Lung necrosis and neutrophils reflect common pathways of susceptibility to Mycobacterium tuberculosis in genetically diverse, immune-competent mice

DMM Disease Models and Mechanisms

Volumn 8, Issue 9, 2015, Pages 1141-1153

  Niazi, Muhammad K K ^a   Dhulekar, Nimit ^b   Schmidt, Diane ^c   Major, Samuel ^c   Cooper, Rachel ^c   Abeijon, Claudia ^c   Gatti, Daniel M ^d   Kramnik, Igor ^e   Yener, Bulent ^b   Gurcan, Metin ^a   Beamer, Gillian ^c  

^a OHIO STATE UNIVERSITY   (United States)

^b RENSSELAER POLYTECHNIC INSTITUTE   (United States)

^c TUFTS UNIVERSITY   (United States)

^d JACKSON LABORATORY   (United States)

^e BOSTON UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

CXCL1; CXCL2; CXCL5; Diversity outbred; DO; Machine learning; Mycobacterium tuberculosis; Necrosis; Neutrophils; Tuberculosis

Indexed keywords

CXCL1 CHEMOKINE; CXCL2 CHEMOKINE; EPITHELIAL DERIVED NEUTROPHIL ACTIVATING FACTOR 78; GAMMA INTERFERON; INTERLEUKIN 10; INTERLEUKIN 12; INTERLEUKIN 2; TUMOR NECROSIS FACTOR; BIOLOGICAL MARKER; CHEMOKINE; CXCL1 PROTEIN, MOUSE; CXCL2 PROTEIN, MOUSE; CXCL5 PROTEIN, MOUSE; CYTOKINE;

ANIMAL CELL; ANIMAL EXPERIMENT; ANIMAL MODEL; ANIMAL TISSUE; APOPTOSIS; ARTICLE; BACTERIAL LOAD; CLASSIFIER; CONTROLLED STUDY; CYTOKINE PRODUCTION; DISEASE PREDISPOSITION; FEMALE; LUNG DISEASE; LUNG NECROSIS; LUNG TUBERCULOSIS; MOLECULAR PATHOLOGY; MOUSE; MYCOBACTERIUM TUBERCULOSIS; NECROSIS; NEUTROPHIL; NONHUMAN; PHENOTYPE; PRIORITY JOURNAL; SIGNAL TRANSDUCTION; STATISTICAL ANALYSIS; SURVIVAL RATE; WEIGHT REDUCTION; ANIMAL; BLOOD; C57BL MOUSE; DISEASE MODEL; GENETIC PREDISPOSITION; LUNG; MACHINE LEARNING; METABOLISM; PATHOLOGY; TUBERCULOSIS;

ANIMALS; BIOMARKERS; CHEMOKINE CXCL1; CHEMOKINE CXCL2; CHEMOKINE CXCL5; CHEMOKINES; CYTOKINES; DISEASE MODELS, ANIMAL; FEMALE; GENETIC PREDISPOSITION TO DISEASE; INTERFERON-GAMMA; LUNG; MACHINE LEARNING; MICE; MICE, INBRED C57BL; MYCOBACTERIUM TUBERCULOSIS; NECROSIS; NEUTROPHILS; TUBERCULOSIS; TUMOR NECROSIS FACTOR-ALPHA;

EID: 84941558449     PISSN: 17548403     EISSN: 17548411     Source Type: Journal    
DOI: 10.1242/dmm.020867     Document Type: Article

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