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.

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.

OBJECTIVE To investigate the effects of calcitriol on sepsis-induced immunosuppression and its potential mechanism. METHODS A sepsis-induced immunosuppression mice model was established using cecal ligation and puncture （CLP）. The 7-day survival rate， serum levels of tumor necrosis factor- α （TNF- α）， interleukin-6 （IL-6）， and IL-1β were determined in sham operation group， CLP group and calcitriol group （1 μg/kg）； the morphological changes of lung tissue in mice were observed. Lipopolysaccharide （LPS） tolerance macrophage models （representing sepsis-induced immunosuppression） were established using mice macrophage cell line RAW264.7 cells. The levels of TNF-α and IL-6 in cell supernatants as well as mRNA expressions of IL-1β， nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 （NLRP3）， IL-18 and caspase-1 were assessed in culture medium group， LPS group， LPS tolerance group， and calcitriol （5 μmol/L） group. The following parameters were measured： propidium iodide （PI）-positive cell ratio， caspase-1 activity， lactate dehydrogenase （LDH） release， and Ca2+ levels. RESULTS Compared with CLP group， 7-day survival rate and serum levels of TNF-α， IL-6 and IL-1β were increased significantly in calcitriol group （P＜0.05）. Additionally， pulmonary tissue damage was markedly attenuated in calcitriol group. Compared with LPS tolerance group， the levels of TNF-α and IL-6 in cell supernatants， mRNA expressions of IL- 1β， NLRP3， IL-18 and caspase-1， PI-positive cell ratio， caspase-1 activity， LDH release， and Ca2+ levels were all increased significantly in calcitriol group （P＜0.05）. CONCLUSIONS Calcitriol can reverse sepsis-induced immunosuppression， and the mechanism of action may be E-mail：yarfwy@163.com achieved by the binding of calcitriol to vitamin D receptor，which promotes the release of Ca2+ from the endoplasmic reticulum， thereby driving the NLRP3/caspase-1-mediated pyroptosis pathway.

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

Fecal microbiota transplantation (FMT) technology originated in China during the Eastern Jin Dynasty and has rapidly developed over the past two decades, becoming a primary method for studying the causal relationship between gut microbiota and the occurrence and progression of diseases. At the same time, the therapeutic effects of FMT in the field of gastrointestinal diseases have gained widespread recognition and are gradually expanding into other disease areas. The FMT procedure is relatively complex, and there is currently no standardized method; its success is influenced by various factors, including the donor, recipient, processing of the fecal material, and the method of implantation. Given the increasingly recognized relationship between gut microbiota and various diseases, FMT has become a research hotspot in both scientific studies and clinical applications, achieving a series of significant advancements. To help researchers better understand this technology, this paper will outline the development history of FMT, summarize common operational methods in research and clinical settings, review its application progress, and look forward to future development directions.

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.

BACKGROUND: Acupuncture therapy provides a complementary and alternative approach to treating major depressive disorder (MDD), but its efficacy and safety have still not been comprehensively assessed. Recently published systematic reviews remain confusing and inconclusive. OBJECTIVE: This systematic review evaluated the efficacy and safety of acupuncture therapy alone or combined with antidepressants for adult patients with mild and moderate MDD. SEARCH STRATEGY: Chinese Biomedical Literature Database, China National Knowledge Infrastructure Database, Wanfang Database, Chinese Science and Technology Journal Database, PubMed, Embase, and Cochrane Library were searched from their inceptions to March 2025. INCLUSION CRITERIA: Randomized controlled trials that compared acupuncture therapy with antidepressants, or acupuncture therapy plus antidepressants with acupuncture therapy or antidepressants for adult patients with mild and moderate MDD were included. DATA EXTRACTION AND ANALYSIS: Five reviewers independently extracted data from original literature using a standardized form, and the data were verified by two reviewers to ensure accuracy. Statistical meta-analyses, publication bias analyses, and subgroup analyses were performed by using Review Manager 5.3 software. The Grading of Recommendations Assessment, Development, and Evaluation approach was used to assess the certainty of the evidence. RESULTS: A total of 60 eligible studies including 4675 participants were included. Low-certainty evidence showed that compared with antidepressants, acupuncture therapy (standardized mean difference [SMD] = -0.57; 95% confidence interval [CI] = [-0.87, -0.27]; I² = 86%; P = 0.006) or acupuncture therapy plus antidepressants (SMD = -1.00; 95% CI = [-1.18, -0.81]; I² = 77%; P < 0.00001) may reduce the severity of depression at the end of treatment. Low-certainty evidence indicated that compared with acupuncture therapy alone, acupuncture therapy plus antidepressants slightly reduced the severity of depression at the end of treatment (SMD = -0.38; 95% CI = [-0.61, -0.14]; I² = 18%; P = 0.002). Similar results were also found for acupuncture's relief of insomnia. The reported adverse effects of acupuncture therapy were mild and transient. For most of the subgroup analyses, acupuncture type, scale type, and the course of treatment did not show a significant relative effect. CONCLUSION Acupuncture therapy may provide antidepressant effects and relieve insomnia with mild adverse effects for adult patients with mild and moderate MDD. But the certainty of evidence was very low. More high-quality, well designed, large-scale studies with long-term follow-up are needed in the future. Please cite this article as: Kuang HJ, Yang HS, Feng YX, Tang H, Fan Q, Xu YQ, Cui S, Musil R, Luxenburger H, Zhang YX, Zhao H, Zhang YQ. Efficacy and safety of acupuncture therapies for adult patients with mild and moderate major depressive disorder: A systematic review and meta-analysis. J Integr Med. 2025; 23(5):471-491.
Humans ; Acupuncture Therapy/methods* ; Depressive Disorder, Major/therapy* ; Adult ; Antidepressive Agents/therapeutic use* ; Treatment Outcome ; Randomized Controlled Trials as Topic