P < 0.01). The CAI group exhibited a lesser alteration in ankle inversion angle compared to the non-CAI group. Notably, during the one-foot landing period, the CAI group demonstrated a significantly greater maximum ankle inversion angle in contrast to the non-CAI group . Furthermore, the CAI group displayed a substantially larger maximum dorsiflexion angle at the ankle joint compared to the non-CAI group . Additionally, the CAI group exhibited a prolonged peak time for ankle dorsiflexion moment as compared to the non-CAI group . Collectively, the findings elucidated a reduction in the maximum ankle joint inversion angle during the one-foot push-off phase in individuals with CAI. Furthermore, increased maximum inversion angle and maximum dorsiflexion angle of the ankle joint were observed during the one-foot landing period, alongside a lengthening of the peak time of ankle dorsiflexion moment. These results contribute valuable insights into the selection of training methodologies for basketball players afflicted by CAI.At present, the effects of chronic ankle instability (CAI) on the biomechanics of the ankle joint in the three-step layup of basketball players are not clear. This work aims to thoroughly investigate the impact of CAI on the biomechanical characteristics of the ankle during the execution of a three-step layup in basketball players. Thirty male basketball players were stratified into distinct groups—namely, a CAI group and a non-CAI group—comprising 15 individuals each, based on the presence or absence of CAI. Demographic attributes, including age, weight, height, and the Cumberland Ankle Instability Tool (CAIT) score, were subjected to rigorous statistical examination within both athlete cohorts. The research employed four Whistler 9281CA 3D force measuring platforms (Switzerland), recording at 1000 Hz, in conjunction with eight camera motion analysis systems (USA), functioning at a frequency of 200 Hz. The study recorded maximal plantarflexion angle, inversion angle, dorsiflexion angle, and peak ankle dorsiflexion moment across the subjects during the distinct phases of push-off, landing, and the ensuing landing period. The findings notably exhibited that within the context of the one-foot push-off phase, the maximum ankle inversion angle was notably diminished in the CAI group as contrasted with the non-CAI group, demonstrating statistical significance (t = − 3.006,  Within the realm of basketball, the frequent actions of jumping and landing impose escalated loads upon the ankle joint3, which stands as a primary site of injury4. Research findings reveal that 78% of basketball-related injuries occur in the lower extremities, with ankle injuries accounting for 48% of these incidents5. Pertinent data from studies underscore that ankle sprains constitute 15% of injuries among collegiate athletes in the United States, with a notably elevated incidence rate among accomplished basketball players6. Initial investigations established that ankle sprains in numerous athletes often tend to recur7. In various team sports, the recurrence rate of ankle sprains in basketball approaches approximately 28%8, often attributed to neglect of rehabilitation following the initial injury10.The rapid evolution of basketball has spurred continuous enhancements in players’ athletic abilities and physical confrontation capacities, concurrently augmenting the likelihood of player injuries11. Such instability has the potential to detrimentally impact an athlete’s physical capabilities, performance in competitions, and daily activities. CAI patients commonly exhibit symptoms such as recurring sprains, altered sensory perceptions, impaired muscle control, swelling, pain, and reduced athletic prowess. As a prevalent ankle ailment, CAI is frequently observed among athletes, particularly in the realm of basketball12. This encompasses chronic lateral ankle sprains that compromise ankle joint stability and escalate the risk of in-game injuries for athletes13. CAI can lead to repetitive ankle sprains, consequently influencing an athlete’s performance in competitions and overall quality of life. CAI is caused by structural or functional instability of the ankle and peripheral soft tissues, changes in joint range of motion, abnormal balance function, and posture control in patients, with the main clinical manifestations being repeated ankle sprains14. Ankle sprains often result in laxity of the anterior talofibular ligament, with CAI patients showing a notable increase in the length of the anterior talofibular ligament15. In individuals with CAI, the affected ankle presents greater anterior displacement in the sagittal plane compared to healthy individuals, leading to atypical range of motion16. Football, basketball, and volleyball represent the sports most frequently associated with CAI incidence. Pertinent research underscores that approximately 70% of basketball players afflicted by acute ankle injuries encounter relapses within an 18-month span following the initial trauma, with nearly 20–40% of this subset progressing to develop CAI17. CAI, a prevalent disorder among basketball players, manifests with symptomatic ankle pain, muscular debility, proprioceptive deficiencies, and compromised functional performances; severe CAI detrimentally impinges upon specialized athletic capabilities18. The ramifications of CAI encompass diminished ankle muscle potency, restricted range of ankle motion, compromised proprioception, impaired self-reported functionality, hampered neuromuscular governance, and diminished equilibrium capabilities19. Moreover, CAI emerges as a pivotal contributor to lower limb structural injuries , and the interplay between structural and functional impairments of the lateral ankle drives the onset of CAI. This interrelationship is intertwined with neuromuscular and sensorimotor control aberrations20. Investigations have unveiled that individuals grappling with CAI exhibit decreased preactivation and a delay in the onset of peroneal muscle activation during dynamic tasks21. Researchers López-González et al. noted that patients with CAI exhibited postural stability deficits in both static and dynamic situations22.Chronic ankle instability (CAI) refers to a condition where, following one or more instances of ankle sprain, the ankle fails to fully recuperate, resulting in diminished stability of the ankle joint. This leads to recurrent episodes of ankle instability23. Notably, the majority of ankle sprains occur upon landing on one or both feet25, thereby accentuating the significance of lower limb stability during landing to avert sports-related injuries. Within the domain of basketball, characterized by continuous takeoff and landing actions, the athlete’s airborne trajectory post-descent hinges on the takeoff foot’s strength and the direction of impact. The execution of a three-step layup demands players to swiftly perform consecutive footwork and jumping actions within a short timeframe, encompassing requisites pertaining to ankle stability, muscle control, and coordination26. However, individuals with CAI may encounter heightened biomechanical challenges during such maneuvers due to compromised ankle joint stability, potentially leading to instability in the execution of movements. The decreased stability of the ankle joint among CAI patients renders them more susceptible to injuries during physical activity, particularly in scenarios like the three-step layup that involve rapid movements and changes in direction, consequently elevating their risk of injury27. CAI could result in diminished control over the ankle joint for athletes, rendering them less capable of precise execution in actions requiring accurate footwork and jumping. The three-step layup necessitates the completion of multiple steps within a brief duration, placing substantial demands on ankle joint control and stability, a domain potentially affected by CAI. Due to functional loss and damage to ankle joints in CAI patients, when RSLJ is performed with the affected side as the starting foot, the height and landing stability of CAI patients will be affected to a certain extent28. However, the effects of CAI on the biomechanics of the ankle in the three-step layup of basketball players are still unclear, and many existing research results cannot be applied to basketball players. Therefore, this work focused on second-tier basketball players and aimed to investigate the impact of CAI on the biomechanical characteristics of ankle joints during the execution of a standard three-step layup maneuver. By analyzing the kinematic and kinetic parameter changes in the ankle joints of both CAI-afflicted and non-CAI basketball players, this work aimed to provide an in-depth understanding of how CAI influences the biomechanics of ankle joints during the three-step layup among basketball players. The results were intended to offer a foundation for informed choices in training methods for basketball players while also contributing valuable insights to the study of ankle-related conditions and the development of rehabilitation strategies.The three-step layup is a common scoring technique in basketball games, encompassing the fundamental concept where, upon receiving the ball, the player executes a sequence of three consecutive steps to perform a layup shot. This technique aims to swiftly penetrate the defense and subsequently score. The three-step layup represents a basketball offensive maneuver involving three distinct stages: a short step, a long step, and a jump step. Employing this sequence of continuous footwork, players can rapidly approach the basket, evade defensive players, and create close-range scoring opportunities. Functioning as a scoring technique, the three-step layup not only enriches tactical choices within the game but also augments players’ prospects of scoring. Moreover, it serves as a test of players’ technical skills and decision-making abilities. In the realm of basketball, the execution of a three-step layup, encompassing a rapid single-leg jump (RSLJ) subsequent to a brief run-up, culminates in a landing on either one or both feet. During this intricate maneuver, the running pace is heightened, placing emphasis on the ball of the foot, and in certain instances, even the forefoot. This heightened pace engenders a dynamic interplay between the torso’s forward-moving inertia and the restraining force exerted by the lower limbs, consequently instigating a reciprocal action between body elevation and landing, rendering balance precarious. This interplay could lead to transient ankle joint inversion, precipitating the involvement of lateral ligaments, thereby predisposing to partial or even complete ligamentous rupture. Simultaneous rupture of the anterior talofibular and calcaneofibular ligaments may yield ankle joint instability, accompanied by temporary injury, dislocation, or subluxation29. The application of reflective markers was carried out by the same operator to ensure consistency in marker placement across different individuals. Since all the indicators required in this study were related to ankle joints, only marker points in the Helen Hayes model were selected to paste markers, which included the selection of landmarks on the ankle, knee center, hip joint center, thigh and shank, as well as the foot.Prior to the commencement of testing, participants underwent a 3-min stationary warm-up session followed by a practice session involving the execution of a ball-less three-step layup. Subsequently, reflective marker points were meticulously affixed to predetermined anatomical locations on the lower limb surfaces of the subjects, meticulously adhering to the refinements incorporated in the Helen Hayes modelIn this study, all participants typically initiated the three-step layup maneuver using their left leg as the push-off support foot. Therefore, for the purpose of this study, the left leg should continue to serve as the push-off support foot. Following the approach run, the participants executed a ball-less three-step layup maneuver while adhering to a naturally inclined landing trajectory. The initial progression involved stepping onto the designated No. 4 force platform Fig.  with theDefinition of different phases in the three-step layup is as follows.The one-foot push-off period refers to the moment during the execution of the three-step layup maneuver when one foot is off the ground, while the other foot is in contact with the floor. During this phase, the athlete utilizes the pushing force generated by the single supporting foot to lift off from the ground, preparing for the layup shot. This period typically occurs after the final step, where the player leverages the propulsion from the final step’s jump. The landing moment signifies the instance when an athlete completes the layup shot, and one foot makes contact with the ground after being airborne. At this moment, the player needs to land in a stable manner to prepare for subsequent actions, such as jumping again or changing direction. The stability during the landing moment is crucial to prevent injuries, ensuring the smooth execution and effectiveness of the subsequent actions. The one-foot landing period designates the duration between the time when one foot lands and the moment before the other foot lands in the three-step layup. Within this time frame, the athlete must maintain balance and control over their body posture to smoothly complete the maneuver. This phase typically involves flexion and control of the knee and ankle joints to ensure body stability.30: (1) individuals meeting the criteria for CAI screening31; (2) unilateral ankle joint had at least one history of a severe sprain, pain, swelling, and other inflammatory symptoms within 2 years before the test; (3) unilateral ankle joint experienced uncontrollable and/or sprained and/or unstable sensation twice or more in the last 1 year; and (4) Cumberland Ankle Instability Tool (CAIT)32 score ≤ 27. Exclusion criteria were as follows: (1) athletes in the stage of acute injury and rehabilitation; (2) athletes unable to participate in normal classes, training, competition, and other activities for other reasons; and (3) athletes unwilling to participate in this experiment. Non-CAI inclusion criteria were as follows: normal basketball players without a history of ankle sprains, no head injury, acute lower limb injury, balance dysfunction, or chronic lower limb dysfunction within the past 3 months, and CAIT score > 27 points. The experimental procedure of this work was approved by the Ethics Committee of the Sports Science Experiment of Beijing Sport University (No. 2022154H), and all subjects signed informed consent forms. During the work process, all methods were performed in accordance with the relevant guidelines and regulations.Male second-level basketball players were selected and divided into a CAI group and a non-CAI group according to whether they were accompanied by CAI, with 15 participants in each group. Baseline data of athletes in the CAI and non-CAI groups are shown in Table 33. Hence, to comprehensively and objectively analyze varying conditions and actions, the effect size was set at 0.5. This adjustment reduces the overlap among the population distributions, enhancing the clarity of differences. A statistical significance level (α) of 0.02 and a statistical power (1-β) of 0.8 were established. The calculated total sample size was determined to be 12 individuals. Ultimately, this study included a total of 30 participants.The sample size was calculated using GPower 3.0.18, with the three-step layup ankle biomechanics as the main result. This study was anticipated to encompass four measurement variables in both the CAI group and the non-CAI group. The effect size is employed as an estimation of the standard mean difference—a metric that is independent of the current sample and quantifies the magnitude of differences between distinct sampled populations. Effect size provides a more accurate description of differences. It signifies the degree of overlap between two population distributions; larger effect sizes indicate lesser overlap and more pronounced differences, while smaller effect sizes indicate the opposite. Variance analysis effect sizes are categorized as 0.1 , 0.3 (medium effect), and 0.5 (large effect)In this study, four Kistler 9281CA (Switzerland) 3D force measuring tables (specification: 40 cm × 60 cm × 10 cm) were used to collect and process the subjects’ movements. The Motion Analysis Raptor-4 high-speed infrared motion capture system, equipped with 8 cameras, along with a force plate from Motion Analysis company, was employed to collect kinematic parameters of reflective markers on the subjects. The camera system features a resolution of 2352 × 1728 pixels and operates at a sampling frequency of 200 Hz. Data collection was conducted over a period of 10 s. The collection of kinematic and dynamic data was triggered synchronously. To ensure the validity of the experimental data, each subject collected valid data 3 times.Prior to testing, spatial calibration was conducted to ensure that subjects were entirely captured after completing their actions and to prevent interference from other reflective objects that might affect data collection. The general area of subject movement was defined within the testing environment, and calibration was carried out using a Direct Linear Transformation (DLT) technique. Personnel sequentially calibrated the determined area using calibration poles, guaranteeing comprehensive spatial coverage. The calibration space encompassed the range above the testing area, measuring 3.0 m × 2.5 m × 2.5 m, corresponding to the region where subjects performed the test actions.34. In data processing, the link coordinate system was established through infrared reflective marks on the body surface of the subject, and the moment and angle of the ankle joint were calculated according to the trajectory change of the movement and the coordinate system. The index definition of the left ankle was as follows: in ankle angle and moment, the ankle joint performs dorsiflexion and plantarflexion movements in the sagittal plane, where positive values represent plantarflexion and negative values represent dorsiflexion. It also executes inversion and eversion movements in the frontal plane, with positive values denoting inversion and negative values denoting eversion. Additionally, internal and external rotation movements occur in the transverse plane, where positive values signify internal rotation and negative values signify external rotation. Utilizing the Helen Hayes human body model parameters, 3D moments of force at the ankle joint were computed using inverse dynamics method35. Kinematic and kinetic data were concurrently collected using the infrared motion capture system, Seeker.The variable selected in this study were ankle angle, moment, and ground reaction force36.Cortex (version 2.6.2.1169) was used to process the kinematics data, and Kistler Bio Ware (version 3.2.6.104) was used to extract the dynamics data. The Butterworth low-pass filtering method was used to smooth the 3d coordinates of all identification points, and the truncation frequency was 10 HzThe center of the knee joint is located at the midpoint between the medial and lateral knee points, while the center of the ankle joint is situated at the midpoint between the medial and lateral ankle points. Once the ankle joint center position was determined, a ground coordinate system (GCS) was established using corresponding marker points. Additionally, a local coordinate system (LCS) for the ankle joint was established. For the knee joint, the origin of the coordinate system was set at the knee joint center, the line connecting the right and left points defined the positive X-axis direction, and the line from the distal end to the proximal end established the Z-axis. The Y-axis was then derived by computing the cross product of the normal vectors of the X-axis and Z-axis. For the ankle joint coordinate system, the X-axis aligned with the lower leg, the Z-axis pointed from the ankle joint center to the tip of the foot, and similarly, the Y-axis of the foot coordinate system was obtained through a cross product.In accordance with the original force plate setup and the configuration of the testing environment, the Z-axis of the force plate was oriented vertically upwards, the X-axis corresponded to the direction of a sudden stop jump shot’s jumping motion, and the Y-axis extended from the athlete’s right to left side. In the Cortex software, the pressure threshold of the force plate was adjusted to 10 N, enabling the automatic exclusion of force values below 10 N. Force plate data was exported from the Cortex, and using the Helen Hayes human body model parameters, inverse dynamics were applied to compute the magnitude of the 3D ankle joint moments of force. The ankle joint’s 3D moments of force were calculated based on the Winter formula.t test, and the statistical significance level was set to P < 0.05. T tests and SPM were performed using SPSS 22.0  and MATLAB R2016a , respectively.In this research, the calculation of force and moment variables was normalized by weight. Additionally, relative value comparison was employed to assess differences among the various data sets. First, the normality of the data was examined using the Shapiro–Wilk test, while the homogeneity of the data was analyzed using the Bartlett test. The significance criterion was set at a type I error probability not exceeding 0.05. The analysis results indicated that all data in this study adhered to a normal distribution and met the assumption of homogeneity of variance. Statistical parametric mapping (SPM) was adopted for the test. The peak values of the maximum foot flexion angle, the maximum foot inversion angle, the maximum dorsiflexion angle, and the maximum ankle dorsiflexion moment in the two groups of subjects were analyzed by using the paired sample P > 0.05). The maximum ankle joint inversion angles in the CAI and non-CAI groups were 11.82 ± 5.05° and 16.52 ± 3.32°, respectively. The maximum ankle joint inversion angle in the CAI group was significantly smaller than that in the non-CAI group, and the difference between the two groups was extremely significant . Therefore, there was no significant difference in the peak time of the maximum plantar flexion angle and maximum inversion angle of the ankle between the CAI group and the non-CAI group (P > 0.05). Figure In Table P > 0.05), and there was no significant difference in the occurrence time of peak moment between the two groups .The peak moment in this part refers to the maximum ankle moment in the whole stage of the one-foot push-off. When taking off, the lower limbs exert force, and the ankle joints move in the direction of plantar flexion. The following results can be observed from Table P > 0.05).In Table P > 0.05).The concept of 3D moment encompasses the magnitude of the ankle joint moment across three distinct orientations: the sagittal plane, oriented vertically; the frontal plane, spanning the lateral axis; and the horizontal plane, encompassing the anteroposterior axis. During the phases of takeoff and landing, the lateral force magnitude denotes the ankle joint’s lateral stability, while the anterior–posterior force magnitude signifies forward acceleration or deceleration. As delineated in Table P < 0.001). The maximum dorsiflexion angle of the ankle joint in the CAI group was 11.32 ± 5.73°, and that in the non-CAI group was 7.28 ± 3.83°. The maximum dorsiflexion angle of the ankle joint in the CAI group was significantly larger than that in the non-CAI group . However, there was no significant difference in the peak time of the maximum inversion angle and maximum dorsiflexion angle of the ankle between the CAI and non-CAI groups (P > 0.05).In Table In the whole landing stage, the change in ankle inversion angle in the CAI group was significantly greater than that in the non-CAI group Fig. , indicatP > 0.05). The peak ankle dorsiflexion moment was 0.15 ± 0.05 s in the CAI group and 0.08 ± 0.06 s in the non-CAI group. Therefore, the peak time of ankle dorsiflexion moment in the CAI group was longer than that in the non-CAI group .In Table 37, positing that the “jump-land” sequence constitutes an integrated sequence of actions. This perspective underscores the interdependence between the takeoff and landing components, particularly the strategic considerations governing the jumping phase, in the context of movements like the three-step layup’s RSLJ pattern. This pattern culminates in landing on either a single foot or both feet, serving as a foundational scoring technique and a fundamental basketball maneuver. The stability achieved during the post-push-off landing phase assumes a pivotal role in safeguarding athletes against sports-related injuries. Notably, ground landing diverges from takeoff and entails varied foot positioning contingent on individual differences. Therefore, this study embraces the holistic concept of “jump-land” as an integrated entity and scrutinizes the kinematic attributes of ankle instability during basketball players’ layup sequences at distinct time intervals. By conducting a comprehensive analysis of ankle angle, torque, and related variables across various directions between the experimental and control groups, this study examined the foot kinematic attributes of basketball players afflicted by CAI. Additionally, the impact of ankle stability on fundamental basketball techniques and overall sports performance was investigated. The outcomes of this investigation revealed a noteworthy decrease in the maximum ankle joint inversion angle during the one-foot push-off phase among individuals with CAI. Conversely, the one-foot landing phase showcased an elevation in both the maximum inversion angle and maximum dorsiflexion angle of the ankle joint. Furthermore, the peak time of ankle dorsiflexion moment exhibited an extended duration in individuals with CAI.While previous investigations have typically segregated takeoff and landing as distinct entities, a contrasting perspective has been proposed by Akbari et al.38. However, there remains a dearth of inquiries into the impact of CAI on the ankle joint biomechanics during basketball players’ execution of the three-step layup. Notably, a subset of researchers has ascertained that the muscles governing ankle joint dorsiflexion and plantar flexion predominantly assume the role of prime motor units during the pedal extension phase of the push-off leg. In this context, the muscles controlling plantar flexion movements manifest the highest activation levels. Consequently, the primary motive force in the ankle joint during this juncture emanates from plantar flexion39. Ankle joint injuries among basketball players frequently result in an inversion disposition. Consequently, the lateral malleolus ligaments experience a gradual reduction in both elasticity and tautness due to injury. Within the ankle joint, the talofibular and calcaneal fibular ligaments operate synergistically to counteract ankle inversion. Particularly, the anterior talofibular ligament displays heightened tension during plantar flexion, serving the purpose of curbing excessive inversion during this phase. Conversely, the calcaneal fibular ligament attains its maximal tension during dorsiflexion, functioning to deter ankle pronation in the dorsiflexion plane. The results of this study showed that the maximum ankle inversion angle in the CAI group was significantly smaller than that in the non-CAI group. This phenomenon contrasts with the maximal angle shift of the ankle joint in cases of CAI incidence. A heightened ankle joint angle during takeoff signifies an advantageous augmentation of initial velocity. Conversely, an excessively diminished angle may accentuate resistance from the knee flexor musculature. Moreover, the ankle muscle robustness and suppleness in CAI-afflicted individuals exert an influence on ankle joint extension angles. Conversely, CAI participants demonstrated a greater range of ankle joint motion during abrupt halts40. However, in the CAI group, the maximal peak value and range of inversion angle were comparatively smaller than those observed in the non-CAI group, a divergence potentially linked to dissimilar modes of movement. In alignment with Cho et al.41, our study resonates with the notion that the atrophy of ankle joint-supporting musculature significantly contributes to the waning physical performance in CAI patients. Moreover, compromised postural control may be intertwined with limitations in ankle joint mobility. Consequently, the outcomes of this research possibly stem from biomechanical shifts within ankle joints among CAI patients, curbing both lower limb ankle strength and the range of joint motion during takeoff42.Angular characteristics of the ankle joint across distinct phases of the three-step layup hold significant scholarly interest. Prior research, both domestic and international, has predominantly concentrated on dissecting and explicating the kinematic and mechanical attributes of the lower extremities, encompassing the hip, knee, and ankle joints. Such studies have formulated optimized movement patterns for diverse actions through a thorough examination of pertinent indicators43. Allet et al.44 conducted an assessment of the ankle angle among CAI patients pre- and post-landing, concluding that patients with subacute ankle sprains displayed larger dorsiflexion angles both before and after ground contact compared to non-CAI individuals. Similarly, Kim et al.45 observed that, during initial ankle joint-ground contact, individuals with ankle instability exhibited a reduced rearfoot plantar flexion angle in contrast to both the Coper group  and the control group. Furthermore, a noticeable trend of increasing dorsiflexion angle was noted. This phenomenon is attributed to the proclivity of CAI patients to experience episodes of “giving away” (ankle instability) during daily activities and sports. This instability, stemming from damage to the talofibular ligament, engenders ligamentous relaxation relative to non-CAI counterparts. Consequently, the dorsiflexed position of the ankle joint during descent affords heightened stability. Dorsiflexion also effectively mitigates undue stress on the lateral ligaments of the ankle. The reflexive self-protective mechanism exhibited by patients prompts an innate adjustment to augment dorsiflexion angle, thereby mitigating the risk of injury.Landing constitutes a ubiquitous motion in both daily life and sports, characterized by an initial touchdown on the forefoot, followed by swift transition to the sole. This action is accompanied by concurrent hip flexion, knee bending, and ankle extension. Scholars have emphasized that augmenting the range of motion in ankle joint plantar flexion and dorsiflexion during the landing phase can enhance the ankle joint’s shock-absorbing capacityP > 0.05). The findings of this study elucidate a correlation between alterations in ankle inversion angle and changes in joint muscle strength. Dynamic stability of the ankle joint hinges on the coordinated contraction of the surrounding muscle groups. In various lower limb activities like walking, running, and jumping, athletes rely on concerted muscle contractions, particularly centrifugal contractions, to regulate the interplay of forces between the foot and the ground. Joint injury triggers peripheral neuromuscular perturbations, precipitating a continuous reflexive response in the muscles. For the preservation of bodily posture stability, individuals with CAI must curtail the range of motion in hip and knee joints. This action serves to mitigate the lateral swaying of the torso upon unilateral landing of the ankle joint. Nonetheless, due to the substantial ground reaction force encountered during early ground contact, the ankle joint necessitates a notable range of motion to ensure landing stability.From the analysis of the whole landing movement process, the push-off height of athletes when they perform the three-step layup usually exceeds 50% of their height. The higher the height is, the greater the impact of the ground on the feet. In this study, the ankle inversion angle of subjects in the CAI group was higher than that in the non-CAI group when landing, but there was no significant difference in the ankle inversion angle and ankle dorsi flexion angle between the CAI group and non-CAI group when landing (46. Further investigations reveal that the peak plantar-flexion moment in CAI patients, across various angular velocities, remains consistently lower than in their healthy counterparts. These insights underscore functional impairments in plantar-flexion capabilities among CAI patients, particularly evident during routine and sport-specific activities, rendering them susceptible to recurrent ankle sprains. Comparative analyses of peak plantar-flexion moment values at different temporal intervals between the two cohorts unveil a salient finding. Specifically, this study discerns that during single-leg takeoff, the experimental group of CAI subjects exhibits diminished peak plantar-flexion moment values in contrast to their normally functioning counterparts in the control group. In the context of the three-step layup technique, athletes engage in a running approach, followed by a forceful leap that propels them both forward and upward. As they ascend, they aim to attain the highest point in their trajectory precisely as the ball enters the basket. This strategy maximizes the effectiveness of the jump shot, with proximity to the basket correlating to an elevated leap. Consequently, athletes must not only possess robust lower limb explosive strength but also exhibit proficient control over anterior–posterior directionality in the ankle. Given that the ankle joint’s movement involves the interplay of plantar and dorsiflexion during takeoff, and joint torque is intricately influenced by muscle strength and stability, empirical investigations have confirmed that individuals with CAI exhibit inadequate ankle joint muscle strength and diminished postural control capacity. Thus, the ankle joint serves as the pivotal point for initiating lower limb joint forces during the takeoff phase of the three-step layup. In CAI patients, deficient muscle strength within the ankle joint’s plantar and dorsiflexor muscles contributes to a weakened ability to generate upward propulsive forces against the ground and to propel the lower limbs forward. This dynamic ultimately exerts a detrimental impact on sports performance.Torque profiles of the ankle across distinct stages of the three-step layup exhibit the subsequent characteristics. Notably, it has been observed that the peak plantar flexor moment of the ankle joint in CAI patients registers a significant reduction compared to that in individuals without ankle instability. This phenomenon signifies inadequate function within the plantar flexor muscle group during natural ambulation47 and Thompson48 found through the isokinetic muscle force test that the peak values of eversion and plantar-flexion moment of patients with CAI at different angular speeds were smaller than those of healthy people. The results were consistent with this study, but the difference was that the isokinetic muscle force test obtained the peak values of ankle moment by setting a fixed angular velocity and movement direction. In this study, the peak value of ankle moment was collected when subjects fell naturally, without setting a uniform speed and direction. In this case, it is more consistent with the actual situation of athletes in the process of sports, which has practical significance for later training practice and injury prevention.The moment of the ankle joint in the frontal plane of the CAI group was smaller than that in the control group. When the ankle joint touched the ground for the first time, the ankle joint of the CAI group showed a decrease in the function of inversion and inversion muscle compared with the normal person, while the moment of the sagittal plane and horizontal plane showed no significant difference. This may be related to the fact that the toe just touched the ground at the moment of touching the ground and had not yet been subjected to a large ground reaction force, so there was no difference between the two groups in the sagittal plane and horizontal plane. On the other hand, it may also be related to the large pronation angle of CAI at the moment of touching the ground. Due to insufficient muscle strength, it is difficult for the ankle joint to control and land safely within a stable range when falling to the ground, which increases the risk of ankle injury or CAI when landing. As the plantar flexors all touch the ground in the landing process, the comparison of the peak torque in the plantar flexor direction shows that the CAI result is smaller than that of the non-CAI group. Although the difference is not obvious, the arrival time of the peak torque in the CAI group is delayed. Both WangHowever, there were still some shortcomings in this work. It was pointed out that the test subjects in this work all run at the same starting way and speed, which was difficult to do in the training field. Therefore, in future work, the influence of CAI on the dynamics of basketball players’ ankle joints under different takeoff modes and running speeds will be further analyzed.This work discussed the changes in ankle biomechanical indexes of CAI and non-CAI basketball players in typical three-step layup movement from the perspectives of dynamics and kinematics. The results showed that the maximum ankle joint inversion angle decreased during the one-foot push-off period of CAI. The maximum inversion angle and maximum dorsiflexion angle of the ankle joint increased during the one-foot landing period, and the peak time of ankle dorsiflexion moment was prolonged. In conclusion, this work provided a reference for the choice of training methods for basketball players with CAI.Supplementary Information 1.Supplementary Information 2.Supplementary Information 3.Supplementary Information 4.


Introduction: Usnic acid (UA) and barbatic acid (BA), two typical dibenzofurans and depsides in lichen, have a wide range of pharmacological activities and hepatotoxicity concerns. This study aimed to clarify the metabolic pathway of UA and BA and illuminate the relationship between metabolism and toxicity.Methods: An UPLC-Q-TOF-MS method was developed for metabolite identification of UA and BA in human liver microsomes (HLMs), rat liver microsomes (RLMs), and S9 fraction (RS9). The key metabolic enzymes responsible for UA and BA were identified by enzyme inhibitors combined with recombinant human cytochrome P450 (CYP450) enzymes. The cytotoxicity and metabolic toxicity mechanism of UA and BA were determined by the combination model of human primary hepatocytes and mouse 3T3 fibroblasts.Results: The hydroxylation, methylation, and glucuronidation reactions were involved in the metabolic profiles of UA and BA in RLMs, HLMs, and RS9. CYP2C9, CYP3A4, CYP2C8, and UGT1A1 are key metabolic enzymes responsible for metabolites of UA and CYP2C8, CYP2C9, CYP2C19, CYP1A1, UGT1A1, UGT1A3, UGT1A7, UGT1A8, UGT1A9, and UGT1A10 for metabolites of BA. UA and BA did not display evident cytotoxicity in human primary hepatocytes at concentrations of 0.01–25 and 0.01–100 µM, respectively, but showed potential cytotoxicity to mouse 3T3 fibroblasts with 50% inhibitory concentration values of 7.40 and 60.2 µM.Discussion: In conclusion, the attenuated cytotoxicity of BA is associated with metabolism, and UGTs may be the key metabolic detoxification enzymes. The cytotoxicity of UA may be associated with chronic toxicity. The present results provide important insights into the understanding of the biotransformation behavior and metabolic detoxification of UA and BA.  Usnea have been widely used in fodder, dyes, food, perfumery, cosmetics, pharmaceuticals, preservatives, deodorants, ecological applications, and miscellaneous purposes throughout the world, particularly in Europe and East Asian countries, such as China, Japan, and India  , longiusnine (−)-placodiolic acid, depsides barbatic acid (BA), evernic acid, diffractaic acid, and ramalic acid  , antipyracteria) , anti-inacteria) , antitumacteria)  and antiacteria) , for theacteria) , photopracteria) , antioxiacteria) . All thelic acid . Figure However, recent reports associated with liver-related adverse events of UA-containing products aroused widespread concern , and theHepatic enzymes, especially cytochrome P450 (CYP450), commonly have an important role in the metabolism of drugs or chemicals. UA can significantly induce P450 activity in HepG2 cells at concentrations of 10 µM or higher, and slight UA metabolism by CYP1A1 may be present . One stuin vivo and in vitro. However, no liver drug enzymes responsible for UA metabolism have been identified and confirmed, which resulted in an incomplete understanding of UA metabolites and metabolic pathways. In addition, there is an absence of direct evidence of the relationship between metabolism and attenuated toxicity of UA. For BA, another important depside component in Usnea, our previous pharmacokinetic results showed that the exposure of BA in rats was comparable to that of UA after oral administration of Usnea extract , rat liver microsomes (RLMs), and S9 fraction (RS9) combined with UPLC with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) technology to analyze and identify the metabolites and metabolic pathways of UA and BA. The method of enzyme inhibitor combined with recombinant human CYP450 enzymes was used to identify and confirm the metabolic enzymes responsible for UA and BA. Finally, the co-incubation model of HLMs and mouse 3T3 fibroblasts was used to evaluate the correlation between UA and BA metabolism and hepatocyte toxicity by the Cell Counting Kit-8 test and clarify the mechanism of toxicity induced or attenuated by metabolism. The results of this study will provide a basis for the systematic understanding of metabolic profiles and potential toxic mechanisms of UA and BA.This study aimed to use UA  with a purity of >98% was obtained from Chengdu Desite Biotechnology Co., Ltd.  and BA  with a purity of >98% was obtained from Wuxi Apptec Co., Ltd. . D-Glucose 6-phosphate (G-6-P) disodium salt hydrate, glucose-6-phosphate dehydrogenase (G-6-P-DH) from leuconostoc mesenteroides, β-nicotinamide adenine dinucleotide phosphate disodium salt (NADP+), uridine 5′-diphospho-glucuronidation trisodium salt (UDPGA), 3′-phosphoadenosine-5′-phosphosulfate (PAPS), α-naphthoflavone, 8-methoxypsoralen, orphenadrine, sulfaphenazole, quinidine, 4-methylpyridine, neutral red, tamoxifen, and LC-MS-grade formic acid were purchased from Sigma-Aldrich . Furafylline, nootkatone, and ketoconazole were obtained from Shanghai Yuanye Bio-Technology Co., Ltd. . Quercetin and alamethicin were provided by J&K Scientific . Montelukast was obtained from TCI Development Co., Ltd. . Tris-base was obtained from Shanghai Majorbio Bio-pharm Technology Co., Ltd. . Bradford reagent was purchased from Sangon Biotech Co., Ltd. . cDNA-expressed recombinant CYP1A1, CYP1A2, CYP2A6, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP2E1, and CYP3A4 Bactosomes were acquired from Cypex Limited . Dimethyl sulfoxide, MgCl2, and HCl were purchased from Sinopharm Chemical Reagent Co., Ltd. . Mouse 3T3 fibroblasts were provided by CobioerBiosciences Co., Ltd. . RLMs and their liver S9 fractions (RLS9) were prepared from pooled liver tissues by standard differential ultracentrifugation . HLMs, pThe metabolic profiling study was carried out using a Shimadzu 30A UPLC system  coupled with AB SCIEX Triple TOF™ 5600+ system  equipped with an electrospray ionization (ESI) source. Mass spectrometric detection was performed in negative mode. Nitrogen was used as the nebulizer and auxiliary gas. The flow rates of nebulizer gas (GS 1), heater gas (gas 2), and curtain gas were 55, 55, and 35 psi, respectively. The turbo spray temperature was 550°C. The ion spray voltage floating was −4500 V, and the declustering potential was −100 V. The collision energy (CE) was −35 eV, and the CE spread was set to 15 eV. The TOF scan range was set from m/z 100 to m/z 1200.Chromatographic separations were conducted on an ACQUITY UPLC HSS T3 column . The mobile phase was a gradient system consisting of 0.1% formic acid in water (A) and acetonitrile (B) with a gradient elution system: 10% B (0–1.5 min), 10%–40% B (1.5–3 min), 40%–95% B (3–10 min), 95% B (10–11.5 min), 95%–5% B (11–11.6 min), and 5% B (11.6–12 min). The column temperature was set to 40°C, the flow rate to 0.3 mL/min, and the injection volume to 5 µL.For the phase I metabolism study, the incubation mixture, with a total volume of 200 μL, included liver microsomes (rat: 10.0 mg protein/mL or human: 21.9 mg protein/mL), 50 mM Buffer , NADPH-generating system , and substrate (1 µM). For the phase II metabolism study, the liver microsomes were first mixed with alamethicin (25 μg/mL), which was used as a perforating agent for 5 min preincubation at 37°C in a shaking water bath. The incubation system contained an additional 5 mM UDPGA, and the other reagents were the same as those in phase I. For the RLS9 metabolism study, as for the phase II metabolism study, the RLS9 was first mixed with alamethicin (25 μg/mL) for 5 min preincubation at 37°C in a shaking water bath. The incubation system contained additional 100 µM PAPS, and the other reagents were the same as those in phase I. The substrates were previously dissolved in methanol, and the final methanol concentration was below 1% (v/v) in the system. The reaction was initiated by the addition of a NADPH-generating system. After 60 min incubation at 37°C in a shaking water bath, the reaction was terminated by the addition of 1.0 mL ice-cold acetonitrile. The mixture was kept on ice until it was centrifuged at 12,000 × g for 10 min at 4°C. The supernatants were transferred and dried under a gentle stream of nitrogen at 37°C and then dissolved with 100 µL methanol for analysis. Blank control samples without substrates and negative control samples without NADP+ (for phase I metabolism study) or NADP+ and UDPGA (for phase II metabolism study) or NADP+ and PAPS (for RLS9 metabolism study) were included. Each group was prepared in triplicates.Chemical inhibitor methods together with recombinant CYP and UGT enzymes were used to identify the CYP and UGT isozymes involved in the metabolic pathways of UA and BA.Chemical inhibition studies were performed by the addition of different human CYP inhibitors to the incubation mixture before the addition of the NADPH-generating system. The liver microsomes were first mixed with different concentrations of inhibitors and preincubated at 37°C for 5 min. The incubation system was similar to the phase I liver microsomal reaction system. The selective inhibitors of 10 major CYPs were as follows: α-naphthoflavone for CYP1A1, furafylline for CYP1A2, 8-methoxypsoralen for CYP2A6, orphenadrine for CYP2B6, quercetin for CYP2C8, sulfaphenazole for CYP2C9, quinidine for CYP2D6, nootkatone for CYP2C19, 4-methylpyridine for CYP2E1, and ketoconazole for CYP3A4. The concentrations of the 10 selective inhibitors were 5, 10, 20, 50, and 100 µM.For the recombinant CYP and UGT enzyme method, the incubation system was similar to the phase I and II liver microsomal reaction systems. The liver microsomes or RLS9 were substituted with recombinant enzymes. The 10 recombinant CYP enzymes were as follows: CYP1A1, CYP1A2, CYP2A6, CYP2B6, CYP2C8, CYP2C9, CYP2D6, CYP2C19, CYP2E1, and CYP3A4. The 12 recombinant UGT enzymes were as follows: UGT1A1, UGT1A3, UGT1A4, UGT1A6, UGT1A7, UGT1A8, UGT1A9, UGT1A10, UGT2B4, UGT2B7, UGT2B15, and UGT2B17.The subsequent steps were performed as described in 2 at an initial density of 7 × 105 cells/mL per well at 37°C until the formation of a single-cell layer. The plating medium was changed to an incubation medium, and incubation was continued overnight. Mouse 3T3 fibroblasts were incubated under 5% CO2 at 37°C for 24 h. Different concentrations of UA or BA (100 µL) were incubated with human primary hepatocytes or mouse 3T3 fibroblasts for 48 h, respectively. At the end of incubation, the medium was removed quickly, and cells were washed once with 250 µL Hank’s balanced salt solution (HBSS). A total of 250 µL neutral red (250 μg/mL) was added for staining for 3 h. After neutral red was removed, 100 µL chromogenic solution was added, and shaking was carried out for 30 min at room temperature. The optical density (OD) of each well was read at 570 and 690 nm using a microplate reader, and the relative cell viability  was calculated. Control samples without UA or BA and the positive control group were included. The amount of organic solvent was below 1% (v/v) in the system, and each group was prepared in triplicates.The cytotoxicity of UA and BA was assessed in primary human hepatocytes and mouse 3T3 fibroblasts seeded in 96-well plates, respectively. The concentrations of UA were 0.01, 0.1, 1, 10.0, and 25 μM, those of BA were 0.01, 0.1, 1, 10, and 100 μM, and tamoxifen (50 µM) was set as a positive control. The primary hepatocytes were incubated under 5% CO2 at 37°C overnight. At different concentrations of UA or BA, blank incubation medium (90 µL) as the control group and tamoxifen as the positive control group 1 were incubated with mouse 3T3 fibroblasts for 4 h. The HLMs were preincubated with different concentrations of UA or BA, NADPH, NADPH and UDPGA, or NADPH and UDPGA and inhibitors of CYP2C8, CYP2C9, and CYP3A4 at 37°C for 1 h. Positive control group 2 was also preincubated with HLMs together with NADPH and UDPGA. After preincubation, 90 µL supernatant was incubated with mouse 3T3 fibroblasts under 5% CO2 at 37°C for 4 h. The amount of organic solvent was below 1% (v/v) in the system, and each group was prepared in triplicates.To determine the effect of metabolism on the cytotoxicity of UA and BA, fibroblast NIH mouse 3T3 fibroblasts were assessed and seeded in 96-well plates. The concentrations of UA were 1, 2, 5, 10, 25, and 50 μM, those of BA were 1, 10, 20, 50, 100, and 200 μM, and that of tamoxifen as positive control was 50 µM. Montelukast, sulfaphenazole, and ketoconazole were selected as exclusive inhibitors of CYP2C8, CYP2C9, and CYP3A4, respectively, and the concentrations were 100, 10, and 5 μM, respectively. Mouse 3T3 fibroblasts were incubated under 5% COThe subsequent steps were performed as described in All values were expressed as mean ± standard deviation (SD). The correlated fitting analyses were performed with Analyst TF 1.7.1, PeakView 2.2 , and Graph pad Prism 6.0 .The cell viability was calculated as follows:50) was calculated by Graph pad Prism as follows:The 50% inhibitory concentration . UA provided abundant fragment ions at [M-H-CH3]- m/z 328.0610  [M-H-2CH3]- m/z 313.0366  [M-H-2CH3-CH2]- m/z 299.0944  [M-H-CH3-C3HO2]- m/z 259.0635 , and [M-H-CH3-C3HO2-CO]- m/z 231.0678 . To identify its metabolites, we first investigated the MS/MS fragmentation behaviors of UA by UPLC/ESI-QTOF-MS. UA was eluted at 10.141 min and showed [M-H]in vitro. Metabolites M1-1 (tR = 5.181 min), M1-2 (tR = 5.789 min), M1-3 (tR = 7.276 min), M1-4 (tR = 8.262 min), and M1-5 (tR = 10.127 min) showed similar quasi-molecular of C18H15O8− (m/z 359.0772 [M-H]-), which was 15.9949 Da higher than that of UA. In the MS/MS spectra, the [M-H]- of M1-1 showed fragment ions at [M-H-C4H4O3-CO]- m/z 231.0711 (C13H11O4−) and [M-H-C11H8O4]- m/z 155.0363 (C7H7O4−). The [M-H]- of M1-2 exhibited fragment ions at [M-H-CH3]- m/z 344.0534 (C17H12O8−) [M-H-CH3-C2H2O]- m/z 302.0453 (C15H10O7−), and [M-H-CH3-C4H6O2]- m/z 258.0190 (C13H6O6−). The [M-H]- of M1-3 revealed fragment ions at [M-H-CH3]- m/z 344.0562 (C17H12O8−) [M-H-OH-H]- m/z 341.0686 (C18H13O7−) [M-H-CH3-OH-H]- m/z 326.0448 (C17H10O7−) [M-H-CH3-OH-H-CO]- m/z 298.0495 (C16H10O6−) [M-H-C4H6O3]- m/z 257.0481 (C14H9O5−), and [M-H-C4H6O3-CO]- 229.0490 (C13H9O4−). The [M-H]- of M1-4 presented fragment ions at [M-H-CH3]- m/z 344.0568 (C17H12O8−) [M-H-2CH3]- m/z 329.0334 (C16H9O8−) [M-H-CH3-OH-H-CO]- m/z 298.0522 (C16H10O6−) [M-H-C2H5O2]- m/z 285.0437 (C16H10O6−) [M-H-C4H4O2]- m/z 275.0589 (C14H11O6−) [M-H-C4H6O3]- m/z 257.0476 (C14H9O5−), and [M-H-C4H6O3-CO]- m/z 229.0542 (C13H9O4−). The [M-H]- of M1-5 showed fragment ions at [M-H-CH3]- m/z 344.0504 (C17H12O8−) [M-H-2CH3-CO]- m/z 301.0324 (C15H9O7−) [M-H-CH2OH-CH3-2CO]- m/z 257.0518 (C14H9O5−), and [M-H-C4H6O3-CO]- m/z 229.0509 (C13H9O4−). The proposed fragmentation pathway of these metabolites, including the loss of methyl radical and retro Diels–Alder (RDA) transform, is similar to that of UA. In addition, the fragmentation behaviors between these metabolites were very similar. As no more information was observed, the specific structure of each compound could not be established from the mass spectrum data alone. Five hydroxylation metabolites of UA were identified in the microsomal incubation system M1-6 (tR = 4.483 min), M1-7 (tR = 4.791 min), M1-8 (tR = 5.561 min), M1-9 (tR = 5.841 min), M1-10 (tR = 7.170 min), M1-11 (tR = 8.159 min), and M1-12 (tR = 10.050 min) showed similar quasi-molecular ion of C18H15O9− (m/z 375.0721 [M-H]-), which was 31.9898 Da higher than that of UA. In the MS/MS spectra, the [M-H]- of M1-6 showed fragment ions at [M-H-CH3]- m/z 360.0503 (C17H12O9−) and [M-H-CH3-C2H4O2]- m/z 300.0265 (C15H8O7−). The [M-H]- of M1-7 exhibited fragment ions at [M-H-CH3]- m/z 360.0493 (C17H12O9−) [M-H-CH3-CH2-CO]- m/z 318.0382 (C15H10O8−), and [M-H-CH3-CH2-CO-C2H2O]- m/z 259.0258 (C13H7O6−). The [M-H]- of M1-8 presented fragment ions at [M-H-OH-H]- m/z 357.0603 (C18H13O8−) [M-H-OH-H-CH3]- m/z 342.0385 (C17H10O8−), and [M-H-2CH2-2OH]- m/z 313.0380 (C16H9O7−). The [M-H]- of M1-9 displayed fragment ions at [M-H-CH3]- m/z 360.0564 (C17H12O9−) [M-H-CH2-CO]- m/z 333.0579 (C16H13O8−), and [M-H-CH3-CH2-CO]- m/z 302.0489 (C15H10O7−). The [M-H]- of M1-10 manifested fragment ions at [M-H-OH-H]- m/z 357.0656 (C18H13O8−) [M-H-CO-2OH]- m/z 313.0715 (C17H13O6−), and [M-H-2CH3-CO-OH-H]- m/z 299.0150 (C15H7O7−). The [M-H]- of M1-11 showed fragment ions at [M-H-O]- m/z 359.0776 (C18H15O8−) [M-H-CO-O]- m/z 331.0914 (C17H15O7−) [M-H-C2H6O-O]- m/z 313.0345 (C16H9O7−), and [M-H-CO-O-C4H4O2]- m/z 247.0649 (C13H11O5−). The [M-H]- of M1-12 indicated fragment ions at [M-H-C6H5O43-]- m/z 235.0623 (C12H11O5−) [M-H-C6H7O43-]- m/z 233.0468 (C12H9O5−) [M-H-C6H5O43--CO]- m/z 207.0597 (C11H11O4−), and [M-H-C12H11O53-]- m/z 141.0211 (C6H5O4−). M1-6 to M1-12 were tentatively identified as a metabolite of 2 × hydroxylation. Metabolites M1-13 was detected at 7.329 min and showed quasi-molecular at m/z 347.1150 . In the MS/MS spectra, the [M-H]- of M1-13 showed fragment ions at [M-H-C4H4O2-CH3-OH]- m/z 231.0616  and [M-H-C14H14O5]- m/z 85.0290 . The proposed fragmentation pathway of M1-13 revealed similar characteristics to that of UA, including the RDA transform. Metabolite M1-14 was detected at 5.409 min and showed quasi-molecular at m/z 373.0594 . In the MS/MS spectra, the [M-H]- of M1-14 exhibited fragment ions at [M-H-OH-H]- m/z 355.0445  [M-H-CH3-CO-H]- m/z 329.0334  [M-H-CO-OH-H]- m/z 327.0495  [M-H-C3H4O-CO-OH-H]- m/z 271.0197 , and [M-H-C3H4O-2CO-OH-H]- m/z 243.0248 . M1-14 was tentatively identified as a metabolite of hydroxylation and oxidation. M1-14.Metabolite M1-15 presented a quasi-molecular ion at m/z 519.1149  and could be detected at 5.357 min, which was 176.0321 Da higher than that of UA m/z 343.0851  and indicates the characteristic loss of glucuronic acid group (C6H10O7-H2O). The MS/MS spectra exhibited fragment ions at [M-H-C6H8O6]- m/z 343.0838  [M-H-C6H8O6-CH3]- m/z 328.0622 , and [M-H-C6H8O6-CH3-C3HO2]- m/z 259.0636 . The proposed fragmentation pathway of metabolites M1-15 was similar to that of UA, including the loss of methyl radical and RDA transform. As no more information was observed, the specific structure could not be established from the mass spectrum data alone. M1-15.Metabolite M1-16 showed a quasi-molecular ion at m/z 462.0858  and could be detected at 5.107 min. The MS/MS spectra displayed fragment ions at [M-H-CH3]- m/z 447.0627  [M-H-C3H5NO2S-2H]- m/z 341.0663  [M-H-CH3-C3H5NO2S-2H]- m/z 326.0430 , and [M-H-C3H5NO2S-2H-CH3-C3HO2]- m/z 257.0468 . The proposed fragmentation pathway of metabolites M1-16 was similar to that of UA, including the loss of methyl radical and RDA transform. As no more information was observed, the specific structure could not be established from the mass spectra data alone. M1-16.Metabolite M1-17 manifested the quasi-molecular ion at m/z 535.1092  and could be detected at 4.663 min.The MS/MS spectra revealed fragment ions at [M-H-OH-H]- m/z 517.1005  [M-H-OH-H-C6H8O6]- m/z 341.0666  [M-H-OH-H-C6H8O6-CH3]- m/z 326.0424  [M-H-2OH-C6H8O6-CO]- m/z 297.0799 , and [M-H-OH-H-C6H8O6-C3HO2-CH3]−m/z 257.0451 . The proposed fragmentation pathway of metabolite M1-17 was similar to that of UA, including the loss of methyl radical and RDA transform. As no more information was observed, the specific structure could not be established from the mass spectra data alone. M1-17.Metabolite M1-18 unveiled a quasi-molecular ion at m/z 478.0836  and could be detected at 4.726 min. The MS/MS spectra showed fragment ions at [M-H-C3H5NO2S-OH-H]– m/z 341.0665 , and [M-H-C8H8O3]- m/z 326.0339 . As no more information was observed, the specific structure could not be established from the mass spectra data alone. M1-18.Metabolite in vitro were speculated . BA provided abundant fragment ions at [M-H-C10H10O3]- m/z 181.0506  [M-H-C10H12O4]- m/z 163.0390  [M-H-C10H10O3-COO]- m/z 137.0601 , and [M-H-C10H12O4-COO]- m/z 119.0494 . To identify the metabolites of BA, the MS/MS fragmentation behaviors of BA were first investigated by UPLC/ESI-QTOF-MS. BA was eluted at 9.354 min and showed [M-H]M2-1 showed a quasi-molecular ion at m/z 375.1109 and could be detected at 6.832 min.The MS/MS spectra presented fragment ions at [M-H-C10H10O4]- m/z 181.0514  [M-H-C10H12O5]- m/z 163.0411  [M-H-C10H10O4-COO]- m/z 137.0614 , and [M-H-C10H12O5-COO]- m/z 119.0503 . The proposed fragmentation pathway of metabolites M2-1 was similar to that of BA. As no more information was observed, the specific structure could not be established from the mass spectrum data alone. M2-1.Metabolite M2-2 presented a quasi-molecular ion at m/z 389.1260  and could be detected at 6.436 min.The MS/MS spectra exhibited fragment ions at [M-H-C11H12O4]- m/z 181.0515  [M-H-C11H14O5]- m/z 163.0394  [M-H-C11H12O4-COO]- m/z 137.0602 , and [M-H-C11H14O5-COO]- m/z 119.0512 . The proposed fragmentation pathway of metabolite M2-2 was similar to that of BA. As no more information was observed, the specific structure could not be established from the mass spectrum data alone. M2-2.Metabolite M2-3 showed the quasi-molecular ion at m/z 389.1260  and could be detected at 6.436 min.The MS/MS spectra revealed fragment ions at [M-H-COO]- m/z 345.1334  [M-H-COOH-CH2-OH]- m/z 313.1101  [M-H-COOH-CH2-OH-CH3]- m/z 298.0836  [M-H-COO-CH3-CH2-2OH]- m/z 283.0972  [M-H-COO-2CH3-CH2-2OH]- m/z 268.0761  [M-H-C10H8O5]- m/z 181.0854  [M-H-C10H8O5-CH2O]- m/z 151.0773 , and [M-H-C10H8O5-2CH2O]- m/z 121.0658 . M2-3.Metabolite M2-4 presented a quasi-molecular ion at m/z 359.0786  and could be detected at 6.688 min.The MS/MS spectra displayed fragment ions at [M-H-OH-H]- m/z 341.0671  [M-H-CHO-OH]- m/z 313.0701  [M-H-COOH-OH]- m/z 297.0765 , and [M-H-COOH-CHO-CH3]- m/z 270.0519 . As no more information was observed, the specific structure could not be established from the mass spectrum data alone. M2-4.Metabolite M2-5 manifested the quasi-molecular ion at m/z 361.0904  and could be detected at 6.248 min.The MS/MS spectra presented fragment ions at [M-H-C9H8O3]- m/z 197.0484  [M-H-C9H8O4]- m/z 181.0495  [M-H-C9H10O5]- m/z 163.0411  [M-H-C9H8O4-COO]- m/z 137.0604 , and [M-H-C9H10O5-COO]- m/z 119.0492 . The proposed fragmentation pathway of metabolite M2-5 was similar to that of BA. As no more information was observed, the specific structure could not be established from the mass spectrum data alone. M2-5.Metabolite in vitro. Metabolites M2-6 (tR = 5.388 min), M2-7 (tR = 6.064 min), and M2-8 (tR = 7.173 min) showed the same quasi-molecular of C25H27O13− (m/z 535.1452 [M-H]-), which was 176.0321 Da higher than that of BA m/z 359.1147 . This finding indicated the characteristic loss of the glucuronic acid group (C6H10O7-H2O). In the MS/MS spectra, the [M-H]- of M2-6 showed fragment ions at [M-H-C6H8O6]- m/z 359.1139  [M-H-C6H8O6-COO]- m/z 315.1228  [M-H-C6H8O6-C10H10O3]- m/z 181.0511  [M-H-C6H8O6-C10H12O4]- m/z 163.0404  [M-H-C6H8O6-C10H10O3-COO]- m/z 137.0610 , and [M-H-C20H22O10]- m/z 113.0241 . The [M-H]- of M2-7 presented fragment ions at [M-H-C6H8O6]- m/z 359.1136  [M-H-C6H8O6-C10H10O3]- m/z 181.0512  [M-H-C6H8O6-C10H12O4]- m/z 163.0405  [M-H-C6H8O6-C10H10O3-COO]- m/z 137.0608 , and [M-H-C20H22O10]- m/z 113.0241 . The [M-H]- of M2-8 exhibited fragment ions at [M-H-C6H8O6]- m/z 359.1099  [M-H-C6H8O6-C10H10O3]- m/z 181.0495 , and [M-H-C6H8O6-C10H12O4]- m/z 163.0419 . The proposed fragmentation pathway of metabolites M2-6 to M2-8 was similar to that of BA. Moreover, the fragmentation behaviors between these metabolites were very similar. As no more information was observed, the specific structure could not be established from the mass spectrum data alone. Five glucuronidation metabolites of BA were identified in the microsomal incubation system M1-1, and CYP2A6 exhibited a weak inhibition effect only at 5 µM with RLMs. CYP2B6 presented a strong inhibitory effect on M1-3, followed by CYP1A1, 2A6, 2C9, 2C19, and 3A4 with RLMs. As for M1-4, CYP2B6, 2A6, 1A1, 3A4, 2C9, 2C19, 2D6, 2E1,1A2, and 2C8 showed high to low levels of inhibition effect with RLMs. CYP2B6 and 1A1 with RLMs showed a stronger inhibition effect on M1-6 than CYP3A4, 2D6, 2C9, 2C19, 2A6, 1A2, and 2C8. CYP2B6 and 1A1 with RLMs also displayed a stronger inhibition effect on M1-7. In addition, CYP3A4, 2A6, 2C9, 2D6, 2C19, 2C8, 1A2, and 2E1 exhibited high to low levels of inhibition effect with RLMs. As for M1-8, only CYP2C8, 2C19, and 1A1 with RLMs showed low inhibition effects. CYP2C19, 2C8, and 2B6 with RLMs revealed a weak inhibition effect on M1-9. For M1-10, CYP2B6, 1A1, 2A6, and 2C9 presented high to low levels of inhibition effect with RLMs, and CYP3A4 and 2C19 with RLMs showed weak inhibition effects only at 100 µM. For M1-11, CYP2B6, 2A6, 1A1, 2C9, 2C19, 3A4, 2D6, 2E1, and 1A2 with RLMs showed high to low levels of inhibition effects.Chemical inhibition studies reported the different effects of CYP inhibitors on the biotransformation of UA. CYP3A4, 1A1, and 2C9 showed low inhibition effects on M1-1. CYP1A1 and 2A6 showed weak inhibition effects only at 5 µM. For M1-3, CYP2C9, 2E1, 2D6, 2B6, 2C19, 2C8, 3A4, 1A2, 1A1, and 2A6 with HLMs displayed high to low levels of inhibition effects. For M1-6, CYP2C9, 2E1, 2D6, 2B6, 1A1, 2C19, 1A2, and 2A6 with HLMs exhibited high to low levels of inhibition effects, and CYP2C19 with HLMs showed weak inhibition effect only at 5 µM. For M1-8, CYP3A4, 2E1, 2C9, 2B6, 2C19, 1A2, 2C8, and 2D6 with HLMs manifested high to low levels of inhibition effects, and CYP2A6 and 1A1 with HLMs showed a mild inhibition effect only at 5 µM. For M1-10, CYP2C9 presented a strong inhibition effect at all concentrations with HLMs. In addition, CYP2E1, 2D6, 2B6, 1A2, 1A1, 3A4, 2C19, 2C8, and 2A6 showed moderate inhibition effects with HLMs. For M1-13, CYP2E1, 2D6, 2B6, 3A4, 2C8, 2C19, 2A6, 1A2, 1A1, and 2C9 presented high to low levels of inhibition effects with HLMs. For M1-14, CYP2E1, 2D6, 3A4, 2C19, 2B6, 2C9, 2C8, 2A6, 1A1, and 1A2 showed moderately high to low inhibition effects with HLMs. Compared with the control group, the inhibitors of CYP2B6, 1A1, and 2A6 with RLMs inhibited UA metabolism the most  of 0.01 µM–100.00 µM BA in human primary hepatocytes  ranged fTo confirm the contribution of UA and BA or their metabolites to the cytotoxicity of mouse 3T3 fibroblasts, we studied the effects of UA or BA incubation with HLMs, NADPH and UDPGA, and montelukast, sulfaphenazole, and ketoconazole, the exclusive inhibitors of CYP2C8, CYP2C9, and CYP3A4, by measuring cell viability. After incubation with mouse 3T3 fibroblasts for 4 h, the cell viability of UA groups from 1 μM to 50 µM ranged from 80.04% to 106.16%. None of the five groups exhibited cytotoxicity. The results showed that the cytotoxicity mechanism of UA may be related to long-term toxicity as it did not show cytotoxicity within 4 h of incubation in each group .Based on previous experiments, the relative cell viability showed that 100 µM BA exhibited cytotoxicity after incubation with mouse 3T3 fibroblasts for 24 h (26.87%) but not after 4 h (93.35%). Meanwhile, 200 µM BA displayed cytotoxicity after incubation with mouse 3T3 fibroblasts for 4 h (63.07%), which indicated that the cytotoxicity of BA increased in a time- and concentration-dependent manner. When incubated with HLMs, 20 and 200 µM BA showed cytotoxicity toward mouse 3T3 fibroblasts . The relative cell viability of these groups had an overall downward trend from 85.27% to 69.73%. After incubation with HLMs and NADPH or HLMs, NADPH, UDPGA, and inhibitors of CYP2C8, CYP2C9, and CYP3A4 for 4 h, the relative cell viability (% of NC) of 100 and 200 μM BA, which exhibited cytotoxicity toward mouse 3T3 fibroblasts, ranged from 68.26% to 76.84%. BA showed no cytotoxicity to mouse 3T3 fibroblasts with HLMs, NADPH, and UDPGA only . These rDrug-induced liver injury is one of the most common liver diseases. As the earliest lichen compound has been commercialized and developed, recent reports associated with liver-related adverse events of UA and other lichen compounds contained in products aroused widespread concern. Furthermore, the toxicity and mechanism of UA and other lichen compounds that induce hepatotoxicity remain unclear and have become a highly valued topic.®, which is composed of norephedrine hydrochloride (25 mg), sodium usniate (100 mg), 3,5-diiodothyronine (100 μg), yohimbine hydrochloride (3 mg), and caffeine (100 mg)  . In addi(100 mg) . The toxMost cellular studies showed that UA can cause cell necrosis and affects mitochondrial function . Early sCurrently, several scholars suggest that when CYP1A is inhibited, the metabolism of UA will decrease and result in its accumulation, which leads to the excessive inhibition of mitochondrial respiration, insufficient ATP, and cell necrosis. Therefore, several CYP enzyme inhibitors may increase the cytotoxicity of UA on rat hepatocytes, implying that UA might have a metabolic detoxification mechanism . AnotherIn this study, the metabolic profiles of UA and BA were investigated in RLMs, HLMs, and RS9. A total of 14 phase I metabolites and 4 phase II metabolites of UA and 4 phase I metabolites and 6 phase II metabolites of BA were identified. The results revealed that the metabolism of UA and BA with RLMs and HLMs was induced by CYP450 or UGTs and mediated by hydroxylation, methylation, and glucuronidation reactions. These metabolites showed similar fragmentation patterns in MS/MS spectra and only differed in fragment abundance.M1-2 and M1-3 were partially metabolized by CYP1A2. The metabolites of M1-1, M1-3, M1-4, and M1-9 were mainly influenced by CYP3A4, and M1-15 was regulated with UGT1A1. CYP2C9, CYP3A4, CYP2C8, and UGT1A1 are the main metabolic enzyme subtypes responsible for several metabolites of UA.UA is metabolized primarily by CYP1A2, UGT1A1, UGT1A3, and UGT1A8 . In addiin vivo and in vitro. Therefore, this study presents novel results that indicate that CYP2C8, CYP2C9, CYP2C19, CYP1A1, UGT1A1, UGT1A3, UGT1A7, UGT1A8, UGT1A9, and UGT1A10 are the main metabolic enzymes responsible for several metabolites of BA.It is worth mentioning that there are no studies on enzymes responsible for BA metabolism The identification of metabolic enzymes is a challenging study and is influenced by numerous factors and research strategies, such as the selection of target metabolites, activity of metabolic enzymes, specificity and inhibitory intensity of inhibitors, co-participation of multiple metabolic enzymes, and composition of the incubation system. In general, the results confirmed by recombinant isozymes are more reliable. To determine the major metabolic enzymes responsible for a compound, scholars must first identify the major metabolites from multi-metabolites or identify the metabolites related to metabolic activation or metabolic detoxification and then determine metabolic enzymes based on specific metabolites. However, only metabolites and the metabolic pathways of UA and BA were identified and analyzed in this research paper. Given the lack of separation, preparation, and structure confirmation of metabolites, quantitative determination of metabolites is impossible, which leads to the failure of identifying major and key metabolites based on existing results. Therefore, the identification of the key metabolic enzymes responsible for UA and BA is extremely difficult. This work will be further carried out in follow-up studies.50 values of 7.40 and 60.2 µm. The cytotoxicity of UA may be associated with chronic toxicity. The cytotoxicity of BA is associated with metabolism, and UGTs may be the main metabolic detoxification enzymes.The cytotoxic mechanism of drugs is usually based on their effect on hepatic drug-metabolizing enzymes , such asUsnea are due to the coexisting compounds contained in the lichen. Considering a mixture extract of plant herb or polyherbal compound, drug-drug interaction between UA and BA or other coexisting components must be taken into account. In particular, attention should be paid to the inhibitory and inductive effects of different compounds on drug-metabolizing enzymes and on transporters that play key roles in absorption and excretion processes  of rocesses .in vitro experiments, the present results provide important insights into the understanding of the biotransformation behavior and metabolic detoxification of UA and BA. They will provide important references for the research of metabolism behavior and clinical pharmacology of UA, BA, and other similar lichen compounds in vivo.Despite the difficulty of determining the exact structure of metabolites through MS only and confirming the specific mechanism of metabolic detoxification completely through In conclusion, hydroxylation, methylation, and glucuronidation reactions were involved in the metabolic profiles of UA and BA in RLMs, HLMs, and RS9 mediated by CYP450 and UGT. CYP2C9, CYP3A4, CYP2C8, and UGT1A1 were the key metabolic enzymes responsible for the metabolism of UA. CYP2C8, CYP2C9, CYP2C19, CYP1A1, UGT1A1, UGT1A3, UGT1A7, UGT1A8, UGT1A9, and UGT1A10 were the main metabolic enzymes responsible for the metabolism of BA. UA and BA did not display evident cytotoxicity toward human primary hepatocytes but did so toward mouse 3T3 fibroblasts. The attenuated cytotoxicity of BA was associated with metabolism, and UGTs may be the key metabolic detoxification enzymes. The cytotoxicity of UA may be associated with chronic toxicity. Overdose and long-term consumption of UA and BA, as well as the medicinal materials containing these compounds, still have potential risks of liver toxicity, and their application and safety deserve to be studied and receive more attention.


Fertility intentions have been proved to be a reliable predictor of actual fertility behaviour. Also, childbirth-related fear (CBRF) has been proven to be negatively associated with childbirth readiness and fertility intentions among women, while childbirth readiness was positively related to fertility intentions. However, the associations and potential mechanisms between CBRF, childbirth readiness, and fertility intentions remain unknown. This study aimed to investigate the unique association between CBRF, childbirth readiness, and fertility intentions and whether childbirth readiness would mediate the relationship between CBRF and fertility intentions.A cross-sectional study of women  who gave birth within 72 h was conducted. Using a convenience sampling, women were recruited from obstetric wards—10 comprehensive hospitals and 3 specialized hospitals in 7 provinces in mainland China. Pearson correlation was used to examine the relationship between CBRF, childbirth readiness, fertility intentions, and social support. Multivariate linear regression was further used to analyze the association between demographic and personal characteristics, CBRF, childbirth readiness, and fertility intentions. Mediation analysis was used to examine whether childbirth readiness mediates the relationship between CBRF and fertility intentions.β = 0.09, P = 0.002) had higher fertility intentions. However, women with high CBRF  were more likely to have lower fertility intentions. CBRF had both direct and indirect effects on the level of fertility intentions. As predicted, childbirth readiness mediated the relationship between CBRF and the level of fertility intentions . Higher CBRF was associated with lower scores of childbirth readiness, which was associated with lower levels of fertility intentions.Women with high childbirth readiness (This study established the evidence that CBRF had both direct and indirect effects on the level of fertility intentions and childbirth readiness mediated the relationship between CBRF and the level of fertility intentions. Specifically, higher CBRF was associated with lower scores of childbirth readiness, which was associated with lower levels of fertility intentions. This finding suggested that it is important for health policymakers and health providers to pay more attention to improving women’s childbirth readiness, which might reduce the negative influence of CBRF on fertility intentions, thus strengthening their fertility intentions. Over the past two decades, fertility rates have been dropping steadily in most countries. Fertility intentions have been proven to be a reliable predictor of actual fertility behaviour. The worldwide sluggish fertility trend has brought about a series of issues, such as accelerated population ageing, shrinking workforce, and economic decline. China has the largest national population in the world, accounting for nearly one-fifth of the world's population, thus having a huge impact on global population trends. Therefore, in the context of significant fertility decline and population policy changes, timely research on fertility intention is of great significance for China and other low-fertility countries. CBRF has been proven to be negatively associated with childbirth readiness and fertility intentions among women, while childbirth readiness was positively related to fertility intentions. This study aimed to investigate the unique association between fertility intentions, CBRF, and childbirth readiness, and whether childbirth readiness would mediate the relationship between CBRF and fertility intentions. In this cross-sectional study, we found that women with high childbirth readiness had higher fertility intentions. However, women with high CBRF were more likely to have lower fertility intentions. Furthermore, CBRF had both direct and indirect effects on the level of fertility intentions. Childbirth readiness mediated the relationship between CBRF and the level of fertility intentions. Higher CBRF was associated with lower scores of childbirth readiness, which was associated with lower levels of fertility intentions. This finding suggested that it is important for health policymakers and health providers to pay more attention to improving women’s childbirth readiness, which might reduce the negative influence of CBRF on fertility intentions, thus strengthening their fertility intentions. Over the past two decades, fertility rates have been dropping steadily in most countries. Research has found that 179 of 204 countries saw a decline in the total fertility rate (TFR) in the last ten years . In 1979Fertility intentions have been regarded as a reliable predictor of actual fertility behavior . AlthougChildbirth readiness could cause lesser maternal complications and improve women’s childbirth experiences , 19, thuBased on the evidence, we hypothesize that CBRF negatively associates with childbirth readiness and fertility intentions. Considering that childbirth readiness is positively associated with fertility intentions, we further hypothesize that childbirth readiness mediates the relationship between CBRF and fertility intentions. To our knowledge, no study to date has examined the relationship between fertility intentions, CBRF, and childbirth readiness, and explored if childbirth readiness is a mediating factor. We therefore, aimed to assess such association in this study.A cross-sectional study of women (N = 1119) in obstetric wards—10 comprehensive hospitals and 3 specialized hospitals from 7 provinces/municipalities/autonomous regions in mainland China. The National Bureau of Statistics of China divided Chinese economic regions into four regions. Based on the four regions, we randomly selected seven provinces/municipalities/autonomous regions. Then, we contacted the tertiary hospitals and secondary hospitals in the seven provinces/municipalities/autonomous regions that were sampled. This study was conducted from November 2021 to March 2022.A convenient sampling method was used to recruit participants in this study. We included women: (1) who gave birth within 72 h; and (2) were willing to participate in the study. Women with: (1) psychological diseases ; and (2) severe obstetric complications, were excluded from the study. In the pilot study, the standard deviation (SD) of fertility intention scores was 1.50 in some of the hospitals where we conducted the survey; with a maximal tolerance of 0.10 and error of type I at 5%, the minimal sample sizes were 865. Considering 10% invalid sample size, at least 951 participants were needed. Finally, a total of 1119 participants who met our inclusion criteria were recruited.The study protocol was approved by the Ethics Committee of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology (reference number: TJ-IRB20210755). All participants completed the written informed consent before participating in the study.A self-administered online questionnaire was used to collect data. In the process of the questionnaire survey, trained nurses in the ward distributed electronic questionnaires to participants one-on-one.The demographics included age, education level, marital status, marital satisfaction (satisfied/unsatisfied), residence area , monthly household income, pregnancy sleep status, pregnancy exercise status, parity (nulliparous/ multiparous), adverse obstetric history, self-reported obstetric complications, pregnancy life events, etc. The following variables were classified as: age (years)—less than 26, 26–35, and more than 35; education level—primary school or lower, junior high school, senior high school, and college or higher; monthly household income—less than 3001¥, 3001–5000¥, 5001–10,000¥, and more than 10,000¥; pregnancy sleep status—well, moderate, and poor; pregnancy exercise status—always, often, occasionally, and never; with adverse obstetric history, self-reported obstetric complications, and pregnancy life events categorized as yes or no.Social support was measured using the Chinese version of the medical outcomes study social support survey (MOS-SSS), which is a 20-item scale. The MOS-SSS scale includes one item evaluating the support network and 19 items assessing the availability of social support in four dimensions—emotional, tangible, affectionate, and positive social interaction. The MOS-SSS is measured on a 5-point Likert scale ranging from 20 to 100, with a higher score indicating greater social support. The Cronbach α and 2-week test–retest reliability for the Chinese version of the MOS-SSS were 0.98 and 0.84, respectively . CronbacThe Chinese version of the fear of childbirth scale (FOBS) was used to estimate the CBRF . The FOBChildbirth readiness was assessed using the Chinese version of the childbirth readiness scale (CRS). The CRSIndividuals’ fertility intentions were evaluated using the following question: “Would you refuse to have another child due to the experience of this birth?” The five possible responses were: “definitely not”, “probably not”, “not sure”, “probably yes”, and “definitely yes”, on a scale of 1 to 5 . In thist-test and one-way ANOVA were used to describe the differences in demographic and personal characteristics with fertility intentions. Pearson correlation was used to examine the relationship between fertility intentions, CBRF, childbirth readiness, and social support. Multivariate linear regression was further used to analyze the association between demographic and personal characteristics  and PROCESS 4.0 for SPSS macro-program  were useP ≤ 0.007).Participants’ mean age was 29.53  years. More detailed characteristics of the participants are presented in Table r = − 0.237, P < 0.001) and positively related to childbirth readiness  and social support . CBRF was negatively related to childbirth readiness  and social support . Childbirth readiness was positively correlated with social support . All P values were significant and the effect sizes were more than 0.1 between the variables.Table β = − 0.10, P = 0.001) and poor  sleeping patterns, had lower fertility intentions , occasionally , and never  in pregnancy exercise status had a lower level of fertility intentions than those reporting always in exercise status. Those having higher social support  and childbirth readiness  had a higher level of fertility intentions. Whereas, women with higher CBRF  were more likely to be in a lower level of fertility intentions.The multivariate linear regression analysis in this study revealed that compared to women with a well pregnancy sleeping pattern, those with moderate (ns Table . Women wCI: − 0.879 to − 0.384), and positively related to fertility intentions . CBRF was further negatively related to fertility intentions . The mediation analysis supported our study hypothesis of childbirth readiness having an indirect effect on the relationship between CBRF and fertility intentions . Figure The total, direct, and indirect effects of the mediation model are reported in Table This is the first study to assess the association between CBRF, childbirth readiness, and fertility intentions, with childbirth readiness as the mediating factor in China, Asia, and globally. We found CBRF to be a negative predictor, while childbirth readiness was a positive predictor for fertility intentions. The mediation model demonstrated childbirth readiness mediated the relationship between CBRF and fertility intentions, which supported our hypothesis. Specifically, higher CBRF was associated with lower childbirth readiness, which was associated with lower fertility intentions. The current study provides evidence of potential mechanisms between the association of CBRF, childbirth readiness, and fertility intentions.In the present study, we found that women with higher levels of CBRF were more likely to be in lower levels of fertility intentions. This is consistent with previous results suggesting that the development of fear of childbirth is a vicious circle of negative experiences of childbirth from present pregnancy influencing future pregnancy . High leIn the current mediation model, we found that childbirth readiness partially mediated the relationship between CBRF and the level of fertility intentions. The specific relation is that higher CBRF was associated with lower scores on childbirth readiness, which was associated with a lower level of fertility intentions. Previous studies have provided some clues for links between CBRF, childbirth readiness, and fertility intentions. A study conducted among 204 primiparous pregnant women in Iran found that women who regularly attended childbirth preparation classes had lower scores in fear of childbirth compared with non-attending ones . In a quIn this study, several other factors were related to women’s fertility intentions. We found that compared to women with a well sleeping pattern during pregnancy, women with moderate and poor sleeping patterns had lower fertility intentions. Our study supports the evidence that poor sleeping patterns during pregnancy may account for adverse pregnancy outcomes and negative pregnant experiences , 36, whiFirst, in this cross-sectional study, the causal directions of the association cannot be ascertained. Longitudinal studies need to explore how the three variables function in time. Second, the information of CBRF and childbirth readiness was collected within 72 h after giving birth, so recall bias may exist. Future studies could survey women’s CBRF and childbirth readiness during their pregnancy. Third, women’s fertility intention was measured using a single question. In follow-up studies, scales or other more standardized tools could be used to evaluate fertility intentions and the results could be compared.This study established the evidence that CBRF had both direct and indirect effects on the level of fertility intentions and childbirth readiness mediated the relationship between CBRF and the level of fertility intentions. Specifically, higher CBRF was associated with lower scores of childbirth readiness, which was associated with lower levels of fertility intentions. This finding suggested that it is important for health policymakers and health providers to pay more attention to improving women’s childbirth readiness, which might reduce the negative influence of CBRF on fertility intentions, thus strengthening their fertility intentions.