Swarming behaviour is a type of bacterial motility that has been found to be dependent on reaching a local density threshold of cells. With this in mind, the process through which cell-to-cell interactions develop and how an assembly of cells reaches collective motility becomes increasingly important to understand. Additionally, populations of cells and organisms have been modelled through graphs to draw insightful conclusions about population dynamics on a spatial level. In the present study, we make use of analogous random graph structures to model the formation of large chain subgraphs, representing interactions between multiple cells, as a random graph Markov process. Using numerical simulations and analytical results on how quickly paths of certain lengths are reached in a random graph process, metrics for intercellular interaction dynamics at the swarm layer that may be experimentally evaluated are proposed.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4759469 | PMC |
http://dx.doi.org/10.1111/jcmm.12757 | DOI Listing |
J Mater Chem B
January 2025
Biomaterials Drug Delivery and Nanotechnology Unit, Centre for Biomedical and Biomaterials Research (CBBR), University of Mauritius, Réduit, Mauritius.
Tissue regeneration after a wound occurs through three main overlapping and interrelated stages namely inflammatory, proliferative, and remodelling phases, respectively. The inflammatory phase is key for successful tissue reconstruction and triggers the proliferative phase. The macrophages in the non-healing wounds remain in the inflammatory loop, but their phenotypes can be changed interactions with nanofibre-based scaffolds mimicking the organisation of the native structural support of healthy tissues.
View Article and Find Full Text PDFFront Immunol
January 2025
School of Nursing, Zunyi Medical University, Zunyi, China.
Background: Most patients initially diagnosed with non-muscle invasive bladder cancer (NMIBC) still have frequent recurrence after urethral bladder tumor electrodesiccation supplemented with intravesical instillation therapy, and their risk of recurrence is difficult to predict. Risk prediction models used to predict postoperative recurrence in patients with NMIBC have limitations, such as a limited number of included cases and a lack of validation. Therefore, there is an urgent need to develop new models to compensate for the shortcomings and potentially provide evidence for predicting postoperative recurrence in NMIBC patients.
View Article and Find Full Text PDFPak J Med Sci
January 2025
Sadia Anwer Research Student, Biochemistry, Federal Urdu University of Arts, Science & Technology, Karachi, Pakistan.
Objective: To explore the effect of seeds powder { 500 mg} capsule in diabetes Type-2 (T2DM) patients in Karachi.
Methods: A randomized selection of 40 T2DM patients from Sindh Government Hospital New Karachi with their consents was done for a non-blinded controlled trial from October to December 2019 and divided into P (Positive Control, metformin 500 mg) & T (Test, + was also included, using the same dosage of CapCASP on twenty healthy volunteers. The data were analyzed using an online graph pad student's t-test and a one-way ANOVA (SPSS version 24) metformin 500mg each).
Background: Household air pollution is a major contributor to cardiovascular disease burden in women in Sub-Saharan Africa. However, little is known about exposures during pregnancy or the effect of clean cooking interventions on postpartum blood pressure trajectories.
Methods: The Ghana Randomized Air Pollution and Health Study (GRAPHS) randomized 1414 non-smoking women in the first and second trimesters to liquefied petroleum gas (LPG) or improved biomass stoves - vs control (traditional three-stone open fire).
Bayesian Anal
June 2024
Department of Statistics, Purdue University, West Lafayette, IN 47907, USA.
The exponential random graph model (ERGM) is a popular model for social networks, which is known to have an intractable likelihood function. Sampling from the posterior for such a model is a long-standing problem in statistical research. We analyze the performance of the stochastic gradient Langevin dynamics (SGLD) algorithm (also known as noisy Longevin Monte Carlo) in tackling this problem, where the stochastic gradient is calculated via running a short Markov chain (the so-called inner Markov chain in this paper) at each iteration.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!