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Comparative studies on modeling and optimization of fermentation process conditions for fungal asparaginase production using artificial intelligence and machine learning techniques

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Preparative Biochemistry and biotechnology 2025年第1期55卷 93-99页

作者： Baskar, Gurunathan Sivakumar, Rajendran Kadry, Seifedine Dong, Cheng-Di Singhania, Reeta Rani Praveenkumar, Ramanujam Raja Sathendra, Elumalai Department of Biotechnology St. Joseph’s College of Engineering Chennai India School of Engineering Lebanese American University Byblos Lebanon Department of Electronics and Instrumentation Engineering St. Joseph’s College of Engineering Chennai India School of Engineering SIMATS Chennai India Department of Applied Data Science Noroff University College Kristiansand Norway Institute of Aquatic Science and Technology College of Hydrosphere National Kaohsiung University of Science and Technology Kaohsiung City Taiwan Department of Marine Environmental Engineering National Kaohsiung University of Science and Technology Kaohsiung City Taiwan Centre for Energy and Environmental Sustainability Uttar Pradesh Lucknow India Department of Biotechnology Arunai Engineering College Tiruvannamalai India

The L-asparaginase is commercial enzyme used as chemotherapeutic agent in cancer treatment and food processing agent in backed and fried food industries. In the present research work, the artificial intelligence and machine learning techniques were employed for modeling and optimization of fermentation process conditions for enhanced production of L-asparaginase by submerged fermentation of Aspergillus terreus. The experimental L-asparaginase activity obtained using central composite experiment design was used for optimization. The Random Forest algorithms machine learning techniques was found best based on the analysis of regression coefficient of ANN model and metric score values of machine learning algorithms. The experimental L-asparaginase activity of 41.58 IU/mL was obtained at the Random Forest algorithm predicted fermentation process conditions of temperature 31 °C, initial pH 6.3, inoculum size 2% (v/v), agitation rate 150 rpm and fermentation time 66 h. © 2024 Taylor & Francis Group, LLC.

关键词： Artificial neural network asparaginase fermentation process conditions machine learning techniques optimization statistical methods

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Dimensionality and dynamics for next-generation artificial neural networks

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Patterns 2025年

作者： Wang, Ge Fan, Feng-Lei Department of Biomedical Engineering Department of Electrical Computer and Systems Engineering Department of Computer Science Center for Computational Innovations Biomedical Imaging Center Center for Biotechnology and Interdisciplinary Studies Rensselaer Polytechnic Institute TroyNY United States Department of Data Science City University of Hong Kong Kowloon Hong Kong

The recent awarding of the Nobel Prize in Physics to Geoffrey E. Hinton and John J. Hopfield highlights their profound impact on artificial neural networks. In this perspective, we explore how their foundational insights can drive the advancement of next-generation artificial intelligence (AI) models. We propose expanding beyond conventional architectures by introducing dimensionality through intra-layer links and dynamics via feedback loops. Network height and additional dimensions, alongside traditional width and depth, enhance learning capabilities, while entangled loops across scales induce emergent behaviors akin to phase transitions in physics. We discuss how these principles extend beyond transformers, fostering a new paradigm of intelligence inspired by physics-driven models and biological cognition mechanisms. © 2025 The Author(s)

关键词： Neural network models

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Physics-Inspired Generative Models in Medical Imaging

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Annual review of biomedical engineering 2025年第1期27卷 499-525页

作者： Hein, Dennis Bozorgpour, Afshin Merhof, Dorit Wang, Ge Department of Physics KTH Royal Institute of Technology Stockholm Sweden Karolinska University Hospital Stockholm Sweden Faculty of Informatics and Data Science University of Regensburg Regensburg Germany Department of Biomedical Engineering School of Engineering Biomedical Imaging Center Center for Biotechnology and Interdisciplinary Studies Rensselaer Polytechnic Institute Troy New York USA

Physics-inspired generative models (GMs), in particular diffusion models and Poisson flow models, enhance Bayesian methods and promise great utility in medical imaging. This review examines the transformative role of such generative methods. First, a variety of physics-inspired GMs, including denoising diffusion probabilistic models, score-based diffusion models, and Poisson flow generative models (including PFGM++), are revisited, with an emphasis on their accuracy, robustness and acceleration. Then, major applications of physics-inspired GMs in medical imaging are presented, comprising image reconstruction, image generation, and image analysis. Finally, future research directions are brainstormed, including unification of physics-inspired GMs, integration with vision-language models, and potential novel applications of GMs. Since the development of generative methods has been rapid, it is hoped that this review will give peers and learners a timely snapshot of this new family of physics-driven GMs and help capitalize their enormous potential for medical imaging.

关键词： Bayesian theorem consistency model diffusion model image analysis image reconstruction image/data synthesis medical imaging PFGM++ physics-inspired generative models Poisson flow generative model

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Genomic insights into novel extremotolerant bacteria isolated from the NASA Phoenix mission spacecraft assembly cleanrooms

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Microbiome 2025年第1期13卷 1-27页

作者： Schultz, Júnia Jamil, Tahira Sengupta, Pratyay Sivabalan, Shobhan Karthick Muthamilselvi Rawat, Anamika Patel, Niketan Krishnamurthi, Srinivasan Alam, Intikhab Singh, Nitin K. Raman, Karthik Rosado, Alexandre Soares Venkateswaran, Kasthuri Biological and Environmental Science and Engineering Division King Abdullah University of Science and Technology Thuwal Makkah 23955 Saudi Arabia Department of Biotechnology Bhupat and Jyoti Mehta School of Biosciences Indian Institute of Technology Madras Tamil Nadu Chennai 600036 India Center for Integrative Biology and Systems Medicine (IBSE) Indian Institute of Technology Madras Tamil Nadu Chennai 600036 India Robert Bosch Centre for Data Science and Artificial Intelligence (RBCDSAI) Indian Institute of Technology Madras Tamil Nadu Chennai 600036 India Microbial Type Culture Collection and Gene Bank (MTCC) Institute of Microbial Technology Chandigarh 160036 India NASA Jet Propulsion Laboratory California Institute of Technology Pasadena CA United States Department of Data Science and AI Wadhwani School of Data Science and AI Indian Institute of Technology Madras Tamil Nadu Chennai 600036 India Bioscience Program Biological and Environmental Science and Engineering (BESE) Division King Abdullah University of Science and Technology (KAUST) Thuwal Makkah 23955 Saudi Arabia

Background: Human-designed oligotrophic environments, such as cleanrooms, harbor unique microbial communities shaped by selective pressures like temperature, humidity, nutrient availability, cleaning reagents, and radiation. Maintaining the biological cleanliness of NASA’s mission-associated cleanrooms, where spacecraft are assembled and tested, is critical for planetary protection. Even with stringent controls such as regulated airflow, temperature management, and rigorous cleaning, resilient microorganisms can persist in these environments, posing potential risks for space missions. Results: During the Phoenix spacecraft mission, genomes of 215 bacterial isolates were sequenced and based on overall genome-related indices, 53 strains belonging to 26 novel species were recognized. Metagenome mapping indicated less than 0.1% of the reads associated with novel species, suggesting their rarity. Genes responsible for biofilm formation, such as BolA (COG0271) and CvpA (COG1286), were predominantly found in proteobacterial members but were absent in other non-spore-forming and spore-forming species. YqgA (COG1811) was detected in most spore-forming members but was absent in Paenibacillus and non-spore-forming species. Cell fate regulators, COG1774 (YaaT), COG3679 (YlbF, YheA/YmcA), and COG4550 (YmcA, YheA/YmcA), controlling sporulation, competence, and biofilm development processes, were observed in all spore-formers but were missing in non-spore-forming species. COG analyses further revealed resistance-conferring proteins in all spore-formers (n = 13 species) and eight actinobacterial species, responsible for enhanced membrane transport and signaling under radiation (COG3253), transcription regulation under radiation stress (COG1108), and DNA repair and stress responses (COG2318). Additional functional analysis revealed that Agrococcus phoenicis, Microbacterium canaveralium, and Microbacterium jpeli contained biosynthetic gene clusters (BGCs) for ε-poly-L-lysine, benefic

关键词： BGCs Cleanroom Extreme environment Novel species Phoenix mission Phylogenomics

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Cryptotanshinone Suppresses the STAT3/BCL-2 Pathway to Provoke Human Bladder Urothelial Carcinoma Cell Death

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Environmental Toxicology 2025年第4期40卷 624-635页

作者： Tung, Min-Che Chang, Ge-Man Dai, Wen-Chyi Hsu, Chen-Hsuan Chang, Hsiang-Chun Yang, Wei-Ting Ho, Yann-Jen Lu, Chien-Hsing Chen, Yi-Hsin Chang, Chia-Che Division of Urology Department of Surgery Tungs' Taichung MetroHarbor Hospital Taichung Taiwan Graduate Institute of Biomedical Sciences National Chung Hsing University Taichung Taiwan Doctoral Program in Biotechnology Industrial Innovation and Management National Chung Hsing University Taichung Taiwan Department of Life Sciences National Chung Hsing University Taichung Taiwan Department of Obstetrics and Gynecology Taichung Veterans General Hospital Taichung Taiwan Doctoral Program in Translational Medicine National Chung Hsing University Taichung Taiwan Department of Nephrology Taichung Tzu Chi Hospital Buddhist Tzu chi Medical Foundation Taichung Taiwan School of Medicine Tzu Chi University Hualein Taiwan Department of Artificial Intelligence and Data Science National Chung Hsing University Taichung Taiwan Master Program in Precision Health Rong Hsing Research Center for Translational Medicine The iEGG and Animal Biotechnology Research Center National Chung Hsing University Taichung Taiwan Department of Medical Laboratory Science and Biotechnology Asia University Taichung Taiwan Department of Medical Research China Medical University Hospital Taichung Taiwan

Bladder cancer is one of the most common human malignancies worldwide. Aberrant activation of signal transducer and activator of transcription 3 (STAT3) is crucial to driving malignant progression and predicting poor prognosis of multiple human cancers, including bladder cancer, making STAT3 a promising target of cancer therapeutics. Cryptotanshinone (CTS) is an anticancer ingredient of Danshen (Salvia miltiorrhiza), a top-graded Chinese medicinal herb. However, whether CTS targets STAT3 to exert its cytotoxic effect on human bladder cancer remains unknown. Herein, we demonstrated that CTS is cytotoxic to multiple human urinary bladder transitional cell carcinoma (TCC) cell lines while sparing normal human urothelial cells. CTS provoked apoptosis-dependent bladder TCC cytotoxicity, as apoptosis blockage by z-VAD-fmk markedly rescued the clonogenicity of CTS-treated cells. Besides, CTS was found to suppress constitutive and interleukin 6-inducible activation of STAT3, evidenced by the downregulation of STAT3 tyrosine 705 phosphorylation and BCL2, a recognized STAT3 transcriptional target. Notably, ectopic expression of a dominant-active STAT3 mutant (STAT3-C) or BCL-2 alleviated CTS-induced apoptosis and clonogenicity inhibition, thus confirming STAT3 blockade as a pivotal mechanism of CTS's cytotoxic action on bladder TCC cells. Lastly, immunoblotting revealed that CTS lowered the levels of active JAK2, an upstream kinase that mediates STAT3 tyrosine 705 phosphorylation. Altogether, we conclude that the blockade of the JAK2/STAT3/BCL-2 antiapoptotic signaling axis is a vital mechanism whereby CTS provokes bladder cancer cytotoxicity. The current evidence implicates CTS's potential to be translated into a bladder cancer therapeutic agent. © 2024 Wiley Periodicals LLC.

关键词： Cell death

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Translation dysregulation in cancer as a source for targetable antigens

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Cancer Cell 2025年第5期43卷 823-840.e18,20页

作者： Weller, Chen Bartok, Osnat McGinnis, Christopher S. Palashati, Heyilimu Chang, Tian-Gen Malko, Dmitry Shmueli, Merav D. Nagao, Asuteka Hayoun, Deborah Murayama, Ayaka Sakaguchi, Yuriko Poulis, Panagiotis Khatib, Aseel Erlanger Avigdor, Bracha Gordon, Sagi Cohen Shvefel, Sapir Zemanek, Marie J. Nielsen, Morten M. Boura-Halfon, Sigalit Sagie, Shira Gumpert, Nofar Yang, Weiwen Alexeev, Dmitry Kyriakidou, Pelgia Yao, Winnie Zerbib, Mirie Greenberg, Polina Benedek, Gil Litchfield, Kevin Petrovich-Kopitman, Ekaterina Nagler, Adi Oren, Roni Ben-Dor, Shifra Levin, Yishai Pilpel, Yitzhak Rodnina, Marina Cox, Jürgen Merbl, Yifat Satpathy, Ansuman T. Carmi, Yaron Erhard, Florian Suzuki, Tsutomu Buskirk, Allen R. Olweus, Johanna Ruppin, Eytan Schlosser, Andreas Samuels, Yardena Department of Molecular Cell Biology Weizmann Institute of Science Rehovot 7610001 Israel Department of Pathology Stanford University Stanford 94305 CA United States Parker Institute for Cancer Immunotherapy San Francisco 94129 CA United States Department of Cancer Immunology Institute for Cancer Research Oslo University Hospital Oslo 0379 Norway Precision Immunotherapy Alliance University of Oslo Oslo Norway Cancer Data Science Laboratory Center for Cancer Research National Cancer Institute National Institutes of Health Bethesda 20892 MD United States Department of Systems Immunology Weizmann Institute of Science Rehovot 7610001 Israel Department of Chemistry and Biotechnology of Engineering The University of Tokyo Tokyo 113-8656 Japan Department of Physical Biochemistry Max Planck Institute for Multidisciplinary Sciences Göttingen 37077 Germany Department of Pathology Sackler School of Medicine Tel Aviv University Tel Aviv 69978 Israel Department of Immunology and Regenerative Biology Weizmann Institute of Science Rehovot 7610001 Israel Computational Systems Biochemistry Research Group Max-Planck Institute of Biochemistry Martinsried 82152 Germany Department of Veterinary Resources Weizmann Institute of Science Rehovot 7610001 Israel Tissue Typing and Immunogenetics Unit Hadassah Hebrew University Hospital Jerusalem 9112102 Israel CRUK Lung Cancer Centre of Excellence University College London Cancer Institute London WC1E 6DD United Kingdom Tumour Immunogenomics and Immunosurveillance Laboratory University College London Cancer Institute London WC1E 6DD United Kingdom Department of Life Science Core Facilities Weizmann Institute of Science Rehovot 7610001 Israel Bioinformatics Unit Department of Life Sciences Core Facilities Weizmann Institute of Science Rehovot 7610001 Israel de Botton Institute for Protein Profiling the Nancy and Stephen Grand Israel National Center for Personalized Medicine Weizmann Institute of Science Rehovot

Aberrant peptides presented by major histocompatibility complex (MHC) molecules are targets for tumor eradication, as these peptides can be recognized as foreign by T cells. Protein synthesis in malignant cells is dysregulated, which may result in the generation and presentation of aberrant peptides that can be exploited for T cell-based therapies. To investigate the role of translational dysregulation in immunological tumor control, we disrupt translation fidelity by deleting tRNA wybutosine (yW)-synthesizing protein 2 (TYW2) in tumor cells and characterize the downstream impact on translation fidelity and immunogenicity using immunopeptidomics, genomics, and functional assays. These analyses reveal that TYW2 knockout (KO) cells generate immunogenic out-of-frame peptides. Furthermore, Tyw2 loss increases tumor immunogenicity and leads to anti-programmed cell death 1 (PD-1) checkpoint blockade sensitivity in vivo. Importantly, reduced TYW2 expression is associated with increased response to checkpoint blockade in patients. Together, we demonstrate that defects in translation fidelity drive tumor immunogenicity and may be leveraged for cancer immunotherapy. © 2025 The Author(s)

关键词： cancer immunopeptidome immune checkpoint blockade neoantigens non-canonical peptides translation fidelity

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Next-Gen Home Automation: Sensor-Based Connectivity and Appliance Control 1st

Next-Gen Home Automation: Sensor-Based Connectivity and Appl...

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1st International Research Conference on Computing Technologies for Sustainable Development, IRCCTSD 2024

作者： Nithiyaraj, E. Emerson Srinivass, S. Mukilan, K. Muthukumar, M. Nanmaran, R. Srimathi, S. Department of Artificial Intelligence and Data Science Mepco Schlenk Engineering College Sivakasi India Department of ECE Ramco Institute of Technology Rajapalayam India Department of ECE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Department of Biotechnology Saveetha School of Engineering SIMATS Tamilnadu Chennai India

ISBN: (纸本)9783031823824

Internet of Things (IoT) integrated smart home automation systems use sensor networks and communication modules to extend home energy efficiency, security, and convenience. IoT transforms houses into intelligent environment that are remotely monitored and controlled from anywhere using communication technologies. In this paper, a NodeMCU microcontroller and a variety of sensors, such as a PIR for motion detection, a gas sensor for monitoring hazardous gases, a flame sensor for fire detection, a DHT11 for temperature and humidity sensing, as well as smart locks, lights and fans for environmental control, are used to develop and implement a smart home system. With a user-friendly smartphone interface, the suggested system enables residents to monitor and operate their home appliances remotely in real- time, improving security, comfort, and energy efficiency. This article intends to further the development of smart home technology by providing a thorough overview of system design, sensor integration, and functionality. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Smart homes

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CNN-Based Flank Predictor for Quadruped Animal Species

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IET Computer Vision 2025年第1期19卷

作者： Suessle, Vanessa Heurich, Marco Downs, Colleen T. Weinmann, Andreas Hergenroether, Elke Department of Computer Science University of Applied Sciences Darmstadt Darmstadt Germany School of Life Sciences University of KwaZulu-Natal Pietermaritzburg South Africa Algorithms for Computer Vision Imaging and Data Analysis Group University of Applied Sciences Darmstadt Darmstadt Germany Data Science Institute European University of Technology European Union Netherlands Department of National Park Monitoring and Animal Management Bavarian Forest National Park Grafenau Germany Department of Wildlife Ecology and Management Faculty of Environment and Natural Resources University of Freiburg Freiburg Germany Faculty of Applied Ecology Agricultural Sciences and Biotechnology University of Inland Norway Evenstad Norway

The bilateral asymmetry of flanks, where the sides of an animal with unique visual markings are independently patterned, complicates tasks such as individual identification. Automatically generating additional information on the visible side of the animal would improve the accuracy of individual identification. In this study, we used transfer learning on popular convolutional neural network (CNN) image classification architectures to train a flank predictor that predicted the visible flank of quadruped mammalian species in images. We automatically derived the data labels from existing datasets initially labelled for animal pose estimation. The developed models were evaluated across various scenarios involving unseen quadruped species in familiar and unfamiliar habitats. As a real-world scenario, we used a dataset of manually labelled Eurasian lynx (Lynx lynx) from camera traps in the Bavarian Forest National Park, Germany, to evaluate the model. The best model on data obtained in the field was trained on a MobileNetV2 architecture. It achieved an accuracy of 91.7% for the unseen/untrained species lynx in a complex unseen/untrained habitat with challenging light conditions. The developed flank predictor was designed to be embedded as a preprocessing step for automated analysis of camera trap datasets to enhance tasks such as individual identification. © 2025 The Author(s). IET Computer Vision published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.

关键词： Convolutional neural networks

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A Time-Driven UAV Deployment and Content Caching Approach for Multi-UAV-Enabled Consumer Electronics Network

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IEEE Transactions on Consumer Electronics 2025年

作者： Zhang, Jianshan Yang, Xu Ming, Rui Luo, Haibo Wang, Xiaoding Piran, Md. Jalil Minjiang University School of Computer and Big Data Fuzhou350108 China Fujian Normal University College of Computer and Cyber Security Fujian Provincial Key Laboratory of Network Security and Cryptology Fujian Fuzhou350117 China Chinese Academy of Tropical Agricultural Sciences National Key Laboratory for Tropical Crop Breeding Institute of Tropical Bioscience and Biotechnology Sanya Research Institute Hainan Sanya572024 China Sejong University Department of Computer Science and Engineering Seoul05006 Korea Republic of

To address the problem of high delay due to the explosive growth of mobile data traffic in consumer electronics network (CEN), in this paper, we investigate the multiple-unmanned aerial vehicle (UAV)-enabled CEN content caching problem, focusing on minimizing content access delay by jointly optimizing UAV deployment, ground user (GU) access, and content caching while satisfying other resource constraints. We propose an algorithm based on alternating optimization for the scenario where multiple UAVs and base station (BS) collaborate to provide caching services. The algorithm attains a sub-optimal solution with a convergence guarantee by iteratively solving the three sub-problems derived from the decomposition of the target problem. First, a convex difference-based algorithm solves the UAV deployment sub-problem. Second, a greedy-based algorithm is used to solve the content caching sub-problem. Then, a continuous convex approximation algorithm based on the penalty function is used to solve the user access sub-problem. Finally, the above procedure is repeated to obtain a sub-optimal solution to the target problem. The proposed joint optimization algorithm is shown to outperform the benchmark algorithms in terms of average content access delay and cache hit ratio, as evidenced by numerical results. © 1975-2011 IEEE.

关键词： Antennas

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Exploiting CotA laccase from Antarctic Bacillus sp. PAMC28748 for efficient mediator-assisted dye decolorization and ABTS regeneration

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Chemosphere 2025年 372卷 144137页

作者： Karmacharya, Jayram Shrestha, Prasansah Han, So-Ra Lee, Jun Hyuck Oh, Tae-Jin Department of Life Science and Biochemical Engineering SunMoon University Asan31460 Korea Republic of Genome-based Bio-IT Convergence Institute Asan31460 Korea Republic of Bio Big Data-based Chungnam Smart Clean Research Leader Training Program SunMoon University Asan31460 Korea Republic of Division of Life Sciences Korea Polar Research Institute Incheon21990 Korea Republic of Department of Pharmaceutical Engineering and Biotechnology SunMoon University Asan31460 Korea Republic of

Laccases are of particular interest in addressing environmental challenges, such as the degradation of triphenylmethane (TPM) dyes, including crystal violet (CV) and Coomassie Brilliant Blue (CBB), which are commonly used in SDS-PAGE for protein visualization. However, these dyes present significant environmental concerns due to their resistance to degradation, which makes their removal from industrial wastewater a major challenge. To address this, the current study investigates the potential of a novel CotA laccase derived from Bacillus sp. PAMC28748, an Antarctic bacterial isolate, for decolorizing these stubborn dyes. The CotA gene was successfully cloned and expressed, and the enzyme demonstrated optimal activity at pH 3 and 50 °C, which favors its maximum catalytic performance. The recombinant Bacillus sp. PAMC28748 rBCLac effectively decolorized CBB without additional mediators, whereas the degradation of CV required the use of the redox mediator ABTS. With ABTS, over 90 % decolorization was achieved at a 0.35 % concentration of CV after 240 min of incubation. Further investigation through molecular docking studies revealed that hydrogen bonding and hydrophobic interactions between the enzyme and the dye molecules are critical for effective degradation, highlighting the enzyme's specific interaction mechanisms. In addition to its catalytic effectiveness, the study also demonstrated the practical potential of the rBCLac system by recovering and reusing both ABTS and rBCLac through ultracentrifugation and acetone precipitation. The process maintained over 75 % efficiency across three cycles, despite a slight decline in enzyme activity, thus showcasing the system's sustainability and reusability. These findings collectively suggest that rBCLac, isolated from an extreme Antarctic environment, holds considerable promise as a candidate for the removal of industrial wastewater containing persistent dyes, with the added potential for cost-effective and sustainable wat

关键词： Hydrogen bonds

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