One of the perks of being an Associate Editor for ACS Sensors is the chance to talk to the community through editorials. Often these highlight current trends or future opportunities for the field, but sometimes they provide an editor with a chance to grumble (many apologies, Justin). This month, I’d like to spend a couple of minutes talking about the use of the terms “sensitivity” and “limit of detection” in sensor science. I do not think it would be a great surprise to find out that almost all articles published in our journal contain both figures of merit, often on numerous occasions. We include and attempt to quantify them because they are important and often provide us with valuable information about our sensor or analytical method. What may be more surprising is that, despite having very different definitions, they are regularly used in an interchangeable fashion, with little regard for their true meanings. As an Associate Editor, I can confirm that this happens far more often than you might think! “So what?” you might say, “does it make that much difference?” I would argue that it often does. Not least because they are different quantities, but also because there are multiple definitions for each figure of merit and differences of opinion with regard to which definitions are correct. Since my aim is not to provide an in-depth analysis, let me make some simple definitions that are widely accepted from a chemical standpoint. But before I begin, please note that our discussion of sensitivity should not be confused with the use of the term when characterizing diagnostic tests, in which sensitivity refers to the probability that a test will yield a positive result if the tested individual does have the disease. Most analytical chemists would agree that the sensitivity of an analytical method or instrument in some way quantifies its ability to discriminate between small differences in the concentration (or mass) of a target analyte (Note: This quantity will have units of “signal units per unit concentration” or “signal units per unit mass”. For the purposes of my discussion, I will consider only concentrations going forward). The simplest definition of “calibration sensitivity”, and the one recognized by IUPAC, is the slope of the calibration curve at the concentration of interest (m in my sketch). (1,2) Since the calibration curve will only be linear over some range of concentrations, calibration sensitivity must always be accompanied by a statement of this range; it is meaningless if the range is omitted. Such a figure of merit is simple to calculate, but does ignore measurement precision. Accordingly, Mendel and Stiehler introduced the concept of “analytical sensitivity”, which accounts for both the gradient of the calibration curve and analytical precision, and is defined as the calibration sensitivity divided by the standard deviation of the analytical signal measurement (s_s). (3) The limit of detection is in some ways easier to define, but in others a more complex beast. As a starting point, the limit of detection can be broadly defined as the smallest concentration that can be detected with a defined level of confidence. (4) This is of course rather vague, but tells us that random experimental errors are unavoidable and that the limit of detection will depend on the ratio of the signal to the magnitude of statistical fluctuations in the blank signal. As shown in the sketch, the limit of detection (c_m) should be quantified by determining the minimum distinguishable analytical signal through multiple (typically 20–30) blank measurements and substitution of this value into the equation describing the calibration curve. Although there has been much discussion regarding the choice of the multiple, k, a value of 3 is widely accepted by most (including IUPAC and the ACS) as being ideal. (4−6) It should also be remembered that other related figures of merit, such as limit of blank (LoB) and limit of quantitation (LoQ), can be used to assess the minimum concentrations that can be reliably measured using an analytical procedure under given conditions. (7) What should be clear from this fleeting analysis is that, as defined, both figures of merit are quite different in their meaning and often reported in an inconsistent manner. This can lead to uncertainty when sensitivity or limit of detection values are used to compare different analytical procedures, sensors, and instruments. Put simply, any declaration of analytical sensitivity must be accompanied by a statement of the concentration (or concentration range) at which the sensitivity has been calculated, and quoted limits of detection must explicitly state the multiple, k. In addition to this being the correct thing to do, such an approach is the only way to ensure that different assays and methods can be compared in a consistent, fair, and meaningful manner. On the flipside, perhaps I should not be overly surprised about this lack of consistency. Despite the fact that our journal is part of a chemistry publishing house, our authors and contributors come from varied backgrounds, ranging from molecular biology to civil engineering to geology. Accordingly, the language and reporting of scientific ideas will naturally vary between individuals. That said, a clear definition of what is meant by terms such a sensitivity is always sensible and prevents confusion. Finally, while the limit of detection and analytical sensitivity are useful figures of merit, they are not the be-all and end-all when assessing sensor performance. In this regard, it should not be forgotten that clinical decision levels for a range of biomarkers and species, such as glucose, albumin, creatinine, and cholesterol, are of 10 orders of magnitude higher than the limit of detection of most diagnostic tests. In such a situation, the limit of detection is a rather unimportant figure of merit. Indeed, while advances and progress in sensor and assay technologies are most commonly measured by shifts to lower and lower limits of detection, other factors, such as cost, time-to-result, simplicity, and shelf lifetime will be far more important factors in determining whether a test is fit for purpose. So, my request is simple. When using sensitivity and limit of detection to characterize a sensor or analytical method, think about what these values are telling you and report them in a consistent and complete manner. This allows for meaningful comparisons between existing sensors and tests and makes an editor’s job much, much easier. This article references 7 other publications. This article has not yet been cited by other publications. This article references 7 other publications.

中文翻译：

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我对敏感性很敏感

成为ACS Sensors副主编的好处之一是通过社论与社区交流的机会。这些通常突出了该领域当前的趋势或未来的机会，但有时它们为编辑提供了抱怨的机会（许多道歉，贾斯汀）。本月，我想花几分钟时间讨论传感器科学中术语“灵敏度”和“检测限”的使用。我不认为发现我们期刊上发表的几乎所有文章都包含这两种品质因数，而且经常出现在很多场合，这并不令人惊讶。我们包括并尝试量化它们，因为它们很重要，并且经常为我们提供有关我们的传感器或分析方法的有价值的信息。可能更令人惊讶的是，尽管定义非常不同，但它们经常以可互换的方式使用，很少考虑它们的真正含义。作为副主编，我可以确认这种情况发生的频率比您想象的要多得多！“那又怎样？” 你可能会说，“这有那么大的不同吗？” 我会争辩说它经常这样做。不仅因为它们是不同的量，还因为每个品质因数有多种定义，并且对于哪些定义是正确的存在意见分歧。由于我的目的不是提供深入的分析，所以让我做一些从化学角度广泛接受的简单定义。但在我开始之前，请注意，我们对敏感性的讨论不应与表征诊断测试时使用的术语混淆，其中敏感性是指如果被测个体确实患有疾病，测试将产生阳性结果的概率. 大多数分析化学家都同意，分析方法或仪器的灵敏度以某种方式量化了其区分目标分析物浓度（或质量）的微小差异的能力（注意：该数量的单位为“每单位的信号单位浓度”或“每单位质量的信号单位”。为了讨论的目的，我将只考虑未来的浓度）。“校准灵敏度”的最简单定义，也是 IUPAC 认可的定义，是目标浓度下校准曲线的斜率（m在我的草图中）。(1,2) 由于校准曲线仅在某些浓度范围内呈线性，校准灵敏度必须始终附有该范围的说明；如果省略范围是没有意义的。这样的品质因数计算起来很简单，但确实忽略了测量精度。因此，Mendel 和 Stiehler 引入了“分析灵敏度”的概念，它既考虑了校准曲线的梯度，也考虑了分析精度，定义为校准灵敏度除以分析信号测量的标准偏差 ( s _s )。(3)检测极限在某些方面更容易定义，但在其他方面则更为复杂。作为起点，检测限可以广义地定义为在确定的置信水平下可以检测到的最小浓度。(4) 这当然相当模糊，但告诉我们随机实验误差是不可避免的，检测限将取决于信号与空白信号中统计波动幅度的比率。如图所示，检测限（_cm) 应通过多次（通常为 20-30 次）空白测量确定最小可区分分析信号并将该值代入描述校准曲线的方程来量化。尽管关于倍数的选择已经有很多讨论，k，值 3 被大多数人（包括 IUPAC 和 ACS）广泛接受为理想值。(4-6) 还应记住，其他相关的品质因数，例如空白限 (LoB) 和定量限 (LoQ)，可用于评估可以使用分析程序可靠测量的最低浓度在给定条件下。(7) 从这个稍纵即逝的分析中应该清楚的是，根据定义，这两个品质因数在其含义上完全不同，并且经常以不一致的方式报告。当使用灵敏度或检测限值来比较不同的分析程序、传感器和仪器时，这可能会导致不确定性。简单地说，ķ. 除了这是正确的做法之外，这种方法是确保可以以一致、公平和有意义的方式比较不同测定和方法的唯一方法。另一方面，也许我不应该对这种缺乏一致性感到过分惊讶。尽管我们的期刊是化学出版社的一部分，但我们的作者和贡献者来自不同的背景，从分子生物学到土木工程再到地质学。因此，科学思想的语言和报道自然会因人而异。也就是说，对这种敏感性术语的含义进行明确定义始终是明智的，并且可以防止混淆。最后，虽然检测限和分析灵敏度是有用的品质因数，在评估传感器性能时，它们并不是万能的。在这方面，不应忘记一系列生物标志物和物种（如葡萄糖、白蛋白、肌酐和胆固醇）的临床决策水平比大多数诊断测试的检测限高 10 个数量级。在这种情况下，检测限是一个相当不重要的品质因数。事实上，虽然传感器和分析技术的进步和进步最常见的衡量标准是检测限越来越低，但成本、结果时间、简单性和保质期等其他因素将是更重要的因素。确定测试是否适合目的。所以，我的要求很简单。当使用灵敏度和检测限来表征传感器或分析方法时，想想这些价值观告诉你什么，并以一致和完整的方式报告它们。这允许在现有传感器和测试之间进行有意义的比较，并使编辑的工作变得更加轻松。本文引用了其他 7 个出版物。这篇文章尚未被其他出版物引用。本文引用了其他 7 个出版物。