OBJECTIVE To explore the pharmacokinetic characteristics of 3 blood-absorbed components of Xiangshao sanjie oral liquid in rats with hyperplasia of mammary gland （HMG）. METHODS Female SD rats were divided into control group and HMG group according to body weight， with 6 rats in each group. The HMG group was given estrogen+progesterone to construct HMG model. After modeling， two groups were given 1.485 g/kg of Xiangshao sanjie oral liquid （calculated by crude drug） intragastrically， once a day， for 7 consecutive days. Blood samples were collected before the first administration （0 h）， and at 5， 15， 30 minutes and 1， 2， 4， 8， 12， 24 hours after the last administration， respectively. Using chlorzoxazone as the internal standard， the plasma concentrations of ferulic acid， paeoniflorin and rosmarinic acid in rats were detected by UPLC-Q/TOF-MS. The pharmacokinetic parameters [area under the drug time curve （AUC0－24 h， AUC0－∞）， mean residence time （MRT0－∞）， half-life （t1/2）， peak time （tmax）， peak concentration （cmax）] were calculated by the non-atrioventricular model using Phoenix WinNonlin 8.1 software. RESULTS Compared with the control group， the AUC0－24 h， AUC0－∞ and cmax of ferulic acid in the HMG group were significantly increased （P＜0.05）； the AUC0－24 h， AUC0－∞ ， MRT0－∞ ， t1/2 and cmax of paeoniflorin increased， but there was no significant difference between 2 groups （P＞0.05）； the AUC0－24 h and MRT0-∞ of rosmarinic acid were significantly increased or prolonged （P＜0.05）. C ONCLUSIONS In HMG model rats， the exposure of ferulic acid， paeoniflorin and rosmarinic acid in Xiangshao sanjie oral liquid all increase， and the retention time of rosmarinic acid is significantly prolonged.

OBJECTIVE To establish management index system for rational drug use of key monitoring drugs， and provide reference for the management of key monitoring drugs in the hospitals. METHODS First， the management index system for rational drug use of key monitoring drugs was drafted by collecting the evidence from related medical literature. Next， using a modified Delphi method， twenty experienced experts from the fields of pharmacy， medical practice， healthcare insurance， and finance were selected to participate in two rounds of questionnaire consultations. Based on the expert enthusiasm coefficient， authority coefficient， degree of opinion concentration， and degree of coordination， the final indicators were determined to establish a management index system for rational drug use of key monitored drugs in medical institutions. RESULTS The expert enthusiasm coefficients reached 100% in both rounds of consultation. In first-level， second-level and third-level indicators， the authority coefficients of experts were 0.89， 0.86 and 0.87， and coordination coefficients of the experts in importance score were 0.300 （P＜ 0.05）， 0.125 （P＜0.05） and 0.139 （P＜0.05）， respectively. The average score for the importance of all indicators reached over 3.5， in which the full score ratio ranged from 35% to 100%. Except that the variation coefficient of a third-level indicator “number of specifications purchased for key monitored drugs” was 0.26， the variation coefficients of rest indicators were less than or equal to 0.25. Based on the results of expert consultation， final version of the management index system established in this study， including two first-level indicators （drug procurement and use， and rational drug use）， five second-level indicators （such as the accessibility， cost-effectiveness） and twenty third-level indicators （such as the number of specifications purchased for key monitored drugs， the increase in the cost of key monitored drugs）. CONCLUSIONS The management index system established in this study possesses high reliability and strong operability， and may provide a reference for the management of key monitoring drugs in the hospitals.

Biomolecular condensates are formed through phase separation of biomacromolecules such as proteins and RNAs. These condensates exhibit liquid-like properties that can futher transition into more stable material states. They form complex internal structures via multivalent weak interactions, enabling precise spatiotemporal regulations. However, the use of inconsistent and non-standardized terminology has become increasingly problematic, hindering academic exchange and the dissemination of scientific knowledge. Therefore, it is necessary to discuss the terminology related to biomolecular condensates in order to clarify concepts, promote interdisciplinary cooperation, enhance research efficiency, and support the healthy development of this field.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

ObjectiveThe traditional Chinese medicine Strychnos nux-vomica L. (SN) has the clinical effect of reducing swelling and relieving pain; however, SN is toxic due to its alkaloid components. Little is known about the endogenous metabolic changes induced by SN toxicity in rats and their potential effects on the metabolic dysregulation of intestinal microbiota. Therefore, toxicological investigation of SN is of great significance to its safety assessment. In this study, the toxic mechanisms of SN were explored using a combination of metabonomics and 16S rRNA gene sequencing. MethodsThe toxic dose, intensity, and target organ of SN were determined in rats using acute, cumulative, and subacute toxicity tests. UHPLC-MS was used to analyze the serum, liver, and renal samples of rats after intragastric SN administration. The decision tree and K Nearest Neighbor (KNN) model were established based on the bootstrap aggregation (bagging) algorithm to classify the omics data. After samples were extracted from rat feces, the high-throughput sequencing platform was used to analyze the 16S rRNA V3-V4 region of bacteria. ResultsThe bagging algorithm improved the accuracy of sample classification. Twelve biomarkers were identified, where their metabolic dysregulation may be responsible for SN toxicity in vivo. Several types of bacteria such as Bacteroidetes, Anaerostipes, Oscillospira and Bilophila, were demonstrated to be closely related to physiological indices of renal and liver function, indicating that SN-induced liver and kidney damage may be related to the disturbance of these intestinal bacteria. ConclusionThe toxicity mechanism of SN was revealed in vivo, which provides a scientific basis for the safe and rational clinical use of SN.

Through a compound induction method, combined with neurobehavioral, macroscopic characterization and objective pathological evaluation indicators, a murine depression model of liver depression transforming into fire syndrome was constructed and confirmed. The model was constructed using a combination of sleep deprivation, light exposure, and alternate-day food deprivation. Evaluation was conducted at three levels: face validity, constructs validity, and predictive validity. The establishment of the liver depression transforming into fire syndrome depression model was further validated through the counterproof of traditional Chinese medicine formulas. In terms of face validity, compared to the control group, mice in the model group exhibited typical depressive symptoms in neurobehavioral assessments; the general observation of the model group mice reveals disheveled and lackluster fur, along with delayed and easily agitated responses. Additionally, there is a substantial increase in water consumption. In the sleep phase detection of mouse, the model group showed a significant increase in the proportion of time spent in the wake phase during sleep, accompanied by a significant decrease in the proportions of time spent in both non-rapid eye movement (NREM) and rapid eye movement (REM) sleep phases. There are significant differences in physiological indicators such as average blood flow velocity, blood flow rate, tongue, urine, and claw color (r values) in the internal carotid artery. Structural validity demonstrated that levels of 5-hydroxytryptamine (5-HT), dopamine (DA), and γ-aminobutyric acid (GABA) in the hippocampus of model mice decreased significantly, while acetylcholine (ACh), tryptophan (Try), and glutamic acid (Glu) levels increased significantly. Treatment with Danzhi Xiaoyao San led to varying degrees of restoration in the aforementioned neurotransmitters. In terms of predictive validity, the antidepressant paroxetine effectively ameliorated depressive behaviors in the model mice, and the classic formula Danzhi Xiaoyao San demonstrated varying degrees of improvement in depression-related indicators. In conclusion, this study has established a novel animal model of liver-stagnation with the fire depression, thereby expanding the repertoire of traditional Chinese medicine depression models. This development contributes to the diversification of melancholic syndrome models in Chinese medicine, offering a broader spectrum of options for scientific exploration, efficacy evaluation, and drug screening in the future prevention and treatment of depression with traditional Chinese medicine. Animal experiments were conducted with the approval and supervision of the Animal Ethics Committee of Jiangxi University of Traditional Chinese Medicine (ethics number: 20230313040).

Objective To investigate the application value of MRI three-dimensional reconstruction techniques in the identification of offending vessels and affected nerves in cranial neurovascular compression syndrome.Methods A total of 91 patients with trigeminal neuralgia and 72 patients with hemifacial spasm underwent FIESTA and TOF-MRA scanning before microvascular decompression.Two-dimensional and three-dimensional reconstruction techniques(curved planar reconstruction and MR virtual endoscopy)were respectively performed using the original MRI data so as to evaluate the number and category of offending vessels and the degree of compression on cranial nerves.The results of imaging diagnosis were compared with the observations during neurosurgery.Results The correct identification rate of the offending vessels in trigeminal neuralgia was 95.6％by 3D reconstruction technique,with 94.5％diagnostic accuracy of neurovascular compression.In addition,the accurate identification rate was 91.7％on the detection of the offending vessels in hemifacial spasm,with 89.5％accuracy of the judgment on neurovascular compression.It should be noted that the diagnostic accuracy for the simple contact between the offending blood vessels and the cranial nerves using 3D reconstruction was significantly higher than that of the evaluation through 2D observation(P＜0.05).Conclusion 3D reconstruction technique can improve the accuracy of offending blood vessels identification and provide more reliable information on the degree of cranial nerve distortion or atrophy.Therefore,3D MRI images are more suitable for investigating the complex neurovascular compression.

In the study of age estimation in living individuals,a lot of data needs to be analyzed by mathematical statistics,and reasonable medical statistical methods play an important role in data design and analysis.The selection of accurate and appropriate statistical methods is one of the key factors af-fecting the quality of research results.This paper reviews the principles and applicable principles of the commonly used medical statistical methods such as descriptive statistics,difference analysis,consistency test and multivariate statistical analysis,as well as machine learning methods such as shallow learning and deep learning in the age estimation research of living individuals,and summarizes the relevance and application prospects between medical statistical methods and machine learning methods.This paper aims to provide technical guidance for the age estimation research of living individuals to obtain more scientific and accurate results.