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METHOD:PUBLISH
BEGIN:VEVENT
DTSTAMP:20260128T111939Z
DTSTART:20260209T140000Z
DTEND:20260209T150000Z
SUMMARY:Eder Zavala -- Mathematical analysis of endocrine rhythms and wea
 rable time series data [IN PERSON]
UID:{http://www.columbasystems.com/customers/uom/gpp/eventid/}p1jf-mkxxnt
 gx-ohpks6
DESCRIPTION:Join us for this seminar by Eder Zavala (Manchester) as part 
 of the Maths in the Life Sciences seminar series (and the online North W
 est Seminar Series in Mathematical Biology and Data Sciences in collabor
 ation with Liverpool Universities). \n\nTitle: Mathematical analysis of 
 endocrine rhythms and wearable time series data\n\nHormones are essentia
 l for maintaining good health. For example\, cortisol is a vital hormone
  that mediates the body’s stress response\, modulates inflammation\, car
 diometabolic function\, and cognitive performance. In basal\, non-stress
 ed conditions\, cortisol displays circadian (~24 hrs) and ultradian (<24
  hrs) rhythms governed by feedback loops within the Hypothalamic-Pituita
 ry-Adrenal (HPA) axis. Disruption of these hormonal rhythms can occur du
 e to external stimuli (e.g.\, stressors)\, or in slow-progressing stages
  of disease. From a mathematical perspective\, the HPA axis can be thoug
 ht of as a dynamical system adapted to respond to a wide range of stimul
 i. Despite misaligned hormonal rhythms being associated with morbidity\,
  a quantitative understanding of their variability\, mechanistic origin 
 and pathogenicity is missing. Also unknown is what makes these rhythms r
 obust to some perturbations but fragile to others\, especially in diseas
 ed states. Addressing these challenges is a critical step toward the dev
 elopment of digital tools to support clinical decision-making.\n\nThis t
 alk will explore how these challenges are being addressed by combining n
 ovel biosampling techniques with mathematical and computational analysis
  methods. I will showcase digital biomarkers that help quantify variabil
 ity of high-resolution daily profiles of HPA axis rhythms\, define norma
 tive ranges and signal endocrine dysfunction. We will discuss how mathem
 atical models can help us understand endocrine responses to perturbation
 s\, and how non-invasive wearable device data could constitute surrogate
 s of hormonal rhythm misalignment. By shifting from a qualitative to a q
 uantitative description of endocrine function\, these insights will take
  us a step closer to personalised clinical interventions for which timin
 g is key.\n\nThe talk will be also be streamed via Teams\, please contac
 t carl.whitfield@manchester.ac.uk or igor.chernyavsky@manchester.ac.uk f
 or the link\, or sign up to the mailing list.\n\nTo subscribe to the mai
 ling list for this event series\, please send an e-mail with the phrase 
 “subscribe math-lifesci-seminar” in the message body to listserv@listser
 v.manchester.ac.uk
STATUS:TENTATIVE
TRANSP:TRANSPARENT
CLASS:PUBLIC
LOCATION:2.60\, Simon Building\, Manchester
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