Smart Biomimetic Nanozymes for Precise Molecular Imaging: Application and Challenges.

New nanotechnologies for imaging molecules are widely being applied to visualize the expression of specific molecules (e.g., ions, biomarkers) for disease diagnosis. Among various nanoplatforms, nanozymes, which exhibit enzyme-like catalytic activities in vivo, have gained tremendously increasing attention in molecular imaging due to their unique properties such as diverse enzyme-mimicking activities, excellent biocompatibility, ease of surface tenability, and low cost. In addition, by integrating different nanoparticles with superparamagnetic, photoacoustic, fluorescence, and photothermal properties, the nanoenzymes are able to increase the imaging sensitivity and accuracy for better understanding the complexity and the biological process of disease. Moreover, these functions encourage the utilization of nanozymes as therapeutic agents to assist in treatment. In this review, we focus on the applications of nanozymes in molecular imaging and discuss the use of peroxidase (POD), oxidase (OXD), catalase (CAT), and superoxide dismutase (SOD) with different imaging modalities. Further, the applications of nanozymes for cancer treatment, bacterial infection, and inflammation image-guided therapy are discussed. Overall, this review aims to provide a complete reference for research in the interdisciplinary fields of nanotechnology and molecular imaging to promote the advancement and clinical translation of novel biomimetic nanozymes.

GPX4 deficiency-dependent phospholipid peroxidation drives motor deficits of ALS.

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease characterized by oxidative stress that triggers motor neurons loss in the brain and spinal cord. However, the mechanisms underlying the exact role of oxidative stress in ALS-associated neural degeneration are not definitively established. Oxidative stress-generated phospholipid peroxides are known to have extensive physiological and pathological consequences to tissues. Here, we discovered that the deficiency of glutathione peroxidase 4 (GPX4), an essential antioxidant peroxidase, led to the accumulation of phospholipid peroxides and resulted in a loss of motor neurons in spinal cords of ALS mice. Mutant human SOD1G93A transgenic mice were intrathecally injected with neuron-targeted adeno-associated virus (AAV) expressing GPX4 (GPX4-AAV) or phospholipid peroxidation inhibitor, ferrostatin-1. The results showed that impaired motor performance and neural loss induced by SOD1G93A toxicity in the lumbar spine were substantially alleviated by ferrostatin-1 treatment and AAV-mediated GPX4 delivery. In addition, the denervation of neuron-muscle junction and spinal atrophy in ALS mice were rescued by neural GPX4 overexpression, suggesting that GPX4 is essential for the motor neural maintenance and function. In comparison, conditional knockdown of Gpx4 in the spinal cords of Gpx4fl/fl mice triggered an obvious increase of phospholipid peroxides and the occurrence of ALS-like motor phenotype. Altogether, our findings underscore the importance of GPX4 in maintaining phospholipid redox homeostasis in the spinal cord and presents GPX4 as an attractive therapeutic target for ALS treatment.

Comparison of percentage changes in quantitative diffusion parameters for assessing pathological complete response to neoadjuvant therapy in locally advanced rectal cancer: a meta-analysis.

PURPOSE: To evaluate and compare the diagnostic performance of percentage changes in apparent diffusion coefficient (∆ADC%) and slow diffusion coefficient (∆D%) for assessing pathological complete response (pCR) to neoadjuvant therapy in patients with locally advanced rectal cancer (LARC). METHODS: A systematic search in PubMed, EMBASE, the Web of Science, and the Cochrane Library was performed to retrieve related original studies. For each parameter (∆ADC% and ∆D%), we pooled the sensitivity, specificity and calculated the area under summary receiver operating characteristic curve (AUROC) values. Meta-regression and subgroup analyses were performed to explore heterogeneity among the studies on ∆ADC%. RESULTS: 15 original studies (804 patients with 805 lesions, 15 studies on ∆ADC%, 4 of the studies both on ∆ADC% and ∆D%) were included. pCR was observed in 213 lesions (26.46%). For the assessment of pCR, the pooled sensitivity, specificity and AUROC of ∆ADC% were 0.83 (95% confidence intervals [CI] 0.76, 0.89), 0.74 (95% CI 0.66, 0.81), 0.87 (95% CI 0.83, 0.89), and ∆D% were 0.70 (95% CI 0.52, 0.84), 0.81 (95% CI 0.65, 0.90), 0.81 (95% CI 0.77, 0.84), respectively. In the four studies on the both metrics, ∆ADC% yielded an equivalent diagnostic performance (AUROC 0.80 [95% CI 0.76, 0.83]) to ∆D%, but lower than in the studies (n = 11) only on ∆ADC% (AUROC 0.88 [95% CI 0.85, 0.91]). Meta-regression and subgroup analyses showed no significant factors affecting heterogeneity. CONCLUSIONS: Our meta-analysis confirms that ∆ADC% could reliably evaluate pCR in patients with LARC after neoadjuvant therapy. ∆D% may not be superior to ∆ADC%, which deserves further investigation.

DTI-based radiomics signature for the detection of early diabetic kidney damage.

OBJECTIVE: To explore whether a radiomics signature based on diffusion tensor imaging (DTI) can detect early kidney damage in diabetic patients. MATERIALS AND METHODS: Twenty-eight healthy volunteers (group A) and thirty type 2 diabetic patients (group B) with micro-normoalbuminuria, a urinary albumin-to-creatinine ratio (ACR) < 30 mg/g and an estimated glomerular filtration rate (eGFR) of 60-120 mL/(min 1.73 m2) were recruited. Kidney DTI was performed using 1.5T magnetic resonance imaging (MRI).The radiologist manually drew regions of interest (ROI) on the fractional anisotropy (FA) map of the right kidney ROI including the cortex and medulla. The texture features of the ROIs were extracted using MaZda software. The Fisher coefficient, mutual information (MI), and probability of classification error and average correlation coefficient (POE + ACC) methods were used to select the texture features. The most valuable texture features were further selected by the least absolute shrinkage and selection operator (LASSO) algorithm. A LASSO regression model based on the radiomics signature was established. The diagnostic performance of the model for detecting early diabetic kidney changes was evaluated by the area under the receiver operating characteristic (ROC) curve (AUC). Empower (R), R, and MedCalc15.8 software were used for statistical analysis RESULTS: A total of 279 texture features were extracted from ROI of the kidney, and 30 most valuable texture features were selected from groups A and B using MaZda software. After LASSO-logistic regression, a diagnostic model of diabetic kidney damage based on texture features was established. Model discrimination evaluation: AUC = 0.882 (0.770 ± 0.952). Model calibration evaluation: Hosmer-Lemeshow X2 = 5.3611, P = 0.7184, P > 0.05, the model has good calibration. CONCLUSION: The texture features based on DTI could play a promising role in detecting early diabetic kidney damage.

CT-based machine learning model to predict the Fuhrman nuclear grade of clear cell renal cell carcinoma.

PURPOSE: To predict the Fuhrman grade of clear cell renal cell carcinoma (ccRCC) with a machine learning classifier based on single- or three-phase computed tomography (CT) images. MATERIALS AND METHODS: Patients with pathologically proven ccRCC from February 1, 2009 to September 31, 2018 who were not treated were retrospectively collected for machine learning-based analysis. The texture features were extracted and ranked from precontrast phase (PCP), corticomedullary phase (CMP), nephrographic phase (NP) and three-phase CT images, and open-source gradient boosting from the decision tree library of CatBoost was used to establish a machine learning classifier to differentiate low- from high-grade ccRCC. The performances of machine learning classifiers based on features from single- and three-phase CT images were compared with each other. RESULTS: A total of 231 patients with 232 pathologically proven ccRCC lesions were retrospectively collected. 35, 36, 41, and 22 Features were extracted and ranked from PCP, CMP, NP, and three-phase CT images, respectively. The machine learning model based on three-phase CT images [area under the ROC curve (AUC) = 0.87] achieved the best diagnostic performance for differentiating low- from high-grade ccRCC, followed by single-phase NP (AUC = 0.84), CMP (AUC = 0.80), and PCP images (AUC = 0.82). CONCLUSION: Machine learning classifiers can be promising noninvasive techniques to differentiate low- and high-Fuhrman nuclear grade ccRCC, and classifiers based on three-phase CT images are superior to those based on features from each single phase.

Clinical simulation training improves the clinical performance of Chinese medical students.

BACKGROUND: Modern medical education promotes medical students' clinical operating capacity rather than the mastery of theoretical knowledge. To accomplish this objective, clinical skill training using various simulations was introduced into medical education to cultivate creativity and develop the practical ability of students. However, quantitative analysis of the efficiency of clinical skill training with simulations is lacking. METHODS: In the present study, we compared the mean scores of medical students (Jinan University) who graduated in 2013 and 2014 on 16 stations between traditional training (control) and simulative training groups. In addition, in a clinical skill competition, the objective structured clinical examination (OSCE) scores of participating medical students trained using traditional and simulative training were compared. The data were statistically analyzed and qualitatively described. RESULTS: The results revealed that simulative training could significantly enhance the graduate score of medical students compared with the control. The OSCE scores of participating medical students in the clinical skill competition, trained using simulations, were dramatically higher than those of students trained through traditional methods, and we also observed that the OSCE marks were significantly increased for the same participant after simulative training for the clinical skill competition. CONCLUSIONS: Taken together, these data indicate that clinical skill training with a variety of simulations could substantially promote the clinical performance of medical students and optimize the resources used for medical education, although a precise analysis of each specialization is needed in the future.

Role of the texture features of images in the diagnosis of solitary pulmonary nodules in different sizes.

OBJECTIVE: To explore the role of the texture features of images in the diagnosis of solitary pulmonary nodules (SPNs) in different sizes. MATERIALS AND METHODS: A total of 379 patients with pathologically confirmed SPNs were enrolled in this study. They were divided into three groups based on the SPN sizes: ≤10, 11-20, and >20 mm. Their texture features were segmented and extracted. The differences in the image features between benign and malignant SPNs were compared. The SPNs in these three groups were determined and analyzed with the texture features of images. RESULTS: These 379 SPNs were successfully segmented using the 2D Otsu threshold method and the self-adaptive threshold segmentation method. The texture features of these SPNs were obtained using the method of grey level co-occurrence matrix (GLCM). Of these 379 patients, 120 had benign SPNs and 259 had malignant SPNs. The entropy, contrast, energy, homogeneity, and correlation were 3.5597±0.6470, 0.5384±0.2561, 0.1921±0.1256, 0.8281±0.0604, and 0.8748±0.0740 in the benign SPNs and 3.8007±0.6235, 0.6088±0.2961, 0.1673±0.1070, 0.7980±0.0555, and 0.8550±0.0869 in the malignant SPNs (all P<0.05). The sensitivity, specificity, and accuracy of the texture features of images were 83.3%, 90.0%, and 86.8%, respectively, for SPNs sized ≤10 mm, and were 86.6%, 88.2%, and 87.1%, respectively, for SPNs sized 11-20 mm and 94.7%, 91.8%, and 93.9%, respectively, for SPNs sized >20 mm. CONCLUSIONS: The entropy and contrast of malignant pulmonary nodules have been demonstrated to be higher in comparison to those of benign pulmonary nodules, while the energy, homogeneity correlation of malignant pulmonary nodules are lower than those of benign pulmonary nodules. The texture features of images can reflect the tissue features and have high sensitivity, specificity, and accuracy in differentiating SPNs. The sensitivity and accuracy increase for larger SPNs.

Size of solitary pulmonary nodule was the risk factor of malignancy.

OBJECTIVE: The purpose of this study was to analyze the role of the sizes of solitary pulmonary nodules (SPNs) in predicting their potential malignancies. METHODS: A total of 379 patients with pathologically confirmed SPNs were enrolled in this study. They were divided into three groups based on the SPN sizes: ≤10, 11-20, and >20 mm. The computed tomography (CT) findings of these SPNs were analyzed in these three groups to identify the malignant and benign SPNs. The risk factors were analyzed using binary logistic regression analysis. RESULTS: Of these 379 patients, 120 had benign SPNs and 259 had malignant SPNs. In the ≤10 mm SPN group, air cavity density was the risk factor for malignancy, with the sensitivity, specificity, and accuracy being 77.8%, 75.0%, and 76.3%. In the 11-20 mm SPN group, age, glitches and vascular aggregation were the risk factors for malignancy, with the sensitivity, specificity, and accuracy being 91.3%, 56.9%, and 81.5%. In the >20 mm SPN group, age, lobulation, and vascular aggregation were the risk factors for malignancy, with the sensitivity, specificity, and accuracy being 88.6%, 57.1%, and 79.1%. CONCLUSIONS: According to CT findings of SPNs, age, glitches, lobulation, vascular aggregation, and air cavity density are the risk factors of malignancy, whereas calcification and satellite lesions are the protective factors. During the course of development from small to large nodules, air cavity density could be firstly detected in early stages, followed by glitches and vascular aggregation. Lobulation is associated with relatively large lesions.

Differentiation of central lung cancer from atelectasis: comparison of diffusion-weighted MRI with PET/CT.

OBJECTIVE: Prospectively assess the performance of diffusion-weighted magnetic resonance imaging (DW-MRI) for differentiation of central lung cancer from atelectasis. MATERIALS AND METHODS: 38 consecutive lung cancer patients (26 males, 12 females; age range: 28-71 years; mean age: 49 years) who were referred for thoracic MR imaging examinations were enrolled. MR examinations were performed using a 1.5-T clinical scanner and scanning sequences of T1WI, T2WI, and DWI. Cancers and atelectasis were measured by mapping of the apparent diffusion coefficients (ADCs) obtained with a b-value of 500 s/mm(2). RESULTS: PET/CT and DW-MR allowed differentiation of tumor and atelectasis in all 38 cases, but T2WI did not allow differentiation in 9 cases. Comparison of conventional T2WI and DW-MRI indicated a higher contrast noise ratio of the central lung carcinoma than the atelectasis by DW-MRI. ADC maps indicated significantly lower mean ADC in the central lung carcinoma than in the atelectasis (1.83±0.58 vs. 2.90±0.26 mm(2)/s, p<0.0001). ADC values of small cell lung carcinoma were significantly greater than those from squamous cell carcinoma and adenocarcinoma (p<0.0001 for both). CONCLUSIONS: DW-MR imaging provides valuable information not obtained by conventional MR and may be useful for differentiation of central lung carcinoma from atelectasis. Future developments may allow DW-MR imaging to be used as an alternative to PET-CT in imaging of patients with lung cancer.

Ultrasound- and liposome microbubble-mediated targeted gene transfer to cardiomyocytes in vivo accompanied by polyethylenimine.

OBJECTIVES: Gene transfer to cardiomyocytes in vivo has received much research attention in the last decade but remains a substantial hurdle. Gene transfer using ultrasound-targeted microbubble destruction is a promising tool for gene therapy. Little data have shown the feasibility and optimization of this method for primary myocardial disease. In this study, we sought to determine the feasibility and efficiency of in vivo gene transfer to the myocardium mediated by ultrasound-targeted microbubble destruction accompanied by polyethylenimine. METHODS: Three plasmids (luciferase reporter, red fluorescent protein reporter, and enhanced green fluorescent protein reporter) were used in this study. The ultrasound parameters were also optimized. A solution containing phosphate-buffered saline, a plasmid, plasmid complex, or polyethylenimine/plasmid, and liposome microbubbles was injected via a tail vein with (study) or without (control) transthoracic ultrasound irradiation. The efficiency of reporter gene transfer was determined by detection of luciferase activity or microscopy, and histologic investigations of the tissue specimens were performed. RESULTS: Ultrasound-targeted microbubble destruction significantly increased luciferase activity in vivo compared to plasmids and microbubbles alone (P < .001). More importantly, the increase in transgene expression was significantly related to ultrasound-targeted microbubble destruction in the presence of polyethylenimine (P < .001). In addition, fluorescein expression was present in all sections that received ultrasound-targeted microbubble destruction. The fluorescent reporter genes and luciferase plasmid all had similar results. Regardless of ultrasound exposure, expression in other organs was close to a background level except for the liver and lung. Hematoxylin-eosin staining showed no notable myocardial injury or death in control and treated mice. CONCLUSIONS: An atraumatic targeted gene delivery technique based on ultrasound-targeted microbubble destruction and polyethylenimine has been developed to transfect cardiomyocytes in vivo. If a suitable target gene is added, the novel technique could be highly effective in many kinds of heart disease.

Enhancing microRNA transfection to inhibit survivin gene expression and induce apoptosis: could it be mediated by a novel combination of sonoporation and polyethylenimine?

Apoptosis is a physiologically essential mechanism of cell and plays an important role in reducing the development and progression of tumors. The appealing strategy for cancer therapy is to target the lesions that induce apoptosis in cancer cells. Survivin, the smallest member of the mammalian inhibitors of the apoptosis protein family, is upregulated in various malignancies to protect cells from apoptosis. Survivin knockdown could induce cancer cell apoptosis and inhibit tumor-angiogenesis. Survivin expression would be silenced by microRNA (miRNA)-mediated RNA interference. However, noninvasive and tissue-specific gene delivery techniques remain absent recently and the utilizations of miRNA expression vectors have been limited by inefficient delivery technique, especially in vivo. On the other hand, safe and promising technologies of gene transfection would be valuable in clinical gene therapy. Successful treatment of gene transfer method would lead to a new and readily available approach in the anticancer research. Sonoporation is an alternative technique of gene delivery that uses ultrasound targeted microbubble destruction to create pores in the cell membrane. Based on our previous studies, in this article, we postulated that the transfection of miRNA could be mediated by the combination of sonoporation and polyethylenimine (PEI) which was one of the most effective poly-cationic gene vectors and enhance the endocytosis of plasmids DNA and hypothesized that the gene silencing and apoptosis induction with miRNA targeting human Survivin would be improved by this novel technique. In our opinion, this novel combination of sonoporation and PEI could enhance targeted gene delivery effectively and might be a feasible, novel candidate for gene therapy.

[Controlled study on needle-pricking therapy combined with spinal massage for treatment of ankylosing spondylitis].

OBJECTIVE: To observe the therapeutic effect of needle-pricking therapy combined with spinal massage on ankylosing spondylitis and to probe into the mechanism. METHODS: Ninety-three cases who were definitely diagnosed as having ankylosing spondylitis at active stage were randomly divided into a medication group (n=46) and an observation group (n=47). The observation group were treated by needle-pricking the main points, Neck No. 2 nerve, Neck No. 5 nerve point, etc., combined with spinal rotation massage, and the medication group were treated with Azulfidine. Changes of cumulative score of arthralgia and arthroncus, function of joint, Keitel test, and ESR and CRP before and after treatment were observed. RESULTS: The effective rate and the markedly effective rate were 95.8%0 and 68.1% in the observation group and 78.3% and 23.9% in the medication group, respectively, the former being significantly better than the latter (P < 0.01). CONCLUSION: Needle-pricking therapy combined with spinal massage has a significant therapeutic effect with a steady and long-term effect for treatment of ankylosing spondylitis at active stage.