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Background: Parametrial infiltration (PMI) is an important indicator for staging and treatment of cervical cancer (CC). The potential of amide proton transfer-weighted (APTw) parameters of peritumor tissue in predicting PMI is still uncertain. This study aims to explore whether the APTw parameters of peritumor tissue can improve diagnostic value of diffusion-weighted imaging (DWI) in magnetic resonance imaging (MRI). Methods: Eighty-one patients with pathologic analysis-confirmed CC were enrolled in this retrospective study. All patients underwent APTw MRI and DWI. The APTw values of tumor (APTw-t), APTw values in peritumor tissues (APTw-p) and apparent diffusion coefficient (ADC) values were independently reviewed by two radiologists to map the regions of interest and measure the corresponding values. Receiver operating characteristic curves were generated to evaluate the diagnostic performance of these quantitative parameters. Results: The study patients were divided into the PMI group (n=22) and non-PMI group (n=59). The APTw-t and APTw-p values (%) of PMI group were higher than those of the non-PMI group [3.71 (interquartile range, IQR, 3.60-3.98) and 2.75 (IQR, 2.68-2.77) vs. 3.33 (IQR, 3.24-3.60) and 1.98 (IQR, 1.82-2.36); P<0.001]. The ADC values of PMI group were lower than those of non-PMI group [0.88 (IQR, 0.83-0.94) ×10-3 vs. 0.95 (IQR, 0.88-1.04)×10-3 mm2/sec; P<0.001]. The area under the curve (AUC) of APTw-t, APTw-p and ADC value for PMI diagnosis were 0.810, 0.831 and 0.806 respectively. In addition, the AUC value (0.918) of APTw-p + ADC was optimal, with a sensitivity and specificity of 91.20% and 87.20% respectively. Conclusions: APTw in peritumor tissues, combined with ADC value can be used to efficiently distinguish PMI of CC.
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OBJECTIVES: This study aimed to utilize MR radiomics-based machine learning classifiers on a large-sample, multicenter dataset to develop an optimal model for predicting malignant sinonasal tumors and tumor-like lesions. METHODS: This study included 1711 adult patients (875 benign and 836 malignant) with sinonasal tumors or tumor-like lesions from three institutions. Patients from institution 1 (n = 1367) constituted both the training and validation cohorts, while those from institution 2 and 3 (n = 158/186) made up the test cohorts. Manual segmentation of the region of interest of the tumor was performed on T1WI, T2WI, and contrast-enhanced T1WI (CE-T1WI). Data normalization, dimensional reductions, feature selection, and classifications were performed using ten machine-learning classifiers. Four fusion models, namely T1WI + T2WI, T1WI + CE-T1WI, T2WI + CE-T1WI, and T1WI + T2WI + CE-T1WI, were constructed using the top ten features with the highest contribution in feature selection in the optimal models of T1WI, T2WI, and CE-T1WI. The Delong test compared areas under the curve (AUC) between models. RESULTS: The AUCs of training/validation/test1/test2 datasets for T1WI, T2WI, and CE-T1WI were 0.900/0.842/0.872/0.839, 0.876/0.789/0.842/0.863, and 0.899/0.824/0.831/0.707, respectively. The fusion model from T1WI + T2WI + CE-T1WI had the highest AUC. The AUCs of training/validation/test1/test2 datasets were 0.947/0.849/0.871/0.887. The T1WI + T2WI + CE-T1WI model demonstrated a significantly higher AUC than the T2WI + CE-T1WI model in both cohorts (p < 0.05) and outperformed the T2WI model in test 1 (p = 0.008) and the T1WI model in test 2 (p = 0.006). CONCLUSIONS: This fusion model based on radiomics from T1WI + T2WI + CE-T1WI images and machine learning can improve the power in predicting malignant sinonasal tumors with high accuracy, resilience, and robustness. CLINICAL RELEVANCE STATEMENT: Our study proposes a radiomics-based machine learning fusion model from T1- and T2-weighted images and contrast-enhanced T1-weighted images, which can non-invasively identify the nature of sinonasal tumors and improve the performance in predicting malignant sinonasal tumors. KEY POINTS: Differentiating benign and malignant sinonasal tumors is difficult due to similar clinical presentations. A radiomics model from T1 + T2 + contrast-enhanced T1 images can identify the nature of sinonasal tumors. This model can help distinguish benign and malignant sinonasal tumors.
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PURPOSE: This study aimed to apply a newly developed semi-automatic phantom-less QCT (PL-QCT) to measure proximal humerus trabecular bone density based on chest CT and verify its accuracy and precision. METHODS: Subcutaneous fat of the shoulder joint and trapezius muscle were used as calibration references for PL-QCT BMD measurement. A self-developed algorithm based on a convolution map was utilized in PL-QCT for semi-automatic BMD measurements. CT values of ROIs used in PL-QCT measurements were directly used for phantom-based quantitative computed tomography (PB-QCT) BMD assessment. The study included 376 proximal humerus for comparison between PB-QCT and PL-QCT. Two sports medicine doctors measured the proximal humerus with PB-QCT and PL-QCT without knowing each other's results. Among them, 100 proximal humerus were included in the inter-operative and intra-operative BMD measurements for evaluating the repeatability and reproducibility of PL-QCT and PB-QCT. RESULTS: A total of 188 patients with 376 shoulders were involved in this study. The consistency analysis indicated that the average bias between proximal humerus BMDs measured by PB-QCT and PL-QCT was 1.0 mg/cc (agreement range - 9.4 to 11.4; P > 0.05, no significant difference). Regression analysis between PB-QCT and PL-QCT indicated a good correlation (R-square is 0.9723). Short-term repeatability and reproducibility of proximal humerus BMDs measured by PB-QCT (CV: 5.10% and 3.41%) were slightly better than those of PL-QCT (CV: 6.17% and 5.64%). CONCLUSIONS: We evaluated the bone quality of the proximal humeral using chest CT through the semi-automatic PL-QCT system for the first time. Comparison between it and PB-QCT indicated that it could be a reliable shoulder BMD assessment tool with acceptable accuracy and precision. This study developed and verify a semi-automatic PL-QCT for assessment of proximal humeral bone density based on CT to assist in the assessment of proximal humeral osteoporosis and development of individualized treatment plans for shoulders.
Subject(s)
Bone Density , Cancellous Bone , Humerus , Tomography, X-Ray Computed , Humans , Bone Density/physiology , Male , Female , Middle Aged , Tomography, X-Ray Computed/methods , Aged , Reproducibility of Results , Humerus/diagnostic imaging , Humerus/physiology , Cancellous Bone/diagnostic imaging , Cancellous Bone/physiopathology , Cancellous Bone/physiology , Algorithms , Phantoms, Imaging , Adult , Osteoporosis/physiopathology , Osteoporosis/diagnostic imaging , Aged, 80 and overABSTRACT
Anti-inflammatory treatment is the primary and vital therapeutic approach for active, moderate-to-severe thyroid eye disease (TED). Accurate pretreatment prediction of treatment response is of paramount importance for the prognosis of patients. However, relying solely on the clinical activity score asa determinant of activity has led to unsatisfactory treatment outcomes. In recent years, significant advancements have been made in identifying predictive markers for anti-inflammatory treatment response in TED, clinical markers, body fluid biomarkers and imaging biomarkers. Several clinical studies have developed prediction models based on these markers. However, there is still a lack of comprehensive elucidation or comparison between the different markers. Therefore, this review aims to provide a detailed analysis of the definition, characteristics, and application of predictive markers for anti-inflammatory treatment response in TED. Through detailed literature search, 26 articles applying anti-inflammatory treatment effect prediction with a total of 1948 TED patients were used for analysis and discussion. By gaining a better understanding of the current research on predictive markers, we can accelerate and guide the exploration of treatment prediction strategies, leading us towards an era of precise therapy for TED.
Subject(s)
Graves Ophthalmopathy , Humans , Graves Ophthalmopathy/diagnosis , Graves Ophthalmopathy/drug therapy , Anti-Inflammatory Agents/therapeutic use , Treatment Outcome , Prognosis , BiomarkersABSTRACT
Oocyte senescence alters the shape and function, thereby weakening the fertilization potential. Nicotinamide mononucleotide (NMN) reverses age-related dysfunctions in various organs. Studies had shown long-term administration of NMN reduced the physiological decline associated in aged mice and reversed the aging of the ovaries. However, the protective effect of NMN on aged porcine oocytes is still unclear. In this study, we investigated the effects of NMN on aging porcine oocytes and subsequent embryonic development. We established a model of senescence of porcine oocytes after ovulation by extending the culture time in vitro. NMN supplementation significantly reduced reactive oxygen species (ROS) levels in senescence oocytes and increased the mRNA levels of antioxidant genes SOD1 and Cat. The mitochondrial membrane potential of aged oocytes treated with NMN was increased compared with that of untreated oocytes. In addition, the mRNA level of apoptosis-related gene Bax was significantly decreased in senescence oocytes treated with NMN, while the mRNA level of anti-apoptosis-related gene BCL-2 was significantly increased. Furthermore, NMN supplementation enhanced the subsequent development ability of senescent oocytes during in vitro aging. Compared with untreated senescent oocytes, the blastocyst formation rate and pluripotent genes of senescent oocytes treated with NMN were significantly increased. Taken together, these results suggest that NMN is beneficial for delaying the aging process in porcine oocytes.
Subject(s)
In Vitro Oocyte Maturation Techniques , Nicotinamide Mononucleotide , Female , Swine , Animals , Mice , Nicotinamide Mononucleotide/pharmacology , In Vitro Oocyte Maturation Techniques/methods , Oocytes , Embryonic Development , Reactive Oxygen Species/pharmacology , RNA, Messenger/pharmacologyABSTRACT
Liver cancer has high incidence and mortality rates and its treatment generally requires the use of a combination treatment strategy. Therefore, the early detection and diagnosis of liver cancer is crucial to achieving the best treatment effect. In addition, it is imperative to explore multimodal combination therapy for liver cancer treatment and the synergistic effect of two liver cancer treatment drugs while preventing drug resistance and drug side effects to maximize the achievable therapeutic effect. Gold nanoparticles are used widely in applications related to optical imaging, CT imaging, MRI imaging, biomarkers, targeted drug therapy, etc., and serve as an advanced platform for integrated application in the nano-diagnosis and treatment of diseases. Dual-drug-delivery nano-diagnostic and therapeutic agents have drawn great interest in current times. Therefore, the present report aims to review the effectiveness of dual-drug-delivery nano-diagnostic and therapeutic agents in the field of anti-tumor therapy from the particular perspective of liver cancer diagnosis and treatment.
Subject(s)
Antineoplastic Agents , Liver Neoplasms , Metal Nanoparticles , Nanoparticles , Humans , Theranostic Nanomedicine/methods , Gold , Metal Nanoparticles/therapeutic use , Phototherapy/methods , Drug Delivery Systems/methods , Nanoparticles/therapeutic use , Liver Neoplasms/diagnosis , Liver Neoplasms/drug therapy , Antineoplastic Agents/therapeutic useABSTRACT
There have been many studies on the degradation of polyvinyl alcohol (PVA) by the Fenton-like method, but the narrow acid-base (pH) range, poor degradation effect, and time-consuming of the Fenton-like method limit its development. Therefore, to improve the shortcomings of the Fenton-like method, the study aimed to synthesize copper-manganese bimetal oxide loaded catalysts (MnCuO@γ-Al2O3) through the impregnation calcination method, and its potential to activate hydrogen peroxide (H2O2) for the degradation of PVA was evaluated. The X-ray diffraction (XRD), scanning electron microscopy (SEM), Brunauer Emmett Teller (BET), energy dispersive spectroscopy (EDS), and X-ray photoelectron spectroscopy (XPS) characterizations revealed the chemical composition, structure and morphology of the prepared MnCuO@γ-Al2O3, furthermore the synergistic mechanism was proposed. Results indicated that copper and manganese could successfully attach to γ-Al2O3 and reduce the specific surface area of γ-Al2O3, promoting the transformation of multivalent metals and the generation of oxygen vacancies. In addition, comparative experiments demonstrated that the PVA removal efficiency was significantly improved at the catalyst calcination temperature of 500 °C, reaction temperature of 70 °C, H2O2 dosage of 125 [Formula: see text], and catalyst dosage of 625 [Formula: see text] and more than 96% of PVA was removed within 20 min in neutral conditions. Lastly, four catalyst cycle degradation experiments of PVA were carried out, and the degradation effect could reach more than 96% in a certain time.
Subject(s)
Copper , Manganese , Polyvinyl Alcohol , Hydrogen PeroxideABSTRACT
Background and purpose: Inverted papilloma (IP) and nasal polyp (NP), as two benign lesions, are difficult to distinguish on MRI imaging and clinically, especially in predicting whether the olfactory nerve is damaged, which is an important aspect of treatment and prognosis. We plan to establish a new biomarker to distinguish IP and NP that may invade the olfactory nerve, and to analyze its diagnostic efficacy. Materials and methods: A total of 74 cases of IP and 55 cases of NP were collected. A total of 80% of 129 patients were used as the training set (59 IP and 44 NP); the remaining were used as the testing set. As a multimodal study (two MRI sequences and clinical indicators), preoperative MR images including T2-weighted magnetic resonance imaging (T2-WI) and contrast-enhanced T1-weighted magnetic resonance imaging (CE-T1WI) were collected. Radiomic features were extracted from MR images. Then, the least absolute shrinkage and selection operator (LASSO) regression method was used to decrease the high degree of redundancy and irrelevance. Subsequently, the radiomics model is constructed by the rad scoring formula. The area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the model have been calculated. Finally, the decision curve analysis (DCA) is used to evaluate the clinical practicability of the model. Results: There were significant differences in age, nasal bleeding, and hyposmia between the two lesions (p < 0.05). In total, 1,906 radiomic features were extracted from T2-WI and CE-T1WI images. After feature selection, using 12 key features to bulid model. AUC, sensitivity, specificity, and accuracy on the testing cohort of the optimal model were, respectively, 0.9121, 0.828, 0.9091, and 0.899. AUC on the testing cohort of the optimal model was 0.9121; in addition, sensitivity, specificity, and accuracy were, respectively, 0.828, 0.9091, and 0.899. Conclusion: A new biomarker combining multimodal MRI radiomics and clinical indicators can effectively distinguish between IP and NP that may invade the olfactory nerve, which can provide a valuable decision basis for individualized treatment.
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Aromatase inhibitor (AI) is a cornerstone drug for postmenopausal women with estrogen receptor-positive early-stage breast cancer. Fat-bone interactions within the bone marrow milieu are growing areas of scientific interest. Although AI treatment could lead to deterioration of the skeleton, the association between AI medication and subsequent marrow adiposity remains elusive. A total of 40 postmenopausal, early-staged, and hormone receptor-positive breast cancer patients who underwent treatment with adjuvant AIs and 40 matched controls were included. Marrow proton density fat fraction (PDFF) at the L1-L4 vertebral bodies using 3D Fat Analysis & Calculation Technique imaging (FACT) sequence at 3.0T, bone mineral density (BMD) by dual-energy X-ray absorptiometry, and serum bone turnover biomarkers were determined at baseline and at 6 and 12 months. We found that, in comparison to baseline, an increase of type I collagen cross-linked telopeptide was detected at 12 months (P <0.05). From baseline to 12 months, the PDFF measured using FACT was greatly increased. At 12 months, the median percent change of PDFF (4.9% vs. 0.9%, P <0.05) was significantly different between the AI treatments and controls. The same trend was observed for the marrow PDFF at 6 months relative to the respective values at baseline. Although BMD values were significantly reduced after 12 months in AI-treated women, changes in BMD vs. baseline condition were not significantly different between the AI-treated and control groups [Δ BMD -1.6% to -1.8% vs. -0.3% to -0.6%, respectively, P > 0.05]. In the AI-treated group, Δ PDFF was associated with Δ BMD at the lumbar spine (r = -0.585, P < 0.001), but not in the controls. Taken together, over a 12-month period, spinal marrow fat content assessed with FACT sequence significantly increased in postmenopausal women with hormone-receptor-positive breast cancer receiving AI treatment.
Subject(s)
Aromatase Inhibitors , Breast Neoplasms , Aromatase Inhibitors/therapeutic use , Bone Marrow/diagnostic imaging , Breast Neoplasms/chemically induced , Breast Neoplasms/diagnostic imaging , Breast Neoplasms/drug therapy , Female , Humans , Postmenopause , Vertebral BodyABSTRACT
Correction for 'Rational design of Fe3O4@C nanoparticles for simultaneous bimodal imaging and chemo-photothermal therapy in vitro and in vivo' by Qinghe Han et al., J. Mater. Chem. B, 2018, 6, 5443-5450, DOI: 10.1039/C8TB01184B.
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PURPOSE: To evaluate the capability of non-enhanced computed tomography (CT) images for distinguishing between orbital cavernous venous malformations (OCVM) and non-OCVM, and to identify the optimal model from radiomics-based machine learning (ML) algorithms. METHODS: A total of 215 cases of OCVM and 120 cases of non- OCVM were retrospectively analyzed in this study. A stratified random sample of 268 patients (80%) was used as the training set (172 OCVM and 96 non-OCVM); the remaining data were used as the testing set. Six feature selection techniques and thirteen ML models were evaluated to construct an optimal classification model. RESULTS: There were statistically significant differences between the OCVM and non-OCVM groups in the density and tumor location (Pâ <â0.05), whereas other indicators were comparable (age, gender, sharp, Pâ>â0.05). Linear regression (area under the curve [AUC]â=â0.9351; accuracyâ=â0.8657) and Stochastic Gradient Descent (AUCâ=â0.9448; accuracyâ=â0.8806) classifiers, both of which coupled with the f test and L1-based feature selection method, achieved optimal performance. The support vector machine (AUCâ=â0.9186; accuracyâ=â0.8806), Random Forest (AUCâ=â0.9288; accuracyâ=â0.8507) and eXtreme Gradient Boosting (AUCâ=â0.9147; accuracyâ=â0.8507) classifier combined with f test method showed excellent average performance among our study, respectively. CONCLUSIONS: The effect of non-enhanced CT images in OCVM not only can help ophthalmologist to find and locate lesion, but also bring great help for the qualitative diagnosis value using radiomic- based ML algorithms.
Subject(s)
Machine Learning , Tomography, X-Ray Computed , Algorithms , Humans , Linear Models , Retrospective Studies , Tomography, X-Ray Computed/methodsABSTRACT
Among orbital lymphoproliferative disorders, about 55% of diagnosed cancerous tumors are orbital lymphomas, and nearly 50% of benign cases are immunoglobulin G4-related ophthalmic disease (IgG4-ROD). However, due to nonspecific characteristics, the differentiation of the two diseases is challenging. In this study, conventional magnetic resonance imaging-based radiomics approaches were explored for clinical recognition of orbital lymphomas and IgG4-ROD. We investigated the value of radiomics features of axial T1- (T1WI-) and T2-weighted (T2WI), contrast-enhanced T1WI in axial (CE-T1WI) and coronal (CE-T1WI-cor) planes, and 78 patients (orbital lymphoma, 36; IgG4-ROD, 42) were retrospectively reviewed. The mass lesions were manually annotated and represented with 99 features. The performance of elastic net-based radiomics models using single or multiple modalities with or without feature selection was compared. The demographic features showed orbital lymphoma patients were significantly older than IgG4-ROD patients (p < 0.01), and most of the patients were male (72% in the orbital lymphoma group vs. 23% in the IgG4-ROD group; p = 0.03). The MR imaging findings revealed orbital lymphomas were mostly unilateral (81%, p = 0.02) and wrapped eyeballs or optic nerves frequently (78%, p = 0.02). In addition, orbital lymphomas showed isointense in T1WI (100%, p < 0.01), and IgG4-ROD was isointense (60%, p < 0.01) or hyperintense (40%, p < 0.01) in T1WI with well-defined shape (64%, p < 0.01). The experimental comparison indicated that using CE-T1WI radiomics features achieved superior results, and the features in combination with CE-T1WI-cor features and the feature preselection method could further improve the classification performance. In conclusion, this study comparatively analyzed orbital lymphoma and IgG4-ROD from demographic features, MR imaging findings, and radiomics features. It might deepen our understanding and benefit disease management.
Subject(s)
Hypersensitivity, Immediate/diagnostic imaging , Immunoglobulin G4-Related Disease/diagnostic imaging , Lymphoma/diagnostic imaging , Magnetic Resonance Imaging , Orbital Neoplasms/diagnostic imaging , Adult , Age Factors , Aged , Female , Humans , Hypersensitivity, Immediate/therapy , Immunoglobulin G4-Related Disease/therapy , Lymphoma/therapy , Male , Middle Aged , Orbital Neoplasms/therapy , Retrospective Studies , Sex FactorsABSTRACT
OBJECTIVES: To differentiate squamous cell hyperplasia (SCH) (benign) from squamous cell carcinoma (SCC) malignant) using textural features extracted from CT images and thereby, facilitate the preoperative medical diagnosis and treatment of throat cancers without the need for sample biopsies. METHODS: In total, 100 throat cancer patients were selected for this retrospective study. The cases were collected from the Second Hospital of Jilin University, Changchun, China, from June 2017 to January 2019. The patients were separated into a training and validation cohort consisting of 70 and 30 cases, respectively. The Artificial Intelligence Kit software (A.K. software) was used to extract the radiomics features from the CT images. These features were further processed using the minimum redundancy maximum relevance (mRMR) and least absolute shrinkage and selection operator (LASSO) methods to obtain a subset of optimal features. The radiomics model was validated based on area-under-the-curve (AUC) values, accuracy, specificity, and sensitivity using the R-studio software. RESULTS: The diagnostic accuracy, specificity, PPV, NPV, and AUC values obtained for the training cohort was 0.91, 0.9, 0.93, 0.9, and 0.96 CT angiography (CTA), 0.93, 0.93, 0.95, 0.90, and 0.96 computed tomography normal (CTN), and 0.92, 0.87, 0.91, 0.96, and 0.96 CT venogram (CTV). These values were subsequently confirmed in the validation cohort. CONCLUSION: The radiomics-based prediction model proposed in this study successfully differentiated between SCH and SCC throat cancers using CT imaging, thereby facilitating the development of accurate preoperative diagnosis based on specific biomarkers and cancer phenotypes.
Subject(s)
Carcinoma, Squamous Cell/diagnostic imaging , Epithelial Cells/pathology , Head and Neck Neoplasms/diagnostic imaging , Pharynx/diagnostic imaging , Tomography, X-Ray Computed/methods , Diagnosis, Differential , Female , Humans , Hyperplasia/diagnostic imaging , Machine Learning , Male , Nomograms , Predictive Value of Tests , Preoperative Period , Retrospective Studies , Sensitivity and SpecificityABSTRACT
Multifunctional theranostic agents are widely applied in cancer diagnosis and treatment. These agents can significantly improve therapeutic outcomes and reduce adverse effects in current cancer therapy. Here, we have designed and synthesized iron-doped copper sulfide nanoparticles with polyvinylpyrollidone (FCS@PVP NPs) for magnetic resonance imaging (MRI) guided photothermal therapy. The biocompatible FCS@PVP NPs with strong near-infrared absorption could be used as the photothermal agent and the magnetic characteristic of Fe3+ ions could be applied to T 1-weighted magnetic resonance imaging (MRI). The T 1-weighted MRI, high photothermal performance, and the biodistribution of FCS@PVP NPs were investigated in mice after intravenous administration. The data showed that there was a high accumulation of FCS@PVP NPs in the tumor sites because of the enhanced permeability and retention (EPR) effect. This result also indicated that the tumors in tumor-bearing mice were effectively suppressed after FCS@PVP NPs treatment under 808 nm laser irradiation. More importantly, FCS@PVP NPs show low cytotoxicity and few side effects because of the quick and safe elimination through the hepatobiliary/fecal route. This work provided a foundation for the clinical application of FCS@PVP NPs as a promising multifunctional theranostic agent for the MRI guided photothermal therapy of cancer.
Subject(s)
Copper/administration & dosage , Ferrous Compounds/administration & dosage , Phototherapy/methods , Sulfides/administration & dosage , Animals , Biocompatible Materials/chemistry , Cell Line, Tumor , Female , Magnetic Resonance Imaging/methods , Magnetic Resonance Spectroscopy/methods , Mice , Povidone/chemistry , Theranostic Nanomedicine/methods , Tissue DistributionABSTRACT
Co-delivery of two drugs with diverse physicochemical properties and specific administration order for cancer theranostics are vitally important for drug resistance conquering and side effects reducing. Consequently, we explored a unique amphiphilic PCL-AuNC/Fe(OH)3-PAA Janus nanoparticle (JNP) to simultaneously preserve the hydrophilic drug (doxorubicin) and hydrophobic drug (docetaxel) in their distinct domains. Owing to their extraordinary heterostructure and independent pH and NIR sensitive properties, the optional sequential drug release by a single inorganic JNP was realized for the first time, and the results presented the synchronous release of two drugs had 5% better therapeutic effect. In addition, the excellent computed X-ray tomography/magnetic resonance (CT/MR) imaging capabilities from AuNC and Fe(OH)3 suggested our JNPs could effectively guide the cancer therapy. Furthermore, the mice treated with dual drug loaded PCL-AuNC/Fe(OH)3-PAA JNPs under near infrared (NIR) laser irradiation showed better tumor inhibition than solo drug, cocktail and dual drug treated groups, indicating the effectivity and significance of combined cancer therapy.
Subject(s)
Drug Delivery Systems/methods , Liver Neoplasms/diagnosis , Liver Neoplasms/therapy , Nanoparticles/chemistry , Theranostic Nanomedicine/methods , Animals , Docetaxel/administration & dosage , Docetaxel/chemistry , Docetaxel/therapeutic use , Humans , Liver Neoplasms/drug therapy , Microscopy, Electron, Transmission , Nanoparticles/ultrastructureABSTRACT
[This corrects the article DOI: 10.18632/oncotarget.16719.].
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The aim of the present study was to investigate whether oridonin is able to increase the effects of lentinan (LNT) in HepG2 human hepatoblastoma cells by MTT, flow cytometry, reverse transcription-quantitative polymerase chain reaction and western blot analysis. The in vitro results demonstrated that 20 µg/ml of oridonin was a nontoxic concentration for L02 normal liver cells and HepG2 liver cancer cells. Furthermore, treatment with 0-200 µg/ml LNT was only able to decrease the viability of HepG2 liver cancer cells. The growth inhibitory rate of the LNT-L (100 µg/ml) treatment group was 20.7% and the rate of the LNT-H (200 µg/ml) treatment group was 54.8%. Notably, the growth inhibitory rate of the oridonin + LNT-H group was 84.3%. The highest percentage of apoptotic cells was observed in the oridonin + LNT-H group (20 µg/ml oridonin and 200 µg/ml LNT). The percentage of apoptotic cells in the oridonin + LNT-H group was significantly different from the percentage of apoptotic cells in the LNT-H (26.1%) and the LNT-L (16.8%) groups. Treatment with LNT produced an increase in caspase-3, caspase-9, Bcl-2-like protein 4, p53, p21, nuclear factor κB inhibitor-α mRNA and protein expression and a decrease in B-cell lymphoma 2 and nuclear factor-κB expression in HepG2 cells compared with untreated control cells. Treatment with a combination of oridonin and LNT-H induced a further increase in expression with the biggest differences in expression observed between the oridonin + LNT-H group and control. It was observed that treatment with oridonin was able to increase the anticancer effects of LNT in HepG2 cells. Therefore, oridonin may be used to sensitize cells to LNT.
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We report a facile strategy to fabricate well-dispersed Fe3O4@C eccentric core-shell nanoparticles (NPs). The resulting Fe3O4@C eccentric core-shell NPs possess a high payload of doxorubicin (DOX) for use as synergetic pH/near-infrared (NIR)-sensitive drug delivery vehicles, and were applied for dual-modal magnetic resonance imaging (MRI)/photoacoustic imaging (PAI) and synergistic photothermal cancer therapy in vitro and in vivo.
ABSTRACT
We report a facile and simple hydrogen reduction method to fabricate PEGylated branched gold (Au)-iron oxide (Fe3 O4 ) Janus nanoparticles (JNPs). Note that the hydrogen induces the formation of Fe3 O4 during the synthesis process. Due to the strong absorption in the near-infrared range, branched Au-Fe3 O4 JNPs showed a significant photothermal effect with a 40 % calculated photothermal transduction efficiency under a laser irradiation of 808â nm in vitro. Owing to their excellent optical and magnetic properties, branched Au-Fe3 O4 JNPs were demonstrated to be advantageous agents for triple-modal magnetic resonance imaging (MRI)/photoacoustic imaging (PAI)/computed tomography (CT) in vitro. Therefore, the synthetic approach could be extended to prepare Au-metallic oxide JNPs for specific applications.