Objective To evaluate the diagnostic performance of the minimum-cost-path-based CT angiography-derived fractional flow reserve(MCP-FFR)and the deep learning-driven CT angiography-derived fractional flow reserve(DeepCL-FFR),and to particularly explore the potential value of the DeepCL algorithm in improving diagnostic accuracy within the"gray zone."Methods A retrospective analysis was conducted on 151 coronary vessels from 109 patients with coronary artery disease,who were hospitalized at the General Hospital of the People's Liberation Army between January 2020 and June 2021.Pearson correlation and Bland-Altman plots were employed to assess the correlation and agreement of the two CT-FFR methods with invasive FFR.A CT-FFR range of 0.70-0.80 was defined as the diagnostic"gray zone."The accuracy,sensitivity,specificity,positive predictive value,and negative predictive value for detecting hemodynamic abnormalities were calculated and analyzed.The DeLong test was used to compare the areas under the receiver operating characteristic curves(AUC)between the two CT-FFR calculation methods.Results Both CT-FFR methods exhibited a positive correlation with invasive FFR(MCP-FFR:r=0.75,P＜0.001;DeepCL-FFR:r=0.86,P＜0.001)and showed good agreement(MCP-FFR:mean difference=0.010,P=0.351;DeepCL-FFR:mean difference=-0.003,P=0.772).Both DeepCL-FFR(AUC 0.97,95％CI 0.94-0.99)and MCP-FFR(AUC 0.92,95％CI 0.88-0.97)demonstrated favorable diagnostic performance for detecting hemodynamic abnormalities(P=0.122).In the"gray zone"for hemodynamic abnormality,the diagnostic accuracy of MCP-FFR was 68.8％,whereas DeepCL-FFR increased it to 89.7％.DeepCL-FFR also exhibited superior diagnostic performance(AUC 0.89,95％CI 0.73-0.99)within the"gray zone,"which was significantly higher than that of MCP-FFR(AUC 0.71,95％CI 0.54-0.87)(P＜0.001).Conclusions The deep learning-driven coronary centerline extraction algorithm,DeepCL,demonstrates superior diagnostic performance in CT-FFR for detecting hemodynamic abnormalities,particularly by significantly improving diagnostic accuracy in the"gray zone."

Acute lateral ankle sprain (ALAS) is one of the most common sport injuries, with high incidence, recurrence and disability rates. Currently, exercise rehabilitation-based non-surgical treatment is the primary management approach for ALAS. However, there remain improper practices such as excessive immobilization or uncontrolled activity, which contribute to recurrent sprains and chronic ankle instability, significantly impairing patients′ athletic function and quality of life. To standardize the non-surgical management of ALAS, improve the cure rates, and reduce the recurrence and disability rates, Chinese Sports Rehabilitation Medicine Training Project of Chinese Medical Association, Foot and Ankle Basics and Orthopedics Group, Orthopedic Branch of Chinese Medical Doctor Association, and Sports Medicine Branch of Jiangsu Medical Association organized relevant experts to formulate Expert consensus on non-surgical treatment for acute lateral ankle sprain ( version 2025), following the principles of scientific vigor, practicality, and innovation. Thirteen recommendations were proposed for standardized treatment protocols across different healing phases, aiming to provide references for standard management of ALAS and improve the therapeutic outcomes.

BACKGROUND: Our understanding of the correlation between postdischarge cancer and mortality in patients with coronary artery disease (CAD) remains incomplete. The aim of this study was to investigate the relationships between postdischarge cancers and all-cause mortality and cardiovascular mortality in CAD patients. METHODS: In this retrospective cohort study, 25% of CAD patients without prior cancer history who underwent coronary artery angiography between January 1, 2011 and December 31, 2015, were randomly enrolled using SPSS 26.0. Patients were monitored for the incidence of postdischarge cancer, which was defined as cancer diagnosed after the index hospitalization, survival status and cause of death. Cox regression analysis was used to explore the association between postdischarge cancer and all-cause mortality and cardiovascular mortality in CAD patients. RESULTS: A total of 4085 patients were included in the final analysis. During a median follow-up period of 8 years, 174 patients (4.3%) developed postdischarge cancer, and 343 patients (8.4%) died. A total of 173 patients died from cardiovascular diseases. Postdischarge cancer was associated with increased all-cause mortality risk (HR = 2.653, 95% CI: 1.727-4.076, P < 0.001) and cardiovascular mortality risk (HR = 2.756, 95% CI: 1.470-5.167, P = 0.002). Postdischarge lung cancer (HR = 5.497, 95% CI: 2.922-10.343, P < 0.001) and gastrointestinal cancer (HR = 1.984, 95% CI: 1.049-3.750, P = 0.035) were associated with all-cause mortality in CAD patients. Postdischarge lung cancer was significantly associated with cardiovascular death in CAD patients (HR = 4.979, 95% CI: 2.114-11.728, P < 0.001), and cardiovascular death was not significantly correlated with gastrointestinal cancer or other types of cancer. CONCLUSIONS Postdischarge cancer was associated with all-cause mortality and cardiovascular mortality in CAD patients. Compared with other cancers, postdischarge lung cancer had a more significant effect on all-cause mortality and cardiovascular mortality in CAD patients.

This study aims to explore the mechanism of Jiaotai Pills in treating depression based on metabolomics and network pharmacology. The chemical constituents of Jiaotai Pills were identified by UHPLC-Orbitrap Exploris 480, and the targets of Jiaotai Pills and depression were retrieved from online databases. STRING and Cytoscape 3.7.2 were used to construct the protein-protein interaction network of core targets of Jiaotai Pills in treating depression and the "compound-target-pathway" network. DAVID was used for Gene Ontology(GO) function and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analyses of the core targets. The mouse model of depression was established with chronic unpredictable mild stress(CUMS) and treated with different doses of Jiaotai Pills. The behavioral changes and pathological changes in the hippocampus were observed. UHPLC-Orbitrap Exploris 120 was used for metabolic profiling of the serum, from which the differential metabolites and related metabolic pathways were screened. A "metabolite-reaction-enzyme-gene" network was constructed for the integrated analysis of metabolomics and network pharmacology. A total of 34 chemical components of Jiaotai Pills were identified, and 143 core targets of Jiaotai Pills in treating depression were predicted, which were mainly involved in the arginine and proline, sphingolipid, and neurotrophin metabolism signaling pathways. The results of animal experiments showed that Jiaotai Pills alleviated the depression behaviors and pathological changes in the hippocampus of the mouse model of CUMS-induced depression. In addition, Jiaotai Pills reversed the levels of 32 metabolites involved in various pathways such as arginine and proline metabolism, sphingolipid metabolism, and porphyrin metabolism in the serum of model mice. The integrated analysis showed that arginine and proline metabolism, cysteine and methionine metabolism, and porphyrin metabolism might be the key pathways in the treatment of depression with Jiaotai Pills. In conclusion, metabolomics combined with network pharmacology clarifies the antidepressant mechanism of Jiaotai Pills, which may provide a basis for the clinical application of Jiaotai Pills in treating depression.
Animals ; Drugs, Chinese Herbal/chemistry* ; Depression/genetics* ; Mice ; Network Pharmacology ; Metabolomics ; Male ; Disease Models, Animal ; Humans ; Protein Interaction Maps/drug effects* ; Antidepressive Agents

The chemical constituents of the chloroform extract of the 90% methanol extract obtained from the dried branches and leaves of Croton lauioides were investigated. By using silica gel column chromatography, C_(18 )column chromatography, MCI column chromatography, and semi-preparative high-performance liquid chromatography(HPLC), six compounds were isolated. Their structures were identified as lauioidine(1), 2α-methoxy-8α-hydroxy-6-oxogermacra-1(10),7(11)-dien-8,12-olide(2), myrrhanolide B(3), gossweilone(4), 6β,7β-epox-4α-hydroxyguaian-10-ene(5), and 4(15)-eudesmane-1β,5α-diol(6) by analyzing the HR-ESI-MS, IR, ECD, 1D NMR and 2D NMR data, as well as their physicochemical properties. All compounds were isolated from C. lauioides for the first time, among which compound 1 is a new nor-clerodane diterpenoid.
Croton/chemistry* ; Diterpenes, Clerodane/isolation & purification* ; Molecular Structure ; Drugs, Chinese Herbal/isolation & purification* ; Magnetic Resonance Spectroscopy ; Chromatography, High Pressure Liquid

Based on the α7 nicotinic acetylcholine receptor(α7nAChR), this study examined how tetrahydropalmatine(THP) affected BV2 microglia exposed to lipopolysaccharide(LPS), aiming to clarify the possible mechanism underlying the anti-depression effect of THP from the perspectives of preventing inflammation and regulating polarization. First, after molecular docking and determination of the content of Corydalis saxicola Bunting total alkaloids, THP was initially identified as a possible anti-depression component. The BV2 microglia model of inflammation was established with LPS. BV2 microglia were allocated into a normal group, a model group, low-and high-dose(20 and 40 μmol·L~(-1), respectively) THP groups, and a THP(20 μmol·L~(-1))+α7nAChR-specific antagonist MLA(1 μmol·L~(-1)) group. The CCK-8 assay was used to screen the safe concentration of THP. A light microscope was used to examine the morphology of the cells. Western blot and immunofluorescence were used to determine the expression of α7nAChR. qRT-PCR was performed to determine the mRNA levels of inducible nitric oxide synthase(iNOS), cluster of differentiation 86(CD86), suppressor of cytokine signaling 3(SOCS3), arginase-1(Arg-1), cluster of differentiation 206(CD206), tumor necrosis factor(TNF)-α, interleukin(IL)-6, and IL-1β. Enzyme-linked immunosorbent assay(ELISA) was employed to measure the levels of TNF-α, IL-6, and IL-1β in the cell supernatant. The experimental results showed that THP at concentrations of 40 μmol·L~(-1) and below had no effect on BV2 microglia. THP improved the morphology of BV2 microglia, significantly up-regulated the protein level of α7nAChR, significantly down-regulated the mRNA levels of iNOS, CD86, SOCS3, TNF-α, IL-6, and IL-1β, significantly up-regulated the mRNA levels of Arg-1 and CD206, and dramatically lowered the levels of TNF-α, IL-6, and IL-1β in the cell supernatant. However, the antagonist MLA abolished the above-mentioned ameliorative effects of THP on LPS-treated BV2 microglia. As demonstrated by the aforementioned findings, THP protected LPS-treated BV2 microglia by regulating the M1/M2 polarization and preventing inflammation, which might be connected to the regulation of α7nAChR on BV2 microglia.
Berberine Alkaloids/chemistry* ; alpha7 Nicotinic Acetylcholine Receptor/chemistry* ; Microglia/metabolism* ; Mice ; Animals ; Cell Line ; Corydalis/chemistry* ; Humans ; Molecular Docking Simulation ; Inflammation/drug therapy* ; Nitric Oxide Synthase Type II/immunology* ; Tumor Necrosis Factor-alpha/immunology*

Objective To discuss the effect of interleukin-17A(IL-17A)and transforming growth factor-β1(TGF-β1)on the benign tracheal stenosis after tracheal injury in experimental dogs.Methods The trachea stenosis model of healthy Beagle dogs was established by burning the middle part of trachea with electric snare under bronchoscopy guidance.A total of 21 dogs were divided into normal group(n=3,receiving normal feeding),molding group(n=12,after airway modeling every 3 dogs were sacrificed each week for 4 weeks),IL-17A suppression group(n=3,receiving Secukinumab after airway modeling),and IL-17A inhibitor+TGF-β1 inhibitor group(n=3,receiving Secukinumab and SB43154 after airway modeling).Bronchoscopy and CT scan were performed once a week,and the stenosis degree was calculated.RT-qPCR,immunohistochemistry,and HE staining of the obtained tracheal tissues were performed.Results Within 1-4 weeks after molding,in module-making dogs the degree of stenosis of the injured trachea gradually increased,and the expressions of ECM-related proteins,TGF-β1 and IL-17A were up-regulated.After treatment with IL-17A inhibitors,the inflammatory infiltration and granulation tissue hyperplasia were reduced and the early tracheal stenosis was improved(P＜0.05).The combination use of IL-17A inhibitor and TGF-β1 inhibitor had a better remission effect(P＜0.05).Conclusion IL-17A and TGF-β1 may synergistically affect the formation of tracheal stenosis.

Objective:To explore the training experiences of palliative care nurses participating in a prognosis disclosure workshop based on Kolb's experiential learning model, and to provide references for future educational programs in palliative care nursing.Methods:Using purposive sampling, 11 nurses were recruited who had participated in the "Palliative Care Competency Training Program for Nurses" in Shanghai between March and May 2025 and selected the Third Affiliated Hospital of Naval Medical University as their clinical training site. Semi-structured interviews were conducted, and data were analyzed using Colaizzi's seven-step method.Results:A total of three major themes emerged: a sense of benefit from enhanced competencies; complex emotional experiences; recommendations for course optimisation.Conclusions:Workshops based on Kolb's experiential learning model offer positive value in palliative care education. They effectively improve core competencies such as communication and empathy. However, the emotional experiences of nurses must also be considered, and multifaceted optimizations to the training design are recommended to further enhance training outcomes.

Objective:To explore the training experiences of palliative care nurses participating in a prognosis disclosure workshop based on Kolb's experiential learning model, and to provide references for future educational programs in palliative care nursing.Methods:Using purposive sampling, 11 nurses were recruited who had participated in the "Palliative Care Competency Training Program for Nurses" in Shanghai between March and May 2025 and selected the Third Affiliated Hospital of Naval Medical University as their clinical training site. Semi-structured interviews were conducted, and data were analyzed using Colaizzi's seven-step method.Results:A total of three major themes emerged: a sense of benefit from enhanced competencies; complex emotional experiences; recommendations for course optimisation.Conclusions:Workshops based on Kolb's experiential learning model offer positive value in palliative care education. They effectively improve core competencies such as communication and empathy. However, the emotional experiences of nurses must also be considered, and multifaceted optimizations to the training design are recommended to further enhance training outcomes.

Objective To evaluate the diagnostic performance of the minimum-cost-path-based CT angiography-derived fractional flow reserve(MCP-FFR)and the deep learning-driven CT angiography-derived fractional flow reserve(DeepCL-FFR),and to particularly explore the potential value of the DeepCL algorithm in improving diagnostic accuracy within the"gray zone."Methods A retrospective analysis was conducted on 151 coronary vessels from 109 patients with coronary artery disease,who were hospitalized at the General Hospital of the People's Liberation Army between January 2020 and June 2021.Pearson correlation and Bland-Altman plots were employed to assess the correlation and agreement of the two CT-FFR methods with invasive FFR.A CT-FFR range of 0.70-0.80 was defined as the diagnostic"gray zone."The accuracy,sensitivity,specificity,positive predictive value,and negative predictive value for detecting hemodynamic abnormalities were calculated and analyzed.The DeLong test was used to compare the areas under the receiver operating characteristic curves(AUC)between the two CT-FFR calculation methods.Results Both CT-FFR methods exhibited a positive correlation with invasive FFR(MCP-FFR:r=0.75,P＜0.001;DeepCL-FFR:r=0.86,P＜0.001)and showed good agreement(MCP-FFR:mean difference=0.010,P=0.351;DeepCL-FFR:mean difference=-0.003,P=0.772).Both DeepCL-FFR(AUC 0.97,95％CI 0.94-0.99)and MCP-FFR(AUC 0.92,95％CI 0.88-0.97)demonstrated favorable diagnostic performance for detecting hemodynamic abnormalities(P=0.122).In the"gray zone"for hemodynamic abnormality,the diagnostic accuracy of MCP-FFR was 68.8％,whereas DeepCL-FFR increased it to 89.7％.DeepCL-FFR also exhibited superior diagnostic performance(AUC 0.89,95％CI 0.73-0.99)within the"gray zone,"which was significantly higher than that of MCP-FFR(AUC 0.71,95％CI 0.54-0.87)(P＜0.001).Conclusions The deep learning-driven coronary centerline extraction algorithm,DeepCL,demonstrates superior diagnostic performance in CT-FFR for detecting hemodynamic abnormalities,particularly by significantly improving diagnostic accuracy in the"gray zone."