The preparation and characterization of a series of isostructural cobalt complexes [Co(t-Bu)2P(E)Py(E)P(t-Bu)2(CH3CN)2][BF4]2 (Py = pyridine, E = CH2, NH, O, and X = BF4 (1a-c)) and the corresponding one-electron reduced analogues [Co(t-Bu)2P(E)Py(E)P(t-Bu)2(CH3CN)2][BF4]2 (2a-c) are reported. The reactivity of the reduced cobalt complexes with CO2, CO, and H(+) to generate intermediates in a CO2 to CO and H2O reduction cycle are described. The reduction of 1a-c and subsequent reactivity with CO2 was investigated by cyclic voltammetry, and for 1a also by infrared spectroelectrochemistry. The corresponding CO complexes of (2a-c) were prepared, and the Co-CO bond strengths were characterized by IR spectroscopy. Quantum mechanical methods (B3LYP-d3 with solvation) were used to characterize the competitive reactivity of the reduced cobalt centers with H(+) versus CO2. By investigating a series of isostructural complexes, correlations in reactivity with ligand electron withdrawing effects are made.

Objective

Determine maternal and infant characteristics associated with adding cereal into the bottle.

Design

Secondary data analysis.

Participants

Study participants were immigrant, low-income, urban mother-infant dyads (n = 216; 91% Hispanic, 19% US-born) enrolled in a randomized controlled trial entitled the Bellevue Project for Early Language, Literacy and Education Success.

Main outcome measures

Maternal characteristics (age, marital status, ethnicity, primary language, country of origin, education, work status, income, depressive symptoms, and concern about infant's future weight) and infant characteristics (gender, first born, and difficult temperament).

Analysis

Fisher exact test, chi-square test, and simultaneous multiple logistic regression of significant (P < .05) variables identified in unadjusted analyses.

Results

Twenty-seven percent of mothers added cereal into the bottle. After adjusting for confounding variables identified in bivariate analyses, mothers who were single (P = .02), had moderate to severe depressive symptoms (P = .01) and perceived their infant had a difficult temperament (P = .03) were more likely to add cereal into the bottle. Conversely, mothers who expressed concern about their infants becoming overweight were less likely to add cereal (P = .02).

Conclusions and implications

Health care providers should screen for adding cereal in infant bottles. Further research is needed to investigate the impact of adding cereal into the bottle on weight trajectories over time. Causal associations also need to be identified to effectively prevent this practice.

We evaluated ancestry effects on mutation rates, DNA methylation, and mRNA and miRNA expression among 10,678 patients across 33 cancer types from The Cancer Genome Atlas. We demonstrated that cancer subtypes and ancestry-related technical artifacts are important confounders that have been insufficiently accounted for. Once accounted for, ancestry-associated differences spanned all molecular features and hundreds of genes. Biologically significant differences were usually tissue specific but not specific to cancer. However, admixture and pathway analyses suggested some of these differences are causally related to cancer. Specific findings included increased FBXW7 mutations in patients of African origin, decreased VHL and PBRM1 mutations in renal cancer patients of African origin, and decreased immune activity in bladder cancer patients of East Asian origin.

Differential mRNA expression between ancestry groups can be explained by both genetic and environmental factors. We outline a computational workflow to determine the extent to which germline genetic variation explains cancer-specific molecular differences across ancestry groups. Using multi-omics datasets from The Cancer Genome Atlas (TCGA), we enumerate ancestry-informative markers colocalized with cancer-type-specific expression quantitative trait loci (e-QTLs) at ancestry-associated genes. This approach is generalizable to other settings with paired germline genotyping and mRNA expression data for a multi-ethnic cohort. For complete details on the use and execution of this protocol, please refer to Carrot-Zhang et al. (2020), Robertson et al. (2021), and Sayaman et al. (2021).

People of different ancestries vary in cancer risk and outcome, and their molecular differences may indicate sources of these variations. Determining the "local" ancestry composition at each genetic locus across ancestry-admixed populations can suggest causal associations. We present a protocol to identify local ancestry and detect the associated molecular changes, using data from the Cancer Genome Atlas. This workflow can be applied to cancer cohorts with matched tumor and normal data from admixed patients to examine germline contributions to cancer. For complete details on the use and execution of this protocol, please refer to Carrot-Zhang et al. (2020).

RTK/RAS/RAF pathway alterations (RPAs) are a hallmark of lung adenocarcinoma (LUAD). In this study, we use whole-genome sequencing (WGS) of 85 cases found to be RPA(-) by previous studies from The Cancer Genome Atlas (TCGA) to characterize the minority of LUADs lacking apparent alterations in this pathway. We show that WGS analysis uncovers RPA(+) in 28 (33%) of the 85 samples. Among the remaining 57 cases, we observe focal deletions targeting the promoter or transcription start site of STK11 (n = 7) or KEAP1 (n = 3), and promoter mutations associated with the increased expression of ILF2 (n = 6). We also identify complex structural variations associated with high-level copy number amplifications. Moreover, an enrichment of focal deletions is found in TP53 mutant cases. Our results indicate that RPA(-) cases demonstrate tumor suppressor deletions and genome instability, but lack unique or recurrent genetic lesions compensating for the lack of RPAs. Larger WGS studies of RPA(-) cases are required to understand this important LUAD subset.

(Cell Reports 23, 313–326; April 3, 2018) In the originally published version of this article, the author list contained two errors. Specifically, David J. Kwiatkowski was misspelled as David J. Kwaitkowski, and William Y. Kim was inadvertently written as William T. Kim. Both names have been corrected online. The authors regret this error.

(Immunity 48, 812–830.e1–e14; April 17, 2018) In the originally published version of this article, the authors neglected to include Younes Mokrab and Aaron M. Newman as co-authors and misspelled the names of authors Charles S. Rabkin and Ilya Shmulevich. The author names have been corrected here and online. In addition, the concluding sentence of the subsection “Immune Signature Compilation” in the Method Details in the original published article was deemed unclear because it did not specify differences among the gene set scoring methods. The concluding sentences now reads “Gene sets from Bindea et al., Senbabaoglu et al., and the MSigDB C7 collection were scored using single-sample gene set enrichment (ssGSEA) analysis (Barbie et al., 2009), as implemented in the GSVA R package (Hänzelmann et al., 2013). All other signatures were scored using methods found in the associated citations.”