0 98 0 114 0 97 0 110 0 101 0 32 0 82 0 101 0 115 0 105 0 115 0 116 0 97 0 110 0 99 0 101 0 32 0 32 0 32 0 32 0 32 0 32 0 32 0 32 0 61 0 32 0 32];
  9. globalpath='C:\Users\aurel\Documents\GhasemlouLab\Data\Circadian_experiment\PatchClamp\ExVivo\C57BL6\MaleVCAK42';
  10. globalpath='C:\Users\aurel\Documents\GhasemlouLab\Data\Circadian_experiment\PatchClamp\ExVivo\Nav1.8_Bmal1\MaleVCAK42';
  11. cd(globalpath)
  13. AllfilenameAK42=[];
  14. AllfilenameBaseline=[];
  15. newline = char(10); %char(10) is the character for line-break, or "enter"
  17. [~,AllfilenameAK42] = system('dir /s /b *40_Step_VC_Koster2020_hold4mV_AK42.axgd'); %you can also simply write: !dir /s /b *.mat
  18. AllfilenameAK42 = strsplit(AllfilenameAK42,newline)';
  19. AllfilenameAK42(cellfun(@isempty,AllfilenameAK42))=[];
  21. Global=[];
  22. GlobalData=[];
  23. GlobalData.Cells=[];
  24. GlobalData.sizedata=[];
  26. counter=1;
  28. for f=1:size(AllfilenameAK42,1)
  29. filepathAK42=AllfilenameAK42{f};
  30. [dataAK42,~] = importaxographx(filepathAK42);
  31. data=dataAK42*10^12;%in pA
  33. filepathAK42=strrep(filepathAK42,'(','');
  34. filepathAK42=strrep(filepathAK42,')','');
  35. ii=strfind(filepathAK42,'\');
  37. date=filepathAK42(ii(end-3)+1:ii(end-2)-1);
  38. ZT=filepathAK42(ii(end-2)+1:ii(end-1)-1);
  39. cell=filepathAK42(ii(end-1)+1:ii(end)-1);
  40. nrun=filepathAK42(ii(end)+7:ii(end)+9);
  41. run=['AK42_run', nrun];
  44. Global.(date).(ZT).(cell).(run).Date=date;
  45. Global.(date).(ZT).(cell).(run).ZT=ZT;
  46. Global.(date).(ZT).(cell).(run).Cell=cell;
  47. Global.(date).(ZT).(cell).(run).Run=run;
  50. if size(data, 2)>=13 % in case recording interrupted, do not analyzed it
  51. Global.(date).(ZT).(cell).(run).rawdata=data;
  53. Global.(date).(ZT).(cell).(run).IVcurve_m100_before=nanmean(data(8000:10000,2)); %pA
  54. Global.(date).(ZT).(cell).(run).IVcurve_m90_before=nanmean(data(8000:10000,3)); %pA
  55. Global.(date).(ZT).(cell).(run).IVcurve_m80_before=nanmean(data(8000:10000,4)); %pA
  56. Global.(date).(ZT).(cell).(run).IVcurve_m70_before=nanmean(data(8000:10000,5)); %pA
  57. Global.(date).(ZT).(cell).(run).IVcurve_m60_before=nanmean(data(8000:10000,6)); %pA
  58. Global.(date).(ZT).(cell).(run).IVcurve_m50_before=nanmean(data(8000:10000,7)); %pA
  59. Global.(date).(ZT).(cell).(run).IVcurve_m40_before=nanmean(data(8000:10000,8)); %pA
  60. Global.(date).(ZT).(cell).(run).IVcurve_m30_before=nanmean(data(8000:10000,9)); %pA
  61. Global.(date).(ZT).(cell).(run).IVcurve_m20_before=nanmean(data(8000:10000,10)); %pA
  62. Global.(date).(ZT).(cell).(run).IVcurve_m10_before=nanmean(data(8000:10000,11)); %pA
  63. Global.(date).(ZT).(cell).(run).IVcurve_0_before=nanmean(data(8000:10000,12)); %pA
  64. Global.(date).(ZT).(cell).(run).IVcurve_10_before=nanmean(data(8000:10000,13)); %pA
  65. Global.(date).(ZT).(cell).(run).IVcurve_20_before=nanmean(data(8000:10000,14)); %pA
  67. Global.(date).(ZT).(cell).(run).IVcurve_m100_all=nanmean(data(10100:25000,2)); %pA
  68. Global.(date).(ZT).(cell).(run).IVcurve_m90_all=nanmean(data(10100:25000,3)); %pA
  69. Global.(date).(ZT).(cell).(run).IVcurve_m80_all=nanmean(data(10100:25000,4)); %pA
  70. Global.(date).(ZT).(cell).(run).IVcurve_m70_all=nanmean(data(10100:25000,5)); %pA
  71. Global.(date).(ZT).(cell).(run).IVcurve_m60_all=nanmean(data(10100:25000,6)); %pA
  72. Global.(date).(ZT).(cell).(run).IVcurve_m50_all=nanmean(data(10100:25000,7)); %pA
  73. Global.(date).(ZT).(cell).(run).IVcurve_m40_all=nanmean(data(10100:25000,8)); %pA
  74. Global.(date).(ZT).(cell).(run).IVcurve_m30_all=nanmean(data(10100:25000,9)); %pA
  75. Global.(date).(ZT).(cell).(run).IVcurve_m20_all=nanmean(data(10100:25000,10)); %pA
  76. Global.(date).(ZT).(cell).(run).IVcurve_m10_all=nanmean(data(10100:25000,11)); %pA
  77. Global.(date).(ZT).(cell).(run).IVcurve_0_all=nanmean(data(10100:25000,12)); %pA
  78. Global.(date).(ZT).(cell).(run).IVcurve_10_all=nanmean(data(10100:25000,13)); %pA
  79. Global.(date).(ZT).(cell).(run).IVcurve_20_all=nanmean(data(10100:25000,14)); %pA
  81. Global.(date).(ZT).(cell).(run).IVcurve_m100_early=nanmean(data(10100:14100,2)); %pA
  82. Global.(date).(ZT).(cell).(run).IVcurve_m90_early=nanmean(data(10100:14100,3)); %pA
  83. Global.(date).(ZT).(cell).(run).IVcurve_m80_early=nanmean(data(10100:14100,4)); %pA
  84. Global.(date).(ZT).(cell).(run).IVcurve_m70_early=nanmean(data(10100:14100,5)); %pA
  85. Global.(date).(ZT).(cell).(run).IVcurve_m60_early=nanmean(data(10100:14100,6)); %pA
  86. Global.(date).(ZT).(cell).(run).IVcurve_m50_early=nanmean(data(10100:14100,7)); %pA
  87. Global.(date).(ZT).(cell).(run).IVcurve_m40_early=nanmean(data(10100:14100,8)); %pA
  88. Global.(date).(ZT).(cell).(run).IVcurve_m30_early=nanmean(data(10100:14100,9)); %pA
  89. Global.(date).(ZT).(cell).(run).IVcurve_m20_early=nanmean(data(10100:14100,10)); %pA
  90. Global.(date).(ZT).(cell).(run).IVcurve_m10_early=nanmean(data(10100:14100,11)); %pA
  91. Global.(date).(ZT).(cell).(run).IVcurve_0_early=nanmean(data(10100:14100,12)); %pA
  92. Global.(date).(ZT).(cell).(run).IVcurve_10_early=nanmean(data(10100:14100,13)); %pA
  93. Global.(date).(ZT).(cell).(run).IVcurve_20_early=nanmean(data(10100:14100,14)); %pA
  95. Global.(date).(ZT).(cell).(run).IVcurve_m100_late=nanmean(data(23000:25000,2)); %pA
  96. Global.(date).(ZT).(cell).(run).IVcurve_m90_late=nanmean(data(23000:25000,3)); %pA
  97. Global.(date).(ZT).(cell).(run).IVcurve_m80_late=nanmean(data(23000:25000,4)); %pA
  98. Global.(date).(ZT).(cell).(run).IVcurve_m70_late=nanmean(data(23000:25000,5)); %pA
  99. Global.(date).(ZT).(cell).(run).IVcurve_m60_late=nanmean(data(23000:25000,6)); %pA
  100. Global.(date).(ZT).(cell).(run).IVcurve_m50_late=nanmean(data(23000:25000,7)); %pA
  101. Global.(date).(ZT).(cell).(run).IVcurve_m40_late=nanmean(data(23000:25000,8)); %pA
  102. Global.(date).(ZT).(cell).(run).IVcurve_m30_late=nanmean(data(23000:25000,9)); %pA
  103. Global.(date).(ZT).(cell).(run).IVcurve_m20_late=nanmean(data(23000:25000,10)); %pA
  104. Global.(date).(ZT).(cell).(run).IVcurve_m10_late=nanmean(data(23000:25000,11)); %pA
  105. Global.(date).(ZT).(cell).(run).IVcurve_0_late=nanmean(data(23000:25000,12)); %pA
  106. Global.(date).(ZT).(cell).(run).IVcurve_10_late=nanmean(data(23000:25000,13)); %pA
  107. Global.(date).(ZT).(cell).(run).IVcurve_20_late=nanmean(data(23000:25000,14)); %pA
  109. Global.(date).(ZT).(cell).(run).IVcurve_m100_after=nanmean(data(25010:27010,2)); %pA
  110. Global.(date).(ZT).(cell).(run).IVcurve_m90_after=nanmean(data(25010:27010,3)); %pA
  111. Global.(date).(ZT).(cell).(run).IVcurve_m80_after=nanmean(data(25010:27010,4)); %pA
  112. Global.(date).(ZT).(cell).(run).IVcurve_m70_after=nanmean(data(25010:27010,5)); %pA
  113. Global.(date).(ZT).(cell).(run).IVcurve_m60_after=nanmean(data(25010:27010,6)); %pA
  114. Global.(date).(ZT).(cell).(run).IVcurve_m50_after=nanmean(data(25010:27010,7)); %pA
  115. Global.(date).(ZT).(cell).(run).IVcurve_m40_after=nanmean(data(25010:27010,8)); %pA
  116. Global.(date).(ZT).(cell).(run).IVcurve_m30_after=nanmean(data(25010:27010,9)); %pA
  117. Global.(date).(ZT).(cell).(run).IVcurve_m20_after=nanmean(data(25010:27010,10)); %pA
  118. Global.(date).(ZT).(cell).(run).IVcurve_m10_after=nanmean(data(25010:27010,11)); %pA
  119. Global.(date).(ZT).(cell).(run).IVcurve_0_after=nanmean(data(25010:27010,12)); %pA
  120. Global.(date).(ZT).(cell).(run).IVcurve_10_after=nanmean(data(25010:27010,13)); %pA
  121. Global.(date).(ZT).(cell).(run).IVcurve_20_after=nanmean(data(25010:27010,14)); %pA
  123. Global.(date).(ZT).(cell).(run).IVcurve_m100_peakafter=max(data(25010:27010,2)); %pA
  124. Global.(date).(ZT).(cell).(run).IVcurve_m90_peakafter=max(data(25010:27010,3)); %pA
  125. Global.(date).(ZT).(cell).(run).IVcurve_m80_peakafter=max(data(25010:27010,4)); %pA
  126. Global.(date).(ZT).(cell).(run).IVcurve_m70_peakafter=max(data(25010:27010,5)); %pA
  127. Global.(date).(ZT).(cell).(run).IVcurve_m60_peakafter=max(data(25010:27010,6)); %pA
  128. Global.(date).(ZT).(cell).(run).IVcurve_m50_peakafter=max(data(25010:27010,7)); %pA
  129. Global.(date).(ZT).(cell).(run).IVcurve_m40_peakafter=max(data(25010:27010,8)); %pA
  130. Global.(date).(ZT).(cell).(run).IVcurve_m30_peakafter=max(data(25010:27010,9)); %pA
  131. Global.(date).(ZT).(cell).(run).IVcurve_m20_peakafter=max(data(25010:27010,10)); %pA
  132. Global.(date).(ZT).(cell).(run).IVcurve_m10_peakafter=max(data(25010:27010,11)); %pA
  133. Global.(date).(ZT).(cell).(run).IVcurve_0_peakafter=max(data(25010:27010,12)); %pA
  134. Global.(date).(ZT).(cell).(run).IVcurve_10_peakafter=max(data(25010:27010,13)); %pA
  135. Global.(date).(ZT).(cell).(run).IVcurve_20_peakafter=max(data(25010:27010,14)); %pA
  137. %first 10ms after capacitance transient
  138. Global.(date).(ZT).(cell).(run).IVcurve_m100_initial=nanmean(data(10050:10100,2)); %pA
  139. Global.(date).(ZT).(cell).(run).IVcurve_m90_initial=nanmean(data(10050:10100,3)); %pA
  140. Global.(date).(ZT).(cell).(run).IVcurve_m80_initial=nanmean(data(10050:10100,4)); %pA
  141. Global.(date).(ZT).(cell).(run).IVcurve_m70_initial=nanmean(data(10050:10100,5)); %pA
  142. Global.(date).(ZT).(cell).(run).IVcurve_m60_initial=nanmean(data(10050:10100,6)); %pA
  143. Global.(date).(ZT).(cell).(run).IVcurve_m50_initial=nanmean(data(10050:10100,7)); %pA
  144. Global.(date).(ZT).(cell).(run).IVcurve_m40_initial=nanmean(data(10050:10100,8)); %pA
  145. Global.(date).(ZT).(cell).(run).IVcurve_m30_initial=nanmean(data(10050:10100,9)); %pA
  146. Global.(date).(ZT).(cell).(run).IVcurve_m20_initial=nanmean(data(10050:10100,10)); %pA
  147. Global.(date).(ZT).(cell).(run).IVcurve_m10_initial=nanmean(data(10050:10100,11)); %pA
  148. Global.(date).(ZT).(cell).(run).IVcurve_0_initial=nanmean(data(10050:10100,12)); %pA
  149. Global.(date).(ZT).(cell).(run).IVcurve_10_initial=nanmean(data(10050:10100,13)); %pA
  150. Global.(date).(ZT).(cell).(run).IVcurve_20_initial=nanmean(data(10050:10100,14)); %pA
  152. %last 50ms
  153. Global.(date).(ZT).(cell).(run).IVcurve_m100_last=nanmean(data(24750:25000,2)); %pA
  154. Global.(date).(ZT).(cell).(run).IVcurve_m90_last=nanmean(data(24750:25000,3)); %pA
  155. Global.(date).(ZT).(cell).(run).IVcurve_m80_last=nanmean(data(24750:25000,4)); %pA
  156. Global.(date).(ZT).(cell).(run).IVcurve_m70_last=nanmean(data(24750:25000,5)); %pA
  157. Global.(date).(ZT).(cell).(run).IVcurve_m60_last=nanmean(data(24750:25000,6)); %pA
  158. Global.(date).(ZT).(cell).(run).IVcurve_m50_last=nanmean(data(24750:25000,7)); %pA
  159. Global.(date).(ZT).(cell).(run).IVcurve_m40_last=nanmean(data(24750:25000,8)); %pA
  160. Global.(date).(ZT).(cell).(run).IVcurve_m30_last=nanmean(data(24750:25000,9)); %pA
  161. Global.(date).(ZT).(cell).(run).IVcurve_m20_last=nanmean(data(24750:25000,10)); %pA
  162. Global.(date).(ZT).(cell).(run).IVcurve_m10_last=nanmean(data(24750:25000,11)); %pA
  163. Global.(date).(ZT).(cell).(run).IVcurve_0_last=nanmean(data(24750:25000,12)); %pA
  164. Global.(date).(ZT).(cell).(run).IVcurve_10_last=nanmean(data(24750:25000,13)); %pA
  165. Global.(date).(ZT).(cell).(run).IVcurve_20_last=nanmean(data(24750:25000,14)); %pA
  166. end
  168. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
  169. [~,AllfilenameBaseline] = system('dir /s /b *40_Step_VC_Koster2020_hold4mV.axgd');
  170. AllfilenameBaseline = strsplit(AllfilenameBaseline,newline)';
  171. AllfilenameBaseline(cellfun(@isempty,AllfilenameBaseline))=[];
  173. if ~strcmp( AllfilenameBaseline, 'Fichier introuvable')
  174. for b=1:size(AllfilenameBaseline,1)
  175. filepathBaseline=AllfilenameBaseline{b};
  176. [dataBaseline,~] = importaxographx(filepathBaseline);
  177. dataBaseline=dataBaseline*10^12;%in pA
  179. filepathBaseline=strrep(filepathBaseline,'(','');
  180. filepathBaseline=strrep(filepathBaseline,')','');
  181. ib=strfind(filepathBaseline,'\');
  183. date=filepathBaseline(ib(end-3)+1:ib(end-2)-1);
  184. ZT=filepathBaseline(ib(end-2)+1:ib(end-1)-1);
  185. cell=filepathBaseline(ib(end-1)+1:ib(end)-1);
  187. id=filepathBaseline(ib(end)+7:ib(end)+9);
  188. run=['Baseline_run', id];
  190. Global.(date).(ZT).(cell).(run).Date=date;
  191. Global.(date).(ZT).(cell).(run).ZT=ZT;
  192. Global.(date).(ZT).(cell).(run).Cell=cell;
  193. Global.(date).(ZT).(cell).(run).Run=run;
  195. if size(dataBaseline, 2)>=13 % in case recording interrupted, do not analyzed it
  197. Global.(date).(ZT).(cell).(run).rawdata=dataBaseline;
  199. Global.(date).(ZT).(cell).(run).IVcurve_m100_before=nanmean(dataBaseline(8000:10000,2)); %pA
  200. Global.(date).(ZT).(cell).(run).IVcurve_m90_before=nanmean(dataBaseline(8000:10000,3)); %pA
  201. Global.(date).(ZT).(cell).(run).IVcurve_m80_before=nanmean(dataBaseline(8000:10000,4)); %pA
  202. Global.(date).(ZT).(cell).(run).IVcurve_m70_before=nanmean(dataBaseline(8000:10000,5)); %pA
  203. Global.(date).(ZT).(cell).(run).IVcurve_m60_before=nanmean(dataBaseline(8000:10000,6)); %pA
  204. Global.(date).(ZT).(cell).(run).IVcurve_m50_before=nanmean(dataBaseline(8000:10000,7)); %pA
  205. Global.(date).(ZT).(cell).(run).IVcurve_m40_before=nanmean(dataBaseline(8000:10000,8)); %pA
  206. Global.(date).(ZT).(cell).(run).IVcurve_m30_before=nanmean(dataBaseline(8000:10000,9)); %pA
  207. Global.(date).(ZT).(cell).(run).IVcurve_m20_before=nanmean(dataBaseline(8000:10000,10)); %pA
  208. Global.(date).(ZT).(cell).(run).IVcurve_m10_before=nanmean(dataBaseline(8000:10000,11)); %pA
  209. Global.(date).(ZT).(cell).(run).IVcurve_0_before=nanmean(dataBaseline(8000:10000,12)); %pA
  210. Global.(date).(ZT).(cell).(run).IVcurve_10_before=nanmean(dataBaseline(8000:10000,13)); %pA
  211. Global.(date).(ZT).(cell).(run).IVcurve_20_before=nanmean(dataBaseline(8000:10000,14)); %pA
  213. Global.(date).(ZT).(cell).(run).IVcurve_m100_all=nanmean(dataBaseline(10100:25000,2)); %pA
  214. Global.(date).(ZT).(cell).(run).IVcurve_m90_all=nanmean(dataBaseline(10100:25000,3)); %pA
  215. Global.(date).(ZT).(cell).(run).IVcurve_m80_all=nanmean(dataBaseline(10100:25000,4)); %pA
  216. Global.(date).(ZT).(cell).(run).IVcurve_m70_all=nanmean(dataBaseline(10100:25000,5)); %pA
  217. Global.(date).(ZT).(cell).(run).IVcurve_m60_all=nanmean(dataBaseline(10100:25000,6)); %pA
  218. Global.(date).(ZT).(cell).(run).IVcurve_m50_all=nanmean(dataBaseline(10100:25000,7)); %pA
  219. Global.(date).(ZT).(cell).(run).IVcurve_m40_all=nanmean(dataBaseline(10100:25000,8)); %pA
  220. Global.(date).(ZT).(cell).(run).IVcurve_m30_all=nanmean(dataBaseline(10100:25000,9)); %pA
  221. Global.(date).(ZT).(cell).(run).IVcurve_m20_all=nanmean(dataBaseline(10100:25000,10)); %pA
  222. Global.(date).(ZT).(cell).(run).IVcurve_m10_all=nanmean(dataBaseline(10100:25000,11)); %pA
  223. Global.(date).(ZT).(cell).(run).IVcurve_0_all=nanmean(dataBaseline(10100:25000,12)); %pA
  224. Global.(date).(ZT).(cell).(run).IVcurve_10_all=nanmean(dataBaseline(10100:25000,13)); %pA
  225. Global.(date).(ZT).(cell).(run).IVcurve_20_all=nanmean(dataBaseline(10100:25000,14)); %pA
  227. Global.(date).(ZT).(cell).(run).IVcurve_m100_early=nanmean(dataBaseline(10100:14100,2)); %pA
  228. Global.(date).(ZT).(cell).(run).IVcurve_m90_early=nanmean(dataBaseline(10100:14100,3)); %pA
  229. Global.(date).(ZT).(cell).(run).IVcurve_m80_early=nanmean(dataBaseline(10100:14100,4)); %pA
  230. Global.(date).(ZT).(cell).(run).IVcurve_m70_early=nanmean(dataBaseline(10100:14100,5)); %pA
  231. Global.(date).(ZT).(cell).(run).IVcurve_m60_early=nanmean(dataBaseline(10100:14100,6)); %pA
  232. Global.(date).(ZT).(cell).(run).IVcurve_m50_early=nanmean(dataBaseline(10100:14100,7)); %pA
  233. Global.(date).(ZT).(cell).(run).IVcurve_m40_early=nanmean(dataBaseline(10100:14100,8)); %pA
  234. Global.(date).(ZT).(cell).(run).IVcurve_m30_early=nanmean(dataBaseline(10100:14100,9)); %pA
  235. Global.(date).(ZT).(cell).(run).IVcurve_m20_early=nanmean(dataBaseline(10100:14100,10)); %pA
  236. Global.(date).(ZT).(cell).(run).IVcurve_m10_early=nanmean(dataBaseline(10100:14100,11)); %pA
  237. Global.(date).(ZT).(cell).(run).IVcurve_0_early=nanmean(dataBaseline(10100:14100,12)); %pA
  238. Global.(date).(ZT).(cell).(run).IVcurve_10_early=nanmean(dataBaseline(10100:14100,13)); %pA
  239. Global.(date).(ZT).(cell).(run).IVcurve_20_early=nanmean(dataBaseline(10100:14100,14)); %pA
  241. Global.(date).(ZT).(cell).(run).IVcurve_m100_late=nanmean(dataBaseline(23000:25000,2)); %pA
  242. Global.(date).(ZT).(cell).(run).IVcurve_m90_late=nanmean(dataBaseline(23000:25000,3)); %pA
  243. Global.(date).(ZT).(cell).(run).IVcurve_m80_late=nanmean(dataBaseline(23000:25000,4)); %pA
  244. Global.(date).(ZT).(cell).(run).IVcurve_m70_late=nanmean(dataBaseline(23000:25000,5)); %pA
  245. Global.(date).(ZT).(cell).(run).IVcurve_m60_late=nanmean(dataBaseline(23000:25000,6)); %pA
  246. Global.(date).(ZT).(cell).(run).IVcurve_m50_late=nanmean(dataBaseline(23000:25000,7)); %pA
  247. Global.(date).(ZT).(cell).(run).IVcurve_m40_late=nanmean(dataBaseline(23000:25000,8)); %pA
  248. Global.(date).(ZT).(cell).(run).IVcurve_m30_late=nanmean(dataBaseline(23000:25000,9)); %pA
  249. Global.(date).(ZT).(cell).(run).IVcurve_m20_late=nanmean(dataBaseline(23000:25000,10)); %pA
  250. Global.(date).(ZT).(cell).(run).IVcurve_m10_late=nanmean(dataBaseline(23000:25000,11)); %pA
  251. Global.(date).(ZT).(cell).(run).IVcurve_0_late=nanmean(dataBaseline(23000:25000,12)); %pA
  252. Global.(date).(ZT).(cell).(run).IVcurve_10_late=nanmean(dataBaseline(23000:25000,13)); %pA
  253. Global.(date).(ZT).(cell).(run).IVcurve_20_late=nanmean(dataBaseline(23000:25000,14)); %pA
  255. Global.(date).(ZT).(cell).(run).IVcurve_m100_after=nanmean(dataBaseline(25010:27010,2)); %pA
  256. Global.(date).(ZT).(cell).(run).IVcurve_m90_after=nanmean(dataBaseline(25010:27010,3)); %pA
  257. Global.(date).(ZT).(cell).(run).IVcurve_m80_after=nanmean(dataBaseline(25010:27010,4)); %pA
  258. Global.(date).(ZT).(cell).(run).IVcurve_m70_after=nanmean(dataBaseline(25010:27010,5)); %pA
  259. Global.(date).(ZT).(cell).(run).IVcurve_m60_after=nanmean(dataBaseline(25010:27010,6)); %pA
  260. Global.(date).(ZT).(cell).(run).IVcurve_m50_after=nanmean(dataBaseline(25010:27010,7)); %pA
  261. Global.(date).(ZT).(cell).(run).IVcurve_m40_after=nanmean(dataBaseline(25010:27010,8)); %pA
  262. Global.(date).(ZT).(cell).(run).IVcurve_m30_after=nanmean(dataBaseline(25010:27010,9)); %pA
  263. Global.(date).(ZT).(cell).(run).IVcurve_m20_after=nanmean(dataBaseline(25010:27010,10)); %pA
  264. Global.(date).(ZT).(cell).(run).IVcurve_m10_after=nanmean(dataBaseline(25010:27010,11)); %pA
  265. Global.(date).(ZT).(cell).(run).IVcurve_0_after=nanmean(dataBaseline(25010:27010,12)); %pA
  266. Global.(date).(ZT).(cell).(run).IVcurve_10_after=nanmean(dataBaseline(25010:27010,13)); %pA
  267. Global.(date).(ZT).(cell).(run).IVcurve_20_after=nanmean(dataBaseline(25010:27010,14)); %pA
  269. Global.(date).(ZT).(cell).(run).IVcurve_m100_peakafter=max(dataBaseline(25010:27010,2)); %pA
  270. Global.(date).(ZT).(cell).(run).IVcurve_m90_peakafter=max(dataBaseline(25010:27010,3)); %pA
  271. Global.(date).(ZT).(cell).(run).IVcurve_m80_peakafter=max(dataBaseline(25010:27010,4)); %pA
  272. Global.(date).(ZT).(cell).(run).IVcurve_m70_peakafter=max(dataBaseline(25010:27010,5)); %pA
  273. Global.(date).(ZT).(cell).(run).IVcurve_m60_peakafter=max(dataBaseline(25010:27010,6)); %pA
  274. Global.(date).(ZT).(cell).(run).IVcurve_m50_peakafter=max(dataBaseline(25010:27010,7)); %pA
  275. Global.(date).(ZT).(cell).(run).IVcurve_m40_peakafter=max(dataBaseline(25010:27010,8)); %pA
  276. Global.(date).(ZT).(cell).(run).IVcurve_m30_peakafter=max(dataBaseline(25010:27010,9)); %pA
  277. Global.(date).(ZT).(cell).(run).IVcurve_m20_peakafter=max(dataBaseline(25010:27010,10)); %pA
  278. Global.(date).(ZT).(cell).(run).IVcurve_m10_peakafter=max(dataBaseline(25010:27010,11)); %pA
  279. Global.(date).(ZT).(cell).(run).IVcurve_0_peakafter=max(dataBaseline(25010:27010,12)); %pA
  280. Global.(date).(ZT).(cell).(run).IVcurve_10_peakafter=max(dataBaseline(25010:27010,13)); %pA
  281. Global.(date).(ZT).(cell).(run).IVcurve_20_peakafter=max(dataBaseline(25010:27010,14)); %pA
  283. %first 10ms after capacitance transient
  284. Global.(date).(ZT).(cell).(run).IVcurve_m100_initial=nanmean(dataBaseline(10050:10100,2)); %pA
  285. Global.(date).(ZT).(cell).(run).IVcurve_m90_initial=nanmean(dataBaseline(10050:10100,3)); %pA
  286. Global.(date).(ZT).(cell).(run).IVcurve_m80_initial=nanmean(dataBaseline(10050:10100,4)); %pA
  287. Global.(date).(ZT).(cell).(run).IVcurve_m70_initial=nanmean(dataBaseline(10050:10100,5)); %pA
  288. Global.(date).(ZT).(cell).(run).IVcurve_m60_initial=nanmean(dataBaseline(10050:10100,6)); %pA
  289. Global.(date).(ZT).(cell).(run).IVcurve_m50_initial=nanmean(dataBaseline(10050:10100,7)); %pA
  290. Global.(date).(ZT).(cell).(run).IVcurve_m40_initial=nanmean(dataBaseline(10050:10100,8)); %pA
  291. Global.(date).(ZT).(cell).(run).IVcurve_m30_initial=nanmean(dataBaseline(10050:10100,9)); %pA
  292. Global.(date).(ZT).(cell).(run).IVcurve_m20_initial=nanmean(dataBaseline(10050:10100,10)); %pA
  293. Global.(date).(ZT).(cell).(run).IVcurve_m10_initial=nanmean(dataBaseline(10050:10100,11)); %pA
  294. Global.(date).(ZT).(cell).(run).IVcurve_0_initial=nanmean(dataBaseline(10050:10100,12)); %pA
  295. Global.(date).(ZT).(cell).(run).IVcurve_10_initial=nanmean(dataBaseline(10050:10100,13)); %pA
  296. Global.(date).(ZT).(cell).(run).IVcurve_20_initial=nanmean(dataBaseline(10050:10100,14)); %pA
  298. %last 50ms
  299. Global.(date).(ZT).(cell).(run).IVcurve_m100_last=nanmean(dataBaseline(24750:25000,2)); %pA
  300. Global.(date).(ZT).(cell).(run).IVcurve_m90_last=nanmean(dataBaseline(24750:25000,3)); %pA
  301. Global.(date).(ZT).(cell).(run).IVcurve_m80_last=nanmean(dataBaseline(24750:25000,4)); %pA
  302. Global.(date).(ZT).(cell).(run).IVcurve_m70_last=nanmean(dataBaseline(24750:25000,5)); %pA
  303. Global.(date).(ZT).(cell).(run).IVcurve_m60_last=nanmean(dataBaseline(24750:25000,6)); %pA
  304. Global.(date).(ZT).(cell).(run).IVcurve_m50_last=nanmean(dataBaseline(24750:25000,7)); %pA
  305. Global.(date).(ZT).(cell).(run).IVcurve_m40_last=nanmean(dataBaseline(24750:25000,8)); %pA
  306. Global.(date).(ZT).(cell).(run).IVcurve_m30_last=nanmean(dataBaseline(24750:25000,9)); %pA
  307. Global.(date).(ZT).(cell).(run).IVcurve_m20_last=nanmean(dataBaseline(24750:25000,10)); %pA
  308. Global.(date).(ZT).(cell).(run).IVcurve_m10_last=nanmean(dataBaseline(24750:25000,11)); %pA
  309. Global.(date).(ZT).(cell).(run).IVcurve_0_last=nanmean(dataBaseline(24750:25000,12)); %pA
  310. Global.(date).(ZT).(cell).(run).IVcurve_10_last=nanmean(dataBaseline(24750:25000,13)); %pA
  311. Global.(date).(ZT).(cell).(run).IVcurve_20_last=nanmean(dataBaseline(24750:25000,14)); %pA
  312. end
  313. end
  314. end
  318. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
  320. id=strfind(filepathAK42, '\');
  321. folderpath=filepathAK42(1:id(end));
  322. cd(folderpath)
  324. [~,AllfilenameTestPulse] = system('dir /s /b *.axgx'); % special extension for test pusle data
  325. AllfilenameTestPulse = strsplit(AllfilenameTestPulse,newline)';
  326. AllfilenameTestPulse(cellfun(@isempty,AllfilenameTestPulse))=[];
  328. for f=1:size(AllfilenameTestPulse,1)
  329. filepathTEST=AllfilenameTestPulse{f};
  330. SR=[];
  331. MC=[];
  332. MR=[];
  334. % try %avoid issues with corrupted files
  335. [textData] = ReadAxographfiles(filepathTEST);
  337. filepathTEST=strrep(filepathTEST,'(','');
  338. filepathTEST=strrep(filepathTEST,')','');
  339. it=strfind(filepathTEST,'\');
  340. date=filepathTEST(it(end-3)+1:it(end-2)-1);
  341. ZT=filepathTEST(it(end-2)+1:it(end-1)-1);
  342. cell=filepathTEST(it(end-1)+1:it(end)-1);
  343. id=regexprep(filepathTEST(it(end)+1:end-5), ' ', '');
  345. id=lower(id);
  346. runid=NaN;
  348. if strfind(id, 'after')
  349. pos=2;
  350. else
  351. pos=1;
  352. end
  354. if strfind(id,'run')
  355. ir=strfind(id,'run');
  356. runid=str2double(id(ir+3));
  357. elseif size(regexprep(id, 'bis', ''), 2)==16
  358. runid=1;
  359. elseif size(regexprep(id, 'ak42', ''), 2)==16
  360. runid=1;
  361. elseif strcmp(id, 'testpulsewindow')
  362. runid=0;
  363. else
  364. disp(id)
  365. filepath
  366. continue
  367. end
  369. if strfind(id,'ak42')
  370. pr='AK42';
  371. else
  372. pr='Baseline';
  373. end
  375. run=[pr '_run00' num2str(runid)];
  376. i=strfind(textData,char(SeriesResistance));
  377. cellidx=find(~cellfun(@isempty,i'));
  379. if ~isempty(cellidx) && isfield( Global.(date).(ZT).(cell), run)
  380. i=i{~cellfun('isempty',i)};
  381. SR=double(textData{cellidx,1}(i+59:i+66));
  382. SR(SR==0) = [];
  383. SR(SR==32) = [];
  384. SR=char(SR);
  385. SR=str2double(regexp(SR,['\d+\.?\d*'],'match'));
  387. i=strfind(textData,char(MembraneCapacitance));
  388. cellidx=find(~cellfun(@isempty,i'));
  389. i=i{~cellfun('isempty',i)};
  390. MC=double(textData{cellidx,1}(i+51:i+59));
  391. MC(MC==0) = [];
  392. MC(MC==32) = [];
  393. MC=char(MC);
  394. MC=str2double(regexp(MC,['\d+\.?\d*'],'match'));
  396. i=strfind(textData,char(MembraneResistance));
  397. cellidx=find(~cellfun(@isempty,i'));
  398. i=i{~cellfun('isempty',i)};
  399. MR=double(textData{cellidx,1}(i+57:i+67));
  400. MR(MR==0) = [];
  401. MR(MR==32) = [];
  402. MR=char(MR);
  403. MR=str2double(regexp(MR,['\d+\.?\d*'],'match'));
  404. if MR(1)<10 %ig GOhms instead of MOhms
  405. MR=MR(1)*1000;
  406. end
  408. SerieR=['SeriesResistance_' num2str(pos)];
  409. MembR=['MembraneResistance_' num2str(pos)];
  410. MembCap=['MembraneCapacitance_' num2str(pos)];
  411. PulseTime=['TestPulseTime_' num2str(pos)];
  412. TimeFromExtraction=['TimeFromExtraction_' num2str(pos)];
  414. Global.(date).(ZT).(cell).(run).(SerieR)=SR;
  415. Global.(date).(ZT).(cell).(run).(MembCap)=MC;
  416. Global.(date).(ZT).(cell).(run).(MembR)=MR;
  418. i=strfind(textData,'2024');
  419. cellidx=find(~cellfun(@isempty,i'));
  420. i=i{~cellfun('isempty',i)};
  421. hour=double(textData{cellidx,1}(i-41:i-27));
  422. hour(hour==0) = [];
  423. hour(hour==32) = [];
  424. hour=char(hour);
  426. Global.(date).(ZT).(cell).(run).(PulseTime)=hour;
  428. if strcmp(ZT, 'ZT2')
  429. Global.(date).(ZT).(cell).(run).(TimeFromExtraction)=datetime(datenum(hour, 'HH:MM:SS') -datenum({'09:00:00'}, 'HH:MM:SS'), 'ConvertFrom', 'datenum', 'Format', 'HH:mm:ss');
  430. Global.(date).(ZT).(cell).(run).(TimeFromExtraction)=rem(datenum((datetime(datenum(hour, 'HH:MM:SS') -datenum({'09:00:00'}, 'HH:MM:SS'), 'ConvertFrom', 'datenum', 'Format', 'HH:mm:ss'))),1);
  431. else
  432. Global.(date).(ZT).(cell).(run).(TimeFromExtraction)=datetime(datenum(hour, 'HH:MM:SS') -datenum({'21:00:00'}, 'HH:MM:SS'), 'ConvertFrom', 'datenum', 'Format', 'HH:mm:ss');
  433. Global.(date).(ZT).(cell).(run).(TimeFromExtraction)=rem(datenum((datetime(datenum(hour, 'HH:MM:SS') -datenum({'21:00:00'}, 'HH:MM:SS'), 'ConvertFrom', 'datenum', 'Format', 'HH:mm:ss'))),1);
  434. if Global.(date).(ZT).(cell).(run).(TimeFromExtraction)<0
  435. Global.(date).(ZT).(cell).(run).(TimeFromExtraction)=rem(datenum((datetime(datenum(hour, 'HH:MM:SS') -datenum({'21:00:00'}, 'HH:MM:SS'), 'ConvertFrom', 'datenum', 'Format', 'HH:mm:ss'))),1)+1;
  436. end
  437. end
  438. end
  439. end
  440. cd(filepathAK42(1:ii(end)))
  441. end
  443. assignin('base', 'Global', Global)
  445. %% Create the summary table
  446. close all
  447. Global= evalin('base','Global');
  448. Test.SeriesResistance=[];
  449. Test.MembraneCapacitance=[];
  450. Test.MembraneResistance=[];
  451. Test.RMP=[];
  452. Test.Rheobase=[];
  453. % figure;
  454. p=1;
  455. Global_APmorpho=[];
  456. GlobalTable=[];
  457. GlobalTable_Extended=[];
  458. day=fieldnames(Global);
  459. mouseID=1;
  460. for d=1:size(day, 1)
  461. date=day{d};
  462. time=fieldnames(Global.(date));
  463. for z=1:size(time, 1)
  464. ZT=time{z};
  465. cells=fieldnames(Global.(date).(ZT));
  466. for c=1:size(cells, 1)
  467. cell=cells{c};
  468. runs=fieldnames(Global.(date).(ZT).(cell));
  469. EC=[];
  470. for r=1:size(runs, 1)
  471. run=runs{r};
  472. Global.(date).(ZT).(cell).(run).MouseID=mouseID;
  473. if isfield(Global.(date).(ZT).(cell).(run), 'SeriesResistance_1') && isfield( Global.(date).(ZT).(cell).(run), 'SeriesResistance_2')
  474. SR1=Global.(date).(ZT).(cell).(run).SeriesResistance_1;
  475. MR1=Global.(date).(ZT).(cell).(run).MembraneResistance_1;
  476. MC1=Global.(date).(ZT).(cell).(run).MembraneCapacitance_1;
  478. SR2=Global.(date).(ZT).(cell).(run).SeriesResistance_2;
  479. MR2=Global.(date).(ZT).(cell).(run).MembraneResistance_2;
  480. MC2=Global.(date).(ZT).(cell).(run).MembraneCapacitance_2;
  482. varSR=abs((SR2-SR1)/SR1*100); %compared to the first value
  483. varMC=abs((MC2-MC1)/MC1*100);
  484. varMR=abs((MR2-MR1)/MR1*100);
  486. varSR=floor(abs((SR2-SR1)/SR2*100)); %compared to the second value
  487. varMC=floor(abs((MC2-MC1)/MC2*100));
  488. varMR=floor(abs((MR2-MR1)/MR2*100));
  490. if isfield(Global.(date).(ZT).(cell), 'run0')
  491. MR0=Global.(date).(ZT).(cell).run0.MembraneResistance_1;% Requires no variation of MR since the break in
  492. varMR0=abs((MR2-MR0)/MR0*100);
  493. MC0=Global.(date).(ZT).(cell).run0.MembraneCapacitance_1;
  495. if MC1<8 %failure detection pF by Axograph
  496. MC1=Global.(date).(ZT).(cell).run0.MembraneCapacitance_1; %when break in
  497. end
  498. else
  499. varMR0=NaN;
  500. MC0=NaN;
  501. end
  503. Global.(date).(ZT).(cell).(run).MembraneCapacitance_0=MC0;
  504. Global.(date).(ZT).(cell).(run).varSR=varSR;
  505. Global.(date).(ZT).(cell).(run).varMC=varMC;
  506. Global.(date).(ZT).(cell).(run).varMR=varMR;
  507. Global.(date).(ZT).(cell).(run).varMR0=varMR0;
  509. Global.(date).(ZT).(cell).(run).ExclusionCriteria=0;
  511. if SR1>40 %|| SR2>40 %inf to 35mOhms or 40
  512. Global.(date).(ZT).(cell).(run).ExclusionCriteria=1;
  513. end
  515. %MR1 <= 200 || MR2 <= 200 || MC1 >= 45 || MC2 >= 45
  516. if MR1+SR1 <= 200 %|| MR2+SR2 <= 200 % MC1 <= 8 || MC1 >= 40 || MC2 <= 8 || MC2 >= 40 %inf to 40pF sup at 10pF
  517. Global.(date).(ZT).(cell).(run).ExclusionCriteria=1;
  518. end
  520. % % added 19th October 2023
  521. % if MR1 >= 1500 %|| MR2+SR2 <= 200 % MC1 <= 8 || MC1 >= 40 || MC2 <= 8 || MC2 >= 40 %inf to 40pF sup at 10pF
  522. % Global.(date).(ZT).(cell).(run).ExclusionCriteria=1;
  523. % end
  525. if MC1 >= 40 %|| MC2 >= 40 % MC1 <= 8 || MC1 >= 40 || MC2 <= 8 || MC2 >= 40 %inf to 40pF sup at 10pF
  526. Global.(date).(ZT).(cell).(run).ExclusionCriteria=1;
  527. end
  529. % if SR1>10 %no computation of varSR if SR<10
  530. if varSR>40 %more than 30% variation
  531. Global.(date).(ZT).(cell).(run).ExclusionCriteria=1;
  532. end
  533. % end
  535. if isfield(Global.(date).(ZT).(cell).(run), 'IVcurve_m90_before')
  536. varBaseline=abs(Global.(date).(ZT).(cell).(run).IVcurve_m90_before-Global.(date).(ZT).(cell).(run).IVcurve_m100_before);
  537. Global.(date).(ZT).(cell).(run).varBaseline=varBaseline;
  538. if varBaseline>100 %100pA variation before stim--> big weird tail current
  539. Global.(date).(ZT).(cell).(run).ExclusionCriteria=1;
  540. end
  541. if varMR0>100
  542. Global.(date).(ZT).(cell).(run).ExclusionCriteria=1;
  543. end
  545. if Global.(date).(ZT).(cell).(run).IVcurve_0_all<-50 % too much current at 0mV holding
  546. Global.(date).(ZT).(cell).(run).ExclusionCriteria=1;
  547. end
  548. end
  550. EC(end+1,1)=[Global.(date).(ZT).(cell).(run).ExclusionCriteria + varSR/100 + varMR/100];
  551. Global.(date).(ZT).(cell).(run).ExclusionCriteriaAll=[Global.(date).(ZT).(cell).(run).ExclusionCriteria + varSR/100 + varMR/100];
  553. else
  554. EC(end+1,1)=1;
  555. Global.(date).(ZT).(cell).(run).ExclusionCriteriaAll=1; %no seal detected
  556. continue
  557. end
  559. %%% Select best run
  561. [~,i]=min(EC);
  562. if Global.(date).(ZT).(cell).(runs{i}).ExclusionCriteriaAll<1
  563. if isempty(GlobalTable) && isfield(Global.(date).(ZT).(cell).(run),'rawdata')
  564. A=Global.(date).(ZT).(cell).(run);
  565. A = rmfield(A,'rawdata');
  566. tnew=struct2table(A,'AsArray',true);
  567. GlobalTable=tnew;
  568. elseif isfield(Global.(date).(ZT).(cell).(run),'rawdata')
  569. A=Global.(date).(ZT).(cell).(run);
  570. A = rmfield(A,'rawdata');
  571. tnew=struct2table(A,'AsArray',true);
  572. GlobalTable=outerjoin(GlobalTable,tnew,'MergeKeys',true);
  573. else
  574. A=Global.(date).(ZT).(cell).(run);
  575. tnew=struct2table(A,'AsArray',true);
  576. GlobalTable=outerjoin(GlobalTable,tnew,'MergeKeys',true);
  577. end
  578. end
  579. end
  580. end
  581. mouseID=mouseID+1;
  582. end
  583. end
  584. assignin('base', 'Global', Global)
  585. assignin('base', 'GlobalTable', GlobalTable)
  586. GlobalTable = sortrows(GlobalTable,'Run','descend');
  587. GlobalTable = sortrows(GlobalTable,'Cell','descend');
  588. GlobalTable = sortrows(GlobalTable,'ZT','descend');
  589. GlobalTable = sortrows(GlobalTable,'Date','descend');
  591. save([globalpath '\GlobalTable_' regexprep(datestr(datetime), '[^a-zA-Z0-9]','')], 'GlobalTable', '-v7.3')
  592. save([globalpath '\Global_' regexprep(datestr(datetime), '[^a-zA-Z0-9]','')], 'Global', '-v7.3')

VoltageClamp_AK42.m at commit 203c9fd, no license · at the source

Overview

Authors: Aurélie Brécier1,2, Courtney A. Bannerman1, Yu-Feng Xie3, Christopher Dedek3,4, Amanda M. Zacharias1, Ciara D. O’Connor1, Aitana Rickert Llàcer1, Steven D. Miller5, Vina W. Li1, Christina Meier1, Laurel L. Ballantyne1,2, Justin Du Bois5, Qingling Duan1,6, Steven A. Prescott3,4,7,8,9, Nader Ghasemlou1,2,10,11
ORCID iDs: Aurélie Brécier, Courtney A. Bannerman, Yu-Feng Xie, Christopher Dedek, Amanda M. Zacharias, Ciara D. O’Connor, Aitana Rickert Llàcer, Vina W. Li, Christina Meier, Laurel L. Ballantyne, Justin Du Bois, Qingling Duan, Steven A. Prescott, Nader Ghasemlou
  1. Department of Biomedical & Molecular Sciences, Queen’s University,Kingston, Canada
  2. Department of Anesthesiology & Perioperative Medicine, Kingston Health Sciences Centre,Kingston, Canada
  3. Neurosciences and Mental Health, The Hospital for Sick Children,Toronto, Canada
  4. Institute of Biomedical Engineering, University of Toronto,Toronto, Canada
  5. Department of Chemistry, Stanford University,Stanford, USA
  6. School of Computing, Queen’s University,Kingston, Canada
  7. Department of Physiology, University of Toronto,Toronto, Canada
  8. Department of Physiology and Pharmacology, University of Calgary,Calgary, Canada
  9. Hotchkiss Brain Institute, University of Calgary,Calgary, Canada
  10. Krembil Brain Institute, University Health Network,Toronto, Canada
  11. Department of Immunology, University of Toronto,Toronto, Canada
Institutions: Queen's University (Canada); Kingston Health Sciences Centre (Canada); Hospital for Sick Children (Canada); University of Toronto (Canada); Stanford University (United States); University of Calgary (Canada); University Health Network (Canada)
Journal: Nature communications, volume 17, issue 1, article 7053
Dates: received 9 April 2025; accepted 20 May 2026; published online 1 June 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1038/s41467-026-73772-z · PMID 42230621 · PMCID PMC13392263 · OpenAlex W7163184892
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: intracellular / patch clamp (modality), mouse (organism), pain (population), cellular / molecular (subfield)
Methods: Statistics, Smoothing, state filtering, decompositions, Spectral & time-frequency
Keywords: Ion channels in the nervous system, Intrinsic excitability, Patch clamp, Circadian mechanisms
MeSH: ARNTL Transcription Factors*, Circadian Clocks*, Nociception*, Nociceptors*, Pain Perception*, Animals, Chloride Channels, Circadian Rhythm, Female, Ganglia, Spinal, Male, Mice, Mice, Inbred C57BL, NAV1.8 Voltage-Gated Sodium Channel, Optogenetics, Sex Factors (* major topic)
Topic: Circadian rhythm and melatonin (Endocrine and Autonomic Systems, Neuroscience), according to OpenAlex
Funding: Canadian Institutes of Health Research (PJT-497592); Natural Sciences and Engineering Research Council of Canada (RGPIN-05604); Multiple Sclerosis Society of Canada (Société Canadienne de la Sclérose en Plaques) (3316); MS Canada (post-doctoral fellowship)
Citations: cited by 2 papers (Europe PMC); 93 references in the paper

Abstract

The abstract is not reproduced here: the paper's license (CC BY-NC-ND) does not allow it. Read it in the paper, at the publisher or on Europe PMC.

Repositories

Its files are read in the Code ↔ Paper reader above, with 7 matches between paragraphs and lines of code.

ComputationalGenomicsLaboratory/naiveDRG

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: 30d365db39e2d4f70ef32894eda4406020804c58, 11 May 2026
Languages: Shell (99), R (48), Python (1)
Size: 151 files, 148 scripts
Software Heritage: not archived
Found in: “Code availability”
Holds: README, 1 notebook
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: tidyverse (34 files), FastQC (25 files), SAMtools (13 files), ggplot2 (11 files), DESeq2 (5 files), data.table (2 files), reshape2 (2 files), Seurat (2 files), patchwork (1 file), pheatmap (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
149 files
At the source: github.com/ComputationalGenomicsLaboratory/naiveDRG

AurelieBre/DRGPatchClampProcessing

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: 203c9fdada93fca63cd154f6c02ffc0234d42a55, 21 April 2025
Languages: MATLAB (4)
Size: 12 files, 4 scripts
Software Heritage: not archived
Found in: “Code availability”
Holds: README
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: Statistics and Machine Learning Toolbox (2 files), Signal Processing Toolbox (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
5 files
At the source: github.com/AurelieBre/DRGPatchClampProcessing

Zenodo 20072530

License: CC-BY-4.0
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Size: 1 file
Software Heritage: not checked
Found in: “Code availability”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: tidyverse (34 files), FastQC (25 files), SAMtools (13 files), ggplot2 (11 files), DESeq2 (5 files), data.table (2 files), reshape2 (2 files), Seurat (2 files), patchwork (1 file), pheatmap (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers (HTTP 200)
  • 27 September 2026: the link answers (HTTP 200)
149 files
At the source:

Zenodo 19856603

License: CC-BY-4.0
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Size: 1 file
Software Heritage: not checked
Found in: “Code availability”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: Statistics and Machine Learning Toolbox (2 files), Signal Processing Toolbox (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers (HTTP 200)
  • 27 September 2026: the link answers (HTTP 200)
5 files
At the source:

Code availability statement

The paper has a code availability statement. Its license (CC BY-NC-ND) does not allow reproducing it here; in short, from what the harvester recognized in it:

Read it in the paper: doi.org/10.1038/s41467-026-73772-z.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 4 repositories of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 304 scripts, each with its path and the digest of its content;
  • 7 matches between paragraphs of the paper and lines of the code (method lexical-v1);
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

Datasets cited

Data availability statement

The paper has a data availability statement. Its license (CC BY-NC-ND) does not allow reproducing it here; in short, from what the harvester recognized in it:

Read it in the paper: doi.org/10.1038/s41467-026-73772-z.

Versions

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Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 15 authors, 4 keywords, 16 MeSH terms, 4 funders, 89 references.

Cite

This paper

Brécier, A., Bannerman, C. A., Xie, Y.-F., Dedek, C., Zacharias, A. M., O’Connor, C. D., Rickert Llàcer, A., Miller, S. D., Li, V. W., Meier, C., Ballantyne, L. L., Du Bois, J., Duan, Q., Prescott, S. A., & Ghasemlou, N. (2026). Nociceptor circadian clock genes control excitability and pain perception in mice in a sex- and time-dependent manner. Nature communications, 17(1), 7053. https://doi.org/10.1038/s41467-026-73772-z

BibTeX

@article{brecier2026nociceptor,
author = {Brécier, Aurélie and Bannerman, Courtney A. and Xie, Yu-Feng and Dedek, Christopher and Zacharias, Amanda M. and O’Connor, Ciara D. and Rickert Llàcer, Aitana and Miller, Steven D. and Li, Vina W. and Meier, Christina and Ballantyne, Laurel L. and Du Bois, Justin and Duan, Qingling and Prescott, Steven A. and Ghasemlou, Nader},
title = {{Nociceptor circadian clock genes control excitability and pain perception in mice in a sex- and time-dependent manner}},
journal = {Nature communications},
year = {2026},
month = jun,
volume = {17},
number = {1},
pages = {7053},
publisher = {Nature Publishing Group},
issn = {2041-1723},
doi = {10.1038/s41467-026-73772-z},
url = {https://doi.org/10.1038/s41467-026-73772-z},
pmid = {42230621},
pmcid = {PMC13392263}
}

RIS

TY - JOUR
AU - Brécier, Aurélie
AU - Bannerman, Courtney A.
AU - Xie, Yu-Feng
AU - Dedek, Christopher
AU - Zacharias, Amanda M.
AU - O’Connor, Ciara D.
AU - Rickert Llàcer, Aitana
AU - Miller, Steven D.
AU - Li, Vina W.
AU - Meier, Christina
AU - Ballantyne, Laurel L.
AU - Du Bois, Justin
AU - Duan, Qingling
AU - Prescott, Steven A.
AU - Ghasemlou, Nader
TI - Nociceptor circadian clock genes control excitability and pain perception in mice in a sex- and time-dependent manner
T2 - Nature communications
J2 - Nat Commun
PY - 2026
DA - 2026/06/01
VL - 17
IS - 1
SP - 7053
SN - 2041-1723
PB - Nature Publishing Group
DO - 10.1038/s41467-026-73772-z
UR - https://doi.org/10.1038/s41467-026-73772-z
LA - en
ER -

CSL-JSON

{
"id": "10.1038/s41467-026-73772-z",
"type": "article-journal",
"title": "Nociceptor circadian clock genes control excitability and pain perception in mice in a sex- and time-dependent manner",
"container-title": "Nature communications",
"author": [
{
"family": "Brécier",
"given": "Aurélie"
},
{
"family": "Bannerman",
"given": "Courtney A."
},
{
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"given": "Yu-Feng"
},
{
"family": "Dedek",
"given": "Christopher"
},
{
"family": "Zacharias",
"given": "Amanda M."
},
{
"family": "O’Connor",
"given": "Ciara D."
},
{
"family": "Rickert Llàcer",
"given": "Aitana"
},
{
"family": "Miller",
"given": "Steven D."
},
{
"family": "Li",
"given": "Vina W."
},
{
"family": "Meier",
"given": "Christina"
},
{
"family": "Ballantyne",
"given": "Laurel L."
},
{
"family": "Du Bois",
"given": "Justin"
},
{
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"given": "Qingling"
},
{
"family": "Prescott",
"given": "Steven A."
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{
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}
],
"container-title-short": "Nat Commun",
"volume": "17",
"issue": "1",
"page": "7053",
"DOI": "10.1038/s41467-026-73772-z",
"PMID": "42230621",
"PMCID": "PMC13392263",
"ISSN": "2041-1723",
"publisher": "Nature Publishing Group",
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"language": "en",
"issued": {
"date-parts": [
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6,
1
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]
}
}

The tracing map gets a citation of its own once an author has validated it and it has a DOI.

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