Structural characterization of an intrinsically disordered protein complex using integrated small-angle neutron scattering and computing.

Characterizing structural ensembles of intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) of proteins is essential for studying structure-function relationships. Due to the different neutron scattering lengths of hydrogen and deuterium, selective labeling and contrast matching in small-angle neutron scattering (SANS) becomes an effective tool to study dynamic structures of disordered systems. However, experimental timescales typically capture measurements averaged over multiple conformations, leaving complex SANS data for disentanglement. We hereby demonstrate an integrated method to elucidate the structural ensemble of a complex formed by two IDRs. We use data from both full contrast and contrast matching with residue-specific deuterium labeling SANS experiments, microsecond all-atom molecular dynamics (MD) simulations with four molecular mechanics force fields, and an autoencoder-based deep learning (DL) algorithm. From our combined approach, we show that selective deuteration provides additional information that helps characterize structural ensembles. We find that among the four force fields, a99SB-disp and CHARMM36m show the strongest agreement with SANS and NMR experiments. In addition, our DL algorithm not only complements conventional structural analysis methods but also successfully differentiates NMR and MD structures which are indistinguishable on the free energy surface. Lastly, we present an ensemble that describes experimental SANS and NMR data better than MD ensembles generated by one single force field and reveal three clusters of distinct conformations. Our results demonstrate a new integrated approach for characterizing structural ensembles of IDPs.

Evaluating the utility of a global webinar for mentoring medical students and OBGYN residents in REI.

BACKGROUND: In medical school and residency, clinical experiences influence trainee's decisions on what medical specialty they choose. Most trainees have limited access to opportunities to engage in the field of reproductive endocrinology and infertility (REI). Due to the COVID-19 pandemic and the shutdown of away electives, exposure to REI was especially limited. This study aims to evaluate the effectiveness of a live Q and A webinar on improving trainees' access to mentorship and knowledge of the path to becoming a reproductive endocrinology and infertility (REI) physician. MATERIALS AND METHODS: This study is a prospective paired cohort study. Medical students and OBGYN residents participated in a global Q and A webinar featuring REI physicians and fellows. 70 pre- and post-webinar surveys were included in the analysis. Paired nonparametric tests (Wilcoxon signed-rank test) were performed to assess whether post-webinar knowledge was significantly different from pre-webinar knowledge. RESULTS: Of the 268 registrants, 162 (60%) attended the live webinar. A majority of the respondents who completed both surveys were female (90%) and allopathic medical students (80%). Seventy-seven percent reported receiving only minimal advice about an REI career from their medical school or residency program, while 22% reported receiving some advice, and 1% extensive advice. Thirty-four percent had previously shadowed an REI physician and 23% had rotated in an REI office. Post-webinar significantly more trainees had a better understanding of the REI field, the path required to become an REI physician, opportunities to find mentors in the field, opportunities that are conducive to learning more about REI, and applying for rotations in the REI field (p = <.00001). Eighty-two percent agreed that their interest in REI increased due to this webinar. CONCLUSIONS: A webinar featuring REI physicians and fellows was effective in providing mentorship and career advisement for prospective REI trainees who otherwise expressed having limited access to the field.

Understanding interactions between biomolecules and two-dimensional nanomaterials using in silico microscopes.

Two-dimensional (2D) nanomaterials such as graphene are increasingly used in research and industry for various biomedical applications. Extensive experimental and theoretical studies have revealed that 2D nanomaterials are promising drug delivery vehicles, yet certain materials exhibit toxicity under biological conditions. So far, it is known that 2D nanomaterials possess strong adsorption propensities for biomolecules. To mitigate potential toxicity and retain favorable physical and chemical properties of 2D nanomaterials, it is necessary to explore the underlying mechanisms of interactions between biomolecules and nanomaterials for the subsequent design of biocompatible 2D nanomaterials for nanomedicine. The purpose of this review is to integrate experimental findings with theoretical observations and facilitate the study of 2D nanomaterial interaction with biomolecules at the molecular level. We discuss the current understanding and progress of 2D nanomaterial interaction with proteins, lipid membranes, and DNA based on molecular dynamics (MD) simulation. In this review, we focus on the 2D graphene nanosheet and briefly discuss other 2D nanomaterials. With the ever-growing computing power, we can image nanoscale processes using MD simulation that are otherwise not observable in experiment. We expect that molecular characterization of the complex behavior between 2D nanomaterials and biomolecules will help fulfill the goal of designing effective 2D nanomaterials as drug delivery platforms.

Application of Machine Learning Techniques to an Agent-Based Model of Pantoea.

Agent-based modeling (ABM) is a powerful simulation technique which describes a complex dynamic system based on its interacting constituent entities. While the flexibility of ABM enables broad application, the complexity of real-world models demands intensive computing resources and computational time; however, a metamodel may be constructed to gain insight at less computational expense. Here, we developed a model in NetLogo to describe the growth of a microbial population consisting of Pantoea. We applied 13 parameters that defined the model and actively changed seven of the parameters to modulate the evolution of the population curve in response to these changes. We efficiently performed more than 3,000 simulations using a Python wrapper, NL4Py. Upon evaluation of the correlation between the active parameters and outputs by random forest regression, we found that the parameters which define the depth of medium and glucose concentration affect the population curves significantly. Subsequently, we constructed a metamodel, a dense neural network, to predict the simulation outputs from the active parameters and found that it achieves high prediction accuracy, reaching an R 2 coefficient of determination value up to 0.92. Our approach of using a combination of ABM with random forest regression and neural network reduces the number of required ABM simulations. The simplified and refined metamodels may provide insights into the complex dynamic system before their transition to more sophisticated models that run on high-performance computing systems. The ultimate goal is to build a bridge between simulation and experiment, allowing model validation by comparing the simulated data to experimental data in microbiology.

Evolution of Thyroglobulin Loop Kinetics in EpCAM.

Epithelial cell-activating molecule (EpCAM) is an important cancer biomarker and therapeutic target given its elevated expression in epithelial cancers. EpCAM is a type I transmembrane protein that forms cis-dimers along the thyroglobulin type-1A-like domain (TYD) in the extracellular region. The thyroglobulin loop (TY loop) within the TYD is structurally dynamic in the monomer state of human EpCAM, binding reversibly to a TYD site. However, it is not known if this flexibility is prevalent across different species. Here, we conduct over 17 µs of all-atom molecular dynamics simulations to study EpCAM TY loop kinetics of five different species, including human, mouse, chicken, frog, and fish. We find that the TY loop remains dynamic across evolution. In addition to the TYD binding site, we discover a second binding site for the TY loop in the C-terminal domain (CTD). Calculations of the dissociation rate constants from the simulation trajectories suggest a differential binding pattern of fish EpCAM and other organisms. Whereas fish TY loop has comparable binding for both TYD and CTD sites, the TY loops of other species preferably bind the TYD site. A hybrid construct of fish EpCAM with human TY loop restores the TYD binding preference, suggesting robust effects of the TY loop sequence on its dynamic behavior. Our findings provide insights into the structural dynamics of EpCAM and its implication in physiological functions.

Toward Guided Mutagenesis: Gaussian Process Regression Predicts MHC Class II Antigen Mutant Binding.

Antigen-specific immunotherapies (ASI) require successful loading and presentation of antigen peptides into the major histocompatibility complex (MHC) binding cleft. One route of ASI design is to mutate native antigens for either stronger or weaker binding interaction to MHC. Exploring all possible mutations is costly both experimentally and computationally. To reduce experimental and computational expense, here we investigate the minimal amount of prior data required to accurately predict the relative binding affinity of point mutations for peptide-MHC class II (pMHCII) binding. Using data from different residue subsets, we interpolate pMHCII mutant binding affinities by Gaussian process (GP) regression of residue volume and hydrophobicity. We apply GP regression to an experimental data set from the Immune Epitope Database, and theoretical data sets from NetMHCIIpan and Free Energy Perturbation calculations. We find that GP regression can predict binding affinities of nine neutral residues from a six-residue subset with an average R2 coefficient of determination value of 0.62 ± 0.04 (±95% CI), average error of 0.09 ± 0.01 kcal/mol (±95% CI), and with an receiver operating characteristic (ROC) AUC value of 0.92 for binary classification of enhanced or diminished binding affinity. Similarly, metrics increase to an R2 value of 0.69 ± 0.04, average error of 0.07 ± 0.01 kcal/mol, and an ROC AUC value of 0.94 for predicting seven neutral residues from an eight-residue subset. Our work finds that prediction is most accurate for neutral residues at anchor residue sites without register shift. This work holds relevance to predicting pMHCII binding and accelerating ASI design.

Molecular mechanism of secreted amyloid-ß precursor protein in binding and modulating GABABR1a.

A recent phenomenal study discovered that the extension domain of secreted amyloid-ß precursor protein (sAPP) can bind to the intrinsically disordered sushi 1 domain of the γ-aminobutyric acid type B receptor subunit 1a (GABABR1a) and modulate its synaptic transmission. The work provided an important structural foundation for the modulation of GABABR1a; however, the detailed molecular interaction mechanism, crucial for future drug design, remains elusive. Here, we further investigated the dynamical interactions between sAPP peptides and the natively unstructured sushi 1 domain using all-atom molecular dynamics simulations, for both the 17-residue sAPP peptide (APP 17-mer) and its minimally active 9 residue segment (APP 9-mer). We then explored mutations of the APP 9-mer with rigorous free energy perturbation (FEP) calculations. Our in silico mutagenesis studies revealed key residues (D4, W6, and W7) responsible for the binding with the sushi 1 domain. More importantly, one double mutation based on different vertebrate APP sequences from evolution exhibited a stronger binding (ΔΔG = -1.91 ± 0.66 kcal mol-1), indicating a potentially enhanced GABABR1a modulator. These large-scale simulations may provide new insights into the binding mechanism between sAPP and the sushi 1 domain, which could open new avenues in the development of future GABABR1a-specific therapeutics.

Structure-based enzyme engineering improves donor-substrate recognition of Arabidopsis thaliana glycosyltransferases.

Glycosylation of secondary metabolites involves plant UDP-dependent glycosyltransferases (UGTs). UGTs have shown promise as catalysts in the synthesis of glycosides for medical treatment. However, limited understanding at the molecular level due to insufficient biochemical and structural information has hindered potential applications of most of these UGTs. In the absence of experimental crystal structures, we employed advanced molecular modeling and simulations in conjunction with biochemical characterization to design a workflow to study five Group H Arabidopsis thaliana (76E1, 76E2, 76E4, 76E5, 76D1) UGTs. Based on our rational structural manipulation and analysis, we identified key amino acids (P129 in 76D1; D374 in 76E2; K275 in 76E4), which when mutated improved donor substrate recognition than wildtype UGTs. Molecular dynamics simulations and deep learning analysis identified structural differences, which drive substrate preferences. The design of these UGTs with broader substrate specificity may play important role in biotechnological and industrial applications. These findings can also serve as basis to study other plant UGTs and thereby advancing UGT enzyme engineering.

Binding patterns and dynamics of double-stranded DNA on the phosphorene surface.

Phosphorene, a monolayer of black phosphorus, has emerged as one of the most promising two-dimensional (2D) nanomaterials for various applications in the post-graphene-discovery period due to its highly anisotropic structure and novel properties. In order to apply phosphorene in biomedical fields, it is crucial to understand how it interacts with biomolecules. Herein, we use both molecular dynamics (MD) simulations and experimental techniques to investigate the interactions of phosphorene with a dsDNA segment. Our results reveal that dsDNA can form a stable binding on the phosphorene surface through the terminal base pairs and adopt an upright orientation regardless of its initial configurations. Moreover, the binding strength of dsDNA with phosphorene is found to be mild and does not cause significant distortion in the internal structure of dsDNA. This phenomenon is attributed to the weaker dispersion interaction between dsDNA and phosphorene. Further analysis of the free energy profile calculated by the umbrella sampling technique suggests that the puckered surface morphology significantly reduces the adsorption free energy of DNA bases to phosphorene. Compared to graphene, phosphorene is found to show a milder attraction to DNA, which is confirmed by our electrophoresis experiments. We believe that these findings provide valuable insight into the molecular interactions between phosphorene and dsDNA which may prompt further investigation of phosphorene for future biomedical applications.

Graphene-extracted membrane lipids facilitate the activation of integrin αvß8.

Despite the remarkable electrochemical properties of graphene, strong van der Waals attraction between graphene and biomolecules often causes cytotoxicity, which hinders its applications in the biomedical field. Unfortunately, surface passivation of graphene might stimulate undesired immune response as the nanomaterial triggers cytokine production through membrane receptor activation. Herein, we use all-atom Molecular Dynamics (MD) simulations to unravel the underlying mechanism of graphene-induced inside-out activation of integrin αvß8, a prominent membrane receptor expressed in immune cells. We model the transmembrane (TM) domains of integrin αvß8 in a 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) lipid bilayer and observe the structural changes in the integrin-membrane complex when interacting with a graphene nanosheet across the membrane. We find that the ß8 TM domain interacts with the graphene nanosheet directly or indirectly through extracted lipids, facilitating the pulling of a ß8 subunit away from an αv subunit and thus leading to the disruption of the TM domain association by breaking the hydrophobic cluster in the cytoplasmic domains of the αv and ß8 subunits. Alanine substitution of two conserved phenylalanine residues on the αv subunit at this hydrophobic cluster further reveals the importance of a stable T-shaped structure in retaining integrin in its inactive state. Our results agree with previous studies on the interactions between other integrin subtypes and their endogenous activators, suggesting an intriguing role that the graphene nanosheet may play in the integrin-related signal transduction during its interaction with the membrane.

The molecular mechanism of robust macrophage immune responses induced by PEGylated molybdenum disulfide.

Molybdenum disulfide (MoS2), a representative hexagonal transition metal dichalcogenide (TMD), has been extensively exploited in biomedical applications due to its unique physicochemical properties and biocompatibility. However, the lack of adequate data regarding how MoS2 activates immunological responses of macrophages remains a key concern for its risk assessment. Here, we employ a combined theoretical and experimental approach to investigate the interactions of MoS2 and PEGylated MoS2 (MoS2-PEG) with macrophages. We first perform molecular dynamics simulations to examine the atomic-detailed interactions of MoS2 and MoS2-PEG nanoflakes with a realistic model of the macrophage membrane. We show that a small MoS2 nanoflake (edge length of 2.86 nm) is capable of penetrating the macrophage membrane independent of its concentration. We also demonstrate that when initiated with a corner point-on configuration, the surface-bound PEG chains of MoS2-PEG hinder its membrane insertion process, leading to a prolonged passage through the membrane. Moreover, when placed in a face-on arrangement initially, the MoS2-PEG exhibits a lower binding free energy than pristine MoS2 after its adsorption on the membrane surface. The PEG chains can even insert and get buried in the outer leaflet of the membrane, providing additional contact for membrane adsorption. Our flow cytometric experiments then show that the responses of macrophages to either MoS2-PEG or MoS2 are significantly higher than that of the control (no nanomaterial stimulus), with MoS2-PEG eliciting stronger cytokine secretion than the pristine MoS2. The characteristics of slower/prolonged membrane penetration and stronger membrane adsorption of MoS2-PEG compared to pristine MoS2 explain why it triggers more sustained stimulation and higher cytokine secretion in macrophages as observed in our experiments. Our findings reveal the underlying molecular mechanism of how MoS2-PEG influences the immune responses and suggest its potential applications in nanomedicine involving immune stimulation.

Surface Inhomogeneity of Graphene Oxide Influences Dissociation of Aß16-21 Peptide Assembly.

Abnormal peptide assembly and aggregation is associated with an array of neurodegenerative diseases including Alzheimer's disease (AD). A detailed understanding of how nanostructured materials such as oxidized graphene perturb the peptide assembly and subsequently induce fibril dissociation may open new directions for the development of potential AD treatments. Here, we investigate the impact of surface inhomogeneity of graphene oxide (GO) on the assembly of amyloid-beta Aß16-21 peptides on GO surfaces with different degrees of oxidation using molecular dynamics simulations. Interestingly, nonuniform GO nanosheets (in terms of oxidation sites) have a much stronger perturbation effect on the structure of Aß16-21 assembly. The Aß peptides exhibit a remarkable tendency in binding to the scattered interfaces between unoxidized and oxidized regions, which induces the dissociation of Aß amyloid fibril. These findings should deepen our understanding of surface-induced peptide dissociation and stimulate discovery of alternative AD treatments.

Stability of Ligands on Nanoparticles Regulating the Integrity of Biological Membranes at the Nano-Lipid Interface.

When nanoparticles interact with cellular or organelle membranes, the coating ligands are known to affect the integrity of the membranes, which regulate cell death and inflammation. However, the molecular mechanisms of this modulation remain unresolved. Here, we use synchrotron X-ray liquid surface scattering and molecular dynamics simulations to study interface structures between phospholipids and gold nanorods (AuNRs) coated by surfactant and polyelectrolyte. These ligands are two types of widely used surface modification with different self-assembled structures and stabilities on the surface of nanoparticles. We reveal distinct mechanisms of the ligand stability in disrupting membrane integrity. We find that the cationic surfactant ligand cetyltrimethylammonium bromide detaches from the AuNRs and inserts into phospholipids, resulting in reduced membrane thickness by compressing the phospholipids to align with the shorter ligand. Conversely, the cationic polyelectrolyte ligand poly(diallyldimethylammonium chloride) is more stable on AuNRs; although it adsorbs onto the membrane, it does not cause much impairment. The distinct coating ligand interactions with phospholipids are further verified by cellular responses including impaired lysosomal membranes and triggered inflammatory effects in macrophages. Together, the quantitative analysis of interface structures elucidates key bio-nano interactions and highlights the importance of surface ligand stability for safety and rational design of nanoparticles.

Defect-assisted protein HP35 denaturation on graphene.

Structural defects in nanomaterials can alter their physical and chemical properties including magnetization, electronic and thermal conductivities, light absorption, and emission capabilities. Here, we investigated the potential impact of these defects on their biological effects through molecular dynamics simulations. By modeling the interaction between a graphene nanosheet and a widely used model protein, the chicken villin headpiece subdomain (HP35), we observed severe protein denaturation upon contact with defective graphene, while the protein remained intact on ideal graphene. The enhanced toxicity of defective graphene was due to the stronger attraction of the surface residues of HP35 from the defect edges (represented by carboxyl groups in our simulations) than from the ideal graphene. Upon binding to defective graphene, the contacting residues were restrained near the defective sites, which acted as "anchors" for the adsorbed protein. The "anchors" subsequently caused the protein to expose its aromatic and hydrophobic core residues to the graphene surface, via strong π-π stacking and hydrophobic interactions, thus leading to the unfolding of the protein. These findings not only highlight the importance of defects in nanomaterials' impact on biological systems, but also provide insights into fine-tuning the potential biological properties of nanomaterials through defect engineering.

Is Patient Advocacy the Solution to Physician Burnout?

Physician burnout has been on the rise over the last several decades in a variety of specialties, leading to high rates of physician suicide and poor health outcomes for patients. As leaders in healthcare attempt to combat this issue through mental health initiatives and changes in medical training policies, we propose patient advocacy as a powerful technique to combat physician burnout and restore autonomy, purpose, and meaning into physicians' lives.

Charging nanoparticles: increased binding of Gd@C82(OH)22 derivatives to human MMP-9.

Unlike most matrix metalloproteinase (MMP) inhibitors, which target the conserved catalytic zinc site, Gd@C82(OH)22 indirectly inhibits MMP-9 activity by binding at the ligand specificity S1' loop. The allosteric binding makes Gd@C82(OH)22 a promising inhibitor selective for MMP-9. However, the hydrophobic nature of the aromatic carbon cage may cause Gd@C82(OH)22 to self-aggregate in aqueous solutions, hence weakening the binding. In this study, we designed Gd@C82(OH)22 derivatives aiming at improving the binding affinity for MMP-9. Upon a mutation that substitutes a new functional group (-PO42-, -CH2CO2-, -CO2-, -NH3+, or -CONH2) for a hydroxyl group on the fullerenol surface, we calculated the changes in the binding free energy to the catalytic domain of human MMP-9 using the free energy perturbation (FEP) method. We found that the higher the net charge of the functional group, the stronger the binding. Compared with Gd@C82(OH)22, Gd@C82(OH)21(PO4)2- binds at least 1.5 to 2.5 kcal mol-1 more strongly to MMP-9. The binding is specifically controlled by electrostatic interactions between the phosphate group and the charged residues at the binding site. In addition to the net charge, the binding free energy can be delicately adjusted by other factors, such as the functionalization site on Gd@C82(OH)22, the local environment of the putative binding site of MMP-9, and the presence of ions near the charged functional group. The results of our study shed light on the potential of developing Gd@C82(OH)22 derivatives as nanodrugs for treating the pathological diseases associated with unregulated MMP-9 activity.

Evaluating genetic ancestry and self-reported ethnicity in the context of carrier screening.

BACKGROUND: Current professional society guidelines recommend genetic carrier screening be offered on the basis of ethnicity, or when using expanded carrier screening panels, they recommend to compute residual risk based on ethnicity. We investigated the reliability of self-reported ethnicity in 9138 subjects referred to carrier screening. Self-reported ethnicity gathered from test requisition forms and during post-test genetic counseling, and genetic ancestry predicted by a statistical model, were compared for concordance. RESULTS: We identified several discrepancies between the two sources of self-reported ethnicity and genetic ancestry. Only 30.3% of individuals who indicated Mediterranean ancestry during consultation self-reported this on requisition forms. Additionally, the proportion of individuals who reported Southeast Asian but were estimated to have a different genetic ancestry was found to depend on the source of self-report. Finally, individuals who reported Latin American demonstrated a high degree of ancestral admixture. As a result, carrier rates and residual risks provided for patient decision-making are impacted if using self-reported ethnicity. CONCLUSION: Our analysis highlights the unreliability of ethnicity classification based on patient self-reports. We recommend the routine use of pan-ethnic carrier screening panels in reproductive medicine. Furthermore, the use of an ancestry model would allow better estimation of carrier rates and residual risks.

A Prospective Multicenter Registry of Patients Undergoing Hysteroscopic Morcellation of Uterine Polyps and Myomas.

Background: Hysteroscopic morcellation removes uterine pathology under direct visualization with continuous real-time tissue fragment removal. Objective: The aim of this study was to explore the feasibility of hysteroscopic morcellation across a diverse set of facilities, including both surgical and office-based settings. Design: This was a prospective, single-arm, multicenter registry development (Canadian Task Force classification II-3). Materials and Methods: Thirty-four U.S. obstetrics and gynecology facilities enrolled subjects into the registry. Inclusion criteria were women ages 18-65 with indications for hysteroscopic myomectomy and/or polypectomy who were treated with the MyoSure® Hysteroscopic Tissue Removal System (Hologic Inc., Marlborough, MA). Intrauterine lesion type/size and removal parameters, adverse events (AEs), and physician satisfaction ratings were recorded. Results: A total of 559 pathologies (187 fibroids; 372 polyps) were removed from 278 registered subjects (mean age: 43.9 ± 9.0 years), with 250 procedures (89.9%) performed in an ambulatory surgery center or hospital outpatient setting and 28 (10.1%) in a gynecologic office setting. Most patients (n = 206, 74.1%) were treated for abnormal uterine bleeding, and 42 (15.1%) were treated for infertility. Mean fibroid diameter was 2.2 ± 1.2 cm. Mean polyp diameter was 1.3 ± 1.0 cm. Overall mean percentage of pathology removed was 95.4% (polyps 99.3%, fibroids 86.8%). Five AEs included four incidents of blunt cervical trauma and a single postoperative case of pedal edema; all were considered mild and resolved spontaneously. Postprocedure surveys indicated that 95% of reporting physicians were "satisfied" or "highly satisfied" with device performance. Conclusions: Hysteroscopic morcellation of intrauterine pathology was accomplished safely with a high degree of physician satisfaction in 278 patients treated in diverse healthcare settings that are reflective of general community practice in the United States. (J GYNECOL SURG 32:318).

A limited survey-based uncontrolled follow-up study of children born after ooplasmic transplantation in a single centre.

Experimental ooplasmic transplantation from donor to recipient oocyte took place between 1996 and 2001 at Saint Barnabas Medical Center, USA. Indication for 33 patients was repeated implantation failure. Thirteen couples had 17 babies. One patient delivered twins from mixed ooplasmic and donor egg embryos. A limited survey-based follow-up study on the children is reported: 12 out of 13 parents completed a questionnaire on pregnancy, birth, health, academic performance and disclosure. Parents of a quadruplet did not participate. Prenatal development and delivery were uneventful. School grades ranged from good to excellent. Children were of good health. Body mass index (BMI) was normal in 12 out of 13 children. One child had chronic migraine headaches, two mild asthma, three minor vision and three minor skin problems. One boy from a boy/girl twin was diagnosed with borderline pervasive developmental disorder - not otherwise specified at age 18 months, but with no later symptoms. One couple disclosed the use of egg donor to their child. One reported intention to disclose; six were undecided and four reported they would not disclose. This limited follow-up strategy presents a high risk of bias. Parents may not assent to standardized clinical analysis owing to lack of disclosure to their children.