came down with a sinus infection last tuesday. first two days were unremarkable. day 3 is where it got complicated. fasting glucose tuesday morning: 88. by friday: 104. haven’t seen 104 since I was eating badly during the pandemic. I know cortisol from active infection does this - the mechanism isn’t mysterious - but watching it actually land on the log is different from knowing it abstractly. especially when I’m five weeks into tracking luteal-phase readings because I was starting to see something in four cycles of data. illness-state inflammation affects insulin sensitivity in ways that have nothing to do with luteal hormones, so now I have a contaminated window I have to flag before drawing any conclusions. the GHK-Cu situation is what’s actually frustrating me. three weeks in, documenting subq injection site reactions specifically because I couldn’t find reliable timeline data from people actually injecting it - almost everything written is topical application. the persistent quarter-sized red welts have been showing up at every site, lasting 10-14 days. I was finally building a clean read on local inflammation pattern. now I have systemic inflammation layered on top and can’t cleanly attribute the site reactions to the peptide versus my immune system doing its thing. tirz nausea versus illness nausea is also harder to parse. normally there’s a qualitative difference I can feel. not this week. the practical note for anyone else running n=1 protocols while managing peri: when illness hits, flag it explicitly in your log and assess whether your data window is actually usable. I’m not throwing out the readings, just annotating them with a sick-day contamination marker. the tracking isn’t broken, it just needs an asterisk. four cycles of clean luteal data is still four cycles of clean luteal data - I just don’t get to count this one. back to feeling sorry for myself.