University of Michigan

Barbara McKenna

Diane M Simeone

Mary-Ann Mycek

James M Scheiman

Robert H Wilson

Malavika Chandra

Jeremy Taylor

Oliver Lee

Julianne Purdy

Thomas L Chenevert

Elif Arioglu Oral

William Lloyd

Leng-Chun Chen

Charles F Burant

Hero K Hussain

Multimodal optical spectroscopy systems and methods produce a spectroscopic event to obtain spectroscopic response data from biological tissue, either ex vivo or in vivo, and compare the response data with a model configured to correlate the measured response data and the most probable attributes of the tissue, thus facilitating classification of the tissue based on those attributes.

Multimodal spectroscopic systems and methods for classifying biological tissue

The invention generally relates to the use of leptin in the treatment of a leptin-responsive disease or condition in a non-lipodystrophic subject. More particularly, the invention is directed to the use of leptin in the treatment of a fatty liver disease in a non-lipodystrophic subject with a relative leptin deficiency. The invention includes methods for the treatment of nonalcoholic steatohepatitis (NASH), alcoholic fatty liver disease (AFLD), and nonalcoholic fatty liver disease (NAFLD) in a non-lipodystrophic subject. The invention includes the treatment of conditions ranging from ectopic lipid accumulation (steatosis) to cirrhosis.

Method of treating fatty liver diseases and conditions in non-lipodystrophic subjects

Multimodal optical spectroscopy systems and methods produce a spectroscopic event to obtain spectroscopic response data from biological tissue and compare the response data with preset criteria configured to correlate the measured response data and the most probable attributes of the tissue, thus facilitating classification of the tissue based on those attributes for subsequent biopsy or remedial measures as necessary.

Multimodal optical spectroscopy systems and methods produce a spectroscopic event to obtain spectroscopic response data from biological tissue and compare the response data with an empirical equation configured to correlate the measured response data and the most probable attributes of the tissue, thus facilitating classification of the tissue based on those attributes for subsequent biopsy or remedial measures as necessary.

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Ann Arbor, MI, United States of America

Barbara McKenna