Controllable Emission via Tuning the Size of Fluorescent Nano-probes Formed by Polymeric Amphiphiles

Incorporating fluorophores into polymeric nanoparticles has been testified as a feasible way to improve the emitting property and bio-compatibility of nano-emitters, which can be applied as fluorescent probes in labeling cells for imaging. Plenty of efforts have been made on the above direction. However, the size effect of nano-emitters has not been addressed yet mainly given the difficulties in controlling morphology and size of the assemblies. In our preceding study, we employed post-polymerization modification method for preparing amphiphilic copolymers, and obtained core-shell(the hydrophobic fluorophores are wrapped inside the nanoparticle to form the core) assemblies in aqueous solution. By this method, we are able to regulate the ratio of the hydrophilic/hydrophobic moieties, and thus alternate the size of the assemblies in a rather simple way. In this study, we synthesized a series of random copolymers by changing the ratio of poly(ethylene glycol) to tetraphenylethylene groups. Notably, the number of repeating units of the polymer was controlled constant for all the copolymers. The self-assembly of these copolymers resulted in different sizes of nanoparticles, and the size decreased with the decreasing fraction of poly(ethylene glycol). Interestingly, the emission of the nanoparticles showed size dependence, and smaller diameter corresponded to stronger emission. Being cultured with HeLa cells, either the large(diameter of ~300 nm) or the small(diameter of ~180 nm) nano-emitters allowed for very high cell viabilities up to 25 μg·mL-1. Both of them can be applied in cell imaging and provide high contrast fluorescent images.

Functional characterization of a novel, highly expressed ion-driven sugar antiporter in the thoracic muscles of Helicoverpa armigera

Sugar transporters(STs),which mainly mediate cellular sugar exchanges,play critical physiological roles in living organisms,and they may be responsible for sugar exchanges among various insect tissues.However,the molecular and physiological functions of insect STs are largely unknown.Here,16 STs of Helicoverpa armigera were identified.A phylogenetic analysis classified the putative HaSTs into 12 sub-families,and those identified in this study were distributed into 6 sub-families.Real-time polymerase chain reaction indicated that the 16 HaSTs had diverse tissue-specific expression levels.One transporter,HaST10,was highly expressed in thoracic muscles.A functional study using a Xenopus oocyte expression system revealed that HaST10 mediated both H+-driven trehalose and Na+-driven glucose antiport activities with high transport efficiency and low affinity levels.A HaST10 knockout clearly impaired the performance of H.armigera.Thus,HaST10 may participate in sugar-supply regulation and have essential physiological roles in H.armigera.

Data-driven fault diagnosis of control valve with missing data based on modeling and deep residual shrinkage network

A control valve is one of the most widely used machines in hydraulic systems.However,it often works in harsh environments and failure occurs from time to time.An intelligent and robust control valve fault diagnosis is therefore important for operation of the system.In this study,a fault diagnosis based on the mathematical model(MM)imputation and the modified deep residual shrinkage network(MDRSN)is proposed to solve the problem that data-driven models for control valves are susceptible to changing operating conditions and missing data.The multiple fault time-series samples of the control valve at different openings are collected for fault diagnosis to verify the effectiveness of the proposed method.The effects of the proposed method in missing data imputation and fault diagnosis are analyzed.Compared with random and k-nearest neighbor(KNN)imputation,the accuracies of MM-based imputation are improved by 17.87%and 21.18%,in the circumstances of a20.00%data missing rate at valve opening from 10%to 28%.Furthermore,the results show that the proposed MDRSN can maintain high fault diagnosis accuracy with missing data.