AIM: To compare the efficacy and safety of posterior scleral, peripupillary, and intravitreal injections of triamcinolone acetonide(TA)in treating retinal vein occlusion-macular edema(RVO-ME).METHODS: From June 2021 to September 2024, patients with RVO-ME admitted to our hospital were assigned to three groups: group A(posterior scleral injection), group B(peripupillary injection), and group C(intravitreal injection). At 3 mo after treatment, the efficacy, best corrected visual acuity(BCVA LogMAR), central macular thickness(CMT), central retinal artery blood flow parameters, and incidence of complications were compared among the three groups of patients.RESULTS: A total of 93 cases(93 eyes)of RVO-ME were included, with 31 cases(31 eyes)in each group. The mean age in the group A was 50.37±5.71 years old, with 15 males and 16 females, the group B was 48.92±5.36 years old, with 14 males and 17 females, and the group C was 49.66±5.54 years old, with 18 males and 13 females. The overall efficacy rate in the group A(94%)was higher than that in the groups B and C(68% and 74%), and the complication rate(6%)was lower than in the groups B and C(29% and 32%; P<0.05). At 1 and 3 mo after treatment, the BCVA of group A was 0.46±0.06, 0.36±0.04, the end diastolic velocity(EDV)was 11.45±1.79, 13.97±2.28 cm/s, and the peak systolic velocity(PSV)was 2.16±0.31, 2.83±0.42 cm/s; the BCVA of group B was 0.55±0.07, 0.46±0.05, EDV was 9.57±1.38, 12.03±2.14 cm/s, and PSV was 1.93±0.26, 2.41±0.39 cm/s. The BCVA of group C was 0.57±0.09, 0.48±0.06, EDV was 9.39±1.25, 11.91±2.06 cm/s, PSV was 1.87±0.24, 2.35±0.36 cm/s. The BCVA in the group A was better than that of the groups B and C, and EDV and PSV in the group A were greater than those of the groups B and C(all P<0.05); at 1 and 3 mo after treatment, the CMT of patients in the group A was 249.62±29.33 and 141.13±21.59 μm, and resistance index(RI)was 0.71±0.08 and 0.70±0.08, patients in the group B had CMT of 307.13±34.86 and 227.99±28.43 μm, and RI of 0.77±0.09 and 0.76±0.09, while patients in the group C had CMT of 311.42±40.66 and 232.56±31.44 μm, and RI of 0.79±0.11 and 0.78±0.10, with CMT and RI significantly lower in the group A than those in the groups B and C(all P<0.05).CONCLUSION: All three methods improved visual acuity, reduced macular edema, and optimized retinal blood flow parameters. However, posterior scleral injection demonstrated the most significant improvement across all efficacy metrics. In contrast, although peripupillary injection and intravitreal injection demonstrated therapeutic effects, their improvements were relatively limited, and both had a higher incidence of complications. Therefore, posterior scleral injection may represent a superior treatment for RVO-ME.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

Background Work-related musculoskeletal disorders (WMSDs) are a major occupational health concern, particularly among workers exposed to adverse ergonomic conditions. Manganese production involves heavy physical demands, yet research on WMSDs among manganese workers remains limited. Objective To investigate the prevalence and influencing factors of WMSDs among manganese workers in a manganese enterprise in Guangxi. Methods A cross-sectional survey was conducted from May to June 2024 on workers at a manganese factory in Guangxi. The Chinese Musculoskeletal Disorders Questionnaire was used to collect information on demographic characteristics, distribution of musculoskeletal symptoms, and work-related exposures. χ² test was applied to compare differences in positive WMSDs rates across groups, and logistic regression analysis was performed to identify associated factors. Results A total of 1476 workers were enrolled in the study after pre-determined inclusion and exclusion criteria. The overall prevalence of WMSDs was 34.15%. The most commonly affected body regions were the lower back (17.28%), neck (16.67%), and shoulders (13.82%). The results of logistic regression analysis indicated that female, older age, and education level of college or above were associated with a higher risk of WMSDs (P<0.05). Awkward working postures were significantly associated with WMSDs in corresponding body regions; in particular, awkward postures of the neck, upper limbs, trunk, and lower limbs were related to an increased risk of WMSDs in multiple body sites (P<0.05). In addition, poor lighting conditions, high workplace temperature, frequent or sustained arm support during work, and high job demands were associated with an increased risk of overall or site-specific WMSDs (P<0.05). Conclusion The high prevalence of WMSDs among manganese workers is closely associated with demographic characteristics, working postures, and work environment and organizational factors. Targeted ergonomic interventions focusing on high-risk body regions and key ergonomic exposures are warranted to reduce the risk of WMSDs among manganese workers.

Cancer remains a leading cause of global mortality, necessitating the development of advanced therapeutic strategies with enhanced efficacy and reduced systemic toxicity. Among promising bioactive agents, lactoferrin (LF)—a multifunctional iron-binding glycoprotein abundantly found in mammalian milk and exocrine secretions—has garnered significant interest for its potent and multifaceted anti-cancer properties. This review provides a comprehensive analysis of the current understanding of LF’s role in oncology, encompassing its structural biology, diverse mechanisms of action, and groundbreaking advancements in its application through nano-engineering. LF exerts anti-tumor effects through multiple pathways, including extracellular action, intracellular action, and immune regulation. It demonstrates a remarkable affinity for cancer cell membranes, binding to overexpressed anionic components such as glycosaminoglycans and sialic acids, as well as to specific receptors including the low-density lipoprotein receptor-related protein-1 (LRP-1). This selective binding facilitates targeted uptake. Upon internalization, LF orchestrates a direct assault by inducing cell-cycle arrest in phases such as G0/G1 or S phase through the modulation of key regulators including cyclins, CDKs, and p53. Furthermore, it promotes programmed cell death via apoptotic pathways, involving caspase activation and downregulation of anti-apoptotic proteins such as survivin. A more recently elucidated mechanism is the induction of ferroptosis, an iron-dependent form of cell death characterized by overwhelming lipid peroxidation. Beyond direct cytotoxicity, LF acts as a potent immunomodulator. It enhances natural killer (NK) cell activity, modulates T-lymphocyte populations, and crucially reprograms tumor-associated macrophages (TAMs) from a pro-tumor M2 state to an anti-tumor M1 state, thereby reversing the immunosuppressive tumor microenvironment (TME). The translation of LF’s potential has been significantly accelerated by nanotechnology. The inherent biocompatibility and natural tumor-targeting capabilities of LF make it an ideal platform for sophisticated drug-delivery systems. This review details various fabrication strategies for LF-based nanoparticles (NPs), including self-assembly, sol-in-oil emulsion, and electrostatic nanocomplexes, among others. Research demonstrates that nano-formulations not only protect LF from degradation but also enhance its bioactivity and anti-cancer potency. More importantly, LF NPs serve as versatile carriers for a wide array of therapeutic agents, including conventional chemotherapeutics, natural compounds, and imaging agents. These engineered systems enable synergistic therapy and facilitate site-specific delivery. Notably, the ability of LF to bind to receptors on the blood-brain barrier (BBB) has been leveraged to develop nano-systems for glioblastoma treatment. Other innovative designs utilize LF to modulate the TME—for instance, by alleviating tumor hypoxia to sensitize cells to radiotherapy and chemotherapy. Despite compelling pre-clinical evidence, the clinical translation of LF and its nano-formulations remains nascent. While early-phase trials have established a favorable safety profile for recombinant human LF, larger Phase III studies have yielded mixed results, underscoring the complexity of its action in humans. Key challenges include enhancing drug targeting, optimizing loading efficiency, ensuring batch-to-batch reproducibility, and achieving deep tumor penetration. Future research must focus on the rational design of next-generation LF-NPs. This entails developing standardized manufacturing protocols, engineering “smart” stimuli-responsive systems for targeted drug release in the TME, and constructing multi-targeting platforms. A concerted interdisciplinary effort is paramount to bridge the gap between bench and bedside. In conclusion, LF, particularly in its nano-engineered forms, represents a highly promising and versatile agent in the oncological arsenal, holding immense potential for precise and effective cancer therapy.

Cancer remains a leading cause of global mortality, necessitating the development of advanced therapeutic strategies with enhanced efficacy and reduced systemic toxicity. Among promising bioactive agents, lactoferrin (LF)—a multifunctional iron-binding glycoprotein abundantly found in mammalian milk and exocrine secretions—has garnered significant interest for its potent and multifaceted anti-cancer properties. This review provides a comprehensive analysis of the current understanding of LF’s role in oncology, encompassing its structural biology, diverse mechanisms of action, and groundbreaking advancements in its application through nano-engineering. LF exerts anti-tumor effects through multiple pathways, including extracellular action, intracellular action, and immune regulation. It demonstrates a remarkable affinity for cancer cell membranes, binding to overexpressed anionic components such as glycosaminoglycans and sialic acids, as well as to specific receptors including the low-density lipoprotein receptor-related protein-1 (LRP-1). This selective binding facilitates targeted uptake. Upon internalization, LF orchestrates a direct assault by inducing cell-cycle arrest in phases such as G0/G1 or S phase through the modulation of key regulators including cyclins, CDKs, and p53. Furthermore, it promotes programmed cell death via apoptotic pathways, involving caspase activation and downregulation of anti-apoptotic proteins such as survivin. A more recently elucidated mechanism is the induction of ferroptosis, an iron-dependent form of cell death characterized by overwhelming lipid peroxidation. Beyond direct cytotoxicity, LF acts as a potent immunomodulator. It enhances natural killer (NK) cell activity, modulates T-lymphocyte populations, and crucially reprograms tumor-associated macrophages (TAMs) from a pro-tumor M2 state to an anti-tumor M1 state, thereby reversing the immunosuppressive tumor microenvironment (TME). The translation of LF’s potential has been significantly accelerated by nanotechnology. The inherent biocompatibility and natural tumor-targeting capabilities of LF make it an ideal platform for sophisticated drug-delivery systems. This review details various fabrication strategies for LF-based nanoparticles (NPs), including self-assembly, sol-in-oil emulsion, and electrostatic nanocomplexes, among others. Research demonstrates that nano-formulations not only protect LF from degradation but also enhance its bioactivity and anti-cancer potency. More importantly, LF NPs serve as versatile carriers for a wide array of therapeutic agents, including conventional chemotherapeutics, natural compounds, and imaging agents. These engineered systems enable synergistic therapy and facilitate site-specific delivery. Notably, the ability of LF to bind to receptors on the blood-brain barrier (BBB) has been leveraged to develop nano-systems for glioblastoma treatment. Other innovative designs utilize LF to modulate the TME—for instance, by alleviating tumor hypoxia to sensitize cells to radiotherapy and chemotherapy. Despite compelling pre-clinical evidence, the clinical translation of LF and its nano-formulations remains nascent. While early-phase trials have established a favorable safety profile for recombinant human LF, larger Phase III studies have yielded mixed results, underscoring the complexity of its action in humans. Key challenges include enhancing drug targeting, optimizing loading efficiency, ensuring batch-to-batch reproducibility, and achieving deep tumor penetration. Future research must focus on the rational design of next-generation LF-NPs. This entails developing standardized manufacturing protocols, engineering “smart” stimuli-responsive systems for targeted drug release in the TME, and constructing multi-targeting platforms. A concerted interdisciplinary effort is paramount to bridge the gap between bench and bedside. In conclusion, LF, particularly in its nano-engineered forms, represents a highly promising and versatile agent in the oncological arsenal, holding immense potential for precise and effective cancer therapy.

Alzheimer’s disease (AD) is a central neurodegenerative disease characterized by progressive cognitive decline and memory impairment in clinical. Currently, there are no effective treatments for AD. In recent years, a variety of therapeutic approaches from different perspectives have been explored to treat AD. Although the drug therapies targeted at the clearance of amyloid β-protein (Aβ) had made a breakthrough in clinical trials, there were associated with adverse events. Neuroinflammation plays a crucial role in the onset and progression of AD. Continuous neuroinflammatory was considered to be the third major pathological feature of AD, which could promote the formation of extracellular amyloid plaques and intracellular neurofibrillary tangles. At the same time, these toxic substances could accelerate the development of neuroinflammation, form a vicious cycle, and exacerbate disease progression. Reducing neuroinflammation could break the feedback loop pattern between neuroinflammation, Aβ plaque deposition and Tau tangles, which might be an effective therapeutic strategy for treating AD. Traditional Chinese herbs such as Polygonum multiflorum and Curcuma were utilized in the treatment of AD due to their ability to mitigate neuroinflammation. Non-steroidal anti-inflammatory drugs such as ibuprofen and indomethacin had been shown to reduce the level of inflammasomes in the body, and taking these drugs was associated with a low incidence of AD. Biosynthetic nanomaterials loaded with oxytocin were demonstrated to have the capability to anti-inflammatory and penetrate the blood-brain barrier effectively, and they played an anti-inflammatory role via sustained-releasing oxytocin in the brain. Transplantation of mesenchymal stem cells could reduce neuroinflammation and inhibit the activation of microglia. The secretion of mesenchymal stem cells could not only improve neuroinflammation, but also exert a multi-target comprehensive therapeutic effect, making it potentially more suitable for the treatment of AD. Enhancing the level of TREM2 in microglial cells using gene editing technologies, or application of TREM2 antibodies such as Ab-T1, hT2AB could improve microglial cell function and reduce the level of neuroinflammation, which might be a potential treatment for AD. Probiotic therapy, fecal flora transplantation, antibiotic therapy, and dietary intervention could reshape the composition of the gut microbiota and alleviate neuroinflammation through the gut-brain axis. However, the drugs of sodium oligomannose remain controversial. Both exercise intervention and electromagnetic intervention had the potential to attenuate neuroinflammation, thereby delaying AD process. This article focuses on the role of drug therapy, gene therapy, stem cell therapy, gut microbiota therapy, exercise intervention, and brain stimulation in improving neuroinflammation in recent years, aiming to provide a novel insight for the treatment of AD by intervening neuroinflammation in the future.

Objective To discuss the efficacy of transcatheter arterial chemoembolization(TACE)in combination with targeted therapy and immune checkpoint inhibitors for advanced hepatocellular carcinoma(HCC),and to identify the influencing factors.Methods A total of 60 patients with advanced HCC,who were admitted to the Air Force Medical Center of China from January 2016 to December 2022,were enrolled in this study.Thirty patients received TACE combined with targeted therapy and immune checkpoint inhibitors(TACE-L-P group),and the other 30 patients received TACE combined with targeted therapy(TACE-L group).The progression-free survival(PFS),overall survival(OS),disease control rate(DCR),and objective response rate(ORR)were compared between the two groups.Results In the TACE-L group and TACE-L-P group,the median PFS(mPFS)was 7 months and 10 months respectively(P=0.011),the median OS(mOS)was 15.5 months and 29 months respectively(P=0.014).Child-Pugh class B(HR=3.89,95％CI:1.27-11.94,P=0.018)and Barcelona Clinic Liver Cancer(BCLC)stage C(HR=2.83,95％CI:1.32-6.03,P=0.007)were the independent risk factors for OS,while micro wave ablation(HR=0.21,95％CI:0.07-0.63,P=0.005)and TACE-L-P(HR=0.09,95％CI:0.03-0.3,P=0.001)were the independent protection factors for OS.Besides,elevated bilirubin level(HR=1.03,95％CI:1-1.06,P=0.032)and elevated gamma-glutamyl transferase(GGT)level(HR=1.01,95％CI:1-1.01,P=0.002)were the independent risk factors for disease progression,and TACE-L-P(HR=0.27,95％CI:0.09-0.79,P=0.017)was the independent protection factor for disease progression.The ORR and DCR in TACE-L-P group were remarkably higher than those in TACE-L group,which were 43.4％vs 13.3％and 63.4％vs 23.3％respectively,the differences between the two groups were statistically significant(both P＜0.05).Conclusion In treating advanced HCC,TACE combined with targeted therapy and immune checkpoint inhibitors is superior to TACE combined with targeted therapy in therapeutic efficacy.

Objective To investigate the predictive value of atherosclerotic index of plasma(AIP)for the risk of coronary heart disease(CHD)in patients with nonalcoholic fatty liver disease(NAFLD).Methods A retrospective analysis was conducted in 299 patients with NAFLD.Based on presence or absence of CHD,the patients were divided into NAFLD with CHD group(n=177)and NAFLD group(n=122).Clinical data were collected from both groups,and AIP was calculat-ed.Multivariate Logistic regression analysis was performed to explore the independent risk factors for CHD in patients with NAFLD.Receiver operating characteristic(ROC)curves were plotted to evalu-ate the predictive value of AIP for the risk of CHD in patients with NAFLD.Results The NAFLD with CHD group had a higher proportion of males,smokers,and higher levels of alanine aminotrans-ferase(ALT),aspartate aminotransferase(AST),fasting plasma glucose(FPG),triglycerides(TG),low-density lipoprotein cholesterol(LDL-C),γ-glutamyltransferase(GGT),uric acid(UA),and AIP than the NAFLD group.The NAFLD with CHD group also had lower levels of high-density lipoprotein cholesterol(HDL-C)than the NAFLD group(P＜0.05).Multivariate Logistic regression analysis revealed that males(OR=2.548,95％CI,1.402 to 4.632,P=0.002),high levels of AST(OR=1.038,95％CI,1.002 to 1.077,P=0.041),high levels of LDL-C(OR=1.811,95％CI,1.242 to 2.640,P=0.002),and high AIP(OR=16.117,95％CI,1.874 to 138.609,P=0.011)were independent risk factors for CHD in patients with NAFLD(P＜0.05).ROC curve analysis showed that AIP had an area under the curve of 0.746(95％CI,0.688 to 0.804)for pre-dicting CHD in patients with NAFLD,with a sensitivity of 76.3％and a specificity of 73.0％.Conclusion AIP is an independent influencing factor for CHD in patients with NAFLD and has certain predictive value for the risk of CHD in these patients.

Objective:To analyze the registration status of clinical trials related to contraceptives based on the data of World Health Organization International Clinical Trials Registry Platform (ICTRP), so as to understand the situation of contraceptives development, and provide reference for improving the quality of clinical trials.Methods:All records in the database of ICTRP before January 1, 2025 was researched to screen out contraceptives clinical trials, and the registration time, registration platform, regional distribution, trial design and research content were analyzed.Results:A total of 206 clinical trials related to contraceptives were included. The projects were mainly carried out in the United States, Germany, and India. About 95.63% (197/206) of the study subjects were women of reproductive age. The　main　type　of　study　was　intervention [89.32% (184/206)], among which random trials accounted for 53.26% (98/184), and parallel group trials were the most common [82.65% (81/98)]. Over 64.56% (133/206) of the trials were indicated with open-label. Most of the clinical trials were in phase Ⅲ [47.57% (98/206)] and phase Ⅳ [16.50% (34/206)]. The interventions in female studies were mainly in three aspects: oral contraceptive [42.64% (84/197)], intrauterine delivery [15.23% (30/197)], and vaginal delivery [15.23% (30/197)], and the primary outcome included pregnancy rate [54.82% (108/197)], adverse drug reactions [13.20% (26/197)], ovulation inhibition [8.63% (17/197)], and vaginal infection [4.06% (8/197)].Conclusion:The　clinical　trials　of contraceptives were unevenly distributed, the research types were mainly randomized interventional trials, the included participants were mainly women of reproductive age, the intervention measures were mostly oral contraceptive, intrauterine delivery and vaginal delivery.