Birth Weight as a Risk Factor for Breast Cancer: a Meta-Analysis of 18 Epidemiologic Studies

Background: Birth weight has been identified as a birth-related factor associated with the risk of breast cancer. However, the evidence is inconsistent. Methods: To investigate the association between birth weight and breast cancer, we conducted a meta-analysis of published studies between 1996 and 2008. Eighteen studies encompassing 16,424 breast cancer cases were included in the meta-analysis. Data were combined using a fixed-effect or random-effect model depending on the heterogeneity across studies. Results: Women with their own birth weight \u3e4000 g or 8.5 lb had a higher risk for developing breast cancer than those with birth weight(OR¼1.20, 95% CI 1.08, 1.34). Findings were also consistent with a dose-response pattern effect. The summary effect estimate for breast cancer risk per 1 kg increase in birth weight was statistically significant (random effects OR¼1.07, 95% CI 1.02, 1.12). Conclusions: Although these results provided no evidence indicating whether birth weight is more strongly related to early-onset than to later-onset breast cancer, our findings suggest an association between birth weight and breast cancer. The underlying biological mechanism relating to this phenomenon needs additional study

A Remote Substrate Docking Mechanism for the Tec Family Tyrosine Kinases

During T cell signaling, Itk selectively phosphorylates a tyrosine within its own SH3 domain and a tyrosine within PLCγ1. We find that the remote SH2 domain in each of these substrates is required to achieve efficient tyrosine phosphorylation by Itk and extend this observation to two other Tec family kinases, Btk and Tec. Additionally, we detect a stable interaction between the substrate SH2 domains and the kinase domain of Itk and find that addition of specific, exogenous SH2 domains to the in vitro kinase assay competes directly with substrate phosphorylation. On the basis of these results, we show that the kinetic parameters of a generic peptide substrate of Itk are significantly improved via fusion of the peptide substrate to the SH2 domain of PLCγ1. This work is the first characterization of a substrate docking mechanism for the Tec kinases and provides evidence of a novel, phosphotyrosine-independent regulatory role for the ubiquitous SH2 domain

Single-cell western blotting.

To measure cell-to-cell variation in protein-mediated functions, we developed an approach to conduct ∼10(3) concurrent single-cell western blots (scWesterns) in ∼4 h. A microscope slide supporting a 30-μm-thick photoactive polyacrylamide gel enables western blotting: settling of single cells into microwells, lysis in situ, gel electrophoresis, photoinitiated blotting to immobilize proteins and antibody probing. We applied this scWestern method to monitor single-cell differentiation of rat neural stem cells and responses to mitogen stimulation. The scWestern quantified target proteins even with off-target antibody binding, multiplexed to 11 protein targets per single cell with detection thresholds of <30,000 molecules, and supported analyses of low starting cell numbers (∼200) when integrated with FACS. The scWestern overcomes limitations of antibody fidelity and sensitivity in other single-cell protein analysis methods and constitutes a versatile tool for the study of complex cell populations at single-cell resolution

Potential health impacts of heavy metals on HIV-infected population in USA.

Noninfectious comorbidities such as cardiovascular diseases have become increasingly prevalent and occur earlier in life in persons with HIV infection. Despite the emerging body of literature linking environmental exposures to chronic disease outcomes in the general population, the impacts of environmental exposures have received little attention in HIV-infected population. The aim of this study is to investigate whether individuals living with HIV have elevated prevalence of heavy metals compared to non-HIV infected individuals in United States. We used the National Health and Nutrition Examination Survey (NHANES) 2003-2010 to compare exposures to heavy metals including cadmium, lead, and total mercury in HIV infected and non-HIV infected subjects. In this cross-sectional study, we found that HIV-infected individuals had higher concentrations of all heavy metals than the non-HIV infected group. In a multivariate linear regression model, HIV status was significantly associated with increased blood cadmium (p=0.03) after adjusting for age, sex, race, education, poverty income ratio, and smoking. However, HIV status was not statistically associated with lead or mercury levels after adjusting for the same covariates. Our findings suggest that HIV-infected patients might be significantly more exposed to cadmium compared to non-HIV infected individuals which could contribute to higher prevalence of chronic diseases among HIV-infected subjects. Further research is warranted to identify sources of exposure and to understand more about specific health outcomes

Identifiable and interpretable nonparametric factor analysis

Factor models have been widely used to summarize the variability of high-dimensional data through a set of factors with much lower dimensionality. Gaussian linear factor models have been particularly popular due to their interpretability and ease of computation. However, in practice, data often violate the multivariate Gaussian assumption. To characterize higher-order dependence and nonlinearity, models that include factors as predictors in flexible multivariate regression are popular, with GP-LVMs using Gaussian process (GP) priors for the regression function and VAEs using deep neural networks. Unfortunately, such approaches lack identifiability and interpretability and tend to produce brittle and non-reproducible results. To address these problems by simplifying the nonparametric factor model while maintaining flexibility, we propose the NIFTY framework, which parsimoniously transforms uniform latent variables using one-dimensional nonlinear mappings and then applies a linear generative model. The induced multivariate distribution falls into a flexible class while maintaining simple computation and interpretation. We prove that this model is identifiable and empirically study NIFTY using simulated data, observing good performance in density estimation and data visualization. We then apply NIFTY to bird song data in an environmental monitoring application.Comment: 50 pages, 17 figure

Aligning Sub-national Climate Actions for the new post-Paris Climate Regime

The rise of sub-national actors in global climate governance underscores the need for clear alignment between these efforts and their national counterparts. As these sub-national climate actions are filling gaps in mitigation, adaptation, and financing, among other functions, a critical question is how these efforts complement or overlap with national climate pledges. This consideration is particularly important in the context of the Paris Agreement’s mandate for fiveyear review cycles, where national governments will be asked to demonstrate progress towards climate mitigation goals and increase their ambition. In this paper, we argue that alignment – both vertically between multiple jurisdictions and horizontally with external networks and actors – is critical to clarifying climate actions between multiple levels of actors and to maximizing mitigation potential. We use nine case studies to demonstrate the varying degrees and modes of vertical integration between subnational and national climate actors. We find that the case studies embody different styles of vertical alignment, and exhibit significant variation in the degree and direction of vertical alignment within each of these modes. We also find that many case studies rely on horizontally- aligned international networks and coalitions to fill gaps in financial resources or technical support. As a proof of concept, we demonstrate that an additional 1 gigaton carbon dioxide equivalent (CO2e) in 2020 can be achieved in these nine case studies through stronger alignment that makes it possible to scale sub-national climate actions to the national level. These findings suggest there may be a missed opportunity to realize greater mitigation potential by fostering stronger vertical alignment, and enhancing coordination between horizontal networks of climate action and national governments

Underestimating Our Influence over Others’ Unethical Behavior and Decisions

We examined the psychology of “instigators,” i.e., people who surround an unethical act and influence the wrongdoer (the “actor”) without directly committing the act themselves. In four studies, we found that instigators of unethical acts underestimated their influence over actors. In Studies 1 and 2, university students enlisted other students to commit a “white lie” (Study 1) or commit a small act of vandalism (Study 2) after making predictions about how easy it would be to get their fellow students to do so. In Studies 3 and 4, online samples of participants responded to hypothetical vignettes, e.g., about buying children alcohol, and taking office supplies home for personal use. In all 4 studies, instigators failed to recognize the social pressure they levied on actors through simple unethical suggestions, i.e., the discomfort actors would experience by making a decision that was inconsistent with the instigator’s suggestion