Brodalumab for Moderate-to-Severe Psoriasis: A Comprehensive Review of Efficacy, Safety, and Clinical Positioning by Babaei N, Gill M, Cervantes M, Kim D, Yang S, Wu JJ

“…Despite being one of the most effective biologic agents available for psoriasis, brodalumab remains underutilized, highlighting the need for improved awareness of its potential clinical advantages. Further research is warranted to better define its role in treatment algorithms and to assess long-term outcomes in broader patient populations.Keywords: brodalumab, psoriasis, Il-17RA, psoriasis treatment…”
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MAST Kinases’ Function and Regulation: Insights from Structural Modeling and Disease Mutations by Michael C. Lemke, Nithin R. Avala, Michael T. Rader, Stefan R. Hargett, Daniel S. Lank, Brandon D. Seltzer, Thurl E. Harris

“…We set out to describe the origins and diversification of MAST kinases from a structural and bioinformatic perspective to inform future research directions. <b>Methods</b>: We investigated MAST-lineage kinases using database and sequence analysis. …”
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A deep learning model for predicting systemic lupus erythematosus-associated epitopes by Jiale He, Zixia Liu, Xiaopo Tang

“…The framework holds promise for broader applications in immunoinformatics and autoimmune disease research.…”
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A novel hexagonal PtPS monolayer for high anisotropic carrier mobility and potential for photocatalytic water splitting with pronounced optical absorption by Chunying Pu, Pan Zhang, Linxuan Chen, Xindong Pan, Dawei Zhou

“…Motivated by the attractive properties and potential applications of MPX materials, we identified a novel stable hexagonal structure of PtPS monolayer with the space group $$P\bar {3}m1$$ using particle swarm optimization algorithms in conjunction with first-principles calculations. …”
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The impact of a dedicated checklist on the quality of onsite management of critically buried avalanche victims in cardiac arrest in a Swiss helicopter emergency medical service by Maxime Trolliet, Mathieu Pasquier, Marc Blancher, Roland Albrecht, Alban Lovis, Hermann Brugger, Alexandre Kottmann

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Grid Search Based Hyperparameter-Tuned Deep Learning Model for Osteoporosis Diagnosis with Bi-Cubic Interpolation of X-Ray Images by Ruhul Amin, Md.Shamim Reza, Dewan Ahmed Muhtasim, Jungpil Shin, Md. Maniruzzaman, Md.Mahfujul Hasan

“…Even with the widespread use of deep learning (DL) and machine learning (ML) algorithms, the early diagnosis of osteoporosis patients can still be improved. …”
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Assessing the effects of therapeutic combinations on SARS-CoV-2 infected patient outcomes: A big data approach. by Hamidreza Moradi, H Timothy Bunnell, Bradley S Price, Maryam Khodaverdi, Michael T Vest, James Z Porterfield, Alfred J Anzalone, Susan L Santangelo, Wesley Kimble, Jeremy Harper, William B Hillegass, Sally L Hodder, National COVID Cohort Collaborative (N3C) Consortium

“…The approach also provides a framework for simultaneously evaluating multiple real-world therapeutic combinations in future research studies.…”
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Prediction of Shield Tunneling Attitude Based on WM-CTA Method by GAO Su, CHEN Cheng

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OCTNet: A Modified Multi-Scale Attention Feature Fusion Network with InceptionV3 for Retinal OCT Image Classification by Irshad Khalil, Asif Mehmood, Hyunchul Kim, Jungsuk Kim

“…Classification and identification of eye diseases using Optical Coherence Tomography (OCT) has been a challenging task and a trending research area in recent years. Accurate classification and detection of different diseases are crucial for effective care management and improving vision outcomes. …”
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PREDICTION INTERVALS IN MACHINE LEARNING: RESIDUAL BOOTSTRAP AND QUANTILE REGRESSION FOR CASH FLOW ANALYSIS by Wa Ode Rahmalia Safitri, Farit Mochamad Afendi, Budi Susetyo

“…Using transaction data from Bank Rakyat Indonesia (BRI), the research analyzes both office and e-channel transactions with different lag structures based on Granger Causality tests. …”
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358 Rare disease study identification (RDSI): A natural language processing assisted search and visualization tool for clinical studies of rare diseases by Michael Lin, Jennifer Weis, H M Abdul Fattah, Jungwei Fan

“…Objectives/Goals: Identifying and indexing rare disease studies is labor intensive, especially in research centers with a large number of trials. To address this gap, we applied natural language processing (NLP) and visualization techniques to develop an efficient pipeline and user-friendly web interface. …”
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Evaluation of the performance of ERA5, ERA5-Land and MERRA-2 reanalysis to estimate snow depth over a mountainous semi-arid region in Iran by Faezehsadat Majidi, Samaneh Sabetghadam, Maryam Gharaylou, Reza Rezaian

“…Additionally, the study highlights the challenges MERRA-2 faces in capturing snow depth in mountainous regions. Future research could benefit from integrating additional datasets and employing machine learning algorithms to improve snow depth assessments, as these approaches may reduce estimation uncertainties and enhance the understanding of snow dynamics across various regions, ultimately contributing to more reliable hydrological assessments.…”
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Explainable Ensemble Learning Model for Residual Strength Forecasting of Defective Pipelines by Hongbo Liu, Xiangzhao Meng

“…Traditional machine learning algorithms often fail to comprehensively account for the correlative factors influencing the residual strength of defective pipelines, exhibit limited capability in extracting nonlinear features from data, and suffer from insufficient predictive accuracy. …”
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Intelligent assessment of damage and prediction of seismic damage spectrum under the effect of Near-Fault earthquakes in Iran by R. Fazli, M. Shamekhi Amiri, H. Pahlavan

“…Subsequently, a mathematical model is developed by applying gene expression programming and genetic programming algorithms. The Park-Ang damage index is used to compute the seismic damage or damage spectra level. …”
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Markov model of representation of sensual images for the formation of the model of the outside world by A. A. Solodov

“…In this regard, one of the adequate mathematical tools are, apparently, probability-theoretic methods, in particular, the application of the theory of Markov processes. The method of research within the framework of the adopted model is the application of the theory of Markov processes developing at fixed points in time, i.e. …”
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Exploring the ceRNA network involving AGAP2-AS1 as a novel biomarker for preeclampsia by Fan Lu, Ni Zeng, Xiang Xiao, Xingxing Wang, Han Gong, Houkang Lei

“…Abstract Preeclampsia (PE) is an important research subject in obstetrics. Nevertheless, the underlying mechanisms of PE remain elusive. …”
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Innovative approach for gauge-based QPE in arid climates: comparing neural networks and traditional methods by Bayan Banimfreg, Ernesto Damiani, Vesta Afzali Gorooh, Duncan Axisa, Luca Delle Monache, Youssef Wehbe

“…Conclusion By effectively merging advanced neural network algorithms with conventional rainfall estimation methods, this study provides a robust framework for understanding and estimating precipitation in arid regions like the UAE. …”
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Economic approach for optimal allocation of irrigation water in water-scarce region by Xueliang Zhang, Li Ren, Jianshi Zhao

“…Optimizing irrigation water allocation is critical for maximizing grain yields in water-scarce regions. Traditional algorithms face challenges such as lack of interpretable criteria, the curse of dimensionality, and instability. …”
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The application of statistical methods to assess economic assets by D. V. Dianov

“…The application of mathematical-statistical apparatus, therefore, is an objective necessity for obtaining general indicators of the size of the national wealth.In conclusion, we can mention about the methodical approaches, the building of model algorithms application of statistical methods in solving scientific and practical problems, depending on the identification belonging of the valued objects. …”
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Data-driven EV charging infrastructure with uncertainty based on a spatial–temporal flow-driven (STFD) models considering batteries by Talal Alharbi, Ahmed Abdalrahman, Mostafa H. Mostafa

“…The developed mathematical frameworks and algorithms facilitate the optimal sizing and siting of both EV charging stations and ESS. …”
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