Haptics in medicine and clinical skill acquisition

THE clinical skills of medical professionals rely strongly on the sense of touch, combined with anatomical and diagnostic knowledge. Haptic exploratory procedures allow the expert to detect anomalies via gross and fine palpation, squeezing, and contour following. Haptic feedback is also key to medical interventions, for example when an anaesthetist inserts an epidural needle, a surgeon makes an incision, a dental surgeon drills into a carious lesion, or a veterinarian sutures a wound. Yet, current trends in medical technology and training methods involve less haptic feedback to clinicians and trainees. For example, minimally invasive surgery removes the direct contact between the patient and clinician that gives rise to natural haptic feedback, and furthermore introduces scaling and rotational transforms that confuse the relationship between movements of the hand and the surgical site. Similarly, it is thought that computer-based medical simulation and training systems require high-resolution and realistic haptic feedback to the trainee for significant training transfer to occur. The science and technology of haptics thus has great potential to affect the performance of medical procedures and learning of clinical skills. This special section is about understanding

Good practice in reviewing and publishing studies on herbal medicine, with special emphasis on traditional Chinese medicine and Chinese materia medica

Ethnopharmacological relevance: Studies on traditional Chinese medicine (TCM), like those of other systems of traditional medicine (TM), are very variable in their quality, content and focus, resulting in issues around their acceptability to the global scientific community. In an attempt to address these issues, an European Union funded FP7 consortium, composed of both Chinese and European scientists and named “Good practice in traditional Chinese medicine” (GP-TCM), has devised a series of guidelines and technical notes to facilitate good practice in collecting, assessing and publishing TCM literature as well as highlighting the scope of information that should be in future publications on TMs. This paper summarises these guidelines, together with what has been learned through GP-TCM collaborations, focusing on some common problems and proposing solutions. The recommendations also provide a template for the evaluation of other types of traditional medicine such as Ayurveda, Kampo and Unani. Materials and methods: GP-TCM provided a means by which experts in different areas relating to TCM were able to collaborate in forming a literature review good practice panel which operated through e-mail exchanges, teleconferences and focused discussions at annual meetings. The panel involved coordinators and representatives of each GP-TCM work package (WP) with the latter managing the testing and refining of such guidelines within the context of their respective WPs and providing feedback. Results: A Good Practice Handbook for Scientific Publications on TCM was drafted during the three years of the consortium, showing the value of such networks. A “deliverable – central questions – labour division” model had been established to guide the literature evaluation studies of each WP. The model investigated various scoring systems and their ability to provide consistent and reliable semi-quantitative assessments of the literature, notably in respect of the botanical ingredients involved and the scientific quality of the work described. This resulted in the compilation of (i) a robust scoring system and (ii) a set of minimum standards for publishing in the herbal medicines field, based on an analysis of the main problems identified in published TCM literature.

Modelling disease spread and control in networks: implications for plant sciences

Networks are ubiquitous in natural, technological and social systems. They are of increasing relevance for improved understanding and control of infectious diseases of plants, animals and humans, given the interconnectedness of today's world. Recent modelling work on disease development in complex networks shows: the relative rapidity of pathogen spread in scale-free compared with random networks, unless there is high local clustering; the theoretical absence of an epidemic threshold in scale-free networks of infinite size, which implies that diseases with low infection rates can spread in them, but the emergence of a threshold when realistic features are added to networks (e.g. finite size, household structure or deactivation of links); and the influence on epidemic dynamics of asymmetrical interactions. Models suggest that control of pathogens spreading in scale-free networks should focus on highly connected individuals rather than on mass random immunization. A growing number of empirical applications of network theory in human medicine and animal disease ecology confirm the potential of the approach, and suggest that network thinking could also benefit plant epidemiology and forest pathology, particularly in human-modified pathosystems linked by commercial transport of plant and disease propagules. Potential consequences for the study and management of plant and tree diseases are discussed.