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Big data-driven target identification by machine learning: DRD2 as a therapeutic target for psoriasis

Journal of Dermatological Science 2025年

作者： Sakai, Takashi Sawada, Ryusuke Ichinose, Otoha Terabayashi, Takeshi Hatano, Yutaka Yamanishi, Yoshihiro Ishizaki, Toshimasa Department of Dermatology Faculty of Medicine Oita University Oita Japan Department of Pharmacology Okayama University Graduate School of Medicine Dentistry and Pharmaceutical Sciences Okayama Japan Department of Bioscience and Bioinformatics Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology Fukuoka Japan Department of Pharmacology Faculty of Medicine Oita University Oita Japan Department of Complex Systems Science Graduate School of Informatics Nagoya University Aichi Japan

Background: The development of medical treatments has traditionally relied on researchers leveraging scientific knowledge to hypothesize disease mechanisms and identify therapeutic agents. However, the depletion of novel therapeutic targets has become a significant challenge, resulting in stagnation within pharmaceutical research. Objective: To address the scarcity of therapeutic targets, we developed a machine learning (ML)-based system capable of predicting therapeutic target molecules for diseases. To validate its utility, we applied this system to psoriasis, aiming to identify novel treatment strategies. Methods: Our approach utilized a large clinical database to calculate reporting odds ratios for all drugs associated with the prevention of diseases of interest. We identified target proteins by analyzing large chemical structure databases to discover proteins commonly associated with preventive drug candidates. Experimental validation was conducted by administering a predicted therapeutic candidate in an imiquimod-induced psoriasis mouse model. Results: The ML-based predictions identified drugs for Parkinson's disease as potential preventive candidates for psoriasis. Further analysis highlighted dopamine receptor D2 (DRD2) as a therapeutic target. Administration of a DRD2 agonist alleviated psoriasis symptoms in mice, evidenced by the downregulation of mRNA expression in the IL-17 pathway and reduced serum tumor necrosis factor-α levels. Conclusion: This study demonstrates the utility of a novel ML-based system for identifying therapeutic targets, as shown by its successful application in uncovering the role of DRD2 in psoriasis. Beyond psoriasis, this system offers significant potential for exploring pathological mechanisms and discovering therapeutic targets across various diseases. © 2025 The Authors

关键词： artificial intelligence big data dopamine receptor D2 machine learning psoriasis

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Blockchain-based Security Framework for Metaverse: A Decentralized Approach

Blockchain-based Security Framework for Metaverse: A Decentr...

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International Conference on Electronics, computers and Artificial Intelligence (ECAI)

作者： Anand Singh Rajawat S.B. Goyal RamKumar Solanki Maria Simona Raboaca Traian Candin Mihaltan Zoltán Illés Chaman Verma School of Computer Science & Engineering Sandip University Nashik India Faculty of Information Technology City University Petaling Jaya Malaysia ICSI Energy Department National Research and Development Institute for Cryogenics and Isotopic Technologies Ramnicu Valcea Romania Faculty of Building Services Technical University of Cluj-Napoca Cluj-Napoca Romania Department of Media and Educational Informatics Faculty of Informatics Eötvös Loránd University Budapest Hungary

People can act out fake social exchanges in the Metaverse, which is an online community. Security has become a problem in the Metaverse because there are so many online transactions and digital assets. In this thesis, a Blockchain-based security system for the Metaverse is proposed. This would be a decentralised way to keep the virtual world safe. Our system uses Blockchain's autonomous structure to make sure that all financial transactions in the Metaverse are safe, anonymous, and true. We suggest a new consensus process that combines Proof of Stake (PoS) and Proof of Authority (PoA) to make networks safer and allow them to grow. We also have a user-focused, decentralised identity management system that keeps their information safe. We also suggest a way to process Metaverse transactions safely that is based on smart contracts. Our method makes sure that transactional proof, recording, and validation are done in a safe and reliable way. We also show a reputation system that benefits people who follow the law and punishes people who break the law. Lastly, we test how well our suggested structure works with simulations and real-world tests. The results show that our way works to reduce possible security risks in the Metaverse and create a safe, scalable environment for online business. Overall, our Blockchain-based Security Framework for Metaverse: A Decentralised Approach is a good way to keep the security and privacy of digital activities in Metaverse.

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Multiregion Multiscale Image Segmentation with Anisotropic Diffusion 25th

Multiregion Multiscale Image Segmentation with Anisotropic D...

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25th International Conference on Pattern Recognition Workshops, ICPR 2020

作者： Prasath, V. B. Surya Thanh, Dang Ngoc Hoang Hai, Nguyen Hoang Dvoenko, Sergey Department of Electrical Engineering and Computer Science University of Cincinnati CincinnatiOH45221 United States Division of Biomedical Informatics Cincinnati Children’s Hospital Medical Center CincinnatiOH45229 United States Department of Biomedical Informatics College of Medicine University of Cincinnati CincinnatiOH45267 United States Department of Pediatrics University of Cincinnati College of Medicine CincinnatiOH45257 United States Department of Information Technology School of Business Information Technology University of Economics Ho Chi Minh City Ho Chi Minh City Viet Nam Department of Computer Science Vietnam-Korea University of Information and Communication Technology – The University of Danang Danang Viet Nam Department of Information Security Institute of Applied Mathematics and Computer Science Tula State University Tula city Russia

ISBN: (纸本)9783030688202

We present a multiregion image segmentation approach which utilizes multiscale anisotropic diffusion based scale spaces. By combining powerful edge preserving anisotropic diffusion smoothing with isolevel set linking and merging, we obtain coherent segments which are tracked across multiple scales. A hierarchical tree representation of the given input image with progressively simplified regions is used with intra-scale splitting and inter-scale merging for obtaining multiregion segmentations. Experimental results on natural and medical images indicate that multiregion, multiscale image segmentation (MMIS) approach obtains coherent segmentation results. © 2021, Springer Nature Switzerland AG.

关键词： Diffusion

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Scale Estimation with Dual Quadrics for Monocular Object SLAM

arXiv

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arXiv 2022年

作者： Song, Shuangfu Zhao, Junqiao Feng, Tiantian Ye, Chen Xiong, Lu The School of Surveying and Geo-Informatics Tongji University Shanghai200092 China The Department of Computer Science and Technology School of Electronics and Information Engineering Tongji University Shanghai201804 China The Institute of Intelligent Vehicle Tongji University Shanghai201804 China

The scale ambiguity problem is inherently unsolvable to monocular SLAM without the metric baseline between moving cameras. In this paper, we present a novel scale estimation approach based on an object-level SLAM system. To obtain the absolute scale of the reconstructed map, we formulate an optimization problem to make the scaled dimensions of objects conform to the distribution of their sizes in the physical world, without relying on any prior information about gravity direction. The dual quadric is adopted to represent objects for its ability to describe objects compactly and accurately, thus providing reliable dimensions for scale estimation. In the proposed monocular object-level SLAM system, semantic objects are initialized first from fitted 3-D oriented bounding boxes and then further optimized under constraints of 2-D detections and 3-D map points. Experiments on indoor and outdoor public datasets show that our approach outperforms existing methods in terms of accuracy and robustness. Copyright © 2022, The Authors. All rights reserved.

关键词： Semantics

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Clifford circuit based heuristic optimization of fermion-to-qubit mappings

arXiv

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arXiv 2025年

作者： Yu, Jeffery Liu, Yuan Sugiura, Sho Van Voorhis, Troy Zeytinŏglu, Sina Joint Center for Quantum Information and Computer Science NIST University of Maryland College ParkMD20742 United States Joint Quantum Institute NIST University of Maryland College ParkMD20742 United States Department of Electrical and Computer Engineering North Carolina State University RaleighNC27606 United States Department of Computer Science North Carolina State University RaleighNC27606 United States Department of Physics North Carolina State University RaleighNC27606 United States Blocq Inc. 717 Market Street San FranciscoCA94103 United States Department of Chemistry Massachusetts Institute of Technology CambridgeMA02139 United States Institute for Theoretical Physics TU Wien Wiedner Hauptstraße 8-10/136 ViennaA-1040 Austria Physics and Informatics Laboratory NTT Research Inc. SunnyvaleCA94085 United States

Simulation of interacting fermionic Hamiltonians is one of the most promising applications of quantum computers. However, the feasibility of analysing fermionic systems with a quantum computer hinges on the efficiency of fermion-to-qubit mappings that encode non-local fermionic degrees of freedom in local qubit degrees of freedom. While recent works have highlighted the importance of designing fermion-to-qubit mappings that are tailored to specific problem Hamiltonians, the methods proposed so far are either restricted to a narrow class of mappings or they use computationally expensive and unscalable brute-force search algorithms. Here, we address this challenge by designing a heuristic numerical optimization framework for fermion-to-qubit mappings. To this end, we first translate the fermion-to-qubit mapping problem to a Clifford circuit optimization problem, and then use simulated annealing to optimize the average Pauli weight of the problem Hamiltonian. For all fermionic Hamiltonians we have considered, the numerically optimized mappings outperform their conventional counterparts, including ternary-tree-based mappings that are known to be optimal for single creation and annihilation operators. We find that our optimized mappings yield between 15% to 40% improvements on the average Pauli weight when the simulation Hamiltonian has an intermediate level of complexity. Most remarkably, the optimized mappings improve the average Pauli weight for 6×6 nearest-neighbor hopping and Hubbard models by more than 40% and 20%, respectively. Surprisingly, we also find specific interaction Hamiltonians for which the optimized mapping outperform any ternary-tree-based mapping. Our results establish heuristic numerical optimization as an effective method for obtaining mappings tailored for specific fermionic Hamiltonian. © 2025, CC BY.

关键词： Hamiltonians

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Lightning-Fast Dual-Layer Lossless Coding for Radiance Format High Dynamic Range Images

arXiv

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arXiv 2023年

作者： Suzuki, Taizo Yukikata, Sara Yang, Kai Yoshida, Taichi The Institute of Engineering Information and Systems University of Tsukuba Ibaraki305-8573 Japan Sky Co. Ltd. Tokyo108-0075 Japan Da-Jiang Innovations Science and Technology Japan Co. Ltd. Tokyo108-0075 Japan The Department of Computer and Network Engineering Graduate School of Informatics and Engineering The University of Electro-Communications Tokyo182-8585 Japan

This paper proposes a fast dual-layer lossless coding for high dynamic range images (HDRIs) in the Radiance format. The coding, which consists of a base layer and a lossless enhancement layer, provides a standard dynamic range image (SDRI) without requiring an additional algorithm at the decoder and can losslessly decode the HDRI by adding the residual signals (residuals) between the HDRI and SDRI to the SDRI, if desired. To suppress the dynamic range of the residuals in the enhancement layer, the coding directly uses the mantissa and exponent information from the Radiance format. To further reduce the residual energy, each mantissa is modeled (estimated) as a linear function, i.e., a simple linear regression, of the encoded-decoded SDRI in each region with the same exponent. This is called simple linear regressive mantissa estimator. Experimental results show that, compared with existing methods, our coding reduces the average bitrate by approximately 1.57-6.68 % and significantly reduces the average encoder implementation time by approximately 87.13-98.96 %. Copyright © 2023, The Authors. All rights reserved.

关键词： Image enhancement

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An IoT based Solar Park Health Monitoring System for PID and Hotspots Effects

An IoT based Solar Park Health Monitoring System for PID and...

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International Conference on Distributed Computing in Sensor Systems (DCOSS)

作者： Gabriel Filios Ioannis Katsidimas Emmanouil Kerimakis Sotiris Nikoletseas Alexandras Souroulagkas Paul Spirakis Department of Computer Engineering and Informatics University of Patras Greece Computer Technology Institute and Press "Diophantus" Greece Department of Computer Engineering and Informatics University of Patras Greece

ISBN: (数字)9781728143514

ISBN: (纸本)9781728198040

With solar parks being established as one of the most important renewable energy systems, there is a strong need for more efficient use of the services they provide, as well as error detection and performance issues confrontation. Internet of Things (IoT) technology, aims to fill the gap, by offering low cost and sustainable solutions towards the efficient operation of these parks. In this paper, we present an in situ monitoring and alerting system, based on WSN technologies, regarding the early detection of Potential Induced Degradation (PID) and Hotspots failures, that can cause a significant drop in solar panels' performance. In order to do so, specific non-trivial attributes such as temperature, humidity, irradiance, current and voltage are continuously monitored at panel level, and processed in a cloud based platform to early identify these phenomena. In particular, sensor nodes send data to a centralized local sink module using a multi-hop WSN architecture, in order to establish a robust and large coverage area. Afterwards, the information is propagated to the cloud server, where deterministic diagnostic algorithms are applied. We present the reference architecture of our approach, alongside the corresponding hardware and software structural, individual components, as well as the integration process and the use case that runs over a real solar park.

关键词： Solar panels Monitoring Wireless sensor networks Temperature sensors informatics Production Temperature measurement

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Deep and handcrafted feature supported diabetic retinopathy detection: A study

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Procedia computer Science 2023年 218卷 2675-2683页

作者： Seifedine Kadry Rubén González Crespo Enrique Herrera-Viedma Sujatha Krishnamoorthy Venkatesan Rajinikanth Faculty of Applied Computing and Technology Noroff University College Kristiansand 94612 Norway Computer Science Department School of Engineering and Technology Universidad Internacional de La Rioja 26006 Andalusian Spain Research Institute in Data Science and Computational Intelligence University of Granada Granada Spain Zhejiang Bioinformatics International Science and Technology Cooperation Center Wenzhou-Kean University Zhejiang Province China Wenzhou Municipal Key Lab of Applied Biomedical and Biopharmaceutical Informatics Wenzhou-Kean University Zhejiang Province China Department of Electronics and Instrumentation Engineering St. Joseph's College of Engineering OMR Chennai 600119 Tamil Nadu India

The eye is the prime sensory organ in physiology, and the abnormality in the eye severely influences the vision system. Therefore, eye irregularity is commonly assessed using imaging schemes, and Fundus Retinal Image (FRI) supported eye screening is one of the ophthalmological practices. This work proposed a Deep-Learning Procedure (DLP) to recognize Diabetic Retinopathy (DR) in FI. The proposed work presents the experimental work with different DLP methods found in the literature. This work is executed with two modes; (i) DR detection using conventional deep-features and (ii) DR discovery using deep ensemble features. To demonstrate this work, 1800 fundus images (900 regular and 900 DR class) are considered for the assessment, and the advantage of proposed plan is confirmed using various performance metrics. The experimental outcome of this study confirms that the AlexNet-based detection provides a better detection (>96%), and the deep ensemble features of AlexNet, VGG16, and ResNet18 provide a detection accuracy of >98% on the chosen FRI database.

关键词： Eye abnormality Diabetic retinopathy Fundus imaging Deep-Learning Classification

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Automatic detection of lung nodule in CT scan slices using CNN segmentation schemes: A study

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Procedia computer Science 2023年 218卷 2786-2794页

作者： Seifedine Kadry Enrique Herrera-Viedma Rubén González Crespo Sujatha Krishnamoorthy Venkatesan Rajinikanth Faculty of Applied Computing and Technology Noroff University College Kristiansand 94612 Norway Research Institute in Data Science and Computational Intelligence University of Granada Granada Andalusian Spain Computer Science Department School of Engineering and Technology Universidad Internacional de La Rioja 26006 Spain Zhejiang Bioinformatics International Science and Technology Cooperation Center Wenzhou-Kean University Zhejiang Province China Wenzhou Municipal Key Lab of Applied Biomedical and Biopharmaceutical Informatics Wenzhou-Kean University Zhejiang Province China Department of Electronics and Instrumentation Engineering St. Joseph's College of Engineering OMR Chennai 600119 Tamil Nadu India

The lung is one of the prime respiratory organs in human physiology, and its abnormality will severely disrupt the respiratory system. Lung Nodule (LN) is one of the abnormalities, and early screening and treatment are necessary to reduce its harshness. The proposed work aims to implement the Convolutional-Neural-Network (CNN) segmentation methodology to extract the LN in various lung CT slices, such as axial, coronal, and sagittal planes. This work consists of the following phases; (i) Image collection and pre-processing, (ii) Ground-truth generation, (iii) CNN-supported segmentation, and (iv) Performance evaluation and validation. In this work, the merit of pre-trained CNN segmentation schemes is verified using (i) One-fold training and (ii) Two-fold training methods. The test images for this study are collected from The Cancer Imaging Archive (TCIA) database. The experimental investigation is executed using Python®, and the outcome of this study confirms that the VGG-SegNet helps to get better values of Jaccard (>88%), Dice (>93%), and Accuracy (>96%) compared to other CNN methods.

关键词： Lung nodule CT scan CNN segmentation VGG-SegNet Accuracy Detection

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Structured Codes of Graphs

arXiv

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arXiv 2022年

作者： Alon, Noga Gujgiczer, Anna Körner, János Milojević, Aleksa Simonyi, Gábor Department of Mathematics Princeton University PrincetonNJ08544 United States Schools of Mathematics and Computer Science Tel Aviv University Tel Aviv69978 Israel Department of Computer Science and Information Theory Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics MTA-BME Lendület Arithmetic Combinatorics Research Group Budapest Hungary Sapienza University of Rome Italy Department of Mathematics Princeton University PrincetonNJ08544 United States Alfréd Rényi Institute of Mathematics Budapest Hungary Department of Computer Science and Information Theory Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Hungary

We investigate the maximum size of graph families on a common vertex set of cardinality n such that the symmetric difference of the edge sets of any two members of the family satisfies some prescribed condition. We solve the problem completely for infinitely many values of n when the prescribed condition is connectivity or 2-connectivity, Hamiltonicity or the containment of a spanning star. We also investigate local conditions that can be certified by looking at only a subset of the vertex set. In these cases a capacity-type asymptotic invariant is defined and when the condition is to contain a certain subgraph this invariant is shown to be a simple function of the chromatic number of this required subgraph. This is proven using classical results from extremal graph theory. Several variants are considered and the paper ends with a collection of open *** Codes 05C35, 05C51, 05C70, 94B25 Copyright © 2022, The Authors. All rights reserved.

关键词： Graph theory

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