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Abstract Background l-ascorbic acid (Asc) plays a pivotal role in regulating various biological processes, including somatic cell reprogramming, through multiple pathways. However, it remains unclear whether Asc regulates reprogramming directly or functions through its metabolites. Results Asc exhibited dual capabilities in promoting reprogramming through both 2,3-diketo-l-gulonic acid (DKG), a key metabolite during Asc degradation, dependent and independent routes. On the one hand, Asc facilitated reprogramming by promoting cell proliferation and inducing the conversion from pre-induced pluripotent stem cells (pre-iPSCs) to iPSCs through DKG-independent pathways. Additionally, Asc triggered mesenchymal-epithelial transition (MET) and activated glycolysis via DKG-dependent mechanisms. Notably, DKG alone activated a non-canonical tricarboxylic acid cycle characterized by increased succinate, fumarate, and malate. Consequently, this shift redirected oxidative phosphorylation toward glycolysis and induced MET. Moreover, owing to its antioxidant capabilities, Asc directly inhibited glycolysis, thereby preventing positive feedback between glycolysis and epithelial-mesenchymal transition, ultimately resulting in a higher level of MET. Conclusion These findings unveil the intricate functions of Asc in the context of reprogramming. This study sheds light on the DKG-dependent and -independent activities of Asc during reprogramming, offering novel insights that may extend the application of Asc to other biological processes.

Soft robots have received a lot of attention because of their great human-robot interaction and environmental adaptability. Most soft robots are currently limited in their applications due to wired drives. Photoresponsive soft robotics is one of the most effective ways to promote wireless soft drives. Among the many soft robotics materials, photoresponsive hydrogels have received a lot of attention due to their good biocompatibility, ductility, and excellent photoresponse properties. This paper visualizes and analyzes the research hotspots in the field of hydrogels using the literature analysis tool Citespace, demonstrating that photoresponsive hydrogel technology is currently a key research direction. Therefore, this paper summarizes the current state of research on photoresponsive hydrogels in terms of photochemical and photothermal response mechanisms. The progress of the application of photoresponsive hydrogels in soft robots is highlighted based on bilayer, gradient, orientation, and patterned structures. Finally, the main factors influencing its application at this stage are discussed, including the development directions and insights. Advancement in photoresponsive hydrogel technology is crucial for its application in the field of soft robotics. The advantages and disadvantages of different preparation methods and structures should be considered in different application scenarios to select the best design scheme.

Abstract Retinoic acid (RA) and 2-phospho-L-ascorbic acid trisodium salt (AscPNa) promote the reprogramming of mouse embryonic fibroblasts to induced pluripotent stem cells. In the current studies, the lower abilities of RA and AscPNa to promote reprogramming in the presence of each other suggested that they may share downstream pathways at least partially. The hypothesis was further supported by the RNA-seq analysis which demonstrated a high-level overlap between RA-activated and AscPNa activated genes during reprogramming. In addition, RA upregulated Glut1/3, facilitated the membrane transportation of dehydroascorbic acid, the oxidized form of L-ascorbic acid, and subsequently maintained intracellular L-ascorbic acid at higher level and for longer time. On the other hand, AscPNa facilitated the mesenchymal-epithelial transition during reprogramming, downregulated key mesenchymal transcriptional factors like Zeb1 and Twist1, subsequently suppressed the expression of Cyp26a1/b1 which mediates the metabolism of RA, and sustained the intracellular level of RA. Furthermore, the different abilities of RA and AscPNa to induce mesenchymal-epithelial transition, pluripotency, and neuronal differentiation explain their complex contribution to reprogramming when used individually or in combination. Therefore, the current studies identified a positive feedback between RA and AscPNa, or possibility between vitamin A and C, and further explored their contributions to reprogramming.

Summary: Normally, opioids function in a receptor-dependent manner. They bind to opioid receptors, activate or inhibit receptor activation, and subsequently modulate downstream signal transduction. However, the complex functions of opioids and the low expression of opioid receptors and their endogenous peptide agonists in neural stem cells (NSCs) suggest that some opioids may also modulate NSCs via a receptor-independent pathway. In the current study, two opioids, morphine and naloxone, are demonstrated to facilitate NSC proliferation via a receptor-independent and ten-eleven translocation methylcytosine dioxygenase 1 (TET1)-dependent pathway. Morphine and naloxone penetrate cell membrane, bind to TET1 protein via three key residues (1,880–1,882), and subsequently result in facilitated proliferation of NSCs. In addition, the two opioids also inhibit the DNA demethylation ability of TET1. In summary, the current results connect opioids and DNA demethylation directly at least in NSCs and extend our understanding on both opioids and NSCs. : Liang et al. demonstrate a receptor-independent and Tet1-dependent pathway used by opioids naloxone and morphine to facilitate the proliferation of NSCs. The binding of naloxone and morphine to TET1 suggests that DNA methylation should be considered when studying the tolerance- and addiction-induced opioids. Keywords: neural stem cells, naloxone, morphine, Tet1, receptor-independent, proliferation

When the shearer is cutting, the sound signal generated by the cutting drum crushing coal and rock contains a wealth of cutting status information. In order to effectively process the shearer cutting sound signal and accurately identify the cutting mode, this paper proposed a shearer cutting sound signal recognition method based on an improved complete ensemble empirical mode decomposition with adaptive noise (ICCEMDAN) and an improved grey wolf optimizer (IGWO) algorithm-optimized support vector machine (SVM). First, the approach applied ICEEMDAN to process the cutting sound signal and obtained several intrinsic mode function (IMF) components. It used the correlation coefficient to select the characteristic component. Meanwhile, this paper calculated the composite multi-scale permutation entropy (CMPE) of the characteristic components as the eigenvalue. Then, the method introduced a differential evolution algorithm and nonlinear convergence factor to improve the GWO algorithm. It used the improved GWO algorithm to realize the adaptive selection of SVM parameters and established a cutting sound signal recognition model. According to the proportioning plan, the paper made several simulation coal walls for cutting experiments and collected cutting sound signals for cutting pattern recognition. The experimental results show that the method proposed in this paper can effectively process the cutting sound signal of the shearer, and the average accuracy of the cutting pattern recognition model reached 97.67%.

When the shearer cuts coal or rock with different hardness, it will produce corresponding cutting state information. This paper develops a simulation cutting experiment system for the drum shearer based on similarity theory. It took the spiral cutting drum of a shearer as the research target and derived the principal similarity coefficients through the dimensional analysis method. Meanwhile, this paper designed the structure of the cutting power system and hydraulic system. Then, it chose a certain amount of coal powder as an aggregate, cement 325# as cementing material, sand, and water as auxiliary materials to prepare simulated coal samples. The paper adopted the orthogonal experiment method and used a proportion of cement, sand, and water as the influencing factors in designing a simulated coal sample preparation plan. In addition, it utilized the range analysis method to research the influence of various factors on the density and compressive strength of simulated coal samples. Finally, it conducted simulated coal sample cutting tests. The results show that the density of the simulated coal samples is between 1192.59 Kg/m3–1483.51 Kg/m3, and the compressive strength range reaches 0.16 MPa–3.94 MPa. The density of the simulated coal sample is related to the mass proportion of cement and sand. When the ratio gradually increases, the influence of sand increases. Furthermore, the compressive strength is linearly proportional to the proportion of cement. The self-designed simulation cutting experiment system could effectively carry out the relevant experiments and obtain the corresponding cutting condition signals through the sensors. There are differences in vibration signals generated by cutting different strength materials. Extracting the kurtosis value as the characteristic value can distinguish various cutting modes, which can provide a reliable experimental solution for the research of coal-rock identification.