Enhanced Delivery of Rituximab Into Brain and Lymph Nodes Using Timed-Release Nanocapsules in Non-Human Primates.

Tumor metastasis into the central nervous system (CNS) and lymph nodes (LNs) is a major obstacle for effective therapies. Therapeutic monoclonal antibodies (mAb) have revolutionized tumor treatment; however, their efficacy for treating metastatic tumors-particularly, CNS and LN metastases-is poor due to inefficient penetration into the CNS and LNs following intravenous injection. We recently reported an effective delivery of mAb to the CNS by encapsulating the anti-CD20 mAb rituximab (RTX) within a thin shell of polymer that contains the analogs of choline and acetylcholine receptors. This encapsulated RTX, denoted as n-RTX, eliminated lymphoma cells systemically in a xenografted humanized mouse model using an immunodeficient mouse as a recipient of human hematopoietic stem/progenitor cells and fetal thymus more effectively than native RTX; importantly, n-RTX showed notable anti-tumor effect on CNS metastases which is unable to show by native RTX. As an important step toward future clinical translation of this technology, we further analyzed the properties of n-RTX in immunocompetent animals, rats, and non-human primates (NHPs). Our results show that a single intravenous injection of n-RTX resulted in 10-fold greater levels in the CNS and 2-3-fold greater levels in the LNs of RTX, respectively, than the injection of native RTX in both rats and NHPs. In addition, we demonstrate the enhanced delivery and efficient B-cell depletion in lymphoid organs of NHPs with n-RTX. Moreover, detailed hematological analysis and liver enzyme activity tests indicate n-RTX treatment is safe in NHPs. As this nanocapsule platform can be universally applied to other therapeutic mAbs, it holds great promise for extending mAb therapy to poorly accessible body compartments

Characterization of four vaccine-related polioviruses including two intertypic type 3/type 2 recombinants associated with aseptic encephalitis

Temperature sensitivity of 4 poliovirus type 3 isolates. (DOC 31 kb

Increasing the Inflammatory Competence of Macrophages with IL-6 or with Combination of IL-4 and LPS Restrains the Invasiveness of Pancreatic Cancer Cells

Recent studies suggest that pro-inflammatory type M1 macrophages inhibit tumor progression and that anti-inflammatory M2 macrophages enhance it. The aim of this study was to examine the interaction of type M1 and M2 macrophages with pancreatic cancer cells. We studied the migration rate of fluorescein stained pancreatic cancer cells on Matrigel cultured alone or with Granulocyte- Macrophage Colony Stimulating Factor (GM-CSF) differentiated macrophages or with Macrophage Colony Stimulating Factor (M-CSF) differentiated macrophages, skewing the phenotype towards pro- and anti-inflammatory direction, respectively. Macrophage differentiation was assessed with flow cytometry and the cytokine secretion in cell cultures with cytokine array. Both GM-CSF and M-CSF differentiated macrophages increased the migration rate of primary pancreatic adenocarcinoma cell line (MiaPaCa-2) and metastatic cell line (HPAF-II). Stimulation with IL6 or IL4+ LPS reversed the macrophages' increasing effect on the migration rate of Mi-aPaCa-2 completely and partly of HPAF-II. Co-culture with MiaPaCa-2 reduced the inflammatory cytokine secretion of GM-CSF differentiated macrophages. Co-culture of macrophages with pancreatic cancer cells seem to change the inflammatory cytokine profile of GM-CSF differentiated macrophages and this might explain why also GM-CSF differentiated macrophages promoted the invasion. Adding IL6 or IL4+ LPS to the cell culture with MiaPaCa-2 and GM-CSF or M-CSF differentiated macrophages increased the secretion of inflammatory cytokines and this could contribute to the reversion of the macrophage induced increase of cancer cell migration rate.Peer reviewe

The Development and Application of Rhodamine-Based Fluorescent Sensors

Fluorescent sensors are a very promising method for the elucidation of pathologically relevant analytes in complex cellular environments, enabling a deeper understanding of the processes behind health and disease. Rhodamines are highly favorable fluorophores for fluorescent sensors due to their excellent photophysical properties. In this work, several rhodamine-based fluorescent sensors applying sulfur-containing recognition groups have been designed and synthesized. Platinum-based chemotherapeutics have long been successfully used in the clinic for cancer treatment. Fluorescent sensors for platinum drugs and their metabolites are urgently required. Chapter Two describes work towards a rhodamine-based fluorescent sensor, which can selectively respond to Pt(Cl)2(H2O)2, a key metabolite of platinum- based drugs in aqueous environments. While Fenton chemistry has long been known to play a role in inducing cellular stress, the roles that Fenton chemistry plays in pathological processes remain unclear. Chapter Three presents a rhodamine-based fluorescent sensor, RTFt1, which applies both recognition and reactivity strategies to sense the Fenton reactants. The utility of RTFt1 in sensing the Fenton chemistry accompanies ferroptosis and cisplatin-induced cytotoxicity was also demonstrated. Hypochlorous acid is one of the most important ROS, with significant roles in both health and disease. Chapter Four describes investigations of an analogue of RTFt1, RTFt-dimer, that was found to give a selective turn-on response to HOCl. RTFt-dimer was applied to investigations of HOCl in cellular environments, demonstrating that it could be further used to understand HOCl-related biological processes. Considering their versatile application and the diverse sensing strategies by which they can operate, this work confirms that rhodamine-based fluorescent sensors are a powerful tool, and are expected to uncover a greater understanding of biology

The semi-analytical method for damping of tubular transition layer damping structure

To solve the limited vibration consumption of the traditional tubular damping structure (TTDS), the tubular transition layer damping structure (TTLDS) is proposed; Based on viscoelastic materials and theories of thin cylindrical shells, the governing equation, the first order matrix differential equation describing vibration of TTLDS under harmonic excitation, is derived by considering the interaction between all layers and the dissipation caused by the shear deformation for transition layer and damping layer. By using the extended homogeneous capacity precision integration method to solve the control equation, a semi-analytical method for studying the vibration and damping characteristics of TTLDS is given. By way of comparison, the correctness of the method provided in paper is verified. At last, the influence of thickness, material and location of transition layer on damping effect is analyzed. The results show that the change for the thickness or material of the transition layer can make the structural damping effect change greatly, while the change for location of the transition layer plays only a few roles on the structural damping effect

Sparse decomposition based on ADMM dictionary learning for fault feature extraction of rolling element bearing

Sparse decomposition is a novel method for the fault diagnosis of rolling element bearing, whether the construction of dictionary model is good or not will directly affect the results of sparse decomposition. In order to effectively extract the fault characteristics of rolling element bearing, a sparse decomposition method based on the over-complete dictionary learning of alternating direction method of multipliers (ADMM) is presented in this paper. In the process of dictionary learning, ADMM is used to update the atoms of the dictionary. Compared with the K-SVD dictionary learning and non-learning dictionary method, the learned ADMM dictionary has a better structure and faster speed in the sparse decomposition. The ADMM dictionary learning method combined with the orthogonal matching pursuit (OMP) is used to implement the sparse decomposition of the vibration signal. The envelope spectrum technique is used to analyze the results of the sparse decomposition for the fault feature extraction of the rolling element bearing. The experimental results show that the ADMM dictionary learning method can updates the dictionary atoms to better fit the original signal data than K-SVD dictionary learning, the high frequency noise in the vibration signal of the rolling bearing can be effectively suppressed, and the fault characteristic frequency can be highlighted, which is very favorable for the fault diagnosis of the rolling element bearing

Geometry-driven folding of a floating annular sheet

Predicting the large-amplitude deformations of thin elastic sheets is difficult due to the complications of self contact, geometric nonlinearities, and a multitude of low-lying energy states. We study a simple twodimensional setting where an annular polymer sheet floating on an air-water interface is subjected to different tensions on the inner and outer rims. The sheet folds and wrinkles into many distinct morphologies that break axisymmetry. These states can be understood within a recent geometric approach for determining the gross shape of extremely bendable yet inextensible sheets by extremizing an appropriate area functional. Our analysis explains the remarkable feature that the observed buckling transitions between wrinkled and folded shapes are insensitive to the bending rigidity of the sheet

Driver gene alterations in NSCLC patients in southern China and their correlation with clinicopathologic characteristics

IntroductionIn this study, we aimed to explore the relationship between clinicopathological features and driver gene changes in Chinese NSCLC patients.MethodsAmplification refractory mutation system PCR was used to detect the aberrations of 10 driver oncogenes in 851 Chinese NSCLC patients, and their correlation with clinicopathological characteristics was also analyzed. Moreover, three models of logistic regression were used to analyze the association between histopathology and EGFR or KRAS mutations.ResultsThe top two most frequently aberrant target oncogenes were EGFR (48.06%) and KRAS (9.51%). These were followed by ALK (5.41%), HER2 (2.35%), MET (2.23%), RET (2.11%), ROS1 (1.88%), BRAF (0.47%), NRAS (0.24%), and PIK3CA (0.12%). Additionally, 11 (1.29%) patients had synchronous gene alterations in two genes. The main EGFR mutations were exon 21 L858R and exon 19-Del, which accounted for 45.97% and 42.79% of all EGFR mutations, respectively. Logistic regression analysis showed that the frequency of EGFR mutations was positively correlated with women, non-smokers, lung adenocarcinoma, and invasive non-mucinous adenocarcinoma (IA), and negatively correlated with solid nodule, micro-invasive adenocarcinoma, and solid-predominant adenocarcinoma. KRAS mutations were positively associated with men and longer tumor long diameters and negatively correlated with lung adenocarcinoma (P < 0.05 for all).ConclusionOur findings suggest that the EGFR mutation frequency was higher in women, non-smokers, lung adenocarcinoma, and the IA subtype in lung adenocarcinoma patients, while the KRAS mutation rate was higher in men and patients with longer tumor long diameter and lower in lung adenocarcinoma patients