Methanolic leaf extract of Calotropis procera promotes early S100β upregulation and accelerates sensorimotor functional recovery in a mouse model of peripheral nerve injury

2.1 Mining of active compounds

Information on the phytochemical constituents of Calotropis procera was retrieved through a comprehensive literature search across PubMed, Scopus, and Google Scholar. All searches were conducted up to the year 2021. To evaluate pharmacokinetic properties, the absorption, distribution, metabolism, excretion, toxicity (ADMETlab) platform was employed to calculate drug-likeness (DL) and oral bioavailability (F%) scores (Xiong et al., 2021). Drug-likeness reflects the structural and physicochemical similarity of compounds to known therapeutic agents, whereas oral bioavailability represents the fraction of an administered dose reaching systemic circulation. Compounds with a DL score ≥ 0.18 and bioavailability ≥ 30% were considered suitable candidates and selected for further investigations. Canonical simplified molecular input line entry system (SMILES) structures of the selected compounds were acquired from public chemical databases, including PubChem, SwissADME, and ChEMBL (Kim et al., 2016; Daina et al., 2017). Chemical structures were visualized using PubChem and ChemSpider (Pence and Williams, 2010). Subsequently, key pharmacokinetic parameters such as hydrogen bond donors and acceptors, molecular weight, lipophilicity (AlogP), and rotational bond count were compiled using SwissADME to support downstream analysis.

2.2 Screening of compound and PNI-related gene targets

The potential molecular targets associated with the selected phytochemical compounds were identified by submitting their canonical SMILES structures to the swiss target prediction and search tool for interactions of chemicals (STITCH) databases (Gfeller et al., 2014; Szklarczyk et al., 2016). In Swiss Target Prediction, target identification was based on chemical similarity and reverse pharmacophore mapping. Only targets with a probability score ≥ 0.7 were considered for further analysis. Similarly, in the STITCH database, the search was restricted to Homo sapiens, and only interactions with a combined confidence score ≥ 0.7 were retained. To identify genes associated with PNI , the GeneCards and online mendelian inheritance in man (OMIM) databases were queried using the keyword “peripheral nerve injury” (Hamosh et al., 2005; Safran et al., 2010). Gene identifiers were standardized using the UniProtKB database by selecting entries corresponding to Homo sapiens (Boutet et al., 2007). Finally, the lists of compound-related targets and PNI-associated genes were compared using a Venn diagram approach to identify overlapping targets, which were subsequently selected for further analysis.

2.3 Network analysis

Gene ontology (GO) enrichment analysis of the overlapping target genes was executed using the database for annotation, visualization, and integrated discovery (DAVID) database to identify significantly enriched cellular components, biological processes, and molecular functions (Huang et al., 2007). The results were visualized as bubble plots using the ggplot2 package in R. The threshold for statistical significance was set at p < 0.05.

To further explore functional relationships, protein–protein interaction (PPI) networks were constructed using the search tool for the retrieval of interacting genes (STRING) database with a minimum combined score threshold of 0.4 (von Mering et al., 2003). The resulting interaction networks were envisioned and analyzed using Cytoscape software (Shannon et al., 2003).The CytoHubba plugin in Cytoscape was employed to identify the Key regulatory nodes within the network, applying the node degree method to determine the top 10 highly connected proteins, which were considered as hub targets. All database searches were conducted up to the year 2021.

2.4 Plant collection and processing

Fresh leaves of the CP (Calotropis procera) were collected from peripheral regions of Faisalabad, Punjab, and authenticated by experts from the Department of Botany. The collected plant material was thoroughly washed to remove contaminants, shade-dried, and subsequently converted into a fine powder by applying a mechanical grinder, followed by sieving.

Extraction was performed by macerating the powdered plant material in methanol for 7 days with intermittent shaking and then filtering using Whatman No. 1 filter paper. The filtrate was concentrated at 35–40°C under reduced pressure by using a rotary evaporator, followed by air-drying to obtain a semi-solid extract. The resulting product was designated as the methanolic extract of Calotropis procera leaves (CP-Ext).

The extraction procedure was based on previously optimized methodologies; therefore, extraction yield was not quantified in this study, as the focus was on phytochemical characterization and biological evaluation rather than extraction efficiency.

2.5 Chromatography analysis

Reverse-phase high performance liquid chromatography (HPLC) was used to detect and quantify the phenolic constituents present in CP-Ext. 0.1 g of dried extract was diluted in 1 mL of HPLC-grade methanol and filtered to prepare the sample and then 10µL of this solution was injected into the system. Chromatography was performed on an HP 1050 gradient system (Perkin Elmer, MA), equipped with a Shimadzu Shim-Pack CLC-ODS C-18 column (250 mm × 4.6 mm, 5 μm, Shimadzu, Japan). The mobile phases were acetonitrile/methanol (70:30, solvent A) and 0.5% glacial acetic acid in double-distilled water (solvent B). Separation was achieved with a linear gradient of 10 min at room temperature. The chromatographic system was coupled with a Flexer-Binary-LC pump and a UV/Vis liquid chromatography detector SPD-10AV (Shimadzu, Japan). UV spectra were obtained at 275 nm. The identification of compounds was done by matching sample retention times and peaks with standards, namely gallic acid, catechin, and quercetin. Data were analyzed with Chromera software (version 4.2.6410).

2.6 Total phenolic and flavonoid content quantification

Total phenolic content (TPC) of CP-Ext was determined using the Folin–Ciocalteu colorimetric method. Briefly, an aliquot of the extract was mixed with Folin–Ciocalteu reagent, then sodium bicarbonate solution was added. A spectrophotometer was used to detect absorbance at 765 nm following room temperature incubation. The results were reported as milligrams of gallic acid equivalents per gram of extract using gallic acid as a reference standard (Singleton et al., 1999).

Total flavonoid content (TFC) was evaluated using an aluminium chloride-based colorimetric assay. The extract was mixed with aluminium chloride and sodium nitrite solutions, followed by incubation and subsequent addition of sodium hydroxide. Absorbance was recorded at 540 nm, and quercetin was used to construct the standard calibration curve. The findings were reported as milligrams of quercetin equivalents per gram of extract (Kumar and Jain, 2015).

2.7 Antioxidant activity assessment

Antioxidant activity of the extract was evaluated using 2,2’-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid (ABTS); 2,2-diphenyl-1-picrylhydrazyl (DPPH); ferric reducing antioxidant power (FRAP) assays following established methods reported in the literature (Kumar and Jain, 2015). Absorbance changes were measured using a spectrophotometer, and antioxidant capacity was expressed relative to appropriate reference standards.

2.8 Animals and experimental design

All experimental procedures were approved by the ethics review committee (ERC) of government college University Faisalabad (Approval No. 586/2020). Animal care and handling were performed in accordance with the National institutes of health (NIH) guidelines for the care and use of laboratory animals (2011) and the ARRIVE guidelines.

Adult male mice (BALB/c) ageing 8–10 weeks old and weighing 25–35g, were housed under controlled laboratory conditions (25 ± 1°C, 12-hour light/dark cycle) having unrestricted access to food and water. Animals were acclimatized for 1 week prior to the start of the experimental procedure.

The sample size (n = 28/group) was determined based on previously reported data using comparable PNI models to ensure adequate statistical power. Mice were randomly assigned to three groups: sham, crush, and crush + CP-Ext.

CP-Ext was administered orally at a dose of 100 mg/kg daily, starting from the day of injury induction. The dose selection was based on previously published data (Yogi et al., 2016). Control groups received normal saline.

Functional and biochemical assessments were performed at predefined time points, and tissue samples were collected for histological and molecular analyses.

2.9 Sciatic nerve injury

Sciatic nerve injury was made under anaesthesia using xylazine (5 mg/kg) and ketamine (70 mg/kg). The surgical area was sterilized, and the sciatic nerve was carefully exposed without damaging surrounding tissues.

A standardized crush injury was produced by applying persistent pressure using forceps for approximately 15 seconds near the nerve bifurcation. Successful induction of injury was confirmed by the appearance of a translucent ring at the compression site. The incision was then sutured, and an antiseptic solution was applied to prevent infection (Hussain et al., 2013).

2.10 Diet intake and body mass assessment

The daily food intake was recorded by measuring the difference between the weight of the food left in the cage and the weight of the food offered the day before, using a digital balance. This difference gives the quantity of food consumed per day. The body mass of each mouse was also measured daily throughout the study period and expressed as a %age of the initial body mass observed 5 days before injury induction.

2.11 Grip strength test

A grip strength test measured muscle strength by allowing mice to grasp a metal grid with their paws, which was connected to a grip strength meter (Bioseb, Chaville, France). This test was carried out according to the protocol previously reported (Hussain et al., 2013). Grip strength was presented as a percentage of the average grip strength (in N) taken 5 and 2 days before injury induction.

2.12 Walking track analysis

Gait function was assessed using the sciatic functional index (SFI) according to a previously reported method (Hussain et al., 2013). For this purpose, the hind paws of the mouse were inked with non-toxic ink, and the animals were made to walk along a confined track lined with white paper to obtain clear footprints. These prints were subsequently analyzed to calculate SFI values using standard formulas. Key parameters, including print length (PL) and toe spread (TS), were measured to assess functional recovery. SFI values approaching −10 were considered indicative of normal motor function, whereas values near −100 reflected severe impairment. The following formula was applied to calculate the SFI:

$\begin{array}{c}\text{SFI}= \left(-38.3\times -\frac{\text{EPL}-\text{ NPL}}{\text{NPL}}\right)+\left(109.5\times \frac{\text{ETS}-\text{NTS}}{\text{NTS}}\right)\\ +\left(13.3\times \frac{\text{EIT}-\text{NIT}}{\text{NIT}}\right)-8.8\end{array}$

where the PL is the length of the gap between the heel and the top of the 3^rd toe, the intermediate toe spread (IT) is the distance between the 2^nd and 4^th toe, and the TS is the distance between the 1^st and 5^th toe. N represents the normal hind paw (contralateral to the injury site), and E stands for the experimental hind paw (ipsilateral to the injured leg). An SFI value of approximately -10 represents healthy gait or normal walking, while an SFI value of approximately -100 represents a complete loss of motor coordination (Hussain et al., 2013).

2.13 Hot plate test

The thermal nociceptive response was measured using a hot plate test as described previously (Imam and Sumi, 2014). Mice were placed on a heated surface maintained at 56 ± 1°C, and the time taken to display a response, such as jumping, paw licking, or withdrawal, was recorded. To avoid thermal injury, a cut-off time was applied. The average of repeated measurements was calculated and used for further analysis.

2.14 Pinprick test

Mechanical sensitivity was evaluated using a pinprick test adapted from previously described protocols (Zafar et al., 2021). Following an acclimatization period, the plantar of the hind paw was gently stimulated using a fine pin. The animal’s response was recorded as withdrawal behavior, and scoring criteria were used to assess the degree of sensory recovery.

2.15 Muscle histology

The tibialis anterior muscles of the ipsi and contralateral hind limbs were harvested and fixed using 10% neutral buffered formalin. After sequential tissue dehydration and cleaning steps, paraffin-embedded blocks were made to slice the tissues with an RM2125 RTS microtome (Leica Microsystems, Wetzlar, Germany). Thin 5-µm transverse sections were mounted on glass slides, then stained using hematoxylin and eosin dyes according to the procedure adopted from Carriel et al., (2014). After mounting, microphotographs of the sections were taken under an XSZ-107BN optical microscope (Nanjing BW Optics and Instrument, Nanjing, China) at 40X magnification using a B1 digital camera (Optika, Ponteranica, Italy). The cross-sectional area of fibers was quantified by Image J software.

2.16 Total antioxidant capacity (TAC) and total oxidant status (TOS)

TAC was assessed using a previously established colorimetric method (Erel, 2005). The test is based on the ABTS oxidation in the presence of hydrogen peroxide, which creates a dark green solution. The bleaching rate of this solution increases depending on the existence of antioxidants in the sample. The measurements were obtained at a wavelength of 610 nm. The reaction rate was calibrated against known vitamin C concentrations, and the results were expressed as vitamin C equivalents (mM/L). Total oxidant status (TOS) was measured according to a method described previously (Erel, 2005). The test is based on the oxidation of ferrous ion by O-dianisidine in the presence of oxidants in the sample. Then, the added xylenol orange reacted with the ferric ions to form a colored complex, and its intensity was measured using an automated spectrophotometer. H₂O₂ was used for calibration, and the results were presented in terms of H₂O₂ Eq µM/L.

2.17 Paraoxonase and arylesterase activity

Paraoxonase (PON-1) activity was measured based on the extent of enzymatic degradation of paraoxon to p-nitrophenol, as described previously (Elkiran et al., 2007). The formation of p-nitrophenol resulted in a color change, which was measured at 405 nm using a BTS-330 semi-automated chemical analyzer (BioSystems, Barcelona, Spain). The results were presented as PON-1 U/mL. The activity of arylesterase (ARE) was assessed by adopting the method given by Elkiran et al., (2007), which uses phenylacetate as a substrate to be converted to phenol in the presence of ARE. The reaction mixture was prepared by mixing the reagent and the sample at a 35:1 ratio at 37°C. The absorbance was noted immediately at 270 nm, and after 1 min of incubation, the process of absorbance measurement was repeated. The difference between the absorbance values was recorded to estimate the ARE activity. To guarantee precision and repeatability, every measurement was carried out in triplicate.

2.18 Quantification of S100β protein and mRNA

The level of S100β protein in serum was measured using a commercially available ELISA kit and the manufacturer’s instructions were followed during the procedure.

For gene expression, total RNA was extracted from sciatic nerve using TRIzol reagent following standard procedures (Hussain et al., 2013). The concentration of RNA was quantified using a spectrophotometer, and cDNA synthesis was performed using a reverse transcription kit.

Quantitative polymerase chain reaction (PCR) was carried out following SYBR green chemistry. The primer sequences used were as follows:

18S forward 5’-CGTCTGCCCTATCAACTTTCG-3’,

18S reverse 5’-TTCCTTGGATGTGGTAGCCG-3’,

S100β forward 5’-GACTCCAGCAGCAAGGTGAC-3’,

S100β reverse 5’-CATCTTCGTCCAGCGTCTCCA-3’.

PCR amplification conditions included an initial denaturation step followed by multiple amplification cycles under standard conditions. The comparative Ct method was used to calculate relative gene expression levels, with normalization to the reference gene (18S). All experiments were conducted following standard laboratory protocols to ensure accuracy and reproducibility.

2.19 Statistical analysis

Data were expressed as mean ± SEM and analyzed with PRISM version 8 (GraphPad, San Diego, CA). In accordance with PRISM’s recommendations, one-way analysis of variance (ANOVA) was used to compare the means of three or more unmatched groups, while repeated measures two‐way ANOVA for repeated measures was applied to compare the means obtained in different experimental conditions at different time points. Benjamini, Krieger, and Yekutieli’s two-stage step-up approach was applied in both situations to account for multiple comparisons. A p-value < 0.05 was considered statistically significant.

3.1 Data mining identifies phenolic compounds in C. procera potentially affecting PNI-related genes

In silico analysis of 165 C. procera ingredients extracted from the literature revealed 28 constituents with optimal LD and F% scores (Fig. 1). Of these, six flavonoids and three other related compounds were successfully linked to 90 putative gene targets. A parallel literature review also showed 7,444 genes associated with PNI. Cross-referencing these two lists revealed 77 genes related to both PNI and biologically active compounds of C. procera, which were considered for further evaluation (Fig. 2a). GO enrichment analysis of these common genes showed that many of them were involved in the negative regulation of cell death, signal transduction, protein phosphorylation, and redox reactions like biological processes (Fig. 2b). ATP binding and protein kinase activity were two of the most affected molecular functions (Fig. 2c). Finally, their protein products were particularly present at the plasma membrane (Fig. 2d). PPI network analysis revealed significant functional relationships between the 77 genes common to PNI and C. procera (Fig. 3a). Notably, AKT serine/threonine kinase 1 (AKT1), amyloid-beta precursor protein (APP), epidermal growth factor receptor (EGFR), metallopeptidase matrix 2 (MMP2) and 9 (MMP9), myeloperoxidase (MPO), non-receptor protein tyrosine phosphatase type 1 (PTPN1), S100 calcium-binding protein B (S100β), kinase insertion domain receptor (KDR), and SRC proto-oncogene non-receptor tyrosine kinase (SRC) were identified as exhibiting the highest degree of interaction with each other. They were considered the key protein targets of C. procera (Fig. 3b). These findings support the selection of these targets for further evaluation in the PNI model.

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Fig. 1. Flowchart of in silico analysis of C. procera and PNI. Multi-step process leading to the selection of key protein targets, such as S100B, among others, and key mechanisms, including regulation of oxidation-reduction reactions and ligand-receptor interactions at the plasma membrane.

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Fig. 2. Classification of gene targets common to PNI and C. procera compounds. (a) Venn diagram showing the number of genes related to both PNI and the biologically active compounds of C. procera, (b-d) Classification of the 77 genes common to PNI and C. procera was obtained according to GO biological process, (b) molecular function, and (c) cellular component (d). The size of the spots represents the number of hits grouped within a given term, and the color scale indicates the degree of statistical significance.

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Fig. 3. Protein targets common to PNI and C. procera compounds. (a) PPI network showing the interactions between the 77 genes common to PNI and C. procera. The size of the hubs represents the degree of interaction, and (b) Bar plot indicating the node degree score of the best 10 protein hubs after PPI network construction.

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3.2 CP-Ext contains high amounts of phenolic compounds and exhibits antioxidant power

In silico analysis of C. procera ingredients identified several phenolic compounds as potentially affecting specific PNI-related genes or proteins. Based on these findings, a CP-Ext was prepared, which was to be enriched in these phytochemicals of interest. Spectrophotometric analysis of the amounts of TPC and TFC, respectively, confirmed the nature of CP-Ext. Additionally, HPLC analysis revealed the presence of gallic acid, which is a phenolic acid, as well as catechin and quercetin, which are flavonoids. Phenolic compounds are known to exhibit antioxidant properties. We therefore evaluated the antioxidant activity of CP-Ext using three in vitro approaches. Measurements of ferric reducing power and scavenging of ABTS^+• and DPPH radicals demonstrated the capacity of CP-Ext to combat oxidative stress.

3.3 CP-Ext promotes sensorimotor function recovery after transient PNI

Based on its phenolic composition and antioxidant properties, CP-Ext was evaluated in a murine model of transient sciatic nerve injury to assess its therapeutic potential. To ensure that oral administration of CP-Ext did not cause any general adverse effects in the mice, we monitored daily food consumption and body mass throughout the duration of the experiments. No differences were observed at any time between the groups, and the eating behavior of the animals with nerve damage did not change either (Fig. 4). Furthermore, no general signs of disease were detected during routine animal handling. Crushing the sciatic nerve for a few seconds results in loss of stimulus reception from sensory receptors and transfer of the message to the effector muscles. This is followed by a gradual recovery of sensory and motor functions over time. To assess motor function after PNI, we measured muscle strength using the grip strength test and assessed general motor behavior by gait trace analysis. Grip strength in crush and crush + CP-Ext mice was completely abolished 3 days after injury. During the recovery period, days 9 and 12, crush + CP-ext mice showed a significantly 2-fold increase (p < 0.05) in grip strength compared to crush mice. As a result, they approached the force level observed in sham mice more quickly (Fig. 5a). The fingerprint analysis revealed very similar results to those obtained with the grip strength test. Crush + CP-ext mice reached an SFI score very close to normal values 12 days after injury, whereas crush mice were still highly hampered (Fig. 5b).

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Fig. 4. Effect of CP-Ext on body mass and diet intake. Time course of body mass (a) and diet intake, and (b) in the indicated experimental groups. Repeated measures two-way ANOVA, followed by Benjamini, Krieger, and Yekutieli’s test for multiple comparisons, did not reveal any significant difference among groups at any time point, n=7-28.

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Fig. 5. Effect of CP-Ext on sensorimotor function rehabilitation after transient PNI. Time course of muscle grip strength (a) SFI, (b) paw withdrawal latency in the hot plate test, (c) paw withdrawal response to mechanical stimulus in the pinprick test, and (d) in the indicated experimental groups. Repeated measures two-way ANOVA, followed by Benjamini, Krieger, and Yekutieli’s test for multiple comparisons, ***p < 0.001 for sham mice vs crush and crush + CP-Ext mice, and for crush + CP-Ext mice vs crush mice, n=7-28.

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To evaluate sensory function after PNI, we assessed thermoceptive and mechanoceptive responses. As expected, shortly after injury, on days 2 and 4, crush and crush + CP-Ext mice showed at least a 2-fold increase (p < 0.05) in time spent removing the hind paw from the hot plate compared to sham mice. On days 7 and 10, crush + CP-Ext mice displayed progressive and significantly faster responses (p < 0.05) than crush mice, indicating faster recovery of sensation (Fig. 5c). The results of the pinprick test were very similar. After a complete lack of response immediately after nerve injury, the hind paw withdrawal score in response to a mechanical stimulus gradually increased in crush + CP-Ext mice until reaching an almost complete response on day 11. This response was significantly higher (p < 0.05) than in crushed mice (Fig. 5d).

3.4 CP-Ext protects against muscle atrophy induced after transient PNI

Given that CP-Ext was able to accelerate the recovery of sensorimotor function after injury, we wanted to determine whether it could also protect at the muscular level. The fresh mass of the tibialis anterior muscle, known to decrease during denervation, reached normal values in crushed + CP-Ext mice at the end of the recovery period, i.e., the 12^th day after the injury, while in crushed mice it was almost half that observed in sham mice at the same time point (Fig. 6a). These results were confirmed by measuring the cross-sectional area of the muscle fibers. Morphometric analysis of histological sections of the tibialis anterior muscle in crushed mice revealed fibers with reduced cross-sectional area and, frequently, an angulated morphology induced by denervation compared to the contralateral muscle of the same animal. In contrast, the cross-sectional area of the TA muscle in crush + CP-Ext mice at the end of the recovery period was comparable to that observed in sham mice (Figs. 6b and c). Accordingly, the number of fibers per field, thought to be inversely proportional to their size, reached normal values in the ipsilateral muscle of crush + CP-Ext mice, but remained significantly elevated (p < 0.05) in crush mice (Figs. 6b and d).

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Fig. 6. Effect of CP-Ext on muscle atrophy after transient PNI. (a) Fresh mass of tibialis anterior muscle represented as a percentage of body mass in the indicated experimental groups 12 days after injury. One-way ANOVA, followed by Benjamini, Krieger, and Yekutieli’s test for multiple comparisons, *p < 0.05 and **p < 0.01, ns, non-significant, n=7, (b) Representative micrographs showing tibialis anterior muscle cross-sections of ipsilateral and contralateral hind limbs in the indicated experimental groups 12 days after injury. Scale bar=100 µm. Fiber cross-sectional area, (c) and number of fibers per field, and (d) in the tibialis anterior muscle in the indicated experimental groups 12 days after injury. One-way ANOVA, followed by Benjamini, Krieger, and Yekutieli’s test for multiple comparisons, **p < 0.01, ns, non-significant, n=3 (15-50 fibers per field).

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3.5 CP-Ext attenuates systemic oxidative stress in mice suffering from transient PNI

Given the predicted involvement of redox-related pathways, we next investigated systemic oxidative stress parameters in vivo. We measured TAC and TOS, respectively, as an index of the balance between anti- and pro-oxidant events. Twelve days after sciatic nerve injury, crushed mice had a significant decrease (p < 0.05) in TAC and an increase in TOS compared to sham mice, indicating the presence of oxidative stress. In contrast, crush + CP-Ext mice exhibited TAC and TOS levels comparable to normal values (Figs. 7a and b). We also measured the activity of PON-1 and ARE enzymes. Both enzyme activities were significantly decreased (p < 0.05) in crushed mice compared to sham mice, but reached normal values in crushed + CP-Ext mice at the end of the recovery period (Figs 7c and d). These results demonstrate the effect of CP-Ext on antioxidant parameters in vivo.

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Fig. 7. Effect of CP-Ext on systemic oxidative stress after transient PNI. Total antioxidant capacity (TAC), (a) total oxidative status (TOS), (b) paraoxonase (PON-1) enzymatic activity, (c) arylesterase (ARE) enzymatic activity, and (d) in the indicated experimental groups 12 days after injury. One-way ANOVA, followed by Benjamini, Krieger, and Yekutieli’s test for multiple comparisons, **p < 0.01 in A and **p < 0.01 in B, ***p < 0.001, ns, non-significant, n=7.

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3.6 CP-Ext accelerates S100β upregulation in response to transient PNI

Considering that S100β emerged as a key predicted target, we further examined its expression in response to CP-Ext treatment. Our network pharmacology analysis revealed that S100β was one of the most important factors likely to be modulated by active compounds in C. procera. ELISA quantification of S100β protein in sham mouse serum allowed detection at a concentration of approximately 4 pg/mL, which remained constant throughout the duration of the experiments. In crushed mice, S100β content increased twice 6 days after injury, peaked at day 9 (approximately 17 pg/mL), and remained elevated at day 12 (approximately 10 pg/mL) compared to sham mice. In contrast, in crush + CP-Ext mice, the S100β content had already increased significantly (almost 2-fold) (p < 0.05), 3 days after injury. Then it increased on day 6 (approximately 20 pg/mL, 5 and 2.5 times compared to sham and crush mice, respectively), remained elevated (approximately 18 pg/mL) on day 9, and returned to baseline on day 12 at the end of the recovery period (Fig. 8a). These results were reinforced by measuring the expression of S100β in the sciatic nerve. RT-qPCR data displayed a significant increase (p < 0.05) in S100β mRNA in crush and crush + CP-Ext mice 9 days after injury, but this effect was stronger in the latter. At day 12, S100β mRNA was still elevated in crush mice but equal to normal values in crush + CP-Ext mice (Fig. 8b), coinciding with the restoration of basal S100β protein content and acceleration of the functional recovery observed in these mice at this moment.

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Fig. 8. Effect of CP-Ext on S100B upregulation after transient PNI. (a) Time course of serum concentration of S100B protein in the indicated experimental groups at different days after injury (DAI). Repeated measures two-way ANOVA, followed by Benjamini, Krieger, and Yekutieli’s test for multiple comparisons, *p < 0.05, **p < 0.01 at 3 DAI, **p < 0.01 at 6 DAI, ***p < 0.001 indicated in black and green, ns, non-significant, n=7, and (b) Sciatic nerve S100B gene expression represented as a ratio between ipsilateral and contralateral (dotted baseline) nerve in the indicated experimental groups at 9 and 12 DAI. Repeated measures two-way ANOVA, followed by Benjamini, Krieger, and Yekutieli’s test for multiple comparisons, **p < 0.01 indicated in black and green, and ***p < 0.001 at 9 DAI, **p < 0.01 at 12 DAI, ns, non-significant, n=7.

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