Core Technical Solutions and Technological Innovation

(1) Core Technical Plan for the Experiment

• Sample preparation: Preparation of precision-cut liver slices (PCLS) and establishment of a tissue uptake system for fluorescent nanodiamonds (FNDs).
• Imaging and Fixation Techniques: Two-photon microscopy, cryosection immunostaining, transmission electron microscopy, and a stainless-steel anchor‑type fixation device specifically designed for tissue sections.
• Quantum Sensing and Detection: Nanodiamond Relaxation (T1) Measurement System, Pulsed Laser Excitation and Signal Acquisition, Rolling-Window Data Processing
• Activity and Quantitative Methods: ATP-to-Protein Ratio Assay for Assessing Tissue Viability; Flow Cytometry for Quantifying the Proportion of Cells Uptaking FNDs
• Condition optimization: a 5% CO₂ environment maintains tissue viability, and a 650 nm long-pass filter enhances the signal-to-noise ratio. T1 changes are recorded in real time, and detection reliability is validated through integration with tissue viability and imaging data.

(II) Key Innovations in Free Radical Generation Detection Technologies

Nanodiamond Relaxometry (T1) It demonstrates significant innovation in liver tissue detection applications:

Relying on the principles of quantum sensing, it exhibits highly specific responses to free radicals containing unpaired electrons, such as ·OH and ·O₂⁻. It can effectively avoid interference from non-radical substances such as hydrogen peroxide. ; At the signal dynamics level, this method Enables real-time, reversible tracking of the processes by which free radical levels are increased and decreased. , it overcomes the limitations of irreversible reactions inherent in conventional probes. Furthermore, by employing single-particle tracking and filter‑optimization techniques, it It can stably image in liver tissue with high autofluorescence background while also resolving intercellular heterogeneity. , providing a highly precise quantitative assay for studying oxidative stress at the cellular level.

Key Research Findings

The nanodiamond relaxation method is suitable for in vivo liver tissue detection.

Based on the T1 relaxation measurement technique using diamond NV centers, through… 650 nm longpass filter After optimization, spontaneous fluorescence interference in liver tissue is effectively suppressed, enhancing the signal-to-noise ratio of measurements without altering T1 values, thereby enabling stable detection of free-radical signals in tissue samples.

Establishment of a quantitative method for dynamic detection of free radicals at the cellular level

Using finely dissected liver sections as a model, combined with… Stainless steel anchoring and fixing device and 5% CO₂ culture environment It maintains tissue viability and enables real-time recording of continuous T1‑value changes under ethanol induction and antioxidant intervention, thereby facilitating dynamic monitoring of the rise and fall in hepatic free radical levels.

The Applicability of Validation Techniques in Research on Organizational Stress and Aging

This method can distinguish free radical levels across different regions and depths within tissues, with results showing no significant spatial dependence; moreover, it enables quantitative identification. The hepatic free radical burden in aged mice is significantly higher than that in young mice. , providing a reliable nanoscale analytical platform for studies on oxidative stress and aging.

Image and Text Guide

Figure 1. Principle and procedure of the diamond relaxation method for detecting free radicals in mouse liver sections.

Diamond relaxation measurement is used to detect free radicals in mouse liver sections. Precisely cut mouse liver slices preserve the diversity and characteristic features of the organ’s multicellular components. During a 24-hour incubation, free-radical precursors (FNDs) are incorporated into the liver slices. In diamond relaxation measurements, FNDs are excited by a series of green laser pulses, followed by the acquisition of optical readouts. After data processing, the trend of T1‑value changes reflects the dynamic behavior of free radicals under different experimental conditions. An increase in free-radical levels leads to a decrease in T1 values, and vice versa.

Figure 2. Two-photon, immunofluorescence, and electron microscopy characterization of nanodiamonds in finely sectioned mouse liver slices.

Precise cutting of nanodiamonds in mouse liver sections.

(A) Two-photon microscopy image of a mouse liver section. The image was acquired in λ‑mode, with each color corresponding to a distinct emission wavelength ranging from 410 nm (purple) to 690 nm (red). The red signal represents FNDs, while the green signal corresponds to tissue autofluorescence.

(B) Immunostaining results of 4-μm frozen sections. Gray: bright-field image; green: Kupffer cells labeled with anti‑CD68 or endothelial cells labeled with anti‑CD31; red: FNDs (some FNDs are circled); blue: nuclei stained with DAPI.

(C) Electron micrographs of FNDs in the tissue: tomographic slices (left) and a three-dimensional rendered volume of the FNDs (right).

Figure 3. Quantitative comparison of tissue viability in mouse liver sections under different conditions.

Tissue viability of mouse liver slices under different conditions. PCLS were co-incubated with or without FNDs for 24 hours at 37°C, 80% O₂, and 5% CO₂. Subsequently, various methods were employed to maintain tissue viability within 0.5 hours after the slices were removed from the incubator.

The first method involves transferring the PCLS to a 5% CO₂ incubator and culturing it for 0.5 hours.

The second method involves placing the PCLS in WEGG containing 10 mM HEPES buffer and storing it at 37°C.

The third approach combines the two methods. All data were standardized using the FND group as the reference. An unpaired t-test was used to compare differences between the two groups. Error bars represent mean ± standard deviation; *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.

Figure 4. Summary table of the advantages and disadvantages of different fixation methods for liver sections.

Figure 5. Effect of filter wavelength on image quality, signal-to-noise ratio, and T1 values.

The impact of filter wavelength on image and signal quality.

(A) Imaging was performed on the same region of liver sections containing internalized FNDs, using different bandpass filters (600 nm long-pass, 650 nm long-pass, or 700 nm long-pass). As the overall signal intensity decreased, the internalized FNDs (green circles) became more prominent. The calibration bar indicates fluorescence intensity in arbitrary units of photon counts per millisecond.

(B) Comparison of fluorescence intensity, tissue autofluorescence, and recorded T1 values for three distinct FNDs under different filter‑channel wavelengths. FND #1 originates from a batch of small FNDs with an average hydrodynamic diameter of 70 nm, whereas FND #2 and FND #3 have a size of 120 nm, consistent with the specifications of the FNDs used in the remaining experiments of this study. Red bars and yellow bars represent FND fluorescence intensity, while black bars indicate the mean intensity of tissue autofluorescence. The green curve shows the signal‑to‑noise ratio (SNR), defined here as the ratio of FND fluorescence intensity to tissue autofluorescence intensity. The blue curve displays the T1 values measured for the same FND under different filter settings. Error bars denote the 95% confidence interval of the calculated T1 values.

Table 1. 95% Confidence Intervals for T1 Values under Different Filters

Figure 6. Consistency of T1 measurements at different locations and depths within a single liver section.

T1 measurement results at different locations within a single liver biopsy.

(A) In three randomly selected 50×50 μm regions, a total of 42 measurements were performed for the different FNDs; the results showed no statistically significant differences among the measurement sites.

(B) Linear regression analysis indicated that the T1 value was not significantly correlated with the depth of the liver section (measured relative to the bottom of the section). The P-value reflects the significance level of the slope’s deviation from zero. All section-depth data were recorded from the surface, and consistency was maintained across the three measurement locations.

Figure 7. Dynamic changes in T1 values of liver slices under ethanol and ascorbic acid treatment.

(A) 25 mM ethanol (red) induces a rapid decrease in the T1 values recorded by FNDs in liver slices, whereas 0.6 mM L‑ascorbic acid (green) produces the opposite effect. The baseline time point is labeled as “−1” minute. All T1 values are normalized to the corresponding baseline T1 value recorded from the same FND. Data points represent the median of five independent measurements across different liver slices, and error bars indicate the interquartile range.

(B) Paired comparisons of baseline T1 values (“pre‑treatment”) and final T1 values (“post‑treatment”) across the experimental groups. Ethanol treatment resulted in a decrease in T1 values after 33 minutes of incubation, whereas L‑ascorbic acid treatment generally yielded higher T1 values, though this difference did not reach statistical significance. The culture medium (negative control) had no significant effect on the recorded T1 values.

Figure 8. Comparison of free radical burden in liver sections from young and aged mice.

The free radical burden data for young and aged mice were obtained by comparing T1 values in PCLS from 12‑week‑old and 80‑week‑old mice.