Abstract: The disclosure relates to compositions for treating keratinous substrates, such as the hair, comprising at least one monoamine and at least one carboxylic acid, as well as systems and methods for treating keratinous substrates with the compositions.

Abstract: The disclosure relates to compositions for treating keratinous substrates, such as the hair, comprising monoethanolamine and at least one carboxylic acid, as well as systems and methods for treating keratinous substrates with the compositions.

Abstract: The present disclosure relates to cleansing compositions, which are free of sulfates and ethoxylated surfactants. Methods for making and using the cleansing compositions are also described. The cleansing compositions include: (a) at least 3 wt. % of one or more nonionic surfactant(s) that are not fatty esters; (b) one or more fatty ester(s); (c) one or more non-ethoxylated, sulfate-free anionic surfactant(s); and (d) two or more thickening agents. The cleansing compositions exhibit quality cleansing activity, impart pleasant conditioning benefits, and have a desired viscosity and foam properties.

Abstract: The disclosure relates to systems and compositions comprising the systems for use in chemical treatment of keratinous substrates, such as the hair. The systems and compositions comprising the systems comprise at least one active agent and at least one acid. Methods of treating keratinous substrates with the systems and compositions comprising the systems are also disclosed.

Abstract: The disclosure relates to compositions for treating keratinous substrates, such as the hair, comprising monoethanolamine and at least one carboxylic acid, as well as systems and methods for treating keratinous substrates with the compositions.

Abstract: Examples of systems, apparatuses, and methods for classification of electrocardiogram signals during cardiopulmonary resuscitation are described. An example system may include a defibrillator comprising an electrocardiogram analyzer. The electrocardiogram analyzer may be configured to apply a prediction modeling technique to an electrocardiogram signal to generate a predicted signal. The electrocardiogram signal may be captured from a patient undergoing cardiopulmonary resuscitation. The electrocardiogram analyzer may be further configured to subtract the predicted signal from the electrocardiogram signal to generate an error signal and to classify a rhythm of the electrocardiogram signal as one of a shockable rhythm or non-shockable based on the error signal. Decision parameters derived from the signals may be used in conjunction with a machine learning technique to classify the electrocardiogram signal.

Abstract: Formulations containing plant extracts, in particular Astragalus extracts, and their use in inducing telomerase activity in cells, are described. Such compositions include pharmaceutical, including topical, and nutraceutical formulations. The methods and compositions are useful for treating diseases subject to treatment by an increase in telomerase activity in selected cells, such as, for example, HIV infection, various degenerative diseases, and acute or chronic skin ailments. They are also useful for enhancing replicative capacity of cells in culture, as in ex vivo cell therapy and proliferation of stem cells. Also described are cosmetic formulations of such extracts for conditioning the skin.