Bioinformatics and Deep Learning Approach to Discover Food-Derived Active Ingredients for Alzheimer’s Disease Therapy by Junyu Zhou, Chen Li, Yong Kwan Kim, Sunmin Park

“…In conclusion, our findings demonstrate the efficacy of combining bioinformatics with deep neural networks to expedite the discovery of previously unidentified food-derived active ingredients (NCs) for AD intervention.…”
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Protected areas do not outperform urban wastelands in supporting insect pollinators and pollination in central Germany by Panagiotis Theodorou, Wilhelm H.A. Osterman, Janna H. Mrozek, Bilyana S. Wild, Michael Beckmann, Julia Osterman, Robert J. Paxton

“…The Natura 2000 network is central to Europe's conservation efforts to address biodiversity decline, with ongoing plans to expand protected areas and restore habitats across the European Union. …”
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Investigating potential biomarkers associated with antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis using Mendelian randomization and transcriptomic analysis by Yujia Wang, Zhimin Chen, Kaiqi Huang, Keng Ye, Shiwei He, Yanfang Xu, Hong Chen

“…Machine learning algorithms, ROC curve analysis, and expression evaluation were employed to screen for biomarkers. Additionally, artificial neural networks (ANNs) were constructed, enrichment analysis and immune infiltration were performed, a molecular regulatory network was established, and potential drugs were predicted. …”
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Interictal suppression in patients with mesial temporal lobe epilepsy: A simultaneous PET/fMRI study by Jie Hu, Liwei Sun, Kun Guo, Bixiao Cui, Chenyang Yao, Jingjuan Wang, Hui Ouyang, Xu Zhang, Chunlin Li, Jie Lu

“…We also found that the regions within DMN play a critical role in the suppression of SOZs. The pattern of such suppressive network might also serve as potential features for the localization of SOZs. …”
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Cancer Stem Cell Signaling during Repopulation in Head and Neck Cancer by George D. Wilson, Bryan J. Thibodeau, Laura E. Fortier, Barbara L. Pruetz, Sandra Galoforo, Brian Marples, Andrew M. Baschnagel, Jan Akervall, Jiayi Huang

“…The largest network of genes that showed significant changes after irradiation was associated with CD44, NOTCH1, and MET. c-MET and ALDH1A3 staining correlated with the changes in gene expression. …”
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Le modèle SCAUP : Simulation multi-agents à partir de données de CApteurs Urbains pour la Pollution atmosphérique automobile by Justin Emery, Nicolas Marilleau, Nadège Martiny, Thomas Thévenin

“…The purpose of the proposed agent-based model is to simulate road traffic at the scale of a theoretical and controlled road network. In this paper, we present an overview of the sets of parameters, the overall simulation process and its analysis tests, in order to evaluate the SCAUP capacities to simulate a traffic flow pattern with two main input data: road network and traffic counting data.…”
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Data‐Driven Feature Decomposition Integrated Prediction Model for Dust Concentration in Open‐Pit Mines by Shuangshuang Xiao, Jin Liu, Qing Yang, Zhiguo Chang, Yonggui Zhang

“…Combining the characteristics of dust concentration data and the concept of multimodal information integration modeling, a support vector machine (SVM)‐long short‐term memory (LSTM) network was chosen to build a data feature‐driven dust concentration combination prediction model. …”
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Prognostic relevance and performance characteristics of serum IGFBP‐2 and PAPP‐A in women with breast cancer: a long‐term Danish cohort study by Ulrick Espelund, Andrew G. Renehan, Søren Cold, Claus Oxvig, Lee Lancashire, Zhenqiang Su, Allan Flyvbjerg, Jan Frystyk

“…We measured the same biomarkers in 531 noncancer individuals to assess multidimensional relationships (MDR), and evaluated additional prognostic models using survival artificial neural network (SANN) and survival support vector machines (SSVM), as these enhance capture of MDRs. …”
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Mask R-CNN aided fruit surface temperature monitoring algorithm with edge compute enabled internet of things system for automated apple heat stress management by Basavaraj R. Amogi, Rakesh Ranjan, Lav R. Khot

“…Therefore, aim of this study was to develop and field evaluate cultivar and color independent mask region-convolution neural network (R-CNN) aided fruit segmentation model and edge compute compatible FST estimation algorithm. …”
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Learning to Infer Weather States Using Partial Observations by Jie Chao, Baoxiang Pan, Quanliang Chen, Shangshang Yang, Jingnan Wang, Congyi Nai, Yue Zheng, Xichen Li, Huiling Yuan, Xi Chen, Bo Lu, Ziniu Xiao

“…This allows us to evaluate each observation's value in reducing pattern estimation uncertainty, and guide optimal observation network design by pinpointing the most informative sites. …”
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Differential gray matter correlates and machine learning prediction of abuse and internalizing psychopathology in adolescent females by Sara A. Heyn, Taylor J. Keding, Josh Cisler, Katie McLaughlin, Ryan J. Herringa

“…After extensive training, model tuning, and model evaluation, the neural networks performed above chance when predicting IP (63% accuracy) and abuse experiences (71% accuracy) at the level of the individual. …”
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Identification and validation of hub genes related to neutrophil extracellular traps-mediated cell damage and immune recruitment during abdominal aortic aneurysm by Chuanlong Lu, Heng Wang, Maolin Qiao, Runze Chang, Jinshan Chen, Lizheng Li, Keyi Fan, Sheng Yan, Ruijing Zhang, Honglin Dong

“…Following this, receiver operating characteristic curves were created to evaluate the diagnostic significance of these essential genes. …”
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Wide-field electromagnetic method for deep hot dry rock fracturing monitoring: penetrating thick low-resistivity overburden by Shiyin Gao, Shiyin Gao, Wubing Deng, Juncheng Wang, Juncheng Wang, Juncheng Wang, Juncheng Wang, Mingzuan Xu, Mingzuan Xu

“…Future work should focus on integrating WFEM with multi-physical data to further improve fracture network characterization.…”
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NeXtMD: a new generation of machine learning and deep learning stacked hybrid framework for accurate identification of anti-inflammatory peptides by Chengzhi Xie, Yijie Wei, Xinwei Luo, Huan Yang, Hongyan Lai, Fuying Dao, Juan Feng, Hao Lv

“…The first stage generates preliminary predictions using four distinct encoding strategies and ML classifiers, while the second stage employs a multi-branch residual network (ResNeXt) to refine prediction outputs. Benchmark evaluations demonstrate that NeXtMD outperforms current state-of-the-art methods on multiple performance metrics. …”
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Sensory Dysfunction in ALS and Other Motor Neuron Diseases: Clinical Relevance, Histopathology, Neurophysiology, and Insights from Neuroimaging by Jana Kleinerova, Rangariroyashe H. Chipika, Ee Ling Tan, Yana Yunusova, Véronique Marchand-Pauvert, Jan Kassubek, Pierre-Francois Pradat, Peter Bede

“…From an academic standpoint, sensory networks may be ideally suited to evaluate propagation patterns and the involvement of subcortical grey matter structures. …”
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Integrated multi-omics analysis identifies TPX2 as a potential prognostic and immunological biomarker in hepatocellular carcinoma by Hui Peng, Yong-peng Wei, Xin-bo Liu, Yu Wang, Jian-yong Yuan

“…Co-expression modules were identified via weighted gene co-expression network analysis (WGCNA), followed by GO and KEGG enrichment analyses. …”
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An AI explained systematic modular approach for enhanced Electricity Theft Detection for urbanized Smart Grid environment by Muhammad Ammar, Nadeem Javaid, Ali Arishi

“…Traditional detection systems often face challenges like severe data discrepancies, high class imbalance, and volatile consumption patterns, which hinder their ability to detect abnormal movements and limit system dependability. …”
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Toward AI-Driven Cough Sound Analysis for Respiratory Disease Diagnosis by Houda Benaliouche, Houda Hafi, Hakim Bendjenna, Zeyad Alshaikh

“…We methodically evaluate different model architectures, ranging from custom-built networks to pre-trained deep models, applying spectrogram or Mel-Frequency Cepstral Coefficients (MFCC) in transfer learning-based feature extraction, to determine which is the best approach in terms of accuracy, precision, recall, F1-score, and loss. …”
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Advanced artificial intelligence with federated learning framework for privacy-preserving cyberthreat detection in IoT-assisted sustainable smart cities by Mahmoud Ragab, Ehab Bahaudien Ashary, Bandar M. Alghamdi, Rania Aboalela, Naif Alsaadi, Louai A. Maghrabi, Khalid H. Allehaibi

“…Abstract With the fast growth of artificial intelligence (AI) and a novel generation of network technology, the Internet of Things (IoT) has become global. …”
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Expression characteristics, molecular mechanisms, and clinical significance of DICER1 in breast cancer by Xi Zhang, Long Yu, Cuizhi Geng

“…Weighted gene co-expression network analysis (WGCNA) was used to identify gene modules associated with the breast cancer phenotype, and gene set enrichment analysis (GSEA) was performed to explore their biological functions. …”
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