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Preliminary insights into the effects of spinal manipulation therapy of different force magnitudes on blood biomarkers of oxidative stress and pro-resolution of inflammation mediators

Chiropractic & Manual Therapies volume 33, Article number: 8 (2025) Cite this article

Abstract

Background

Evidence has been reported that spinal manipulation therapy (SMT) leads to spine segmental hypoalgesia through neurophysiological and peripheral mechanisms related to regulating inflammatory biomarker function. However, these studies also showed substantial inter-individual variability in the biomarker responses. Such variability may be due to the incomplete understanding of the fundamental effects of force-based manipulations (e.g., patient-specific force-time characteristics) on a person’s physiology in health and disease. This study investigated the short-term effects of distinct SMT force-time characteristics on blood oxidative stress and pro-resolution of inflammation biomarkers.

Methods

Nineteen healthy adults between 18 and 45 years old were recruited between February and March 2020 before the COVID-19 pandemic and clustered into three groups: control (preload only), target total peak force of 400 N, and 800 N. A validated force-sensing table technology (FSTT®) determined the SMT force-time characteristics. Blood samples were collected at pre-intervention, immediately after SMT, and 20 min post-intervention. Parameters of the oxidant system (total oxidant status, lipid peroxidation and lipid hydroperoxide), the antioxidant system (total antioxidant capacity and bilirubin), and lipid-derived resolvin D1 were evaluated in plasma and erythrocytes through enzyme-linked immunosorbent assay and colorimetric assays.

Results

The COVID-19 global pandemic impacted recruitment, and our pre-established target sample size could not be reached. As a result, there was a small sample size, which decreased the robustness of the statistical analysis. Despite the limitations, we observed that 400 N seemed to decrease systemic total oxidant status and lipid peroxidation biomarkers. However, 800 N appeared to transitorily increase these pro-oxidant parameters with a further transitory reduction in plasma total antioxidant capacity and resolvin D1 mediator.

Conclusion

Despite the small sample size, which elevates the risk of type II error (false negatives), and the interruption of recruitment caused by the pandemic, our findings appeared to indicate that different single SMT force-time characteristics presented contrasting effects on the systemic redox signalling biomarkers and pro-resolution of inflammation mediators in healthy participants. The findings need to be confirmed by further research; however, they provide baseline information and guidance for future studies in a clinical population.

Key points

  • A 400 N SMT appears to reduce total oxidant status and lipid peroxidation, while an 800 N SMT seems to temporarily increase these biomarkers in the systemic blood of healthy individuals.

  • Only 800 N SMT appears to transitorily decrease total antioxidant capacity and lipid-derived pro-resolution (resolvin D1) levels in the systemic blood of healthy subjects.

  • Oxidative stress biomarkers and resolvin D1 levels may have predictive value in detecting the short-term effect of SMT with different force-time characteristics in healthy individuals and clinical populations.

  • Due to the study’s limitations, particularly the small sample size, further large-scale trials are required before oxidative stress biomarkers and resolvin D1 levels can be proposed as predictive markers for the effects of SMT with varying force-time characteristics.

Introduction

Chronic musculoskeletal (cMSK) disorders, such as chronic spinal pain, are progressive, long-lasting, highly disabling disorders, representing a significant economic burden to the population and healthcare system worldwide [1, 2]. The World Health Organization (WHO) has recently released a management guideline for adults with chronic primary low back pain (CPLBP) recommending spinal manipulation therapy (SMT) as part of non-surgical interventions to help people experiencing CPLBP [3]. Despite the recommendation, the mechanisms by which SMT affects the physiology of both healthy individuals and those with chronic pain remain poorly understood.

Spinal manipulation therapy is a force-based therapy modality that belongs to a class of treatments labelled as mechanotherapies [4, 5]. A recent review highlighted that SMT leads to spine segmental hypoalgesia through neurobiological mechanisms regulating inflammatory function [6]. For instance, pre-clinical and clinical evidence demonstrated changes in systemic markers of inflammation and oxidative stress following SMT in people with and without neck and low back pain [7,8,9]. Oxidative stress is recognized as free radical dyshomeostasis, meaning that elevated formation of free radicals damages proteins, lipids and DNA, challenging the cellular and, eventually, the system homeostasis [10]. In contrast, ROS low physiological levels act as redox signalling molecules in essential cellular signalling pathways [10]. Importantly, oxidative stress biomarkers have shown positive stratification and predictor value to cardiovascular disease and short-term acute ischemic stroke [11,12,13]. Also, oxidative biomarkers have been shown to be important predictors of work stress and overwork in health care practitioners and in cognitive decline with aging. (14–15) In cMSK, oxidative stress has emerged as a plausible biomarker owing to its intrinsic molecular ability to affect the structure and function of the neuroimmune system with clinical implications on nociceptive amplification and diminished physical and cognitive function [16, 17]. Thus, targeting the production and detoxification of oxidants as a rehabilitative strategy may greatly benefit health and disease.

While it is known that SMT has modulatory effects on systemic markers of inflammation and oxidative stress biomarkers, the changes following SMT showed substantial inter-individual variability [7, 18, 19]. This variability may be due to the lack of understanding of the fundamental effects of the mechanical loading of the SMT (e.g., patient-specific force-time characteristics) on a person’s neurophysiology. Recent preliminary evidence by our team exploring different SMT force-time characteristics and blood inflammatory biomarkers in healthy individuals observed a short-term increase of plasma pro-inflammatory IFN-g (interferon gamma), IL-5 (interleukin 5), and IL-6 (interleukin 6) cytokines when thoracic SMT of total peak force around 800 N was delivered [4]. An opposite behaviour on these biomarkers was observed in SMT with a total peak force of 400 N [4]. Although the clinical relevance of these biomarkers remains unclear, and caution should be taken in the clinical application of these findings, they open an opportunity to continue this research line investigating further biological components of the neuroimmune function that are responsive to variations of SMT’s mechanical loading.

It is well-known that cytokines have an essential role in the inflammatory process; however, resolvins, a lipid-derived pro-resolution mediator, have emerged as a class of active mediators in counteracting inflammation [20]. Resolvins regulate inflammatory and neuroinflammation processes by binding to their receptors on immune and neuronal cells, which eventually implicates dampening inflammation, nociception, sensitization, and pain perception [20, 21]. Thus, both resolvins and oxidative stress biomarkers hold the potential to be further studied, given their participation in cellular signalling, inflammation and peripheral and central sensitization [16, 17, 21]. However, no previous research examined the relationship between mechanical loadings of SMT and pro-resolution mediator and biomarkers of oxidative stress. Therefore, this study aimed to explore the short-term effect of SMT with different force-time characteristics on systemic oxidative stress biomarkers and lipid-derived pro-resolution mediators in healthy individuals. We hypothesized that higher changes on these biomarkers would be seen in the short term when SMT of higher force magnitudes were applied, contrasting with lower SMT force magnitude. The findings from this exploratory study in young, healthy individuals will help inform future studies in the neurobiology and neuroimmunology related to mechanotherapy that can later be investigated in patients with chronic spine pain disorders such as CPLBP.

Methods

Design overview

This parallel repeated-measures study was designed to capture potential treatment and time-dependent alterations of blood biomarkers of oxidative stress and pro-resolution mediators before and after a single thoracic SMT. For experiments, we used three experimental groups: control (preload only), single thoracic SMT with a total peak force of 400 N (400 N), and single thoracic SMT with a total peak force of 800 N (800 N). The study was approved by the Canadian Memorial Chiropractic College (CMCC) Research Ethics Board (REB# 192034). All participants provided written informed consent before participating in this study.

Study participants

Adults of both sexes aged between 18 and 45 from CMCC were invited to participate through e-mail, posters, and word of mouth between February and March 2020 before COVID- 19.

Inclusion and exclusion criteria

Potential participants were screened by a single examiner (FCKD) using a standardized screening form. Participants were included if they were asymptomatic (i.e., reporting no pain in any region of the body in the previous 30 days), had not received SMT in the last seven days, and did not present any acute health condition (e.g., acute musculoskeletal injury, cold, flu) in the week before the data collection day. Participants were excluded if they presented with central nervous system diseases (e.g., depression), inflammatory conditions (e.g., rheumatoid arthritis), hypertension, or chronic metabolic conditions (e.g., diabetes) that require regular intake of medication. Participants were excluded if they were pregnant or presented with any contraindication to thoracic SMT, such as a history of spinal surgery, thoracic spine fracture, spinal cord injury, osteoporosis, spinal infection, or neoplasm.

Sample size

The sample size was estimated based on a previous pre-post-experimental study, which involved dorsal SMT to asymptomatic individuals, resulting in a reported effect size of 30% (average effect size) on plasma biomarkers [22]. By using the General Power Analysis Program (G*Power) (University of Trier, Germany), it was estimated that for a repeated-measures study with three groups and three measurement points, 9 participants per group (3 groups) would be required to achieve an effect size of 0.30, with an alpha error of 5%, and power of 80%. Accounting for a 20% drop-out rate, we adjusted the target sample size to 11 participants per group (33 total).

Randomization and allocation

Using a random number generator (Microsoft Excel), participants were randomly allocated by an investigator not involved in data collection (MF) to one of the three groups: control, 400 N and 800 N. Group allocation was done by concealing opaque envelopes containing the identification numbers of the intervention groups and study participants. The envelopes were handed to the chiropractor (DS) performing the SMT on the testing session day using consecutively opened envelopes. The participants were blinded to their group allocation and, consequently, the experimental group.

The examiner assessing the outcome measures was blinded to the participant’s group allocation.

Force time characteristics: data acquisition

Analog data from the embedded force plate of the force-sensing table (FSTT®, Toronto, ON, Canada) were digitally sampled at 2000 Hz and converted to units of force (Newtons) using the manufacturer-specified calibration matrices. Preload force is defined as the force applied during the initial setup, the total peak force is designated as the maximum force value of the thrust, including the preload force, and time to peak (milliseconds) is defined as the time elapsed between preload force. Total peak force was extracted along all three axes of the force plate’s frame of reference using customized software (MATLAB, The MathWorks Inc., Natick, Massachusetts, USA). Given the prone posterior to anterior (P-A) nature of the forces applied during the thoracic SMT used in this study, variables from the P-A forces (forces vertical to the table - Fz) were extracted for SMT force-time characterization.

Intervention

A prone P-A thoracic SMT was applied at the T6-T9 spine region by a chiropractor (DS) with 13 years of clinical experience and 11 years of experience with the FSTT® to modulate the SMT force-time characteristics on pre-determined force targets. Two experimental groups received thoracic SMT with a total peak force magnitude of 400 N (± 150 N) (group 400 N) and with a total peak force magnitude of 800 N (± 150 N) (group 800 N). We chose 400 N peak force since it represents the average total peak force applied during P-A thoracic SMT according to the literature [23]. The 800 N peak force was selected because it represents a two-fold peak force from the reported average, and it is a common pre-determined peak force target during educational training [23]. To ensure SMT was delivered with the pre-determined forces (400 N and 800 N), real-time visual feedback of SMT force-time graphs was provided to the chiropractor. A third group, receiving P-A thoracic preload force (without thrust), was designed as a control group.

Blood sampling and treatment for analysis

Upon arrival at the laboratory, participants sat comfortably for 5 to 10 min while demographic characteristics (age, sex, height, weight) were recorded. At this point, participants were asked to confirm whether they still met the inclusion criteria, including no pain in any region of the body in the previous 30 days, no acute health issue in the last seven days and had not received SMT in the previous seven days. In addition, participants were asked to complete a set of visual analog scales (VAS) rating their pre-intervention (baseline) discomfort levels at the thoracic shoulder or neck area region from 0 to 10, corresponding to no discomfort and maximum discomfort, respectively. Participants also rated their discomfort level (VAS) a second time immediately after intervention and for the third time 20 min after intervention.

In preparation for blood collection, since we aimed to collect blood in three short-term time points (pre-, immediately after and 20 min after intervention), a peripheral intravenous line was established to avoid multiple venipunctures. Blood samples were consistently collected while participants were resting and seated comfortably. All blood samples were drawn in commercially available 10mL tubes (vacutainers) containing EDTA (ethylenediaminetetraacetic acid) anti-coagulant, gently shaken (2x) to mix blood with EDTA and kept at room temperature until participants’ sample collections were completed. The initial 2mLs were obtained in a tube and discarded [7]. All samples from the study participants were collected in the morning (from 8 am to 12 pm) to avoid circadian rhythm influences on the biochemical parameters assessed [24]. No information on the menstrual cycle of female participants was collected.

After completing the three blood draws from each participant, blood samples (pre-, immediately after and 20 min after intervention) were centrifuged at 3000 RPM for 15 min at four °C in a refrigerated centrifuge (Beckman Coulter Allegra X-22 Series). Plasma samples were aliquoted and stored at -80 °C. Red blood cells (RBCs) were collected and prepared as described previously [9] for analyses of erythrocyte hydroperoxide content (a biomarker of oxidative stress) [7]. For all biochemical studies, a microplate reader capable of measuring absorbance from 200 to 999 nm (Epoch absorbance reader, BioTek-VT-USA) was used; the assays were carried out in duplicate within ten months after collection.

Oxidative stress biomarkers: pro-oxidant parameters

Total oxidant status (plasma)

Total oxidative status (TOS) in blood samples can be used to estimate the overall individual pro-oxidative state. TOS was determined using the colorimetric method described by Erel [25]. The TOS concentration was calculated from the calibration curve of hydrogen peroxide, a potent oxidant. Results regarding micromolar hydrogen peroxide equivalent per litre (µmol H2O2 Equiv/L) were expressed.

Lipid peroxidation (LPO) (plasma)

Lipid peroxidation is a reactive process of oxidative stress-induced cell membrane damage by free radicals and reactive oxygen species (ROS). LPO is commonly determined by the quantification of its product, malondialdehyde (MDA). This study determined MDA content by the surrogate quantification of thiobarbituric acid reagents (TBARS) [26]. For the quantitative determination of TBARS, the R&D commercially available assay kit (TBARS assay, #KGE013) was used according to the manufacturer’s instructions. Results were expressed in micromolar of TBARS.

Lipid hydroperoxide content (LOOH) (erythrocytes)

Lipid hydroperoxide is a non-radical intermediate product generated by lipid peroxidation. The content of hydroperoxides in erythrocytes was determined using the method reported by Ochoa et al. (2003) [27]. Results were expressed in terms of micromolar per milligram of protein (µmol/mg protein).

Oxidative stress biomarkers: antioxidant parameters

Total antioxidant capacity (TAC) (plasma)

TAC works as a surrogate measure of the function of a pool of enzymatic and nonenzymatic antioxidants in the plasma sample that counteract pro-oxidant products. We used the total antioxidant capacity (TAC) assay kit (Cell Meter™ Colorimetric Antioxidant Activity Assay Kit, # 15900) according to the manufacturer’s protocol (AAT Bioquest). The antioxidant capacity of the sample was compared with that of Trolox, a potent antioxidant, and it was calculated as Trolox millimolar (mM) equivalent per litre.

Total bilirubin (plasma)

Bilirubin acts as an antioxidant in the blood by scavenging ROS and preventing oxidative damage to cells and lipids. According to the manufacturer’s protocol, plasma total bilirubin concentration was measured using a bilirubin assay kit (Sigma-Aldrich, #MAK126). Results are expressed in milligrams per deciliter (mg/dL).

Pro-resolution of inflammation mediator (Resolvin D1) (plasma)

Resolvin D1 is a specialized pro-resolvin lipid mediator derived from omega-3 polyunsaturated fatty acids that plays a crucial role in the resolution of inflammation and tissue repair. Resolvin D1 concentration was measured using a competitive ELISA kit per the manufacturer’s protocol (Cayman Chemist, MI-USA, #500380). Results are expressed in picograms per millilitre (pg/mL).

Protein measurement

Protein was measured using Bradford’s method according to manufacturer orientation (Millipore- Sigma, #1103060500, ON-Canada).

Outcomes

The primary outcome measures were blood parameters of oxidants, antioxidants, and pro- resolvin mediator (resolvin D1) sampled at pre-intervention, immediately after the intervention, and 20 min after the intervention. Secondary outcomes included the level of discomfort (VAS) at baseline, immediately and after 20 min of the intervention in the thoracic area, shoulder or neck area, and cavitation. The number of individuals presenting with discomfort relative to baseline in the VAS and the clinician’s perception of an audible popping sound (cavitation) after intervention was recorded and reported.

Statistical analysis

Participant characteristics (sex, age, weight, height, and body mass index calculation) were reported descriptively. Similarly, force-time characteristic outputs, presence of cavitation and number of participants with discomfort after intervention compared to baseline. Blood parameters of oxidants, antioxidants and resolvin D1 were analyzed using a mixed-effect model (REML) for small sample sizes to compare the participants’ biomarkers over time (baseline, immediately after, and after 20 min intervention) between the three groups (control, target 400, and 800 N), followed by Tukey’s multiple comparison test [28]. Pearson correlation coefficient was conducted to assess the linear relationship between the quantitative variables studied (i.e., force magnitude, oxidative stress biomarkers and pro-resolution mediator). Low (positive or negative) correlation corresponded to 0.30 to 0.50; moderate (positive or negative) corresponded to 0.50 to 0.70; high (positive or negative) correlation corresponded to 0.70 to 1 [29].

Data are presented as mean ± standard deviation (SD). Statistical analyses were performed in Prism (V. 9.0). Differences were considered statistically significant when the p- value was ≤ 0.05.

Results

Due to the COVID-19 global pandemic, participant recruitment was limited to the period between February and March 2020. Thirty-seven participants were identified and assessed for eligibility (Fig. 1). Twenty-one participants met the inclusion criteria. Out of the 21, two were excluded: one due to fainting after the first phlebotomy and the other because the pre-established limit of peak force variability (± 150 N) was exceeded in the target 400 N. The limit of peak force value was determined based on previous SMT force-time characteristics studies and aimed to keep the force-time characteristics of the SMT between participants allocated to similar groups within the same range, contributing to the intervention homogeneity and consistency of the force applied, minimizing the treatment’s interindividual variability on the study outcomes [23]. Therefore, data from 19 participants were used for the study analysis. The demographic characteristics of the study participants are presented in Table 1.

Fig. 1
figure 1

Study flow chart shows the number of participants for each intervention group included in the data analysis

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Table 1 Mean and standard deviation of demographic characteristics of the study participants
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Preload, total peak force and time to peak

Preload values were comparable between groups ranging from 151 N to 220 N with the mean(± SD) of 202.4 (16.38), 183.4 (14.24) and 197.8 (9.86) in the control, target 400 and 800 N, respectively (Table 2). Total peak force and time to peak were recorded only on the target 400 N and 800 N groups. The total peak force was highly consistent at the intended targets of 400–800 N, with small variability between individuals within each group (Table 2). As expected, the time to peak was slightly faster in the target 400 N group, approximately 100ms, compared to 134ms in the target 800 N group (Table 2).

Table 2 Mean ± SD of the force-time characteristics of the studied groups, number of participants presenting discomfort and cavitation after the correspondent interventions
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Blood biomarker of oxidative stress and pro-resolution of inflammation

Table 3 presents the mean ± SD values of the pro-oxidants, antioxidants and pro-resolution mediator at baseline, immediately after, and 20 min after intervention. Pro-oxidants, antioxidants and resolvin D1 parameters were normally distributed: Shapiro-Wilk test (p > 0.05). Also, Fig. 2A and B depict a correlation matrix with coefficient values between pro-oxidants, antioxidants and peak force variables right after and 20 min after intervention, respectively. Right after the intervention, we found a positive and significant correlation between pro-oxidant parameters LOOH and TOS (r = 0.72; p = 0.001), and there was a tendency to a positive correlation between pro-oxidant TOS and peak force (r = 0.42; p = 0.073) (Fig. 2A). Twenty minutes after intervention, a positive and significant correlation was found between pro-oxidant LPO and peak force (r = 0.60; p = 0.007) and between pro-oxidant parameters LOOH and TOS (r = 0.55; p = 0.015). In addition, a significant negative correlation between pro-oxidant TOS and resolvin D1 was found 20 min after intervention (r= -0.57; p = 0.011) (Fig. 2B). No other correlation was statistically significant (p < 0.05).

Table 3 Short-term mean ± (SD) group values of pro-oxidants, antioxidants and resolvin D1 in blood in the studied groups
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Fig. 2
figure 2

Paired Pearson correlation matrix between peak force and blood biomarkers of oxidative stress and pro-resolution mediator right after intervention (A) and 20 min after intervention (B). N = 19. Peak force: maximum force value registered during preload (control group), or maximum force value registered during preload + thrust (target 400 N and 800 N); TOS: total oxidant status; Lipid perox: (LPO-Lipid peroxidation); Lipid hydro: (LOOH-Lipid Hydroperoxide content); TAC: total antioxidant capacity; Total Bilirubin and Resolvin D1

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Pro-oxidants: TOS

In the present study, we observed an overall decrease in plasma TOS in both control and target 400 N groups. In contrast, an 80% and 75% increase in TOS was observed immediately after and 20 min after SMT, respectively, compared to the baseline in the 800 N. There was an interaction effect between intervention and time [F (4, 32) = 4.04, p = 0.009] on plasma TOS. Tukey’s multiple comparison test showed a significant difference between 400 N and 800 N (MD= -4.75; 95% CI [-9.364 to -0.142], p = 0.042) (Fig. 3A). In addition, multiple comparison tests showed that compared to baseline, a significant within-group decrease in TOS levels was observed in the target 400 N group immediately after (MD = 3.63; 95%CI [1.011 to 6.255]; p = 0.019) and 20 min after intervention (MD = 3.38; 95% CI [2.059 to 4.701]; p < 0.001 (Fig. 3A). Despite a slight decrease in TOS compared to the baseline in the control group or the increase in the target 800 N, no further main effect was observed, nor within and between-group difference through pairwise post-hoc test (p > 0.05).

Fig. 3
figure 3

Oxidative stress parameters of plasmatic total oxidant status (A), lipid peroxidation (B), and lipid hydroperoxide (C) in erythrocytes. Measurements were assessed pre-intervention (baseline), immediately after, and 20 min after intervention. Control intervention (preload only); 400 N (target 400 N thoracic SMT); 800 N (target 800 N thoracic SMT). SMT: posterior to anterior thoracic spinal manipulation. Values are presented as mean and standard error. Significance was set as an alpha of 0.05. * Denotes significance between baseline and immediately after the intervention. ** Denotes significance between baseline and 20 min after intervention. *** denotes significance between 400 N and 800 N groups. # denotes significance between 400 N and 800 N groups 20 min after intervention

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Pro-oxidants: LPO

Plasma LPO measured by TBARS had about a 20 and 30% decrease over time in the control and target 400 N, respectively, compared to the baseline. In contrast, an increase of approximately 30% over time was observed in the target 800 N compared to the baseline. Analysis of plasma LPO by mixed-effect model yielded a significant main effect of treatment [F (2, 16) = 4.66, p = 0.025] and interaction effect (intervention x time) [F (4, 32) = 3.10, p = 0.028]. Tukey’s multiple comparison tests showed that the decrease of LPO 20 min after 400 N SMT was statistically significant compared to baseline level (MD = 0.046; 95% CI [0.014 to 0.078]; p = 0.007) (Fig. 3B). No other main effect was observed, nor within and between-group statistical difference (p > 0.05).

Pro-oxidants: LOOH content

An overall increase of 15% in erythrocyte LOOH content was observed in the target 800 N, while a decrease of approximately 15% was observed in the target 400 N group. Mixed-effect model analysis revealed an interaction effect between intervention and time in the LOOH content in erythrocytes [F (4, 32) = 2.86, p = 0.038]. Tukey’s multiple comparison tests indicated a statistical difference between the 400 and 800 N groups 20 min after intervention (MD= -1.147; 95% CI [-2.263 to -0.030]; p = 0.044) (Fig. 3C). No other main effect was observed, nor within and between-group statistical difference (p > 0.05).

Antioxidants: TAC

The Mixed-effect model test revealed no main effect of the intervention [F (2, 16) = 1.11, p = 0.325], time [F (2, 16) = 1.02, p = 0.358] or interaction effect between intervention and time [F (4, 32) = 0.57, p = 0.685] (Fig. 4A). Despite the common sense that the multiple comparison tests are best done following the omnibus test’s rejection of the null hypothesis, the outputs from the two tests may only sometimes be concordant since they assess different aspects of the data. While the multiple comparisons test aims to determine if there is a mean difference using a pairwise comparison, the omnibus test compares the variation within each group to the variation of the mean of each group to test if the null hypothesis can be rejected [30]. Thus, when a Tukey’s multiple comparison test was conducted, there was evidence of a decrease of TAC immediately after 800 N compared to its baseline (MD = 0.060; 95% CI [0.008 to 0.112]; p = 0.030) with a fast recovery to its baseline levels after 20 min (Fig. 4A). No other within nor between-group statistical difference was observed (p > 0.05).

Fig. 4
figure 4

Plasmatic antioxidant parameters of total antioxidant capacity (A) and total bilirubin (B). Measurements were assessed pre-intervention (baseline), immediately after, and 20 min after intervention. Control intervention (preload only); 400 N (target 400 N thoracic SMT); 800 N (target 800 N thoracic SMT). SMT: posterior to anterior thoracic spinal manipulation. Values are presented as mean and standard error. Significance was set as an alpha of 0.05. * Denotes a significant within-group difference between baseline and immediately after intervention

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Antioxidants: total bilirubin

No main effect of the intervention [F (2, 16) = 0.96, p = 0.401], time [F (2, 16) = 0.06, p = 0.926] nor interaction effect between intervention and time [F (4, 32) = 0.46, p = 0.759] was observed in the assessment of total bilirubin (Fig. 4B). No other within nor between-group statistical difference was observed (p > 0.05).

Pro-resolution of inflammation mediator: resolvin D1

There was an interaction effect between intervention and time [F (4, 32) = 2.99, p = 0.032] on plasma Resolvin D1. Multiple comparison analysis found that Resolvin D1 levels decreased immediately after 800 N SMT, reaching a statistical difference 20 min after 800 N SMT compared to baseline (MD = 37.62; 95% CI [9.462 to 65.80]; p = 0.019) (Fig. 5). No other main effect was observed, nor within and between-group statistical difference (p > 0.05).

Fig. 5
figure 5

Lipid-derived pro-resolution of inflammation mediator resolvin D1 level in plasma. Measurements were assessed pre-intervention (baseline), immediately after, and 20 min after intervention. Control intervention (preload only); 400 N (target 400 N thoracic SMT); 800 N (target 800 N thoracic SMT). SMT: posterior to anterior thoracic spinal manipulation. Values are presented as mean and standard error. Significance was set as an alpha of 0.05. ** Denotes a significant within-group difference between baseline and 20 min after intervention

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Cavitation and discomfort

Table 2 summarizes the perception of the participant’s spine cavitation, characterized by an audible sound identified by the clinician during the SMT intervention. In short, all participants in the target 800 N group had thoracic cavitation, while six and three were noted in the target 400 N and control groups, respectively. None of the participants reported any discomfort after the intervention compared to baseline except one in the target 800 N group (Table 2).

Discussion

Our results suggest contrasting effects between 400 N and 800 N SMT on systemic blood oxidative stress biomarkers and lipid-derived pro-resolution of inflammation mediators in healthy subjects, although there is a need for further studies given the small sample size (n = 19). The recruitment of participants was severely impacted by the COVID-19 global pandemic, resulting in an insufficient sample size that limited the statistical power of our analyses. Consequently, the potential risk of type I (false positives) and type II (false negatives) errors - particularly type II errors - cannot be ruled out. While caution is required when interpreting these findings, our results are consistent with previous studies [4, 7]. Although the small sample size prevents definitive conclusions, this study underscores the need for further research into the short-term effects of a single thoracic SMT with varying force-time characteristics (force magnitudes) on systemic blood oxidative stress biomarkers and lipid-derived pro-resolution of inflammation mediators in healthy individuals.

Despite the limitations, target 800 N SMT seemed to lead to an increase of plasma and erythrocyte pro-oxidants (TOS, LPO and LOOH) with a parallel decrease in plasma TAC and resolvin D1; in contrast, target 400 N SMT seemed to decrease plasma and erythrocytes pro-oxidants TOS, LPO and LOOH, respectively with no changes in antioxidants nor resolvin D1 levels. Although it is early to conclude, these observations support our hypothesis that different SMT force-time characteristics may trigger contrasting effects on the assessed systemic pro-oxidant, antioxidant biomarkers, and pro-resolution mediators (resolvin D1). In addition, it builds on our previous findings of a panel of inflammatory cytokines presenting opposing behaviour upon target 400 and 800 N SMT thoracic SMT [4].

The oxidant/antioxidant system is a complex and fined-tune system of in vivo physiology.

Systemic redox signalling biomarkers have promising clinical utility in clustering patients according to biomarker characteristics. Previous studies on patients with cardiovascular disorders have shown that systemic redox signalling biomarkers were associated with the risk of developing cardiovascular events in post-menopause females and with poorer whole-body aerobic capacity, with direct implications in physical exercise tolerance in patients with chronic heart failure [31, 32]. In chronic MSK conditions such as osteoarthritis and low back pain, studies have shown that inflammatory cytokines and redox signalling biomarkers, which play a crucial role in regulating inflammatory responses, may be used to identify patients with a higher likelihood of presenting lower physical function, higher pain intensity, greater pain catastrophizing, and multiple painful areas (widespread pain) [16, 33]. Thereby, treatment strategies that aim to modify these biomarkers are of great relevance. In this regard, the findings from the present study are of great potential given the 400 N and 800 N SMT’s ability to modify systemic oxidative stress biomarkers. This is in agreement with pre-clinical and clinical evidence suggesting that SMT can modulate oxidants and antioxidant biomarkers while improving pain and physical function [7, 9, 18].

While several parameters can be used to estimate redox signalling biomarkers, we assessed (1) TOS to estimate the total oxidant content in the plasma sample, (2) LPO by measuring its final product formation after the action of oxidants on cellular membrane polyunsaturated fatty acids, and (3) LOOH in erythrocytes, which is an intermediate product of lipid oxidation [34, 35]. Our findings on pro-oxidants showed that single thoracic SMT of 400 N seemed to provide a short-term reduction in TOS compared to baseline and the target 800 N group (Fig. 3). Similarly, a decrease in the LPO and LOOH levels was observed in the 400 N group. Such a decrease likely allowed the within-group difference between baseline and 20 min in the LPO levels and between 400 N and 800 N in the LOOH.

In the opposite direction to what was observed in the 400 N group, the 800 N SMT induced a slight increase in all systemic pro-oxidant biomarkers compared to baseline. These results suggest that only 800 N increases oxidative stress in plasma and erythrocytes after SMT. Interestingly, peripheral blood mononuclear cells from healthy humans presented an initial reduction in mitochondrial activity after an oxidative challenge. Still, the mononuclear cells restored the physiological activity levels at three hours [36]. Since we did not evaluate oxidative biomarkers longer than 20 min, we cannot exclude the possibility that mononuclear cells are involved in the changes in oxidative stress biomarkers after 400 N and 800 N SMT.

Our preliminary findings that the target 800 N SMT seemed to rise systemic pro-oxidant biomarkers in the short term may be considered harmful and related to adverse events in the first place. For instance, after acute intense exercise in untrained healthy participants, an increase in systemic oxidants such as LPO is associated with the perception of exercise-induced pain in the short-term post-exercise recovery period [37]. In addition, in patients with chronic fatigue syndrome, an accentuated LPO was observed with a parallel decrease in non-enzymatic antioxidants in both a resting state and an acute bout of exercise [38,39,40]. In the present study, only one participant in the target 800 N group reported an increase in the VAS scale from zero to one immediately after the intervention. Also, despite the increase of pro-oxidants, the levels observed did not correspond to systemic levels observed in pathological disorders such as cancer and multiple sclerosis or fibromyalgia and osteoarthritis [41,42,43,44]. Therefore, the heightened pro-oxidant levels observed in the short-term after target 800 N SMT may not be the main drivers underlying the perception of the discomfort or adverse events up to 20 min after SMT, nor be deleterious/pathological. In addition, a pre-post study using massage therapy as an intervention reported increased levels of pro-oxidants and decreased anti-oxidants in healthy young participants [45]. Such a pattern of pro-oxidants/antioxidants has also been described after a bout of physical activity [35, 37]. The transient but not persistent, enhanced redox signalling biomarkers after acute physical activity are crucial in driving muscular, neuroimmune and other systemic adaptations, paving the foundations of regular exercise benefits in the neuro-immune system and pain [10]. Therefore, based on our study findings, we speculate that target 800 N may lead to a short-term, not persistent, transient increase of pro-oxidative stress. Such transient response may have an adaptive functional role as a secondary messenger and in activating transcription factors to enhance cellular survival, similar to what has been shown in other therapeutic strategies, such as regular physical activity [46]. However, further research is needed to determine whether the increase of oxidative stress is a transitory response followed by 800 N SMT and to understand this complex relationship between oxidative stress parameters and mechanical loadings of mechanotherapies.

Parallel to changes in oxidant biomarkers, 800 N total peak force SMT appeared to lead to a transitory decrease in plasma TAC immediately after the intervention since the levels returned to baseline after 20 min. Human plasma is endowed with an array of antioxidant defense mechanisms. TAC assay is widely used to estimate the global enzymatic (e.g., superoxide dismutase, catalase and selenium-dependent glutathione peroxidase) and non-enzymatic (e.g., ascorbate, urate, a-tocopherol, bilirubin, albumin) antioxidant components of a sample [34, 47, 48]. Since 800 SMT triggered a decrease in TAC levels, the antioxidant system was possibly required to counteract the increase of pro-oxidants observed after 800 N. Organisms maintain oxidative homeostasis through a sophisticated regulatory system that includes enzymatic and non-enzymatic antioxidants [49]. The measurement of TAC reflects the activity of important antioxidant defences such as albumin, uric acid, ascorbic acid, α-tocopherol and bilirubin [48]. Thus, the reduction of TAC immediately after 800 N may be associated with one or some of these antioxidants. When we investigated an individual antioxidant (bilirubin), no statistical difference after 800 N SMT was observed on bilirubin levels despite the slight elevation immediately after the intervention. Total bilirubin functions as a plasma non-enzymatic antioxidant, inhibiting nicotinamide adenine dinucleotide phosphate (NADPH) oxidase activity - a significant source of pro-oxidants and free radicals - and synergistically interacting with other antioxidants to inhibit lipid oxidation [50, 51]. Thus, future studies by our group will aim to assess the relationship between force magnitude and bilirubin and other individual antioxidant levels after 800 N SMT.

For the first time, the effects of SMT on lipid-derived pro-resolution of inflammation molecules were demonstrated. We observed a statistical decrease in resolvin D1 in the target 800 N group compared to its baseline, while no changes were observed in the target 400 N or the control group. Resolvin D1, a novel specialized pro-resolvin lipid mediator, contributes to the resolution of inflammation by reducing neutrophil trafficking to the injured site, diminishing oxidative stress and promoting the clearance of tissue debris and apoptotic cells [20]. Evidence also supports the role of resolvin D1 in controlling the exacerbation of afferent nerve activation, such as nociceptors, during peripheral sensitization and mechanical hyperalgesia through action on different TRP afferent receptors [52]. Thus, the decrease in resolvin D1 after 800 N SMT may be related to the parallel increase in pro-oxidants such as TOS, negatively correlated with resolvin D1. However, further basic science and clinical studies are warranted to understand further how SMT’s force-time characteristics relate to pro-resolution mediators and the utility of resolvins in spine pain and other cMSK conditions.

How could SMT alter oxidative stress and resolvin D1 levels? Even though it is early to speculate, it has been suggested that mechanical stimuli have the potential to be translated into mechanochemical signals through mechanotransduction [53]. At a cellular level, such signals can modulate local cellular factors in their respective plasma membrane or propagate the signals from the cellular plasma membrane to the nucleus, altering intracellular signalling biochemistry and gene activity [53]. Several endogenous sources can generate redox signalling biomarkers, such as fibroblasts, neutrophils, monocytes and macrophages, vascular endothelial cells, neurons, and glial cells [54,55,56]. However, muscle cells, neutrophils, monocytes, and macrophages are significant candidates contributing to the systemic levels [31]. In healthy individuals, the responses of both polymorphonuclear neutrophils and monocytes were significantly higher after SMT (compared to baseline) and significantly higher than in sham or soft-tissue treated subjects [57]. In activated immune cells, metabolic reprogramming during immune responses directly produces excessive cytosolic and mitochondrial ROS [58]. Resolvin D1 rescued macrophages from oxidative stress-induced apoptosis during efferocytosis, promoting resolution of inflammation [59]. Thus, immune cells such as monocytes and macrophages may be the link between the changes induced by SMT on oxidative stress biomarkers and resolvin D1 levels. However, this putative relationship should be further studied.

Although our results suggest that SMT force magnitude influences blood biomarkers of oxidative stress, this study has some limitations. Firstly, the small sample size. Our recruitment was limited due to COVID restrictions. The small sample size limited the generalizability of our findings. Thus, the robustness of our results still needed to be verified by large-scale studies. Furthermore, future investigations with a larger sample size will show whether the patient’s response is associated with variability observed after SMT. No cross-over study was made at this moment. Second, there is a lack of information on the menstrual cycle of the study participants. Since there was a higher number of women in 400 N than in 800 N and the control group, it is necessary to consider that this difference may impact our results. Future studies should investigate the relationship between the endocrine system, oxidative stress, inflammatory cytokines and resolvins, and mechanotherapy in women. Third, only a few pro-oxidative/antioxidant parameters were assessed. A recent study highlighted that a single redox signalling marker is of limited diagnostic and prognostic value and is insufficient to determine the extent and the implication of the oxidative stress of a given tissue/organ [36]. Therefore, a more comprehensive range of assays is recommended. Fourth, although no perception of discomfort/adverse event was reported, participants were only followed up to 20 min after SMT. It is known that most adverse events occur within the first 48 h after SMT [60]. Therefore, we cannot discount the possibility that adverse events occurred after the data collection period. Also, most participants had previous experience with chiropractic care and, thus, were not naïve to SMT. Being familiar with the treatment may mitigate perceived discomfort after intervention. Fifth, we conducted the study with young and healthy participants, limiting the findings’ interpretability to the clinical population. However, exploring the force-time characteristics in non-clinical participants allows us to determine which characteristics and outcomes are modifiable by different SMT force-time characteristics while providing highly valuable research direction and baseline values to inform future research in clinical populations. Sixth, we confined our determinations to oxidant/antioxidant biomarkers in systemic blood. Future studies are needed to determine a more comprehensive understanding of the SMT force-time characteristics and redox signalling biomarkers in several other cell types (e.g., muscle, white blood cells). Despite the limitations, this study explored a novel research question to explore how distinct SMT mechanical loadings influence systemic biomarkers of oxidative stress using a reliable, valid and reproducible methodology (FSTT®) to quantify the force-time characteristics during manual therapy interventions (i.e., SMT) [61, 62]. Unveiling the physiological events associated with mechanotherapies in a healthy cohort is a first step before studying the clinical population.

Conclusion

The findings from the present study showed that while 400 N seemed to decrease systemic TOS and lipid peroxidation biomarkers, 800 N appeared to transitorily increase these pro-oxidant parameters with further transitory reduction in plasma TAC and resolvin D1. Although our findings suggest that different SMT force magnitudes applied to the thoracic spine have a contrasting effect on the systemic redox signalling biomarkers and pro-resolution mediators in healthy participants, our study provided limited evidence due to the small sample size. As our results are consistent with previous studies [4, 7], they provide a basis for further research to strengthen and validate these findings. In addition, future studies are required to determine whether similar findings are seen in individuals with cMSK disorders such as CPLBP and neck pain to elucidate the clinical value of SMT’s force-time characteristics on oxidative stress and pro-resolution mediators. These findings are foundational to advancing our understanding of mechanobiology and mechanoimmunology in manual therapies.

Data availability

The datasets used and analyzed during the current study are available from the corresponding author upon reasonable request.

Abbreviations

cMSK:

Chronic musculoskeletal

CPLBP:

Chronic primary low back pain

SMT:

Spinal manipulation therapy

FSTT® :

Force sensing table technology

WHO:

World Health Organization

IFN-g:

Interferon gamma

IL-5:

Interleukin 5

IL-6:

Interleukin 6

P-A:

Posterior to anterior

EDTA:

Ethylenediaminetetraacetic acid

VAS:

Visual analogue scale

RBC:

Red blood cells

TOS:

Total oxidant status

TAC:

Total antioxidant capacity

LOOH:

Lipid Hydroperoxide content: Pro-oxidant

LPO:

Lipid peroxidation: Pro-oxidant

ROS:

Reactive oxygen species

References

  1. Ferreira ML, et al. Global, regional, and national burden of low back pain, 1990– 2020, its attributable risk factors, and projections to 2050: a systematic analysis of the global burden of Disease Study 2021. Lancet Rheumatol. 2023;5:e316–29.

    Article  CAS  Google Scholar 

  2. Hartvigsen J et al. What low back pain is and why we need to pay attention. The Lancet. 2018;391:2356–2367 Preprint at https://doiorg.publicaciones.saludcastillayleon.es/10.1016/S0140-6736(18)30480-X.

  3. World Health Organization. 2023- WHO guideline chronic primary low back pain treatments. WHO (2023). World Health Organization. WHO guideline for non-surgical management of chronic primary low back pain in adults in primary and community care settings. In, Licence: CC BY-NC-SA 30 IGO. Geneva: World Health Organization. 2023. https://www.who.int/publications/i/item/9789240081789

  4. Duarte FCK, et al. Effects of distinct force magnitude of spinal manipulative therapy on blood biomarkers of inflammation: a proof of Principle Study in healthy young adults. J Manipulative Physiol Ther. 2022;45:20–32.

    Article  PubMed  Google Scholar 

  5. Thompson WR, Scott A, Loghmani MT, Ward SR, Warden SJ. Understanding mechanobiology: physical therapists as a force in Mechanotherapy and Musculoskeletal Regenerative Rehabilitation. Phys Ther. 2016;96:560–9.

    Article  PubMed  Google Scholar 

  6. Gevers-Montoro C, Provencher B, Descarreaux M, Ortega de Mues A, Piché M. Neurophysiological mechanisms of chiropractic spinal manipulation for spine pain. Eur J Pain (United Kingdom). 2021;25:1429–48.

    Google Scholar 

  7. Kolberg C, et al. Peripheral oxidative stress blood markers in patients with chronic back or Neck Pain treated with High-Velocity, low-amplitude manipulation. J Manipulative Physiol Ther. 2015;38:119–29.

    Article  PubMed  Google Scholar 

  8. Teodorczyk-Injeyan JA, et al. Effects of spinal manipulative therapy on inflammatory mediators in patients with non-specific low back pain: a non- randomized controlled clinical trial. Chiropr Man Th. 2021;29:3.

    Article  Google Scholar 

  9. Duarte FCK et al. Spinal manipulation therapy improves Tactile Allodynia and Peripheral nerve functionality and modulates blood oxidative stress markers in rats exposed to knee-joint immobilization. J Manipulative Physiol Ther 42, (2019).

  10. Sies H, Jones DP. Reactive oxygen species (ROS) as pleiotropic physiological signalling agents. NNat Rev Mol Cell Biol.2020;21:363–383. Preprint at https://doiorg.publicaciones.saludcastillayleon.es/10.1038/s41580-020-0230-3.

  11. Corbacho-Alonso N, et al. Cardiovascular Risk Stratification based on oxidative stress for early detection of Pathology. Antioxid Redox Signal. 2021;35:602–17.

    Article  CAS  PubMed  Google Scholar 

  12. Tsirebolos G, et al. Emerging markers of inflammation and oxidative stress as potential predictors of coronary artery disease. Int J Cardiol. 2023;376:127–33.

    Article  PubMed  Google Scholar 

  13. Reiche EMV, et al. Immune-inflammatory, oxidative stress and biochemical biomarkers predict short-term acute ischemic stroke death. Metab Brain Dis. 2019. https://doiorg.publicaciones.saludcastillayleon.es/10.1007/s11011-019-00403-6.

    Article  PubMed  Google Scholar 

  14. Biganeh J, et al. Investigating the relationship between job stress, workload and oxidative stress in nurses. Int J Occup Saf Ergon. 2022;28:1176–82.

    Article  PubMed  Google Scholar 

  15. Hajjar I et al. Oxidative stress predicts cognitive decline with aging in healthy adults: an observational study. J Neuroinflammation 15, (2018).

  16. Bruehl S, et al. Oxidative stress is associated with characteristic features of the dysfunctional chronic pain phenotype. Pain. 2022;163:786–94.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Marrocco I, Altieri F, Peluso I. Measurement and clinical significance of biomarkers of oxidative stress in humans. Oxid Med Cell Longev 2017, (2017).

  18. Kolberg C, Horst A, Kolberg A, Belló-Klein A, Partata WA. Effects of High-Velocity, Low-Amplitude Manipulation on Catalase Activity in Men with Neck Pain. J Manipulative Physiol Ther. 2010;33:300–7.

    Article  PubMed  Google Scholar 

  19. Teodorczyk-injeyan JA, Mcgregor M, Triano JJ, Injeyan SH. Elevated Production of Nociceptive CC Chemokines and sE-Selectin in patients with Low Back Pain and the effects of spinal manipulation a Nonrandomized Clinical Trial. Clin J Pain. 2018;34:68–75.

    Article  PubMed  Google Scholar 

  20. Ji RR, Xu ZZ, Strichartz G, Serhan CN. Emerging roles of resolvins in the resolution of inflammation and pain. Trends Neurosci. vol. 2011;34:599–609. Preprint at https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.tins.2011.08.005.

  21. Tao X, Lee MS, Donnelly CR, Ji RR, Neuromodulation. Specialized Proresolvin Mediators, and Resolution of Pain. Neurotherapeutics 2020;17:886-899. Preprint at https://doiorg.publicaciones.saludcastillayleon.es/10.1007/s13311-020-00892-9.

  22. Molina-Ortega F, et al. Immediate effects of spinal manipulation on nitric oxide, substance P and pain perception. Man Ther. 2014;19:411–7.

    Article  PubMed  Google Scholar 

  23. Herzog W. The biomechanics of spinal manipulation. J Bodyw Mov Ther. 2010;14:280–6.

    Article  PubMed  Google Scholar 

  24. Kanabrocki EL, et al. Circadian variation in oxidative stress markers in healthy and type II Diabetic men. Chronobiol Int. 2002;19:423–39.

    Article  CAS  PubMed  Google Scholar 

  25. Erel O. A new automated colorimetric method for measuring total oxidant status. Clin Biochem. 2005;38:1103–11.

    Article  CAS  PubMed  Google Scholar 

  26. Tsikas D. Assessment of lipid peroxidation by measuring malondialdehyde (MDA) and relatives in biological samples: Analytical and biological challenges. Anal Biochem. 2017;524:13–30.

    Article  CAS  PubMed  Google Scholar 

  27. Ochoa JJ, et al. Oxidative stress in erythrocytes from premature and full-term infants during their first 72 h of life. Free Radic Res. 2003;37:317–22.

    Article  CAS  PubMed  Google Scholar 

  28. Detry MA, Ma Y. Analyzing repeated measurements using mixed models. JAMA. 2016;315:407.

    Article  CAS  PubMed  Google Scholar 

  29. Taylor R. Interpretation of the correlation coefficient: a Basic Review. J Diagn Med Sonography. 1990;6:35–9.

    Article  Google Scholar 

  30. Chen T, Xu M, Tu J, Wang H, Niu X. Relationship between Omnibus and Post-hoc tests: an investigation of performance of the F test in ANOVA. Shanghai Arch Psychiatry. 2018;30:60–4.

    PubMed  PubMed Central  Google Scholar 

  31. Yokota T et al. Systemic oxidative stress is associated with lower aerobic capacity and impaired skeletal muscle energy metabolism in heart failure patients. Sci Rep 11, (2021).

  32. Bourgonje MF et al. Systemic oxidative stress, aging and the risk of Cardiovascular events in the General Female Population. Front Cardiovasc Med 8, (2021).

  33. Goode AP et al. Biomarker clusters differentiate phenotypes of lumbar spine degeneration and low back pain: the Johnston County Osteoarthritis Project. Osteoarthr Cartil Open 4, (2022).

  34. Skutnik-Radziszewska A et al. Salivary Antioxidants and Oxidative Stress in Psoriatic Patients: Can Salivary Total Oxidant Status and Oxidative Status Index Be a Plaque Psoriasis Biomarker? Oxid Med Cell Longev. 2020;2020.

  35. Powers SK, Jackson MJ. Exercise-induced oxidative stress: Cellular mechanisms and impact on muscle force production. Physiol Rev. 2008;88:1243–1276. Preprint at https://doiorg.publicaciones.saludcastillayleon.es/10.1152/physrev.00031.2007).

  36. Pistono C, et al. Response to oxidative stress of peripheral blood mononuclear cells from multiple sclerosis patients and healthy controls. Cell Stress Chaperones. 2020;25:81–91.

    Article  CAS  PubMed  Google Scholar 

  37. Bussulo SKD, Ferraz CR, Carvalho TT, Verri WA, Borghi SM. Redox interactions of immune cells and muscle in the regulation of exercise-induced pain and analgesia: implications on the modulation of muscle nociceptor sensory neurons. Free Radic Res. 2021;55(9):757–775. Preprint at https://doiorg.publicaciones.saludcastillayleon.es/10.1080/10715762.2021.1953696.

  38. Jammes Y, Steinberg JG, Delliaux S, Brégeon F. Chronic fatigue syndrome combines increased exercise-induced oxidative stress and reduced cytokine and hsp responses. J Intern Med. 2009;266:196–206.

    Article  CAS  PubMed  Google Scholar 

  39. Lee JS, Kim HG, Lee DS, Son CG. Oxidative stress is a convincing contributor to idiopathic chronic fatigue. Sci Rep 8, (2018).

  40. Polli A, et al. Relationship between Exercise-induced oxidative stress changes and parasympathetic activity in chronic fatigue syndrome: an observational study in patients and healthy subjects. Clin Ther. 2019;41:641–55.

    Article  CAS  PubMed  Google Scholar 

  41. Farias ILG, et al. Correlation between TBARS levels and glycolytic enzymes: the importance to the initial evaluation of clinical outcome of colorectal cancer patients. Biomed Pharmacotherapy. 2011;65:395–400.

    Article  CAS  Google Scholar 

  42. Siotto M et al. Oxidative stress related to iron metabolism in relapsing remitting multiple sclerosis patients with low disability. Front Neurosci 13, (2019).

  43. Sarıfakıoğlu B, Güzelant AY, Güzel EÇ, Güzel S, Kızıler AR. Effects of 12-week combined exercise therapy on oxidative stress in female fibromyalgia patients. Rheumatol Int. 2014;34:1361–7.

    Article  PubMed  Google Scholar 

  44. Zhang X et al. Lipid peroxidation in osteoarthritis: focusing on 4-hydroxynonenal, malondialdehyde, and ferroptosis. Cell Death Discov. 2023;9. Preprint at https://doiorg.publicaciones.saludcastillayleon.es/10.1038/s41420-023-01613-9.

  45. Skubisz Z et al. Influence of Classical Massage on Biochemical Markers of Oxidative Stress in Humans: Pilot Study. Biomed Res Int. 2021;2021.

  46. Ayala A, Muñoz MF, Argüelles S. Lipid peroxidation: Production, metabolism, and signaling mechanisms of malondialdehyde and 4-hydroxy-2- nonenal. Oxid Med Cell Longev. 2014;2014.

  47. Frei B, Stocker R, Ames BN. Antioxidant defenses and lipid peroxidation in human blood plasma. PNAS. 1988;85:9748–52.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Rubio CP, Hernández-Ruiz J, Martinez-Subiela S, Tvarijonaviciute A, Ceron JJ. Spectrophotometric assays for total antioxidant capacity (TAC) in dog serum: an update. BMC Vet Res. 2016;12:1–7.

    Article  Google Scholar 

  49. Poljsak B, Å uput D, Milisav I. Achieving the balance between ROS and antioxidants: When to use the synthetic antioxidants. Oxid Med Cell Longev. 2013. Preprint at https://doiorg.publicaciones.saludcastillayleon.es/10.1155/2013/956792.

  50. Maruhashi T, Kihara Y, Higashi Y. Bilirubin and endothelial function. J Atheroscler Thromb. 2019;26:688–96.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. He L, et al. Antioxidants Maintain Cellular Redox Homeostasis by Elimination of reactive oxygen species. Cell Physiol Biochem. 2017;44:532–53.

    Article  PubMed  Google Scholar 

  52. Serhan CN. Pro-resolvin lipid mediators are leads for resolution physiology. Nature. 2014;510:92–101.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Wang N, Tytell JD, Ingber DE. Mechanotransduction at a distance: mechanically coupling the extracellular matrix with the nucleus. Nat Rev Mol Cell Biol. 2009;10:75–82.

    Article  CAS  PubMed  Google Scholar 

  54. Poljsak B, Å uput D, Milisav I. Achieving the balance between ROS and antioxidants: When to use the synthetic antioxidants. Oxid Med Cell Longev 2013, (2013).

  55. Pizzino G et al. Oxidative Stress: Harms and Benefits for Human Health. Oxid Med Cell Longev. 2017;2017.

  56. Bittar A, et al. Reactive oxygen species affect spinal cell type-specific synaptic plasticity in a model of neuropathic pain. Pain. 2017;158:2137–46.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Brennan PC, et al. Enhanced phagocytic cell respiratory Burst Induced by spinal manipulation: potential role of Substance P. J Manipulative Physiol Ther. 1991;14:399–408.

    CAS  PubMed  Google Scholar 

  58. Sun L et al. Innate-adaptive immunity interplay and redox regulation in immune response. Redox Biol. 2020;37. Preprint at https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.redox.2020.101759.

  59. Lee HN, Surh YJ. Resolvin D1-mediated NOX2 inactivation rescues macrophages undertaking efferocytosis from oxidative stress-induced apoptosis. Biochem Pharmacol. 2013;86:759–69.

    Article  CAS  PubMed  Google Scholar 

  60. Funabashi M, Carlesso LC. Symptoms patients receiving manual therapy experienced and perceived as adverse: a secondary analysis of a survey of patients’ perceptions of what constitutes an adverse response. J Man Manipulative Therapy. 2020;00:1–8.

    Google Scholar 

  61. Starmer DJ, Guist BP, Tuff TR, Warren SC, Williams MGR. Changes in manipulative Peak Force Modulation and Time to Peak Thrust among First-Year Chiropractic Students following a 12-Week Detraining Period. J Manipulative Physiol Ther. 2016;39:311–7.

    Article  PubMed  Google Scholar 

  62. Mikhail J, Funabashi M, Descarreaux M, Pagé I. Assessing forces during spinal manipulation and mobilization: factors influencing the difference between forces at the patient-table and clinician-patient interfaces. Chiropr Man Th. 2020;28:1–10.

    Google Scholar 

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Acknowledgements

We thank Dr. Stephen Injeyan for sharing his expertise and thoughtful insights during the study design and data collection and Isabella Magnani and Steven Tran for their technical support during data collection and analysis.

Funding

Internal Research Support Funding– Canadian Memorial Chiropractic College.

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Authors and Affiliations

  1. School of Health, Medical and Applied Sciences, CQUniversity, Brisbane, QLD, Australia

    Felipe C. K. Duarte

  2. Division of Research and Innovation, Canadian Memorial Chiropractic College, Toronto, ON, Canada

    Felipe C. K. Duarte, Martha Funabashi & David Starmer

  3. Department of Physiology, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil

    Wania A. Partata

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Contributions

FCKD, MF, DS: Contributions to the study conception and design. FCKD, MF, DS, WAP: Substantial contributions to data collection, analysis, and interpretation of data. FCKD: Manuscript drafting. FCKD, MF, DS, WAP: Manuscript review, edits, and comments until approval of the submitted version. FCKD: Principal investigator who obtained the funding.

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Correspondence to Felipe C. K. Duarte.

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Ethical approval was obtained from the Canadian Memorial Chiropractic College (CMCC) Research Ethics Board (REB# 192034). All participants provided written informed consent before participating in this study.

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Duarte, F.C.K., Funabashi, M., Starmer, D. et al. Preliminary insights into the effects of spinal manipulation therapy of different force magnitudes on blood biomarkers of oxidative stress and pro-resolution of inflammation mediators. Chiropr Man Therap 33, 8 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12998-025-00575-2

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Keywords

Chiropractic & Manual Therapies

ISSN: 2045-709X