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position： home > Academic Frontier > Bio-nanomedicine

Do the opposite and make a Nature!

source：beike new material Views：3678time：2021-06-22 QQ Academic Group: 1092348845

In the detection of biological tissue samples, a powerful weapon, fluorescence microscope, has been developed to image microscopic levels invisible to the naked eye and some pathological changes in the depths of the tissue, so that they can be transformed into images or signals visible to the naked eye for scientists to analyze. Although the fluorescence microscope works well in many scientific research and practical activities, it also has its inherent defects, such as the need for staining, prone to false positive and so on. Therefore, people also need to develop a variety of other technologies to complement each other in order to improve the accuracy of biological tissue sample detection. Stimulated Raman scattering ((SRS)) microscopic imaging technology is a new kind of technology which is comparable to fluorescence microscopy. It is a kind of optical imaging method which can produce high-resolution biological tissue images. The source of the contrast of different regions in the images obtained by SRS technology is the difference of molecular vibration in different positions, which makes tissue imaging without staining with fluorescent dyes. Even so, the lowest molecular concentration that can be detected by this technique is still higher than that of fluorescence microscopy dyed with fluorescent dyes, thus limiting its scope of application.

On the contrary, it has been challenging to suppress noise and improve sensitivity to find ways to fundamentally improve the detection sensitivity of this technique. Recently, the team of Professor Warwick P. Bowen of the University of Queensland in Australia described a method to improve sensitivity by suppressing noise in SRS signals through quantum enhancement. This work was published in Nature under the title Quantum-enhanced nonlinear microscopy , and was introduced by Professor Eric O. Potma of the University of California in Nature in a special report entitled Squeezed light improves sensitivity of microscopy technique .

What is the principle of the SRS method? The basic principle of SRS method is Raman effect. The so-called Raman effect, also known as Raman scattering, refers to the phenomenon that the frequency of light waves changes after they are scattered. In SRS technology, two types of photons are used, one is called pump photon, its frequency is ω 1, the pump photon interacts with the molecule to excite its characteristic vibration, and the other is called Stokes photon, which has a lower frequency ω 2, which can change the frequency after being scattered by the characteristic vibration of the molecule. The frequency difference between the two represents the different vibration modes of the molecules. Since the frequency parameters of incident photons are known, the vibration mode of the detected position can be known only by detecting the frequency information of Stokes photons in the output optical signal. The Stokes photon frequency information of different parts of the tested sample can be collected and the image can be obtained.

Figure 1. Traditional SRS technology (pump light is not shown) [what are the current challenges of SRS technology? At present, there are three main problems in SRS technology: first, the signal of Stokes photons in outgoing light is too weak and the signal-to-noise ratio is too low. As mentioned earlier, in SRS technology, two types of light fields need to be used, including the pump field with frequency ω 1 and the Stokes field with frequency ω 2. Compared with the traditional linear Raman effect (only one type of incident light is needed), the noise level of the outgoing light is higher, and the signal is relatively more hidden in the noise. Second, because the signal-to-noise ratio is too low, the detection and receiving device is more complex, and it takes a long time to analyze the integrated signal; third, any fluctuation (fluctuation) of the background laser intensity will make it more difficult to detect the SRS contribution. How to overcome these three difficulties is a big challenge in the field of SRS.

Figure 2. Traditional SRS technology has low signal-to-noise ratio [quantum enhanced nonlinear technology] the conventional way to improve the sensitivity and resolution of SRS technology is to increase the intensity of incident light and enhance the signal, so that it is easier to be detected. However, because the detected biological sample itself is fragile, in order to avoid being damaged by light, the intensity of the incident laser can not be improved indefinitely. As a result, the effect of traditional methods to enhance the sensitivity of SRS technology is limited. The Warwick P. Bowen team took a completely different approach to improving the sensitivity of SRS technology. This method makes the incident Stokes light in a squeezed quantum state, when the Stokes photons are no longer completely independent, which means that the fluctuation of the number of photons in the beam no longer follows the statistical distribution observed in the classical laser beam. Different from the traditional idea of improving signal strength through various improvements, the noise signal can be greatly reduced by using quantum enhanced nonlinear technology. by reducing the background noise below the shot noise limit, the researchers increased the signal-to-noise ratio of SRS imaging by 35% and reduced the minimum detectable molecular concentration by 14%. This improvement is realized without increasing the intensity of the laser beam, thus maintaining the integrity of the biological sample. It is worth noting that the accuracy of the data obtained by this method can not exceed that of the existing traditional SRS technology, but this method still has a lot of room for improvement. Through the use of this technology, it can perfectly overcome the three challenges of SRS technology, represent the direction of future technology development, and make SRS technology become better and better.

Figure 3. Quantum enhanced nonlinear technology can reduce noise.

Figure 4. Schematic diagram of quantum enhanced nonlinear technology.

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