The Challenges of O2 Detection in Biological Fluids: Classical Methods and Translation to Clinical Applications

Abstract

Dissolved oxygen (DO) is deeply involved in preserving the life of cellular tissues and human beings due to its key role in cellular metabolism: its alterations may reflect important pathophysiological conditions. DO levels are measured to identify pathological conditions, explain pathophysiological mechanisms, and monitor the efficacy of therapeutic approaches. This is particularly relevant when the measurements are performed in vivo but also in contexts where a variety of biological and synthetic media are used, such as ex vivo organ perfusion. A reliable measurement of medium oxygenation ensures a high-quality process. It is crucial to provide a high-accuracy, real-time method for DO quantification, which could be robust towards different medium compositions and temperatures. In fact, biological fluids and synthetic clinical fluids represent a challenging environment where DO interacts with various compounds and can change continuously and dynamically, and further precaution is needed to obtain reliable results. This study aims to present and discuss the main oxygen detection and quantification methods, focusing on the technical needs for their translation to clinical practice. Firstly, we resumed all the main methodologies and advancements concerning dissolved oxygen determination. After identifying the main groups of all the available techniques for DO sensing based on their mechanisms and applicability, we focused on transferring the most promising approaches to a clinical in vivo/ex vivo setting.

Keywords: absolute and relative techniques; biological fluids; clinical applications; dissolved oxygen quantification; oxygen sensing; technical innovation in clinics.

Figure 1

Body fluids classification and relative amount in volume and weight.

Figure 2

(A). Representation of the relation between partial oxygen pressure(pO₂) and the C_O2 content of different solutions. O2 is poorly dissolved in water (blue curve), while the presence of carriers such as red blood cells (RBC), perfluorocarbons (PFC), or a hemoglobin-based oxygen carrier (HBOC-201) greatly improves the C_O2 of the fluid. From [21] (B). Typical “dissociation curve” describing the relationship between paO₂ and Hemoglobin saturation (Sa_O2). The distribution of total DO in O₂ combined with heme and dissolved O₂ is also highlighted. From [26].

Figure 3

Schematic of the visual changes occurring during a Winkler method-based titration of a perfusion solution. (A) Perfusion solution (B) Addition of Mn, KI, and KOH (turbid solution with MnO(OH)₂ precipitate). (C) Addition of H₂SO₄ (D) Characteristic straw yellow color obtained during iodine titration. When reached, the starch indicator must be added to the system. (E) System after the addition of the starch indicator. (F) System at the end of titration.

Figure 4

(A) Scheme of typical fluorescence quenching-based DO sensors. The blue excitation LED is the one used for the excitation of the emitting material. The red one is used instead as an internal reference. When these sensors exploit the modulation technique, the blue LED is modulated to a frequency related to the luminophore’s luminescence lifetime and the upper and lower lifetimes. Blue arrow: LED emission; red arrow: fluorescence (B) Scheme of typical fluorescence quenching-based DO sensors with optic fiber technology. The detector and the light sources communicate are not integrated into the sensing tip and communicate with it through the fiber allowing the miniaturization of the sensing probe.

Figure 5

Schematization of Clark electrode and of the reactions in the system.

Figure 6

Translation of DO sensing methods from classical to clinical settings of increasing complexity.

Figure 7

Experimental setup for in vivo optical imaging of oxygen metabolism in brain tissues using a planar phosphorescence PtBP-based oxygen sensor. Pink asterisk: physical stimulation of the rat whisker. The skull cortex of the mouse is illuminated with light at 630 nm, and the emitted photons with a wavelength above 690 nm are acquired with a CCD camera. Adapted with permission from [123].

Figure 8

Schematic of a blood gas analyzer system. The sample enters a thermostatic chamber containing the electrodes (E1) due to pump aspiration. E2-R2 represents the pH reference electrode.

Figure 9

Example of a microelectrode exploiting a Silica and Gold Nanochannel Membrane to monitor in vivo O₂ levels on rat brain. Adapted with permission from [142].

Figure 10

Schematic of the classical DO detection methods in biological fluids and of the advanced solution for clinical applications.

Figure 11

DO detection methods for biological matrices and clinical settings.