# | Rank | Similarity | Title + Abs. | Year | PMID |
|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | 4 | 5 |
| 4279 | 0 | 1.0000 | Simulation Model of Bacterial Resistance to Antibiotics Using Individual-Based Modeling. We designed and implemented simulation models of bacterial growth and antibiotic resistance to determine the appropriate antibiotics to use against antibiotic-resistant bacteria. Simulation models were designed using individual-based modeling, and a simulation tool, ARSim, was developed to conduct experiments using the models. Simulations of bacterial growth were conducted by virtually growing Klebsiella pneumoniae bacteria in a virtual environment with predefined parameters. Other experiments included predicting the effects of antibiotics when added to two different groups, one group of nonresistant bacteria and another group of both resistant and nonresistant bacteria. Carbapenem class antibiotics such as Imipenem were used for the simulation. The simulation results showed that the biological principles of bacteria and their antibiotic resistance mechanisms were correctly designed and implemented. Using the computational approaches developed in this study, we hope to provide researchers with a more effective method for finding new ways to fight antibiotic resistance. | 2018 | 29927616 |
| 4061 | 1 | 0.9998 | Beyond serial passages: new methods for predicting the emergence of resistance to novel antibiotics. Market launching of a new antibiotic requires knowing in advance its benefits and possible risks, and among them how rapidly resistance will emerge and spread among bacterial pathogens. This information is not only useful from a public health point of view, but also for pharmaceutical industry, in order to reduce potential waste of resources in the development of a compound that might be discontinued at the short term because of resistance development. Most assays currently used for predicting the emergence of resistance are based on culturing the target bacteria by serial passages in the presence of increasing concentrations of antibiotics. Whereas these assays may be valuable for identifying mutations that might cause resistance, they are not useful to establish how fast resistance might appear, neither to address the risk of spread of resistance genes by horizontal gene transfer. In this article, we review recent information pertinent for a more accurate prediction on the emergence and dispersal of antibiotic resistance. | 2011 | 21835695 |
| 4295 | 2 | 0.9998 | Antibiotic resistance in the intensive care unit. The increase in antibiotic resistance over the past 10 years can be traced to several factors. This includes exogenous transmission of bacteria, usually by hospital personnel. The use of potent antibiotics also can select for resistant bacteria initially present in low quantities. Strategies to reduce antibiotic resistance can be tailored to specific outbreaks in a given ICU. General strategies for reducing antibiotic resistance, on the other hand, include varying the agents used in the ICU over time. Reduction of the duration of therapy may prove to be another method of reducing antibiotic resistance. | 2002 | 12357111 |
| 4125 | 3 | 0.9998 | The epidemiology of antibiotic resistance in hospitals: paradoxes and prescriptions. A simple mathematical model of bacterial transmission within a hospital was used to study the effects of measures to control nosocomial transmission of bacteria and reduce antimicrobial resistance in nosocomial pathogens. The model predicts that: (i) Use of an antibiotic for which resistance is not yet present in a hospital will be positively associated at the individual level (odds ratio) with carriage of bacteria resistant to other antibiotics, but negatively associated at the population level (prevalence). Thus inferences from individual risk factors can yield misleading conclusions about the effect of antibiotic use on resistance to another antibiotic. (ii) Nonspecific interventions that reduce transmission of all bacteria within a hospital will disproportionately reduce the prevalence of colonization with resistant bacteria. (iii) Changes in the prevalence of resistance after a successful intervention will occur on a time scale of weeks to months, considerably faster than in community-acquired infections. Moreover, resistance can decline rapidly in a hospital even if it does not carry a fitness cost. The predictions of the model are compared with those of other models and published data. The implications for resistance control and study design are discussed, along with the limitations and assumptions of the model. | 2000 | 10677558 |
| 4060 | 4 | 0.9998 | Current status of antibiotic resistance in animal production. It is generally accepted that the more antibiotics we use, the faster bacteria will develop resistance. Further it has been more or less accepted that once an antibiotic is withdrawn from the clinic, the resistance genes will eventually disappear, [table: see text] since they will no more be of any survival value for the bacterial cell. However, recent research has shown that after a long time period of exposure to antibiotics, certain bacterial species may adapt to this environment in such a way that they keep their resistance genes stably also after the removal of antibiotics. Thus, there is reason to believe that once resistance has developed it will not even in the long term be eradicated. What then can we do not to increase further the already high level of antibiotic-resistant bacteria in animals? We should of course encourage a prudent use of these valuable drugs. In Sweden antibiotics are not used for growth promoting purposes and are available only after veterinary prescription on strict indications. Generally, antimicrobial treatment of animals on individual or on herd basis should not be considered unless in connection with relevant diagnostics. The amounts of antibiotics used and the development of resistance in important pathogens should be closely monitored. Furthermore, resistance monitoring in certain non-pathogenic intestinal bacteria, which may serve as a reservoir for resistance genes is probably more important than hitherto anticipated. Once the usage of or resistance to a certain antibiotic seems to increase in an alarming way, steps should be taken to limit the usage of the drug in order to prevent further spread of resistance genes in animals, humans and the environment. Better methods for detecting and quantifying antibiotic resistance have to be developed. Screening methods must be standardized and evaluated in order to obtain comparable and reliable results from different countries. The genetic mechanisms for development of resistance and spread of resistance genes should be studied in detail. Research in these areas will lead to new ideas on how to inhibit the resistance mechanisms. So far, it has been well established that a heavy antimicrobial drug selective pressure in overcrowded populations of production animals creates favourable environments both for the emergence and the spread of antibiotic resistance genes. | 1999 | 10783714 |
| 4280 | 5 | 0.9998 | Droplet Microfluidics for High-Throughput Analysis of Antibiotic Susceptibility in Bacterial Cells and Populations. Antibiotic-resistant bacteria are an increasing concern both in everyday life and specialized environments such as healthcare. As the rate of antibiotic-resistant infections rises, so do complications to health and the risk of disability and death. Urgent action is required regarding the discovery of new antibiotics and rapid diagnosis of the resistance profile of an infectious pathogen as well as a better understanding of population and single-cell distribution of the resistance level. High-throughput screening is the major affordance of droplet microfluidics. Droplet screens can be exploited both to look for combinations of drugs that could stop an infection of multidrug-resistant bacteria and to search for the source of resistance via directed-evolution experiments or the analysis of various responses to a drug by genetically identical bacteria. In droplet techniques that have been used in this way for over a decade, aqueous droplets containing antibiotics and bacteria are manipulated both within and outside of the microfluidic devices. The diagnostics problem was approached by producing a series of microfluidic systems with integrated dilution modules for automated preparation of antibiotic concentration gradients, achieving the speed that allowed for high-throughput combinatorial assays. We developed a method for automated emulsification of a series of samples that facilitated measuring the resistance levels of thousands of individual cells encapsulated in droplets and quantifying the inoculum effect, the dependence of resistance level on bacterial cell count. Screening of single cells encapsulated in droplets with varying antibiotic contents has revealed a distribution of resistance levels within populations of clonally identical cells. To be able to screen bacteria from clinical samples, a study of fluorescent dyes in droplets determined that a derivative of a popular viability marker is more suitable for droplet assays. We have developed a detection system that analyzes the growth or death state of bacteria with antibiotics for thousands of droplets per second by measuring the scattering of light hitting the droplets without labeling the cells or droplets. The droplet-based microchemostats enabled long-term evolution of resistance experiments, which will be integrated with high-throughput single-cell assays to better understand the mechanism of resistance acquisition and loss. These techniques underlie automated combinatorial screens of antibiotic resistance in single cells from clinical samples. We hope that this Account will inspire new droplet-based research on the antibiotic susceptibility of bacteria. | 2022 | 35119826 |
| 4057 | 6 | 0.9998 | A model of the transmission of antibiotic-resistant bacteria in the intensive care unit. Antibiotic resistance is a growing problem, affecting microorganisms found both in hospitals and in the community. In most patients, resistant organisms arise by transmission of already resistant microorganisms from another person, rather than arising by mutation in the index patient. Antibiotic resistance genes are often borne on plasmids or transposons on which they may be spread rapidly to other organisms in the same species or in other species. Plasmids and transposons readily pick up genes for resistance to other antibiotics or nonantibiotic agents ("linked resistance"). Control of the spread of antibiotic resistance may require limitation of the usage of other agents with linked resistance as well as of the antibiotics of primary interest. A model is described for the analysis of the transmission of antibiotic-resistant enteric bacteria in the ICU. The model deals with the baseline level of antibiotic resistance in the "source" patient, the effect of antibiotics in augmenting the concentration of resistant organisms in that patient, the role of patient-to-patient contact, and factors which may influence the "colonizability" of the recipient patient. Possible measures to reduce the spread of antibiotic resistance are discussed. It is hoped that the model may serve to focus discussion on some key ingredients of the transmission cycle. | 1996 | 8856750 |
| 4293 | 7 | 0.9998 | Resistance to ocular antibiotics: an overview. The introduction of new antibiotic compounds into therapy initiates the development of resistance by the target bacteria. Resistance increases the risk of treatment failure with potentially serious consequences. Local application of antibacterial compounds to the eyes may lead to bacterial resistance in bacterial isolates from the eyes. The incidence of resistant strains of common pathogens is probably increasing. As compounds can be absorbed into the systemic circulation following ocular administration, the subsequent low concentrations in the blood could provide the selective pressure for the survival of resistant bacteria in the body. Despite this possibility, there are no reports of systemic resistance in bacteria following ocular administration of antibacterial compounds. All health-care professionals should be concerned about this possibility and continue to use these important compounds with respect. | 2007 | 17535364 |
| 4274 | 8 | 0.9998 | Antibiotic resistance: counting the cost. Acquisition of drug resistance should impose a cost on bacteria. Recent studies, however, suggest that natural selection acts to reduce, or eliminate, the growth disadvantage of resistant bacteria, making it difficult to reverse the high levels of antibiotic resistance currently found in hospitals and the community. | 1996 | 8939559 |
| 4098 | 9 | 0.9998 | Population Dynamics of Patients with Bacterial Resistance in Hospital Environment. During the past decades, the increase of antibiotic resistance has become a major concern worldwide. The researchers found that superbugs with new type of resistance genes (NDM-1) have two aspects of transmission characteristics; the first is that the antibiotic resistance genes can horizontally transfer among bacteria, and the other is that the superbugs can spread between humans through direct contact. Based on these two transmission mechanisms, we study the dynamics of population in hospital environment where superbugs exist. In this paper, we build three mathematic models to illustrate the dynamics of patients with bacterial resistance in hospital environment. The models are analyzed using stability theory of differential equations. Positive equilibrium points of the system are investigated and their stability analysis is carried out. Moreover, the numerical simulation of the proposed model is also performed which supports the theoretical findings. | 2016 | 26904150 |
| 4294 | 10 | 0.9998 | Anaerobic infections: update on treatment considerations. Anaerobic bacteria are the predominant indigenous flora of humans and, as a result, play an important role in infections, some of which are serious with a high mortality rate. These opportunistic pathogens are frequently missed in cultures of clinical samples because of shortcomings in collection and transport procedures as well as lack of isolation and susceptibility testing of anaerobes in many clinical microbiology laboratories. Correlation of clinical failures with known antibacterial resistance of anaerobic bacteria is seldom possible. Changes in resistance over time, and the discovery and characterization of resistance determinants in anaerobic bacteria, has increased recognition of problems in empirical treatment and has even resulted in changes in treatment guidelines. This review discusses the role of anaerobic bacteria in the normal flora of humans, their involvement in different mixed infections, developments in antibacterial resistance of the most frequent anaerobic pathogens and possible new treatment options. | 2010 | 20426496 |
| 9435 | 11 | 0.9998 | Why are bacteria refractory to antimicrobials? The incidence of antibiotic resistance in pathogenic bacteria is rising. Antibiotic resistance can be achieved via three distinct routes: inactivation of the drug, modification of the target of action, and reduction in the concentration of drug that reaches the target. It has long been recognized that specific antibiotic resistance mechanisms can be acquired through mutation of the bacterial genome or by gaining additional genes through horizontal gene transfer. Recent attention has also brought to light the importance of different physiological states for the survival of bacteria in the presence of antibiotics. It is now apparent that bacteria have complex, intrinsic resistance mechanisms that are often not detected in the standard antibiotic sensitivity tests performed in clinical laboratories. The development of resistance in bacteria found in surface-associated aggregates or biofilms, owing to these intrinsic mechanisms, is paramount. | 2002 | 12354553 |
| 4058 | 12 | 0.9998 | Antimicrobial resistance: a complex issue. The discovery of antibiotics represented a turning point in human history. However, by the late 1950s infections that were difficult to treat, involving resistant bacteria, were being reported. Nowadays, multiresistant strains have become a major concern for public and animal health. Antimicrobial resistance is a complex issue, linked to the ability of bacteria to adapt quickly to their environment. Antibiotics, and antimicrobial-resistant bacteria and determinants, existed before the discovery and use of antibiotics by humans. Resistance to antimicrobial agents is a tool that allows bacteria to survive in the environment, and to develop. Resistance genes can be transferred between bacteria by horizontal transfer involving three mechanisms: conjugation, transduction and transformation. Resistant bacteria can emerge in any location when the appropriate conditions develop. Antibiotics represent a powerful selector for antimicrobial resistance in bacteria. Reducing the use of antimicrobial drugs is one way to control antimicrobial resistance; however, a full set of measures needs to be implemented to achieve this aim. | 2012 | 22849265 |
| 4292 | 13 | 0.9998 | The impact of different antibiotic regimens on the emergence of antimicrobial-resistant bacteria. BACKGROUND: The emergence and ongoing spread of antimicrobial-resistant bacteria is a major public health threat. Infections caused by antimicrobial-resistant bacteria are associated with substantially higher rates of morbidity and mortality compared to infections caused by antimicrobial-susceptible bacteria. The emergence and spread of these bacteria is complex and requires incorporating numerous interrelated factors which clinical studies cannot adequately address. METHODS/PRINCIPAL FINDINGS: A model is created which incorporates several key factors contributing to the emergence and spread of resistant bacteria including the effects of the immune system, acquisition of resistance genes and antimicrobial exposure. The model identifies key strategies which would limit the emergence of antimicrobial-resistant bacterial strains. Specifically, the simulations show that early initiation of antimicrobial therapy and combination therapy with two antibiotics prevents the emergence of resistant bacteria, whereas shorter courses of therapy and sequential administration of antibiotics promote the emergence of resistant strains. CONCLUSIONS/SIGNIFICANCE: The principal findings suggest that (i) shorter lengths of antibiotic therapy and early interruption of antibiotic therapy provide an advantage for the resistant strains, (ii) combination therapy with two antibiotics prevents the emergence of resistance strains in contrast to sequential antibiotic therapy, and (iii) early initiation of antibiotics is among the most important factors preventing the emergence of resistant strains. These findings provide new insights into strategies aimed at optimizing the administration of antimicrobials for the treatment of infections and the prevention of the emergence of antimicrobial resistance. | 2008 | 19112501 |
| 4118 | 14 | 0.9998 | Antimicrobial resistance in livestock. Antimicrobial resistance may become a major problem in veterinary medicine as a consequence of the intensive use and misuse of antimicrobial drugs. Related problems are now arising in human medicine, such as the appearance of multi-resistant food-borne pathogens. Product characteristics, dose, treatment interval and duration of treatment influence the selection pressure for antimicrobial drug resistance. There are theoretical, experimental and clinical indications that the emergence of de novo resistance in a pathogenic population can be prevented by minimizing the time that suboptimal drug levels are present in the infected tissue compartment. Until recently, attention has been focused on target pathogens. However, it should be kept in mind that when antimicrobial drugs are used in an individual, resistance selection mainly affects the normal body flora. In the long term, this is at least equally important as resistance selection in the target pathogens, as the horizontal transfer of resistance genes converts almost all pathogenic bacteria into potential recipients for antimicrobial resistance. Other factors contributing to the epidemiology of antimicrobial resistance are the localization and size of the microbial population, and the age, immunity and contact intensity of the host. In livestock, dynamic herd-related resistance patterns have been observed in different animal species. | 2003 | 12667177 |
| 4236 | 15 | 0.9998 | Resistance of bacteria to antibacterial agents: report of Task Force 2. The use of a growing number of antibacterial agents over the past half century has elicited a widespread deployment of genes for resistance to these agents in populations of bacteria throughout the world. Task Force 2 of the NIH Study on Antibiotic Use and Antibiotic Resistance Worldwide found that data on prevalence of resistance was fragmentary and underanalyzed but indicative of several trends. Resistance to older antibacterial agents appears to have stabilized overall, but shifts of resistance genes into new strains and species have continued to cause new clinical problems. Resistance to newer antibacterial agents has increased. Resistance is more prevalent in developing countries. Systematic surveillance of resistance integrated with understanding of its molecular basis is needed for control of resistance. | 1987 | 3299646 |
| 3823 | 16 | 0.9998 | Emergence, spread, and environmental effect of antimicrobial resistance: how use of an antimicrobial anywhere can increase resistance to any antimicrobial anywhere else. Use of an antimicrobial agent selects for overgrowth of a bacterial strain that has a gene expressing resistance to the agent. It also selects for the assembly and evolution of complex genetic vectors encoding, expressing, linking, and spreading that and other resistance genes. Once evolved, a competitive construct of such genetic elements may spread widely through the world's bacterial populations. A bacterial isolate at any place may thus be resistant-not only because nearby use of antimicrobials had amplified such a genetic construct locally, but also because distant use had caused the construct or its components to evolve in the first place and spread there. The levels of resistance at any time and place may therefore reflect in part the total number of bacteria in the world exposed to antimicrobials up until then. Tracing the evolution and spread of such genetic elements through bacterial populations far from one another, such as those of animals and humans, can be facilitated by newer genetic methods. | 2002 | 11988877 |
| 4052 | 17 | 0.9998 | Functional metagenomics for the investigation of antibiotic resistance. Antibiotic resistance is a major threat to human health and well-being. To effectively combat this problem we need to understand the range of different resistance genes that allow bacteria to resist antibiotics. To do this the whole microbiota needs to be investigated. As most bacteria cannot be cultivated in the laboratory, the reservoir of antibiotic resistance genes in the non-cultivatable majority remains relatively unexplored. Currently the only way to study antibiotic resistance in these organisms is to use metagenomic approaches. Furthermore, the only method that does not require any prior knowledge about the resistance genes is functional metagenomics, which involves expressing genes from metagenomic clones in surrogate hosts. In this review the methods and limitations of functional metagenomics to isolate new antibiotic resistance genes and the mobile genetic elements that mediate their spread are explored. | 2014 | 24556726 |
| 9697 | 18 | 0.9998 | Origins and evolution of antibiotic resistance. The massive prescription of antibiotics and their non-regulated and extensive usage has resulted in the development of extensive antibiotic resistance in microorganisms; this has been of great clinical significance. Antibiotic resistance occurs not only by mutation of microbial genes which code for antibiotic uptake into cells or the binding sites for antibiotics, but mostly by the acquisition of heterologous resistance genes from external sources. The physical characteristics of the microbial community play a major role in gene exchange, but antimicrobial agents provide the selective pressure for the development of resistance and promote the transfer of resistance genes among bacteria. The control of antibiotic usage is essential to prevent the development of resistance to new antibiotics. | 1996 | 9019139 |
| 9803 | 19 | 0.9998 | Combating antibiotic resistance in bacteria. Combinations of certain antibiotics select against resistant strains of bacteria. This finding may provide a strategy of combating antibiotic resistant bacteria. | 2007 | 23100665 |