Contested Language and the Study of Later Life

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A Universal, Genomewide GuideFinder for CRISPR/Cas9 Targeting in Microbial Genomes.

The CRISPR/Cas system has significant potential to facilitate gene editing in a variety of bacterial species. CRISPR interference (CRISPRi) and CRISPR activation (CRISPRa) represent modifications of the CRISPR/Cas9 system utilizing a catalytically inactive Cas9 protein for transcription repression and activation, respectively. While CRISPRi and CRISPRa have tremendous potential to systematically investigate gene function in bacteria, few programs are specifically tailored to identify guides in draft bacterial genomes genomewide. Furthermore, few programs offer open-source code with flexible design parameters for bacterial targeting. To address these limitations, we created GuideFinder, a customizable, user-friendly program that can design guides for any annotated bacterial genome. GuideFinder designs guides from NGG protospacer-adjacent motif (PAM) sites for any number of genes by the use of an annotated genome and FASTA file input by the user. Guides are filtered according to user-defined design parameters and removed if they contain any off-target matches. Iteration with lowered parameter thresholds allows the program to design guides for genes that did not produce guides with the more stringent parameters, one of several features unique to GuideFinder. GuideFinder can also identify paired guides for targeting multiplicity, whose validity we tested experimentally. GuideFinder has been tested on a variety of diverse bacterial genomes, finding guides for 95% of genes on average. Moreover, guides designed by the program are functionally useful-focusing on CRISPRi as a potential application-as demonstrated by essential gene knockdown in two staphylococcal species. Through the large-scale generation of guides, this open-access software will improve accessibility to CRISPR/Cas studies of a variety of bacterial species

Burst pressure prediction of API 5L X-grade dented pipelines using deep neural network

Mechanical damage is recognized as a problem that reduces the performance of oil and gas pipelines and has been the subject of continuous research. The artificial neural network in the spotlight recently is expected to be another solution to solve the problems relating to the pipelines. The deep neural network, which is on the basis of artificial neural network algorithm and is a method amongst various machine learning methods, is applied in this study. The applicability of machine learning techniques such as deep neural network for the prediction of burst pressure has been investigated for dented API 5L X-grade pipelines. To this end, supervised learning is employed, and the deep neural network model has four layers with three hidden layers, and the neural network uses the fully connected layer. The burst pressure computed by deep neural network model has been compared with the results of finite element analysis based parametric study, and the burst pressure calculated by the experimental results. According to the comparison results, it showed good agreement. Therefore, it is concluded that deep neural networks can be another solution for predicting the burst pressure of API 5L X-grade dented pipelines

Global Learnings Evidence Brief: Protecting Health Care Workers in South Korea During the COVID-19 Pandemic

The research outlines how South Korea has successfully maintained one of the world’s lowest rates of COVID-19 infections in health care workers. The brief draws on findings from interviews with front line physicians and system leaders in South Korea, along with an in-depth review of national guidelines from Korea Centers for Disease Control and Prevention and hospital-level protocols

A comparative study of cross discipline referral patterns of Chinese Medicine Association practitioners over a ten-year period (2006 - 2016) : an australian national study

University of Technology Sydney. Faculty of Science.Background: The concept of patient-centred care has spurred the frequent involvement of multiple healthcare practitioners for a single patient. This raises professional considerations regarding clinical communication, which have health and safety impacts. Chinese Medicine (CM), which is classified as a Complementary and Alternative Medicine (CAM) practice, has recently undergone national registration and regulation within Australia reflecting its growing popularity. Currently, referral practices and behaviours of CM practitioners have not been researched. A survey was therefore undertaken to determine current referral practices and behaviours within a major Australian professional association. Method: Data was collected from two sources. The first was retrospective, collected in 2006 (n = 386). The second dataset was generated by using a revised survey based on the 2006 version (n = 112). Both surveys were administered to members of the Australian Acupuncture and Chinese Medicine Association, the peak professional body representing CM practitioners in Australia. Survey 1 was administered in hardcopy while survey 2 was administered through an online platform (Survey Monkey). Results: It was found that over the ten-year period, some aspects of the practitioners’ referral practices had not statistically changed. There were however, statistically significant changes observed for some aspects. This included an increase in the provision of written referral contact; a decrease in the provision of verbal referral contact by CM practitioners to other allied health and CAM practitioner; as well as a statistically significant change in the provision of referral reason to other allied health and CAM practitioners. Conclusion: Strategies to improve referral practices and behaviours of CM practitioners such as inter-disciplinary education and inter-professional communication needs to be further encouraged to achieve improved referral practices in a patient-centred environment

Baryon Magnetic Moments in Relativistic Quark Models

It is shown that the phenomenological description of the baryon magnetic moments in the quark model carries over to the Poincar\'e covariant extension of the model. This applies to all the three common forms of relativistic kinematics with structureless constituent currents, which are covariant under the corresponding kinematic subgroups. In instant and front form kinematics the calculated magnetic moments depend strongly on the constituent masses, while in point form kinematics the magnetic moments are fairly insensitive to both the quark masses and the wave function model. The baryon charge radii and magnetic moments are determined in the different forms of kinematics for the light-flavor, strange and charm hyperons. The wave function model is determined by a fit to the electromagnetic form factor of the proton.Comment: Six references and one paragraph adde

Combining Theoretical and Experimental Techniques to Study Murine Heart Transplant Rejection

The quality of life of organ transplant recipients is compromised by complications associated with life-long immunosuppression, such as hypertension, diabetes, opportunistic infections, and cancer. Moreover, the absence of established tolerance to the transplanted tissues causes limited long-term graft survival rates. Thus, there is a great medical need to understand the complex immune system interactions that lead to transplant rejection so that novel and effective strategies of intervention that redirect the system toward transplant acceptance (while preserving overall immune competence) can be identified. This study implements a systems biology approach in which an experimentally based mathematical model is used to predict how alterations in the immune response influence the rejection of mouse heart transplants. Five stages of conventional mouse heart transplantation are modeled using a system of 13 ordinary differential equations that tracks populations of both innate and adaptive immunity as well as proxies for pro- and anti-inflammatory factors within the graft and a representative draining lymph node. The model correctly reproduces known experimental outcomes, such as indefinite survival of the graft in the absence of CD4(+) T cells and quick rejection in the absence of CD8(+) T cells. The model predicts that decreasing the translocation rate of effector cells from the lymph node to the graft delays transplant rejection. Increasing the starting number of quiescent regulatory T cells in the model yields a significant but somewhat limited protective effect on graft survival. Surprisingly, the model shows that a delayed appearance of alloreactive T cells has an impact on graft survival that does not correlate linearly with the time delay. This computational model represents one of the first comprehensive approaches toward simulating the many interacting components of the immune system. Despite some limitations, the model provides important suggestions of experimental investigations that could improve the understanding of rejection. Overall, the systems biology approach used here is a first step in predicting treatments and interventions that can induce transplant tolerance while preserving the capacity of the immune system to protect against legitimate pathogens

Large-Scale CRISPRi and Transcriptomics of Staphylococcus epidermidis Identify Genetic Factors Implicated in Lifestyle Versatility.

Staphylococcus epidermidis is a ubiquitous human commensal skin bacterium that is also one of the most prevalent nosocomial pathogens. The genetic factors underlying this remarkable lifestyle plasticity are incompletely understood, mainly due to the difficulties of genetic manipulation, precluding high-throughput functional profiling of this species. To probe the versatility of S. epidermidis to survive across a diversity of environmental conditions, we developed a large-scale CRISPR interference (CRISPRi) screen complemented by transcriptional profiling (RNA sequencing) across 24 diverse conditions and piloted a droplet-based CRISPRi approach to enhance throughput and sensitivity. We identified putative essential genes, importantly revealing amino acid metabolism as crucial to survival across diverse environments, and demonstrated the importance of trace metal uptake for survival under multiple stress conditions. We identified pathways significantly enriched and repressed across our range of stress and nutrient-limited conditions, demonstrating the considerable plasticity of S. epidermidis in responding to environmental stressors. Additionally, we postulate a mechanism by which nitrogen metabolism is linked to lifestyle versatility in response to hyperosmotic challenges, such as those encountered on human skin. Finally, we examined the survival of S. epidermidis under acid stress and hypothesize a role for cell wall modification as a vital component of the survival response under acidic conditions. Taken together, this study integrates large-scale CRISPRi and transcriptomics data across multiple environments to provide insights into a keystone member of the human skin microbiome. Our results additionally provide a valuable benchmarking analysis for CRISPRi screens and are a rich resource for other staphylococcal researchers