Improved therapeutic efficacy in two mouse models of methylmalonic acidemia (MMA) using a second-generation mRNA therapy.

Isolated methylmalonic acidemia/aciduria (MMA) due to MMUT enzyme deficiency is an ultra-rare pediatric disease with high morbidity and mortality, with no approved disease-altering therapies. Previous publications showed that systemic treatment with a codon-optimized mRNA encoding wild-type human MMUT (MMUT) is a promising strategy for treatment of MMA. We developed a second-generation drug product, mRNA-3705, comprised of an mRNA encoding the MMUT enzyme formulated in a lipid nanoparticle (LNP) with incorporation of enhancements over the previous clinical candidate mRNA-3704.

Selecting PedsQL items to derive the PedsUtil health state classification system to measure health utilities in children.

Background: There is a lack of preference-based health-related quality of life (HRQoL) measures that consistently value health across a full range of child age groups. The PedsQL is a generic HRQoL instrument validated for children 2-18 years, but it is not preference-based. The objective of this study was to derive the PedsUtil health state classification system from the PedsQL as a basis for a preference-based HRQoL measure for children.

Nonparametric analysis of delayed treatment effects using single-crossing constraints.

Clinical trials involving novel immuno-oncology therapies frequently exhibit survival profiles which violate the proportional hazards assumption due to a delay in treatment effect, and, in such settings, the survival curves in the two treatment arms may have a crossing before the two curves eventually separate. To flexibly model such scenarios, we describe a nonparametric approach for estimating the treatment arm-specific survival functions which constrains these two survival functions to cross at most once without making any additional assumptions about how the survival curves are related. A main advantage of our approach is that it provides an estimate of a crossing time if such a crossing exists, and, moreover, our method generates interpretable measures of treatment benefit including crossing-conditional survival probabilities and crossing-conditional estimates of restricted residual mean life.

Biomarker-Directed Therapy in Black and White Men With Metastatic Castration-Resistant Prostate Cancer.

Importance: Black men have higher incidence and mortality from prostate cancer. Whether precision oncology disparities affect Black men with metastatic castration-resistant prostate cancer (mCRPC) is unknown.

Objective: To compare precision medicine data and outcomes between Black and White men with mCRPC.

Effects of and genotype on systemic anastrozole and fulvestrant concentrations in SWOG S0226.

This study tested associations of genotype-predicted activity of CYP3A4, other pharmacogenes, (rs11648166) and (rs28845026) with systemic concentrations of the endocrine therapies anastrozole and fulvestrant in SWOG S0226 trial participants. Participants in the anastrozole-only arm with low CYP3A4 activity (i.e.

Clinical implications of AR alterations in advanced prostate cancer: A multi-institutional collaboration.

Background: gene alterations can develop in response to pressure of testosterone suppression and androgen receptor targeting agents (ARTA). Despite this, the relevance of these gene alterations in the context of ARTA treatment and clinical outcomes remains unclear.

Methods: Patients with castration-resistant prostate cancer (CRPC) who had undergone genomic testing and received ARTA treatment were identified in the Prostate Cancer Precision Medicine Multi-Institutional Collaborative Effort (PROMISE) database.

Computational and Experimental Evidence for Templated Macrocyclization: The Role of a Hydrogen Bond Network in the Quantitative Dimerization of 24-Atom Macrocycles.

In the absence of preorganization, macrocyclization reactions are often plagued by oligomeric and polymeric side products. Here, a network of hydrogen bonds was identified as the basis for quantitative yields of macrocycles derived from the dimerization of monomers. Oligomers and polymers were not observed.

BaySyn: Bayesian Evidence Synthesis for Multi-system Multiomic Integration.

The discovery of cancer drivers and drug targets are often limited to the biological systems - from cancer model systems to patients. While multiomic patient databases have sparse drug response data, cancer model systems databases, despite covering a broad range of pharmacogenomic platforms, provide lower lineage-specific sample sizes, resulting in reduced statistical power to detect both functional driver genes and their associations with drug sensitivity profiles. Hence, integrating evidence across model systems, taking into account the pros and cons of each system, in addition to multiomic integration, can more efficiently deconvolve cellular mechanisms of cancer as well as learn therapeutic associations.

Antenna movements as a function of odorants' biological value in honeybees (Apis mellifera L.).

In honeybees, the antennae are highly mobile sensory organs that express scanning movements in various behavioral contexts and toward many stimuli, especially odorants. The rules underlying these movements are still unclear. Using a motion-capture system, we analyzed bees' antennal responses to a panel of pheromonal and other biologically relevant odorants.

Single-cell analysis of Sézary syndrome reveals novel markers and shifting gene profiles associated with treatment.

Cutaneous T-cell lymphomas (CTCLs) are a spectrum of diseases with varied clinical courses caused by malignant clonal proliferation of skin-tropic T cells. Most patients have an indolent disease course managed with skin-directed therapies. In contrast, others, especially in advanced stages of disease or with specific forms, have aggressive progression and poor median survival.

Exploratory polarization facilitates mating partner selection in .

Yeast decode pheromone gradients to locate mating partners, providing a model for chemotropism. How yeast polarize toward a single partner in crowded environments is unclear. Initially, cells often polarize in unproductive directions, but then they relocate the polarity site until two partners' polarity sites align, whereupon the cells "commit" to each other by stabilizing polarity to promote fusion.

A transcriptomic map of murine and human alopecia areata.

Alopecia areata (AA) is a common autoimmune condition, presenting initially with loss of hair without other overt skin changes. The unremarkable appearance of the skin surface contrasts with the complex immune activity occurring at the hair follicle. AA pathogenesis is due to the loss of immune privilege of the hair follicle, leading to autoimmune attack.

Ratiometric GPCR signaling enables directional sensing in yeast.

Accurate detection of extracellular chemical gradients is essential for many cellular behaviors. Gradient sensing is challenging for small cells, which can experience little difference in ligand concentrations on the up-gradient and down-gradient sides of the cell. Nevertheless, the tiny cells of the yeast Saccharomyces cerevisiae reliably decode gradients of extracellular pheromones to find their mates.

AR(1) latent class models for longitudinal count data.

In a variety of applications involving longitudinal or repeated-measurements data, it is desired to uncover natural groupings or clusters that exist among study subjects. Motivated by the need to recover clusters of longitudinal trajectories of conduct problems in the field of developmental psychopathology, we propose a method to address this goal when the response data in question are counts. We assume the subject-specific observations are generated from a first-order autoregressive process that is appropriate for count data.

Individualized treatment effects with censored data via fully nonparametric Bayesian accelerated failure time models.

Individuals often respond differently to identical treatments, and characterizing such variability in treatment response is an important aim in the practice of personalized medicine. In this article, we describe a nonparametric accelerated failure time model that can be used to analyze heterogeneous treatment effects (HTE) when patient outcomes are time-to-event. By utilizing Bayesian additive regression trees and a mean-constrained Dirichlet process mixture model, our approach offers a flexible model for the regression function while placing few restrictions on the baseline hazard.

Considerations when assessing heterogeneity of treatment effect in patient-centered outcomes research.

When baseline risk of an outcome varies within a population, the effect of a treatment on that outcome will vary on at least one scale (e.g., additive, multiplicative).

Logistic Regression Likelihood Ratio Test Analysis for Detecting Signals of Adverse Events in Post-market Safety Surveillance.

The Vaccine Adverse Event Reporting System (VAERS) and other product surveillance systems compile reports of product-associated adverse events (AEs), and these reports may include a wide range of information including age, gender, and concomitant vaccines. Controlling for possible confounding variables such as these is an important task when utilizing surveillance systems to monitor post-market product safety. A common method for handling possible confounders is to compare observed product-AE combinations with adjusted baseline frequencies where the adjustments are made by stratifying on observable characteristics.

Bayesian analysis of heterogeneous treatment effects for patient-centered outcomes research.

Evaluation of heterogeneity of treatment effect (HTE) is an essential aspect of personalized medicine and patient-centered outcomes research. Our goal in this article is to promote the use of Bayesian methods for subgroup analysis and to lower the barriers to their implementation by describing the ways in which the companion software can facilitate these types of analyses. To advance this goal, we describe several key Bayesian models for investigating HTE and outline the ways in which they are well-suited to address many of the commonly cited challenges in the study of HTE.

Making the cut: improved ranking and selection for large-scale inference.

Identifying leading measurement units from a large collection is a common inference task in various domains of large-scale inference. Testing approaches, which measure evidence against a null hypothesis rather than effect magnitude, tend to overpopulate lists of leading units with those associated with low measurement error. By contrast, local maximum likelihood (ML) approaches tend to favor units with high measurement error.

Fast Pure R Implementation of GEE: Application of the Matrix Package.

Generalized estimating equation solvers in R only allow for a few pre-determined options for the link and variance functions. We provide a package, , which is implemented entirely in R and allows for user specified link and variance functions. The sparse matrix representations provided in the package enable a fast implementation.