Information Recovery-Driven Deep Incomplete Multiview Clustering Network

Incomplete multi-view clustering is a hot and emerging topic. It is well known that unavoidable data incompleteness greatly weakens the effective information of multi-view data. To date, existing incomplete multi-view clustering methods usually bypass unavailable views according to prior missing information, which is considered as a second-best scheme based on evasion. Other methods that attempt to recover missing information are mostly applicable to specific two-view datasets. To handle these problems, in this paper, we propose an information recovery-driven deep incomplete multi-view clustering network, termed as RecFormer. Concretely, a two-stage autoencoder network with the self-attention structure is built to synchronously extract high-level semantic representations of multiple views and recover the missing data. Besides, we develop a recurrent graph reconstruction mechanism that cleverly leverages the restored views to promote the representation learning and the further data reconstruction. Visualization of recovery results are given and sufficient experimental results confirm that our RecFormer has obvious advantages over other top methods.Comment: Accepted by TNNLS 2023. Please contact me if you have any questions: [email protected]. The code is available at: https://github.com/justsmart/RecForme

Targeting cellular senescence in senile osteoporosis: therapeutic potential of traditional Chinese medicine

Senile osteoporosis (SOP) is a prevalent manifestation of age-related bone disorders, resulting from the dysregulation between osteoblast (OB)-mediated bone formation and osteoclast (OC)-mediated bone resorption, coupled with the escalating burden of cellular senescence. Traditional Chinese medicine (TCM) herbs, renowned for their remarkable attributes encompassing excellent tolerability, low toxicity, heightened efficacy, and minimal adverse reactions, have gained considerable traction in OP treatment. Emerging evidence substantiates the therapeutic benefits of various TCM formulations and their active constituents, including Zuogui wan, Fructus Ligustri Lucidi, and Resveratrol, in targeting cellular senescence to address SOP. However, a comprehensive review focusing on the therapeutic efficacy of TCM against SOP, with a particular emphasis on senescence, is currently lacking. In this review, we illuminate the pivotal involvement of cellular senescence in SOP and present a comprehensive exploration of TCM formulations and their active ingredients derived from TCM, delineating their potential in SOP treatment through their anti-senescence properties. Notably, we highlight their profound effects on distinct aging models that simulate SOP and various senescence characteristics. Finally, we provide a forward-looking discussion on utilizing TCM as a strategy for targeting cellular senescence and advancing SOP treatment. Our objective is to contribute to the unveiling of safer and more efficacious therapeutic agents for managing SOP

Full-sky ray-tracing simulation of weak lensing using ELUCID simulations: exploring galaxy intrinsic alignment and cosmic shear correlations

The intrinsic alignment of galaxies is an important systematic effect in weak-lensing surveys, which can affect the derived cosmological parameters. One direct way to distinguish different alignment models and quantify their effects on the measurement is to produce mocked weak-lensing surveys. In this work, we use full-sky ray-tracing technique to produce mock images of galaxies from the ELUCID $N$-body simulation run with the WMAP9 cosmology. In our model we assume that the shape of central elliptical galaxy follows that of the dark matter halo, and spiral galaxy follows the halo spin. Using the mocked galaxy images, a combination of galaxy intrinsic shape and the gravitational shear, we compare the predicted tomographic shear correlations to the results of KiDS and DLS. It is found that our predictions stay between the KiDS and DLS results. We rule out a model in which the satellite galaxies are radially aligned with the center galaxy, otherwise the shear-correlations on small scales are too high. Most important, we find that although the intrinsic alignment of spiral galaxies is very weak, they induce a positive correlation between the gravitational shear signal and the intrinsic galaxy orientation (GI). This is because the spiral galaxy is tangentially aligned with the nearby large-scale overdensity, contrary to the radial alignment of elliptical galaxy. Our results explain the origin of detected positive GI term from the weak-lensing surveys. We conclude that in future analysis, the GI model must include the dependence on galaxy types in more detail.Comment: 23 pages, 13 figures, published in ApJ. Our mock galaxy catalog is available upon request by email to the author ([email protected], [email protected]

ELUCID V. Lighting dark matter halos with galaxies

In a recent study, using the distribution of galaxies in the north galactic pole of SDSS DR7 region enclosed in a 500\mpch box, we carried out our ELUCID simulation (Wang et al. 2016, ELUCID III). Here we {\it light} the dark matter halos and subhalos in the reconstructed region in the simulation with galaxies in the SDSS observations using a novel {\it neighborhood} abundance matching method. Before we make use of thus established galaxy-subhalo connections in the ELUCID simulation to evaluate galaxy formation models, we set out to explore the reliability of such a link. For this purpose, we focus on the following a few aspects of galaxies: (1) the central-subhalo luminosity and mass relations; (2) the satellite fraction of galaxies; (3) the conditional luminosity function (CLF) and conditional stellar mass function (CSMF) of galaxies; and (4) the cross correlation functions between galaxies and the dark matter particles, most of which are measured separately for all, red and blue galaxy populations. We find that our neighborhood abundance matching method accurately reproduces the central-subhalo relations, satellite fraction, the CLFs and CSMFs and the biases of galaxies. These features ensure that thus established galaxy-subhalo connections will be very useful in constraining galaxy formation processes. And we provide some suggestions on the three levels of using the galaxy-subhalo pairs for galaxy formation constraints. The galaxy-subhalo links and the subhalo merger trees in the SDSS DR7 region extracted from our ELUCID simulation are available upon request.Comment: 18 pages, 13 figures, ApJ accepte

Mechanisms of action and synergetic formulas of plant-based natural compounds from traditional Chinese medicine for managing osteoporosis: a literature review

Osteoporosis (OP) is a systemic skeletal disease prevalent in older adults, characterized by substantial bone loss and deterioration of microstructure, resulting in heightened bone fragility and risk of fracture. Traditional Chinese Medicine (TCM) herbs have been widely employed in OP treatment owing to their advantages, such as good tolerance, low toxicity, high efficiency, and minimal adverse reactions. Increasing evidence also reveals that many plant-based compounds (or secondary metabolites) from these TCM formulas, such as resveratrol, naringin, and ginsenoside, have demonstrated beneficial effects in reducing the risk of OP. Nonetheless, the comprehensive roles of these natural products in OP have not been thoroughly clarified, impeding the development of synergistic formulas for optimal OP treatment. In this review, we sum up the pathological mechanisms of OP based on evidence from basic and clinical research; emphasis is placed on the in vitro and preclinical in vivo evidence-based anti-OP mechanisms of TCM formulas and their chemically active plant constituents, especially their effects on imbalanced bone homeostasis regulated by osteoblasts (responsible for bone formation), osteoclasts (responsible for bone resorption), bone marrow mesenchymal stem cells as well as bone microstructure, angiogenesis, and immune system. Furthermore, we prospectively discuss the combinatory ingredients from natural products from these TCM formulas. Our goal is to improve comprehension of the pharmacological mechanisms of TCM formulas and their chemically active constituents, which could inform the development of new strategies for managing OP

Novel Y-chromosomal microdeletions associated with non-obstructive azoospermia uncovered by high throughput sequencing of sequence-tagged sites (STSs)

Y-chromosomal microdeletion (YCM) serves as an important genetic factor in non-obstructive azoospermia (NOA). Multiplex polymerase chain reaction (PCR) is routinely used to detect YCMs by tracing sequence-tagged sites (STSs) in the Y chromosome. Here we introduce a novel methodology in which we sequence 1,787 (post-filtering) STSs distributed across the entire male-specific Y chromosome (MSY) in parallel to uncover known and novel YCMs. We validated this approach with 766 Chinese men with NOA and 683 ethnically matched healthy individuals and detected 481 and 98 STSs that were deleted in the NOA and control group, representing a substantial portion of novel YCMs which significantly influenced the functions of spermatogenic genes. The NOA patients tended to carry more and rarer deletions that were enriched in nearby intragenic regions. Haplogroup O2* was revealed to be a protective lineage for NOA, in which the enrichment of b1/b3 deletion in haplogroup C was also observed. In summary, our work provides a new high-resolution portrait of deletions in the Y chromosome.National Key Scientific Program of China [2011CB944303]; National Nature Science Foundation of China [31271244, 31471344]; Promotion Program for Shenzhen Key Laboratory [CXB201104220045A]; Shenzhen Project of Science and Technology [JCYJ20130402113131202, JCYJ20140415162543017]SCI(E)[email protected]; [email protected]; [email protected]

CSST Strong Lensing Preparation: a Framework for Detecting Strong Lenses in the Multi-color Imaging Survey by the China Survey Space Telescope (CSST)

Strong gravitational lensing is a powerful tool for investigating dark matter and dark energy properties. With the advent of large-scale sky surveys, we can discover strong lensing systems on an unprecedented scale, which requires efficient tools to extract them from billions of astronomical objects. The existing mainstream lens-finding tools are based on machine learning algorithms and applied to cut-out-centered galaxies. However, according to the design and survey strategy of optical surveys by CSST, preparing cutouts with multiple bands requires considerable efforts. To overcome these challenges, we have developed a framework based on a hierarchical visual Transformer with a sliding window technique to search for strong lensing systems within entire images. Moreover, given that multi-color images of strong lensing systems can provide insights into their physical characteristics, our framework is specifically crafted to identify strong lensing systems in images with any number of channels. As evaluated using CSST mock data based on an Semi-Analytic Model named CosmoDC2, our framework achieves precision and recall rates of 0.98 and 0.90, respectively. To evaluate the effectiveness of our method in real observations, we have applied it to a subset of images from the DESI Legacy Imaging Surveys and media images from Euclid Early Release Observations. 61 new strong lensing system candidates are discovered by our method. However, we also identified false positives arising primarily from the simplified galaxy morphology assumptions within the simulation. This underscores the practical limitations of our approach while simultaneously highlighting potential avenues for future improvements.Comment: The paper is accepted by the AJ. The complete code could be downloaded with DOI of: 10.12149/101393. Comments are welcom

ACSL4-Mediated Ferroptosis and Its Potential Role in Central Nervous System Diseases and Injuries

As an iron-dependent regulated form of cell death, ferroptosis is characterized by iron-dependent lipid peroxidation and has been implicated in the occurrence and development of various diseases, including nervous system diseases and injuries. Ferroptosis has become a potential target for intervention in these diseases or injuries in relevant preclinical models. As a member of the Acyl-CoA synthetase long-chain family (ACSLs) that can convert saturated and unsaturated fatty acids, Acyl—CoA synthetase long-chain familymember4 (ACSL4) is involved in the regulation of arachidonic acid and eicosapentaenoic acid, thus leading to ferroptosis. The underlying molecular mechanisms of ACSL4-mediated ferroptosis will promote additional treatment strategies for these diseases or injury conditions. Our review article provides a current view of ACSL4-mediated ferroptosis, mainly including the structure and function of ACSL4, as well as the role of ACSL4 in ferroptosis. We also summarize the latest research progress of ACSL4-mediated ferroptosis in central nervous system injuries and diseases, further proving that ACSL4-medicated ferroptosis is an important target for intervention in these diseases or injuries

Incomplete Multi-View Multi-Label Learning via Label-Guided Masked View- and Category-Aware Transformers

As we all know, multi-view data is more expressive than single-view data and multi-label annotation enjoys richer supervision information than single-label, which makes multi-view multi-label learning widely applicable for various pattern recognition tasks. In this complex representation learning problem, three main challenges can be characterized as follows: i) How to learn consistent representations of samples across all views? ii) How to exploit and utilize category correlations of multi-label to guide inference? iii) How to avoid the negative impact resulting from the incompleteness of views or labels? To cope with these problems, we propose a general multi-view multi-label learning framework named label-guided masked view- and category-aware transformers in this paper. First, we design two transformer-style based modules for cross-view features aggregation and multi-label classification, respectively. The former aggregates information from different views in the process of extracting view-specific features, and the latter learns subcategory embedding to improve classification performance. Second, considering the imbalance of expressive power among views, an adaptively weighted view fusion module is proposed to obtain view-consistent embedding features. Third, we impose a label manifold constraint in sample-level representation learning to maximize the utilization of supervised information. Last but not least, all the modules are designed under the premise of incomplete views and labels, which makes our method adaptable to arbitrary multi-view and multi-label data. Extensive experiments on five datasets confirm that our method has clear advantages over other state-of-the-art methods