Single-Dose Intravenous Toxicity Study of IRDye 800CW in Sprague-Dawley Rats

Objective: Fluorophore-labeled contrast imaging agents are moving toward clinical use for a number of applications. The near-infrared dye IRDye 800CW is frequently used in its N-hydroxysuccinamide (NHS) ester form for labeling these agents. Following conjugation or breakdown of a labeled ligand, excess NHS ester is converted to the carboxylate form. To prepare for clinical use as a near-infrared fluorophore, a toxicity study was conducted on IRDye 800CW carboxylate. Methods: Male and female Sprague–Dawley rats were given a single intravenous or intradermal administration of IRDye 800CW carboxylate; Indocyanine Green was used as a comparative control. Animals were injected with varying doses of the test and control articles and observed for up to 14 days. Clinical chemistry, hematological, and pharmacokinetic analyses were performed on subgroups of animals. Organs were analyzed for content of the test article. Tissues were analyzed microscopically for pathological changes. Results: Based on hematologic, clinical chemistry, and histopathologic evaluation, single administration of IRDye 800CW carboxylate intravenously at dose levels of 1, 5, and 20 mg/kg or 20 mg/kg intradermally produced no pathological evidence of toxicity. Conclusion: A dose of 20 mg/kg was identified as the no observed adverse effect level following IV or ID routes of administration of IRDye 800CW

Menin as a hub controlling mixed lineage leukemia

Mixed lineage leukemia (MLL) fusion protein (FP)‐induced acute leukemia is highly aggressive and often refractory to therapy. Recent progress in the field has unraveled novel mechanisms and targets to combat this disease. Menin, a nuclear protein, interacts with wild‐type (WT) MLL, MLL‐FPs, and other partners such as the chromatin‐associated protein LEDGF and the transcription factor C‐Myb to promote leukemogenesis. The newly solved co‐crystal structure illustrating the menin–MLL interaction, coupled with the role of menin in recruiting both WT MLL and MLL‐FPs to target genes, highlights menin as a scaffold protein and a central hub controlling this type of leukemia. The menin/WT MLL/MLL‐FP hub may also cooperate with several signaling pathways, including Wnt, GSK3, and bromodomain‐containing Brd4‐related pathways to sustain MLL‐FP‐induced leukemogenesis, revealing new therapeutic targets to improve the treatment of MLL‐FP leukemias. In MLL fusion protein‐induced leukemias, menin is a central hub due to its role in recruiting WT MLL and MLL‐FPs to target genes. Menin also links C‐Myb/LEDGF to the MLL N‐terminus, underscoring menin's central role. Targeting menin may be especially effective due to its hub role in MLL fusion leukemias.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/93527/1/771_ftp.pd

Global, regional, and national age-sex specific all-cause and cause-specific mortality for 240 causes of death, 1990-2013: A systematic analysis for the Global Burden of Disease Study 2013

Background Up-to-date evidence on levels and trends for age-sex-specific all-cause and cause-specific mortality is essential for the formation of global, regional, and national health policies. In the Global Burden of Disease Study 2013 (GBD 2013) we estimated yearly deaths for 188 countries between 1990, and 2013. We used the results to assess whether there is epidemiological convergence across countries. Methods We estimated age-sex-specific all-cause mortality using the GBD 2010 methods with some refinements to improve accuracy applied to an updated database of vital registration, survey, and census data. We generally estimated cause of death as in the GBD 2010. Key improvements included the addition of more recent vital registration data for 72 countries, an updated verbal autopsy literature review, two new and detailed data systems for China, and more detail for Mexico, UK, Turkey, and Russia. We improved statistical models for garbage code redistribution. We used six different modelling strategies across the 240 causes; cause of death ensemble modelling (CODEm) was the dominant strategy for causes with sufficient information. Trends for Alzheimer's disease and other dementias were informed by meta-regression of prevalence studies. For pathogen-specific causes of diarrhoea and lower respiratory infections we used a counterfactual approach. We computed two measures of convergence (inequality) across countries: the average relative difference across all pairs of countries (Gini coefficient) and the average absolute difference across countries. To summarise broad findings, we used multiple decrement life-tables to decompose probabilities of death from birth to exact age 15 years, from exact age 15 years to exact age 50 years, and from exact age 50 years to exact age 75 years, and life expectancy at birth into major causes. For all quantities reported, we computed 95% uncertainty intervals (UIs). We constrained cause-specific fractions within each age-sex-country-year group to sum to all-cause mortality based on draws from the uncertainty distributions. Findings Global life expectancy for both sexes increased from 65·3 years (UI 65·0-65·6) in 1990, to 71·5 years (UI 71·0-71·9) in 2013, while the number of deaths increased from 47·5 million (UI 46·8-48·2) to 54·9 million (UI 53·6-56·3) over the same interval. Global progress masked variation by age and sex: for children, average absolute differences between countries decreased but relative differences increased. For women aged 25-39 years and older than 75 years and for men aged 20-49 years and 65 years and older, both absolute and relative differences increased. Decomposition of global and regional life expectancy showed the prominent role of reductions in age-standardised death rates for cardiovascular diseases and cancers in high-income regions, and reductions in child deaths from diarrhoea, lower respiratory infections, and neonatal causes in low-income regions. HIV/AIDS reduced life expectancy in southern sub-Saharan Africa. For most communicable causes of death both numbers of deaths and age-standardised death rates fell whereas for most non-communicable causes, demographic shifts have increased numbers of deaths but decreased age-standardised death rates. Global deaths from injury increased by 10·7%, from 4·3 million deaths in 1990 to 4·8 million in 2013; but age-standardised rates declined over the same period by 21%. For some causes of more than 100 000 deaths per year in 2013, age-standardised death rates increased between 1990 and 2013, including HIV/AIDS, pancreatic cancer, atrial fibrillation and flutter, drug use disorders, diabetes, chronic kidney disease, and sickle-cell anaemias. Diarrhoeal diseases, lower respiratory infections, neonatal causes, and malaria are still in the top five causes of death in children younger than 5 years. The most important pathogens are rotavirus for diarrhoea and pneumococcus for lower respiratory infections. Country-specific probabilities of death over three phases of life were substantially varied between and within regions. Interpretation For most countries, the general pattern of reductions in age-sex specific mortality has been associated with a progressive shift towards a larger share of the remaining deaths caused by non-communicable disease and injuries. Assessing epidemiological convergence across countries depends on whether an absolute or relative measure of inequality is used. Nevertheless, age-standardised death rates for seven substantial causes are increasing, suggesting the potential for reversals in some countries. Important gaps exist in the empirical data for cause of death estimates for some countries; for example, no national data for India are available for the past decade. Funding Bill & Melinda Gates Foundation

International Consensus Statement on Rhinology and Allergy: Rhinosinusitis

Background: The 5 years since the publication of the first International Consensus Statement on Allergy and Rhinology: Rhinosinusitis (ICAR‐RS) has witnessed foundational progress in our understanding and treatment of rhinologic disease. These advances are reflected within the more than 40 new topics covered within the ICAR‐RS‐2021 as well as updates to the original 140 topics. This executive summary consolidates the evidence‐based findings of the document. Methods: ICAR‐RS presents over 180 topics in the forms of evidence‐based reviews with recommendations (EBRRs), evidence‐based reviews, and literature reviews. The highest grade structured recommendations of the EBRR sections are summarized in this executive summary. Results: ICAR‐RS‐2021 covers 22 topics regarding the medical management of RS, which are grade A/B and are presented in the executive summary. Additionally, 4 topics regarding the surgical management of RS are grade A/B and are presented in the executive summary. Finally, a comprehensive evidence‐based management algorithm is provided. Conclusion: This ICAR‐RS‐2021 executive summary provides a compilation of the evidence‐based recommendations for medical and surgical treatment of the most common forms of RS

mTOR kinase inhibitors promote antibody class switching via mTORC2 inhibition

The mammalian target of rapamycin (mTOR) is a kinase that functions in two distinct complexes, mTORC1 and mTORC2. In peripheral B cells, complete deletion of mTOR suppresses germinal center B-cell responses, including class switching and somatic hypermutation. The allosteric mTORC1 inhibitor rapamycin blocks proliferation and differentiation, but lower doses can promote protective IgM responses. To elucidate the complexity of mTOR signaling in B cells further, we used ATP-competitive mTOR kinase inhibitors (TOR-KIs), which inhibit both mTORC1 and mTORC2. Although TOR-KIs are in clinical development for cancer, their effects on mature lymphocytes are largely unknown. We show that high concentrations of TOR-KIs suppress B-cell proliferation and differentiation, yet lower concentrations that preserve proliferation increase the fraction of B cells undergoing class switching in vitro. Transient treatment of mice with the TOR-KI compound AZD8055 increased titers of class-switched high-affinity antibodies to a hapten–protein conjugate. Mechanistic investigation identified opposing roles for mTORC1 and mTORC2 in B-cell differentiation and showed that TOR-KIs enhance class switching in a manner dependent on forkhead box, subgroup O (FoxO) transcription factors. These observations emphasize the distinct actions of TOR-KIs compared with rapamycin and suggest that TOR-KIs might be useful to enhance production of class-switched antibodies following vaccination

Comparison of Pyrolysis Mass Spectrometry and Near Infrared Spectroscopy for Genetic Analysis of Lignocellulose Chemical Composition in Populus

Genetic analysis of wood chemical composition is often limited by the cost and throughput of direct analytical methods. The speed and low cost of Fourier transform near infrared (FT-NIR) overcomes many of these limitations, but it is an indirect method relying on calibration models that are typically developed and validated with small sample sets. In this study, we used >1500 young greenhouse grown trees from a clonally propagated single Populus family, grown at low and high nitrogen, and compared FT-NIR calibration sample sizes of 150, 250, 500 and 750 on calibration and prediction model statistics, and heritability estimates developed with pyrolysis molecular beam mass spectrometry (pyMBMS) wood chemical composition. As calibration sample size increased from 150 to 750, predictive model statistics improved slightly. Overall, stronger calibration and prediction statistics were obtained with lignin, S-lignin, S/G ratio, and m/z 144 (an ion from cellulose), than with C5 and C6 carbohydrates, and m/z 114 (an ion from xylan). Although small differences in model statistics were observed between the 250 and 500 sample calibration sets, when predicted values were used for calculating genetic control, the 500 sample set gave substantially more similar results to those obtained with the pyMBMS data. With the 500 sample calibration models, genetic correlations obtained with FT-NIR and pyMBMS methods were similar. Quantitative trait loci (QTL) analysis with pyMBMS and FT-NIR predictions identified only three common loci for lignin traits. FT-NIR identified four QTLs that were not found with pyMBMS data, and these QTLs were for the less well predicted carbohydrate traits