Cytokine production by the immune system contributes importantly to both health and disease. The nervous system, via an inflammatory reflex of the vagus nerve, can inhibit cytokine release and thereby prevent tissue injury and death. The efferent neural signaling pathway is termed the cholinergic antiinflammatory pathway. Cholinergic agonists inhibit cytokine synthesis and protect against cytokine-mediated diseases. Stimulation of the vagus nerve prevents the damaging effects of cytokine release in experimental sepsis, endotoxemia, ischemia/reperfusion injury, hemorrhagic shock, arthritis, and other inflammatory syndromes. Herein is a review of this physiological, functional anatomical mechanism for neurological regulation of cytokine-dependent disease that begins to define an immunological homunculus.

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Physiology and immunology of the cholinergic antiinflammatory pathway

Inflammation can cause damage and even death. What controls this primitive and potentially lethal innate immune response to injury and infection? Molecular and neurophysiological studies during the past decade have revealed a pivotal answer: immunity is coordinated by neural circuits that operate reflexively. The afferent arc of the reflex consists of nerves that sense injury and infection. This activates efferent neural circuits, including the cholinergic anti-inflammatory pathway, that modulate immune responses and the progression of inflammatory diseases. It might be possible to develop therapeutics that target neural networks for the treatment of inflammatory disorders.

Reflex control of immunity.

Diabetic autonomic neuropathy

https://www.internationaljournalofcardiology.com/article/S0167-5273(12)00326-9/pdf

How accurate is pulse rate variability as an estimate of heart rate variability?: A review on studies comparing photoplethysmographic technology with an electrocardiogram

The reasoning that neural reflexes maintain homeostasis in other body organs, and that the immune system is innervated, prompted a search for neural circuits that regulate innate and adaptive immunity. This elucidated the inflammatory reflex, a prototypical reflex circuit that maintains immunological homeostasis. Molecular products of infection or injury activate sensory neurons traveling to the brainstem in the vagus nerve. The arrival of these incoming signals generates action potentials that travel from the brainstem to the spleen and other organs. This culminates in T cell release of acetylcholine, which interacts with α7 nicotinic acetylcholine receptors (α7 nAChR) on immunocompetent cells to inhibit cytokine release in macrophages. Herein is reviewed the neurophysiological basis of reflexes that provide stability to the immune system, the neural- and receptor-dependent mechanisms, and the potential opportunities for developing novel therapeutic devices and drugs that target neural pathways to treat inflammatory diseases.

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Reflex Principles of Immunological Homeostasis

Heart rate variability as early marker of multiple organ dysfunction syndrome in septic patients.

The conventional Poincare plot for heart rate variability (HRV) analysis is a scatterplot of successive (lag 1) pairs of RR intervals (intervals between heartbeats), and its width (SD1) is considered a measure of short-term variability It has been shown that SD1 correlates better with HF than with LF (high- and low-frequency bands of the spectrum, respectively) Our aim was to assess how these correlations were affected when SD1 was obtained for longer lags 10 min ECGs were used to construct Poincare plots with lags of 1–10 heartbeats in two groups of subjects, one with normal HRV and the other with impaired HRV (control and diabetic groups respectively, N = 15 each) SD1 was quantified for these subjects and HRV spectral indices were estimated The diabetic group had lower LF, HF and SD1 than the control group (p 09), while SD1 for lags ≥ 4 correlated better with LF (rs ≥ 09) than with HF (065 ≤ rs ≤ 073) However, in the diabetic group, the correlation results did not change in that way for different lags (correlation results between HF and SD1: rs ≥ 095 for lags 1–10) In conclusion, the comparative strength of the correlations between lagged Poincare widths and spectral indices might be useful to distinguish normal from pathological HRV

https://iopscience.iop.org/article/10.1088/0967-3334/28/1/008/pdf

Correlations between frequency-domain HRV indices and lagged Poincaré plot width in healthy and diabetic subjects.

Heart rate variability related to heart rate decelerations and accelerations is reduced in patients with type 1 diabetes compared to healthy individuals both in resting 10-min and ambulatory 24-h ECGs.

Asymmetrical properties of heart rate variability in type 1 diabetes.

Background: The definitive incorporation of heart rate variability (HRV) as a clinical tool depends on the development of more confident techniques of measurement. The length of the studies is a critical issue. Whereas Holter studies allow the monitorization at different hours and activities, short-term recordings allow the control of environmental conditions. Recording length is also strongly related to the procedure of analysis; for instance, some time-domain indexes are strongly affected by the duration of the study. Meanwhile, spectral analyses require stationary conditions, only achieved in short-term studies. Our main goal was to determine if HRV indexes obtained from short-term analyses were as useful as those from Holter monitoring for diagnosis of reduced HRV in diabetes.



Methods: We studied two groups: one with impaired HRV (15 diabetic patients) and another with normal HRV (15 healthy subjects). HRV indexes obtained from 24-hour Holter recordings (SDNN, rMSSD, and the power of LF and HF bands), were correlated with analog indexes obtained from 10-minute digital acquired studies within each group. Besides, we compared the diabetic and control groups using the indexes obtained with both methodologies.



Results: The correlation was high (0.70≤r ≤ 0.85, P ≤ 0.0032) in the diabetic group, but was poor in the control group. HRV values were significantly lower in the diabetic group either for 24-hour or short-term studies (P ≤ 0.0113).



Conclusion: We conclude that short-term studies are at least as powerful as Holter to differentiate the diabetic group (impaired HRV) from the control group.

/pdf/heart-rate-variability-short-term-studies-are-as-useful-as-5a6upwwb6v.pdf

Heart rate variability: short-term studies are as useful as holter to differentiate diabetic patients from healthy subjects.

Background: In R-R analysis for heart rate variability, rhythm modificatipns other than those related to autonomic nervous system activity must be avoided. We describe an algorithm that performs a correction based on the comparison of each interval with a normal standard.



Methods: Starting with a given R-R list, a parameter R between 0 and 1 is chosen, the normal R-R range is defined as: (1-R, 1+R]. The first interval then is divided by the mode of the entire R-R list. If the resulting value lies within the normal range, then it could be accepted as normal. Subsequent intervals are divided by the last accepted one and the mean value of the accepted intervals. If either of these results is inside.the normal range, then the considered interval is accepted. The abnormal intervals are evaluated to find out if they are in the expected range, which is [T-1, T+11, where T is a new parameter smaller than R. Not expected intervals are handled differently to be corrected and in a few cases are eliminated.



Results: Two types of tests were carried out. One uses real recordings containing artifacts. The other test was carried out by means of a computer program that generates corrupted data. R value was set in 0.2 and T in 0.05. Comparisons between our filter and other automatic algorithms were done.



Conclusions: Our filter is fast and strong enough to perform an accurate automatic correction.

Paola Contreras

Papers

Heart rate variability as early marker of multiple organ dysfunction syndrome in septic patients.

Correlations between frequency-domain HRV indices and lagged Poincaré plot width in healthy and diabetic subjects.

Asymmetrical properties of heart rate variability in type 1 diabetes.

Heart rate variability: short-term studies are as useful as holter to differentiate diabetic patients from healthy subjects.

Automatic Filtering of R‐R Intervals for Heart Rate Variability Analysis