Review
Food Science & Technology
Dragan Milenkovic, Frederic Capel, Lydie Combaret, Blandine Comte, Dominique Dardevet, Bertrand Evrard, Christelle Guillet, Laurent-Emmanuel Monfoulet, Alexandre Pinel, Sergio Polakof, Estelle Pujos-Guillot, Didier Remond, Yohann Wittrant, Isabelle Savary-Auzeloux
Summary: Impairment of gut function is a mechanism for the decline in health status in the elderly, involving declines in digestive physiology, metabolism, and immune status. This is associated with changes in the composition and function of the gut microbiota. These alterations can be targeted through nutritional strategies to prevent or delay the occurrence of age-related pathologies.
CRITICAL REVIEWS IN FOOD SCIENCE AND NUTRITION
(2022)
Article
Nutrition & Dietetics
Elaine A. Yu, Ngoc-Anh Le, Aryeh D. Stein
Summary: The research on postprandial metabolic flexibility involves measuring metabolic responses after meals, with recent advancements focusing on acute short-term nutrition challenges and utilizing diverse metabolic flexibility indicators. Studies have shown potential for novel dynamic indicators of metabolic diseases through nonclassical measurements and methodologies.
JOURNAL OF NUTRITION
(2021)
Review
Biochemistry & Molecular Biology
Aurelio A. Moya-Garcia, Almudena Pino-Angeles, Francisca Sanchez-Jimenez, Jose Luis Urdiales, Miguel Angel Medina
Summary: Histamine is a highly pleiotropic biogenic amine involved in various physiological processes, with complex effects mediated by different receptors. Its metabolism forms a complex network connecting important metabolic processes for homeostasis. Current research focuses on the relationship between the histamine system and other metabolic modules, aiming to fill information gaps and explore new perspectives.
Article
Biochemical Research Methods
Kate E. Dray, Joseph J. Muldoon, Niall M. Mangan, Neda Bagheri, Joshua N. Leonard
Summary: Mathematical modeling is crucial for understanding and designing synthetic biological systems. However, the model development process is complex and nonintuitive, requiring iteration and comparison with experimental data. To address these challenges, we introduce the GAMES workflow, which combines automated and human-in-the-loop processes. This workflow enables biologists to more easily build and analyze models for various applications.
ACS SYNTHETIC BIOLOGY
(2022)
Article
Engineering, Electrical & Electronic
Joshua Adam Bull, Helen Mary Byrne
Summary: This article introduces the significant increase in understanding cancer biology over the past 25 years and the role of mathematical modeling in unraveling complex processes, testing hypotheses, and improving cancer treatment. The article emphasizes the collaboration between mathematical modelers and cancer scientists, as well as the integration of modeling with experimental and clinical studies for disease diagnosis and personalized treatment improvement.
PROCEEDINGS OF THE IEEE
(2022)
Article
Geriatrics & Gerontology
U. Hab, C. Herpich, B. Kochlik, D. Weber, T. Grune, K. Norman
Summary: The study found that a pro-inflammatory diet reflected by the Dietary Inflammatory Index (DII) is associated with higher systemic inflammation, slower gait speed, and lower muscle mass in old adults. Intervention studies are needed to examine whether anti-inflammatory dietary approaches can help to improve muscle mass and function and thus minimize the risk for sarcopenia in the long-term.
JOURNAL OF NUTRITION HEALTH & AGING
(2022)
Article
Oncology
Chang Gong, Alvaro Ruiz-Martinez, Holly Kimko, Aleksander S. Popel
Summary: The study aims to develop a platform that combines the strengths of QSP and ABM models to create a cancer development model in the context of anti-cancer immunity and immune checkpoint inhibition therapy, which can be applied in virtual clinical trials and biomarker discovery.
Article
Green & Sustainable Science & Technology
Walied Alharbi
Summary: The penetration of electric vehicles into the market is expected to significantly increase EV charging demand, leading to a surge in the demand for electrical energy. To address this, swapping EV batteries instead of traditional charging can provide capacity support for the power distribution grid during off-peak periods. This study presents a mathematical optimization model that assesses distribution system margins considering different EV charging infrastructures, maximizing system margins while considering battery swapping station loads and grid limitations.
Review
Ophthalmology
Gavin W. Roddy
Summary: Metabolic syndrome is a risk factor that may accelerate aging in retinal neurons and contribute to neurodegeneration in glaucomatous optic neuropathy and age-related macular degeneration.
CURRENT OPINION IN OPHTHALMOLOGY
(2021)
Article
Mathematics
Diana T. Pham, Zdzislaw E. Musielak
Summary: Non-standard Lagrangians, which lack discernible energy-like terms, are found to produce the same equations of motion as standard Lagrangians, which contain identifiable energy-like terms. A novel method is developed for deriving non-standard Lagrangians for second-order nonlinear differential equations with damping, and the limitations of this method are explored. It is demonstrated that these limitations only exist for nonlinear dynamical systems that can be converted into linear ones. The derived results are then applied to selected population dynamics models to derive non-standard Lagrangians, their corresponding null Lagrangians, and gauge functions, and to discuss their roles in population dynamics.
Article
Microbiology
Alex J. Metcalf, Nanette R. Boyle
Summary: In this study, the researchers developed a transient metabolic model for diurnal growth of algae that can predict phenotype from genotype. This model allows evaluation of the impact of genetic and environmental changes on growth, biomass composition, and intracellular fluxes.
Article
Biotechnology & Applied Microbiology
Junmin Wang, Alireza Delfarah, Patrick E. Gelbach, Emma Fong, Paul Macklin, Shannon M. Mumenthaler, Nicholas A. Graham, Stacey D. Finley
Summary: Colorectal cancer is a significant health issue in the United States. The metabolic interactions between CRC cells and cancer-associated fibroblasts (CAFs) play a crucial role in promoting CRC development. CAFs reprogram CRC metabolism through stimulation of glycolysis, the oxidative arm of the pentose phosphate pathway (PPP), and glutaminolysis, while being especially sensitive to inhibitions of key enzymes like hexokinase and glucose-6-phosphate. This study provides insights into potential therapeutic targets for CRC treatment.
METABOLIC ENGINEERING
(2022)
Review
Biotechnology & Applied Microbiology
Neha Tanwar, Sagar S. Arya, James E. Rookes, David M. Cahill, Sangram K. Lenka, Kailash C. Bansal
Summary: Chloroplast genome engineering is a promising approach for enhancing the nutritional value of food crops by increasing the levels of existing metabolites, restoring lost metabolites during crop domestication, and introducing novel nutritional compounds.
CRITICAL REVIEWS IN BIOTECHNOLOGY
(2023)
Article
Oncology
Qiuyang Zhang, S. Michal Jazwinski
Summary: Cancer is a disease of aging and the relationship between aging and cancer is not well understood. This study explores the role of aging-related inflammation in prostate cancer and presents a novel method for generating age-related cancer models in mice. The findings contribute to a better understanding of the impact of age on cancer initiation and progression.
Article
Biotechnology & Applied Microbiology
Qianqian Yuan, Fan Wei, Xiaogui Deng, Aonan Li, Zhenkun Shi, Zhitao Mao, Feiran Li, Hongwu Ma
Summary: This study reconstructed a metabolic network model iQY1018 for Pseudomonas stutzeri A1501 based on substrate utilization experiments, with extensive curations to improve the prediction accuracy. The analysis revealed new functional abilities in central metabolism and predicted its suitability for producing Acetyl CoA-derived products.
SYNTHETIC AND SYSTEMS BIOTECHNOLOGY
(2023)
Article
Biochemistry & Molecular Biology
Nico Curti, Yuri Merli, Corrado Zengarini, Enrico Giampieri, Alessandra Merlotti, Daniele Dall'Olio, Emanuela Marcelli, Tommaso Bianchi, Gastone Castellani
Summary: Appropriate wound management is beneficial in terms of shorter healing times and reduced costs. This study aims to develop an efficient AI method for wound segmentation, based on a convolutional neural network, to improve physician efficiency and pave the way for further analysis of ulcer characteristics.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Nutrition & Dietetics
Marlijne C. G. de Graaf, Jean L. J. M. Scheijen, Corinne E. G. M. Spooren, Zlatan Mujagic, Marieke J. Pierik, Edith J. M. Feskens, Daniel Keszthelyi, Casper G. Schalkwijk, Daisy M. A. E. Jonkers
Summary: A Western diet high in dicarbonyls and advanced glycation endproducts (AGEs) may worsen inflammation in inflammatory bowel disease (IBD) and irritable bowel syndrome (IBS). This study examined the intake of dicarbonyls and AGEs in the habitual diet of IBD and IBS patients and their association with intestinal inflammation. The results showed that the absolute intake of dicarbonyls and AGEs was higher in IBD and healthy control subjects compared to IBS. However, after adjusting for energy intake, only glyoxal was lower in IBD compared to IBS and healthy controls. No significant association was found between dietary dicarbonyls and AGEs and intestinal inflammation in either patient group. The findings suggest that potential harmful effects of these compounds in the diet of Dutch patients with IBD or IBS may be counteracted by anti-inflammatory components in the food matrix.
Article
Chemistry, Multidisciplinary
Stefano Polizzi, Nico Curti, Lorenzo Dall'Olio, Laura Cercenelli, Luigi Fontana, Nicola Valsecchi, Emanuela Marcelli, Gastone Castellani, Piera Versura
Summary: Pupillometry is a promising technique for the diagnosis of neurological pathologies. In this work, advanced signal processing techniques and physics methods were applied to extract features from pupillometric curves obtained from 12 subjects. Machine learning techniques were used for classification between Optic Neuritis (ON) and healthy subjects, with an average accuracy of 76%. A possible neurological interpretation of the extracted pupillometry features in relation to ON vs. Healthy classification was provided.
APPLIED SCIENCES-BASEL
(2023)
Article
Chemistry, Multidisciplinary
Riccardo Biondi, Matteo Renzulli, Rita Golfieri, Nico Curti, Gianluca Carlini, Claudia Sala, Enrico Giampieri, Daniel Remondini, Giulio Vara, Arrigo Cattabriga, Maria Adriana Cocozza, Luigi Vincenzo Pastore, Nicolo Brandi, Antonino Palmeri, Leonardo Scarpetti, Gaia Tanzarella, Matteo Cescon, Matteo Ravaioli, Gastone Castellani, Francesca Coppola
Summary: This study evaluated the possibility of using radiomic features to predict the presence/absence of microvascular invasion (MVI) in hepatocellular carcinoma liver tumors. The results showed that radiomic features from the tumor region of contrast-enhanced computed tomography (CECT) images had good predictive performance for MVI.
APPLIED SCIENCES-BASEL
(2023)
Article
Biochemistry & Molecular Biology
Maria Maddalena Tumedei, Filippo Piccinini, Irene Azzali, Francesca Pirini, Sara Bravaccini, Serena De Matteis, Claudio Agostinelli, Gastone Castellani, Michele Zanoni, Michela Cortesi, Barbara Vergani, Biagio Eugenio Leone, Simona Righi, Anna Gazzola, Beatrice Casadei, Davide Gentilini, Luciano Calzari, Francesco Limarzi, Elena Sabattini, Andrea Pession, Marcella Tazzari, Clara Bertuzzi
Summary: The majority of patients with Follicular Lymphoma (FL) experience subsequent phases of remission and relapse, making the disease virtually incurable. Clinical-based prognostic scores have been proposed to predict the outcome of FL patients at diagnosis, but they continue to fail for a subset of patients. Gene expression profiling has highlighted the pivotal role of the tumor microenvironment (TME) in the FL prognosis, but there is still a need to standardize the assessment of immune-infiltrating cells for prognostic classification.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Biophysics
Nicolas Derus, Nico Curti, Enrico Giampieri, Daniele Dall'olio, Claudia Sala, Gastone Castellani
Summary: Histopathology involves analyzing microscopic tissue images for diagnosing and studying diseases. Artificial Intelligence algorithms have shown success in diagnosing diseases related to these medical images. However, challenges such as limited access to real datasets and biases in the data hinder research progress in this area.
JOURNAL OF MECHANICS IN MEDICINE AND BIOLOGY
(2023)
Article
Cell Biology
Katarzyna Malgorzata Kwiatkowska, Eleni Mavrogonatou, Adamantia Papadopoulou, Claudia Sala, Luciano Calzari, Davide Gentilini, Maria Giulia Bacalini, Daniele Dall'Olio, Gastone Castellani, Francesco Ravaioli, Claudio Franceschi, Paolo Garagnani, Chiara Pirazzini, Dimitris Kletsas
Summary: The aim of this study was to characterize DNA methylation patterns in replicative and induced senescence in different human cell types. Three epigenetic signatures were identified: cell type- and treatment-specific signature, cell type-specific senescence-related signature, and cell type-transversal replicative senescence-related signature. Cluster analysis revealed distinct DNA methylation patterns in replicative senescent cells, and enrichment in pathways related to the nervous system was shown. Despite no statistically significant evidence of age acceleration, a trend of increased biological age in replicative senescent cultures of all three cell types was observed. This work highlights the heterogeneity of senescent cells and their impact on tissue homeostasis.
Article
Agriculture, Dairy & Animal Science
Daniele Buschi, Nico Curti, Veronica Cola, Gianluca Carlini, Claudia Sala, Daniele Dall'Olio, Gastone Castellani, Elisa Pizzi, Sara Del Magno, Armando Foglia, Massimo Giunti, Luciano Pisoni, Enrico Giampieri
Summary: Proper wound management is beneficial for patients and can reduce healthcare costs. This study introduces a novel pipeline for pet wound image segmentation using advanced training strategies to minimize human intervention. The proposed approach provides a valuable tool for pet wound treatment and offers a methodology for generating large image segmentation datasets.
Article
Health Care Sciences & Services
Gianluca Carlini, Caterina Gaudiano, Rita Golfieri, Nico Curti, Riccardo Biondi, Lorenzo Bianchi, Riccardo Schiavina, Francesca Giunchi, Lorenzo Faggioni, Enrico Giampieri, Alessandra Merlotti, Daniele Dall'Olio, Claudia Sala, Sara Pandolfi, Daniel Remondini, Arianna Rustici, Luigi Vincenzo Pastore, Leonardo Scarpetti, Barbara Bortolani, Laura Cercenelli, Eugenio Brunocilla, Emanuela Marcelli, Francesca Coppola, Gastone Castellani
Summary: This study aimed to build a machine learning model to distinguish between benign renal tumors, such as renal oncocytoma, and malignant renal cell carcinomas. By selecting appropriate radiomic features and using a decision tree classifier, we successfully established a model that could differentiate between these two types of renal tumors. The results confirmed the efficiency of radiomic features in capturing tumor characteristics, but also highlighted the need to consider the true generalization capabilities of the models.
JOURNAL OF PERSONALIZED MEDICINE
(2023)
Article
Health Care Sciences & Services
Kristel C. M. M. Polhuis, Lenneke Vaandrager, Maria A. Koelen, Johanna M. Geleijnse, Sabita S. Soedamah-Muthu
Summary: This study aims to examine the quantitative and qualitative effects of the SALUD program on healthy eating and well-being in people with type 2 diabetes mellitus. The SALUD program provides valuable information on salutogenic interventions and serves as a concrete, web-based tool. The combination of quantitative and qualitative measures allows for a comprehensive evaluation of effects, which can be used to optimize interventions for type 2 diabetes mellitus.
JMIR RESEARCH PROTOCOLS
(2023)
Article
Computer Science, Information Systems
Laura Verzellesi, Andrea Botti, Marco Bertolini, Valeria Trojani, Gianluca Carlini, Andrea Nitrosi, Filippo Monelli, Giulia Besutti, Gastone Castellani, Daniel Remondini, Gianluca Milanese, Stefania Croci, Nicola Sverzellati, Carlo Salvarani, Mauro Iori
Summary: This study aims to propose a user-friendly and low-cost tool for COVID-19 mortality prediction using both machine learning and deep learning approaches.
