ObjectiveTo investigate the mechanism of salt processing of Psoraleae Fructus （PF） through modern analytical techniques and biotechnology， focusing on its effects related to hepatotoxicity and anti-osteoporosis activity. MethodsThe zebrafish model was utilized to evaluate the impact of PF and salt-processed Psoraleae Fructus （SPF） on the hepatotoxicity （using 134.17 ， 178.89， 268.34 mg·L^-1 as low， medium， and high dose groups of PF， 135.04， 180.06， 270.08 mg·L^-1 as low， medium， and high dose groups of SPF， respectively） and anti-osteoporotic activity （using 33.54 ， 67.08 and 134.17 mg·L^-1 as low， medium， and high dose groups of PF， 33.76， 67.52， 135.04 mg·L^-1 as low， medium， and high dose groups of SPF， respectively）， which was using alizarin red skull staining of zebrafish as an indicator of different batches of PF. The specific dosage of a batch of PF was taken as an example. Then ultra-performance liquid chromatography-quadrupole-time of flight-mass spectrometry（UPLC-Q-TOF-MS） analysis was employed to identify the chemical composition of PF before and after salt processing， and PCA， OPLS-DA， and independent sample t-test were used to elucidating the compositional changes associated with the effects of salt processing on hepatotoxicity and anti-osteoporosis activity. ResultsUnder specific conditions， PF induced notable hepatotoxicity in zebrafish while simultaneously demonstrating protective effect against prednisolone-induced osteoporosis. In comparison to PF， SPF showed alleviated hepatotoxicity while retaining significant anti-osteoporosis activity. UPLC-Q-TOF-MS analysis revealed that after salt processing， the overall chemical composition of PF showed a downward trend， with 69 components showing a decrease in content， represented by psoralen， and 13 components showing an increase， represented by 4′-O-methyl psoralen B. Further multivariate statistical analysis revealed 11 key differential components before and after salt processing of PF， including psoralen and bakuchiol. ConclusionSalt processing effectively diminishes hepatotoxicity without impairing therapeutic efficacy against osteoporosis of PF， which may be related to the compositional changes before and after salt processing of PF and provides key evidence to reveal the scientific significance of salt processing of PF.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

OBJECTIVES: To investigate the role of the BNIP3-PI3K/Akt signaling pathway in mediating the inhibitory effect of Buyang Huanwu Decoction (BYHWT) on mitochondrial autophagy in human synovial fibroblasts from rheumatoid arthritis patients (FLS-RA) cultured under a hypoxic condition. METHODS: Forty normal Wistar rats were randomized into two groups (n=20) for daily gavage of BYHWT or distilled water for 7 days to prepare BYHWT-medicated or control sera. FLS-RA were cultured in routine condition or exposed to hypoxia (10% O₂) for 24 h wigh subsequent treatment with IL-1β, followed by treatment with diluted BYHWT-medicated serum (5%, 10% and 20%) or control serum. AnnexinV-APC/7-AAD double staining and T-AOC kit were used for detecting apoptosis and total antioxidant capacity of the cells, and the changes in ROS, ATP level, mitochondrial membrane potential and Ca²⁺ homeostasis were analyzed. The changes in mRNA and protein expressions of BNIP3, PI3K and AKT and mRNA expressions of LC3, Beclin-1 and P62 were detected using RT-qPCR and Western blotting. RESULTS: Treatment with BYHWT-medicated serum dose-dependently lowered apoptosis rate of IL-1β-induced FLS-RA with hypoxic exposure. The treatment significantly decreased T-AOC concentration, increased ROS production, autophagosome formation and ATPase levels, and lowered mitochondrial membrane potential and Ca²⁺ level in the cells. In IL-1β-induced FLS-RA with hypoxic exposure, treatment with BYHWT-medicated serum significantly increased BNIP3 protein expression, decreased the protein expressions of PI3K and AKT, increased the mRNA expressions of BNIP3 and P62, and lowered the mRNA expressions of PI3K, AKT, LC3 and Beclin-1 without significantly affecting Beclin-1 protein expression. The cells treated with 5% and 10% BYHWT-medicated serum showed no significant changes in LC3 expression. CONCLUSIONS BYHWT inhibits mitochondrial autophagy in IL-1β-induced FLS-RA with hypoxic exposure possibly by inhibiting BNIP3-mediated PI3K/AKT signaling pathway.
Drugs, Chinese Herbal/pharmacology* ; Arthritis, Rheumatoid/pathology* ; Animals ; Signal Transduction/drug effects* ; Proto-Oncogene Proteins c-akt/metabolism* ; Autophagy/drug effects* ; Humans ; Fibroblasts/cytology* ; Rats, Wistar ; Membrane Proteins/metabolism* ; Rats ; Phosphatidylinositol 3-Kinases/metabolism* ; Mitochondria/metabolism* ; Cells, Cultured ; Proto-Oncogene Proteins/metabolism* ; Apoptosis/drug effects* ; Cell Hypoxia ; Synovial Membrane/cytology* ; Male ; Mitochondrial Proteins

OBJECTIVES: To assess the regulatory effect of cannabidiol (CBD) on circadian rhythm sleep disorders following general anesthesia and explore its potential mechanism in a rat model of propofol-induced rhythm sleep disorder. METHODS: An electrode was embedded in the skull for cortical EEG recording in 24 male SD rats, which were randomized into control, propofol, CBD treatment, and diazepam treatment groups (n=6). Eight days later, a single dose of propofol (10 mg/kg) was injected via the tail vein with anesthesia maintenance for 3 h in the latter 3 groups, and daily treatment with saline, CBD or diazepam was administered via gavage; the control rats received only saline injection. A wireless system was used for collecting EEG, EMG, and body temperature data within 72 h after propofol injection. After data collection, blood samples and hypothalamic tissue samples were collected for determining serum levels of oxidative stress markers and hypothalamic expressions of the key clock proteins. RESULTS: Compared with the control rats, the rats with CBD treatment showed significantly increased sleep time at night (20:00-6:00), especially during the time period of 4:00-6:00 am. Compared with the rats in propofol group, which had prolonged SWS time and increased sleep episodes during 18:00-24:00 and sleep-wake transitions, the CBD-treated rats exhibited a significant reduction of SWS time and fewer SWS-to-active-awake transitions with increased SWS aspects and sleep-wake transitions at night (24:00-08:00). Diazepam treatment produced similar effect to CBD but with a weaker effect on sleep-wake transitions. Propofol caused significant changes in protein expressions and redox state, which were effectively reversed by CBD treatment. CONCLUSIONS CBD can improve sleep structure and circadian rhythm in rats with propofol-induced sleep disorder possibly by regulating hypothalamic expressions of the key circadian clock proteins, suggesting a new treatment option for perioperative sleep disorders.
Animals ; Rats, Sprague-Dawley ; Male ; Cannabidiol/therapeutic use* ; Rats ; Circadian Rhythm/drug effects* ; Propofol/adverse effects* ; Anesthesia, General/adverse effects* ; Sleep Wake Disorders/chemically induced* ; Hypothalamus/metabolism* ; Electroencephalography

Approximately 30%-40% of epilepsy patients do not respond well to adequate anti-seizure medications (ASMs), a condition known as pharmacoresistant epilepsy. The management of pharmacoresistant epilepsy remains an intractable issue in the clinic. Its early prediction is important for prevention and diagnosis. However, it still lacks effective predictors and approaches. Here, a classical model of pharmacoresistant temporal lobe epilepsy (TLE) was established to screen pharmacoresistant and pharmaco-responsive individuals by applying phenytoin to amygdaloid-kindled rats. Ictal electroencephalograms (EEGs) recorded before phenytoin treatment were analyzed. Based on ictal EEGs from pharmacoresistant and pharmaco-responsive rats, a convolutional neural network predictive model was constructed to predict pharmacoresistance, and achieved 78% prediction accuracy. We further found the ictal EEGs from pharmacoresistant rats have a lower gamma-band power, which was verified in seizure EEGs from pharmacoresistant TLE patients. Prospectively, therapies targeting the subiculum in those predicted as "pharmacoresistant" individual rats significantly reduced the subsequent occurrence of pharmacoresistance. These results demonstrate a new methodology to predict whether TLE individuals become resistant to ASMs in a classic pharmacoresistant TLE model. This may be of translational importance for the precise management of pharmacoresistant TLE.
Epilepsy, Temporal Lobe/diagnosis* ; Animals ; Drug Resistant Epilepsy/drug therapy* ; Electroencephalography/methods* ; Rats ; Anticonvulsants/pharmacology* ; Neural Networks, Computer ; Male ; Humans ; Phenytoin/pharmacology* ; Adult ; Disease Models, Animal ; Female ; Rats, Sprague-Dawley ; Young Adult ; Convolutional Neural Networks

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Since the first successful transcatheter aortic valve replacement (TAVR) was performed globally in 2002, the TAVR technology has become increasingly mature. With more than a decade of development in China, its application experience, device research and development, procedural improvements, evidence-based medicine, and guideline updates have continuously progressed, leading to a significant increase in the number of procedures conducted. Compared to traditional surgical operations, TAVR has different postoperative monitoring points and principles for the prevention and management of complications, necessitating the formulation of corresponding monitoring and treatment protocols that align with the technical characteristics of the procedure. This guideline is based on clinical practice and incorporates both domestic and international literature as well as the experiences of Fuwai Hospital. It distills and organizes routine postoperative monitoring practices, process optimization, and complication management for TAVR, establishing a set of practical guidelines for postoperative monitoring in China. These guidelines have strong practical value for optimizing postoperative management strategies and preventing and managing complications, which is beneficial for early functional recovery of patients, shortening hospital stays, and reducing complication rates. They provide guidance and reference for domestic peers and support the standardized development and quality improvement of postoperative management for TAVR in China.