Progress in Aptamer-Mediated Drug Delivery Vehicles for Cancer Targeting and Its Implications in Addressing Chemotherapeutic Challenges

Aptamers are novel oligonucleotides with flexible three-dimensional configurations that recognize and bind to their cognate targets, including tumor surface receptors, in a high-affinity and highly specific manner. Because of their unique intrinsic properties, a variety of aptamer-mediated nanovehicles have been developed to directionally transport anti-cancer drugs to tumor sites to minimize systemic cytotoxicity and to enhance permeation by these tumoricidal agents. Despite advances in the selection and synthesis of aptamers and in the conjugation and self-assembly of nanotechnologies, current chemotherapy and drug delivery systems face great challenges. These challenges are due to the limitations of aptamers and vehicles and because of complicated tumor mechanisms, including heterogeneity, anti-cancer drug resistance, and hypoxia-induced aberrances. In this review, we will summarize current approaches utilizing tumor surface hallmarks and aptamers and their roles and mechanisms in therapeutic nanovehicles targeting tumors. Delivery forms include nanoparticles, nanotubes, nanogels, aptamer-drug conjugates, and novel molecular trains. Moreover, the obstacles posed by the aforementioned issues will be highlighted, and possible solutions will be acknowledged. Furthermore, future perspectives will be presented, including cutting-edge integration with RNA interference nanotechnology and personalized chemotherapy, which will facilitate innovative approaches to aptamer-based therapeutics

Distribution of nucleosides in populations of Cordyceps cicadae

A rapid HPLC method had been developed and used for the simultaneous determination of 10 nucleosides (uracil, uridine, 2'-deoxyuridine, inosine, guanosine, thymidine, adenine, adenosine, 2'-deoxyadenosine and cordycepin) in 10 populations of Cordyceps cicadae, in order to compare four populations of Ophicordyceps sinensis and one population of Cordyceps militaris. Statistical analysis system (SAS) 8.1 was used to analyze the nucleoside data. The pattern of nucleoside distribution was analyzed in the sampled populations of C. cicadae, O. sinensis and C. militaris, using descriptive statistical analysis, nested analysis and Q cluster analysis. The total amount of the 10 nucleosides in coremium was 1,463.89-5,678.21 mu g/g in 10 populations of C. cicadae, 1,369.80-3,941.64 mu g/g in sclerotium. The average contents of the 10 analytes were 4,392.37 mu g/g and 3,016.06 mu/g in coremium and sclerotium, respectively. The coefficient of variation (CV) of nucleosides ranged from 8.36% to 112.36% in coremium of C. cicadae, and from 10.77% to 155.87% in sclerotium of C. cicadae. The CV of the nucleosides was wide within C. cicadae populations. The nested variation analysis by the nine nucleosides' distribution indicated that about 42.29% of the nucleoside variability in coremium was attributable to the differentiation among populations, and the remaining 57.71% resided in the populations. It was also shown that about 28.94% of the variation in sclerotium was expressed between populations, while most of the variation (71.06%) corresponded to the populations

Cyclic intensive light exposure induces retinal lesions similar to age-related macular degeneration in APPswe/PS1 bigenic mice

<p>Abstract</p> <p>Background</p> <p>Intensive light exposure and beta-amyloid (Aβ) aggregates have been known as a risk factor for macular degeneration and an important component in the pathologic drusen structure involved in this disorder, respectively. However, it is unknown whether Aβ deposition mediates or exacerbates light exposure-induced pathogenesis of macular degeneration. Several studies including the one from us already showed accumulation of Aβ deposits in the retina in Alzheimer's transgenic mice. Using histopathological analysis combined with electroretinographic functional assessment, we investigated the effects of cyclic intensive light exposure (CILE) on the architecture of retina and related function in the APPswe/PS1bigenic mouse.</p> <p>Results</p> <p>Histopathological analysis has found significant loss of outer nuclear layer/photoreceptor outer segment and outer plexiform layer along with abnormal hypo- and hyper-pigmentation in the retinal pigment epithelium (RPE), remarkable choroidal neovascularization (CNV), and exaggerated neuroinflammatory responses in the outer retina of APPswe/PS1 bigenic mice following cyclic intensive light exposure (CILE), whereas controls remained little change contrasted with age-matched non-transgenic littermates. CILE-induced degenerative changes in RPE are further confirmed by transmission electron microcopy and manifest as formation of basal laminar deposits, irregular thickening of Bruch's membrane (BrM), deposition of outer collagenous layer (OCL) in the subretinal space, and vacuolation in the RPE. Immunofluorescence microscopy reveals drusenoid Aβ deposits in RPE as well as neovessels attached which are associated with disruption of RPE integrity and provoked neuroinflammatory response as indicated by markedly increased retinal infiltration of microglia. Moreover, both immunohistochemistry and Western blots detect an induction of vascular endothelial growth factor (VEGF) in RPE, which corroborates increased CNV in the outer retina in the bigenic mice challenged by CILE.</p> <p>Conclusions</p> <p>Our findings demonstrate that degenerative changes in the outer retina in the APPswe/PS1 bigenic mouse induced by CILE are consistent with these in AMD. These results suggest that an Alzheimer's transgenic animal model with accumulation of Aβ deposits might be an alternative animal model for AMD, if combined with other confounding factors such as intensive light exposure for AMD.</p

Robot sensor calibration via neural network and particle swarm optimization enhanced with crossover and mutation

U cilju određivanja položaja i orijentacije nekog predmeta u zglobu za robot, treba procijeniti odnos transformacije sustava ruka-oko, što se opisuje kao rotacijska matrica i vektor translacije. Predlaže se novi pristup koji integrira neuronsku mrežu i algoritam optimaizacije roja čestica s operacijom križanja i mutacije za kalibraciju osjećaja robota. Najprije se strukturira neuronska mreža s matricom rotacijske težine gdje su težine elementi rotacijskog dijela homogenog prijenosa sustava ruka-oko. Tada se algoritam optimalizacije roja čestica integrira u program rješavanja, gdje se faktori težine inercije i vjerojatnosti mutacije sami podešavaju prema putanji gibanja čestica u longitudinalnom pravcu i lateralnom pravcu. Kad je zadovoljen kriterij terminacije, rotaciona matrica se dobiva iz nepromjenljivih težina neuronske mreže. Tada se rješava vektor translacije i postiže se položaj i orijentacija slike s kamere u odnosu na sliku sa zgloba. Predloženi pristup pruža novu šemu za kalibraciju robota tehnikom samo-adaptacije, što garantira ortogonalnost riješenih rotacijskih komponenti homogenog transforma.In order to determine the position and orientation of an object in the wrist frame for robot, transform relation of hand-eye system should be estimated, which is described as rotational matrix and translational vector. A new approach integrating neural network and particle swarm optimization algorithm with crossover and mutation operation for robot sense calibration is proposed. First the neural network with rotational weight matrix is structured, where the weights are the elements of rotational part of homogeneous transform of the hand-eye system. Then the particle swarm optimization algorithm is integrated into the solving program, where the inertia weight factor and mutation probability are tuned self-adaptively according to the motion trajectory of particles in longitudinal direction and lateral direction. When the termination criterion is satisfied, the rotational matrix is obtained from the neural network’s stable weights. Then the translational vector is solved, so the position and orientation of camera frame with respect to wrist frame is achieved. The proposed approach provides a new scheme for robot sense calibration with self-adaptive technique, which guarantees the orthogonality of solved rotational components of the homogeneous transform

Robot sensor calibration via neural network and particle swarm optimization enhanced with crossover and mutation

U cilju određivanja položaja i orijentacije nekog predmeta u zglobu za robot, treba procijeniti odnos transformacije sustava ruka-oko, što se opisuje kao rotacijska matrica i vektor translacije. Predlaže se novi pristup koji integrira neuronsku mrežu i algoritam optimaizacije roja čestica s operacijom križanja i mutacije za kalibraciju osjećaja robota. Najprije se strukturira neuronska mreža s matricom rotacijske težine gdje su težine elementi rotacijskog dijela homogenog prijenosa sustava ruka-oko. Tada se algoritam optimalizacije roja čestica integrira u program rješavanja, gdje se faktori težine inercije i vjerojatnosti mutacije sami podešavaju prema putanji gibanja čestica u longitudinalnom pravcu i lateralnom pravcu. Kad je zadovoljen kriterij terminacije, rotaciona matrica se dobiva iz nepromjenljivih težina neuronske mreže. Tada se rješava vektor translacije i postiže se položaj i orijentacija slike s kamere u odnosu na sliku sa zgloba. Predloženi pristup pruža novu šemu za kalibraciju robota tehnikom samo-adaptacije, što garantira ortogonalnost riješenih rotacijskih komponenti homogenog transforma.In order to determine the position and orientation of an object in the wrist frame for robot, transform relation of hand-eye system should be estimated, which is described as rotational matrix and translational vector. A new approach integrating neural network and particle swarm optimization algorithm with crossover and mutation operation for robot sense calibration is proposed. First the neural network with rotational weight matrix is structured, where the weights are the elements of rotational part of homogeneous transform of the hand-eye system. Then the particle swarm optimization algorithm is integrated into the solving program, where the inertia weight factor and mutation probability are tuned self-adaptively according to the motion trajectory of particles in longitudinal direction and lateral direction. When the termination criterion is satisfied, the rotational matrix is obtained from the neural network’s stable weights. Then the translational vector is solved, so the position and orientation of camera frame with respect to wrist frame is achieved. The proposed approach provides a new scheme for robot sense calibration with self-adaptive technique, which guarantees the orthogonality of solved rotational components of the homogeneous transform

Optimal Energy Control Strategy Design for a Hybrid Electric Vehicle

A heavy-duty parallel hybrid electric truck is modeled, and its optimal energy control is studied in this paper. The fundamental architecture of the parallel hybrid electric truck is modeled feed-forwardly, together with necessary dynamic features of subsystem or components. Dynamic programming (DP) technique is adopted to find the optimal control strategy including the gear-shifting sequence and the power split between the engine and the motor subject to a battery SOC-sustaining constraint. Improved control rules are extracted from the DP-based control solution, forming near-optimal control strategies. Simulation results demonstrate that a significant improvement on the fuel economy can be achieved in the heavy-duty vehicle cycle from the natural driving statistics