Abstract: A composition including anatabine or a salt thereof is provided for treating a nuclear factor erythroid 2-related factor 2 (NRF2)-regulated disorder.) A composition including anatabine or a salt thereof is also provided for prophylactic treatment of a subject requiring NRF2 activation.

Abstract: Pharmaceutical compositions may include chloroquine. More specifically, a pharmaceutical composition comprising chloroquine or pharmaceutically acceptable salt(s) thereof for use in the treatment or prevention of a viral lung infection, preferably caused by Betacoronavirus, including but not limited to 2019-nCoV (coronavirus), SARS-CoV and Middle East respiratory syndrome CoV (MERS-CoV), wherein the pharmaceutical composition is administered by inhalation. An improved delivery into the lungs of a subject with minimum systemic exposure may be achieved.

Abstract: A pharmaceutical composition may include hydroxychloroquine or a pharmaceutically acceptable salt thereof, and a solvent. The pharmaceutical composition may include 1 to 400 mg/mL hydroxychloroquine or a pharmaceutically acceptable salt thereof, wherein the solvent is selected from propylene glycol, glycerine, propane-1,3-diol and water or combinations thereof and. The pharmaceutical composition may be suitable for thermal aerosolization. A pharmaceutical composition including hydroxychloroquine or a pharmaceutically acceptable salt thereof may be used in the treatment or prevention of a viral lung infection, wherein the pharmaceutical composition is administered by oral inhalation.

Abstract: An apparatus includes (i) a test chamber having an inlet and an outlet; (ii) an introduction system configured to introduce a test pollutant into the test chamber such that the test pollutant is entrained in air flowing from the inlet to the outlet; (iii) a support configured to retain the test article, wherein the support defines a passageway downstream of a location of the test article such that air flowing from the inlet to the outlet passes through the filter medium prior to entering the passageway; (iv) an air flow apparatus configured to draw air from within the test chamber through the passageway and the outlet; and (v) a respiratory conditions simulation system configured to simulate an aspect of respiration, an external environment simulation system configured to simulate an aspect of an external environment, or both the respiratory conditions simulation system and the external environment simulation system.

Abstract: A compound of Formula I and formulations including such a compound may be used for the reduction of infestation with ectoparasites, in particular ectoparasites of the insect class, including fleas and mosquitoes, and/or ectoparasites of the arachnid class, including ticks and mites, etc. Methods for controlling ectoparasites and/or formulations including such compounds may include use as a repellent, and/or application to a mammal, e.g., a human, dog, cat, cattle, horse, or sheep, or to an object or a fabric. The form may be a topical formulation, a shampoo composition, a cleansing composition, or a treatment composition, preferably a lotion, cream, ointment, gel, foam, patch, powder, solid, sponge, tape, vapor, paste, tincture, or spray.

Abstract: A formulation containing an extract of a tobacco plant enriched for a compound of formula (I), or a salt or crystal thereof, where the formulation is used for reducing the infestation of ectoparasites: where R represents hydrogen or C1-C5 alkyl, and represents a double bond.

Abstract: Systems and methods are provided herein for generating a classifier for phenotypic prediction. A computational causal network model representing a biological system includes a plurality of nodes and a plurality of edges connecting pairs of nodes. A first set of data corresponding to activities of a first subset of biological entities obtained under a first set of conditions is received, and a second set of data corresponding to activities of the first subset of biological entities obtained under a second set of conditions is received. A set of activity measures representing a difference between the first and second sets of data for a first subset of nodes is calculated. A set of activity values for a second subset of nodes, which are unmeasured, is generated. A classifier is generated for the phenotypes based on the set of activity measures, the set of activity values, or both.

Abstract: Systems and methods are described for quantifying the response of a biological system to one or more perturbations. First and second datasets corresponding to a response of a biological system to first and second treatments are received. A plurality of computational network models that represent the biological system are provided, each model including nodes representing a plurality of biological entities and edges representing relationships between the nodes in the model. A first set of scores is generated, representing the perturbation of the biological system based on the first dataset and the plurality of models, and a second set of scores representing the perturbation of the biological system based on the second dataset and the plurality of computational models. One or more biological impact factors are generated based on each of the first set and second set of scores that represent the biological impact of the perturbation on the biological system.

Abstract: Systems and methods are provided for assessing perturbation of a target biological tissue caused by exposure to an agent. A set of scores indicative of a perturbation of the target biological tissue is determined based on a set of contrast data and a computational causal network model of xenobiotic metabolism in the target biological tissue and a surrogate biological tissue. The contrast data includes differences between activity measures of measurable nodes obtained from the surrogate biological tissue while exposed to the agent, and while exposed to a control. To determine the set of scores, a set of values is computed that indicates a perturbation of the surrogate biological tissue caused by the agent. A correlation is identified between the set of values for the backbone nodes obtained from the surrogate biological tissue and the set of scores that is indicative of a perturbation of the target biological tissue.

Abstract: There is disclosed a cell culture plate comprising at least two sequentially arranged wells and a channel adapted for fluid communication between the wells, wherein the channel is connected or coupled to a first pump via openings at each end of the channel, and wherein said first pump is operable to circulate fluid between the at least two wells. Devices and systems incorporating the cell culture plate and methods and uses employing same are also disclosed.

Abstract: The systems and methods described herein include a technique for generating both reproducible and interpretable gene signatures. The technique involves resampling a data set and choosing genes having a high frequency of emergence. In particular, the systems and methods described herein include repeated sampling of data sets, ranking genes based on frequency of occurrence in gene signatures generated through the repeated sampling process, and iteratively selecting the best gene signature.

Abstract: Described herein are systems and methods for classifying a data set using an ensemble classification technique. Classifiers are iteratively generated by applying machine learning techniques to a training data set, and training class sets are generated by classifying the elements in the training data set according to the classifiers. Objective values are computed based on the training class sets, and objective values associated with different classifiers are compared until a desired number of iterations is reached, and a final training class set is output.

Abstract: Systems and methods are described for quantifying the response of a biological system to one or more perturbations. First and second datasets corresponding to a response of a biological system to first and second treatments are received. A plurality of computational network models that represent the biological system are provided, each model including nodes representing a plurality of biological entities and edges representing relationships between the nodes in the model. A first set of scores is generated, representing the perturbation of the biological system based on the first dataset and the plurality of models, and a second set of scores representing the perturbation of the biological system based on the second dataset and the plurality of computational models. One or more biological impact factors are generated based on each of the first set and second set of scores that represent the biological impact of the perturbation on the biological system.

Abstract: Systems and methods are described for quantifying the response of a biological system to one or more perturbations. First and second datasets corresponding to a response of a biological system to first and second treatments are received. A plurality of computational network models that represent the biological system are provided, each model including nodes representing a plurality of biological entities and edges representing relationships between the nodes in the model. A first set of scores is generated, representing the perturbation of the biological system based on the first dataset and the plurality of models, and a second set of scores representing the perturbation of the biological system based on the second dataset and the plurality of computational models. One or more biological impact factors are generated based on each of the first set and second set of scores that represent the biological impact of the perturbation on the biological system.

Abstract: Systems and methods are provided for curating and disseminating a network model. A representation of a network model is provided, and data is received that is representative of user actions. The user actions are directed to at least one element of the network model. A score is assigned to each respective element based on a number of user actions received for the respective element. A verified subset of edges is identified that have assigned scores that exceed a verification threshold, and a rejected subset of edges is identified that have assigned scores that are below a rejection threshold. The verified subset of edges and the associated nodes are provided as a curated network model, which omits the rejected subset of edges.

Abstract: Systems and methods are provided herein for generating a classifier for phenotypic prediction. A computational causal network model representing a biological system includes a plurality of nodes and a plurality of edges connecting pairs of nodes. A first set of data corresponding to activities of a first subset of biological entities obtained under a first set of conditions is received, and a second set of data corresponding to activities of the first subset of biological entities obtained under a second set of conditions is received. A set of activity measures representing a difference between the first and second sets of data for a first subset of nodes is calculated. A set of activity values for a second subset of nodes, which are unmeasured, is generated. A classifier is generated for the phenotypes based on the set of activity measures, the set of activity values, or both.

Abstract: The systems and methods described herein include a technique for generating both reproducible and interpretable gene signatures. The technique involves resampling a data set and choosing genes having a high frequency of emergence. In particular, the systems and methods described herein include repeated sampling of data sets, ranking genes based on frequency of occurrence in gene signatures generated through the repeated sampling process, and iteratively selecting the best gene signature.

Abstract: Described herein are systems and methods for classifying a data set using an ensemble classification technique. Classifiers are iteratively generated by applying machine learning techniques to a training data set, and training class sets are generated by classifying the elements in the training data set according to the classifiers. Objective values are computed based on the training class sets, and objective values associated with different classifiers are compared until a desired number of iterations is reached, and a final training class set is output.

Abstract: A method of implementing verification of a complex workflow includes partitioning the workflow into modules, wherein the modules have inputs, processing steps and outputs; selecting, from the workflow, one of the partitioned modules for independent verification by challenge thereof; running, with a computing device, a challenge of the selected module, the challenge comprising comparing reference outputs to outputs of the selected module, wherein reference inputs are received by the selected module and the reference outputs are generated using the reference inputs and one of an ideal performing module or a well-established module; determining whether outputs of the selected module meet verification criteria with respect to the reference outputs, and based on the determining, implementing one of: declaring the selected module verified; subdividing the selected module into smaller modules and repeating the challenge on the smaller modules; or declaring the selected module not verified.

Abstract: Systems and methods are directed to computerized methods and one or more computer processors for quantifying the perturbation of a biological system in response to an agent. A set of treatment data corresponding to a response of a biological system to an agent and a set of control data are received. A computational causal network model represents the biological system and includes nodes representing biological entities, edges representing relationships between the biological entities, and direction values representing the expected direction of change between the control data and the treatment data. Activity measures are calculated and represent a difference between the treatment data and the control data, and weight values are calculated for the nodes. A score for the computational model is generated representative of the perturbation of the biological system to the agent and is based on the direction values, the weight values and the activity measures.