The short-wave infrared region (SWIR) is promising for deep-tissue visualization and temperature sensing due to higher penetration depth and reduced scattering of radiation. However, the strong quenching of luminescence in biological media and low thermal sensitivity of nanothermometers in this region are major drawbacks that limit their practical application. Nanoparticles doped with rare-earth ions are widely used as thermal sensors operating in the SWIR region through the luminescence intensity ratio (LIR) approach. In this study, the effect of the shell on the sensitivity of temperature determination using NaGdF₄ nanoparticles doped with rare-earth ions (REI) Yb³⁺, Ho³⁺, and Er³⁺ coated with an inert NaYF₄ shell was investigated. We found that coating the nanoparticles with a shell significantly increases the intensity of luminescence in the SWIR range, prevents water from quenching luminescence, and decreases the temperature of laser-induced heating. Thermometry in the SWIR spectral region was demonstrated using synthesized nanoparticles in dry powder and in water. The core-shell nanoparticles obtained had intense luminescence and made it possible to determine temperatures in the range of 20–40 °C. The relative thermal sensitivity of core-shell NPs was 0.68% °C⁻¹ in water and 4.2% °C⁻¹ in dry powder.

The determination of pH in live cells and tissues is of high importance in physiology and cell biology. In this report, we outline the process of the creation of SypHerExtra, a genetically encoded fluorescent sensor that is capable of measuring extracellular media pH in a mildly alkaline range. SypHerExtra is a protein created by fusing the previously described pH sensor SypHer3s with the neurexin transmembrane domain that targets its expression to the cytoplasmic membrane. We showed that with excitation at 445 nm, the fluorescence lifetime of both SypHer3s and SypHerExtra strongly depend on pH. Using FLIM microscopy in live eukaryotic cells, we demonstrated that SypHerExtra can be successfully used to determine extracellular pH, while SypHer3s can be applied to measure intracellular pH. Thus, these two sensors are suitable for quantitative measurements using the FLIM method, to determine intracellular and extracellular pH in a range from pH 7.5 to 9.5 in different biological systems.

Emission spectral properties and quantum efficiency of upconversion particles NaYF ₄ , SrF ₂ , LaF ₃ , BaF ₂ и CaF ₂ , doped with rare earth ions pair Yb ³⁺ –Er ³⁺ were studied using continuous wave (CW) and pulsed periodic excitation modes in the near infrared (NIR) spectral range. Analysis of the obtained results showed that the intensity ratio of upconversion luminescence in green and red spectral ranges depends on excitation pulse duration. Thus, by changing the pulse duration the spectral properties of upconversion luminescence can be controlled. Crystals with higher phonon energy are more sensitive to the change of pumping mode. Interpretation of results was performed on the rate equation model basis. Using numerical methods for all energy levels involved in the upconversion process the population and depopulation dynamics were obtained with respect to the duration of the excitation pulses. It was shown that about 30 ms was required for the complete population of ⁴ F _9/2 state, from which the luminescence in the red spectral range occurs. When the pulse duration was less than 30 ms, the ⁴ F _9/2 population did not reach a steady state and the intensity of the luminescence in the red part of the spectrum was reduced. The theoretical dependence of the upconversion luminescence intensity in the green and red ranges of the excitation pulse duration for NaYF ₄ :Yb _0.2 –Er _0.02 composition was obtained and demonstrates good agreement with the experimental results.

The great interest in upconversion nanoparticles exists due to their high efficiency under multiphoton excitation. However, when these particles are used in scanning microscopy, the upconversion luminescence causes a streaking effect due to the long lifetime. This article describes a method of upconversion microparticle luminescence lifetime determination with help of modified Lucy–Richardson deconvolution of laser scanning microscope (LSM) image obtained under near-IR excitation using nondescanned detectors. Determination of the upconversion luminescence intensity and the decay time of separate microparticles was done by intensity profile along the image fast scan axis approximation. We studied upconversion submicroparticles based on fluoride hosts doped with $Yb3+-Er3+$ and $Yb3+-Tm3+$ rare earth ion pairs, and the characteristic decay times were 0.1 to 1.5 ms. We also compared the results of LSM measurements with the photon counting method results; the spread of values was about 13% and was associated with the approximation error. Data obtained from live cells showed the possibility of distinguishing the position of upconversion submicroparticles inside and outside the cells by the difference of their lifetime. The proposed technique allows using the upconversion microparticles without shells as probes for the presence of $OH−$ ions and $CO2$ molecules.

The neurosurgery of intracranial tumors is often complicated by the difficulty of distinguishing tumor center, infiltration area, and normal tissue. The current standard for intraoperative navigation is fluorescent diagnostics with a fluorescent agent. This approach can be further enhanced by measuring the Raman spectrum of the tissue, which would provide additional information on its composition even in the absence of fluorescence. However, for the Raman spectra to be immediately helpful for a neurosurgeon, they must be additionally processed. In this work, we analyzed the Raman spectra of human brain glioblastoma multiforme tissue samples obtained during the surgery and investigated several approaches to dimensionality reduction and data classificatin to distinguish different types of tissues. In our study two approaches to Raman spectra dimensionality reduction were approbated and as a result we formulated new technique combining both of them: feature filtering based on the selection of those shifts which correspond to the biochemical components providing the statistically significant differences between groups of examined tissues (center of glioblastoma multiforme, tissues from infiltration area and normally appeared white matter) and principal component analysis. We applied the support vector machine to classify tissues after dimensionality reduction of registered Raman spectra. The accuracy of the classification of malignant tissues (tumor edge and center) and normal ones using the principal component analysis alone was 83% with sensitivity of 96% and specificity of 44%. With a combined technique of dimensionality reduction we obtained 83% accuracy with 77% sensitivity and 92% specificity of tumor tissues classification.