Embryonic tissues and multicellular aggregates of adult cells mimic the behavior of highly viscous liquids. The liquid analogy helps to understand morphogenetic phenomena, such as cell sorting and tissue fusion, observed in developmental biology and tissue engineering. Tissue fusion is vital in tissue printing, an emergent technique based on computer-controlled deposition of tissue fragments and biocompatible materials. Computer simulations proved useful in predicting post-printing shape changes of tissue constructs. The simulation methods available to date, however, are unable to describe the time evolution of living systems made of millions of cells. The Lattice Boltzmann (LB) approach allows the implementation of interaction forces between the constituents of the system and yields time evolution in terms of distribution functions. With tissue engineering applications in mind, we have developed a finite difference Lattice Boltzmann model of a multicellular system and applied it to simulate the sidewise fusion of two contiguous cylinders made of cohesive cells and embedded in a medium (hydrogel). We have identified a biologically relevant range of model parameters. The proposed LB model may be extended to describe the time evolution of more complex multicellular structures such as sheets or tubes produced by tissue printing.
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http://dx.doi.org/10.3233/BIR-2011-0595 | DOI Listing |
Purpose: To better understand burnout in oncology and clinician well-being along the career continuum starting with training, we sought to characterize the professional well-being of physicians training in medical oncology in 2023 and to identify trends over time comparing to fellows from a decade prior.
Methods: All US medical oncology fellows taking the 2023 ASCO Medical Oncology In-Training Exam (ITE) were invited to complete an optional post-exam survey evaluating fatigue, satisfaction with work-life integration (WLI), emotional exhaustion and depersonalization. 2023 ITE survey responses were compared to the 2013 ASCO post-ITE survey (n=1345).
Arq Bras Cir Dig
January 2025
D'Or Institute for Research and Education, Digestive Surgery Residency Program - Rio de Janeiro (RJ), Brazil.
Liver metastases from melanomas, sarcomas, and renal tumors are less frequent. Treatment and prognosis will depend on whether they are isolated or multiple, size and location, the presence or absence of extrahepatic neoplastic disease, age, stage of the initial disease, initial treatments instituted, time of evolution, and clinical condition of the patient. Recently, a high number of oncological therapies including monotherapy or in combination, neoadjuvants or adjuvants, and immuno-oncological treatments have been developed and tested, increasing disease-free time and survival.
View Article and Find Full Text PDFEpidemiol Serv Saude
January 2025
Universidade de Brasília, Faculdade de Ceilândia, Brasília, DF, Brasil.
Objective: To investigate the evolution of prevalence of catastrophic health expenditure in the Brazilian Federal District at three different times (2003, 2009 and 2018), as well, to identify the composition of outof- pocket expenditure in the respective years.
Method: Time series study, using descriptive data from the Family Budget Survey. Prevalence was stratified by consumption quintiles.
Phys Rev Lett
December 2024
Key Laboratory for Laser Plasmas and School of Physics and Astronomy, and Collaborative Innovation Center of IFSA, Shanghai Jiao Tong University, Shanghai 200240, China.
Time-dependent density functional theory (TDDFT) is widely used for understanding and predicting properties and behaviors of matter. As one of the fundamental theorems in TDDFT, Van Leeuwen theorem [Phys. Rev.
View Article and Find Full Text PDFPhys Rev Lett
December 2024
California Institute of Technology, Division of Chemistry and Chemical Engineering, Pasadena, California 91125, USA.
We introduce a change of perspective on tensor network states that is defined by the computational graph of the contraction of an amplitude. The resulting class of states, which we refer to as tensor network functions, inherit the conceptual advantages of tensor network states while removing computational restrictions arising from the need to converge approximate contractions. We use tensor network functions to compute strict variational estimates of the energy on loopy graphs, analyze their expressive power for ground states, show that we can capture aspects of volume law time evolution, and provide a mapping of general feed-forward neural nets onto efficient tensor network functions.
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