Objective To conduct a comprehensive review of the risk factors for post-transplant pulmonary infection in kidney transplant recipients. Methods Following the methodology guidelines for systematic reviews, the research question was clearly defined. Systematic searches were conducted in both Chinese and English literature databases, with the search period ranging from the establishment of the database to May 1, 2025. Two researchers independently screened and extracted the risk factors related to post-transplant pulmonary infection in kidney transplant recipients, and the research results were qualitatively described. Results A total of 45 articles were finally included, involving 30 risk factors for post-transplant pulmonary infection in kidney transplant recipients, including five aspects as donor factors, recipient factors, disease factors, treatment factors and laboratory test result factors. Conclusions The occurrence of post-transplant pulmonary infection in kidney transplant recipients is related to donor factors, recipient factors, disease factors, treatment factors and laboratory test result factors, providing a reference for clinical prevention, screening, and intervention.

Objective: To explore whether the long-term and frequent use of citrate anticoagulants negatively affects the bone metabolism balance of female frequent plateletpheresis donors, so as to better protect their health. Methods: A total of 65 female plateletpheresis donors and 55 female whole-blood donors from Guangzhou Blood Center (May to December 2024) were enrolled as experimental and control groups respectively, stratified into age subgroups (18-39 years and 40-60 years). Serum levels of 25-hydroxyvitamin D [25(OH)D], procollagen type I N-terminal propeptide (PINP), osteocalcin (OC), and type I collagen carboxy-terminal telopeptide (CTX) were measured. Differences in bone metabolism markers between experimental and control groups across age subgroups were compared. ANOVA was used to analyze dose-response relationships between donation age, annual apheresis donation frequency, and biochemical indicators. Results: In the 40-60 age subgroup, 25(OH)D levels were significantly lower in the experimental group (P<0.05), exhibiting a linear increase with age and a linear decrease with annual donation frequency. No significant differences in CTX or PINP levels were observed between experimental and control groups in either age subgroup. Conclusion: High-frequency plateletpheresis donation does not disrupt bone metabolic balance in female donors. However, it is associated with reduced vitamin D levels in female donors aged >40 years, potentially increasing the risk of osteoporosis. Vitamin D supplementation is recommended for high-frequency female plateletpheresis donors in this age group.

Background The quality of occupational health technical services is directly linked to the protection of workers' health rights and the efficacy of occupational disease prevention and control. However, the industry still faces critical challenges: sporadic instances of institutional non-compliance and persistent irregularities in professional practice continue to undermine overall service performance. Objective To assess the current quality status of occupational health technical services in Zhejiang Province and propose countermeasures for quality improvement, providing a scientific basis for policy optimization and service delivery quality enhancement. Methods A total of 69 occupational health technical service institutions in Zhejiang Province that obtained formal accreditation as of April 30, 2024, were sampled, including 3 public institutions and 66 private institutions (comprising 3 formerly Class-A, 28 formerly Class-B, 11 formerly Class-C, and 24 newly certified institutions). Following the Technical Protocol for Quality Monitoring of Occupational Health Technical Service in Zhejiang Province and the Technical Protocol for Proficiency Testing of Occupational Health Detection in Zhejiang Province, a quality assessment task force comprising national and provincial experts was established. Evaluation was conducted across four dimensions: qualification maintenance and compliance, standardization of technical services, authenticity of technical services, and proficiency testing, utilizing a combination of document review, on-site inspections, and technical skill assessments. Results The occupational health technical service institutions in Zhejiang Province were predominantly private entities (82.5%), with significant disparities in overall service quality. The pass rates for qualification maintenance and compliance, technical service standardization, technical service authenticity, and the excellence rate for laboratory proficiency testing were 81.5%, 80.7%, 97.3%, and 90.4%, respectively. Regarding qualification maintenance, the pass rates for "environmental conditions" (49.8%, 56.7%) and "instrumentation and equipment" (58.2%、65.6%) were significantly lower for formerly Class-C and newly certified institutions compared to other categories. In terms of technical standardization, "standardized on-site inspections" recorded the lowest pass rate (67.4%), with newly certified institutions at only 48.0%. Regarding technical service authenticity, formerly Class-C institutions exhibited issues such as missing raw chromatograms for blank samples (85.7% pass rate). In laboratory proficiency testing, public and formerly Class-A institutions achieved 100% excellence rates, but the performance of formerly Class-C and newly certified institutions was comparatively weak; specifically, the failure rate for organic analysis in formerly Class-C institutions reached 20%; the failure rate for dust testing items in newly certified institutions was 10.3%. Conclusion The overall quality of occupational health technical services in Zhejiang Province still requires significant improvement, particularly in basic institutional conditions, the standardization of on-site inspections, and laboratory proficiency in organic and dust analysis. Formerly Class-C and newly certified institutions should be the primary focus of quality management efforts. Differentiated regulatory strategies are recommended, alongside strengthening interim and ex-post supervision to gradually enhance the quality of occupational health technical services across all institutions.

OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

Reproductive system diseases are among the primary contributors to the decline in social fertility rates and the intensification of aging, posing significant threats to both physical and mental health, as well as quality of life. Recent research has revealed the substantial potential of the gut microbiota in improving reproductive system diseases. Under healthy conditions, the gut microbiota maintains a dynamic balance, whereas dysfunction can trigger immune-inflammatory responses, metabolic disorders, and other issues, subsequently leading to reproductive system diseases through the gut-gonadal axis. Reproductive diseases, in turn, can exacerbate gut microbiota imbalance. This article reviews the impact of the gut microbiota and its metabolites on both male and female reproductive systems, analyzing changes in typical gut microorganisms and their metabolites related to reproductive function. The composition, diversity, and metabolites of gut bacteria, such as Bacteroides, Prevotella, and Firmicutes, including short-chain fatty acids, 5-hydroxytryptamine, γ-aminobutyric acid, and bile acids, are closely linked to reproductive function. As reproductive diseases develop, intestinal immune function typically undergoes changes, and the expression levels of immune-related factors, such as Toll-like receptors and inflammatory cytokines (including IL-6, TNF-α, and TGF-β), also vary. The gut microbiota and its metabolites influence reproductive hormones such as estrogen, luteinizing hormone, and testosterone, thereby affecting folliculogenesis and spermatogenesis. Additionally, the metabolism and absorption of vitamins can also impact spermatogenesis through the gut-testis axis. As the relationship between the gut microbiota and reproductive diseases becomes clearer, targeted regulation of the gut microbiota can be employed to address reproductive system issues in both humans and animals. This article discusses the regulation of the gut microbiota and intestinal immune function through microecological preparations, fecal microbiota transplantation, and drug therapy to treat reproductive diseases. Microbial preparations and drug therapy can help maintain the intestinal barrier and reduce chronic inflammation. Fecal microbiota transplantation involves transferring feces from healthy individuals into the recipient’s intestine, enhancing mucosal integrity and increasing microbial diversity. This article also delves into the underlying mechanisms by which the gut microbiota influences reproductive capacity through the gut-gonadal axis and explores the latest research in diagnosing and treating reproductive diseases using gut microbiota. The goal is to restore reproductive capacity by targeting the regulation of the gut microbiota. While the gut microbiota holds promise as a therapeutic target for reproductive diseases, several challenges remain. First, research on the association between gut microbiota and reproductive diseases is insufficient to establish a clear causal relationship, which is essential for proposing effective therapeutic methods targeting the gut microbiota. Second, although gut microbiota metabolites can influence lipid, glucose, and hormone synthesis and metabolism via various signaling pathways—thereby indirectly affecting ovarian and testicular function—more in-depth research is required to understand the direct effects of these metabolites on germ cells or granulosa cells. Lastly, the specific efficacy of gut microbiota in treating reproductive diseases is influenced by multiple factors, necessitating further mechanistic research and clinical studies to validate and optimize treatment regimens.

Circadian rhythm is an endogenous biological clock mechanism that enables organisms to adapt to the earth’s alternation of day and night. It plays a fundamental role in regulating physiological functions and behavioral patterns, such as sleep, feeding, hormone levels and body temperature. By aligning these processes with environmental changes, circadian rhythm plays a pivotal role in maintaining homeostasis and promoting optimal health. However, modern lifestyles, characterized by irregular work schedules and pervasive exposure to artificial light, have disrupted these rhythms for many individuals. Such disruptions have been linked to a variety of health problems, including sleep disorders, metabolic syndromes, cardiovascular diseases, and immune dysfunction, underscoring the critical role of circadian rhythm in human health. Among the numerous systems influenced by circadian rhythm, the skin—a multifunctional organ and the largest by surface area—is particularly noteworthy. As the body’s first line of defense against environmental insults such as UV radiation, pollutants, and pathogens, the skin is highly affected by changes in circadian rhythm. Circadian rhythm regulates multiple skin-related processes, including cyclic changes in cell proliferation, differentiation, and apoptosis, as well as DNA repair mechanisms and antioxidant defenses. For instance, studies have shown that keratinocyte proliferation peaks during the night, coinciding with reduced environmental stress, while DNA repair mechanisms are most active during the day to counteract UV-induced damage. This temporal coordination highlights the critical role of circadian rhythms in preserving skin integrity and function. Beyond maintaining homeostasis, circadian rhythm is also pivotal in the skin’s repair and regeneration processes following injury. Skin regeneration is a complex, multi-stage process involving hemostasis, inflammation, proliferation, and remodeling, all of which are influenced by circadian regulation. Key cellular activities, such as fibroblast migration, keratinocyte activation, and extracellular matrix remodeling, are modulated by the circadian clock, ensuring that repair processes occur with optimal efficiency. Additionally, circadian rhythm regulates the secretion of cytokines and growth factors, which are critical for coordinating cellular communication and orchestrating tissue regeneration. Disruptions to these rhythms can impair the repair process, leading to delayed wound healing, increased scarring, or chronic inflammatory conditions. The aim of this review is to synthesize recent information on the interactions between circadian rhythms and skin physiology, with a particular focus on skin tissue repair and regeneration. Molecular mechanisms of circadian regulation in skin cells, including the role of core clock genes such as Clock, Bmal1, Per and Cry. These genes control the expression of downstream effectors involved in cell cycle regulation, DNA repair, oxidative stress response and inflammatory pathways. By understanding how these mechanisms operate in healthy and diseased states, we can discover new insights into the temporal dynamics of skin regeneration. In addition, by exploring the therapeutic potential of circadian biology in enhancing skin repair and regeneration, strategies such as topical medications that can be applied in a time-limited manner, phototherapy that is synchronized with circadian rhythms, and pharmacological modulation of clock genes are expected to optimize clinical outcomes. Interventions based on the skin’s natural rhythms can provide a personalized and efficient approach to promote skin regeneration and recovery. This review not only introduces the important role of circadian rhythms in skin biology, but also provides a new idea for future innovative therapies and regenerative medicine based on circadian rhythms.

The tetraspanins are closely associated with the development and therapeutic prognosis of colorectal tumors. These proteins play a role in cell proliferation, metastasis, and invasion, regulate apoptosis and autophagy of colorectal tumor cells. affect immune escape by releasing exosomes, intervening the epithelial-mesenchymal transition process, and altering the tumor microenvironment, and enhance tumor stemness through specific pathways. This paper reviews the mechanisms and current research regarding the status of tetraspanins in colorectal cancer, aiming to improve early diagnosis and providing valuable insights for treatment strategies.

ObjectiveTo evaluate the efficacy of Shuanghua drink in treating primary dysmenorrhea in the rat model and explore its mechanism of action. MethodsAn oxytocin-induced writhing mouse model was established to evaluate the analgesic effect of Shuanghua drink. Forty-eight non-pregnant female institute of cancer research （ICR） mice were randomly divided into six groups， including a blank group， a model group， an ibuprofen group （85.00 mg·kg^-1）， a low-dose group of Shuanghua drink （7.14 mL·kg^-1）， a medium-dose group of Shuanghua drink （14.28 mL·kg^-1）， and a high-dose group of Shuanghua drink （28.57 mL·kg^-1）. Each group consisted of eight mice. All treatment groups received daily intragastric administration at corresponding doses for 10 consecutive days. One hour after the final administration， 2 U of oxytocin was intraperitoneally injected per mouse. The writhing latency and number of writhing within 20 minutes were recorded. A primary dysmenorrhea rat model was established by using estradiol benzoate and oxytocin to evaluate the inhibitory effect of Shuanghua drink on the contraction of uterine smooth muscle. Forty-eight non-pregnant female Sprague-Dawley （SD） rats were divided into six groups， including a blank group， a model group， an ibuprofen group （51.00 mg·kg^-1）， a low-dose group of Shuanghua drink （4.28 mL·kg^-1）， a medium-dose group of Shuanghua drink （8.57 mL·kg^-1）， and a high-dose group of Shuanghua drink （17.10 mL·kg^-1）. Each group consisted of eight rats. Rats received subcutaneous injections of estradiol benzoate for 10 consecutive days to enhance uterine sensitivity. On the eleventh day， oxytocin （2 U/rat） was intraperitoneally administered to induce abnormal uterine contractions for establishing the primary dysmenorrhea model. All treatment groups received daily intragastric administration from the second day of modeling for 10 days. The effects of Shuanghua drink were evaluated by using parameters including uterine motility and the variation rate of uterine motility. The mechanism of action was investigated in rats with primary dysmenorrhea. The content of prostaglandin F_2α （PGF_2α）， prostaglandin E₂ （PGE₂）， thromboxane B₂ （TXB₂）， prostacyclin metabolite （6-keto-PGF_1α）， and β-endorphin （β-EP） in uterine tissue of rats was detected by using enzyme-linked immunosorbent assay （ELISA）. The changes in the content of nitric oxide （NO） and inducible nitric oxide synthase （iNOS） were analyzed via colorimetric assay. Western blot was performed to determine the content of phosphorylated inhibitor of kappa B kinase beta （p-IKKβ）/IKKβ， phosphorylated inhibitor of kappa B alpha （p-IκBα）， IκBα， phosphorylated p65 （p-p65）， p65， and cyclooxygenase-2 （COX-2） proteins in uterine tissue of rats. ResultsIn the oxytocin-induced writhing mouse model， the model group exhibited significantly shortened writhing latency and increased writhing frequency compared to the control group （P<0.01）. Both the ibuprofen group and the high-dose group of Shuanghua drink displayed prolonged writhing latency （P<0.05）， while the ibuprofen group and the low-dose， medium-dose， and high-dose groups of Shuanghua drink exhibited reduced writhing frequency （P<0.01）. In the primary dysmenorrhea rat model， the uterine motility and its variation rate in the model group were significantly higher than those in the blank group （P<0.01）. These parameters were markedly suppressed by ibuprofen and Shuanghua drink at all tested doses （P<0.01）. For the mechanism of action， the model group showed significantly increased PGF_2α/PGE₂， TXB₂/6-keto-PGF_1α， NO， and iNOS in uterine tissue （P<0.05， P<0.01） and significantly decreased β-EP （P<0.01）. These parameters were significantly attenuated in the ibuprofen group and the low-dose， medium-dose， and high-dose groups of Shuanghua drink. The PGF_2α/PGE₂ （P<0.01）， TXB₂/6-keto-PGF_1α （P<0.01）， NO （medium-dose group P<0.05）， and iNOS （P<0.01） were reduced， and the β-EP （medium-dose group P<0.05） was up-regulated. Compared to the model group， the ibuprofen group and medium-dose group of Shuanghua drink showed significantly increased content of β-EP in the serum of rats （P<0.05）. Compared to the blank group， the model group showed significantly elevated expressions of COX-2， p-IKKβ/IKKβ， p-IκBα/IκBα， and p-p65/p65 proteins （P<0.01） and significantly reduced anti-inflammatory protein IκBα （P<0.05）. Compared to the model group， the ibuprofen group and the low-dose， medium-dose， and high-dose groups of Shuanghua drink showed significantly reduced expressions of COX-2 （P<0.01）， p-IKKβ/IKKβ （P<0.01）， p-IκBα/IκBα （P<0.05， P<0.01）， and p-p65/p65（P<0.01） and up-regulated expression of IκBα protein （P<0.05， P<0.01）. ConclusionShuanghua drink effectively alleviates primary dysmenorrhea through analgesia and suppression of abnormal contractions of uterine smooth muscle. Its mechanism may be mediated by reduced levels of PGF_2α/PGE₂， TXB₂/6-keto-PGF_1α， iNOS， and NO， elevated β-EP level， and inhibited COX-2/NF-κB signaling pathway.

ObjectiveTo evaluate the efficacy of Shuanghua drink in treating primary dysmenorrhea in the rat model and explore its mechanism of action. MethodsAn oxytocin-induced writhing mouse model was established to evaluate the analgesic effect of Shuanghua drink. Forty-eight non-pregnant female institute of cancer research （ICR） mice were randomly divided into six groups， including a blank group， a model group， an ibuprofen group （85.00 mg·kg^-1）， a low-dose group of Shuanghua drink （7.14 mL·kg^-1）， a medium-dose group of Shuanghua drink （14.28 mL·kg^-1）， and a high-dose group of Shuanghua drink （28.57 mL·kg^-1）. Each group consisted of eight mice. All treatment groups received daily intragastric administration at corresponding doses for 10 consecutive days. One hour after the final administration， 2 U of oxytocin was intraperitoneally injected per mouse. The writhing latency and number of writhing within 20 minutes were recorded. A primary dysmenorrhea rat model was established by using estradiol benzoate and oxytocin to evaluate the inhibitory effect of Shuanghua drink on the contraction of uterine smooth muscle. Forty-eight non-pregnant female Sprague-Dawley （SD） rats were divided into six groups， including a blank group， a model group， an ibuprofen group （51.00 mg·kg^-1）， a low-dose group of Shuanghua drink （4.28 mL·kg^-1）， a medium-dose group of Shuanghua drink （8.57 mL·kg^-1）， and a high-dose group of Shuanghua drink （17.10 mL·kg^-1）. Each group consisted of eight rats. Rats received subcutaneous injections of estradiol benzoate for 10 consecutive days to enhance uterine sensitivity. On the eleventh day， oxytocin （2 U/rat） was intraperitoneally administered to induce abnormal uterine contractions for establishing the primary dysmenorrhea model. All treatment groups received daily intragastric administration from the second day of modeling for 10 days. The effects of Shuanghua drink were evaluated by using parameters including uterine motility and the variation rate of uterine motility. The mechanism of action was investigated in rats with primary dysmenorrhea. The content of prostaglandin F_2α （PGF_2α）， prostaglandin E₂ （PGE₂）， thromboxane B₂ （TXB₂）， prostacyclin metabolite （6-keto-PGF_1α）， and β-endorphin （β-EP） in uterine tissue of rats was detected by using enzyme-linked immunosorbent assay （ELISA）. The changes in the content of nitric oxide （NO） and inducible nitric oxide synthase （iNOS） were analyzed via colorimetric assay. Western blot was performed to determine the content of phosphorylated inhibitor of kappa B kinase beta （p-IKKβ）/IKKβ， phosphorylated inhibitor of kappa B alpha （p-IκBα）， IκBα， phosphorylated p65 （p-p65）， p65， and cyclooxygenase-2 （COX-2） proteins in uterine tissue of rats. ResultsIn the oxytocin-induced writhing mouse model， the model group exhibited significantly shortened writhing latency and increased writhing frequency compared to the control group （P<0.01）. Both the ibuprofen group and the high-dose group of Shuanghua drink displayed prolonged writhing latency （P<0.05）， while the ibuprofen group and the low-dose， medium-dose， and high-dose groups of Shuanghua drink exhibited reduced writhing frequency （P<0.01）. In the primary dysmenorrhea rat model， the uterine motility and its variation rate in the model group were significantly higher than those in the blank group （P<0.01）. These parameters were markedly suppressed by ibuprofen and Shuanghua drink at all tested doses （P<0.01）. For the mechanism of action， the model group showed significantly increased PGF_2α/PGE₂， TXB₂/6-keto-PGF_1α， NO， and iNOS in uterine tissue （P<0.05， P<0.01） and significantly decreased β-EP （P<0.01）. These parameters were significantly attenuated in the ibuprofen group and the low-dose， medium-dose， and high-dose groups of Shuanghua drink. The PGF_2α/PGE₂ （P<0.01）， TXB₂/6-keto-PGF_1α （P<0.01）， NO （medium-dose group P<0.05）， and iNOS （P<0.01） were reduced， and the β-EP （medium-dose group P<0.05） was up-regulated. Compared to the model group， the ibuprofen group and medium-dose group of Shuanghua drink showed significantly increased content of β-EP in the serum of rats （P<0.05）. Compared to the blank group， the model group showed significantly elevated expressions of COX-2， p-IKKβ/IKKβ， p-IκBα/IκBα， and p-p65/p65 proteins （P<0.01） and significantly reduced anti-inflammatory protein IκBα （P<0.05）. Compared to the model group， the ibuprofen group and the low-dose， medium-dose， and high-dose groups of Shuanghua drink showed significantly reduced expressions of COX-2 （P<0.01）， p-IKKβ/IKKβ （P<0.01）， p-IκBα/IκBα （P<0.05， P<0.01）， and p-p65/p65（P<0.01） and up-regulated expression of IκBα protein （P<0.05， P<0.01）. ConclusionShuanghua drink effectively alleviates primary dysmenorrhea through analgesia and suppression of abnormal contractions of uterine smooth muscle. Its mechanism may be mediated by reduced levels of PGF_2α/PGE₂， TXB₂/6-keto-PGF_1α， iNOS， and NO， elevated β-EP level， and inhibited COX-2/NF-κB signaling pathway.