An integrated approach based on advanced CTG parameters and Doppler measurements for late growth restriction management.

BACKGROUND: The clinical diagnosis of late Fetal Growth Restriction (FGR) involves the integration of Doppler ultrasound data and Fetal Heart Rate (FHR) monitoring through computer assisted computerized cardiotocography (cCTG). The aim of the study was to evaluate the diagnostic power of combined Doppler and cCTG parameters by contrasting late FGR -and healthy controls. METHODS: The study was conducted from January 2018 to May 2020. Only pregnant women who had the last Doppler measurement obtained within 1 week before delivery and cCTG performed within 24 h before delivery were included in the study. Two hundred forty-nine pregnant women fulfilling the inclusion criteria were enrolled in the study; 95 were confirmed as late FGR and 154 were included in the control group. RESULTS: Among the extracted cCTG parameters, Delta Index, Short Term Variability (STV), Long Term Variability (LTV), Acceleration and Deceleration Phase Rectified Slope (APRS, DPRS) values were lower in the late FGR participants compared to the control group. In the FGR cohort, Delta, STV, APRS, and DPRS were found different when stratifying by MCA_PI (MCA_PI <5th centile or > 5th centile). STV and DPRS were the only parameters to be found different when stratifying by (UA_PI >95th centile or UA_PI <95th centile). Additionally, we measured the predictive power of cCTG parameters toward the identification of associated Doppler measures using figures of merit extracted from ROC curves. The AUC of ROC curves were accurate for STV (0,70), Delta (0,68), APRS (0,65) and DPRS (0,71) when UA_PI values were > 95th centile while, the accuracy attributable to the prediction of MCA_PI was 0.76, 0.77, 0.73, and 0.76 for STV, Delta, APRS, and DPRS, respectively. An association of UA_PI>95th centile and MCA_PI<5th centile with higher risk for NICU admission, was observed, while CPR < 5th centile resulted not associated with any perinatal outcome. Values of STV, Delta, APRS, DPRS were significantly lower for FGR neonates admitted to NICU, compared with the uncomplicated FGR cohort. CONCLUSIONS: The results of this study show the contribution of advanced cCTG parameters and fetal Doppler to the identification of late FGR and the association of those parameters with the risk for NICU admission. TRIAL REGISTRATION: Retrospectively registered.

Impact of nuchal cord on antenatal and intrapartum foetal heart rate surveillance and perinatal outcome.

Analysing antepartum and intrapartum computerised cardiotocographic (cCTG) parameters in physiological term pregnancies with nuchal (NC) or body cord (BC), in order to correlate them with labour events and neonatal outcome. We enrolled 808 pregnant women, composed of 264 with 'one NC', 121 with 'multiple NCs', 39 with BC and 384 with 'no NC', were monitored from the 37th week of gestation before labour, while 49 pregnant women with 'one or more NCs' and 47 with 'no NCs' were analysed during labour. No differences in maternal characteristics, foetal pH at birth and 5-min Apgar score were observed. The birth weight was significantly lower in the 'multiple NCs' group, while 1-minute Apgar score was lower in the BC group than the other groups, respectively. No relevant differences in cCTG parameters were observed, except for LTI, Delta and number of variable decelerations in antepartum period and only variable deceleration in intrapartum period.Impact statementWhat is already known on this subject? Ultrasound cannot predict which foetuses with NCs are likely to have problem during labour. The question arose if single or multiple NC could affects FHR monitoring prior and during labour.What do the results of this study add? Computerised cardiotocography (cCTG) is a standardised method developed to reduce inter- and intra-observer variability and the poor reproducibility of visual analysis. Few studies have investigated the influence of NCs on FHR variability and, to our knowledge, no one has evaluated its linear and nonlinear characteristics in antepartum and intrapartum period using a computerised analysis system. No differences in maternal characteristics, foetal pH at birth and 5-min Apgar score were observed. Birth weight was significantly lower in the 'multiple NCs' group, while 1-min Apgar score was lower in the BC group than the other groups, respectively. Foetuses with 'one or more NCs' evidenced a larger number of prolonged second stage and meconium-stained liquor cases, while the operative vaginal delivery and emergency caesarean section rates were unchanged. No relevant differences in cCTG parameters were observed, except for LTI, Delta and number of variable decelerations in antepartum period and only variable deceleration in intrapartum period.What are the implications of these findings for clinical practice and/or further research? cCTG monitoring results confirmed their usefulness for assessing the state of good oxygenation for all foetuses investigated.

Fetal heart rate monitoring and neonatal outcome in a population of early- and late-onset intrauterine growth restriction.

AIM: The early-onset intrauterine growth restriction (IUGR) is associated with severe placental insufficiency and Doppler abnormalities. The late-onset IUGR is associated with mild placental insufficiency and normal Doppler velocimetry. The computerized cardiotocographic (cCTG) monitoring is used to evaluate the fetal well-being in pregnancies complicated by IUGR. Our aim was to investigate the cardiotocographic characteristics of IUGR fetuses and to identify every cCTG difference between Healthy and IUGR fetuses. METHODS: Four hundred thirty pregnant women were enrolled starting from the 28th week of gestation until the time of delivery: 200 healthy and 230 IUGR fetuses. Fetal heart rate (FHR) baseline (FHR), short-term variability (STV), long-term irregularity (LTI), delta, interval index (II), approximate entropy (ApEn), high frequency (HF), low frequency (LF), movement frequency (MF), LF/(HF + MF) ratio (LF/(HF + MF)) and number of decelerations were examined. Newborn baby data were also collected. RESULTS: The parameters of short- and medium-term variability discriminate between IUGR and healthy fetuses before 36 weeks including FHR, STV, LTI and delta discriminate between each subgroup of IUGR were compared to each one of the other two (P < 0.05). CONCLUSION: cCTG is a useful tool for the evaluation of chronic hypoxemia, which causes a delay in the maturation of all components of the autonomic and central nervous system. However, cCTG requires integration with fetal ultrasound and Doppler vessels evaluation to improve the ability to predict the neonatal outcome.

A Wavelet Transform-Based Neural Network Denoising Algorithm for Mobile Phonocardiography.

Cardiovascular pathologies cause 23.5% of human deaths, worldwide. An auto-diagnostic system monitoring heart activity, which can identify the early symptoms of cardiac illnesses, might reduce the death rate caused by these problems. Phonocardiography (PCG) is one of the possible techniques able to detect heart problems. Nevertheless, acoustic signal enhancement is required since it is exposed to various disturbances coming from different sources. The most common denoising enhancement is based on the Wavelet Transform (WT). However, the WT is highly susceptible to variations in the noise frequency distribution. This paper proposes a new adaptive denoising algorithm, which combines WT and Time Delay Neural Networks (TDNN). The acquired signal is decomposed by means of the WT using the coif five-wavelet basis at the tenth decomposition level and then provided as input to the TDNN. Besides the advantage of adaptive thresholding, the reason for using TDNNs is their capacity of estimating the Inverse Wavelet Transform (IWT). The best parameters of the TDNN were found for a NN consisting of 25 neurons in the first and 15 in the second layer and the delay block of 12 samples. The method was evaluated on several pathological heart sounds and on signals recorded in a noisy environment. The performance of the developed system with respect to other wavelet-based denoising approaches was validated by the online questionnaire.

Ethnic analogies and differences in fetal heart rate variability signal: A retrospective study.

AIM: We aimed to analyze computerized cardiotocographic (cCTG) parameters (including fetal heart rate baseline, short-term variability, Delta, long-term irregularity [LTI], interval index [II], low frequency [LF], movement frequency [MF], high frequency [HF], and approximate entropy [ApEn]) in physiological term pregnancies in order to correlate them with ethnic differences. The clinical meaning of numerical parameters may explain physiological or paraphysiological phenomena that occur in fetuses of different ethnic origins. METHODS: A total of 696 pregnant women, including 384 from Europe, 246 from sub-Saharan Africa, 45 from South-East Asia, and 21 from South America, were monitored from the 37th to the 41st week of gestation. Statistical analysis was performed with the analysis of variance test, Pearson correlation test and receiver-operator curves (P < 0.05). RESULTS: Our results showed statistically significant differences (P < 0.05) between white and black women for Delta, LTI, LF, MF, HF, and ApEn; between white and Asian women for Delta, LTI, MF, and the LF/(HF + MF) ratio; and between white and Latina women for Delta, LTI, and ApEn. In particular, Delta and LTI performed better in the white group than in the black, Asian, and Latina groups. Instead, LF, MF, HF, and ApEn performed better in the black than in the white group. CONCLUSION: Our results confirmed the integrity and normal functionality of both central and autonomic nervous system components for all fetuses investigated. Therefore, CTG monitoring should include both linear and nonlinear components of fetal heart rate variability in order to avoid misinterpretations of the CTG trace among ethnic groups.

Telemedicine to Improve Access to Specialist Care in Fetal Heart Rate Monitoring: Analysis of 17 Years of TOCOMAT Network Clinical Activity.

BACKGROUND: The objective of this article is to provide an overview of the clinical experience of our telemedicine network (TOCOMAT) for fetal well-being assessment through computerized Cardiotocography (cCTG), analyzing cultural, socioeconomic, and environmental conditions of pregnant women and its economic sustainability over time. MATERIALS AND METHODS: We used the central data store, including all cCTG records collected in Campania region (Italy) during 17 years of activity. The Operations Center acquires the traces recorded in the Remote Units and simultaneously performs a complex fetal heart rate analysis. An Internet or phone conference calling is available to discuss the information transmitted. Finally, the report is send back to the Remote Units. RESULTS: The number of cCTG traces performed was constantly increasing, despite the progressive reduction in the number of peripheral units involved. Pregnant women in Remote Unit group were younger and overweight and showed a higher incidence of diabetes and fetal defects than Operations Center ones. Moreover, a high rate of African migrant women and low socioeconomic and cultural standards were found in Remote Unit group. The cost analysis showed an economic advantage both in the reduction of inappropriate admissions and in the improvement of admission indicators (hospital stay days) for pregnant women. DISCUSSION: The global economic recession has had a significant impact on the Italian regional healthcare system and socioeconomic deprivation. CONCLUSIONS: Telemedicine could avoid unnecessary referral to Level III centers (Hospital) in Campania region, where the average population density is very high, allowing equal access to ultra-specialist assessment irrespective of the geographical location of the pregnant woman with medium to high risk, as well as rationalizing the costs for maternal and fetal care.

Computerised analysis of antepartum foetal heart parameters: New reference ranges.

We selected 4012 cCTG records (one trace for each patient) performed in healthy pregnancies from 30th to 42nd gestational week using foetal heart rate (FHR), short-term variability (STV), long-term irregularity (LTI), Delta, approximate entropy (ApEn), spectral components as low frequency (LF), median frequency (MF), high frequency (HF) and LF/(HF + MF) ratio were analysed. Reference nomograms were created and sensitivity and specificity for the prediction of foetal compromise were calculated which were 90% and 89%, respectively. Changes of cCTG parameters according to gestational week were evaluated: FHR (r = -.65) and LF (r = -.87) showed a statistically significant reduction (p < .05) with gestational age. STV (r = .59), LTI (r = .69), Delta (r = .67), and MF (r = .88) showed a statistically significant increase (p < .05) with gestational age. In contrast, for ApEn (r = -.098), HF (r = .14) and LF/(HF + MF) ratio (r = -.47) a non-statistically significant change was found (p > .05). The identification of reference ranges for cCTG indexes in according to gestational age could provide a more objective examination of cCTG trace.

Pre-exposure of neuroblastoma cell line to pulsed electromagnetic field prevents H2 O2 -induced ROS production by increasing MnSOD activity.

Electromagnetic fields (EMFs) have been linked to increased risk of cancers and neurodegenerative diseases; however, EMFs can also elicit positive effects on biological systems, and redox status seems crucially involved in EMF biological effects. This study aimed to assess whether a short and repeated pulsed EMF (PEMF) could trigger adaptive responses against an oxidative insult in a neuronal cellular model. We found that a 40 min overall (four times a week, 10 min each) pre-exposure to PEMF did not affect major physiological parameters and led to a significant increase of Mn-dependent superoxide dismutase activity in the human neuroblastoma SH-SY5Y cell line. In addition, we found PEMF-pre-exposed cells exhibited decreased reactive oxygen species production following a 30 min H2 O2 challenge, with respect to non pre-exposed cells. Our findings might provide new insights on the role played by short and repeated PEMF stimulations in the enhancement of cellular defenses against oxidative insults. Although studies in normal neuronal cells would be useful to further confirm our hypothesis, we suggest that specific PEMF treatments may have potential biological repercussions in diseases where oxidative stress is implicated.

Autophagy is modulated in human neuroblastoma cells through direct exposition to low frequency electromagnetic fields.

In neurogenerative diseases, comprising Alzheimer's (AD), functional alteration in autophagy is considered one of the pathological hallmarks and a promising therapeutic target. Epidemiological investigations on the possible causes undergoing these diseases have suggested that electromagnetic fields (EMF) exposition can contribute to their etiology. On the other hand, EMF have therapeutic implications in reactivating neuronal functionality. To partly clarify this dualism, the effect of low-frequency EMF (LF-EMF) on the modulation of autophagy was investigated in human neuroblastoma SH-SY5Y cells, which were also subsequently exposed to Aß peptides, key players in AD. The results primarily point that LF-EMF induce a significant reduction of microRNA 30a (miR-30a) expression with a concomitant increase of Beclin1 transcript (BECN1) and its corresponding protein. Furthermore, LF-EMF counteract the induced miR-30a up-regulation in the same cells transfected with miR-30a mimic precursor molecules and, on the other side, rescue Beclin1 expression after BECN1 siRNA treatment. The expression of autophagy-related markers (ATG7 and LC3B-II) as well as the dynamics of autophagosome formation were also visualized after LF-EMF exposition. Finally, different protocols of repeated LF-EMF treatments were assayed to contrast the effects of Aß peptides in vitro administration. Overall, this research demonstrates, for the first time, that specific LF-EMF treatments can modulate in vitro the expression of a microRNA sequence, which in turn affects autophagy via Beclin1 expression. Taking into account the pivotal role of autophagy in the clearance of protein aggregates within the cells, our results indicate a potential cytoprotective effect exerted by LF-EMF in neurodegenerative diseases such as AD. J. Cell. Physiol. 229: 1776-1786, 2014. © 2014 Wiley Periodicals, Inc.

Fetal heart rate spectral analysis in raw signals and PRSA-derived curve: normal and pathological fetuses discrimination.

Cardiotocography (CTG) is the most common technique for electronic fetal monitoring and consists of the simultaneous recording of fetal heart rate (FHR) and uterine contractions. In analogy with the adult case, spectral analysis of the FHR signal can be used to assess the functionality of the autonomic nervous system. To do so, several methods can be employed, each of which has its strengths and limitations. This paper aims at performing a methodological investigation on FHR spectral analysis adopting 4 different spectrum estimators and a novel PRSA-based spectral method. The performances have been evaluated in terms of the ability of the various methods to detect changes in the FHR in two common pregnancy complications: intrauterine growth restriction (IUGR) and gestational diabetes. A balanced dataset containing 2178 recordings distributed between the 32nd and 38th week of gestation was used. The results show that the spectral method derived from the PRSA better differentiates high-risk pregnancies vs. controls compared to the others. Specifically, it more robustly detects an increase in power percentage within the movement frequency band and a decrease in high frequency between pregnancies at high risk in comparison to those at low risk.

Mouse embryonic stem cells irradiated with γ-rays differentiate into cardiomyocytes but with altered contractile properties.

Embryonic stem cells (ESCs) for their derivation from the inner cell mass of a blastocyst represent a valuable in vitro model to investigate the effects of ionizing radiation on early embryonic cellular response. Following irradiation, both human and mouse ESCs (mESCs) maintain their pluripotent status and the capacity to differentiate into embryoid bodies and to form teratomas. Although informative of the maintenance of a pluripotent status, these studies never investigated the capability of irradiated ESCs to form specific differentiated phenotypes. Here, for the first time, 5Gy-irradiated mESCs were differentiated into cardiomyocytes, thus allowing the analysis of the long-term effects of ionizing radiations on the differentiation potential of a pluripotent stem cell population. On treated mESCs, 96h after irradiation, a genome-wide expression analysis was first performed in order to determine whether the treatment influenced gene expression of the surviving mESCs. Microarrays analysis showed that only 186 genes were differentially expressed in treated mESCs compared to control cells; a quarter of these genes were involved in cellular differentiation, with three main gene networks emerging, including cardiogenesis. Based on these results, we differentiated irradiated mESCs into cardiomyocytes. On day 5, 8 and 12 of differentiation, treated cells showed a significant alteration (qRT-PCR) of the expression of marker genes (Gata-4, Nkx-2.5, Tnnc1 and Alpk3) when compared to control cells. At day 15 of differentiation, although the organization of sarcomeric α-actinin and troponin T proteins appeared similar in cardiomyocytes differentiated from either mock or treated cells, the video evaluation of the kinematics and dynamics of the beating cardiac syncytium evidenced altered contractile properties of cardiomyocytes derived from irradiated mESCs. This alteration correlated with significant reduction of Connexin 43 foci. Our results indicate that mESCs populations that survive an ionizing irradiation treatment are capable to differentiate into cardiomyocytes, but they have altered contractile properties.

Fetal states identification in cardiotocographic tracings through discrete emissions multivariate hidden Markov models.

BACKGROUND AND OBJECTIVES: Computerized Cardiotocography (cCTG) allows to analyze the Fetal Heart Rate (FHR) objectively and thoroughly, providing valuable insights on fetal condition. A challenging but crucial task in this context is the automatic identification of fetal activity and quiet periods within the tracings. Different neural mechanisms are involved in the regulation of the fetal heart, depending on the behavioral states. Thereby, their correct identification has the potential to increase the interpretability and diagnostic capabilities of FHR quantitative analysis. Moreover, the most common pathologies in pregnancy have been associated with variations in the alternation between quiet and activity states. METHODS: We address the problem of fetal states clustering by means of an unsupervised approach, resorting to the use of a multivariate Hidden Markov Models (HMM) with discrete emissions. A fixed length sliding window is shifted on the CTG traces and a small set of features is extracted at each slide. After an encoding procedure, these features become the emissions of a multivariate HMM in which quiet and activity are the hidden states. After an unsupervised training procedure, the model is used to automatically segment signals. RESULTS: The achieved results indicate that our developed model exhibits a high degree of reliability in identifying quiet and activity states within FHR signals. A set of 35 CTG signals belonging to different pregnancies were independently annotated by an expert gynecologist and segmented using the proposed HMM. To avoid any bias, the physician was blinded to the results provided by the algorithm. The overall agreement between the HMM's predictions and the clinician's interpretations was 90%. CONCLUSIONS: The proposed method reliably identified fetal behavioral states, the alternance of which is an important factor in the fetal development. One key strength of our approach lies in the ease of interpreting the obtained results. By utilizing a small set of parameters that are already used in cCTG and possess clear intrinsic meanings, our method provides a high level of explainability. Another significant advantage of our approach is its fully unsupervised learning process. The states identified by our model using the Baum-Welch algorithm are associated with the "Active" and "Quiet" states only after the clustering process, removing the reliance on expert annotations. By autonomously identifying the clusters based solely on the intrinsic characteristics of the signal, our method achieves a more objective evaluation that overcomes the limitations of subjective interpretations. Indeed, we believe it could be integrated in cCTG systems to obtain a more complete signal analysis.

Real-time myoelectric control of a multi-fingered hand prosthesis using principal components analysis.

BACKGROUND: In spite of the advances made in the design of dexterous anthropomorphic hand prostheses, these sophisticated devices still lack adequate control interfaces which could allow amputees to operate them in an intuitive and close-to-natural way. In this study, an anthropomorphic five-fingered robotic hand, actuated by six motors, was used as a prosthetic hand emulator to assess the feasibility of a control approach based on Principal Components Analysis (PCA), specifically conceived to address this problem. Since it was demonstrated elsewhere that the first two principal components (PCs) can describe the whole hand configuration space sufficiently well, the controller here employed reverted the PCA algorithm and allowed to drive a multi-DoF hand by combining a two-differential channels EMG input with these two PCs. Hence, the novelty of this approach stood in the PCA application for solving the challenging problem of best mapping the EMG inputs into the degrees of freedom (DoFs) of the prosthesis. METHODS: A clinically viable two DoFs myoelectric controller, exploiting two differential channels, was developed and twelve able-bodied participants, divided in two groups, volunteered to control the hand in simple grasp trials, using forearm myoelectric signals. Task completion rates and times were measured. The first objective (assessed through one group of subjects) was to understand the effectiveness of the approach; i.e., whether it is possible to drive the hand in real-time, with reasonable performance, in different grasps, also taking advantage of the direct visual feedback of the moving hand. The second objective (assessed through a different group) was to investigate the intuitiveness, and therefore to assess statistical differences in the performance throughout three consecutive days. RESULTS: Subjects performed several grasp, transport and release trials with differently shaped objects, by operating the hand with the myoelectric PCA-based controller. Experimental trials showed that the simultaneous use of the two differential channels paradigm was successful. CONCLUSIONS: This work demonstrates that the proposed two-DoFs myoelectric controller based on PCA allows to drive in real-time a prosthetic hand emulator into different prehensile patterns with excellent performance. These results open up promising possibilities for the development of intuitive, effective myoelectric hand controllers.

A Novel Large Structured Cardiotocographic Database.

In this work we present the creation of a large, structured database of CardioTocoGraphic (CTG) recordings, starting from a raw dataset containing tracings collected between 2013 and 2021 by the medical team of the University Hospital Federico II of Naples. The aim of the work is to provide a big, structured database of real clinical cardiotocographic data, useful for subsequent processing and analysis through state-of-the-art methods, in particular Deep Learning Methods. This organized dataset could lead to an increase of the diagnostic accuracy of CTG analysis in the discrimination of healthy and unhealthy fetuses.

A deep learning mixed-data type approach for the classification of FHR signals.

The Cardiotocography (CTG) is a widely diffused monitoring practice, used in Ob-Gyn Clinic to assess the fetal well-being through the analysis of the Fetal Heart Rate (FHR) and the Uterine contraction signals. Due to the complex dynamics regulating the Fetal Heart Rate, a reliable visual interpretation of the signal is almost impossible and results in significant subjective inter and intra-observer variability. Also, the introduction of few parameters obtained from computer analysis did not solve the problem of a robust antenatal diagnosis. Hence, during the last decade, computer aided diagnosis systems, based on artificial intelligence (AI) machine learning techniques have been developed to assist medical decisions. The present work proposes a hybrid approach based on a neural architecture that receives heterogeneous data in input (a set of quantitative parameters and images) for classifying healthy and pathological fetuses. The quantitative regressors, which are known to represent different aspects of the correct development of the fetus, and thus are related to the fetal healthy status, are combined with features implicitly extracted from various representations of the FHR signal (images), in order to improve the classification performance. This is achieved by setting a neural model with two connected branches, consisting respectively of a Multi-Layer Perceptron (MLP) and a Convolutional Neural Network (CNN). The neural architecture was trained on a huge and balanced set of clinical data (14.000 CTG tracings, 7000 healthy and 7000 pathological) recorded during ambulatory non stress tests at the University Hospital Federico II, Napoli, Italy. After hyperparameters tuning and training, the neural network proposed has reached an overall accuracy of 80.1%, which is a promising result, as it has been obtained on a huge dataset.

Placental dysfunction in uncomplicated and complicated intrauterine growth restriction by preeclampsia and neonatal outcome.

OBJECTIVES: To investigate the use of computerized cardiotocography (cCTG) parameters in Intrauterine Growth Restriction (IUGR) pregnancies for the prediction of 1) complication with preeclampsia; 2) placental histological abnormalities, and 3) neonatal outcomes. . STUDY DESIGN: A single-center observational retrospective case-control study was performed by reviewing medical records, cCTG databases and pathological reports of women with singleton pregnancy and IUGR uncomplicated (controls) and complicated by preeclampsia (cases). Primary endpoint was the association between cCTG parameters and preeclampsia in IUGR. Secondary endpoints were the association between cCTG parameters and 1) placental abnormalities, and 2) neonatal outcomes. The one-way ANOVA test was used to compare cCTG parameters in cases and controls. t-test was applied to compare neonatal outcomes and placental abnormalities in both groups. The Spearman Test value Correlation coefficients between the cCTG parameters and neonatal outcome in the two groups. A p value < .05 was considered significant for all analyses. RESULTS: Among all cCTG parameters, a significant association with preeclampsia in IUGR was found for Fetal Heart Rate (FHR, p = .008), Delta (p = .018), Short Term Variability (STV, p = .021), Long Term Variability (LTV, p = .028), Acceleration Phase Rectified Slope (APRS, p = .018) and Deceleration Phase Rectified Slope (DPRS, p = .038). Of all placental histologic abnormalities, only vascular alterations at least moderate were significantly associated with increased FHR (p = .02). About neonatal outcomes, all cCTG parameters were significantly associated with birth weight, Apgar index at 1 and 5 min, pH and pCO2. FHR, LTI, Delta, Approximate Entropy (ApEn) and LF were significantly associated with pO2; LTI, Interval Index (II) and ApEn with base excess. Among controls, Delta, ApEn, Low Frequency (LF) and High Frequency (HF) were significantly associated with pCO2, while among cases, STV and Delta were significantly associated with pH; STV, LTI, Delta, ApEn, LF and HF with pCO2; STV, LTI, Delta and ApEn with pO2; HF with base excess; FHR and LF with lactates. CONCLUSIONS: cCTG parameters may be useful to detect complication with preeclampsia in IUGR pregnancies. Regarding placental status, cCTG parameters may detect overall circulation alterations, but not specific histological abnormalities. Lastly, all cCTG parameters may predict neonatal outcomes, helping to tailor the patients' management.

Localization of Magic-F1 transgene, involved in muscular hypertrophy, during early myogenesis.

We recently showed that Magic-F1 (Met-activating genetically improved chimeric factor 1), a human recombinant protein derived from hepatocyte growth factor/scatter factor (HGF/SF) induces muscle cell hypertrophy but not progenitor cell proliferation, both in vitro and in vivo. Here, we examined the temporal and spatial expression pattern of Magic-F1 in comparison with Pax3 (paired box gene 3) transcription factor during embryogenesis. Ranging from 9.5 to 17.5 dpc (days post coitum) mouse embryos were analyzed by in situ hybridization using whole mounts during early stages of development (9.5-10.5-11.5 dpc) and cryostat sections for later stages (11.5-13.5-15.5-17.5 dpc). We found that Magic-F1 is expressed in developing organs and tissues of mesenchymal origin, where Pax3 signal appears to be downregulated respect to the wt embryos. These data suggest that Magic-F1 could be responsible of muscular hypertrophy, cooperating with Pax3 signal pathway in skeletal muscle precursor cells.

A Machine Learning Approach to Monitor the Emergence of Late Intrauterine Growth Restriction.

Late intrauterine growth restriction (IUGR) is a fetal pathological condition characterized by chronic hypoxia secondary to placental insufficiency, resulting in an abnormal rate of fetal growth. This pathology has been associated with increased fetal and neonatal morbidity and mortality. In standard clinical practice, late IUGR diagnosis can only be suspected in the third trimester and ultimately confirmed at birth. This study presents a radial basis function support vector machine (RBF-SVM) classification based on quantitative features extracted from fetal heart rate (FHR) signals acquired using routine cardiotocography (CTG) in a population of 160 healthy and 102 late IUGR fetuses. First, the individual performance of each time, frequency, and nonlinear feature was tested. To improve the unsatisfactory results of univariate analysis we firstly adopted a Recursive Feature Elimination approach to select the best subset of FHR-based parameters contributing to the discrimination of healthy vs. late IUGR fetuses. A fine tuning of the RBF-SVM model parameters resulted in a satisfactory classification performance in the training set (accuracy 0.93, sensitivity 0.93, specificity 0.84). Comparable results were obtained when applying the model on a totally independent testing set. This investigation supports the use of a multivariate approach for the in utero identification of late IUGR condition based on quantitative FHR features encompassing different domains. The proposed model allows describing the relationships among features beyond the traditional linear approaches, thus improving the classification performance. This framework has the potential to be proposed as a screening tool for the identification of late IUGR fetuses.

Principal components analysis based control of a multi-DoF underactuated prosthetic hand.

BACKGROUND: Functionality, controllability and cosmetics are the key issues to be addressed in order to accomplish a successful functional substitution of the human hand by means of a prosthesis. Not only the prosthesis should duplicate the human hand in shape, functionality, sensorization, perception and sense of body-belonging, but it should also be controlled as the natural one, in the most intuitive and undemanding way. At present, prosthetic hands are controlled by means of non-invasive interfaces based on electromyography (EMG). Driving a multi degrees of freedom (DoF) hand for achieving hand dexterity implies to selectively modulate many different EMG signals in order to make each joint move independently, and this could require significant cognitive effort to the user. METHODS: A Principal Components Analysis (PCA) based algorithm is used to drive a 16 DoFs underactuated prosthetic hand prototype (called CyberHand) with a two dimensional control input, in order to perform the three prehensile forms mostly used in Activities of Daily Living (ADLs). Such Principal Components set has been derived directly from the artificial hand by collecting its sensory data while performing 50 different grasps, and subsequently used for control. RESULTS: Trials have shown that two independent input signals can be successfully used to control the posture of a real robotic hand and that correct grasps (in terms of involved fingers, stability and posture) may be achieved. CONCLUSIONS: This work demonstrates the effectiveness of a bio-inspired system successfully conjugating the advantages of an underactuated, anthropomorphic hand with a PCA-based control strategy, and opens up promising possibilities for the development of an intuitively controllable hand prosthesis.

Low-power ultrasounds as a tool to culture human osteoblasts inside cancellous hydroxyapatite.

Bone graft substitutes and cancellous biomaterials have been widely used to heal critical-size long bone defects due to trauma, tumor resection, and tissue degeneration. In particular, porous hydroxyapatite is widely used in reconstructive bone surgery owing to its biocompatibility. In addition, the in vitro modification of cancellous hydroxyapatite with osteogenic signals enhances the tissue regeneration in vivo, suggesting that the biomaterial modification could play an important role in tissue engineering. In this study, we have followed a tissue-engineering strategy where ultrasonically stimulated SAOS-2 human osteoblasts proliferated and built their extracellular matrix inside a porous hydroxyapatite scaffold. The ultrasonic stimulus had the following parameters: average power equal to 149 mW and frequency of 1.5 MHz. In comparison with control conditions, the ultrasonic stimulus increased the cell proliferation and the surface coating with bone proteins (decorin, osteocalcin, osteopontin, type-I collagen, and type-III collagen). The mechanical stimulus aimed at obtaining a better modification of the biomaterial internal surface in terms of cell colonization and coating with bone matrix. The modified biomaterial could be used, in clinical applications, as an implant for bone repair.