Bacterial Proliferation
Bacterial Proliferation - Related Videos
02:23
Abnormal Proliferation
0 Views •
2021
Under normal conditions, most adult cells remain in a non-proliferative state unless stimulated by internal or external factors to replace lost cells. Abnormal cell proliferation is a condition in which the cell's growth exceeds and is uncoordinated with normal cells. In such situations, cell division persists in the same excessive manner even after cessation of the stimuli, leading to persistent tumors. The tumor arises from the damaged cells that replicate to pass the damage to the daughter...
02:23
Abnormal Proliferation
0 Views •
2023
Under normal conditions, most adult cells remain in a non-proliferative state unless stimulated by internal or external factors to replace lost cells. Abnormal cell proliferation is a condition in which the cell's growth exceeds and is uncoordinated with normal cells. In such situations, cell division persists in the same excessive manner even after cessation of the stimuli, leading to persistent tumors. The tumor arises from the damaged cells that replicate to pass the damage to the daughter...
03:57
Bacterial Infection Quantitation Assay: A Method to Quantify Intraocular Bacterial Load in Mouse Model of Bacterial Endophthalmitis
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2025
This video describes the technique of quantifying bacterial infection from eye homogenates obtained from a murine model of bacterial endophthalmitis caused by Bacillus cereus. This technique helps study the host immune response and its dependency on the host and ocular bacterial gene expression in murine models.
10:21
Proliferation and Differentiation of Murine Myeloid Precursor 32D/G-CSF-R Cells
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Cited by 3 •
2018
Here detailed protocols for culturing the murine myeloid precursor 32D/G-CSF-R cell line, performing viral infections, and carrying out proliferation and differentiation assays are presented. This cell line is suitable for studying myeloid cell development, and the role of genes of interest in myeloid cell growth and neutrophilic differentiation.
04:10
The Use of Carboxyfluorescein Diacetate Succinimidyl Ester (CFSE) to Monitor Lymphocyte Proliferation
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Cited by 214 •
2010
CFSE covalently labels long-lived intracellular molecules with the fluorescent dye, carboxyfluorescein. As such, when a CFSE-labeled cell divides, its progeny have half the amount of fluorescence, which can thereby be used to assess cell division. This article describes the procedures typically used for labeling mouse lymphocytes with CFSE.
FAQs
During an exponential phase, each division adds cells in proportion to the population already present. A differential-equation model represents this change with a growth rate, while doubling time expresses how long the population takes to multiply by two. Shorter doubling times indicate faster proliferation under the modeled conditions, allowing researchers to compare cultures quantitatively.
The logistic model accounts for conditions that restrict continued expansion, especially limited nutrients or space. Its curve initially resembles exponential growth, then slows as those constraints become important. This leveling pattern helps distinguish unrestricted expansion from a population approaching environmental limits, preventing researchers from overestimating later population sizes by extending an early growth rate indefinitely.
Doubling time provides an intuitive measure for comparing growth conditions because it describes the interval required for the population to double. A shorter interval corresponds to a higher effective growth rate, whereas a longer interval indicates slower increase. Researchers can therefore use doubling times to evaluate how environmental conditions influence modeled proliferation without relying only on final population counts.
Differential equations let a model represent population size as changing over time rather than as a single endpoint. A growth-rate term describes how rapidly that quantity changes, so the equation can generate trajectories and support estimates at later times. This mathematical representation connects biological observations, such as changing cell numbers, with predictions about proliferation under specified conditions.
A researcher can begin with a starting population, select a growth rate or doubling time, and project population size with a mathematical model. If nutrients or space are expected to limit expansion, the model can instead use a logistic curve. Comparing these projections with observed changes helps researchers evaluate growth conditions and identify whether unrestricted or limited growth better fits the situation.
Models can project how a bacterial population changes over time, helping researchers estimate contamination and compare growth under different conditions. They can also represent changes produced by interventions such as antibiotics, allowing population trajectories before and after treatment to be evaluated mathematically. These outcomes support quantitative assessment of whether an intervention alters the expected proliferation pattern.