Demographic Correlates of Endometriosis Diagnosis Among United States Women Aged 15-50.

OBJECTIVE: To compare demographic characteristics for women with and without a diagnosis of endometriosis. DESIGN: Data were collected from the National Survey of Family Growth - a publicly available survey designed and administered by the Centers for Disease Control, which uses a nationally-representative sample of the United States population. Univariate data were reported as survey-weighted percentages and means, and were analyzed using chi-square, t-tests, and logistic regression. Analyses accounted for complex survey design. SETTING: United States PARTICIPANTS: Interviews were conducted with 6,141 female respondents, aged 15-50, between 2017 and 2019. INTERVENTIONS: Data were collected through in-person interviews. RESULTS: Nationally, 5.7% reported a diagnosis of endometriosis (95% CI 4.6-6.9%). Those with endometriosis were older, with a mean age of 39 (95% CI 38.1-39.9), compared to 31.7 (95% CI 31.2-32.2) among those without (p < 0.0005). Endometriosis diagnosis was significantly associated with race. Compared to non-Hispanic White women, Hispanic women had an adjusted odds ratio (aOR) of 0.37 (95% CI 0.21-0.65) for diagnosis of endometriosis, and non-Hispanic Black women had an aOR of 0.54 (95% CI 0.35-0.84). We also observed a difference in diagnosis by health insurance: compared to those with private insurance or Medi-Gap coverage, those with Medicare or military insurance had an aOR for endometriosis diagnosis of 2.49 (95% CI 1.36-4.55). Finally, compared to those with less than a high school education, those who had completed high school or greater had an aOR for endometriosis diagnosis of 2.84 (95% CI 1.15-6.99). CONCLUSION: These disparities in endometriosis diagnosis suggest that intersecting barriers may preclude certain groups from accessing timely endometriosis diagnosis and management. Further studies are warranted to explore these hypothesis-generating data, and to identify and address specific barriers to equitable endometriosis diagnosis and management.

Longitudinal impact of a residency-based postplacental levonorgestrel intrauterine device insertion program: Expulsion rates in years 1, 2, and 3.

OBJECTIVE: To evaluate expulsion rates in the first 3 years of an academic postplacental levonorgestrel intrauterine device (LNG-IUD) insertion program. STUDY DESIGN: Retrospective case series, January 2016 to December 2018. We measured LNG-IUD expulsion rates by 12 weeks postpartum. RESULTS: Of 235 LNG-IUD insertions, in years 1, 2, and 3, expulsion rates were 11/39 (28%), 9/94 (10%), and 15/102 (15%) (p = 0.03). After vaginal delivery, manual insertion was associated with a higher expulsion rate than ring-forceps (10/28 [36%] vs 17/105 [16%], p = 0.04). CONCLUSIONS: LNG-IUD expulsion rates decreased after program year 1, suggesting program maturity may be associated with a lower expulsion risk.

Approximating Projections of Conformational Boltzmann Distributions with AlphaFold2 Predictions: Opportunities and Limitations.

Protein thermodynamics is intimately tied to biological function and can enable processes such as signal transduction, enzyme catalysis, and molecular recognition. The relative free energies of conformations that contribute to these functional equilibria evolved for the physiology of the organism. Despite the importance of these equilibria for understanding biological function and developing treatments for disease, computational and experimental methods capable of quantifying the energetic determinants of these equilibria are limited to systems of modest size. Recently, it has been demonstrated that the artificial intelligence system AlphaFold2 can be manipulated to produce structurally valid protein conformational ensembles. Here, we extend these studies and explore the extent to which AlphaFold2 contact distance distributions can approximate projections of the conformational Boltzmann distributions. For this purpose, we examine the joint probability distributions of inter-residue contact distances along functionally relevant collective variables of several protein systems. Our studies suggest that AlphaFold2 normalized contact distance distributions can correlate with conformation probabilities obtained with other methods but that they suffer from peak broadening. We also find that the AlphaFold2 contact distance distributions can be sensitive to point mutations. Overall, we anticipate that our findings will be valuable as the community seeks to model the thermodynamics of conformational changes in large biomolecular systems.

Time-resolved live-cell spectroscopy reveals EphA2 multimeric assembly.

Ephrin type-A receptor 2 (EphA2) is a receptor tyrosine kinase that initiates both ligand-dependent tumor-suppressive and ligand-independent oncogenic signaling. We used time-resolved, live-cell fluorescence spectroscopy to show that the ligand-free EphA2 assembles into multimers driven by two types of intermolecular interactions in the ectodomain. The first type entails extended symmetric interactions required for ligand-induced receptor clustering and tumor-suppressive signaling that inhibits activity of the oncogenic extracellular signal-regulated kinase (ERK) and protein kinase B (AKT) protein kinases and suppresses cell migration. The second type is an asymmetric interaction between the amino terminus and the membrane proximal domain of the neighboring receptors, which supports oncogenic signaling and promotes migration in vitro and tumor invasiveness in vivo. Our results identify the molecular interactions that drive the formation of the EphA2 multimeric signaling clusters and reveal the pivotal role of EphA2 assembly in dictating its opposing functions in oncogenesis.

Contraception and Abortion Care for People Living With HIV: A Clinical Guide for Reproductive Health Practitioners.

People capable of pregnancy are disproportionately affected by HIV. Family planning needs and services are often unmet in this population, and clinical care guidelines regarding contraceptive options and abortion care are not well elucidated. Individuals living with HIV often face unique barriers in accessing contraception and abortion services due to internalized stigma, medically complex care (eg, drug-drug interactions, adverse effects of antiretroviral therapy), and distrust of health care providers. There is also a lack of clarity among reproductive health, primary, and infectious disease care providers on best-practice contraceptive counseling and contraceptive care for individuals living with HIV, given limited opportunities to enhance expertise in reproductive infectious disease. In this review, we summarize existing and updated evidence and clinical considerations regarding contraceptive counseling and abortion care in this population.

The photometric variability of massive stars due to gravity waves excited by core convection.

Massive stars die in catastrophic explosions that seed the interstellar medium with heavy elements and produce neutron stars and black holes. Predictions of the explosion's character and the remnant mass depend on models of the star's evolutionary history. Models of massive star interiors can be empirically constrained by asteroseismic observations of gravity wave oscillations. Recent photometric observations reveal a ubiquitous red noise signal on massive main sequence stars; a hypothesized source of this noise is gravity waves driven by core convection. We present three-dimensional simulations of massive star convection extending from the star's centre to near its surface, with realistic stellar luminosities. Using these simulations, we predict the photometric variability due to convectively driven gravity waves at the surfaces of massive stars, and find that gravity waves produce photometric variability of a lower amplitude and lower characteristic frequency than the observed red noise. We infer that the photometric signal of gravity waves excited by core convection is below the noise limit of current observations, and thus the red noise must be generated by an alternative process.

Approximating conformational Boltzmann distributions with AlphaFold2 predictions.

Protein dynamics are intimately tied to biological function and can enable processes such as signal transduction, enzyme catalysis, and molecular recognition. The relative free energies of conformations that contribute to these functional equilibria are evolved for the physiology of the organism. Despite the importance of these equilibria for understanding biological function and developing treatments for disease, the computational and experimental methods capable of quantifying them are limited to systems of modest size. Here, we demonstrate that AlphaFold2 contact distance distributions can approximate conformational Boltzmann distributions, which we evaluate through examination of the joint probability distributions of inter-residue contact distances along functionally relevant collective variables of several protein systems. Further, we show that contact distance probability distributions generated by AlphaFold2 are sensitive to points mutations thus AF2 can predict the structural effects of mutations in some systems. We anticipate that our approach will be a valuable tool to model the thermodynamics of conformational changes in large biomolecular systems.

Acquired Secondary HER2 Mutations Enhance HER2/MAPK Signaling and Promote Resistance to HER2 Kinase Inhibition in Breast Cancer.

HER2 mutations drive the growth of a subset of breast cancers and are targeted with HER2 tyrosine kinase inhibitors (TKI) such as neratinib. However, acquired resistance is common and limits the durability of clinical responses. Most HER2-mutant breast cancers progressing on neratinib-based therapy acquire secondary mutations in HER2. It is unknown whether these secondary HER2 mutations, other than the HER2T798I gatekeeper mutation, are causal to neratinib resistance. Herein, we show that secondary acquired HER2T862A and HER2L755S mutations promote resistance to HER2 TKIs via enhanced HER2 activation and impaired neratinib binding. While cells expressing each acquired HER2 mutation alone were sensitive to neratinib, expression of acquired double mutations enhanced HER2 signaling and reduced neratinib sensitivity. Computational structural modeling suggested that secondary HER2 mutations stabilize the HER2 active state and reduce neratinib binding affinity. Cells expressing double HER2 mutations exhibited resistance to most HER2 TKIs but retained sensitivity to mobocertinib and poziotinib. Double-mutant cells showed enhanced MEK/ERK signaling, which was blocked by combined inhibition of HER2 and MEK. Together, these findings reveal the driver function of secondary HER2 mutations in resistance to HER2 inhibition and provide a potential treatment strategy to overcome acquired resistance to HER2 TKIs in HER2-mutant breast cancer. SIGNIFICANCE: HER2-mutant breast cancers acquire secondary HER2 mutations that drive resistance to HER2 tyrosine kinase inhibitors, which can be overcome by combined inhibition of HER2 and MEK.

Abortion Policy Positions of Federal Legislators Who Received Support From the American College of Obstetricians and Gynecologists, 2012-2022.

This cross-sectional study analyzes the abortion policy positions of legislators financially supported by Ob-GynPAC, a political action committee funded by the American College of Obstetricians and Gynecologists (ACOG), between 2012 and 2022.

Macrocyclic Octapeptide Binding and Inferences on Protein Substrate Binding to Histone Deacetylase 6.

Histone deacetylases (HDACs) are essential for the regulation of myriad biological processes, and their aberrant function is implicated in cancer, neurodegeneration, and other diseases. The cytosolic isozyme HDAC6 is unique among the greater family of deacetylases in that it contains two catalytic domains, CD1 and CD2. HDAC6 CD2 is responsible for tubulin deacetylase and tau deacetylase activities, inhibition of which is a key goal as new therapeutic approaches are explored. Of particular interest as HDAC inhibitors are naturally occurring cyclic tetrapeptides such as Trapoxin A or HC Toxin, or the cyclic depsipeptides Largazole and Romidepsin. Even more intriguing are larger, computationally designed macrocyclic peptide inhibitors. Here, we report the 2.0 Å resolution crystal structure of HDAC6 CD2 complexed with macrocyclic octapeptide 1. Comparison with the previously reported structure of the complex with macrocyclic octapeptide 2 reveals that a potent thiolate-zinc interaction made by the unnatural amino acid (S)-2-amino-7-sulfanylheptanoic acid contributes to nanomolar inhibitory potency for each inhibitor. Apart from this zinc-binding residue, octapeptides adopt strikingly different overall conformations and make few direct hydrogen bonds with the protein. Intermolecular interactions are dominated by water-mediated hydrogen bonds; in essence, water molecules appear to cushion the enzyme-octapeptide interface. In view of the broad specificity observed for protein substrates of HDAC6 CD2, we suggest that the binding of macrocyclic octapeptides may mimic certain features of the binding of macromolecular protein substrates.

Abortion policies at the bedside: incorporating an ethical framework in the analysis and development of abortion legislation.

About 6% of women in the world live in countries that ban all abortions, and 34% in countries that only allow abortion to preserve maternal life or health. In the USA, over the last decades-even before Dobbs v. Jackson Women's Health Organization overturned the federal right to abortion-various states have sought to restrict abortion access. Often times, this legislation has been advanced based on legislators' personal moral values. At the bedside, in contrast, provision of abortion care should adhere to the normative principles of medical ethics and reproductive justice, centreing patients and their individual reproductive intentions and desires. Abortion regulations, through their influence on patients and providers, may facilitate or impede such ethical care at the bedside. In this paper, we present a framework to model how abortion legislation should fit into the patient-provider relationship and to clarify the dynamics by which legislation may affect healthcare encounters. Our proposed framework serves as a tool to analyse the ethical impact of abortion regulations. We propose a model for assessing abortion policies based not on legislators' or advocates' individual moral claims, but on the shared, normative framework of clinical medical ethics. Through contrasting case studies, we demonstrate how a robust normative ethical framework can recentre patients and their reproductive needs. Our model is one way to account for-and safeguard-patients' diverse viewpoints and needs in the development of abortion policy, and it can serve to ground narratives for advocacy by healthcare workers and their professional organisations.

Allele-specific activation, enzyme kinetics, and inhibitor sensitivities of EGFR exon 19 deletion mutations in lung cancer.

Oncogenic mutations within the epidermal growth factor receptor (EGFR) are found in 15 to 30% of all non-small-cell lung carcinomas. The term exon 19 deletion (ex19del) is collectively used to refer to more than 20 distinct genomic alterations within exon 19 that comprise the most common EGFR mutation subtype in lung cancer. Despite this heterogeneity, clinical treatment decisions are made irrespective of which EGFR ex19del variant is present within the tumor, and there is a paucity of information regarding how individual ex19del variants influence protein structure and function. Herein, we identified allele-specific functional differences among ex19del variants attributable to recurring sequence and structure motifs. We built all-atom structural models of 60 ex19del variants identified in patients and combined molecular dynamics simulations with biochemical and biophysical experiments to analyze three ex19del mutations (E746_A750, E746_S752 > V, and L747_A750 > P). We demonstrate that sequence variation in ex19del alters oncogenic cell growth, dimerization propensity, enzyme kinetics, and tyrosine kinase inhibitor (TKI) sensitivity. We show that in contrast to E746_A750 and E746_S752 > V, the L747_A750 > P variant forms highly active ligand-independent dimers. Enzyme kinetic analysis and TKI inhibition experiments suggest that E746_S752 > V and L747_A750 > P display reduced TKI sensitivity due to decreased adenosine 5'-triphosphate Km. Through these analyses, we propose an expanded framework for interpreting ex19del variants and considerations for therapeutic intervention.

Computational identification of HCV neutralizing antibodies with a common HCDR3 disulfide bond motif in the antibody repertoires of infected individuals.

Despite recent success in hepatitis C virus (HCV) treatment using antivirals, an HCV vaccine is still needed to prevent reinfections in treated patients, to avert the emergence of drug-resistant strains, and to provide protection for people with no access to the antiviral therapeutics. The early production of broadly neutralizing antibodies (bNAbs) associates with HCV clearance. Several potent bNAbs bind a conserved HCV glycoprotein E2 epitope using an unusual heavy chain complementarity determining region 3 (HCDR3) containing an intra-loop disulfide bond. Isolation of additional structurally-homologous bNAbs would facilitate the recognition of key determinants of such bNAbs and guide rational vaccine design. Here we report the identification of new antibodies containing an HCDR3 disulfide bond motif using computational screening with the Rosetta software. Using the newly-discovered and already-known members of this antibody family, we review the required HCDR3 amino acid composition and propose determinants for the bent versus straight HCDR3 loop conformation observed in these antibodies.

Introduction to the BioChemical Library (BCL): An Application-Based Open-Source Toolkit for Integrated Cheminformatics and Machine Learning in Computer-Aided Drug Discovery.

The BioChemical Library (BCL) cheminformatics toolkit is an application-based academic open-source software package designed to integrate traditional small molecule cheminformatics tools with machine learning-based quantitative structure-activity/property relationship (QSAR/QSPR) modeling. In this pedagogical article we provide a detailed introduction to core BCL cheminformatics functionality, showing how traditional tasks (e.g., computing chemical properties, estimating druglikeness) can be readily combined with machine learning. In addition, we have included multiple examples covering areas of advanced use, such as reaction-based library design. We anticipate that this manuscript will be a valuable resource for researchers in computer-aided drug discovery looking to integrate modular cheminformatics and machine learning tools into their pipelines.

Dissecting Monomer-Dimer Equilibrium of an RNase P Protein Provides Insight Into the Synergistic Flexibility of 5' Leader Pre-tRNA Recognition.

Ribonuclease P (RNase P) is a universal RNA-protein endonuclease that catalyzes 5' precursor-tRNA (ptRNA) processing. The RNase P RNA plays the catalytic role in ptRNA processing; however, the RNase P protein is required for catalysis in vivo and interacts with the 5' leader sequence. A single P RNA and a P protein form the functional RNase P holoenzyme yet dimeric forms of bacterial RNase P can interact with non-tRNA substrates and influence bacterial cell growth. Oligomeric forms of the P protein can also occur in vitro and occlude the 5' leader ptRNA binding interface, presenting a challenge in accurately defining the substrate recognition properties. To overcome this, concentration and temperature dependent NMR studies were performed on a thermostable RNase P protein from Thermatoga maritima. NMR relaxation (R1, R2), heteronuclear NOE, and diffusion ordered spectroscopy (DOSY) experiments were analyzed, identifying a monomeric species through the determination of the diffusion coefficients (D) and rotational correlation times (τc). Experimental diffusion coefficients and τc values for the predominant monomer (2.17 ± 0.36 * 10-10 m2/s, τ c = 5.3 ns) or dimer (1.87 ± 0.40* 10-10 m2/s, τ c = 9.7 ns) protein assemblies at 45°C correlate well with calculated diffusion coefficients derived from the crystallographic P protein structure (PDB 1NZ0). The identification of a monomeric P protein conformer from relaxation data and chemical shift information enabled us to gain novel insight into the structure of the P protein, highlighting a lack of structural convergence of the N-terminus (residues 1-14) in solution. We propose that the N-terminus of the bacterial P protein is partially disordered and adopts a stable conformation in the presence of RNA. In addition, we have determined the location of the 5' leader RNA in solution and measured the affinity of the 5' leader RNA-P protein interaction. We show that the monomer P protein interacts with RNA at the 5' leader binding cleft that was previously identified using X-ray crystallography. Data support a model where N-terminal protein flexibility is stabilized by holoenzyme formation and helps to accommodate the 5' leader region of ptRNA. Taken together, local structural changes of the P protein and the 5' leader RNA provide a means to obtain optimal substrate alignment and activation of the RNase P holoenzyme.

Co-occurring gain-of-function mutations in HER2 and HER3 modulate HER2/HER3 activation, oncogenesis, and HER2 inhibitor sensitivity.

Activating mutations in HER2 (ERBB2) drive the growth of a subset of breast and other cancers and tend to co-occur with HER3 (ERBB3) missense mutations. The HER2 tyrosine kinase inhibitor neratinib has shown clinical activity against HER2-mutant tumors. To characterize the role of HER3 mutations in HER2-mutant tumors, we integrate computational structural modeling with biochemical and cell biological analyses. Computational modeling predicts that the frequent HER3E928G kinase domain mutation enhances the affinity of HER2/HER3 and reduces binding of HER2 to its inhibitor neratinib. Co-expression of mutant HER2/HER3 enhances HER2/HER3 co-immunoprecipitation and ligand-independent activation of HER2/HER3 and PI3K/AKT, resulting in enhanced growth, invasiveness, and resistance to HER2-targeted therapies, which can be reversed by combined treatment with PI3Kα inhibitors. Our results provide a mechanistic rationale for the evolutionary selection of co-occurring HER2/HER3 mutations and the recent clinical observations that HER3 mutations are associated with a poor response to neratinib in HER2-mutant cancers.

Structure-function analysis of oncogenic EGFR Kinase Domain Duplication reveals insights into activation and a potential approach for therapeutic targeting.

Mechanistic understanding of oncogenic variants facilitates the development and optimization of treatment strategies. We recently identified in-frame, tandem duplication of EGFR exons 18 - 25, which causes EGFR Kinase Domain Duplication (EGFR-KDD). Here, we characterize the prevalence of ERBB family KDDs across multiple human cancers and evaluate the functional biochemistry of EGFR-KDD as it relates to pathogenesis and potential therapeutic intervention. We provide computational and experimental evidence that EGFR-KDD functions by forming asymmetric EGF-independent intra-molecular and EGF-dependent inter-molecular dimers. Time-resolved fluorescence microscopy and co-immunoprecipitation reveals EGFR-KDD can form ligand-dependent inter-molecular homo- and hetero-dimers/multimers. Furthermore, we show that inhibition of EGFR-KDD activity is maximally achieved by blocking both intra- and inter-molecular dimerization. Collectively, our findings define a previously unrecognized model of EGFR dimerization, providing important insights for the understanding of EGFR activation mechanisms and informing personalized treatment of patients with tumors harboring EGFR-KDD. Finally, we establish ERBB KDDs as recurrent oncogenic events in multiple cancers.

General Purpose Structure-Based Drug Discovery Neural Network Score Functions with Human-Interpretable Pharmacophore Maps.

The BioChemical Library (BCL) is an academic open-source cheminformatics toolkit comprising ligand-based virtual high-throughput screening (vHTS) tools such as quantitative structure-activity/property relationship (QSAR/QSPR) modeling, small molecule flexible alignment, small molecule conformer generation, and more. Here, we expand the capabilities of the BCL to include structure-based virtual screening. We introduce two new score functions, BCL-AffinityNet and BCL-DockANNScore, based on novel distance-dependent signed protein-ligand atomic property correlations. Both metrics are conventional feed-forward dropout neural networks trained on the new descriptors. We demonstrate that BCL-AffinityNet is one of the top performing score functions on the comparative assessment of score functions 2016 affinity prediction and affinity ranking tasks. We also demonstrate that BCL-AffinityNet performs well on the CSAR-NRC HiQ I and II test sets. Furthermore, we demonstrate that BCL-DockANNScore is competitive with multiple state-of-the-art methods on the docking power and screening power tasks. Finally, we show how our models can be decomposed into human-interpretable pharmacophore maps to aid in hit/lead optimization. Altogether, our results expand the utility of the BCL for structure-based scoring to aid small molecule discovery and design. BCL-AffinityNet, BCL-DockANNScore, and the pharmacophore mapping application, as well as the remainder of the BCL cheminformatics toolkit, are freely available with an academic license at the BCL Commons site hosted on http://meilerlab.org/.