Article
Computer Science, Interdisciplinary Applications
Megan E. Brasch, Alexis N. Pena, James H. Henderson
Summary: In this study, a computational, image analysis-based approach was introduced to accurately identify and characterize distinct functional cell phenotypic subpopulations. Using a heterogeneous model system of endothelial and smooth muscle cells, it was found that cells exhibited different motility rates in co-culture compared to monoculture. This non-destructive and non-invasive imaging method can be broadly applied to heterogeneous cell culture model systems to advance understanding of how heterogeneity affects cell phenotype.
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
(2021)
Article
Multidisciplinary Sciences
Khatereh Sabaghian, Keyhan Khamforoosh, Abdolbaghi Ghaderzadeh
Summary: This paper proposes an algorithm to reduce the number of replications in big data transfer and rank replication sites using VIKOR. By considering different variables, the VIKOR method can take all effective parameters into account when evaluating site ranks.
Article
Biology
Francesco Padovani, Benedikt Mairhoermann, Pascal Falter-Braun, Jette Lengefeld, Kurt M. Schmoller
Summary: Cell-ACDC is an open-source user-friendly framework written in Python for segmentation, tracking, and cell cycle annotations in live cell imaging data. It includes state-of-the-art deep learning models, visualization and error correction tools, and allows for fast integration of new methods.
Article
Multidisciplinary Sciences
Tamer Z. Emara, Thanh Trinh, Joshua Zhexue Huang
Summary: Nowadays, companies are choosing to store and replicate their data across multiple data centers. This paper proposes a geographically distributed data management framework to address the challenges of storing and analyzing massive amounts of data.
SCIENTIFIC REPORTS
(2023)
Article
Microbiology
Julian Schwanbeck, Ines Oehmig, Uwe Gross, Andreas E. Zautner, Wolfgang Bohne
Summary: The translation discusses the importance of flagellar motility for intestinal pathogens and highlights the swimming strategy of Clostridioides difficile at the single cell level and its dependence on environmental parameters.
FRONTIERS IN MICROBIOLOGY
(2021)
Review
Chemistry, Analytical
Zhao Zhang, Xuewei Liao, Wenjun Tong, Jin Wang, Chen Wang
Summary: At the microscale, bacteria have developed various motility mechanisms for movement towards nutrients and habitable habitats. Research on bacterial motility is valuable for applications like investigating interactions between biological entities and surfaces, microbial cell captures and detection, and analyzing flagellar motion mechanisms. Optical-based analysis is considered the most intuitive and robust approach for studying bacterial motility, and advancements in experimental technologies and data analysis methods have expanded the capabilities of optical-based analysis. This review provides an overview of recent advances in optical-based imaging/analysis techniques for bacterial motility, including dark-field microscope-based analysis, fluorescence microscope-based analysis, surface plasmon resonance microscope-based analysis, and phase contrast microscope-based analysis. The review also discusses future directions and development in this research field.
TRAC-TRENDS IN ANALYTICAL CHEMISTRY
(2023)
Article
Cell Biology
Jozsef Meszaros, Peter Geggier, Jamie J. Manning, Wesley B. Asher, Jonathan A. Javitch
Summary: Single-molecule FRET (smFRET) is a powerful imaging platform for studying dynamic changes in biological molecules. Expanding smFRET imaging to living cells provides new research opportunities and challenges. Automating dataset curation is crucial for consistent and efficient analysis, allowing researchers to advance the technical boundaries of imaging living cells. Our automated approach addresses the problem of multiple particles entering a region of interest, increasing FRET data quantity and accuracy, and improving understanding of biological functions.
FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY
(2023)
Article
Oncology
Botai Xuan, Deepraj Ghosh, Michelle R. Dawson
Summary: This article reviews the important role of polyploid giant cancer cells (PGCCs) in cancer progression, focusing on their biomolecular phenotype and cytoskeletal features. Understanding the characteristics of PGCCs could lead to the development of therapeutic strategies specifically targeting these tumor cells.
SEMINARS IN CANCER BIOLOGY
(2022)
Article
Chemistry, Analytical
Hansen Zhao, Feng Ge, Yongyu Zhang, Zhenrong Huang, Xiangjun Shi, Bin Xiong, Xuebin Liao, Sichun Zhang, Yan He
Summary: Understanding spatiotemporal dynamics of particles in complex biological environments is crucial. SEES, a method based on historical experience vector analysis, automatically presents global trajectory patterns and local continuities without predefined models, showing greater sensitivity to rare events and multivariable observations compared to the Hidden Markov model. Application of SEES to analyze interactions between nanoparticles and PD-L1 expressing cells successfully pinpointed rare events, visualized Brownian motion, and evaluated different dynamics. These findings could help in designing highly efficient nanocargoes.
ANALYTICAL CHEMISTRY
(2021)
Article
Computer Science, Artificial Intelligence
Hamza Osman Ilhan, Mecit Yuzkat, Nizamettin Aydin
Summary: Semen analysis is currently performed using two techniques: a manual observation based technique and computer based expert systems. A new hybrid expert system has been proposed in this study to combine the advantages of both techniques. Experimental results show that this new system has more advantages in terms of portability, cost, and modularity compared to other expert systems.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Chemistry, Analytical
Renmeng Liu, Zhibo Yang
Summary: Single cell metabolomics using mass spectrometry techniques explores cellular metabolism, focusing on cell differences at single-cell level, and is expected to have more potential applications in translational and clinical fields with the implementation of advanced data analysis methods.
ANALYTICA CHIMICA ACTA
(2021)
Article
Multidisciplinary Sciences
Catarina A. Marques, Melanie Ridgway, Michele Tinti, Andrew Cassidy, David Horn
Summary: In this study, a genome-wide RNA-interference library screen was used to investigate the cell cycle defects in Trypanosoma brucei. The results provide comprehensive functional genomic evidence for the known and novel machineries, pathways, and regulators that coordinate trypanosome cell cycle progression.
NATURE COMMUNICATIONS
(2022)
Article
Chemistry, Multidisciplinary
Yerbol Tagay, Sina Kheirabadi, Zaman Ataie, Rakesh K. Singh, Olivia Prince, Ashley Nguyen, Alexander S. Zhovmer, Xuefei Ma, Amir Sheikhi, Denis Tsygankov, Erdem D. Tabdanov
Summary: The principal cause of death in cancer patients is metastasis, which is conventionally linked to actomyosin-driven cell locomotion. However, this study identifies a complementary mechanism of metastatic locomotion powered by dynein-generated forces. These findings provide new insights into the fundamental understanding of cell locomotion mechanisms and expand the spectrum of clinical targets against metastasis.
Article
Multidisciplinary Sciences
Chao Jiang, Hong-Yu Luo, Xinpeng Xu, Shuo-Xing Dou, Wei Li, Dongshi Guan, Fangfu Ye, Xiaosong Chen, Ming Guo, Peng-Ye Wang, Hui Li
Summary: Cell migration plays important roles in biological processes, but the mechanisms behind how cells regulate their speed and direction are still unclear. This study reveals a strong positive correlation between intracellular diffusion and cell migration speed, and identifies a switching of cell migration modes associated with reversible intracellular diffusion variation and lamellipodium structure deformation. The findings suggest a mechanism involving actin polymerization and molecular crowding in the lamellipodium to coordinate intracellular diffusion dynamics and lamellipodium structure during cell migration.
NATURE COMMUNICATIONS
(2023)
Article
Multidisciplinary Sciences
Eunsun Ko, Dasom Kim, Dong Wha Min, Seung-Hae Kwon, Ji-Yun Lee
Summary: Nrf2 is a important regulator of antioxidant and anti-inflammatory enzymes, interacting with Keap1 to affect the transcription of cytoprotective enzymes. The Nrf2/Keap1 pathway may impact cell motility through dysregulation of the RhoA-ROCK1 signaling pathway in non-small cell lung cancer cells.
SCIENTIFIC REPORTS
(2021)
Article
Biochemistry & Molecular Biology
Andrea Pelliccia, Francesco Capradossi, Francesca Corsi, Greta Deidda Tarquini, Emanuele Bruni, Albrecht Reichle, Francesco Torino, Lina Ghibelli
Summary: Androgen deprivation therapy (ADT) induces a metastable quasi-apoptotic state (QUAPS) in mHSPC cells, characterized by partial mitochondrial permeabilization and moderate induction of caspase-dependent dsDNA breaks, promoting genetic instability. QUAPS is stabilized by PARP and can be reverted upon androgen restoration. The cells re-acquire resistance to PARP inhibitors and exhibit an increased micronuclei frequency, suggesting a potential pathway for the progression of mHSPC to CRPC.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Chemistry, Analytical
Rosamaria Capuano, Antonella Mansi, Emilia Paba, Anna Maria Marcelloni, Alessandra Chiominto, Anna Rita Proietto, Andrea Gordiani, Alexandro Catini, Roberto Paolesse, Giovanna Tranfo, Corrado Di Natale
Summary: This paper characterizes the volatile organic compounds (VOCs) pattern emitted in vitro by Legionella pneumophila cultures and compares it with those produced by other Legionella species and by Pseudomonas aeruginosa. The results show that the VOCs can differentiate Legionella pneumophila from other waterborne microorganisms.
Article
Environmental Sciences
Daniele La Forgia, Gaetano Paparella, Rahel Signorile, Francesca Arezzo, Maria Colomba Comes, Gennaro Cormio, Antonella Daniele, Annarita Fanizzi, Agnese Maria Fioretti, Gianluca Gatta, Miria Lafranceschina, Alessandro Rizzo, Gian Maria Zaccaria, Angelo Rosa, Raffaella Massafra
Summary: Lean management is a new organizational vision applied in the healthcare and administrative sector, inspired by the automotive industry, aiming to emphasize value and reduce waste through process analysis. This approach could serve as a cost-effective solution for production companies during times of economic constraints. The study analyzes the presentation and initial management of ministerial research projects in an Italian research institute, examining both the current obstacles faced by users and conducting perspective analyses with reference indicators to explore the potential benefits of implementing a Lean model in 2021.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2023)
Article
Health Care Sciences & Services
Annarita Fanizzi, Elisabetta Graps, Domenica Antonia Bavaro, Marco Farella, Samantha Bove, Francesco Campobasso, Maria Colomba Comes, Cristian Cristofaro, Daniele La Forgia, Martina Milella, Serena Iacovelli, Rossella Villani, Rahel Signorile, Alessio De Bartolo, Vito Lorusso, Raffaella Massafra
Summary: This study proposes a model to evaluate the optimal distribution of resources in a Department of Breast Radiodiagnosis. A cost-benefit analysis was performed to estimate the costs and health effects of the screening program. The results show that reducing the current waiting lists from 32 to 16 months is the most cost-effective approach and allows for an increased screening scope of 60,000 patients in 3 years.
BMC HEALTH SERVICES RESEARCH
(2023)
Article
Multidisciplinary Sciences
Samantha Bove, Annarita Fanizzi, Federico Fadda, Maria Colomba Comes, Annamaria Catino, Angelo Cirillo, Cristian Cristofaro, Michele Montrone, Annalisa Nardone, Pamela Pizzutilo, Antonio Tufaro, Domenico Galetta, Raffaella Massafra
Summary: This study applies transfer learning to predict recurrence risk in NSCLC patients using data acquired during the screening phase. Experimental results show that the model analyzing CROP 20 images, which contain more peritumoral area, achieves the best performance in predicting NSCLC recurrence.
Article
Chemistry, Analytical
Leonardo Papale, Alexandro Catini, Rosamaria Capuano, Valerio Allegra, Eugenio Martinelli, Massimo Palmacci, Giovanna Tranfo, Corrado Di Natale
Summary: Indoor locations with limited air exchange can easily be contaminated by harmful volatile compounds. Thus, it is important to monitor the distribution of chemicals indoors to reduce associated risks. In this study, a monitoring system based on a Machine Learning approach is introduced, which utilizes a low-cost wearable VOC sensor in a Wireless Sensor Network (WSN) to process information and localize mobile sensor units.
Article
Engineering, Electrical & Electronic
A. Mencattini, V. Rizzuto, G. Antonelli, D. Di Giuseppe, M. D'Orazio, J. Filippi, M. C. Comes, P. Casti, J. L. Vives Corrons, M. Garcia-Bravo, J. C. Segovia, Maria del Mar Manu-Pereira, M. J. Lopez-Martinez, J. Samitier, E. Martinelli
Summary: Microfluidics offers great potential for conducting large-scale biological experiments, but the difficulty of managing available information limits its widespread use. In this study, we propose combining microfluidics with machine learning approaches to enhance the diagnostic capability of lab-on-chip devices. By introducing data analysis methodologies within the deep learning framework, we are able to encode cell morphology beyond standard cell appearance. Using a dedicated microfluidics device, our machine learning platform accurately recognizes Pyruvate Kinase Disease (PKD) in red blood cell samples, achieving over 85% accuracy in simulated and real experiments.
SENSORS AND ACTUATORS A-PHYSICAL
(2023)
Article
Multidisciplinary Sciences
Annarita Fanizzi, Domenico Pomarico, Alessandro Rizzo, Samantha Bove, Maria Colomba Comes, Vittorio Didonna, Francesco Giotta, Daniele La Forgia, Agnese Latorre, Maria Irene Pastena, Nicole Petruzzellis, Lucia Rinaldi, Pasquale Tamborra, Alfredo Zito, Vito Lorusso, Raffaella Massafra
Summary: This paper presents a machine learning survival model for estimating Invasive Disease-Free Events in early stage endocrine-positive Her2 negative breast cancer patients. The model is trained on clinical and histological data commonly collected in clinical practice. The machine learning models outperform the Cox proportional hazards regression in predicting patient risk and can help reduce unnecessary chemotherapy in hormone therapy.
SCIENTIFIC REPORTS
(2023)
Article
Biochemistry & Molecular Biology
Francesca Corsi, Erika Di Meo, Daniela Lulli, Greta Deidda Tarquini, Francesco Capradossi, Emanuele Bruni, Andrea Pelliccia, Enrico Traversa, Elena Dellambra, Cristina Maria Failla, Lina Ghibelli
Summary: Cerium oxide nanoparticles (nanoceria) are biocompatible and multifunctional nanozymes that mimic the activities of superoxide-dismutase and catalase. They can shield from UV exposure, protect tissues from oxidative damage, and accelerate the recovery of skin cells. Nanoceria can also neutralize the side effects of titanium dioxide nanoparticles, a common ingredient in UV-shielding lotions. These properties make nanoceria a promising solution for preventing UV-induced skin damage and carcinogenesis.
Article
Biology
A. Mencattini, M. D'Orazio, P. Casti, M. C. Comes, D. Di Giuseppe, G. Antonelli, J. Filippi, F. Corsi, L. Ghibelli, I. Veith, C. Di Natale, M. C. Parrini, E. Martinelli
Summary: One of the major problems in bioimaging is whether features extracted for a discrimination or regression task can remain valid in the presence of unpredictable perturbations during image acquisition process. This is especially important in the context of deep learning features due to the lack of known relationship between the black-box descriptors and the phenotypic properties of the biological entities. The use of pre-trained Convolutional Neural Networks (CNNs) is hindered by their lack of apparent physical meaning and sensitivity to unspecific biases.
COMMUNICATIONS BIOLOGY
(2023)
Article
Chemistry, Analytical
Mauro Tomassetti, Riccardo Pezzilli, Claudio Leonardi, Giuseppe Prestopino, Corrado Di Natale, Luigi Campanella, Pier Gianni Medaglia
Summary: This study demonstrates that introducing nanostructured layered double hydroxides (LDHs) into the anode compartment can enhance the kinetic performance of a direct catalytic ethanol fuel cell (DCEFC). The calibration sensitivity of the method increases by 1.3-fold with the introduction of LDHs and even further in the presence of hydrogen peroxide. By modifying the fuel cell with enzyme catalase crosslinked on LDHs and in the presence of hydrogen peroxide, the calibration sensitivity increases by 8-times. This modification shows positive results in ethanol detection for analytical applications and can also improve the energy performance of a DCEFC.
Article
Health Care Sciences & Services
Domenica Antonia Bavaro, Annarita Fanizzi, Serena Iacovelli, Samantha Bove, Maria Colomba Comes, Cristian Cristofaro, Daniela Cutrignelli, Valerio De Santis, Annalisa Nardone, Fulvia Lagattolla, Alessandro Rizzo, Cosmo Maurizio Ressa, Raffaella Massafra
Summary: Immediate breast reconstruction after mastectomy surgery has become more common in the treatment of breast cancer patients, but capsular contracture remains a major complication. This study evaluated the association between clinical, histological, and therapeutic parameters and the occurrence of capsular contracture. Machine learning techniques were used to predict the occurrence of capsular contracture based on collected data.
Article
Chemistry, Analytical
Lorena Di Zazzo, Sujithkumar Ganesh Moorthy, Rita Meunier-Prest, Eric Lesniewska, Corrado Di Natale, Roberto Paolesse, Marcel Bouvet
Summary: The versatility of metal complexes of corroles has raised interest in the use of these molecules as elements of chemical sensors. To compensate for the scarce conductivity, corroles are often used to functionalize the surface of conductive materials or incorporated into heterojunction devices. These heterostructure sensors can detect ammonia and relative humidity with high sensitivity.
Article
Chemistry, Multidisciplinary
Giacomo Picci, Sara Farotto, Jessica Milia, Claudia Caltagirone, Vito Lippolis, Maria Carla Aragoni, Corrado Di Natale, Roberto Paolesse, Larisa Lvova
Summary: We have developed a new type of acyclicsquaramidereceptors (L1-L5) that can selectively detect ketoprofen and naproxen anions (KF- and NS-, respectively) in water. The receptors form hydrogen bonds with the anions, and compounds L1-L5 have been tested as ionophores for the detection of KF- and NS- in polymeric membranes. The developed sensors show high precision detection capabilities with low relative errors and high sensitivity and selectivity towards NS-.
