Gender Differences in Completed Schooling

This paper summarizes the dramatic changes in relative male-females educational attainment over the past three decades. Stock measures of education among the entire adult population show rising attainment levels for both men and women, with men enjoying an advantage in schooling levels throughout this interval. Cohort specific analysis reveals that these stock measures mask two interesting patterns: (a) gender difference at the cohort level had vanished by the early 1950 birth cohort and reversed sign ever since; (b) for several cohorts, attainment rates were flat for women and flat and falling for men. This last is puzzling in the face of the large college premia that these cohorts observed when making their schooling choices. We present a simple human capital model showing how the anticipated dispersion of future wages should affect educational investment and find that a model which includes measures of future earnings dispersion fits the data for relative schooling patterns quite well.

Breast Cancer Medications and Vision: Effects of Treatments for Early-stage Disease

This review concerns the effects on vision and the eye of medications prescribed at three phases of treatment for women with early-stage breast cancer (BC): (1) adjuvant cytotoxic chemotherapy, (2) adjuvant endocrine therapy, and (3) symptomatic relief. The most common side effects of cytotoxic chemotherapy are epiphora and ocular surface irritation, which can be caused by any of several different regimens. Most notably, the taxane docetaxel can lead to epiphora by inducing canalicular stenosis. The selective-estrogen-receptor-modulator (SERM) tamoxifen, long the gold-standard adjuvant-endocrine-therapy for women with hormone-receptor-positive BC, increases the risk of posterior subcapsular cataract. Tamoxifen also affects the optic nerve head more often than previously thought, apparently by causing subclinical swelling within the first 2 years of use for women older than ∼50 years. Tamoxifen retinopathy is rare, but it can cause foveal cystoid spaces that are revealed with spectral-domain optical coherence tomography (OCT) and that may increase the risk for macular holes. Tamoxifen often alters the perceived color of flashed lights detected via short-wavelength-sensitive (SWS) cone response isolated psychophysically; these altered perceptions may reflect a neural-response sluggishness that becomes evident at ∼2 years of use. The aromatase inhibitor (AI) anastrozole affects perception similarly, but in an age-dependent manner suggesting that the change of estrogen activity towards lower levels is more important than the low estrogen activity itself. Based on analysis of OCT retinal thickness data, it is likely that anastrozole increases the tractional force between the vitreous and retina. Consequently, AI users, myopic AI users particularly, might be at increased risk for traction-related vision loss. Because bisphosphonates are sometimes prescribed to redress AI-induced bone loss, clinicians should be aware of their potential to cause scleritis and uveitis occasionally. We conclude by suggesting some avenues for future research into the visual and ocular effects of AIs, particularly as relates to assessment of cognitive function

Estimating Water Yields in Utah by Principal Component Analysis

The basic hydrologic data required to determine the water yield are usually unavailable for small basins and streams while increasing emphasis is being placed on their development. Therefore, some methods and techniques for estimating the amount of water available for development of these small units is needed. The purpose of this study is to use the concepts and techniques of statistical analysis to develop equations which are useful in estimating the water yield of watersheds for which no stream flow records are available. The approach is an extension of earlier studies at Utah State University (1, 10) in which physiographic and topographic parameters were related to mean annual runoff of Utah watersheds. Previous studies used multiple regression techniques primarily. The work reported herein utilizes the same data as in the earlier work but analysis is based on the multivariate technique of principal component analysis. Results and evaluations derived from the principal component analysis are compared with those obtained from multiple regression analysis

Application of Multivariate Analysis in Predicting Water Yields in Utah

The basic hydrologic data required to determine the water yield are usually unavailable for small basins and streams while increasing emphasis is being placed on their development. Therefore, some methods and techniques for estimating the amount of water available for development of these small units is needed . The purpose of this study is to use the concepts and techniques of statistical analysis to develop equations which are useful in estimating the water yield of watersheds for which no stream flow records are available . The approach is an extension of earlier studies at Utah State University (1, lQ) in which physiographic and topographic parameters were related to mean annual runoff of Utah watersheds. Previous studies used multiple regression techniques primarily . The work reported herein utilizes the same data as in the earlier work but analysis is based on the multivariate technique of principal component analysis. Results and evaluations derived from the principal component analysis are compared with those obtained from multiple regression analysis

Direct genetic demonstration of Gα13 coupling to the orphan G protein-coupled receptor G2A leading to RhoA-dependent actin rearrangement

G2A is an orphan G protein-coupled receptor (GPCR), expressed predominantly in T and B cells and homologous to a small group of GPCRs of unknown function expressed in lymphoid tissues. G2A is transcriptionally induced in response to diverse stimuli, and its ectopic expression suppresses transformation of B lymphoid precursors by BCR-ABL. G2A induces morphological transformation of NIH 3T3 fibroblasts. Microinjection of constructs encoding G2A into Swiss 3T3 fibroblasts induces actin reorganization into stress fibers that depends on RhoA, but not CDC42 or RAC. G2A elicits RhoA-dependent transcriptional activation of serum response factor. Direct evaluation of RhoA activity demonstrates elevated levels of RhoA-GTP in G2A-expressing cells. Microinjection of embryonic fibroblasts derived from various Galpha knockout mice establishes a requirement for Galpha 13 but not Galpha 12 or Galpha q/11 in G2A-induced actin rearrangement. In conclusion, G2A represents a family of GPCRs expressed in lymphocytes that may link diverse stimuli to cytoskeletal reorganization and transcriptional activation through a pathway involving Galpha 13 and RhoA

Electron Transfer Control in Soluble Methane Monooxygenase

The hydroxylation or epoxidation of hydrocarbons by bacterial multicomponent monooxygenases (BMMs) requires the interplay of three or four protein components. How component protein interactions control catalysis, however, is not well understood. In particular, the binding sites of the reductase components on the surface of their cognate hydroxylases and the role(s) that the regulatory proteins play during intermolecular electron transfer leading to the hydroxylase reduction have been enigmatic. Here we determine the reductase binding site on the hydroxylase of a BMM enzyme, soluble methane monooxygenase (sMMO) from Methylococcus capsulatus (Bath). We present evidence that the ferredoxin domain of the reductase binds to the canyon region of the hydroxylase, previously determined to be the regulatory protein binding site as well. The latter thus inhibits reductase binding to the hydroxylase and, consequently, intermolecular electron transfer from the reductase to the hydroxylase diiron active site. The binding competition between the regulatory protein and the reductase may serve as a control mechanism for regulating electron transfer, and other BMM enzymes are likely to adopt the same mechanism.National Institutes of Health (U.S.) (Grant GM032134)Waters Corporatio

Mutation of SIVA, a candidate metastasis gene identified from clonally related bilateral breast cancers, promotes breast cancer cell spread in vitro and in vivo.

Metastasis is the most dreaded outcome after a breast cancer diagnosis, and little is known regarding what triggers or promotes breast cancer to spread distally, or how to prevent or eradicate metastasis effectively. Bilateral breast cancers are an uncommon form of breast cancers. In our study, a percentage of bilateral breast cancers were clonally related based on copy number variation profiling. Whole exome sequencing and comparative sequence analysis revealed that a limited number of somatic mutations were acquired in this breast-to-breast metastasis that might promote breast cancer distant spread. One somatic mutation acquired was SIVA-D160N that displayed pro-metastatic phenotypes in vivo and in vitro. Over-expression of SIVA-D160N promoted migration and invasion of human MB-MDA-231 breast cancer cells in vitro, consistent with a dominant negative interfering function. When introduced via tail vein injection, 231 cells over-expressing SIVA-D160N displayed enhanced distant spread on IVIS imaging. Over-expression of SIVA-D160N promoted invasion and anchorage independent growth of mouse 4T1 breast cancer cells in vitro. When introduced orthotopically via mammary fat pad injection in syngeneic Balb/c mice, over-expression of SIVA-D160N in 4T1 cells increased orthotopically implanted mammary gland tumor growth as well as liver metastasis. Clonally related bilateral breast cancers represented a novel system to investigate metastasis and revealed a role of SIVA-D160N in breast cancer metastasis. Further characterization and understanding of SIVA function, and that of its interacting proteins, may elucidate mechanisms of breast cancer metastasis, providing clinically useful biomarkers and therapeutic targets

GeneHub-GEPIS: digital expression profiling for normal and cancer tissues based on an integrated gene database

GeneHub-GEPIS is a web application that performs digital expression analysis in human and mouse tissues based on an integrated gene database. Using aggregated expressed sequence tag (EST) library information and EST counts, the application calculates the normalized gene expression levels across a large panel of normal and tumor tissues, thus providing rapid expression profiling for a given gene. The backend GeneHub component of the application contains pre-defined gene structures derived from mRNA transcript sequences from major databases and includes extensive cross references for commonly used gene identifiers. ESTs are then linked to genes based on their precise genomic locations as determined by GMAP. This genome-based approach reduces incorrect matches between ESTs and genes, thus minimizing the noise seen with previous tools. In addition, the gene-centric design makes it possible to add several important features, including text searching capabilities, the ability to accept diverse input values, expression analysis for microRNAs, basic gene annotation, batch analysis and linking between mouse and human genes. GeneHub-GEPIS is available at http://www.cgl.ucsf.edu/Research/genentech/genehub-gepis/ or http://www.gepis.org/

Pharmacogenetic variants and risk of remdesivir-associated liver enzyme elevations in Million Veteran Program participants hospitalized with COVID-19

Remdesivir is the first US Food and Drug Administration (FDA)-approved drug for the treatment of coronavirus disease 2019 (COVID-19). We conducted a retrospective pharmacogenetic study to examine remdesivir-associated liver enzyme elevation among Million Veteran Program participants hospitalized with COVID-19 between March 15, 2020, and June 30, 2021. Pharmacogene phenotypes were assigned using Stargazer. Linear regression was performed on peak log-transformed enzyme values, stratified by population, adjusted for age, sex, baseline liver enzymes, comorbidities, and 10 population-specific principal components. Patients on remdesivir had higher peak alanine aminotransferase (ALT) values following treatment initiation compared with patients not receiving remdesivir. Remdesivir administration was associated with a 33% and 24% higher peak ALT in non-Hispanic White (NHW) and non-Hispanic Black (NHB) participants (p < 0.001), respectively. In a multivariable model, NHW CYP2C19 intermediate/poor metabolizers had a 9% increased peak ALT compared with NHW normal/rapid/ultrarapid metabolizers (p = 0.015); this association was not observed in NHB participants. In summary, remdesivir-associated ALT elevations appear to be multifactorial, and further studies are needed