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Social isolation hampers immune system function, and the biological mechanisms driving this effect remain understudied. We hypothesized that oxytocin (OT), a key neuropeptide involved in social cognition, is a critical mediator of social context on immune function. In the California mouse (Peromyscus californicus), we examined how female and male immune function is influenced by (1) social isolation from same-sex peers, (2) social peer affiliation, and (3) exogenous OT. We evaluated immune function through wound size progression following a skin biopsy and proinflammatory cytokines in the wound fluid. Unexpectedly, social isolation alone did not influence wound healing, but isolation +OT increased wound size in a dose dependent manner. Wound size progression interacted with sex and OT in socially-housed mice, suggesting that OT increases inflammation in females, while decreasing inflammation in males in a social context-dependent manner. Inflammatory biomarker interleukin-6 (IL-6) mRNA expression correlated with wound size overall, supporting wound healing as an index of inflammatory response. However, isolation +OT mice did not have higher levels of IL-6, suggesting that the mechanism through which isolation +OT influences wound size is not through IL-6 activity. Behaviorally, higher levels of affiliation were negatively associated with wound size, and this effect was diminished by OT treatment. Our results highlight that the anti-inflammatory effects of OT are likely highly dependent on social context. 

Interactive visualization interfaces enable users to efficiently explore, analyze, and make sense of their datasets. However, as data grows in size, it becomes increasingly challenging to build data interfaces that meet the interface designer’s desired latency expectations and resource constraints. Cloud DBMSs, while optimized for scalability, often fail to meet latency expectations, necessitating complex, bespoke query execution and optimization techniques for data interfaces. This involves manually navigating a huge optimization space that is sensitive to interface design and resource constraints, such as client vs server data and compute placement, choosing which computations are done offline vs online, and selecting from a large library of visualization-optimized data structures. This paper advocates for a Physical Visualization Design (PVD) tool that decouples interface design from system design to provide design independence. Given an interfaces underlying data flow, interactions with latency expectations, and resource constraints, PVD checks if the interface is feasible and, if so, proposes and instantiates a middleware architecture spanning the client, server, and cloud DBMS that meets the expectations. To this end, this paper presents Jade, the first prototype PVD tool that enables design independence. Jade proposes an intermediate representation called Diffplans to represent the data flows, develops cost estimation models that trade off between latency guarantees and plan feasibility, and implements an optimization framework to search for the middleware architecture that meets the guarantees. We evaluate Jade on six representative data interfaces as compared to Mosaic and Azure SQL database. We find Jade supports a wider range of interfaces, makes better use of available resources, and can meet a wider range of data, latency, and resource conditions. 

Building interactive data interfaces is hard because the design of an interface depends on the data processing needs for the underlying analysis task, yet we do not have a good representation for analysis tasks. To fill this gap, this paper advocates for a Data Interface Grammar (DIG) as an intermediate representation of analysis tasks. We show that DIG is compatible with existing data engineering practices, compact to represent any analysis, simple to translate into an interface design, and amenable to offline analysis. We further illustrate the potential benefits of this abstraction, such as automatic interface generation, automatic interface backend optimization, tutorial generation, and workload generation.