ObjectiveTo systematically assess the public health governance capacity in Zhejiang Province, to conduct an in-depth analysis of its strengths and weaknesses, so as to provide scientific basis and strategic recommendations for further enhancement. MethodsA systematic collection of policy documents, public information reports, and research literature related to public health governance capacity in Zhejiang Province from 2002 to 2023 was conducted (encompassing a total of 1 263 policy documents, 138 pieces of information reports and 631 research articles). Based on the evaluation criteria suitable for public health systems previously developed by the research team, the basic status and magnitude of change in public health governance capacity in Zhejiang Province was evaluated. Additionally, normative gap analyses were employed to identify the strengths and weaknesses. ResultsZhejiang Province ranked 4th nationwide in terms of public health governance capacity with a score of 733.4 points (1 000.0-point maximum). The province has effectively implemented the principle of health first (scoring 698.5 points in the assessment of health-first strategy implementation) and attached sufficient importance to health-related goals (scoring 658.2 points in the scientific rationality of goal setting). However, the implementation of inter-departmental coordination and incentive mechanisms only scored 178.7 points, the feasibility of management and monitoring mechanisms scored even lower at only 144.0 points, and the coverage of incentive mechanisms scored 286.0 points. ConclusionZhejiang Province has effectively implemented its health first strategy and attached great importance to health targets, but still needs to strengthen cross-departmental coordination mechanisms and health-oriented incentives.

BACKGROUND:The development of artificial intelligence in the medical field is rapidly advancing,with increasing research on its applications in the field of bone trauma.Through bibliometric analysis,this paper analyzed the research hotspots of artificial intelligence in the field of bone trauma in recent years,and predicted the future research trend. OBJECTIVE:To summarize the development history,research status,hot spots,and future development trends of artificial intelligence technology in the field of bone trauma to provide new insights for future research. METHODS:This study selected relevant literature from the Web of Science core database,covering the period from the inception to August 2023,and retrieved 420 articles related to the application of artificial intelligence,machine learning,and deep learning in the field of bone trauma.After manual screening,202 articles related to this article were exported,and Citespace software was used for visual analysis of cooperation of countries,institutions,cited journals,citation analysis,keyword co-occurrence,and other aspects. RESULTS AND CONCLUSION:(1)The overall number of publications from the 202 selected articles showed an upward trend,indicating significant research potential for future studies.The country with the highest centrality and the highest publication volume was the United States.The University of California(USA)was the most prolific research institution.(2)The top five most commonly used keywords in bone trauma research using artificial intelligence were deep learning,artificial intelligence,bone density,machine learning,and diagnosis.The keyword with the highest centrality was bone density,and the keyword with the highest frequency was deep learning.(3)The top 10 most cited reference papers provided comprehensive insights into the feasibility of applying artificial intelligence techniques to the diagnosis of bone trauma from various perspectives.Among them,eight papers focused on bone and joint injuries and deep convolutional neural networks.One paper discussed the use of deep learning in detecting osteoporosis in CT scans to prevent fragility fractures,while another paper explored the correlation between the application of artificial intelligence in identifying changes in skin texture and the recognition of bone characteristics.(4)In the future,the research hotspots of artificial intelligence will mainly focus on the specific study of fractures caused by bone and joint trauma and osteoporosis.The research trend mainly focuses on improving the performance of artificial intelligence algorithms,using new artificial intelligence technologies to accurately classify and quickly and efficiently diagnose bone injuries,especially for the diagnosis of complex and hidden fractures.By establishing finite element analysis models,more standardized evaluations of bone injuries can be achieved.

The chemical constituents in dried roots of Atractylodes macrocephala were investigated in this study. Through utilizing normal-phase silica gel and ODS column chromatography, TLC, and semi-preparative HPLC, 4 new sesquiterpenoids were purified from the ethyl acetate extract of A. macrocephala. By various spectroscopic techniques, such as 1D and 2D NMR, HR-ESI-MS, IR, UV, and CD, their structures were identified as atractylmacron A (1), 9β-hydroxyasterolide (2), atractylenolide H (3), atractylenolide J (4). Compound 1 possesses a rare 6/7 bicyclic skeleton.

Nine compounds were isolated and purified from 90% ethanol extract of Alstonia mairei Lévl by using various chromatographic methods, including silica gel, SephadexLH-20, MCI Gel and ODS column chromatography, combined with semi-preparative liquid phase separation methods. Modern spectroscopic methods (1D and 2D NMR, UV, IR, MS, etc.) were used to identify the structures of the isolated compounds. They were identified as mairoside A (1), 3′,6-di-O-sinaloylsucrose (2), myristic acid (3), methyl myristate (4), ethyl myristate (5), 3,4,5-trimethoxycinnamic acid (6), 3,4,5-trimethoxybenzoic acid (7), vinoline (8), kaempferol-3-O-rutinoside (9), among which compound 1 is a new glycoside, compounds 4 and 5 are new natural products, and the nuclear magnetic data of compound 4 were reported for the first time.

Eight compounds were isolated and purified from the ethyl acetate part of 70% acetone extract of Rehmannia glutinosa by various chromatographic techniques such as silica gel, MCI gel CHP-20, ODS, Toyopearl HW-40C, combined with TLC and semi-preparative HPLC. Their structures were elucidated by modern spectroscopy techniques (NMR, MS, UV, IR), and identified as neomartynoside A (1), osmanthuside B₆ (2), martynoside (3), isomartynoside (4), (E)-p-hydroxycinnamic acid (5), caffeic acid (6), ferulic acid (7), and methyl caffeate (8). Compound 1 is a new phenylethanol glycoside, which was identified as neomartynoside A. Compound 2 was isolated from Rehmannia glutinosa for the first time. In addition, compounds 2, 6 and 7 significantly increased relative glucose consumption, showing potential hypoglycemic activity.

Metabolic-associated fatty liver disease (MAFLD) and osteoporosis (OP) are two very common metabolic diseases. A growing body of experimental evidence supports a pathophysiological link between MAFLD and OP. MAFLD is often associated with the development of OP. Rutaecarpine (RUT) is one of the main active components of Chinese medicine Euodiae Fructus. Our previous studies have demonstrated that RUT has lipid-lowering, anti-inflammatory and anti-atherosclerotic effects, and can improve the OP of rats. However, whether RUT can improve both fatty liver and OP symptoms of MAFLD mice at the same time remains to be investigated. In this study, we used C57BL/6 mice fed a high-fat diet (HFD) for 4 months to construct a MAFLD model, and gave the mice a low dose (5 mg·kg^-1) and a high dose (15 mg·kg^-1) of RUT by gavage for 4 weeks. The effects of RUT on liver steatosis and bone metabolism were then evaluated at the end of the experiment [this experiment was approved by the Experimental Animal Ethics Committee of Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences (approval number: IMB-20190124D₃03)]. The results showed that RUT treatment significantly reduced hepatic steatosis and lipid accumulation, and significantly reduced bone loss and promoted bone formation. In summary, this study shows that RUT has an effect of improving fatty liver and OP in MAFLD mice.

Objective To explore the effects of nicotinamide mononucleotide （NMN） on hypertensive rats. Methods Two rat hypertension models including spontaneously hypertensive rats（SHR）and two-kidney two-clip （2K2C） rats were used to be given single, long-term or lifelong administration of NMN respectively. NMN’s effects were assessed comprehensively by monitoring survival time, blood pressure levels, and the extent of organ damage in hypertensive model rats. Results It was revealed that NMN did not exhibit protective effects in terms of lowering blood pressure levels, reducing organ damage or increasing survival time in hypertensive rats. Conclusion This study suggested that NMN did not demonstrate anti-hypertensive effects in rat hypertension models and could provide valuable insights for future clinical observation on NMN.

BACKGROUND: Non-invasive computed tomography angiography (CTA)-based fractional flow reserve (CT-FFR) could become a gatekeeper to invasive coronary angiography. Deep learning (DL)-based CT-FFR has shown promise when compared to invasive FFR. To evaluate the performance of a DL-based CT-FFR technique, DeepVessel FFR (DVFFR). METHODS: This retrospective study was designed for iScheMia Assessment based on a Retrospective, single-center Trial of CT-FFR (SMART). Patients suspected of stable coronary artery disease (CAD) and undergoing both CTA and invasive FFR examinations were consecutively selected from the Beijing Anzhen Hospital between January 1, 2016 to December 30, 2018. FFR obtained during invasive coronary angiography was used as the reference standard. DVFFR was calculated blindly using a DL-based CT-FFR approach that utilized the complete tree structure of the coronary arteries. RESULTS: Three hundred and thirty nine patients (60.5 ±10.0 years and 209 men) and 414 vessels with direct invasive FFR were included in the analysis. At per-vessel level, sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of DVFFR were 94.7%, 88.6%, 90.8%, 82.7%, and 96.7%, respectively. The area under the receiver operating characteristics curve (AUC) was 0.95 for DVFFR and 0.56 for CTA-based assessment with a significant difference (P < 0.0001). At patient level, sensitivity, specificity, accuracy, PPV and NPV of DVFFR were 93.8%, 88.0%, 90.3%, 83.0%, and 95.8%, respectively. The computation for DVFFR was fast with the average time of 22.5 ± 1.9 s. CONCLUSIONS The results demonstrate that DVFFR was able to evaluate lesion hemodynamic significance accurately and effectively with improved diagnostic performance over CTA alone. Coronary artery disease (CAD) is a critical disease in which coronary artery luminal narrowing may result in myocardial ischemia. Early and effective assessment of myocardial ischemia is essential for optimal treatment planning so as to improve the quality of life and reduce medical costs.

OBJECTIVE: To explore the potential effects and mechanisms of Liang-Ge-San (LGS) for the treatment of acute respiratory distress syndrome (ARDS) through network pharmacology analysis and to verify LGS activity through biological experiments. METHODS: The key ingredients of LGS and related targets were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. ARDS-related targets were selected from GeneCards and DisGeNET databases. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed using the Metascape Database. Molecular docking analysis was used to confirm the binding affinity of the core compounds with key therapeutic targets. Finally, the effects of LGS on key signaling pathways and biological processes were determined by in vitro and in vivo experiments. RESULTS: A total of LGS-related targets and 496 ARDS-related targets were obtained from the databases. Network pharmacological analysis suggested that LGS could treat ARDS based on the following information: LGS ingredients luteolin, wogonin, and baicalein may be potential candidate agents. Mitogen-activated protein kinase 14 (MAPK14), recombinant V-Rel reticuloendotheliosis viral oncogene homolog A (RELA), and tumor necrosis factor alpha (TNF-α) may be potential therapeutic targets. Reactive oxygen species metabolic process and the apoptotic signaling pathway were the main biological processes. The p38MAPK/NF-κ B signaling pathway might be the key signaling pathway activated by LGS against ARDS. Moreover, molecular docking demonstrated that luteolin, wogonin, and baicalein had a good binding affinity with MAPK14, RELA, and TNF α. In vitro experiments, LGS inhibited the expression and entry of p38 and p65 into the nucleation in human bronchial epithelial cells (HBE) cells induced by LPS, inhibited the inflammatory response and oxidative stress response, and inhibited HBE cell apoptosis (P<0.05 or P<0.01). In vivo experiments, LGS improved lung injury caused by ligation and puncture, reduced inflammatory responses, and inhibited the activation of p38MAPK and p65 (P<0.05 or P<0.01). CONCLUSION LGS could reduce reactive oxygen species and inflammatory cytokine production by inhibiting p38MAPK/NF-κ B signaling pathway, thus reducing apoptosis and attenuating ARDS.
Drugs, Chinese Herbal/pharmacology* ; Respiratory Distress Syndrome/enzymology* ; p38 Mitogen-Activated Protein Kinases/metabolism* ; NF-kappa B/metabolism* ; Animals ; Signal Transduction/drug effects* ; Molecular Docking Simulation ; Humans ; Male ; Network Pharmacology ; Apoptosis/drug effects* ; Mice

OBJECTIVE: To investigate the effect of zedoarondiol on neovascularization of atherosclerotic (AS) plaque by exosomes experiment. METHODS: ApoE^-/- mice were fed with high-fat diet to establish AS model and treated with high- and low-dose (10, 5 mg/kg daily) of zedoarondiol, respectively. After 14 weeks, the expressions of anti-angiogenic protein thrombospondin 1 (THBS-1) and its receptor CD36 in plaques, as well as platelet activation rate and exosome-derived miR-let-7a were detected. Then, zedoarondiol was used to intervene in platelets in vitro, and miR-let-7a was detected in platelet-derived exosomes (Pexo). Finally, human umbilical vein endothelial cells (HUVECs) were transfected with miR-let-7a mimics and treated with Pexo to observe the effect of miR-let-7a in Pexo on tube formation. RESULTS: Animal experiments showed that after treating with zedoarondiol, the neovascularization density in plaques of AS mice was significantly reduced, THBS-1 and CD36 increased, the platelet activation rate was markedly reduced, and the miR-let-7a level in Pexo was reduced (P<0.01). In vitro experiments, the platelet activation rate and miR-let-7a levels in Pexo were significantly reduced after zedoarondiol's intervention. Cell experiments showed that after Pexo's intervention, the tube length increased, and the transfection of miR-let-7a minics further increased the tube length of cells, while reducing the expressions of THBS-1 and CD36. CONCLUSION Zedoarondiol has the effect of inhibiting neovascularization within plaque in AS mice, and its mechanism may be potentially related to inhibiting platelet activation and reducing the Pexo-derived miRNA-let-7a level.
Animals ; MicroRNAs/genetics* ; Exosomes/drug effects* ; Plaque, Atherosclerotic/genetics* ; Neovascularization, Pathologic/genetics* ; Human Umbilical Vein Endothelial Cells/metabolism* ; Humans ; Blood Platelets/drug effects* ; Apolipoproteins E/deficiency* ; Thrombospondin 1/metabolism* ; CD36 Antigens/metabolism* ; Platelet Activation/drug effects* ; Male ; Mice ; Mice, Inbred C57BL