Can physiological network mapping reveal pathophysiological insights into emerging diseases? Lessons from COVID-19 Network physiology is a multidisciplinary field that offers a comprehensive view of the complex interactions within the human body, emphasising the critical role of organ system connectivity in health...

Application of Network Thinking and Network Physiology in Emerging Disease; Lessons from the first wave of COVID-19. dx.plos.org/10.1371/jour... #NetworkPhysiology

We are starting our first projects in Network Physiology, contributing to new approaches to understand system-level physiological interactions.
#NetworkPhysiology #AltitudeResearch #EnvironmentalResilience #HumanPerformance #IntegrativePhysiology #SystemsBiology #HERRN

Amazing fact from The Physiological Society Network Physiology webinar. If you measure 100 physiological parameters at 100 Hz for 1 day in 1 person, you’ll collect more data than there are base pairs in the human genome-and there are ~4 billion base pairs. 🤯

#NetworkPhysiology #PhysiologyFacts

Adriatica Summer School 2025 | DNISC Adriatica Summer School 2025 - DNISC

📢 Last Week to Apply!

Registration for the Adriatica Summer School 2025 closes July 31st.

⏳ Time is running out.

Learn more and apply here:
www.dnisc.unich.it/pagina-adria...

#Adriatica2025 #SummerSchool #BrainBodyInteraction #Neuroscience #Wellbeing
#Interoception #NetworkPhysiology

Decreased cardio-respiratory information transfer is associated with deterioration and a poor prognosis in critically ill patients with sepsis | Journal of Applied Physiology | American Physiological Society Assessing illness severity in the intensive care unit (ICU) is crucial for early prediction of deterioration and prognosis. Traditional prognostic scores often treat organ systems separately, overlooking the body’s interconnected nature. Network physiology offers a new approach to understanding these complex interactions. This study used the concept of transfer entropy (TE) to measure information flow between heart rate (HR), respiratory rate (RR), and capillary oxygen saturation in critically ill patients with sepsis, hypothesizing that TE between these signals would correlate with disease outcome. The retrospective cohort study utilized the Medical Information Mart for Intensive Care III Clinical Database, including patients who met Sepsis-3 criteria on admission and had 30 min of continuous HR, RR, and data. TE between the signals was calculated to create physiological network maps. Cox regression assessed the relationship between cardiorespiratory network indices and both deterioration [Sequential Organ Failure Assessment (SOFA) score increase of ≥2 points at 48 h] and 30-day mortality. Among 164 patients, higher information flow from to HR [TE ( → HR)] and reciprocal flow between HR and RR [TE (RR → HR) and TE (HR → RR)] were linked to reduced mortality, independent of age, mechanical ventilation, SOFA score, and comorbidity. Reductions in TE (HR → RR), TE (RR → HR), TE ( → RR), and TE ( → HR) were associated with an increased risk of 48-h deterioration. After adjustment for potential confounders, only TE (HR → RR) and TE (RR → HR) remained statistically significant. The study confirmed that physiological network mapping using routine signals in patients with sepsis could indicate illness severity and that higher TE values were generally associated with improved outcomes. NEW & NOTEWORTHY This study adopts an integrative approach through physiological network analysis to investigate sepsis, with the goal of identifying differences in information transfer between physiological signals in sepsis survivors versus nonsurvivors. We found that greater information flow between heart rate, respiratory rate, and capillary oxygen saturation was associated with reduced mortality, independent of age, disease severity, and comorbidities. In addition, reduced information transfer was linked to an increased risk of 48-h deterioration in patients with sepsis.

A recent report on application of physiological network mapping in sepsis and critical care #NetworkPhysiology
journals.physiology.org/doi/full/10....

Parenclitic network mapping predicts survival in critically ill patients with sepsis Sepsis is a complex disease involving multiple organ systems. A network physiology approach to sepsis may reveal collective system behaviors and intrinsic organ interactions. However, mapping functio...

The latest report from UCL Network Physiology Lab on pathophysiology of sepsis. #NetworkPhysiology Parenclitic network mapping predicts survival in critically ill patients with sepsis - Ito - 2025 - Physiological Reports - Wiley Online Library physoc.onlinelibrary.wiley.com/doi/full/10....

Network Physiology webinar series - YouTube

The recordings of our Network Physiology Webinar Series are now available on The Physiological Society’s YouTube channel. Many thanks to our excellent speakers and dedicated event organisers for making this series so engaging and insightful. #NetworkPhysiology
youtube.com/playlist?lis...

Network Physiology: Mapping Physiological Networks in Health and Disease Network Physiology, learn more about the new multidisciplinary field with The Physiological Society's webinar series.

💡 Join our upcoming webinar series on #NetworkPhysiology, engage with experts, and be part of the conversation.

More details and registration links for each of the sessions available here: buff.ly/3ERXUPW 🧵 3/3

Network Physiology: Mapping Physiological Networks in Health and Disease Network Physiology, learn more about the new multidisciplinary field with The Physiological Society's webinar series.

Professor Plamen Ivanov was the first to introduce the #NetworkPhysiology framework, the new frontier in physiology & #medicine.

🎥 💻 He’ll be speaking about the multidisciplinary field in our webinar series on 26 March to 4 April ⬇️ buff.ly/3EMVJwU 🧵1/3

Professor Plamen Ch. Ivanov was the first to introduce the #NetworkPhysiology framework. He has joined Dr Alireza Mani & Dr Tope Oyelade to explain the benefits of exploring cross-communication and integration in #physiology.