**Application Prospects of FTIR Spectroscopy and CLSM to Monitor the Drugs Interaction with Bacteria Cells Localized in Macrophages for Diagnosis and Treatment Control of Respiratory Diseases**

**Igor D. Zlotnikov 1, Alexander A. Ezhov 2, Maksim A. Vigovskiy 3,4, Olga A. Grigorieva 3,4, Uliana D. Dyachkova 3,4, Natalia G. Belogurova <sup>1</sup> and Elena V. Kudryashova 1,\***

	- Lomonosov Moscow State University, 27/10, Lomonosovsky Ave., 119192 Moscow, Russia

**Abstract:** Visualization of the interaction of drugs with biological cells creates new approaches to improving the bioavailability, selectivity, and effectiveness of drugs. The use of CLSM and FTIR spectroscopy to study the interactions of antibacterial drugs with latent bacterial cells localized in macrophages create prospects to solve the problems of multidrug resistance (MDR) and severe cases. Here, the mechanism of rifampicin penetration into *E. coli* bacterial cells was studied by tracking the changes in the characteristic peaks of cell wall components and intracellular proteins. However, the effectiveness of the drug is determined not only by penetration, but also by efflux of the drugs molecules from the bacterial cells. Here, the efflux effect was studied and visualized using FTIR spectroscopy, as well as CLSM imaging. We have shown that because of efflux inhibition, eugenol acting as an adjuvant for rifampicin showed a significant (more than three times) increase in the antibiotic penetration and the maintenance of its intracellular concentration in *E. coli* (up to 72 h in a concentration of more than 2 μg/mL). In addition, optical methods have been applied to study the systems containing bacteria localized inside of macrophages (model of the latent form), where the availability of bacteria for antibiotics is reduced. Polyethylenimine grafted with cyclodextrin carrying trimannoside vector molecules was developed as a drug delivery system for macrophages. Such ligands were absorbed by CD206+ macrophages by 60–70% versus 10–15% for ligands with a non-specific galactose label. Owing to presence of ligands with trimannoside vectors, the increase in antibiotic concentration inside macrophages, and thus, its accumulation into dormant bacteria, is observed. In the future, the developed FTIR+CLSM techniques would be applicable for the diagnosis of bacterial infections and the adjustment of therapy strategies.

**Keywords:** FTIR spectroscopy; CLSM; macrophage; latent infection; drug resistance

#### **1. Introduction**

Respiratory tract diseases (tuberculosis, pneumonia, mycoplasmosis etc) caused by pathogenic microorganisms are an acute problem in modern society [1,2]. Moreover, the resistant forms of microorganisms practically insensitive to antibiotics are caused by a number of factors, including the drug efflux effect, which is particularly dangerous [3–8]. For several decades, the main causative agents of bacterial forms of respiratory diseases have been *S. pneumoniae*, *M. tuberculosis*, *H. influenzae* type b, *S. pyogenes*, *M. catarrhalis*, and *S. aureus* [9]. These pathogens develop resistance to amoxicillin, rifampicin, macrolides, and cephalosporins. Resistance to antibiotics is multifactorial and may be caused by one or

**Citation:** Zlotnikov, I.D.; Ezhov, A.A.; Vigovskiy, M.A.; Grigorieva, O.A.; Dyachkova, U.D.; Belogurova, N.G.; Kudryashova, E.V. Application Prospects of FTIR Spectroscopy and CLSM to Monitor the Drugs Interaction with Bacteria Cells Localized in Macrophages for Diagnosis and Treatment Control of Respiratory Diseases. *Diagnostics* **2023**, *13*, 698. https://doi.org/ 10.3390/diagnostics13040698

Academic Editor: Viktor Dremin

Received: 26 December 2022 Revised: 8 February 2023 Accepted: 9 February 2023 Published: 12 February 2023

**Copyright:** © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

a combination of mutations in target genes, increased production of multidrug-resistant outflow pumps (MDR), or modifying enzymes and/or target-protecting proteins [10,11]. In this paper, special attention is focused on the study of efflux and ligands that increase specificity, which are considered as one of the main processes that reduces the effectiveness of antibiotics.

A special problem in the treatment of diseases are pathogens localized in macrophages and granulomas, thereby passing into a dormant form (but still dangerous) and are difficult to treat, as seen in some forms of tuberculosis, leishmaniasis, and respiratory diseases caused by chlamydial infections, which are particularly prevalent in children and people with weakened immunity, etc. [6,12,13]. This work is devoted to the development of spectral and optical methods for studying drug interactions with bacterial cells in their individual form and inside macrophages—as a model of latent infections. The considered approaches are perspective in application of the bacterial disease diagnosis by analysis of the FTIR spectra of pulmonary lavages using library data on microorganisms, as well as the optimization of the action of drugs for each patient. The possibility of analyzing pulmonary lavage is described in the work [14], where the combination of FTIR and confocal microscopy establishes the composition of the biological fluid [14]. However, for accurate validation, reference spectra and the use of several methods are necessary. The spectra biological objects such as cells are usually too multifactorial and it is not yet fully clear how to specify and isolate analytically significant signals; however, with the development of technologies, new prospects are opening up, such as time-resolved spectroscopy and 2D analysis. The literature describes the use of Raman scattering for the study of bacterial cells and identification of pathogens and strains [15]. Currently, the method is unreliable and, accordingly, not very informative, since it analyzes not the intrinsic spectra of substances in the giant Raman scattering, but only indirect ones—the effect of bacteria on the optical properties of nanoparticles. It strongly depends on the quality of the sample application, on the batch of particles, and on the conditions of strain cultivation [16,17].

On the contrary, FTIR spectroscopy, which is a highly informative method of analyzing chemical compounds, provides information about chemical bonds and the microenvironment of molecules, and is quite sensitive to changes in fine organization at the molecular level [6,18–20]. This makes it possible to study the structures of complex biological objects (cells, organelles), which is of limited use for other spectral methods that require the optical transparency of samples, which clearly does not apply to cells. Practical applications of FTIR spectroscopy include: analysis of biological tissues [21], tumor diagnosis [22], identification of pathogenic bacteria [23], and the study of molecular mechanisms of adaptation to changes in external conditions [24]—which opens up the opportunities to study the development of resistance. We assume that by using FTIR spectroscopy it would be possible to monitor the course of treatment, or the effectiveness of the drug used, as well as analyzing the biological fluids, regulating treatment regimes, and determining sensitivity to antibiotics. The advantages of FTIR spectroscopy include a small amount of substance for analysis (50 μL), non-invasive and giving numerical reagents, and biochemical changes at the molecular level. It has been widely discussed that the optical method of FTIR spectroscopy can potentially be used by doctors to accelerate the diagnosis of a patient or as an auxiliary method of analysis—during or before surgery [25].

Confocal Laser Scanning Microscopy (CLSM) is an optical imaging technique for increasing the optical resolution and contrast of micrography by using a spatial point hole to block out-of-focus light during image formation. Confocal microscopy allows direct, non-invasive sequential optical cutting of intact, thick, living samples with minimal sample preparation. Practical applications of CLSM include imaging of various tissues, cells, and drug interactions. CLSM provides efficient characterization of the physicochemical properties of drug delivery systems [26], diagnostics, and examination of cancerous tissues [27] and visualization of bacteria [6,28–30]. Confocal microscopy makes it possible to visualize the accumulation of drugs in cells and to study the mechanisms affecting the effectiveness of the therapeutic agent [6,28,29,31–34].

As possible promising experimental bases to solve the problem of latent infections localized in macrophages and multidrug resistance of bacteria, we propose two approaches: the use of a targeted drug delivery system to macrophages to concentrate drugs in the lungs [6,28,31,32,35–56], as well as the use of adjuvants (allylbenzenes and terpenoids) that inhibit efflux and increase the permeability of the membrane of pathogenic microorganisms [6–8,34,57–61]. We used rifampicin (Rif) [35,53,62] and doxorubicin (Dox) [35,57] as model (fluorophore) drugs, and studied their synergism with adjuvants (terpenoids from plant extracts) as well as the molecular mechanisms of such combined drug action that can be visualized by optical and spectral methods.

Thus, this study is aimed at developing a new approach based on spectral and optical methods for possible use in medical practice: monitoring the course of treatment based on spectral data of biological fluids, potential diagnosis of bacterial diseases, and strengthening existing therapeutic formulations.

#### **2. Materials and Methods**

#### *2.1. Reagents*

Carbonyldiimidazole (CDI) was obtained from GL Biochem Ltd. (Shanghai, China) via an intermediary Himprocess (Moscow, Russia). D-mannose, galactose, PEI 1.8 kDa (branched), fluorescein isothiocyanate (FITC), NaBH3CN, DMF, DMSO, Et3N, 2-hydroxypropyl-β-cyclodextrin (HPCD), 1M 2,4,6-trinitrobenzenesulfonic acid, rifampicin, and doxorubicin were obtained from Sigma Aldrich (St. Louis, MI, USA). Eosin-5-maleimide was purchased from Invitrogen (Molecular Probes, Eugene, Oregon, USA). Mannotriose-di- (N-acetyl-D-glucosamine) was obtained from Dayang Chem Co., Ltd. (Hangzhou, China). Eugenol and safrole at the highest commercial quality were purchased from Acros Organics (Flanders, Belgium). The preparation of apiol and plant extracts was carried out in the same way as described earlier [63]. Other chemicals such as salts and acids were obtained from Reakhim Production (Moscow, Russia).

#### *2.2. Synthesis and Characterization of Conjugates*

#### 2.2.1. Synthesis of Grafted Chitosan and Cyclodextrin

The synthesis, purification, and characterization of conjugates were carried out as described earlier [6,20,50], including steps of HPCD activation by carbonyldiimidazole, subsequent conjugation with PEI amino groups, and modification by three types of carbohydrate labels: linear galactose, linear mannose, and trimannoside—to determine the affinity to CD206 receptors of macrophages. Introduction of the FITC label: to the aqueous solution of PEI1.8 (5% in 0.01M HCl, 1 g), a solution of FITC (15 mg in 1.5 mL DMSO) was added drop by drop with stirring; the pH was brought to 9.2 (sodium borate buffer, 0.1M). The mixture was incubated at 40 ◦C for 1 h, followed by purification by dialysis against water (cut-off 1 kDa) for 6 h. Purification by dialysis and HPLC: characterization was performed using by NMR, FTIR spectroscopy, analysis of nanoparticle trajectories, and dynamic light scattering.

#### 2.2.2. Dynamic Light Scattering (DLS)

The particle sizes and zeta potentials were measured using a Zetasizer Nano S «Malvern» (Worcestershire, UK) (4 mW He–Ne-laser, 633 nm, scattering angle 173◦). The experiment was performed in a temperature-controlled cell at 25 ◦C. Autocorrelation functions of intensity fluctuations of light scattering were obtained using the correlation of the Correlator system K7032-09 «Malvern» (Worcestershire, UK). Experimental data were processed using «Zetasizer Software» (v. 8.02).

#### 2.2.3. Nanoparticle Tracking Analysis (NTA)

Determination of the hydrodynamic diameter of the synthesized polymers was carried out by NTA using a Nanosight LM10-HS device (Great Britain). Samples were diluted with MilliQ purified water to a concentration of 107–109 particles/mL and kept in an ultrasonic bath for 30 s. The hydrodynamic diameter was determined by the Stokes– Einstein equation relating to the analysis of the trajectory of the Brownian motion of particles. Each sample was measured three times. The hydrodynamic diameter of the particles was also determined using the method of dynamic light scattering.

#### *2.3. Drug Loading*

Loading of model fluorophores-antibiotics and adjuvants (eugenol) into HPCD-PEI1.8 delivery systems was carried out by 2-h incubation at 50 ◦C (0.005 M HCl)—a five–fold mass excess of polymer over the drug.

#### *2.4. FTIR Spectroscopy Studying of the Antibiotic's Actions on E. coli or CD206+ Macrophages Cells*

*Escherichia coli* JM109 cells (overnight culture in liquid nutrient medium Luria–Bertani (pH 7.2), 10<sup>8</sup> CFU) were washed twice with 0.01 M sterile PBS from the culture medium by centrifuging (Eppendorf centrifuge 5415C, 10 min, 12,000× *g*). Cell suspensions (10<sup>7</sup> CFU/mL) were incubated with antibiotic samples; then, after 1-2-12-24 h, the cell's samples were suspended and aliquots of 0.5 mL were taken. The cells are precipitated by centrifugation and separated from the supernatant, washed twice, and resuspended in 50 μL PBS to register the IR spectra. The supernatant is separated to determine the amounts of unabsorbed substances. ATR-FTIR spectra of cells samples suspension were recorded using a Bruker Tensor 27 spectrometer equipped with a liquid nitrogen-cooled MCT (mercury cadmium telluride) detector. Samples were placed in a thermostatic cell BioATR-II with a ZnSe ATR element (Bruker, Bremen, Germany). The FTIR spectrometer was purged with a constant flow of dry air (Jun-Air, Michigan, USA). FTIR spectra were acquired from 900 to 3000 cm−<sup>1</sup> with 1 cm−<sup>1</sup> spectral resolution. For each spectrum, 50–70 scans were accumulated at a 20 kHz scanning speed and averaged. Spectral data were processed using the Bruker software system Opus 8.2.28 (Bruker, Bremen, Germany), which includes linear blank subtraction, baseline correction, differentiation (second order, 9 smoothing points), min-max normalization, and atmosphere compensation. When necessary, 11-point Savitsky–Golay smoothing was used to remove noise. Peaks were identified by the standard Bruker picking-peak procedure. The concentration of Rif inside the cells was calculated from the material balance considering the unabsorbed Rif by UV-vis spectroscopy.

#### *2.5. Macrophages Cell Lines*

For the macrophage phagocytose assay, a human monocyte cell line THP-1 was used. Cells were obtained from the bank of cell lines at Lomonosov Moscow State University. THP-1 cells were cultured on T25 flasks in 5 mL RPMI-1640 (Gibco, Carlsbad, CA, USA), supplemented with GlutaMAX™ supplement (Gibco, Carlsbad, CA, USA) and buffered with 10 mM HEPES pH 7.4 containing 10% heat-inactivated FBS (Gibco, Carlsbad, CA, USA) and 1% antimycotic antibiotic (HyClone) at 37 ◦C and 5% CO2. To derive macrophage-like cells, THP-1 cells were seeded on 6-well plates in 2 mL of RPMI-1640 (Gibco, Carlsbad, CA, USA), supplemented with GlutaMAX™ supplement (Gibco, Carlsbad, CA, USA) and buffered with 10 mM HEPES pH 7.4 containing 10% heat-inactivated FBS (Gibco, Carlsbad, CA, USA) and 1% antimycotic antibiotic (HyClone) with the addition of 100 nM phorbol 12- myristate 13-acetate (PMA, p8139, Sigma Aldrich, St. Louis, MI, USA) for 72 h. After 72 h, the medium containing PMA was replaced with RPMI-1640 (composition described above) without PMA and cells were cultured for another 96 h.

CD206-evaluation. To block nonspecific binding sites, cells were incubated with a 10% solution of normal goat serum in PBS with 1% bovine serum albumin BSA for 1 h at RT. Then, the samples were incubated with a solution of anti-CD206 antibodies (ab64693, Abcam, 1:100) or rabbit polyclonal control IgG (910801, Biolegend) as a control for 2 h at RT and subsequently with goat-anti-rabbit antibody conjugated with Alexa594 (A11037, Invitrogen, 1:1000). The nuclei were labeled with DAPI (Sigma-Aldrich, St. Louis, MO, USA). Samples were analyzed with a Leica DM6000B fluorescent microscope equipped with a Leica DFC 360FX camera (Leica Microsystems GmbH, Wetzlar, Germany).

#### *2.6. Confocal Laser Scanning Microscopy*

*Escherichia coli* JM109 cells (overnight culture in liquid nutrient medium Luria–Bertani (pH 7.2), 108 CFU) were centrifuged twice (Eppendorf centrifuge 5415C, 10 min, 12,000× *<sup>g</sup>*) and washed with 0.01 M PBS from the culture medium. Next, the cells were incubated for 60 min at 37 ◦C with 1 μg/mL of eosin-5-maleimide solution followed by twice-washing. Macrophages (CD206+ human monocyte cell line THP-1) placed in a 96-well fluorescent plate (Costar) were incubated for 1 h with eosin-labeled bacteria followed by washing (10 min, 4000× *g*). Samples (Dox in free form and with FITC-labeled delivery systems) were added to macrophages with absorbed *E. coli*. The cells were centrifuged twice with PBS washing (10 min, 4000× *g*). The cell centrifuge was suspended in 200 μL of PBS, followed by the addition 100 μL of a 5% agarose solution at 45 ◦C to solidify the cell suspension in the wells of a fluorescent plate. Fluorescence images were obtained by the confocal laser scanning microscope (CLSM) Olympus FluoView FV1000 equipped with both a spectral version scan unit with emission detectors and a transmitted light detector. CLSM is based on the motorized inverted microscope Olympus IX81. Emission fluorescence spectra of FITC (drug delivery system labelled), eosin (*E. coli* labelled), and Dox was obtained by CLSM. The excitation wavelength 488 nm (multiline Argon laser) and dry objective lens Olympus UPLSAPO 40X NA 0.90 were used for the measurements. Laser power, sampling speed, and averaging were the same for all image acquisitions. The scan area was <sup>80</sup> × <sup>80</sup> <sup>μ</sup>m2. FITC, Eosin, and Dox fluorescence was collected using the emission windows set at 505–540, 540–575 nm, and 575–675, respectively, at 488 nm excitation. The signals were adjusted to the linear range of the detectors. Olympus FV10 ASW 1.7 software was used for acquisition of the images. FITC fluorescence is shown in green, Dox is red, Eosin is magenta, and the image on the light is gray.

#### *2.7. Dox, FITC-Labelled Ligand, and Eosin-Labelled E. coli Determination Macrophage Uptake*

Quantitative analysis of Dox, FITC-labelled ligand (as in paper [50]), and eosin-labelled *E. coli* (Section 2.6) content in CD206+ macrophages was performed using fluorescence spectroscopy. λexci (Dox or FITC) = 490 nm. λexci (eosin) = 515 nm. λemi (Dox) = 595 nm, λemi (eosin) = 560 nm, λemi (FITC) = 520 nm. Registration of fluorescence spectra was carried out using a SpectraMax M5 device (Pennsylvania, USA) in the Costar black/clear bottom tablet (96 wells). T = 25 ◦C. The concentration of Dox, FITC, and eosin inside the cells was calculated from the material balance considering the unabsorbed fluorophore's concentration determined by fluorescence intensity. Intracellular concentrations of fluorophores were determined after destruction of macrophage cells by 10-min incubation with 1% Triton X-100 solutions.

#### *2.8. Antibacterial Activity of Rif*

The strain used in this study was *Escherichia coli* JM109 (J.Messing, USA). The culture was cultivated for 18–20 h at 37 ◦C to CFU ≈ 1.5 × 108–2 × <sup>10</sup><sup>8</sup> (colony-forming unit, determined by A600) in the liquid nutrient medium Luria–Bertani (pH 7.2) without stirring. The experiments in liquid media were conducted by adding 50 μL of the samples in 5000 μL of cell culture. The specimens were incubated at 37 ◦C for seven days. At the specific time, 100 μL of each sample was taken, diluted with distilled water, and the absorbance was measured at 600 nm. For quantitative analysis, the dependences of CFU (cell viability) on the concentration of Rif, 50 μL of each sample was diluted 105–109 times and seeded on the Petri dish. Dishes were placed in the incubator at 37 ◦C for 24 h. Then, the number of the colonies (CFU) was counted.

#### *2.9. Statistical Analysis*

A statistical analysis of the obtained data was carried out using the Student's *t*-test Origin 2022 software (OriginLab Corporation, Northampton, MA, USA). Values are presented as the mean ± SD of three experiments (three replicates).

#### **3. Results and Discussion**

#### *3.1. FTIR Spectroscopy of E. coli—Drug Interaction's Tracking*

FTIR spectroscopy can be effectively used to monitor the molecular details of the interactions of medicinal preparations with cells. In the cell, it is possible to distinguish the main structural units that contribute to the absorption of IR radiation (Figure 1): cell membrane lipids (2800–3000 cm<sup>−</sup>1), proteins, especially transmembrane (1500–1700 cm−1), DNA phosphate groups (1240 cm−1), and carbohydrates, including lipopolysaccharides (900–1100 cm<sup>−</sup>1). The main fluctuations of bonds in the structural units of E. coli cells were: 2960–2850 cm−<sup>1</sup> CH, CH2, CH3 in fatty acids, 1655–1637 cm−<sup>1</sup> amide I bands (α-helical and β-pleated sheet structures), 1548 cm−<sup>1</sup> amide II band, 1515 cm−<sup>1</sup> aromatic band, 1465–1470 C–H deformation, 1310–1240 cm−<sup>1</sup> amide III band components of proteins, 1250–1220 and 1084–1088 cm−<sup>1</sup> P=O stretching of PO2 <sup>−</sup> − phosphodiesters, and 1100–900 cm−<sup>1</sup> C– O–C, C–O of saccharide ring vibrations [23]. The IR spectrum of lipids and phospholipids has the following characteristic peaks of functional groups: two bands of symmetric and asymmetric vibrations of hydrocarbon bonds, vibrations of the carbonyl group C=O, and vibrations of the phosphate (Figure 1). The position of the bands and their shape are sensitive to binding of the bilayer with ligands or drug molecules, hydrogen bond formation, aggregation, and oxidation, etc. [64].

**Figure 1.** FTIR spectra of *E. coli* cells suspension in water. T = 22 ◦C.

To enhance the antibiotics efficiency, we used polymer nanoparticles HPCD-PEII1.8 triMan (polyethyleneimines grafted with cyclodextrins and with a carbohydrate labels on CD206 macrophage receptors (Table 1), as well as an adjuvant (on the example of eugenol), which inhibits the pumping of drugs from cells and increases bioavailability [6,50].


**Table 1.** Characteristics of drug delivery systems and their affinity to mannose receptor.

\* FITC-labeled ligands were used only for experiments with macrophages. \*\* n is the number of carbohydrate labels. \*\*\* by NTA. \*\*\*\* by DLS.

Rif and EG are only poorly soluble in water, so they need to be included in the delivery system, and the simplest is methyl-cyclodextrin (MCD). Further, the authors use cyclodextrin to prove the effectiveness of polymeric conjugates grafted by CD vs. simple cyclodextrin. Figure 2 shows the difference FTIR spectra (the spectrum is subtracted at zero time) of *E. coli* cell suspensions incubated with free Rif, Rif as part of a molecular container, EG in the form of an inclusion complex with β-cyclodextrin, and a combined formulation of antibiotic and adjuvant loaded into the delivery system. The aim of the experiment is to study the influence of the concentration of substances and the incubation time with cells on the changes in IR spectra of the cells, in other words, how the interaction of drugs and polymers with bacteria and macrophages is reflected on the spectra. The most pronounced changes are observed in the absorption bands of amides 1 and 2 (1600–1700 and 1500–1600 cm<sup>−</sup>1), oscillations of CH2 groups (2800–3000 cm<sup>−</sup>1), as well as in the region of 1240 cm−<sup>1</sup> (PO2 <sup>−</sup> phospholipids and DNA) and 1000–1100 cm−<sup>1</sup> (C-O-C carbohydrates).

**Figure 2.** Difference FTIR spectra of *E. coli* incubated with rifampicin (Rif) or/and eugenol (EG) drug formulations. The spectra at the zero moment of time are subtracted. T = 22 ◦C.

Changes in the W1 region (Figures 1 and 2) correspond to a change in the structural organization of the membrane and the accumulation of an antibiotic or EG inside the cells. For free Rif (Figure 2) in the first hour, there is a significant (*p*-value = 0.014) decrease in the intensity of ATR in W1, which indicates the incorporation of hydrophobic Rif molecules into the bacterial membrane (disordering of lipids). After 2 h of incubation, the antibiotic has already begun to accumulate inside the cells (the difference intensity in the IR spectrum decreases dramatically in the W1 region), which correlates with the data that the Rif penetrates into cells after 2–3 h (Figure 3). After 24 h, the antibiotic was eliminated by more than 70% cells (Figure 3), most probably because of efflux (quantitative determination of efflux was carried out by us earlier) [6]. The Rif concentration and ability to interact with transmembrane proteins correlate with the intensity of amide peaks 1 and 2 (Figure 2).

**Figure 3.** Intracellular (*E. coli*) concentrations of Rif pre-incubated with cells in the form of various formulations: free form, in the delivery system, and enhanced with the adjuvant (EG).

The inclusion of antibiotics in the delivery system to CD206+ macrophages (without EG) leads to significant (*p* < 0.003) effects on the accumulation of drugs inside cells (Figure 3). Accelerated drug absorption compared to free form is observed: (1) owing to the adsorption of polymer particles on the membrane surface (0.004–0.009 ATR vs. 0.001–0.004 in W2) and (2) owing to the occurrence of local defects in the membrane and increased penetration of the drug into the bacteria. In addition, the prolonged action of Rif in the delivery system is achieved, which can be observed by the changed in the intensity of amide 1 (Figure 2, top row). After 12–24 h, free Rif is characterized by a low intracellular concentration (Figure 3), and the drug in polymer particles is still working for 2–4 days [65,66]. The FTIR spectra of *E. coli* incubated with drug delivery system HPCD-PEI1.8-triMan itself are presented in Figure S1; the observed increase in intensity in the W2 region indicates the polymer carrier interacts with transmembrane proteins.

The interaction of EG–MCD (efflux inhibitor and enhancing membrane permeability agent [6]) with bacterial cells (Figure 2, bottom row) leads to: (i) inhibition of efflux pumps (as can be judged from increase in the intensity of amides 1 and 2) and (ii) the creation of defects (earlier was shown using CLSM [6]), which is reflected in a decrease W1 FTIR intensity and increase W3, corresponding to DNA and phospholipids). This explains the synergy of EG with antibiotics: we previously showed for levofloxacin and moxifloxacin enhancing antibacterial activity and we found enhanced absorption by CLSM in the sample with EG [6,20,50,63]. Similar effects are observed here for rifampicin by FTIR. The greatest effect is achieved for the combined antibiotic and adjuvant system in a polymer carrier (Figure 2, bottom row): strong amplification of W2 and W3 peaks, which correlates with blocking of efflux and high intracellular Rif concentration (Figure 3).

The changes discussed above in the FTIR spectra of *E. coli* when interacting with antibacterial agents reflect the accumulation of Rif inside cells (Figure 3). The concentration of free Rif does not exceed 1.5 μg/mL (calculated from the material balance considering the unabsorbed Rif by UV-VIS spectroscopy) and drops after 2–4 h of incubation. However, in the complex polymeric formulation, the penetration of the antibiotic is much more effective: a concentration of >2.5–3.5 μg/mL is achieved and, moreover, it is maintained at >2 μg/mL for 72 h.

#### *3.2. FTIR Spectroscopy of E. coli in CD206+ Macrophages—Drug Interaction's Monitoring*

The CD206 mannose receptor is of greatest interest, which is involved in the recognition of pathogens stemming from the interaction of protein-binding domains with oligosaccharide patterns of microorganisms (*Candida albicans*, *Pneumocystis carinii*, *Leishmania donovani*, *Mycobacterium tuberculosis*, *Klebsiella pneumoniae*, etc.) [67,68]. The CD206 receptor mainly allows for targeting activated macrophages, in which resistant and dormant infections can accumulate. Selectivity toward micro-organisms is achieved because of the specificity of CD206 to mannose, fucose, and N-acetylglucosamine residues, which often cover the surface of pathogen cells, unlike mammals [31,41,49,56,69].

As shown above, the HPCD-PEI1.8-triMan molecular container and eugenol adjuvant enhance Rif penetration into bacterial cells and cause prolonged action according to FTIR spectroscopy data. Pathogens are least accessible when they localized in macrophages, so it is necessary to deliver antibacterial agents to macrophages, for example through the CD206 receptor.

Figure 4 shows the FTIR spectra of CD206+ macrophages with bacteria absorbed by them. We studied the interaction of macrophages with polymer carriers with three carbohydrate vectors of different affinity to CD206 (galactose—with low affinity to CD206, mannose with medium affinity and high affinity trimannoside vector), as well as the use of the EG adjuvant using FTIR spectroscopy, orthe effect of phagocytosis on the spectra. As shown earlier by flow cytometry [6,50] and confirmed here with FTIR spectroscopy (Figure 4), macrophages phagocytize polymer particles mainly with a high-affinity vector (triMan). Changes in the membrane of macrophages and E. coli are reflected in the region of 3000–2850 cm−1: the highest intensity means increased phagocytic activity and, consequently, greater accessibility for bacterial cells, which is further confirmed by an increase in the intensity of the peak of 1150–1000 cm−<sup>1</sup> corresponding to the number of polymers adsorbed on *E. coli* and absorbed by macrophages. The CD206+ dependent binding of drug delivery systems to macrophages is confirmed by quenching peaks of amides 1 and 2, which is typical only for mannose-labeled polymers. Eugenol additionally enhances the accumulation of only high-affinity ligands (bottom row, Figure 4—amide region 1 and 2) and thereby increases the selectivity of the developed HPCD-PEI1.8-triMan carriers.

#### *3.3. CLSM of E. coli in CD206+ Macrophages—Drug Interaction's Visualization*

To clarify the action mechanisms of polymeric carriers and adjuvant, CLSM and fluorescent studies of the drugs interaction with bacteria were carried out. We made a model system of macrophages with absorbed *E. coli*, which are colored with eosin, to study phagocytosis by macrophages of FITC-labeled HPCD-PEI1.8-triMan loaded with the fluorophore—antibiotic doxorubicin (Dox).

We studied three groups of samples:

(1) Control Dox to study the penetration and accumulation of free drug in macrophages and inside bacterial cells;

(2) Dox in a polymeric ligand (with different CD206-affinity labels: non-specific galactose, medium-affine mannose and high-affine triMan) to study macrophage phagocytosis

activity and the effect of polymer on the adsorption efficiency on the bacterial cells and penetration of Dox;

(3) Dox in a polymeric ligand enhanced with EG as an agent enhancing the membrane permeability and efflux inhibitor.

The assignment of fluorescence signals (Dox, eosin, and FITC) is based on the fluorescence spectra of substances in the systems under consideration (Figure S2, Method section). Confocal images of macrophages with insider bacteria are shown in Figure 5 and S3. On confocal images, large macrophages can be observed, inside of which *E. coli* are highlighted in pink, in which Dox accumulates asred dots.

**Figure 4.** FTIR spectra of CD206+ Macrophages with absorbed E. coli incubated with drug delivery systems with different carbohydrate vectors and eugenol-enhanced formulations.

Free Dox accumulates weakly in macrophages and inside *E. coli* (Figure 5a). Dox is released from the bacteria by pumping proteins in a process of efflux, and macrophages, in principle, poorly absorb small drug molecules.

The effect of adjuvant EG (Figure 5b) *on the accumulation of Dox.* An increase in the degree of Dox accumulation in bacterial cells in macrophages is observed. EG acts in two directions: creates defects in the membrane and inhibits pump proteins, as we showed in the last article [6].

The effect of drug delivery systems on the accumulation of Dox (Figure 5c–e). CD206 positive cells effectively phagocytosed predominantly high-affinity polymeric conjugate with trimannoside HPCD-PEI1.8-triMan, but not conjugate with linear galactose, which follows from the intensity of macrophage-associated fluorescence in the FITC channel (green). The label of linear mannose on the conjugate is medium effective. Inside the macrophages, colored dots are visible (in all channels), corresponding to the bacteria on which the polymer is adsorbed. Owing to the high penetration of HPCD-PEI1.8-triMan into macrophages, the accumulation of Dox in *E. coli* is very high, relative to control samples (Dox). Earlier, our cytometry assay determined that 80% of macrophage-like cells were FITC-positive after adding HPCD-PEI1.8-triMan, 60% were FITC-positive after adding HPCD-PEI1.8-Man, and 15% were FITC-positive after adding HPCD-PEI1.8-Gal [50]. Therefore, the data on CLSM and FTIR correlate with the flow cytometry data.

**Figure 5.** *Cont*.

**Figure 5.** *Cont*.

**Figure 5.** *Cont*.

**Figure 5.** *Cont*.

**Figure 5.** Confocal laser scanning images of CD206+ macrophages with absorbed eosin-labelled *E. coli*.

Incubation 2 h with Dox 10 μg/mL and FITC-labeled HPCD-PEI1.8. Dox 10 μg/mL: (**a**) free, (**b**) with 1 mg/mL EG, (**c**) in FITC-labelled HPCD-PEI1.8-Gal, (**d**) in FITC-labelled HPCD-PEI1.8-triMan, (**e**) in FITC-labelled HPCD-PEI1.8-Man, (**f**) in FITC-labelled HPCD-PEI1.8-triMan with 1 mg/mL EG. The scale segment is 100 μm (division value is 20 μm); 4–6 channels are shown: red, Dox; green, FITC; magenta, eosin; gray, transmission light mode; and overlay. λem = 488 nm (multiline Argon laser).

The synergy effect antibiotic and adjuvant, loaded into polymeric nanoparticles (Figure 5f and S3). Dox in combination with eugenol, which enhances penetration through cell membranes and inhibits drug pumping, accumulates 10 times more efficiently than a simple substance in the composition of high-affinity conjugates to CD206+ macrophages. Thus, the complex formulation antibiotic and adjuvant in a drug delivery system is a perfect approach to accumulate the drug in the target macrophages with pathogenic bacteria.

In summary, by using CLSM and FTIR, we were able to distinguish bacteria inside macrophages, and showed how ligands penetrate into macrophages and thereby increase the accumulation of drugs inside bacteria.

Thus, confocal microscopy confirms the data of FTIR spectroscopy in the terms of enhancing the permeability of the bacterial membrane to the drug caused by polymers and adjuvants (efflux inhibitors) and phagocytosis by macrophages. Therefore, spectral changes are confirmed visually and quantitatively (Section 3.4. Table 2).


**Table 2.** The amounts of Dox and FITC-labeled carrier absorbed by macrophages with E. coli inside. Fluorescence detection (Method section). T = 22 ◦C.

#### *3.4. Quantitative Data on the Penetration of Drugs into Macrophages with E. coli*

Table 2 presents quantitative data on the absorption of Dox and FITC-labeled conjugates (determined based on the material balance of extracellular and intracellular concentrations in macrophages after lysis with 1% Triton X-100, fluorescent detection). The data on ligand uptake correlate with those previously obtained by flow cytometry: the carrier with the trimannoside vector is absorbed by cells by more than 60–70%, and galactose-labeled by only 10–15%. Thus, owing to polymer ligand and adjuvants (eugenol or its analogues), it is possible to increase the accumulation of Dox inside macrophages by more than three times. Taking into account the previously obtained values for isolated *E. coli* [6], the accumulation of Dox directly in the bacteria increased by more than 10 times (it implies the total effect of enhanced penetration into macrophages x 3–4 and then in *E. coli* inside macrophages × 3).

#### *3.5. Rif Antibacterial Activity on E. coli*

Using FTIR spectroscopy, changes in cells during incubation with drugs have been demonstrated—therefore, it is important to show how these data correlate with antibacterial activity. The antibacterial activity of Rif in a free form and in the composition of molecular containers and enhanced with eugenol demonstrates correlations between the observed effects using spectral and optical methods and what is actually observed in a microbiological experiment. Figure 6 shows the curves of the survival of *E. coli* bacterial cells on the incubation time with various forms of Rif in comparison with the control (without the addition of an antibiotic). Apparently, polymers accelerate the penetration of antibiotics into cells because of the adsorption of polysaccharides on the cell wall surface. According to the data on CFU and the turbidity of the cell suspension (A600), the HPCD-PEI1.8 triMan polymer itself does not affect cell growth, and the Rif efficiency practically does not increase when incorporated into cyclodextrin (MCD); however, when loaded into the polymer system, the efficiency increases significantly (0.5–1 CFU order). Eugenol in the form of a complex with MCD demonstrates antibacterial activity; however, it is not bright in itself. At the same time, eugenol acts as a synergist as an adjuvant to the antibiotic Rif, so cell growth is quickly suspended, and the number of viable cells falls. Previously, the synergism of antibiotics (moxifloxacin and levofloxacin) with eugenol, menthol, and apiol was demonstrated by us [20,63,70]. Thus, the complex formulation of antibiotic and booster adjuvant in the delivery system with active targeting function is a promising combination for the possible strengthening of existing therapies.

Thus, the correlations of the antibacterial activity of therapeutic agents with the observed effects in the FTIR spectra and visually in a confocal microscope are demonstrated. Optical methods are applicable for the diagnosis and optimization of the treatment of bacterial infections.

**Figure 6.** *Cont*.

**Figure 6.** Antibacterial activity of Rif (1 μg/mL) in free form and loaded into HPCD-PEI1.8-triMan, enhanced with eugenol (0.1 mg/mL): (**a**) absorbance of samples (in terms of the diluted samples (absorption was determined in aliquots diluted 4–10 times)) correlated with CFU, and (**b**) CFU dependences determined by quantitative seeding on petri dishes. Rif: polymer mass ratio = 1:10. pH 7.4 (0.01 M PBS), 37 ◦C.

#### **4. Conclusions**

Visualization of the action of therapeutic agents at the molecular level seems to be a powerful way to find out the points of increasing the effectiveness of antibacterial drugs, and in the future, cytostatic ones. The methods of FTIR spectroscopy and confocal microscopy are potentially applicable for the diagnosis of latent infections localized in macrophages, such as pneumonia, tuberculosis, and mycoplasma. Using FTIR spectroscopy, it was shown that the accumulation of rifampicin in model *E. coli* cells increases with the use of polymeric molecular containers and adjuvants that inhibit efflux and increase membrane permeability. The penetration of the model fluorophore antibiotic doxorubicin into CD206+ macrophages with *E. coli* localized in them was visualized using CLSM. The efficiency of phagocytosis of polymer drug carriers by macrophages depending on the carbohydrate label (galactose, mannose, trimannoside) was compared. The developed delivery systems increase the effectiveness of the therapeutic agent (Dox or Rif) by more than 10 times (it implies the total effect of enhanced penetration into macrophages ×3–4 and then inside macrophages in *E. coli* ×3). Thus, we presented the potential of practical application of optical and spectral methods (FTIR + CLSM) in aspects of drug study and possible diagnosis of diseases.

**Supplementary Materials:** The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/diagnostics13040698/s1, Figure S1. FTIR spectra of *E. coli* incubated with drug delivery system HPCD-PEI1.8-triMan. T = 22 ◦C. Figure S2. Emission fluorescence spectra of FITC (drug delivery system labelled), eosin (*E. coli* labelled), and Dox obtained by CLSM. λem = 488 nm (multiline Argon laser). **Figure S3**. Confocal laser scanning images of CD206+ macrophages with absorbed eosin-labelled *E. coli.* Incubation with Dox and FITC-labeled

HPCD-PEI1.8-triMan. The scale segment is 100 μm (division value is 20 μm); 4–6 channels are shown: red, Dox; green, FITC; magenta, eosin; gray, transmission light mode; and overlay λem = 488 nm (multiline Argon laser).

**Author Contributions:** Conceptualization, I.D.Z. and E.V.K.; methodology, I.D.Z., A.A.E. and E.V.K.; software, M.A.V., N.G.B., U.D.D. and O.A.G.; formal analysis, I.D.Z. and A.A.E.; investigation, I.D.Z., A.A.E., N.G.B., M.A.V., U.D.D. and O.A.G.; data curation, I.D.Z.; writing—original draft preparation, I.D.Z.; writing—review and editing, E.V.K.; project administration, E.V.K.; funding acquisition, E.V.K. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the Russian Science Foundation, grant number 22-24-00604.

**Institutional Review Board Statement:** All procedures with the involvement of animals complied with the ethical standards approved by the legal acts of the Russian Federation, the principles of the Basel Declaration, and the recommendations of the Bioethics Committee at Lomonosov Moscow State University.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The data presented in this study are available in the main text and Supplementary Materials.

**Acknowledgments:** The work was performed using equipment (FTIR spectrometer Bruker Tensor 27, Scanning probe microscope NT-MDT and Jasco J-815 CD Spectrometer) of the program for the development of Moscow State University.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **Abbreviations**


#### **References**


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## *Article* **Assessment of Blood Microcirculation Changes after COVID-19 Using Wearable Laser Doppler Flowmetry**

**Elena V. Zharkikh 1,\*, Yulia I. Loktionova 1, Andrey A. Fedorovich 1,2, Alexander Y. Gorshkov <sup>2</sup> and Andrey V. Dunaev <sup>1</sup>**


**Abstract:** The present work is focused on the study of changes in microcirculation parameters in patients who have undergone COVID-19 by means of wearable laser Doppler flowmetry (LDF) devices. The microcirculatory system is known to play a key role in the pathogenesis of COVID-19, and its disorders manifest themselves long after the patient has recovered. In the present work, microcirculatory changes were studied in dynamics on one patient for 10 days before his disease and 26 days after his recovery, and data from the group of patients undergoing rehabilitation after COVID-19 were compared with the data from a control group. A system consisting of several wearable laser Doppler flowmetry analysers was used for the studies. The patients were found to have reduced cutaneous perfusion and changes in the amplitude–frequency pattern of the LDF signal. The obtained data confirm that microcirculatory bed dysfunction is present in patients for a long period after the recovery from COVID-19.

**Keywords:** laser doppler flowmetry; wearable blood perfusion sensors; COVID-19; SARS-CoV-2; rehabilitation; blood perfusion; blood flow oscillations; wavelet analysis

#### **1. Introduction**

The propagation of coronavirus infection, also known as COVID-19, has caused a huge number of illnesses and deaths. To date, there have been more than 650 million confirmed cases of SARS-CoV-2 infection and more than 6 million deaths worldwide (according to the Johns Hopkins University Coronavirus Resource Center). Three years after the first reported cases of SARS-CoV-2 infection, the pandemic is still far from being over. Despite the development and widespread implementation of vaccines and containment measures, COVID-19 still has a significant impact on the lives of millions of people worldwide. Emerging evidence suggests a close link between severe clinical COVID-19 and an increased risk of its vascular complications, such as thromboembolism [1]. Approximately 40–45% of cases are asymptomatic with SARS-CoV-2, but clinical observations suggest that complications may occur even in the asymptomatic course of the disease [2].

Although COVID-19 was originally considered a respiratory disease, it has now been established that it affects multiple organs and systems, including the cardiovascular system, gastrointestinal system, brain, kidney, liver, skeletal muscle, and skin of infected patients [3,4]. Recently, there is increasing evidence of the negative impact of this disease on the microcirculatory system of the blood [5–7]. It is known that SARS-CoV-2 affects the microcirculatory bed, causing edema and damage to endothelial cells, affects the development of microthrombosis, and capillary blockage, and causes a variety of other negative effects [8]. The development of these disorders, in addition to the direct threat to the patient's life and health, can also be a key factor in the development of long-term consequences of coronavirus infection, significantly reducing the quality of life of patients.

**Citation:** Zharkikh, E.V.; Loktionova, Y.I.; Fedorovich, A.A.; Gorshkov, A.Y.; Dunaev, A.V. Assessment of Blood Microcirculation Changes after COVID-19 Using Wearable Laser Doppler Flowmetry. *Diagnostics* **2023**, *13*, 920. https://doi.org/10.3390/ diagnostics13050920

Academic Editor: Juan Aguirre

Received: 30 December 2022 Revised: 20 February 2023 Accepted: 24 February 2023 Published: 1 March 2023

**Copyright:** © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

Serious concerns are caused by the fact that proinflammatory status and procoagulation activity can remain in patients for a long time after the recovery [9].

Recent observations show that a fairly large proportion of patients who have recovered from a coronavirus infection subsequently suffer long-term effects of the disease [10]. These include symptoms such as weakness, breathlessness, chest, and joint pain, confusion, memory and concentration problems (so-called "brain fog"), mood changes, etc. These and other symptoms can persist for months after the disease itself and significantly reduce patients' quality of life [11]. These disorders are referred to as "long COVID" or post-COVID syndrome. Current research is largely focused on the acute stage of SARS-CoV-2, but ongoing monitoring of the long-term effects of the disease is also necessary. In this context, the need for research into the rehabilitation of patients after coronavirus infection is clear.

There is a significant body of evidence suggesting that cardiovascular complications of coronavirus can also occur in an asymptomatic course [2], making it even more difficult to detect such complications at an early stage. This means that there will be an urgent need for both diagnostic and rehabilitative measures in the next few years for patients who have suffered from this disease. In addition, there are risks of a similar clinical outcome not only with COVID-19 but also with possible future epidemics of respiratory infections. Existing diagnostic methods routinely used in clinical practice do not allow adequate assessment of blood flow at the microcirculatory level. Currently, there is a need to develop new approaches to the diagnosis of microcirculatory disorders occurring in coronavirus infection, as well as to develop strategies for individual therapy and rehabilitation of patients after COVID-19.

Despite the widespread prevalence of the disease and the incidence of cardiovascular complications, as well as the proven extensive involvement of microvasculature in pathological processes, only very few papers have been published to date on the noninvasive assessment of blood microcirculation after COVID-19 [12–14].

One of the most common and applicable methods for diagnosing the state of the blood microcirculation system is laser Doppler flowmetry (LDF) [15,16]. This method is widely used in the diagnosis of complications of diabetes mellitus [17,18], rheumatic diseases [19], hypertension [20] and a number of other socially important diseases. Over the years, different modifications of the conventional laser Doppler technique had been introduced, including several attempts at developing wearable devices [21–23].

In the COVID-19 clinic, the main focus of research using LDF was on studying the dynamic characteristics of blood flow, including the application of functional tests. It has been shown that, during the acute phase of COVID-19, patients demonstrate a reduced vasodilatory response to local heating and reduced microvascular reactivity [24]. The correlations between microcirculatory parameters measured by LDF and laboratory test results of patients during the acute period of the disease were also analysed [25]. Another study using laser speckle contrast imaging technology demonstrated reduced vasodilation in patients with COVID-19 in response to acetylcholine and sodium nitroprusside, which persists for at least 3 months after the disease [26]. We did not find any studies in the English-language literature devoted to spectral analysis of LDF recordings in patients who underwent COVID-19. Since it is known that such analysis provides valuable diagnostic information about the state of systems regulating blood flow, including the nervous system and endothelial function, the present work aimed to fill the gaps in this area.

In this context, this work aimed to comprehensively examine the changes in blood microcirculation that occur both in the acute period of the COVID-19 disease and in the long term during rehabilitation procedures.

#### **2. Materials and Methods**

#### *2.1. Experimental Equipment*

A distributed system consisting of 4 wireless wearable microcirculatory blood flow analysers implementing LDF method "LAZMA PF" (LAZMA Ltd, Russia; in EU/UK this device made by Aston Medical Technology Ltd., UK as "FED-1b") was used for data recording in this study [27–29]. These analysers use VCSEL die chips (850 nm, 1.4 mW/3.5 mA, Philips, The Netherlands) as a single-mode radiation source. The analysers are implemented without optical fibres with direct skin irradiation from a window at the back of the instrument. This allows for avoiding fibre coupling losses as well as decreasing the movement artefacts which are common in fibre-based LDF monitors. The devices operate autonomously on internal battery power and transfer the measured signal via Bluetooth and/or Wi-Fi. The devices also have built-in motion and temperature sensors to eliminate the possible influence of motion artefacts and temperature changes on the recorded signal. When processing motion sensor data, recordings simultaneous with the subject's movements are identified as potential sources of distortion of the LDF gram and filtered using special software. The appearance of the analysers (left) as well as the options for mounting them on the volunteer's hands (right) are shown in Figure 1.

**Figure 1.** The appearance of the analysers (**left**) and the options for mounting them on the volunteer's hands (**right**).

#### *2.2. Experimental Protocol*

The present study comprised 2 phases. The first stage involved a dynamic assessment of the processes occurring in the blood microcirculatory system during the acute period of coronavirus infection. During routine daily LDF measurements, an 18-year-old male patient was found to be accidentally infected with SARS-CoV-2 (confirmed by PCR analysis of nasopharyngeal swabs). The patient had not been vaccinated against COVID-19 prior to the study nor did he have previous experience with COVID-19. The measurements were carried out in the supine position, each lasting for 10 min. To record signals, analysers were attached to the pads of the third fingers and big toes, as well as on the dorsal surfaces of the wrists and the inner parts of the upper third of the shins. The positioning and attachment of wearable devices on the patient's body during the study are shown in Figure 2. The measurements were taken 10 days before the onset of the disease and during 26 days after the recovery. No measurements were taken during the acute phase of the disease (7 days) because of the patient's poor well-being. A total of more than 170 LDF signals were measured and processed over the entire study period for this patient.

**Figure 2.** Location of the analysers on the patient's body during the study: on fingers (**A**), toes (**B**), wrists (**C**) and shins (**D**). The device attachment positions are indicated by red areas.

The second phase of the study involved the comparison of blood microcirculation parameters measured by LDF in a group of patients undergoing rehabilitation procedures after COVID-19 and a group of conditionally healthy volunteers with no previous history of coronavirus infection. The main group consisted of 23 subjects who had long COVID symptoms for a prolonged period of time after the recovery from an acute coronavirus infection and were undergoing rehabilitation in a private healthcare facility. Three of them had had a severe COVID-19 infection; all the other patients experienced moderate symptoms of COVID-19. Patients in the main group were measured between 1 and 6 months after the recovery. The mean age of the main group was 58 ± 9 years. The control group included 13 conventionally healthy volunteers of a matching age who were measured in 2019 before the pandemic spread, suggesting that the volunteers in the control group had never encountered COVID-19. Volunteers with any history of cardiovascular or other serious chronic diseases affecting the circulatory system were excluded from the study. The study was conducted with the subject in the supine position in a relaxed state and consisted of a 10-min measurement of microcirculation using a wearable LDF device ("LAZMA-PF"). The analysers were attached to the dorsal surface of the forearms at a point 2 cm above the styloid process and on the inside of the upper third of the shins (see Figure 2C,D) as these points proved to be the most informative from the previous stage of the study. Figure 3 shows a diagram of the experimental design of the study.

**Figure 3.** A diagram of the experimental design.

#### *2.3. Data Analysis*

In the present study, the analysed parameters were the value of the index of blood microcirculation—*Im* and amplitudes of blood flow oscillations in the different frequency bands corresponding to different mechanisms of microcirculatory blood flow regulation, measured in relative perfusion units (p.u.) [30]. The endothelial (*Ae*) band (0.005–0.021 Hz) reflects the vascular tone regulation due to the endothelium activity, both NO-dependent and independent; the neurogenic (*An*) band (0.021–0.052 Hz) represents the influence of neural innervation on blood flow; the myogenic (*Am*) band (0.052–0.145 Hz) corresponds to vascular smooth muscle activity; and respiratory (*Ar*) and cardiac (*Ac*) bands (0.145–0.6 Hz and 0.6–2 Hz, respectively) carry information about the influence of heart rate and movement of the thorax on the peripheral blood flow [31,32]. To calculate the amplitude–frequency spectra of the LDF signal, we used a mathematical apparatus of wavelet transform implemented in the software of wireless wearable analysers "LAZMA-PF". This software performs a continuous wavelet transform using the complex-valued Morlet wavelet as the analysing wavelet.

In addition, the parameter of nutritive blood flow (*Imn*), estimated by a well-known algorithm [33], was calculated. The use of this parameter makes it possible to estimate the distribution of blood flow along capillary and shunt vessels.

The statistical analysis of the data was performed in Origin Pro 2021 software. Due to the limited sample size, a non-parametric Mann–Whitney U test was used to check the statistical significance of differences. Values of *p* < 0.05 were considered significant. The results are presented as the mean ± SD unless otherwise indicated.

#### **3. Results**

The first phase of the study demonstrated that COVID-19 results in changes in microcirculatory blood flow regulation mechanisms, which can be measured by assessing the spectral characteristics of the LDF signal. The results of the measurements are shown in Table 1.


**Table 1.** Results of the first part of the study.

\*—The significance of the difference between the values before and after the disease was confirmed with *p* < 0.05 according to the Mann–Whitney U test.

No significant changes were observed in fingers and toes in this measurement. However, there was a general trend towards a decrease in microcirculation after the disease, and also in the magnitude of the nutritive blood flow in the upper extremities. Figure 4 shows box plots of the amplitude of blood flow oscillations for the stages before and after the disease, measured in wrists and shins.

**Figure 4.** Box plots of blood flow oscillation amplitudes measured in wrists (**left panel**) and shins (**right panel**). \*—The significance of the difference between the values was confirmed with *p* < 0.05 according to the Mann–Whitney U test.

A statistically significant decrease in the amplitude of myogenic oscillations was found in the arms after the disease. In the legs, a significant decrease in the amplitudes of respiratory and cardiac oscillations was observed. Similar changes can be traced in the upper extremities, but they do not reach statistically significant levels there. Figure 5 shows the dynamic changes in blood flow oscillations measured in wrists (a) and shins (b).

**Figure 5.** Changes in blood flow oscillations in the wrists (**left**) and shins (**right**) during the course of the disease and recovery.

The figures show that COVID-19 causes high-amplitude changes in the magnitude of endothelial and neurogenic blood flow oscillations immediately after the recovery, which probably caused a high variability of these values at the "After" stage and failure to achieve a statistically significant difference in them when there is a trend for their increase after the disease. These changes are especially pronounced in the upper extremities. In the legs, there is a significant drop in the amplitude of the cardiac oscillations immediately after the disease and of the respiratory oscillations one week after the recovery, which also correlates with the results obtained in the upper extremities.

The results of the second stage of the experimental study were subsequently analysed. Table 2 presents the data obtained from the second stage of the study.


**Table 2.** Results of the second part of the study.

\*—The significance of the difference between the values of control group and patients was confirmed with *p* < 0.05 according to the Mann–Whitney U test.

Both upper and lower extremities show significantly lower values of microcirculation and nutritive blood flow. Whisker boxes for these parameters are shown in Figure 6.

**Figure 6.** Box plots of the index of microcirculation and nutritive blood flow measured in wrists (**left panel**) and shins (**right panel**).\*—The significance of the difference between the values was confirmed with *p* < 0.05 according to the Mann–Whitney U test.

An increase in overall oscillatory blood flow activity was also noted in both upper and lower extremities, with statistically significant differences in the neurogenic, respiratory and cardiac ranges in wrists. Whisker boxes for the respiratory and cardiac oscillations measured in wrists are shown in Figure 7.

**Figure 7.** Box plots of the respiratory and cardiac oscillations measured in wrists. \*—The significance of the difference between the values was confirmed with *p* < 0.05 according to the Mann–Whitney U test.

#### **4. Discussion**

In the present work, we obtained experimental data, which confirm the presence of microcirculatory bed dysfunction for a long period after the recovery from COVID-19. The first part of the study, which included daily measurements of one volunteer for 10 days before his disease and almost a month after the recovery, showed that after a month the parameters did not recover to their original values.

This stage of the studies revealed a decrease in the myogenic activity of microcirculation in the upper extremities. It is worth noting that the changes in the patterns of peripheral blood flow oscillations in the post-COVID phase have not yet been studied in detail. Myogenic oscillations play an important role in the process of oxygen delivery to biological tissues [34]. A decrease in myogenic oscillations leads to an increase in the dynamic resistance of microvessels and, as a consequence, to a decrease in the nutritive blood flow. Combined with the observed decrease in neurogenic regulatory activity, this change may indicate the activation of blood flow shunt pathways. In addition, some studies show that high temperature can inhibit vasomotion [35,36], so the decrease in myogenic activity revealed in our study may be a consequence of the high body temperature of the patient during the period of the disease.

The period immediately after the recovery from COVID-19 in this study was also characterized by decreased values of respiratory and cardiac microcirculatory oscillations in both upper and lower extremities (with significant differences in legs). In this case, dynamic observations show that cardiac fluctuations are reduced immediately after the disease, and respiratory fluctuations change during the week after the recovery.

Another interesting observation of this study was the increased amplitude of endothelial oscillations in the post-COVID phase and the dynamics of these changes. Numerous studies demonstrate endothelial dysfunction as one of the main pathogenic mechanisms of COVID-19 [37,38], which can persist for more than 12 months after the recovery. Studies also show that long COVID-19 symptoms, especially nonrespiratory symptoms, are due to persistent endothelial dysfunction [39]. In our work, we observed increased amplitudes of these fluctuations both in the early stages of recovery from the disease and in the later stages (in the second phase of the study), although these differences did not reach a statistically significant level.

In a group of patients undergoing rehabilitation after COVID-19, the most interesting observation in the amplitude–frequency spectrum of the LDF signal, in our opinion, was an increase in the amplitude of neurogenic oscillations. A decrease in neurogenic tone leads to the dilation of the arterioles [40,41] and, consequently, the amplitude of cardiac oscillations significantly increases (which we can observe in our study).

The lumen size of skin arterio-venous anastomoses (AVA) is regulated exclusively by neurogenic mechanisms, so we can assume that they also expand amidst the decrease of neurogenic tone. The dilation of AVA leads to arterio-venous shunting of the blood bypassing the capillary channel, which explains the significant decrease of *Imn*, a decrease of the number of functioning capillaries [13,14], reduction of perfusion (*Im*) and venular overflow due to arterial blood discharge that in its turn leads to the dilation of venules [40,41] and a significant increase of the amplitude of respiratory-driven blood flow oscillations amplitude.

#### *Study Limitations*

The present study was conducted on a small group of patients, some of whom had comorbidities, so there is no certainty that the results will be true for the broader study population. The data obtained, however, should be taken into account for the development of new diagnostic criteria in assessing the degree of microcirculatory disturbances and rehabilitation processes in recently recovered patients. There is a need for additional studies with a larger group of patients, including patients with different courses of COVID-19 (mild, moderate, and severe disease).

Despite the already three-year history of coronavirus infection and the undoubted advantages of the LDF method for diagnosing microcirculatory disorders, there are almost no studies devoted to spectral analysis of LDF signal in COVID-19 pathology. In this pilot study, we demonstrated the possibilities of laser Doppler flowmetry coupled with the wavelet analysis of the obtained signals to detect microcirculatory disorders in patients who have undergone COVID-19 that makes it a promising tool for future research and assessment of the dynamical changes in microcirculation during the recovery process.

#### **5. Conclusions**

The present work demonstrates the use of laser Doppler flowmetry and peripheral blood flow oscillations analysis to diagnose vascular disorders in patients who have undergone COVID-19 in their early and advanced stages of recovery. Our work demonstrated a significant increase in the amplitude of neurogenic oscillations in the upper extremities of patients undergoing COVID-19, which, as we suggest, may be a factor preceding dilation of arterioles and venules and redirection of microcirculatory blood flow from the nutritive to the shunt pathways.

The obtained data show that optical noninvasive technologies have the potential for further application, but more research is needed to fully understand the changes in the mechanisms of blood flow regulation that occur after an infection.

**Author Contributions:** Funding acquisition, project administration, discussion and writing—review and editing, E.V.Z.; investigation, formal analysis and writing—original draft preparation, Y.I.L.; conceptualization, writing—original draft preparation and discussion, A.A.F.; methodology and formal analysis, A.Y.G.; investigation, supervision, conceptualization, and methodology, A.V.D. All authors edited the manuscript. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was supported by the Russian Science Foundation under Project No. 23-25-00522.

**Institutional Review Board Statement:** The study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics committee of Orel State University (Protocol No. 15 of 21.02.2019).

**Informed Consent Statement:** Informed consent was obtained from all subjects involved in the study.

**Data Availability Statement:** The data presented in this study are available on request from the corresponding author.

**Acknowledgments:** The authors express their acknowledgements to all the volunteers who contributed to the present study. The authors would like to thank the staff of the private treatment and prevention institution "Sanatorium Hilovo" (Pskov region, Russia) and E.V. Shuraeva for their help in organising the experimental studies.

**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study, data collection, analysis and interpretation, writing of the manuscript, or in the decision to publish the results.

#### **References**


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