Genetic Algorithm for Sparse Optimization of Mills Cross Array Used in Underwater Acoustic Imaging

Underwater acoustic imaging employs a special form of array which includes numerous transducer elements to achieve beamforming. Although a large-scale array can bring high imaging resolution, it will also cause difficulties in hardware complexity and real-time application. In this paper, in order to reduce the number of array elements, a sparse optimization for Mills cross is proposed, considering the elements’ distributions and weights design. The improved genetic algorithm is adopted to generate evolutions for sparse solution. In order to ensure effective convergence and successful evolution, relevant genetic operators are proposed, including appropriate population coding, correct fitness function, reasonable selection strategy and efficient two-point orthogonal crossover, among others. Essentially, a satisfied sparse solution is a result of mutual restraint between array elements’ survivals and their weights. The simulations reveal that our sparse cross array decreases the number of elements by 8.25% compared to the conventional Mills cross multiplicative array, while keeping the advantages of narrow main lobe width and low sidelobe level. Improved genetic algorithm is an effective method for the underwater acoustic imaging array to implement the sparse optimization

LanguageBind: Extending Video-Language Pretraining to N-modality by Language-based Semantic Alignment

The video-language (VL) pretraining has achieved remarkable improvement in multiple downstream tasks. However, the current VL pretraining framework is hard to extend to multiple modalities (N modalities, N>=3) beyond vision and language. We thus propose LanguageBind, taking the language as the bind across different modalities because the language modality is well-explored and contains rich semantics. Specifically, we freeze the language encoder acquired by VL pretraining, then train encoders for other modalities with contrastive learning. As a result, all modalities are mapped to a shared feature space, implementing multi-modal semantic alignment. While LanguageBind ensures that we can extend VL modalities to N modalities, we also need a high-quality dataset with alignment data pairs centered on language. We thus propose VIDAL-10M with Video, Infrared, Depth, Audio and their corresponding Language, naming as VIDAL-10M. In our VIDAL-10M, all videos are from short video platforms with complete semantics rather than truncated segments from long videos, and all the video, depth, infrared, and audio modalities are aligned to their textual descriptions. LanguageBind has achieved superior performance on a wide range of 15 benchmarks covering video, audio, depth, and infrared. Moreover, multiple experiments have provided evidence for the effectiveness of LanguageBind in achieving indirect alignment and complementarity among diverse modalities. Code address: https://github.com/PKU-YuanGroup/LanguageBindComment: Accepted by ICLR 202

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Natural compounds ursolic acid and digoxin exhibit inhibitory activities to cancer cells in RORγ-dependent and -independent manner.

Natural compounds ursolic acid (UA) and digoxin isolated from fruits and other plants display potent anti-cancer effects in preclinical studies. UA and digoxin have been at clinical trials for treatment of different cancers including prostate cancer, pancreatic cancer and breast cancer. However, they displayed limited benefit to patients. Currently, a poor understanding of their direct targets and mechanisms of action (MOA) severely hinders their further development. We previously identified nuclear receptor RORγ as a novel therapeutic target for castration-resistant prostate cancer (CRPC) and triple-negative breast cancer (TNBC) and demonstrated that tumor cell RORγ directly activates gene programs such as androgen receptor (AR) signaling and cholesterol metabolism. Previous studies also demonstrated that UA and digoxin are potential RORγt antagonists in modulating the functions of immune cells such as Th17 cells. Here we showed that UA displays a strong activity in inhibition of RORγ-dependent transactivation function in cancer cells, while digoxin exhibits no effect at clinically relevant concentrations. In prostate cancer cells, UA downregulates RORγ-stimulated AR expression and AR signaling, whereas digoxin upregulates AR signaling pathway. In TNBC cells, UA but not digoxin alters RORγ-controlled gene programs of cell proliferation, apoptosis and cholesterol biosynthesis. Together, our study reveals for the first-time that UA, but not digoxin, acts as a natural antagonist of RORγ in the cancer cells. Our finding that RORγ is a direct target of UA in cancer cells will help select patients with tumors that likely respond to UA treatment

Deregulation of Cholesterol Homeostasis by a Nuclear Hormone Receptor Crosstalk in Advanced Prostate Cancer

Metastatic castration-resistant prostate cancer (mCRPC) features high intratumoral cholesterol levels, due to aberrant regulation of cholesterol homeostasis. However, the underlying mechanisms are still poorly understood. The retinoid acid receptor-related orphan receptor gamma (RORγ), an attractive therapeutic target for cancer and autoimmune diseases, is strongly implicated in prostate cancer progression. We demonstrate in this study that in mCRPC cells and tumors, RORγ plays a crucial role in deregulation of cholesterol homeostasis. First, we found that RORγ activates the expression of key cholesterol biosynthesis proteins, including HMGCS1, HMGCR, and SQLE. Interestingly, we also found that RORγ inhibition induces cholesterol efflux gene program including ABCA1, ABCG1 and ApoA1. Our further studies revealed that liver X receptors (LXRα and LXRβ), the master regulators of cholesterol efflux pathway, mediate the function of RORγ in repression of cholesterol efflux. Finally, we demonstrated that RORγ antagonist in combination with statins has synergistic effect in killing mCRPC cells through blocking statin-induced feedback induction of cholesterol biosynthesis program and that the combination treatment also elicits stronger anti-tumor effects than either alone. Altogether, our work revealed that in mCRPC, RORγ contributes to aberrant cholesterol homeostasis by induction of cholesterol biosynthesis program and suppression of cholesterol efflux genes. Our findings support a therapeutic strategy of targeting RORγ alone or in combination with statin for effective treatment of mCRPC

Table2_Natural compounds ursolic acid and digoxin exhibit inhibitory activities to cancer cells in RORγ-dependent and -independent manner.DOCX

Natural compounds ursolic acid (UA) and digoxin isolated from fruits and other plants display potent anti-cancer effects in preclinical studies. UA and digoxin have been at clinical trials for treatment of different cancers including prostate cancer, pancreatic cancer and breast cancer. However, they displayed limited benefit to patients. Currently, a poor understanding of their direct targets and mechanisms of action (MOA) severely hinders their further development. We previously identified nuclear receptor RORγ as a novel therapeutic target for castration-resistant prostate cancer (CRPC) and triple-negative breast cancer (TNBC) and demonstrated that tumor cell RORγ directly activates gene programs such as androgen receptor (AR) signaling and cholesterol metabolism. Previous studies also demonstrated that UA and digoxin are potential RORγt antagonists in modulating the functions of immune cells such as Th17 cells. Here we showed that UA displays a strong activity in inhibition of RORγ-dependent transactivation function in cancer cells, while digoxin exhibits no effect at clinically relevant concentrations. In prostate cancer cells, UA downregulates RORγ-stimulated AR expression and AR signaling, whereas digoxin upregulates AR signaling pathway. In TNBC cells, UA but not digoxin alters RORγ-controlled gene programs of cell proliferation, apoptosis and cholesterol biosynthesis. Together, our study reveals for the first-time that UA, but not digoxin, acts as a natural antagonist of RORγ in the cancer cells. Our finding that RORγ is a direct target of UA in cancer cells will help select patients with tumors that likely respond to UA treatment.</p

Table1_Natural compounds ursolic acid and digoxin exhibit inhibitory activities to cancer cells in RORγ-dependent and -independent manner.DOCX

Natural compounds ursolic acid (UA) and digoxin isolated from fruits and other plants display potent anti-cancer effects in preclinical studies. UA and digoxin have been at clinical trials for treatment of different cancers including prostate cancer, pancreatic cancer and breast cancer. However, they displayed limited benefit to patients. Currently, a poor understanding of their direct targets and mechanisms of action (MOA) severely hinders their further development. We previously identified nuclear receptor RORγ as a novel therapeutic target for castration-resistant prostate cancer (CRPC) and triple-negative breast cancer (TNBC) and demonstrated that tumor cell RORγ directly activates gene programs such as androgen receptor (AR) signaling and cholesterol metabolism. Previous studies also demonstrated that UA and digoxin are potential RORγt antagonists in modulating the functions of immune cells such as Th17 cells. Here we showed that UA displays a strong activity in inhibition of RORγ-dependent transactivation function in cancer cells, while digoxin exhibits no effect at clinically relevant concentrations. In prostate cancer cells, UA downregulates RORγ-stimulated AR expression and AR signaling, whereas digoxin upregulates AR signaling pathway. In TNBC cells, UA but not digoxin alters RORγ-controlled gene programs of cell proliferation, apoptosis and cholesterol biosynthesis. Together, our study reveals for the first-time that UA, but not digoxin, acts as a natural antagonist of RORγ in the cancer cells. Our finding that RORγ is a direct target of UA in cancer cells will help select patients with tumors that likely respond to UA treatment.</p

Exploring the mechanism of the Fructus Mume and Rhizoma Coptidis herb pair intervention in Ulcerative Colitis from the perspective of inflammation and immunity based on systemic pharmacology

Abstract Purpose Ulcerative Colitis (UC) is a chronic nonspecific inflammatory disease of the colon and rectum. Fructus Mume (FM) and Rhizoma Coptidis (RC) exert effects on inflammatory and immune diseases. We evaluated the hypothesis of the FM and RC (FM-RC) herb pair remedy in alleviating dextran sulfate sodium (DSS)-induced colitis, through network pharmacology-based analyses, molecular docking, and experimental validation. Methods The Traditional Chinese medicine systematic pharmacology analysis platform(TCMSP) and Swiss database were used to predict potential targets of FM-RC and the GeneCards database was utilized to collect UC genes. Cytoscape software was used to construct and analyze the networks, and DAVID was utilized to perform enrichment analysis. AutoDock software was used to dock the core chemical components of the FM-RC herb pair with key UC targets. Animal experiments were performed to validate the prediction results and general conditions and body weight were observed. Pathological changes in colon tissue were observed by staining with hematoxylin and eosin. The levels of TNF-α, IL-8, IL-17, and IL-4 in serum and colon tissue were detected by ELISA. Results Eighteen effective components of the herb couple were screened, and their potential therapeutic targets in the treatment of UC were acquired from 110 overlapped targets. GO and KEGG analyses revealed that these targets were highly correlated with protein autophosphorylation, plasma membrane, ATP binding, cancer pathways, the PI3K-AKt signaling pathway, and the Rap1 signaling pathway. Molecular docking established the core protein interactions with compounds having a docking energy < 0 kJ·mol−1, indicating the core active components had strong binding activities with the core targets. FM-RC herb pair relieved pathological indicators and reduced the concentration of TNF-α, IL-8, and IL-17 and increased IL-4 levels in the serum and colon tissues of UC rats. Conclusion Collectively, FM-RC herb pair administration alleviated UC. These beneficial effects targeted MAPK1 signaling related to inflammation and immunity, which provided a basis for a better understanding of FM-RC in the treatment of UC