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Detection of Dermatophytes Using PCR followed by Array Technology; a Validation Study

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03 September 2025

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03 September 2025

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Abstract
Infections of the skin, hair, and nails are frequently caused by dermatophytes, fungi that metabolize keratin, and present as tinea corporis, tinea capitis, tinea pedis, tinea ungui-um, and related conditions. In immunocompetent patients these infections are typically superficial, limited to the epidermis, but may still trigger immune reactions of variable severity. Diagnosis currently relies on culture, which is time-consuming, requiring up to four weeks and skilled microscopy. The Euroarray Dermatomycosis, a PCR-based biochip assay targeting 56 fungal species, offers a markedly shorter turnaround time of 48 hours. We conducted an analytical validation study assessing sensitivity, specificity, accuracy, reproducibility, limit of detection, and linearity. Hair, nail, and skin specimens from healthy donors were spiked with genomic DNA from dermatophytes and yeasts includ-ing Trichophyton, Microsporum, Epidermophyton, Fusarium, Candida, Scopulariopsis, and Nannizzia; plasmids were used for linearity and detection limit testing. The assay demonstrated high sensitivity (91.7–100%) and specificity (100%) across species, repro-ducibility ranging from 88.9–100%, and limits of detection as low as 10–100 copies/ml depending on specimen type and organism, with excellent linearity (R² 0.9677–0.9987). In conclusion, Euroarray Dermatomycosis shows strong analytical performance and has the potential to significantly improve accuracy, reliability, and speed of fungal diagnosis. Furthermore, adopting molecular techniques for dermatophyte detection may facilitate future exploration of resistance mechanisms in fungi, providing earlier insights into emerging antifungal resistance patterns and supporting the development of targeted therapies.
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1. Introduction

Dermatophytes are a group of fungi that hydrolyze keratin, and therefore can infect keratinized structures such as skin, hair, and nails, causing dermatophytoses. In immunocompetent hosts, these infections are generally restricted to the epidermis, yet they may still elicit immune responses of varying severity (1). Major forms include tinea corporis (body, excluding feet, groin, face, scalp, or beard hair), tinea pedis (feet), tinea cruris (groin and upper thighs), tinea faciei (face), and tinea manuum (hands) [2]. Tinea capitis and tinea barbae affect scalp and beard hair, respectively, while tinea unguium (onychomycosis) is the most common nail infection [2]. Although superficial, dermatophytoses require careful clinical and laboratory evaluation. Diagnosis depends on clinical presentation, which varies by infection type. For instance, tinea pedis often presents as pruritic erosions between toes or a “moccasin” distribution on feet, while tinea cruris typically appears as erythematous lesions on the inner thigh. Because patients may harbor multiple infections simultaneously, thorough examination of skin, hair, and nails is essential [2].
Dermatophytes are classified into three main genera: Epidermophyton, Microsporum, and Trichophyton [3]. Their prevalence varies worldwide [4], with higher burdens in warm climates. For example, >70% of children in northern Brazil with dermatophytosis present with tinea capitis [5], while tinea pedis affects over 50% of adults in parts of Europe. Tinea cruris is more common in adults, whereas other types often predominate in children [6]. Globally, 10–15% of the population is expected to experience a dermatophyte infection. Females are more commonly affected, with peak incidence between ages 51–60 [4]. Onychomycosis shows a prevalence of 14% in the United States [7] and 8% in Canada [8].
Traditional diagnosis relies on culture and phenotypic identification. Methods include assessing colony morphology, pigmentation, texture, growth rate, microscopic features, temperature tolerance, and biochemical reactions [9,10]. Culture requires 3–4 weeks of incubation and is prone to contamination and external variability [9,10,11]. This process is time-consuming and demands specialized expertise, potentially delaying reliable identification and treatment [12]. Diagnosis is further complicated in immunocompromised patients, whose presentations may deviate from typical patterns [15]. Recent molecular advances have introduced new approaches, with PCR demonstrating high sensitivity and reproducibility compared to morphology-based methods [11,13].
PCR can generate characteristic DNA polymorphisms using repetitive sequences and gel banding patterns [10,14]. The GACA sequence has proven useful for dermatophyte identification [14], while the chitin synthase 1 [CHS1] gene of Microsporum canis has also shown strong diagnostic potential (13,16). Although PCR improves turnaround time, sensitivity, and specificity, designing primers for each species remains challenging. Multiplex PCR, which amplifies multiple DNA targets simultaneously, enables detection of several organisms from one sample [11]. When combined with microarray technology, this allows identification of numerous dermatophytes within hours. After PCR amplification, microarray hybridization provides a comprehensive profile of detected species [12]. This study will evaluate the clinical application of combined PCR and microarray techniques for the rapid identification of dermatophytoses.
This work highlights how molecular platforms like PCR and microarray, beyond enabling rapid dermatophyte identification, can also be adapted for the detection of antifungal resistance genes. Incorporating resistance gene markers into diagnostic panels would allow earlier recognition of mutations that compromise therapy, ensuring more accurate treatment decisions. Such integration positions dermatophyte testing as a model for broader fungal diagnostics, where simultaneous detection of pathogens and resistance determinants is essential for addressing emerging antifungal resistance.

2. Results

A PCR and microarray-based diagnostic test was evaluated for dermatophyte detection in nail, skin, and hair samples. Each specimen type was tested with dermatophytes typically pathogenic to that source. For nail samples (Table 1), eight dermatophyte species were assessed, and all showed 100% correct detection except for Fusarium oxysporum, which demonstrated only 33.3% accuracy. The overall sensitivity across all species was 96.0%, and 100% when the outlier species was excluded. Skin samples were tested for ten different species; six were detected with 100% accuracy, Trichophyton mentagrophytes quinkeanum at 96.0%, T. mentagrophytes interdigitale and T. equinum at 91.3%, and T. concentricum at only 30.8%. Overall sensitivity for skin was 94.3%, increasing to 97.9% when T. concentricum was excluded. Hair samples were tested for five species; three had 100% detection, T. violaceum had 96.0%, and M. audouinii had 85.7%, giving an overall sensitivity of 96.0%.
Certain species tested should be categorized as yeasts or molds rather than dermatophytes. To test specificity, each sample type was analyzed for classification as either dermatophyte or yeast/mold (Table 2). In nail samples (Table 2A), 15 species were identified as dermatophytes and five as yeasts/molds (Candida spp., F. oxysporum, and S. brevicaulis), with 100% correct detection in both categories. Hair samples (Table 2B) and skin samples (Table 2C) showed similar results, with all dermatophytes and all yeasts/molds detected with 100% specificity.
Reproducibility was assessed for each species (Table 3). Nail organisms showed 100% reproducibility except F. oxysporum. In skin, six species were 100% reproducible, T. mentagrophytes quinkeanum was 88.9%, T. equinum and T. mentagrophytes interdigitale were 77.8%, and T. concentricum showed 0%. In hair, three species were 100% reproducible, while T. violaceum and M. audouinii were 88.9% and 66.7%, respectively.
For limit of detection testing, the lowest gDNA concentration detected was recorded. In nail samples (Table 4), all species had 100% detection at all concentrations except C. albicans and C. parapsilosis. C. albicans showed 33.3% detection at 1.00E+02 copies/µl and no detection at 1.00E+01, while C. parapsilosis showed 33.3% detection at 1.00E+01. In skin samples (Table 5), N. persicolor and T. interdigitale had 100% detection at all concentrations, whereas others showed partial or no detection at lower concentrations, with T. concentricum showing 0% across all. In hair (Table 6), all species except M. canis had 100% detection. M. canis was detected at 75.0% in the highest concentration, 50% in the next, and 0% at lower levels. T. violaceum and M. audouinii were detectable across all concentrations but demonstrated 0 average intensity.
Linearity was assessed by comparing average signal intensities across concentration levels (Table 7). Graphs and R² values were generated for each species, with R² serving as the measure of linearity. For example, T. interdigitale in nail samples (Figure 1) demonstrated 97.9% linearity.

2.2. Figures, Tables and Schemes

All figures and tables should be cited in the main text as Figure 1, Table 1, etc.
Table 1. Accuracy of detection of tested dermatophytes in nail, skin, and hair samples.
Table 1. Accuracy of detection of tested dermatophytes in nail, skin, and hair samples.
Accuracy Dermatophyte detection in Nail samples Accuracy Dermatophyte detection in Skin samples Accuracy Dermatophyte detection in Hair samples
Spike Count of Correct Percent of Correct Count of Correct Percent of Correct Count of Correct Percent of Correct
T. interdigitale 27 100.0% 27 100% - -
T. rubrum 27 100.0% - - - -
C.albicans 27 100.0% - - - -
C.parapsilosis 27 100.0% - - - -
C.guillermondii 27 100.0% - - - -
E.floccosum 27 100.0% 27 100% - -
S.brevicaulis 27 100.0% - - - -
T.menta inter - - 21 91.3% - -
T.equinum - - 21 91.3% - -
T.violaceum - - 27 100.0% 24 96.0%
T. menta quinkeanum - - 24 96.0% - -
M.canis - - 27 100.0% 18 100.0%
N.persicolor - - 27 100.0% 9 100.0%
T.schoenleinii - - 27 100.0% - -
T.tonsurans - - - - 27 100.0%
M.audouinii - - - - 18 85.7%
Sensitivity 189 100% 228 97.9% 96 96.3%
Table 2. Detection of organisms as either dermatophytes or yeast/mold in nail (A), hair (B.), and skin (C) samples. Y/M indicates yeast and mold, other than those that are also considered dermatophytes.
Table 2. Detection of organisms as either dermatophytes or yeast/mold in nail (A), hair (B.), and skin (C) samples. Y/M indicates yeast and mold, other than those that are also considered dermatophytes.
Sample Name Hair
Expected Detected with Dermatophytes
Not detetced with Y/M
Accuracy UDA/YM detection in Nail, Hair, Skin samples
Detected Derm, Not detected YM Not delected Derm, Detected YM
Spike Count of detetced % of Detected Count of ND % of Non detected
T. interdigitale 54 100.0% 0 0.0%
T. rubrum 54 100.0% 0 0.0%
C.albicans 0 0.0% 27 100.0%
C.parapsilosis 0 0.0% 27 100.0%
C.guillermondii 0 0.0% 27 100.0%
E.floccosum 27 100.0% 0 0.0%
F.oxisporum 0 0.0% 27 100.0%
S.brevicaulis 0 0.0% 27 100.0%
T.menta inter 27 100.0% 0 0.0%
T.concentricum 27 100.0% 0 0.0%
T.equinum 27 100.0% 0 0.0%
T.violaceum 54 100.0% 0 0.0%
E.floccosum 27 100.0% 0 0.0%
T. menta quinkeanum 27 100.0% 0 0.0%
M.canis 54 100.0% 0 0.0%
N.persicolor 54 100.0% 0 0.0%
T.schoenleinii 27 100.0% 0 0.0%
T.tonsurans 27 100.0% 0 0.0%
M.audouinii 27 100.0% 0 0.0%
N.persicolor 27 100.0% 0 0.0%
540 100.0% 135 100.0%
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Table 3. Reproducibility rates for the detection of different organisms in nail, skin, and hair samples. Total concordant refers to instances of no change and when the organisms were constantly detected. .
Table 3. Reproducibility rates for the detection of different organisms in nail, skin, and hair samples. Total concordant refers to instances of no change and when the organisms were constantly detected. .
Target Organism Total Concordant Total Discordant Reproducibility
Nail T. interdigitale 207 0 100.0%
T. rubrum 207 0 100.0%
C.albicans 207 0 100.0%
C.parapsilosis 207 0 100.0%
C.guillermondii 207 0 100.0%
E.floccosum 207 0 100.0%
F.oxisporum 23 184 11.1%
S.brevicaulis 207 0 100.0%
Skin T.interdigitale 207 0 100.0%
T.menta inter 161 46 77.8%
T.concentricum 0 207 0.0%
T.equinum 161 46 77.8%
T.violaceum 207 0 100.0%
E.floccosum 207 0 100.0%
T. menta quinkeanum 184 23 88.9%
M.canis 207 0 100.0%
N.persicolor 207 0 100.0%
T.schoenleinii 207 0 100.0%
Hair T.tonsurans 207 0 100.0%
T.violaceum 184 23 88.9%
M.audouinii 138 69 66.7%
M.canis 207 0 100.0%
N.persicolor 207 0 100.0%
Table 4. Detection levels at different concentrations of organisms in nail samples. Units are copy per micrometer (cp/mcl). When there is a detection, the light given off is quantified as average intensity. Higher means good detection, and is directly related to higher amount of copies .
Table 4. Detection levels at different concentrations of organisms in nail samples. Units are copy per micrometer (cp/mcl). When there is a detection, the light given off is quantified as average intensity. Higher means good detection, and is directly related to higher amount of copies .
LOD Dermatophyte detection in Nail samples
1,000 750 100 10 1 1,000 750 100 10
1.00E+03 7.50E+02 1.00E+02 1.00E+01 1.00E+00 Average
Intensity
1.00E+03 7.50E+02 1.00E+02 1.00E+01
Spike Count of Detected Percent of Detected
T. interdigitale 3 3 3 3 3 9,482 100.0% 100.0% 100.0% 100.0%
T. rubrum 3 3 3 3 3 57,330 100.0% 100.0% 100.0% 100.0%
C.albicans 3 3 1 0 0 3,690 100.0% 100.0% 33.3% 0.0%
C.parapsilosis 3 3 3 1 1 48,884 100.0% 100.0% 100.0% 33.3%
C.guillermondii 3 3 3 3 3 14,915 100.0% 100.0% 100.0% 100.0%
E.floccosum 3 3 3 3 3 29,880 100.0% 100.0% 100.0% 100.0%
F.oxisporum 3 3 3 3 3 6,471 100.0% 100.0% 100.0% 100.0%
S.brevicaulis 3 3 3 3 3 28,481 100.0% 100.0% 100.0% 100.0%
Universal Dermatophyte 3 3 3 3 3 100.0% 100.0% 100.0% 100.0%
Table 5. Detection levels at different concentrations of organisms in skin samples. Units are copy per micrometer. .
Table 5. Detection levels at different concentrations of organisms in skin samples. Units are copy per micrometer. .
LOD Dermatophyte detection in Skin samples
1,000 750 100 10 1 1,000 750 100 10
1.00E+03 7.50E+02 1.00E+02 1.00E+01 1.00E+00 Average
Intensity
1.00E+03 7.50E+02 1.00E+02 1.00E+01
Spike Count of Detected Percent of Detected
T.interdigitale 4 4 4 4 2 5,010 100.0% 100.0% 100.0% 100.0%
T.menta inter 1 1 1 1 1 0 25.0% 25.0% 25.0% 25.0%
T.concentricum 0 0 0 0 0 0 0.0% 0.0% 0.0% 0.0%
T.equinum 2 1 0 0 0 1,378 50.0% 25.0% 0.0% 0.0%
T.violaceum 4 4 3 0 0 1,794 100.0% 100.0% 75.0% 0.0%
E.floccosum 4 4 4 3 3 7,544 100.0% 100.0% 100.0% 75.0%
T. menta quinkeanum 4 4 4 1 0 10,373 100.0% 100.0% 100.0% 25.0%
M.canis 3 2 2 2 0 2,714 75.0% 50.0% 50.0% 50.0%
N.persicolor 4 4 4 4 4 33,662 100.0% 100.0% 100.0% 100.0%
T.schoenleinii 4 4 4 3 0 18,366 100.0% 100.0% 100.0% 75.0%
Universal Dermatophyte 4 4 4 4 4 100.0% 100.0% 100.0% 100.0%
Table 6. Detection levels at different concentrations of organisms in skin samples. Units are copy per micrometer. .
Table 6. Detection levels at different concentrations of organisms in skin samples. Units are copy per micrometer. .
LOD Dermatophyte detection in Hair samples
1,000 750 100 10 1 1,000 750 100 10
1.00E+03 7.50E+02 1.00E+02 1.00E+01 1.00E+00 Average
Intensity
1.00E+03 7.50E+02 1.00E+02 1.00E+01
Spike Count of Detected Percent of Detected
T.tonsurans 4 4 4 4 0 5,010 100.0% 100.0% 100.0% 100.0%
T.violaceum 4 4 4 4 2 0 100.0% 100.0% 100.0% 100.0%
M.audouinii 4 4 4 4 0 0 100.0% 100.0% 100.0% 100.0%
M.canis 3 2 0 0 0 1,378 75.0% 50.0% 0.0% 0.0%
N.persicolor 4 4 4 4 4 1,794 100.0% 100.0% 100.0% 100.0%
Universal Dermatophyte 4 4 4 4 4 100.0% 100.0% 100.0% 100.0%
Table 7. Linearity measurements for organism detected at different concentrations in nail, skin, and hair samples .
Table 7. Linearity measurements for organism detected at different concentrations in nail, skin, and hair samples .
Linearity
1 10 100 750 1,000 10,000
Log10 Concentration 0.00 1.00 2.00 3.00 4.00 5.00 Sum
Mean of Intensity Nail T. interdigitale (nail) - 3988 7383.75 9200 12804 14032 47,407.8
T. rubrum (nail) - 42030 54028 59848 64319 66423 286,648.0
C.albicans (nail) - 2096 3184 3876 4628 4668 18,452.0
C.parapsilosis (nail) - 19520 38668 55579.75 64255 66399 244,421.8
C.guillermondii (nail) - 3308 7600 17052 22216 24400 74,576.0
E.floccosum (nail) - 9272 18776 29388 35512 56450 149,398.0
F.oxisporum (nail) - 2136 2508 6084 9716 11912 32,356.0
S.brevicaulis (nail) - 6048 16340 26732 44676 48608 142,404.0
Skin T.interdigitale (skin) - 4512 5160 4648 4808 5920 25,048.0
T.menta inter (skin) - 0 0 0 0 0 0.0
T.concentricum (skin) - 0 0 0 0 0 0.0
T.equinum (skin) - 104 248 1360 1384 3792 6,888.0
T.violaceum (skin) - 16 1216 1464 1888 4384 8,968.0
E.floccosum (skin) - 3944 3536 6672 7512 16056 37,720.0
T. menta quinkeanum (skin) - 1080 1776 8848 15848 24312 51,864.0
M.canis (skin) - 8 0 1976 3120 8464 13,568.0
N.persicolor (skin) - 8344 11768 35520 52248 60431.5 168,311.5
T.schoenleinii (skin) - 5104 8304 21824 24312 32288 91,832.0
Hair T.tonsurans (hair) - 56 3280 6160 8104 9312 26,912.0
T.violaceum (hair) - 2544 3184 4000 6576 8456 24,760.0
M.audouinii (hair) - 72 784 672 816 1352 3,696.0
M.canis (hair) - 200 960 2240 2944 2848 9,192.0
N.persicolor (hair) - 17128 16448 26168 31760 30720 122,224.0
Figure 1. Graphs of linearity for organisms detected in nail samples.
Figure 1. Graphs of linearity for organisms detected in nail samples.
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Figure 2. Graphs of linearity for organisms detected in skin samples .
Figure 2. Graphs of linearity for organisms detected in skin samples .
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Figure 3. Graphs of linearity for organisms detected in hair samples .
Figure 3. Graphs of linearity for organisms detected in hair samples .
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3. Discussion

Conventional dermatophyte detection methods include direct microscopic examination and culture. Direct microscopy with potassium hydroxide (KOH) is rapid but has limited sensitivity (17). The current gold standard remains culture on species-specific media, which can take up to 4 weeks (18). Periodic acid-Schiff (PAS) staining provides high sensitivity for histological detection but cannot precisely identify the pathogen [19]
The validation results presented here confirm the high sensitivity and specificity of the Euroarray Dermatomycosis PCR-based assay. Compared to culture, it provides accurate species-level identification of dermatophytes and other fungi within 48 hours. Faster turnaround facilitates timelier initiation of targeted therapy, which improves outcomes and helps prevent further spread of infection. The assay consistently achieved sensitivities above 94% across sample types, and 100% when outliers (Fusarium oxysporum in nails, T. concentricum in skin) were excluded. These outliers likely reflect limitations in probe hybridization or strain-specific genomic variability.
Specificity was strong, with reliable discrimination between dermatophytes and non-dermatophyte yeasts or molds, a critical advantage in mixed infections or atypical presentations. This ability reduces the risk of inappropriate antifungal use, contributing to antimicrobial stewardship. Reproducibility was high overall, though F. oxysporum in nails and T. concentricum in skin highlighted areas requiring probe refinement. Limit of detection testing confirmed assay reliability for low-burden infections, particularly in nail and hair samples, though probe optimization is needed for some skin species. Linearity was excellent for nails and hair (R² >0.90), with greater variability in skin specimens, suggesting further optimization.
The clinical importance of this work extends to antifungal resistance. Rising terbinafine resistance in T. rubrum, T. mentagrophytes, and T. indotineae is driven by mutations in the squalene epoxidase (SQLE) gene [20], while efflux pump overexpression and ergosterol alterations confer resistance to azoles [21]. Although the Euroarray does not yet target resistance markers, its molecular design and demonstrated performance provide a foundation for integrating resistance genotyping. Expanding probe sets to include known resistance mutations would enable early recognition of resistant strains, real-time monitoring of therapeutic effectiveness, and more precise tailoring of antifungal regimens.
In summary, this study demonstrates that the Euroarray Dermatomycosis assay is a highly sensitive, specific, and time-efficient diagnostic platform. With further integration of resistance detection, this technology has the potential to become a comprehensive clinical tool for both accurate dermatophyte identification and surveillance of antifungal resistance mechanisms.

4. Materials and Methods

4.1. Sample Collection and DNA Extraction

Clinical materials consisted of hair stubs, nail clippings, and skin scales collected under sterile conditions to minimize contamination. Non-viable cells such as crusts were also acceptable for testing. Samples were disinfected prior to collection. DNA extraction was performed using the EUROArray SwiftX-traction kit following the manufacturer’s instructions. In some runs, automated extraction was performed on the EUROArray Workstation to ensure consistency and reproducibility.

4.2. PCR Amplification

Extracted DNA was subjected to multiplex PCR with pre-formulated, ready-to-use reagents supplied by EUROIMMUN. This step amplified pathogen-specific gene segments while simultaneously incorporating fluorescent labels. Internal amplification controls were included in each reaction to verify the success of PCR and to rule out inhibition.

4.3. Microarray Hybridization and Detection

Amplified products were hybridized to the EUROArray Dermatomycosis BIOCHIP, a glass microarray slide with immobilized oligonucleotide probes specific to dermatophytes and common non-dermatophyte fungi. Hybridization was performed at 55 °C under controlled conditions. Slides were then washed to remove unbound DNA and scanned using the EUROArrayScanner.

4.4. Data Analysis

Fluorescent signals from hybridized probes were automatically analyzed using EUROArrayScan software. Results were interpreted against internal positive and negative controls, with each probe corresponding to a specific fungal species. Reports were automatically generated and archived for traceability.

4.5. gDNA

gDNA for all the tested fungi were provided by Euroimmune- Germany

5. Conclusions

In conclusion, the Euroarray Dermatomycosis PCR-based assay showed high sensitivity, specificity, and reproducibility for the detection of dermatophytes and related fungi in nail, skin, and hair samples, while reducing turnaround time significantly compared to conventional culture. A few species such as Fusarium oxysporum and T. concentricum demonstrated lower performance, but overall the validation confirmed the strength and reliability of this molecular approach. By allowing rapid and accurate species identification, this technique provides clear advantages in supporting timely clinical management, reducing diagnostic uncertainty, and preventing inappropriate antifungal use. Furthermore, the molecular design of the assay creates an opportunity to integrate resistance genotyping in the future, enabling early recognition of antifungal resistance mechanisms and supporting more precise treatment strategies against emerging resistant strains.

Author Contributions

Conceptualization, Z.D.; methodology, Z.D. and S.C.; validation, Z.D. and S.C.; resources, A.D. and S.C.; data curation, Z.D. and S.C.; writing—original draft preparation, S.C. and A.D.; writing—review and editing,Z.D., S.C., and A.D.; visualization,S.C. and A.D.; supervision, Z.D.; project administration, Z.D.; funding acquisition, Z.D. All authors have read and agreed to the published version of the manuscript.”.

Funding

“This research received no external funding”.

Conflicts of Interest

“The authors declare no conflicts of interest.”.

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