Balancing WNT signaling in early forebrain development

During early forebrain development, the establishment of the regional identity of neural progenitor cells (NPCs) relies on the integration of signals from multiple signaling centers, including the WNT signaling pathway. WNT pathway is essential for embryonic development and is regulated by LDL receptor related proteins (LRPs), which act as co-receptors of frizzled. While the LRP family member - LRP5 and LRP6 are well known as co-receptors of frizzled, acting as the main receptor of WNT3a. Recent evidence suggests that LRP4 also plays a role in the central nervous system. My aim is to shed light on the common and distinct functions of LRP4 and LRP6 and the interactions between LRP4/6 linked to the WNT pathway during early forebrain development. To achieve this, a genetic approach was used to analyze the forebrain development of LRP4-, LRP6-deficient mouse embryos, as well as Lrp4-/-; Lrp6-/- double mutant mouse embryos at E9.5. High-resolution immunofluorescence imaging, cell culture models and molecular biology approaches were employed to investigate the effects of genetic inactivation of LRP4 and LRP6 on canonical WNT activity, mitotic activity of forebrain neuronal precursors, and the development of NTDs. The results of this study indicate that loss of LRP6 can lead to a developmental disorder in E9.5 embryos, such as caudal truncation, neural tube defects (NTDs) and forebrain hypoplasia. Importantly, loss of LRP4 can partially rescue these deficits in Lrp6 null mutants. Specially, caudal truncation and impaired mitotic activity of forebrain neuronal precursors observed in Lrp6-/- mutants were rescued in Lrp4-/-; Lrp6-/- double mutants. However, cranial NTDs in LRP6-deficient mice were not ameliorated by genetic ablation of Lrp4. Additionally, it was demonstrated that genetic inactivation of LRP4 rescued impaired canonical WNT activity and the downstream targets in Lrp6-/- mutants. Moreover, the data suggest that LRP4 and LRP6 also influence the proliferation of human retinal pigment epithelial (hTERT RPE-1) cells in cell culture, adding to their roles in embryonic development. Furthermore, the study revealed that LRP4 modulates LRP6-dependent WNT signaling in a more general context, as demonstrated in hTERT RPE-1 cells. Overall, these results highlight the important and complex role of LRP4 and LRP6 in forebrain development and WNT signaling regulation. The findings suggest that LRP4 2 acts as a negative regulator of LRP6-mediated canonical WNT signaling and plays a critical role in the regulation of mitotic activity of neuronal precursors in the early developing forebrain. Additionally, the results suggest that LRP5 or an as-yet undetermined receptor can compensate for the loss of LRP6 as an FZD co-receptor in the absence of LRP4. These findings provide new insights into the molecular mechanisms that regulate forebrain development and may have implications for the understanding and treatment of developmental disorders

An sTGC Prototype Readout System for ATLAS New-Small-Wheel Upgrade

This paper presents a readout system designed for testing the prototype of Small-Strip Thin Gap Chamber (sTGC), which is one of the main detector technologies used for ATLAS New-Small-Wheel Upgrade. This readout system aims at testing one full-size sTGC quadruplet with cosmic muon triggers

Discriminating 1D new physics solutions in b→sℓℓb\to s\ell\ell decays

The recent measurements of $R_{K^+}$, $R_{K_S^0}$, $R_{K^{*+}}$, $B_s\to\mu^+\mu^-$, a set of CP-averaged angular observables for the $B^0\to K^{*0}\mu^+\mu^-$ decay, and its isospin partner $B^+\to K^{*+}\mu^+\mu^-$ by the LHCb Collaboration, consistently hint at lepton universality violation in the $b\to s\ell\ell$ transitions. In this work, we first perform global fits to the $b\to s\ell\ell$ data and show that five one-dimensional scenarios, i.e, $\delta C_9^{\mu}$, $\delta C_{10}^{\mu}$, $\delta C_L^{\mu}$, $\delta C_9^{\mu}=C_{10}^{\mu\prime}$, and $\delta C_9^{\mu}=-C_9^{\mu\prime}$ can best explain the so-called B anamolies. Furthermore, we explore how these scenarios can be distinguished from each other. For this purpose, we first study the combinations of four angular asymmetries $A_i$~$(i=3,4,5,9)$ and find that they cannot distinguish the five new physics scenarios. We then show that a newly constructed ratio $R_{S}$ can uniquely discriminate the five new physics scenarios in proper intervals of $q^2$ if it can be measured with a percent level precision.Comment: 16 pages, 6 figures; latest $R_{K_S^0}$, $R_{K^{*+}}$ data include

Patient Dropout Prediction in Virtual Health: A Multimodal Dynamic Knowledge Graph and Text Mining Approach

Virtual health has been acclaimed as a transformative force in healthcare delivery. Yet, its dropout issue is critical that leads to poor health outcomes, increased health, societal, and economic costs. Timely prediction of patient dropout enables stakeholders to take proactive steps to address patients' concerns, potentially improving retention rates. In virtual health, the information asymmetries inherent in its delivery format, between different stakeholders, and across different healthcare delivery systems hinder the performance of existing predictive methods. To resolve those information asymmetries, we propose a Multimodal Dynamic Knowledge-driven Dropout Prediction (MDKDP) framework that learns implicit and explicit knowledge from doctor-patient dialogues and the dynamic and complex networks of various stakeholders in both online and offline healthcare delivery systems. We evaluate MDKDP by partnering with one of the largest virtual health platforms in China. MDKDP improves the F1-score by 3.26 percentage points relative to the best benchmark. Comprehensive robustness analyses show that integrating stakeholder attributes, knowledge dynamics, and compact bilinear pooling significantly improves the performance. Our work provides significant implications for healthcare IT by revealing the value of mining relations and knowledge across different service modalities. Practically, MDKDP offers a novel design artifact for virtual health platforms in patient dropout management

Effects of time-varying β\beta in SNLS3 on constraining interacting dark energy models

It has been found that, for the Supernova Legacy Survey three-year (SNLS3) data, there is strong evidence for the redshift-evolution of color-luminosity parameter $\beta$. In this paper, adopting the $w$-cold-dark-matter ($w$CDM) model and considering its interacting extensions (with three kinds of interaction between dark sectors), we explore the evolution of $\beta$ and its effects on parameter estimation. In addition to the SNLS3 data, we also take into account the Planck distance priors data of the cosmic microwave background (CMB), the galaxy clustering (GC) data extracted from SDSS DR7 and BOSS, as well as the direct measurement of Hubble constant from the Hubble Space Telescope (HST) observation. We find that, for all the interacting dark energy (IDE) models, adding a parameter of $\beta$ can reduce $\chi^2$ by $\sim$ 34, indicating that $\beta_1 = 0$ is ruled out at 5.8$\sigma$ confidence level (CL). Furthermore, it is found that varying $\beta$ can significantly change the fitting results of various cosmological parameters: for all the dark energy models considered in this paper, varying $\beta$ yields a larger $\Omega_{c0}$ and a larger $w$; on the other side, varying $\beta$ yields a smaller $h$ for the $w$CDM model, but has no impact on $h$ for the three IDE models. This implies that there is a degeneracy between $h$ and $\gamma$. Our work shows that the evolution of $\beta$ is insensitive to the interaction between dark sectors, and then highlights the importance of considering $\beta$'s evolution in the cosmology fits.Comment: 11 pages, 6 figures, 1 table; revised version accepted by EPJC. arXiv admin note: substantial text overlap with arXiv:1310.6109, arXiv:1312.018

An integrated geophysical approach for investigating hydro-geological characteristics of a debris landslide in the Wenchuan Earthquake area

Debris landslides are one of the most widely distributed types of landslides in the Wenchuan earthquake area. The hydro-geological structure characteristics are the fundamental basis for stability evaluation, performing protection and administration of a landslide. The rock and soil mass of a debris landslide was highly non-uniform and preferential seepage paths were normally developed in it. Therefore, in situ identification of the underground water seepage system became particularly important. Recently, investigations on the seepage paths of underground water in debris landslides were restricted to indoor model testing and site observation, which were far from meeting the actual demand for landslide prevention and mitigation. To locate the seepage paths, we conducted survey work on a debris landslide seated in the Xishan Village, Li County, Sichuan Province, China, by combing four different geophysical methods. They were multichannel analysis of surface wave (MASW), electrical resistivity tomography (ERT), ground penetrating radar (GPR) and microtremor survey method (MSM). The geophysical interpretation was verified with field engineering surveys and monitoring data. The results suggested that a dendritic pipe-network seepage system usually developed in debris landslides. Varisized infiltration pipes showed the characteristics of inhomogeneity and concentration of the seepage. This work highlighted that geophysical parameters (shear wave velocity Vs, dielectric constant ε and resistivity value ρ) could provide reliable qualitative and quantitative information about the colluvial layer, bedrock interface, potential sliding surface and underground water seepage system of a landslide. The optimum combination of geophysical methods was suitable to survey the hydro-geological characteristics of debris landslides in the Wenchuan earthquake area

Robo-centric ESDF: A Fast and Accurate Whole-body Collision Evaluation Tool for Any-shape Robotic Planning

For letting mobile robots travel flexibly through complicated environments, increasing attention has been paid to the whole-body collision evaluation. Most existing works either opt for the conservative corridor-based methods that impose strict requirements on the corridor generation, or ESDF-based methods that suffer from high computational overhead. It is still a great challenge to achieve fast and accurate whole-body collision evaluation. In this paper, we propose a Robo-centric ESDF (RC-ESDF) that is pre-built in the robot body frame and is capable of seamlessly applied to any-shape mobile robots, even for those with non-convex shapes. RC-ESDF enjoys lazy collision evaluation, which retains only the minimum information sufficient for whole-body safety constraint and significantly speeds up trajectory optimization. Based on the analytical gradients provided by RC-ESDF, we optimize the position and rotation of robot jointly, with whole-body safety, smoothness, and dynamical feasibility taken into account. Extensive simulation and real-world experiments verified the reliability and generalizability of our method.Comment: Accepted at IROS 202