Abstract: A method of measuring efficacy of test treatment of an autoimmune disease in an animal in a vivarium is described. Animal activity data is collected at multiple times during the night. Sequential time regions of the night are identified as high-activity, activity-drop, or low-activity regions. Embodiments are described to quantify a drop, during the night, of an animal's activity level. These quantified activity-drop scalars for consecutive nights are accumulated in an animal health dataset. This dataset is compared to healthy animals, a standard of care or a reference treatment for the first disease to determine efficacy of the test treatment. One embodiment quantifies an activity-drop by fitting straight-line curves through the data in the three nightly regions. Other embodiment uses a Fourier transform on a circle, LASSO, RANSAC or regression analyses for curve fitting. Another embodiment compares areas under data curves in the regions. Animals may be housed in cages with other animals.

Abstract: A method for preparing a card containing at least one sequestered compound is provided. The method includes preparing a first waxy phase, preparing a first volatile phase comprising a first sequestered compound, creating a first emulsion from the first waxy phase and the first volatile phase, depositing the first emulsion on the card, and cooling the first emulsion.

Abstract: A method of determining a cognitive state of an experimental animal in a cage is provided. The cage includes one or more walls that enclose a living space for containing the experimental animal, and a heating structure. The method includes installing a card with at least a first type of sequestered olfactory compound, directing the heating structure to selectively heat the card to release the first type of sequestered first type of olfactory compound to subject the experimental animal to a novel olfactory experience, creating a first assessment of a behavior of the laboratory animal, subjecting the experimental animal to experimental procedures and/or waiting a selected amount of time, directing the heating structure to selectively heat the card to release more of the first type of sequestered olfactory compound, creating a second assessment of a behavior of the experimental animal, and evaluating the first and second assessments to determine the cognitive state of the experimental animal.

Abstract: The field of this invention is classifying animal behaviors. In particular the fields of this invention include using animals in vivariums, such as rodents, particularly mice. Ultrasonic vocalizations of mice in a vivarium are compared to a predetermined set of positive phenotypes and to a predetermined set of negative phenotypes. The output of those comparisons are then compared to determine a metric of distance to classify vocalizations as closer to or more distant from elements of the positive or negative sets.

Abstract: The field of this invention is classifying animal behaviors. In particular the fields of this invention include using animals in vivariums, such as rodents, particularly mice. Animal behaviors are classified according to behaviors consistent with healthy or unhealthy organs or locations within organs, such as the brain. Injected neoplastic cells may be used to create an unhealthy organ or location within an organ. Classifications also include responses to different therapies. The behavior of the animals is observed using fully automatic, continuous monitoring using per-cage ultrasonic and video sensors, where behavior recording is free of human, manual actions. Observed behavior is consistent with healthy or unhealthy behaviors specific to the injection site. Both positive and negative baseline behaviors are collected, typically using the same system or method.

Abstract: An animal exercise device is described in the form a rotating wheel, generally cylindrical in form, open on one face for an animal to enter and exit, and solidly closed on the other face, which also provides a bearing for rotation. The wall and closed face are solid to avoid injury to an animal. The wheel's axis of rotation is at an angle from horizontal. The inside surface of the wall comprises spaced ridges for gripping by the animal's toes or feet. A contrasting marking on the outside surface of the wall aids vision-based rotation measurement. Embodiments are supported solely through the bearing and have no rotation drive other than use by an animal. Methods of use include automated measurement, using equipment external to the cage, of animal health and use in a multihoused cage where unique animal ID is associated with wheel use.

Abstract: An apparatus for sequestering and releasing compounds into the air is provided. The apparatus includes a card with a first side and a second side, and a plurality of compound-sequestering structures affixed to the first side. Each of the plurality of compound-sequestering structures is configured to release a compound into the air when heated to a first temperature.

Abstract: A method of measuring efficacy of test treatment of an autoimmune disease in an animal in a vivarium is described. Animal activity data is collected at multiple times during the night. Sequential time regions of the night are identified as high-activity, activity-drop, or low-activity regions. Embodiments are described to quantify a drop, during the night, of an animal's activity level. These quantified activity-drop scalars for consecutive nights are accumulated in an animal health dataset. This dataset is compared to healthy animals, a standard of care or a reference treatment for the first disease to determine efficacy of the test treatment. One embodiment quantifies an activity-drop by fitting straight-line curves through the data in the three nightly regions. Other embodiment uses a Fourier transform on a circle, LASSO, RANSAC or regression analyses for curve fitting. Another embodiment compares areas under data curves in the regions. Animals may be housed in cages with other animals.

Abstract: A method of predicting severity of multiple sclerosis (MS) in an animal in a vivarium is described. Animal activity data is collected at multiple times during the night. Sequential time regions of the night are identified as high-activity, activity-drop, or low-activity regions. Embodiments are described to quantify a drop, during the night, of an animal's activity level. These quantified activity-drop scalars for consecutive nights are accumulated in an animal health dataset. Then, an MS severity index function is applied to this dataset that, in response to the level of activity change and the speed of activity change, predicts or measures severity of MS in the animal. One embodiment quantifies an activity-drop by fitting straight-line curves through the data in the three nightly regions. Another embodiment uses a Fourier transform on a circle and a linear combination. Another embodiment compares areas under data curves in the regions. Animals may be housed in cages with other animals.

Abstract: The field of this invention is classifying animal behaviors. In particular the fields of this invention include using animals in vivariums, such as rodents, particularly mice. In a vivarium cage, animals create ultrasonic vocalizations. In addition, their phenotype changes over time. The vocalizations, a current phenotype, and the cage environments are inputs to a multi-dimensional classifier using clustering algorithms to find multi-dimensional close relationships. Such close relationships may be identified as particular behavior.

Abstract: The field of this invention is classifying animal behaviors. In particular the fields of this invention include using animals in vivariums, such as rodents, particularly mice. Ultrasonic vocalizations are compared to times-shifted video behaviors of the same mice to identify vocalizations that occur prior to, during, and after particular video behaviors. The comparisons generate correlations weights that may then be used to apply known classifications of the video behaviors to the vocalizations.

Abstract: A method of measuring efficacy of treatment of multiple sclerosis (MS) in an animal in a vivarium is described. Animal activity data is collected at multiple times during the night. Sequential time regions of the night are identified as high-activity, activity-drop, or low-activity regions. Embodiments are described to quantify a drop, during the night, of an animal's activity level. These quantified activity-drop scalars for consecutive nights are accumulated in an animal health dataset. This dataset is compared to healthy animals or a standard of care to determine efficacy. One embodiment quantifies an activity-drop by fitting straight-line curves through the data in the three nightly regions. Another embodiment uses a Fourier transform on a circle and a linear combination. Another embodiment compares areas under data curves in the regions. Animals may be housed in cages with other animals.

Abstract: A method of measuring efficacy of treatment of multiple sclerosis (MS) in an animal in a vivarium is described. Animal activity data is collected at multiple times during the night. Sequential time regions of the night are identified as high-activity, activity-drop, or low-activity regions. Embodiments are described to quantify a drop, during the night, of an animal's activity level. These quantified activity-drop scalars for consecutive nights are accumulated in an animal health dataset. This dataset is compared to healthy animals or a standard of care to determine efficacy. One embodiment quantifies an activity-drop by fitting straight-line curves through the data in the three nightly regions. Another embodiment uses a Fourier transform on a circle and a linear combination. Another embodiment compares areas under data curves in the regions. Animals may be housed in cages with other animals.

Abstract: A method for determining at least one physiological characteristic of at least one experimental animal in a cage is disclosed. The method may include capturing at least one infrared image of the at least one experimental animal in a band of infrared radiation that is within the range of from about 3 ?m to about 14 ?m in wavelength and capturing at least one visible image of the at least one experimental animal. The method may further include correlating the at least one image and the at least one visible light image and determining the at least one physiological characteristic of the at least one experimental animal based at least in part on the correlation. An apparatus to determine at least one physiological characteristic of at least one experimental animal is also disclosed.

Abstract: Systems and methods of measuring drug efficacy and side effects using non-invasive or husbandry-only testing are described. Steps include testing a cohort with a proposed husbandry-only protocol against an existing gold-standard treatment, and then validating the use of a created surrogate, non-invasive metric in place of an invasive metric. Then, the validated non-invasive surrogate metric and the husbandry-only protocols are used with an animal treatment cohort to study a new proposed treatment. A control cohort is also used, subject to the same husbandry-only testing and the surrogate metric. A statistical difference in outcomes, using one or more surrogate metrics, between the treatment cohort and the control cohort is the drug efficacy, for a drug used to treat the treatment cohort.

Abstract: An animal exercise device is described in the form a rotating wheel, generally cylindrical in form, open on one face for an animal to enter and exit, and solidly closed on the other face, which also provides a bearing for rotation. The wall and closed face are solid to avoid injury to an animal. The wheel's axis of rotation is at an angle from horizontal. The inside surface of the wall comprises spaced ridges for gripping by the animal's toes or feet. A contrasting marking on the outside surface of the wall aids vision-based rotation measurement. Embodiments are supported solely through the bearing and have no rotation drive other than use by an animal. Methods of use include automated measurement, using equipment external to the cage, of animal health and use in a multihoused cage where unique animal ID is associated with wheel use.

Abstract: A device, system and method of equipment sets, “furniture,” to provide animal husbandry functions are described. Embodiments include: a frame in the form of a ring adapted to sit in a single possible orientation within an animal cage, wherein the frame comprises hollow, open-top vertical columns, adapted to receive pieces of furniture comprising mating pins; a running wheel mounted on a axle integral to the monolithic frame; a horizontal climbing ladder; and a food tray. Embodiments include feet extending from the frame for fixed positioning within a cage; a reserved area to hold a weight scale; curved corners for cage fit; monolithic construction of all individual elements; a canted wheel axis; a sloped inner edge of a food tray to permit unobstructed views of animals in a cage. Methods include assembly; use in an animal cage; and use to observe and measure animal activity using husbandry-only procedures for the animals; and for animal studies using non-invasive procedures.

Abstract: A method of early detection of multiple sclerosis (MS) in an animal in a vivarium is described. Animal activity data is collected at multiple times during the night. Sequential time regions of the night are identified as high-activity, activity-drop, or low-activity regions. Embodiments are described to quantify a drop, during the night, of an animal's activity level. These quantified activity-drop scalars for consecutive nights are accumulated in an animal health dataset. Then, a health detection function is applied to this dataset that, in response to the level of activity change and the speed of activity change, predicts or detects MS in the animal. One embodiment quantifies an activity-drop by fitting straight-line curves through the data in the three nightly regions. Another embodiment uses a Fourier transform on a circle and a linear combination. Another embodiment compares areas under data curves in the regions. Animals may be housed in cages with other animals.

Abstract: A method of early detection of multiple sclerosis (MS) in an animal in a vivarium is described. Animal activity data is collected at multiple times during the night. Sequential time regions of the night are identified as high-activity, activity-drop, or low-activity regions. Embodiments are described to quantify a drop, during the night, of an animal's activity level. These quantified activity-drop scalars for consecutive nights are accumulated in an animal health dataset. Then, a health detection function is applied to this dataset that, in response to the level of activity change and the speed of activity change, predicts or detects MS in the animal. One embodiment quantifies an activity-drop by fitting straight-line curves through the data in the three nightly regions. Another embodiment uses a Fourier transform on a circle and a linear combination. Another embodiment compares areas under data curves in the regions. Animals may be housed in cages with other animals.