Frontiers in Network Physiology

Acute and chronic insomnia have different causes and may require different treatments. They are investigated with multi-night nocturnal actigraphy data from two sleep studies. Two different wrist-worn actigraphy devices were used to measure physical activities. This required data pre-processing and transformations to smooth the differences between devices. Statistical, power spectrum, fractal and entropy analyses were used to derive features from the actigraphy data. Sleep parameters were also extracted from the signals. The features were then submitted to four machine learning algorithms. The best performing model was able to distinguish acute from chronic insomnia with an accuracy of 81%. The algorithms were then used to evaluate the acute and chronic groups compared to healthy sleepers. The differences between acute insomnia and healthy sleep were more prominent than between chronic insomnia and healthy sleep. This may be associated with the adaptation of the physiology to prolonged periods of disturbed sleep for individuals with chronic insomnia. The new model is a powerful addition to our suite of machine learning models aiming to pre-screen insomnia at home with wearable devices.

S. Rani

S. Shelyag

C. Karmakar

Ye Zhu

R. Fossion

J. G. Ellis

S. P. A. Drummond

M. Angelova

Differentiating acute from chronic insomnia with machine learning from actigraphy time series data

利用机器学习从活动记录仪时间序列数据中区分急性与慢性失眠

The Constrained Disorder Principle (CDP) defines all systems in nature by their degree of inherent variability. Per the CDP, the intrinsic variability is mandatory for their proper function and is dynamically changed based on pressures. The CDP defines the boundaries of inherent variability as a mechanism for continuous adaptation to internal and external perturbations, enabling survival and function under dynamic conditions. The laws of nature govern the world’s natural phenomena and underlie the function of all systems. Nevertheless, the laws of physics do not entirely explain systems’ functionality under pressure, which is essential for determining the correct operation of complex systems in nature. Variability and noise are two broad sources of inherent unpredictability in biology and technology. This paper explores how the CDP defines the function of systems and provides examples from various areas in nature where the CDP applies, including climate, genetic, biology, and human behavioral variabilities. According to the CDP, system malfunction results from inappropriate performance of the boundaries of inherent variability. The environment influences the physiological variability, and species interactions influence eco-evolutionary outcomes. The CDP defines human behavior as being driven by randomness and accounts for malfunctions and their corrections. The paper reviews variability-based CDP algorithms and CDP-based second-generation artificial intelligence systems and their potential for improving systems’ prediction and efficiency by using variability.

Yaron Ilan

The constrained-disorder principle defines the functions of systems in nature

受限无序原理定义了自然界中系统的功能

Metabolic dysfunction–associated steatotic liver disease (MASLD) is a multisystemic disease with a multifactorial pathogenesis involving dietary, environmental, and genetic factors. Previous mouse models suggested that circadian misalignment may additionally influence its development as it influences metabolism in diverse organs including the liver. Further, data from sleep questionnaires proved sleep-wake disruption in patients with MASLD. We objectively assessed sleep-wake rhythms in patients with biopsy-proven MASLD (n = 35) and healthy controls (HC, n = 16) using actigraphy 24/7 for 4 weeks. With the aim to re-align sleep rhythms a single standardized sleep hygiene education session was performed after 2 weeks. Actigraphy data revealed that MASLD patients had more awakenings per night (MASLD vs. HC 8.5 vs. 5.5, p = 0.0036), longer wakefulness after sleep onset (MASLD vs. HC 45.4 min vs. 21.3 min, p = 0.0004), and decreased sleep efficiency (MASLD vs. HC 86.5% vs. 92.8%, p = 0.0008) compared with HC despite comparable sleep duration. Patients with MASLD self-reported shorter sleep duration (MASLD vs. HC 6 h vs. 6 h 45 min, p = 0.01) and prolonged sleep latency contributing to poorer sleep quality. Standardized sleep hygiene education did not produce significant changes in sleep parameters. Our findings indicate fragmented nocturnal sleep in patients with MASLD, characterized by increased wakefulness and reduced sleep efficiency, perceived subjectively as shortened sleep duration and delayed onset. A single sleep hygiene education session did not improve sleep parameters.

Sofia Schaeffer

Andrijana Bogdanovic

Talitha Hildebrandt

Emilio Flint

Anne Geng

Sylvia Pecenko

Paul Lussier

Michael A. Strumberger

Martin Meyer

Jakob Weber

Markus H. Heim

Christian Cajochen

Christine Bernsmeier

Significant nocturnal wakefulness after sleep onset in metabolic dysfunction–associated steatotic liver disease

代谢功能障碍相关脂肪性肝病睡眠开始后显著的夜间觉醒

A steadily increasing number of publications support the concept of physiological networks, and how cellular bioelectrical properties drive cell proliferation and cell synchronization. All cells, especially cancer cells, are known to possess characteristic electrical properties critical for physiological behavior, with major differences between normal and cancer cell counterparts. This opportunity can be explored as a novel treatment modality in Oncology. Cancer cells exhibit autonomous oscillations, deviating from normal rhythms. In this context, a shift from a static view of cellular processes is required for a better understanding of the dynamic connections between cellular metabolism, gene expression, cell signaling and membrane polarization as states in constant flux in realistic human models. In oncology, radiofrequency electromagnetic fields have produced sustained responses and improved quality of life in cancer patients with minimal side effects. This review aims to show how non-thermal systemic radiofrequency electromagnetic fields leads to promising therapeutic responses at cellular and tissue levels in humans, supporting this newly emerging cancer treatment modality with early favorable clinical experience specifically in advanced cancer.

Frederico P. Costa

Bertram Wiedenmann

Eckehard Schöll

Jack Tuszynski

Emerging cancer therapies: targeting physiological networks and cellular bioelectrical differences with non-thermal systemic electromagnetic fields in the human body – a comprehensive review

新兴癌症疗法：利用非热系统电磁场靶向人体生理网络和细胞生物电差异——全面综述

To date, there is no neurophysiologic or neuroimaging biomarker that can accurately delineate the epileptogenic network. High-frequency oscillations (HFO) have been proposed as biomarkers for epileptogenesis and the epileptogenic network. The pathological HFO have been associated with areas of seizure onset and epileptogenic tissue. Several studies have demonstrated that the resection of areas with high rates of pathological HFO is associated with favorable postoperative outcomes. Recent studies have demonstrated the spatiotemporal organization of HFO into networks and their potential role in defining epileptogenic networks. Our review will present the existing literature on HFO-associated networks, specifically focusing on their role in defining epileptogenic networks and their potential significance in surgical planning.

Aline Herlopian

Networks through the lens of high-frequency oscillations

透过高频振荡的视角看网络

Human group connectome analysis relies on combining individual connectome data to construct a single representative network which can be used to describe brain organisation and identify differences between subject groups. Existing methods adopt different strategies to select the network structural features to be retained or optimised at group level. In the absence of ground truth, however, it is unclear which structural features are the most suitable and how to evaluate the consequences on the group network of applying any given strategy. In this investigation, we consider the impact of defining a connectome as representative if it can recapitulate not just the structure of the individual networks in the cohort tested but also their dynamical behaviour, which we measured using a model of coupled oscillators. We applied the widely used approach of consensus thresholding to a dataset of individual structural connectomes from a healthy adult cohort to construct group networks for a range of thresholds and then identified the most dynamically representative group connectome as that having the least deviation from the individual connectomes given a dynamical measure of the system. We found that our dynamically representative network recaptured aspects of structure for which it did not specifically optimise, with no significant difference to other group connectomes constructed via methods which did optimise for those metrics. Additionally, these other group connectomes were either as dynamically representative as our chosen network or less so. While we suggest that dynamics should be at least one of the criteria for representativeness, given that the brain has evolved under the pressure of carrying out specific functions, our results suggest that the question persists as to which of these criteria are valid and testable.

Eleanna Kritikaki

Matteo Mancini

Diana Kyriazis

Natasha Sigala

Simon F. Farmer

Luc Berthouze

Constructing representative group networks from tractography: lessons from a dynamical approach

从纤维束成像构建代表性群体网络：动态方法的启示

Publication Information	Publisher: Frontiers Media SA，Publishing cycle: ，Journal Type: journal，Open Access Journals: Yes
Basic data	Year of publication: 2021，Proportion of original research papers: ，Self Citation Rate:， Gold OA Rate:
Journal Fees	$2125Details
Average review cycle	13 weeks

Frontiers in Network Physiology

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Differentiating acute from chronic insomnia with machine learning from actigraphy time series data

The constrained-disorder principle defines the functions of systems in nature

Significant nocturnal wakefulness after sleep onset in metabolic dysfunction–associated steatotic liver disease

Emerging cancer therapies: targeting physiological networks and cellular bioelectrical differences with non-thermal systemic electromagnetic fields in the human body – a comprehensive review

Networks through the lens of high-frequency oscillations

The constrained-disorder principle defines the functions of systems in nature

Emerging cancer therapies: targeting physiological networks and cellular bioelectrical differences with non-thermal systemic electromagnetic fields in the human body – a comprehensive review

Significant nocturnal wakefulness after sleep onset in metabolic dysfunction–associated steatotic liver disease

Networks through the lens of high-frequency oscillations

Constructing representative group networks from tractography: lessons from a dynamical approach