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.

Diterpenoid ferruginol is a key intermediate in biosynthesis of active ingredients such as tanshinone and carnosic acid.However, the traditional process of obtaining ferruginol from plants is often cumbersome and inefficient. In recent years, the increasingly developing gene editing technology has been gradually applied to the heterologous production of natural products, but the production of ferruginol in microbe is still very low, which has become an obstacle to the efficient biosynthesis of downstream chemicals, such as tanshinone. In this study, miltiradiene was produced by integrating the shortened diterpene synthase fusion protein,and the key genes in the MVA pathway were overexpressed to improve the yield of miltiradiene. Under the shake flask fermentation condition, the yield of miltiradiene reached about(113. 12±17. 4)mg·L~(-1). Subsequently, this study integrated the ferruginol synthase Sm CYP76AH1 and Sm CPR1 to reconstruct the ferruginol pathway and thereby realized the heterologous synthesis of ferruginol in Saccharomyces cerevisiae. The study selected the best ferruginol synthase(Il CYP76AH46) from different plants and optimized the expression of pathway genes through redox partner engineering to increase the yield of ferruginol. By increasing the copy number of diterpene synthase, CYP450, and CPR, the yield of ferruginol reached(370. 39± 21. 65) mg·L~(-1) in the shake flask, which was increased by 21. 57-fold compared with that when the initial ferruginol strain JMLT05 was used. Finally, 1 083. 51 mg·L~(-1) ferruginol was obtained by fed-batch fermentation, which is the highest yield of ferruginol from biosynthesis so far. This study provides not only research ideas for other metabolic engineering but also a platform for the construction of cell factories for downstream products.
Saccharomyces cerevisiae/genetics* ; Diterpenes/metabolism* ; Metabolic Engineering ; Fermentation ; Abietanes

OBJECTIVE: To explore the mechanism of colon dialysis with Yishen Decoction (YS) in improving the autophagy disorder of intestinal epithelial cells in chronic renal failure (CRF) in vivo and in vitro. METHODS: Thirty male SD rats were randomly divided into normal, CRF, and colonic dialysis with YS groups by a random number table method (n=10). The CRF model was established by orally gavage of adenine 200 mg/(kg•d) for 4 weeks. CRF rats in the YS group were treated with colonic dialysis using YS 20 g/(kg•d) for 14 consecutive days. The serum creatinine (SCr) and urea nitrogen (BUN) levels were detected by enzyme-linked immunosorbent assay. Pathological changes of kidney and colon tissues were observed by hematoxylin and eosin staining. Autophagosome changes in colonic epithelial cells was observed with electron microscopy. In vitro experiments, human colon cancer epithelial cells (T84) were cultured and divided into normal, urea model (74U), YS colon dialysis, autophagy activator rapamycin (Ra), autophagy inhibitor 3-methyladenine (3-MA), and SIRT1 activator resveratrol (Re) groups. RT-PCR and Western blot were used to detect the mRNA and protein expressions of zonula occludens-1 (ZO-1), Claudin-1, silent information regulator sirtuin 1 (SIRT1), LC3, and Beclin-1 both in vitro and in vivo. RESULTS: Colonic dialysis with YS decreased SCr and BUN levels in CRF rats (P<0.05), and alleviated the pathological changes of renal and colon tissues. Expressions of SIRT1, ZO-1, Claudin-1, Beclin-1, and LC3II/I were increased in the YS group compared with the CRF group in vivo (P<0.05). In in vitro study, compared with normal group, the expressions of SIRT1, ZO-1, and Claudin-1 were decreased, and expressions of Beclin-1, and LC3II/I were increased in the 74U group (P<0.05). Compared with the 74U group, expressions of SIRT1, ZO-1, and Claudin-1 were increased, whereas Beclin-1, and LC3II/I were decreased in the YS group (P<0.05). The treatment of 3-MA and rapamycin regulated autophagy and the expression of SIRT1. SIRT1 activator intervention up-regulated autophagy as well as the expressions of ZO-1 and Claudin-1 compared with the 74U group (P<0.05). CONCLUSION Colonic dialysis with YS could improve autophagy disorder and repair CRF intestinal mucosal barrier injury by regulating SIRT1 expression in intestinal epithelial cells.
Animals ; Sirtuin 1/metabolism* ; Drugs, Chinese Herbal/therapeutic use* ; Autophagy/drug effects* ; Male ; Intestinal Mucosa/drug effects* ; Rats, Sprague-Dawley ; Epithelial Cells/metabolism* ; Colon/drug effects* ; Humans ; Kidney Failure, Chronic/drug therapy* ; Signal Transduction/drug effects* ; Renal Dialysis ; Rats ; Kidney/drug effects*

OBJECTIVE: As an age-related neurodegenerative disease, the prevalence of mild cognitive impairment (MCI) increases with age. Within the framework of traditional Chinese medicine, spleen-kidney deficiency syndrome (SKDS) is recognized as the most frequent MCI subtype. Due to the covert and gradual onset of MCI, in community settings it poses a significant challenge for patients and their families to discern between typical aging and pathological changes. There exists an urgent need to devise a preliminary diagnostic tool designed for community-residing older adults with MCI attributed to SKDS (MCI-SKDS). METHODS: This investigation enrolled 312 elderly individuals diagnosed with MCI, who were randomly distributed into training and test datasets at a 3:1 ratio. Five machine learning methods, including logistic regression (LR), decision tree (DT), naive Bayes (NB), support vector machine (SVM), and gradient boosting (GB), were used to build a diagnostic prediction model for MCI-SKDS. Accuracy, sensitivity, specificity, precision, F1 score, and area under the curve were used to evaluate model performance. Furthermore, the clinical applicability of the model was evaluated through decision curve analysis (DCA). RESULTS: The accuracy, precision, specificity and F1 score of the DT model performed best in the training set (test set), with scores of 0.904 (0.845), 0.875 (0.795), 0.973 (0.875) and 0.973 (0.875). The sensitivity of the training set (test set) of the SVM model performed best among the five models with a score of 0.865 (0.821). The area under the curve of all five models was greater than 0.9 for the training dataset and greater than 0.8 for the test dataset. The DCA of all models showed good clinical application value. The study identified ten indicators that were significant predictors of MCI-SKDS. CONCLUSION The risk prediction index derived from machine learning for the MCI-SKDS prediction model is simple and practical; the model demonstrates good predictive value and clinical applicability, and the DT model had the best performance. Please cite this article as: Ai YT, Zhou S, Wang M, Zheng TY, Hu H, Wang YC, Li YC, Wang XT, Zhou PJ. Development of a machine learning-based risk prediction model for mild cognitive impairment with spleen-kidney deficiency syndrome in the elderly. J Integr Med. 2025; 23(4): 390-397.
Humans ; Cognitive Dysfunction/diagnosis* ; Aged ; Male ; Female ; Machine Learning ; Spleen ; Aged, 80 and over ; Kidney ; Medicine, Chinese Traditional

Alzheimer's disease(AD)is a common neurodegenerative disease in the elderly.Increasing evidence shows that peripheral immune cells are involved in the occurrence and development of AD.Both gut microbiota dysbiosis and abnormalities of peripheral immune cells occur in the early stage of AD.The gut microbiota can influence the central nervous system through mechanisms such as the gut-brain axis and the regulatory effects on peripheral immune cells.AD treatment methods targeting the gut microbiota and immune cells have been receiving increasing attention.This review summarizes the regulatory effects and mechanisms of the gut microbiota on peripheral immune cells,as well as the research progress on the gut microbiota's roles in the occurrence and development of AD,aiming to provide new ideas for relevant research on the prevention,diagnosis,and treatment of AD.

Objective To investigate the status of population dynamics and distribution changes of Aedes aegypti in Guangdong Province.Methods Continuous monitoring was conducted from May 2018 to July 2024 in Wushi Town and Qishui Town,Leizhou City,Zhanjiang City,Guangdong Province.Additionally,a survey of the distribution of Ae.aegypti along the Leizhou Peninsula coast was carried out.Results The density of Ae.aegypti in Zhanjiang showed a gradual decline from 2018 to 2024.The last detection of adult Ae.aegypti in Wushi Town was in September 2021,and the last larva was found in October 2023.No Ae.aegypti was detected in Qishui Town during surveys from 2021 to 2024.A survey of 18 coastal villages in the Leizhou Peninsula revealed no detections of Ae.aegypti.Conclusions This study provides a basis for understanding the distribution and population density fluctuations of Ae.aegypti,assessing its invasion risk,and scientifically conducting relevant prevention and control efforts.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.

Celastrol and wilforlide A are the main active triterpenoids of the traditional Chinese medicine Lei Gong Teng, which have anti-tumour, anti-inflammatory and immunosuppressive activities, and are the material basis for the clinical efficacy of Lei Gong Teng-related Chinese medicinal preparations. By analysing the biosynthetic pathway of active ingredients, optimizing genetic elements and utilizing "cell factory" to produce triterpenoids heterologously will be an effective way to obtain from Tripterygium wilfordii in the future in a "low-cost and high-efficient" manner. CYP712Ks are the first cytochrome P450s involved in the skeleton modification of friedelane-type and oleanane-type triterpenoids in T. wilfordii, and they can catalyse the generation of polpunonic acid from friedelin and 3-epi-katonic acid from β-amyrin by carboxylation at C-29 position. In this study, four multifunctional TwCYP712K1/2/3/5 were used to clarify the catalytic function and substrate selection preference using in vivo functional characterization in Saccharomyces cerevisiae. The spatial structure of the protein-substrate binding was clarified through homology modeling and molecular docking, and then the differential amino acids in the active pocket of the protein were mutated to clarify the crucial amino acids determining the catalytic function and the selection of substrate structure. A total of 63 mutant elements were constructed, and the amino acid sites affecting the carboxylation function of TwCYP712Ks were analyzed. In particular, the key amino acids affecting the substrate selectivity of TwCYP712K2 towards oleanane-type and friedelane-type triterpenoids were revealed and the TwCYP712K2^F127I and TwCYP712K2^A227T mutants would result in a reversal of the product ratio. In conclusion, four proteins of TwCYP712Ks were semi-rationally designed by homologous protein alignment and mutual mutation to elucidate multiple amino acid sites determining the catalytic function of the proteins, and a series of activity-enhancing or altering mutants were obtained, which provide abundant catalytic elements for the biosynthesis of active triterpenoids from T. wilfordii, and the mechanism of carboxylation in the C-29 position was initially elucidated.

Combined radiation and burn injury (CRBI) is a severe syndrome, which is induced by the simultaneous or successive radiation and burn; but no appropriate clinical therapies are available. Loong oil (LO) is a traditional Chinese medicine oil composed of the oil extracts of cuttlebone, safflower, walnut oil, and rapeseed oil, which has been demonstrated to own anti-radiation and tissue healing functions. In this study, glyceryl monostearate (GMO) was used for the preparation of lyotropic liquid crystals that loaded LO to obtain Loong oil-lyotropic liquid crystals (LOL) for the treatment of skin CRBI. The hexagonal phase structure of LOL was proved by small X-ray scattering (SAXS) analysis with an approximate 7:9:11 ratio of peaks and under the polarizing microscope with the birefringence phenomenon. LOL had a high LO loading capacity (4%) and good bio-adhesive force, favoring skin administration. Animal experiments were approved by the Ethics Committee of the Beijing Institute of Radiation Medicine, Academy of Military Medical Sciences and the experiments were conducted in accordance with relevant guidelines and regulations (approval number: IACUC-DWZX-2022-834). Compared to triethanolamine creams, LOL had higher skin permeability with total skin penetration within 1 h, benefiting the treatment of deep CRBI. A deep II degree burn CRBI mouse model was established after whole-body irradiation with 5 Gy ⁶⁰Co γ-ray and the next 6-second 100 ℃ burn injury. LOL promoted LO skin penetration, improved epithermal cell proliferation and the formation of hair follicles, accelerated wound healing, and inhibited scarring, which benefitted the therapy of CRBI. In this study, LO application fields are expanded and LO is a promising medication for the treatment of CRBI.

Objective To compare the effects of 20 mg qd and 10 mg bidadministration of iprrazole enteric-coated tablets on the control of gastric acid in healthy subjects.Methods A randomized,single-center,parallel controlled trial was designed to include 8 healthy subjects.Randomly divided into 2 groups,20 mg qd administration group:20 mg enteric-coated tablets of iprrazole in the morning;10 mg bid administration group:10 mg enteric-coated tablets of iprrazole in the morning and 10 mg in the evening.The pH values in the stomach of the subjects before and 24 h after administration were monitored by pH meter.The plasma concentration of iprazole after administration was determined by HPLC-MS/MS.The main pharmacokinetic parameters were calculated by Phoenix WinNonlin(V8.0)software.Results The PK parameters of iprrazole enteric-coated tablets and reference preparations in fasting group were as follows:The Cmax of 20 mg qd group and 10 mg bid group were(595.75±131.15)and(283.50±96.98)ng·mL-1;AUC0-t were(5 531.94±784.35)and(4 686.67±898.23)h·ng·mL-1;AUC0-∞ were(6 003.19±538.59)and(7 361.48±1 816.77)h·ng·mL-1,respectively.The mean time percentage of gastric pH＞3 after 20 mg qd and 10 mg bid were 82.64％and 61.92％,and the median gastric pH within 24 h were 6.25±1.49 and 3.53±2.05,respectively.The mean gastric pH values within 24 h were 5.71±1.36 and 4.23±1.45,respectively.The correlation analysis of pharmacokinetic/pharmacodynamics showed that there was no significant correlation between the peak concentration of drug in plasma and the inhibitory effect of acid.Conclusion Compared with the 20 mg qd group and the 10 mg bid group,the acid inhibition effect is better,the administration times are less,and the safety of the two administration regimes is good.