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We introduce RLang, a domain-specific language (DSL) for communicating domain knowledge to an RL agent. Unlike existing RL DSLs that ground to single elements of a decision-making formalism (e.g., the reward function or policy), RLang can specify information about every element of a Markov decision process. We define precise syntax and grounding semantics for RLang, and provide a parser that grounds RLang programs to an algorithm-agnostic partial world model and policy that can be exploited by an RL agent. We provide a series of example RLang programs demonstrating how different RL methods can exploit the resulting knowledge, encompassing model-free and model-based tabular algorithms, policy gradient and value-based methods, hierarchical approaches, and deep methods. 

Rapid and accurate detection of the pathogens, such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) for COVID-19, is critical for mitigating the COVID-19 pandemic. Current state-of-the-art pathogen tests for COVID-19 diagnosis are done in a liquid medium and take 10–30 min for rapid antigen tests and hours to days for polymerase chain reaction (PCR) tests. Herein we report novel accurate pathogen sensors, a new test method, and machine-learning algorithms for a breathalyzer platform for fast detection of SARS-CoV-2 virion particles in the aerosol in 30 s. The pathogen sensors are based on a functionalized molecularly-imprinted polymer, with the template molecules being the receptor binding domain spike proteins for different variants of SARS-CoV-2. Sensors are tested in the air and exposed for 10 s to the aerosols of various types of pathogens, including wild-type, D614G, alpha, delta, and omicron variant SARS-CoV-2, BSA (Bovine serum albumin), Middle East respiratory syndrome–related coronavirus (MERS-CoV), influenza, and wastewater samples from local sewage. Our low-cost, fast-responsive pathogen sensors yield accuracy above 99% with a limit-of-detection (LOD) better than 1 copy/μL for detecting the SARS-CoV-2 virus from the aerosol. The machine-learning algorithm supporting these sensors can accurately detect the pathogens, thereby enabling a new and unique breathalyzer platform for rapid COVID-19 tests with unprecedented speeds. 

Defense of the central nervous system (CNS) against infection must be accomplished without generation of potentially injurious immune cell-mediated or off-target inflammation which could impair key functions. As the CNS is an immune-privileged compartment, inducible innate defense mechanisms endogenous to the CNS likely play an essential role in this regard. Pituitary adenylate cyclase-activating polypeptide (PACAP) is a neuropeptide known to regulate neurodevelopment, emotion, and certain stress responses. While PACAP is known to interact with the immune system, its significance in direct defense of brain or other tissues is not established. Here, we show that our machine-learning classifier can screen for immune activity in neuropeptides, and correctly identified PACAP as an antimicrobial neuropeptide in agreement with previous experimental work. Furthermore, synchrotron X-ray scattering, antimicrobial assays, and mechanistic fingerprinting provided precise insights into how PACAP exerts antimicrobial activities vs. pathogens via multiple and synergistic mechanisms, including dysregulation of membrane integrity and energetics and activation of cell death pathways. Importantly, resident PACAP is selectively induced up to 50-fold in the brain in mouse models ofStaphylococcus aureusorCandida albicansinfection in vivo, without inducing immune cell infiltration. We show differential PACAP induction even in various tissues outside the CNS, and how these observed patterns of induction are consistent with the antimicrobial efficacy of PACAP measured in conditions simulating specific physiologic contexts of those tissues. Phylogenetic analysis of PACAP revealed close conservation of predicted antimicrobial properties spanning primitive invertebrates to modern mammals. Together, these findings substantiate our hypothesis that PACAP is an ancient neuro-endocrine-immune effector that defends the CNS against infection while minimizing potentially injurious neuroinflammation.