Medicare part D prescribing for direct oral anticoagulants in the United States: Cost, use and the "rubber effect". by Panayiotis D Ziakas, Irene S Kourbeti, Loukia S Poulou, Georgios S Vlachogeorgos, Eleftherios Mylonakis

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Systemic longitudinal immune profiling identifies proliferating Treg cells as predictors of immunotherapy benefit: biomarker analysis from the phase 3 CONTINUUM and DIPPER trials by Sai-Wei Huang, Wei Jiang, Sha Xu, Yuan Zhang, Juan Du, Ya-Qin Wang, Kun-Yu Yang, Ning Zhang, Fang Liu, Guo-Rong Zou, Feng Jin, Hai-Jun Wu, Yang-Ying Zhou, Xiao-Dong Zhu, Nian-Yong Chen, Cheng Xu, Han Qiao, Na Liu, Ying Sun, Jun Ma, Ye-Lin Liang, Xu Liu

“…Further validation through flow cytometry (n = 120) confirmed the predictive value of this Treg subset. Multiplex immunohistochemistry (n = 249) demonstrated that Ki67+ Tregs in tumors could predict immunotherapy benefit, with aPD1 improving EFS only in patients with low baseline levels of Ki67+ Tregs. …”
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All‐in‐one perovskite memristor with tunable photoresponsivity by Guan‐Hua Dun, Yuan‐Yuan Li, Hai‐Nan Zhang, Fan Wu, Xi‐Chao Tan, Ken Qin, Yi‐Chu He, Ze‐Shu Wang, Yu‐Hao Wang, Tian Lu, Shi‐Wei Tian, Dan Xie, Jia‐Li Peng, Xiang‐Shun Geng, Xiao‐Tong Zhao, Jia‐He Zhang, Yu‐Han Zhao, Xiaoyu Wu, Ning‐Qin Deng, Zheng‐Qiang Zhu, Yan Li, Xian‐Zhu Liu, Xing Wu, Weida Hu, Peng Zhou, Yang Chai, Mario Lanza, He Tian, Yi Yang, Tian‐Ling Ren

“…As a result, the memristor showed a large tunable ratio of 35.9 dB, while its photoresponsivity presented a maximum of 2.7 × 103 mA W−1 and a long‐term memory behavior with over 104 s, making it suitable for realizing all‐in‐one processing tasks. By mapping the algorithm parameters onto the photoresponsivity, we successfully performed both recognition and processing tasks based on the TPR memristor array. …”
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Remote Sensing in the 15 µm CO₂ Band: Key Concepts and Implications for the Heat Balance of Mesosphere and Thermosphere by Alexander Kutepov, Artem Feofilov, Ladislav Rezac, Konstantinos S. Kalogerakis

“…We investigated the algorithms and physical models currently applied to remote sensing of the mesosphere and lower thermosphere (MLT) using space-based observations of the CO₂ 15 µm emission. …”
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Design, Construction, and Evaluation of an Automatic Feeder Control System for Sugarcane Billet Planters by B. Abbasian, M. E. Khorasani Ferdavani, H. Zaki Dizaji

“…It delivered performance that matches manual control in terms of cane spillage reduction and planting quality, all while eliminating the need for an operator. …”
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Research Progress on Selective Depolymerization of Waste Plastics to High-Quality Liquid Fuels by Xinze LI, Zhicheng LUO, Rui XIAO

“…Economically, catalytic pyrolysis shows near-term viability with a break-even cost of 0.8 – 1.2 $/L for diesel-range fuels, while photocatalysis requires a 50% – 70% reduction in catalyst synthesis costs (e.g., replacing Pt with Fe-Ni sulfides). …”
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Immune Microenvironment Characterization and Machine Learning-Guided Identification of Diagnostic Biomarkers for Ulcerative Colitis by Zheng Q, Wang L, Zhang Y, Peng J, Hou J, Wang H, Ma Y, Tang P, Li Y, Li H, Chen Y, Li J, Chen Y

“…It employs machine learning algorithms to construct diagnostic models, including an optimal 8-gene model (GATA2, IL8, LAT, NOLC1, SMARCA5, SMC3, STX10, ZMIZ1), which demonstrates high predictive performance (AUC of 0.964 in training datasets and 0.884 in testing datasets). …”
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Representation Learning of Multi-Spectral Earth Observation Time Series and Evaluation for Crop Type Classification by Andrea González-Ramírez, Clement Atzberger, Deni Torres-Roman, Josué López

“…To develop accurate solutions for RS-based applications, often supervised shallow/deep learning algorithms are used. However, such approaches usually require fixed-length inputs and large labeled datasets. …”
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Skin microbiome-biophysical association: a first integrative approach to classifying Korean skin types and aging groups by Seyoung Mun, Seyoung Mun, Seyoung Mun, HyungWoo Jo, HyungWoo Jo, Young Mok Heo, Chaeyun Baek, Hye-Been Kim, Haeun Lee, Kyeongeui Yun, Kyeongeui Yun, Jinuk Jeong, Wooseok Lee, Dasom Jeon, Dasom Jeon, So Min Kang, So Min Kang, Seunghyun Kang, Young-Bong Choi, Young-Bong Choi, Sangjin Han, Gabriel Kim, Kung Ahn, Dong Hun Lee, Yong Ju Ahn, Dong-Geol Lee, Dong-Geol Lee, Kyudong Han, Kyudong Han, Kyudong Han, Kyudong Han

“…To further amplify our findings, we harnessed the potent capabilities of the CatBoost boosting algorithm and achieved a reliable framework for predicting skin types based on microbial composition with an impressive average accuracy of 0.96 AUC value. …”
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Guidelines for the management of emergencies and critical illness in pediatric and adult patients with sickle cell disease by Armand Mekontso Dessap, Stephane Dauger, Mehdi Khellaf, Maite Agbakou, Sophie Agut, François Angoulvant, Jean-Benoît Arlet, Cécile Aubron, Florent Baudin, Florence Boissier, Nicolas Bounaud, Pierre Catoire, Jérôme Cecchini, Djamila Chaiba, Anthony Chauvin, Richard Chocron, Benedicte Douay, Delphine Douillet, Narcisse Elenga, Olivier Flechelle, Ségolène Gendreau, Sybille Goddet, Jeremy Guenezan, Anoosha Habibi, Claire Heilbronner, Bérengère Koehl, Pierrick Le Borgne, Philippe Le Conte, Annick Legras, Michael Levy, Bernard Maitre, Mathieu Oberlin, Mehdi Oualha, Nicolas Peschanski, France Pirenne, Corinne Pondarre, Jérôme Rambaud, Keyvan Razazi, Geoffroy Rousseau, Aurélie Schirmann, Isabelle Thuret, Ruddy Valentino, Guillaume Voiriot, Barbara Villoing, Marion Grimaud, Sandrine Jean

“…The recommendations and therapeutic algorithms received strong agreement from the experts.…”
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Development and validation of a prognostic staging system for primary plasma cell leukemia by Mengru Tian, Gang An, Weijun Fu, Wenqiang Yan, Lu Li, Chunyan Sun, Zhenyu Li, Lijuan Chen, Aijun Liao, Guangxun Gao, Xiaoqi Qin, Mengyao Li, Chunrui Li, Hua Xue, Li Gao, Yi Wang, Aili He, Fan Zhou, Dongmei Guo, Yujun Dong, Zhihong Fang, Xiaoxia Chu, Jianqing Mi, Chengcheng Fu, Hui Zeng, Shuling Hou, Xiaotao Wang, Hua Wang, Yongqiang Wei, Xinyue Liang, Xingcheng Yi, Yue Sun, Lugui Qiu, Yun Dai, Fengyan Jin

“…Univariate and multivariate analyses were conducted to identify variables predicting overall survival (OS) to develop a staging system. …”
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Standardised packaging, minimum excise tax, and RYO focussed tax rise implications for UK tobacco pricing. by Rosemary Hiscock, Nicole H Augustin, J Robert Branston, Anna B Gilmore

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Smart CAR-T Nanosymbionts: archetypes and proto-models by Juan C. Baena, Juan C. Baena, Juan Sebastián Victoria, Juan Sebastián Victoria, Alejandro Toro-Pedroza, Alejandro Toro-Pedroza, Cristian C. Aragón, Cristian C. Aragón, Joshua Ortiz-Guzman, Joshua Ortiz-Guzman, Joshua Ortiz-Guzman, Juan Esteban Garcia-Robledo, Juan Esteban Garcia-Robledo, David Torres, Lady J. Rios-Serna, Lady J. Rios-Serna, Ludwig Albornoz, Joaquin D. Rosales, Joaquin D. Rosales, Carlos A. Cañas, Carlos A. Cañas, Carlos A. Cañas, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Felipe Ocampo Osorio, Felipe Ocampo Osorio, Felipe Ocampo Osorio, Tania Fleitas, Ivan Laponogov, Alexandre Loukanov, Alexandre Loukanov, Alexandre Loukanov, Kirill Veselkov, Kirill Veselkov

“…At the same time, artificial intelligence (AI), with its powerful algorithms for data analysis and predictive modeling, is transforming how we design, evaluate, and monitor advanced therapies, including the optimization of manufacturing processes. …”
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Feasibility of estimating the percentage of desert pavement using Tasseled Cap Transformation indices extracted from Landsat 8 images by farzaneh Fotouhi Firoozabad, Atefeh jebali

“…The obtained model can predict approximately 61% of surface pavement changes in the study area. …”
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Comprehensive Analysis of the Expression, Prognosis and Function of TRAF Family Proteins 
in NSCLC by Yixuan WANG, Qiang CHEN, Yaguang FAN, Shuqi TU, Yang ZHANG, Xiuwen ZHANG, Hongli PAN, Xuexia ZHOU, Xuebing LI

“…The correlation between the expression levels of TRAF family members and the tumor immune microenvironment was analyzed using the ESTIMATE algorithm based on RNA sequencing data from the TCGA database. …”
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Neural Network Constraints on the Cosmic-Ray Ionization Rate and Other Physical Conditions in NGC 253 with ALCHEMI Measurements of HCN and HNC by Erica Behrens, Jeffrey G. Mangum, Serena Viti, Jonathan Holdship, Ko-Yun Huang, Mathilde Bouvier, Joshua Butterworth, Cosima Eibensteiner, Nanase Harada, Sergio Martín, Kazushi Sakamoto, Sebastien Muller, Kunihiko Tanaka, Laura Colzi, Christian Henkel, David S. Meier, Víctor M. Rivilla, Paul P. van der Werf, ALMA Comprehensive High-resolution Extragalactic Molecular Inventory (ALCHEMI) collaboration

“…The neural network model successfully recovers UCLCHEM molecular abundances with ∼3% error and, when used with our Bayesian inference algorithm, increases the parameter-inference speed tenfold. …”
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LimeSoDa: A dataset collection for benchmarking of machine learning regressors in digital soil mapping by Jonas Schmidinger, Sebastian Vogel, Viacheslav Barkov, Anh-Duy Pham, Robin Gebbers, Hamed Tavakoli, Jose Correa, Tiago R. Tavares, Patrick Filippi, Edward J. Jones, Vojtech Lukas, Eric Boenecke, Joerg Ruehlmann, Ingmar Schroeter, Eckart Kramer, Stefan Paetzold, Masakazu Kodaira, Alexandre M.J.-C. Wadoux, Luca Bragazza, Konrad Metzger, Jingyi Huang, Domingos S.M. Valente, Jose L. Safanelli, Eduardo L. Bottega, Ricardo S.D. Dalmolin, Csilla Farkas, Alexander Steiger, Taciara Z. Horst, Leonardo Ramirez-Lopez, Thomas Scholten, Felix Stumpf, Pablo Rosso, Marcelo M. Costa, Rodrigo S. Zandonadi, Johanna Wetterlind, Martin Atzmueller

“…We demonstrated the use of LimeSoDa for benchmarking by comparing the predictive performance of four learning algorithms across all datasets. …”
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A selective CutMix approach improves generalizability of deep learning-based grading and risk assessment of prostate cancer by Sushant Patkar, Stephanie Harmon, Isabell Sesterhenn, Rosina Lis, Maria Merino, Denise Young, G. Thomas Brown, Kimberly M. Greenfield, John D. McGeeney, Sally Elsamanoudi, Shyh-Han Tan, Cara Schafer, Jiji Jiang, Gyorgy Petrovics, Albert Dobi, Francisco J. Rentas, Peter A. Pinto, Gregory T. Chesnut, Peter Choyke, Baris Turkbey, Joel T. Moncur

“…Our objective was to train an artificial intelligence (AI)-based algorithm to grade prostate cancer in specimens from patients who underwent radical prostatectomy (RP) and to assess the correlation of AI-estimated proportions of different Gleason patterns with biochemical recurrence-free survival (RFS), metastasis-free survival (MFS), and overall survival (OS). …”
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High-flow nasal cannula therapy versus continuous positive airway pressure for non-invasive respiratory support in paediatric critical care: the FIRST-ABC RCTs by Padmanabhan Ramnarayan, Alvin Richards-Belle, Karen Thomas, Laura Drikite, Zia Sadique, Silvia Moler Zapata, Robert Darnell, Carly Au, Peter J Davis, Izabella Orzechowska, Julie Lester, Kevin Morris, Millie Parke, Mark Peters, Sam Peters, Michelle Saull, Lyvonne Tume, Richard G Feltbower, Richard Grieve, Paul R Mouncey, David Harrison, Kathryn Rowan

“…To standardise treatment, clinical criteria and guidance for the initiation, maintenance and weaning of HFNC were provided in a trial algorithm. As per the algorithm, patients were assessed for response to the treatment, readiness to wean and for stopping HFNC at least twice per day. …”
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Using machine learning techniques to evaluate the impact of future climate change on wheat yields in Xinjiang, China by Xuehui Gao, Jian Liu, Haixia Lin, Tehseen Javed, Feihu Yin, Rui Chen, Yue Wen, Jinzhu Zhang, Kefan Yi, Zhenhua Wang

“…Additionally, the impacts of climate change scenarios on wheat yield were predicted using two emission scenarios (SSP45 and SSP85) from global climate models (GCMs) and machine learning (ML) algorithms. …”
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