The genus jujube(Ziziphus jujuba Mill.)within the Rhamnaceae family encompasses numerous varieties,such as Ziziphus jujuba Mill.var.jujuba,Ziziphus jujuba var.inermis,and var.spinosa,etc.Among these,the jujube fructus has the most abundant cultivated variants across the country,including Ziziphus jujuba cv.Hamidazao and Ziziphus jujuba cv.Huanghetanzao.Jujube plants are rich in variety and are used for both medicinal and food purposes.Polysaccharides,one of the main active ingredients of jujube,are important medicinal components that contribute to its efficacy.Jujube polysaccharides have been found to promote hematopoiesis,exhibit antioxidant and anti-tumor activities,repair liver damage,regulate the immune system,and provide anti-inflammatory effects.By comprehensively summarizing and analyzing the literature on jujube polysaccharides from different varieties and origins,this paper reviews the potential mechanisms of action of jujube polysaccharides in exerting biological activities.It also summarizes the primary structural features,such as relative molecular mass,monosaccharide composition,glycosidic linkage,and the substituent modifications of jujube polysaccharides by sulfation,phosphorylation,carboxymethylation,selenization,and acetylation.This review aims to provide a reference for the research and development of jujube in the fields of innovative polysaccharide drugs and functional foods.

Objective To investigate the application of machine learning to predict the hemodynamic parameters of combined stenotic left coronary artery(LCA)aneurysms.Methods Parameterized modeling and simulation based on the geometric parameter range of combined stenosis LCA aneurysms in clinical statistics were conducted.The obtained simulation data was used as the dataset,and two common machine learning models were constructed and trained for optimization to predict two key hemodynamic parameters:wall shear stress(WSS)and pressure.By comparing and analyzing the performances of these models on the training and testing sets,the accuracy of each model was evaluated,and the effectiveness of the data-driven prediction of hemodynamic parameters for LCA aneurysms with concomitant stenosis was verified.Results The effectiveness of machine learning method in inverting the hemodynamic parameters of aneurysms was determined.For WSS prediction,the trained deep learning model and random forest model achieved mean squared error(MSE),mean absolute error(MAE),and determination coefficient R2 of 0.052 8,0.032 2,0.988 3,and 0.078 2,0.046 3,and 0.976 6,respectively.For pressure prediction,the accuracies of the deep learning models and random forest models were comparable,with MSE,MAE,and R2 of 4.67×10-6,3×10-4,0.999 7,and 1.07×10-5,5×10-4,and 0.999 3,respectively.Conclusions Machine learning methods show high accuracy in predicting the hemodynamic parameters of combined stenotic coronary artery aneurysm models.The predictive accuracy of the model,computational efficiency,and needs of the application scenarios need to be considered in machine learning prediction so that the appropriate model can be selected according to the specific situation.This study has clinical significance,helping doctors to more accurately evaluate a patient's condition and provide new ideas and method for the diagnosis and treatment of cardiovascular diseases.

Objective To investigate the risk factors for postoperative pulmonary embolism in patients with spontaneous cerebral hemorrhage,and construct and verify the nomogram model.Methods A retrospective cohort study was conducted on 558 patients admitted in the First Affiliated Hospital of Chongqing Medical University and the Three Gorges Hospital Affiliated to Chongqing University.And 393 of them who hospitalized from January 2015 to January 2021 were assigned into a modeling group,and the other 165 patients from February 2021 to January 2023 into a validation group.Univariate and multivariate stepwise logistic regression analyses were used to screen out the risk factors associated with pulmonary embolism after spontaneous cerebral hemorrhage surgery.Then a nomogram model was build based on these factors and verified.Results Based on age,blood loss,Glasgow coma scale(GCS)score,surgical treatments,levels of fibrin degradation products,D-dimer and hemoglobin,plasma osmolality,and deep vein thrombosis,a risk model of pulmonary embolism was built.Receiver operating characteristic(ROC)curve analysis showed the model had good discriminability for the presence of pulmonary embolism,and the area under the curve(AUC)value was 0.908.Hosmer-Lemeshow goodness-fit test indicated that the model had a good fit to the verification set(Chi-square=14.805,df=8,P=0.063),the correction curve was close to the ideal curve,and the prediction probability of the model was close to the actual occurrence probability,suggesting the model having good accuracy.Decision curve analysis revealed that the established nomogram model can get benefits under a large range of threshold probabilities.Conclusion We develop a prediction model for postoperative pulmonary embolism in patients with spontaneous cerebral hemorrhage after surgical treatment,which shows good prediction performance in both the training and validation groups,and can be used for accurate,prompt and quick identification for the occurrence of pulmonary embolism in clinical practice.

The neurovascular unit (NVU) is highly responsible for cerebral homeostasis and its dysfunction emerges as a critical contributor to Alzheimer's disease (AD) pathology. Hence, rescuing NVU dysfunction might be a viable approach to AD treatments. Here, we fabricated a self-regulated muti-functional nano-modulator (siR/PIO@RP) that can intelligently navigate to damaged blood-brain barrier and release therapeutical cargoes for synergetic AD therapy. The resulting siR/PIO@RP enables self-regulation of its distribution in accordance with the physio/pathological state (low/high RAGE expression) of the target site via a feedback loop. siR/PIO@RP is capable of performing intricate tasks and goes beyond the capabilities of single-target therapeutic agents utilized in AD therapy, such as reducing cerebral Aβ load, relieving neuroinflammation, and alleviating the dysfunction of NVU. Overall, the current study provides proof of concept that normalizing NVU holds promise as a means of alleviating AD symptoms.

Gut microbiota dysbiosis is an avenue for the promotion of atherosclerosis (AS) and this effect is mediated partly via the circulating microbial metabolites. More microbial metabolites related to AS vascular inflammation, and the mechanisms involved need to be clarified urgently. Paeonol (Pae) is an active compound isolated from Paeonia suffruticoas Andr. with anti-AS inflammation effect. However, considering the low oral bioavailability of Pae, it is worth exploring the mechanism by which Pae reduces the harmful metabolites of the gut microbiota to alleviate AS. In this study, ApoE^-/- mice were fed a high-fat diet (HFD) to establish an AS model. AS mice were administrated with Pae (200 or 400 mg·kg^-1) by oral gavage and fecal microbiota transplantation (FMT) was conducted. 16S rDNA sequencing was performed to investigate the composition of the gut microbiota, while metabolomics analysis was used to identify the metabolites in serum and cecal contents. The results indicated that Pae significantly improved AS by regulating gut microbiota composition and microbiota metabolic profile in AS mice. We also identified α-hydroxyisobutyric acid (HIBA) as a harmful microbial metabolite reduced by Pae. HIBA supplementation in drinking water promoted AS inflammation in AS mice. Furthermore, vascular endothelial cells (VECs) were cultured and stimulated by HIBA. We verified that HIBA stimulation increased intracellular ROS levels, thereby inducing VEC inflammation via the TXNIP/NLRP3 pathway. In sum, Pae reduces the production of the microbial metabolite HIBA, thus alleviating the ROS/TXNIP/NLRP3 pathway-mediated endothelial inflammation in AS. Our study innovatively confirms the mechanism by which Pae reduces the harmful metabolites of gut microbiota to alleviate AS and proposes HIBA as a potential biomarker for AS clinical judgment.
Animals ; Mice ; Atherosclerosis/drug therapy* ; Diet, High-Fat ; Endothelial Cells ; Inflammation/drug therapy* ; Mice, Inbred C57BL ; NLR Family, Pyrin Domain-Containing 3 Protein/genetics* ; Reactive Oxygen Species

Using chemoproteomic techniques, we first identified EIF2AK2, eEF1A1, PRDX3 and VPS4B as direct targets of berberine (BBR) for its synergistically anti-inflammatory effects. Of them, BBR has the strongest affinity with EIF2AK2 via two ionic bonds, and regulates several key inflammatory pathways through EIF2AK2, indicating the dominant role of EIF2AK2. Also, BBR could subtly inhibit the dimerization of EIF2AK2, rather than its enzyme activity, to selectively modulate its downstream pathways including JNK, NF-κB, AKT and NLRP3, with an advantage of good safety profile. In EIF2AK2 gene knockdown mice, the inhibitory IL-1β, IL-6, IL-18 and TNF-α secretion of BBR was obviously attenuated, confirming an EIF2AK2-dependent anti-inflammatory efficacy. The results highlight the BBR's network mechanism on anti-inflammatory effects in which EIF2AK2 is a key target, and inhibition of EIF2AK2 dimerization has a potential to be a therapeutic strategy against inflammation-related disorders.

Existing traditional Chinese medicine (TCM)-related databases are still insufficient in data standardization, integrity and precision, and need to be updated urgently. Herein, an Encyclopedia of Traditional Chinese Medicine version 2.0 (ETCM v2.0, http://www.tcmip.cn/ETCM2/front/#/) was constructed as the latest curated database hosting 48,442 TCM formulas recorded by ancient Chinese medical books, 9872 Chinese patent drugs, 2079 Chinese medicinal materials and 38,298 ingredients. To facilitate the mechanistic research and new drug discovery, we improved the target identification method based on a two-dimensional ligand similarity search module, which provides the confirmed and/or potential targets of each ingredient, as well as their binding activities. Importantly, five TCM formulas/Chinese patent drugs/herbs/ingredients with the highest Jaccard similarity scores to the submitted drugs are offered in ETCM v2.0, which may be of significance to identify prescriptions/herbs/ingredients with similar clinical efficacy, to summarize the rules of prescription use, and to find alternative drugs for endangered Chinese medicinal materials. Moreover, ETCM v2.0 provides an enhanced JavaScript-based network visualization tool for creating, modifying and exploring multi-scale biological networks. ETCM v2.0 may be a major data warehouse for the quality marker identification of TCMs, the TCM-derived drug discovery and repurposing, and the pharmacological mechanism investigation of TCMs against various human diseases.

ObjectiveTo investigate whether the effects of paeonol （Pae） on angiotensin Ⅱ （AngⅡ）-induced senescence in vascular smooth muscle cells （VSMCs） were related to angiotensinogen of silencing regulatory information factor 6 （SIRT6）/adenosine diphosphate ribose polymerase 1 （PARP1） signaling pathway in VSMCs. MethodThe model of VSMC-stress aging induced by AngⅡ （100 nmol·L^-1） was established. The rats were divided into normal group， model group， low， medium， and high-concentration Pae groups （30， 60， 120 μmol·L^-1）. The positive rate of cell senescence was detected by SA-β-Gal staining， the ability of cell proliferation was detected by the cell counting kit-8 （CCK-8） method， the expression of SIRT6， PARP1， p16， p21， p53， proliferating cell nuclear antigen （PCNA）， deoxyribonucleic acid （DNA）-damaged protein γ-H2AX was detected by Western blot， and VSMC proliferation was detected by EdU staining. The silenced VSMCs were prepared by siRNA-SIRT6 transfection， and the protein expressions of SIRT6， PARP1， p16， and γ-H2AX in VSMCs silenced by SIRT6 were observed. ResultThe results of SA-β-Gal staining showed that the senescence positive rate of SA-β-Gal staining in the model group was higher than that in the normal group （P<0.01）， and the positive rate of SA-β-Gal staining in the Pae group was significantly lower than that in the model group （P<0.05， P<0.01）. The results of Western blot showed that as compared with the normal group， the expression of PCNA， SIRT6， and PARP1 in the model group was down-regulated， and the expression of aging-related proteins p16， p21， p53， and γ-H2AX was up-regulated in the model group （P<0.05， P<0.01）. Compared with the model group， Pae promoted the protein expression of PCNA， SIRT6， and PARP1 and inhibited the protein expression of p16， p21， p53， and γ-H2AX in a dose-dependent manner （P<0.05， P<0.01）. The results of EdU staining showed that the number of EdU positive cells in the model group was lower than that in the normal group （P<0.01）， and the number of EdU positive cells in Pae groups was significantly higher than that in the model group （P<0.05， P<0.01）. After SIRT6 silencing， the effects of Pae on promoting SIRT6 and PARP1 and inhibiting P16 were reversed （P<0.05， P<0.01）. In addition， the addition of SIRT6 inhibitor （IN-1） promoted the occurrence of cell senescence induced by AngⅡ （P<0.05， P<0.01）. ConclusionPae can effectively inhibit the aging of VSMCs， and its mechanism may be related to the regulation of SIRT6/PARP1 signal pathway.

Background: The efficacy of ustekinumab (UST) in the treatment of patients with inflammatory bowel disease (IBD) has been affirmed abroad, but its efficacy and safety have not been reported in China due to its short term of use. Aims: To analyze the clinical efficacy and safety of UST in the treatment of IBD. Methods: The clinical data of IBD patients treated with UST from November 2020 to June 2022 in the First Affiliated Hospital of Air Force Medical University were analyzed retrospectively. Results: A total of 46 patients with IBD treated with UST were enrolled, including 41 patients with Crohn’s disease (CD) and 5 patients with ulcerative colitis (UC). At the 8