Current status of malaria and potential for control

Malaria remains one of the world's worst health problems with 1.5 to 2.7 million deaths annually; these deaths are primarily among children under 5 years of age and pregnant women in sub-Saharan Africa. Of significance, more people are dying from malaria today than 30 years ago. This review considers the factors which have contributed to this gloomy picture, including those which relate to the vector, the female anopheline mosquito; to human activity such as creating new mosquito breeding sites, the impact of increased numbers of people, and how their migratory behavior can increase the incidence and spread of malaria; and the problems of drug resistance by the parasites to almost all currently available antimalarial drugs. In a selective manner, this review describes what is being done to ameliorate this situation both in terms of applying existing methods in a useful or even crucial role in control and prevention and in terms of new additions to the antimalarial armory that are being developed. Topics covered include biological control of mosquitoes, the use of insecticide-impregnated bed nets, transgenic mosquitoes manipulated for resistance to malaria parasites, old and new antimalarial drugs, drug resistance and how best to maintain the useful life of antimalarials, immunity to malaria and the search for antimalarial vaccines, and the malaria genome project and the potential benefits to accrue from it.     

Genomics of the future: identification of quantitative trait loci in the mouse

Positional cloning of quantitative trait loci in rodents is a common approach to identify genes involved in complex phenotypes, including genes important to human disease. However, cloning the causative genes has proved to be more difficult than determining their positions. New tools such as genomic sequence, clone libraries, and new genomic-based methods offer new approaches to identify these genes. Here we review how these new tools and approaches will improve our ability to discover the genes important in complex traits.     

Guidelines for cognitively efficient multimedia learning tools: educational strategies, cognitive load, and interface design.

The field of medical education has consistently embraced new technologies in an attempt to improve the training process of our nation's doctors. There are thousands of available multimedia learning tools (MMLTs), but no quantitative scale exists to assess their efficiency and overall educational value. The authors review existing literature and suggest guidelines for creating cognitively efficient medical MMLTs. In 2004, the authors searched PubMed to identify articles regarding mutimedia learning, including educational strategies and existing MMLTs. The primary search terms included "multimedia learning," "cognitive load," and "surgical education." The resulting articles were evaluated and reviewed for educational and interface design techniques, and a list of common features was generated. The authors cross-referenced these features with extensive theories of cognitive load to create a list of methods that demonstrated improved learning. Techniques common to existing MMLTs often neglect to account for theories of cognitive load and may be detrimental to the learning process. The authors outlined important educational considerations and guidelines for the design of effective MMLTs. With large resources being spent to produce MMLTs, more research is necessary to establish successful design techniques. The authors summarized existing research, outlined educational issues in multimedia design, and proposed future directions for study.     

Methods for Fabrication of Nanoscale Topography for Tissue Engineering Scaffolds

Observations of how controlling the microenvironment of cell cultures can lead to changes in a variety of parameters has lead investigators to begin studying how the nanoenvironment of a culture can affects cells. Cells have many structures at the nanoscale such as filipodia and cytoskeletal and membrane proteins that interact with the environment surrounding them. By using techniques that can control the nanoenvironment presented to a cell, investigators are beginning to be able to mimic the nanoscale topographical features presented to cells by extracellular matrix proteins such as collagen, which has precise and repeating nanotopography. The belief is that these nanoscale surface features are important to creating more natural cell growth and function. A number of techniques are currently being used to create nanoscale topographies for cell scaffolding. These techniques fall into two main categories: techniques that create ordered topographies and those that create unordered topographies. Electron Beam lithography and photolithograpghy are two standard techniques for creating ordered features. Polymer demixing, phase separation, colloidal lithography and chemical etching are most typically used for creating unordered surface patterns. This review will give an overview of these techniques and cite observations from experiments carried out using them.     

Review paper: principles and applications of surface analytical techniques at the vascular interface

Surface properties have been found to be one of the key parameters which cause degradation and of thrombogenicity in all polymers used in biomedical devices, thus signifying the importance and the necessity for quantitative and accurate characterization of the polymer surface itself as used in the construction of the device. The characterization techniques employed generally involve thermal and spectroscopic measurements, in which class the electrochemical investigations and scanning probe microscopies can also be included. Current hypotheses on the correlations that exist between surface parameters and hemocompatibility and degradation of polymers are examined herein, but concentrating on the field of clinically utilized polymeric materials as used within medical devices themselves. Furthermore, this review provides a brief but complete synopsis of these techniques and other emerging ones, which have proven useful in the analysis of the surface properties of polymeric materials as used in the construction of cardiovascular devices. Statements and examples are given as to how specific information can be acquired from these differing methodologies and how it aids in the design and development of new polymers for usage in biomedical device construction.     

Developing and Monitoring a Standard-of-Care Chimeric Antigen Receptor (CAR) T Cell Clinical Quality and Regulatory Program

As the world of cellular therapy expands to include immune effector cell (IEC) products such as commercial chimeric antigen receptor (CAR) T cells, quality management (QM) professionals are faced with creating either new IEC stand-alone programs or expand existing hematopoietic cell transplantation (HCT) programs to promote patient safety and be aligned with quality, regulatory, and accreditation requirements. The team professionals at City of Hope (COH) recently expanded the quality HCT program to include IEC products and, in doing so, implemented new regulatory infrastructure while maintaining high quality patient care. At COH, we developed the quality structure of our cellular therapy program through collaborations between quality, regulatory, and CAR T patient care committees, which included physicians and nurse coordinators. To ensure the quality of our program, we monitor data collection and reporting, perform quarterly proactive audits of, for example, outcome analysis, and measure selected end-points for benchmarking purposes. QM professionals play a critical role in the monitoring and evaluation processes and provide guidance on how to implement accreditation requirements and what impact the requirements may have on care management. Here we describe the process by which COH expanded our HCT QM program to include IEC therapy. We share examples of how we developed our overall program structure and other key items such as how we addressed patient care management and accreditation to apprise other programs that wish to create and/or expand existing programs.     

AIDS: ethics and scientific investigation on human beings

The experimentation on human being of one or several therapeutic molecules discovered in laboratory is necessary and important because it helps to find new treatments or new diagnostic methods. But, it presents serious ethical problems. In this article we are analysing the example of the HIV infection. We are succinctly describing the research methods in laboratory for therapeutic molecules, first the experimentation on animals and then on human being in clinical trials. We will then try to show, with several examples, how during these last 25 years of HIV infection, the research of new molecules has not always respected the ethical rules set out in Helsinki declaration, "Code de la santé publique" or "Guide de bonnes pratiques cliniques-ICH" etc. We are discussing here the way to avoid these irregularities.     

The ins and outs of DNA fingerprinting the infectious fungi

DNA fingerprinting methods have evolved as major tools in fungal epidemiology. However, no single method has emerged as the method of choice, and some methods perform better than others at different levels of resolution. In this review, requirements for an effective DNA fingerprinting method are proposed and procedures are described for testing the efficacy of a method. In light of the proposed requirements, the most common methods now being used to DNA fingerprint the infectious fungi are described and assessed. These methods include restriction fragment length polymorphisms (RFLP), RFLP with hybridization probes, randomly amplified polymorphic DNA and other PCR-based methods, electrophoretic karyotyping, and sequencing-based methods. Procedures for computing similarity coefficients, generating phylogenetic trees, and testing the stability of clusters are then described. To facilitate the analysis of DNA fingerprinting data, computer-assisted methods are described. Finally, the problems inherent in the collection of test and control isolates are considered, and DNA fingerprinting studies of strain maintenance during persistent or recurrent infections, microevolution in infecting strains, and the origin of nosocomial infections are assessed in light of the preceding discussion of the ins and outs of DNA fingerprinting. The intent of this review is to generate an awareness of the need to verify the efficacy of each DNA fingerprinting method for the level of genetic relatedness necessary to answer the epidemiological question posed, to use quantitative methods to analyze DNA fingerprint data, to use computer-assisted DNA fingerprint analysis systems to analyze data, and to file data in a form that can be used in the future for retrospective and comparative studies.     

Update on influenza diagnostics: lessons from the novel H1N1 influenza A pandemic

The menu of diagnostic tools that can be utilized to establish a diagnosis of influenza is extensive and includes classic virology techniques as well as new and emerging methods. This review of how the various existing diagnostic methods have been utilized, first in the context of a rapidly evolving outbreak of novel influenza virus and then during the different subsequent phases and waves of the pandemic, demonstrates the unique roles, advantages, and limitations of each of these methods. Rapid antigen tests were used extensively throughout the pandemic. Recognition of the low negative predictive values of these tests is important. Private laboratories with preexisting expertise, infrastructure, and resources for rapid development, validation, and implementation of laboratory-developed assays played an unprecedented role in helping to meet the diagnostic demands during the pandemic. FDA-cleared assays remain an important element of the diagnostic armamentarium during a pandemic, and a process must be developed with the FDA to allow manufacturers to modify these assays for detection of novel strains in a timely fashion. The need and role for subtyping of influenza viruses and antiviral susceptibility testing will likely depend on qualitative (circulating subtypes and their resistance patterns) and quantitative (relative prevalence) characterization of influenza viruses circulating during future epidemics and pandemics.     

Biometrical genetics

Biometrical genetics is the science concerned with the inheritance of quantitative traits. In this review we discuss how the analytical methods of biometrical genetics are based upon simple Mendelian principles. We demonstrate how the phenotypic covariance between related individuals provides information on the relative importance of genetic and environmental factors influencing that trait, and how factors such as assortative mating, gene-environment correlation and genotype-environment interaction complicate such interpretations. Twin and adoption studies are discussed as well as their assumptions and limitations. Structural equation modeling (SEM) is introduced and we illustrate how this approach may be applied to genetic problems. In particular, we show how SEM can be used to address complicated issues such as analyzing the causes of correlation between traits or determining the direction of causation (DOC) between variables.     

Forecasting the future of HIV epidemics: the impact of antiretroviral therapies & imperfect vaccines

Mathematical models can be used as health policy tools and predictive tools. Here we review how mathematical models have been used both to predict the consequences of specific epidemic control strategies and to design epidemic control strategies. We review how models have been used to evaluate the potential impact on HIV epidemics of (i) combination antiretroviral therapies (ART) and (ii) imperfect vaccines. In particular, we discuss how models have been used to predict the potential effect of ART on incidence rates, and to predict the evolution of an epidemic of drug-resistant HIV. We also discuss, in detail, how mathematical models have been used to evaluate the potential impact of prophylactic, live-attenuated and therapeutic HIV vaccines. We show how HIV vaccine models can be used to evaluate the epidemic-level impact of vaccine efficacy, waning in vaccine-induced immunity, vaccination coverage level, and changes (increases or decreases) in risky behavior. We also discuss how mathematical models can be used to determine the levels of cross-immunity that vaccines will need to attain if they are to be used to control HIV epidemics in countries where more than one subtype is being transmitted.     

Predictive data mining in clinical medicine: current issues and guidelines

BACKGROUND: The widespread availability of new computational methods and tools for data analysis and predictive modeling requires medical informatics researchers and practitioners to systematically select the most appropriate strategy to cope with clinical prediction problems. In particular, the collection of methods known as 'data mining' offers methodological and technical solutions to deal with the analysis of medical data and construction of prediction models. A large variety of these methods requires general and simple guidelines that may help practitioners in the appropriate selection of data mining tools, construction and validation of predictive models, along with the dissemination of predictive models within clinical environments. PURPOSE: The goal of this review is to discuss the extent and role of the research area of predictive data mining and to propose a framework to cope with the problems of constructing, assessing and exploiting data mining models in clinical medicine. METHODS: We review the recent relevant work published in the area of predictive data mining in clinical medicine, highlighting critical issues and summarizing the approaches in a set of learned lessons. RESULTS: The paper provides a comprehensive review of the state of the art of predictive data mining in clinical medicine and gives guidelines to carry out data mining studies in this field. CONCLUSIONS: Predictive data mining is becoming an essential instrument for researchers and clinical practitioners in medicine. Understanding the main issues underlying these methods and the application of agreed and standardized procedures is mandatory for their deployment and the dissemination of results. Thanks to the integration of molecular and clinical data taking place within genomic medicine, the area has recently not only gained a fresh impulse but also a new set of complex problems it needs to address.     

The non-O157 shiga-toxigenic (verocytotoxigenic) Escherichia coli; under-rated pathogens

Following a brief review of the ecology of Escherichia coli in general, the role of Shiga-Toxigenic (Verocytotoxigenic) E. coli (STEC) as pathogens is addressed. While STEC belonging to the serogroup O157 have been extensively studied and shown to be involved in many cases and outbreaks of human disease, the importance of STEC belonging to other serogroups has not been recognized as much. This review addresses the problems associated with these pathogens, demonstrating that increasing the awareness of them is a major part of the problem. This review then demonstrates how widespread isolations especially from food animals and human disease have been, discussing in particular STEC belonging to serogroups O8, O26, O103, O111, O113 and O128. The animal host-specificity of these STEC is also reviewed. In conclusion some methods of improving isolation of these pathogens is addressed.     

Maps of the brain

We review recent developments in brain mapping and computational anatomy that have greatly expanded our ability to analyze brain structure and function. The enormous diversity of brain maps and imaging methods has spurred the development of population-based digital brain atlases. These atlases store information on how the brain varies across age and gender, across time, in health and disease, and in large human populations. We describe how brain atlases, and the computational tools that align new datasets with them, facilitate comparison of brain data across experiments, laboratories, and from different imaging devices. The major methods are presented for the construction of probabilistic atlases, which store information on anatomic and functional variability in a population. Algorithms are reviewed that create composite brain maps and atlases based on multiple subjects. We show that group patterns of cortical organization, asymmetry, and disease-specific trends can be resolved that may not be apparent in individual brain maps. Finally, we describe the creation of four-dimensional (4D) maps that store information on the dynamics of brain change in development and disease. Digital atlases that correlate these maps show considerable promise in identifying general patterns of structural and functional variation in human populations, and how these features depend on demographic, genetic, cognitive, and clinical parameters.     

Guidelines for Reporting and Using Prediction Tools for Genetic Variation Analysis

Computational prediction methods are widely used for the analysis of human genome sequence variants and their effects on gene/protein function, splice site aberration, pathogenicity, and disease risk. New methods are frequently developed. We believe that guidelines are essential for those writing articles about new prediction methods, as well as for those applying these tools in their research, so that the necessary details are reported. This will enable readers to gain the full picture of technical information, performance, and interpretation of results, and to facilitate comparisons of related methods. Here, we provide instructions on how to describe new methods, report datasets, and assess the performance of predictive tools. We also discuss what details of predictor implementation are essential for authors to understand. Similarly, these guidelines for the use of predictors provide instructions on what needs to be delineated in the text, as well as how researchers can avoid unwarranted conclusions. They are applicable to most prediction methods currently utilized. By applying these guidelines, authors will help reviewers, editors, and readers to more fully comprehend prediction methods and their use.     

Evidence-based medicine, medical decision analysis, and pathology

Recent advances in molecular pathology and other technologies such as proteomics present pathologists with the challenge of integrating the new information generated with high-throughput methods with current diagnostic models based mostly on histopathology and clinicopathologic correlations. Parallel developments in the field of medical informatics and bioinformatics provide the technical and mathematical methods to approach these problems in a rational manner. However, it remains unclear whether pathologists or other medical specialists will become primarily responsible for the development and maintenance of these multivariate and multidisciplinary diagnostic and prognostic models that are hoped to provide more accurate, individualized patient-based information. Evidence-based medicine (EBM) and medical decision analysis (MDA) are relatively new disciplines that use quantitative methods to assess the value of information, differentiate fact from myth, and integrate so-called best evidence into multivariate models for the assessment of prognosis, response to therapy, selection of laboratory tests, and other complex problems that influence individual patient care. We review from an epistemological viewpoint the current approach to information in pathology and describe some of the concepts developed by the practitioners of EBM and MDA.     

Shared decision-making – transferring research into practice: The Analytic Hierarchy Process (AHP)

ObjectiveTo illustrate how the Analytic Hierarchy Process (AHP) can be used to promote shared decision-making and enhance clinician–patient communication.MethodsTutorial review.ResultsThe AHP promotes shared decision-making by creating a framework that is used to define the decision, summarize the information available, prioritize information needs, elicit preferences and values, and foster meaningful communication among decision stakeholders.ConclusionsThe AHP and related multi-criteria methods have the potential for improving the quality of clinical decisions and overcoming current barriers to implementing shared decision-making in busy clinical settings. Further research is needed to determine the best way to implement these tools and to determine their effectiveness.Practice implicationsMany clinical decisions involve preference-based trade-offs between competing risks and benefits. The AHP is a well-developed method that provides a practical approach for improving patient–provider communication, clinical decision-making, and the quality of patient care in these situations.     

Microfabricated substrates as a tool to study cell mechanotransduction

Mechanical cell–substrate interactions affect many cellular functions such as spreading, migration, and even differentiation. These interactions can be studied by incorporating micro- and nanotechnology-related tools. The design of substrates based on these technologies offers new possibilities to probe the cellular responses to changes in their physical environment. The investigations of the mechanical interactions of cells and their surrounding matrix can be carried out in well-defined and near physiological conditions. In particular, this includes the transmission of forces as well as rigidity and topography sensing mechanisms. Here, we review techniques and tools based on nano- and micro-fabrication that have been developed to analyze the influence of the mechanical properties of the substrate on cell functions. We also discuss how microfabrication methods have improved our knowledge on cell adhesion and migration and how they could solve remaining problems in the field of mechanobiology.