Optical and Microdialysis Monitoring of Succinate Prodrug Treatment in a Rotenone-Induced Model of Mitochondrial Dysfunction in Swine

Optical and Microdialysis Monitoring of Succinate Prodrug Treatment in a Rotenone-Induced Model of Mitochondrial Dysfunction in Swine | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Optical and Microdialysis Monitoring of Succinate Prodrug Treatment in a Rotenone-Induced Model of Mitochondrial Dysfunction in Swine Alistair Lewis, Rodrigo M. Forti, Tiffany S. Ko, Eskil Elmér, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8148374/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Succinate prodrug NV354 is a promising therapy for mitochondrial dysfunction. We used diffuse optical and microdialysis techniques to characterize its effects on cerebral oxygen metabolism during rotenone poisoning. One-month-old swine received a four-hour co-infusion of rotenone with either the succinate prodrug NV354 (n = 5) or placebo (n = 5). Cerebral interstitial lactate continually increased in the placebo group (p < 0.01), but lactate levels plateaued in the NV354 group (p = 0.90), which is consistent with NV354’s ability to increase oxygen metabolism in large animals. The study presents first in vivo optical measurements of changes in cytochrome-c-oxidase redox state induced by primary mitochondrial dysfunction and mitochondrial-targeted drugs. Health sciences/Medical research Biological sciences/Neuroscience Biological sciences/Physiology Primary mitochondrial disease Succinate prodrug Cerebral oxygen metabolism Cytochrome-c-oxidase Diffuse optical spectroscopy Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Patients with primary mitochondrial disease are a heterogeneous population that experience mitochondrial dysfunction due to mutations in nuclear or mitochondrial DNA. 1 – 3 Mitochondrial dysfunction negatively affects almost every organ in the body, but the brain, with its high energy demand and critical dependence on mitochondrial bioenergetics, is especially at risk. 2 – 4 Among the most common causes of mitochondrial dysfunction in these patients is complex I dysfunction. 1 , 5 Current therapies are mostly limited to symptom management, but new emerging therapies, such as prodrugs and gene therapy, show promise. 6 , 7 Non-invasive tools that detect metabolic improvements could aid in the precision application of these and other neuroprotective therapies. Diffuse optical methods hold promise to address this need via their assessment of cerebral oxygen metabolism. 8 – 11 Here, assessments include a mitochondrial metric that probes the change in redox state of cytochrome-c-oxidase (CCO, also known as complex IV), 12–17 and hemodynamic metrics that probe cerebral blood flow (CBF), oxygen extraction fraction (OEF), and an index of cerebral metabolic rate of oxygen derived from CBF and OEF. 18 – 22 In healthy mitochondria, the electron transport chain transfers electrons from complexes I and II to coenzyme Q. Subsequently, electrons are transported through complex III and complex IV (CCO), culminating in the reduction of O 2 to water. Primary mitochondrial dysfunction impedes the electron in-flow rate to CCO. We hypothesize that this alters the equilibrium redox ratio of CCO, i.e. , it decreases the reduced form of CCO (redCCO) and increases the oxidized form (oxCCO). Primary mitochondrial dysfunction is also expected to induce secondary decreases in oxygen metabolism, which will decrease the tissue oxygen extraction from the blood, i.e. , OEF decreases. Herein, we aim to show the sensitivity of the optical metrics to complex I dysfunction induced by rotenone in swine. Rotenone is a highly specific complex I inhibitor, 23 and its administration in swine was previously shown to increase blood lactate and venous oxygen tension. 24 We also aim to characterize the metabolic effects of the succinate prodrug NV354 (methyl 3-[(2-acetylaminoethylthio)carbonyl]propionate) in the swine model. NV354 is designed to increase the concentration of succinate in mitochondria. 25 The provision of substrate directly to complex II enables increased electron flow through complex II to compensate for impaired electron flow through complex I. 25,26 Succinate itself will not passively transport across cell membranes due to its charged nature. NV354, however, is a stable, water-soluble thioester that does pass through cell membranes. Once inside the cell, NV354 is hydrolyzed by cellular esterases to release succinate (see supplementary material), which then enters mitochondria via the dicarboxylate carrier. NV354 has been shown to mitigate acute mitochondrial dysfunction in cellular and rodent models, 25–32 but its effects in large animal models have not been studied. Herein, we use diffuse optical methods together with cerebral microdialysis to monitor cerebral metabolism in a rotenone-induced swine model of complex I dysfunction. Cerebral microdialysis invasively measures the concentrations of interstitial lactate and pyruvate, and increases in interstitial lactate and lactate-pyruvate ratio (LPR) are often indicative of decreases in oxygen metabolism. 33 , 34 We track the temporal changes of the optical and microdialysis metrics induced by rotenone poisoning with and without NV354 treatment. We also directly compare mitochondrial and vascular-based optical metabolism metrics during these processes, i.e. , we determined the association between the variations of oxidized CCO (oxCCO) and OEF. These proof-of-concept results provide mechanistic insight into how succinate supplementation might benefit patients during metabolic crises. To our knowledge, this study also presents the first in vivo optical measurements and comparison of oxCCO and OEF changes induced by primary mitochondrial dysfunction and mitochondrial-targeted drugs. 2. Materials and Methods All animal care and procedures were conducted in adherence to the National Institute of Health Guide for the Care and Use of Laboratory Animals, with approval obtained from the Institutional Animal Care and Use Committee of the University of Pennsylvania. We confirm that this study is reported in accordance with ARRIVE guidelines ( https://arriveguidelines.org ). 2.1 Study Design Non-invasive broadband (bDOS) and frequency-domain (FD-DOS) diffuse optical spectroscopy, and invasive cerebral microdialysis sampling, were performed on 15 one-month-old Yorkshire swine ( sus scrofa , mean [range] weight = 10.8 [9.1–13.2] kg; purchased from Meck Farms, Lancaster, PA, USA) divided into three groups: a control group (n = 5), a rotenone + placebo group (n = 5), and a rotenone + prodrug group (n = 5). Relative cerebral blood flow was also monitored invasively with a laser Doppler probe (PeriFlux, Perimed Inc., Stockholm, Sweden). Neuromonitoring was performed during a 10-minute baseline period and for four hours during intravenous infusions (Fig. 1 ). The rotenone + placebo group received intravenous infusions of rotenone (0.125 mg/kg/h; Sigma-Aldrich, Burlington, MA, USA) and normal saline (100mg/kg/hr); the rotenone + prodrug group received intravenous infusions of rotenone (0.125 mg/kg/hr) and succinate prodrug (100 mg/kg/hr, NV354; Abliva AB, Lund, Sweden); the control group received no intravenous infusions. The rotenone + prodrug co-infusion models scenarios wherein intervention occurs during acute metabolic crisis. Thus, this study is designed to provide a proof-of-concept of NV354 prodrug’s ability to maintain mitochondrial function under stress; this maintenance of mitochondrial function is essential to show before testing rescue therapy protocols. Note, based on prior swine work, 24 we expected our choice of the rotenone infusion dose to result in complex I dysfunction without hemodynamic instability. Note also, the NV354 infusion dose we used was about twice as large as the doses that resulted in therapeutic benefits in rodent models. 26 , 31 , 32 Given the species differences in metabolism and the need to overcome potential blood-brain-barrier limitations, this larger dose helps ensure that therapeutic NV354 levels accumulate in the swine brain. Additional pre-study pilot testing of two one-month-old Yorkshire swine demonstrated that administration of this dose over 4 hours did not cause hemodynamic instability. Finally, we note that the neuroprotective benefits of NV354 were observed at 3 hours after initiation of treatment in rodent models. 31 , 32 This observation, along with unpublished data in rats that shows rapid uptake and release of succinate in the brain tissue at 5 minutes after intravenous bolus injection of 13 C-labeled NV354 (20 mg/kg), suggests that 4 hours enables assessment of drug effects after steady-state tissue levels of NV354 are achieved. Neuromonitoring devices were removed after the monitoring period, but intravenous infusions continued and animals were transferred to a magnetic resonance imaging (MRI) scanner. Intravenous infusions were stopped after a total duration of 6 hours. Animals were euthanized after MRI via bolus injection of potassium chloride. The present paper focuses on the changes in cerebral physiology measured during the first four hours of infusion; thus, the MRI analyses are outside the scope of this paper. 2.2. Animal Preparation, Anesthesia and Respiratory Management Swine were initially sedated with intramuscular injections of ketamine (20 mg/kg) and buprenorphine (0.02 mg/kg), followed by 2–3% inhaled isoflurane. After confirmation of adequate sedation via the absence of withdrawal response on toe pinch, swine were intubated with a 32 Fr/CH left-endotracheal tube (Covidien, Medtronic, Dublin, Ireland), and then mechanically ventilated with 2–3% isoflurane and 21% FiO 2 (positive end-expiratory pressure, 5 cmH 2 O; peak inspiratory pressure, 1-1.5 cmH 2 O/kg). The respiratory rate and maximum ventilation pressure were adjusted to maintain the end-tidal CO 2 between 38–42 mmHg. Catheters were placed with ultrasound guidance in the right femoral artery and bilateral femoral veins for arterial blood pressure monitoring, blood gas sampling, and drug administration. A central venous catheter was also placed in the superior vena cava for rotenone infusion; succinate prodrug and normal saline infusions were administered via the femoral vein. Next, neuromonitoring was placed; a hybrid bDOS/FD-DOS optical probe was sutured to the left forehead, a microdialysis catheter (CMA 71 Elite, mDialysis, Stockholm, Sweden) was inserted through a cranial burr hole to a depth of 1-1.5 cm into the brain parenchyma of the right frontal cortex, and a laser Doppler probe was inserted through a cranial burr hole and secured to the right frontal dura matter (Fig. 1 ). Intravenous fentanyl infusion (10 µg/kg/hr) was then started approximately 10 minutes prior to baseline data acquisition to provide analgesia for the duration of the study. 2.3. Data Acquisition Optical neuromonitoring of the left frontal cortex was performed with interleaved FD-DOS and bDOS data acquisition (Section 2.3.1 ). Baseline measurements were obtained immediately prior to the initiation of the 4-hour IV infusion period (Fig. 1 ). During baseline, 5-minutes of bDOS data was acquired first, followed by 5-minutes of FD-DOS data. During the IV infusion period (Fig. 1 ), the monitoring was comprised of 28 minutes of bDOS acquisition interleaved with 2 minutes of FD-DOS acquisition. Continuous laser Doppler monitoring of baseline-normalized relative cerebral blood flow ( i.e. , rCBF = CBF / CBF Baseline ) was performed in parallel. Cerebral microdialysis sampling (Section 2.3.2 ) was acquired at the end of the baseline period and every 30 minutes during the IV infusion period. Finally, systemic arterial and venous blood gas samples were drawn at the end of baseline, and at 30 minutes, 60 minutes, 120 minutes, 180 minutes, and 240 minutes during the IV infusion period. Per blood gas, we examined the venous lactate concentration (an indication of systemic anaerobic metabolism), arterial blood oxygen saturation (SaO 2 ), and hematocrit (Hct). Arterial blood oxygen content is readily calculated from the latter metrics: CaO 2 = 1.36×Hct×32.2×SaO 2 (units, mL O 2 / mL blood). 19 , 35 2.3.1 Optical Neuromonitoring FD-DOS and bDOS measurements were acquired with a commercially available system (MetaOx, ISS Inc, Champaign, IL, USA) and a custom-built system, respectively, using a single optical probe secured to the forehead (Fig. 1 , the probe is described in detail in supplementary material). The FD-DOS system comprised 16 intensity modulated lasers (4 lasers at each of 4 wavelengths, i.e., 680, 760, 805, 830 nm; modulation frequency, 110 MHz modulation) and 4 PMT detectors. (Note, the MetaOx is also capable of diffuse correlation spectroscopy (DCS) monitoring of blood flow; regrettably, DCS data quality was not sufficient for analysis due to low signal intensity (< 5,000 detected photons a second)). The bDOS system was comprised of a fiber-coupled halogen lamp (HL-2000-HP-FHSA, Ocean Optics, Dunedin, FL, USA) and a fiber-coupled custom f/1.5 high throughput spectrometer (650–1050 nm spectral range, 100 µm slit width, 4.8 nm FWHM resolution, TEC cooled to -15°C; Wasatch Photonics, Morrisville, NC, USA). FD-DOS and bDOS acquisition were sequentially interleaved as shown in Fig. 1 . During FD-DOS acquisition, the bDOS lamp shutter was closed, and during bDOS acquisition, the FD-DOS lasers and detectors were shut off. The FD-DOS and bDOS measurements were also calibrated before and after each monitoring session using a solid phantom with known optical properties and a spectrally flat reflectance standard (see supplementary material). 20 Cerebral measurements of OEF, tissue blood oxygen saturation (StO 2 ), total hemoglobin concentration (HbT), and differential change in the concentration of oxCCO relative to baseline (ΔoxCCO) were computed once every minute (see supplementary material). Note, optical monitoring specifically detects changes in the CuA center redox state in CCO; we do not probe CuB or other metallic centers. All concentration measurements are per volume of tissue. 2.3.2 Cerebral Microdialysis The cerebral microdialysis catheter is a selectively permeable membrane which permits the diffusion of small molecule biomarkers from interstitial fluid in the brain into circulating saline perfusate. 33 Normal saline was infused through the catheter (CMA 71 Elite, mDialysis AB, Stockholm, Sweden) at a rate of 1 µl/min, and the resulting dialysate was collected in a microvial. Microvial samples were stored and replaced every 30 minutes to examine temporal changes in collected biomarkers (Fig. 1 ). The samples were analyzed to determine their concentrations of lactate, pyruvate, glucose, and glycerol using an automated ISCUS Flex ™ Microdialysis Analyzer (mDialysis AB, Stockholm, Sweden). We also computed the lactate-pyruvate ratio (LPR) in each sample. Elevated LPR and elevated glycerol are often used as indications of increased anaerobic metabolism and cell injury, respectively. 33 2.4 Statistical Analysis Statistical analyses were performed in MATLAB R2022a (Mathworks Inc., Natick, MA, USA), and p-values ≤ 0.05 were considered significant. First, to assess differences between baseline physiology across experimental groups, we performed Kruskal-Wallis tests; if significance was found, we used a post hoc Wilcoxon rank-sum test between each group. Our primary hypotheses were: a) rotenone-induced complex I dysfunction in swine increases oxCCO, decreases OEF, and increases LPR, and b) prodrug treatment reduces these changes. We tested these hypotheses using time-averages of the differential changes from baseline, i.e. , ΔoxCCO and ΔOEF, averaged across 5-minute intervals before the microdialysis sampling points; this scheme provided uniform sampling of the optical and microdialysis metrics. To investigate temporal changes during the 4-hour IV infusion period, we performed both simple linear and 2-period piecewise linear mixed effects regressions of ΔoxCCO vs. time, ΔOEF vs. time, and LPR vs. time for the rotenone + placebo and rotenone + prodrug groups (using the fitlme MATLAB function). The time periods of the piecewise linear regressions were 0–2 hours and 2–4 hours. For the ΔoxCCO and ΔOEF regressions, random slopes were incorporated for each animal to account for individual variations in the trends (the intercept was forced to zero in the regressions because ΔoxCCO and ΔOEF are, by definition, zero at time zero). For the LPR regression, random slopes and intercepts were incorporated for each animal. Our rationale for using the 2-period piecewise regression is that it is among the simplest of analyses to account for a possible time-dependent effect. Such time-dependence could arise because the total delivered dose of rotenone and succinate prodrug increases with infusion time, and because higher doses (longer infusion times) may alter physiological responses. In the rotenone + placebo group, the adjusted R 2 values were larger for the simple linear regressions than for the piecewise linear regressions. The reverse was true for the rotenone + prodrug group. Thus, we present simple linear regressions for the rotenone + placebo group, and piecewise linear regressions for the rotenone + prodrug group. Note, for the control group, we only performed simple linear mixed effects regressions. In secondary analyses, we also evaluated the temporal changes of ΔHbT, StO 2 , mean arterial blood pressure (MAP), venous lactate, cerebral blood flow (measured with laser Doppler), hematocrit, arterial blood oxygen content (CaO 2 ), and additional microdialysis metrics ( i.e. , lactate, pyruvate, glycerol). As in the primary analyses, simple linear mixed effects regressions were performed for the control and rotenone + placebo groups, and 2-period piecewise linear mixed effects regressions were performed for the rotenone + prodrug group. We additionally hypothesized that oxidized CCO increases and OEF decreases are both associated with LPR increases, and that oxidized CCO increases are associated with OEF decreases. These hypotheses were tested with simple linear mixed effects regressions of LPR vs ΔoxCCO, LPR vs ΔOEF, and ΔOEF vs ΔoxCCO. We deemed an association to be significant if its regression slope p-value was ≤ 0.05. 3. Results Pre-infusion baseline summary statistics for the cerebral optical metrics, cerebral microdialysis metrics, and systemic lactate were similar between groups (Table 1 ). There was a marginally significant difference in baseline MAP between groups (p = 0.05). From post-hoc tests, MAP was found to be lower in the rotenone + placebo group compared to the control group (p = 0.02). MAP was not different between the rotenone + placebo and rotenone + prodrug groups, however, and thus MAP should not be a confounder per the differing temporal trends in optical and microdialysis metrics between those groups. Table 1 Pre-infusion baseline variables (from cerebral optical, cerebral microdialysis, and systemic measurements) presented as medians and interquartile ranges (p values from Kruskal-Wallis tests). The tissue scattering amplitude (A) and power (b) are defined in the supplementary material. Parameter Controls Rotenone + Placebo Rotenone + prodrug p Cerebral Optics OEF 0.63 (0.59, 0.66) 0.58 (0.54, 0.60) 0.58 (0.56, 0.63) 0.53 HbT (µM) 49.0 (44.4, 58.3) 49.8 (49.1, 55.2) 47.1 (46.6, 51.6) 0.57 StO 2 0.52 (0.49, 0.54) 0.55 (0.53, 0.58) 0.56 (0.51, 0.57) 0.47 A (cm − 1 ) 14.6 (14.2, 16.4) 15.4 (13.7, 16.3) 14.3 (13.7, 15.9) 0.89 b 1.0 (0.93, 1.1) 0.96 (0.89, 1.0) 1.0 (0.95, 1.1) 0.59 Microdialysis Lactate (mM) 0.84 (0.75, 1.5) 1.6 (0.95, 1.6) 0.59 (0.52, 0.74) 0.08 Pyruvate (µM) 70.2 (59.5, 105) 85.1 (57.0, 128) 65.6 (44.7, 79.6) 0.59 LPR 10.5 (9.34, 17.1) 16.5 (10.4, 21.3) 12.0 (8.23, 13.0) 0.60 Glycerol (µM) 17.4 (14.8, 20.9) 22.5 (18.3, 26.7) 9.83 (8.89, 14.2) 0.08 Systemic Venous Lactate (mM) 1.1 (0.79, 1.3) 1.0 (0.75, 1.3) 1.0 (0.79, 1.7) 0.91 MAP (mmHg) 73.6 (62.1, 83.3) 56.3 (52.7, 58.0) 66.8 (56.5, 78.7) 0.05 Hct (%) 22.0 (19.0, 25.0) 18.5 (17.5, 20.0) 18.0 (17.0, 20.2) 0.25 SaO 2 (%) 97.0 (96.5, 98.0) 97.0 (96.8, 97.2) 98.0 (97.8, 98.2) 0.14 CaO 2 (mL O 2 /mL blood) 9.44 (8.25, 10.8) 8.03 (7.62, 8.62) 7.98 (7.46, 8.86) 0.28 The cerebral microdialysis measurements of LPR, lactate, and pyruvate as a function of time for each group are shown in Fig. 2 (the glycerol metric is not plotted, but its regression slopes are tabulated in Table 2 ). As hypothesized, LPR remained constant in the control group and increased in the rotenone + placebo group (p = 0.02). The slope of the rotenone + placebo group increase, 2.3 per hour, shows a clinically meaningful change, i.e. , LPR approaches abnormal levels (> 20) 36 within a few hours. Contrary to our hypothesis, LPR also increased during the last two hours of infusion in the rotenone + prodrug group (p < 0.01) to levels of about 20. Interestingly, the LPR increase was driven by increasing lactate in the rotenone + placebo group, but in the rotenone + prodrug group, the LPR increase was driven by decreasing pyruvate (in combination with stabilizing lactate levels). The lactate increase in the rotenone + placebo group suggests increased anaerobic metabolism caused by rotenone-induced mitochondrial dysfunction. The pyruvate decrease and stabilized lactate in the rotenone + prodrug group suggest increased mitochondrial oxygen metabolism during the last two hours of infusion (the different trends in the first two hours of infusion could be due to drug loading; see Discussion). Table 2 Slopes (in per hour units) of the linear mixed effects regression fits of MAP, microdialysis glycerol, systemic venous lactate, and CaO 2 versus infusion time for each experimental group (see Table 1 for metric units). Note, there are two slopes in the piecewise fit for the prodrug group (period 1, 0–2 hours of infusion; period 2, 2–4 hours of infusion). The p-values for the null hypothesis of zero slope are also included. Controls Rotenone + Placebo Rotenone + Prodrug (Period 1 | Period 2) Slope (95% CI), p Slope (95% CI), p Slope (95% CI), p Slope (95% CI), p MAP -3.9 (-6.4, -1.5), < 0.01 -2.3 (-3.2, -1.3), < 0.01 -3.0 (-8.6, 2.5), 0.3 2.2 (-2.9, 7.3), 0.4 Glycerol 0.21 (-0.85, 1.3), 0.7 0.37 (-0.81, 1.6), 0.5 -2.2 (-7.6, 3.2), 0.4 0.85 (-1.4, 3.1), 0.4 Venous Lactate -0.03 (-0.17, 0.11), 0.6 0.25 (-0.01, 0.51), 0.06 0.32 (0.10, 0.52), < 0.01 0.94 (0.12, 1.76), 0.03 CaO 2 0.10 (-0.53, 0.73), 0.7 0.12 (-0.39, 0.63), 0.6 0.59 (-0.18, 1.37), 0.1 0.94 (-0.12, 2.00), 0.08 Small but significant cerebral lactate increases were observed in the control group (p = 0.03) and during the first two hours of infusion in the rotenone + prodrug group (p = 0.03). The control group increase might be a consequence of decreasing MAP (see Table 2 ), while the rotenone + prodrug group increase might reflect the residual lactate production following exposure to rotenone and prodrug. Cerebral glycerol concentration was approximately constant in all groups (Table 2 ), which suggests that cerebral cell membrane damage did not occur. The concurrent optical cerebral ΔoxCCO and ΔOEF data are plotted in Fig. 3 . oxCCO and OEF were constant in the control group. In the rotenone + placebo group, oxCCO marginally increased (p = 0.05), but contrary to our hypothesis, OEF remained constant (p = 0.80). Lastly, and contrary to our hypothesis, the rotenone + prodrug group exhibited a pronounced increase in oxCCO (p < 0.01) and decrease in OEF (p < 0.01). In addition, hematocrit (Hct) substantially increased in the rotenone + prodrug group (Fig. 4), which resulted in pronounced increases of optically measured total hemoglobin concentration (HbT). In the other two groups, small HbT increases were observed that may reflect a vasodilation response to decreasing MAP (Table 2 ). Laser Doppler showed constant rCBF in the control and placebo groups, and decreasing rCBF during the first two hours of infusion in the prodrug group. Finally, the direct associations ( i.e. , linear regressions slopes) between the metabolism metrics for each experimental group are reported in Table 3 . In the rotenone + prodrug group, LPR increases were linearly associated with an increase in oxCCO (p < 0.01) and a decrease in OEF (p < 0.01). In the other two groups, LPR increases were not associated with changes in the optical metrics. Similarly, oxCCO increases were linearly associated with OEF decreases only in the rotenone + prodrug group (p < 0.01). \ Figure 4 Temporal trends of cerebral ΔHbT (top row), Hct (middle row), and rCBF (bottom row) during the 4-hour infusion period of each experimental group (infusion begins at time zero). Note, laser Doppler measures the baseline-normalized rCBF. Each color represents a different subject, and the ΔHbT and rCBF points are five-minute averages of data prior to microdialysis sampling times. In all plots, the linear regression fit (solid line) with its 95% CI (shaded region) is shown, along with the p-value for the null hypothesis of zero slope. The fit is simple linear for the control and rotenone + placebo groups, and 2-period piecewise linear for the rotenone + prodrug group. rCBF data was available for only 4, 3, and 4 of the 5 subjects, respectively, in the control, rotenone + placebo, and rotenone + prodrug groups. Table 3 Linear associations between changes in metabolism metrics during the 4-hour infusion period of each experimental group. The linear mixed effects regression slope (95% confidence interval) and the p-value for the null hypothesis of zero slope are reported. Note, the slope units for the two ΔoxCCO associations are 1/µM, and the slope unit for LPR vs ΔOEF is dimensionless. Controls Rotenone + Placebo Rotenone + Prodrug Association Slope (95% CI), p Slope (95% CI), p Slope (95% CI), p LPR vs ΔoxCCO -0.96 (-5.6, 3.7), 0.68 0.67 (-6.6, 7.9), 0.93 4.9 (3.2, 6.7), <0.01 LPR vs ΔOEF -5.4 (-22, 11), 0.51 -0.76 (-59, 58), 0.98 -54 (-74, -35), <0.01 OEF vs ΔoxCCO 0.04 (-0.01, 0.09),0.12 -0.0005 (-0.026, 0.025), 0.97 -0.06 (-0.10, 0.02), <0.01 4. Discussion We performed non-invasive optical neuromonitoring and invasive microdialysis neuromonitoring in swine to evaluate the impairment of cerebral oxygen metabolism caused by rotenone inhibition of mitochondrial complex I, and the effects of NV354 succinate prodrug treatment on cerebral oxygen metabolism. Our use of a swine model with clinically relevant molecular and physiologic responses, and our technical innovations to monitor the metabolic responses (discussed below), are strengths of this work. Overall, the results suggest that rotenone exposure impaired cerebral oxygen metabolism, and that NV354 treatment increased cerebral oxygen metabolism during rotenone infusion. Thus, the results motivate the potential of NV354 to limit metabolic crisis. Furthermore, the results suggest that there are differences in metabolic effects of NV354 treatment in the early versus late periods of the infusion. Finally, though optical neuromonitoring shows promise to provide an additional outcome metric for adaptive trial design of patients with mitochondrial disease, future improvements in the technology’s brain sensitivity are needed to improve its ability to monitor small metabolic changes. 4.1 Cerebral Physiological Response to Rotenone Exposure Microdialysis evidence, i.e. , increasing LPR driven by increasing lactate concentration, supports the expectation that rotenone exposure impairs mitochondrial complex I. The cerebral lactate increase is a consequence of the increase in anaerobic metabolism needed to compensate for decreased oxygen metabolism. The optically measured oxCCO increase is consistent with our hypothesis. The observed oxCCO increase, however, was only marginally significant (p = 0.05), and the oxCCO data were not directly associated with the LPR changes. In addition, we had expected that diminished aerobic metabolism would result in less oxygen extraction from the vasculature (or decreased OEF), but the OEF optical metric remained constant. The lack of robust optical detection of the complex I impairment, e.g. , compared to detection by microdialysis, could be a consequence of extra-cerebral tissue contamination ( e.g. , from scalp and skull) and experimental noise, both of which reduce the sensitivity of optics to cerebral metabolic changes. 37 – 39 Specifically, we expect that extra-cerebral tissues to have a much lower metabolic rate of oxygen than the brain, and thus extra-cerebral tissues may not be impacted significantly by rotenone. Accordingly, extra-cerebral tissue contamination can lead to underestimation of the cerebral metabolic effect, which makes it more challenging to separate metabolic effects from experimental noise. Prior work has suggested that oxCCO, which directly probes mitochondria, is less confounded by extra-cerebral tissue contamination because of much higher concentrations of mitochondria in the brain compared to the skull or scalp. 37 , 40 , 41 Thus, our observations of increased oxCCO and constant OEF could be a consequence of the improved brain sensitivity of the oxCCO metric. Finally, although we hypothesized that complex I inhibition should increase oxCCO concentration, this expectation requires assumptions and is not obvious. Since Complex I inhibition lowers mitochondrial metabolism, one might anticipate a decrease in both the electron in-flow rate to CCO and the out-flow rate from CCO. The concentration of oxCCO depends on both in-flow and out-flow rates; with Complex I inhibition, both rates should decrease. However, oxCCO concentration can still increase if the decrease of in-flow rate is larger than the decrease of out-flow rate. Indeed, if the net difference between the in-flow and out-flow rates is smaller than the absolute reduction in the in-flow rate, then rotenone-induced complex I inhibition will have a smaller effect on oxCCO concentration compared to its effect on cerebral lactate. As to why oxCCO increases at all, the out-flow rate during complex I inhibition might be sustained by normal intracellular oxygen concentrations. Indeed, in patients with acute brain injury, there is evidence of an association between oxygen concentration and the CCO redox state. 42 , 43 Thus, although isolated rat liver 44 , 45 and pigeon heart 46 mitochondria experiments show that non-hypoxic intracellular oxygen concentrations ( i.e. , above ~ 10 mmHg 44 , 45 and ~ 1 mmHg 46 thresholds) do not influence the redox state of CCO in healthy mitochondria, the rotenone-induced impairment could yield “unhealthy” mitochondria that have altered relationships between CCO redox state and oxygen. 4.2 Cerebral Physiological Response to Succinate Prodrug Treatment Our results suggest that NV354 prodrug treatment increased oxygen metabolism during rotenone infusion, and that the prodrug had different metabolic effects early versus late in the infusion period. The primary evidence supporting these findings is derived from microdialysis metrics. Cerebral interstitial lactate levels stabilized later in the infusion period; this observation suggests that cerebral lactate production was normalized as a result of increased oxygen metabolism and increased generation of ATP from mitochondria. In addition, the increase in cerebral lactate during the first 2 hours of prodrug infusion appears to be attenuated compared to the increase in cerebral lactate from rotenone infusion alone (unfortunately, we are not powered to show a significant difference). The complete stabilization of cerebral lactate during the second 2 hours of infusion might be due to the accumulation of larger intracellular succinate levels. In addition, the stabilization of cerebral lactate coincided with pyruvate decreases. Note, the different early- versus late-time metabolic effects could be a consequence of drug loading. That is, since the total drug dose delivered increases with infusion time, the drug might only reach therapeutic levels inside cells during the second 2 hours of treatment. Our results also illustrate the complexities of interpreting the microdialysis LPR metabolism metric, which was observed to increase in both the rotenone + placebo and rotenone + prodrug groups. Specifically, an increase in LPR driven by increased lactate reflects indicate glycolytic upregulation and impaired oxygen metabolism. An increase in LPR driven by decreased pyruvate and stabilized lactate levels, by contrast, suggests enhanced oxygen metabolism. Thus, changes in LPR are best interpreted in context of the separate, independent changes in lactate and pyruvate concentration. The observed OEF decrease in the rotenone + prodrug group is not consistent with our original hypothesis. Rather, the OEF decrease is likely explained by the increased arterial blood oxygen content (CaO 2 ) that arose from increased hematocrit, i.e. , OEF will decrease if the increase in cerebral oxygen delivery exceeds the increase in cerebral oxygen metabolism. 19 , 35 The observed hematocrit increase was puzzling and unexpected, and a future study is needed to confirm and understand the effect. Similarly, the rCBF decrease during the first two hours of infusion was also unexpected and might be a consequence of increased CaO 2 . Note however, the laser Doppler blood flow measurements may also have artifacts from vasculature in the dura matter, 47 since the laser Doppler probe was resting on top of the dura. Artifacts could arise, for example, if dural and cortical flows had different trends. Finally, the observed increase in oxCCO during rotenone and prodrug infusion was not consistent with our original hypothesis. Since the change in oxCCO concentration depends on the difference between electron in-flow rate to CCO and electron out-flow rate from CCO (see Fig. 5 ), an increase in oxygen metabolism from increased mitochondrial respiration is typically accompanied by increases in both the electron in-flow and out-flow rates. The oxCCO concentration will only vary if the difference between the out-flow and in-flow rates changes. Accordingly, the oxCCO increase we observed indicates that the out-flow rate increased more than the in-flow rate. This could be explained by a prodrug-induced decrease in the proton electrochemical potential across the inner mitochondrial membrane and a resultant increase in ATP synthesis (see Fig. 5 ); prior work has suggested that this effect will disproportionately increase the electron out-flow rate. 48 Future work is needed to better understand and test predictions about the relation between oxCCO concentration and metabolic demand in vivo , given the different factors at play in our study. 4.3 Importance of the Analysis Algorithm for oxCCO measurements Our optical analysis algorithm leveraged photon diffusion theory to quantify changes in oxCCO (see supplementary material). In contrast to the modified Beer-Lambert schemes that are commonly used for these measurements (see supplementary material), 9 photon diffusion theory more readily accounts for changes in tissue scattering. 15 , 49 In our experiments, we did indeed observe significant tissue scattering changes over time. Specifically, in the rotenone + placebo group, the Mie scattering parameters, A (p < 0.01) and b (p = 0.02), both decreased over time, and in the rotenone + prodrug group, b decreased over time (p = 0.02). Importantly, we found that if the modified Beer-Lambert scheme was used for analysis, then the estimated ΔoxCCO temporal change was no longer significant in the rotenone + placebo group ( i.e. , p = 0.80). Further, although the modified Beer-Lambert scheme still showed 2nd period increases in ΔoxCCO for the rotenone + prodrug group, the magnitude of the increase was smaller than that of the photon diffusion theory scheme ( i.e. , a slope of 0.08 µM/h (p = 0.04) versus 0.19 µM/h (p < 0.01) obtained with photon diffusion theory). These findings thus suggest the importance of employing full photon diffusion theory for oxCCO measurement if tissue scattering changes. 4.4 Limitations The sample size of our study is small (n = 5 in each group), and therefore our findings need confirmation from a larger study. Second, while our suggestion of increased mitochondrial oxygen metabolism is consistent with the data, we lack direct evidence of increased pyruvate usage in the tricarboxylic acid (TCA) cycle during prodrug treatment. In future work, such evidence could be gleaned from cerebral metabolomics analysis of the metabolites involved in glycolysis and TCA cycles. 50 Third, the co-treatment paradigm at a single prodrug dose regiment limits direct therapeutic interpretation. However, the stabilization of cerebral lactate levels and normalized pyruvate metabolism demonstrates that NV354 prodrug can maintain oxidative capacity under metabolic stress. This proof-of-concept is essential before testing rescue therapy protocols, and it also provides mechanistic insight into how succinate supplementation might benefit patients during metabolic crises. Future dose-response investigations will be important for clinical translation. Future study of the effects of NV354 treatment alone are also warranted. Though the present study does not have an NV354-only experimental group, we note that in a prior study of rodents, 31 NV354 treatment alone did not show any differences (compared to shams) in MAP, venous blood gases, and cerebral mitochondrial respirometry. Thus, we expect that our findings of baseline stability in our control group will be similar to those that result from the administration of NV354 treatment alone. Fourth, future study with longer-term monitoring is needed to relate the acute effects of prodrug treatment to longer-term therapeutic effects. That said, the acute intervention efficacy we observed is a prerequisite for longer-term benefits, and it is also relevant for mitochondrial emergencies that require rapid intervention in acute critical illness. Thus the present study has taken an important step on the clinical translation pathway for human studies. Finally, to derive the optical metrics, we have assumed homogeneous tissue optical properties and constant total CCO concentration. These assumptions can lead to errors, for example caused by extra-cerebral tissue contamination or by tissue-dependent changes in mitochondria density. The magnitude of the errors arising from these effects should be explored in future work. 5. Conclusion We employed frequency-domain and broadband diffuse optical spectroscopy techniques to monitor cerebral oxygen extraction fraction (OEF), oxidized cytochrome-c-oxidase concentration changes (ΔoxCCO), and total hemoglobin concentration (HbT) in a preclinical trial of a novel succinate prodrug (NV354) for treating rotenone-induced mitochondrial complex I dysfunction in swine. Invasive cerebral microdialysis measurements of lactate, pyruvate, and lactate-pyruvate ratio (LPR) in the interstitial fluid of the brain parenchyma were also obtained, providing traditional information about cerebral metabolism. Our results indicate mildly impaired cerebral oxygen metabolism from rotenone-induced complex I dysfunction in the rotenone-placebo group and increased cerebral oxygen metabolism due to prodrug treatment in the rotenone-prodrug group. Specifically, the former impairment is suggested by increased LPR, lactate and oxCCO concentrations. The latter metabolism enhancement is suggested by stabilized cerebral lactate concentration and decreased pyruvate concentration. Thus, our results demonstrate that the prodrug treatment normalized cerebral lactate production in large animals with mitochondrial impairment, which provides a proof-of-concept of the prodrug’s ability to maintain mitochondrial function under stress. To our knowledge, this study provides the first in vivo optical measurements of oxCCO and OEF changes induced by primary mitochondrial dysfunction and mitochondria-targeted drugs. Notably, the oxCCO metric of metabolism that probes the mitochondria was found to be more sensitive to mitochondrial dysfunction than the OEF metric that probes the tissue vasculature. Interpreting the oxCCO metric, however, is challenging. Our work suggests that it increased in both the placebo group and the prodrug group for different reasons. Declarations Acknowledgments: The authors would like to thank the veterinary staff at the Children’s Hospital of Philadelphia, members of the Resuscitation Science Center (Lucas Hobson, Yuxi Lin, Karli Wulwick, Anthony Davis, Takayuki Sueishi, Shannon Morton, Sarah Morton, Kate Stumpf, Jonathan Starr and Nick Fagan), the June and Steve Wolfson Laboratory (Nicolina Raneri, Alyssa Seeney, Rika Goto, April Hurlock and Darci Anderson), and the Yodh Biomedical Optics Group (Joseph Majeski, Zaha Shahdad and Ken Abramson) for their constructive discussion and comradery. The authors would also like to thank Sarah Piel, Magnus Hansson, and Sergei Vinogradov for their feedback and comments. Finally, the authors gratefully acknowledge discussions with Gemma Bale and Ilias Tachtsidis for their advice about the optical cytochrome-c-oxidase measurements. Author contributions: Conceptualization: T.J.K., M.J.M, W.B.B., T.S.K., R.M.F.; experiments: A.L., R.M.F., T.S.K., M.J.M.; data analysis and figures: A.L., R.M.F., E.E., T.S.K., A.G.Y., W.B.B.; interpretation of data: all authors; drafting the work (A.L., W.B.B.) or revising it critically for important intellectual content (R.M.F., T.S.K., E.E., M.J.M., A.G.Y., T.J.K.). All authors approved the final version. Funding: National Institutes of Health grants R01-NS113945 (W.B.B.), P41-EB029469 (A.G.Y.), and R01NS114656 (M.J.M); the Children’s Hospital of Philadelphia Frontier Program (T.S.K., R.M.F., W.B.B., T.J.K.), Department of Defense grant PR171698 (T.J.K), and American Heart Association grant 24SCEFIA1260971 (T.S.K.). Competing interests: E.E. has received salary support and/or travel reimbursements and/or grants from Abliva AB, a Swedish public company developing pharmaceuticals in the field of mitochondrial medicine. E.E. is currently an Abliva employee and member of its management team. Abliva AB has filed patents related to succinate prodrugs (listed below), some of which name E.E. as an inventor. The other authors declare no competing interests. Succinate prodrug, compositions containing the succinate prodrug and uses thereof (US20230033294-A1, 11565998-B2, 20220162162-A1) Novel cell-permeable succinate compounds (US20210401792-A1, 20170105961-A1) Cell-permeable succinate compounds (US11147789-B2) Succinate prodrugs for use in the treatment of lactic acidosis or drug-induced side-effects due to Complex I-related impairment of mitochondrial oxidative phosphorylation (US10307389-B2, 20170100359-A1) Protected succinates for enhancing mitochondrial ATP-production (US9670175-B2, 20150259317-A1) Prodrugs of succinic acid for increasing ATP-production (US20170105960-A1) Data availability: The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. References Niyazov, D. M., Kahler, S. G. & Frye, R. E. Primary Mitochondrial Disease and Secondary Mitochondrial Dysfunction: Importance of Distinction for Diagnosis and Treatment. Mol. 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Lee, J., Armstrong, J., Kreuter, K., Tromberg, B. J. & Brenner, M. Non-invasive in vivo diffuse optical spectroscopy monitoring of cyanide poisoning in a rabbit model. Physiol. Meas. 28 , 1057–1066. 10.1088/0967-3334/28/9/007 (2007). Gowda, G. A. et al. Metabolomics-based methods for early disease diagnostics. Expert Rev. Mol. Diagn. 8 , 617–633. 10.1586/14737159.8.5.617 (2008). Additional Declarations Competing interest reported. E.E. has received salary support and/or travel reimbursements and/or grants from Abliva AB, a Swedish public company developing pharmaceuticals in the field of mitochondrial medicine. E.E. is currently an Abliva employee and member of its management team. Abliva AB has filed patents related to succinate prodrugs (listed below), some of which name E.E. as an inventor. The other authors declare no competing interests. Succinate prodrug, compositions containing the succinate prodrug and uses thereof (US20230033294-A1, 11565998-B2, 20220162162-A1) Novel cell-permeable succinate compounds (US20210401792-A1, 20170105961-A1) Cell-permeable succinate compounds (US11147789-B2) Succinate prodrugs for use in the treatment of lactic acidosis or drug-induced side-effects due to Complex I-related impairment of mitochondrial oxidative phosphorylation (US10307389-B2, 20170100359-A1) Protected succinates for enhancing mitochondrial ATP-production (US9670175-B2, 20150259317-A1) Prodrugs of succinic acid for increasing ATP-production (US20170105960-A1) Supplementary Files LewisSciReportsSupplementaryMaterial.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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09:13:41","extension":"png","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":44706,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8148374/v1/a162b00cd6ef74fa92aec735.png"},{"id":97382732,"identity":"889f5ac2-44ff-4bfd-8d80-2ca2e2d5ac0c","added_by":"auto","created_at":"2025-12-03 18:40:09","extension":"png","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":167416,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8148374/v1/20622f9ce0fd3f7eb7fefd3b.png"},{"id":97382729,"identity":"100c42e5-71c7-4c71-bb7a-af7181df221e","added_by":"auto","created_at":"2025-12-03 18:40:09","extension":"png","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":121862,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8148374/v1/b04feafb38a629fb97657665.png"},{"id":97665490,"identity":"2999f040-454d-41ed-88b3-6068826448ea","added_by":"auto","created_at":"2025-12-08 09:18:43","extension":"png","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":147247,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8148374/v1/9f15fc302338ad2c448d6de9.png"},{"id":97664735,"identity":"849559ab-ab99-4b78-8d1b-2e2e67c1b407","added_by":"auto","created_at":"2025-12-08 09:13:37","extension":"png","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":64165,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8148374/v1/2857cf868a56642d7fa6ae4d.png"},{"id":97382734,"identity":"c70dfd63-54b3-4089-a933-be931b1bd556","added_by":"auto","created_at":"2025-12-03 18:40:09","extension":"xml","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":148378,"visible":true,"origin":"","legend":"","description":"","filename":"93a73a7444964efa855f585edb9ba32f1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8148374/v1/1cdbb89977b00685b283890c.xml"},{"id":97382736,"identity":"471d3245-b0d1-47ee-942c-6803397821fb","added_by":"auto","created_at":"2025-12-03 18:40:09","extension":"html","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":162880,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8148374/v1/f0f3044e43a3706203d6cd31.html"},{"id":97382721,"identity":"42631121-32e7-4230-bbda-dd46a369f555","added_by":"auto","created_at":"2025-12-03 18:40:09","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":171140,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStudy Timeline: \u003c/strong\u003eAfter baseline measurements (\u003cem\u003ei.e., \u003c/em\u003e5-minutes bDOS, then 5-minutes FD-DOS), physiological monitoring was performed for a four-hour IV infusion period (infusion administered according to group). Monitoring was comprised of 28 minutes of bDOS (solid grey line) interleaved with 2 minutes of FD-DOS (red rectangles), cerebral microdialysis sampling (green circles), and systemic blood gas sampling (black circles); continuous cortical perfusion monitoring was also acquired invasively with a laser Doppler probe secured to the frontal dura matter.\u003cstrong\u003e \u003c/strong\u003eThe FD-DOS/bDOS opticalprobe was sutured to the skin on the left forehead, and the microdialysis sensor was inserted through a burr hole into the interstitial space of the right frontal cortex. The optical probe comprised one bDOS and four FD-DOS source-detector pairs (bDOS source-detector separation, 3.0cm; FD-DOS source-detector separations, 1.5, 2.0, 2.5, 3.0 cm). Finally, the structural formula of the NV354 succinate prodrug is depicted within the purple box.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8148374/v1/df2fadd3fa3608fb94cb221c.jpeg"},{"id":97665037,"identity":"af202cfb-b819-4c22-9521-51a328f0a931","added_by":"auto","created_at":"2025-12-08 09:16:02","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":671789,"visible":true,"origin":"","legend":"\u003cp\u003eTemporal trends of cerebral microdialysis LPR (top row), lactate (middle row), and pyruvate (bottom row) metrics during the 4-hour infusion period of each experimental group (infusion begins at time zero). Each color represents a different subject. In the rotenone+prodrug group, LPR data for 1 of the 5 subjects is missing due to instrument malfunction (there are also 3 missing datapoints in another subject, light blue color). In all plots, the linear regression fit (solid line) with its 95% CI (shaded region) is shown, along with the p-value for the null hypothesis of zero slope. The fit is simple linear for the control and rotenone+placebo groups, and 2-period piecewise linear (periods separated by dashed vertical line) for the rotenone+prodrug group (see Section 2.4).\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8148374/v1/af221f41b12124321703c1e7.png"},{"id":97382720,"identity":"fc5e085f-c033-4596-aa46-eca4cc5f4145","added_by":"auto","created_at":"2025-12-03 18:40:09","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":471373,"visible":true,"origin":"","legend":"\u003cp\u003eTemporal trends of cerebral ΔoxCCO (top row) and ΔOEF (bottom row) during the 4-hour infusion period of each experimental group (infusion begins at time zero). Each color represents a different subject, and the points are five-minute averages of data prior to microdialysis sampling times (see Figure 1). In all plots, the linear regression fit (solid line) with its 95% CI (shaded region) is shown, along with the p-value for the null hypothesis of zero slope. The fit is simple linear for the control and rotenone+placebo groups, and 2-period piecewise linear (periods separated by dashed vertical line, p-value for the null hypothesis of zero slope shown for each period) for the rotenone+prodrug group (see Section 2.4).\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8148374/v1/d15e0d190a12de6c3223fa3b.png"},{"id":97664900,"identity":"09bf196e-47e8-449f-b5ea-41bd409f6834","added_by":"auto","created_at":"2025-12-08 09:15:25","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":571446,"visible":true,"origin":"","legend":"\u003cp\u003eTemporal trends of cerebral ΔHbT (top row), Hct (middle row), and rCBF (bottom row) during the 4-hour infusion period of each experimental group (infusion begins at time zero). Note, laser Doppler measures the baseline-normalized rCBF. Each color represents a different subject, and the ΔHbT and rCBF points are five-minute averages of data prior to microdialysis sampling times. In all plots, the linear regression fit (solid line) with its 95% CI (shaded region) is shown, along with the p-value for the null hypothesis of zero slope. The fit is simple linear for the control and rotenone+placebo groups, and 2-period piecewise linear for the rotenone+prodrug group. rCBF data was available for only 4, 3, and 4 of the 5 subjects, respectively, in the control, rotenone+placebo, and rotenone+prodrug groups.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8148374/v1/ec42108d10c756b24e81928d.png"},{"id":97382725,"identity":"3c981cef-3db6-46dc-ac50-29f460e86104","added_by":"auto","created_at":"2025-12-03 18:40:09","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":172586,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic of the mitochondrial electron transport chain. In normal mitochondrial function, electrons from complex I and complex II ultimately flow through cytochrome-c-oxidase (CCO; or complex IV) to reduce O\u003csub\u003e2\u003c/sub\u003e to H\u003csub\u003e2\u003c/sub\u003eO, and pump protons (H\u003csup\u003e+\u003c/sup\u003e) into the intermembrane space. ATP Synthase uses the resultant H\u003csup\u003e+\u003c/sup\u003e gradient to generate ATP. CCO is reduced and oxidized by electron in-flow and out-flow, respectively (more precisely, it is the reduced and oxidized form of CuA, the di-copper center cofactor in CCO, which is monitored using optics). Change in the electron in-flow rate relative to the out-flow rate alters the redox ratio of CuA from its equilibrium state. Rotenone impairs function by inhibiting complex I (the electron out-flow rate from complex I is decreased). Succinate NV354 prodrug offers a possible means to restore function by increasing the electron out-flow rate from complex II. Specifically, after passive entry into cells from the vasculature, NV354 is hydrolyzed to release succinate, which increases succinate concentration in the mitochondrial matrix. Other electron carriers shown include the coenzyme Q and cytochrome-c protein.\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8148374/v1/5c15d5b4bbf3d4eef9e6216c.jpeg"},{"id":98622720,"identity":"455b9f14-571e-4784-8c26-5832b5e9d241","added_by":"auto","created_at":"2025-12-19 17:01:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3036248,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8148374/v1/940dc018-b41f-4875-8ca6-eeaf12ec9027.pdf"},{"id":97665508,"identity":"54aeb0e6-1b14-4280-8daa-8c704eca35e9","added_by":"auto","created_at":"2025-12-08 09:18:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":515097,"visible":true,"origin":"","legend":"","description":"","filename":"LewisSciReportsSupplementaryMaterial.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8148374/v1/56376725333137c1c703227b.pdf"}],"financialInterests":"Competing interest reported. E.E. has received salary support and/or travel reimbursements and/or grants from Abliva AB, a Swedish public company developing pharmaceuticals in the field of mitochondrial medicine. E.E. is currently an Abliva employee and member of its management team. Abliva AB has filed patents related to succinate prodrugs (listed below), some of which name E.E. as an inventor. The other authors declare no competing interests.\n\nSuccinate prodrug, compositions containing the succinate prodrug and uses thereof (US20230033294-A1, 11565998-B2, 20220162162-A1)\nNovel cell-permeable succinate compounds (US20210401792-A1, 20170105961-A1)\nCell-permeable succinate compounds (US11147789-B2)\nSuccinate prodrugs for use in the treatment of lactic acidosis or drug-induced side-effects due to Complex I-related impairment of mitochondrial oxidative phosphorylation (US10307389-B2, 20170100359-A1)\nProtected succinates for enhancing mitochondrial ATP-production (US9670175-B2, 20150259317-A1)\nProdrugs of succinic acid for increasing ATP-production (US20170105960-A1)","formattedTitle":"Optical and Microdialysis Monitoring of Succinate Prodrug Treatment in a Rotenone-Induced Model of Mitochondrial Dysfunction in Swine","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003ePatients with primary mitochondrial disease are a heterogeneous population that experience mitochondrial dysfunction due to mutations in nuclear or mitochondrial DNA.\u003csup\u003e\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Mitochondrial dysfunction negatively affects almost every organ in the body, but the brain, with its high energy demand and critical dependence on mitochondrial bioenergetics, is especially at risk.\u003csup\u003e\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e Among the most common causes of mitochondrial dysfunction in these patients is complex I dysfunction.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e Current therapies are mostly limited to symptom management, but new emerging therapies, such as prodrugs and gene therapy, show promise.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e Non-invasive tools that detect metabolic improvements could aid in the precision application of these and other neuroprotective therapies.\u003c/p\u003e\u003cp\u003eDiffuse optical methods hold promise to address this need via their assessment of cerebral oxygen metabolism.\u003csup\u003e\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e Here, assessments include a mitochondrial metric that probes the change in redox state of cytochrome-c-oxidase (CCO, also known as complex IV),\u003csup\u003e12\u0026ndash;17\u003c/sup\u003e and hemodynamic metrics that probe cerebral blood flow (CBF), oxygen extraction fraction (OEF), and an index of cerebral metabolic rate of oxygen derived from CBF and OEF.\u003csup\u003e\u003cspan additionalcitationids=\"CR19 CR20 CR21\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e In healthy mitochondria, the electron transport chain transfers electrons from complexes I and II to coenzyme Q. Subsequently, electrons are transported through complex III and complex IV (CCO), culminating in the reduction of O\u003csub\u003e2\u003c/sub\u003e to water. Primary mitochondrial dysfunction impedes the electron in-flow rate to CCO. We hypothesize that this alters the equilibrium redox ratio of CCO, \u003cem\u003ei.e.\u003c/em\u003e, it decreases the reduced form of CCO (redCCO) and increases the oxidized form (oxCCO). Primary mitochondrial dysfunction is also expected to induce secondary decreases in oxygen metabolism, which will decrease the tissue oxygen extraction from the blood, \u003cem\u003ei.e.\u003c/em\u003e, OEF decreases. Herein, we aim to show the sensitivity of the optical metrics to complex I dysfunction induced by rotenone in swine. Rotenone is a highly specific complex I inhibitor,\u003csup\u003e23\u003c/sup\u003e and its administration in swine was previously shown to increase blood lactate and venous oxygen tension.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eWe also aim to characterize the metabolic effects of the succinate prodrug NV354 (methyl 3-[(2-acetylaminoethylthio)carbonyl]propionate) in the swine model. NV354 is designed to increase the concentration of succinate in mitochondria.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e The provision of substrate directly to complex II enables increased electron flow through complex II to compensate for impaired electron flow through complex I.\u003csup\u003e25,26\u003c/sup\u003e Succinate itself will not passively transport across cell membranes due to its charged nature. NV354, however, is a stable, water-soluble thioester that does pass through cell membranes. Once inside the cell, NV354 is hydrolyzed by cellular esterases to release succinate (see supplementary material), which then enters mitochondria via the dicarboxylate carrier. NV354 has been shown to mitigate acute mitochondrial dysfunction in cellular and rodent models,\u003csup\u003e25\u0026ndash;32\u003c/sup\u003e but its effects in large animal models have not been studied.\u003c/p\u003e\u003cp\u003eHerein, we use diffuse optical methods together with cerebral microdialysis to monitor cerebral metabolism in a rotenone-induced swine model of complex I dysfunction. Cerebral microdialysis invasively measures the concentrations of interstitial lactate and pyruvate, and increases in interstitial lactate and lactate-pyruvate ratio (LPR) are often indicative of decreases in oxygen metabolism.\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e We track the temporal changes of the optical and microdialysis metrics induced by rotenone poisoning with and without NV354 treatment. We also directly compare mitochondrial and vascular-based optical metabolism metrics during these processes, \u003cem\u003ei.e.\u003c/em\u003e, we determined the association between the variations of oxidized CCO (oxCCO) and OEF. These proof-of-concept results provide mechanistic insight into how succinate supplementation might benefit patients during metabolic crises. To our knowledge, this study also presents the first \u003cem\u003ein vivo\u003c/em\u003e optical measurements and comparison of oxCCO and OEF changes induced by primary mitochondrial dysfunction and mitochondrial-targeted drugs.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eAll animal care and procedures were conducted in adherence to the National Institute of Health Guide for the Care and Use of Laboratory Animals, with approval obtained from the Institutional Animal Care and Use Committee of the University of Pennsylvania. We confirm that this study is reported in accordance with ARRIVE guidelines (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://arriveguidelines.org\u003c/span\u003e\u003cspan address=\"https://arriveguidelines.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Study Design\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eNon-invasive broadband (bDOS) and frequency-domain (FD-DOS) diffuse optical spectroscopy, and invasive cerebral microdialysis sampling, were performed on 15 one-month-old Yorkshire swine (\u003cem\u003esus scrofa\u003c/em\u003e, mean [range] weight\u0026thinsp;=\u0026thinsp;10.8 [9.1\u0026ndash;13.2] kg; purchased from Meck Farms, Lancaster, PA, USA) divided into three groups: a control group (n\u0026thinsp;=\u0026thinsp;5), a rotenone\u0026thinsp;+\u0026thinsp;placebo group (n\u0026thinsp;=\u0026thinsp;5), and a rotenone\u0026thinsp;+\u0026thinsp;prodrug group (n\u0026thinsp;=\u0026thinsp;5). Relative cerebral blood flow was also monitored invasively with a laser Doppler probe (PeriFlux, Perimed Inc., Stockholm, Sweden). Neuromonitoring was performed during a 10-minute baseline period and for four hours during intravenous infusions (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The rotenone\u0026thinsp;+\u0026thinsp;placebo group received intravenous infusions of rotenone (0.125 mg/kg/h; Sigma-Aldrich, Burlington, MA, USA) and normal saline (100mg/kg/hr); the rotenone\u0026thinsp;+\u0026thinsp;prodrug group received intravenous infusions of rotenone (0.125 mg/kg/hr) and succinate prodrug (100 mg/kg/hr, NV354; Abliva AB, Lund, Sweden); the control group received no intravenous infusions.\u003c/p\u003e\u003cp\u003eThe rotenone\u0026thinsp;+\u0026thinsp;prodrug co-infusion models scenarios wherein intervention occurs during acute metabolic crisis. Thus, this study is designed to provide a proof-of-concept of NV354 prodrug\u0026rsquo;s ability to maintain mitochondrial function under stress; this maintenance of mitochondrial function is essential to show before testing rescue therapy protocols. Note, based on prior swine work,\u003csup\u003e24\u003c/sup\u003e we expected our choice of the rotenone infusion dose to result in complex I dysfunction without hemodynamic instability. Note also, the NV354 infusion dose we used was about twice as large as the doses that resulted in therapeutic benefits in rodent models.\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e Given the species differences in metabolism and the need to overcome potential blood-brain-barrier limitations, this larger dose helps ensure that therapeutic NV354 levels accumulate in the swine brain. Additional pre-study pilot testing of two one-month-old Yorkshire swine demonstrated that administration of this dose over 4 hours did not cause hemodynamic instability.\u003c/p\u003e\u003cp\u003eFinally, we note that the neuroprotective benefits of NV354 were observed at 3 hours after initiation of treatment in rodent models.\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e This observation, along with unpublished data in rats that shows rapid uptake and release of succinate in the brain tissue at 5 minutes after intravenous bolus injection of \u003csup\u003e13\u003c/sup\u003eC-labeled NV354 (20 mg/kg), suggests that 4 hours enables assessment of drug effects after steady-state tissue levels of NV354 are achieved.\u003c/p\u003e\u003cp\u003eNeuromonitoring devices were removed after the monitoring period, but intravenous infusions continued and animals were transferred to a magnetic resonance imaging (MRI) scanner. Intravenous infusions were stopped after a total duration of 6 hours. Animals were euthanized after MRI via bolus injection of potassium chloride. The present paper focuses on the changes in cerebral physiology measured during the first four hours of infusion; thus, the MRI analyses are outside the scope of this paper.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Animal Preparation, Anesthesia and Respiratory Management\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eSwine were initially sedated with intramuscular injections of ketamine (20 mg/kg) and buprenorphine (0.02 mg/kg), followed by 2\u0026ndash;3% inhaled isoflurane. After confirmation of adequate sedation via the absence of withdrawal response on toe pinch, swine were intubated with a 32 Fr/CH left-endotracheal tube (Covidien, Medtronic, Dublin, Ireland), and then mechanically ventilated with 2\u0026ndash;3% isoflurane and 21% FiO\u003csub\u003e2\u003c/sub\u003e (positive end-expiratory pressure, 5 cmH\u003csub\u003e2\u003c/sub\u003eO; peak inspiratory pressure, 1-1.5 cmH\u003csub\u003e2\u003c/sub\u003eO/kg). The respiratory rate and maximum ventilation pressure were adjusted to maintain the end-tidal CO\u003csub\u003e2\u003c/sub\u003e between 38\u0026ndash;42 mmHg. Catheters were placed with ultrasound guidance in the right femoral artery and bilateral femoral veins for arterial blood pressure monitoring, blood gas sampling, and drug administration. A central venous catheter was also placed in the superior vena cava for rotenone infusion; succinate prodrug and normal saline infusions were administered via the femoral vein. Next, neuromonitoring was placed; a hybrid bDOS/FD-DOS optical probe was sutured to the left forehead, a microdialysis catheter (CMA 71 Elite, mDialysis, Stockholm, Sweden) was inserted through a cranial burr hole to a depth of 1-1.5 cm into the brain parenchyma of the right frontal cortex, and a laser Doppler probe was inserted through a cranial burr hole and secured to the right frontal dura matter (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Intravenous fentanyl infusion (10 \u0026micro;g/kg/hr) was then started approximately 10 minutes prior to baseline data acquisition to provide analgesia for the duration of the study.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Data Acquisition\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eOptical neuromonitoring of the left frontal cortex was performed with interleaved FD-DOS and bDOS data acquisition (Section \u003cspan refid=\"Sec6\" class=\"InternalRef\"\u003e2.3.1\u003c/span\u003e). Baseline measurements were obtained immediately prior to the initiation of the 4-hour IV infusion period (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). During baseline, 5-minutes of bDOS data was acquired first, followed by 5-minutes of FD-DOS data. During the IV infusion period (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), the monitoring was comprised of 28 minutes of bDOS acquisition interleaved with 2 minutes of FD-DOS acquisition. Continuous laser Doppler monitoring of baseline-normalized relative cerebral blood flow (\u003cem\u003ei.e.\u003c/em\u003e, rCBF\u0026thinsp;=\u0026thinsp;CBF / CBF\u003csub\u003eBaseline\u003c/sub\u003e) was performed in parallel. Cerebral microdialysis sampling (Section \u003cspan refid=\"Sec7\" class=\"InternalRef\"\u003e2.3.2\u003c/span\u003e) was acquired at the end of the baseline period and every 30 minutes during the IV infusion period. Finally, systemic arterial and venous blood gas samples were drawn at the end of baseline, and at 30 minutes, 60 minutes, 120 minutes, 180 minutes, and 240 minutes during the IV infusion period. Per blood gas, we examined the venous lactate concentration (an indication of systemic anaerobic metabolism), arterial blood oxygen saturation (SaO\u003csub\u003e2\u003c/sub\u003e), and hematocrit (Hct). Arterial blood oxygen content is readily calculated from the latter metrics: CaO\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;1.36\u0026times;Hct\u0026times;32.2\u0026times;SaO\u003csub\u003e2\u003c/sub\u003e (units, mL O\u003csub\u003e2\u003c/sub\u003e / mL blood).\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\u003ch2\u003e2.3.1 Optical Neuromonitoring\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eFD-DOS and bDOS measurements were acquired with a commercially available system (MetaOx, ISS Inc, Champaign, IL, USA) and a custom-built system, respectively, using a single optical probe secured to the forehead (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the probe is described in detail in supplementary material). The FD-DOS system comprised 16 intensity modulated lasers (4 lasers at each of 4 wavelengths, i.e., 680, 760, 805, 830 nm; modulation frequency, 110 MHz modulation) and 4 PMT detectors. (Note, the MetaOx is also capable of diffuse correlation spectroscopy (DCS) monitoring of blood flow; regrettably, DCS data quality was not sufficient for analysis due to low signal intensity (\u0026lt;\u0026thinsp;5,000 detected photons a second)). The bDOS system was comprised of a fiber-coupled halogen lamp (HL-2000-HP-FHSA, Ocean Optics, Dunedin, FL, USA) and a fiber-coupled custom f/1.5 high throughput spectrometer (650\u0026ndash;1050 nm spectral range, 100 \u0026micro;m slit width, 4.8 nm FWHM resolution, TEC cooled to -15\u0026deg;C; Wasatch Photonics, Morrisville, NC, USA).\u003c/p\u003e\u003cp\u003eFD-DOS and bDOS acquisition were sequentially interleaved as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. During FD-DOS acquisition, the bDOS lamp shutter was closed, and during bDOS acquisition, the FD-DOS lasers and detectors were shut off. The FD-DOS and bDOS measurements were also calibrated before and after each monitoring session using a solid phantom with known optical properties and a spectrally flat reflectance standard (see supplementary material).\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eCerebral measurements of OEF, tissue blood oxygen saturation (StO\u003csub\u003e2\u003c/sub\u003e), total hemoglobin concentration (HbT), and differential change in the concentration of oxCCO relative to baseline (ΔoxCCO) were computed once every minute (see supplementary material). Note, optical monitoring specifically detects changes in the CuA center redox state in CCO; we do not probe CuB or other metallic centers. All concentration measurements are per volume of tissue.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\u003ch2\u003e2.3.2 Cerebral Microdialysis\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe cerebral microdialysis catheter is a selectively permeable membrane which permits the diffusion of small molecule biomarkers from interstitial fluid in the brain into circulating saline perfusate.\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e Normal saline was infused through the catheter (CMA 71 Elite, mDialysis AB, Stockholm, Sweden) at a rate of 1 \u0026micro;l/min, and the resulting dialysate was collected in a microvial. Microvial samples were stored and replaced every 30 minutes to examine temporal changes in collected biomarkers (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The samples were analyzed to determine their concentrations of lactate, pyruvate, glucose, and glycerol using an automated ISCUS Flex\u003csup\u003e\u0026trade;\u003c/sup\u003e Microdialysis Analyzer (mDialysis AB, Stockholm, Sweden). We also computed the lactate-pyruvate ratio (LPR) in each sample. Elevated LPR and elevated glycerol are often used as indications of increased anaerobic metabolism and cell injury, respectively.\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Statistical Analysis\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eStatistical analyses were performed in MATLAB R2022a (Mathworks Inc., Natick, MA, USA), and p-values\u0026thinsp;\u0026le;\u0026thinsp;0.05 were considered significant. First, to assess differences between baseline physiology across experimental groups, we performed Kruskal-Wallis tests; if significance was found, we used a post hoc Wilcoxon rank-sum test between each group.\u003c/p\u003e\u003cp\u003eOur primary hypotheses were: a) rotenone-induced complex I dysfunction in swine increases oxCCO, decreases OEF, and increases LPR, and b) prodrug treatment reduces these changes. We tested these hypotheses using time-averages of the differential changes from baseline, \u003cem\u003ei.e.\u003c/em\u003e, ΔoxCCO and ΔOEF, averaged across 5-minute intervals before the microdialysis sampling points; this scheme provided uniform sampling of the optical and microdialysis metrics. To investigate temporal changes during the 4-hour IV infusion period, we performed both simple linear and 2-period piecewise linear mixed effects regressions of ΔoxCCO vs. time, ΔOEF vs. time, and LPR vs. time for the rotenone\u0026thinsp;+\u0026thinsp;placebo and rotenone\u0026thinsp;+\u0026thinsp;prodrug groups (using the \u003cem\u003efitlme\u003c/em\u003e MATLAB function). The time periods of the piecewise linear regressions were 0\u0026ndash;2 hours and 2\u0026ndash;4 hours. For the ΔoxCCO and ΔOEF regressions, random slopes were incorporated for each animal to account for individual variations in the trends (the intercept was forced to zero in the regressions because ΔoxCCO and ΔOEF are, by definition, zero at time zero). For the LPR regression, random slopes and intercepts were incorporated for each animal.\u003c/p\u003e\u003cp\u003eOur rationale for using the 2-period piecewise regression is that it is among the simplest of analyses to account for a possible time-dependent effect. Such time-dependence could arise because the total delivered dose of rotenone and succinate prodrug increases with infusion time, and because higher doses (longer infusion times) may alter physiological responses. In the rotenone\u0026thinsp;+\u0026thinsp;placebo group, the adjusted R\u003csup\u003e2\u003c/sup\u003e values were larger for the simple linear regressions than for the piecewise linear regressions. The reverse was true for the rotenone\u0026thinsp;+\u0026thinsp;prodrug group. Thus, we present simple linear regressions for the rotenone\u0026thinsp;+\u0026thinsp;placebo group, and piecewise linear regressions for the rotenone\u0026thinsp;+\u0026thinsp;prodrug group. Note, for the control group, we only performed simple linear mixed effects regressions.\u003c/p\u003e\u003cp\u003eIn secondary analyses, we also evaluated the temporal changes of ΔHbT, StO\u003csub\u003e2\u003c/sub\u003e, mean arterial blood pressure (MAP), venous lactate, cerebral blood flow (measured with laser Doppler), hematocrit, arterial blood oxygen content (CaO\u003csub\u003e2\u003c/sub\u003e), and additional microdialysis metrics (\u003cem\u003ei.e.\u003c/em\u003e, lactate, pyruvate, glycerol). As in the primary analyses, simple linear mixed effects regressions were performed for the control and rotenone\u0026thinsp;+\u0026thinsp;placebo groups, and 2-period piecewise linear mixed effects regressions were performed for the rotenone\u0026thinsp;+\u0026thinsp;prodrug group.\u003c/p\u003e\u003cp\u003eWe additionally hypothesized that oxidized CCO increases and OEF decreases are both associated with LPR increases, and that oxidized CCO increases are associated with OEF decreases. These hypotheses were tested with simple linear mixed effects regressions of LPR vs ΔoxCCO, LPR vs ΔOEF, and ΔOEF vs ΔoxCCO. We deemed an association to be significant if its regression slope p-value was \u0026le;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003ePre-infusion baseline summary statistics for the cerebral optical metrics, cerebral microdialysis metrics, and systemic lactate were similar between groups (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). There was a marginally significant difference in baseline MAP between groups (p\u0026thinsp;=\u0026thinsp;0.05). From post-hoc tests, MAP was found to be lower in the rotenone\u0026thinsp;+\u0026thinsp;placebo group compared to the control group (p\u0026thinsp;=\u0026thinsp;0.02). MAP was not different between the rotenone\u0026thinsp;+\u0026thinsp;placebo and rotenone\u0026thinsp;+\u0026thinsp;prodrug groups, however, and thus MAP should not be a confounder per the differing temporal trends in optical and microdialysis metrics between those groups.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePre-infusion baseline variables (from cerebral optical, cerebral microdialysis, and systemic measurements) presented as medians and interquartile ranges (p values from Kruskal-Wallis tests). The tissue scattering amplitude (A) and power (b) are defined in the supplementary material.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControls\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRotenone\u0026thinsp;+\u0026thinsp;Placebo\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRotenone\u0026thinsp;+\u0026thinsp;prodrug\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCerebral Optics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOEF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.63 (0.59, 0.66)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.58 (0.54, 0.60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.58 (0.56, 0.63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.53\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHbT (\u0026micro;M)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e49.0 (44.4, 58.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e49.8 (49.1, 55.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e47.1 (46.6, 51.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.57\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.52 (0.49, 0.54)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.55 (0.53, 0.58)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.56 (0.51, 0.57)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.47\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA (cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e14.6 (14.2, 16.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e15.4 (13.7, 16.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e14.3 (13.7, 15.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.89\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eb\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.0 (0.93, 1.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.96 (0.89, 1.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.0 (0.95, 1.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.59\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMicrodialysis\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLactate (mM)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.84 (0.75, 1.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.6 (0.95, 1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.59 (0.52, 0.74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePyruvate (\u0026micro;M)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e70.2 (59.5, 105)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e85.1 (57.0, 128)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e65.6 (44.7, 79.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.59\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLPR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10.5 (9.34, 17.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e16.5 (10.4, 21.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e12.0 (8.23, 13.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.60\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGlycerol (\u0026micro;M)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e17.4 (14.8, 20.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e22.5 (18.3, 26.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9.83 (8.89, 14.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSystemic\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVenous Lactate (mM)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.1 (0.79, 1.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.0 (0.75, 1.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.0 (0.79, 1.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.91\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMAP (mmHg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e73.6 (62.1, 83.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e56.3 (52.7, 58.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e66.8 (56.5, 78.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.05\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHct (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e22.0 (19.0, 25.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e18.5 (17.5, 20.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e18.0 (17.0, 20.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSaO\u003csub\u003e2\u003c/sub\u003e (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e97.0 (96.5, 98.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e97.0 (96.8, 97.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e98.0 (97.8, 98.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCaO\u003csub\u003e2\u003c/sub\u003e (mL O\u003csub\u003e2\u003c/sub\u003e/mL blood)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e9.44 (8.25, 10.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8.03 (7.62, 8.62)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.98 (7.46, 8.86)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.28\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe cerebral microdialysis measurements of LPR, lactate, and pyruvate as a function of time for each group are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e (the glycerol metric is not plotted, but its regression slopes are tabulated in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). As hypothesized, LPR remained constant in the control group and increased in the rotenone\u0026thinsp;+\u0026thinsp;placebo group (p\u0026thinsp;=\u0026thinsp;0.02). The slope of the rotenone\u0026thinsp;+\u0026thinsp;placebo group increase, 2.3 per hour, shows a clinically meaningful change, \u003cem\u003ei.e.\u003c/em\u003e, LPR approaches abnormal levels (\u0026gt;\u0026thinsp;20)\u003csup\u003e36\u003c/sup\u003e within a few hours. Contrary to our hypothesis, LPR also increased during the last two hours of infusion in the rotenone\u0026thinsp;+\u0026thinsp;prodrug group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) to levels of about 20.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eInterestingly, the LPR increase was driven by increasing lactate in the rotenone\u0026thinsp;+\u0026thinsp;placebo group, but in the rotenone\u0026thinsp;+\u0026thinsp;prodrug group, the LPR increase was driven by decreasing pyruvate (in combination with stabilizing lactate levels). The lactate increase in the rotenone\u0026thinsp;+\u0026thinsp;placebo group suggests increased anaerobic metabolism caused by rotenone-induced mitochondrial dysfunction. The pyruvate decrease and stabilized lactate in the rotenone\u0026thinsp;+\u0026thinsp;prodrug group suggest increased mitochondrial oxygen metabolism during the last two hours of infusion (the different trends in the first two hours of infusion could be due to drug loading; see Discussion).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSlopes (in per hour units) of the linear mixed effects regression fits of MAP, microdialysis glycerol, systemic venous lactate, and CaO\u003csub\u003e2\u003c/sub\u003e versus infusion time for each experimental group (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e for metric units). Note, there are two slopes in the piecewise fit for the prodrug group (period 1, 0\u0026ndash;2 hours of infusion; period 2, 2\u0026ndash;4 hours of infusion). The p-values for the null hypothesis of zero slope are also included.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026minus;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026minus;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControls\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRotenone\u0026thinsp;+\u0026thinsp;Placebo\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eRotenone\u0026thinsp;+\u0026thinsp;Prodrug\u003c/p\u003e\u003cp\u003e(Period 1 | Period 2)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSlope (95% CI), p\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSlope (95% CI), p\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSlope (95% CI), p\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSlope (95% CI), p\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMAP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e\u003cp\u003e-3.9 (-6.4, -1.5), \u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c3\"\u003e\u003cp\u003e-2.3 (-3.2, -1.3), \u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-3.0 (-8.6, 2.5), 0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.2 (-2.9, 7.3), 0.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGlycerol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e\u003cp\u003e0.21 (-0.85, 1.3), 0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c3\"\u003e\u003cp\u003e0.37 (-0.81, 1.6), 0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-2.2 (-7.6, 3.2), 0.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.85 (-1.4, 3.1), 0.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVenous Lactate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e\u003cp\u003e-0.03 (-0.17, 0.11), 0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c3\"\u003e\u003cp\u003e0.25 (-0.01, 0.51), 0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.32 (0.10, 0.52), \u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.94 (0.12, 1.76), \u003cb\u003e0.03\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCaO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e\u003cp\u003e0.10 (-0.53, 0.73), 0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c3\"\u003e\u003cp\u003e0.12 (-0.39, 0.63), 0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.59 (-0.18, 1.37), 0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.94 (-0.12, 2.00), 0.08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eSmall but significant cerebral lactate increases were observed in the control group (p\u0026thinsp;=\u0026thinsp;0.03) and during the first two hours of infusion in the rotenone\u0026thinsp;+\u0026thinsp;prodrug group (p\u0026thinsp;=\u0026thinsp;0.03). The control group increase might be a consequence of decreasing MAP (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), while the rotenone\u0026thinsp;+\u0026thinsp;prodrug group increase might reflect the residual lactate production following exposure to rotenone and prodrug. Cerebral glycerol concentration was approximately constant in all groups (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), which suggests that cerebral cell membrane damage did not occur.\u003c/p\u003e\u003cp\u003eThe concurrent optical cerebral ΔoxCCO and ΔOEF data are plotted in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. oxCCO and OEF were constant in the control group. In the rotenone\u0026thinsp;+\u0026thinsp;placebo group, oxCCO marginally increased (p\u0026thinsp;=\u0026thinsp;0.05), but contrary to our hypothesis, OEF remained constant (p\u0026thinsp;=\u0026thinsp;0.80). Lastly, and contrary to our hypothesis, the rotenone\u0026thinsp;+\u0026thinsp;prodrug group exhibited a pronounced increase in oxCCO (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and decrease in OEF (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e\u003cp\u003eIn addition, hematocrit (Hct) substantially increased in the rotenone\u0026thinsp;+\u0026thinsp;prodrug group (Fig.\u0026nbsp;4), which resulted in pronounced increases of optically measured total hemoglobin concentration (HbT). In the other two groups, small HbT increases were observed that may reflect a vasodilation response to decreasing MAP (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Laser Doppler showed constant rCBF in the control and placebo groups, and decreasing rCBF during the first two hours of infusion in the prodrug group.\u003c/p\u003e\u003cp\u003eFinally, the direct associations (\u003cem\u003ei.e.\u003c/em\u003e, linear regressions slopes) between the metabolism metrics for each experimental group are reported in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. In the rotenone\u0026thinsp;+\u0026thinsp;prodrug group, LPR increases were linearly associated with an increase in oxCCO (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and a decrease in OEF (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). In the other two groups, LPR increases were not associated with changes in the optical metrics. Similarly, oxCCO increases were linearly associated with OEF decreases only in the rotenone\u0026thinsp;+\u0026thinsp;prodrug group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e\\\u003c/b\u003e \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eFigure 4\u003c/strong\u003e\u003cp\u003eTemporal trends of cerebral ΔHbT (top row), Hct (middle row), and rCBF (bottom row) during the 4-hour infusion period of each experimental group (infusion begins at time zero). Note, laser Doppler measures the baseline-normalized rCBF. Each color represents a different subject, and the ΔHbT and rCBF points are five-minute averages of data prior to microdialysis sampling times. In all plots, the linear regression fit (solid line) with its 95% CI (shaded region) is shown, along with the p-value for the null hypothesis of zero slope. The fit is simple linear for the control and rotenone\u0026thinsp;+\u0026thinsp;placebo groups, and 2-period piecewise linear for the rotenone\u0026thinsp;+\u0026thinsp;prodrug group. rCBF data was available for only 4, 3, and 4 of the 5 subjects, respectively, in the control, rotenone\u0026thinsp;+\u0026thinsp;placebo, and rotenone\u0026thinsp;+\u0026thinsp;prodrug groups.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eLinear associations between changes in metabolism metrics during the 4-hour infusion period of each experimental group. The linear mixed effects regression slope (95% confidence interval) and the p-value for the null hypothesis of zero slope are reported. Note, the slope units for the two ΔoxCCO associations are 1/\u0026micro;M, and the slope unit for LPR vs ΔOEF is dimensionless.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026minus;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026minus;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControls\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRotenone\u0026thinsp;+\u0026thinsp;Placebo\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRotenone\u0026thinsp;+\u0026thinsp;Prodrug\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAssociation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSlope (95% CI), p\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSlope (95% CI), p\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSlope (95% CI), p\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLPR vs ΔoxCCO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e\u003cp\u003e-0.96 (-5.6, 3.7), 0.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c3\"\u003e\u003cp\u003e0.67 (-6.6, 7.9), 0.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.9 (3.2, 6.7), \u003cb\u003e\u0026lt;0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLPR vs ΔOEF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e\u003cp\u003e-5.4 (-22, 11), 0.51\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c3\"\u003e\u003cp\u003e-0.76 (-59, 58), 0.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-54 (-74, -35), \u003cb\u003e\u0026lt;0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOEF vs ΔoxCCO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c2\"\u003e\u003cp\u003e0.04 (-0.01, 0.09),0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c3\"\u003e\u003cp\u003e-0.0005 (-0.026, 0.025), 0.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.06 (-0.10, 0.02), \u003cb\u003e\u0026lt;0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eWe performed non-invasive optical neuromonitoring and invasive microdialysis neuromonitoring in swine to evaluate the impairment of cerebral oxygen metabolism caused by rotenone inhibition of mitochondrial complex I, and the effects of NV354 succinate prodrug treatment on cerebral oxygen metabolism. Our use of a swine model with clinically relevant molecular and physiologic responses, and our technical innovations to monitor the metabolic responses (discussed below), are strengths of this work. Overall, the results suggest that rotenone exposure impaired cerebral oxygen metabolism, and that NV354 treatment increased cerebral oxygen metabolism during rotenone infusion. Thus, the results motivate the potential of NV354 to limit metabolic crisis. Furthermore, the results suggest that there are differences in metabolic effects of NV354 treatment in the early versus late periods of the infusion. Finally, though optical neuromonitoring shows promise to provide an additional outcome metric for adaptive trial design of patients with mitochondrial disease, future improvements in the technology\u0026rsquo;s brain sensitivity are needed to improve its ability to monitor small metabolic changes.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Cerebral Physiological Response to Rotenone Exposure\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eMicrodialysis evidence, \u003cem\u003ei.e.\u003c/em\u003e, increasing LPR driven by increasing lactate concentration, supports the expectation that rotenone exposure impairs mitochondrial complex I. The cerebral lactate increase is a consequence of the increase in anaerobic metabolism needed to compensate for decreased oxygen metabolism. The optically measured oxCCO increase is consistent with our hypothesis. The observed oxCCO increase, however, was only marginally significant (p\u0026thinsp;=\u0026thinsp;0.05), and the oxCCO data were not directly associated with the LPR changes. In addition, we had expected that diminished aerobic metabolism would result in less oxygen extraction from the vasculature (or decreased OEF), but the OEF optical metric remained constant.\u003c/p\u003e\u003cp\u003eThe lack of robust optical detection of the complex I impairment, \u003cem\u003ee.g.\u003c/em\u003e, compared to detection by microdialysis, could be a consequence of extra-cerebral tissue contamination (\u003cem\u003ee.g.\u003c/em\u003e, from scalp and skull) and experimental noise, both of which reduce the sensitivity of optics to cerebral metabolic changes.\u003csup\u003e\u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e Specifically, we expect that extra-cerebral tissues to have a much lower metabolic rate of oxygen than the brain, and thus extra-cerebral tissues may not be impacted significantly by rotenone. Accordingly, extra-cerebral tissue contamination can lead to underestimation of the cerebral metabolic effect, which makes it more challenging to separate metabolic effects from experimental noise. Prior work has suggested that oxCCO, which directly probes mitochondria, is less confounded by extra-cerebral tissue contamination because of much higher concentrations of mitochondria in the brain compared to the skull or scalp.\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e Thus, our observations of increased oxCCO and constant OEF could be a consequence of the improved brain sensitivity of the oxCCO metric.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFinally, although we hypothesized that complex I inhibition should increase oxCCO concentration, this expectation requires assumptions and is not obvious. Since Complex I inhibition lowers mitochondrial metabolism, one might anticipate a decrease in both the electron in-flow rate to CCO and the out-flow rate from CCO. The concentration of oxCCO depends on both in-flow and out-flow rates; with Complex I inhibition, both rates should decrease. However, oxCCO concentration can still increase if the decrease of in-flow rate is larger than the decrease of out-flow rate. Indeed, if the net difference between the in-flow and out-flow rates is smaller than the absolute reduction in the in-flow rate, then rotenone-induced complex I inhibition will have a smaller effect on oxCCO concentration compared to its effect on cerebral lactate. As to why oxCCO increases at all, the out-flow rate during complex I inhibition might be sustained by normal intracellular oxygen concentrations. Indeed, in patients with acute brain injury, there is evidence of an association between oxygen concentration and the CCO redox state.\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e,\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e Thus, although isolated rat liver\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e and pigeon heart\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e mitochondria experiments show that non-hypoxic intracellular oxygen concentrations (\u003cem\u003ei.e.\u003c/em\u003e, above ~\u0026thinsp;10 mmHg \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e and ~\u0026thinsp;1 mmHg \u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e thresholds) do not influence the redox state of CCO in healthy mitochondria, the rotenone-induced impairment could yield \u0026ldquo;unhealthy\u0026rdquo; mitochondria that have altered relationships between CCO redox state and oxygen.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Cerebral Physiological Response to Succinate Prodrug Treatment\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eOur results suggest that NV354 prodrug treatment increased oxygen metabolism during rotenone infusion, and that the prodrug had different metabolic effects early versus late in the infusion period. The primary evidence supporting these findings is derived from microdialysis metrics. Cerebral interstitial lactate levels stabilized later in the infusion period; this observation suggests that cerebral lactate production was normalized as a result of increased oxygen metabolism and increased generation of ATP from mitochondria. In addition, the increase in cerebral lactate during the first 2 hours of prodrug infusion appears to be attenuated compared to the increase in cerebral lactate from rotenone infusion alone (unfortunately, we are not powered to show a significant difference). The complete stabilization of cerebral lactate during the second 2 hours of infusion might be due to the accumulation of larger intracellular succinate levels. In addition, the stabilization of cerebral lactate coincided with pyruvate decreases. Note, the different early- versus late-time metabolic effects could be a consequence of drug loading. That is, since the total drug dose delivered increases with infusion time, the drug might only reach therapeutic levels inside cells during the second 2 hours of treatment.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eOur results also illustrate the complexities of interpreting the microdialysis LPR metabolism metric, which was observed to increase in both the rotenone\u0026thinsp;+\u0026thinsp;placebo and rotenone\u0026thinsp;+\u0026thinsp;prodrug groups. Specifically, an increase in LPR driven by increased lactate reflects indicate glycolytic upregulation and impaired oxygen metabolism. An increase in LPR driven by decreased pyruvate and stabilized lactate levels, by contrast, suggests enhanced oxygen metabolism. Thus, changes in LPR are best interpreted in context of the separate, independent changes in lactate and pyruvate concentration.\u003c/p\u003e\u003cp\u003eThe observed OEF decrease in the rotenone\u0026thinsp;+\u0026thinsp;prodrug group is not consistent with our original hypothesis. Rather, the OEF decrease is likely explained by the increased arterial blood oxygen content (CaO\u003csub\u003e2\u003c/sub\u003e) that arose from increased hematocrit, \u003cem\u003ei.e.\u003c/em\u003e, OEF will decrease if the increase in cerebral oxygen delivery exceeds the increase in cerebral oxygen metabolism.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e The observed hematocrit increase was puzzling and unexpected, and a future study is needed to confirm and understand the effect. Similarly, the rCBF decrease during the first two hours of infusion was also unexpected and might be a consequence of increased CaO\u003csub\u003e2\u003c/sub\u003e. Note however, the laser Doppler blood flow measurements may also have artifacts from vasculature in the dura matter,\u003csup\u003e47\u003c/sup\u003e since the laser Doppler probe was resting on top of the dura. Artifacts could arise, for example, if dural and cortical flows had different trends.\u003c/p\u003e\u003cp\u003eFinally, the observed increase in oxCCO during rotenone and prodrug infusion was not consistent with our original hypothesis. Since the change in oxCCO concentration depends on the difference between electron in-flow rate to CCO and electron out-flow rate from CCO (see Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003e), an increase in oxygen metabolism from increased mitochondrial respiration is typically accompanied by increases in both the electron in-flow and out-flow rates. The oxCCO concentration will only vary if the difference between the out-flow and in-flow rates changes. Accordingly, the oxCCO increase we observed indicates that the out-flow rate increased more than the in-flow rate. This could be explained by a prodrug-induced decrease in the proton electrochemical potential across the inner mitochondrial membrane and a resultant increase in ATP synthesis (see Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003e); prior work has suggested that this effect will disproportionately increase the electron out-flow rate.\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e Future work is needed to better understand and test predictions about the relation between oxCCO concentration and metabolic demand \u003cem\u003ein vivo\u003c/em\u003e, given the different factors at play in our study.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e4.3 Importance of the Analysis Algorithm for oxCCO measurements\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eOur optical analysis algorithm leveraged photon diffusion theory to quantify changes in oxCCO (see supplementary material). In contrast to the modified Beer-Lambert schemes that are commonly used for these measurements (see supplementary material),\u003csup\u003e9\u003c/sup\u003e photon diffusion theory more readily accounts for changes in tissue scattering.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e In our experiments, we did indeed observe significant tissue scattering changes over time. Specifically, in the rotenone\u0026thinsp;+\u0026thinsp;placebo group, the Mie scattering parameters, A (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and b (p\u0026thinsp;=\u0026thinsp;0.02), both decreased over time, and in the rotenone\u0026thinsp;+\u0026thinsp;prodrug group, b decreased over time (p\u0026thinsp;=\u0026thinsp;0.02). Importantly, we found that if the modified Beer-Lambert scheme was used for analysis, then the estimated ΔoxCCO temporal change was no longer significant in the rotenone\u0026thinsp;+\u0026thinsp;placebo group (\u003cem\u003ei.e.\u003c/em\u003e, p\u0026thinsp;=\u0026thinsp;0.80). Further, although the modified Beer-Lambert scheme still showed 2nd period increases in ΔoxCCO for the rotenone\u0026thinsp;+\u0026thinsp;prodrug group, the magnitude of the increase was smaller than that of the photon diffusion theory scheme (\u003cem\u003ei.e.\u003c/em\u003e, a slope of 0.08 \u0026micro;M/h (p\u0026thinsp;=\u0026thinsp;0.04) versus 0.19 \u0026micro;M/h (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) obtained with photon diffusion theory). These findings thus suggest the importance of employing full photon diffusion theory for oxCCO measurement if tissue scattering changes.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e4.4 Limitations\u003c/h2\u003e\u003cp\u003eThe sample size of our study is small (n\u0026thinsp;=\u0026thinsp;5 in each group), and therefore our findings need confirmation from a larger study. Second, while our suggestion of increased mitochondrial oxygen metabolism is consistent with the data, we lack direct evidence of increased pyruvate usage in the tricarboxylic acid (TCA) cycle during prodrug treatment. In future work, such evidence could be gleaned from cerebral metabolomics analysis of the metabolites involved in glycolysis and TCA cycles.\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eThird, the co-treatment paradigm at a single prodrug dose regiment limits direct therapeutic interpretation. However, the stabilization of cerebral lactate levels and normalized pyruvate metabolism demonstrates that NV354 prodrug can maintain oxidative capacity under metabolic stress. This proof-of-concept is essential before testing rescue therapy protocols, and it also provides mechanistic insight into how succinate supplementation might benefit patients during metabolic crises. Future dose-response investigations will be important for clinical translation. Future study of the effects of NV354 treatment alone are also warranted. Though the present study does not have an NV354-only experimental group, we note that in a prior study of rodents,\u003csup\u003e31\u003c/sup\u003e NV354 treatment alone did not show any differences (compared to shams) in MAP, venous blood gases, and cerebral mitochondrial respirometry. Thus, we expect that our findings of baseline stability in our control group will be similar to those that result from the administration of NV354 treatment alone.\u003c/p\u003e\u003cp\u003eFourth, future study with longer-term monitoring is needed to relate the acute effects of prodrug treatment to longer-term therapeutic effects. That said, the acute intervention efficacy we observed is a prerequisite for longer-term benefits, and it is also relevant for mitochondrial emergencies that require rapid intervention in acute critical illness. Thus the present study has taken an important step on the clinical translation pathway for human studies.\u003c/p\u003e\u003cp\u003eFinally, to derive the optical metrics, we have assumed homogeneous tissue optical properties and constant total CCO concentration. These assumptions can lead to errors, for example caused by extra-cerebral tissue contamination or by tissue-dependent changes in mitochondria density. The magnitude of the errors arising from these effects should be explored in future work.\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eWe employed frequency-domain and broadband diffuse optical spectroscopy techniques to monitor cerebral oxygen extraction fraction (OEF), oxidized cytochrome-c-oxidase concentration changes (ΔoxCCO), and total hemoglobin concentration (HbT) in a preclinical trial of a novel succinate prodrug (NV354) for treating rotenone-induced mitochondrial complex I dysfunction in swine. Invasive cerebral microdialysis measurements of lactate, pyruvate, and lactate-pyruvate ratio (LPR) in the interstitial fluid of the brain parenchyma were also obtained, providing traditional information about cerebral metabolism. Our results indicate mildly impaired cerebral oxygen metabolism from rotenone-induced complex I dysfunction in the rotenone-placebo group and increased cerebral oxygen metabolism due to prodrug treatment in the rotenone-prodrug group. Specifically, the former impairment is suggested by increased LPR, lactate and oxCCO concentrations. The latter metabolism enhancement is suggested by stabilized cerebral lactate concentration and decreased pyruvate concentration. Thus, our results demonstrate that the prodrug treatment normalized cerebral lactate production in large animals with mitochondrial impairment, which provides a proof-of-concept of the prodrug\u0026rsquo;s ability to maintain mitochondrial function under stress. To our knowledge, this study provides the first \u003cem\u003ein vivo\u003c/em\u003e optical measurements of oxCCO and OEF changes induced by primary mitochondrial dysfunction and mitochondria-targeted drugs. Notably, the oxCCO metric of metabolism that probes the mitochondria was found to be more sensitive to mitochondrial dysfunction than the OEF metric that probes the tissue vasculature. Interpreting the oxCCO metric, however, is challenging. Our work suggests that it increased in both the placebo group and the prodrug group for different reasons.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e The authors would like to thank the veterinary staff at the Children’s Hospital of Philadelphia, members of the Resuscitation Science Center (Lucas Hobson, Yuxi Lin, Karli Wulwick, Anthony Davis, Takayuki Sueishi, Shannon Morton, Sarah Morton, Kate Stumpf, Jonathan Starr and Nick Fagan), the June and Steve Wolfson Laboratory (Nicolina Raneri, Alyssa Seeney, Rika Goto, April Hurlock and Darci Anderson), and the Yodh Biomedical Optics Group (Joseph Majeski, Zaha Shahdad and Ken Abramson) for their constructive discussion and comradery. The authors would also like to thank Sarah Piel, Magnus Hansson, and Sergei Vinogradov for their feedback and comments. Finally, the authors gratefully acknowledge discussions with Gemma Bale and Ilias Tachtsidis for their advice about the optical cytochrome-c-oxidase measurements.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u0026nbsp;\u003c/strong\u003eConceptualization: T.J.K., M.J.M, W.B.B., T.S.K., R.M.F.; experiments: A.L., R.M.F., T.S.K., M.J.M.; data analysis and figures: A.L., R.M.F., E.E., T.S.K., A.G.Y., W.B.B.; interpretation of data: all authors; drafting the work (A.L., W.B.B.) or revising it critically for important intellectual content (R.M.F., T.S.K., E.E., M.J.M., A.G.Y., T.J.K.). All authors approved the final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e National Institutes of Health grants R01-NS113945 (W.B.B.), P41-EB029469 (A.G.Y.), and R01NS114656 (M.J.M); the Children’s Hospital of Philadelphia Frontier Program (T.S.K., R.M.F., W.B.B., T.J.K.), Department of Defense grant PR171698 (T.J.K), and American Heart Association grant 24SCEFIA1260971 (T.S.K.).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e E.E. has received salary support and/or travel reimbursements and/or grants from Abliva AB, a Swedish public company developing pharmaceuticals in the field of mitochondrial medicine. E.E. is currently an Abliva employee and member of its management team. Abliva AB has filed patents related to succinate prodrugs (listed below), some of which name E.E. as an inventor. The other authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003eSuccinate prodrug, compositions containing the succinate prodrug and uses thereof (US20230033294-A1, 11565998-B2, 20220162162-A1)\u003c/p\u003e\n\u003cp\u003eNovel cell-permeable succinate compounds (US20210401792-A1, 20170105961-A1)\u003c/p\u003e\n\u003cp\u003eCell-permeable succinate compounds (US11147789-B2)\u003c/p\u003e\n\u003cp\u003eSuccinate prodrugs for use in the treatment of lactic acidosis or drug-induced side-effects due to Complex I-related impairment of mitochondrial oxidative phosphorylation\u003c/p\u003e\n\u003cp\u003e(US10307389-B2, 20170100359-A1)\u003c/p\u003e\n\u003cp\u003eProtected succinates for enhancing mitochondrial ATP-production (US9670175-B2, 20150259317-A1)\u003c/p\u003e\n\u003cp\u003eProdrugs of succinic acid for increasing ATP-production (US20170105960-A1)\u003c/p\u003e\n\u003cp\u003eData availability: The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eNiyazov, D. 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Diagn.\u003c/em\u003e \u003cb\u003e8\u003c/b\u003e, 617\u0026ndash;633. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1586/14737159.8.5.617\u003c/span\u003e\u003cspan address=\"10.1586/14737159.8.5.617\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2008).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Primary mitochondrial disease, Succinate prodrug, Cerebral oxygen metabolism, Cytochrome-c-oxidase, Diffuse optical spectroscopy","lastPublishedDoi":"10.21203/rs.3.rs-8148374/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8148374/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSuccinate prodrug NV354 is a promising therapy for mitochondrial dysfunction. We used diffuse optical and microdialysis techniques to characterize its effects on cerebral oxygen metabolism during rotenone poisoning. One-month-old swine received a four-hour co-infusion of rotenone with either the succinate prodrug NV354 (n\u0026thinsp;=\u0026thinsp;5) or placebo (n\u0026thinsp;=\u0026thinsp;5). Cerebral interstitial lactate continually increased in the placebo group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), but lactate levels plateaued in the NV354 group (p\u0026thinsp;=\u0026thinsp;0.90), which is consistent with NV354\u0026rsquo;s ability to increase oxygen metabolism in large animals. The study presents first \u003cem\u003ein vivo\u003c/em\u003e optical measurements of changes in cytochrome-c-oxidase redox state induced by primary mitochondrial dysfunction and mitochondrial-targeted drugs.\u003c/p\u003e","manuscriptTitle":"Optical and Microdialysis Monitoring of Succinate Prodrug Treatment in a Rotenone-Induced Model of Mitochondrial Dysfunction in Swine","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-03 18:40:05","doi":"10.21203/rs.3.rs-8148374/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a87b3a75-f64b-41ad-8384-16dff73f2abb","owner":[],"postedDate":"December 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":58978631,"name":"Health sciences/Medical research"},{"id":58978632,"name":"Biological sciences/Neuroscience"},{"id":58978633,"name":"Biological sciences/Physiology"}],"tags":[],"updatedAt":"2025-12-11T02:53:53+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-03 18:40:05","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8148374","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8148374","identity":"rs-8148374","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}