Rapid and accurate identification of stem cell differentiation stages via SERS and convolutional neural networks.

Monitoring the transition of cell states during induced pluripotent stem cell (iPSC) differentiation is crucial for clinical medicine and basic research. However, both identification category and prediction accuracy need further improvement. Here, we propose a method combining surface-enhanced Raman spectroscopy (SERS) with convolutional neural networks (CNN) to precisely identify and distinguish cell states during stem cell differentiation. First, mitochondria-targeted probes were synthesized by combining AuNRs and mitochondrial localization signal (MLS) peptides to obtain effective and stable SERS spectra signals at various stages of cell differentiation. Then, the SERS spectra served as input datasets, and their distinctive features were learned and distinguished by CNN. As a result, rapid and accurate identification of six different cell states, including the embryoid body (EB) stage, was successfully achieved throughout the stem cell differentiation process with an impressive prediction accuracy of 98.5%. Furthermore, the impact of different spectral feature peaks on the identification results was investigated, which provides a valuable reference for selecting appropriate spectral bands to identify cell states. This is also beneficial for shortening the spectral acquisition region to enhance spectral acquisition speed. These results suggest the potential for SERS-CNN models in quality monitoring of stem cells, advancing the practical applications of stem cells.

SERS-based long-term mitochondrial pH monitoring during differentiation of human induced pluripotent stem cells to neural progenitor cells.

As one of the important organelles in the process of cell differentiation, mitochondria regulate the whole process of differentiation by participating in energy supply and information transmission. Mitochondrial pH value is a key indicator of mitochondrial function. Therefore, real-time monitoring of mitochondrial pH value during cell differentiation is of great significance for understanding cell biochemical processes and exploring differentiation mechanisms. In this study, Surface-enhanced Raman scattering (SERS) technology was used to achieve the real-time monitoring of mitochondrial pH during induced pluripotent stem cells (iPSCs) differentiation into neural progenitor cells (NPCs). The results showed that the variation trend of mitochondrial pH in normal and abnormal differentiated batches was different. The mitochondrial pH value of normal differentiated cells continued to decline from iPSCs to embryoid bodies (EB) day 4, and continued to rise from EB day 4 to the NPCs stage, and the mitochondrial microenvironment of iPSCs to NPCs differentiation became acidic. In contrast, the mitochondrial pH value of abnormally differentiated cells declined continuously during differentiation. This study improves the information on acid-base balance during cell differentiation and may provide a basis for further understanding of the changes and regulatory mechanisms of mitochondrial metabolism during cell differentiation. This also helps to improve more accurate and useful differentiation protocols based on the microenvironment within the mitochondria, improving the efficiency of cell differentiation.

DHM/SERS reveals cellular morphology and molecular changes during iPSCs-derived activation of astrocytes.

The activation of astrocytes derived from induced pluripotent stem cells (iPSCs) is of great significance in neuroscience research, and it is crucial to obtain both cellular morphology and biomolecular information non-destructively in situ, which is still complicated by the traditional optical microscopy and biochemical methods such as immunofluorescence and western blot. In this study, we combined digital holographic microscopy (DHM) and surface-enhanced Raman scattering (SERS) to investigate the activation characteristics of iPSCs-derived astrocytes. It was found that the projected area of activated astrocytes decreased by 67%, while the cell dry mass increased by 23%, and the cells changed from a flat polygonal shape to an elongated star-shaped morphology. SERS analysis further revealed an increase in the intensities of protein spectral peaks (phenylalanine 1001 cm-1, proline 1043 cm-1, etc.) and lipid-related peaks (phosphatidylserine 524 cm-1, triglycerides 1264 cm-1, etc.) decreased in intensity. Principal component analysis-linear discriminant analysis (PCA-LDA) modeling based on spectral data distinguished resting and reactive astrocytes with a high accuracy of 96.5%. The increase in dry mass correlated with the increase in protein content, while the decrease in projected area indicated the adjustment of lipid composition and cell membrane remodeling. Importantly, the results not only reveal the cellular morphology and molecular changes during iPSCs-derived astrocytes activation but also reflect their mapping relationship, thereby providing new insights into diagnosing and treating neurodegenerative diseases.

Adaptive phase-shifting interferometry based on a phase-shifting digital holography algorithm.

Phase-shifting interferometry (PSI) requires accurate phase shifts between interferograms for realizing high-accuracy phase retrieval. This paper presents an adaptive PSI through synchronously capturing phase shifts measurement interferograms and phase measurement interferograms, in which the former is a series of spatial carrier frequency phase-shifting interferograms generated by an additional assembly and the phase shifts are calculated with the single-spectrum phase shifts measurement algorithm (SS-PSMA), the latter is employed for phase retrieval with an adaptive phase-shifting digital holography algorithm (PSDHA) based on complex amplitude recovery. In addition to exhibiting excellent reliability, high-accuracy phase retrieval (0.02 rad), and short calculation time (<25 ms), the proposed adaptive PSDHA is suitable for various interferograms with different fringe shapes and numbers. Importantly, both simulation analysis and experimental result demonstrate that this adaptive PSI based on PSDHA can effectively eliminate phase-shifting errors caused by phase shifter and external disturbance, ensuring high-accuracy phase shifts measurement and phase retrieval, meanwhile significantly reducing phase-shifting interferograms acquisition time and phase retrieval calculation time.

Simultaneous Spectral Tuning and Thermal Stability Adjustment in Ca8ZnGa(1-x)Lax(PO4)7:Eu2+ Phosphors.

The modifications of local structure in solid solution are a crucial step to regulate the photoluminescence properties of rare-earth ion-based phosphors. However, the structural diversity of host matrices and the uncertain occupation of activators make it challenging to obtain phosphors with both high stability and tailored emission. Herein, We synthesized a series of ß-Ca3(PO4)2-type Ca8ZnGa(1-x)Lax(PO4)7:Eu2+ solid solution phosphors by design. By modifying the Ga/La ratio, controllable regulation of the emission spectrum and thermal stability of the phosphors can be achieved at the same time. The introduction of La3+ can regulate the crystal field splitting strength of the Eu2+ activators, causing redshifts in the emission spectrum while increasing Ga3+ content will lead to enhanced energy transfer between the oxygen vacancy and Eu2+, as well as improved thermal stability. Through local structure modification, the spectrum and thermal stability of phosphors can be facilely tuned. The results indicate that this series of phosphors have versatile potentials in various applications.