High resolution dynamic ultrasound atlas of embryonic and fetal development of the common marmoset.

PURPOSE: The common marmoset (Callithrix jacchus) provides an ideal model to study early development of primates, and an in vivo platform to validate conclusions from in vitro studies of human embryos and embryo models. Currently, however, no established staging atlas of marmoset embryonic development exists. Using high-resolution, longitudinal ultrasound scans on live pregnant marmosets, we present the first dynamic in vivo imaging of entire primate gestation beginning with attachment until the last day before birth. METHODS: Our study unveils the first dynamic images of an in vivo attached mammalian embryo developing in utero, and the intricacies of the delayed development period unique to the common marmoset amongst primates, revealing a window for somatic interventions. RESULTS: Established obstetric and embryologic measurements for each scan were used comparatively with the standardized Carnegie staging of human development to highlight similarities and differences. Our study also allows for tracking the development of major organs. We focus on the ontogeny of the primate heart and brain. Finally, input ultrasound images were used to train deep neural networks to accurately determine the gestational age. All our ultrasounds and staging data recording are posted online so that the atlas can be used as a community resource toward monitoring and managing marmoset breeding colonies. CONCLUSION: The temporal and spatial resolution of ultrasound achieved in this study demonstrates the promise of noninvasive imaging in the marmoset for the in vivo study of primate-specific aspects of embryonic and fetal development.

Case report: A novel biallelic FTO variant causing multisystem anomalies with severe epilepsy, widening the spectrum of FTO syndrome.

The fat mass and obesity-associated gene (FTO) codes for a DNA/RNA demethylase. Pathological variants in this gene are rare, with only three reports in the literature, all with mutations in the catalytic domain. We report the first biallelic human variant in fat mass and obesity-associated gene (c.287G>C, p.Arg96Pro/R96P) outside the catalytic site, causing numerous abnormalities across multiple organ systems, affecting respiratory, cardiovascular, and neurological function. Biochemical assays of cells with the patient's variant were performed to further quantify the effect of the variant on function. Loss-of-function resulting from the patient's R96P missense variant was demonstrated with in vitro biochemical characterization of demethylase activity, resulting in a 90% reduction in function of the fat mass and obesity-associated protein compared to wild-type. Our findings demonstrate a novel fat mass and obesity-associated gene non-catalytic site variant with a unique patient phenotype of bilateral multifocal epilepsy and multisystem congenital anomalies.

Development of Deep Belief Network for Tool Faults Recognition.

The controlled interaction of work material and cutting tool is responsible for the precise outcome of machining activity. Any deviation in cutting parameters such as speed, feed, and depth of cut causes a disturbance to the machining. This leads to the deterioration of a cutting edge and unfinished work material. Recognition and description of tool failure are essential and must be addressed using intelligent techniques. Deep learning is an efficient method that assists in dealing with a large amount of dynamic data. The manufacturing industry generates momentous information every day and has enormous scope for data analysis. Most intelligent systems have been applied toward the prediction of tool conditions; however, they must be explored for descriptive analytics for on-board pattern recognition. In an attempt to recognize the variation in milling operation leading to tool faults, the development of a Deep Belief Network (DBN) is presented. The network intends to classify in total six tool conditions (one healthy and five faulty) through image-based vibration signals acquired in real time. The model was designed, trained, tested, and validated through datasets collected considering diverse input parameters.

Particle Swarm Optimization Algorithm for Guided Waves Based Damage Localization Using Fiber Bragg Grating Sensors in Remote Configuration.

Structural health monitoring (SHM) systems may allow a reduction in maintenance costs and extend the lifetime of the structure. As a result, they are of interest to the research community. Ideally, the SHM methods should be low cost, while being able to detect and localize small levels of damage reliably and accurately. The fiber Bragg grating (FBG) sensors are light in weight, insensitive to electric and magnetic fields, and can be embedded. The edge filtering configuration for transduction allows the use of FBG for guided wave (GW) sensing. This sensitivity may be further enhanced through their application in the remote bonded configuration. This paper provides a proof-of-concept for the use of remotely bonded FBG for damage localization. In order to improve the computational efficiency, a particle swarm optimization (PSO) based algorithm is developed. The PSO allows a significant improvement in the computation time which makes it better suited for real-time damage localization. The proposed objective function is based on the exponential elliptical approach. First, the suitability of the PSO for damage localization is shown. Then the performance of the chosen objective function is compared with the brute-force algorithm as well as other objective functions found in the literature. The methodology is employed on a simple aluminum plate. The results indicate that indeed the objective function along with the PSO is suitable for damage localization. Also as the objective function is developed taking into consideration the specific challenges with the use of FBG sensors, performs better than the other objective functions as well as the brute force algorithm.

Spectral element modeling of ultrasonic guided wave propagation in optical fibers.

Recent advancements in fiber optic methods have enabled their use for guided wave sensing. It opens up new possibilities for Structural Health Monitoring. The aim of this paper is to provide insight for the physics related to guided wave propagation and coupling between the optical fiber and solid structure. For this purpose, a new approach for non-matching interface based on Lagrange multipliers and the time domain spectral element method was developed. A parallelized code has been implemented in order to simulate the guided wave propagation in the structure, its coupling into the optical fiber and the propagation in the fiber in a computationally efficient way. The paper presents four studies showing the efficacy of the modeling approach. The paper first shows the improvement in the computation speed through the use of parallelization and a more efficient implementation. Then the results of the simulation of wave propagation in the fiber are compared with results from previous simulation studies using commercially available software. The third study shows that the spectral element method is able to capture the directional sensitivity of optical fiber based sensors. Lastly, the simulation is used for detection of simulated damage using the spectral element method based simulation. The results indicate that indeed the spectral element implementation is able to recreate the wave coupling phenomena, capture the physics of the system including directional sensitivity and reflections from damage.

Multi-objective optimization for joint actuator and sensor placement for guided waves based structural health monitoring using fibre Bragg grating sensors.

Structural Health Monitoring (SHM) systems have a potential to reduce lifecycle costs of structures. As a result, there is a lot of active research in the area for SHM of civil and mechanical structures. Guided waves (GW) based SHM techniques allow monitoring of large plate-like structures with a few sensors and have been identified as the most promising of techniques for SHM. Fibre Bragg grating (FBG) sensors due to their low weight, and ability to be multiplexed have been long thought to be ideal sensors for SHM. The recent development of the edge filtering approach has increased their sensitivity to GW sensing and made them ideal sensors. Unfortunately the FBG sensors are passive sensors and show directional sensitivity. These operational constraints make extension of the earlier developed GW based SHM techniques for FBG sensors difficult. Recently the authors developed a technique for damage detection specifically designed for a network with FBG sensors. This paper builds on the past work by the authors and develops a methodology for a design of an actuator-sensor (AS) network for improving the damage assessment capability of the previously proposed method. The paper develops a multi objective optimization technique for the joint optimization of actuator and sensor placement for a network with FBG sensors. The joint optimization of the actuators and sensors is necessary due to the passive nature of the FBG sensors and also incorporates the directional nature of the FBG sensors. The paper develops an integer encoded NSGA-II for the optimization of the AS network. The objectives for the optimization are derived from the specific damage detection technique tailored for the use of FBG sensors. The objective are: coverage with at least 2 AS pairs, coverage with at least 1 edge reflected path and the cost of the deployed network. The results indicate that the encoding of the objectives of the optimization is valid and indeed the damage detection capabilities of the AS network are as predicted analytically. The paper for the first time develops a joint optimization of network for FBG sensors. It is also the first attempt at a truly multi-objective optimization of the AS network and promises to have applications on real structures.

Optical Fiber Sensors for Ultrasonic Structural Health Monitoring: A Review.

Guided waves (GW) and acoustic emission (AE) -based structural health monitoring (SHM) have widespread applications in structures, as the monitoring of an entire structure is possible with a limited number of sensors. Optical fiber-based sensors offer several advantages, such as their low weight, small size, ability to be embedded, and immunity to electro-magnetic interference. Therefore, they have long been regarded as an ideal sensing solution for SHM. In this review, the different optical fiber technologies used for ultrasonic sensing are discussed in detail. Special attention has been given to the new developments in the use of FBG sensors for ultrasonic measurements, as they are the most promising and widely used of the sensors. The paper highlights the physics of the wave coupling to the optical fiber and explains the different phenomena such as directional sensitivity and directional coupling of the wave. Applications of the different sensors in real SHM applications have also been discussed. Finally, the review identifies the encouraging trends and future areas where the field is expected to develop.

Depletion of aneuploid cells in human embryos and gastruloids.

Chromosomal instability leading to aneuploidy is pervasive in early human embryos1-3 and is considered as a major cause of infertility and pregnancy wastage4,5. Here we provide several lines of evidence that blastocysts containing aneuploid cells are worthy of in vitro fertilization transfer. First, we show clinically that aneuploid embryos can lead to healthy births, suggesting the presence of an in vivo mechanism to eliminate aneuploidy. Second, early development and cell specification modelled in micropatterned human 'gastruloids' grown in confined geometry show that aneuploid cells are depleted from embryonic germ layers, but not from extraembryonic tissue, by apoptosis in a bone morphogenetic protein 4 (BMP4)-dependent manner. Third, a small percentage of euploid cells rescues embryonic tissue in mosaic gastruloids when mixed with aneuploid cells. Finally, single-cell RNA-sequencing analysis of early human embryos revealed a decline of aneuploidy beginning on day 3. Our findings challenge two current dogmas: that a single trophectoderm biopsy at blastocyst stage to perform prenatal genetic testing can accurately determine the chromosomal make-up of a human embryo, and that aneuploid embryos should be withheld from embryo transfer in association with in vitro fertilization.

A Two-Step Guided Waves Based Damage Localization Technique Using Optical Fiber Sensors.

Structural health monitoring (SHM) systems help in reducing maintenance cost and avoiding catastrophic failure of the structure. As a result, they have been a focus of research for the past few decades. Ideally, the methods employed should be low cost and able to detect and localize small levels of damage reliably and accurately. This paper describes a guided waves (GW) based two-step technique for damage detection and localization using fiber Bragg grating (FBG) sensors. The FBG sensors offer benefits such as the ability to be embedded and multiplexed as well as being lightweight and insensitive to electric and magnetic fields, and they have long been seen as a promising solution for the GW measurements in structures. Unfortunately, in the conventional wavelength-based interrogation they have very low signal to noise ratio and as a result low sensitivity. Therefore, the FBG sensor is incorporated in the edge filtering configuration. The major challenges in the use of FBG sensors for GW-based detection are their directional sensitivity and passive nature. The passive nature leads to the reduction in the available actuator-sensor (AS) pairs while the directionality makes the signal processing a challenge. The proposed two-step methodology overcomes these shortcomings of FBG sensors. In the first step the amplitude weighted elliptical approach is used to identify the hotspots due to the inadequate number of AS pairs, the elliptical approach is not sufficient for damage localization. Therefore, in order to further localize the damage the edge reflection based ray-tracing approach is implemented in the second step. Through the two step method, the damage is accurately located. The paper provides the proof of concept of the proposed methodology on an aluminum plate with simulated damage. The results indicate, that indeed the two-step methodology allows accurate damage localization and overcomes the possibility of false detections.

A Variable Data Fusion Approach for Electromechanical Impedance-Based Damage Detection.

There is continuing research in the area of structural health monitoring (SHM) as it may allow a reduction in maintenance costs as well as lifetime extension. The search for a low-cost health monitoring system that is able to detect small levels of damage is still on-going. The present study is one more step in this direction. This paper describes a data fusion technique by combining the information for robust damage detection using the electromechanical impedance (EMI) method. The EMI method is commonly used for damage detection due to its sensitivity to low levels of damage. In this paper, the information of resistance (R) and conductance (G) is studied in a selected frequency band and a novel data fusion approach is proposed. A novel fused parameter (F) is developed by combining the information from G and R. The difference in the new metric under different damage conditions is then quantified using established indices such as the root mean square deviation (RMSD) index, mean absolute percentage deviation (MAPD), and root mean square deviation using k-th state as the reference (RMSDk). The paper presents an application of the new metric for detection of damage in three structures, namely, a thin aluminum (Al) plate with increasing damage severity (simulated with a drilled hole of increasing size), a glass fiber reinforced polymer (GFRP) composite beam with increasing delamination and another GFRP plate with impact-induced damage scenarios. Based on the experimental results, it is apparent that the variable F increases the robustness of the damage detection as compared to the quantities R and G.

A Study of Sensor Placement Optimization Problem for Guided Wave-Based Damage Detection.

Guided waves (GW) allow fast inspection of a large area and hence have attracted research interest from the structural health monitoring (SHM) community. Thus, GW-based SHM is ideal for thin structures such as plates, pipes, etc., and is finding applications in several fields like aerospace, automotive, wind energy, etc. The GW propagate along the surface of the sample and get reflected from discontinuities in the structure in the form of boundaries and damage. Through proper signal processing of the reflected waves based on their time of arrival, the damage can be detected and isolated. For complex structures, a higher number of sensors may be required, which increases the cost of the equipment, as well as the mass. Thus, there is an effort to reduce the number of sensors without compromising the quality of the monitoring achieved. It is of utmost importance that the entire structure can be investigated. Hence, it is necessary to optimize the locations of the sensors in order to maximize the coverage while limiting the number of sensors used. A genetic algorithm (GA)-based optimization strategy was proposed by the authors for use in a simple aluminum plate. This paper extends the optimization methodology for other shape plates and presents experimental, analytical, and numerical studies. The sensitivity studies have been carried out by changing the relative weights of the application demands and presented in the form of a Pareto front. The Pareto front allows comparison of the relative importance of the different application demands, and an appropriate choice can be made based on the information provided.

Kalman Filter Based Load Monitoring in Beam Like Structures Using Fibre-Optic Strain Sensors.

The paper presents a proof of concept of a new methodology for the load estimation in beam-like structures under complex loading. The paper customizes a Kalman Filter (KF) based estimation technique which is shown to be robust to the presence of measurement noise as well as the changing condition of the beam for estimation of loads in beam-like structures. The methodology was validated using numerical as well as experimental data. The initial studies indicate that the proposed methodology has promise for applications where monitoring and classification of the strains is necessary, such as those in continuous welded rails.

Screening Mammography for Women in Their 40s: The Potential Impact of the American Cancer Society and U.S. Preventive Services Task Force Breast Cancer Screening Recommendations.

OBJECTIVE: The purpose of this study was to review screening mammograms obtained in one practice with the primary endpoint of determining the rate of detection of breast cancer and associated prognostic features in women 40-44 and 45-49 years old. MATERIALS AND METHODS: The retrospective cohort study included women in their 40s with breast cancer detected at screening from June 2014 through May 2016. The focus was on cancer detection rate, pathologic findings, and risk factors. RESULTS: A total of 32,762 screens were performed, and 808 biopsies were recommended. These biopsies yielded 224 breast cancers (cancer detection rate, 6.84 per 1000 screens). Women 40-49 years old had 18.8% of cancers detected; 50-59 years, 21.8%; 60-69 years, 32.6%; and 70-79 years, 21.4%. Among the 40- to 49-year-old women, women 40-44 years old underwent 5481 (16.7%) screens, had 132 biopsies recommended, and had 20 breast cancers detected (cancer detection rate, 3.6/1000). Women 45-49 years old underwent 5319 (16.2%) screens, had 108 biopsies recommended, and had 22 breast cancers detected (cancer detection rate, 4.1/1000). Thus, women 40-44 years old had 8.9% and women 45-49 years old had 9.8% of all screen-detected breast cancers. Of these only a small percentage of women with detected cancers had a first-degree relative with breast cancer (40-44 years, 15%; 45-49 years, 32%) or a BRCA mutation (40-44 years, 5%; 45-49 years, 5%), and over 60% of the cancers were invasive. CONCLUSION: Women 40-49 years old had 18.8% of all screen-detected breast cancers. The two cohorts (40-44 and 45-49 years old) had similar incidences of screen-detected breast cancer (8.9%, 9.8%) and cancer detection rates within performance benchmark standards, supporting a similar recommendation for both cohorts and the American College of Radiology recommendation of annual screening mammography starting at age 40.

Microbioreactors to manipulate oxygen tension and shear stress in the microenvironment of vascular stem and progenitor cells.

The dynamics of dissolved oxygen (DO) and shear stress in the vasculature microenvironment play a major role in determining the fate of stem cells in adults and during early embryonic development. In this study, we present a microbioreactor (MBR) that provides independent control over oxygen tension and shear stress in cultures of stem and progenitor cell types. We first describe the design principles and use a model-driven approach for the optimization of the MBR geometry and operating conditions prior to its fabrication and assembly. We then demonstrate the utilization of the MBR for culturing adult human endothelial progenitors, human umbilical vein endothelial cells, and human embryonic stem cell-derived smooth muscle cells under different DO and shear stress levels.