44 research outputs found
pH-responsive stearic acid- O -carboxymethyl chitosan assemblies as carriers delivering small molecular drug for chemotherapy
Abstract(#br)Recently, chemotherapy is still widely exploited to treat the residual, infiltrative tumor cells after surgical resection. However, many anticancer drugs are limited in clinical application due to their poor water-solubility (hydrophibic) and stability, low bioavailability, and unfavorable pharmacokinetics. Herein, an amphiphilic stearic acid- O -carboxymethyl chitosan (SA-CMC) conjugate was synthesized by amide linkage of SA to the backbone of CMC polymer and then self-assembled into nanoparticles (SA-CMC NPs) with the hydrodynamic particle size of ~100 nm. Subsequently, Paclitaxel (PTX) as a potent and broad-spectrum anticancer drug was loaded into SA-CMC NPs by a probe sonication combined with dialysis method. Owing to the multi-hydrophobic inner cores, the prepared PTX-SA-CMC NPs showed a considerable drug-loading capacity of ~19 wt% and a biphasic release behavior with an accumulative release amount in the range of 70–90% within 72 h. PTX-SA-CMC NPs remarkably enhanced the accumulation at the tumor sites by passive targeting followed by cellular endocytosis. Upon the stimuli of acid, PTX-SA-CMC NPs showed exceptional instability by pH change, thereby triggering the rapid disassembly and accelerated drug release. Consequently, compared with Cremophor EL-based free PTX treatment, PTX-SA-CMC NPs under pH-stimuli accomplished highly efficient apoptosis in cancer cells and effectively suppression of tumors by chemotherapy. Overall, PTX-SA-CMC NPs integrating imaging capacity might be a simple yet feasible PTX nanosystem for tumor-targeted delivery and cancer therapy
pH-responsive stearic acid-O-carboxymethyl chitosan assemblies as carriers delivering small molecular drug for chemotherapy.
Recently, chemotherapy is still widely exploited to treat the residual, infiltrative tumor cells after surgical resection. However, many anticancer drugs are limited in clinical application due to their poor water-solubility (hydrophibic) and stability, low bioavailability, and unfavorable pharmacokinetics. Herein, an amphiphilic stearic acid-O-carboxymethyl chitosan (SA-CMC) conjugate was synthesized by amide linkage of SA to the backbone of CMC polymer and then self-assembled into nanoparticles (SA-CMC NPs) with the hydrodynamic particle size of ~100 nm. Subsequently, Paclitaxel (PTX) as a potent and broad-spectrum anticancer drug was loaded into SA-CMC NPs by a probe sonication combined with dialysis method. Owing to the multi-hydrophobic inner cores, the prepared PTX-SA-CMC NPs showed a considerable drug-loading capacity of ~19 wt% and a biphasic release behavior with an accumulative release amount in the range of 70-90% within 72 h. PTX-SA-CMC NPs remarkably enhanced the accumulation at the tumor sites by passive targeting followed by cellular endocytosis. Upon the stimuli of acid, PTX-SA-CMC NPs showed exceptional instability by pH change, thereby triggering the rapid disassembly and accelerated drug release. Consequently, compared with Cremophor EL-based free PTX treatment, PTX-SA-CMC NPs under pH-stimuli accomplished highly efficient apoptosis in cancer cells and effectively suppression of tumors by chemotherapy. Overall, PTX-SA-CMC NPs integrating imaging capacity might be a simple yet feasible PTX nanosystem for tumor-targeted delivery and cancer therapy
Pharmacokinetics and Tissue Distribution of DVDMS-2 in Tumor-bearing Mice.
DVDMS-2 is a novel candidate for photodynamic therapy of tumors. The purpose of the present study was to assess the distribution and elimination of DVDMS-2 in mice bearing hepatoma 22 tumors. DVDMS-2 (1, 2 and 4 mg kg-1 ) was injected intravenously into the mice, extracted from biological tissues and quantified using a fluorescence assay. The data obtained were processed with WinNonlin pharmacokinetic software. The fluorescence assay established for DVDMS-2 quantification was a rapid, reproducible, sensitive and specific method with good linearity. The pharmacokinetics of DVDMS-2 in tumor-bearing mice conformed to a two-compartment model. DVDMS-2 accumulated in tumor tissue to a greater extent than adjacent tissues (skin, muscle) and sustained a relatively high-level concentration 12 to 24 h following administration, which may be the optimal treatment time point. In conclusion, DVDMS-2 selectively accumulated in tumor tissue and was eliminated at a rapid rate in tumor-bearing mice, suggesting that DVDMS-2 may have few side effects, including skin phototoxicity. The present study established the pharmacokinetic characteristics of DVDMS-2, which may be beneficial in future clinical study
The 2023 China report of the Lancet Countdown on health and climate change: taking stock for a thriving future
Household, community, sub-national and country-level predictors of primary cooking fuel switching in nine countries from the PURE study
Introduction. Switchingfrom polluting (e.g. wood, crop waste, coal)to clean (e.g. gas, electricity) cooking
fuels can reduce household air pollution exposures and climate-forcing emissions.While studies have
evaluated specific interventions and assessed fuel-switching in repeated cross-sectional surveys, the role
of different multilevel factors in household fuel switching, outside of interventions and across diverse
community settings, is not well understood. Methods.We examined longitudinal survey data from
24 172 households in 177 rural communities across nine countries within the Prospective Urban and
Rural Epidemiology study.We assessed household-level primary cooking fuel switching during a
median of 10 years offollow up (∼2005–2015).We used hierarchical logistic regression models to
examine the relative importance of household, community, sub-national and national-level factors
contributing to primary fuel switching. Results. One-half of study households(12 369)reported
changing their primary cookingfuels between baseline andfollow up surveys. Of these, 61% (7582)
switchedfrom polluting (wood, dung, agricultural waste, charcoal, coal, kerosene)to clean (gas,
electricity)fuels, 26% (3109)switched between different polluting fuels, 10% (1164)switched from clean
to polluting fuels and 3% (522)switched between different clean fuels
Household, community, sub-national and country-level predictors of primary cooking fuel switching in nine countries from the PURE study
A novel semantic matching method for chatbots based on convolutional neural network and attention mechanism
Influence of Ungrafted Monomers in Graft Copolymers on Electrical Insulating Properties of Polyethylene
Research on Repetition Counting Method Based on Complex Action Label String
Smart factories have real-time demands for the statistics of productivity to meet the needs of quick reaction capabilities. To solve this problem, a counting method based on our decomposition strategy of actions was proposed for complex actions. Our method needs to decompose complex actions into several essential actions and define a label string for each complex action according to the sequence of the essential actions. While counting, we firstly employ an online action recognition algorithm to transform video frames into label numbers, which will be stored in a result queue. Then, the label strings are searched for their results in queue. If the search succeeds, a complex action will be considered to have occurred. Meanwhile, the corresponding counter should be updated to accomplish counting. The comparison test results in a video dataset of workers’ repetitive movements in package printing production lines and illustrate that our method has a lower counting errors, MAE (mean absolute error) less than 5% as well as an OBOA (off-by-one accuracy) more than 90%. Moreover, to enhance the adaptability of the action recognition model to deal with the change of action duration, we propose an adaptive parameter module based on the Kalman filter, which improves counting performances to a certain extent. The conclusions are that our method can achieve high counting performance, and the adaptive parameter module can further improve performances
A direct power control strategy for AC/DC converter based on best switching state approach
In this paper, we propose a direct power control (DPC) method for the ac/dc converter based on the designed dynamic nonlinear model and an approach on selecting the best possible switching state, aiming at guaranteeing the ac current quality, and improving the transient performance, especially under the unbalanced power-source voltage conditions. The proposed DPC mainly consists of three parts, sector selection, outer dc voltage control loop, and inner power control loop. Certain logical expressions are proposed in the sector selection to determine the position of the positive sequence power-source voltage vector. In the outer dc voltage loop, a control law is constructed based on a Lyapunov function. Moreover, a controller based on the best switching state is designed in the inner power loop to eliminate the negative sequence current. The proposed scheme is tested on an experimental platform, and the results show that, compared with the conventional DPC method, the total harmonic distortion of ac currents is reduced by more than 40%, and the transient settling time is almost reduced by 57% under the balanced power-source voltage condition. When the power-source voltage is unbalanced, the ac current quality can still be guaranteed with the proposed control method