Improving Chronic Wound healing with Intelligent Dressings

150年前，科赫设计了观察标本中细菌的方法。直到今天，这些方法仍然没有改变。鉴定临床样本中的细菌是非常劳动密集型的，需要很长的时间--最多需要十天。在收到临床标本的任何信息方面的这种时间延迟意味着医生必须最好地猜测是哪种细菌导致了感染。出于这个原因，抗生素治疗感染的处方往往是猜测的，可能是错误的。不正确的处方导致了抵抗传统疗法的细菌的出现。这现在是一个主要的世界卫生问题。我们的研究计划在临床现场快速评估细菌感染，并在未来通过类似于糖尿病监测的家庭测试来进行评估。了解伤口内存在哪些细菌和多少细菌将使医生能够迅速开出有效的抗生素，并根据每个人的需要进行最佳治疗。我们的研究计划将开发两个新的测试系统来测量腿部伤口中的细菌数量和类型。作为一个模型，我们将研究慢性皮肤伤口中的细菌，原因有两个。首先，这些伤口是一个巨大的临床问题，在英国，每100名60岁以上的人中就有3人受到影响，国民医疗服务每年要花费10亿美元来治疗。其次，所获得的信息将直接为每个患者提供最佳治疗方案，避免不必要的抗生素使用。将研究两个系统，一个留在家里，随着时间的推移留在伤口上，另一个供医生在临床上立即报告。这种智能敷料的工作原理是通过使用生物蛋白质来创建数字仪器信号来测量细菌指示器。这种敷料将首先在实验室进行测试，然后在腿部伤口无法愈合的患者身上进行测试。智能敷料将有助于减少抗生素的使用，指示伤口何时需要治疗。智能实时系统还有助于研究新一代抗生素的基本特性，并探索导致细菌对这些治疗产生抗药性的机制。

One hundred and fifty years ago, Koch designed methods to look at bacteria in specimens. The methods remain unchanged to this day. Identifying bacteria in clinical samples is very labour intensive and takes a long time - up to ten days. This time delay in receiving any information on a clinical specimen means that the doctor has to best guess which bacteria are causing the infection. For this reason, the prescription of antibiotics to treat the infection is often by guess work and may be wrong.Incorrect prescribing has contributed to the emergence of bacteria which resist conventional therapy. This is now a major world health problem. Our research plans to make assessment of bacterial infections rapid, on site in the clinic and, in the future by home-testing similar to diabetes monitoring. Knowing which and how many bacteria are present within a wound will allow the doctor to prescribe effective antibiotics quickly and to each person's needs for the best treatment.Our research programme will develop two new test systems to measure the number and type of bacteria in a leg wound. As a model, we will study bacteria in chronic skin wounds for two reasons. Firstly, these wounds represent a huge clinical problem, affecting three in every hundred people over 60 years old in the UK and costing 1 billion for the National Health Service to treat every year. Secondly, the information obtained will directly inform the best treatment for each patient, avoiding unnecessary antibiotic use.Two systems will be researched, one to be left on the wound over time at home and the other for the doctor to use for an immediate report in the clinic. The intelligent dressing materials will work by measuring bacterial indicators by using biological proteins to create a digital instrument signal. The dressings will be tested first in the laboratory and then with patients suffering from leg wounds that are not healing.The intelligent dressings will help reduce antibiotic use, indicating when wounds need treatment. The intelligent real-time systems also help to research the properties essential in new generations of antibiotics and explore the mechanisms that lead to bacteria becoming resistant to these treatments.