Dysregulated placental expression of kynurenine pathway enzymes is associated with inflammation and depression in pregnancy.

BACKGROUND: Perinatal depression (including antenatal-, postnatal-, and depression that spans both timepoints) is a prevalent disorder with high morbidity that affects both mother and child. Even though the full biological blueprints of perinatal depression remain incomplete, multiple studies indicate that, at least for antenatal depression, the disorder has an inflammatory component likely linked to a dysregulation of the enzymatic kynurenine pathway. The production of neuroactive metabolites in this pathway, including quinolinic acid (QUIN), is upregulated in the placenta due to the multiple immunological roles of the metabolites during pregnancy. Since neuroactive metabolites produced by the pathway also may affect mood by directly affecting glutamate neurotransmission, we sought to investigate whether the placental expression of kynurenine pathway enzymes controlling QUIN production was associated with both peripheral inflammation and depressive symptoms during pregnancy. METHODS: 68 placentas obtained at birth were analyzed using qPCR to determine the expression of kynurenine pathway enzymes. Cytokines and metabolites were quantified in plasma using high-sensitivity electroluminescence and ultra-performance liquid chromatography, respectively. Maternal depressive symptoms were assessed using the Edinburgh Postnatal Depression Scale (EPDS) throughout pregnancy and the post-partum. Associations between these factors were assessed using robust linear regression with ranked enzymes. RESULTS: Low placental quinolinate phosphoribosyl transferase (QPRT), the enzyme responsible for degrading QUIN, was associated with higher IL-6 and higher QUIN/kynurenic acid ratios at the 3rd trimester. Moreover, women with severe depressive symptoms in the 3rd trimester had significantly lower placental expression of both QPRT and 2-amino-3-carboxymuconate-6-semialdehyde decarboxylase (ACMSD); impaired activity of these two enzymes leads to QUIN accumulation. CONCLUSION: Overall, our data support that a compromised placental environment, featuring low expression of critical kynurenine pathway enzymes is associated with increased levels of plasma cytokines and the dysregulated kynurenine metabolite pattern observed in depressed women during pregnancy.

Improving the localisation of features for the calibration of cameras using EfficientNets.

Camera-based methods for optical coordinate metrology, such as digital fringe projection, rely on accurate calibration of the cameras in the system. Camera calibration is the process of determining the intrinsic and distortion parameters which define the camera model and relies on the localisation of targets (in this case, circular dots) within a set of calibration images. Localising these features with sub-pixel accuracy is key to providing high quality calibration results which in turn allows for high quality measurement results. A popular solution to the localisation of calibration features is provided in the OpenCV library. In this paper, we adopt a hybrid machine learning approach where an initial localisation is given by OpenCV which is then refined through a convolutional neural network based on the EfficientNet architecture. Our proposed localisation method is then compared with the OpenCV locations without refinement, and to an alternative refinement method based on traditional image processing. We show that under ideal imaging conditions, both refinement methods provide a reduction in the mean residual reprojection error of approximately 50%. However, in adverse imaging conditions, with high noise levels and specular reflection, we show that the traditional refinement degrades the results given by pure OpenCV, increasing the mean residual magnitude by 34%, which corresponds to 0.2 pixels. In contrast, the EfficientNet refinement is shown to be robust to the unideal conditions and is still able to reduce the mean residual magnitude by 50% compared to OpenCV. The EfficientNet feature localisation refinement, therefore, enables a greater range of viable imaging positions across the measurement volume. leading to more robust camera parameter estimations.

Stitching Locally Fitted T-Splines for Fast Fitting of Large-Scale Freeform Point Clouds.

Parametric splines are popular tools for precision optical metrology of complex freeform surfaces. However, as a promising topologically unconstrained solution, existing T-spline fitting techniques, such as improved global fitting, local fitting, and split-connect algorithms, still suffer the problems of low computational efficiency, especially in the case of large data scales and high accuracy requirements. This paper proposes a speed-improved algorithm for fast, large-scale freeform point cloud fitting by stitching locally fitted T-splines through three steps of localized operations. Experiments show that the proposed algorithm produces a three-to-eightfold efficiency improvement from the global and local fitting algorithms, and a two-to-fourfold improvement from the latest split-connect algorithm, in high-accuracy and large-scale fitting scenarios. A classical Lena image study showed that the algorithm is at least twice as fast as the split-connect algorithm using fewer than 80% control points of the latter.

Crosstalk decoupling measurement method to determine the six degrees of freedom of motion error of linear stages.

The simultaneous measurement of all six degrees of freedom of motion error for a linear stage is significantly faster than methods that measure each degree of freedom separately. However, in current simultaneous measurement methods, error crosstalk issues significantly affect measurement accuracy. In this paper, a direct and simple crosstalk decoupling simultaneous measurement method to determine the six degrees of freedom of motion error of a linear stage is proposed. Based on the combination of single-frequency laser interferometry and laser self-collimation, a novel, to the best of our knowledge, optical configuration with a complete error decoupling relationship is designed, and a mathematical model is derived for error decoupling to address the crosstalk issue. A prototype system based on the new method is developed, and experiments are conducted to verify its effectiveness. Analysis shows that, compared with a commercial laser interferometer for linear stage measurement, the deviations of the positioning, horizontal straightness, vertical straightness, roll, pitch, and yaw errors are±0.50µm, ±0.58µm, ±0.50µm, ±1.02in., ±0.72in., and ±0.87in. respectively, over a 200 mm measurement range.

Surface measuring coherence scanning interferometry beyond the specular reflection limit.

The capability of optical surface topography measurement methods for measurement of steep and tilted surfaces is investigated through modelling of a coherence scanning interferometer. Of particular interest is the effect on the interference signal and measured topography when tilting the object at angles larger than the numerical aperture slope limit (i.e. the specular reflection limit) of the instrument. Here we use theoretical modelling to predict the results across a range of tilt angles for a blazed diffraction grating. The theoretically predicted interference patterns and surface height measurements are then verified directly with experimental measurements. Results illustrate the capabilities, limitations and modelling methods for interferometers to measure beyond the specular reflection limit.

Two-dimensional spectral signal model for chromatic confocal microscopy.

In chromatic confocal microscopy, the signal characteristics influence the accuracy of the signal processing, which in turn determines measurement performance. Thus, a full understanding of the spectral characteristics is critical to enhance the measurement performance. Existing spectral models only describe the signal intensity-wavelength characteristics, without taking the displacement-wavelength relation into consideration. These models require prior knowledge of the optical design, which reduces the effectiveness in the optical design process. In this paper, we develop a two-dimensional spectral signal model to describe the signal intensity-wavelength-displacement characteristics in chromatic confocal microscopy without prior knowledge of the optical design layout. With this model, the influence of the dimensional characteristics of the confocal setup and the displacement-wavelength characteristics and monochromatic aberrations of the hyperchromatic objective are investigated. Experimental results are presented to illustrate the effectiveness of our signal model. Using our model, further evaluation of the spectral signal can be used to enhance the measurement performance of chromatic confocal microscopy.

Locally adaptive thresholding centroid localization in confocal microscopy.

We introduce an iteration-free approach, based on a centroid algorithm with a locally adaptive threshold, for nanometer-level peak position localization of the axial response signal in confocal microscopy. This approach has localization accuracies that are near theoretical limits, especially when there is a small number of sampling points within the discrete signal. The algorithm is also orders of magnitude faster compared to fitting schemes based on maximum likelihood estimation. Simulations and experiments demonstrate the localization performance of the approach.

Differences in cervical cancer screening and follow-up for black and white women in the United States.

OBJECTIVE: To study differences in screening adherence and follow-up after an abnormal Pap test in Non-Hispanic Black (Black) and Non-Hispanic White (White) women. METHODS: An observational cohort study using 2010 National Health Interview Survey cancer module to examine HPV knowledge, screening behavior, and follow-up to abnormal Pap test in Black and White women 18 years of age or older without a hysterectomy. We fit logistic regression models to examine associations between race and primary outcome variables including: HPV awareness, Pap test in the last three years, provider recommended Pap test, received Pap test results, had an abnormal Pap test, recommended follow-up, and adhered to the recommendation for follow-up. RESULTS: Analyzing data for 7509 women, Black women had lower odds ratios [OR] for: 1) HPV awareness (71% vs 83%; OR = 0.42; 95% CI = 0.36-0.49); 2) reporting Pap screening was recommended (59% vs 64%; OR = 0.76; 95% CI = 0.66-0.88), and 3) acknowledging receipt of Pap results (92% vs 94%; OR = 0.64; 95% CI = 0.49-0.83). Group differences persisted after covariates adjustment. In adjusted models, Black women had higher odds of reporting recent Pap screening (84% vs 77%; OR = 1.7; 95% CI = 1.42-2.03), but reported lower odds of receiving a follow-up recommendation subsequent to abnormal test (78% vs 87%; OR = 0.54; 95% CI = 0.31-0.95). CONCLUSION: Black women reported higher cervical cancer screening adherence but lower rates of being informed of an abnormal Pap test and contacted for follow-up treatment. We recommend a multilevel approach to deliver culturally appropriate education and communication for patients, physicians, clinicians in training, and clinic level ancillary staff.

Scattering and three-dimensional imaging in surface topography measuring interference microscopy.

Surface topography measuring interference microscopy is a three-dimensional (3D) imaging technique that provides quantitative analysis of industrial and biomedical specimens. Many different instrument modalities and configurations exist, but they all share the same theoretical foundation. In this paper, we discuss a unified theoretical framework for 3D image (interferogram) formation in interference microscopy. We show how the scattered amplitude is linearly related to the surface topography according to the Born and the Kirchhoff approximations and highlight the main differences and similarities of each. With reference to the Ewald and McCutchen spheres, the relationship between the spatial frequencies that characterize the illuminating and scattered waves, and those that characterize the object, are defined and formulated as a 3D linear filtering process. It is shown that for the case of near planar surfaces, the 3D filtering process can be reduced to two dimensions under the small height approximation. However, the unified 3D framework provides significant additional insight into the scanning methods used in interference microscopy, effects such as interferometric defocus and ways to mitigate errors introduced by aberrations of the optical system. Furthermore, it is possible to include the nonlinear effects of multiple scattering into the generalized framework. Finally, we consider the inherent nonlinearities introduced when estimating surface topography from the recorded interferogram.

FSH dose is negatively correlated with number of oocytes retrieved: analysis of a data set with ~650,000 ART cycles that previously identified an inverse relationship between FSH dose and live birth rate.

PURPOSE: To evaluate whether total FSH dose was negatively correlated with number of oocytes retrieved in a large data set where previously, a negative correlation between FSH dose and live birth rate was identified. METHODS: Data from 650,637 fresh autologous in vitro fertilization (IVF) cycles reported to the Society for Assisted Reproductive Technology between 2004 and 2012 were included. Logistic regression analysis was performed to determine if the relationship between total FSH dose used during ART with number of oocytes retrieved was impacted by the patient's health prognosis, age, BMI, ovarian stimulation protocol, or infertility diagnosis. RESULTS: The number of oocytes retrieved was negatively correlated with FSH dose (P < 0.0001). Regardless of patient prognosis, age, BMI, ovarian stimulation protocol, and infertility diagnosis, the highest number of oocytes retrieved was in the 1001-2000 IU FSH group, and was 36-51% lower in the > 5000 IU compared with the optimal, 1001-2000 IU, FSH groups. Overall, ~80% of patients received FSH doses outside of the optimal FSH dose. Moreover, 61% of good prognosis patients (excludes individuals likely prescribed higher FSH doses) received doses exceeding the optimal dose range. CONCLUSION: The inverse relationship between FSH dose and the number of oocytes retrieved independent of patient age or health implies that excessive FSH doses during ART may be detrimental to oocyte retrieval.

Traceable Reference Full Metrology Chain for Innovative Aspheric and Freeform Optical Surfaces Accurate at the Nanometer Level.

The design of innovative reference aspheric and freeform optical elements was investigated with the aim of calibration and verification of ultra-high accurate measurement systems. The verification is dedicated to form error analysis of aspherical and freeform optical surfaces based on minimum zone fitting. Two thermo-invariant material measures were designed, manufactured using a magnetorheological finishing process and selected for the evaluation of a number of ultra-high-precision measurement machines. All collected data sets were analysed using the implemented robust reference minimum zone (Hybrid Trust Region) fitting algorithm to extract the values of form error. Agreement among the results of several partners was observed, which demonstrates the establishment of a traceable reference full metrology chain for aspherical and freeform optical surfaces with small amplitudes.

Inflammation and kynurenine pathway dysregulation in post-partum women with severe and suicidal depression.

Depression during pregnancy and the post-partum is common, with severe cases resulting in suicidal behavior. Despite the urgent and unmet medical need, the biological underpinnings of peri-partum depression remain unclear. It has been suggested that it is triggered by dynamic changes of the immune system during pregnancy and at delivery. Therefore, we investigated whether a pro-inflammatory status in plasma, together with changes in the kynurenine pathway activity, is associated with the development of severe depression and suicidal behavior in the post-partum. Our cross-sectional study targets a unique, understudied population in which the pronounced severity of symptoms required hospitalization. We analyzed plasma IL-1ß, IL-2, IL-6, IL-8, TNF-α, tryptophan, serotonin, kynurenine, nicotinamide, quinolinic- and kynurenic acids in post-partum women diagnosed with peripartum onset depression (PPD) and healthy controls (n = 165). We assessed depression severity using the Edinburgh Postnatal Depression Scale and suicidality using the Columbia-Suicide Severity Rating Scale. We found that increased plasma IL-6 and IL-8 and reductions of serotonin, IL-2 and quinolinic acid were associated with the severity of depressive symptoms and increased the risk for PPD. Moreover, women with lower serotonin levels were at an increased risk for suicidal behavior, even when adjusting for depression severity, psychosocial factors, age BMI, and medication. Our results indicate that severe depression in the post-partum involves dysregulation of the immune response and the kynurenine pathway, with a concomitant reduction in serotonin levels. We propose that inflammatory cytokines and the kynurenine pathway are potential treatment targets in PPD, opening up the possibility of novel therapeutic strategies targeting the peripartum.

Genetic and genomic characterization of vulva size traits in Yorkshire and Landrace gilts.

BACKGROUND: Reproductive performance is critical for efficient swine production. Recent results indicated that vulva size (VS) may be predictive of reproductive performance in sows. Study objectives were to estimate genetic parameters, identify genomic regions associated, and estimate genomic prediction accuracies (GPA) for VS traits. RESULTS: Heritability estimates of VS traits, vulva area (VA), height (VH), and width (VW) measurements, were moderately to highly heritable in Yorkshire, with 0.46 ± 0.10, 0.55 ± 0.10, 0.31 ± 0.09, respectively, whereas these estimates were low to moderate in Landrace, with 0.16 ± 0.09, 0.24 ± 0.11, and 0.08 ± 0.06, respectively. Genetic correlations within VS traits were very high for both breeds, with the lowest of 0.67 ± 0.29 for VH and VW for Landrace. Genome-wide association studies (GWAS) for Landrace, reveled genomic region associated with VS traits on Sus scrofa chromosome (SSC) 2 (154-157 Mb), 7 (107-110 Mb), 8 (4-6 Mb), and 10 (8-19 Mb). For Yorkshire, genomic regions on SSC 1 (87-91 and 282-287 Mb) and 5 (67 Mb) were identified. All regions explained at least 3.4% of the genetic variance. Accuracies of genomic prediction were moderate in Landrace, ranging from 0.30 (VH) to 0.61 (VA), and lower for Yorkshire, with 0.07 (VW) to 0.11 (VH). Between-breed and multi-breed genomic prediction accuracies were low. CONCLUSIONS: Our findings suggest that VS traits are heritable in Landrace and Yorkshire gilts. Genomic analyses show that major QTL control these traits, and they differ between breed. Genomic information can be used to increase genetic gains for these traits in gilts. Additional research must be done to validate the GWAS and genomic prediction results reported in our study.

Genome sequencing identifies major causes of severe intellectual disability.

Severe intellectual disability (ID) occurs in 0.5% of newborns and is thought to be largely genetic in origin. The extensive genetic heterogeneity of this disorder requires a genome-wide detection of all types of genetic variation. Microarray studies and, more recently, exome sequencing have demonstrated the importance of de novo copy number variations (CNVs) and single-nucleotide variations (SNVs) in ID, but the majority of cases remain undiagnosed. Here we applied whole-genome sequencing to 50 patients with severe ID and their unaffected parents. All patients included had not received a molecular diagnosis after extensive genetic prescreening, including microarray-based CNV studies and exome sequencing. Notwithstanding this prescreening, 84 de novo SNVs affecting the coding region were identified, which showed a statistically significant enrichment of loss-of-function mutations as well as an enrichment for genes previously implicated in ID-related disorders. In addition, we identified eight de novo CNVs, including single-exon and intra-exonic deletions, as well as interchromosomal duplications. These CNVs affected known ID genes more frequently than expected. On the basis of diagnostic interpretation of all de novo variants, a conclusive genetic diagnosis was reached in 20 patients. Together with one compound heterozygous CNV causing disease in a recessive mode, this results in a diagnostic yield of 42% in this extensively studied cohort, and 62% as a cumulative estimate in an unselected cohort. These results suggest that de novo SNVs and CNVs affecting the coding region are a major cause of severe ID. Genome sequencing can be applied as a single genetic test to reliably identify and characterize the comprehensive spectrum of genetic variation, providing a genetic diagnosis in the majority of patients with severe ID.

Advances in optical metrology and instrumentation: introduction.

Optical measurement and characterization are two of the pillars of metrology. The ability to measure precisely with high dynamic range and accuracy betters our understanding of nature and the universe. In this feature issue, we present a collection of articles that delves into the fundamental techniques used to advance the field.

On-machine surface defect detection using light scattering and deep learning.

This paper presents an on-machine surface defect detection system using light scattering and deep learning. A supervised deep learning model is used to mine the information related to defects from light scattering patterns. A convolutional neural network is trained on a large dataset of scattering patterns that are predicted by a rigorous forward scattering model. The model is valid for any surface topography with homogeneous materials and has been verified by comparing with experimental data. Once the neural network is trained, it allows for fast, accurate, and robust defect detection. The system capability is validated on microstructured surfaces produced by ultraprecision diamond machining.

Multi-view fringe projection system for surface topography measurement during metal powder bed fusion.

Metal powder bed fusion (PBF) methods need in-process measurement methods to increase user confidence and encourage further adoption in high-value manufacturing sectors. In this paper, a novel measurement method for PBF systems is proposed that uses multi-view fringe projection to acquire high-resolution surface topography information of the powder bed. Measurements were made using a mock-up of a commercial PBF system to assess the system's accuracy and precision in comparison to conventional single-view fringe projection techniques for the same application. Results show that the multi-view system is more accurate, but less precise, than single-view fringe projection on a point-by-point basis. The multi-view system also achieves a high degree of surface coverage by using alternate views to access areas not measured by a single camera.

Width determination for deep grooves based on a variable point spread function imaging model.

In three-dimensional confocal microscopy, two-dimensional width measurement can be significantly influenced by the groove height. The groove height not only results in deformation of the input light field due to the effect of edge occlusions, but also introduces a defocus error to the detection plane. This paper proposes a new, to the best of our knowledge, edge-setting method to determine groove width, which engineers the point spread function to correct for the groove edge obstruction effect and develops an edge obstruction imaging model (EOIM) based on the variable point spread function. This model gives a relationship between the groove height and the normalized intensity at the groove edge and can use this relationship to determine the groove edge position that would result from focusing at the groove's lower surface. Experimental results show that an EOIM-based width determination method is more accurate than the traditional 1/4 edge-setting method. Compared to the 1/4 edge-setting method, the deviation from a reference width measured with traceable scanning electron microscopy is reduced by a factor of 2.1 with a 1.3 times smaller standard deviation.

Corrected parabolic fitting for height extraction in confocal microscopy.

Accurate and reliable peak extraction of axial response signals plays a critical role in confocal microscopy. For axial response signal processing, nonlinear fitting algorithms, such as parabolic, Gaussian or sinc2 fitting may cause significant systematic peak extraction errors. Also, existing error compensation methods require a priori knowledge of the full-width-at-half-maximum of the axial response signal, which can be difficult to obtain in practice. In this paper, we propose a generalised error compensation method for peak extraction from axial response signals. This full-width-at-half-maximum-independent method is based on a corrected parabolic fitting algorithm. With the corrected parabolic fitting algorithm, the systematic error of a parabolic fitting is characterised using a differential equation, following which, the error is estimated and compensated by solving this equation with a first-order approximation. We demonstrate, by Monte Carlo simulations and experiments with various axial response signals with symmetrical and asymmetrical forms, that the corrected parabolic fitting algorithm has significant improvements over existing algorithms in terms of peak extraction accuracy and precision.

Characterization of the displacement response in chromatic confocal microscopy with a hybrid radial basis function network.

Characterization of the displacement response is critical for accurate chromatic confocal measurement. Current characterization methods usually provide a linear or polynomial relationship between the extracted peak wavelengths of the spectral signal and displacement. However, these methods are susceptible to errors in the peak extraction algorithms and errors in the selected model. In this paper, we propose a hybrid radial basis function network method to characterise the displacement response. With this method, the peak wavelength of the spectral signal is firstly extracted with a state-of-art peak extraction algorithm, following which, a higher-accuracy chromatic dispersion model is applied to determine the displacement-wavelength relationship. Lastly, a radial basis function network is optimized to provide a mapping between the spectral signals and the residual fitting errors of the chromatic dispersion model. Using experimental tests, we show that the hybrid radial basis function network method significantly improves the measurement accuracy, when compared to the existing characterizing methods.