Inflammation-Mediated Regulation of MicroRNA Expression in Transplanted Pancreatic Islets by Valia Bravo-Egana, Samuel Rosero, Dagmar Klein, Zhijie Jiang, Nancy Vargas, Nicholas Tsinoremas, Marco Doni, Michele Podetta, Camillo Ricordi, R. Damaris Molano, Antonello Pileggi, Ricardo L. Pastori

“…The association between these miRNAs and mRNA target-predicting algorithms in genome-wide RNA studies of β-cell inflammation identified 238 potential miRNA gene targets. …”
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Using Neural Networks to Automate the Identification of Brightest Cluster Galaxies in Large Surveys by Patrick Janulewicz, Tracy M. A. Webb, Laurence Perreault-Levasseur

“…Training on simulations yields a squared correlation coefficient, R ^2 , between predictions and ground truth of R ^2  ≈ 0.94 when testing on simulations, which decreases to R ^2  ≈ 0.60 when testing on real data owing to discrepancies between data sets. …”
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Congo red fluorescence enhances digital pathology workflow in cardiac amyloidosis by Giorgio Cazzaniga, Monica De Gaspari, Vincenzo L’Imperio, Carlo Beretta, Angela Greco, Stefania Rizzo, Cristina Basso, Fabio Pagni

“…AI achieved an AUC-ROC of 0.87, 0.86 and 0.79 on the training, validation and test set, respectively, in tile-level classification for amyloidosis positivity and IoU and Dice scores indicating partial but reasonable overlap between predictions and ground truth in amyloid segmentation. …”
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Evaluation and Early Detection of Downy Mildew of Lettuce Using Hyperspectral Imagery by Songtao Ban, Minglu Tian, Dong Hu, Mengyuan Xu, Tao Yuan, Xiuguo Zheng, Linyi Li, Shiwei Wei

“…Moreover, regression models developed using Partial Least Squares (PLS), Random Forest (RF), and Convolutional Neural Network (CNN) algorithms demonstrated high accuracy and reliability in predicting DI, flavonoids, and anthocyanins, with the highest R² of 0.857, 0.910, and 0.963, respectively. …”
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Optimal Operation Strategy of Cascade Hydro-Wind-Solar-Pumped Storage Complementary System Considering Flexible Regulation Ability by XIA Jinlei, TANG Yijie, WANG Lingling, JIANG Chuanwen, GU Jiu

“…To overcome the limitations of traditional models such as low predictive accuracy and the subjective selection of long short-term memory (LSTM) hyperparameters, the particle swarm optimization (PSO) algorithm is used to optimize the parameters of LSTM and the optimized LSTM model is then used to forecast the output of wind and solar power. …”
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Biomarkers associated with cell-in-cell structure in kidney renal clear cell carcinoma based on transcriptome sequencing by Zehua Wang, Zhongxiao Zhang

“…Five hub genes (CDKN2A, VIM, TGFB1, CTSS, and CDC20) were biomarkers with area under the curve (AUC) values > 0.8, indicating high predictive performance. In vitro validation experiments demonstrated that the expressions of all five biomarkers in KIRC cells were elevated, and the knockdown of CTSS could inhibit the migration and invasion of KIRC cells. …”
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Scenario Modelling for Reproducing Investment Potential of Institutional Sectors in the Regions of the Siberian Federal District by I. V. Naumov, A. V. Trynov, A. O. Safonov

“…This model suggests systems of predictive scenarios for the reproduction and choosing the optimal one to achieve positive dynamics of the socio-economic development of the regions. …”
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Identification of exosome-related genes associated with prognosis and immune infiltration features in pancreatic cancer by Jie Wang, Ming Qing, Jie Gui, Pingyong Zhong, Hao Hua

“…An ERG_score was developed for forecasting overall survival and its predictive capacity was confirmed in PC cases. A precise nomogram was established to enhance the clinical utility of the ERG_score. …”
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Association of MTHFR Polymorphisms with H-Type Hypertension: A Systemic Review and Network Meta-Analysis of Diagnostic Test Accuracy by Yixuan Kong, Jinghui Zheng, Lijuan Li, Liying Lu, Jie Wang

“…The present result suggests that MTHFR C667T rs1801133 polymorphism is associated with H-HTN risk and may act as a promising predictive biomarker for H-HTN risk. However, further well-designed studies are warranted to confirm these results.…”
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Integrating taxonomic and phenotypic information through FISH-enhanced flow cytometry for microbial community dynamics analysis by Valérie Mattelin, Josefien Van Landuyt, Frederiek-Maarten Kerkhof, Yorick Minnebo, Nico Boon

“…As a reference to correlate increased distinction with the incorporation of taxonomic information, 16S rRNA gene sequencing was used. Finally, a predictive algorithm was trained to correctly classify samples in the differently treated groups. …”
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Psychometric properties of the German version of the Traumatic Grief Inventory-Self Report Plus (TGI-SR+) by Julia Treml, Viktoria Schmidt, Elmar Braehler, Matthias Morfeld, Anette Kersting

“…Despite the same name, both versions of PGD differ in symptom count, content, and diagnostic algorithm. A single instrument to screen for both PGD diagnoses is critical for bereavement research and care. …”
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Advancing Marine Surveillance: A Hybrid Approach of Physics Infused Neural Network for Enhanced Vessel Tracking Using Automatic Identification System Data by Tasmiah Haque, Md Asif Bin Syed, Srinjoy Das, Imtiaz Ahmed

“…This combination harnesses the physical laws governing vessel movements alongside data driven pattern mining, thereby enhancing the predictive accuracy of vessel locations. To assess the performance of standalone and hybrid models, various scenarios with different levels of complexity are generated. …”
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Modeling and optimization of culture media for recombinant Helicobacter pylori vaccine antigen HpaA by Runqing Tan, Song Zhou, Min Sun, Yu Liu, Xiumei Ni, Jin He, Gang Guo, Kaiyun Liu

“…The artificial neural network linked genetic algorithm (ANN-GA) model exhibited superior predictive accuracy, achieving a rHpaA yield of 0.61 g/L, which represents a 93.2% increase compared to the initial medium. …”
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Parameter Sensitivity Analysis and Irrigation Regime Optimization for Jujube Trees in Arid Regions Using the WOFOST Model by Shihao Sun, Yingjie Ma, Pengrui Ai, Ming Hong, Zhenghu Ma

“…In this regard, the use of crop models can compensate for time-consuming and costly field trials to screen for better irrigation regimes, but their predictive accuracy is often compromised by parameter uncertainty. …”
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Prognostic value of gene signatures and proliferation in lymph-node-negative breast cancer. by Kristin Jonsdottir, Jörg Assmus, Aida Slewa, Einar Gudlaugsson, Ivar Skaland, Jan P A Baak, Emiel A M Janssen

“…<h4>Introduction</h4>The overall survival rate is good for lymph-node-negative breast cancer patients, but they still suffer from serious over- and some undertreatments. Prognostic and predictive gene signatures for node-negative breast cancer have a high number of genes related to proliferation. …”
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The signature based on interleukin family and receptors identified IL19 and IL20RA in promoting nephroblastoma progression through STAT3 pathway by Chen Ding, Hongjie Gao, Liting Zhang, Zhiyi Lu, Bowen Zhang, Ding Li, Fengyin Sun

“…The prognostic model incorporating these five genes demonstrated robust predictive power in both training and validation cohorts. …”
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A Novel Multi-Scale Joint Approach for Estimating Lithium-ion Battery Model Parameters and SOC Considering Hysteresis Effect and Temperature by Xinhui Zhang, Wenyuan Bai, Shuyu Xie, Jiatong Wang, Danny Sutanto, Kashem M. Muttaqi

“…Experimental validation under DST, US06, and FUDS conditions demonstrates the effectiveness of the proposed method, achieving a maximum voltage prediction error of 0.0650 and a maximum SOC estimation error of 0.0092 across the full temperature range.…”
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Climatic suitability and potential distribution of earleaf acacia and its candidate biological control agent Trichilogaster sp by Sara S. MacDonald, Emily J. Le Falchier, Lindsay P. Campbell, Ryan Zonneveld, Carey R. Minteer

“…Both models exhibit high predictive accuracy, with AUC values above 0.9. This study emphasizes the need for continued monitoring and management of ELA and evaluates areas in Florida predicted to have suitable climatic conditions for Trichilogaster sp. nov. …”
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Prox-STA-LSTM: A Sparse Representation for the Attention-Based LSTM Networks for Industrial Soft Sensor Development by Yurun Wang, Yi Huang, Dongsheng Chen, Longyan Wang, Lingjian Ye, Feifan Shen

“…For deep learning based soft sensors, the spatiotemporal attention (STA)-LSTM is a newly emerged technique which provides efficient predictions for quality variables of industrial processes. …”
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Scientific planning of dynamic crops in complex agricultural landscapes based on adaptive optimization hybrid SA-GA method by Changlong Li, Zengye Su, Yudan Nie, Zhiyi Ye, Jinyi Li, Jing Wang, Zicong Yang, Xuxin Li, Weijian Zeng, Yanjian Chen

“…This framework is underpinned by a sophisticated model integrating advanced monitoring systems with a Hybrid Simulated Annealing Genetic Algorithm (H-SAGA), further enhanced by neural network-driven real-time predictions. …”
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