Detecting Ultra-light Dark Matter with Stimulated Annihilation

Ultra-light Dark Matter (ULDM) is one of the most promising DM candidates. In the presence of background photon radiation, the annihilation rate of the ULDM can be greatly enhanced due to the Bose enhancement. We propose to utilize such stimulated annihilation to probe the ULDM by emitting a beam of radio into the space. This could lead to a distinctive reflected electromagnetic wave with an angular frequency equal to the ULDM mass. We show that low-frequency radio telescopes, such as LOFAR, UTR-2 and ngBOLO, can offer a new avenue of detecting this signal, especially for the Earth halo model. With a power of 50 MW emitter, the expected limits could be several orders of magnitude stronger than that from Big Bang nucleosynthesis (BBN) in the ULDM mass $m_\phi$ range, $2.07 \times 10^{-8}\mathrm{~eV} \sim 4.5 \times 10^{-8}\mathrm{~eV}$.Comment: 6 pages, 2 figure

AdaptDHM: Adaptive Distribution Hierarchical Model for Multi-Domain CTR Prediction

Large-scale commercial platforms usually involve numerous business domains for diverse business strategies and expect their recommendation systems to provide click-through rate (CTR) predictions for multiple domains simultaneously. Existing promising and widely-used multi-domain models discover domain relationships by explicitly constructing domain-specific networks, but the computation and memory boost significantly with the increase of domains. To reduce computational complexity, manually grouping domains with particular business strategies is common in industrial applications. However, this pre-defined data partitioning way heavily relies on prior knowledge, and it may neglect the underlying data distribution of each domain, hence limiting the model's representation capability. Regarding the above issues, we propose an elegant and flexible multi-distribution modeling paradigm, named Adaptive Distribution Hierarchical Model (AdaptDHM), which is an end-to-end optimization hierarchical structure consisting of a clustering process and classification process. Specifically, we design a distribution adaptation module with a customized dynamic routing mechanism. Instead of introducing prior knowledge for pre-defined data allocation, this routing algorithm adaptively provides a distribution coefficient for each sample to determine which cluster it belongs to. Each cluster corresponds to a particular distribution so that the model can sufficiently capture the commonalities and distinctions between these distinct clusters. Extensive experiments on both public and large-scale Alibaba industrial datasets verify the effectiveness and efficiency of AdaptDHM: Our model achieves impressive prediction accuracy and its time cost during the training stage is more than 50% less than that of other models

Dynamic Task Scheduling in Remote Sensing Data Acquisition from Open-Access Data Using CloudSim

With the rapid development of cloud computing and network technologies, large-scale remote sensing data collection tasks are receiving more interest from individuals and small and medium-sized enterprises. Large-scale remote sensing data collection has its challenges, including less available node resources, short collection time, and lower collection efficiency. Moreover, public remote data sources have restrictions on user settings, such as access to IP, frequency, and bandwidth. In order to satisfy users’ demand for accessing public remote sensing data collection nodes and effectively increase the data collection speed, this paper proposes a TSCD-TSA dynamic task scheduling algorithm that combines the BP neural network prediction algorithm with PSO-based task scheduling algorithms. Comparative experiments were carried out using the proposed task scheduling algorithms on an acquisition task using data from Sentinel2. The experimental results show that the MAX-MAX-PSO dynamic task scheduling algorithm has a smaller fitness value and a faster convergence speed

Co-delivery of gemcitabine and Triapine by calcium carbonate nanoparticles against chemoresistant pancreatic cancer

Pancreatic cancer is a malignant disease with high mortality, and its systemic treatment strategy mainly focuses on chemotherapy. Yet, the overall prognosis of pancreatic cancer patients is still extremely poor with a low survival rate. Gemcitabine (GEM) is a widely used chemotherapeutic agent for the treatment of pancreatic cancer. However, GEM chemoresistance remains the major challenge. In this study, we prepared calcium carbonate nanoparticles (CaCO3 NPs) loaded with a nucleotide reductase inhibitor (Triapine) and GEM to suppress the GEM resistance of pancreatic cancer cells (PANC-1/GEM) and solve the problem of poor solubility of Triapine. CaCO3-GEM-Triapine NPs nano-formulations enhanced the therapeutic effect of GEM-based chemotherapy by inhibiting cancer cell proliferation, migration, and resistance to GEM using both 2D PANC-1/GEM cells and 3D tumor spheroids. The study indicated that CaCO3 NPs loaded with GEM and Triapine could provide an effective treatment option to overcome drug resistance in pancreatic cancer

Fibroblast Growth Factor-10 (FGF-10) Mobilizes Lung-resident Mesenchymal Stem Cells and Protects Against Acute Lung Injury.

FGF-10 can prevent or reduce lung specific inflammation due to traumatic or infectious lung injury. However, the exact mechanisms are poorly characterized. Additionally, the effect of FGF-10 on lung-resident mesenchymal stem cells (LR-MSCs) has not been studied. To better characterize the effect of FGF-10 on LR-MSCs, FGF-10 was intratracheally delivered into the lungs of rats. Three days after instillation, bronchoalveolar lavage was performed and plastic-adherent cells were cultured, characterized and then delivered therapeutically to rats after LPS intratracheal instillation. Immunophenotyping analysis of FGF-10 mobilized and cultured cells revealed expression of the MSC markers CD29, CD73, CD90, and CD105, and the absence of the hematopoietic lineage markers CD34 and CD45. Multipotency of these cells was demonstrated by their capacity to differentiate into osteocytes, adipocytes, and chondrocytes. Delivery of LR-MSCs into the lungs after LPS injury reduced the inflammatory response as evidenced by decreased wet-to-dry ratio, reduced neutrophil and leukocyte recruitment and decreased inflammatory cytokines compared to control rats. Lastly, direct delivery of FGF-10 in the lungs of rats led to an increase of LR-MSCs in the treated lungs, suggesting that the protective effect of FGF-10 might be mediated, in part, by the mobilization of LR-MSCs in lungs

Docetaxel-loaded M1 macrophage-derived exosomes for a safe and efficient chemoimmunotherapy of breast cancer

The conversion of tumor-promoting M2 macrophage phenotype to tumor-suppressing M1 macrophages is a promising therapeutic approach for cancer treatment. However, the tumor normally provides an abundance of M2 macrophage stimuli, which creates an M2 macrophage-dominant immunosuppressive microenvironment. In our study, docetaxel (DTX) as chemotherapeutic modularity was loaded into M1 macrophage-derived exosomes (M1-Exo) with M1 proinflammatory nature to establish DTX-M1-Exo drug delivery system. We found that DTX-M1-Exo induced naïve M0 macrophages to polarize to M1 phenotype, while failed to repolarize to M2 macrophages upon Interleukin 4 restimulation due to impaired mitochondrial function. This suggests that DTX-M1-Exo can achieve long-term robust M1 activation in immunosuppressive tumor microenvironment. The in vivo results further confirmed that DTX-M1-Exo has a beneficial effect on macrophage infiltration and activation in the tumor tissues. Thus, DTX-M1-Exo is a novel macrophage polarization strategy via combined chemotherapy and immunotherapy to achieve great antitumor therapeutic efficacy

M1 macrophage-derived exosomes loaded with Gemcitabine and Deferasirox against chemoresistant pancreatic cancer

Pancreatic cancer is a malignant disease with high mortality and poor prognosis due to lack of early diagnosis and low treatment efficiency after diagnosis. Although Gemcitabine (GEM) is used as the first-line chemotherapeutic drug, chemoresistance is still the major problem that limits its therapeutic efficacy. Here in this study, we developed a specific M1 macrophage-derived exosome (M1Exo)-based drug delivery system against GEM resistance in pancreatic cancer. In addition to GEM, Deferasirox (DFX) was also loaded into drug carrier, M1Exo, in order to inhibit ribonucleotide reductase regulatory subunit M2 (RRM2) expression via depleting iron, and thus increase chemosensitivity of GEM. The M1Exo nanoformulations combining both GEM and DFX significantly enhanced the therapeutic efficacy on the GEM-resistant PANC-1/GEM cells and 3D tumor spheroids by inhibiting cancer cell proliferation, cell attachment and migration, and chemoresistance to GEM. These data demonstrated that M1Exo loaded with GEM and DFX offered an efficient therapeutic strategy for drug-resistant pancreatic cancer

Beyond cellulose: pharmaceutical potential for bioactive plant polysaccharides in treating disease and gut dysbiosis

Polysaccharides derived from plants, algae, or fungi serve as the major components of some human diets. Polysaccharides have been shown to exhibit diverse biological activities in improving human health, and have also been proposed to function as potent modulators of gut microbiota composition, thus playing a bi-directional regulatory role in host health. Here, we review a variety of polysaccharide structures potentially linked to biological functions, and cover current research progress in characterizing their pharmaceutical effects in various disease models, including antioxidant, anticoagulant, anti-inflammatory, immunomodulatory, hypoglycemic, and antimicrobial activities. We also highlight the effects of polysaccharides on modulating gut microbiota via enrichment for beneficial taxa and suppression of potential pathogens, leading to increased microbial expression of carbohydrate-active enzymes and enhanced short chain fatty acid production. This review also discusses polysaccharide-mediated improvements in gut function by influencing interleukin and hormone secretion in host intestinal epithelial cells