Fractal dimension analysis: A new tool for analyzing colony-forming units.
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ABSTRACT:
SUBMITTER: Nai GA
PROVIDER: S-EPMC8374233 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Measuring the abundance of microbes in a sample is a common procedure with a long history, but best practices are not well-conserved across microbiological fields. Serial dilution methods are commonly used to dilute bacterial cultures to produce countable numbers of colonies, and from these counts, to infer bacterial concentrations measured in colony-forming units (CFUs). The most common methods to generate data for CFU point estimates involve plating bacteria on (or in) a solid growth medium and counting their resulting colonies or counting the number of tubes at a given dilution that have growth. Traditionally, these types of data have been analyzed separately using different analytic methods. Here, we build a direct correspondence between these approaches, which allows one to extend the use of the most probable number method from the liquid tubes experiments, for which it was developed, to the growth plates by viewing colony-sized patches of a plate as equivalent to individual tubes. We also discuss how to combine measurements taken at different dilutions, and we review several ways of analyzing colony counts, including the Poisson and truncated Poisson methods. We test all point estimate methods computationally using simulated data. For all methods, we discuss their relevant error bounds, assumptions, strengths, and weaknesses. We provide an online calculator for these estimators.Estimation of the number of microbes in a sample is an important problem with a long history. Yet common practices, such as combining results from different measurements, remain sub-optimal. We provide a comparison of methods for estimating abundance of microbes and detail a mapping between different methods, which allows to extend their range of applicability. This mapping enables higher precision estimates of colony-forming units (CFUs) using the same data already collected for traditional CFU estimation methods. Furthermore, we provide recommendations for how to combine measurements of colony counts taken across dilutions, correcting several misconceptions in the literature.
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Project description:To assess if descendants of the hypertrophic chondrocytes behaved as skeletal stem and progenitor cells, we performed colony unit formation. We observed a near equal proportion of colonies derived from hypertrophic chondrocytes (tomato+) and derived from other sources (likely periosteum). We performed bulk RNA-sequencing on 3 colonies from each origin to compare the gene profiles and potential differentiation capacity or niche support.
2022-02-16 | GSE179174 | GEO
Project description:Currently, in the state of Colorado and all other states within the United States of America with legalized marijuana programs, testing is required for bacteria, yeast, and mold on marijuana products. The Code of Colorado Regulations, 1 CCR 212-1, considers a passing result when a 1 g sample contains <104 colony forming units (CFU) for the total yeast and mold count (TYMC). These measurements are usually obtained by manually counting colonies on petri-dishes or 3 M™ Petrifilms™, which is a time consuming and user subjective process. Therefore, an automated counting method utilizing ImageJ has been developed for CFU analysis of TYMC on Petrifilms. The performance of this colony counting method was demonstrated by comparing manual and automated counts from marijuana flower samples containing spikes of Candida albicans as well as samples that tested positive for the presence of yeast and mold. Fifteen images of Petrifilms showing various concentrations of colonies were studied by fifteen users at two institutions using both the automated and manual counting methods. All counts from the automated ImageJ procedure were within 12% of those obtained manually. In twelve out of fifteen Petrifilms, the average count of the automated method was statistically similar to the manual counts. The statistical differences of the other three samples were observed to be random and caused by user errors. The automated counting method could be used to quickly count numbers that are as high as 400 CFUs, reducing time of analysis with improved documentation because the images and the electronic colony counts can be saved on a computer or cloud for long term storage and data access.
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Project description:Several bone marrow-derived cell populations may have angiogenic activity, including cells termed endothelial progenitor cells. Decreased numbers of circulating angiogenic cell populations have been associated with increased cardiovascular risk. However, few data exist from large, unselected samples, and the genetic determinants of these traits are unclear.We examined the clinical and genetic correlates of early-outgrowth colony-forming units (CFUs) in 1799 participants of the Framingham Heart Study (mean age, 66 years; 54% women). Among individuals without cardiovascular disease (n = 1612), CFU number was inversely related to advanced age (P = 0.004), female sex (P = 0.04), and triglycerides (P = 0.008) and positively related to hormone replacement (P = 0.008) and statin therapy (P = 0.027) in stepwise multivariable analyses. Overall, CFU number was inversely related to the Framingham risk score (P = 0.01) but not with prevalent cardiovascular disease. In genome-wide association analyses in the entire sample, polymorphisms were associated with CFUs at the MOSC1 locus (P = 3.3 × 10(-7)) and at the SLC22A3-LPAL2-LPA locus (P = 4.9 × 10(-7)), a previously replicated susceptibility locus for myocardial infarction. Furthermore, alleles at the SLC22A3-LPAL2-LPA locus that were associated with decreased CFUs were also related to increased risk of myocardial infarction (P = 1.1 × 10(-4)).In a community-based sample, early-outgrowth CFUs are inversely associated with select cardiovascular risk factors. Furthermore, genetic variants at the SLC22A3-LPAL2-LPA locus are associated with both decreased CFUs and an increased risk of myocardial infarction. These findings are consistent with the hypothesis that decreased circulating angiogenic cell populations promote susceptibility to myocardial infarction.
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Project description:Highlights • Epidemic curves can be approached from a fractal interpolation point of view.• Looking at the Covid-19 epidemic curves from a fractal point of view might benefit the medical community to understand better the dynamics and evolution of the pandemic.• Fractal interpolation of data regarding Covid-19 can help retrieve missing pieces of information due to limited testing.• Analyzing maps of the spreading of Covid-19 in different countries from a fractal dimension point of view can be a useful tool in assessing the complexity of the pandemic on the territory of a country. The present paper proposes a reconstruction of the epidemic curves from the fractal interpolation point of view. Looking at the epidemic curves as fractal structures might be an efficient way to retrieve missing pieces of information due to insufficient testing and predict the evolution of the disease. A fractal approach of the epidemic curve can contribute to the assessment and modeling of other epidemics. On the other hand, we have considered the spread of the epidemic in countries like Romania, Italy, Spain, and Germany and analyzed the spread of the disease in those countries based on their fractal dimension.
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Project description:Fractal Dimension (FD) has shown to be a promising means to describe the morphology of cortical structures across different neurologic and psychiatric conditions, displaying a good sensitivity in capturing atrophy processes. In this study, we aimed at exploring the morphology of cortical areas by means of FD in 58 female patients with Anorexia Nervosa (AN) (38 currently underweight and 20 fully recovered) and 38 healthy controls (HC). All participants underwent high-resolution MRI. Surface extraction was completed using FreeSurfer, FD was computed using the calcFD toolbox. The whole cortex mean FD value was lower in acute AN patients compared to HC (p < 0.001). Recovered AN patients did not show differences in the global FD when compared to HC. However, some brain areas showed higher FD in patients than controls, while others showed the opposite pattern. Parietal regions showed lower FD in both AN groups. In acute AN patients, the FD correlated with age (p < 0.001), body mass index (p = 0.019) and duration of illness (p = 0.011). FD seems to represent a feasible method to explore cortical complexity in patients with AN since it demonstrated to be sensitive to the effects of both severity and duration of malnutrition.
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Project description:Fractals are geometric objects that are self-similar at different scales and whose geometric dimensions differ from so-called fractal dimensions. Fractals describe complex continuous structures in nature. Although indications of self-similarity and fractality of complex networks has been previously observed, it is challenging to adapt the machinery from the theory of fractality of continuous objects to discrete objects such as networks. In this article, we identify and study fractal networks using the innate methods of graph theory and combinatorics. We establish analogues of topological (Lebesgue) and fractal (Hausdorff) dimensions for graphs and demonstrate that they are naturally related to known graph-theoretical characteristics: rank dimension and product dimension. Our approach reveals how self-similarity and fractality of a network are defined by a pattern of overlaps between densely connected network communities. It allows us to identify fractal graphs, explore the relations between graph fractality, graph colourings and graph descriptive complexity, and analyse the fractality of several classes of graphs and network models, as well as of a number of real-life networks. We demonstrate the application of our framework in evolutionary biology and virology by analysing networks of viral strains sampled at different stages of evolution inside their hosts. Our methodology revealed gradual self-organization of intra-host viral populations over the course of infection and their adaptation to the host environment. The obtained results lay a foundation for studying fractal properties of complex networks using combinatorial methods and algorithms.
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Project description:A failure of adaptive inference-misinterpreting available sensory information for appropriate perception and action-is at the heart of clinical manifestations of schizophrenia, implicating key subcortical structures in the brain including the hippocampus. We used high-resolution, three-dimensional (3D) fractal geometry analysis to study subtle and potentially biologically relevant structural alterations (in the geometry of protrusions, gyri and indentations, sulci) in subcortical gray matter (GM) in patients with schizophrenia relative to healthy individuals. In particular, we focus on utilizing Fractal Dimension (FD), a compact shape descriptor that can be computed using inputs with irregular (i.e., not necessarily smooth) surfaces in order to quantify complexity (of geometrical properties and configurations of structures across spatial scales) of subcortical GM in this disorder. Probabilistic (entropy-based) information FD was computed based on the box-counting approach for each of the seven subcortical structures, bilaterally, as well as the brainstem from high-resolution magnetic resonance (MR) images in chronic patients with schizophrenia (n = 19) and age-matched healthy controls (n = 19) (age ranges: patients, 22.7-54.3 and healthy controls, 24.9-51.6 years old). We found a significant reduction of FD in the left hippocampus (median: 2.1460, range: 2.07-2.18 vs. median: 2.1730, range: 2.15-2.23, p<0.001; Cohen's effect size, U3 = 0.8158 (95% Confidence Intervals, CIs: 0.6316, 1.0)), the right hippocampus (median: 2.1430, range: 2.05-2.19 vs. median: 2.1760, range: 2.12-2.21, p = 0.004; U3 = 0.8421 (CIs: 0.5263, 1)), as well as left thalamus (median: 2.4230, range: 2.40-2.44, p = 0.005; U3 = 0.7895 (CIs: 0.5789, 0.9473)) in schizophrenia patients, relative to healthy individuals. Our findings provide in-vivo quantitative evidence for reduced surface complexity of hippocampus, with reduced FD indicating a less complex, less regular GM surface detected in schizophrenia.
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Project description:OBJECTIVES:We had developed a method that can help detect and identify lymph nodes affected by the neoplastic process. Our group evaluated the fractal dimension (FD) and X-ray attenuation (XRA) of lymph nodes in HL and compared to their metabolic activity as measured by 18F-FDG-PET examination. METHODS:The training set included 72 lymph nodes from 31 consecutive patients, and the tested set of 71 lymph nodes from next 19 patients. The measurement of FD of each lymph node was performed before the start of therapy using original software. X-ray attenuation (XRA) expressed in HU (Hounsfield Units) from CT scans was compared with the metabolic activity of the lymphatic nodes, measured by 18F-FDG-PET examination. RESULTS:Significant differences were observed between XRAmax and FDmax values in assessing the PET(+) and PET(-) nodes. All nodes were scored from 0 to 2. The HUFRA test properly qualified 95% with a score of 2 and 0 points as PET(+) or PET(-). CONCLUSION:The HUFRA test can differentiate about 70-80% of lymph nodes as PET(+) or PET(-) based solely on the CT examination. It can be useful in patients who were not subjected to 18FFDG-PET/CT examination before the treatment, or who had an unreliable result of 18F-FDG-PET/CT with further research requirements.
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