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The prevalence of inflammatory diseases is increasing in modern urban societies. Inflammation increases risk of stress-related pathology; consequently, immunoregulatory or antiinflammatory approaches may protect against negative stress-related outcomes. We show that stress disrupts the homeostatic relationship between the microbiota and the host, resulting in exaggerated inflammation. Repeated immunization with a heat-killed preparation of Mycobacterium vaccae, an immunoregulatory environmental microorganism, reduced subordinate, flight, and avoiding behavioral responses to a dominant aggressor in a murine model of chronic psychosocial stress when tested 1-2 wk following the final immunization. Furthermore, immunization with M. vaccae prevented stress-induced spontaneous colitis and, in stressed mice, induced anxiolytic or fear-reducing effects as measured on the elevated plus-maze, despite stress-induced gut microbiota changes characteristic of gut infection and colitis. Immunization with M. vaccae also prevented stress-induced aggravation of colitis in a model of inflammatory bowel disease. Depletion of regulatory T cells negated protective effects of immunization with M. vaccae on stress-induced colitis and anxiety-like or fear behaviors. These data provide a framework for developing microbiome- and immunoregulation-based strategies for prevention of stress-related pathologies.

Background: Machine learning and artificial intelligence have shown promising results in many areas and are driven by the increasing amount of available data. However, these data are often distributed across different institutions and cannot be easily shared owing to strict privacy regulations. Federated learning (FL) allows the training of distributed machine learning models without sharing sensitive data. In addition, the implementation is time-consuming and requires advanced programming skills and complex technical infrastructures. Objective: Various tools and frameworks have been developed to simplify the development of FL algorithms and provide the necessary technical infrastructure. Although there are many high-quality frameworks, most focus only on a single application case or method. To our knowledge, there are no generic frameworks, meaning that the existing solutions are restricted to a particular type of algorithm or application field. Furthermore, most of these frameworks provide an application programming interface that needs programming knowledge. There is no collection of ready-to-use FL algorithms that are extendable and allow users (eg, researchers) without programming knowledge to apply FL. A central FL platform for both FL algorithm developers and users does not exist. This study aimed to address this gap and make FL available to everyone by developing FeatureCloud, an all-in-one platform for FL in biomedicine and beyond. Methods: The FeatureCloud platform consists of 3 main components: a global frontend, a global backend, and a local controller. Our platform uses a Docker to separate the local acting components of the platform from the sensitive data systems. We evaluated our platform using 4 different algorithms on 5 data sets for both accuracy and runtime. Results: FeatureCloud removes the complexity of distributed systems for developers and end users by providing a comprehensive platform for executing multi-institutional FL analyses and implementing FL algorithms. Through its integrated artificial intelligence store, federated algorithms can easily be published and reused by the community. To secure sensitive raw data, FeatureCloud supports privacy-enhancing technologies to secure the shared local models and assures high standards in data privacy to comply with the strict General Data Protection Regulation. Our evaluation shows that applications developed in FeatureCloud can produce highly similar results compared with centralized approaches and scale well for an increasing number of participating sites. Conclusions: FeatureCloud provides a ready-to-use platform that integrates the development and execution of FL algorithms while reducing the complexity to a minimum and removing the hurdles of federated infrastructure. Thus, we believe that it has the potential to greatly increase the accessibility of privacy-preserving and distributed data analyses in biomedicine and beyond. [ABSTRACT FROM AUTHOR]

Peripheral immune activation can have profound physiologic and behavioral effects. One mechanism through which immune activation may affect physiology and behavior is through actions on brainstem neuromodulatory systems, such as serotonergic systems. To test this hypothesis, in Experiment 1, adult male BALB/c mice were implanted with telemetric recording devices and then immunized with Mycobacterium vaccae NCTC 11659 (0.1 mg, s.c.; Days − 28, − 14; N = 36). On Day 1, mice received an acute challenge with M. vaccae (0.1 mg, s.c.) or borate-buffered saline vehicle. Core body temperature and locomotor activity recordings were conducted during a 36 h period beginning 24 h prior to challenge; 12 h following acute challenge, mice were either tested in a 6-min forced swim test, or served as home cage controls ( n = 9 per group). In Experiment 2, the protocol was repeated, but with the aim of assessing c-Fos expression in brainstem serotonergic neurons, assessed 90 min following exposure to forced swim ( N = 32; n = 8 per group). In Experiment 1, acute M. vaccae challenge in M. vaccae-immunized mice, relative to vehicle-challenged controls, decreased locomotor activity and core body temperature measured 3 h following challenge, as measured by continuous telemetric recordings, and decreased immobility in the forced swim test measured 12 h following challenge. In Experiment 2, acute M. vaccae challenge in M. vaccae-immunized mice decreased home cage locomotion, in alignment with findings in Experiment 1, as measured by video-based behavioral analysis, and, among mice exposed to the forced swim test, increased c-Fos expression in subsets of serotonergic neurons within the dorsal raphe nucleus (DR) measured 13.5 h following challenge. Together, these data are consistent with the hypothesis that acute peripheral immune activation with a heat-killed preparation of M. vaccae transiently induces mild hypothermia in association with suppression of locomotor activity, activates subsets of serotonergic neurons in the DR, and induces antidepressant-like behavioral responses. [ABSTRACT FROM AUTHOR]