B. E. Etchebarne
Michigan State University
Network
Latest external collaboration on country level. Dive into details by clicking on the dots.
Publication
Featured researches published by B. E. Etchebarne.
Journal of Dairy Science | 2008
L. F. P. Silva; B. E. Etchebarne; M.S. Weber Nielsen; J.S. Liesman; Matti Kiupel; M.J. VandeHaar
High energy intake and excessive body fatness impair mammogenesis in prepubertal ruminants. High energy intake and excessive fatness also increase serum leptin. Our objective was to determine if an infusion of leptin decreases proliferation of mammary epithelial cells of prepubertal heifers in vivo. Ovine leptin at 100 microg/ quarter per d with or without 10 microg of insulin-like growth factor (IGF)-I was infused via the teat canal into mammary glands of prepubertal dairy heifers; contralateral quarters were used as controls. After 7 d of treatment, bromodeoxyuridine was infused intravenously and heifers were slaughtered approximately 2 h later. Tissue from 3 regions of the mammary parenchyma was collected and immunostained for bromodeoxyuridine (BrdU), proliferating cell nuclear antigen (Ki-67), and caspase-3. Leptin decreased the number of mammary epithelial cells in the S-phase of the cell cycle by 48% in IGF-I-treated quarters and by 19% in saline-treated quarters. Leptin did not alter the number of mammary epithelial cells within the cell cycle, as indicated by Ki-67 labeling. Caspase-3 immunostaining within the mammary parenchyma was very low in these heifers, but leptin significantly increased labeling in saline-treated quarters. Leptin enhanced SOCS-3 expression in IGF-I-treated quarters but did not alter SOCS-1 or SOCS-5 expression. We conclude that a high concentration of leptin in the bovine mammary gland reduces proliferation of mammary epithelial cells. The reduced proliferation is accompanied by an increase in SOCS-3 expression, suggesting a possible mechanism for leptin inhibition of IGF-I action. Whether leptin might be a physiological regulator of mammogenesis remains to be determined.
FEMS Microbiology Ecology | 2016
Robert D. Stedtfeld; Maggie R. Williams; Umama Fakher; Timothy A. Johnson; Tiffany M. Stedtfeld; Fang Wang; Walid T. Khalife; Mary J. Hughes; B. E. Etchebarne; James M. Tiedje; Syed A. Hashsham
An antibiotic resistance (AR) Dashboard application is being developed regarding the occurrence of antibiotic resistance genes (ARG) and bacteria (ARB) in environmental and clinical settings. The application gathers and geospatially maps AR studies, reported occurrence and antibiograms, which can be downloaded for offline analysis. With the integration of multiple data sets, the database can be used on a regional or global scale to identify hot spots for ARGs and ARB; track and link spread and transmission, quantify environmental or human factors influencing presence and persistence of ARG harboring organisms; differentiate natural ARGs from those distributed via human or animal activity; cluster and compare ARGs connections in different environments and hosts; and identify genes that can be used as proxies to routinely monitor anthropogenic pollution. To initially populate and develop the AR Dashboard, a qPCR ARG array was tested with 30 surface waters, primary influent from three waste water treatment facilities, ten clinical isolates from a regional hospital and data from previously published studies including river, park soil and swine farm samples. Interested users are invited to download a beta version (available on iOS or Android), submit AR information using the application, and provide feedback on current and prospective functionalities.
Analytical Methods | 2017
Maggie R. Williams; Robert D. Stedtfeld; Hassan Waseem; Tiffany M. Stedtfeld; Brad L. Upham; Walid T. Khalife; B. E. Etchebarne; Mary J. Hughes; James M. Tiedje; Syed A. Hashsham
Antimicrobial resistance (AMR) is recognized as a global threat to human health. Rapid detection and characterization of AMR is a critical component of most antibiotic stewardship programs. Methods based on amplification of nucleic acids for detection of AMR are generally faster than culture-based approaches but they still require several hours to more than a day due to the need for transporting the sample to a centralized laboratory, processing of sample, and sometimes DNA purification and concentration. Nucleic acids-based point-of-care (POC) devices are capable of rapidly diagnosing antibiotic-resistant infections which may help in making timely and correct treatment decisions. However, for most POC platforms, sample processing for nucleic acids extraction and purification is also generally required prior to amplification. Direct amplification, an emerging possibility for a number of polymerases, has the potential to eliminate these steps without significantly impacting diagnostic performance. This review summarizes direct amplification methods and their implication for rapid measurement of AMR. Future research directions that may further strengthen the possibility of integrating direct amplification methods with POC devices are also summarized.
Frontiers in Microbiology | 2017
B. E. Etchebarne; Zenggang Li; Robert D. Stedtfeld; Michael C. Nicholas; Maggie R. Williams; Timothy A. Johnson; Tiffany M. Stedtfeld; Tanja Kostic; Walid T. Khalife; James M. Tiedje; Syed A. Hashsham; Mary J. Hughes
Battling infection is a major healthcare objective. Untreated infections can rapidly evolve toward the condition of sepsis in which the body begins to fail and resuscitation becomes critical and tenuous. Identification of infection followed by rapid antimicrobial treatment are primary goals of medical care, but precise identification of offending organisms by current methods is slow and broad spectrum empirical therapy is employed to cover most potential pathogens. Current methods for identification of bacterial pathogens in a clinical setting typically require days of time, or a 4- to 8-h growth phase followed by DNA extraction, purification and PCR-based amplification. We demonstrate rapid (70–120 min) genetic diagnostics methods utilizing loop-mediated isothermal amplification (LAMP) to test for 15 common infection pathogen targets, called the Infection Diagnosis Panel (In-Dx). The method utilizes filtration to rapidly concentrate bacteria in sample matrices with lower bacterial loads and direct LAMP amplification without DNA purification from clinical blood, urine, wound, sputum and stool samples. The In-Dx panel was tested using two methods of detection: (1) real-time thermocycler fluorescent detection of LAMP amplification and (2) visual discrimination of color change in the presence of Eriochrome Black T (EBT) dye following amplification. In total, 239 duplicate samples were collected (31 blood, 122 urine, 73 mucocutaneous wound/swab, 11 sputum and two stool) from 229 prospectively enrolled hospital patients with suspected clinical infection and analyzed both at the hospital and by In-Dx. Sensitivity (Se) of the In-Dx panel targets pathogens from urine samples by In-Dx was 91.1% and specificity (Sp) was 97.3%, with a positive predictive value (PPV) of 53.7% and a negative predictive value (NPV) of 99.7% as compared to clinical microbial detection methods. Sensitivity of detection of the In-Dx panel from mucocutaneous swab samples was 65.5% with a Sp of 99.3%, and a PPV of 84% and NPV of 98% as compared to clinical microbial detection methods. Results indicate the LAMP-based In-Dx panel allows rapid and precise diagnosis of clinical infections by targeted pathogens across multiple culture types for point-of-care utilization.
Asian-australasian Journal of Animal Sciences | 2009
M. Baik; B. E. Etchebarne; J. Bong; M.J. VandeHaar
Biomedical Microdevices | 2015
Robert D. Stedtfeld; Yen Cheng Liu; Tiffany M. Stedtfeld; Tanja Kostic; Maggie Kronlein; Onnop Srivannavit; Walid T. Khalife; James M. Tiedje; Erdogan Gulari; Mary J. Hughes; B. E. Etchebarne; Syed A. Hashsham
Journal of Dairy Science | 2005
L. F. P. Silva; J.S. Liesman; B. E. Etchebarne; M.S. Weber Nielsen; M.J. VandeHaar
Journal of Animal and Feed Sciences | 2004
B. E. Etchebarne; W. Nobis; M. S. Allen; M. J. Van de Haar
Archive | 2018
B. E. Etchebarne
Analytical Methods | 2017
Maggie R. Williams; Robert D. Stedtfeld; Hassan Waseem; Tiffany M. Stedtfeld; Brad L. Upham; Walid T. Khalife; B. E. Etchebarne; Mary J. Hughes; James M. Tiedje; Syed A. Hashsham