Targeting Integrin-β1 Impedes Cytokine-Induced Osteoclast Differentiation: A Potential Pharmacological Intervention in Pathological Osteolysis

Purpose: To examine whether integrin-β1 is essential for osteoclast differentiation and function and if it can be targeted for pharmacological intervention in pathological osteolysis.Methods: Control and Integrin-β1 knockdown RAW 264.7 cells were treated with receptor activator of nuclear factor kappa-B (RANKL) or TNF-α and evaluated for osteoclast differentiation. Osteoclast differentiation and function were evaluated by marker protein analysis, tartrate-resistant acid phosphatase (TRAP) and resorption assays. Furthermore, downstream molecular signaling analysis was probed using small molecule inhibitors and blocking antibodies, and evaluated by immunoblotting.Results: Integrin-β1 knockdown cells showed reduced osteoclast differentiation following TNF-α treatment while no change was seen after RANKL treatment (p < 0.05). Immunoblot-based molecular signaling analysis showed involvement of MAPK kinase signaling in mediating TNF-α/integrin-β1- induced osteoclastogenesis. Finally, when MAPK kinase inhibitor (2.5 and 5 μM; p < 0.05) and integrin- β1 blocking antibody (2.5 and 5 μg/mL; p < 0.05) was used to specifically attenuate TNF-α induced osteoclastogenesis, no change was observed in RANKL-induced osteoclast formation.Conclusion: The data obtained highlight the role of integrin-β1 in TNF-α-induced osteoclastogenesis, but not in RANKL pathway. Given that, inflammatory cytokine secretions such as TNF-α are progressively implicated in pathological osteolysis, targeting this pathway may attenuate osteolysis in pathological bone tissues.Keywords: Osteoclast differentiation, Integrin-β1, Receptor activator of nuclear factor kappa-B, TNFalpha, Mitogen activated protein kinase, Cytokines, Skeletal diseas

DynPoint: Dynamic Neural Point For View Synthesis

The introduction of neural radiance fields has greatly improved the effectiveness of view synthesis for monocular videos. However, existing algorithms face difficulties when dealing with uncontrolled or lengthy scenarios, and require extensive training time specific to each new scenario. To tackle these limitations, we propose DynPoint, an algorithm designed to facilitate the rapid synthesis of novel views for unconstrained monocular videos. Rather than encoding the entirety of the scenario information into a latent representation, DynPoint concentrates on predicting the explicit 3D correspondence between neighboring frames to realize information aggregation. Specifically, this correspondence prediction is achieved through the estimation of consistent depth and scene flow information across frames. Subsequently, the acquired correspondence is utilized to aggregate information from multiple reference frames to a target frame, by constructing hierarchical neural point clouds. The resulting framework enables swift and accurate view synthesis for desired views of target frames. The experimental results obtained demonstrate the considerable acceleration of training time achieved - typically an order of magnitude - by our proposed method while yielding comparable outcomes compared to prior approaches. Furthermore, our method exhibits strong robustness in handling long-duration videos without learning a canonical representation of video content

Supermassive Black Holes with High Accretion Rates in Active Galactic Nuclei. III. Detection of Fe II Reverberation in Nine Narrow-Line Seyfert 1 Galaxies

This is the third in a series of papers reporting on a large reverberation-mapping campaign aimed to study the properties of active galactic nuclei (AGNs) with high accretion rates. We present new results on the variability of the optical Fe II emission lines in 10 AGNs observed by the Yunnan Observatory 2.4m telescope during 2012--2013. We detect statistically significant time lags, relative to the AGN continuum, in nine of the sources. This accurate measurement is achieved by using a sophisticated spectral fitting scheme that allows for apparent flux variations of the host galaxy, and several narrow lines, due to the changing observing conditions. Six of the newly detected lags are indistinguishable from the Hbeta lags measured in the same sources. Two are significantly longer and one is slightly shorter. Combining with Fe II lags reported in previous studies, we find a Fe II radius--luminosity relationship similar to the one for Hbeta, although our sample by itself shows no clear correlation. The results support the idea that Fe II emission lines originate in photoionized gas which, for the majority of the newly reported objects, is indistinguishable from the Hbeta-emitting gas. We also present a tentative correlation between the lag and intensity of Fe II and Hbeta and comment on its possible origin.Comment: 14 pages, 10 figures, accepted for publication in The Astrophysical Journa

Multi-body SE(3) Equivariance for Unsupervised Rigid Segmentation and Motion Estimation

A truly generalizable approach to rigid segmentation and motion estimation is fundamental to 3D understanding of articulated objects and moving scenes. In view of the tightly coupled relationship between segmentation and motion estimates, we present an SE(3) equivariant architecture and a training strategy to tackle this task in an unsupervised manner. Our architecture comprises two lightweight and inter-connected heads that predict segmentation masks using point-level invariant features and motion estimates from SE(3) equivariant features without the prerequisites of category information. Our unified training strategy can be performed online while jointly optimizing the two predictions by exploiting the interrelations among scene flow, segmentation mask, and rigid transformations. We show experiments on four datasets as evidence of the superiority of our method both in terms of model performance and computational efficiency with only 0.25M parameters and 0.92G FLOPs. To the best of our knowledge, this is the first work designed for category-agnostic part-level SE(3) equivariance in dynamic point clouds