Review
Plant Sciences
Kate Harline, Jesus Martinez-Gomez, Chelsea D. Specht, Adrienne H. K. Roeder
Summary: Modeling has become a popular tool in biological disciplines, but the literacy among biologists has not kept pace. The lack of understanding inhibits communication and progress in data analysis. A blueprint has been proposed to empower biologists to apply models in their field.
FRONTIERS IN PLANT SCIENCE
(2021)
Editorial Material
Multidisciplinary Sciences
Marina. G. G. Guenza
Summary: Many biological processes rely on protein aggregates that have dynamic behaviors spanning different scales. A clever combination of spectroscopy and simulation can be used to investigate these diverse dynamics.
Article
Engineering, Chemical
Ann Kathrin Schomberg, Arno Kwade, Jan Henrik Finke
Summary: The aim of this study is to develop a process model for tablet die filling under gravity and investigate its scalability from pilot scale to industrial scale rotary presses. An evolving differential pressure in the dies at larger scales facilitated the filling process, which was covered by a model extension based on Bernoulli's equation. The model allows the calculation of critical paddle speeds required for complete die filling under gravity.
Article
Materials Science, Multidisciplinary
Ali Can Kaya, Paul Zaslansky, Claudia Fleck
Summary: Finite element models were used to study the mechanical behavior of open-cell gray cast iron foams in different loading directions, revealing the significant influence of graphite particle orientation and strut cross-sectional shape on foam properties. Simulation results considering damage factors showed good agreement with experimental results, highlighting the impact of material damage on foam performance.
ADVANCED ENGINEERING MATERIALS
(2022)
Article
Multidisciplinary Sciences
Yongxiang Zhao, Jiemin Shen, Qinzhe Wang, Manuel Jose Ruiz Munevar, Pietro Vidossich, Marco De Vivo, Ming Zhou, Erhu Cao
Summary: This study presents the cryoelectron microscopy structure of human K+-Cl- cotransporter (KCC)1 in an outward-open state bound with the VU0463271 inhibitor. The findings reveal that the extracellular ion permeation path in KCC1 does not involve hinge-bending motions of specific transmembrane segments, but rather relies on rocking and displacement of other segments. The study also identifies two distinct dimeric states of KCC1. These findings provide insights into the mechanisms of CCCs and potential inhibitory compounds.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Article
Engineering, Manufacturing
Brian Snider-Simon, George Frantziskonis
Summary: As metal additive manufacturing moves towards producing in-service parts, there is a need for methodologies to predict material response and reliability. Physics-based approaches and data-driven models have their pros and cons, with physics-based methods requiring high computational costs and data-driven models struggling with interpretation and potential bias. This paper introduces a novel workflow that combines process parameters, build strategy, and standard material science tests data to develop finite element models for predicting material reliability without explicitly modeling the physics behind the manufacturing process.
ADDITIVE MANUFACTURING
(2022)
Review
Microbiology
Christian Diener, Sean M. Gibbons
Summary: Microbial consortia play a crucial role in various essential processes, but it is challenging to understand their functional capacities based on their composition alone. Community-scale metabolic models have the potential to simulate complex microbial communities, but there is no consensus on the fitness function and community-wide growth. Transitioning from single-taxon models to multitaxon models poses challenges as well. Dynamic approaches are a solution but are computationally expensive, while two steady-state approaches provide ecologically relevant solutions with improved scalability.
Article
Geochemistry & Geophysics
Dandan Wang, Yunhao Chen, Leiqiu Hu, James A. Voogt
Summary: This study compares MODIS-derived thermal anisotropy with airborne observations and assesses the factors controlling anisotropic features of LST at seasonal and diurnal scales. The study finds that the seasonally aggregated MODIS-derived anisotropy is closer to the instantaneous model-derived or airborne-measured anisotropy in the morning and afternoon.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Astronomy & Astrophysics
Namita Uppal, Shashikiran Ganesh, D. Bisht
Summary: The optical linear polarization observation of stars towards the core of the Czernik 3 cluster reveals a non-uniform distribution of dust with at least two dust layers along the line of sight at distances of around 1 and 3.4 kpc. The presence of dust in the center of the cluster is indicated by an increase in the degree of polarization and WISE W4 flux. The large-scale distribution of dust shows a region of low dust content between the Local Arm and the Perseus arm.
ASTRONOMICAL JOURNAL
(2022)
Article
Microbiology
Lauren M. Lui, Erica L-W Majumder, Heidi J. Smith, Hans K. Carlson, Frederick von Netzer, Matthew W. Fields, David A. Stahl, Jizhong Zhou, Terry C. Hazen, Nitin S. Baliga, Paul D. Adams, Adam P. Arkin
Summary: The advancements in technology in the field of microbial ecology have enabled the rapid acquisition of extensive datasets for microbial communities, but the challenge now lies in integrating diverse data types to reach a causal and mechanistic understanding of microbial communities' behavior. The need for a conceptual, quantitative framework connecting genomic potential, the environment, and forces driving microbial growth is emphasized to predict and address microbially mediated global problems effectively.
FRONTIERS IN MICROBIOLOGY
(2021)
Review
Polymer Science
Timur A. Nadzharyan, Mikhail Shamonin, Elena Yu Kramarenko
Summary: This review presents the latest theoretical advances in understanding magnetomechanical effects and phenomena observed in magnetoactive elastomers (MAEs), which are polymer networks filled with magnetic micro- and/or nanoparticles, under external magnetic fields. Theoretical modeling on various spatial scales is discussed, ranging from the behavior of individual magnetic particles in an elastic medium to the overall mechanical properties of an MAE sample. The review demonstrates how theoretical models enable qualitative and quantitative interpretation of experimental results and highlights the limitations and challenges of current approaches, as well as the most promising lines of research in this area.
Article
Chemistry, Multidisciplinary
Bryan H. H. Ferlez, Henning Kirst, Basil J. J. Greber, Eva Nogales, Markus Sutter, Cheryl A. A. Kerfeld
Summary: Many bacteria use bacterial microcompartments (BMCs) to organize enzymatic reactions. Shell proteins derived from BMCs can self-assemble into various structures and are used in biotechnology. This study shows that empty synthetic shells with different end-cap structures can be derived from a specific microcompartment, demonstrating the plasticity of BMC-based biomaterials. It also discovers new nanotube and nanocone morphologies that share architectural principles with other structures.
ADVANCED MATERIALS
(2023)
Article
Engineering, Environmental
Wenhua Cong, Pin Song, Yong Zhang, Su Yang, Weifeng Liu, Tianyuan Zhang, Jiadong Zhou, Meiling Wang, Xuguang Liu
Summary: In this study, the size of Mo-based nanostructures was precisely controlled and supported on N, P, O co-doped carbon to improve the detection sensitivity of hydroquinone. The supported Mo single atoms showed excellent sensing performance with a wide linear range and a low detection limit.
JOURNAL OF HAZARDOUS MATERIALS
(2022)
Article
Engineering, Environmental
Wenhua Cong, Pin Song, Yong Zhang, Su Yang, Weifeng Liu, Tianyuan Zhang, Jiadong Zhou, Meiling Wang, Xuguang Liu
Summary: This study demonstrates the synthesis of Mo-based nanostructures with different sizes and structures, anchored on carbon support, for electrochemical monitoring of hydroquinone. The Mo single atoms show superior sensitivity and catalytic ability compared to other nanostructures, with wide linear range and low detection limit.
JOURNAL OF HAZARDOUS MATERIALS
(2022)
Article
Geosciences, Multidisciplinary
Xiancan Wu, Zhigang Li, Xue Yang, Chuang Sun, Weitao Wang, Rafael Almeida, Xiangming Dai, Yipeng Zhang, Binbin Xu, Hao Liang, Gege Hui, Liangwei Lv, Weiwang Long
Summary: Our study establishes fundamental geometric relationships for curved thrust fault-propagation folds by examining the geometries and kinematics of three contractional structures at different scales. We successfully reproduce the fold geometry with a smoothly curving backlimb and an abrupt forelimb, and discover that the deformation of the folded backlimb is a combination of limb rotation and kink-band migration. Our results show that curved faults do not experience greater slips compared to planar faults of similar dips. The choice of fault geometry is crucial for the deformation of folded backlimb and landform surface.
JOURNAL OF STRUCTURAL GEOLOGY
(2023)
Article
Biochemical Research Methods
Avisa Maleki, Giulia Russo, Giuseppe Alessandro Parasiliti Palumbo, Francesco Pappalardo
Summary: This study designed a recombinant multi-epitope vaccine based on a highly conserved epitope of hemagglutinin, neuraminidase, and membrane matrix proteins using an immunoinformatic approach. The vaccine showed good immunological properties and immune response prediction.
BMC BIOINFORMATICS
(2022)
Article
Biochemical Research Methods
Giulia Russo, Valentina Di Salvatore, Giuseppe Sgroi, Giuseppe Alessandro Parasiliti Palumbo, Pedro A. Reche, Francesco Pappalardo
Summary: The COVID-19 pandemic has emphasized the importance of using bioinformatics software to quickly develop intervention solutions. Advances in computer modeling and simulation have improved the discovery, development, assessment, and monitoring of therapeutic strategies. The combined use of molecular prediction tools and computer simulation plays a crucial role in predicting the efficacy and safety of new vaccines.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Oncology
G. Catanuto, N. Rocco, A. Maglia, P. Barry, A. Karakatsanis, G. Sgroi, G. Russo, F. Pappalardo, M. B. Nava
Summary: This study used Delphi survey to investigate key factors in the decision making process of surgical oncology on the breast. The results, validated by text mining and natural language processing techniques, indicated that there are specific decision drivers and outcomes recognized by experts in breast cancer surgery decision making.
Article
Engineering, Biomedical
Cristina Curreli, Valentina Di Salvatore, Giulia Russo, Francesco Pappalardo, Marco Viceconti
Summary: This study develops a computer simulation environment that can predict the dose-response of new therapeutic vaccines against tuberculosis, supporting the optimal design of clinical trials. Before using this in silico methodology, it is important to assess the credibility of the predictive model and a risk-informed credibility assessment plan is presented.
ANNALS OF BIOMEDICAL ENGINEERING
(2023)
Review
Energy & Fuels
Carlo Bianca
Summary: This paper is a survey of the recent proposed frameworks of the thermostatted kinetic theory for the modeling of a hybrid energy-multisource network, reviewing the recent proposed models. The approach models the evolution of an energy source and its interactions with other energy sources through the introduction of distribution functions and interaction rates.
Editorial Material
Multidisciplinary Sciences
Carlo Bianca
Summary: The recent developments in dynamical systems theory and non-equilibrium statistical mechanics have opened up new possibilities for modeling complex phenomena in nature and society. This editorial introduces the topic and highlights the contributions of this Special Issue, which focuses on the development of new methods and models from dynamical system theory and statistical mechanics, as well as addressing existing framework-related problems and applications in various systems.
Article
Biochemical Research Methods
Giuseppe Sgroi, Giulia Russo, Anna Maglia, Giuseppe Catanuto, Peter Barry, Andreas Karakatsanis, Nicola Rocco, Francesco Pappalardo
Summary: This study applies natural language processing and machine learning to predict the context related to Delphi surveys in surgical decision-making, enhancing the usefulness of Delphi surveys and suggesting keywords for evaluation.
BMC BIOINFORMATICS
(2022)
Article
Pharmacology & Pharmacy
Flora T. Musuamba, S. Y. Amy Cheung, Pieter Colin, Elin H. Davies, Jeffrey S. Barret, Francesco Pappalardo, Michael Chappell, Jean-Michel Dogne, Adriana Ceci, Oscar Della Pasqua, Ine S. Rusten
Summary: The benefit/risk balance is the most important question when considering market access for medicinal products. This assessment involves evaluating efficacy, safety, dose selection, pharmacology, and drug quality. However, there is currently no systematic approach to assess and establish the acceptability of alternative methods and data sources, leading to regulatory skepticism toward new data types and methods. To mitigate uncertainties in efficacy and safety characterization, a data-knowledge backbone is needed. This white paper proposes an ecosystem based on a repository, high-quality standards, and credibility assessment for better regulatory decision making.
CLINICAL PHARMACOLOGY & THERAPEUTICS
(2023)
Article
Computer Science, Information Systems
Francesco Pappalardo, John Wilkinson, Francois Busquet, Antoine Bril, Mark Palmer, Barry Walker, Cristina Curreli, Giulia Russo, Thierry Marchal, Elena Toschi, Rossana Alessandrello, Vincenzo Costignola, Ingrid Klingmann, Martina Contin, Bernard Staumont, Matthias Woiczinski, Christian Kaddick, Valentina Di Salvatore, Alessandra Aldieri, Liesbet Geris, Marco Viceconti
Summary: In Silico Trials methodologies will have a significant impact on the development and risk reduction of medical devices in the future. The regulatory pathway for Digital Patient and Personal Health Forecasting solutions is clear, but more complex for In Silico Trials solutions. It is suggested that the European regulatory system should start an innovation process to avoid companies focusing on other markets like the USA.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2022)
Article
Biology
Alessia Rondinella, Elena Crispino, Francesco Guarnera, Oliver Giudice, Alessandro Ortis, Giulia Russo, Clara Di Lorenzo, Davide Maimone, Francesco Pappalardo, Sebastiano Battiato
Summary: This paper proposes a framework that exploits an augmented U-Net architecture with a convolutional long short-term memory layer and attention mechanism to segment and quantify multiple sclerosis lesions detected in magnetic resonance images. Quantitative and qualitative evaluation demonstrate that the method outperforms previous state-of-the-art approaches, reporting an overall Dice score of 89% and showing robustness and generalization ability on never seen new test samples of a new dedicated dataset under construction.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Biochemistry & Molecular Biology
Avisa Maleki, Elena Crispino, Serena Anna Italia, Valentina Di Salvatore, Maria Assunta Chiacchio, Fianne Sips, Roberta Bursi, Giulia Russo, Davide Maimone, Francesco Pappalardo
Summary: Multiple sclerosis is an autoimmune inflammatory disease that affects the central nervous system. Universal Immune System Simulator can be potentially used to predict the effects of treatments against multiple sclerosis. The retrospective validation of UISS-MS with clinical data confirms its ability to simulate the mechanisms and outcomes of treatments.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2023)
Article
Biochemical Research Methods
Giulia Russo, Giuseppe Alessandro Parasiliti Palumbo, Marzio Pennisi, Francesco Pappalardo
Summary: This article introduces an automatic tool for the verification assessment of mechanistic Agent-Based Models and demonstrates its application through a case study of an Agent-Based Model in silico trial. The described workflow allows researchers and practitioners to easily perform verification steps and provide strong evidence for further regulatory requirements.
BMC BIOINFORMATICS
(2022)
Article
Biochemistry & Molecular Biology
Francesco Pappalardo, Giulia Russo, Emanuela Corsini, Alicia Paini, Andrew Worth
Summary: The identification of immunotoxicity hazard aims to assess the unintended effects of chemical exposure on the immune system. Perfluorinated alkylate substances (PFAS) have been found to be immunotoxic and associated with lower antibody responses and increased susceptibility to diseases. Mathematical modeling and simulation platforms can be utilized to evaluate the adverse effects of immunotoxicants. The Universal Immune System Simulator demonstrates the potential for assessing immunotoxicity through computational models.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2022)
