Imaging Pipeline Research Articles

Decoding Insulin Secretory Granule Maturation Using Genetically Encoded pH Sensors.

Insulin is a peptide hormone secreted from pancreatic beta cells to regulate blood glucose homeostasis. Maturation of active insulin occurs within insulin secretory granules (ISG) by acidification of the lumen and enzymatic cleavage of insulin before secretion. This process is dysregulated in diabetes, and many questions remain on how the cell controls insulin maturation. We address this gap in knowledge by designing two genetically encoded fluorescence pH sensors and a fluorescence lifetime imaging and analysis pipeline to monitor the pH of individual secretory ISGs within live cells at higher resolution and precision than previously possible. We observed different subpopulations of ISGs based on their pH and subcellular localization. Signals regulating metabolism vs membrane depolarization mobilize different subpopulations of ISGs for secretion, and we confirm that maturation signals acidify ISGs. We conclude that different signaling networks uniquely impact ISG mobilization and secretion. Future applications of these tools will be useful for exploring how these processes are dysregulated in diabetes and provide new paths for developing more effective treatments.

In situ isotropic 3D imaging of vasculature perfusion specimens using x-ray microscopic dual-energy CT.

Ex vivo x-ray angiography provides high-resolution, three-dimensional information on vascular phenotypes down to the level of capillaries. Sample preparation for ex vivo angiography starts with the removal of blood from the vascular system, followed by perfusion with an x-ray dense contrast agent mixed with a carrier such as gelatine or a polymer. Subsequently, the vascular micro-architecture of harvested organs is imaged in the intact fixed organ. In the present study, we present novel microscopic dual-energy CT (microDECT) imaging protocols that allow to visualise and analyse microvasculature in situ with reference to the morphology of hard and soft tissue. We show that the spectral contrast of µAngiofil and Micropaque barium sulphate in perfused specimens allows for the effective separation of vasculature from mineralised skeletal tissues. Furthermore, we demonstrate the counterstaining of perfused specimens using established x-ray dense contrast agents to depict blood vessels together with the morphology of soft tissue. Phosphotungstic acid (PTA) is used as a counterstain that shows excellent spectral contrast in both µAngiofil and Micropaque barium sulphate-perfused specimens. A novel Sorensen-buffered PTA protocol is introduced as a counterstain for µAngiofil specimens, as the polyurethane polymer is susceptible to artefacts when using conventional staining solutions. Finally, we demonstrate that counterstained samples can be automatically processed into three separate image channels (skeletal tissue, vasculature and stained soft tissue), which offers multiple new options for data analysis. The presented microDECT workflows are suited as tools to screen and quantify microvasculature and can be implemented in various correlative imaging pipelines to target regions of interest for downstream light microscopic investigation.

Multi-step reconstruction of radio-interferometric images

The large aperture arrays for the currently under construction SKA Observatory (SKAO) will allow for observations of the universe in the radio spectrum at unprecedented resolution and sensitivity. However, these telescopes will produce data on the scale of exabytes, introducing a slew of hardware and software design challenges. This paper proposes a multi-step image reconstruction framework that allows for partitioning of visibility data by baseline length. This enables more flexible data distribution and parallelization, aiding in processing radio-astronomical observations within given constraints. Additionally, as each step of the framework only relies on a subset of the total visibilities, one can perform reconstruction progressively, with the initial step performed on the SKAO Science Data Processors and the second on local clusters. The multi-step reconstruction is separated into two steps. First a low-resolution image is reconstructed with only short-baseline visibilities, and then using this image together with the long-baseline visibilities, the full-resolution image is reconstructed. The proposed method only operates in the minor cycle, and it can be easily integrated into existing imaging pipelines. We show that our proposed method allows for partitioning of visibilities by baseline without introducing significant additional drawbacks, reconstructing images of similar quality within similar numbers of major cycles compared to a single-step all-baselines approach that uses the same reconstruction method as well as compared to multi-scale CLEAN.

Prophylactic (R,S)-ketamine and (2S,6S)-HNK decrease fear expression by differentially modulating fear neural ensembles

We previously reported that a single injection of (R,S)-ketamine or its metabolite (2S,6S)-hydroxynorketamine (HNK) prior to stress attenuates learned fear. However, whether these drugs attenuate learned fear through divergent or convergent effects on neural activity remains to be determined. 129S6/SvEv male mice were injected with saline, (R,S)-ketamine, or (2S,6S)-HNK one week before a 3-shock contextual fear conditioning (CFC) paradigm. Five days later, mice were re-exposed to the aversive context, and euthanized one hour later to quantify active cells. Brains were processed for c-fos immunoreactivity, and neural networks were built with a novel, wide-scale imaging pipeline. We found that (R,S)-ketamine and (2S,6S)-HNK attenuate learned fear. Fear-related neural activity was altered in: dorsal CA3 following (2S,6S)-HNK; ventral CA3 and CA1, infralimbic (IL) and prelimbic (PL) regions, insular cortex (IC), retrosplenial cortex (RSP), piriform cortex (PIR), nucleus reuniens (RE), and periaqueductal grey (PAG) following both (R,S)-ketamine and (2S,6S)-HNK; and in the paraventricular nucleus of thalamus (PVT) following (R,S)-ketamine. Dorsal CA3 and ventral hippocampus activation correlated with freezing in the (R,S)-ketamine group, and RSP activation correlated with freezing in both (R,S)-ketamine and (2S,6S)-HNK groups. (R,S)-ketamine increased connectivity between cortical and subcortical regions while (2S,6S)-HNK increased connectivity within these regions. This work identifies novel nodes in fear networks, involving the RE, PIR, IC, PAG and RSP, that can be targeted with neuromodulatory strategies or pharmaceutical compounds to treat fear-induced disorders. This approach could be used to optimize target engagement and dosing strategies of existing medications.

Assembly and evaluation of a confocal microscopy image analysis pipeline useful in revealing the secrets of plant-fungal interactions

The ability of laser scanning confocal microscopy to generate high-contrast 2D and 3D images has become essential in studying plant-fungal interactions. Techniques such as visualization of native fluorescence, fluorescent protein tagging of microbes, GFP/RFP-fusion proteins, and fluorescent labelling of plant and fungal proteins have been widely used to aid in these investigations. Use of fluorescent proteins has several pitfalls including variability of expression in planta and the requirement of gene transformation. Here we used the unlabeled pathogens Parastagonospora nodorum, Pyrenophora teres f. teres, and Cercospora beticola infecting wheat, barley, and sugar beet respectively, to show the utility of a staining and imaging pipeline that uses propidium iodide (PI), which stains RNA and DNA, and wheat germ agglutinin labeled with fluorescein isothiocyanate (WGA-FITC), which stains chitin, to visualize fungal colonization of plants. This pipeline relies on the use of KOH to remove the cutin layer of the leaf, increasing its permeability, allowing the different stains to penetrate and effectively bind to their targets, resulting in a consistent visualization of cellular structures. To expand the utility of this pipeline, we used the staining techniques in conjunction with machine learning to analyze fungal biomass through volume analysis, as well as quantifying nuclear breakdown, an early indicator of programmed cell death (PCD). This pipeline is simple to use, robust, consistent across host and fungal species and can be applied to most plant-fungal interactions. Therefore, this pipeline can be used to characterize model systems as well as non-model interactions where transformation is not routine.

LiverMap pipeline for 3D imaging of human liver reveals volumetric spatial dysregulation of cirrhotic vasculobiliary architecture.

The liver contains an intricate microstructure that is critical for liver function. Architectural disruption of this spatial structure is pathologic. Unfortunately, 2D histopathology - the gold standard for pathological understanding of many liver diseases - can misrepresent or leave gaps in our understanding of complex 3D structural features. Here, we utilized immunostaining, tissue clearing, microscopy, and computational software to create 3D multilobular reconstructions of both non-fibrotic and cirrhotic human liver tissue. We found that spatial architecture in human cirrhotic liver samples with varying etiologies had sinusoid zonation dysregulation, reduction in glutamine synthetase-expressing pericentral hepatocytes, regression of central vein networks, disruption of hepatic arterial networks, and fragmentation of biliary networks, which together suggest a pro-portalization/decentralization phenotype in cirrhotic tissue. Further implementation of 3D pathological analyses may provide a deeper understanding of cirrhotic pathobiology and inspire novel treatments for liver disease.

High-throughput drug screening identifies novel therapeutics for Low Grade Serous Ovarian Carcinoma

Low grade serous carcinoma (LGSOC) is a rare epithelial ovarian cancer with unique molecular characteristics compared to the more common tubo-ovarian high-grade serous ovarian carcinoma. Pivotal clinical trials guiding the management of epithelial ovarian cancer lack sufficient cases of LGSOC for meaningful subgroup analysis, hence overall findings cannot be extrapolated to rarer chemo-resistant subtypes such as LGSOC. Furthermore, there is a need for more effective therapies for the treatment of relapsed disease, as treatment options are limited. To address this, we conducted the largest quantitative high-throughput drug screening effort (n = 3436 compounds) in 12 patient-derived LGSOC cell lines and one normal ovary cell line to identify unexplored therapeutic avenues. Using a combination of high-throughput robotics, high-content imaging and novel data analysis pipelines, our data set identified 60 high and 19 moderate confidence hits which induced cancer cell specific cytotoxicity at the lowest compound dose assessed (0.1 µM). We also revealed a series of known (mTOR/PI3K/AKT) and novel (EGFR and MDM2-p53) drug classes in which LGSOC cell lines showed demonstrable susceptibility to.

A new microscopy pipeline for studying the initial stages of nuclear and micronuclear rupture and repair.

Nuclear envelope repair is a fundamental cellular response to stress, especially for cells experiencing frequent nuclear ruptures, such as cancer cells. Moreover, for chromosomally unstable cancer cells, characterized by the presence of micronuclei, the irreversible rupture of these structures constitutes a fundamental step toward cancer progression and therapy resistance. For these reasons, the study of nuclear envelope rupture and repair is of paramount importance. Nonetheless, due to the constraint imposed by the stochastic nature of rupture events, a precise characterization of the initial stage of nuclear repair remains elusive. In this study, we overcame this limitation by developing a new imaging pipeline that deterministically induces rupture while simultaneously imaging fluorescently tagged repair proteins. We provide a detailed step-by-step protocol to implement this method on any confocal microscope and applied it to study the major nuclear repair protein, barrier-to-autointegration factor (BAF). As a proof of principle, we demonstrated two different downstream analysis methods and showed how BAF is differentially recruited at sites of primary and micronuclear rupture. Additionally, we applied this method to study the recruitment at primary nuclei of the inner nuclear membrane protein LEM-domain 2 (LEMD2) and Charged Multivesicular Protein 7 (CHMP7), the scaffolding protein of the endosomal sorting complex required for transport III (ESCRT-III) membrane remodeling complex. The CHMP7-LEMD2 binding is the fundamental step allowing the recruitment of ESCRT-III, which represents the other major nuclear repair mechanism. This demonstrates the method's applicability for investigating protein dynamics at sites of nuclear and micronuclear envelope rupture and paves the way to more time-resolved studies of nuclear envelope repair.

Evaluation of a hyperspectral image pipeline toward building a generalisation capable crop dry matter content prediction model

Hyperspectral imaging has proven to be a reliable technique for estimating dry matter, a common variable when considering the quality of the fresh produce. However, developing models capable of generalising across different crops is challenging. In this study, several pipelines were explored towards achieving a robust and accurate generic regression model were evaluated and the development of Automatic Relevance Determination (ARD) and Partial Least Squares (PLS) algorithms for fruit and vegetable dry matter estimation. The models were built using a VIS-NIR dataset that includes both fruit and vegetables, namely, apples, broccoli and leek (n = 779). The PLS regression model obtained Root Mean Square on Prediction (RMSEP) = 0.0137, outperforming ARD regression (RMSEP = 0.0140) on a 10x5-fold cross-validation protocol. The evaluated preprocessing techniques affect the two regression algorithms differently, with the best results achieved when the pipeline was used without feature extraction. Overall, the pipeline using either ARD or PLS regression shows strong performance and generalisation for Visible-Near Infrared (VIS-NIR)-based dry matter estimation across diverse fruits and vegetables.

Sex-specific loss of mitochondrial membrane integrity in the auditory brainstem of a mouse model of Fragile X syndrome.

Sound sensitivity is one of the most common sensory complaints for people with autism spectrum disorders (ASDs). How and why sounds are perceived as overwhelming by affected people is unknown. To process sound information properly, the brain requires high activity and fast processing, as seen in areas like the medial nucleus of the trapezoid body (MNTB) of the auditory brainstem. Recent work has shown dysfunction in mitochondria, which are the primary source of energy in cells, in a genetic model of ASD, Fragile X syndrome (FXS). Whether mitochondrial functions are also altered in sound-processing neurons, has not been characterized yet. To address this question, we imaged the MNTB in a mouse model of FXS. We stained MNTB brain slices from wild-type and FXS mice with two mitochondrial markers, TOMM20 and PMPCB, located on the Outer Mitochondrial Membrane and in the matrix, respectively. These markers allow exploration of mitochondrial subcompartments. Our integrated imaging pipeline reveals significant sex-specific differences between genotypes. Colocalization analyses between TOMM20 and PMPCB reveal that the integrity of mitochondrial subcompartments is most disrupted in female FXS mice compared to female wildtype mice. We highlight a quantitative fluorescence microscopy pipeline to monitor mitochondrial functions in the MNTB from control or FXS mice and provide four complementary readouts. Our approach paves the way to understanding how cellular mechanisms important to sound encoding are altered in ASDs.

Automatic Tumor Cellularity Measurement: AI-Based Pipeline for Multi-Organ Pathology Imaging.

Tumor Cellularity (TC) is an important metric for assessing organ tumor burden. However, manual cell counting is not feasible due to large volumes of pathology images and inconsistent measurements between pathologists. The PAIP 2023 Challenge aimed to solve this problem using AI. The challenge presented two main obstacles: the need to evaluate pancreas-trained data for effective use in the colon, and the common miscounting of clustered cells in segmentation results. To address these, we proposed a novel pipeline. It included channel normalization, which standardizes RGB values to ensure consistent model performance across different organs. By introducing CacoX, a specialized model for accurate cell segmentation, we used Coordinate Attention Gates for accurate cell localization and non-local learning. Finally, the implementation of a watershed algorithm allowed the automatic separation of clustered cells. This approach secured 3rd place in the PAIP 2023 Challenge with an impressive ICC score of 95.69%.

SICKO: Systematic Imaging of Caenorhabditis Killing Organisms.

Caenorhabditis elegans are an important model system for research on host-microbe interaction. Their rapid life cycle, short lifespan, and transparent body structure allow simple quantification of microbial load and the influence of microbial exposure on host survival. C. elegans host-microbe interaction studies typically examine group survival and infection severity at fixed timepoints. Here we present an imaging pipeline, Systematic Imaging of Caenorhabditis Killing Organisms (SICKO), that allows longitudinal characterization of microbes colonizing isolated C. elegans, enabling dynamic tracking of tissue colonization and host survival in the same animals. Using SICKO, we show that Escherichia coli or Pseudomonas aeruginosa gut colonization dramatically shortens C. elegans lifespan and that immunodeficient animals lacking pmk-1 are more susceptible to colonization but display similar colony growth relative to wild type. SICKO opens new avenues for detailed research into bacterial pathogenesis, the benefits of probiotics, and the role of the microbiome in host health.

Towards assessing and improving the reliability of ultrashort echo time quantitative magnetization transfer (UTE-qMT) MRI of cortical bone: In silico and ex vivo study.

To assess and improve the reliability of the ultrashort echo time quantitative magnetization transfer (UTE-qMT) modeling of the cortical bone. Simulation-based digital phantoms were created that mimic the UTE-qMT properties of cortical bones. A wide range of SNR from 25 to 200 was simulated by adding different levels of noise to the synthesized MT-weighted images to assess the effect of SNR on UTE-qMT fitting results. Tensor-based denoising algorithm was applied to improve the fitting results. These results from digital phantom studies were validated via ex vivo rat leg bone scans. The selection of initial points for nonlinear fitting and the number of data points tested for qMT analysis have minimal effect on the fitting result. Magnetization exchange rate measurements are highly dependent on the SNR of raw images, which can be substantially improved with an appropriate denoising algorithm that gives similar fitting results from the raw images with an 8-fold higher SNR. The digital phantom approach enables the assessment of the reliability of bone UTE-qMT fitting by providing the known ground truth. These findings can be utilized for optimizing the data acquisition and analysis pipeline for UTE-qMT imaging of cortical bones.

PanIN and CAF transitions in pancreatic carcinogenesis revealed with spatial data integration

This study introduces a new imaging, spatial transcriptomics (ST), and single-cell RNA-sequencing integration pipeline to characterize neoplastic cell state transitions during tumorigenesis. We applied a semi-supervised analysis pipeline to examine premalignant pancreatic intraepithelial neoplasias (PanINs) that can develop into pancreatic ductal adenocarcinoma (PDAC). Their strict diagnosis on formalin-fixed and paraffin-embedded (FFPE) samples limited the single-cell characterization of human PanINs within their microenvironment. We leverage whole transcriptome FFPE ST to enable the study of a rare cohort of matched low-grade (LG) and high-grade (HG) PanIN lesions to track progression and map cellular phenotypes relative to single-cell PDAC datasets. We demonstrate that cancer-associated fibroblasts (CAFs), including antigen-presenting CAFs, are located close to PanINs. We further observed a transition from CAF-related inflammatory signaling to cellular proliferation during PanIN progression. We validate these findings with single-cell high-dimensional imaging proteomics and transcriptomics technologies. Altogether, our semi-supervised learning framework for spatial multi-omics has broad applicability across cancer types to decipher the spatiotemporal dynamics of carcinogenesis.

HiFAST: An H i Data Calibration and Imaging Pipeline for FAST. II. Flux Density Calibration

Accurate flux density calibration is essential for precise analysis and interpretation of observations across different observation modes and instruments. In this research, we first introduce the flux calibration model that incorporated in HiFAST pipeline, and designed for processing H i 21 cm spectra. Furthermore, we investigate different calibration techniques and assess the dependence of the gain parameter on the time and environmental factors. A comparison is carried out in various observation modes (e.g., tracking and scanning modes) to determine the flux density gain (G), revealing insignificant discrepancies in G among different methods. Long-term monitoring data shows a linear correlation between G and atmospheric temperature. After subtracting the G–Temperature dependence, the dispersion of G is reduced to <3% over a one-year timescale. The stability of the receiver response of Five-hundred-meter Aperture Spherical radio Telescope (FAST) is considered sufficient to facilitate H i observations that can accommodate a moderate error in flux calibration (e.g., > ∼ 5%) when utilizing a constant G for calibration purposes. Our study will serve as a useful addition to the results provided by Jiang et al. Detailed measurement of G for the 19 beams of FAST, covering the frequency range 1000–1500 MHz, can be found on the HiFAST homepage: https://hifast.readthedocs.io/fluxgain.

Mapping the nuclear landscape with multiplexed super-resolution fluorescence microscopy.

The nucleus coordinates many different processes. Visualizing how these are spatially organized requires imaging protein complexes, epigenetic marks, and DNA across scales from single molecules to the whole nucleus. To accomplish this, we developed a multiplexed imaging protocol to localize 13 different nuclear targets with nanometer precision in single cells. We show that nuclear specification into active and repressive states exists along a spectrum of length scales, emerging below one micron and becoming strengthened at the nanoscale with unique organizational principles in both heterochromatin and euchromatin. HP1-α was positively correlated with DNA at the microscale but uncorrelated at the nanoscale. RNA Polymerase II, p300, and CDK9 were positively correlated at the microscale but became partitioned below 300 nm. Perturbing histone acetylation or transcription disrupted nanoscale organization but had less effect at the microscale. We envision that our imaging and analysis pipeline will be useful to reveal the organizational principles not only of the cell nucleus but also other cellular compartments.

Correction Method for Perspective Distortions of Pipeline Images

It is common to find severe perspective distortion in a pipeline’s image in medium-diameter pipeline defect detection by the panoramic image unwrapping method, resulting in low-quality image unwrapping and stitching, which is caused by the camera’s optical axis being completely deviated from the pipeline’s center. To solve this problem, a novel correction method for reducing perspective distortion in pipeline images was proposed for pipeline defect detection. Firstly, the method enhances the edges of unevenly illuminated regions within a pipeline to facilitate image segmentation and identify key points necessary for correcting perspective distortion. Then, a six-feature-point extraction method was proposed for a circle target to establish the projection relationship between the extracted feature and mapped points on the reference circle. Finally, a perspective matrix was constructed to complete the perspective transformation correction of the distorted images. The results show that the average correction rate and the average relative error of the proposed correction method can reach 90.85% and 1.31%, respectively. The study innovatively used the enhancement of uneven illumination to find distorted edge information. It proposed an extraction method using a reference circle and six key feature points to build a mapping model. It can provide a novel method which can be used to obtain a superior image for pipeline detection and lay a solid foundation for subsequent high-quality pipeline image stitching.

Robust Ultrafast Projection Pipeline for Structural and Angiography Imaging of Fourier-Domain Optical Coherence Tomography.

The current methods to generate projections for structural and angiography imaging of Fourier-Domain optical coherence tomography (FD-OCT) are significantly slow for prediagnosis improvement, prognosis, real-time surgery guidance, treatments, and lesion boundary definition. This study introduced a robust ultrafast projection pipeline (RUPP) and aimed to develop and evaluate the efficacy of RUPP. RUPP processes raw interference signals to generate structural projections without the need for Fourier Transform. Various angiography reconstruction algorithms were utilized for efficient projections. Traditional methods were compared to RUPP using PSNR, SSIM, and processing time as evaluation metrics. The study used 22 datasets (hand skin: 9; labial mucosa: 13) from 8 volunteers, acquired with a swept-source optical coherence tomography system. RUPP significantly outperformed traditional methods in processing time, requiring only 0.040 s for structural projections, which is 27 times faster than traditional summation projections. For angiography projections, the best RUPP variation took 0.15 s, making it 7518 times faster than the windowed eigen decomposition method. However, PSNR decreased by 41-45% and SSIM saw reductions of 25-74%. RUPP demonstrated remarkable speed improvements over traditional methods, indicating its potential for real-time structural and angiography projections in FD-OCT, thereby enhancing clinical prediagnosis, prognosis, surgery guidance, and treatment efficacy.

A deep cut into early cryptococcal pathogenesis.

Dissemination from one organ system to another is common to many pathogens and often the key process separating simple illness from fatal infection. The pathogenic Cryptococcus species offer a prime example. Cryptococcal infection is thought to begin in the lungs, as a mild or asymptomatic pneumonia. However, bloodborne dissemination from the lungs to the brain is responsible for the most devastating forms of infection. As with other disseminating infections, the transition likely depends on rare but crucial events, such as the crossing of a tissue barrier. By their nature, these events are difficult to study. Francis et al. (mBio 15:e03078-23, 2024, https://doi.org/10.1128/mbio.03078-23) have addressed this difficulty by developing a powerful imaging pipeline to scan through unprecedented volumes of tissue from mice infected with Cryptococcus at multiple stages of infection. Their observations challenge some of our basic assumptions about cryptococcal pathogenesis, including when and how the organism reaches the bloodstream and the central nervous system.

Modeling normal mouse uterine contraction and placental perfusion with non-invasive longitudinal dynamic contrast enhancement MRI.

The placenta is a transient organ critical for fetal development. Disruptions of normal placental functions can impact health throughout an individual's entire life. Although being recognized by the NIH Human Placenta Project as an important organ, the placenta remains understudied, partly because of a lack of non-invasive tools for longitudinally evaluation for key aspects of placental functionalities. Our goal is to create a non-invasive preclinical imaging pipeline that can longitudinally probe murine placental health in vivo. We use advanced imaging processing schemes to establish functional biomarkers for non-invasive longitudinal evaluation of placental development. We implement dynamic contrast enhancement magnetic resonance imaging (DCE-MRI) and analysis pipeline to quantify uterine contraction and placental perfusion dynamics. We use optic flow and time-frequency analysis to quantify and characterize contraction-related placental motion. Our novel imaging and analysis pipeline uses subcutaneous administration of gadolinium for steepest slope-based perfusion evaluation, enabling non-invasive longitudinal monitoring. We demonstrate that the placenta exhibits spatially asymmetric contractile motion that develops from E14.5 to E17.5. Additionally, we see that placental perfusion, perfusion delivery rate, and substrate delivery all increase from E14.5 to E17.5, with the High Perfusion Chamber (HPC) leading the placental changes that occur from E14.5 to E17.5. We advance the placental perfusion chamber paradigm with a novel, physiologically based threshold model for chamber localization and demonstrate spatially varying placental chambers using multiple functional metrics that assess mouse placental development and remodeling throughout gestation. Our pipeline enables the non-invasive, longitudinal assessment of multiple placenta functions from a single imaging session. Our pipeline serves as a key toolbox for advancing research in mouse models of placental disease and disorder.