MiR-550a-3p restores damaged vascular smooth muscle cells by inhibiting thrombomodulin in an <em>in vitro</em> atherosclerosis model

Thrombomodulin (TM) is involved in the pathological process of atherosclerosis; however, the underlying mechanism remains unclear. Oxidised low-density lipoprotein (Ox-LDL; 100 μg/mL) was used to induce human vascular smooth muscle cells (HVSMCs) into a stable atherosclerotic cell model. The expression levels of miR-550a-3p and TM were detected by real-time reverse transcription-polymerase chain reaction. Cell proliferation was estimated using CCK8 and EDU assays. Wound scratch and transwell assays were used to measure the ability of cells to invade and migrate. Propidium iodide fluorescence-activated cell sorting was used to detect apoptosis and cell cycle changes. A dual-luciferase reporter assay was performed to determine the binding of miR-550a-3p to TM. Our results suggested the successful development of a cellular atherosclerosis model. Our data revealed that TM overexpression significantly promoted the proliferation, invasion, migration, and apoptosis of HVSMCs as well as cell cycle changes. Upregulation of miR-550a-3p inhibited the growth and metastasis of HVSMCs. Furthermore, miR-550a-3p was confirmed to be a direct target of TM. Restoration of miR-550a-3p expression rescued the effects of TM overexpression. Thus, miR-550a-3p might play a role in atherosclerosis and, for the first time, normalised the function of injured vascular endothelial cells by simultaneous transfection of TM and miR-550a-3p. These results suggest that the miR-550a-3p/TM axis is a potential therapeutic target for atherosclerosis

Effect of pruning young branches on fruit and seed set in cassava

Flowering in cassava is closely linked with branching. Early-flowering genotypes branch low and abundantly. Although farmers prefer late flowering genotypes because of their erect plant architecture, their usefulness as progenitors in breeding is limited by their low seed production. In general, the first inflorescence aborts in cassava. Preventing this abortion would result in early production of seeds and make cassava breeding more efficient. The objective of this study was to assess if pruning young branches prevents the abortion of first inflorescences and promotes early fruit and seed set. Four genotypes with early, late, very late, and no flowering habits were grown under an extended photoperiod (EP) or normal dark night conditions (DN). Additional treatments included pruning young branches at the first or second flowering event and spraying (or not) benzyladenine (BA) after pruning. One genotype failed to flower and was not considered further. For the remaining genotypes, EP proved crucial to induce an earlier flowering, which is a pre-requisite for pruning. Total production of seeds in EP plots was 2,971 versus 150 in DN plots. For plants grown under EP, the average number of seeds per plant without pruning was 3.88, whereas those pruned produced 17.60 seeds per plant. Pruning at the first branching event led to higher number of seeds per plant (26.25) than pruning at the second flowering event (8.95). In general, applying BA was beneficial (38.52 and 13.98 seeds/plant with or without spraying it, respectively). The best combination of treatments was different for each genotype. Pruning young branches and applying BA in the first flowering event not only prevented the abortion of inflorescences but also induced the feminization of male flowers into hermaphrodite or female-only flowers. The procedures suggested from this study (combining EP, pruning young branches, and spraying BA), allowed the production of a high number of seeds from erect cassava genotypes in a short period. The implementation of these procedures will improve the breeding efficiency in cassava

Optimal quantum dataset for learning a unitary transformation

Unitary transformations formulate the time evolution of quantum states. How to learn a unitary transformation efficiently is a fundamental problem in quantum machine learning. The most natural and leading strategy is to train a quantum machine learning model based on a quantum dataset. Although presence of more training data results in better models, using too much data reduces the efficiency of training. In this work, we solve the problem on the minimum size of sufficient quantum datasets for learning a unitary transformation exactly, which reveals the power and limitation of quantum data. First, we prove that the minimum size of dataset with pure states is $2^n$ for learning an $n$-qubit unitary transformation. To fully explore the capability of quantum data, we introduce a practical quantum dataset consisting of $n+1$ elementary tensor product states that are sufficient for exact training. The main idea is to simplify the structure utilizing decoupling, which leads to an exponential improvement on the size over the datasets with pure states. Furthermore, we show that the size of quantum dataset with mixed states can be reduced to a constant, which yields an optimal quantum dataset for learning a unitary. We showcase the applications of our results in oracle compiling and Hamiltonian simulation. Notably, to accurately simulate a 3-qubit one-dimensional nearest-neighbor Heisenberg model, our circuit only uses $48$ elementary quantum gates, which is significantly less than $4320$ gates in the circuit constructed by the Trotter-Suzuki product formula.Comment: 11 pages including appendix, v2 added remarks and reference

Electrochemical Activation of Surface Oxygen for Efficient Oxidative Dehydrogenation Reaction at Elevated Temperatures

Oxidative dehydrogenation (ODH) of alkane with CO2 as the oxidant has attracted worldwide attention as a promising approach for simultaneously producing valuable alkenes and greenhouse gas utilization. The selectivity and yield of the produced alkene, nevertheless, require further enhancement for practical applications. In this work, taking Sr2Ti0.8Co0.6Fe0.6O6‑δ (STCF) as the electrode material, we demonstrate that a solid oxide electrolysis cell (SOEC) can efficiently catalyze the ODH of ethane to ethylene on the anode and reduce CO2 to CO at the cathode. The optimal yield of ethylene reached 66.3% at 800 °C, which is among the highest values reported in the literature. Such ethane ODH activity is attributed to the activation of surface oxygen on the STCF anode by electrolytic voltage, as revealed experimentally by advanced spectroscopic techniques. The density functional theory calculation further implied that the electrochemically driven formation of active oxygen species on the STCF surface upshifts the O 2p-band center, facilitates electron transfer, and enhances surface adsorption, leading to a strongly promoted dehydrogenation process. The results clarify the critical role of oxygen activity in determining the electrochemical ODH performance and can guide the rational design of catalysts for other electrosynthesis processes

Probiotic Clostridium butyricum ameliorates cognitive impairment in obesity via the microbiota-gut-brain axis

Obesity is a risk factor for cognitive dysfunction and neurodegenerative disease, including Alzheimer\u27s disease (AD). The gut microbiota-brain axis is altered in obesity and linked to cognitive impairment and neurodegenerative disorders. Here, we targeted obesity-induced cognitive impairment by testing the impact of the probiotic Clostridium butyricum, which has previously shown beneficial effects on gut homeostasis and brain function. Firstly, we characterized and analyzed the gut microbial profiles of participants with obesity and the correlation between gut microbiota and cognitive scores. Then, using an obese mouse model induced by a Western-style diet (high-fat and fiber-deficient diet), the effects of Clostridium butyricum on the microbiota-gut-brain axis and hippocampal cognitive function were evaluated. Finally, fecal microbiota transplantation was performed to assess the functional link between Clostridium butyricum remodeling gut microbiota and hippocampal synaptic protein and cognitive behaviors. Our results showed that participants with obesity had gut microbiota dysbiosis characterized by an increase in phylum Proteobacteria and a decrease in Clostridium butyricum, which were closely associated with cognitive decline. In diet-induced obese mice, oral Clostridium butyricum supplementation significantly alleviated cognitive impairment, attenuated the deficit of hippocampal neurite outgrowth and synaptic ultrastructure, improved hippocampal transcriptome related to synapses and dendrites; a comparison of the effects of Clostridium butyricum in mice against human AD datasets revealed that many of the genes changes in AD were reversed by Clostridium butyricum; concurrently, Clostridium butyricum also prevented gut microbiota dysbiosis, colonic barrier impairment and inflammation, and attenuated endotoxemia. Importantly, fecal microbiota transplantation from donor-obese mice with Clostridium butyricum supplementation facilitated cognitive variables and colonic integrity compared with from donor obese mice, highlighting that Clostridium butyricum\u27s impact on cognitive function is largely due to its ability to remodel gut microbiota. Our findings provide the first insights into the neuroprotective effects of Clostridium butyricum on obesity-associated cognitive impairments and neurodegeneration via the gut microbiota-gut-brain axis