| Chapter title |
In Vitro and In Vivo Biofilm Wound Models and Their Application
|
|---|---|
| Chapter number | 5002 |
| Book title |
Advances in Microbiology, Infectious Diseases and Public Health
|
| Published in |
Advances in experimental medicine and biology, November 2015
|
| DOI | 10.1007/5584_2015_5002 |
| Pubmed ID | |
| Book ISBNs |
978-3-31-926319-9, 978-3-31-926320-5
|
| Authors |
Brackman, Gilles, Coenye, Tom, Gilles Brackman, Tom Coenye |
| Editors |
Gianfranco Donelli |
| Abstract |
Chronic wounds are wounds which are detained in one or more phases of normal wound healing. It is estimated that 1-2 % of the population of developed countries will experience a chronic wound during their lifetime and this number is expected to increase given the growing world population, increase in age, body mass index and associated diseases such as diabetes and cardiovascular diseases. Although several factors contribute to wound healing, presence of bacterial biofilms significantly affects healing and success of wound treatment. This indicates that wound-care therapies should be directed towards targeting biofilms within chronic wounds. Despite this, the role of biofilms in chronic wound pathogenesis and the effect of wound-care therapies against biofilms within wounds are not well understood. In order to address these issues, appropriate biofilm models are necessary. To this end, several model systems mimicking the conditions observed in a biofilm infected chronic wound have been developed. In this review we present an overview of these different in vitro and in vivo biofilm wound model systems and discuss their advantages and disadvantages. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | 25% |
| Belgium | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 75% |
| Science communicators (journalists, bloggers, editors) | 1 | 25% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 127 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 22 | 17% |
| Student > Master | 19 | 15% |
| Researcher | 16 | 13% |
| Student > Bachelor | 11 | 9% |
| Student > Doctoral Student | 6 | 5% |
| Other | 19 | 15% |
| Unknown | 34 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 23 | 18% |
| Medicine and Dentistry | 17 | 13% |
| Agricultural and Biological Sciences | 16 | 13% |
| Immunology and Microbiology | 10 | 8% |
| Engineering | 6 | 5% |
| Other | 16 | 13% |
| Unknown | 39 | 31% |