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目的:观察非霍奇金淋巴瘤(non-Hodgkin's lymphoma,NHL)患者自体造血干细胞移植(autologous hematopoietic stem cell transplantation,ASCT)术后应用重组人α-2b干扰素(α-2b IFN)进行早期干预治疗的临床疗效。方法:选取18例行ASCT的NHL患者为研究对象,移植前疾病评估均未达到完全缓解(complete remission,CR),试验组血象恢复后给予IFN 3 000 000 U次/隔日干预治疗,3个月后停用;对照组未行干扰素干预治疗,分析总体疗效及两组对比的生存情况。结果:随访中位时间为34(10~50)个月,患者中位生存时间为37(31~45)个月,3年总体无进展生存(progressive free survival,PFS)、总生存(overall survivial,OS)分别为54.7%、66.8%。ASCT后试验组1年内无疾病复发,2年内复发率为12.5%;对照组1年内复发率为20%,2年内复发率为30%。结论:NHL患者在ASCT后给予重组人α-2b IFN早期干预治疗,患者耐受性好,可能降低移植后早期复发率。 相似文献
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《Respiratory investigation》2022,60(1):137-145
BackgroundSome chronic obstructive pulmonary disease (COPD) patients develop hypoxemia with disease progression, with some even requiring long-term oxygen therapy (LTOT). Lung function, especially diffusing capacity, and the annual decline in PaO2, are reported to be predictive factors of chronic respiratory failure. However, the association between lung morphometry evaluated using computed tomography (CT) images and LTOT initiation is unknown.MethodsWe retrospectively evaluated the relationship between clinical indices, including pulmonary function, body mass index (BMI), and CT parameters, at baseline and LTOT initiation in two prospective COPD cohorts. In the Nara Medical University cohort (n = 76), the low attenuation area (LAA) and its fractal dimension (fractal D) were adapted as the indices for parenchymal destruction in CT images. The association between these CT measurements and LTOT initiation was replicated in the Kyoto University cohort (n = 130).ResultsIn the Nara Medical University cohort, lower BMI (hazard ratio [HR]:0.70, p = 0.006), lower % diffusing capacity (%DLCO) (HR: 0.92, p = 0.006), lower %DLCO/VA (HR, 0.90, p = 0.008), higher RV/TLC (HR, 1.26, p = 0.012), higher LAA% (HR: 1.18, p = 0.001), and lower fractal D (HR: 3.27 × 10?8, p < 0.001) were associated with LTOT initiation. Multivariate analysis in the Kyoto University cohort confirmed that lower %DLCO and lower fractal D were independently associated with LTOT initiation, whereas LAA% was not.ConclusionFractal D, which is the index for morphometric complexity of LAA in CT analysis, is predictive of LTOT initiation in COPD patients. 相似文献
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《Journal of endodontics》2020,46(10):1455-1464
IntroductionThe aim of this study was to investigate whether mineral trioxide aggregate (MTA) can be modified with caffeic acid (CA) to form caffeic acid/mineral trioxide aggregate (CAMTA) cement and to evaluate its physicochemical and biological properties as well as its capability in immune suppression and angiogenesis.MethodsMTA was immersed in trishydroxymethyl aminomethane buffer with CA to allow coating onto MTA powders. X-ray diffractometry and tensile stress-strain tests were conducted to assess for physical characteristics of CAMTA and to evaluate for successful modification of MTA. Then, the CAMTA cement was immersed in simulated body fluid to evaluate its hydroxyapatite formation capabilities and Si release profiles. In addition, RAW 264.7 cells and human dental pulp stem cells were used to evaluate CAMTA’s immunosuppressive capabilities and cell responses, respectively. hDPSCs were also used to assess CAMTA’s angiogenic capabilities.ResultsThe X-ray diffractometry results showed that CA can be successfully coated onto MTA without disrupting or losing MTA’s original structural properties, thus allowing us to retain the initial advantages of MTA. CAMTA was shown to have higher mechanical properties compared with MTA and had rougher pitted surfaces, which were hypothesized to lead to enhanced adhesion, proliferation, and secretion of angiogenic- and odontogenic-related proteins. In addition, it was found that CAMTA was able to enhance hydroxyapatite formation and immunosuppressive capabilities compared with MTA.ConclusionsCAMTA cements were found to have improved physicochemical and biological characteristics compared with their counterpart. In addition, CAMTA cements had enhanced odontogenic, angiogenic, and immunosuppressive properties compared with MTA. All of the results of this study proved that CAMTA cements could be a biomaterial for future clinical applications and tissue engineering use. 相似文献
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《Diagnostic and interventional imaging》2020,101(9):555-564
PurposeThe purpose of this study was to determine whether computed tomography (CT)-based machine learning of radiomics features could help distinguish autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC).Materials and MethodsEighty-nine patients with AIP (65 men, 24 women; mean age, 59.7 ± 13.9 [SD] years; range: 21–83 years) and 93 patients with PDAC (68 men, 25 women; mean age, 60.1 ± 12.3 [SD] years; range: 36–86 years) were retrospectively included. All patients had dedicated dual-phase pancreatic protocol CT between 2004 and 2018. Thin-slice images (0.75/0.5 mm thickness/increment) were compared with thick-slices images (3 or 5 mm thickness/increment). Pancreatic regions involved by PDAC or AIP (areas of enlargement, altered enhancement, effacement of pancreatic duct) as well as uninvolved parenchyma were segmented as three-dimensional volumes. Four hundred and thirty-one radiomics features were extracted and a random forest was used to distinguish AIP from PDAC. CT data of 60 AIP and 60 PDAC patients were used for training and those of 29 AIP and 33 PDAC independent patients were used for testing.ResultsThe pancreas was diffusely involved in 37 (37/89; 41.6%) patients with AIP and not diffusely in 52 (52/89; 58.4%) patients. Using machine learning, 95.2% (59/62; 95% confidence interval [CI]: 89.8–100%), 83.9% (52:67; 95% CI: 74.7–93.0%) and 77.4% (48/62; 95% CI: 67.0–87.8%) of the 62 test patients were correctly classified as either having PDAC or AIP with thin-slice venous phase, thin-slice arterial phase, and thick-slice venous phase CT, respectively. Three of the 29 patients with AIP (3/29; 10.3%) were incorrectly classified as having PDAC but all 33 patients with PDAC (33/33; 100%) were correctly classified with thin-slice venous phase with 89.7% sensitivity (26/29; 95% CI: 78.6–100%) and 100% specificity (33/33; 95% CI: 93–100%) for the diagnosis of AIP, 95.2% accuracy (59/62; 95% CI: 89.8–100%) and area under the curve of 0.975 (95% CI: 0.936–1.0).ConclusionsRadiomic features help differentiate AIP from PDAC with an overall accuracy of 95.2%. 相似文献
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Rafiye Ciftciler Haluk Demiroglu Yahya Buyukasık Elifcan Aladag Salih Aksu Ibrahim C. Haznedaroglu Nilgun Sayınalp Osman Ozcebe Umit Yavuz Malkan Hakan Goker 《Clinical Lymphoma, Myeloma & Leukemia》2019,19(3):177-182