Effects of Pharmacologically Induced Hypogonadism on Mood and Behavior in Healthy Young Women

The relationship between depression and estrogen withdrawal remains controversial. The authors examined the effects of gonadotropin-releasing hormone agonist-induced ovarian suppression on mood, sleep, sexual function, and nighttime hot flushes. They focused on whether participating women experienced clinically significant depressive symptoms and whether specific symptoms associated with hypogonadism (nighttime hot flushes and disturbed sleep) increased susceptibility to depression

Effects of Estradiol Withdrawal on Mood in Women With Past Perimenopausal Depression: A Randomized Clinical Trial

IMPORTANCE: Perimenopause is accompanied by an increased risk of new and recurrent depression. The coincidence of declining ovarian function with the onset of depression led to the inference that "withdrawal" from physiologic estradiol levels underpinned depression in perimenopause. To our knowledge, this is the first controlled systematic study to directly test the estrogen withdrawal theory of perimenopausal depression (PMD). OBJECTIVE: To examine the role of estradiol withdrawal in PMD. DESIGN, SETTING, AND PARTICIPANTS: Initial open-label treatment with estradiol followed by randomized, double-blind, placebo-controlled, parallel-design evaluation of continued estradiol treatment was evaluated at an outpatient research facility at the National Institutes of Health Clinical Center. An intent-to-treat analysis was performed between October 2003 and July 2012. Participants included asymptomatic postmenopausal women with past PMD responsive to hormone therapy (n = 26) and asymptomatic postmenopausal women with no history of depression (n = 30) matched for age, body mass index, and reproductive status who served as controls. Data were analyzed between November 2012 and October 2013 by repeated-measures analysis of variance. INTERVENTIONS: After 3 weeks of open-label administration of transdermal estradiol (100 µg/d), participants were randomized to a parallel design to receive either estradiol (100 µg/d; 27 participants) or matched placebo skin patches (29 participants) for 3 additional weeks under double-blind conditions. MAIN OUTCOMES AND MEASURES: Center for Epidemiologic Studies-Depression Scale and 17-item Hamilton Depression Rating Scale (completed by raters blind to diagnosis and randomization status), self-administered visual analog symptom ratings, and blood hormone levels obtained at weekly clinic visits. RESULTS: None of the women reported depressive symptoms during open-label use of estradiol. Women with past PMD who were crossed over from estradiol to placebo experienced a significant increase in depression symptom severity demonstrated using the Center for Epidemiologic Studies-Depression Scale and 17-item Hamilton Depression Rating Scale, with mean (SD) scores increasing from estradiol (ie, 2.4 [2.0] and 3.0 [2.5]) to placebo (8.8 [4.9] and 6.6 [4.5], respectively [P = .0004 for both]). Women with past PMD who continued estradiol therapy and all women in the control group remained asymptomatic. Women in both groups had similar hot-flush severity and plasma estradiol levels during use of placebo. CONCLUSIONS AND RELEVANCE: In women with past PMD that was previously responsive to hormone therapy, the recurrence of depressive symptoms during blinded hormone withdrawal suggests that normal changes in ovarian estradiol secretion can trigger an abnormal behavioral state in these susceptible women. Women with a history of PMD should be alert to the risk of recurrent depression when discontinuing hormone therapy. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT00060736

On the Use of Unmanned Aerial Systems for Environmental Monitoring

Environmental monitoring plays a central role in diagnosing climate and management impacts on natural and agricultural systems; enhancing the understanding of hydrological processes; optimizing the allocation and distribution of water resources; and assessing, forecasting, and even preventing natural disasters. Nowadays, most monitoring and data collection systems are based upon a combination of ground-based measurements, manned airborne sensors, and satellite observations. These data are utilized in describing both small- and large-scale processes, but have spatiotemporal constraints inherent to each respective collection system. Bridging the unique spatial and temporal divides that limit current monitoring platforms is key to improving our understanding of environmental systems. In this context, Unmanned Aerial Systems (UAS) have considerable potential to radically improve environmental monitoring. UAS-mounted sensors offer an extraordinary opportunity to bridge the existing gap between field observations and traditional air- and space-borne remote sensing, by providing high spatial detail over relatively large areas in a cost-effective way and an entirely new capacity for enhanced temporal retrieval. As well as showcasing recent advances in the field, there is also a need to identify and understand the potential limitations of UAS technology. For these platforms to reach their monitoring potential, a wide spectrum of unresolved issues and application-specific challenges require focused community attention. Indeed, to leverage the full potential of UAS-based approaches, sensing technologies, measurement protocols, postprocessing techniques, retrieval algorithms, and evaluation techniques need to be harmonized. The aim of this paper is to provide an overview of the existing research and applications of UAS in natural and agricultural ecosystem monitoring in order to identify future directions, applications, developments, and challengespublishersversionPeer reviewe

Learning Transcriptional Regulatory Relationships Using Sparse Graphical Models

Understanding the organization and function of transcriptional regulatory networks by analyzing high-throughput gene expression profiles is a key problem in computational biology. The challenges in this work are 1) the lack of complete knowledge of the regulatory relationship between the regulators and the associated genes, 2) the potential for spurious associations due to confounding factors, and 3) the number of parameters to learn is usually larger than the number of available microarray experiments. We present a sparse (L1 regularized) graphical model to address these challenges. Our model incorporates known transcription factors and introduces hidden variables to represent possible unknown transcription and confounding factors. The expression level of a gene is modeled as a linear combination of the expression levels of known transcription factors and hidden factors. Using gene expression data covering 39,296 oligonucleotide probes from 1109 human liver samples, we demonstrate that our model better predicts out-of-sample data than a model with no hidden variables. We also show that some of the gene sets associated with hidden variables are strongly correlated with Gene Ontology categories. The software including source code is available at http://grnl1.codeplex.com

Detection of recurrent rearrangement breakpoints from copy number data

<p>Abstract</p> <p>Background</p> <p>Copy number variants (CNVs), including deletions, amplifications, and other rearrangements, are common in human and cancer genomes. Copy number data from array comparative genome hybridization (aCGH) and next-generation DNA sequencing is widely used to measure copy number variants. Comparison of copy number data from multiple individuals reveals recurrent variants. Typically, the interior of a recurrent CNV is examined for genes or other loci associated with a phenotype. However, in some cases, such as gene truncations and fusion genes, the target of variant lies at the boundary of the variant.</p> <p>Results</p> <p>We introduce Neighborhood Breakpoint Conservation (NBC), an algorithm for identifying rearrangement breakpoints that are highly conserved at the same locus in multiple individuals. NBC detects recurrent breakpoints at varying levels of resolution, including breakpoints whose location is exactly conserved and breakpoints whose location varies within a gene. NBC also identifies pairs of recurrent breakpoints such as those that result from fusion genes. We apply NBC to aCGH data from 36 primary prostate tumors and identify 12 novel rearrangements, one of which is the well-known TMPRSS2-ERG fusion gene. We also apply NBC to 227 glioblastoma tumors and predict 93 novel rearrangements which we further classify as gene truncations, germline structural variants, and fusion genes. A number of these variants involve the protein phosphatase PTPN12 suggesting that deregulation of PTPN12, via a variety of rearrangements, is common in glioblastoma.</p> <p>Conclusions</p> <p>We demonstrate that NBC is useful for detection of recurrent breakpoints resulting from copy number variants or other structural variants, and in particular identifies recurrent breakpoints that result in gene truncations or fusion genes. Software is available at <url>http://http.//cs.brown.edu/people/braphael/software.html</url>.</p

Enhanced production yields of rVSV-SARS-CoV-2 vaccine using Fibra-Cel® macrocarriers

The COVID-19 pandemic has led to high global demand for vaccines to safeguard public health. To that end, our institute has developed a recombinant viral vector vaccine utilizing a modified vesicular stomatitis virus (VSV) construct, wherein the G protein of VSV is replaced with the spike protein of SARS-CoV-2 (rVSV-ΔG-spike). Previous studies have demonstrated the production of a VSV-based vaccine in Vero cells adsorbed on Cytodex 1 microcarriers or in suspension. However, the titers were limited by both the carrier surface area and shear forces. Here, we describe the development of a bioprocess for rVSV-ΔG-spike production in serum-free Vero cells using porous Fibra-Cel® macrocarriers in fixed-bed BioBLU®320 5p bioreactors, leading to high-end titers. We identified core factors that significantly improved virus production, such as the kinetics of virus production, the use of macrospargers for oxygen supply, and medium replenishment. Implementing these parameters, among others, in a series of GMP production processes improved the titer yields by at least two orders of magnitude (2e9 PFU/mL) over previously reported values. The developed process was highly effective, repeatable, and robust, creating potent and genetically stable vaccine viruses and introducing new opportunities for application in other viral vaccine platforms