Olmesartan restores the protective effect of remote ischemic perconditioning against myocardial ischemia/reperfusion injury in spontaneously hypertensive rats

OBJECTIVES: Remote ischemic perconditioning is the newest technique used to lessen ischemia/reperfusion injury. However, its effect in hypertensive animals has not been investigated. This study aimed to examine the effect of remote ischemic perconditioning in spontaneously hypertensive rats and determine whether chronic treatment with Olmesartan could influence the effect of remote ischemic perconditioning. METHODS: Sixty rats were randomly divided into six groups: vehicle-sham, vehicle-ischemia/reperfusion injury, vehicle-remote ischemic perconditioning, olmesartan-sham, olmesartan-ischemia/reperfusion and olmesartan-remote ischemic perconditioning. The left ventricular mass index, creatine kinase concentration, infarct size, arrhythmia scores, HIF-1α mRNA expression, miR-21 expression and miR-210 expression were measured. RESULTS: Olmesartan significantly reduced the left ventricular mass index, decreased the creatine kinase concentration, limited the infarct size and reduced the arrhythmia score. The infarct size, creatine kinase concentration and arrhythmia score during reperfusion were similar for the vehicle-ischemia/reperfusion group and vehicle-remote ischemic perconditioning group. However, these values were significantly decreased in the olmesartan-remote ischemic perconditioning group compared to the olmesartan-ischemia/reperfusion injury group. HIF-1α, miR-21 and miR-210 expression were markedly down-regulated in the Olmesartan-sham group compared to the vehicle-sham group and significantly up-regulated in the olmesartan-remote ischemic perconditioning group compared to the olmesartan-ischemia/reperfusion injury group. CONCLUSION: The results indicate that (1) the protective effect of remote ischemic perconditioning is lost in vehicle-treated rats and that chronic treatment with Olmesartan restores the protective effect of remote ischemic perconditioning; (2) chronic treatment with Olmesartan down-regulates HIF-1α, miR-21 and miR-210 expression and reduces hypertrophy, thereby limiting ischemia/reperfusion injury; and (3) recovery of the protective effect of remote ischemic perconditioning is related to the up-regulation of HIF-1α, miR-21 and miR-210 expression

Dark matter: an efficient catalyst for intermediate-mass-ratio-inspiral events

Gravitational waves (GWs) can be produced if a stellar compact object, such as a black hole (BH) or neutron star, inspirals into an intermediate-massive black hole (IMBH) of $(10^3 \sim 10^5)\,M_\odot$. Such a system may be produced in the center of a globular cluster (GC) or a nuclear star cluster (NSC), and is known as an intermediate- or extreme-mass-ratio inspiral (IMRI or EMRI). Motivated by the recent suggestions that dark matter minispikes could form around IMBHs, we study the effect of dynamical friction against DM on the merger rate of IMRIs/EMRIs. We find that the merger timescale of IMBHs with BHs and NSs would be shortened by two to three orders of magnitude. As a result, the event rate of IMRIs/EMRIs are enhanced by orders of magnitude relative to that in the case of no DM minispikes. In the most extreme case where IMBHs are small and the DM minispikes have a steep density profile, all the BH in GCs and NSCs might be exhausted so that the mergers with NSs would dominate the current IMRIs/EMRIs. Our results suggest that the mass function of the IMBHs below $10^4 \,M_\odot$ would bear imprints of the distribution of DM minispikes because these low-mass IMBHs can grow efficiently in the presence of DM minispikes by merging with BHs and NSs. Future space-based GW detectors, like LISA, Taiji, and Tianqin, can measure the IMRI/EMRI rate and hence constrain the distribution of DM around IMBHs.Comment: 17 pages, 10 figure

MotionGPT: Human Motion as a Foreign Language

Though the advancement of pre-trained large language models unfolds, the exploration of building a unified model for language and other multi-modal data, such as motion, remains challenging and untouched so far. Fortunately, human motion displays a semantic coupling akin to human language, often perceived as a form of body language. By fusing language data with large-scale motion models, motion-language pre-training that can enhance the performance of motion-related tasks becomes feasible. Driven by this insight, we propose MotionGPT, a unified, versatile, and user-friendly motion-language model to handle multiple motion-relevant tasks. Specifically, we employ the discrete vector quantization for human motion and transfer 3D motion into motion tokens, similar to the generation process of word tokens. Building upon this "motion vocabulary", we perform language modeling on both motion and text in a unified manner, treating human motion as a specific language. Moreover, inspired by prompt learning, we pre-train MotionGPT with a mixture of motion-language data and fine-tune it on prompt-based question-and-answer tasks. Extensive experiments demonstrate that MotionGPT achieves state-of-the-art performances on multiple motion tasks including text-driven motion generation, motion captioning, motion prediction, and motion in-between.Comment: Project Page: https://github.com/OpenMotionLab/MotionGP

Dynamical critical quantum sensing with a single parametrically-driven nonlinear resonator

Critical phenomena of quantum systems are useful for enhancement of quantum sensing. We here investigate the performance of a sensing scheme, where the signal is encoded in the dynamically-evolving state of an oscillator, featuring a competition of the Kerr nonlinearity and parametric driving. We calculate the quantum Fisher information, and perform a simulation, which confirms the criticality-enabled enhancement. We further detail the response of one of the quadratures to the variation of the control parameter. The numerical results reveal that its inverted variance exhibits a diverging behavior at the critical point.Comment: 6 pages, 7 figure