MetaboLabPy—An Open-Source Software Package for Metabolomics NMR Data Processing and Metabolic Tracer Data Analysis by Christian Ludwig

“…<b>Materials and Methods:</b> The software is implemented in Python and uses numerous Python toolboxes, such as numpy, scipy, pandas, etc. …”
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Total cardiolipin levels in gastric and colon cancer: evaluating the prognostic potential by Pavels Dimitrijevs, Ilona Freiliba, Andrejs Pčolkins, Marcis Leja, Pavel Arsenyan

“…Abstract Background Cardiolipin (CL) is a signature phospholipid of mitochondria that maintains the integrity of mitochondrial membrane and supports proper mitochondrial function. …”
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Factors associated with the presence and intensity of ongoing symptoms in Long COVID. by Niels Brinkman, Teun Teunis, Seung Choi, David Ring, W Michael Brode

“…This emphasizes the need for comprehensive, whole person treatment strategies that integrate evidence-based interventions to address the multifaceted nature of PASC.…”
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A cross-sectional study comparing machine learning and logistic regression techniques for predicting osteoporosis in a group at high risk of cardiovascular disease among old adults by Yuyi Peng, Chi Zhang, Bo Zhou

“…Methods We carried out a cross-sectional investigation of a high-risk group in cardiovascular patients. …”
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Classification of collagen remodeling in asthma using second-harmonic generation imaging, supervised machine learning and texture-based analysis by Natasha N. Kunchur, Joshua J. A. Poole, Jesse Levine, Tillie-Louise Hackett, Rebecca Thornhill, Rebecca Thornhill, Leila B. Mostaço-Guidolin

“…Traditional histological staining methods used to visualize the fibrotic response are poorly suited to capture the morphological traits of extracellular matrix (ECM) proteins in their native state, hindering our understanding of disease pathology. …”
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Disentangling the gut microbiota of Aldabra giant tortoises of different ages and environments by Douaa Zakaria, Camillo Sandri, Monica Modesto, Caterina Spiezio, Donatella Scarafile, Allen Cedras, Luigimaria Borruso, Paolo Manghi, Paolo Trevisi, Nicola Segata, Paola Mattarelli, Masanori Arita

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Investigating causal effects of income on health using two-sample Mendelian randomisation by Erik Igelström, Marcus R. Munafò, Ben M. Brumpton, Neil M. Davies, George Davey Smith, Pekka Martikainen, Desmond Campbell, Peter Craig, Jim Lewsey, S. Vittal Katikireddi

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Harnessing synergy of machine learning and nature-inspired optimization for enhanced compressive strength prediction in concrete by Abba Bashir, Esar Ahmad, Shashivendra Dulawat, Sani I. Abba

“…Given the nonlinear characteristics of supplementary cement material concrete (SCMC) mixtures, researchers are increasingly turning to machine learning methods. This study assesses nine machine learning models, integrating conventional AI algorithms, such as artificial neural network (ANN), support vector regression (SVR), and random forest (RF) with nature-inspired optimization techniques including chicken swarm optimization (CSO), moth flame optimization algorithm (MFO), and whale optimization algorithm (WOA). …”
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High-Accuracy HLA Type Inference from Whole-Genome Sequencing Data Using Population Reference Graphs. by Alexander T Dilthey, Pierre-Antoine Gourraud, Alexander J Mentzer, Nezih Cereb, Zamin Iqbal, Gil McVean

“…Genetic variation at the Human Leucocyte Antigen (HLA) genes is associated with many autoimmune and infectious disease phenotypes, is an important element of the immunological distinction between self and non-self, and shapes immune epitope repertoires. …”
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Factors that influence the delivery of chiropractic services to equity-deserving groups in Canada: a qualitative study by Nora Bakaa, Stephanie DiPelino, Danielle Southerst, Silvano Mior, Lisa Carlesso, Joy MacDermid, Luciana Macedo

“…Participants were recruited as part of a larger mixed-methods research study, where we conducted a cross-sectional survey assessing Canadian chiropractors' diversity and cultural competency. …”
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Toward Smart Condition Monitoring of Rotatory Machines: An Optimized Probabilistic Signal Reconstruction Methodology for Fault Prediction With Multisource Uncertainties by Xiaomo Jiang, Weijian Tang, Haixin Zhao, Xueyu Cheng

“…Three signal reconstruction methods, that is, Bayesian wavelet multiscale decomposition, probabilistic principal component analysis, and auto-associative kernel regression, were seamlessly integrated to address the noise, high dimensionality, and correlation in the sensed multivariate vibration data for accurate fault prediction. …”
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Fluorescence and Hyperspectral Sensors for Nondestructive Analysis and Prediction of Biophysical Compounds in the Green and Purple Leaves of <i>Tradescantia</i> Plants by Renan Falcioni, Roney Berti de Oliveira, Marcelo Luiz Chicati, Werner Camargos Antunes, José Alexandre M. Demattê, Marcos Rafael Nanni

“…These methods offer a good strategy for promoting sustainability in future agricultural practices across a broad range of plant species, supporting cell biology and material analyses.…”
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Plasma Metabolic Outliers Identified in Estonian Human Knockouts by Ketian Yu, Estonian Biobank Research Team, Karol Estrada, Tõnu Esko, Mart Kals, Tiit Nikopensius, Jaanika Kronberg, Urmo Võsa, Arthur Wuster, Lorenzo Bomba

“…<b>Background/Objectives:</b> Metabolomics, in combination with genetic data, is a powerful approach to study the biochemical consequences of genetic variation. We assessed the impact of human gene knockouts (KOs) on the metabolite levels of Estonia Biobank (EstBB) participants and integrated the results with electronic health record data. …”
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A Quantitative Monitoring Study of Environmental Factors Activating Caihua and Wooden Heritage Cracks in the Palace Museum, Beijing, China by Xiang He, Hong Li, Yilun Liu, Binhao Wu, Mengmeng Cai, Xiangna Han, Hong Guo

“…However, due to limited data acquisition methods and quantitative analysis models, the stability and risks of defects such as cracks during environmental changes remain unclear. …”
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Efficacy of the entomopathogenic fungus, Metarhizium anisopliae (Metsch.) Sorokin, against larvae of Hellula undalis, under laboratory conditions by Malyaj R. Prajapati, Ravi Shanker, Reetesh P. Singh, Rajendra Singh, Pankaj Kumar, Jitender Singh, Mahesh K. Bharti, Lokesh K. Gangwar

“…Area of study: The research focused on entomopathogenic fungi and particularly examined the impact of different concentrations of M. anisopliae spores on the mortality of H. undalis larvae under controlled conditions. Material and methods: Fourth instar larvae of H. undalis were exposed to different concentrations of M. anisopliae spores. …”
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AI-driven assessment of over-scanning in chest CT: A systematic review and meta-analysis by Mo’men Bani-Ahmad, Andrew England, Laura McLaughlin, Marwan Alshipli, Kholoud Alzyoud, Yasser H. Hadi, Mark McEntee

“…This review explores the role of artificial intelligence (AI) in addressing manual over-scanning in chest CT imaging. Methods: A systematic search of peer-reviewed publications was conducted between December 2015 and March 2025 in Embase, Scopus, Ovid, EBSCOhost, and PubMed. …”
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JWST Early Release Science Program TEMPLATES: Targeting Extremely Magnified Panchromatic Lensed Arcs and Their Extended Star Formation by Jane R. Rigby, Joaquin D. Vieira, Kedar A. Phadke, Taylor A. Hutchison, Brian Welch, Jared Cathey, Justin S. Spilker, Anthony H. Gonzalez, Prasanna Adhikari, M. Aravena, Matthew B. Bayliss, Jack E. Birkin, Emmy Bursk, Scott C. Chapman, Håkon Dahle, Lauren A. Elicker, Travis C. Fischer, Michael K. Florian, Michael D. Gladders, Christopher C. Hayward, Rose Hewald, Lily A. Kettler, Gourav Khullar, Seonwoo Kim, David R. Law, Guillaume Mahler, Sangeeta Malhotra, Eric J. Murphy, Desika Narayanan, Grace M. Olivier, James E. Rhoads, Keren Sharon, Manuel Solimano, Athish Thiruvengadam, David Vizgan, Nikolas Younker, TEMPLATES collaboration

“…The science goals of TEMPLATES are to demonstrate attenuation-robust diagnostics of star formation, map the distribution of star formation, compare the young and old stellar populations, and measure the physical conditions of star formation and their spatial variation across the galaxies. In addition, TEMPLATES has the technical goal to establish best practices for the integral field units within the NIRSpec and MIRI instruments, both in terms of observing strategy and in terms of data reduction. …”
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Echocardiographic Evaluation of Indices of Severity of Pulmonary Stenosis in Dogs: Reproducibility and Effects of General Anesthesia by Evan S. Ross, Lance C. Visser, Lalida Tantisuwat, Khursheed Mama, Brianna M. Potter, Brian A. Scansen

“…Animals Thirty‐nine dogs with PS. Methods Prospective cross‐sectional study. Five repeated echocardiograms were performed over 3 days. …”
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Looking into opportunities for maternity continuum of care improvement within the primary health care system in Northwest Ethiopia: primary health care-oriented research by Muhabaw Shumye Mihret, Kassahun Alemu, Debrework Tesgera Beshah, Lemma Derseh Gezie, Kerstin Erlandsson, Helena Lindgren

“…Abstract Background The maternity continuum of care (MCC) is an integral component of universal health coverage and a crucial strategy for reducing maternal and neonatal mortality. …”
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How to take action beyond ambulatory glucose profile: Latin American expert recommendations on CGM data interpretation by Luis Eduardo Calliari, Álvaro Contreras Sepúlveda, Nicolás Coronel-Restrepo, Laura Kabakian, Rodrigo N. Lamounier, Emma Picasso, Adrian Proietti, Alex Ramírez-Rincón, Alicia E. Yépez-Rodriguez

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