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Bortezomib is a novel proteasome inhibitor, which has been successfully used to treat mantle cell lymphoma and multiple myeloma. However, the direct effects of bortezomib on acute promyelocytic leukaemia (APL) have not been fully investigated. In the present study, the WST-8 assay, western blotting, flow cytometry, monodansylcadaverine staining and transmission electron microscopy were performed. It was demonstrated that bortezomib treatment induced a time- and dose-dependent decrease in the viability of NB4 cells. Bortezomib treatment induced cell apoptosis in NB4 cells, as assessed by Annexin V/propidium iodide analysis, and the detection of cleaved caspase-3, cleaved poly(ADP-ribose) polymerase, Bax and Bcl-2 expression. Furthermore, bortezomib treatment induced autophagy in NB4 cells, as indicated by autophagosome formation, p62 degradation, LC3-I to LC3-II conversion and formation of acidic autophagic vacuoles. Notably, autophagy induced by bortezomib was initiated prior to apoptosis. Inhibition of autophagy by knocking down Beclin-1 expression increased bortezomib-induced apoptosis in NB4 cells. Therefore, the present study revealed that the combination of bortezomib and autophagy inhibition may be a potential treatment strategy for APL.  相似文献   
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Introduction: Immune checkpoint inhibitors (ICI) are now a standard of care in the treatment of many cancers leading to durable responses in patients with metastatic disease. These agents are generally well tolerated but may lead to the occurrence of immune-related adverse events (irAEs). As any organ may be affected, clinicians should be aware of the broad range of clinical manifestations and symptoms and keep in mind that toxicities may occur late, at any point along a patient’s treatment course. Although the most common irAEs are rarely severe, some of them may be associated with great morbidity and even become life-threatening. The rate of occurrence, type and severity of irAEs may vary with the type of ICI; thus, grade 3 and 4 irAEs are reported in more than 55% of patients treated with the combination of ipilimumab 3 mg/kg and nivolumab 1 mg/kg.

Area covered: This review presents the management of irAEs resulting from checkpoint blockade, with a focus on rare irAEs.

Expert commentary: With the development of immuno-oncology and the expanding role of ICI, physicians have learnt to diagnose and treat most of the irAEs that can occur. This review provides an overview of current guidelines, previously published studies and our multidisciplinary team based practices.  相似文献   

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This study is focussed on micro-encapsulation of essential oils in polylactic acid (PLA) and a poly(methyl methacrylate) (PMMA) matrix as well as blends of the same. Microspheres were prepared by the solvent evaporation technique and characterised by scanning electron microscopy (SEM), differential scanning calorimetry (DSC) and Fourier transform infra-red spectroscopy (FTIR). The encapsulation efficiencies and release profiles of the essential oils were studied by gas chromatography mass spectrometry (GC-MS) and head-space solid-phase microextraction GC-MS, respectively. Furthermore, the microspheres were tested for antibacterial activity against both Gram-negative and Gram-positive bacterial strains.

The results showed that the microspheres compositions (PLA/PMMA ratio) have significant effect on their characteristics. The process adopted for preparing the microspheres promoted formation of spherical particles at the sizes of 1.5–9.5?µm. The highest encapsulation efficiency of the prepared microspheres was observed in systems consisting of linalool (81.10?±?10.0?wt. % for PLA system and 76.0?±?3.3?wt. % for PMMA system). Confirmation was also made that the release rate of the microspheres was affected by the size of the same.  相似文献   

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目的总结近年来股骨转子间骨折在稳定性重建方面的概念演化与研究进展。方法查阅国内外相关文献并结合自身经验,从股骨转子间骨折的解剖特点、稳定型骨折与不稳定型骨折分类、稳定性复位与不稳定性复位、术中加压初始稳定与术后滑动二次稳定、内固定术后稳定性评估、早期下地站立负重等方面进行总结分析。结果股骨转子间骨折发生于股骨颈干骺端转换区,具有天然的内翻不稳定倾向。骨折复位质量是影响后续内固定物安放的最重要前提因素。判断骨折复位质量有对线和对位两方面,对线采用 Garden 指数;在对位方面,随着皮质对位理念(正性、中性、负性)的提出,特别强调前内侧皮质的相互砥住支撑(解剖、正性),是获得骨折稳定性复位的关键,而不再强调后内侧小转子骨块的作用。术后影像学的稳定性评分为早期下地站立负重提供了量化指标。但术中的前内侧皮质支撑复位,在术后头颈骨块滑动获得二次稳定的过程中,仍有皮质对位丢失现象,需研究其危险因素和防范措施。结论股骨转子间骨折在取得良好对线的基础上,只要获得了前内侧皮质的相互砥住和支撑,并用内固定器械维持住,就获得了术后稳定性。术后稳定性评分优良者,可以安全地早期下地负重、站立行走活动。  相似文献   
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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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