Novel approach for fetal heart rate classification introducing grammatical evolution

Fetal heart rate (FHR) variations reflect the level of oxygenation and blood pressure of the fetus. Electronic Fetal Monitoring (EFM), the continuous monitoring of the FHR, was introduced into clinical practice in the late 1960s and since then it has been considered as an indispensable tool for fetal surveillance. However, EFM evaluation and its merit is still an open field of controversy, mainly because it is not consistently reproducible and effective. In this work, we present a novel method based on grammatical evolution to discriminate acidemic from normal fetuses, utilizing features extracted from the FHR signal during the minutes immediately preceding delivery. The proposed method identifies linear and nonlinear correlations among the originally extracted features and creates/constructs a set of new ones, which, in turn, feed a nonlinear classifier. The classifier, which also uses a hybrid method for training, along with the constructed features was tested using a set of real data achieving an overall performance of 90% (specificity = sensitivity = 90%).     

Fractal Analysis and Hurst Parameter for Intrapartum Fetal Heart Rate Variability Analysis: A Versatile Alternative to Frequency Bands and LF/HF Ratio

Background

The fetal heart rate (FHR) is commonly monitored during labor to detect early fetal acidosis. FHR variability is traditionally investigated using Fourier transform, often with adult predefined frequency band powers and the corresponding LF/HF ratio. However, fetal conditions differ from adults and modify spectrum repartition along frequencies.

Aims

This study questions the arbitrariness definition and relevance of the frequency band splitting procedure, and thus of the calculation of the underlying LF/HF ratio, as efficient tools for characterizing intrapartum FHR variability.

Study Design

The last 30 minutes before delivery of the intrapartum FHR were analyzed.

Subjects

Case-control study. A total of 45 singletons divided into two groups based on umbilical cord arterial pH: the Index group with pH ≤ 7.05 (n = 15) and Control group with pH > 7.05 (n = 30).

Outcome Measures

Frequency band-based LF/HF ratio and Hurst parameter.

Results

This study shows that the intrapartum FHR is characterized by fractal temporal dynamics and promotes the Hurst parameter as a potential marker of fetal acidosis. This parameter preserves the intuition of a power frequency balance, while avoiding the frequency band splitting procedure and thus the arbitrary choice of a frequency separating bands. The study also shows that extending the frequency range covered by the adult-based bands to higher and lower frequencies permits the Hurst parameter to achieve better performance for identifying fetal acidosis.

Conclusions

The Hurst parameter provides a robust and versatile tool for quantifying FHR variability, yields better acidosis detection performance compared to the LF/HF ratio, and avoids arbitrariness in spectral band splitting and definitions.     

Monitoring fetal electrocortical activity during labour for predicting worsening acidemia: a prospective study in the ovine fetus near term

Background

Severe fetal acidemia during labour with arterial pH below 7.00 is associated with increased risk of hypoxic-ischemic brain injury. Electronic fetal heart rate (FHR) monitoring, the mainstay of intrapartum surveillance, has poor specificity for detecting fetal acidemia. We studied brain electrical activity measured with electrocorticogram (ECOG) in the near term ovine fetus subjected to repetitive umbilical cord occlusions (UCO) inducing FHR decelerations, as might be seen in human labour, to delineate the time-course for ECOG changes with worsening acidemia and thereby assess the potential clinical utility of fetal ECOG.

Methodology/Principal Findings

Ten chronically catheterized fetal sheep were studied through a series of mild, moderate and severe UCO until the arterial pH was below 7.00. At a pH of 7.24±0.04, 52±13 min prior to the pH dropping <7.00, spectral edge frequency (SEF) increased to 23±2 Hz from 3±1 Hz during each FHR deceleration (p<0.001) and was correlated to decreases in FHR and in fetal arterial blood pressure during each FHR deceleration (p<0.001).

Conclusions/Significance

The UCO-related changes in ECOG occurred in advance of the pH decreasing below 7.00. These ECOG changes may be a protective mechanism suppressing non-essential energy needs when oxygen supply to the fetal brain is decreased acutely. By detecting such “adaptive brain shutdown,” the need for delivery in high risk pregnant patients may be more accurately predicted than with FHR monitoring alone. Therefore, monitoring fetal electroencephalogram (EEG, the human equivalent of ECOG) during human labour may be a useful adjunct to FHR monitoring.     

Thiolated pectin nanoparticles: Preparation, characterization and ex vivo corneal permeation study

The objective of present study was to prepare thiolated pectin nanoparticles and to evaluate them for ocular delivery. Thiolated pectin nanoparticles were prepared by ionotropic-gelation technique using magnesium chloride as the ionic cross-linker and timolol maleate as the model drug. The results revealed that increasing the concentration of magnesium chloride results in significant increase in particle size, while % entrapment is decreased significantly by increase in the concentration of thiolated pectin. The optimal formulation having particle size of 237 nm and % entrapment of 94.6% was obtained at concentrations of thiolated pectin - 0.01% (w/v) and magnesium chloride - 0.01% (w/v). On comparative evaluation, thiolated pectin nanoparticulate formulation provided significantly higher ex vivo corneal permeation of timolol maleate across the excised goat cornea than the conventional aqueous solution.     

Color Measurement of Tea Leaves at Different Drying Periods Using Hyperspectral Imaging Technique

This study investigated the feasibility of using hyperspectral imaging technique for nondestructive measurement of color components (ΔL*, Δa* and Δb*) and classify tea leaves during different drying periods. Hyperspectral images of tea leaves at five drying periods were acquired in the spectral region of 380–1030 nm. The three color features were measured by the colorimeter. Different preprocessing algorithms were applied to select the best one in accordance with the prediction results of partial least squares regression (PLSR) models. Competitive adaptive reweighted sampling (CARS) and successive projections algorithm (SPA) were used to identify the effective wavelengths, respectively. Different models (least squares-support vector machine [LS-SVM], PLSR, principal components regression [PCR] and multiple linear regression [MLR]) were established to predict the three color components, respectively. SPA-LS-SVM model performed excellently with the correlation coefficient (r_p) of 0.929 for ΔL*, 0.849 for Δa*and 0.917 for Δb*, respectively. LS-SVM model was built for the classification of different tea leaves. The correct classification rates (CCRs) ranged from 89.29% to 100% in the calibration set and from 71.43% to 100% in the prediction set, respectively. The total classification results were 96.43% in the calibration set and 85.71% in the prediction set. The result showed that hyperspectral imaging technique could be used as an objective and nondestructive method to determine color features and classify tea leaves at different drying periods.     

Comparison of a Novel Computerized Analysis Program and Visual Interpretation of Cardiotocography

Objective

To compare a novel computerized analysis program with visual cardiotocography (CTG) interpretation results.

Methods

Sixty-two intrapartum CTG tracings with 20- to 30-minute sections were independently interpreted using a novel computerized analysis program, as well as the visual interpretations of eight obstetricians, to evaluate the baseline fetal heart rate (FHR), baseline FHR variability, number of accelerations, number/type of decelerations, uterine contraction (UC) frequency, and the National Institute of Child Health and Human Development (NICHD) 3-Tier FHR classification system.

Results

There was no significant difference in interobserver variation after adding the components of computerized analysis to results from the obstetricians'' visual interpretations, with excellent agreement for the baseline FHR (ICC 0.91), the number of accelerations (ICC 0.85), UC frequency (ICC 0.97), and NICHD category I (kappa statistic 0.91); good agreement for baseline variability (kappa statistic 0.68), the numbers of early decelerations (ICC 0.78) and late decelerations (ICC 0.67), category II (kappa statistic 0.78), and overall categories (kappa statistic 0.80); and moderate agreement for the number of variable decelerations (ICC 0.60), and category III (kappa statistic 0.50).

Conclusions

This computerized analysis program is not inferior to visual interpretation, may improve interobserver variations, and could play a vital role in prenatal telemedicine.     

Automatic detection of epileptic EEG signals using higher order cumulant features

The unpredictability of the occurrence of epileptic seizures makes it difficult to detect and treat this condition effectively. An automatic system that characterizes epileptic activities in EEG signals would allow patients or the people near them to take appropriate precautions, would allow clinicians to better manage the condition, and could provide more insight into these phenomena thereby revealing important clinical information. Various methods have been proposed to detect epileptic activity in EEG recordings. Because of the nonlinear and dynamic nature of EEG signals, the use of nonlinear Higher Order Spectra (HOS) features is a seemingly promising approach. This paper presents the methodology employed to extract HOS features (specifically, cumulants) from normal, interictal, and epileptic EEG segments and to use significant features in classifiers for the detection of these three classes. In this work, 300 sets of EEG data belonging to the three classes were used for feature extraction and classifier development and evaluation. The results show that the HOS based measures have unique ranges for the different classes with high confidence level (p-value < 0.0001). On evaluating several classifiers with the significant features, it was observed that the Support Vector Machine (SVM) presented a high detection accuracy of 98.5% thereby establishing the possibility of effective EEG segment classification using the proposed technique.     

Development and Evaluation of New Microemulsion-Based Hydrogel Formulations for Topical Delivery of Fluconazole

The aim of the present investigation was to develop and evaluate microemulsion-loaded hydrogels (MEHs) for the topical delivery of fluconazole (FZ). The solubility of FZ in oils, surfactants and cosurfactants was evaluated to identify the components of the microemulsion. The pseudo-ternary phase diagrams were constructed using the novel phase diagram by micro-plate dilution method. Carbopol EDT 2020 was used to convert FZ-loaded microemulsions into gel form without affecting their structure. The selected microemulsions were assessed for globule size, zeta potential and polidispersity index. Besides this, the microemulsion-loaded hydrogel (MEH) formulations were evaluated for drug content, pH, rheological properties and in vitro drug release through synthetic membrane and excised pig ear skin in comparison with a conventional hydrogel. The optimised MEH FZ formulations consisting of FZ 2%, Transcutol P 11.5% and 11%, respectively, as oil phase, Lansurf SML 20-propyleneglycol 52% and 50%, respectively, as surfactant–cosurfactant (2:1), Carbopol EDT 2020 1.5% as gelling agent and water 34.5% and 37%, respectively, showed highest flux values and high release rate values, and furthermore, they had low surfactant content. The in vitro FZ permeation through synthetic membrane and excised pig ear skin from the studied MEHs was best described by the zero-order and first-order models. Finally, the optimised MEH FZ formulations showed similar or slightly higher antifungal activity as compared to that of conventional hydrogel and Nizoral® cream, respectively. The results suggest the potential use of developed MEHs as vehicles for topical delivery of FZ, encouraging further in vitro and in vivo evaluation.KEY WORDS: fluconazole, in vitro skin permeation, microemulsion, microemulsion-loaded hydrogel, topical     

Effect of method and clinician on stallion sperm morphology evaluation

The objective of this study was to determine the effects of method and clinician on stallion sperm morphology evaluation. Five clinicians evaluated 60 semen samples using wet-mount preparations with phase-contrast, eosin/nigrosin-stained semen smears, and Papanicolaou-stained semen smears. There were significant differences among methods for all sperm morphology categories and most intra-class correlation coefficients were only fair to moderate. The use of wet-mount preparations facilitated detection of acrosome defects, nuclear vacuoles, and cytoplasmic droplets when compared to stained smears. Smearing stallion semen samples onto slides increased the proportion of detached sperm heads. In addition, acrosome defects, nuclear vacuoles, rough/swollen midpieces, and cytoplasmic droplets were difficult to observe with Papanicolaou stain; this method resulted in overestimation of normal sperm when compared to other methods. There were significant differences among clinicians for all sperm morphology classification categories. In conclusion, this study demonstrated that sperm morphology evaluation results varied, depending on the evaluation method and clinician. Wet-mount preparation with phase-contrast microscopy appeared to be more sensitive for identification of abnormal stallion sperm when compared to stained smears. Veterinary andrology laboratories should invest in training, continuing education, proficiency testing, and other quality control measures to minimize the variation of sperm morphology evaluation results among clinicians.     

Development of Silymarin Self-Microemulsifying Drug Delivery System with Enhanced Oral Bioavailability

The objective of this work was to develop a self-microemulsifying drug delivery system (SMEDDS) for improving oral absorption of poorly water-soluble drug, silymarin. The pseudo-ternary phase diagrams were constructed using ethyl linoleate, Cremophor EL, ethyl alcohol, and normal saline to identify the efficient self-microemulsification region. The particle size and its distribution of the resultant microemulsions were determined using dynamic light scattering. The optimal formulation with the best self-microemulsifying and solubilization ability consisted of 10% (w/w) of ethyl linoleate, 30% of Cremophor EL, and 60% of ethyl alcohol. The release of silymarin from SMEDDS was significantly faster than that from the commercial silymarin preparation hard capsule (Legalon®). The bioavailability results indicated that the oral absorption of silymarin SMEDDS was enhanced about 2.2-fold compared with the hard capsule in fasted dogs. It could be concluded that SMEDDS would be a promising drug delivery system for poorly water-soluble drugs by the oral route.     

Maternal group B streptococcus infection, neonatal outcome and the role of preventive strategies

To determine the newborn infection rate with group B streptococcus infection (GBS) before and after American Academy of Pediatrics Protocol (AAP) implementation in Croatia, antenatal risk factors, neonatal outcome and necessity for introducing national policy for intrapartum chemoprophylaxis. To evaluate the role of intrapartum chemoprophylaxis in preterm labor at < 37 weeks of gestation, premature rupture of membranes at < 37 weeks of gestation, fever during labor, ruptures of membranes > 18 hours before delivery and previous delivery of a sibling with GBS disease. A total of 784 neonates admitted to the Neonatal Intensive Care Unit, from 1 January 2005 to 31 December 2005. 60 (10/1000 live born) developed early-onset infection (EOGBS). The dominant presentation for EOGBS was sepsis (65%), pneumonia (32.2%) and meningitis (3%). Mean gestational age was 34.5 (+/- 5.3) weeks. There were 2 neonatal deaths (3%) in EOGBS, both preterm. EOGBS disease was associated with following risk factors: rupture of the membranes > 12 hours (49.3%), chorioamnionitis (11.9%), status post cerclage (10.4%), diabetes mellitus (4.5%), delivery out of hospital (3%), uroinfection (1.5%). After AAP implementation the incidence of GBS infection decreased from 15/1000 to 10/1000 of live born infants. The mortality from EOGBS dropped from 5% to 3%. The incidence of GBS infection in our study was considerably higher than in all current reports. Reasons for that can be inadequate perinatal screen in some parts of the country and no established policy for intrapartum antibiotic treatment of women with risk factors. Our results documented that intrapartum chemo-prophylaxis for GBS infection significantly reduces perinatal mortality due to neonatal infection and sepsis.     

Noninvasive Characterization of Locally Advanced Breast Cancer Using Textural Analysis of Quantitative Ultrasound Parametric Images

PURPOSE: The identification of tumor pathologic characteristics is an important part of breast cancer diagnosis, prognosis, and treatment planning but currently requires biopsy as its standard. Here, we investigated a noninvasive quantitative ultrasound method for the characterization of breast tumors in terms of their histologic grade, which can be used with clinical diagnostic ultrasound data. METHODS: Tumors of 57 locally advanced breast cancer patients were analyzed as part of this study. Seven quantitative ultrasound parameters were determined from each tumor region from the radiofrequency data, including mid-band fit, spectral slope, 0-MHz intercept, scatterer spacing, attenuation coefficient estimate, average scatterer diameter, and average acoustic concentration. Parametric maps were generated corresponding to the region of interest, from which four textural features, including contrast, energy, homogeneity, and correlation, were determined as further tumor characterization parameters. Data were examined on the basis of tumor subtypes based on histologic grade (grade I versus grade II to III). RESULTS: Linear discriminant analysis of the means of the parametric maps resulted in classification accuracy of 79%. On the other hand, the linear combination of the texture features of the parametric maps resulted in classification accuracy of 82%. Finally, when both the means and textures of the parametric maps were combined, the best classification accuracy was obtained (86%). CONCLUSIONS: Textural characteristics of quantitative ultrasound spectral parametric maps provided discriminant information about different types of breast tumors. The use of texture features significantly improved the results of ultrasonic tumor characterization compared to conventional mean values. Thus, this study suggests that texture-based quantitative ultrasound analysis of in vivo breast tumors can provide complementary diagnostic information about tumor histologic characteristics.     

Chromosome anomalies of infants dying during the perinatal period and premature newborn

Summary 363 samples of different tissues were taken for cultivation from 118 antepartum deaths, 85 intrapartum deaths and 112 newborn dying during the first days after delivery. Successful growth of culture was noticed in 48.2% (15.4%) of antepartum deaths; 71.8% of intrapartum deaths and 68.1% of newborn dying during the first days of life. Among the 22 antepartum deaths 3 (13.6%) infants were found to have anomalies of karyotype; among 61 intrapartum deaths 3 (4.9%) infants were found to have karyotype anomalies; and among 92 early neonatal deaths 6 ones (6.5%) had karyotype anomalies. The total frequency of chromosome anomalies among the infants dying during the perinatal period was 6.9%.The final result of cytogenetic investigation of 607 premature infants was that chromosome anomalies were found among 2.5%, that is 3.5 times as much, as in the general newborn population. Among the types of chromosome anomalies the main defects were anomalies in the system of sex chromosomes and trisomy-21, and that is the proof of the fact, that other types of anomalies, found in newborn populations lead to earlier lethality.     

Multidisciplinary prospective study of mother-to-child chikungunya virus infections on the island of La Réunion

Background

An outbreak of chikungunya virus affected over one-third of the population of La Réunion Island between March 2005 and December 2006. In June 2005, we identified the first case of mother-to-child chikungunya virus transmission at the Groupe Hospitalier Sud-Réunion level-3 maternity department. The goal of this prospective study was to characterize the epidemiological, clinical, biological, and radiological features and outcomes of all the cases of vertically transmitted chikungunya infections recorded at our institution during this outbreak.

Methods and Findings

Over 22 mo, 7,504 women delivered 7,629 viable neonates; 678 (9.0%) of these parturient women were infected (positive RT-PCR or IgM serology) during antepartum, and 61 (0.8%) in pre- or intrapartum. With the exception of three early fetal deaths, vertical transmission was exclusively observed in near-term deliveries (median duration of gestation: 38 wk, range 35–40 wk) in the context of intrapartum viremia (19 cases of vertical transmission out of 39 women with intrapartum viremia, prevalence rate 0.25%, vertical transmission rate 48.7%). Cesarean section had no protective effect on transmission. All infected neonates were asymptomatic at birth, and median onset of neonatal disease was 4 d (range 3–7 d). Pain, prostration, and fever were present in 100% of cases and thrombocytopenia in 89%. Severe illness was observed in ten cases (52.6%) and mainly consisted of encephalopathy (n = 9; 90%). These nine children had pathologic MRI findings (brain swelling, n = 9; cerebral hemorrhages, n = 2), and four evolved towards persistent disabilities.

Conclusions

Mother-to-child chikungunya virus transmission is frequent in the context of intrapartum maternal viremia, and often leads to severe neonatal infection. Chikungunya represents a substantial risk for neonates born to viremic parturients that should be taken into account by clinicians and public health authorities in the event of a chikungunya outbreak.     

Voice Pathologies Classification and Detection Using EMD-DWT Analysis Based on Higher Order Statistic Features

BackgroundThe voice is a prominent tool allowing people to communicate and to change information in their daily activities. However, any slight alteration in the voice production system may affect the voice quality. Over the last years, researchers in biomedical engineering field worked to develop a robust automatic system that may help clinicians to perform a preventive diagnosis in order to detect the voice pathologies in an early stage.MethodIn this context, pathological voice detection and classification method based on EMD-DWT analysis and Higher Order Statistics (HOS) features, is proposed. Also DWT coefficients features are extracted and tested. To carry out our experiments a wide subset of voice signal from normal subjects and subjects which suffer from the five most frequent pathologies in the Saarbrücken Voice Database (SVD), is selected. In The first step, we applied the Empirical Mode Decomposition (EMD) to the voice signal. Afterwards, among the obtained candidates of Intrinsic Mode Functions (IMFs), we choose the robust one based on temporal energy criterion. In the second step, the selected IMF was decomposed via the Discrete Wavelet Transform (DWT). As a result, two features vector includes six HOSs parameters, and a features vector includes six DWT features were formed from both approximation and detail coefficients. In order to classify the obtained data a support vector machine (SVM) is employed. After having trained the proposed system using the SVD database, the system was evaluated using voice signals of volunteer's subjects from the Neurological department of RABTA Hospital of Tunis.ResultsThe proposed method gives promising results in pathological voices detection. The accuracies reached 99.26% using HOS features and 93.1% using DWT features for SVD database. In the classification, an accuracy of 100% was reached for “Funktionelle Dysphonia vs. Rekrrensparese” based on HOS features. Nevertheless, using DWT features the accuracy achieved was 90.32% for “Hyperfunktionelle Dysphonia vs. Rekurrensparse”. Furthermore, in the validation the accuracies reached were 94.82%, 91.37% for HOS and DWT features, respectively. In the classification the highest accuracies reached were for classifying “Parkinson versus Paralysis” 94.44% and 88.87% based on HOS and DWT features, respectively.ConclusionHOS features show promising results in the automatic voice pathology detection and classification compared to DWT features. Thus, it can reliably be used as noninvasive tool to assist clinical evaluation for pathological voices identification.     

An integrated diabetic index using heart rate variability signal features for diagnosis of diabetes

Electrocardiogram (ECG) signals are difficult to interpret, and clinicians must undertake a long training process to learn to diagnose diabetes from subtle abnormalities in these signals. To facilitate these diagnoses, we have developed a technique based on the heart rate variability signal obtained from ECG signals. This technique uses digital signal processing methods and, therefore, automates the detection of diabetes from ECG signals. In this paper, we describe the signal processing techniques that extract features from heart rate (HR) signals and present an analysis procedure that uses these features to diagnose diabetes. Through statistical analysis, we have identified the correlation dimension, Poincaré geometry properties (SD2), and recurrence plot properties (REC, DET, L _mean) as useful features. These features differentiate the HR data of diabetic patients from those of patients who do not have the illness, and have been validated by using the AdaBoost classifier with the perceptron weak learner (yielding a classification accuracy of 86%). We then developed a novel diabetic integrated index (DII) that is a combination of these nonlinear features. The DII indicates whether a particular HR signal was taken from a person with diabetes. This index aids the automatic detection of diabetes, thereby allowing a more objective assessment and freeing medical professionals for other tasks.     

Effect of socioeconomic deprivation and health service utilisation on antepartum and intrapartum stillbirth: population cohort study from rural Ghana

BACKGROUND: No studies have examined the effect of socioeconomic deprivation on antepartum and intrapartum stillbirths in the poorest women in low income countries. METHODOLOGY/ PRINCIPAL FINDINGS: This study used data from a prospective population based surveillance system involving all women of childbearing age and their babies in rural Ghana. The primary objective was to evaluate associations between household wealth and risk of antepartum and intrapartum stillbirth. The secondary objective was to assess whether any differences in risk were mediated by utilisation of health services during pregnancy. Data were analysed using multivariable logistic regression. Random effect models adjusted for clustering of women who delivered more than one infant. There were 80267 babies delivered from 1 July 2003 to 30 September 2008: 77666 live births and 2601 stillbirths. Of the stillbirths 1367 (52.6%) were antepartum, 989 (38.0%) were intrapartum and 245 (9.4%) had no data on the timing of death. 94.8% of the babies born in the study (76129/80267) had complete data on all covariates and outcomes. 36 878 (48.4%) of babies were born to women in the two poorest quintiles and 3697 (4.9%) had no pregnancy care. There was no association between wealth and antepartum stillbirths. There was a marked 'dose response' of increasing risk of intrapartum stillbirth with increasing levels of socioeconomic deprivation (adjOR 1.09 [1.03-1.16] p value 0.002). Women in the poorest two quintiles had greater risk of intrapartum stillbirth (adjOR 1.19 [1.02-1.38] p value 0.023) compared to the richest women. Adjusting for heath service utilisation and other variables did not alter results. CONCLUSIONS/ SIGNIFICANCE: Poor women had a high risk of intrapartum stillbirth and this risk was not influenced by health service utilisation. Health system strengthening is required to meet the needs of poor women in our study population.     

Multi-method analysis of MRI images in early diagnostics of Alzheimer's disease

The role of structural brain magnetic resonance imaging (MRI) is becoming more and more emphasized in the early diagnostics of Alzheimer's disease (AD). This study aimed to assess the improvement in classification accuracy that can be achieved by combining features from different structural MRI analysis techniques. Automatically estimated MR features used are hippocampal volume, tensor-based morphometry, cortical thickness and a novel technique based on manifold learning. Baseline MRIs acquired from all 834 subjects (231 healthy controls (HC), 238 stable mild cognitive impairment (S-MCI), 167 MCI to AD progressors (P-MCI), 198 AD) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database were used for evaluation. We compared the classification accuracy achieved with linear discriminant analysis (LDA) and support vector machines (SVM). The best results achieved with individual features are 90% sensitivity and 84% specificity (HC/AD classification), 64%/66% (S-MCI/P-MCI) and 82%/76% (HC/P-MCI) with the LDA classifier. The combination of all features improved these results to 93% sensitivity and 85% specificity (HC/AD), 67%/69% (S-MCI/P-MCI) and 86%/82% (HC/P-MCI). Compared with previously published results in the ADNI database using individual MR-based features, the presented results show that a comprehensive analysis of MRI images combining multiple features improves classification accuracy and predictive power in detecting early AD. The most stable and reliable classification was achieved when combining all available features.     

Acceleration and Deceleration Capacity of Fetal Heart Rate in an In-Vivo Sheep Model

Background

Fetal heart rate (FHR) variability is an indirect index of fetal autonomic nervous system (ANS) integrity. FHR variability analysis in labor fails to detect early hypoxia and acidemia. Phase-rectified signal averaging (PRSA) is a new method of complex biological signals analysis that is more resistant to non-stationarities, signal loss and artifacts. It quantifies the average cardiac acceleration and deceleration (AC/DC) capacity.

Objective

The aims of the study were: (1) to investigate AC/DC in ovine fetuses exposed to acute hypoxic-acidemic insult; (2) to explore the relation between AC/DC and acid-base balance; and (3) to evaluate the influence of FHR decelerations and specific PRSA parameters on AC/DC computation.

Methods

Repetitive umbilical cord occlusions (UCOs) were applied in 9 pregnant near-term sheep to obtain three phases of MILD, MODERATE, and SEVERE hypoxic-acidemic insult. Acid-base balance was sampled and fetal ECGs continuously recorded. AC/DC were calculated: (1) for a spectrum of T values (T = 1÷50 beats; the parameter limits the range of oscillations detected by PRSA); (2) on entire series of fetal RR intervals or on “stable” series that excluded FHR decelerations caused by UCOs.

Results

AC and DC progressively increased with UCOs phases (MILD vs. MODERATE and MODERATE vs. SEVERE, p<0.05 for DC  = 2–5, and AC  = 1–3). The time evolution of AC/DC correlated to acid-base balance (0.4<<0.9, p<0.05) with the highest for . PRSA was not independent from FHR decelerations caused by UCOs.

Conclusions

This is the first in-vivo evaluation of PRSA on FHR analysis. In the presence of acute hypoxic-acidemia we found increasing values of AC/DC suggesting an activation of ANS. This correlation was strongest on time scale dominated by parasympathetic modulations. We identified the best performing parameters (), and found that AC/DC computation is not independent from FHR decelerations. These findings establish the basis for future clinical studies.     

The solution structure of the complement deregulator FHR5 reveals a compact dimer and provides new insights into CFHR5 nephropathy

The human complement Factor H–related 5 protein (FHR5) antagonizes the main circulating complement regulator Factor H, resulting in the deregulation of complement activation. FHR5 normally contains nine short complement regulator (SCR) domains, but a FHR5 mutant has been identified with a duplicated N-terminal SCR-1/2 domain pair that causes CFHR5 nephropathy. To understand how this duplication causes disease, we characterized the solution structure of native FHR5 by analytical ultracentrifugation and small-angle X-ray scattering. Sedimentation velocity and X-ray scattering indicated that FHR5 was dimeric, with a radius of gyration (R_g) of 5.5 ± 0.2 nm and a maximum protein length of 20 nm for its 18 domains. This result indicated that FHR5 was even more compact than the main regulator Factor H, which showed an overall length of 26–29 nm for its 20 SCR domains. Atomistic modeling for FHR5 generated a library of 250,000 physically realistic trial arrangements of SCR domains for scattering curve fits. Only compact domain structures in this library fit well to the scattering data, and these structures readily accommodated the extra SCR-1/2 domain pair present in CFHR5 nephropathy. This model indicated that mutant FHR5 can form oligomers that possess additional binding sites for C3b in FHR5. We conclude that the deregulation of complement regulation by the FHR5 mutant can be rationalized by the enhanced binding of FHR5 oligomers to C3b deposited on host cell surfaces. Our FHR5 structures thus explained key features of the mechanism and pathology of CFHR5 nephropathy.