Failure to Recover from Proactive Semantic Interference Differentiates Amnestic Mild Cognitive Impairment and PreMCI from Normal Aging after Adjusting for Initial Learning Ability

Background: There is increasing evidence that the failure to recover from proactive semantic interference (frPSI) may be an early cognitive marker of preclinical Alzheimer’s disease (AD). However, it is unclear whether frPSI effects reflect deficiencies in an individual’s initial learning capacity versus the actual inability to learn new semantically related targets. Objective: The current study was designed to adjust for learning capacity and then to examine the extent to which frPSI, proactive semantic interference (PSI) and retroactive semantic interference (RSI) effects could differentiate between older adults who were cognitively normal (CN), and those diagnosed with either Pre-Mild Cognitive Impairment (PreMCI) or amnestic MCI (aMCI). Methods: We employed the LASSI-L cognitive stress test to examine frPSI, PSI and RSI effects while simultaneously controlling for the participant’s initial learning capacity among 50 CN, 35 aMCI, and 16 PreMCI participants who received an extensive diagnostic work-up. Results: aMCI and PreMCI participants showed greater frPSI deficits (50% and 43.8% respectively) compared to only 14% of CNparticipants. PSI effects were observed for aMCI but not PreMCI participants relative to their CN counterparts. RSI failed to differentiate between any of the study groups. Conclusion: By using participants as their own controls and adjusting for overall learning and memory, it is clear that frPSI deficits occur with much greater frequency in individuals at higher risk for Alzheimer’s disease (AD), and likely reflect a failure of brain compensatory mechanisms.Fil: Curiel, Rosie E.. University of Miami; Estados UnidosFil: Crocco, Elizabeth A.. University of Miami; Estados UnidosFil: Raffo, Arlene. University of Miami; Estados UnidosFil: Guinjoan, Salvador Martín. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay; Argentina. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Nemeroff, Charles B.. University of Miami; Estados UnidosFil: Penate, Ailyn. Mount Sinai Medical Center; Estados Unidos. University of Miami; Estados UnidosFil: Piña, Daema. University of Miami; Estados UnidosFil: Loewenstein, David A.. Mount Sinai Medical Center; Estados Unidos. University of Miami; Estados Unido

Medicaid home visitation and maternal and infant care and health: A reassessment of program effectiveness

Introduction: The Maternal Infant Health Program, MIHP, is Michigan\u27s largest home visiting program for Medicaid-eligible pregnant women and infants. Prior quasi-experimental propensity score matched MIHP evaluations were limited by the possibility of selection bias due to the limited available baseline characteristics. The purpose of this study was to assess the effectiveness of MIHP including previously unobserved baseline characteristics to mitigate the possibility of selection bias. Methods: We analyzed health care and outcomes of mothers and their infants using linked administrative and screening data. All Medicaid pregnant women with a singleton birth in Michigan between 2009 and 2012 who were prenatally screened into the statewide home visiting program were studied (n=69,408). Propensity score adjustment regressions were used to compare screened-only program participants to those screened who received additional program services. Data were assembled and analyzed between 2014-2016. Results: Compared to screened-only pregnant women, those who received additional program services had higher odds of receiving adequate prenatal care (OR=1.12), an appropriate postnatal checkup (OR=1.27), reduced odds of low birthweight (OR=0.84), very low birthweight (OR=0.63), preterm (OR=0.83), or very preterm birth (OR=0.67), and infants had increased odds of receiving the appropriate number of well-child visits in the first year of life (OR=1.3, p Conclusions: Favorable home visiting effects on maternal and infant care and health previously observed in quasi-experimental matched evaluations were supported by this study after accounting for an expanded set of characteristics and risk factors which reduced the possibility of selection bias

Automatic detection of complete and measurable cardiac cycles in antenatal pulsed-wave Doppler signals

Background and objective: Pulsed-wave Doppler (PWD) echocardiography is the primary tool for antenatal cardiological diagnosis. Based on it, different measurements and validated reference parameters can be extracted. The automatic detection of complete and measurable cardiac cycles would represent a useful tool for the quality assessment of the PWD trace and the automated analysis of long traces. Methods: This work proposes and compares three different algorithms for this purpose, based on the preliminary extraction of the PWD velocity spectrum envelopes: template matching, supervised classification over a reduced set of relevant waveshape features, and supervised classification over the whole waveshape potentially representing a cardiac cycle. A custom dataset comprising 43 fetal cardiac PWD traces (174,319 signal segments) acquired on an apical five-chamber window was developed and used for the assessment of the different algorithms. Results: The adoption of a supervised classifier trained with the samples representing the upper and lower envelopes of the PWD, with additional features extracted from the image, achieved significantly better results (p < 0.0001) than the other algorithms, with an average accuracy of 98% ± 1% when using an SVM classifier and a leave-one-subject-out cross-validation. Further, the robustness of the results with respect to the classifier model was proved. Conclusions: The results reveal excellent detection performance, suggesting that the proposed approach can be adopted for the automatic analysis of long PWD traces or embedded in ultrasound machines as a first step for the extraction of measurements and reference clinical parameters

Impact of pulsed-wave-Doppler velocity-envelope tracing techniques on classification of complete fetal cardiac cycles

Fetal echocardiography is an operator-dependent examination technique requiring a high level of expertise. Pulsed-wave Doppler (PWD) is often used as a reference for the mechanical activity of the heart, from which several quantitative parameters can be extracted. These aspects suggest the development of software tools that can reliably identify complete and clinically meaningful fetal cardiac cycles that can enable their automatic measurement. Several scientific works have addressed the tracing of the PWD velocity envelope. In this work, we assess the different steps involved in the signal processing chains that enable PWD envelope tracing. We apply a supervised classifier trained on envelopes traced by different signal processing chains for distinguishing complete and measurable PWD heartbeats from incomplete or malformed ones, which makes it possible to determine the impact of each of the different processing steps on the detection accuracy. In this study, we collected 43 images and labeled 174,319 PWD segments from 25 pregnant women volunteers. By considering seven envelope tracing techniques and the 23 different processing steps involved in their implementation, the results of our study reveal that, compared to the steps investigated in most other works, those that achieve binarisation and envelope extraction are significantly more important (p < 0.05). The best approaches among those studied enabled greater than 98% accuracy on our large manually annotated dataset

A non-invasive multimodal foetal ECG–Doppler dataset for antenatal cardiology research

Non-invasive foetal electrocardiography (fECG) continues to be an open topic for research. The development of standard algorithms for the extraction of the fECG from the maternal electrophysiological interference is limited by the lack of publicly available reference datasets that could be used to benchmark different algorithms while providing a ground truth for foetal heart activity when an invasive scalp lead is unavailable. In this work, we present the Non-Invasive Multimodal Foetal ECG-Doppler Dataset for Antenatal Cardiology Research (NInFEA), the first open-access multimodal early-pregnancy dataset in the field that features simultaneous non-invasive electrophysiological recordings and foetal pulsed-wave Doppler (PWD). The dataset is mainly conceived for researchers working on fECG signal processing algorithms. The dataset includes 60 entries from 39 pregnant women, between the 21st and 27th week of gestation. Each dataset entry comprises 27 electrophysiological channels (2048 Hz, 22 bits), a maternal respiration signal, synchronised foetal trans-abdominal PWD and clinical annotations provided by expert clinicians during signal acquisition. MATLAB snippets for data processing are also provided

Annotated real and synthetic datasets for non-invasive foetal electrocardiography post-processing benchmarking

Non-invasive foetal electrocardiography (fECG) can be obtained at different gestational ages by means of surface electrodes applied on the maternal abdomen. The signal-to-noise ratio (SNR) of the fECG is usually low, due to the small size of the foetal heart, the foetal-maternal compartment, the maternal physiological interferences and the instrumental noise. Even after powerful fECG extraction algorithms, a post-processing step could be required to improve the SNR of the fECG signal. In order to support the researchers in the field, this work presents an annotated dataset of real and synthetic signals, which was used for the study “Wavelet Denoising as a Post-Processing Enhancement Method for Non-Invasive Foetal Electrocardiography” [1]. Specifically, 21 15 s-long fECG, dual-channel signals obtained by multi-reference adaptive filtering from real electrophysiological recordings were included. The annotation of the foetal R peaks by an expert cardiologist was also provided. Recordings were performed on 17 voluntary pregnant women between the 21st and the 27th week of gestation. The raw recordings were also included for the researchers interested in applying a different fECG extraction algorithm. Moreover, 40 10 s-long synthetic non-invasive fECG were provided, simulating the electrode placement of one of the abdominal leads used for the real dataset. The annotation of the foetal R peaks was also provided, as generated by the FECGSYN tool used for the signals’ creation. Clean fECG signals were also included for the computation of indexes of signal morphology preservation. All the signals are sampled at 2048 Hz. The data provided in this work can be used as a benchmark for fECG post-processing techniques but can also be used as raw signals for researchers interested in foetal QRS detection algorithms and fECG extraction methods

Wavelet denoising as a post-processing enhancement method for non-invasive foetal electrocardiography

Background and Objective: The detection of a clean and undistorted foetal electrocardiogram (fECG) from non-invasive abdominal recordings is an open research issue. Several physiological and instrumental noise sources hamper this process, even after that powerful fECG extraction algorithms have been used. Wavelet denoising is widely used for the improvement of the SNR in biomedical signal processing. This work aims to systematically assess conventional and unconventional wavelet denoising approaches for the post-processing of fECG signals by providing evidence of their effectiveness in improving fECG SNR while preserving the morphology of the signal of interest. Methods: The stationary wavelet transform (SWT) and the stationary wavelet packet transform (SWPT) were considered, due to their different granularity in the sub-band decomposition of the signal. Three thresholds from the literature, either conventional (Minimax and Universal) and unconventional, were selected. To this aim, the unconventional one was adapted for the first time to SWPT by trying different approaches. The decomposition depth was studied in relation to the characteristics of the fECG signal. Synthetic and real datasets, publicly available for benchmarking and research, were used for quantitative analysis in terms of noise reduction, foetal QRS detection performance and preservation of fECG morphology. Results: The adoption of wavelet denoising approaches generally improved the SNR. Interestingly, the SWT methods outperformed the SWPT ones in morphology preservation (p<0.04) and SNR (p<0.0003), despite their coarser granularity in the sub-band analysis. Remarkably, the Han et al. threshold, adopted for the first time for fECG processing, provided the best quality improvement (p<0.003). Conclusions: The findings of our systematic analysis suggest that particular care must be taken when selecting and using wavelet denoising for non-invasive fECG signal post-processing. In particular, despite the general noise reduction capability, signal morphology can be significantly altered on the basis of the parameterization of the wavelet methods. Remarkably, the adoption of a finer sub-band decomposition provided by the wavelet packet was not able to improve the quality of the processing

A Comprehensive Overview of the Temperature-Dependent Modeling of the High-Power GaN HEMT Technology Using mm-Wave Scattering Parameter Measurements (Invited Paper)

The gallium-nitride (GaN) high electron-mobility transistor (HEMT) technology has emerged as an attractive candidate for high-frequency, high-power, and high-temperature applications due to the unique physical characteristics of the GaN material. Over the years, much effort has been spent on measurement-based modeling since accurate models are essential for allowing the use of this advanced transistor technology at its best. The present analysis is focused on the modeling of the scattering (S-) parameter measurements for a 0.25 μm GaN HEMT on silicon carbide (SiC) substrate at extreme operating conditions: a large gate width (i.e., the transistor is based on an interdigitated layout consisting of ten fingers, each with a length of 150 μm, resulting in a total gate periphery of 1.5 mm), a high ambient temperature (i.e., from 35 °C up to 200 °C with a step of 55 °C), a high dissipated power (i.e., 5.1 W at 35 °C), and a high frequency in the millimeter-wave range (i.e., from 200 MHz up to 65 GHz with a step of 200 MHz). Three different modeling approaches are investigated: the equivalent-circuit model, artificial neural networks (ANNs), and gated recurrent units (GRUs). As is shown, each modeling approach has its pros and cons that need to be considered, depending on the target performance and their specifications. This implies that an appropriate selection of the transistor modeling approach should be based on discerning and prioritizing the key features that are indeed the most important for a given application

Human fertilization: epididymal hCRISP1 mediates sperm zona pellucida binding through its interaction with ZP3

Human epididymal CRISP1 (hCRISP1) associates with sperm during maturation and participates in gamete fusion through egg complementary sites. Its homology with both rodent epididymal CRISP1 and CRISP4 reported to participate in the previous stage of sperm binding to the zona pellucida (ZP), led us to further investigate the functional role of hCRISP1 by studying its involvement in human sperm-ZP interaction. Human hemizona (HZ) were inseminated with human capacitated sperm in the presence of either anti-hCRISP1 polyclonal antibody to inhibit sperm hCRISP1, or bacterially-expressed hCRISP1 (rec-hCRISP1) to block putative hCRISP1 binding sites in the ZP. Results revealed that both anti-hCRISP1 and rec-hCRISP1 produced a significant inhibition in the number of sperm bound per HZ compared with the corresponding controls. The finding that neither anti-hCRISP1 nor rec-hCRISP1 affected capacitation-associated events (i.e. sperm motility, protein tyrosine phosphorylation or acrosome reaction) supports a specific inhibition at the sperm?egg interaction level. Moreover, immunofluorescence experiments using human ZP-intact eggs revealed the presence of complementary sites for hCRISP1 in the ZP. To identify the ligand of hCRISP1 in the ZP, human recombinant proteins ZP2, ZP3 and ZP4 expressed in insect cells were co-incubated with hCRISP1 and protein?protein interaction was analyzed by ELISA. Results revealed that rec-hCRISP1 mainly interacted with ZP3 in a dose-dependent and saturable manner, supporting the specificity of this interaction. Altogether, these results indicate that hCRISP1 is a multifunctional protein involved notonly in sperm?egg fusion but also in the previous stage of sperm?ZP binding through its specific interaction with human ZP3.Fil: Maldera, Julieta Antonella. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental (i); Argentina. Heidelberg University. Center for Molecular Biology; AlemaniaFil: Weigel Muñoz, Mariana. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental (i); ArgentinaFil: Chirinos, M.. Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubiran; MéxicoFil: Busso, Dolores. Pontificia Universidad Católica de Chile; Chile. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental (i); ArgentinaFil: Raffo, F. G. E.. Centro Médico Fertilab; ArgentinaFil: Battistone, Maria Agustina. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental (i); ArgentinaFil: Blaquier, J. A.. Centro Médico Fertilab; ArgentinaFil: Larrea, F.. Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubiran; MéxicoFil: Cuasnicu, Patricia Sara. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental (i); Argentin