Delineating the heterogeneity of matrix-directed differentiation toward soft and stiff tissue lineages via single-cell profiling.

Mesenchymal stromal/stem cells (MSCs) form a heterogeneous population of multipotent progenitors that contribute to tissue regeneration and homeostasis. MSCs assess extracellular elasticity by probing resistance to applied forces via adhesion, cytoskeletal, and nuclear mechanotransducers that direct differentiation toward soft or stiff tissue lineages. Even under controlled culture conditions, MSC differentiation exhibits substantial cell-to-cell variation that remains poorly characterized. By single-cell transcriptional profiling of nonconditioned, matrix-conditioned, and early differentiating cells, we identified distinct MSC subpopulations with distinct mechanosensitivities, differentiation capacities, and cell cycling. We show that soft matrices support adipogenesis of multipotent cells and early endochondral ossification of nonadipogenic cells, whereas intramembranous ossification and preosteoblast proliferation are directed by stiff matrices. Using diffusion pseudotime mapping, we outline hierarchical matrix-directed differentiation and perform whole-genome screening of mechanoresponsive genes. Specifically, top-ranked tropomyosin-1 is highly sensitive to stiffness cues both at RNA and protein levels, and changes in TPM1 expression determine the differentiation toward soft versus stiff tissue lineage. Consistent with actin stress fiber stabilization, tropomyosin-1 overexpression maintains YAP1 nuclear localization, activates YAP1 target genes, and directs osteogenic differentiation. Knockdown of tropomyosin-1 reversed YAP1 nuclear localization consistent with relaxation of cellular contractility, suppressed osteogenesis, activated early endochondral ossification genes after 3 d of culture in induction medium, and facilitated adipogenic differentiation after 1 wk. Our results delineate cell-to-cell variation of matrix-directed MSC differentiation and highlight tropomyosin-mediated matrix sensing.

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.

Embryo classification beyond pregnancy: early prediction of first trimester miscarriage using machine learning.

PURPOSE: First trimester miscarriage is a major concern in IVF-ET treatments, accounting for one out of nine clinical pregnancies and for up to one out of three recognized pregnancies. To develop a machine learning classifier for predicting the risk of cleavage-stage embryos to undergo first trimester miscarriage based on time-lapse images of preimplantation development. METHODS: Retrospective study of a 4-year multi-center cohort of 391 women undergoing intra-cytoplasmatic sperm injection (ICSI) and fresh single or double embryo transfers. The study included embryos with positive indication of clinical implantation based on gestational sac visualization either with first trimester miscarriage or live-birth outcome. Miscarriage was determined based on negative fetal heartbeat indication during the first trimester. Data were recorded and obtained in hospital setting and research was performed in university setting. RESULTS: A minimal subset of six non-redundant morphodynamic features were screened that maintained high prediction capacity. Features that account for the distribution of the nucleolus precursor bodies within the small pronucleus and pronuclei dynamics were highly predictive of miscarriage outcome as evaluated using the SHapley Additive exPlanations (SHAP) methodology. Using this feature subset, XGBoost and random forest models were trained following a 100-fold Monte-Carlo cross validation scheme. Miscarriage was predicted with AUC 0.68 to 0.69. CONCLUSION: We report the development of a decision-support tool for identifying the embryos with high risk of miscarriage. Prioritizing embryos for transfer based on their predicted risk of miscarriage in combination with their predicted implantation potential is expected to improve live-birth rates and shorten time-to-pregnancy.

Delineating the heterogeneity of embryo preimplantation development using automated and accurate morphokinetic annotation.

PURPOSE: Our objective was to design an automated deep learning model that extracts the morphokinetic events of embryos that were recorded by time-lapse incubators. Using automated annotation, we set out to characterize the temporal heterogeneity of preimplantation development across a large number of embryos. METHODS: To perform a retrospective study, we used a dataset of video files of 67,707 embryos from four IVF clinics. A convolutional neural network (CNN) model was trained to assess the developmental states that appear in single frames from 20,253 manually-annotated embryos. Probability-weighted superposition of multiple predicted states was permitted, thus accounting for visual uncertainties. Superimposed embryo states were collapsed onto discrete series of morphokinetic events via monotonic regression of whole-embryo profiles. Unsupervised K-means clustering was applied to define subpopulations of embryos of distinctive morphokinetic profiles. RESULTS: We perform automated assessment of single-frame embryo states with 97% accuracy and demonstrate whole-embryo morphokinetic annotation with R-square 0.994. High quality embryos that had been valid candidates for transfer were clustered into nine subpopulations, as characterized by distinctive developmental dynamics. Retrospective comparative analysis of transfer versus implantation rates reveals differences between embryo clusters as marked by poor synchronization of the third mitotic cell-cleavage cycle. CONCLUSIONS: By demonstrating fully automated, accurate, and standardized morphokinetic annotation of time-lapse embryo recordings from IVF clinics, we provide practical means to overcome current limitations that hinder the implementation of morphokinetic decision-support tools within clinical IVF settings due to inter-observer and intra-observer manual annotation variations and workload constrains. Furthermore, our work provides a platform to address embryo heterogeneity using dimensionality-reduced morphokinetic descriptions of preimplantation development.

Does quantity equal quality?-A morphokinetic assessment of embryos obtained from young women with decreased ovarian response to controlled ovarian stimulation.

PURPOSE: To assess oocyte quality in young patients with decreased ovarian response to controlled ovarian stimulation using time-lapse analysis. METHODS: A retrospective cohort study conducted at five medical centers between 2013 and 2017. The "decreased ovarian response" (DOR) group consisted of 241 women who underwent controlled ovarian stimulation with ≤ 5 retrieved oocytes and 519 cultured embryos. The "normal response" (NOR) group consisted of 667 women with ≥ 6 retrieved oocytes resulting in 3633 embryos. Data included annotation of morphokinetic events of embryos cultured in a time-lapse incubator from time of pronuclei appearance to time of starting blastocyst formation (tSB). Comparison was made between morphokinetic parameters of DOR and NOR patients with additional subgroup analysis according to the implantation status. RESULTS: Implantation and clinical pregnancy rates were significantly higher in the NOR group compared with the DOR group (44.5% vs. 31.6% and 51.5% vs. 37.7%, respectively; p < 0.05). Embryos from the DOR group reached the morphokinetic milestones later than embryos obtained from NOR patients. In the DOR group, implanted embryos reached starting blastocyst formation (tSB) faster than embryos which failed to be implanted, however, manifested a protracted course compared with implanted embryos from the NOR group. In a multivariate analysis-decreased ovarian response, nulliparity, number of transferred embryos, and t4, and were predictive for implantation. CONCLUSIONS: The quantitative decrease in ovarian response is associated with reduced oocyte quality, reflected by a slower developmental rate and lower implantation and pregnancy rates.

Spherical Equivalent Prediction Analysis in IOL Power Calculations Using Eyetemis, A Comprehensive Approach.

PURPOSE: To compare two different datasets, using Eyetemis, an online analytical tool designed for assessing the spherical equivalent prediction errors (SEQ-PE) of intraocular lens (IOL) power calculation formulas following cataract surgery. SETTING: Institutional. DESIGN: Retrospective case series. METHODS: The study was comprised of two distinct datasets of patients who had undergone successful cataract surgery. Dataset-1 includes standard eyes whereas Dataset-2 includes eyes with keratoconus. An online tool was used for SEQ-PE analysis across the 2 datasets, adhering to ISO standards for evaluating accuracy based upon trueness and precision. The tool incorporates robust t-tests for comparing the trimmed-mean of the data, adjusting for heteroscedasticity. IOL constants in Dataset-1 were optimized for the comparison of Hoffer Q, Holladay1, SRK/T, Haigis and Barrett Universal II (BUII) formulas. In Dataset-2, IOL constants from the IOLCon website, were used for the comparison of the BUII and its designated KCN-version: Barrett TrueK Keratoconus (TrueK [KCN]). RESULTS: For Dataset-1: the trimmed-mean SEQ-PE values of all formulas were not significantly different from zero. BUII had superior precision and accuracy compared to all other formulas except from Haigis (P≤ 0.04). For Dataset-2: BUII's trimmed-mean SEQ-PE was significantly different from zero (0.59D, P< 0.01), unlike the TrueK [KCN] (0.12D, P= 0.10). Additionally, TrueK [KCN] exhibited enhanced precision and accuracy relative to BUII (P< 0.01). CONCLUSIONS: The online analysis tool provides a streamlined approach for assessing the prediction accuracy of SEQ refraction following cataract surgery, effectively evaluating trueness, precision, and overall accuracy through the use of advanced statistical methods.

Comparison of Intraocular Lens Power Prediction Accuracy Between 2 Swept-Source Optical Coherence Tomography Biometry Devices.

PURPOSE: To compare intraocular lens (IOL) power prediction accuracy of the Eyestar 900 (EyeS900) and the IOLMaster 700 (IOLM700) based on estimated and measured posterior corneal power. DESIGN: Retrospective, interinstrument reliability study. METHODS: Setting: Institutional. PARTICIPANTS: Two hundred twenty-five eyes of 225 cataract surgery patients. MEASUREMENTS: Patients underwent measurements by both devices preoperatively. MAIN OUTCOME MEASURES: Spherical Equivalent Prediction Error (SEQ-PE), spread of the SEQ-PE (precision) and the absolute SEQ-PE (accuracy) of each device using Barrett Universal II (BUII) formula with either estimated posterior keratometry (E-PK) or measured posterior keratometry (M-PK). RESULTS: Trimmed mean SEQ-PEs of EyeS900 E-PK, EyeS900 M-PK, IOLM700 E-PK, and IOLM700 M-PK were 0.03, 0.08, 0.02, and 0.09 D, respectively with no significant differences between EyeS900 E-PK and IOLM700 E-PK (P = 0.31) as well as between EyeS900 M-PK and IOLM700 M-PK (P = 0.31). Statistically significant SEQ-PE differences were found when E-PK and M-PK were compared, regardless of the device used, showing hyperopic SEQ-PE in M-PK calculations. Excellent correlation and agreement in SEQ-PE were found between the devices for both E-PK (P < 0.001, r = 0.848, mean bias: +0.01 D, 95% LOA of -0.32 to +0.34 D) and M-PK (P < 0.001, r = 0.776, mean bias: -0.01 D, 95% LOA of -0.42 to +0.39 D). No significant differences were found comparing absolute SEQ-PE and precision of the devices. CONCLUSION: The Eyestar 900 and the IOLMaster 700 show comparable IOL power prediction accuracy by the BUII formula using either estimated or measured posterior keratometry. An adjusted lens factor may be required for BUII when utilizing measured posterior keratometry in both devices.

Comparing the efficacy of anti-seizure medications using matched cohorts on a large insurance claims database.

Epilepsy is a severe chronic neurological disease affecting 60 million people worldwide. Primary treatment is with anti-seizure medicines (ASMs), but many patients continue to experience seizures. We used retrospective insurance claims data on 280,587 patients with uncontrolled epilepsy (UE), defined as status epilepticus, need for a rescue medicine, or admission or emergency visit for an epilepsy code. We conducted a computational risk ratio analysis between pairs of ASMs using a causal inference method, in order to match 1034 clinical factors and simulate randomization. Data was extracted from the MarketScan insurance claims Research Database records from 2011 to 2015. The cohort consisted of individuals over 18 years old with a diagnosis of epilepsy who took one of eight ASMs and had more than a year of history prior to the filling of the drug prescription. Seven ASM exposures were analyzed: topiramate, phenytoin, levetiracetam, gabapentin, lamotrigine, valproate, and carbamazepine or oxcarbazepine (treated as the same exposure). We calculated the risk ratio of UE between pairs of ASM after controlling for bias with inverse propensity weighting applied to 1034 factors, such as demographics, confounding illnesses, non-epileptic conditions treated by ASMs, etc. All ASMs exhibited a significant reduction in the prevalence of UE, but three drugs showed pair-wise differences compared to other ASMs. Topiramate consistently was associated with a lower risk of UE, with a mean risk ratio range of 0.68-0.93 (average 0.82, CI: 0.56-1.08). Phenytoin and levetiracetam were consistently associated with a higher risk of UE with mean risk ratio ranges of 1.11 to 1.47 (average 1.13, CI 0.98-1.65) and 1.15 to 1.43 (average 1.2, CI 0.72-1.69), respectively. Large-scale retrospective insurance claims data - combined with causal inference analysis - provides an opportunity to compare the effect of treatments in real-world data in populations 1,000-fold larger than those in typical randomized trials. Our causal analysis identified the clinically unexpected finding of topiramate as being associated with a lower risk of UE; and phenytoin and levetiracetam as associated with a higher risk of UE (compared to other studied drugs, not to baseline). However, we note that our data set for this study only used insurance claims events, which does not comprise actual seizure frequencies, nor a clear picture of side effects. Our results do not advocate for any change in practice but demonstrate that conclusions from large databases may differ from and supplement those of randomized trials and clinical practice and therefore may guide further investigation.

Accuracy of Toric Intraocular Lens Calculations Using Estimated Versus Measured Posterior Corneal Astigmatism.

PURPOSE: To compare the prediction accuracy of toric intraocular lens calculations using estimated vs measured posterior corneal astigmatism (PCA). DESIGN: Retrospective case series. METHODS: A total of 110 eyes of 110 patients with uncomplicated toric intraocular lens implantation were included in this study. Predicted postoperative refractive astigmatism was calculated with the Barrett Toric Calculator using the estimated PCA (E-PCA), the measured IOLMaster 700 PCA (I-PCA), and the measured Pentacam PCA (P-PCA). Refractive astigmatism prediction errors (RA-PEs), including their trimmed (tr-) centroid (mean vector), spread (precision), tr-mean absolute RA-PE (accuracy), and percentage within a certain threshold, were determined using vector analysis and compared between groups. SETTING: University Eye Clinic, Maastricht University Medical Center+, the Netherlands. RESULTS: The tr-centroid RA-PEs of the E-PCA (0.02 diopter [D] at 82.2°), the I-PCA (0.08 D at 35.5°), and the P-PCA (0.09 D at 69.1°) were significantly different from each other (P < .01), but not significantly different from zero (P = .75, P = .05, and P = .05, respectively). The E-PCA had the best precision (tr-mean 0.40 D), which was not significantly lower than the I-PCA (0.42 D, P = .53) and P-PCA (0.43 D, P = .06). The E-PCA also had the best accuracy (0.40 D), which was not significantly different from the I-PCA (0.42 D, P = .26) and significantly better than the P-PCA (0.44 D, P < .01). The precision and accuracy of the I-PCA did not significantly differ from those of the P-PCA. There were no statistically significant differences in the percentage of eyes within a certain absolute RA-PE threshold. CONCLUSIONS: The Barrett Toric Calculator using the E-PCA, I-PCA, or P-PCA showed a comparable prediction of postoperative refractive astigmatism in standard clinical practice.

Measured Corneal Astigmatism Versus Pseudophakic Predicted Refractive Astigmatism in Cataract Surgery Candidates.

PURPOSE: To compare standard and total corneal astigmatism measurements to the predicted pseudophakic (nontoric) refractive astigmatism in candidates for cataract surgery. DESIGN: A retrospective, cross-sectional study. METHODS: A single-center analysis of consecutive eyes measured with a swept-source optical coherence tomography biometer at a large tertiary medical center between February 2018 and June 2020. Corneal astigmatism was calculated based on standard keratometry astigmatism (KA), total corneal astigmatism (TCA), and predicted refractive astigmatism (PRA) for a monofocal nontoric intraocular lens (IOL) implantation calculated by the Barrett toric calculator using the predicted posterior corneal astigmatism (PRA(Predicted-PCA)) and the measured posterior corneal astigmatism (PRA(Measured-PCA)) options. Separate analyses were performed for each eye. SETTING: Ophthalmology Department, Shaare Zedek Medical Center, Jerusalem, Israel. RESULTS: In total, 8152 eyes of 5320 patients (4221 right eyes [OD] and 3931 left eyes [OS], mean age 70.6±12.2 years, 54.2% females) were included in the study. The mean vector values (centroid) for KA, TCA, PRA(Predicted-PCA), and PRA(Measured-PCA) were 0.07 diopters [D] at 19.5°, 0.27 D at 7.5°, 0.44 D at 2.9°, and 0.43 D at 179.3°, respectively (P < .01), for OD and 0.02 D at 150.3°, 0.23 D at 169.7°, 0.40 D at 179.4°, and 0.42 D at 169.5°, respectively (P < .01), for OS. More than 73% of eyes had a PRA >0.5 D. CONCLUSIONS: Standard and total corneal astigmatism measurements differ significantly from the PRA by the Barrett toric calculator. The PRA, rather than the KA or TCA, should be used as the reference guide for astigmatism correction with toric IOL implantation.

Measuring pupil size and light response through closed eyelids.

Monitoring pupillary size and light-reactivity is a key component of the neurologic assessment in comatose patients after stroke or brain trauma. Currently, pupillary evaluation is performed manually at a frequency often too low to ensure timely alert for irreversible brain damage. We present a novel method for monitoring pupillary size and reactivity through closed eyelids. Our method is based on side illuminating in near-IR through the temple and imaging through the closed eyelid. Successfully tested in a clinical trial, this technology can be implemented as an automated device for continuous pupillary monitoring, which may save staff resources and provide earlier alert to potential brain damage in comatose patients.

Does sperm origin-Ejaculated or testicular-Affect embryo morphokinetic parameters?

BACKGROUND: It is unclear whether sperm origin, either ejaculated or testicular, in couples diagnosed with male factor infertility, affects the timing of the embryo's developmental events evaluated by time-lapse monitoring and implantation rates. OBJECTIVE: To examine the effect of sperm origin on embryo morphokinetics in couples diagnosed with male factor infertility. MATERIALS AND METHODS: This study included a retrospective analysis of morphokinetic parameters performed by time-lapse monitoring between 2013 and 2017. The developmental processes and morphokinetic parameters of 419 embryos obtained from couples with male factor infertility attributed to oligo-astheno-teratozoospermia, 158 embryos derived from surgically extracted testicular spermatozoa from couples diagnosed with non-obstructive azoospermia, and 190 embryos from couples with normal ejaculated spermatozoa and female mechanical factor-related infertility, were evaluated. A comparison of morphokinetic parameters, implantation, and clinical pregnancy rates was performed between the groups with additional analysis in accordance with implantation status. RESULTS: Embryos from the normal ejaculated spermatozoa and oligo-astheno-teratozoospermia patients reached the later morphokinetic milestones-synchronous division (S3) and time to morula (tM)-faster than embryos obtained from testicular spermatozoa. Implantation rate was similar in the normal ejaculated spermatozoa and oligo-astheno-teratozoospermia groups (41.9% vs. 45.8%, NS), with higher implantation rate in the oligo-astheno-teratozoospermia group compared to the testicular spermatozoa group (45.8% vs. 33.6%, p = 0.02). Comparison of Known Implantation Data (KID) positive (KIDp) and KID negative (KIDn) embryos in each group revealed more rapid development in KIDp embryos in the normal ejaculated spermatozoa and the oligo-astheno-teratozoospermia groups, while in the testicular spermatozoa group implanted embryos reached the late morphokinetic milestones (time to 8 cell stage-t8, ECC3, S3, and tM) significantly faster than embryos that failed to implant. In a multivariate logistic regression analysis of the male factor infertility population, (oligo-astheno-teratospermia) (OR = 2.54, p = 0.003) and t8 (OR = 0.95, p = 0.027) were predictive of successful implantation. Male factor infertility embryos that reached the t8 milestone within 48-56 h had favorable implantation rates (p < 0.001). DISCUSSION: The study results may highlight another pathophysiology by means of which sperm origin affects embryo developmental kinetics. Selecting embryos demonstrating a faster developmental rate at t8 and specifically the 48- to 56 h interval following time of pronuclei fading (tPNf) may improve implantation rates in cases of male factor infertility. CONCLUSION: This study showed that ejaculated spermatozoa is associated with faster late cell divisions, more rapid compaction, and higher implantation rates compared to testicular spermatozoa. Additionally, t8 is an important predictor for implantation in the male factor infertility population.