Functional constipation （FC） is a common functional disorder of the intestines， mainly characterized by reduced bowel movement frequency， difficulty in defecation， a sensation of incomplete evacuation， and hard stools， which severely affect patients’ quality of life. Research indicates that the pathogenesis of FC is closely related to gut microbiota dysbiosis and abnormal bile acid secretion. Bile acids， as endogenous natural laxatives， promote bowel movements by enhancing colonic secretion and regulating intestinal motility； meanwhile， gut microbiota influence colonic transit function by regulating the enteric nervous system， immune system， and their metabolic products. Based on an overview of the relationship between gut microbiota and bile acid metabolism， this article systematically reviews the current research status on the mechanisms of traditional Chinese medicine （TCM） in treating FC by regulating the balance of the gut microbiota-bile acid axis. It is found that single Chinese medicinal herbs （such as Atractylodes macrocephala）， isolated compounds （such as Platycodon grandiflorum polysaccharides）， herbal formulas （such as Shanger huang pill）， acupuncture， and moxibustion can up-regulate the abundance of beneficial bacteria， reshape the microbial structure， correct bile acid metabolism， and activate the Takeda G-protein receptor 5/farnesoid X receptor pathway to treat FC.

Objective: To address the dual challenges of long-tail distribution and feature sparsity in traditional Chinese medicine (TCM) syndrome differentiation within real clinical settings, we propose a data-efficient learning framework enhanced by knowledge graphs. Methods: We developed Agent-GNN, a three-stage decoupled learning framework, and validated it on the Traditional Chinese Medicine Syndrome Diagnosis (TCM-SD) dataset containing 54 152 clinical records across 148 syndrome categories. First, we constructed a comprehensive medical knowledge graph encoding the complete TCM reasoning system. Second, we proposed a Functional Patient Profiling (FPP) method that utilizes large language models (LLMs) combined with Graph Retrieval-Augmented Generation (RAG) to extract structured symptom-etiology-pathogenesis subgraphs from medical records. Third, we employed heterogeneous graph neural networks to learn structured combination patterns explicitly. We compared our method against multiple baselines including BERT, ZY-BERT, ZY-BERT + Know, GAT, and GPT-4 Few-shot, using macro-F1 score as the primary evaluation metric. Additionally, ablation experiments were conducted to validate the contribution of each key component to model performance. Results: Agent-GNN achieved an overall macro-F1 score of 72.4%, representing an 8.7 percentage points improvement over ZY-BERT + Know (63.7%), the strongest baseline among traditional methods. For long-tail syndromes with fewer than 10 samples, Agent-GNN reached a macro-F1 score of 58.6%, compared with 39.3% for ZY-BERT + Know and 41.2% for GPT-4 Few-shot, representing relative improvements of 49.2% and 42.2%, respectively. Ablation experiments confirmed that the explicit modeling of etiology-pathogenesis nodes contributed 12.4 percentage points to this enhanced long-tail syndrome performance. Conclusion This study proposes Agent-GNN, a knowledge graph-enhanced framework that effectively addresses the long-tail distribution challenge in TCM syndrome differentiation. By explicitly modeling manifestation-mechanism-essence patterns through structured knowledge graphs, our approach achieves superior performance in data-scarce scenarios while providing interpretable reasoning paths for TCM intelligent diagnosis.

Aromatic Chinese medicinal essential oils are volatile oils extracted from aromatic Chinese herbs， which can prevent and treat respiratory infectious diseases through multiple synergistic mechanisms including pathogen inhibition， immune regulation， and inflammatory response regulation. Essential oils are primarily used externally on the body to prevent infections and alleviate symptoms through methods like inhalation， smearing， topical application， bathing， gargling or as a suppository. They can also be utilized in the environment for disinfection and air purification， through methods like diffusion， vaporization， or spraying. The external application of essential oils extracted from Chinese aromatic herbs has the advantages of convenience， quick absorption， and simultaneous influence on both the body and mind. However， there are still challenges and deficiencies in aspects such as the positioning of functions， indications， safety， and the research on the mechanism of action. It has been proposed to combine the theory of aromatic Chinese medicinals with the characteristics of essential oils， and formulate prescriptions of Chinese medicinal essential oils under the principles of traditional Chinese medicine syndrome differentiation， and prevent and treat respiratory infectious diseases efficiently， accurately， and safely， thereby expanding the clinical application of aromatic Chinese medicinals and the preventive theory of traditional Chinese medicine.

In managing metabolic dysfunction-associated steatotic liver disease, which affects over 30% of the general population, effective noninvasive biomarkers for assessing disease severity, monitoring disease progression, predicting the development of liver-related complications, and assessing treatment response are crucial. The advantage of simple fibrosis scores lies in their widespread accessibility through routinely performed blood tests and extensive validation in different clinical settings. They have shown reasonable accuracy in diagnosing advanced fibrosis and good performance in excluding the majority of patients with a low risk of liver-related complications. Among patients with elevated serum fibrosis scores, a more specific fibrosis and imaging biomarker has proved useful to accurately identify patients at risk of liver-related complications. Among specific fibrosis blood biomarkers, enhanced liver fibrosis is the most widely utilized and has been approved in the United States as a prognostic biomarker. For imaging biomarkers, the availability of vibration-controlled transient elastography has been largely improved over the past years, enabling the use of liver stiffness measurement (LSM) for accurate assessment of significant and advanced fibrosis, and cirrhosis. Combining LSM with other routinely available blood tests enhances the ability to diagnose at-risk metabolic dysfunction-associated steatohepatitis and predict liver-related complications, some reaching an accuracy comparable to that of liver biopsy. Magnetic resonance imaging-based modalities provide the most accurate quantification of liver fibrosis, though the current utilization is limited to research settings. Expanding their future use in clinical practice depends on factors such as cost and facility availability.

In managing metabolic dysfunction-associated steatotic liver disease, which affects over 30% of the general population, effective noninvasive biomarkers for assessing disease severity, monitoring disease progression, predicting the development of liver-related complications, and assessing treatment response are crucial. The advantage of simple fibrosis scores lies in their widespread accessibility through routinely performed blood tests and extensive validation in different clinical settings. They have shown reasonable accuracy in diagnosing advanced fibrosis and good performance in excluding the majority of patients with a low risk of liver-related complications. Among patients with elevated serum fibrosis scores, a more specific fibrosis and imaging biomarker has proved useful to accurately identify patients at risk of liver-related complications. Among specific fibrosis blood biomarkers, enhanced liver fibrosis is the most widely utilized and has been approved in the United States as a prognostic biomarker. For imaging biomarkers, the availability of vibration-controlled transient elastography has been largely improved over the past years, enabling the use of liver stiffness measurement (LSM) for accurate assessment of significant and advanced fibrosis, and cirrhosis. Combining LSM with other routinely available blood tests enhances the ability to diagnose at-risk metabolic dysfunction-associated steatohepatitis and predict liver-related complications, some reaching an accuracy comparable to that of liver biopsy. Magnetic resonance imaging-based modalities provide the most accurate quantification of liver fibrosis, though the current utilization is limited to research settings. Expanding their future use in clinical practice depends on factors such as cost and facility availability.

In managing metabolic dysfunction-associated steatotic liver disease, which affects over 30% of the general population, effective noninvasive biomarkers for assessing disease severity, monitoring disease progression, predicting the development of liver-related complications, and assessing treatment response are crucial. The advantage of simple fibrosis scores lies in their widespread accessibility through routinely performed blood tests and extensive validation in different clinical settings. They have shown reasonable accuracy in diagnosing advanced fibrosis and good performance in excluding the majority of patients with a low risk of liver-related complications. Among patients with elevated serum fibrosis scores, a more specific fibrosis and imaging biomarker has proved useful to accurately identify patients at risk of liver-related complications. Among specific fibrosis blood biomarkers, enhanced liver fibrosis is the most widely utilized and has been approved in the United States as a prognostic biomarker. For imaging biomarkers, the availability of vibration-controlled transient elastography has been largely improved over the past years, enabling the use of liver stiffness measurement (LSM) for accurate assessment of significant and advanced fibrosis, and cirrhosis. Combining LSM with other routinely available blood tests enhances the ability to diagnose at-risk metabolic dysfunction-associated steatohepatitis and predict liver-related complications, some reaching an accuracy comparable to that of liver biopsy. Magnetic resonance imaging-based modalities provide the most accurate quantification of liver fibrosis, though the current utilization is limited to research settings. Expanding their future use in clinical practice depends on factors such as cost and facility availability.

OBJECTIVES: To explore the relationship between white matter injury (WMI) and cerebral perfusion in preterm infants using arterial spin labeling (ASL). METHODS: A total of 293 preterm infants (gestational age <34 weeks) hospitalized at the Third Affiliated Hospital of Zhengzhou University between June 2022 and June 2024 were included. After achieving clinical stability, the infants underwent brain magnetic resonance imaging (MRI) and ASL. Based on MRI findings, infants were classified into WMI (n=66) and non-WMI (n=227) groups. Cerebral perfusion parameters were compared between groups, and the association between WMI and perfusion alterations was evaluated. RESULTS: The WMI group showed a higher incidence of mild intraventricular hemorrhage (IVH) than the non-WMI group (P<0.05). Significantly lower cerebral perfusion was observed in the WMI group across bilateral frontal, temporal, parietal, and occipital lobes, as well as the basal ganglia and thalamus (P<0.05). After adjusting for gestational age, corrected gestational age at ASL scan, and mild IVH, WMI remained significantly associated with reduced regional perfusion (P<0.05). CONCLUSIONS WMI in preterm infants correlates with localized cerebral hypoperfusion. ASL-detected perfusion abnormalities may provide novel insights into WMI pathogenesis.
Humans ; White Matter/blood supply* ; Infant, Newborn ; Spin Labels ; Infant, Premature ; Female ; Male ; Cerebrovascular Circulation ; Magnetic Resonance Imaging