Heart and spleen deficiency syndrome is the most common syndrome type in patients with insomnia. Based on the theory of disease syndrome-combined animal model， this paper used multiple databases to search for the keywords "heart and spleen deficiency"， "insomnia"， "sleepless"， "disease syndrome-combined animal model"， "model evaluation"， etc. It selected the literature related to the animal model of insomnia with heart and spleen deficiency in the past 20 years to evaluate from the aspects of model establishment， modeling factors， syndrome model， disease model， macro characterization & macro characterization evaluation scale， micro indicators， etc. It is found that the existing animal model of insomnia with heart and spleen deficiency is not completely constructed by the method of disease syndrome combination of disease modeling factors and syndrome modeling factors. In the model using this method， the single establishment factor of heart and spleen deficiency does not conform to the clinical reality of disease， and the selection of the factors for the insomnia model is not closely related to or even separated from the syndrome performance. There is a problem of insufficient quantification of macro representation when the macro representation of the model replaces the symptoms related to heart and spleen deficiency syndrome and insomnia in an equivalent manner for macro representation evaluation， which can be improved according to the quantitative ideas and examples of the existing macro representation and macro representation evaluation scale. There are few specific indicators of heart and spleen deficiency syndrome in micro indicators. The micro research of heart and spleen deficiency syndrome and the essence of other traditional Chinese medicine （TCM） syndromes can be carried out by metabonomics and other technologies combined with the theory of corresponding prescription and syndrome， along the specific related ideas of "prescription and syndrome， treatment principle and selection of prescription， treatment principle and selection of acupoints， as well as therapeutic mechanism and syndrome essence". The future users and researchers of animal models of insomnia with heart and spleen deficiency can get improved methods and ideas through the shortcomings of animal models of heart and spleen deficiency listed in this paper and construct animal models of insomnia with heart and spleen deficiency that are more suitable for clinical practice， so as to establish a more perfect modeling method and evaluation system of disease syndrome-combined animal model.

Heart and spleen deficiency syndrome is the most common syndrome type in patients with insomnia. Based on the theory of disease syndrome-combined animal model， this paper used multiple databases to search for the keywords "heart and spleen deficiency"， "insomnia"， "sleepless"， "disease syndrome-combined animal model"， "model evaluation"， etc. It selected the literature related to the animal model of insomnia with heart and spleen deficiency in the past 20 years to evaluate from the aspects of model establishment， modeling factors， syndrome model， disease model， macro characterization & macro characterization evaluation scale， micro indicators， etc. It is found that the existing animal model of insomnia with heart and spleen deficiency is not completely constructed by the method of disease syndrome combination of disease modeling factors and syndrome modeling factors. In the model using this method， the single establishment factor of heart and spleen deficiency does not conform to the clinical reality of disease， and the selection of the factors for the insomnia model is not closely related to or even separated from the syndrome performance. There is a problem of insufficient quantification of macro representation when the macro representation of the model replaces the symptoms related to heart and spleen deficiency syndrome and insomnia in an equivalent manner for macro representation evaluation， which can be improved according to the quantitative ideas and examples of the existing macro representation and macro representation evaluation scale. There are few specific indicators of heart and spleen deficiency syndrome in micro indicators. The micro research of heart and spleen deficiency syndrome and the essence of other traditional Chinese medicine （TCM） syndromes can be carried out by metabonomics and other technologies combined with the theory of corresponding prescription and syndrome， along the specific related ideas of "prescription and syndrome， treatment principle and selection of prescription， treatment principle and selection of acupoints， as well as therapeutic mechanism and syndrome essence". The future users and researchers of animal models of insomnia with heart and spleen deficiency can get improved methods and ideas through the shortcomings of animal models of heart and spleen deficiency listed in this paper and construct animal models of insomnia with heart and spleen deficiency that are more suitable for clinical practice， so as to establish a more perfect modeling method and evaluation system of disease syndrome-combined animal model.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

BACKGROUND: While emotional distress, encompassing anxiety and depression, has been associated with negative clinical outcomes, its impact across various clinical departments and general hospitals has been less explored. Previous studies with limited sample sizes have examined the effectiveness of specific treatments (e.g., antidepressants) rather than a systemic management strategy for outcome improvement in non-psychiatric inpatients. To enhance the understanding of the importance of addressing mental health care needs among non-psychiatric patients in general hospitals, this study retrospectively investigated the impacts of emotional distress and the effects of early detection and management of depression and anxiety on hospital length of stay (LOS) and rate of long LOS (LLOS, i.e., LOS >30 days) in a large sample of non-psychiatric inpatients. METHODS: This retrospective cohort study included 487,871 inpatients from 20 non-psychiatric departments of a general hospital. They were divided, according to whether they underwent a novel strategy to manage emotional distress which deployed the Huaxi Emotional Distress Index (HEI) for brief screening with grading psychological services (BS-GPS), into BS-GPS ( n = 178,883) and non-BS-GPS ( n = 308,988) cohorts. The LOS and rate of LLOS between the BS-GPS and non-BS-GPS cohorts and between subcohorts with and without clinically significant anxiety and/or depression (CSAD, i.e., HEI score ≥11 on admission to the hospital) in the BS-GPS cohort were compared using univariable analyses, multilevel analyses, and/or propensity score-matched analyses, respectively. RESULTS: The detection rate of CSAD in the BS-GPS cohort varied from 2.64% (95% confidence interval [CI]: 2.49%-2.81%) to 20.50% (95% CI: 19.43%-21.62%) across the 20 departments, with a average rate of 5.36%. Significant differences were observed in both the LOS and LLOS rates between the subcohorts with CSAD (12.7 days, 535/9590) and without CSAD (9.5 days, 3800/169,293) and between the BS-GPS (9.6 days, 4335/178,883) and non-BS-GPS (10.8 days, 11,483/308,988) cohorts. These differences remained significant after controlling for confounders using propensity score-matched comparisons. A multilevel analysis indicated that BS-GPS was negatively associated with both LOS and LLOS after controlling for sociodemographics and the departments of patient discharge and remained negatively associated with LLOS after controlling additionally for the year of patient discharge. CONCLUSION Emotional distress significantly prolonged the LOS and increased the LLOS of non-psychiatric inpatients across most departments and general hospitals. These impacts were moderated by the implementation of BS-GPS. Thus, BS-GPS has the potential as an effective, resource-saving strategy for enhancing mental health care and optimizing medical resources in general hospitals.
Humans ; Retrospective Studies ; Male ; Length of Stay/statistics & numerical data* ; Female ; Middle Aged ; Adult ; Psychological Distress ; Inpatients/psychology* ; Aged ; Anxiety/diagnosis* ; Depression/diagnosis*

In this paper, near-infrared spectroscopy(NIRS) was employed to analyze 129 batches of commercial products of Reduning Injection. The batch reporting rate was estimated according to the report of Reduning Injection in the direct adverse drug reaction(ADR) reporting system of the drug marketing authorization holder of the Center for Drug Reevaluation of the National Medical Products Administration(National Center for ADR Monitoring) from August 2021 to August 2022. According to the batch reporting rate, the samples of Reduning Injection were classified into those with potential risks and those being safe. No processing, random oversampling(ROS), random undersampling(RUS), and synthetic minority over-sampling technique(SMOTE) were then employed to balance the unbalanced data. After the samples were classified according to appropriate sampling methods, competitive adaptive reweighted sampling(CARS), successive projections algorithm(SPA), uninformative variables elimination(UVE), and genetic algorithm(GA) were respectively adopted to screen the features of spectral data. Then, support vector machine(SVM), logistic regression(LR), k-nearest neighbors(KNN), naive bayes(NB), random forest(RF), and artificial neural network(ANN) were adopted to establish the risk prediction models. The effects of the four feature extraction methods on the accuracy of the models were compared. The optimal method was selected, and bayesian optimization was performned to optimize the model parameters to improve the accuracy and robustness of model prediction. To explore the correlations between potential risks of clinical use and quality test data, TreeNet was employed to identify potential quality parameters affecting the clinical safety of Reduning Injection. The results showed that the models established with the SVM, LR, KNN, NB, RF, and ANN algorithms had the F1 scores of 0.85, 0.85, 0.86, 0.80, 0.88, and 0.85 and the accuracy of 88%, 88%, 88%, 85%, 91%, and 88%, respectively, and the prediction time was less than 5 s. The results indicated that the established models were accurate and efficient. Therefore, near infrared spectroscopy combined with machine learning algorithms can quickly predict the potential risks of clinical use of Reduning Injection in batches. Three key quality parameters that may affect clinical safety were identified by TreeNet, which provided a scientific basis for improving the safety standards of Reduning Injection.
Spectroscopy, Near-Infrared/methods* ; Drugs, Chinese Herbal/administration & dosage* ; Machine Learning ; Algorithms ; Humans ; Quality Control

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

Jiuwei Xifeng Granules have become a Chinese patent medicine in the market. Because the formula contains Os Draconis, a top-level protected fossil of ancient organisms, the formula was to be improved by replacing Os Draconis with Ostreae Concha. To evaluate whether the improved formula has the same effectiveness and safety as the original formula, a randomized, double-blind, parallel-controlled, equivalence clinical trial was conducted. This study enrolled 288 tic disorder(TD) of children and assigned them into two groups in 1∶1. The treatment group and control group took the modified formula and original formula, respectively. The treatment lasted for 6 weeks, and follow-up visits were conducted at weeks 2, 4, and 6. The primary efficacy endpoint was the difference in Yale global tic severity scale(YGTSS)-total tic severity(TTS) score from baseline after 6 weeks of treatment. The results showed that after 6 weeks of treatment, the declines in YGTSS-TSS score showed no statistically significant difference between the two groups. The difference in YGTSS-TSS score(treatment group-control group) and the 95%CI of the full analysis set(FAS) were-0.17[-1.42, 1.08] and those of per-protocol set(PPS) were 0.29[-0.97, 1.56], which were within the equivalence boundary [-3, 3]. The equivalence test was therefore concluded. The two groups showed no significant differences in the secondary efficacy endpoints of effective rate for TD, total score and factor scores of YGTSS, clinical global impressions-severity(CGI-S) score, traditional Chinese medicine(TCM) response rate, or symptom disappearance rate, and thus a complete evidence chain with the primary outcome was formed. A total of 6 adverse reactions were reported, including 4(2.82%) cases in the treatment group and 2(1.41%) cases in the control group, which showed no statistically significant difference between the two groups. No serious suspected unexpected adverse reactions were reported, and no laboratory test results indicated serious clinically significant abnormalities. The results support the replacement of Os Draconis by Ostreae Concha in the original formula, and the efficacy and safety of the modified formula are consistent with those of the original formula.
Adolescent ; Child ; Child, Preschool ; Female ; Humans ; Male ; Double-Blind Method ; Drugs, Chinese Herbal/therapeutic use* ; Tic Disorders/drug therapy* ; Treatment Outcome

This study aims to investigate the protective effects and mechanisms of polysaccharide extract PCP1 from Polygonatum cyrtonema in ameliorating cerebral ischemia-reperfusion(I/R) injury in rats through modulation of the Toll-like receptor 4(TLR4)/NOD-like receptor protein 3(NLRP3) signaling pathway. In vivo, SD rats were randomly divided into the sham group, model group, PCP1 group, nimodipine(NMDP) group, and TLR4 signaling inhibitor(TAK-242) group. A middle cerebral artery occlusion/reperfusion(MCAO/R) model was established, and neurological deficit scores and infarct size were evaluated 24 hours after reperfusion. Hematoxylin-eosin(HE) and Nissl staining were used to observe pathological changes in ischemic brain tissue. Transmission electron microscopy(TEM) assessed ultrastructural damage in cortical neurons. Enzyme-linked immunosorbent assay(ELISA) was used to measure the levels of interleukin-1β(IL-1β), interleukin-6(IL-6), interleukin-18(IL-18), tumor necrosis factor-α(TNF-α), interleukin-10(IL-10), and nitric oxide(NO) in serum. Immunofluorescence was used to analyze the expression of TLR4 and NLRP3 proteins. In vitro, a BV2 microglial cell oxygen-glucose deprivation/reperfusion(OGD/R) model was established, and cells were divided into the control, OGD/R, PCP1, TAK-242, and PCP1 + TLR4 activator lipopolysaccharide(LPS) groups. The CCK-8 assay evaluated BV2 cell viability, and ELISA determined NO release. Western blot was used to analyze the expression of TLR4, NLRP3, and downstream pathway-related proteins. The results indicated that, compared with the model group, PCP1 significantly reduced neurological deficit scores, infarct size, ischemic tissue pathology, cortical cell damage, and the levels of inflammatory factors IL-1β, IL-6, IL-18, TNF-α, and NO(P<0.01). It also elevated IL-10 levels(P<0.01) and decreased the expression of TLR4 and NLRP3 proteins(P<0.05, P<0.01). Moreover, in vitro results showed that, compared with the OGD/R group, PCP1 significantly improved BV2 cell viability(P<0.05, P<0.01), reduced cell NO levels induced by OGD/R(P<0.01), and inhibited the expression of TLR4-related inflammatory pathway proteins, including TLR4, myeloid differentiation factor 88(MyD88), tumor necrosis factor receptor-associated factor 6(TRAF6), phosphorylated nuclear factor-kappaB dimer RelA(p-p65)/nuclear factor-kappaB dimer RelA(p65), NLRP3, cleaved-caspase-1, apoptosis-associated speck-like protein(ASC), GSDMD-N, IL-1β, and IL-18(P<0.05, P<0.01). The protective effects of PCP1 were reversed by LPS stimulation. In conclusion, PCP1 ameliorates cerebral I/R injury by modulating the TLR4/NLRP3 signaling pathway, exerting anti-inflammatory and anti-pyroptotic effects.
Animals ; Toll-Like Receptor 4/genetics* ; NLR Family, Pyrin Domain-Containing 3 Protein/genetics* ; Rats, Sprague-Dawley ; Rats ; Reperfusion Injury/genetics* ; Male ; Signal Transduction/drug effects* ; Polysaccharides/isolation & purification* ; Polygonatum/chemistry* ; Brain Ischemia/genetics* ; Drugs, Chinese Herbal/administration & dosage* ; Mice ; Humans

In the present study, a mouse model of coronary artery ligation was employed to evaluate the effects of Jiming Powder on mitophagy in the mouse model of myocardial infarction and elucidate its underlying mechanisms. A mouse model of myocardial infarction post heart failure was constructed by ligating the left anterior descending branch of the coronary artery. The therapeutic efficacy of Jiming Powder was assessed from multiple perspectives, including ultrasonographic imaging, hematoxylin-eosin(HE) staining, Masson staining, and serum cardiac enzyme profiling. Dihydroethidium(DHE) staining was employed to evaluate the oxidative stress levels in the hearts of mice from each group. Mitophagy levels were assessed by scanning electron microscopy and immunofluorescence co-localization. Western blot was employed to determine the levels of key proteins involved in mitophagy, including Bcl-2-interacting protein beclin 1(BECN1), sequestosome 1(SQSTM1), microtubule-associated protein 1 light chain 3 beta(LC3B), PTEN-induced putative kinase 1(PINK1), phospho-Parkinson disease protein(p-Parkin), and Parkinson disease protein(Parkin). The results demonstrated that compared with the model group, high and low doses of Jiming Powder significantly reduced the left ventricular internal diameter in systole(LVIDs) and left ventricular internal diameter in diastole(LVIDd) and markedly improved the left ventricular ejection fraction(LVEF) and left ventricular fractional shortening(LVFS), effectively improving the cardiac function in post-myocardial infarction mice. Jiming Powder effectively reduced the levels of myocardial injury markers such as creatine kinase(CK), creatine kinase isoenzyme(CK-MB), and lactate dehydrogenase(LDH), thereby protecting ischemic myocardium. HE staining revealed that Jiming Powder attenuated inflammatory cell infiltration after myocardial infarction. Masson staining indicated that Jiming Powder effectively inhibited ventricular remodeling. Western blot results showed that Jiming Powder activated the PINK1-Parkin pathway, up-regulated the protein level of BECN1, down-regulated the protein level of SQSTM1, and increased the LC3Ⅱ/LC3Ⅰ ratio to promote mitophagy. In conclusion, Jiming Powder exerts therapeutic effects on myocardial infarction by inhibiting ventricular remodeling. The findings pave the way for subsequent pharmacological studies on the active components of Jiming Powder.
Animals ; Myocardial Infarction/physiopathology* ; Mitophagy/drug effects* ; Mice ; Drugs, Chinese Herbal/administration & dosage* ; Protein Kinases/genetics* ; Male ; Ubiquitin-Protein Ligases/genetics* ; Humans ; Disease Models, Animal ; Mice, Inbred C57BL ; Signal Transduction/drug effects*