The depth-gating capacity of a spatially quasi-incoherent imaging interferometer is investigated in relation to the 3D correlation properties of diffraction field laser speckles. The system exploits a phase-stepped imaging Michelson-type interferometer in which spatially quasi-incoherent illumination is generated by passing an unexpanded laser beam through a rotating diffuser. Numerical simulations and optical experiments both verify that the depth-gating capacity of the imaging interferometer scales as 𝜆/2NA2𝑝λ/2NAp2, where 𝜆λ is the wavelength of the laser and NA𝑝NAp is the numerical aperture of the illumination. For a set depth gate of 150 µm, the depth-gating capacity of the interferometer is demonstrated by scanning a standard USAF target through the measurement volume. The results obtained show that an imaging tool of this kind is expected to provide useful capabilities for imaging through disturbing media and where a single wavelength is required.

An interferometric technique that utilize a spatially quasi-incoherent light source to perform interferometric measurements involving diffusely scattering objects is presented. The proposed technique is demonstrated with settings that give a depth gate of 90 µm.

Mitochondrial Cytochrome c Oxidase Subunit 4 Isoform 2 (Cox4i2) is essential for acute oxygen sensing and signaling in pulmonary arterial smooth muscle cells (PASMCs) by triggering the production of superoxide during acute hypoxia [1]. However, the molecular mechanism underlying Cox4i2-dependent oxygen sensing remains elusive. We analysed oxygen-dependent respiration by high resolution respirometry, redox changes of the electron transport chain (ETC) by RAMAN spectroscopy, and supercomplex formation by blue native gel analysis of PASMCs isolated from wild type (WT) and Cox4i2-/- mice. To understand the role of Cox4i2-specific cysteine residues we determined hypoxia-induced superoxide production and oxygen affinity in a mouse epithelial cell line (CMT167 cells) overexpressing either Cox4i1, or WT Cox4i2, or Cox4i2 mutants (C41S, C55A, C109S). Respiration and supercomplex formation were similar in WT and Cox4i2-/- PASMCs. Interestingly, hypoxia-induced reduction of ETC components (NADH, ubiquinol, and reduced cytochrome c) was prevented in Cox4i2-/- PASMCs. CMT167 cells expressing either Cox4i1, or Cox4i2 mutants lacked hypoxia-induced superoxide release, which was detected only in cells expressing WT Cox4i2. In contrast, overexpression of Cox4i1, or Cox4i2, or Cox4i2 mutants did not affect oxygen affinity. Our findings suggest that Cox4i2 does not alter superoxide production by rearrangement of supercomplexes, whereas its specific cysteines are needed for the superoxide release. In conclusion, Cox4i2 plays a major role in the hypoxia-induced reduction of ETC components, likely mediated through its redox-active cysteine residues.

Delineating cancer tissue while leaving functional tissue intact is crucial in brain tumor resection. Despite several available aids, surgeons are limited by preoperative or subjective tools. Raman spectroscopy is a label-free optical technique with promising indications for tumor tissue identification. To allow direct comparisons between measurements preprocessing of the Raman signal is required. There are many recognized methods for preprocessing Raman spectra; however, there is no universal standard. In this paper, six different preprocessing methods were tested on Raman spectra (n > 900) from fresh brain tissue samples (n = 34). The sample cohort included both primary brain tumors, such as adult-type diffuse gliomas and meningiomas, as well as metastases of breast cancer. Each tissue sample was classified according to the CNS WHO 2021 guidelines. The six methods include both direct and iterative polynomial fitting, mathematical morphology, signal derivative, commercial software, and a neural network. Data exploration was performed using principal component analysis, t-distributed stochastic neighbor embedding, and k-means clustering. For each of the six methods, the parameter combination that explained the most variance in the data, i.e., resulting in the highest Gap-statistic, was chosen and compared to the other five methods. Depending on the preprocessing method, the resulting clusters varied in number, size, and associated spectral features. The detected features were associated with hemoglobin, neuroglobin, carotenoid, water, and protoporphyrin, as well as proteins and lipids. However, the spectral features seen in the Raman spectra could not be unambiguously assigned to tissue labels, regardless of preprocessing method. We have illustrated that depending on the chosen preprocessing method, the spectral appearance of Raman features from brain tumor tissue can change. Therefore, we argue both for caution in comparing spectral features from different Raman studies, as well as the importance of transparency of methodology and implementation of the preprocessing. As discussed in this study, Raman spectroscopy for in vivo guidance in neurosurgery requires fast and adaptive preprocessing. On this basis, a pre-trained neural network appears to be a promising approach for the operating room.

Stimulated Raman scattering is a phenomenon with potential use in providing real-time molecular information in three-dimensions (3D) of a sample using imaging. For precise imaging, the knowledge about the spatial generation of stimulated Raman scattering is essential. To investigate the spatial behavior in an idealized case, computer simulations and experiments were performed. For the computer simulations, diffraction theory was used for the beam propagation complemented with nonlinear phase modulation describing the interaction between the light and matter. For the experiments, a volume of ethanol was illuminated by an expanded light beam and a plane inside the volume was imaged in transmission. For generating stimulated Raman scattering, a pump beam was focused into this volume and led to a beam dump after passing the volume. The pulse duration of the two beams were 6 ns and the pump beam energy ranged from 1 to 27 mJ. The effect of increasing pump power on the spatial distribution of the Raman gain and the spatial growth of the signal at different interaction lengths between the beam and the sample was investigated. The spatial width of the region where the stimulated Raman scattering signal was generated for experiments and simulation was 0.21 and 0.09 mm, respectively. The experimental and simulation results showed that most of the stimulated Raman scattering is generated close to the pump beam focus and the maximum peak of the Stokes intensity spatially comes shortly after the peak of the pump intensity.

Species specific 3D imaging requires control of where in the sample stimulated Raman gain is achieved. By using a phase spatial light modulator the signal position can be calculated, controlled and directly imaged in 3D.

The ability to sense changes in oxygen availability is fundamentally important for the survival of all aerobic organisms. However, cellular oxygen sensing mechanisms and pathologies remain incompletely understood and studies of acute oxygen sensing, in particular, have produced inconsistent results. Current methods cannot simultaneously measure the key cellular events in acute hypoxia (i.e., changes in redox state, electrophysiological properties, and mechanical responses) at controlled partial pressures of oxygen (pO₂). The lack of such a comprehensive method essentially contributes to the discrepancies in the field. A sealed microfluidic system that combines i) Raman spectroscopy, ii) patch-clamp electrophysiology, and iii) live-cell imaging under precisely controlled pO₂ have therefore been developed. Merging these modalities allows label-free and simultaneous observation of oxygen-dependent alterations in multiple cellular redox couples, membrane potential, and cellular contraction. This technique is adaptable to any cell type and allows in-depth insight into acute oxygen sensing processes underlying various physiologic and pathologic conditions. 

Prostate cancer surgery risks erectile problems and incontinence for the patient. An instrument for guiding surgeons to avoid nerve bundle damage and ensure complete cancer removal is desirable. We present a tactile resonance sensor made of PZT ceramics, mounted in a 3D motorized translation stage for scanning and measuring tissue stiffness for detecting cancer in human prostate. The sensor may be used during surgery for guidance, scanning the prostate surface for the presence of cancer, indicating migration of cancer cells into surrounding tissue. Ten fresh prostates, obtained from patients undergoing prostate cancer surgery, were cut into 0.5 cm thick slices. Each slice was measured for tissue stiffness at about 25 different sites and compared to histology for validation cancer prediction by stiffness. The statistical analysis was based on a total of 148 sites with non-cancer and 40 sites with cancer. Using a generalized linear mixed model (GLMM), the stiffness data predicted cancer with an area under the curve of 0.74, after correcting for overfitting using bootstrap validation. Mean prostate stiffness on the logarithmic scale (p = 0.015) and standardized Z-scores (p = 0.025) were both significant predictors of cancer. This study concludes that stiffness measured by the tactile resonance sensor is a significant predictor of prostate cancer with potential for future development towards a clinical instrument for surgical guidance.