Effect of ursolic acid on obesity-induced insulin resistance in rat liver

Purpose: To determine the expression of protein tyrosine phosphatase-1B (PTP-1B) and insulin receptor substrate-2 (IRS-2) in the liver tissue of obesity-induced insulin-resistant rats.Methods: Insulin resistance (IR) was induced in Wistar rats by placing them on a high fat diet for 6weeks, and ursolic acid (UA) was administered. Metformin served as positive control drug. The rats were divided into 5 groups based on the  treatments given: normal group, positive control group, metformin group, high-dose UA group, and low-dose UA group. The general conditions of the rats were assessed 4 and 8 weeks after the various treatments. Liver glycogen levels were measured, and liver  histological examination carried out after tissue processing and staining with hematoxylin and eosin (H & E). Real-time polymerase chain reaction (RT-PCR) was employed for the determination of hepatic expressions of PTP-1B and IRS-2 mRNAs, while expressions of PTP-1B protein and IRS-2 protein, and  phosphorylation of IRS-2 tyrosine were assayed by Western blotting.Results: Liver glycogen levels were significantly increased in the UA-treated groups (p < 0.05). Moreover, UA provoked reductions in the expression of PTP-1B protein (p < 0.05), but up-regulated the expression of IRS-2 protein (p < 0.05), and enhanced IRS-2 tyrosine phosphorylation (p < 0.05).Conclusion: These results suggest that UA mitigates IR through blockage of PTP-1B expression and up-regulation of the expression of IRS-2 mRNA. Therefore, PTP-1B is a potential target for the treatment of type 2 diabetes.Keywords: Ursolic acid, Insulin resistance, Liver, Protein tyrosine phosphatase-1B, Insulin receptor substrate

The role of environmental justice reform in corporate green transformation: Evidence from the establishment of China’s environmental courts

Purpose: The establishment of environmental courts in China provides a good opportunity to explores the economic effects of environmental justice reform. This paper investigates how the environmental justice reform can influence corporate green transformation from the perspective of green technology innovation and explores the potential mechanisms of how the environmental courts affect green technology innovation. The heterogeneous effects of environmental courts are also considered.Methodology: Using the establishment of environmental courts in China as a quasi-natural experiment, this paper adopts a difference-in-difference (DID) method to conduct empirical test based on data on Chinese listed A-shared firms from 2004 to 2019. Moreover, this paper use propensity score matching (PSM), tobit and negative binomial regression method to address possible estimation bias.Findings: The establishment of environmental courts significantly enhances green technology innovation among enterprises. The more effective judicial enforcement and better public awareness of the environment brought by the environmental courts will increase the cost of illegality and external supervision pressure for firms, which will lead firms to innovate in green technology. Furthermore, the positive and significant effect of environmental courts on green technology innovation is more pronounced in state-owned enterprises (SOEs) and enterprises located in regions where local protectionism is more serious or regions with more ideal environmental legal system

A Study on Differentiable Logic and LLMs for EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition 2023

In this technical report, we present our findings from a study conducted on the EPIC-KITCHENS-100 Unsupervised Domain Adaptation task for Action Recognition. Our research focuses on the innovative application of a differentiable logic loss in the training to leverage the co-occurrence relations between verb and noun, as well as the pre-trained Large Language Models (LLMs) to generate the logic rules for the adaptation to unseen action labels. Specifically, the model's predictions are treated as the truth assignment of a co-occurrence logic formula to compute the logic loss, which measures the consistency between the predictions and the logic constraints. By using the verb-noun co-occurrence matrix generated from the dataset, we observe a moderate improvement in model performance compared to our baseline framework. To further enhance the model's adaptability to novel action labels, we experiment with rules generated using GPT-3.5, which leads to a slight decrease in performance. These findings shed light on the potential and challenges of incorporating differentiable logic and LLMs for knowledge extraction in unsupervised domain adaptation for action recognition. Our final submission (entitled `NS-LLM') achieved the first place in terms of top-1 action recognition accuracy.Comment: Technical report submitted to CVPR 2023 EPIC-Kitchens challenge

Latte: Latent Diffusion Transformer for Video Generation

We propose a novel Latent Diffusion Transformer, namely Latte, for video generation. Latte first extracts spatio-temporal tokens from input videos and then adopts a series of Transformer blocks to model video distribution in the latent space. In order to model a substantial number of tokens extracted from videos, four efficient variants are introduced from the perspective of decomposing the spatial and temporal dimensions of input videos. To improve the quality of generated videos, we determine the best practices of Latte through rigorous experimental analysis, including video clip patch embedding, model variants, timestep-class information injection, temporal positional embedding, and learning strategies. Our comprehensive evaluation demonstrates that Latte achieves state-of-the-art performance across four standard video generation datasets, i.e., FaceForensics, SkyTimelapse, UCF101, and Taichi-HD. In addition, we extend Latte to text-to-video generation (T2V) task, where Latte achieves comparable results compared to recent T2V models. We strongly believe that Latte provides valuable insights for future research on incorporating Transformers into diffusion models for video generation.Comment: Project page: https://maxin-cn.github.io/latte_projec

The relationship between ostracism and negative risk-taking behavior: the role of ego depletion and physical exercise

BackgroundAs a major public health problem globally, negative risk-taking behavior of college students may be related to their ostracism experience, but the reason for this association is unclear. Based on the limited resource theory, combined with the integrative model of athletic performance, we tested a moderated mediation model in which ego depletion mediated the association between ostracism and risk-taking, and physical exercise moderated the mediation process to examine the mechanisms underlying the association between ostracism and negative risk-taking behavior.MethodsOne thousand three hundred seven students (43% female) from four universities in China were recruited using cluster random sampling. The experience of being ostracized, ego depletion, physical exercise level, and negative risk-taking behavior were measured through an anonymous online questionnaire in “www.sojump.com.”ResultsAfter controlling for gender and grade in college, ostracism was positively related to negative risk-taking behavior; ego depletion mediated this relationship; and physical exercise level attenuated these direct and indirect relationships.ConclusionThe results highlight individual risk and protective factors associated with negative risk-taking behavior, and provide new perspectives on ways to prevent and reduce college students’ negative risk-taking behavior

Metabolic clues to aging: exploring the role of circulating metabolites in frailty, sarcopenia and vascular aging related traits and diseases

Background: Physical weakness and cardiovascular risk increase significantly with age, but the underlying biological mechanisms remain largely unknown. This study aims to reveal the causal effect of circulating metabolites on frailty, sarcopenia and vascular aging related traits and diseases through a two-sample Mendelian Randomization (MR) analysis.Methods: Exposures were 486 metabolites analyzed in a genome-wide association study (GWAS), while outcomes included frailty, sarcopenia, arterial stiffness, atherosclerosis, peripheral vascular disease (PAD) and aortic aneurysm. Primary causal estimates were calculated using the inverse-variance weighted (IVW) method. Methods including MR Egger, weighted median, Q-test, and leave-one-out analysis were used for the sensitive analysis.Results: A total of 125 suggestive causative associations between metabolites and outcomes were identified. Seven strong causal links were ultimately identified between six metabolites (kynurenine, pentadecanoate (15:0), 1-arachidonoylglycerophosphocholine, androsterone sulfate, glycine and mannose) and three diseases (sarcopenia, PAD and atherosclerosis). Besides, metabolic pathway analysis identified 13 significant metabolic pathways in 6 age-related diseases. Furthermore, the metabolite-gene interaction networks were constructed.Conclusion: Our research suggested new evidence of the relationship between identified metabolites and 6 age-related diseases, which may hold promise as valuable biomarkers

Phenformin has anti-tumorigenic effects in human ovarian cancer cells and in an orthotopic mouse model of serous ovarian cancer

Obesity and diabetes have been associated with increased risk and worse outcomes in ovarian cancer (OC). The biguanide metformin is used in the treatment of type 2 diabetes and is also believed to have anti-tumorigenic benefits. Metformin is highly hydrophilic and requires organic cation transporters (OCTs) for entry into human cells. Phenformin, another biguanide, was taken off the market due to an increased risk of lactic acidosis over metformin. However, phenformin is not reliant on transporters for cell entry; and thus, may have increased potency as both an anti-diabetic and anti-tumorigenic agent than metformin. Thus, our goal was to evaluate the effect of phenformin on established OC cell lines, primary cultures of human OC cells and in an orthotopic mouse model of high grade serous OC. In three OC cell lines, phenformin significantly inhibited cellular proliferation, induced cell cycle G1 arrest and apoptosis, caused cellular stress, inhibited adhesion and invasion, and activation of AMPK and inhibition of the mTOR pathway. Phenformin also exerted anti-proliferative effects in seven primary cell cultures of human OC. Lastly, phenformin inhibited tumor growth in an orthotopic mouse model of serous OC, coincident with decreased Ki-67 staining and phosphorylated-S6 expression and increased expression of caspase 3 and phosphorylated-AMPK. Our findings demonstrate that phenformin has anti-tumorigenic effects in OC as previously demonstrated by metformin but it is yet to be determined if it is superior to metformin for the potential treatment of this disease

Rhein targets macrophage SIRT2 to promote adipose tissue thermogenesis in obesity in mice.

Rhein, a component derived from rhubarb, has been proven to possess anti-inflammatory properties. Here, we show that rhein mitigates obesity by promoting adipose tissue thermogenesis in diet-induced obese mice. We construct a macrophage-adipocyte co-culture system and demonstrate that rhein promotes adipocyte thermogenesis through inhibiting NLRP3 inflammasome activation in macrophages. Moreover, clues from acetylome analysis identify SIRT2 as a potential drug target of rhein. We further verify that rhein directly interacts with SIRT2 and inhibits NLRP3 inflammasome activation in a SIRT2-dependent way. Myeloid knockdown of SIRT2 abrogates adipose tissue thermogenesis and metabolic benefits in obese mice induced by rhein. Together, our findings elucidate that rhein inhibits NLRP3 inflammasome activation in macrophages by regulating SIRT2, and thus promotes white adipose tissue thermogenesis during obesity. These findings uncover the molecular mechanism underlying the anti-inflammatory and anti-obesity effects of rhein, and suggest that rhein may become a potential drug for treating obesity

Tailoring MoS2 Valley-Polarized Photoluminescence with Super Chiral Near-Field

Transition metal dichalcogenides with intrinsic spin–valley degrees of freedom hold great potentials for applications in spintronic and valleytronic devices. MoS2 monolayer possesses two inequivalent valleys in the Brillouin zone, with each valley coupling selectively with circularly polarized photons. The degree of valley polarization (DVP) is a parameter to characterize the purity of valley-polarized photoluminescence (PL) of MoS2 monolayer. Usually, the detected values of DVP in MoS2 monolayer show achiral property under optical excitation of opposite helicities due to reciprocal phonon-assisted intervalley scattering process. Here, it is reported that valley-polarized PL of MoS2 can be tailored through near-field interaction with plasmonic chiral metasurface. The resonant field of the chiral metasurface couples with valley-polarized excitons, and tailors the measured PL spectra in the far-field, resulting in observation of chiral DVP of MoS2-metasurface under opposite helicities excitations. Valley-contrast PL in the chiral heterostructure is also observed when illuminated by linearly polarized light. The manipulation of valley-polarized PL in 2D materials using chiral metasurface represents a viable route toward valley-polaritonic devices