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Optical diffraction tomography is an emerging label-free microscopic technique with its capability of label-free, quantitative, and rapid imaging of biological samples. In this work, we present the imaging and analysis of a living diatom Cylindrotheca sp. in seawater without using any pretreatment such as fluorescence staining. The 3D refractive index (RI) of a living diatom cell was measured, to which quantitative image analysis was perform to investigate subcellular parts of the diatom. Each part of the cell was well distinguished as RI values and distributions. From the analysis, RI values of frustules, protoplasm, vacuole, and chloroplast were estimated to be in the range of 1.

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Semiconductor single-walled carbon nanotubes (SWNTs) have unique characteristics owing to differences in the three-dimensional structure (chirality) expressed by the chiral index (n,m), and many studies on the redox characteristics of chirality have been reported. In this study, we investigated the relationship between the chirality of SWNTs and the oxidizing power of oxidants by measuring the near-infrared (NIR) absorption spectra of two double-stranded DNA-SWNT complexes with the addition of three oxidants with different oxidizing powers. A dispersion was prepared by mixing 0.5 mg of SWNT powder with 1 mg/mL of DNA solution. Different concentrations of hydrogen peroxide (H2O2), potassium hexachloroidylate (IV) (K2IrCl6), or potassium permanganate (KMnO4) were added to the dispersion to induce oxidation. Thereafter, a catechin solution was added to observe if the absorbance of the oxidized dispersion was restored by the reducing action of the catechin. We found that the difference in the oxidizing power had a significant effect on the detection sensitivity of the chiralities of the SWNTs. Furthermore, we revealed a detectable range of oxidants with different oxidizing powers for each chirality.

It has been reported that even if single-walled carbon nanotubes (SWNTs) are coated with the same polymer, the redox characteristics change of each chirality may differ. Particularly, the addition of hydrogen peroxide (H2O2) minimally affects the near-infrared (NIR) absorption spectra of the dsDNA-(6,5)-enriched SWNT complex (DNA-SWNT complex). Detecting the redox properties of (6,5) chirality using NIR absorption spectra has been one of the issues to be solved. We hypothesized that an oxidizing agent with high oxidizing power is required to detect the absorption spectra of (6,5) chirality. In this study, we used KMnO4, which contains atoms with a high oxidation number. A dispersion was prepared by mixing 0.5 mg of (6,5)-enriched SWNT powder with 1 mg/mL of DNA solution. After adding H2O2 or KMnO4 to this dispersion and oxidizing it, catechin solutions were added to reduce the dispersion. The absorption peak of the DNA-SWNT complex decreased by 23.9% following the addition of KMnO4 (final concentration: 0.5 µM) and recovered 30.7% following the addition of the catechin solution. We revealed that the changes in the absorption spectra change of (6,5) chirality, which could not be detected by H2O2, can be detected by using KMnO4. We also varied the concentration of KMnO4 and verified whether the adsorption of KMnO4 can be modeled as a Langmuir adsorption isotherm.

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DNA-wrapped single-walled carbon nanotubes (DNA-SWCNTs) in stable dispersion are expected to be used as biosensors in the future, because they have the property of absorption of light in the near infrared (NIR) region, which is safe for the human body. However, this practical application requires the understanding of the DNA-SWCNTs’ detailed response characteristics. The purpose of this study is to predict, in detail, the response characteristics of the absorption spectra that result when the antioxidant catechin is added to oxidized DNA-SWCNTs, from a small amount of experimental data. Therefore, in the present study, we predicted the characteristics of the absorption spectra of DNA-SWCNTs using the Bayesian regularization backpropagation neural network (BRBPNN) model. The BRBPNN model was trained with the catechin concentration and initial absorption peaks as inputs and the absorption spectra after catechin addition as outputs. The accuracy of the predicted absorption peaks and wavelengths after the addition of catechin, as predicted by the BRBPNN model, was within 1% of the error of the experimental data. By inputting the catechin concentrations under hundreds of conditions into this BRBPNN model, we were able to obtain detailed prediction curves for the absorption peaks. This method has the potential to help to reduce the experimental costs and improve the efficiency of investigating the properties of high-cost materials such as SWCNTs.