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Using functional near-infrared spectroscopy (fNIRS) in bottlenose dolphins (Tursiops truncatus) could help to understand how echolocating animals perceive their environment and how they focus on specific auditory objects, such as fish, in noisy marine settings.
Aim
To test the feasibility of near-infrared spectroscopy (NIRS) in medium-sized marine mammals, such as dolphins, we modeled the light propagation with computational tools to determine the wavelengths, optode locations, and separation distances that maximize sensitivity to brain tissue.
Approach
Using frequency-domain NIRS, we measured the absorption and reduced scattering coefficient of dolphin sculp. We assigned muscle, bone, and brain optical properties from the literature and modeled light propagation in a spatially accurate and biologically relevant model of a dolphin head, using finite-element modeling. We assessed tissue sensitivities for a range of wavelengths (600 to 1700 nm), source–detector distances (50 to 120 mm), and animal sizes (juvenile model 25% smaller than adult).
Results
We found that the wavelengths most suitable for imaging the brain fell into two ranges: 700 to 900 nm and 1100 to 1150 nm. The optimal location for brain sensing positioned the center point between source and detector 30 to 50 mm caudal of the blowhole and at an angle 45 deg to 90 deg lateral off the midsagittal plane. Brain tissue sensitivity comparable to human measurements appears achievable only for smaller animals, such as juvenile bottlenose dolphins or smaller species of cetaceans, such as porpoises, or with source–detector separations ≫100 mm in adult dolphins.
Conclusions
Brain measurements in juvenile or subadult dolphins, or smaller dolphin species, may be possible using specialized fNIRS devices that support optode separations of >100 mm. We speculate that many measurement repetitions will be required to overcome hemodynamic signals originating predominantly from the muscle layer above the skull. NIRS measurements of muscle tissue are feasible today with source–detector separations of 50 mm, or even less.
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Continuous wave near infrared spectroscopy (CW-NIRS) is widely exploited in clinics to estimate skeletal muscles and brain cortex oxygenation. Spatially resolved spectroscopy (SRS) is generally implemented in commercial devices. However, SRS suffers from two main limitations: the a priori assumption on the spectral dependence of the reduced scattering coefficient [μs′(λ)] and the modeling of tissue as homogeneous.
Aim
We studied the accuracy and robustness of SRS NIRS. We investigated the errors in retrieving hemodynamic parameters, in particular tissue oxygen saturation (StO2), when μs′(λ) was varied from expected values, and when layered tissue was considered.
Approach
We simulated hemodynamic variations mimicking real-life scenarios for skeletal muscles. Simulations were performed by exploiting the analytical solutions of the photon diffusion equation in different geometries: (1) semi-infinite homogeneous medium and constant μs′(λ); (2) semi-infinite homogeneous medium and linear changes in μs′(λ); (3) two-layered media with a superficial thickness s1 = 5, 7.5, 10 mm and constant μs′(λ). All simulated data were obtained at source-detector distances ρ = 35, 40, 45 mm, and analyzed with the SRS approach to derive hemodynamic parameters (concentration of oxygenated and deoxygenated hemoglobin, total hemoglobin concentration, and tissue oxygen saturation, StO2) and their relative error.
Results
Variations in μs′(λ) affect the estimated StO2 (up to ±10 % ), especially if changes are different at the two wavelengths. However, the main limitation of the SRS method is the presence of a superficial layer: errors strongly larger than 20% were retrieved for the estimated StO2 when the superficial thickness exceeds 5 mm.
Conclusions
These results highlight the need for more sophisticated strategies (e.g., the use of multiple short and long distances) to reduce the influence of superficial tissues in retrieving hemodynamic parameters and warn the SRS users to be aware of the intrinsic limitation of this approach, particularly when exploited in the clinical environment.
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Plasmo-thermo-electrophoresis (PTEP) involves using plasmonic microstructures to generate both a large-scale convection current and a near-field attraction force (thermo-electrophoresis). These effects facilitate the collective locomotion (i.e., swarming) of microscale particles in suspension, which can be utilized for numerous applications, such as particle/cell manipulation and targeted drug delivery. However, to date, PTEP for ensemble manipulation has not been well characterized, meaning its potential is yet to be realized.
Aim
Our study aims to provide a characterization of PTEP on the motion and swarming effect of various particles and bacterial cells to allow rational design for bacteria-based microrobots and drug delivery applications.
Approach
Plasmonic optical fibers (POFs) were fabricated using two-photon polymerization. The particle motion and swarming behavior near the tips of optical fibers were characterized by image-based particle tracking and analyzing the spatiotemporal concentration variation. These results were further correlated with the shape and surface charge of the particles defined by the zeta potential.
Results
The PTEP demonstrated a drag force ranging from a few hundred fN to a few tens of pN using the POFs. Furthermore, bacteria with the greater (negative) zeta potential ( | ζ | > 10 mV) and smoother shape (e.g., Klebsiella pneumoniae and Escherichia coli) exhibited the greatest swarming behavior.
Conclusions
The characterization of PTEP-based bacteria swarming behavior investigated in our study can help predict the expected swarming behavior of given particles/bacterial cells. As such, this may aid in realizing the potential of PTEP in the wide-ranging applications highlighted above.
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The number of injections administered has increased dramatically worldwide due to vaccination campaigns following the COVID-19 pandemic, creating a problem of disposing of syringes and needles. Accidental needle sticks occur among medical and cleaning staff, exposing them to highly contagious diseases, such as hepatitis and human immunodeficiency virus. In addition, needle phobia may prevent adequate treatment. To overcome these problems, we propose a needle-free injector based on thermocavitation.
Aim
Experimentally study the dynamics of vapor bubbles produced by thermocavitation inside a fully buried 3D fused silica chamber and the resulting high-speed jets emerging through a small nozzle made at the top of it. The injected volume can range from ∼0.1 to 2 μL per shot. We also demonstrate that these jets have the ability to penetrate agar skin phantoms and ex-vivo porcine skin.
Approach
Through the use of a high-speed camera, the dynamics of liquid jets ejected from a microfluidic device were studied. Thermocavitation bubbles are generated by a continuous wave laser (1064 nm). The 3D chamber was fabricated by ultra-short pulse laser-assisted chemical etching. Penetration tests are conducted using agar gels (1%, 1.25%, 1.5%, 1.75%, and 2% concentrations) and porcine tissue as a model for human skin.
Result
High-speed camera video analysis showed that the average maximum bubble wall speed is about 10 to 25 m/s for almost any combination of pump laser parameters; however, a clever design of the chamber and nozzle enables one to obtain jets with an average speed of ∼70 m / s. The expelled volume per shot (0.1 to 2 μl) can be controlled by the pump laser intensity. Our injector can deliver up to 20 shots before chamber refill. Penetration of jets into agar of different concentrations and ex-vivo porcine skin is demonstrated.
Conclusions
The needle-free injectors based on thermocavitation may hold promise for commercial development, due to their cost and compactness.
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Light emitting diodes (LEDs) are commonly utilized for tissue spectroscopy due to their small size, low cost, and simplicity. However, LEDs are often approximated as single-wavelength devices despite having relatively broad spectral bandwidths. When paired with photodiodes, the wavelength information of detected light cannot be resolved. This can result in errors during chromophore concentration calculations. These errors are particularly apparent when analyzing water and fat in the 900 to 1000 nm window where the spectral bandwidth of LEDs can encompass much of the analysis region, resulting in intense crosstalk.
Aim
We utilize and present a spectral correction (SC) algorithm to correct for the spectral bandwidth of LEDs. We show the efficacy using a narrowband technique of spectrally broad and overlapping LEDs.
Approach
Narrowband diffuse reflectance spectroscopy (nb-DRS), a technique capable of quantifying the hydration ratio (RH2O) of turbid media, was utilized. nb-DRS typically requires a broadband light source and spectrometer. We reduce the hardware to just five LEDs and a photodiode detector, relying on SC to compensate for spectral crosstalk. The effectiveness of our SC approach was tested in simulations as well as in an emulsion phantom and limited selection of human tissue.
Results
In simulations, we show that calculated RH2O errors increased with the spectral bandwidth of LEDs but could be corrected using SC. Likewise, in emulsions, we found an average error of 8.7% (maximum error 14%) if SC was not used. By contrast, applying SC reduced the average error to 2.2% (maximum error of 6.4%). We show that despite utilizing multiple, spectrally broad, and overlapping LEDs, SC was still able to restore the performance of our narrowband method, making it comparable to a much larger full broadband system.
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Pancreatic cancer tumors are known to be avascular, but their neovascular capillaries are still chaotic leaky vessels. Capillary permeability could have significant value for therapy assessment, and its quantification might be possible with macroscopic imaging of indocyanine green (ICG) kinetics in tissue.
Aim
The capacity of using standard fluorescence surgical systems for ICG kinetic imaging as a probe for capillary leakage was evaluated using a clinical surgical fluorescence imaging system, as interpreted through vascular permeability modeling.
Approach
Xenograft pancreatic adenocarcinoma models were imaged in mice during bolus injection of ICG to capture the kinetics of uptake. Image analysis included ratiometric data, normalization, and match to theoretical modeling. Kinetic data were converted into the extraction fraction of the capillary leakage.
Results
Pancreatic tumors were usually less fluorescent than the surrounding healthy tissues, but still the rate of tumor perfusion could be assessed to quantify capillary extraction. Model simulations showed that flow kinetics stabilized after about 1 min beyond the initial bolus injection and that the relative extraction fraction model estimates matched the experimental data of normalized uptake within the tissue. The kinetics in the time period of 1 to 2 min post-injection provided optimal differential data between AsPC1 and BxPC3 tumors, although high individual variation exists between tumors.
Conclusions
ICG kinetic imaging during the initial leakage phase was diagnostic for quantitative vascular permeability within pancreatic tumors. Methods for autogain correction and normalized model-based interpretation allowed for quantification of extraction fraction and difference identification between tumor types in early timepoints.
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Maternal exposure to drugs during pregnancy is known to have detrimental effects on the fetus. Alcohol (ethanol) and nicotine are two of the most commonly co-abused substances during pregnancy, and prenatal poly-drug exposure is common due, in part, to the prevalence of unplanned pregnancies. The second trimester is a critical period for fetal neurogenesis and angiogenesis. When drug exposure occurs during this time, fetal brain development is affected. Several behavioral, morphological, and functional studies have evaluated the changes in fetal brain development due to exposure to these drugs individually. However, research on the combined effects of ethanol and nicotine is far more limited, specifically on fetal vasculature changes and development.
Aim
We use correlation mapping optical coherence angiography (cm-OCA) to evaluate acute changes in fetal brain vasculature caused by maternal exposure to a combination of ethanol and nicotine.
Approach
Ethanol (16.6% v/v, at a dose of 0.75g / kg) and nicotine (at a dose of 0.1 mg / kg) were administered to pregnant mice after initial cm-OCA measurements in utero. Subsequent measurements were taken at 5-min intervals for a total period of 45 min. Results from these experiments were compared to results from our previous studies in which the mother was exposed to only ethanol (dose: 0.75 g / kg) or nicotine (dose: 0.1 mg / kg).
Results
While results from exposure to ethanol or nicotine independently showed vasoconstriction, no significant change in vasculature was observed with combined exposure.
Conclusion
Results suggested antagonistic effects of ethanol and nicotine on fetal brain vasculature.
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The accurate large-scale mapping of cerebral microvascular blood flow velocity is crucial for a better understanding of cerebral blood flow (CBF) regulation. Although optical imaging techniques enable both high-resolution microvascular angiography and fast absolute CBF velocity measurements in the mouse cortex, they usually require different imaging techniques with independent system configurations to maximize their performances. Consequently, it is still a challenge to accurately combine functional and morphological measurements to co-register CBF speed distribution from hundreds of microvessels with high-resolution microvascular angiograms.
Aim
We propose a data acquisition and processing framework to co-register a large set of microvascular blood flow velocity measurements from dynamic light scattering optical coherence tomography (DLS-OCT) with the corresponding microvascular angiogram obtained using two-photon microscopy (2PM).
Approach
We used DLS-OCT to first rapidly acquire a large set of microvascular velocities through a sealed cranial window in mice and then to acquire high-resolution microvascular angiograms using 2PM. The acquired data were processed in three steps: (i) 2PM angiogram coregistration with the DLS-OCT angiogram, (ii) 2PM angiogram segmentation and graphing, and (iii) mapping of the CBF velocities to the graph representation of the 2PM angiogram.
Results
We implemented the developed framework on the three datasets acquired from the mice cortices to facilitate the coregistration of the large sets of DLS-OCT flow velocity measurements with 2PM angiograms. We retrieved the distributions of red blood cell velocities in arterioles, venules, and capillaries as a function of the branching order from precapillary arterioles and postcapillary venules from more than 1000 microvascular segments.
Conclusions
The proposed framework may serve as a useful tool for quantitative analysis of large microvascular datasets obtained by OCT and 2PM in studies involving normal brain functioning, progression of various diseases, and numerical modeling of the oxygen advection and diffusion in the realistic microvascular networks.
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Altered lipid metabolism of cancer cells has been implicated in increased radiation resistance. A better understanding of this phenomenon may lead to improved radiation treatment planning. Stimulated Raman scattering (SRS) microscopy enables label-free and quantitative imaging of cellular lipids but has never been applied in this domain.
Aim
We sought to investigate the radiobiological response in human breast cancer MCF7 cells using SRS microscopy, focusing on how radiation affects lipid droplet (LD) distribution and cellular morphology.
Approach
MCF7 breast cancer cells were exposed to either 0 or 30 Gy (X-ray) ionizing radiation and imaged using a spectrally focused SRS microscope every 24 hrs over a 72-hr time period. Images were analyzed to quantify changes in LD area per cell, lipid and protein content per cell, and cellular morphology. Cell viability and confluency were measured using a live cell imaging system while radiation-induced lipid peroxidation was assessed using BODIPY C11 staining and flow cytometry.
Results
The LD area per cell and total lipid and protein intensities per cell were found to increase significantly for irradiated cells compared to control cells from 48 to 72 hrs post irradiation. Increased cell size, vacuole formation, and multinucleation were observed as well. No significant cell death was observed due to irradiation, but lipid peroxidation was found to be greater in the irradiated cells than control cells at 72 hrs.
Conclusions
This pilot study demonstrates the potential of SRS imaging for investigating ionizing radiation-induced changes in cancer cells without the use of fluorescent labels.
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Multi-photon fluorescence recovery after photobleaching (MPFRAP) is a nonlinear microscopy technique used to measure the diffusion coefficient of fluorescently tagged molecules in solution. Previous MPFRAP fitting models calculate the diffusion coefficient in systems with diffusion or diffusion in laminar flow.
Aim
We propose an MPFRAP fitting model that accounts for shear stress in laminar flow, making it a more applicable technique for in vitro and in vivo studies involving diffusion.
Approach
Fluorescence recovery curves are generated using high-throughput molecular dynamics simulations and then fit to all three models (diffusion, diffusion and flow, and diffusion and shear flow) to define the limits within which accurate diffusion coefficients are produced. Diffusion is simulated as a random walk with a variable horizontal bias to account for shear flow.
Results
Contour maps of the accuracy of the fitted diffusion coefficient as a function of scaled velocity and scaled shear rate show the parameter space within which each model produces accurate diffusion coefficients; the shear-flow model covers a larger area than the previous models.
Conclusion
The shear-flow model allows MPFRAP to be a viable optical tool for studying more biophysical systems than previous models.
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TOPICS: Signal to noise ratio, Fluorophores, Fluorescence, Tissues, Signal detection, Target detection, Near infrared, Interference (communication), In vivo imaging, Skin
Diffuse in vivo flow cytometry (DiFC) is an emerging fluorescence sensing method to non-invasively detect labeled circulating cells in vivo. However, due to signal-to-noise ratio (SNR) constraints largely attributed to background tissue autofluorescence (AF), DiFC’s measurement depth is limited.
Aim
The dual ratio (DR)/dual slope is an optical measurement method that aims to suppress noise and enhance SNR to deep tissue regions. We aim to investigate the combination of DR and near-infrared (NIR) DiFC to improve circulating cells’ maximum detectable depth and SNR.
Approach
Phantom experiments were used to estimate the key parameters in a diffuse fluorescence excitation and emission model. This model and parameters were implemented in Monte Carlo to simulate DR DiFC while varying noise and AF parameters to identify the advantages and limitations of the proposed technique.
Results
Two key factors must be true to give DR DiFC an advantage over traditional DiFC: first, the fraction of noise that DR methods cannot cancel cannot be above the order of 10% for acceptable SNR. Second, DR DiFC has an advantage, in terms of SNR, if the distribution of tissue AF contributors is surface-weighted.
Conclusions
DR cancelable noise may be designed (e.g., through the use of source multiplexing), and indications point to the AF contributors’ distribution being truly surface-weighted in vivo. Successful and worthwhile implementation of DR DiFC depends on these considerations, but results point to DR DiFC having possible advantages over traditional DiFC.
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