Removal of epididymal visceral adipose tissue prevents obesity-induced multi-organ insulin resistance in male mice

Obesity is associated with insulin resistance, an important risk factor of type 2 diabetes, atherogenic dyslipidemia, and nonalcoholic fatty liver disease. The major purpose of this study was to test hypothesize that prophylactic removal of epididymal visceral adipose tissue (VAT) prevents obesity-induced multi-organ (liver, skeletal muscle, adipose tissue) insulin resistance. Accordingly, we surgically removed epididymal VAT pads from adult C57BL/6J mice and evaluated in vivo and cellular metabolic pathways involved in glucose and lipid metabolism following chronic high-fat diet (HFD) feeding. We found that VAT removal decreases HFD-induced body weight gain while increasing subcutaneous adipose tissue (SAT) mass. Strikingly, VAT removal prevents obesity-induced insulin resistance and hyperinsulinemia and markedly enhances insulin-stimulated AKT-phosphorylation at serine-473 (Ser473) and threonine-308 (Thr308) sites in SAT, liver, and skeletal muscle. VAT removal leads to decreases in plasma lipid concentrations and hepatic triglyceride (TG) content. In addition, VAT removal increases circulating adiponectin, a key insulin-sensitizing adipokine, whereas it decreases circulating interleukin 6, a pro-inflammatory adipokine. Consistent with these findings, VAT removal increases adenosine monophosphate-activated protein kinase C phosphorylation, a major downstream target of adiponectin signaling. Data obtained from RNA sequencing suggest that VAT removal prevents obesity-induced oxidative stress and inflammation in liver and SAT, respectively. Taken together, these findings highlight the metabolic benefits and possible action mechanisms of prophylactic VAT removal on obesity-induced insulin resistance and hepatosteatosis. Our results also provide important insight into understanding the extraordinary capability of adipose tissue to influence whole-body glucose and lipid metabolism as an active endocrine organ

Bis[2-(cyclo­pentyl­imino­meth­yl)-4-nitro­phenolato-κ2 N 2,O]cobalt(II)

In the title compound, [Co(C12H13N2O3)2], the CoII ion is situated on a twofold rotation axis and is coordinated by two N and two O atoms from two symmetry-related Schiff base 2-(cyclo­pentyl­imino­meth­yl)-4-nitro­phenolate ligands (L) in a distorted tetra­hedral geometry. The cyclo­pentyl ring in L is disordered over two conformations in a 0.640 (19):0.360 (19) ratio

Biodegradation of 2, 4, 6- Trinitrotoluene (TNT) in Contaminated Soil and Microbial Remediation Options for Treatment

This review paper provides a critical examination on current microbial biodegradation of 2, 4, 6-Trinitrotoluene (TNT) and its metabolites in soil, with focus on: (i) extent of biological degradation of TNT and its metabolites in soil, (ii) factors affecting the TNT transformations, and (iii) microbial bioremediation technologies , and related challenges. This was carried out through an extensive examination of relevant published literature on the topic. The review paper found that the detoxification of TNT contaminated sites by microorganisms based- technologies have been employed but TNT has been proven to resist biological mineralization and undergo biotransformations, leading to immobilization of toxic and unstable transformation products. TNT mineralization is however achievable, but scientific studies are far away from attaining the best desired in situ bioremediation practices and much remains to be delineated. We provide future research directions to design effective bioremediation technologies for solving the problems of TNT and minimize environmental impacts.

MagicProp: Diffusion-based Video Editing via Motion-aware Appearance Propagation

This paper addresses the issue of modifying the visual appearance of videos while preserving their motion. A novel framework, named MagicProp, is proposed, which disentangles the video editing process into two stages: appearance editing and motion-aware appearance propagation. In the first stage, MagicProp selects a single frame from the input video and applies image-editing techniques to modify the content and/or style of the frame. The flexibility of these techniques enables the editing of arbitrary regions within the frame. In the second stage, MagicProp employs the edited frame as an appearance reference and generates the remaining frames using an autoregressive rendering approach. To achieve this, a diffusion-based conditional generation model, called PropDPM, is developed, which synthesizes the target frame by conditioning on the reference appearance, the target motion, and its previous appearance. The autoregressive editing approach ensures temporal consistency in the resulting videos. Overall, MagicProp combines the flexibility of image-editing techniques with the superior temporal consistency of autoregressive modeling, enabling flexible editing of object types and aesthetic styles in arbitrary regions of input videos while maintaining good temporal consistency across frames. Extensive experiments in various video editing scenarios demonstrate the effectiveness of MagicProp

Varstrometry Selected Radio-Loud Candidates of Dual and Off-Nucleus Quasars at Sub-kpc Scales

Dual super massive black holes at sub-kpc to kpc scales, the product of galaxy mergers, are progenitors of eventually coalescing binary SMBHs. If both or one of the dual SMBHs are accreting, they may appear as dual AGNs or off-nucleus AGNs. Studying such systems is essential to learn the dynamical evolution of binary SMBHs as well as the process of galaxy merging. Recently a novel astrometry-based method named varstrometry has been put forward to search for dual SMBHs at high redshift, as the unsynchronized flux variability of dual AGNs (or off-nucleus AGNs) will cause astrometric jitters detectable by Gaia without spatially resolving them. Based on Gaia varstrometry we select a rare sample of 5 radio loud quasars with clear Gaia astrometric jitters. With e-MERLIN observations we have revealed a single compact radio source for each of them. Remarkably all but one exhibit clear Gaia-radio offsets of ~ 9 -- 60 mas. The observed Gaia jitters appear consistent with the expected values. These detected Gaia-radio offsets suggest these candidate dual SMBHs may have projected separations as small as ~ 0.01 -- 0.1'' (~ 0.1 kpc, depending on the optical flux ratio of two SMBHs). Meanwhile, this work highlights the remarkably high efficiency of Gaia varstrometry selection of jittering sources.Comment: 6 pages, 5 figures, 1 table; accepted for publication in MNRAS Letter

Dyonic Reissner-Nordstrom Black Holes and Superradiant Stability

Black holes immersed in magnetic fields are believed to be important systems in astrophysics. One interesting topic on these systems is their superradiant stability property. In the present paper, we analytically obtain the superradiantly stable regime for the asymptotically flat dyonic Reissner-Nordstrom black holes with charged massive scalar perturbation. The effective potential experienced by the scalar perturbation in the dyonic black hole background is obtained and analyzed. It is found that the dyonic black hole is superradiantly stable in the regime $0<r_{-}/r_{+}<2/3$, where $r_\pm$ are the event horizons of the dyonic black hole. Compared with the purely electrically charged Reissner-Nordstrom black hole case, our result indicates that the additional coupling of the charged scalar perturbation with the magnetic field makes the black hole and scalar perturbation system more superradiantly unstable, which provides further evidence on the instability induced by magnetic field in black hole superradiance process

LLM as A Robotic Brain: Unifying Egocentric Memory and Control

Embodied AI focuses on the study and development of intelligent systems that possess a physical or virtual embodiment (i.e. robots) and are able to dynamically interact with their environment. Memory and control are the two essential parts of an embodied system and usually require separate frameworks to model each of them. In this paper, we propose a novel and generalizable framework called LLM-Brain: using Large-scale Language Model as a robotic brain to unify egocentric memory and control. The LLM-Brain framework integrates multiple multimodal language models for robotic tasks, utilizing a zero-shot learning approach. All components within LLM-Brain communicate using natural language in closed-loop multi-round dialogues that encompass perception, planning, control, and memory. The core of the system is an embodied LLM to maintain egocentric memory and control the robot. We demonstrate LLM-Brain by examining two downstream tasks: active exploration and embodied question answering. The active exploration tasks require the robot to extensively explore an unknown environment within a limited number of actions. Meanwhile, the embodied question answering tasks necessitate that the robot answers questions based on observations acquired during prior explorations