From Traditional Typing to Genomic Precision: Whole-Genome Sequencing of <i>Listeria monocytogenes</i> Isolated from Refrigerated Foods in Chile by Julio Parra-Flores, Beatriz Daza-Prieto, Pamela Chavarria, Miriam Troncoso, Anna Stöger, Guillermo Figueroa, Jetsi Mancilla-Rojano, Ariadnna Cruz-Córdova, Aleksandra Martinovic, Werner Ruppitsch

“…Whole-genome sequencing (WGS) enhances the investigation of foodborne outbreaks by enabling the tracking of pathogen sources and the prediction of genetic traits related to virulence, stress, and antimicrobial resistance, which benefit food safety management. …”
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Phytocompounds from Indonesia Medicinal Herbs as Potential Apelin Receptor Agonist for Heart Failure Therapy: An In-silico Approach by Muhamad Rizqy Fadhillah, Wawaimuli Arozal, Muhammad Habiburrahman, Somasundaram Arumugam, Heri Wibowo, Suci Widya Primadhani, Aryo Tedjo, Surya Dwira, Nurul Gusti Khatimah

“…This study investigates bioactive phytochemicals from ten Indonesian medicinal herbs using computer-aided drug design (CADD) to predict ligand-receptor interactions via molecular docking and bioactivity prediction through machine learning. …”
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Systems immunology integrates the complex endotypes of recessive dystrophic epidermolysis bullosa by Nell Hirt, Enzo Manchon, Qian Chen, Clara Delaroque, Aurelien Corneau, Patrice Hemon, Safaa Saker-Delye, Pauline Bataille, Jean-David Bouaziz, Emmanuelle Bourrat, Alain Hovnanian, Helene Le Buanec, Fawzi Aoudjit, Hicham El Costa, Nabila Jabrane-Ferrat, Reem Al-Daccak

“…Artificial intelligence prediction models and principal component analysis stress that RDEB is not solely confined to cutaneous issues but has complex systemic endotypes marked by immune dysregulation and hyperinflammation. …”
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Detection and classification of long terminal repeat sequences in plant LTR-retrotransposons and their analysis using explainable machine learning by Jakub Horvath, Pavel Jedlicka, Marie Kratka, Zdenek Kubat, Eduard Kejnovsky, Matej Lexa

“…Furthermore, this approach can be utilized for the classification and prediction of LTRs. Results We used machine learning methods suitable for DNA sequence classification and applied them to a large dataset of plant LTR retrotransposon sequences. …”
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Diagnostic Value of Fractional Exhaled Nitric Oxide and Small Airway Function in Differentiating Cough-Variant Asthma from Typical Asthma by Yanqi Wang, Lixuan Zhao, Fang Chen, Yufeng Guo, Hongxia Ma, Baofen Han, Jiang Yi, Xiaomei Kong

“…The combination of FeNO and FEF25%, Fres, R5-R20, and X5 provided a significantly better prediction than either alone.…”
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Analysis of the mechanism of Zangjiangzhi capsule in the treatment of hyperlipidemia based on its ingredients identified by UHPLC-Q-Exactive-Orbitrap-MS by Changting He, Yuling Zhao, Yongchun Huang, Yudong Su, Shoude Zhang

“…Network pharmacology analysis was used to explore the mechanism of action of ZJZC in HLP treatment. The SwissTargetPrediction database was used to predict compound targets, and GeneCards, DisGeNet, OMIM, and DRUGBANK databases were used to identify HLP-related targets. …”
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Idiopathic pulmonary fibrosis is a risk factor for cardiovascular disease: potential role of KL-6 and systemic inflammation by Mohamed F. AbdelGhany, Waleed GamalEldin Khaleel, Asmaa Omar Ahmed, Ahmad BaheyElden Ahmed, Lamees M. Bakkar

“…Sensitivity 90.0%, specificity 94.6%, and accuracy 92.5% were associated with a cutoff value of KL-6 ≥ 299 for prediction of associated cardiovascular comorbidities among the studied IPF group. …”
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Surrogate-based model parameter optimization in simulations of the West African monsoon by M. Fischer, P. Knippertz, C. Proppe

“…The findings underscore the importance of considering uncertainties in MOO and the need for a holistic understanding of the WAM's dynamics to enhance prediction skills.</p>…”
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The role of Artificial Intelligence in detecting breast lesions using ultrasound by Daria Ziemińska, Karina Motolko, Rafał Burczyk, Konrad Duszyński, Elżbieta Tokarczyk, Martyna Michalska, Adam Łabuda

“…AI aids BI-RADS lesion classification, ultrasound lesion detection, lymph node analysis, and treatment response prediction, often surpassing radiologists. Its future relies on real-world validation, improved outcomes, and clinical integration. …”
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Adaptive cognitive control in 4 to 7-year-old children and potential effects of school-based yoga-mindfulness interventions: an exploratory study in Italy by Lisa Toffoli, Giulia Stefanelli, Giulia Manca, Fiorella Del Popolo Cristaldi, Gian Marco Duma, Michele Guidi, Francesca Incagli, Luca Sbernini, Luca Sbernini, Vincenza Tarantino, Giovanni Mento, Giovanni Mento

“…We utilized the Dynamic Temporal Prediction (DTP) task and a modified version of the Flanker task to assess the effect of context predictability on motor preparation/inhibition and interference control, respectively. …”
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HIDRA3: a deep-learning model for multipoint ensemble sea level forecasting in the presence of tide gauge sensor failures by M. Rus, M. Rus, H. Mihanović, M. Ličer, M. Ličer, M. Kristan

“…The new architecture brings several benefits: (i) it improves training at locations with scarce historical SSH data, (ii) it enables predictions even at locations with sensor failures, and (iii) it reliably estimates prediction uncertainties. …”
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Vis/NIR Spectroscopy and Vis/NIR Hyperspectral Imaging for Non-Destructive Monitoring of Apricot Fruit Internal Quality with Machine Learning by Tiziana Amoriello, Roberto Ciorba, Gaia Ruggiero, Francesca Masciola, Daniela Scutaru, Roberto Ciccoritti

“…In recent years, machine learning techniques, such as artificial neural networks (ANNs), have been successfully applied to more efficiently extract valuable information from spectral data and to accurately predict quality traits. In this study, prediction models were developed based on a multilayer perceptron artificial neural network (ANN-MLP) combined with the Levenberg–Marquardt learning algorithm. …”
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Empirical Models of foF2 and hmF2 Reconstituted by Global Ionosonde and Reanalysis Data and COSMIC Observations by Fuqing Huang, Haibing Ruan, Jiuhou Lei, Jiahao Zhong, Xinan Yue, Guozhu Li, Yiding Chen, Jianhui He, Na Li, Xiaoli Luan, Chao Xiong, Xiankang Dou

“…The USTC models are validated against the IRI CCIR model prediction. The comparison results revealed that the empirical foF2 model performs better in capturing the foF2 variations than the IRI CCIR model, which can overcome the underestimation of the IRI CCIR model at low latitudes. …”
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Electroencephalogram biomarkers as predictors of mortality and functional recovery in patients with severe traumatic brain injury: Protocol study by Walter Gomes da Silva Filho, Layza Julhia do Nascimento Moura, Arthur Barcelos Massariol Nascimento, Gabrielle Cristina Tessmann, Fabricia Silva Miranda, Vitória Caroline Reinoso de Almeida, Bárbara Vargens Broedel, Miller Lucas de Faria, Fernando Zanela da Silva Arêas

“…This protocol assesses the potential of quantitative electroencephalogram (EEG) biomarkers, associated with inflammatory indicators, to predict mortality and functional recovery in patients with severe TBI. …”
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Association of neutrophil-to-lymphocyte ratio with severe abdominal aortic calcification: new evidence from the United States by Hao Deng, Mengmeng Sun, Zhentong Zhao, Kun Fan, Zizhang Zhao, Yifan Chi, Wei Sheng

“…BackgroundAbdominal aortic calcification (AAC), an early indicator of abdominal aortic wall atherosclerosis, is a marker of subclinical atherosclerosis and a predictive factor for vascular-associated morbidity and mortality. …”
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Heatstroke characteristics and meteorological conditions in Hefei, China: thresholds and driving factors by Xueliang Deng, Liang Zhao, Changchun Xiao, Rui Dai, Qianqian Xu, Yeqing Yao, Caimeng Liang, Lei Yao, Dongyan He

“…Conclusions A meteorological threshold system had been established to forecast heatstroke occurrence in a short-term time, and a key climate driving factor of heatstroke was found for long-term heatstroke prediction in Hefei. These findings could facilitate the disease control department to take preventive and control measures to reduce the impact of heatstroke on human health and society.…”
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Cetacean feeding modelling using machine learning: A case study of the Central-Eastern Mediterranean Sea by Carla Cherubini, Giulia Cipriano, Leonardo Saccotelli, Giovanni Dimauro, Giovanni Coppini, Roberto Carlucci, Carmelo Fanizza, Rosalia Maglietta

“…These differences in predictive performance might reflect the distinct trophic niches of the studied odontocetes. …”
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Potential Value of Circular RNA circTBC1D4 in Gastrointestinal Stromal Tumors by null Chunyan-Zou, null Yanpeng-He, null Changshun-Xie, null Fulai-Gao, null Xiaoli-Xie, null Xiukun-Chai, null Chenxi-He, null Dongqiang-Zhao

“…Moreover, we discovered a new molecular landmarker for the prediction, diagnosis, and therapy of patients.…”
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Hirudo extract ameliorates proliferative vitreoretinopathy by promoting autophagy and attenuating the THBS2/PI3K/Akt pathway by Hui Huang, Qun Huang, Jing Wang, Wanjie Wang, Yanlin Zheng

“…The targets and pathways of the active compounds of Hirudo against PVR were predicted via a network pharmacology technique. ARPE-19 cells were treated with several doses of Hirudo extract, that did or did not contain TGF-β2 (10 ng/mL). …”
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Analysis of the Influence of Upper Protective Layer Mining on the Effect of Pressure Relief and Protection of Coal and Rock Masses between the Lower Overburden Layers by Jiaxin Dang, Min Tu, Xiangyang Zhang, Qingwei Bu

“…Effective theoretical calculation methods in the current studies on the prediction of pressure relief protection effect of interbed coal and rock masses and their distribution laws are lacking. …”
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