Characteristics, blood counts, treatments, and clinical outcomes of 5871 patients with polycythemia vera treated in US community practices.

Objective: This study aimed to describe clinical characteristics-including blood counts and pharmacologic cytoreductive treatment patterns-and outcomes after 6 months of hydroxyurea (HU) treatment among patients with polycythemia vera (PV) in US community practices.

Methods: This retrospective observational study included adult patients with a PV diagnosis (1JAN2008-31JAN2020) and ≥2 postdiagnosis visits in the iKnowMed electronic health record database (US Oncology Network and non-Network clinics). Suboptimal HU response required ≥1 criterion after ≥3 months of treatment: white blood cell count (WBC) >10 × 10/L, platelet count >400 × 10/L, and/or hematocrit >45%.

Discovery and validation of genes driving drug-intake and related behavioral traits in mice.

Substance use disorders are heritable disorders characterized by compulsive drug use, the biological mechanisms for which remain largely unknown. Genetic correlations reveal that predisposing drug-naïve phenotypes, including anxiety, depression, novelty preference and sensation seeking, are predictive of drug-use phenotypes, thereby implicating shared genetic mechanisms. High-throughput behavioral screening in knockout (KO) mice allows efficient discovery of the function of genes.

DISCOVERY AND VALIDATION OF GENES DRIVING DRUG-INTAKE AND RELATED BEHAVIORAL TRAITS IN MICE.

Substance use disorders (SUDs) are heritable disorders characterized by compulsive drug use, but the biological mechanisms driving addiction remain largely unknown. Genetic correlations reveal that predisposing drug-naïve phenotypes, including anxiety, depression, novelty preference, and sensation seeking, are predictive of drug-use phenotypes, implicating shared genetic mechanisms. Because of this relationship, high-throughput behavioral screening of predictive phenotypes in knockout (KO) mice allows efficient discovery of genes likely to be involved in drug use.

Durvalumab real-world treatment patterns and outcomes in patients with stage III non-small-cell lung cancer treated in a US community setting.

For eligible patients with unresectable stage III non-small-cell lung cancer, durvalumab consolidation therapy following chemoradiotherapy is the standard of care. This was a retrospective study of durvalumab-treated patients diagnosed between 1 August 2017 and 29 February 2020. Electronic health record data were assessed descriptively, with Kaplan-Meier methods used for duration of treatment and overall survival (OS).

Circulating eNAMPT as a biomarker in the critically ill: acute pancreatitis, sepsis, trauma, and acute respiratory distress syndrome.

Background: Nicotinamide phosphoribosyltransferase (NAMPT) exhibits dual functionality - as an intracellular enzyme regulating nicotinamide adenine dinucleotide metabolism and as an extracellular secreted protein (eNAMPT) to function as a cytokine regulator of innate immunity via binding to Toll-Like receptor 4 and NF-κB activation. In limited preclinical and clinical studies, eNAMPT was implicated in the pathobiology of acute respiratory distress syndrome (ARDS) suggesting that eNAMPT could potentially serve as a diagnostic and prognostic biomarker. We investigated the feasibility of circulating eNAMPT levels to serve as a biomarker in an expanded cohort of patients with ARDS and ARDS-predisposing conditions that included acute pancreatitis, sepsis, and trauma with comparisons to controls.

The acute respiratory distress syndrome biomarker pipeline: crippling gaps between discovery and clinical utility.

Recent innovations in translational research have ushered an exponential increase in the discovery of novel biomarkers, thereby elevating the hope for deeper insights into "personalized" medicine approaches to disease phenotyping and care. However, a critical gap exists between the fast pace of biomarker discovery and the successful translation to clinical use. This gap underscores the fundamental biomarker conundrum across various acute and chronic disorders: how does a biomarker address a specific unmet need? Additionally, the gap highlights the need to shift the paradigm from a focus on biomarker discovery to greater translational impact and the need for a more streamlined drug approval process.

A Microbe Associated with Sleep Revealed by a Novel Systems Genetic Analysis of the Microbiome in Collaborative Cross Mice.

The microbiome influences health and disease through complex networks of host genetics, genomics, microbes, and environment. Identifying the mechanisms of these interactions has remained challenging. Systems genetics in laboratory mice () enables data-driven discovery of biological network components and mechanisms of host-microbial interactions underlying disease phenotypes.

Development of a biomarker mortality risk model in acute respiratory distress syndrome.

Background: There is a compelling unmet medical need for biomarker-based models to risk-stratify patients with acute respiratory distress syndrome. Effective stratification would optimize participant selection for clinical trial enrollment by focusing on those most likely to benefit from new interventions. Our objective was to develop a prognostic, biomarker-based model for predicting mortality in adult patients with acute respiratory distress syndrome.

Large-scale discovery of mouse transgenic integration sites reveals frequent structural variation and insertional mutagenesis.

Transgenesis has been a mainstay of mouse genetics for over 30 yr, providing numerous models of human disease and critical genetic tools in widespread use today. Generated through the random integration of DNA fragments into the host genome, transgenesis can lead to insertional mutagenesis if a coding gene or an essential element is disrupted, and there is evidence that larger scale structural variation can accompany the integration. The insertion sites of only a tiny fraction of the thousands of transgenic lines in existence have been discovered and reported, due in part to limitations in the discovery tools.

Longer lifespan in male mice treated with a weakly estrogenic agonist, an antioxidant, an α-glucosidase inhibitor or a Nrf2-inducer.

The National Institute on Aging Interventions Testing Program (ITP) evaluates agents hypothesized to increase healthy lifespan in genetically heterogeneous mice. Each compound is tested in parallel at three sites, and all results are published. We report the effects of lifelong treatment of mice with four agents not previously tested: Protandim, fish oil, ursodeoxycholic acid (UDCA) and metformin - the latter with and without rapamycin, and two drugs previously examined: 17-α-estradiol and nordihydroguaiaretic acid (NDGA), at doses greater and less than used previously.

Association of novelty-related behaviors and intravenous cocaine self-administration in Diversity Outbred mice.

Rationale: The preference for and reaction to novelty are strongly associated with addiction to cocaine and other drugs. However, the genetic variants and molecular mechanisms underlying these phenomena remain largely unknown. Although the relationship between novelty- and addiction-related traits has been observed in rats, studies in mice have failed to demonstrate this association.

Statistical inference methods for sparse biological time series data.

Background: Comparing metabolic profiles under different biological perturbations has become a powerful approach to investigating the functioning of cells. The profiles can be taken as single snapshots of a system, but more information is gained if they are measured longitudinally over time. The results are short time series consisting of relatively sparse data that cannot be analyzed effectively with standard time series techniques, such as autocorrelation and frequency domain methods.

pkDACLASS: Open source software for analyzing MALDI-TOF data.

Unlabelled: In recent years, mass spectrometry has become one of the core technologies for high throughput proteomic profiling in biomedical research. However, reproducibility of the results using this technology was in question. It has been realized that sophisticated automatic signal processing algorithms using advanced statistical procedures are needed to analyze high resolution and high dimensional proteomic data, e.