Evaluating the heterogeneous effect of extended culture to blastocyst transfer on the implantation outcome via causal inference in fresh ICSI cycles.

PURPOSE: In IVF treatments, extended culture to single blastocyst transfer is the recommended protocol over cleavage-stage transfer. However, evidence-based criteria for assessing the heterogeneous implications on implantation outcomes are lacking. The purpose of this work is to estimate the causal effect of blastocyst transfer on implantation outcome. METHODS: We fit a causal forest model using a multicenter observational dataset that includes an exogenous source of variability in treatment assignment and has a strong claim for satisfying the assumptions needed for valid causal inference from observational data. RESULTS: We quantified the probability difference in embryo implantation if transferred as a blastocyst versus cleavage stage. Blastocyst transfer increased the average implantation rate; however, we revealed a subpopulation of embryos whose implantation potential is predicted to increase via cleavage-stage transfer. CONCLUSION: Relative to the current policy, the proposed embryo transfer policy retrospectively improves implantation rate from 0.2 to 0.27. Our work demonstrates the efficacy of implementing causal inference in reproductive medicine and motivates its utilization in medical disciplines that are dominated by retrospective datasets.

Development, Validation, and Evaluation of the Pediatric Inflammatory Crohn's Magnetic Resonance Enterography Index From the ImageKids Study.

BACKGROUND & AIMS: Cross-sectional imaging is important in the assessment of transmural inflammation in Crohn's disease (CD). Small bowel involvement is often more extensive in pediatric CD, requiring a panentering measuring tool. We undertook to develop a magnetic resonance enterography (MRE)-based index that would measure inflammation in all segments of the intestine, without rectal contrast. METHODS: Children with CD underwent ileocolonoscopy and MRE and half were prospectively followed for 18 months when MRE was repeated. Item generation and reduction were performed by a Delphi panel of pediatric radiologists, a systematic literature review, a cross-sectional study of 48 MREs, and a steering committee. Formatting and weighting were performed using multivariate modeling adjusted by a steering committee. MREs were read locally and centrally. Reliability, validity, and responsiveness were determined using several clinimetric and psychometric approaches. RESULTS: Thirty items were initially generated and reduced to 5 using regression analysis on 159 MREs: wall thickness, wall diffusion weighted imaging, ulcerations, mesenteric edema, and comb sign. In the validation cohort of 81 MREs, the weighted global PICMI correlated well with the radiologist global assessment (r = 0.85; P < .001) and with the simple endoscopic score in a subsample with ileocolonic disease (r = 0.63; P < .001). Interobserver and test-retest reliability were high (interclass correlation coefficients, 0.84; 95% confidence interval [CI], 0.79-0.87; and 0.81, 95% CI, 0.65-0.90, respectively; both P < .001). Excellent responsiveness was found at repeated visits (n = 116 MREs; area under the receiver operating characteristic curve 0.96; 95% CI, 0.93-0.99). Transmural healing was defined as PICMI ≤10 and response as a change of >20 points with excellent discriminative validity (area under the receiver operating characteristic curve = 0.96; 95% CI, 0.93-0.99). CONCLUSIONS: The PICMI is a valid, reliable, and responsive index for assessing transmural inflammation in pediatric CD. It scores the entire bowel length and does not require intravenous contrast or rectal enema and, therefore, is suitable for use in children. (ClinicalTrials.gov, Number: NCT01881490.).

Local conformal autoencoder for standardized data coordinates.

We propose a local conformal autoencoder (LOCA) for standardized data coordinates. LOCA is a deep learning-based method for obtaining standardized data coordinates from scientific measurements. Data observations are modeled as samples from an unknown, nonlinear deformation of an underlying Riemannian manifold, which is parametrized by a few normalized, latent variables. We assume a repeated measurement sampling strategy, common in scientific measurements, and present a method for learning an embedding in [Formula: see text] that is isometric to the latent variables of the manifold. The coordinates recovered by our method are invariant to diffeomorphisms of the manifold, making it possible to match between different instrumental observations of the same phenomenon. Our embedding is obtained using LOCA, which is an algorithm that learns to rectify deformations by using a local z-scoring procedure, while preserving relevant geometric information. We demonstrate the isometric embedding properties of LOCA in various model settings and observe that it exhibits promising interpolation and extrapolation capabilities, superior to the current state of the art. Finally, we demonstrate LOCA's efficacy in single-site Wi-Fi localization data and for the reconstruction of three-dimensional curved surfaces from two-dimensional projections.

Near-optimal matrix recovery from random linear measurements.

In matrix recovery from random linear measurements, one is interested in recovering an unknown M-by-N matrix [Formula: see text] from [Formula: see text] measurements [Formula: see text], where each [Formula: see text] is an M-by-N measurement matrix with i.i.d. random entries, [Formula: see text] We present a matrix recovery algorithm, based on approximate message passing, which iteratively applies an optimal singular-value shrinker-a nonconvex nonlinearity tailored specifically for matrix estimation. Our algorithm typically converges exponentially fast, offering a significant speedup over previously suggested matrix recovery algorithms, such as iterative solvers for nuclear norm minimization (NNM). It is well known that there is a recovery tradeoff between the information content of the object [Formula: see text] to be recovered (specifically, its matrix rank r) and the number of linear measurements n from which recovery is to be attempted. The precise tradeoff between r and n, beyond which recovery by a given algorithm becomes possible, traces the so-called phase transition curve of that algorithm in the [Formula: see text] plane. The phase transition curve of our algorithm is noticeably better than that of NNM. Interestingly, it is close to the information-theoretic lower bound for the minimal number of measurements needed for matrix recovery, making it not only state of the art in terms of convergence rate, but also near optimal in terms of the matrices it successfully recovers.

Fecal Markers of Inflammation and Disease Activity in Pediatric Crohn Disease: Results from the ImageKids Study.

BACKGROUND: Noninvasive and accurate methods to monitor inflammatory bowel disease are required. As a planned ancillary study of the prospective ImageKids cohort, we aimed to assess the performance of fecal calprotectin (FC) with comparison to 3 fecal inflammatory markers; S100A12 (FA12), tumor pyruvate kinase isoenzyme type M2 (FM2PK) and fecal osteoprotegerin (FOPG) as indicators of a number of disease characteristics. METHODS: The ImageKids study was a multicenter study designed to develop 2 magnetic resonance enterography-based measures for children with Crohn disease (6-18 years old). All patients underwent magnetic resonance enterography, a complete ileocolonoscopic evaluation and provided a fecal sample. Fecal samples were assay for FC, FA12, FM2PK, and FOPG by ELISA. RESULTS: One-hundred fifty-six children provided 190 fecal samples. Median (interquartile range) for fecal makers were FC, 602 (181-1185) µg/g; FA12, 21 (3-109) µg/g; FM2PK, 16 (2-20) U/mL; and FOPG, 125 (125-312) µg/g. All markers correlated with simple endoscopic severity index for Crohn disease and with other constructs of disease activity, but FC had the highest overall correlations. FA12, however, predicted mucosal healing with significantly higher specificity (87% vs 70%, P = 0.004) and equivalent sensitivity (91% vs 90%) compared to FC. CONCLUSION: This study has confirmed that FC is useful, and overall best, marker to monitor mucosal inflammation in inflammatory bowel disease. FA12, however, appears to be a more suitable maker for prediction of mucosal healing in children.

Random subsets of structured deterministic frames have MANOVA spectra.

We draw a random subset of [Formula: see text] rows from a frame with [Formula: see text] rows (vectors) and [Formula: see text] columns (dimensions), where [Formula: see text] and [Formula: see text] are proportional to [Formula: see text] For a variety of important deterministic equiangular tight frames (ETFs) and tight non-ETFs, we consider the distribution of singular values of the [Formula: see text]-subset matrix. We observe that, for large [Formula: see text], they can be precisely described by a known probability distribution-Wachter's MANOVA (multivariate ANOVA) spectral distribution, a phenomenon that was previously known only for two types of random frames. In terms of convergence to this limit, the [Formula: see text]-subset matrix from all of these frames is shown to be empirically indistinguishable from the classical MANOVA (Jacobi) random matrix ensemble. Thus, empirically, the MANOVA ensemble offers a universal description of the spectra of randomly selected [Formula: see text] subframes, even those taken from deterministic frames. The same universality phenomena is shown to hold for notable random frames as well. This description enables exact calculations of properties of solutions for systems of linear equations based on a random choice of [Formula: see text] frame vectors of [Formula: see text] possible vectors and has a variety of implications for erasure coding, compressed sensing, and sparse recovery. When the aspect ratio [Formula: see text] is small, the MANOVA spectrum tends to the well-known Marcenko-Pastur distribution of the singular values of a Gaussian matrix, in agreement with previous work on highly redundant frames. Our results are empirical, but they are exhaustive, precise, and fully reproducible.

Simple Endoscopic Score of Crohn Disease and Magnetic Resonance Enterography in Children: Report From ImageKids Study.

OBJECTIVES: We aimed to explore the ability of magnetic resonance enterography (MRE) to impute the simple endoscopic score of Crohn disease (SES-CD) in children with CD, in whom failure of ileal intubation is common and may impair SES-CD calculation in clinical studies. METHODS: This is a substudy of the prospective ImageKids study in which children with CD underwent ileocolonoscopy (scored by SES-CD) and MRE (scored on a 100 mm visual analogue scale [VAS] and by MaRIA). Mucosal healing (MH) was defined as SES-CD <3, MRE-VAS <20 mm, and/or MaRIA <7. RESULTS: A total of 237 children (22 centers, age 11.5 ±â€Š3.3 years), were enrolled. Ileal intubation has failed in 40 of 237 (17%). The agreement between SES-CD and MRE was 75% (k = 0.508, P < 0.001) in the ileum, and 68% to 85% in the colonic segments (k = 0.21-0.50, P < 0.001). The sensitivity and specificity of ileal MRE-VAS for MH were 91.7% (95% confidence interval 0.84-0.96) and 53.1% (95% confidence interval 0.43-0.63), respectively. The ileal MaRIA score (calculated in 33/40) was higher in the children without ileal intubation than in the others (20.5 ±â€Š7.1 vs 15.1 ±â€Š10.8, respectively, P = 0.0018). In 7% (16/237) of children, isolated active ileal disease would have been missed when considering SES-CD only. A multivariable model predicted the ileal SES-CD subscore from the MaRIA: SES-CDileum = 1.145 + 0.169 × MaRIAileum rounded to the nearest whole number (R = 0.17). Applying this model to the children without ileal intubation revealed that 29 of 33 (88%) had ileal disease; 8 of 29 patients (28%) with normal colonic SES-CD had imputed ileal SES-CD ≥3. CONCLUSIONS: MRE is useful for imputing the ileal disease in pediatric clinical studies, overcoming the problem of ileal nonintubation.

Optimal Shrinkage of Eigenvalues in the Spiked Covariance Model.

We show that in a common high-dimensional covariance model, the choice of loss function has a profound effect on optimal estimation. In an asymptotic framework based on the Spiked Covariance model and use of orthogonally invariant estimators, we show that optimal estimation of the population covariance matrix boils down to design of an optimal shrinker η that acts elementwise on the sample eigenvalues. Indeed, to each loss function there corresponds a unique admissible eigenvalue shrinker η* dominating all other shrinkers. The shape of the optimal shrinker is determined by the choice of loss function and, crucially, by inconsistency of both eigenvalues and eigenvectors of the sample covariance matrix. Details of these phenomena and closed form formulas for the optimal eigenvalue shrinkers are worked out for a menagerie of 26 loss functions for covariance estimation found in the literature, including the Stein, Entropy, Divergence, Fréchet, Bhattacharya/Matusita, Frobenius Norm, Operator Norm, Nuclear Norm and Condition Number losses.

The phase transition of matrix recovery from Gaussian measurements matches the minimax MSE of matrix denoising.

Let X(0) be an unknown M by N matrix. In matrix recovery, one takes n < MN linear measurements y(1),…,y(n) of X(0), where y(i) = Tr(A(T)iX(0)) and each A(i) is an M by N matrix. A popular approach for matrix recovery is nuclear norm minimization (NNM): solving the convex optimization problem min ||X||*subject to y(i) =Tr(A(T)(i)X) for all 1 ≤ i ≤ n, where || · ||* denotes the nuclear norm, namely, the sum of singular values. Empirical work reveals a phase transition curve, stated in terms of the undersampling fraction δ(n,M,N) = n/(MN), rank fraction ρ=rank(X0)/min {M,N}, and aspect ratio ß=M/N. Specifically when the measurement matrices Ai have independent standard Gaussian random entries, a curve δ*(ρ) = δ*(ρ;ß) exists such that, if δ > δ*(ρ), NNM typically succeeds for large M,N, whereas if δ < δ*(ρ), it typically fails. An apparently quite different problem is matrix denoising in Gaussian noise, in which an unknown M by N matrix X(0) is to be estimated based on direct noisy measurements Y =X(0) + Z, where the matrix Z has independent and identically distributed Gaussian entries. A popular matrix denoising scheme solves the unconstrained optimization problem min|| Y-X||(2)(F)/2+λ||X||*. When optimally tuned, this scheme achieves the asymptotic minimax mean-squared error M(ρ;ß) = lim(M,N → ∞)inf(λ)sup(rank(X) ≤ ρ · M)MSE(X,X(λ)), where M/N → . We report extensive experiments showing that the phase transition δ*(ρ) in the first problem, matrix recovery from Gaussian measurements, coincides with the minimax risk curve M(ρ)=M(ρ;ß) in the second problem, matrix denoising in Gaussian noise: δ*(ρ)=M(ρ), for any rank fraction 0 < ρ < 1 (at each common aspect ratio ß). Our experiments considered matrices belonging to two constraint classes: real M by N matrices, of various ranks and aspect ratios, and real symmetric positive-semidefinite N by N matrices, of various ranks.

Deterministic matrices matching the compressed sensing phase transitions of Gaussian random matrices.

In compressed sensing, one takes samples of an N-dimensional vector using an matrix A, obtaining undersampled measurements Y = Ax(0). For random matrices with independent standard Gaussian entries, it is known that, when is k-sparse, there is a precisely determined phase transition: for a certain region in the (k/n,n/N)-phase diagram, convex optimization typically finds the sparsest solution, whereas outside that region, it typically fails. It has been shown empirically that the same property--with the same phase transition location--holds for a wide range of non-Gaussian random matrix ensembles. We report extensive experiments showing that the Gaussian phase transition also describes numerous deterministic matrices, including Spikes and Sines, Spikes and Noiselets, Paley Frames, Delsarte-Goethals Frames, Chirp Sensing Matrices, and Grassmannian Frames. Namely, for each of these deterministic matrices in turn, for a typical k-sparse object, we observe that convex optimization is successful over a region of the phase diagram that coincides with the region known for Gaussian random matrices. Our experiments considered coefficients constrained to X(N) for four different sets X [symbol: see text]{[0, 1], R(=), R, C}, and the results establish our finding for each of the four associated phase transitions.

Development and Validation of a Pediatric MRI-Based Perianal Crohn Disease (PEMPAC) Index-A Report from the ImageKids Study.

BACKGROUND: As part of the prospective multicenter ImageKids study, we aimed to develop and validate the pediatric MRI-based perianal Crohn disease (PEMPAC) index. METHODS: Children with Crohn disease with any clinical perianal findings underwent pelvic magnetic resonance imaging at 21 sites globally. The site radiologist and 2 central radiologists provided a radiologist global assessment (RGA) on a 100 mm visual analog scale and scored the items selected by a Delphi group of 35 international radiologists and a review of the literature. Two weighted multivariable statistical models were constructed against the RGA. RESULTS: Eighty children underwent 95 pelvic magnetic resonance imaging scans; 64 were used for derivation and 31 for validation. The following items were included: fistula number, location, length and T2 hyperintensity; abscesses; rectal wall involvement; and fistula branching. The last 2 items had negative beta scores and thus were excluded in a contending basic model. In the validation cohort, the full and the basic models had the same strong correlation with the RGA (r = 0.75; P < 0.01) and with the adult Van Assche index (VAI; r = 0.93 and 0.92; P < 0.001). The correlation of the VAI with the RGA was similar (r = 0.77; P < 0.01). The 2 models and the VAI had a similar ability to differentiate remission from active disease (area under the receiver operating characteristic curve, 0.91-0.94). The PEMPAC index had good responsiveness to change (area under the receiver operating characteristic curve, 0.89; 95% confidence interval, 0.69-1.00). CONCLUSIONS: Using a blended judgmental and mathematical approach, we developed and validated an index for quantifying the severity of perianal disease in children with CD. The adult VAI may also be used with confidence in children.

The Association of Inflammatory Bowel Diseases with Autoimmune Disorders: A Report from the epi-IIRN.

BACKGROUND AND AIMS: There are conflicting data on the association between inflammatory bowel diseases [IBD] and autoimmunity disorders. The aim of this study was to explore this association including the effect of medications. METHODS: We utilized health administrative data collected by three of the four health maintenance organizations [HMOs] in Israel, covering 52% of the country's population. We explored the prevalence of the following autoimmune disorders: insulin-dependent diabetes mellitus [IDDM], psoriasis, Sjögren syndrome, coeliac disease, systemic lupus erythematosus [SLE], primary sclerosis cholangitis [PSC] and autoimmune thyroiditis, among all IBD patients vs non-IBD controls. Case ascertainment was determined according to validated computerized algorithms. RESULTS: In total, 12625 IBD patients were compared to 12625 controls. A total of 1395 [11.1%] IBD patients had at least one autoimmune disease compared with 740 [5.9%] of non-IBD controls (odds ratio [OR] = 1.99 [95% confidence interval 1.81-2.19]; p < 0.05); all autoimmune diseases, except for thyroiditis, were more prevalent among IBD patients. Adjusted for confounding variables, anti-tumour necrosis factor [anti-TNF] medications were associated with a higher prevalence of psoriasis (54 [5.7%] in IBD vs 177 [4.1%] in controls; OR = 1.50 [1.07-2.08]; p < 0.05) but lower prevalence of Sjögren (1 [0.1%] vs 39 [0.9%]; OR [95% CI] = 0.13 [0.02-0.94]; p < 0.05) and coeliac disease (11 [1.2%] vs 68 [1.6%]; OR [95% CI] = 0.51 [0.27-0.99]; p < 0.05). Thiopurines and 5-aminosalicylates were not associated with any autoimmune disorder. CONCLUSION: IBD is associated with all autoimmune diseases explored here except for thyroiditis. Anti-TNF users have a higher prevalence of psoriasis, and lower prevalence of Sjögren and coeliac disease.

Genetic code symmetry and efficient design of GC-constrained coding sequences.

MOTIVATION: Cloning of long DNA sequences (40-60 bases) into phage display libraries using polymerase chain reaction (PCR) is a low efficiency process, in which PCR is used to incorporate a DNA insert, coding for a certain peptide, into the amplified sequence. The PCR efficiency in this process is strongly affected by the distribution of G-C bases in the amplified sequence. As any DNA insert coding for the target peptide may be attempted, there is a flexibility in choosing part of the amplified sequence. Since the number of inserts coding for the same peptide is exponential in the peptide length, a computational problem naturally arises--that of efficiently finding an insert, whose parameters are optimal for PCR cloning. RESULTS: The GC distribution requirements are formulated as a search problem. We developed an efficient, linear time 'one pass' algorithm for this problem. Interestingly, our algorithm strongly relies on an interesting symmetry, which we observed in the standard genetic code. Most non-standard genetic codes examined possess this symmetry as well, yet some do not. We generalize the search problem and consider the case of a non-standard, or arbitrary, genetic code where this symmetry does not necessary hold. We solve the generalized problem in polynomial, but nonlinear, time. AVAILABILITY: An implementation of the proposed algorithm is available upon request from the authors.