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"Meyer, H."
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Inheritance of paternal DNA damage by histone-mediated repair restriction
How paternal exposure to ionizing radiation affects genetic inheritance and disease risk in the offspring has been a long-standing question in radiation biology. In humans, nearly 80% of transmitted mutations arise in the paternal germline
1
, but the transgenerational effects of ionizing radiation exposure has remained controversial and the mechanisms are unknown. Here we show that in sex-separated
Caenorhabditis elegans
strains, paternal, but not maternal, exposure to ionizing radiation leads to transgenerational embryonic lethality. The offspring of irradiated males displayed various genome instability phenotypes, including DNA fragmentation, chromosomal rearrangement and aneuploidy. Paternal DNA double strand breaks were repaired by maternally provided error-prone polymerase theta-mediated end joining. Mechanistically, we show that depletion of an orthologue of human histone H1.0, HIS-24, or the heterochromatin protein HPL-1, could significantly reverse the transgenerational embryonic lethality. Removal of HIS-24 or HPL-1 reduced histone 3 lysine 9 dimethylation and enabled error-free homologous recombination repair in the germline of the F
1
generation from ionizing radiation-treated P
0
males, consequently improving the viability of the F
2
generation. This work establishes the mechanistic underpinnings of the heritable consequences of paternal radiation exposure on the health of offspring, which may lead to congenital disorders and cancer in humans.
In
Caenorhabditis elegans
, paternal exposure to ionizing radiation results in HIS-24 and HPL-1-dependent genome instability phenotypes, causing embryonic lethality in the offspring.
Journal Article
New venture creation : an innovator's guide to entrepreneurship
The authors establish innovation as a necessary first step before writing a business plan or developing a financial model. Focussing on high-technology ventures, this guide is devoted to helping students understand how innovation works and how to incorporate it into their process of conceptualizing and implementing their business idea.
Book
The Sexual Victimization of Men in America: New Data Challenge Old Assumptions
We assessed 12-month prevalence and incidence data on sexual victimization in 5 federal surveys that the Bureau of Justice Statistics, the Centers for Disease Control and Prevention, and the Federal Bureau of Investigation conducted independently in 2010 through 2012. We used these data to examine the prevailing assumption that men rarely experience sexual victimization. We concluded that federal surveys detect a high prevalence of sexual victimization among men—in many circumstances similar to the prevalence found among women. We identified factors that perpetuate misperceptions about men’s sexual victimization: reliance on traditional gender stereotypes, outdated and inconsistent definitions, and methodological sampling biases that exclude inmates. We recommend changes that move beyond regressive gender assumptions, which can harm both women and men.
Journal Article
Minority stress and physical health among sexual minority individuals
This study examined the effects of minority stress on the physical health of lesbians, gay men, and bisexuals (LGBs). Participants (
N
= 396) completed baseline and one year follow-up interviews. Exposure to stress and health outcomes were assessed with two methods: a subjective self-appraisal method and a method whereby two independent judges externally rated event narratives using standardized criteria. The odds of experiencing a physical health problem at follow-up were significantly higher among LGBs who experienced an externally rated prejudice event during the follow-up period compared to those who did not. This association persisted after adjusting for experiences of general stressful life events that were not related to prejudice. Self-appraised minority stress exposures were not associated with poorer physical health at 1-year follow-up. Prejudice-related stressful life events have a unique deleterious impact on health that persists above and beyond the effect of stressful life events unrelated to prejudice.
Journal Article
Hate crimes against LGBT people: National Crime Victimization Survey, 2017-2019
We estimate the prevalence and characteristics of violent hate crime victimization of lesbian, gay, bisexual, and transgender (LGBT) people in the United States, and we compare them to non-LGBT hate crime victims and to LGBT victims of violent non-hate crime. We analyze pooled 2017-2019 data from the National Crime Victimization Survey ( n persons = 553, 925; n incidents = 32, 470), the first nationally representative and comprehensive survey on crime that allows identification of LGBT persons aged 16 or older. Descriptive and bivariate analysis show that LGBT people experienced 6.6 violent hate crime victimizations per 1,000 persons compared with non-LGBT people’s 0.6 per 1,000 persons (odds ratio = 8.30, 95% confidence interval = 1.94, 14.65). LGBT people were more likely to be hate crime victims of sexual orientation or gender bias crime and less likely to be victims of race or ethnicity bias crimes compared to non-LGBT hate crime victims. Compared to non-LGBT victims, LGBT victims of hate crime were more likely to be younger, have a relationship with their assailant, and have an assailant who is white. Compared to LGBT victims of non-hate violence, more LGBT hate crime victims reported experiencing problems in their social lives, negative emotional responses, and physical symptoms of distress. Our findings affirm claims that hate crimes have adverse physical and psychological effects on victims and highlight the need to ensure that LGBT persons who experience hate crime get necessary support and services in the aftermath of the crime.
Journal Article
Brain Tumor Segmentation Using an Ensemble of 3D U-Nets and Overall Survival Prediction Using Radiomic Features
Accurate segmentation of different sub-regions of gliomas such as peritumoral edema, necrotic core, enhancing, and non-enhancing tumor core from multimodal MRI scans has important clinical relevance in diagnosis, prognosis and treatment of brain tumors. However, due to the highly heterogeneous appearance and shape of these tumors, segmentation of the sub-regions is challenging. Recent developments using deep learning models has proved its effectiveness in various semantic and medical image segmentation tasks, many of which are based on the U-Net network structure with symmetric encoding and decoding paths for end-to-end segmentation due to its high efficiency and good performance. In brain tumor segmentation, the 3D nature of multimodal MRI poses challenges such as memory and computation limitations and class imbalance when directly adopting the U-Net structure. In this study we aim to develop a deep learning model using a 3D U-Net with adaptations in the training and testing strategies, network structures, and model parameters for brain tumor segmentation. Furthermore, instead of picking one best model, an ensemble of multiple models trained with different hyper-parameters are used to reduce random errors from each model and yield improved performance. Preliminary results demonstrate the effectiveness of this method and achieved the 9th place in the very competitive 2018 Multimodal Brain Tumor Segmentation (BraTS) challenge. In addition, to emphasize the clinical value of the developed segmentation method, a linear model based on the radiomics features extracted from segmentation and other clinical features are developed to predict patient overall survival. Evaluation of these innovations shows high prediction accuracy in both low-grade glioma and glioblastoma patients, which achieved the 1st place in the 2018 BraTS challenge.
Journal Article