Promoting Health Across the Lifespan: Relationships Topics

This document contains six lesson plans. The first lesson plan is designed to address sex in U.S. culture. The second lesson plan addresses healthy young adult relationships through the lenses of warning signs of unhealthy relationships, dating violence, and through the introduction of methods to improve an unhealthy relationship. The third lesson plan discusses healthy relationships utilizing self-assessment. The fourth lesson plan includes statistics about STIs and is designed to help identify prevention behaviors for safe sex. The fifth lesson plan is designed to address the principle of consent and information about sexual violence. The sixth lesson plan is designed as a simulation game to address the decision making process for individuals affected by an STI or unplanned pregnancy and provides resources for real encounters with these events. The content is intended for college-aged students and health care professionals. Each lesson plan has a topic overview, time and format information, Healthy People 2020 Objectives, National Health Education Standards information, learning objectives, key concepts and terms, materials needed, and teaching steps. This material was developed by Plymouth State University students as a part of their coursework for Promoting Health Across the Lifespan, in fall 2016 with Dr. Barbara McCahan

Genetic markers for screening animals for improved disease resistance (NRAMP)

A method for determining improved innate immunity, disease resistance or performance in animals is disclosed. The method involves assays for a genetic differences in the NRAMP1 gene of the animal which is associated with superior disease resistance. Novel NRAMP1 sequence, assays, and compositions for identifying the presence of absence of these alleles are provided

Association of bacterial infection traits with genetic variation at candidate genes for porcine disease resistance

We predict that it may be possible to improve pig disease resistance to Salmonella infection by studying genes that control a piglet’s initial immune response. The NRAMP1 gene controls susceptibility to multiple pathogens and acts within the macrophage. The BPI gene encodes a neutrophil protein with inhibitory/killing functions against multiple gram-negative bacteria. We investigated NRAMP1 and BPI as candidate genes for contributing to resistance in Salmonella choleraesuis (SC) challenge in pigs. Five NRAMP1 sequence differences (polymorphisms, SNPs) were found, while we cloned and sequenced the full-length BPI gene and identified four polymorphisms at BPI. The effects these polymorphisms have on resistance to infection were tested in two experimental disease studies. In study 1, results showed NRAMP1 and BPI genotypes were associated with decreased fecal bacterial load during infection (P values: \u3c .0006 to \u3c .06). Immune cell numbers were also associated with BPI genotypes. In the second study, many additional immune traits and spleen and liver bacterial counts were collected. The NRAMP1 genotypes were associated with bacterial count in liver (P \u3c .05 and P \u3c .0006) and with polymorphonuclear phagocytes (P values from \u3c .003 to \u3c .05). The BPI genotypes were significantly associated with bacteria uptake by immune cells and with bacterial counts in liver (P\u3c.1) and lymphocyte response post-challenge (P\u3c.0001). These data indicate NRAMP1 and/or BPI gene variation may control, in part, response to Salmonella infection in pigs, and that these differences could be used to identify resistant animals

An emerging viral pathogen truncates population age structure in a European amphibian and may reduce population viability

Infectious diseases can alter the demography of their host populations, reducing their viability even in the absence of mass mortality. Amphibians are the most threatened group of vertebrates globally, and emerging infectious diseases play a large role in their continued population declines. Viruses belonging to the genus Ranavirus are responsible for one of the deadliest and most widespread of these diseases. To date, no work has used individual level data to investigate how ranaviruses affect population demographic structure. We used skeletochronology and morphology to evaluate the impact of ranaviruses on the age structure of populations of the European common frog (Rana temporaria) in the UK. We compared ecologically similar populations that differed most notably in their historical presence or absence of ranavirosis (the acute syndrome caused by ranavirus infection). Our results suggest that ranavirosis may truncate the age structure of R. temporaria populations. One potential explanation for such a shift might be increased adult mortality and subsequent shifts in the life history of younger age classes that increase reproductive output earlier in life. Additionally, we constructed population projection models which indicated that such increased adult mortality could heighten the vulnerability of frog populations to stochastic environmental challenges

SPAG17 Mediates Nuclear Translocation of Protamines During Spermiogenesis

Protamines (PRM1 and PRM2) are small, arginine-rich, nuclear proteins that replace histones in the final stages of spermiogenesis, ensuring chromatin compaction and nuclear remodeling. Defects in protamination lead to increased DNA fragmentation and reduced male fertility. Since efficient sperm production requires the translocation of protamines from the cytoplasm to the nucleus, we investigated whether SPAG17, a protein crucial for intracellular protein trafficking during spermiogenesis, participates in protamine transport. Initially, we assessed the protein-protein interaction between SPAG17 and protamines using proximity ligation assays, revealing a significant interaction originating in the cytoplasm and persisting within the nucleus. Subsequently, immunoprecipitation and mass spectrometry (IP/MS) assays validated this initial observation. Sperm and spermatids fro

Common Raven Impacts on Nesting Western Snowy Plovers: Integrating Management to Facilitate Species Recovery

The U.S. Pacific coast population of the western snowy plover (Charadrius nivosus nivosus; plover) has declined due to loss and degradation of coastal habitats, predation, and anthropogenic disturbance. The U.S. Fish and Wildlife Service listed the subspecies in 1993 as threatened under the Endangered Species Act due to the population declines and habitat loss. Predation of nests and chicks has been identified as an important cause of historic population declines, and thus, most predator management actions for this subspecies are focused on reducing this pressure. In recent years, common ravens (Corvus corax; ravens) have become the most common and pervasive predators of plover nests and chicks, especially in areas with subsidized food sources for ravens and sites without predator management. We compiled data from a variety of sources to document the impact of raven predation on plover nesting success. We discuss current raven management and suggest several tools and strategies to increase plover nesting success, including multi-state approval for the use of the avicide DRC-1339, the use of lures and new trap types, and an increase in funding for predator management. The lack of coordinated and integrated management continues to impede the recovery of the Pacific coast plover population

A large annotated medical image dataset for the development and evaluation of segmentation algorithms

Semantic segmentation of medical images aims to associate a pixel with a label in a medical image without human initialization. The success of semantic segmentation algorithms is contingent on the availability of high-quality imaging data with corresponding labels provided by experts. We sought to create a large collection of annotated medical image datasets of various clinically relevant anatomies available under open source license to facilitate the development of semantic segmentation algorithms. Such a resource would allow: 1) objective assessment of general-purpose segmentation methods through comprehensive benchmarking and 2) open and free access to medical image data for any researcher interested in the problem domain. Through a multi-institutional effort, we generated a large, curated dataset representative of several highly variable segmentation tasks that was used in a crowd-sourced challenge - the Medical Segmentation Decathlon held during the 2018 Medical Image Computing and Computer Aided Interventions Conference in Granada, Spain. Here, we describe these ten labeled image datasets so that these data may be effectively reused by the research community

The Medical Segmentation Decathlon

International challenges have become the de facto standard for comparative assessment of image analysis algorithms given a specific task. Segmentation is so far the most widely investigated medical image processing task, but the various segmentation challenges have typically been organized in isolation, such that algorithm development was driven by the need to tackle a single specific clinical problem. We hypothesized that a method capable of performing well on multiple tasks will generalize well to a previously unseen task and potentially outperform a custom-designed solution. To investigate the hypothesis, we organized the Medical Segmentation Decathlon (MSD) - a biomedical image analysis challenge, in which algorithms compete in a multitude of both tasks and modalities. The underlying data set was designed to explore the axis of difficulties typically encountered when dealing with medical images, such as small data sets, unbalanced labels, multi-site data and small objects. The MSD challenge confirmed that algorithms with a consistent good performance on a set of tasks preserved their good average performance on a different set of previously unseen tasks. Moreover, by monitoring the MSD winner for two years, we found that this algorithm continued generalizing well to a wide range of other clinical problems, further confirming our hypothesis. Three main conclusions can be drawn from this study: (1) state-of-the-art image segmentation algorithms are mature, accurate, and generalize well when retrained on unseen tasks; (2) consistent algorithmic performance across multiple tasks is a strong surrogate of algorithmic generalizability; (3) the training of accurate AI segmentation models is now commoditized to non AI experts

GA4GH: International policies and standards for data sharing across genomic research and healthcare.

The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits

New insights into the genetic etiology of Alzheimer's disease and related dementias

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele