The microtubule-stabilizing drug paclitaxel (PTX) is a chemotherapeutic agent widely prescribed for the treatment of various tumor types. The main adverse effect of PTX-mediated therapy is chemotherapy-induced peripheral neuropathy (CIPN) and neuropathic pain, which are similar to the adverse effects associated with other chemotherapeutic agents. Dorsal root ganglia (DRG) contain primary sensory neurons; any damage to these neurons or their axons may lead to neuropathic pain. To gain molecular and neurobiological insights into the peripheral sensory system under conditions of PTX-induced neuropathic pain, we used transcriptomic analysis to profile mRNA and non-coding RNA expression in the DRGs of adult male C57BL/6 mice treated using PTX. RNA sequencing and in-depth gene expression analysis were used to analyze the expression levels of 67,228 genes. We identified 372 differentially expressed genes (DEGs) in the DRGs of vehicle- and PTX-treated mice. Among the 372 DEGs, there were 8 mRNAs, 3 long non-coding RNAs (lncRNAs), 16 circular RNAs (circRNAs), and 345 microRNAs (miRNAs). Moreover, the changes in the expression levels of several miRNAs and circRNAs induced by PTX have been confirmed using the quantitative polymerase chain reaction method. In addition, we compared the expression levels of differentially expressed miRNAs and mRNA in the DRGs of mice with PTX-induced neuropathic pain against those evaluated in other models of neuropathic pain induced by other chemotherapeutic agents, nerve injury, or diabetes. There are dozens of shared differentially expressed miRNAs between PTX and diabetes, but only a few shared miRNAs between PTX and nerve injury. Meanwhile, there is no shared differentially expressed mRNA between PTX and nerve injury. In conclusion, herein, we show that treatment with PTX induced numerous changes in miRNA expression in DRGs. Comparison with other neuropathic pain models indicates that DEGs in DRGs vary greatly among different models of neuropathic pain.
The slate re-ranking problem considers the mutual influences between items to improve user satisfaction in e-commerce, compared with the point-wise ranking. Previous works either directly rank items by an end to end model, or rank items by a score function that trades-off the point-wise score and the diversity between items. However, there are two main existing challenges that are not well studied: (1) the evaluation of the slate is hard due to the complex mutual influences between items of one slate; (2) even given the optimal evaluation, searching the optimal slate is challenging as the action space is exponentially large. In this paper, we present a novel Generator and Critic slate re-ranking approach, where the Critic evaluates the slate and the Generator ranks the items by the reinforcement learning approach. We propose a Full Slate Critic (FSC) model that considers the real impressed items and avoids the "impressed bias" of existing models. For the Generator, to tackle the problem of large action space, we propose a new exploration reinforcement learning algorithm, called PPO-Exploration. Experimental results show that the FSC model significantly outperforms the state of the art slate evaluation methods, and the PPO-Exploration algorithm outperforms the existing reinforcement learning methods substantially. The Generator and Critic approach improves both the slate efficiency(4% gmv and 5% number of orders) and diversity in live experiments on one of the largest e-commerce websites in the world.
Starch-g-poly(acrylic acid)/organo-mordenite (St-g-PAA/OMOR) superabsorbent composites were prepared via inverse suspension polymerizationutilizing potassium persulfate as an initiator and N, N’-methylene bisacrylamide as a crosslinker. Different dosages of cetyltrimethylammonium bromide were used to obtain organo-mordenite (OMOR) samples with different organification degrees. The effects of the organification degree of OMOR on the water absorbency, swelling behavior, and reswelling properties of St-g-PAA/OMOR were studied. The results from both FTIR and XRD analyses indicate that the Si–OH group of OMOR was involved in the formation of the St-g-PAA/OMOR composite. SEM analyses showed that the organification degree of OMOR influenced the morphology of the St-g-PAA/OMOR composite. The water absorption absorbency, swelling rate, and reswelling capability of the St-g-PAA/OMOR composite prepared using the OMOR with the optimal organification degree were superior to those of the St-g-PAA/mordenite composite. The swelling behaviors of the St-g-PAA/OMOR composites, which were measured in distilled water, obeyed Schott’s second-order kinetics model. The St-g-PAA/OMOR composite prepared using the OMOR with the 8 wt.% organification degree had the highest water absorption capacity and the highest swelling rate. Moreover, after five swelling–shrinking cycles, the composite retained its excellent water absorption capacity.
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