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Katebi N, Sameni R, Rohloff P, Clifford GD. Hierarchical Attentive Network for Gestational Age Estimation in Low-Resource Settings. IEEE J Biomed Health Inform 2023; 27:2501-2511. [PMID: 37027652 PMCID: PMC10482160 DOI: 10.1109/jbhi.2023.3246931] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/22/2023]
Abstract
Assessing fetal development is essential to the provision of healthcare for both mothers and fetuses. In low- and middle-income countries, conditions that increase the risk of fetal growth restriction (FGR) are often more prevalent. In these regions, barriers to accessing healthcare and social services exacerbate fetal maternal health problems. One of these barriers is the lack of affordable diagnostic technologies. To address this issue, this work introduces an end-to-end algorithm applied to a low-cost, hand-held Doppler ultrasound device for estimating gestational age (GA), and by inference, FGR. The Doppler ultrasound signals used in this study were collected from 226 pregnancies (45 low birth weight at delivery) between 5 and 9 months GA by lay midwives in highland Guatemala. We designed a hierarchical deep sequence learning model with an attention mechanism to learn the normative dynamics of fetal cardiac activity in different stages of development. This resulted in a state-of-the-art GA estimation performance, with an average error of 0.79 months. This is close to the theoretical minimum for the given quantization level of one month. The model was then tested on Doppler recordings of the fetuses with low birth weight and the estimated GA was shown to be lower than the GA calculated from last menstruation. Thus, this could be interpreted as a potential sign of developmental retardation (or FGR) associated with low birth weight, and referral and intervention may be necessary.
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Ferber SG, Geva R, Weller A. When the Mind Comes to Live Inside the Body: The Ontogeny of the Perceptual Control Clock. Curr Neuropharmacol 2023; 21:13-21. [PMID: 35410607 PMCID: PMC10193756 DOI: 10.2174/1570159x20666220411095508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Revised: 03/18/2022] [Accepted: 04/09/2022] [Indexed: 02/04/2023] Open
Abstract
In this editorial, we discuss the neurobiological processes underlying the early emergence of awareness that we term the "when" and "how" the mind comes to live inside the body. We describe an accumulative developmental process starting during embryonic life and continuing to fetal and postnatal development, of coupling of heart rate, body movements, and sleep states on the behavioral level with underlying mechanisms on the structural, functional, cellular, and molecular levels. A developmental perspective is proposed based on Perceptual Control Theory (PCT). This includes a developing sequence of modules starting from early sensing of neural intensities to early manifestation of human mindful capacities. We also address pharmacological treatments administered to preterm infants, which may interfere with this development, and highlight the need to consider this potential "side effect" of current pharmaceuticals when developing novel pharmacogenomic treatments.
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Affiliation(s)
- Sari Goldstein Ferber
- Department of Psychology and the Leslie and Susan Gonda (Goldschmied) Multidisciplinary Brain Research Center, Bar Ilan University, Ramat Gan, Israel
| | - Ronny Geva
- Department of Psychology and the Leslie and Susan Gonda (Goldschmied) Multidisciplinary Brain Research Center, Bar Ilan University, Ramat Gan, Israel
| | - Aron Weller
- Department of Psychology and the Leslie and Susan Gonda (Goldschmied) Multidisciplinary Brain Research Center, Bar Ilan University, Ramat Gan, Israel
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Cerritelli F, Frasch MG, Antonelli MC, Viglione C, Vecchi S, Chiera M, Manzotti A. A Review on the Vagus Nerve and Autonomic Nervous System During Fetal Development: Searching for Critical Windows. Front Neurosci 2021; 15:721605. [PMID: 34616274 PMCID: PMC8488382 DOI: 10.3389/fnins.2021.721605] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Accepted: 08/19/2021] [Indexed: 12/17/2022] Open
Abstract
The autonomic nervous system (ANS) is one of the main biological systems that regulates the body's physiology. Autonomic nervous system regulatory capacity begins before birth as the sympathetic and parasympathetic activity contributes significantly to the fetus' development. In particular, several studies have shown how vagus nerve is involved in many vital processes during fetal, perinatal, and postnatal life: from the regulation of inflammation through the anti-inflammatory cholinergic pathway, which may affect the functioning of each organ, to the production of hormones involved in bioenergetic metabolism. In addition, the vagus nerve has been recognized as the primary afferent pathway capable of transmitting information to the brain from every organ of the body. Therefore, this hypothesis paper aims to review the development of ANS during fetal and perinatal life, focusing particularly on the vagus nerve, to identify possible "critical windows" that could impact its maturation. These "critical windows" could help clinicians know when to monitor fetuses to effectively assess the developmental status of both ANS and specifically the vagus nerve. In addition, this paper will focus on which factors-i.e., fetal characteristics and behaviors, maternal lifestyle and pathologies, placental health and dysfunction, labor, incubator conditions, and drug exposure-may have an impact on the development of the vagus during the above-mentioned "critical window" and how. This analysis could help clinicians and stakeholders define precise guidelines for improving the management of fetuses and newborns, particularly to reduce the potential adverse environmental impacts on ANS development that may lead to persistent long-term consequences. Since the development of ANS and the vagus influence have been shown to be reflected in cardiac variability, this paper will rely in particular on studies using fetal heart rate variability (fHRV) to monitor the continued growth and health of both animal and human fetuses. In fact, fHRV is a non-invasive marker whose changes have been associated with ANS development, vagal modulation, systemic and neurological inflammatory reactions, and even fetal distress during labor.
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Affiliation(s)
- Francesco Cerritelli
- Research and Assistance for Infants to Support Experience Lab, Foundation Center for Osteopathic Medicine Collaboration, Pescara, Italy
| | - Martin G. Frasch
- Department of Obstetrics and Gynecology and Center on Human Development and Disability, University of Washington, Seattle, WA, United States
| | - Marta C. Antonelli
- Facultad de Medicina, Instituto de Biología Celular y Neurociencia “Prof. E. De Robertis”, Universidad de Buenos Aires, Buenos Aires, Argentina
- Department of Obstetrics and Gynecology, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
| | - Chiara Viglione
- Research and Assistance for Infants to Support Experience Lab, Foundation Center for Osteopathic Medicine Collaboration, Pescara, Italy
| | - Stefano Vecchi
- Research and Assistance for Infants to Support Experience Lab, Foundation Center for Osteopathic Medicine Collaboration, Pescara, Italy
| | - Marco Chiera
- Research and Assistance for Infants to Support Experience Lab, Foundation Center for Osteopathic Medicine Collaboration, Pescara, Italy
| | - Andrea Manzotti
- Research and Assistance for Infants to Support Experience Lab, Foundation Center for Osteopathic Medicine Collaboration, Pescara, Italy
- Department of Pediatrics, Division of Neonatology, “V. Buzzi” Children's Hospital, Azienda Socio-Sanitaria Territoriale Fatebenefratelli Sacco, Milan, Italy
- Research Department, Istituto Osteopatia Milano, Milan, Italy
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Ponsiglione AM, Cosentino C, Cesarelli G, Amato F, Romano M. A Comprehensive Review of Techniques for Processing and Analyzing Fetal Heart Rate Signals. SENSORS (BASEL, SWITZERLAND) 2021; 21:6136. [PMID: 34577342 PMCID: PMC8469481 DOI: 10.3390/s21186136] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 09/04/2021] [Accepted: 09/10/2021] [Indexed: 02/07/2023]
Abstract
The availability of standardized guidelines regarding the use of electronic fetal monitoring (EFM) in clinical practice has not effectively helped to solve the main drawbacks of fetal heart rate (FHR) surveillance methodology, which still presents inter- and intra-observer variability as well as uncertainty in the classification of unreassuring or risky FHR recordings. Given the clinical relevance of the interpretation of FHR traces as well as the role of FHR as a marker of fetal wellbeing autonomous nervous system development, many different approaches for computerized processing and analysis of FHR patterns have been proposed in the literature. The objective of this review is to describe the techniques, methodologies, and algorithms proposed in this field so far, reporting their main achievements and discussing the value they brought to the scientific and clinical community. The review explores the following two main approaches to the processing and analysis of FHR signals: traditional (or linear) methodologies, namely, time and frequency domain analysis, and less conventional (or nonlinear) techniques. In this scenario, the emerging role and the opportunities offered by Artificial Intelligence tools, representing the future direction of EFM, are also discussed with a specific focus on the use of Artificial Neural Networks, whose application to the analysis of accelerations in FHR signals is also examined in a case study conducted by the authors.
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Affiliation(s)
- Alfonso Maria Ponsiglione
- Department of Electrical Engineering and Information Technology (DIETI), University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy; (A.M.P.); (F.A.)
| | - Carlo Cosentino
- Department of Experimental and Clinical Medicine ‘Gaetano Salvatore’, University Magna Graecia of Catanzaro, Viale Tommaso Campanella 185, 88100 Catanzaro, Italy;
| | - Giuseppe Cesarelli
- Department of Chemical, Materials and Production Engineering (DICMaPI), University of Naples Federico II, Piazzale Tecchio 80, 80125 Naples, Italy;
| | - Francesco Amato
- Department of Electrical Engineering and Information Technology (DIETI), University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy; (A.M.P.); (F.A.)
| | - Maria Romano
- Department of Electrical Engineering and Information Technology (DIETI), University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy; (A.M.P.); (F.A.)
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Franke K, Bublak P, Hoyer D, Billiet T, Gaser C, Witte OW, Schwab M. In vivo biomarkers of structural and functional brain development and aging in humans. Neurosci Biobehav Rev 2021; 117:142-164. [PMID: 33308708 DOI: 10.1016/j.neubiorev.2017.11.002] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2017] [Revised: 11/01/2017] [Accepted: 11/03/2017] [Indexed: 12/25/2022]
Abstract
Brain aging is a major determinant of aging. Along with the aging population, prevalence of neurodegenerative diseases is increasing, therewith placing economic and social burden on individuals and society. Individual rates of brain aging are shaped by genetics, epigenetics, and prenatal environmental. Biomarkers of biological brain aging are needed to predict individual trajectories of aging and the risk for age-associated neurological impairments for developing early preventive and interventional measures. We review current advances of in vivo biomarkers predicting individual brain age. Telomere length and epigenetic clock, two important biomarkers that are closely related to the mechanistic aging process, have only poor deterministic and predictive accuracy regarding individual brain aging due to their high intra- and interindividual variability. Phenotype-related biomarkers of global cognitive function and brain structure provide a much closer correlation to age at the individual level. During fetal and perinatal life, autonomic activity is a unique functional marker of brain development. The cognitive and structural biomarkers also boast high diagnostic specificity for determining individual risks for neurodegenerative diseases.
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Affiliation(s)
- K Franke
- Department of Neurology, Jena University Hospital, Jena, Germany.
| | - P Bublak
- Department of Neurology, Jena University Hospital, Jena, Germany
| | - D Hoyer
- Department of Neurology, Jena University Hospital, Jena, Germany
| | | | - C Gaser
- Department of Neurology, Jena University Hospital, Jena, Germany; Department of Psychiatry, Jena University Hospital, Jena, Germany
| | - O W Witte
- Department of Neurology, Jena University Hospital, Jena, Germany
| | - M Schwab
- Department of Neurology, Jena University Hospital, Jena, Germany
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Chiera M, Cerritelli F, Casini A, Barsotti N, Boschiero D, Cavigioli F, Corti CG, Manzotti A. Heart Rate Variability in the Perinatal Period: A Critical and Conceptual Review. Front Neurosci 2020; 14:561186. [PMID: 33071738 PMCID: PMC7544983 DOI: 10.3389/fnins.2020.561186] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Accepted: 08/28/2020] [Indexed: 12/18/2022] Open
Abstract
Neonatal intensive care units (NICUs) greatly expand the use of technology. There is a need to accurately diagnose discomfort, pain, and complications, such as sepsis, mainly before they occur. While specific treatments are possible, they are often time-consuming, invasive, or painful, with detrimental effects for the development of the infant. In the last 40 years, heart rate variability (HRV) has emerged as a non-invasive measurement to monitor newborns and infants, but it still is underused. Hence, the present paper aims to review the utility of HRV in neonatology and the instruments available to assess it, showing how HRV could be an innovative tool in the years to come. When continuously monitored, HRV could help assess the baby’s overall wellbeing and neurological development to detect stress-/pain-related behaviors or pathological conditions, such as respiratory distress syndrome and hyperbilirubinemia, to address when to perform procedures to reduce the baby’s stress/pain and interventions, such as therapeutic hypothermia, and to avoid severe complications, such as sepsis and necrotizing enterocolitis, thus reducing mortality. Based on literature and previous experiences, the first step to efficiently introduce HRV in the NICUs could consist in a monitoring system that uses photoplethysmography, which is low-cost and non-invasive, and displays one or a few metrics with good clinical utility. However, to fully harness HRV clinical potential and to greatly improve neonatal care, the monitoring systems will have to rely on modern bioinformatics (machine learning and artificial intelligence algorithms), which could easily integrate infant’s HRV metrics, vital signs, and especially past history, thus elaborating models capable to efficiently monitor and predict the infant’s clinical conditions. For this reason, hospitals and institutions will have to establish tight collaborations between the obstetric, neonatal, and pediatric departments: this way, healthcare would truly improve in every stage of the perinatal period (from conception to the first years of life), since information about patients’ health would flow freely among different professionals, and high-quality research could be performed integrating the data recorded in those departments.
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Affiliation(s)
- Marco Chiera
- Research and Assistance for Infants to Support Experience Lab, Foundation Center for Osteopathic Medicine Collaboration, Pescara, Italy.,Research Commission on Manual Therapies and Mind-Body Disciplines, Societ Italiana di Psico Neuro Endocrino Immunologia, Rome, Italy
| | - Francesco Cerritelli
- Research and Assistance for Infants to Support Experience Lab, Foundation Center for Osteopathic Medicine Collaboration, Pescara, Italy
| | - Alessandro Casini
- Research and Assistance for Infants to Support Experience Lab, Foundation Center for Osteopathic Medicine Collaboration, Pescara, Italy
| | - Nicola Barsotti
- Research and Assistance for Infants to Support Experience Lab, Foundation Center for Osteopathic Medicine Collaboration, Pescara, Italy.,Research Commission on Manual Therapies and Mind-Body Disciplines, Societ Italiana di Psico Neuro Endocrino Immunologia, Rome, Italy
| | | | - Francesco Cavigioli
- Neonatal Intensive Care Unit, "V. Buzzi" Children's Hospital, Azienda Socio Sanitaria Territoriale Fatebenefratelli-Sacco, Milan, Italy
| | - Carla G Corti
- Pediatric Cardiology Unit-Pediatric Department, Azienda Socio Sanitaria Territoriale Fatebenefratelli-Sacco, Milan, Italy
| | - Andrea Manzotti
- Research and Assistance for Infants to Support Experience Lab, Foundation Center for Osteopathic Medicine Collaboration, Pescara, Italy.,Neonatal Intensive Care Unit, "V. Buzzi" Children's Hospital, Azienda Socio Sanitaria Territoriale Fatebenefratelli-Sacco, Milan, Italy.,Research Department, SOMA, Istituto Osteopatia Milano, Milan, Italy
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Comparison of fetal heart rate variability by symbolic dynamics at the third trimester of pregnancy and low-risk parturition. Heliyon 2020; 6:e03485. [PMID: 32195385 PMCID: PMC7075801 DOI: 10.1016/j.heliyon.2020.e03485] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2019] [Revised: 09/26/2019] [Accepted: 02/20/2020] [Indexed: 12/15/2022] Open
Abstract
Fetal heart rate variability (fHRV) is an essential source of information to monitor fetal well-being during pregnancy. This study aimed to apply a nonlinear approach, known as symbolic dynamics (SD), for comparing human fHRV in the third trimester of pregnancy during active fetal state (TT) and active labor at term (P). We performed a longitudinal, prospective, descriptive, and comparative study composed of 42 longitudinal recordings of 5-minutes of fetal heartbeat interval series. Recordings were collected from 21 low-risk, healthy, pregnant women attending the Maternal and Child Research Center (CIMIGen), Mexico City. We calculated relevant linear parameters of fHRV between TT and P stages, such as the percentage of differences between adjacent RR intervals >5 ms (PRR5, related to vagal modulations) and other SD parameters such as the percentage of no variations between three successive symbols (%0V, reflects sympathetic modulations) and the probability of low variability with a threshold of 4 ms (POLVAR4, associated with a low variability). We identified statistical differences for PRR5 between TT and P (37.13% [28.47-47.60%] vs. 28.84% [19.36-36.76%], p = 0.03), respectively. Also, for 0V% (65.66% [59.01-71.80%] vs. 71.14% [65.94-75.87%], p = 0.03) and for POLVAR4 values (0.06 [0.04-0.11] vs. 0.15 [0.09-0.24], p = 0.002), respectively. Our results indicate that during parturition, the short-term fetal fHRV is decreased, showing a decreased vagal modulations and higher adrenergic response of the heart. These autonomic modifications may result from the fetal response to the stressful inflammatory challenge of labor. We thus confirmed that the analysis of the SD applied to fHRV time series could be a potential clinical biomarker to differentiate the fetal autonomic cardiac condition at different stages of pregnancy.
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Hoyer D, Schmidt A, Gustafson KM, Lobmaier SM, Lakhno I, van Leeuwen P, Cysarz D, Preisl H, Schneider U. Heart rate variability categories of fluctuation amplitude and complexity: diagnostic markers of fetal development and its disturbances. Physiol Meas 2019; 40:064002. [PMID: 31071684 DOI: 10.1088/1361-6579/ab205f] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
OBJECTIVE In fetal diagnosis the myriad and diversity of heart rate variability (HRV) indices prevents a comparable routine evaluation of disturbances in fetal development and well-being. The work aims at the extraction of a small set of HRV key indices that could help to establish a universal, overarching tool to screen for any disturbance. APPROACH HRV indices were organized in categories of short-term (prefix s) and long-term (prefix l) amplitude fluctuations (AMP), complexity (COMP), and patterns (PATTERN) and common representatives for each category were extracted. This procedure was done with respect to the diagnostic value in the evaluation of the maturation age throughout the second and complete third trimester of pregnancy as well as to potential differences associated with maternal life-style factors (physical exercise, smoking), nutrient intervention (docosahexaenoic acid (DHA) supplementation), and complications of pregnancy (gestational diabetes mellitus (GDM), intra-uterine growth restriction (IUGR)). MAIN RESULTS We found a comprehensive minimal set that includes [lAMP: short term variation (STV), initially introduced in cardiotocography, sAMP: heart rate increase across one interbeat interval of phase rectified averaged signal - acceleration capacity (ACst1), lCOMP: scale 4 multi-scale entropy (MSE4), PATTERN: skewness] for the maturation age prediction, and partly overlapping [lAMP: STV, sAMP: ACst1, sCOMP: Lempel Ziv complexity (LZC)] for the discrimination of the deviations. SIGNIFICANCE The minimal set of category-based HRV representatives allows for a screening of fetal development and well-being. These results are an important step towards a universal and comparable diagnostic tool for the early identification of developmental disturbances. Novelty & Significance Fetal development and its disturbances have been reported to be associated with a multiplicity of HRV indices. Furthermore, these HRV indices change with maturation. We propose the abstraction of HRV categories defined by short- and long-term fluctuation amplitude, complexity, and pattern indices that cover all relevant aspects of maturational age, behavioral influences and a series of pathological disturbances. The study data are provided by multiple centers. Our approach is an important step towards the goal of a standardized diagnostic tool for early identification of fetal developmental disturbances with respect to the reduction of serious complications in the later life.
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Affiliation(s)
- Dirk Hoyer
- Hans Berger Department of Neurology, Biomagnetic Center, Jena University Hospital, Jena 07747, Germany
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Antenatal electronic fetal heart monitoring for extremely and very preterm newborns. GINECOLOGIA.RO 2019. [DOI: 10.26416/gine.26.4.2019.2705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
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Schneider U, Bode F, Schmidt A, Nowack S, Rudolph A, Doelcker EM, Schlattmann P, Götz T, Hoyer D. Developmental milestones of the autonomic nervous system revealed via longitudinal monitoring of fetal heart rate variability. PLoS One 2018; 13:e0200799. [PMID: 30016343 PMCID: PMC6049949 DOI: 10.1371/journal.pone.0200799] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2017] [Accepted: 07/03/2018] [Indexed: 01/28/2023] Open
Abstract
BACKGROUND Fetal heart rate variability (fHRV) of normal-to-normal (NN) beat intervals provides high-temporal resolution access to assess the functioning of the autonomic nervous system (ANS). AIM To determine critical periods of fetal autonomic maturation. The developmental pace is hypothesized to change with gestational age (GA). STUDY DESIGN Prospective longitudinal observational study. SUBJECTS 60 healthy singleton fetuses were followed up by fetal magnetocardiographic heart rate monitoring 4-11 times (median 6) during the second half of gestation. OUTCOME MEASURE FHRV parameters, accounting for differential aspects of the ANS, were studied applying linear mixed models over four predefined pregnancy segments of interest (SoI: <27; 27+0-31+0; 31+1-35+0; >35+1 weeks GA). Periods of fetal active sleep and quiescence were accounted for separately. RESULTS Skewness of the NN interval distribution VLF/LF band power ratio and complexity describe a saturation function throughout the period of interest. A decreasing LF/HF ratio and an increase in pNN5 indicate a concurrent shift in sympathovagal balance. Fluctuation amplitude and parameters of short-term variability (RMSSD, HF band) mark a second acceleration towards term. In contrast, fetal quiescence is characterized by sequential, but low-margin transformations; ascending overall variability followed by an increase of complexity and superseded by fluctuation amplitude. CONCLUSIONS An increase in sympathetic activation, connected with by a higher ability of parasympathetic modulation and baseline stabilization, is reached during the transition from the late 2nd into the early 3rd trimester. Pattern characteristics indicating fetal well-being saturate at 35 weeks GA. Pronounced fetal breathing efforts near-term mirror in fHRV as respiratory sinus arrhythmia.
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Affiliation(s)
- Uwe Schneider
- Department of Obstetrics, Division of Prenatal Diagnostics and Fetal Physiology, Jena University Hospital, Jena, Germany
- * E-mail:
| | - Franziska Bode
- Department of Obstetrics, Division of Prenatal Diagnostics and Fetal Physiology, Jena University Hospital, Jena, Germany
| | - Alexander Schmidt
- Hans Berger Clinic of Neurology, Biomagnetic Center, Jena University Hospital, Jena, Germany
| | - Samuel Nowack
- Hans Berger Clinic of Neurology, Biomagnetic Center, Jena University Hospital, Jena, Germany
| | - Anja Rudolph
- Department of Obstetrics, Division of Prenatal Diagnostics and Fetal Physiology, Jena University Hospital, Jena, Germany
| | - Eva-Maria Doelcker
- Hans Berger Clinic of Neurology, Biomagnetic Center, Jena University Hospital, Jena, Germany
- Institute of Biomedical Engineering and Informatics, Technical University, Ilmenau, Germany
| | - Peter Schlattmann
- Institute for Medical Statistics, Computer and Data Sciences, Jena University Hospital, Jena, Germany
| | - Theresa Götz
- Hans Berger Clinic of Neurology, Biomagnetic Center, Jena University Hospital, Jena, Germany
- Institute for Medical Statistics, Computer and Data Sciences, Jena University Hospital, Jena, Germany
| | - Dirk Hoyer
- Hans Berger Clinic of Neurology, Biomagnetic Center, Jena University Hospital, Jena, Germany
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Schmidt A, Schukat-Talamazzini EG, Zöllkau J, Pytlik A, Leibl S, Kumm K, Bode F, Kynass I, Witte OW, Schleussner E, Schneider U, Hoyer D. Universal characteristics of evolution and development are inherent in fetal autonomic brain maturation. Auton Neurosci 2018. [DOI: 10.1016/j.autneu.2018.02.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
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12
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Frasch MG, Lobmaier SM, Stampalija T, Desplats P, Pallarés ME, Pastor V, Brocco MA, Wu HT, Schulkin J, Herry CL, Seely AJE, Metz GAS, Louzoun Y, Antonelli MC. Non-invasive biomarkers of fetal brain development reflecting prenatal stress: An integrative multi-scale multi-species perspective on data collection and analysis. Neurosci Biobehav Rev 2018; 117:165-183. [PMID: 29859198 DOI: 10.1016/j.neubiorev.2018.05.026] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2018] [Revised: 05/09/2018] [Accepted: 05/25/2018] [Indexed: 02/07/2023]
Abstract
Prenatal stress (PS) impacts early postnatal behavioural and cognitive development. This process of 'fetal programming' is mediated by the effects of the prenatal experience on the developing hypothalamic-pituitary-adrenal (HPA) axis and autonomic nervous system (ANS). We derive a multi-scale multi-species approach to devising preclinical and clinical studies to identify early non-invasively available pre- and postnatal biomarkers of PS. The multiple scales include brain epigenome, metabolome, microbiome and the ANS activity gauged via an array of advanced non-invasively obtainable properties of fetal heart rate fluctuations. The proposed framework has the potential to reveal mechanistic links between maternal stress during pregnancy and changes across these physiological scales. Such biomarkers may hence be useful as early and non-invasive predictors of neurodevelopmental trajectories influenced by the PS as well as follow-up indicators of success of therapeutic interventions to correct such altered neurodevelopmental trajectories. PS studies must be conducted on multiple scales derived from concerted observations in multiple animal models and human cohorts performed in an interactive and iterative manner and deploying machine learning for data synthesis, identification and validation of the best non-invasive detection and follow-up biomarkers, a prerequisite for designing effective therapeutic interventions.
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Affiliation(s)
- Martin G Frasch
- Department of Obstetrics and Gynecology, University of Washington, Seattle, USA.
| | - Silvia M Lobmaier
- Frauenklinik und Poliklinik, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Tamara Stampalija
- Unit of Fetal Medicine and Prenatal Diagnosis, Institute for Mother and Child Health IRCCS Burlo Garofolo, Trieste, Italy
| | - Paula Desplats
- University of California, Departments of Neurosciences and Pathology, San Diego, USA
| | - María Eugenia Pallarés
- Instituto de Biología Celular y Neurociencia "Prof. Eduardo De Robertis", Facultad de Medicina, Universidad de Buenos Aires, Argentina
| | - Verónica Pastor
- Instituto de Biología Celular y Neurociencia "Prof. Eduardo De Robertis", Facultad de Medicina, Universidad de Buenos Aires, Argentina
| | - Marcela A Brocco
- Instituto de Investigaciones Biotecnológicas - Instituto Tecnológico de Chascomús (IIB-INTECH), Universidad Nacional de San Martín - Consejo Nacional de Investigaciones Científicas y Técnicas (UNSAM-CONICET), San Martín, Buenos Aires, Argentina
| | - Hau-Tieng Wu
- Department of Mathematics and Department of Statistical Science, Duke University, Durham, NC, USA; Mathematics Division, National Center for Theoretical Sciences, Taipei, Taiwan
| | - Jay Schulkin
- Department of Obstetrics and Gynecology, University of Washington, Seattle, USA
| | | | | | - Gerlinde A S Metz
- Canadian Centre for Behavioural Neuroscience, Department of Neuroscience, University of Lethbridge, Lethbridge, Alberta, Canada
| | - Yoram Louzoun
- Bar-Ilan University, Department of Applied Mathematics, Israel
| | - Marta C Antonelli
- Instituto de Biología Celular y Neurociencia "Prof. Eduardo De Robertis", Facultad de Medicina, Universidad de Buenos Aires, Argentina
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Li Y, Liu Y, Wang P, Wang J, Xu S, Qiu M. Dependency criterion based brain pathological age estimation of Alzheimer's disease patients with MR scans. Biomed Eng Online 2017; 16:50. [PMID: 28438167 PMCID: PMC5404315 DOI: 10.1186/s12938-017-0342-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2016] [Accepted: 04/19/2017] [Indexed: 12/20/2022] Open
Abstract
Objectives Traditional brain age estimation methods are based on the idea that uses the real age as the training label. However, these methods ignore that there is a deviation between the real age and the brain age due to the accelerated brain aging. Methods This paper considers this deviation and obtains it by maximizing the correlation between the estimated brain age and the class label rather than by minimizing the difference between the estimated brain age and the real age. Firstly, set the search range of the deviation as the deviation candidates according to the prior knowledge. Secondly, use the support vector regression as the age estimation model to minimize the difference between the estimated age and the real age plus deviation rather than the real age itself. Thirdly, design the fitness function based on the correlation criterion. Fourthly, conduct age estimation on the validation dataset using the trained age estimation model, put the estimated age into the fitness function, and obtain the fitness value of the deviation candidate. Fifthly, repeat the iteration until all the deviation candidates are involved and get the optimal deviation with maximum fitness values. The real age plus the optimal deviation is taken as the brain pathological age. Results The experimental results showed that the separability of the samples was apparently improved. For normal control- Alzheimer’s disease (NC-AD), normal control- mild cognition impairment (NC-MCI), and mild cognition impairment—Alzheimer’s disease (MCI-AD), the average improvements were 0.164 (31.66%), 0.1284 (34.29%), and 0.0206 (7.1%), respectively. For NC-MCI-AD, the average improvement was 0.2002 (50.39%). The estimated brain pathological age could be not only more helpful for the classification of AD but also more precisely reflect the accelerated brain aging. Conclusion In conclusion, this paper proposes a new kind of brain age—brain pathological age and offers an estimation method for it that can distinguish different states of AD, thereby better reflecting accelerated brain aging. Besides, the brain pathological age is most helpful for feature reduction, thereby simplifying the relevant classification algorithm.
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Affiliation(s)
- Yongming Li
- College of Communication Engineering, Chongqing University, Shapingba District, Chongqing, 400044, China. .,Department of Medical Image, College of Biomedical Engineering, Third Military Medical University, Chongqing, 400038, China. .,Collaborative Innovation Center for Brain Science, Chongqing University, Chongqing, 400044, China.
| | - Yuchuan Liu
- College of Communication Engineering, Chongqing University, Shapingba District, Chongqing, 400044, China
| | - Pin Wang
- College of Communication Engineering, Chongqing University, Shapingba District, Chongqing, 400044, China
| | - Jie Wang
- College of Communication Engineering, Chongqing University, Shapingba District, Chongqing, 400044, China
| | - Sha Xu
- College of Communication Engineering, Chongqing University, Shapingba District, Chongqing, 400044, China
| | - Mingguo Qiu
- Department of Medical Image, College of Biomedical Engineering, Third Military Medical University, Chongqing, 400038, China
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Moorman R, Simmons M. Martin Black award for the best paper published in 2015. Physiol Meas 2016; 37:E27-E28. [PMID: 27754985 DOI: 10.1088/0967-3334/37/11/e27] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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