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Special Issue "Diagnosis, Treatment and Prevention of Fetal Diseases and Fetal Risk Factors for Non-Communicable Diseases"

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Obstetrics & Gynecology".

Deadline for manuscript submissions: 31 August 2019

Special Issue Editor

Guest Editor
Dr. Michael Skilton

Boden Institute of Obesity, Nutrition, Exercise and Eating Disorders, D17-Charles Perkins Centre, The University of Sydney, Sydney, Australia
Website 1 | Website 2 | E-Mail
Interests: nutrition; cardiovascular disease; developmental origins of health and disease; indigenous health

Special Issue Information

Dear Colleagues,

Diseases of the fetal period include chorioamnionitis, fetal growth restriction, preterm birth, and congenital heart diseases amongst others, in addition to emerging threats such as those secondary to Zika virus. These diseases of the fetal period have a disproportionately large impact on the burden of disease and disability across the life course.

There are distinct challenges in the diagnosis, treatment and prevention of diseases of the fetal period. Diagnosis, particularly in the early stage of disease, is often challenging; treatments often lack effectiveness; and there are inherent risks associated with prevention strategies implemented during pregnancy.

Furthermore, beyond immediate disease outcomes in the fetal and perinatal periods, there is evidence that a variety of intrauterine exposures can influence the risk of non-communicable diseases across the life course. While most evidence has focused on cardiovascular diseases, allergic diseases, obesity and diabetes, there is emerging evidence of links between early life exposures and a number of cancers.

Evidence from animal models, epidemiology, applied and clinical research, particularly clinical trials, are required to advance the science, prevention, diagnosis and treatment within this field.

Dr. Michael Skilton
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Clinical Medicine is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Fetus
  • Pregnancy
  • Fetal diseases
  • Prevention
  • Treatment
  • Developmental origins of disease
  • Non-communicable diseases

Published Papers (3 papers)

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Research

Open AccessArticle
FABP4 in Gestational Diabetes—Association between Mothers and Offspring
J. Clin. Med. 2019, 8(3), 285; https://doi.org/10.3390/jcm8030285
Received: 29 December 2018 / Revised: 18 February 2019 / Accepted: 22 February 2019 / Published: 27 February 2019
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Abstract
Fetuses exposed to gestational diabetes mellitus (GDM) have a higher risk of abnormal glucose homeostasis in later life. The molecular mechanisms of this phenomenon are still not fully understood. Fatty acid binding protein 4 (FABP4) appears to be one of the most probable [...] Read more.
Fetuses exposed to gestational diabetes mellitus (GDM) have a higher risk of abnormal glucose homeostasis in later life. The molecular mechanisms of this phenomenon are still not fully understood. Fatty acid binding protein 4 (FABP4) appears to be one of the most probable candidates involved in the pathophysiology of GDM. The main aim of the study was to investigate whether umbilical cord serum FABP4 concentrations are altered in term neonates born to GDM mothers. Two groups of subjects were selected—28 healthy controls and 26 patients with GDM. FABP4, leptin, and ghrelin concentrations in the umbilical cord serum, maternal serum, and maternal urine were determined via an enzyme-linked immunosorbent assay. The umbilical cord serum FABP4 levels were higher in the GDM offspring and were directly associated with the maternal serum FABP4 and leptin levels, as well as the prepregnancy body mass index (BMI) and the BMI at and after delivery; however, they correlated negatively with birth weight and lipid parameters. In the multiple linear regression models, the umbilical cord serum FABP4 concentrations depended positively on the maternal serum FABP4 and negatively on the umbilical cord serum ghrelin levels and the high-density lipoprotein cholesterol. There are many maternal variables that can affect the level of FABP4 in the umbilical cord serum, thus, their evaluation requires further investigation. Full article
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Open AccessArticle
Body Fatness and Cardiovascular Health in Newborn Infants
J. Clin. Med. 2018, 7(9), 270; https://doi.org/10.3390/jcm7090270
Received: 16 August 2018 / Revised: 4 September 2018 / Accepted: 8 September 2018 / Published: 11 September 2018
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Abstract
Birth weight is associated with cardiovascular disease, with those at both ends of the spectrum at increased risk. However, birth weight is a crude surrogate of fetal growth. Measures of body composition may more accurately identify high risk infants. We aimed to determine [...] Read more.
Birth weight is associated with cardiovascular disease, with those at both ends of the spectrum at increased risk. However, birth weight is a crude surrogate of fetal growth. Measures of body composition may more accurately identify high risk infants. We aimed to determine whether aortic wall thickening, cardiac autonomic control, and cardiac structure/function differ in newborns with high or low body fatness compared to those with average body fatness. 189 healthy singleton term born neonates were recruited and stratified by body fat percentiles (sex and gestation-specific). Infants with low body fat had higher aortic intima-media thickness (43 µm (95% confidence interval (CI) 7, 78), p = 0.02), lower heart rate variability (log total power, −0.5 (95% CI −0.8, −0.1), p = 0.008), and thicker ventricular walls (posterior wall thickness, 3.1 mm (95% CI 1.6, 4.6), p < 0.001) compared to infants with average body fatness. Infants with high body fat showed no differences in aortic intima-media thickness (−2 µm (95% CI −37, 33), p = 0.91) or cardiac structure compared to average body fatness, although stroke volume (−0.3 mL/kg (95% CI −0.6, −0.0), p = 0.003) and heart rate variability were lower (log total power, −0.8 (95% CI −1.1, −0.5), p < 0.001). The non-linear association of body fatness with heart rate variability was independent of birth weight. Infants born with low or high body fat have altered markers of cardiovascular health. Assessment of body fatness alongside birth weight may assist in identifying high risk individuals. Full article
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Open AccessArticle
A Comprehensive Feature Analysis of the Fetal Heart Rate Signal for the Intelligent Assessment of Fetal State
J. Clin. Med. 2018, 7(8), 223; https://doi.org/10.3390/jcm7080223
Received: 16 July 2018 / Revised: 14 August 2018 / Accepted: 16 August 2018 / Published: 20 August 2018
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Abstract
Continuous monitoring of the fetal heart rate (FHR) signal has been widely used to allow obstetricians to obtain detailed physiological information about newborns. However, visual interpretation of FHR traces causes inter-observer and intra-observer variability. Therefore, this study proposed a novel computerized analysis software [...] Read more.
Continuous monitoring of the fetal heart rate (FHR) signal has been widely used to allow obstetricians to obtain detailed physiological information about newborns. However, visual interpretation of FHR traces causes inter-observer and intra-observer variability. Therefore, this study proposed a novel computerized analysis software of the FHR signal (CAS-FHR), aimed at providing medical decision support. First, to the best of our knowledge, the software extracted the most comprehensive features (47) from different domains, including morphological, time, and frequency and nonlinear domains. Then, for the intelligent assessment of fetal state, three representative machine learning algorithms (decision tree (DT), support vector machine (SVM), and adaptive boosting (AdaBoost)) were chosen to execute the classification stage. To improve the performance, feature selection/dimensionality reduction methods (statistical test (ST), area under the curve (AUC), and principal component analysis (PCA)) were designed to determine informative features. Finally, the experimental results showed that AdaBoost had stronger classification ability, and the performance of the selected feature set using ST was better than that of the original dataset with accuracies of 92% and 89%, sensitivities of 92% and 89%, specificities of 90% and 88%, and F-measures of 95% and 92%, respectively. In summary, the results proved the effectiveness of our proposed approach involving the comprehensive analysis of the FHR signal for the intelligent prediction of fetal asphyxia accurately in clinical practice. Full article
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J. Clin. Med. EISSN 2077-0383 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
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