4,444 research outputs found

    The production of charmonium pentaquark from b-baryon and B-meson decay: SU(3) analysis

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    In this paper, we study the production of charmonium pentaquark ccˉqqqc \bar c q q q from bottom baryon and B-meson decays under the flavor SU(3) symmetry. Decay amplitudes for various processes are parametrized in terms of the SU(3) irreducible nonperturbative amplitudes. A number of relations between decay widths have been deduced. Moreover, the strong decays of pentaquark is also taken into account. These results can be tested in future measurements at LHCb, Belle II and CEPC. Once a few decay branching fractions have been measured, our work could provide hints for exploring new decay channels or new pentaquark states.Comment: 10 pages,2 figure

    NExT-GPT: Any-to-Any Multimodal LLM

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    While recently Multimodal Large Language Models (MM-LLMs) have made exciting strides, they mostly fall prey to the limitation of only input-side multimodal understanding, without the ability to produce content in multiple modalities. As we humans always perceive the world and communicate with people through various modalities, developing any-to-any MM-LLMs capable of accepting and delivering content in any modality becomes essential to human-level AI. To fill the gap, we present an end-to-end general-purpose any-to-any MM-LLM system, NExT-GPT. We connect an LLM with multimodal adaptors and different diffusion decoders, enabling NExT-GPT to perceive inputs and generate outputs in arbitrary combinations of text, images, videos, and audio. By leveraging the existing well-trained highly-performing encoders and decoders, NExT-GPT is tuned with only a small amount of parameter (1%) of certain projection layers, which not only benefits low-cost training and also facilitates convenient expansion to more potential modalities. Moreover, we introduce a modality-switching instruction tuning (MosIT) and manually curate a high-quality dataset for MosIT, based on which NExT-GPT is empowered with complex cross-modal semantic understanding and content generation. Overall, our research showcases the promising possibility of building an AI agent capable of modeling universal modalities, paving the way for more human-like AI research in the community. Project page: https://next-gpt.github.io/Comment: work in progres

    Buccal Transmucosal Delivery System of Enalapril for Improved Cardiac Drug Delivery: Preparation and Characterization

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    Purpose: To prepare and characterize buccal transmucosal delivery system of enalapril maleate for overcoming its low bioavailability, and hence provide improved therapeutic efficacy and patient compliance.Methods: Transmucosal drug delivery systems of enalapril maleate were formulated as buccal films by solvent casting technique using polyvinylpyrrolidone K90, hydroxypropyl methylcellulose, sodium carboxymethylcellulose (high viscosity). The films were evaluated for film weight, thickness, folding endurance, drug content uniformity, surface pH, in vitro residence time, in vitro drug release and ex-vivo permeation.Results: All the formulations showed high drug content (96.45 to 98.49 %). Those with good swelling showed good residence time. In vitro drug release was highest for films prepared with high viscosity grade sodium carboxymethylcellulose (SCMC- HV,F2), releasing 92.24 % of drug in 1.5 h) followed by F4 (containing polyvinyl pyrrolidone K-90 1 % w/v and SCMC (HV) 1 % w/v). Ex-vivo drug permeation at the end of 10 h was 82.24 and 89.9 % for F2 and F4, respectively.Conclusion: Prompt drug release was obtained from the formulation (F2) containing SCMC 2 % w/v with 10 mg enalapril. However, on the basis of the highest swelling and residence time, and controlled drug release, formulation F4 (containing PVP K-90 and SCMC HV) would be suitable for the development of buccal film for effective therapy of cardiac diseases.Keywords: Cardiac disease, Transmucosal, Buccal films, Enalapril maleate, Drug release, Ex-vivo permeatio

    eIF3a: A new anticancer drug target in the eIF family

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    eIF3a is the largest subunit of eIF3, which is a key player in all steps of translation initiation. During the past years, eIF3a is recognized as a proto-oncogene, which is an important discovery in this field. It is widely reported to be correlated with cancer occurrence, metastasis, prognosis, and therapeutic response. Recently, the mechanisms of eIF3a action in the carcinogenesis are unveiled gradually. A number of cellular, physiological, and pathological processes involving eIF3a are identified. Most importantly, it is emerging as a new potential drug target in the eIF family, and some small molecule inhibitors are being developed. Thus, we perform a critical review of recent advances in understanding eIF3a physiological and pathological functions, with specific focus on its role in cancer and anticancer drug targets
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