Bartender: Martini 3 Bonded Terms via Quantum Mechanics-Based Molecular Dynamics.

Coarse-grained (CG) molecular dynamics (MD) simulations have grown in applicability over the years. The recently released version of the Martini CG force field (Martini 3) has been successfully applied to simulate many processes, including protein-ligand binding. However, the current ligand parametrization scheme is manual and requires an a priori reference all-atom (AA) simulation for benchmarking. For systems with suboptimal AA parameters, which are often unknown, this translates into a CG model that does not reproduce the true dynamical behavior of the underlying molecule. Here, we present Bartender, a quantum mechanics (QM)/MD-based parametrization tool written in Go. Bartender harnesses the power of QM simulations and produces reasonable bonded terms for Martini 3 CG models of small molecules in an efficient and user-friendly manner. For small, ring-like molecules, Bartender generates models whose properties are indistinguishable from the human-made models. For more complex, drug-like ligands, it is able to fit functional forms beyond simple harmonic dihedrals and thus better captures their dynamical behavior. Bartender has the power to both increase the efficiency and the accuracy of Martini 3-based high-throughput applications by producing numerically stable and physically realistic CG models.

Joint hypermobility in functional neurological disorder: A cross-sectional study.

BACKGROUND: Functional Neurological Disorder (FND) is associated with anxiety and depression, and perhaps with joint hypermobility, which is itself associated with anxiety and depression. We conducted a survey to explore the relationship between these. METHODS: An online survey of people with FND was conducted, with participants asked to nominate healthy controls from their social group to join. Participants were asked about their anxiety (measured with GAD7), depression (measured with PHQ9) and joint hypermobility (measured with 5PQ). A regression analysis was conducted using a general linear model. RESULTS: 215 people with FND and 22 people without FND were included in the analysis. GAD7, PHQ9 and hypermobility scores were all higher in the group with FND, with 74% of people with FND meeting the common cut-off for a diagnosis of joint hypermobility syndrome, as compared with 45% of those without FND. Anxiety, depression and joint hypermobility scores all predicted FND status, with joint hypermobility the strongest. Hypermobility moderated the effect of anxiety, with the effect being stronger at lower levels of anxiety. CONCLUSION: While anxiety, depression and hypermobility symptoms each appear to contribute to FND, the role of anxiety is moderated by hypermobility, particularly when anxiety is lower.

Assessing the Martini 3 protein model: A review of its path and potential.

Coarse-grained (CG) protein models have become indispensable tools for studying many biological protein details, from conformational dynamics to the organization of protein macro-complexes, and even the interaction of proteins with other molecules. The Martini force field is one of the most widely used CG models for bio-molecular simulations, partly because of the enormous success of its protein model. With the recent release of a new and improved version of the Martini force field - Martini 3 - a new iteration of its protein model was also made available. The Martini 3 protein force field is an evolution of its Martini 2 counterpart, aimed at improving many of the shortcomings that had been previously identified. In this mini-review, we first provide a general overview of the model and then focus on the successful advances made in the short time since its release, many of which would not have been possible before. Furthermore, we discuss reported limitations, potential directions for model improvement and comment on what the likely future development and application avenues are.

Differentiation between atypical anorexia nervosa and anorexia nervosa using machine learning.

OBJECTIVE: Body mass index (BMI) is the primary criterion differentiating anorexia nervosa (AN) and atypical anorexia nervosa despite prior literature indicating few differences between disorders. Machine learning (ML) classification provides us an efficient means of accurately distinguishing between two meaningful classes given any number of features. The aim of the present study was to determine if ML algorithms can accurately distinguish AN and atypical AN given an ensemble of features excluding BMI, and if not, if the inclusion of BMI enables ML to accurately classify between the two. METHODS: Using an aggregate sample from seven studies consisting of individuals with AN and atypical AN who completed baseline questionnaires (N = 448), we used logistic regression, decision tree, and random forest ML classification models each trained on two datasets, one containing demographic, eating disorder, and comorbid features without BMI, and one retaining all features and BMI. RESULTS: Model performance for all algorithms trained with BMI as a feature was deemed acceptable (mean accuracy = 74.98%, mean area under the receiving operating characteristics curve [AUC] = 74.75%), whereas model performance diminished without BMI (mean accuracy = 59.37%, mean AUC = 59.98%). DISCUSSION: Model performance was acceptable, but not strong, if BMI was included as a feature; no other features meaningfully improved classification. When BMI was excluded, ML algorithms performed poorly at classifying cases of AN and atypical AN when considering other demographic and clinical characteristics. Results suggest a reconceptualization of atypical AN should be considered. PUBLIC SIGNIFICANCE: There is a growing debate about the differences between anorexia nervosa and atypical anorexia nervosa as their diagnostic differentiation relies on BMI despite being similar otherwise. We aimed to see if machine learning could distinguish between the two disorders and found accurate classification only if BMI was used as a feature. This finding calls into question the need to differentiate between the two disorders.

Using Instrumental Variables to Measure Causation over Time in Cross-Lagged Panel Models.

Cross-lagged panel models (CLPMs) are commonly used to estimate causal influences between two variables with repeated assessments. The lagged effects in a CLPM depend on the time interval between assessments, eventually becoming undetectable at longer intervals. To address this limitation, we incorporate instrumental variables (IVs) into the CLPM with two study waves and two variables. Doing so enables estimation of both the lagged (i.e., "distal") effects and the bidirectional cross-sectional (i.e., "proximal") effects at each wave. The distal effects reflect Granger-causal influences across time, which decay with increasing time intervals. The proximal effects capture causal influences that accrue over time and can help infer causality when the distal effects become undetectable at longer intervals. Significant proximal effects, with a negligible distal effect, would imply that the time interval is too long to estimate a lagged effect at that time interval using the standard CLPM. Through simulations and an empirical application, we demonstrate the impact of time intervals on causal inference in the CLPM and present modeling strategies to detect causal influences regardless of the time interval in a study. Furthermore, to motivate empirical applications of the proposed model, we highlight the utility and limitations of using genetic variables as IVs in large-scale panel studies.

Characterizing two-mode-squeezed light from four-wave mixing in rubidium vapor for quantum sensing and information processing.

We present a study of homodyne measurements of two-mode, vacuum-seeded, quadrature-squeezed light generated by four-wave mixing in warm rubidium vapor. Our results reveal that the vacuum squeezing can extend down to measurement frequencies of less than 1 Hz, and the squeezing bandwidth, similar to the seeded intensity-difference squeezing measured in this system, reaches up to approximately 20 MHz for typical pump parameters. By dividing the squeezing bandwidth into smaller frequency bins, we show that different sideband frequencies represent independent sources of two-mode squeezing. These properties are useful for quantum sensing and quantum information processing applications. We also investigate the impact of group velocity delays on the correlations in the system, which allows us to optimize the useful spectrum.

Are central eating disorder network symptoms sensitive to item selection and sample? Implications for conceptualization of eating disorder psychopathology from a network perspective.

Item selection is a critical decision in modeling psychological networks. The current preregistered two-study research used random selections of 1,000 symptom networks to examine which eating disorder (ED) and co-occurring symptoms are most central in longitudinal networks among individuals with EDs (N = 71, total observations = 6,060) and tested whether centrality changed based on which items were included in the network. Participants completed 2 weeks of ecological momentary assessment (five surveys/day). In Study 1, we obtained initial strength centrality values by estimating an a priori network using eight items with the highest means. We then estimated 1,000 networks and their centrality from a random selection of unique eight-item symptom combinations. We compared the strength centrality from the a priori network to the distribution of strength centrality estimates from the random-item networks. In Study 2, we repeated this procedure in an independent longitudinal dataset (N = 41, total observations = 4,575) to determine if our results generalized across samples. Shame, guilt, worry, and fear of losing control were consistently central across networks, regardless of items included in the network or sample. Results suggest that these symptoms may be important to the structure of ED psychopathology and have implications for how we understand the structure of ED psychopathology. Existing methods for item inclusion in psychological networks may distort the structure of ED symptom networks by either under- or overestimating strength centrality, or by omitting consistently central symptoms that are nontraditional ED symptoms. Future research should consider including these symptoms in models of ED psychopathology. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Martini 3 Coarse-Grained Force Field for Cholesterol.

Cholesterol plays a crucial role in biomembranes by regulating various properties, such as fluidity, rigidity, permeability, and organization of lipid bilayers. The latest version of the Martini model, Martini 3, offers significant improvements in interaction balance, molecular packing, and inclusion of new bead types and sizes. However, the release of the new model resulted in the need to reparameterize many core molecules, including cholesterol. Here, we describe the development and validation of a Martini 3 cholesterol model, addressing issues related to its bonded setup, shape, volume, and hydrophobicity. The proposed model mitigates some limitations of its Martini 2 predecessor while maintaining or improving the overall behavior.

Pragmatic Coarse-Graining of Proteins: Models and Applications.

The molecular details involved in the folding, dynamics, organization, and interaction of proteins with other molecules are often difficult to assess by experimental techniques. Consequently, computational models play an ever-increasing role in the field. However, biological processes involving large-scale protein assemblies or long time scale dynamics are still computationally expensive to study in atomistic detail. For these applications, employing coarse-grained (CG) modeling approaches has become a key strategy. In this Review, we provide an overview of what we call pragmatic CG protein models, which are strategies combining, at least in part, a physics-based implementation and a top-down experimental approach to their parametrization. In particular, we focus on CG models in which most protein residues are represented by at least two beads, allowing these models to retain some degree of chemical specificity. A description of the main modern pragmatic protein CG models is provided, including a review of the most recent applications and an outlook on future perspectives in the field.

Power, measurement error, and pleiotropy robustness in twin-design extensions to Mendelian Randomization.

Mendelian Randomization (MR) has become an important tool for causal inference in the health sciences. It takes advantage of the random segregation of alleles to control for background confounding factors. In brief, the method works by using genetic variants as instrumental variables, but it depends on the assumption of exclusion restriction, i.e., that the variants affect the outcome exclusively via the exposure variable. Equivalently, the assumption states that there is no horizontal pleiotropy from the variant to the outcome. This assumption is unlikely to hold in nature, so several extensions to MR have been developed to increase its robustness against horizontal pleiotropy, though not eliminating the problem entirely (Sanderson et al. 2022). The Direction of Causation (DoC) model, which affords information from the cross-twin cross-trait correlations to estimate causal paths, was extended with polygenic scores to explicitly model horizontal pleiotropy and a causal path (MR-DoC, Minica et al 2018). MR-DoC was further extended to accommodate bidirectional causation (MR-DoC2 ; Castro-de-Araujo et al. 2023). In the present paper, we compared the power of the DoC model, MR-DoC, and MR-DoC2. We investigated the effect of phenotypic measurement error and the effect of misspecification of unshared (individual-specific) environmental factors on the parameter estimates.

Expulsion mechanism of the substrate-translocating subunit in ECF transporters.

Energy-coupling factor (ECF)-type transporters mediate the uptake of micronutrients in many bacteria. They consist of a substrate-translocating subunit (S-component) and an ATP-hydrolysing motor (ECF module) Previous data indicate that the S-component topples within the membrane to alternately expose the binding site to either side of the membrane. In many ECF transporters, the substrate-free S-component can be expelled from the ECF module. Here we study this enigmatic expulsion step by cryogenic electron microscopy and reveal that ATP induces a concave-to-convex shape change of two long helices in the motor, thereby destroying the S-component's docking site and allowing for its dissociation. We show that adaptation of the membrane morphology to the conformational state of the motor may favour expulsion of the substrate-free S-component when ATP is bound and docking of the substrate-loaded S-component after hydrolysis. Our work provides a picture of bilayer-assisted chemo-mechanical coupling in the transport cycle of ECF transporters.

Kinbank: A global database of kinship terminology.

For a single species, human kinship organization is both remarkably diverse and strikingly organized. Kinship terminology is the structured vocabulary used to classify, refer to, and address relatives and family. Diversity in kinship terminology has been analyzed by anthropologists for over 150 years, although recurrent patterning across cultures remains incompletely explained. Despite the wealth of kinship data in the anthropological record, comparative studies of kinship terminology are hindered by data accessibility. Here we present Kinbank, a new database of 210,903 kinterms from a global sample of 1,229 spoken languages. Using open-access and transparent data provenance, Kinbank offers an extensible resource for kinship terminology, enabling researchers to explore the rich diversity of human family organization and to test longstanding hypotheses about the origins and drivers of recurrent patterns. We illustrate our contribution with two examples. We demonstrate strong gender bias in the phonological structure of parent terms across 1,022 languages, and we show that there is no evidence for a coevolutionary relationship between cross-cousin marriage and bifurcate-merging terminology in Bantu languages. Analysing kinship data is notoriously challenging; Kinbank aims to eliminate data accessibility issues from that challenge and provide a platform to build an interdisciplinary understanding of kinship.

Feedback-loop between psychotic symptoms and brain volume: A cross-lagged panel model study.

Brain structural changes are known to be associated with psychotic symptoms, with worse symptoms consistently associated with brain volume loss in some areas. It is not clear whether volume and symptoms interfere with each other over the course of psychosis. In this paper, we analyse the temporal relationships between psychosis symptom severity and total gray matter volume. We applied a cross-lagged panel model to a public dataset from the NUSDAST cohorts. The subjects were assessed at three-time points: baseline, 24 months, and 48 months. Psychosis symptoms were measured by SANS and SAPS scores. The cohort contained 673 subjects with schizophrenia, healthy subjects and their siblings. There were significant effects of symptom severity on total gray matter volume and vice-versa. The worse the psychotic symptoms, the smaller the total gray volume, and the smaller the volume, the worse the symptomatology. There is a bidirectional temporal relationship between symptoms of psychosis and brain volume.

Revealing the impact of organic spacers and cavity cations on quasi-2D perovskites via computational simulations.

Two-dimensional hybrid lead iodide perovskites based on methylammonium (MA) cation and butylammonium (BA) organic spacer-such as [Formula: see text]-are one of the most explored 2D hybrid perovskites in recent years. Correlating the atomistic profile of these systems with their optoelectronic properties is a challenge for theoretical approaches. Here, we employed first-principles calculations via density functional theory to show how the cation partially canceled dipole moments through the [Formula: see text] terminal impact the structural/electronic properties of the [Formula: see text] sublattices. Even though it is known that at high temperatures, the organic cation assumes a spherical-like configuration due to the rotation of the cations inside the cage, our results discuss the correct relative orientation according to the dipole moments for ab initio simulations at 0 K, correlating well structural and electronic properties with experiments. Based on the combination of relativistic quasiparticle correction and spin-orbit coupling, we found that the MA horizontal-like configuration concerning the inorganic sublattice surface leads to the best relationship between calculated and experimental gap energy throughout n = 1, 2, 3, 4, and 5 number of layers. Conversely, the dipole moments cancellation (as in BA-MA aligned-like configuration) promotes the closing of the gap energies through an electron depletion mechanism. We found that the anisotropy [Formula: see text] isotropy optical absorption conversion (as a bulk convergence) is achieved only for the MA horizontal-like configuration, which suggests that this configuration contribution is the majority in a scenario under temperature effects.

Personalizing eating disorder treatment using idiographic models: An open series trial.

OBJECTIVE: Treatments for adults with eating disorders (EDs) only work in about 50% of individuals, and for some diagnoses (e.g., anorexia nervosa; atypical anorexia nervosa), there are no existing evidence-based treatments. Part of the reason that treatments may only work in a subset of individuals is because of the high heterogeneity present in the EDs, even within diagnoses. Manualized treatments delivered in a standard format may not always address the most relevant symptoms for a specific individual. METHOD: The current open series trial recruited participants with transdiagnostic ED diagnoses (N = 79) to investigate the feasibility, acceptability, and initial clinical efficacy of a 10-session network-informed personalized treatment for eating disorders. This treatment uses idiographic (i.e., one-person) network models of ecological momentary assessment symptom data to match participants to evidence-based modules of treatment. RESULTS: We found that network-informed personalized treatment was highly feasible with low dropout rates, was rated as highly acceptable, and had strong initial clinical efficacy. ED severity decreased from pre- to posttreatment and at 1-year follow-up with a large effect size. ED cognitions, behaviors, clinical impairment, worry, and depression also decreased from pre- to posttreatment. CONCLUSIONS: These data suggest that network-informed personalized treatment has high acceptability and feasibility and can decrease ED and related pathology, possibly serving as a feasible alternative to existing treatments. Future randomized controlled trials comparing network-informed personalized treatment for ED to existing gold standard treatments are needed. Additionally, more research is needed on this type of personalized treatment both in the EDs, as well as in additional forms of psychopathology, such as depression. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

How cation nature controls the bandgap and bulk Rashba splitting of halide perovskites.

Because of instability issues presented by metal halide perovskites based on methylammonium (MA), its replacement to Cs has emerged as an alternative to improve the materials' durability. However, the impact of this replacement on electronic properties, especially gap energy and bulk Rashba splitting remains unclear since electrostatic interactions from organic cations can play a crucial role. Through first-principles calculations, we investigated how organic/inorganic cations impact the electronic properties of MAPbI 3 and CsPbI 3 perovskites. Although at high temperatures the organic cation can assume spherical-like configurations due to its rotation into the cages, our results provide a complete electronic mechanism to show, from a chemical perspective based on ab initio calculations at 0 K , how the MA dipoles suppression can reduce the MAPbI 3 gap energy by promoting a degeneracy breaking in the electronic states from the PbI 3 framework, while the dipole moment reinforcement is crucial to align theory ↔ experiment, increasing the bulk Rashba splitting through higher Pb off-centering motifs. The lack of permanent dipole moment in Cs results in CsPbI 3 polymorphs with a pronounced Pb on-centering-like feature, which causes suppression in their respective bulk Rashba effect.

A phase 1/2, open-label, multicenter study of isatuximab in combination with cemiplimab in patients with lymphoma.

Patients with relapsed or refractory lymphoma have limited treatment options, requiring newer regimens. In this Phase 1/2 study (NCT03769181), we assessed the safety, efficacy, and pharmacokinetics of isatuximab (Isa, anti-CD38 antibody) in combination with cemiplimab (Cemi, anti-programmed death-1 [PD-1] receptor antibody; Isa + Cemi) in patients with classic Hodgkin lymphoma (cHL), diffuse large B-cell lymphoma (DLBCL), and peripheral T-cell lymphoma (PTCL). In Phase 1, we characterized the safety and tolerability of Isa + Cemi with planned dose de-escalation to determine the recommended Phase 2 dose (RP2D). Six patients in each cohort were treated with a starting dose of Isa + Cemi to determine the RP2D. In Phase 2, the primary endpoints were complete response in Cohort A1 (cHL anti-PD-1/programmed death-ligand 1 [PD-L1] naïve), and objective response rate in Cohorts A2 (cHL anti-PD-1/PD-L1 progressors), B (DLBCL), and C (PTCL). An interim analysis was performed when the first 18 (Cohort A1), 12 (Cohort A2), 17 (Cohort B), and 11 (Cohort C) patients in Phase 2 had been treated and followed up for 24 weeks. Isa + Cemi demonstrated a manageable safety profile with no new safety signals. No dose-limiting toxicities were observed at the starting dose; thus, the starting dose of each drug was confirmed as the RP2D. Based on the Lugano 2014 criteria, 55.6% (Cohort A1), 33.3% (Cohort A2), 5.9% (Cohort B), and 9.1% (Cohort C) of patients achieved a complete or partial response. Pharmacokinetic analyses suggested no effect of Cemi on Isa exposure. Modest clinical efficacy was observed in patients with cHL regardless of prior anti-PD-1/PD-L1 exposure. In DLBCL or PTCL cohorts, interim efficacy analysis results did not meet prespecified criteria to continue enrollment in Phase 2 Stage 2. Isa + Cemi did not have a synergistic effect in these patient populations.

MR-DoC2: Bidirectional Causal Modeling with Instrumental Variables and Data from Relatives.

Establishing causality is an essential step towards developing interventions for psychiatric disorders, substance use and many other conditions. While randomized controlled trials (RCTs) are considered the gold standard for causal inference, they are unethical in many scenarios. Mendelian randomization (MR) can be used in such cases, but importantly both RCTs and MR assume unidirectional causality. In this paper, we developed a new model, MRDoC2, that can be used to identify bidirectional causation in the presence of confounding due to both familial and non-familial sources. Our model extends the MRDoC model (Minica et al. in Behav Genet 48:337-349,  https://doi.org/10.1007/s10519-018-9904-4 , 2018), by simultaneously including risk scores for each trait. Furthermore, the power to detect causal effects in MRDoC2 does not require the phenotypes to have different additive genetic or shared environmental sources of variance, as is the case in the direction of causation twin model (Heath et al. in Behav Genet 23:29-50,  https://doi.org/10.1007/BF01067552 , 1993).

Main and moderated effects of multimorbidity and depressive symptoms on cognition

Objective: Multimorbidity, or the occurrence of two or more chronic conditions, is a global challenge, with implications for mortality, morbidity, disability, and life quality. Psychiatric disorders are common among the chronic diseases that affect patients with multimorbidity. It is still not well understood whether psychiatric symptoms, especially depressive symptoms, moderate the effect of multimorbidity on cognition. Methods: We used a large (n=2,681) dataset to assess whether depressive symptomatology moderates the effect of multimorbidity on cognition using structural equation modelling. Results: It was found that the more depressive symptoms and chronic conditions, the worse the cognitive performance, and the higher the educational level, the better the cognitive performance. We found a significant but weak (0.009; p = 0.04) moderating effect. Conclusion: We have provided the first estimate of the moderating effect of depression on the relation between multimorbidity and cognition, which was small. Although this moderation has been implied by many previous studies, it was never previously estimated.

Avaliação do perfil clínico-terapêutico e da resposta à profilaxia dos portadores de hemofilia A e B em um centro de referência no Ceará / Evaluation of the clinical-therapeutic profile and the response to prophylaxis of patients with hemophilia A and B in a reference center in Ceará

Objetivo: Avaliar o perfil clínico-terapêutico e a resposta à profilaxia em pacientes hemofílicos A e B em um centro de referência no Ceará. Métodos: Estudo de coorte retrospectivo, com dados de 133 hemofílicos A e B, em profilaxia entre 2016 e 2021, por meio de prontuários médicos e sistema Web Coagulopatias. Resultados: Os pacientes todos do sexo masculino em sua maioria foram hemofílicos A (93,2%), na forma grave, residentes em Fortaleza, com maior prevalência do município de Guaiúba. A maioria fazia uso de Fator VIII recombinante e em profilaxia secundária, em relação ao comprometimento articular a maioria não apresentou relato de hemartroses (66,9%), articulação-alvo (87,9%) ou artropatia (54,9%), porém os hemofílicos em profilaxia terciária apresentaram um maior comprometimento articular em relação a profilaxia primária e secundária. Verificou-se uma correlação negativa entre o tempo de profilaxia e a dose de fator utilizada, demonstrando que quanto maior o tempo de profilaxia menor a dose do fator utilizada. Um total de 13 hemofílicos A grave desenvolveram inibidor de fator VIII realizando imunotolerância (ITI) com sucesso total em 84,6%. Por meio da curva ROC, foi verificado uma associação entre a necessidade de ITI e a dose de fator de coagulação, com acurácia de 67,7% de que o uso de doses maiores de fator predispõe ao desenvolvimento de inibidores. Conclusão: Os dados do estudo permitem inferir que quanto mais precoce o tratamento de profilaxia menor é comprometimento articular, dose do fator utilizada e menor predisposição de desenvolver inibidores dos fatores da coagulação.

Objective: to evaluate the clinical-therapeutic profile and response to prophylaxis in hemophiliac A and B patients at a referral center in Ceará. Methods: Retrospective cohort study, with data from 133 hemophiliacs A and B, undergoing prophylaxis between 2016 and 2021, using medical records and the Web Coagulopathies system. Results: Most of the patients were male patients with severe hemophilia A (93.2%), residing in Fortaleza, with a higher prevalence in the city of Guaiúba. Most made use of recombinant Factor VIII and in secondary prophylaxis, in relation to joint involvement, the majority did not report hemarthroses (66.9%), target joint (87.9%) or arthropathy (54.9%). however, hemophiliacs on tertiary prophylaxis showed greater joint impairment in relation to primary and secondary prophylaxis. There was a negative correlation between the prophylaxis time and the factor dose used, demonstrating that the longer the prophylaxis time, the lower the factor dose used. A total of 13 severe A hemophiliacs developed factor VIII inhibitor performing immunotolerance (ITI) with total success in 84.6%. Using the ROC curve, an association was verified between the need for ITI and the dose of coagulation factor, with an accuracy of 67.7% that the use of higher doses of factor predisposes to the development of inhibitors. Conclusion: The study data allow us to infer that the earlier the prophylaxis treatment, the less joint impairment, the dose of the factor used and the less predisposition to develop coagulation factor inhibitors.