Objective: To evaluate the efficacy and safety of ruxolitinib combined with low-dose hormone for patients with acute graft-versus-host disease (aGVHD) after allogeneic hematopoietic stem cell transplantation (allo-HSCT). Methods: Thirty patients with aGVHD after allo-HSCT admitted to the Department of Hematology of the General Hospital of Western Theater Command from November 2021 to November 2024 were retrospectively analyzed. All patients were treated with low-dose hormone (methylprednisolone 0.3-1 mg kg -d ) combined with ruxolitinib 5-10 mg d . The efficacy and adverse reactions were observed during the follow-up period to analyze the survival outcomes of the patients. Results: A total of 30 patients with aGVHD after allo-HSCT were included in this study, consisting of 15 (50%) males and 15 (50%) females with a median age of 34 year-old (ranging from 14 to 62). Classification by disease type: there were 18 cases of acute myeloid leukemia, 4 cases of acute lymphoblastic leukemia, 4 cases of aplastic anemia, and 4 cases of myelodysplastic syndrome. Classification by aGVHD severity: there were 27 cases (90%) of Ⅱ-Ⅳ degree aGVHD and 11 cases (36.7%) of Ⅲ-Ⅳ degree aGVHD. Ruxolitinib in combination with low-dose glucocorticoid treatment yield responses in 28 (93.3%) patients, of which 27 (90%) achieved complete remission (CR), while 1 (3.3%) showed partial remission (PR). One patient (3.3%) had no response (NR), and 1 patient (3.3%) exhibited progressed disease (PD). Overall survival (OS) at 1 year of transplantation was 73.9% (95%CI 49.5% to 87.7%), progression-free survival (PFS) was 93.3% (95%CI 75.9% to 98.3%), non-relapse mortality (NRM) was 20.6% (95%CI 7.9% to 47.4%), and median survival time was 27.6 months. Conclusion: Ruxolitinib combined with low-dose hormones is safe and effective in the treatment of aGVHD after allo-HSCT.

AIM To study the chemical constituents from Dictamni Cortex.METHODS The 70％ethanol extract from Dictamni Cortex was isolated and purified by HP-20 macroporous resin,silica gel,MCI,ODS and preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.RESULTS Thirty-three compounds were isolated and identified as rutin(1),apigenin(2),catechin(3),hesperetin(4),leonuriside A(5),androsin(6),2-methoxy-4-acetylphenol-O-α-rhamnopyranosyl-(1"-6')-β-glucopyranoside(7),vanillic acid(8),gallic acid(9),4-hydroxybenzoic acid(10),benzoic acid(11),involcranoside B(12),benzyl β-D-glucopyranoside(13),bphenylethyl-rutinoside(14),1-bromonaphthalene(15),cimifugin(16),9(S),12(S),13(S)-trihydroxyoctadeca-10(E),15(Z)-dienoic acid(17),methyl-9,12,13-trihydroxyoctadeca-10,15-dienoate(18),7,8-dihydroxy-9,12(Z,Z)-octadecadienoic acid(19),vernolic acid(20),9,10(erythro)-dihydroxy-11 E-octadecadienoic acid methyl ester(21),(7Z,9E,13Z)-11-hydroxyhexadeca-7,9,13-trienoic acid(22),(7Z,10Z,14E,16Z,19Z)-13-hydroxydocosa-7,10,14,16,19-pentaenoic acid(23),(9E)-8,11,12-trihydroxyoctadecenoic acid methyl ester(24),n-hexanol-O-rutinoside(25),hexyl β-sophoroside(26),3-pentyl 6'-(3-hydroxy-3-methylglutaryl)-β-D-glucopyranoside(27),3-methylbut-3-enyl-6-O-β-D-glucopyranosyl-β-D-glucopyranoside(28),3-methyl-but-2-en-1-yl β-D-glucopyranoside(29),3-methylbutan-1-ol-β-D-glucopyranoside(30),pregnenolone(31),2-butoxytetrahydrofuran(32),psydrin(33).CONCLUSION Compounds 2-4,8-13,15-16,25-28 and 32-33 are isolated from Rutaceae family for the first time.

Objective To investigate the dosimetric differences in preoperative short-course volumetric modulated arc therapy(VMAT)for rectal cancer using different fluence smoothing(FS)levels in the Monaco Treatment Planning System(Monaco TPS).Methods Twenty rectal cancer patients who received preoperative neoadjuvant short-course VMAT at some hospital from September 2021 to December 2022 were retrospectively selected.Four groups of radiotherapy plans were formulated using the Monaco TPS for each case,which were classified into an off group,a low group,a medium group and a high group based on the FS levels.Then the four groups were compared in terms of the dosimetric parameters,monitor unit and number of the segments in the planning target volume(PTV)and organ at risk(OAR).Statistical analysis was performed using SPSS 27.0 software.Results All the four groups had the doses to the target volume meeting clinical requirements,which had no significant differences in the doses to 5％(D5％)and 95％(D95％)to the target volume and the maximum dose(Dmax),minimum dose(Dmin),mean dose(Dmean)and conformity index(all P＞0.05).Statistical differences were found between the homogeneity indexes of the four groups(P＜0.05),with the medium group behaving the best.The number of the segments rose while the mornitor units decreased siginificantly with the increase of FS levels,with the differences being statistically significant(P＜0.05).There were no significant differences between the V25,V20,V15 and V10 of the small intestine,the V25 and V20 of the bladder and the V15 and V10 of the left and right femur(all P＞0.05).Conclusion In preoperative short-course VMAT for rectal cancer,clinical requirements can be met with different FS levels in the Monaco TPS,and medium-level FS results in optimal overall dose distribution in terms of treatment planning.[Chinese Medical Equipment Journal,2025,46(5):48-53]

[This corrects the article DOI: 10.1016/j.apsb.2022.05.019.].

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

AIM To study the chemical constituents from Dictamni Cortex.METHODS The 70％ethanol extract from Dictamni Cortex was isolated and purified by HP-20 macroporous resin,silica gel,MCI,ODS and preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.RESULTS Thirty-three compounds were isolated and identified as rutin(1),apigenin(2),catechin(3),hesperetin(4),leonuriside A(5),androsin(6),2-methoxy-4-acetylphenol-O-α-rhamnopyranosyl-(1"-6')-β-glucopyranoside(7),vanillic acid(8),gallic acid(9),4-hydroxybenzoic acid(10),benzoic acid(11),involcranoside B(12),benzyl β-D-glucopyranoside(13),bphenylethyl-rutinoside(14),1-bromonaphthalene(15),cimifugin(16),9(S),12(S),13(S)-trihydroxyoctadeca-10(E),15(Z)-dienoic acid(17),methyl-9,12,13-trihydroxyoctadeca-10,15-dienoate(18),7,8-dihydroxy-9,12(Z,Z)-octadecadienoic acid(19),vernolic acid(20),9,10(erythro)-dihydroxy-11 E-octadecadienoic acid methyl ester(21),(7Z,9E,13Z)-11-hydroxyhexadeca-7,9,13-trienoic acid(22),(7Z,10Z,14E,16Z,19Z)-13-hydroxydocosa-7,10,14,16,19-pentaenoic acid(23),(9E)-8,11,12-trihydroxyoctadecenoic acid methyl ester(24),n-hexanol-O-rutinoside(25),hexyl β-sophoroside(26),3-pentyl 6'-(3-hydroxy-3-methylglutaryl)-β-D-glucopyranoside(27),3-methylbut-3-enyl-6-O-β-D-glucopyranosyl-β-D-glucopyranoside(28),3-methyl-but-2-en-1-yl β-D-glucopyranoside(29),3-methylbutan-1-ol-β-D-glucopyranoside(30),pregnenolone(31),2-butoxytetrahydrofuran(32),psydrin(33).CONCLUSION Compounds 2-4,8-13,15-16,25-28 and 32-33 are isolated from Rutaceae family for the first time.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Guided by the theory of "the kidney storing essence, governing the bones, and producing marrow", this study explored the mechanism of icariin(ICA) in regulating the osteogenic differentiation of rat bone mesenchymal stem cells(BMSCs) through caveolin-1(Cav1) via in vitro and in vivo experiments, aiming to provide a theoretical basis for the prevention and treatment of postmenopausal osteoporosis with traditional Chinese medicine(TCM). Primary cells were obtained from 4-week-old female SD rats using the whole bone marrow adherent method. Flow cytometry was used to detect the expression of surface markers CD29, CD90, CD11b, and CD45. The potential for osteogenic and adipogenic differentiation was assessed. The effect of ICA on cell viability was determined using the CCK-8 assay, and the impact of ICA on the formation of mineralized nodules was verified by alizarin red staining. A stable Cav1-silenced cell line was constructed using lentivirus. The effect of Cav1 silencing on osteogenic differentiation was observed via alizarin red staining. Western blot analysis was conducted to detect the expression of Cav1, Hippo/TAZ, and osteogenic markers such as Runt-related transcription factor 2(RUNX2) and alkaline phosphatase(ALP). The results showed that primary cells were successfully obtained using the whole bone marrow adherent method, positively expressing surface markers of rat BMSCs and possessing the potential for both osteogenic and adipogenic differentiation. The CCK-8 assay and alizarin red staining results indicated that 1×10~(-7) mol·L~(-1) was the optimal concentration of ICA for intervention in this experiment(P<0.05). During osteogenic induction, ICA inhibited Cav1 expression(P<0.05) while promoting TAZ expression(P<0.05). Alizarin red staining demonstrated that Cav1 silencing significantly promoted the osteogenic differentiation of BMSCs. After ICA intervention, TAZ expression was activated, and the expression of osteogenic markers ALP and RUNX2 was increased. In conclusion, Cav1 silencing significantly promotes the osteogenic differentiation of BMSCs, and ICA promotes this differentiation by inhibiting Cav1 and regulating the Hippo/TAZ signaling pathway.
Animals ; Mesenchymal Stem Cells/metabolism* ; Caveolin 1/genetics* ; Osteogenesis/drug effects* ; Rats, Sprague-Dawley ; Rats ; Cell Differentiation/drug effects* ; Female ; Signal Transduction/drug effects* ; Flavonoids/administration & dosage* ; Protein Serine-Threonine Kinases/genetics* ; Drugs, Chinese Herbal/pharmacology* ; Cells, Cultured ; Humans

The chemical constituents were systematically separated from the roots of Berberis polyantha by various chromatographic methods, including silica gel column chromatography, HP20 column chromatography, polyamide column chromatography, reversed-phase C_(18) column chromatography, and preparative high-performance liquid chromatography. The structures of the compounds were identified by physicochemical properties and spectroscopic techniques(1D NMR, 2D NMR, UV, MS, and CD). Four phenylpropanoids were isolated from the methanol extract of the roots of B. polyantha, and they were identified as(2R)-1-(4-hydroxy-3,5-dimethoxyphenyl)-1-propanone-O-β-D-glucopyranoside(1), methyl 4-hydroxy-3,5-dimethoxybenzoate(2),(+)-syringaresinol(3), and syringaresinol-4-O-β-D-glucopyranoside(4). Compound 1 was a new compound, and other compounds were isolated from this plant for the first time. The anti-inflammatory activity of these compounds was evaluated based on the release of nitric oxide(NO) in the culture of lipopolysaccharide(LPS)-induced RAW264.7 macrophages. At a concentration of 10 μmol·L~(-1), all the four compounds inhibited the LPS-induced release of NO in RAW264.7 cells, demonstrating potential anti-inflammatory properties.
Plant Roots/chemistry* ; Animals ; Mice ; Berberis/chemistry* ; RAW 264.7 Cells ; Macrophages/immunology* ; Drugs, Chinese Herbal/isolation & purification* ; Nitric Oxide/metabolism* ; Molecular Structure ; Anti-Inflammatory Agents/isolation & purification*