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Barefoot Running and Hip Kinematics

Good News for the Knee?


Author Information
Medicine & Science in Sports & Exercise: May 2015 - Volume 47 - Issue 5 - p 1009-1016
doi: 10.1249/MSS.0000000000000505
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Running is a relatively simple, accessible, effective, and popular recreational fitness activity, but unfortunately, injuries are common (34). The most common clinical entities causing disability occur at the knee, often as patellofemoral pain syndrome (PFPS) and iliotibial band friction syndrome (ITBS) (1,33).

Distal biomechanical factors such as increased rearfoot eversion and increased tibial internal rotation have been identified as potentially contributing to both PFPS (27,39) and ITBS (14,25). Recently, research and clinical practice have focused on “proximal” influences from above the knee on knee pain and function. Specifically, measures of hip strength and hip kinematics have become a major focus (6,22). The incidences of PFPS and ITBS are higher in women than in men, and sex differences in hip anatomy, strength, and kinematics could be responsible (3,33). Systematic reviews (22,29) have reported that PFPS is associated with decreased hip strength, specifically of abduction and external rotation. A correlation has also been established between PFPS and faulty hip mechanics during running; namely, excessive hip internal rotation (HIR) and adduction (HADD) (6,22,26,27,35). There is prospective evidence that greater HADD is present among women who go on to develop PFPS (26). Studies have proposed that increasing HADD and HIR results in displacement of the patella laterally relative to the femur, thus decreasing patellofemoral contact area and increasing lateral patellofemoral joint (PFJ) stress and forces on the subchondral bone, leading to pain (28,38).

This dynamic valgus movement of the distal femur and knee has also been suggested to increase strain on the ITB, compressing the richly innervated fat-pad underlying it at the lateral femoral condyle, leading to pain (25). Noehren et al. (25) reported that excessive HADD was one of the strongest predictors of developing ITBS in a prospective study of 100 female runners. Ferber et al. (14) also documented that female runners with a history of ITBS exhibited significantly greater HADD than those with no history. Contralateral pelvic drop (CLPD) is when the level of the pelvis of the nonstance leg drops during running or single leg functional exercises; CLPD increases because of weak hip abductors on the stance side and excessive CLPD has been identified in female runners with PFPS (35).

Recognition of the importance of hip structures and movements on knee injuries has resulted in recommendations that both hip strength and faulty hip kinematics be addressed when treating PFPS and ITBS (6,22,25). Although pure hip strengthening protocols have been reported to improve symptoms in PFPS (11,13) and ITBS (15), improvements in strength alone may not be sufficient to alter kinematics (11,13,36). Recently, interventions focusing on altering running kinematics via real-time gait feedback (28) and mirror gait retraining (38) have shown promising results for PFPS. Changes in hip and knee kinematics have also been observed with step rate manipulation (16), but a correlation with injury risk has not yet been established.

Interest and participation in barefoot running, or running in minimalist shoes, have gained popularity. This is partly due to claims that it may reduce running injuries (30), but the mechanism(s) by which barefoot running might influence injury risk has not been clearly demonstrated (23). Differences in kinetics (forces) between barefoot and shod running have been reported (20), especially during forefoot strike (FFS) running, which is the predominant strike type in habitually barefoot runners (20,32). The lower vertical impact peak observed during barefoot or FFS running compared to rearfoot strike (RFS) during the first half of stance (absorptive phase) (10,20,32) has been theorized as having potential to reduce the risk of impact-related running injuries (10,20). A decreased incidence of repetitive-type injuries in athletes who FFS has been supported by the findings of one retrospective study (8). Differences in joint kinematics (movements) between barefoot and shod running, particularly at the ankle and knee, have also been reported (4,9,20), but how barefoot running might contribute to injury risk remains unproven and unclear (23).

Despite acknowledgment of the contribution of hip movements to common running injuries, there is a paucity of research reporting the effect of barefoot running on three-dimensional hip kinetics or kinematics (4,17). Kerrigan et al. (17) reported significant differences in kinetics but did not report on kinematics. Bonacci et al. (4) reported no significant differences in kinematics at the hip when comparing barefoot and shod gait in various shoe conditions. However, these cohorts were highly trained (4) or male runners (17) with lower limb kinematics which may be different from those of recreational female runners (12).

Therefore, this study investigated whether differences in lower limb touchdown geometry (9) during barefoot running would result in changes in stance-phase hip kinematics in a group of habitually shod recreational female runners. Specifically, hip kinematic variables associated with PFPS and ITBS, namely, HADD, HIR, and CLPD (14,22,25–27,35), were assessed. We hypothesized that the more FFS pattern induced by barefoot gait would lead to shorter strides and a touchdown position of the lower limb that would be closer to the body’s center of mass than shod RFS running. This could facilitate greater control of HADD, HIR, and CLPD by the hip musculature and result in decreases to initial and peak values during stance for these variables. If such changes could be demonstrated in a single session of barefoot running, it would provide a theoretical rationale for consideration of barefoot running as a therapeutic or preventative strategy for PFPS and ITBS. Also, we hypothesized that differences between conditions would be evident in sagittal plane kinematics for hip and knee flexion and for spatiotemporal parameters.



An a priori power analysis was conducted for expected outcomes with a Type I error probability of 0.05 and an effect size of 0.8. This analysis indicated that n = 23 would provide a statistical power of ∼95% (G*Power v3.0.10 free software; Institute of Experimental Psychology, Heinrich Heine University, Dusseldorf, Germany). Twenty-three female recreational runners, recruited from collegiate and local clubs and via university notice boards, completed the study protocol. Participants had a mean ± SD age of 30 ± 3 yr, height 1.64 ± 0.06 m, body mass 57.5 ± 5.5 kg, BMI 21.3 ± 1.6 kg·m−2, and mean weekly running distances of 29.7 ± 14.0 km. All participants were running in standard cushioned shoes before the study, including neutral, stability, and anti-pronation-type models. All were running >15 km·wk−1 for at least the previous 6 wk, and all had previous experience of treadmill running. Participants were excluded if they had any neurological or musculoskeletal condition that had prevented them training in the previous 6 months, were currently attending physiotherapy or following a lower limb rehabilitation or prehabilitation program, were currently or had ever ran in minimalist footwear, or ran in “racing flats” in training (use in races was allowed). Written informed consent was obtained from all participants before study enrollment. The study was conducted in accordance with international ethical standards and University of Dublin ethics committee granted approval.

Experimental protocol.

Participants were assessed while running at 3.33 m·s−1 (12 km·h−1) on a conventional motorized treadmill (Proform 700 ZLT, UT) in both barefoot and shod conditions. This velocity was chosen because it reflected a comfortable running pace for the recreational running sample. Participants ran shod first because that was the standard footwear condition for all participants at baseline, and it discounted the possibility of a task performed immediately before (barefoot running) having caused motor pattern carryover. Test conditions were identical for barefoot and shod trials and took place indoors in a temperature-controlled room with artificial lighting. Participants avoided strenuous exercise in the 24-h pretest and warmed up by following their usual routines. All participants wore standard, neutral-cushioned shoes (Adidas Duramo, weight 250 g, EVA/Adiprene sole) for the shod trials. After placement of kinematic markers in each condition, participants ran at a self-selected velocity for at least 4 min to become comfortable running on the treadmill with gait analysis equipment attached (10). At 4 min, treadmill velocity was increased to 3.33 m·s−1 for >50 s before data collection. All participants expressed comfort with treadmill running with kinematic markers attached before data acquisition and were not aware of when kinematic data were being captured. A 10-min break followed the shod trial, during which participants performed an active recovery, and kinematic markers were changed from running shoes to bare feet. Participants received no verbal instruction as to how they should run in either condition and were not informed of what kinematic variables were being assessed or of the study hypotheses.

Equipment and data collection.

Three-dimensional running kinematics were captured and analyzed using the Coda Dual CX1 system (Charnwood Dynamics, Rothley, UK). Two sensor units, placed equidistant (3 m) and orthogonally to the left and right sides of the sagittal plane of the participant, captured horizontal and vertical motions of active infrared LED markers (circumference = 5 mm) attached to discrete anatomical locations on the participant. Signals were cross-correlated in real time, and three-dimensional marker trajectories were sampled at 200 Hz. Twenty markers (10 per side) were located as follows: on the pelvic frame (ASIS and PSIS), knee joint center (lateral joint line, 15 mm anterior to the level of the head of the fibula), lateral malleolus, lateral calcaneus (“heel”), and overlying the fifth metatarsal head (“toe”) (Fig. 1). Thigh and shank wands (plastic, attached to the skin via silicone rubber bases with Velcro strapping) carried a pair of markers to define axial orientation of their host segment and were aligned perpendicular to the knee and ankle joint axes, respectively (Fig. 1). Skin adhesive spray and tape were used to minimize artefact marker movement on the participants’ skin. For shod trials, kinematic markers were placed on the shoe upper, overlying the foot landmarks. Before each testing procedure, anthropometric variables of height, mass, pelvic width and depth, and knee and ankle joint width were assessed. Reference points were calculated by software for the sacrum; hip, knee, and ankle joint centers; and for thigh, shank, and foot segments. The hip joint center was calculated according to the method of Bell et al. (2). The medial knee reference was determined by the Codamotion software as one knee width distance from the lateral knee reference point, in a direction perpendicular to the virtual hip and the two thigh wand markers. The knee center reference point was subsequently calculated as the midpoint of the medial–lateral reference axis. The ankle marker was labeled as the lateral ankle reference point. The medial ankle reference point was determined by the Codamotion software as one ankle joint width from the lateral ankle reference point in a direction perpendicular to the virtual knee joint center and two tibial horizontal wand markers. The ankle center reference point was determined as the midpoint of these two points. Eulerian joint angles and segment rotations were calculated automatically for every time point by Codamotion segmental analysis (Version 6.76.4). Because an instrumented treadmill was unavailable, stance phase and foot strike pattern (FSP) were identified kinematically, using a method described previously (21). For each trial, a 5-s epoch of data was analyzed from each participant’s dominant leg.

Schema of marker position for segment calculation with CODA. Hip joint center (R.Hip) and R.Asis are virtual markers calculated from PSIS and ASIS marker positions and participant pelvic measurements. R.Post.Fem, R.Ant.Fem and R.Post.Tib, R.Ant.Tib are located on the femoral and tibial wands, respectively, and secured to participant’s skin. Adapted with permission from Coda CX1 user guide. (Charnwood Dynamics Limited, 2008, p. 62.)

Data reduction.

Five stance phases were extracted from each 5-s data epoch and transferred to Matlab for processing using customized program (Matlab, V7.14 R2012a; MathWorks, Natick, MA). Temporal information (in ms) for heel–toe latency (positive for RFS, negative for FFS) and ground contact time (GCT) were initially calculated, and step rate was computed using the time between foot strikes. Strides were then temporally normalized (cubic spline fitting) to 100 data points to eliminate interstride variations in duration. Kinematic variables of interest were subsequently identified, namely, HADD and HIR angles and CLPD, along with knee and hip flexion angles. Previous studies of kinetic data for running have identified two discrete force peaks during stance: the vertical impact peak, occurring shortly after foot strike at approximately 10% of stance, where the rate of loading is greatest, and peak ground reaction force (occurring at approximately 40% of stance, the transition from the absorptive to propulsive phase) (9,20,37). Hence, for each variable in this study, joint angles at initial contact (IC), at 10% of stance, and peak angles during stance were computed. Analysis of pilot data showed that peak HIR may occur late in stance and that peak hip flexion occurred at IC. Thus, for HIR and hip flexion, an analysis of data at 40% of the gait cycle was also performed. This corresponded with the timing of peak data for knee flexion, HADD and HIR in this study, and also with the point at which peak ground reaction forces have been recorded in other kinetic studies (9,20).

Statistical analysis.

Normality of data was assessed using the D’Agostino and Pearson omnibus normality test. Where data across time and group for a variable were normally distributed, paired Student’s t-tests were used to detect differences between shod and barefoot kinematics; P < 0.05 was selected to indicate significance. Where a statistically significant difference between conditions was observed, effect sizes (Cohen d) were computed, with <0.2 considered trivial, 0.20–0.49 small, 0.50–0.79 moderate, and ≥0.80 large. Descriptive statistics are presented as means ± SD. All statistical tests and analyses were performed using GraphPad Prism version 6.00 (GraphPad Software, San Diego, CA).


Group means (SD) for each variable are presented for shod and barefoot conditions, along with calculated mean differences (Table 1). Significant differences between conditions were observed for all spatiotemporal variables. Overall stride duration and GCT were significantly shorter barefoot than when shod (P < 0.001). Correspondingly, there was a significant increase in step rate when barefoot (P < 0.001). The group mean heel–toe latency switched from indicating RFS when shod, to slight FFS when barefoot (P < 0.001). The mean knee flexion peak occurred earlier in the stance phase when barefoot (P < 0.001). No significant differences were recorded in group mean timing of peak data for HADD and CLPD in either condition. For hip kinematics during the absorptive phase of stance (Table 1 and Fig. 2), a significant reduction in HADD, HIR, and CLPD were observed at IC when barefoot (−1.6°, P < 0.001; −0.9°, P < 0.001; +0.8°, P < 0.01, respectively). At 10% of stance, HADD, HIR, and CLPD remained significantly lower barefoot when compared to shod (−1.0°, P < 0.01; −2.9°, P < 0.01; +0.5°, P < 0.05; respectively). There were no significant differences between conditions in peak stance data for HADD or CLPD or at 40% of stance for HIR. However, a greater hip flexion angle at 40% stance was observed in the shod condition (2.9°, P < 0.001).

Group mean ± SD spatiotemporal and kinematic data for shod and barefoot trials.
Group mean hip kinematic graphs during stance phase of the gait cycle. Positive values denote hip internal rotation (bottom left panel). Negative values indicate pelvic drop (top right panel). Asterisk (*) indicates significant differences between conditions at initial contact. Plus (+) indicates significant differences between conditions at 10% of stance. Hash (#) indicates significant differences between conditions at 40% of stance (* or + infers P < 0.05, ** or ++ infers P < 0.01, and *** or ### infers P < 0.001). Vertical lines indicate group SD at discrete 2% increments of the stance phase.

In addition, greater knee flexion at IC, a lower peak knee flexion and lower knee range of motion (ROM) in the absorptive phase of stance (all P < 0.001) were observed when barefoot (Table 1 and Fig. 3). Significant differences between conditions in hip kinematics were associated with small to moderate effect sizes, with moderate to large effect sizes for differences detected in spatiotemporal data and knee kinematics.

Group mean knee flexion during stance phase of the gait cycle. Asterisk (*) indicates significant differences between conditions at initial contact. Plus (+) indicates significant differences between conditions at 10% of stance. Hash (#) indicates significant differences between conditions at peak flexion (***, +++, or ### infers P < 0.001). Vertical lines indicate group SD at discrete 2% increments of the stance phase.


This study is the first to specifically examine the effects of barefoot running on three-dimensional stance-phase hip kinematics in habitually shod female runners—a group known to be at high risk for knee injuries and often due to faulty hip kinematics. The hypothesis that running barefoot would result in lower values at IC for HADD, HIR, and CLPD angles was accepted. Similar reductions were also evident at 10% of stance, corresponding with the likely occurrence of the vertical impact peak. Time-normalized mean kinematic graphs (Fig. 2) illustrate that differences between conditions disappear by approximately 20% of the stance phase for HADD and CLPD and by 35% for HIR. Kinematics for the propulsive phase of stance (from approximately 40% onward) are almost identical in both barefoot and shod conditions for HADD and CLPD, with HIR being slightly greater during the propulsive phase when barefoot. Spatiotemporal findings of increased step rate, shorter GCT, and a more FFS pattern when barefoot in this study agreed with those of other authors (4,9,10,17). However, the hip kinematic findings were different from those of Bonacci et al. (4), who recorded no significant differences in hip kinematics at IC or peak joint angles when comparing barefoot and shod conditions, in a mixed-sex sample of 22 highly trained runners (8 females). Kerrigan et al. (17) studied 68 habitually shod, healthy participants (37 females) when running barefoot and in stability running footwear. They reported a mean 54% decrease in hip internal rotation torque when running barefoot compared with shod but did not report on kinematics. Other comparisons of barefoot and shod kinematics examined only sagittal plane kinematics (9) or knee and ankle kinematics only (20,32).

As a potential method of altering stance-phase hip kinematics during running, our data can be compared with acute studies that assessed the effect of step rate or FSP manipulation as well as with longitudinal studies involving strengthening programs or gait retraining.

Two studies involving a hip strength and movement education program in healthy females with excessive HADD either during running (36) or during single-leg squat (40) did not bring about changes in peak or ROM data for hip kinematic variables during running, despite changes in strength. Earl and Hoch (11) reported nonsignificant increases in HADD and HIR ROM (angle at IC to peak joint angle) in female participants with PFPS after an 8-wk hip and core strengthening program. Snyder et al. (31) recorded an increased HADD ROM (mean difference = 1.4°) and a trend toward decreased HIR ROM (mean difference = 0.8°) after a 6-wk program of closed-chain hip rotation exercises in 15 healthy women. Similar to the current study, Snyder et al. (31) also recorded a reduced HIR angle at IC. Limitations to ROM as a measure were acknowledged by these authors. Noehren et al. (28) selected 10 female participants with PFPS and excessive HADD, who engaged in eight sessions of real-time gait retraining, where visual feedback of HADD during stance was provided to participants during treadmill running, and gradually withdrawn over the last four sessions. Participants were directed to “contract their gluteal muscles,” “run with the knees pointing straight ahead,” and “maintain a level pelvis.” There was a significant decrease in mean peak HADD (5.5°) and CLPD (2.3°) after the retraining. A similar study by Willy et al. (38) involved 10 female participants with PFPS and baseline HADD >20°. After eight sessions of gait retraining using mirror feedback and similar verbal cues, the authors recorded a decrease in peak HADD (5.9°) and CLPD (1.9°), along with improvements in pain and function. These data suggest that gait retraining may be more successful at changing running kinematics than isolated strength training. How much participant bias on postintervention testing contributed to these findings is not quantifiable. The more modest kinematic changes observed in the present study were recorded from a single session, without any verbal cues to participants. Also, participants were not preselected as having abnormal shod mechanics; thus, the potential for differences between conditions may have been smaller. As a potential intervention to affect stance-phase hip kinematics when running, our data suggest that simply removing shoes is at least as effective as a 4- to 8-wk strength training program (11,31,36,40) but, based on limited data, that larger kinematic changes may occur following instructed gait retraining (28,38). We suggest that a combination of gait retraining plus footwear changes may yield greater acute and long-term gait alterations than either method alone.

No differences would occur in hip strength between trials in participants in the current study and no form of gait retraining was undertaken. Therefore, three possible mechanisms for the observed changes in hip and knee kinematics when running barefoot are proposed: increase in step rate, effects of FSP, and increase in afferent information from the plantar surface influencing muscle activation proximally.

Group mean step rate in the current study was 3.5% higher when barefoot (178 vs 172 steps per minute; P < 0.001). This increase in step rate has been a consistent finding of research comparing barefoot and shod gaits (4,9,10,17,32). Two recent articles have investigated the effect of isolated step rate manipulation on hip and knee mechanics and on muscle activation. Heiderscheit et al. (16) measured kinetic and kinematic variables in healthy recreational runners during three step rate conditions: preferred (173 ± 9 steps per minute), +5%, and +10%. At the percentage step rate increase comparable to that observed when comparing barefoot and shod gaits (+5%), mean peak HADD during the loading response was significantly lower (−0.9°) than at preferred step rate and mean peak knee flexion angle was also decreased (−2.2°). There was no effect at +5% on hip flexion or internal rotation. In the same participants, Chumanov et al. (7) reported increased EMG activity in gluteus maximus and medius in late swing/preactivation (just before IC), when rate was increased by 10% (but not 5%) from the preferred step rate. Chumanov et al. (7) proposed that increased muscle activity in anticipation of ground contact was likely to alter the landing posture of the limb, subsequent joint moments, and energy absorption. The effect on impact forces of such “tuning” of muscles in preparing for landing has been discussed by Nigg and Wakeling (24). Although EMG was not measured in the current study, the proposal (7) of an increased preactivation of gluteal muscles might account for the significantly lower HIR, HADD, and CLPD observed at IC and at 10% of stance in study participants here when tested barefoot.

Differences in FSP between conditions may account for some of the differences in hip kinematics recorded in the current study. Kulmala et al. (18) compared three-dimensional kinematics between 19 RFS and 19 FFS runners (shod) and observed significantly lower peak HADD in the FFS group, without any differences in step rate or hip abduction strength between groups. One possible explanation for this is that increased loading distally at the ankle during FFS (18) could have effects proximally on hip loading. Such a trade-off in joint loading has already been reported between the ankle and knee (4,18). In the current study, all individuals displayed a reduced heel–toe latency when barefoot, with the group mean shifting from indicating RFS when shod, to slight FFS when barefoot. In addition, we speculate that a link between an FFS pattern and increased activation of gluteus maximus may exist, regardless of footwear type. The human gluteus maximus is a major extensor, abductor, and external rotator of the hip and has been hypothesized to have developed in humans as a specific adaptation to running (19). Gluteus maximus is more active with increased running velocity, and with uphill running, two activities are also associated with FFS. However, such a link is unproven and warrants further research.

A third possible mechanism for differences in hip kinematics observed in the current study is via increased activation of the hip musculature during or just before stance, as a result of increased sensory input from the richly innervated glabrous epithelium of the foot. It has been suggested that, in running, muscle activities are predetermined by previous repetitive impacts (24). Perhaps increased sensory afferents from the soles of the feet, when barefoot, could modulate both the gait pattern and the pattern of muscle activation compared with the insulating effect of wearing cushioned shoes, described by one author as being “pseudo-neuropathic” (30). Neurophysiological and EMG data would be required to evaluate such a hypothesis.

At the knee, earlier peak knee flexion (32% vs 38% of stance) and a more extended hip throughout stance when barefoot suggest a shorter “braking period” after IC in the barefoot condition. Significant differences in knee flexion at IC, peak flexion, and flexion ROM in the absorptive phase of stance were also observed—outcomes in agreement with other studies of barefoot and shod gaits (4,9,20). A decrease in peak knee flexion and flexion ROM between IC and mid stance, as observed during barefoot running, reduces knee extension moment and subsequent PFJ stress (5,18). This also could have clinical significance for prevention and treatment of knee injuries.

Certain limitations exist in the current study that must be considered before drawing conclusions. A value of 10% of stance was used to approximate the vertical impact peak based on the findings of other studies (9,18,20); however, this cannot be confirmed without recorded force data for each individual. Combining kinetic, kinematic, and EMG data would give more complete information on changes in hip function when running barefoot. The greatest differences in hip kinematics were observed at IC and 10% of stance; however, it is not clear which part of stance has the greatest influence on injury risk (39). Future research should seek to elucidate the relationship, if any, between kinematics, kinetics, and spatiotemporal variations and their effect on injury risk. Although statistically significant, the absolute differences in hip joint kinematics observed between conditions were modest (0.5°–2.9°). However, other researchers in PFPS (28,38) have reported 86%–96% decreases in pain scores for a difference of 1.5° to 5.9° in HADD, HIR, and CLPD after gait retraining in symptomatic participants. Bonacci et al. (5) reported a 12% decrease in PFJ stress after a 2.1° decrease in peak knee flexion. These studies (5,28,38) suggest that small changes in joint kinematics may have more significant effects on tissue stress and subjective symptoms. Finally, this is an acute study of a change in footwear condition, without a habituation period. The kinematics of participants in this study do not necessarily reflect those of habitually barefoot runners. Greater differences in kinematics in previously shod runners may be evident after a habituation period (21).

In conclusion, excess HADD, HIR, and CLPD have been associated with PFPS and ITBS, particularly in female runners. In this study, running barefoot, as opposed to shod, resulted in significant decreases in HADD, HIR, and CLPD at IC and at 10% of stance in female recreational runners. Thus, barefoot running has theoretical potential as a treatment modality or as a preventative measure for these common running injuries in this cohort. When considered in conjunction with likely decreases in PFJ stress as a result of decreased knee flexion peak and ROM during stance when barefoot, the case for barefoot running as treatment or for the prevention of knee injuries is strengthened further. However, evidence from prospective research, which directly investigates the effects of barefoot running on knee injury risk, is required to confirm any links between the two.

The authors would like to acknowledge the Department of Physiotherapy at St. James’s Hospital Dublin 8 for the use of the gait laboratory. The authors also thank all participants in the study for giving freely and generously of their time. No external funding was received. There are no conflicts of interest among any of the authors of this article. The results of the present study do not constitute endorsement by the American College of Sports and Exercise Medicine.


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