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Protein detection and quantification is a routinely performed procedure in research laboratories, predominantly executed either by spectroscopy-based measurements, such as NanoDrop, or by colorimetric assays. The detection limits of such assays, however, are limited to μM concentrations. To establish an approach that achieves general protein detection at an enhanced sensitivity and without necessitating the requirement for signal amplification steps or a multicomponent detection system, here, we established a chemiluminescence-based protein detection assay. Our assay specifically targeted primary amines in proteins, which permitted characterization of any protein sample and, moreover, its latent nature eliminated the requirement for washing steps providing a simple route to implementation. Additionally, the use of a chemiluminescence-based readout ensured that the assay could be operated in an excitation source-free manner, which did not only permit an enhanced sensitivity due to a reduced background signal but also allowed for the use of a very simple optical setup comprising only an objective and a detection element. Using this assay, we demonstrated quantitative protein detection over a concentration range of five orders of magnitude and down to a high sensitivity of 10pgmL1, corresponding to pM concentrations. The capability of the platform presented here to achieve a high detection sensitivity without the requirement for a multistep operation or a multicomponent optical system sets the basis for a simple yet universal and sensitive protein detection strategy.  相似文献   

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The paper describes the phenomena associated with the reflection of a sharply defined beam of hydrogen atoms from a crystal of LiF. Of primary interest is the fact that the atoms show interference effects in agreement with the wave mechanics theory and plane grating diffraction patterns are photographed. Evidence of the thermal agitation of the surface ions is obtained from the diffuse reflection with surrounds the specular beam.The Schrödinger wave equation for the motion of a free particle of mass m is
2ψ ? 4πmih?t = 0 (I)
. The solution of this equation corresponding to the kinetic energy mv22 is
ψ = Ae2πi(vt?σxx?σyy?σxz), (2)
where
v  mv22and σ mvh
. The motion of such a particle should have the characteristics of a plane wave of frequency ν and wave-length λ = 1σ. The experiments of various investigators1 have shown the validity of the wave theory of the motion of the free electron and have given values of the wave-length in agreement with the theory.The free motion of atoms, ions and molecules should likewise have wave characteristics. In the case of the hydrogen atom, as the simplest example, the complete wave equation may be written in the form
Im2 x,y,zψ + Iμ2η,μζψ ?2μ?ψmh2η2 + μ2 + ζ2
? 4πih?t = 0, (3)
where x, y, z, are the coördinates of the center of mass of the atom and ξ, η, ζ the coördinates of the electron with respect to the center of mass. If m? and m+ are the masses of electron and proton, m and μ have the significance
m = m? + m+and Iμ = Im? + Im+
. Equation (3) is solved by
ψ = U1(x,y,z) U2(η, ν ζ) ?2πiEth
, where E may have a continuous set of values and represents the total energy. U1 and U2 must satisfy the equations
12U1 + 2mβU1h2 = 0, (4)
and
22U2 + 2μh2 (α ? μ?mη2 + ν2 + ζ2)U2 = 0 (5)
, where
α + β + E
.  相似文献   

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This paper presents an approach to measuring business sentiment based on textual data. Business sentiment has been measured by traditional surveys, which are costly and time-consuming to conduct. To address the issues, we take advantage of daily newspaper articles and adopt a self-attention-based model to define a business sentiment index, named S-APIR, where outlier detection models are investigated to properly handle various genres of news articles. Moreover, we propose a simple approach to temporally analyzing how much any given event contributed to the predicted business sentiment index. To demonstrate the validity of the proposed approach, an extensive analysis is carried out on 12 years’ worth of newspaper articles. The analysis shows that the S-APIR index is strongly and positively correlated with established survey-based index (up to correlation coefficient r=0.937) and that the outlier detection is effective especially for a general newspaper. Also, S-APIR is compared with a variety of economic indices, revealing the properties of S-APIR that it reflects the trend of the macroeconomy as well as the economic outlook and sentiment of economic agents. Moreover, to illustrate how S-APIR could benefit economists and policymakers, several events are analyzed with respect to their impacts on business sentiment over time.  相似文献   

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