Mouse models of obesity and male fertility: a systematic review and network meta-analysis

Introduction

In the past 40 years, obesity prevalence increased in every country. The worldwide number of adult men with obesity increased nine-fold (1). More than an energy imbalance condition, obesity is a complex and multifactorial disease with both genetic and environmental causes (2). Meanwhile, the adverse effects of obesity on male fertility have been considered a health problem and received more and more attention these years. Many epidemiological studies show that body mass index (BMI) is negatively correlated with male reproductive potential (3-5).

The mechanisms by which obesity reduces reproductive capacity are complex, such as endocrine disorders, inducing sexual dysfunction, elevated scrotal temperature, and decreased semen parameters (6-9). Overexpression of aromatase in obese people drives enhanced conversion of androgens to estrogens, which in turn causes androgen deficiency, a condition linked to sexual dysfunction and male infertility (8,10-13). Furthermore, research indicates that mean scrotal temperatures are significantly elevated among obese individuals relative to normal-weight counterparts; even brief episodes of scrotal hyperthermia can drastically lower sperm concentration, compromise sperm motility and viability, induce morphological defects in spermatozoa, and modify the spatial organization of testicular structures during the spermatogenic cycle (10). In addition, metabolic homeostasis exerts pivotal regulation over the energy demands of the reproductive system, and obesity-induced metabolic derangements compromise overall reproductive function (14). All of the above evidence indicates that a statistically significant negative correlation exists between elevated BMI and concentrations of seminal biochemical markers such as alpha-glucosidase (15). Many of the above-mentioned mechanisms have been investigated using animal models (16).

Over the past decades, a broad spectrum of animal models has been adopted to explore the correlations between obesity and male fertility. The three most prevalent mammalian animal models are mice, rats, and rabbits (17). The mouse model is the most widely used. A host of factors may compromise model reliability and final experimental results, such as mouse strains, transgenic design strategies, dietary interventions, and intervention periods. Compared with wild-type (WT) mice, specific transgenic mouse models exhibit a greater tendency to develop obesity, among which leptin receptor (LepR) db/db, leptin (Lep) ob/ob, and low-density lipoprotein receptor knockout (Ldlr^−/−) mice are widely applied (18-20). Notwithstanding the above limitations, diet-induced obese (DIO) models established with high-calorie diets recapitulate key biological phenotypes of human obesity to a greater degree than transgenic strains, given their superior alignment with the metabolic state observed in obese patients (21). Despite the wide availability of transgenic obese mouse strains, nevertheless, there exists no universal strategy to guarantee stable obese phenotypes, as key experimental parameters such as dietary composition and intervention duration differ markedly between independent research groups. To address this gap, we performed this meta-analysis to screen out appropriate dietary schemes for mouse models exploring obesity-related male reproductive dysfunction. We present this article in accordance with the PRISMA-NMA reporting checklist (available at https://tau.amegroups.com/article/view/10.21037/tau-2025-aw-880/rc).

Methods

Study protocol registration

The protocol of the current meta-analysis is registered on the INPLASY website. The registration number is INPLASY202250116. The DOI number is 10.37766/inplasy2022.5.0116.

Search strategy

Three major electronic databases (PubMed, Web of Science, and Embase) were systematically searched. The full search strategy is provided in Appendix 1.

All original studies adopting DIO mouse models to investigate male fertility outcomes were eligible for inclusion (conference abstracts, unpublished reports, and dissertations were excluded). The primary objective of this analysis was to clarify the causal link between obesity and male fertility. We excluded publications that only evaluated how obesity-associated complications, including type 2 diabetes and erectile dysfunction (ED), affect reproductive outcomes. Primary outcome measurements were categorized into two sets: indices reflecting obesity status and biomarkers of male fertility.

Intervention categories

To investigate the influences of dietary fat content and the duration of high-fat feeding on the success of obese animal models, we categorized all included dietary intervention protocols as detailed below. All aforementioned high-fat diet (HFD) groups were compared with normal diet (ND) control groups; standard ND formulations typically derive less than 10% of total caloric intake from fat, accompanied by matched intervention durations. Detailed grouping information is summarized in Table 1.

Article screening

EndNote 20 reference management software was employed to organize all retrieved search records. Literature screening proceeded in three sequential stages. First, two independent reviewers initially screened all retrieved publications by title. Articles with ambiguous eligibility were retained to advance to the subsequent abstract screening stage. In the second stage, the retained citations underwent abstract evaluation against predefined inclusion criteria by the same two reviewers. Discrepancies between reviewers were settled via consensus discussion or arbitration by a third independent member of the review panel. In the final full-text screening stage, remaining eligible records were assessed in full text following the established inclusion standards; any outstanding disagreements were again resolved through group discussion among the review team.

Data extraction

• We extracted the mean, standard deviation, and sample size from the ND and HFD treatment groups for nine obesity-related indices and nine reproductive parameters (Table 2). These indicators were grouped into four main categories: obesity index (OI), reproductive morphology (RM), standard semen analysis traits (ST), and advanced sperm functional indices [sperm stress (SS)]. Notably, the relative weight of reproductive organs (calculated as organ mass divided by corresponding body weight per group) was derived from original reported data (17). All retrievable raw data were collected, yet only endpoints with sufficient published data were retained to conduct the network meta-analysis.

  Table 2

  Data extraction project

  
  

  Category	Trait	Description
  OI	Body weight	body weight of research mice
  	BMI	body weight divided by the square of the naso-anal length (g/cm2)
  	TG	Serum total triglyceride
  	TC	Serum total cholesterol
  	HDL-C	Serum high-density lipoprotein
  	LDL-C	Serum low-density lipoprotein
  	Insulin	Serum insulin
  	Lep	Serum Lep
  	BG	Blood glucose concentration
  RM	Testes mass	Absolute weight of single testis (g)
  	Epididymis mass	Absolute weight of epididymis (g)
  	Relative testes mass	Weight of single testis, relative to body weight (g)
  	Relative epididymis mass	Weight of epididymis, relative to body weight (g)
  ST	Sperm count	Estimate of number of sperm subcategories: sperm concentration (million sperm per mL)
  	Sperm motility	% motile sperm
  	Progressive motility	% PR sperm
  	Sperm morphology	% sperm with normal morphology
  	Sperm viability	% viable sperm
  	DFI	% or DNA fragmentation index

  BG, blood glucose; BMI, body mass index; DFI, DNA fragmentation index; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; Lep, leptin; OI, obesity index; PR, progressive motility; RM, reproductive morphology; ST, standard semen analysis traits; TC, total cholesterol; TG, triglycerides.
• For studies presenting data solely in graphical format, numerical values were extracted utilizing GetData Graph Digitizer version 2.26 (http://getdata-graph-digitizer.com). In cases where outcomes were reported as medians with interquartile ranges—indicating non-normal distributions—we estimated the mean and standard deviation using the quantile estimation approach proposed by Wan et al. in 2014 (22). Additionally, we compiled moderator variables including species type, specific dietary manipulations, initial male age at treatment onset, intervention duration, and mean body weight per experimental group.

Risk of bias assessment

Based on SYRCLE’s risk of bias tool for animal studies (23), two trained researchers independently evaluated and cross-checked the inherent risk of bias in the included studies, covering selection bias, implementation bias, measurement bias, follow-up bias, reporting bias, and other bias from a list of 10 questions or tools. A difference in opinions was negotiated or decided by a third party. The answer to the assessment questions (tools) should be either “yes”, which indicated low risk of bias, or “no”, which indicated high risk of bias. For unclear items, an answer with “some concern” was assigned.

The results are shown in Figure 1. Although there are some blanks in study design and writing report, and reporting standards for similar animal experiments need to be further standardized. The results still showed overall good quality.

Figure 1 Overall risk of bias.

Results

Studies included

A total of 784 records were retrieved from electronic databases. After removing 343 duplicates, 21 records marked as ineligible by automation tools, and 256 records not relevant to the topic, 164 records entered title and abstract screening, among which 93 irrelevant records were excluded.

Full-text retrieval was attempted for the leftover 71 publications, and none of these documents failed to be obtained. During full-text eligibility assessment, 8 studies were eliminated for multiple causes. Finally, a total of 63 qualified studies were incorporated into this network meta-analysis. The PRISMA 2020 flow chart is presented in Figure 2. All the studies included are provided in Appendix 2.

Figure 2 PRISMA 2020 flow diagram for new systematic reviews which included searches of databases and registers only.

Network meta-analyses were performed using R software (version 4.1.3) to separately quantify the impacts of different dietary interventions on obesity and male reproductive outcomes in mouse models. Inconsistency was evaluated via node-splitting analysis. Heterogeneity was assessed using the Q statistic and I² value; low heterogeneity was defined as I²<40%, whereas substantial heterogeneity (I²>40%) was further explored through network meta-regression. Treatment ranking was generated to identify the optimal intervention protocol (24).

Body weight

A total of 51 studies reported the data with a sample size of 1,241. A summary of direct comparisons between interventions is presented in the treatment comparison network. Specifically, direct head-to-head evidence was available for seven pairwise comparisons. The number of included studies for each direct comparison was listed in Table 3.

Bayesian network meta-analysis was performed using a mean difference (MD) model. The results showed in Table 4. All HFD groups exhibited significantly higher obesity indices compared with the ND group. The magnitude of increases in obesity indicators ranked from highest to lowest as HFD4, followed by HFD2, HFD3, and HFD1. HFD4 produced the most prominent elevation in obesity-related outcomes among all regimens. The I² statistic was 0.8%, indicating negligible heterogeneity. The Gelman diagnostic test confirmed excellent convergence (Rhat =1 for all parameters).

According to the rank probability matrix with a preferred direction of lower values (direction =−1), the dietary interventions were hierarchically ranked from the lowest to the highest obesity levels as follows: ND (rank 1: 99.76%), HFD1 (rank 2: 75.67%), HFD3 (rank 3: 69.30%), HFD2 (rank 4: 75.68%), and HFD4 (rank 5: 86.41%). Notably, HFD4 had the highest probability of being the most obesogenic diet, followed by HFD2. These findings indicate that dietary fat content and intervention duration jointly affect the success of obese model establishment. All results are shown in Figure 3.

Figure 3 Analysis results on weight. (A) Network relationship diagram; (B) forest diagram; (C) stacking sorting diagram. HFD1: the proportion of fat energy supply in the feed is between 10% and 45%, maintained for 4–12 weeks. HFD2: the proportion of fat energy supply in the feed is between 10% and 45%, maintained for more than 12 weeks. HFD3: the proportion of fat energy supply in the feed is above 45%, maintained for 4–12 weeks. HFD4: the proportion of fat energy supply in the feed is above 45%, maintained for more than 12 weeks. CrI, credible interval; HFD, high-fat diet; ND, normal diet.

Sperm count

Thirty-nine studies reported the data with a sample size of 833. A summary of direct comparisons between interventions is presented in the treatment comparison network. Specifically, direct evidence was available for eight pairwise comparisons. The number of included studies for each direct comparison was listed in Tables 5,6. The network plot of included comparisons is presented in Figure 4.

Figure 4 Analysis results on sperm count. (A) Network relationship diagram; (B) forest diagram; (C) stacking sorting diagram. HFD1: the proportion of fat energy supply in the feed is between 10% and 45%, maintained for 4–12 weeks. HFD2: the proportion of fat energy supply in the feed is between 10% and 45%, maintained for more than 12 weeks. HFD3: the proportion of fat energy supply in the feed is above 45%, maintained for 4–12 weeks. HFD4: the proportion of fat energy supply in the feed is above 45%, maintained for more than 12 weeks. CrI, credible interval; HFD, high-fat diet; ND, normal diet.

Bayesian network meta-analysis based on MD was performed for sperm count. Compared with ND, HFD3 significantly reduced sperm count. By contrast, HFD1, HFD2 and HFD4 did not significantly alter sperm count, with their 95% credible intervals (CrIs) all crossing zero. The between-study heterogeneity was low (I²=24%), and Gelman-Rubin diagnostic values equaled 1 across all parameters, indicating satisfactory model convergence.

Sperm viability

Thirty-seven studies reported the data with a sample size of 776. The number of original studies for each direct comparison was shown in Tables 7,8. Bayesian network meta-analysis with the MD model was conducted for sperm motility. Compared with ND, HFD2, HFD3 and HFD4 significantly reduced sperm motility, while HFD1 showed no significant difference versus ND (MD =−8.85; 95% CrI: −20.85, 3.11; interval crossed zero). No between-study heterogeneity was observed (I²=0%). Gelman-Rubin convergence diagnostic values were all equal to 1, indicating excellent model convergence. The network plot of included comparisons is presented in Figure 5.

Figure 5 Analysis results on sperm viability. (A) Network relationship diagram; (B) forest diagram; (C) stacking sorting diagram. HFD1: the proportion of fat energy supply in the feed is between 10% and 45%, maintained for 4–12 weeks. HFD2: the proportion of fat energy supply in the feed is between 10% and 45%, maintained for more than 12 weeks. HFD3: the proportion of fat energy supply in the feed is above 45%, maintained for 4–12 weeks. HFD4: the proportion of fat energy supply in the feed is above 45%, maintained for more than 12 weeks. CrI, credible interval; HFD, high-fat diet; ND, normal diet.

Progressive motility (PR) sperm

Twenty-seven studies reported the data with a sample size of 573. Five direct pairwise comparisons were available for PR. The number of relevant studies for each direct comparison was shown in Tables 9,10. Bayesian network meta-analysis of PR was performed using the MD model. Compared with ND, HFD1, HFD3 and HFD4 significantly decreased PR values. In contrast, HFD2 exerted no obvious influence on PR (MD =−10.58; 95% CrI: −22.75, 1.51; CrI crossed zero). Heterogeneity was negligible (I²=2%), and all Gelman-Rubin statistics were equal to 1, suggesting favorable model convergence. The rank probability was calculated with preferred direction =−1, meaning rank 1 corresponded to the lowest PR value and rank 5 to the highest PR value. HFD4 had an 87.98% probability of ranking first (the lowest PR), while ND possessed a 95.43% probability of ranking fifth (the highest PR). The overall descending order of PR was ND > HFD2 > HFD3 > HFD1 > HFD4, confirming all four HFDs significantly reduced PR compared with ND, with the most remarkable reduction observed in HFD4. The network plot of included comparisons is presented in Figure 6.

Figure 6 Analysis results on PR. (A) Network relationship diagram; (B) forest diagram; (C) stacking sorting diagram. HFD1: the proportion of fat energy supply in the feed is between 10% and 45%, maintained for 4–12 weeks. HFD2: the proportion of fat energy supply in the feed is between 10% and 45%, maintained for more than 12 weeks. HFD3: the proportion of fat energy supply in the feed is above 45%, maintained for 4–12 weeks. HFD4: the proportion of fat energy supply in the feed is above 45%, maintained for more than 12 weeks. CrI, credible interval; HFD, high-fat diet; ND, normal diet; PR, progressive motility.

Sperm morphology

Twenty studies reported the data with a sample size of 385. The number of original studies for each direct comparison was shown in Tables 11,12. Bayesian network meta-analysis was performed on sperm malformation rate, with higher values indicating severer sperm morphological damage. No statistically significant differences in sperm malformation rate were observed between ND and all HFD groups, or among different HFD groups. Between-study heterogeneity was negligible (I²=1%), and all Gelman-Rubin convergence indicators were equal to 1, confirming robust and reliable model performance. No statistically significant differences in sperm malformation rate were found between each HFD group and the ND group. Nevertheless, the ranking probability plot indicated that HFD4 possessed the highest malformation rate. The network plot of included comparisons is presented in Figure 7.

Figure 7 Analysis results on sperm morphology. (A) Network relationship diagram; (B) forest diagram; (C) stacking sorting diagram. HFD1: the proportion of fat energy supply in the feed is between 10% and 45%, maintained for 4–12 weeks. HFD2: the proportion of fat energy supply in the feed is between 10% and 45%, maintained for more than 12 weeks. HFD3: the proportion of fat energy supply in the feed is above 45%, maintained for 4–12 weeks. HFD4: the proportion of fat energy supply in the feed is above 45%, maintained for more than 12 weeks. CrI, credible interval; HFD, high-fat diet; ND, normal diet.

Relative testes mass

Twenty-eight studies reported the data with a sample size of 573. Five direct pairwise comparisons were available for Relative testes mass. The number of relevant studies for each direct comparison was shown in Tables 13,14. Compared with the ND, all HFD groups showed significantly lower testicular index, with a statistically significant difference observed between the HFD2 and ND groups (MD =1.64; 95% CrI: 0.29, 2.99). The network meta-analysis model showed excellent convergence and negligible heterogeneity (I²=2%), confirming the reliability of the results. The network plot of included comparisons is presented in Figure 8.

Figure 8 Analysis results on relative testes mass. (A) Network relationship diagram; (B) forest diagram; (C) stacking sorting diagram. HFD1: the proportion of fat energy supply in the feed is between 10% and 45%, maintained for 4–12 weeks. HFD2: the proportion of fat energy supply in the feed is between 10% and 45%, maintained for more than 12 weeks. HFD3: the proportion of fat energy supply in the feed is above 45%, maintained for 4–12 weeks. HFD4: the proportion of fat energy supply in the feed is above 45%, maintained for more than 12 weeks. CrI, credible interval; HFD, high-fat diet; ND, normal diet.

Discussion

This study conducted a systematic network meta-analysis to compare the effects of four distinct HFDs (HFD1, HFD2, HFD3, HFD4) on adiposity indicators and reproductive function relative to the ND. The pooled outcomes effectively quantified the differential impacts of various high-fat formulas on male reproductive function, overcoming the limitation of conventional pairwise meta-analysis that cannot achieve indirect comparisons among multiple intervention regimens. Fortunately, our findings are consistent with prior studies confirming that diet-induced obesity damages male reproductive function in animal models; importantly, our analysis further provides novel insights regarding specific high-fat dietary patterns (17).

The quality of included studies determines the reliability of network meta-analysis results. Accordingly, extensive literature screening was performed in advance, and 63 eligible publications were ultimately selected from an initial pool of 784 retrieved articles. Existing literature highlights that male reproductive impairment induced by obesity remains a major public health concern (25,26). All included studies adopted mouse experimental models, leading to limitations in rigorous risk-of-bias assessment. Although multiple indicators related to adiposity and reproductive function in mice were initially collected, endpoints with insufficient effect-size data were excluded from the final network meta-analysis due to data constraints. Consequently, six primary outcomes were analyzed: body weight, sperm count, sperm motility, PR sperm, sperm abnormality rate, and testicular index.

According to Figure 3, Pooled results demonstrated that all tested high-fat regimens effectively induced obesity in mice relative to ND controls. The rank-probability stacked bar chart revealed that HFD4 (>45% HFD, >12 weeks) produced the most prominent weight gain, indicating that dietary fat content and feeding duration were positively correlated with the severity of obesity in mice.

In terms of reproductive parameters, the corresponding results were more complicated. HFD3 (>45% HFD, 4–12 weeks) yielded the lowest sperm count. Sperm viability was markedly reduced in HFD2 (10%< HFD ≤45%, >12 weeks), HFD3 and HFD4 groups, while HFD4 exhibited the most prominent decline in PR sperm proportion. Nevertheless, no obvious alterations in sperm morphology and relative testes mass were observed across all HFD regimens. Collectively, these results indicate that obesity induced by high-fat feeding is strongly correlated with the development of oligozoospermia and asthenospermia, whereas it exerts minimal adverse effects on sperm morphological integrity.

Our findings are consistent with the investigation by Ghosh et al. and Jia et al., who reported that long-term obesity-related insults compromise male reproductive capacity (27,28). The mechanism may be that long-term HFD intervention stimulates chronic inflammation, which results in excessive accumulation of ROS and reduces the level of capacitated spermatozoa (29). Similarly significant connections between spermatozoa morphology and ROS were found in Agarwal’s studies proving strong interrelations between the two parameters (30). Such dietary model in mice mimics important features of human overconsumption (31). The deficiencies are, due to the difference of macronutrients and micronutrients in diet and the difference of energy density, concentration, flavor, physical formula, and taste, there are differences in energy intake, body composition, and body weight in mice. So, it’s meaningful to explore a fixed formulation for this research.

Regarding sperm malformation rate, none of the four HFD groups differed statistically from ND after pooled network meta-analysis. Rank probability distribution suggested a numerical tendency that HFD4 had the highest sperm malformation rate among all interventions, despite absence of statistical intergroup difference. Existing animal experiments have confirmed excessive fat intake can induce spermatogenic cell damage, raise sperm malformation ratio via oxidative stress and testicular inflammatory injury. However, substantial between-study variation in experimental animal strains, feeding cycles, and detailed high-fat feed ingredients contributed to wide overlapping CrIs for all pairwise comparisons, eventually resulting in the lack of statistical significance between each HFD and ND. Though without statistical difference in direct comparison, the surface under the cumulative ranking curve (SUCRA)-based sequential ranking provided suggestive trend evidence for the relative harm of different HFDs on sperm quality, which can supply reference for subsequent animal experimental design. Available evidence also suggests that adequate intake of high-fat feed constitutes a critical prerequisite for successfully establishing mouse models of obesity accompanied by reproductive impairment. Specifically, HFD2 features prolonged intervention duration, HFD3 contains elevated dietary fat content, whereas HFD4 combines both above two characteristics. Collectively, pooled outcomes verify that HFD4 serves as the optimal dietary protocol for establishing the obese reproductive injury mouse model. Further well-designed, standardized animal experiments with unified feeding criteria are required to validate the present ranking tendency and clarify the exact dose-effect relationship of different high-fat formulas on male reproductive injury.

In addition, mouse strain is another confounding factor for model establishment, particularly transgenic mouse lines related to Lep and LepR. Transgenic mice with modified Lep/LepR genes are prone to developing obesity. Lep acts as a pivotal physiological modulator of multiple endocrine pathways in mammals (32). The Ldlr^−/− Leiden mouse model, which recapitulates core metabolic pathways underlying human obesity, also represents a promising candidate for modelling (18,33). Although existing data fail to confirm that transgenic backgrounds shorten the modelling period, exploration of such transgenic strains remains a valuable direction for future research. Relevant experimental verification on transgenic animals will be supplemented in our follow-up investigations.

Strengths and limitations

Several limitations should be acknowledged in this network meta-analysis. First, partial pairwise comparisons contained merely one original trial, insufficient sample size may reduce the statistical power of indirect comparison. Second, marked heterogeneity of baseline parameters, including animal age and feeding duration, existed across included literature, which could interfere pooled effect values despite low overall (I²). Third, unreported raw data limited further subgroup and sensitivity analysis.

Implications for obesity model

Compared with conventional aggregate meta-analysis methods, network meta-analysis possess a unique advantage: they can integrate all available data from clinical trials, encompassing both direct and indirect comparative evidence. Nevertheless, the evidence is limited by the reporting and quality of the trials included. There will surely be many more animal studies on obesity and male reproductive function in the future. In order to improve the reliability and reproducibility of animal study, quality control in modeling is critical. This network meta-analysis provides some valuable information.

Conclusions

Based on the network meta-analysis of qualified published studies, pairwise direct and indirect comparisons were conducted among diverse high-fat dietary regimens in the establishment of mouse models. Contrary to conventional viewpoints from prior literature, our results reveal that the reliable establishment of obese mouse models with reproductive dysfunction depends on the synergistic effects of elevated dietary fat content and extended feeding period, instead of a single influencing factor. Adequate feeding duration (≥12 weeks) together with increased fat proportion helps yield stable animal models. Accordingly, researchers can rationally customize dietary fat percentages in accordance with individual experimental purposes. For the sake of enhancing inter-experiment reproducibility, unified and widely acknowledged HFD specifications (e.g., formulations with 45% or 60% of total calories derived from fat) are highly desirable for subsequent in vivo animal studies.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the PRISMA-NMA reporting checklist. Available at https://tau.amegroups.com/article/view/10.21037/tau-2025-aw-880/rc

Peer Review File: Available at https://tau.amegroups.com/article/view/10.21037/tau-2025-aw-880/prf

Funding: This work was supported by the National Natural Science Foundation Program (Nos. 82174392, 82405406, and 82505581), the Hubei Provincial Natural Science Foundation for Youth (No. 2024AFB356), and the Guiding Project of Hubei Provincial Administration of Traditional Chinese Medicine (No. ZY2025L289).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tau.amegroups.com/article/view/10.21037/tau-2025-aw-880/coif). All authors report that this study was supported by the National Natural Science Foundation Program (Nos. 82174392, 82405406, and 82505581), the Hubei Provincial Natural Science Foundation for Youth (No. 2024AFB356), and the Guiding Project of Hubei Provincial Administration of Traditional Chinese Medicine (No. ZY2025L289). The authors have no other conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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