Evolutionary effects of alternative artificial propagation programs: implications for viability of endangered anadromous salmonids

Most hatchery programs for anadromous salmonids have been initiated to increase the numbers of fish for harvest, to mitigate for habitat losses, or to increase abundance in populations at low abundance. However, the manner in which these programs are implemented can have significant impacts on the evolutionary trajectory and long-term viability of populations. In this paper, we review the potential benefits and risks of hatchery programs relative to the conservation of species listed under the US Endangered Species Act. To illustrate, we present the range of potential effects within a population as well as among populations of Chinook salmon (Oncorhynchus tshawytscha) where changes to major hatchery programs are being considered. We apply evolutionary considerations emerging from these examples to suggest broader principles for hatchery uses that are consistent with conservation goals. We conclude that because of the evolutionary risks posed by artificial propagation programs, they should not be viewed as a substitute for addressing other limiting factors that prevent achieving viability. At the population level, artificial propagation programs that are implemented as a short-term approach to avoid imminent extinction are more likely to achieve long-term population viability than approaches that rely on long-term supplementation. In addition, artificial propagation programs can have out-of-population impacts that should be considered in conservation planning

Visual Censorship: A Deep Learning-Based Approach to Preventing the Leakage of Confidential Content in Images

Online social networks (OSNs) are fertile ground for information sharing and public relationships. However, the uncontrolled dissemination of information poses a significant risk of the inadvertent disclosure of sensitive information. This poses a notable challenge to the information security of many organizations. Improving organizations’ ability to automatically identify data leaked within image-based content requires specialized techniques. In contrast to traditional vision-based tasks, detecting data leaked within images presents a unique challenge due to the context-dependent nature and sparsity of the target objects, as well as the possibility that these objects may appear in an image inadvertently as background or small elements rather than as the central focus of the image. In this paper, we investigated the ability of multiple state-of-the-art deep learning methods to detect censored objects in an image. We conducted a case study utilizing Instagram images published by members of a large organization. Six types of objects that were not intended for public exposure were detected with an average accuracy of 0.9454 and an average macro F1-score of 0.658. A further analysis of relevant OSN images revealed that many contained confidential information, exposing the organization and its members to security risks

Characterization of neural crest stem cells for a DPN-specific treatment

Diabetic peripheral neuropathy (DPN), a term that encompasses the damage of peripheral nerves-in particular those found in the extremities-is the most frequently observed serious and chronic complication of diabetes. With a prevalence of 30-50% among patients with diabetes, \u3e70% of those with DPN describe it as severely painful, significantly impacting their quality of life. While some studies using pharmacological treatments have proven successful, pharmacological treatments are described as disappointing, and provide no improvement for \u3e35% of patients with DPN. The quality of life destroying effects of DPN and severe lack of success using pharmaceuticals underscore the dire need for a specific, long-term DPN treatment. In DPN, there are changes in the peripheral and central nervous systems. An increase in the release of the excitatory neurotransmitter glutamate and in the amount of its receptor may lead to excessive nerve firing in DPN. Additionally, there is the death of GABAergic interneurons (responsible for inhibiting nerve firing) and the decrease in their receptors. Together, this is known as central sensitization. The objective of this application is to characterize neural crest derived stem cells (NCSCs) from dental tissues to determine their therapeutic potential for DPN. The central hypothesis is that NCSCs will be amenable to neuro-differentiation and display more desirable properties than other stem cells. Our hypothesis is formulated on the basis that stem cells have been differentiated towards a GABAergic lineage. The rationale for the proposed research is that a DPN treatment may be achieved through characterization and differentiation, which will create a micro-environment that will arrest/reduce the effects of DPN in-vivo. We plan to test our central hypothesis and attain the objective of this application by pursuing the following specific aims: 1) Establish and characterize NCSC lines from various dental tissues and 2) Develop a neuro-differentiation protocol for the NCSC lines, including optimization of length of treatment and growth factor combination. In Aim 1, we will purify stem cells and use immunohistochemical (IHC) and genetic analysis to verify the resulting NCSCs. In Aim 2, we will neuro-differentiate NCSCs and use IHC, genetic, and neural assays to examine the effects of differentiation. Our research is innovative and significant because it is geared towards a DPN-specific treatment, is based on an etiology of DPN and central sensitization, and uses an approach geared towards reducing time from bench to bedside. This research may lead to a novel stem cell-based treatment for DPN