The miR-19a/Cylindromatosis Axis Regulates Pituitary Adenoma Bone Invasion by Promoting Osteoclast Differentiation.

BACKGROUND: The presence of bone invasion in aggressive pituitary adenoma (PA) was found in our previous study, suggesting that PA cells may be involved in the process of osteoclastogenesis. miR-19a (as a key member of the miR-17-92 cluster) has been reported to activate the nuclear factor-кB (NF-кB) pathway and promote inflammation, which could be involved in the process of the bone invasion of pituitary adenoma. METHODS: In this work, FISH was applied to detect miR-19a distribution in tissues from patients with PA. A model of bone invasion in PA was established, GH3 cells were transfected with miR-19a mimic, and the grade of osteoclastosis was detected by HE staining. qPCR was performed to determine the expression of miR-19a throughout the course of RANKL-induced osteoclastogenesis. After transfected with a miR-19a mimic, BMMs were treated with RANKL for the indicated time, and the osteoclast marker genes were detected by qPCR and Western Blot. Pit formation and F-actin ring assay were used to evaluate the function of osteoclast. The TargetScan database and GSEA were used to find the potential downstream of miR-19a, which was verified by Co-IP, Western Blot, and EMSA. RESULTS: Here, we found that miR-19a expression levels were significantly correlated with the bone invasion of PA, both in clinical samples and animal models. The osteoclast formation prior to bone resorption was dramatically enhanced by miR-19, which was mediated by decreased cylindromatosis (CYLD) expression, increasing the K63 ubiquitination of tumor necrosis factor receptor-associated factor 6 (TRAF6). Consequently, miR-19a promotes osteoclastogenesis by the activation of the downstream NF-кB and mitogen-activated protein kinase (MAPK) pathways. CONCLUSIONS: To summarize, the results of this study indicate that PA-derived miR-19a promotes osteoclastogenesis by inhibiting CYLD expression and enhancing the activation of the NF-кB and MAPK pathways.

Ruminal Fluid Transplantation Accelerates Rumen Microbial Remodeling and Improves Feed Efficiency in Yaks.

A relatively stable microbial ecological balance system in the rumen plays an important role in rumen environment stability and ruminant health maintenance. No studies have reported how rumen fluid transplantation (RFT) affects the composition of rumen microorganisms and yak growth performance. In this experiment, we transplanted fresh rumen fluid adapted to house-feeding yaks to yaks transitioned from natural pastures to house-feeding periods to investigate the effects of rumen fluid transplantation on rumen microbial community regulation and production performance. Twenty yaks were randomly divided into the control group (CON; n = 10) and the rumen fluid transplantation group (RT; n = 10). Ten yaks that had been adapted to stall fattening feed in one month were selected as the rumen fluid donor group to provide fresh rumen fluid. Ruminal fluid transplantation trials were conducted on the 1st, 3rd, and 5th. Overall, 1 L of ruminal fluid was transplanted to each yak in the RT and CON group. The formal trial then began with both groups fed the same diet. After this, growth performance was measured, rumen fluid was collected, and rumen microbial composition was compared using 16s rRNA sequencing data. The results showed that rumen fluid transplantation had no significant effect on yak total weight gain or daily weight gain (p > 0.05), and feed efficiency was higher in the RT group than in the CON group at 3 months (treatment × month: p < 0.01). Ruminal fluid transplantation significantly affected rumen alpha diversity (p < 0.05). Up to day 60, the RT group had significantly higher OTU numbers, Shannon diversity, and Simpson homogeneity than the CON group. Principal coordinate analysis showed that the rumen microbiota differed significantly on days 4 and 7 (p < 0.05). Bacteroidota, Firmicutes, Proteobacteria, and Spirochaetes were the most abundant phyla in the rumen. The relative abundances of Bacteroidota, Proteobacteria, and Spirochaetes were lower in the RT group than in the CON group, with a decrease observed in Bacteroidota in the RT group on days 7 and 28 after rumen fluid transplantation (p = 0.013), while Proteobacteria showed a decreasing trend in the CON group and an increasing trend in RT; however, this was only at day 4 (p = 0.019). The relative abundance of Firmicutes was significantly higher in the RT group than in the CON group on days 4, 7, and 28 (p = 0.001). Prevotella and Rikenellaceae_RC9_gut_group were the predominant genera. In conclusion, our findings suggest that rumen fluid transplantation improves yak growth performance and rumen microbial reshaping. The findings of this study provide new insights into yak microbial community transplantation and a reference for improving feed efficiency in the yak industry.

Enhanced Charge Separation for Efficient Photocatalytic H2 Production by Long-Lived Trap-State-Induced Interfacial Charge Transfer.

Photogeneration of charge carriers in semiconductors provides the scientific fundamental for photocatalytic water splitting. However, an ongoing challenge is the development of a new mechanism promoting charge carrier separation. Here we propose a trap-state-induced interfacial charge-transfer transition mechanism (TSICTT), in which electrons in long-lived trap states recombine with holes on the valence band (VB) of the semiconductor, thus prolonging the electron lifetime. We demonstrate this concept in the Sr4Al14O25:Eu2+, Dy3+/CdS (SAO/CdS) heterostructure, where trapped electrons with a lifetime of up to several hours in the SAO persistent luminescence phosphor (PLP) can continuously consume holes on the VB of CdS nanoparticles (NPs). We discover that the interfacial interaction and the work function difference between SAO and CdS are crucial for the TSICTT, which finally contributes to the improved H2 production from 34.4 to 1212.9 µmol gCdS-1 h-1 under visible-light irradiation. This model introduces a new strategy to manipulate charge carrier transport for the effective utilization of solar energy.

π-d Electron-Coupled PBDIT/CdS Heterostructure Enables Hole Extraction for Efficient Photocatalytic Hydrogen Production.

Construction of heterostructures is one of the most promising strategies for designing photocatalysts for highly efficient solar hydrogen (H2) production because the introduction of an electron-donating counterpart contributes to more effective photon absorption, while the heterostructures benefit spatial carrier separation. However, the hole-transfer rate is usually 2-3 orders of magnitude slower than that of the electron-transfer rate within the heterostructures, ensuing serious charge recombination. Here, we find the energy band offset-driven charge-transfer behavior in a donor-acceptor (D-A)-conjugated polymer/CdS organic/inorganic heterostructure and realize hole-transfer improvement in cooperation with a further hole removal motif of poly(3,4-ethylenedioxythiophene) polystyrene sulfonate. The photocatalytic H2 production activity is increased by nearly 2 orders of magnitude with the apparent quantum yield hitting ca. 80% at 450 nm without co-catalysts. Ultrafast transient absorption together with surface photovoltage characterizations consolidates the hole extraction mechanism. The intimate bond formed at the interface between the polymer and the inorganic semiconductor acts as an interpenetrating network at the nanoscale level, thus providing a charge-transfer freeway for boosting charge separation.

Intelligent L2-L∞ Consensus of Multiagent Systems under Switching Topologies via Fuzzy Deep Q Learning.

The problem of intelligent L 2-L ∞ consensus design for leader-followers multiagent systems (MASs) under switching topologies is investigated based on switched control theory and fuzzy deep Q learning. It is supposed that the communication topologies are time-varying, and the model of MASs under switching topologies is constructed based on switched systems. By employing linear transformation, the problem of consensus of MASs is converted into the issue of L 2-L ∞ control. The consensus protocol is composed of the dynamics-based protocol and learning-based protocol, where the robust control theory and deep Q learning are applied for the two parts to guarantee the prescribed performance and improve the transient performance. The multiple Lyapunov function (MLF) method and mode-dependent average dwell time (MDADT) method are combined to give the scheduling interval, which ensures stability and prescribed attenuation performance. The sufficient existing conditions of consensus protocol are given, and the solutions of the dynamics-based protocol are derived based on linear matrix inequalities (LMIs). Then, the online design of the learning-based protocol is formulated as a Markov decision process, where the fuzzy deep Q learning is utilized to compensate for the uncertainties and achieve optimal performance. The variation of the learning-based protocol is modeled as the external compensation on the dynamics-based protocol. Therefore, the convergence of the proposed protocol can be guaranteed by employing the nonfragile control theory. In the end, a numerical example is given to validate the effectiveness and superiority of the proposed method.