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Kurtz, D. M.

Publications and source records attributed to Kurtz, D. M..

2 recordsLinked to original sources

Toxigenic Profile of Clostridium perfringens Strains Isolated from Natural Ingredient Laboratory Animal Diets

Clostridium perfringens is an anaerobic, gram-positive, spore-forming bacterium that ubiquitously inhabits a wide variety of natural environments including the gastrointestinal tract of humans and animals. C. perfringens is an opportunistic enteropathogen capable of producing at least 20 different toxins in various combinations. Strains of C. perfringens are currently categorized into seven toxinotypes (A, B, C, D, E, F & G) based on the presence/absence of four major toxins (alpha, beta, epsilon & iota) and two minor toxins (enterotoxin & netB). Each toxinotype is associated with specific histotoxic and enteric diseases. The Quality Assurance Laboratory (QAL) at the National Institute of Environmental Health Sciences (NIEHS) screens incoming animal feeds for aerobic, enteric pathogens, such as Salmonella spp. and E. coli. Recently, QAL has incorporated anaerobic screening of incoming animal feeds. To date, the lab has isolated numerous Clostridium species, including C. perfringens, from 23 lots of natural-ingredient laboratory animal diets. ImportancePublished reports of Clostridium perfringens isolation from laboratory animal feeds could not be found in the literature. Therefore, we performed a toxin profile screening of our isolated strains of C. perfringens to determine which toxinotypes were present in our laboratory animal diets. As studies progress with immunocompromised strains, gnotobiotic models, and animals with perturbed gut flora, the presence of C. perfringens could potentially lead to infection, disease and mortality which would substantiate the need to properly eliminate the bacterium and its spores from diets given to high risk animal populations.

microbiology↗

A mathematical model of ctDNA shedding predicts tumor detection size

Early cancer detection aims to find tumors before they progress to an incurable stage. We developed a stochastic mathematical model of tumor evolution and circulating tumor DNA (ctDNA) shedding to determine the potential and the limitations of cancer early detection tests. We inferred normalized ctDNA shedding rates from 176 early stage lung cancer subjects and calculated that a 15 mL blood sample contains on average 1.7 genome equivalents of ctDNA for lung tumors with a volume of 1 cm3. For annual screening, the model predicts median detection sizes between 3.8 and 6.6 cm3 corresponding to lead times between 310 and 450 days compared to current lung tumor sizes at diagnosis. For monthly cancer relapse testing based on 20 a priori known mutations, the model predicts a median detection size of 0.26 cm3 corresponding to a lead time of 150 days. This mechanistic framework can help to optimize early cancer detection approaches.

cancer biology↗