Preservation of an Automated Feeding System to Enhance Nonhuman Primate Social Management

保留自动喂养系统以加强非人类灵长类动物的社会管理

• 批准号: 10601495
• 负责人: Kelly F Ethun
• 金额: $ 25.85万
• 依托单位: EMORY UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10601495
• 关键词: Administrative Supplement; Aggressive behavior; Animal Feed; Animals; Award; Behavioral; Biomedical Research; Breeding; Caring; Censuses; Clinical; Data; Databases; Devices; Diet Research; Equipment; Event; Feeding Patterns; Food; Fostering; Funding; Future; Goals; Gold; Growth; Health; Housing; Injury; Investments; Leadership; Letters; Macaca mulatta; Machine Learning; Manufacturer Name; Memory; Methodology; Methods; Monoclonal Antibody R24; Network Infrastructure; Network-based; Operating System; Overweight; Parents; Pathway Analysis; Pattern; Performance; Personal Satisfaction; Population; Practice Management; Primates; Request for Applications; Research; Resources; Rhesus; Risk; Running; Schedule; Science; Social Dominance; System; Time; Vendor; Weight maintenance regimen; animal resource; base; behavior observation; cost; data access; data acquisition; data management; family structure; feeding; fighting; flexibility; improved; machine learning model; male; member; nonhuman primate; obesity management; operation; pandemic disease; parent grant; parent project; physical conditioning; preservation; social; social group; success; time use; validation studies; virtual machine; wasting; wound

ABSTRACT For the past 8 years, the YNPRC Field Station has successfully maintained a large-scale automated feeding system to enhance the care and management of its rhesus macaque social groups. Currently, 8 compounds are equipped with automated feeders, housing approx. 37% of its SPF rhesus population. This automated feeding system offers several advantages over standard bin feeding practices, including reduced food waste, improved clinical oversight of animal health, weight management of overweight animals, and an automated method to conduct group census. Given our prior success, recent research efforts have focused on increasing the utility of feeding data in nonhuman primate (NHP) social management. Indeed, a common challenge in rhesus social management is the utilization of efficient social health surveillance methodology to identify groups at risk for social instability before the onset of significant fighting and wounding. The interactions that define dominance and affiliative relationships in these groups are sparce; thus, the gathering of sufficient behavioral data to unequivocally detect social instability requires considerable time and staff resources. The parent grant (R24 OD030035) of this supplement application seeks to establish a more efficient data acquisition strategy for NHP social management by developing feeding interaction network (FIN)-based machine learning (ML) models that can be used to supplement behavioral data and help managers identify groups at risk for social instability. Although the automated feeding system at the YNPRC Field Station has been operated successfully for many years, we have recently encountered unanticipated equipment challenges. First, the circuit boards of our oldest feeder units have been discontinued by the manufacturer. Currently, two compounds are equipped with these older feeders (4 units/compound) and one unit’s circuit board is non-operational. Secondly, the virtual machine operating system of our current data server is no longer supported and cannot receive upgrades. Thus, this supplement application requests support for 1) 8 new automated feeders to replace 8 discontinued units and 2) an upgraded server with a faster processor and large storage capacity along with a new virtual machine operating system, to preserve the 8-compound automated feeding system at the YNPRC Field Station. Given that automated feeding data is central to the aims of the parent grant, the purchase of an upgraded server and automated feeding units is critical to the success of this project and its potential to improve animal wellbeing and management efficiency, which in turn, fosters the conduct of high-quality science using NHPs. Additionally, the preservation of an 8-compound automated feeding system will allow necessary flexibility to select the most appropriate social groups to study (2 groups/yr, 6 groups total), considering changes in breeder male introduction schedules, group size and stability, and family structures. Use of the most appropriate social groups based on criteria outlined in the parent grant will be critical for building robust FIN-driven ML models that will exert a sustained impact on NHP social management practices at YNPRC and other captive NHP colonies.

抽象的 8年来，YNPRC野外站成功保持了大规模自动化饲养 加强对恒河猴社会群体的照顾和管理。目前，有8种化合物 配备自动喂食器，外壳约。 37% 的 SPF 恒河猴种群。这种自动喂食 与标准垃圾箱喂食方法相比，系统具有多种优势，包括减少食物浪费、改进 动物健康的临床监督、超重动物的体重管理以及自动化方法 进行群体普查。鉴于我们之前的成功，最近的研究工作集中在提高 非人类灵长类动物 (NHP) 社会管理中的喂养数据。事实上，恒河猴社交中的一个常见挑战 管理是利用有效的社会健康监测方法来识别有风险的群体 重大战斗和伤人事件发生之前的社会不稳定。定义主导地位的相互作用 这些群体中的隶属关系很少；因此，收集足够的行为数据 明确地发现社会不稳定需要大量的时间和人力资源。家长补助金（R24 该补充应用程序的 OD030035) 旨在为 NHP 建立更有效的数据采集策略 通过开发基于喂养互动网络 (FIN) 的机器学习 (ML) 模型来进行社会管理 可用于补充行为数据并帮助管理者识别面临社会不稳定风险的群体。 尽管YNPRC野外站的自动饲喂系统已经成功运行了许多 多年来，我们最近遇到了意想不到的设备挑战。首先，我们最古老的电路板 制造商已停产供料装置。目前，有两个化合物配备了这些 较旧的馈线（4 个单元/院落）和一个单元的电路板无法运行。其次，虚拟机 我们当前数据服务器的操作系统不再受支持并且无法接收升级。因此，这个 补充申请请求支持 1) 8 个新的自动送料器以替换 8 个已停产的装置以及 2) 升级后的服务器具有更快的处理器和大存储容量以及新的虚拟机运行 系统，以保留 YNPRC 野外站的 8 个化合物自动饲喂系统。 鉴于自动喂养数据是家长补助金目标的核心，购买升级版 服务器和自动饲喂装置对于该项目的成功及其改善动物的潜力至关重要 福祉和管理效率，进而促进利用 NHP 进行高质量的科学研究。 此外，保留 8 种化合物的自动饲喂系统将提供必要的灵活性 考虑饲养员的变化，选择最合适的社会群体进行研究（每年 2 组，总共 6 组） 男性介绍时间表、群体规模和稳定性以及家庭结构。使用最合适的社交 基于父资助中概述的标准的小组对于构建强大的 FIN 驱动的 ML 模型至关重要 将对 YNPRC 和其他 NHP 圈养地的 NHP 社会管理实践产生持续影响。