Free PCR virus detection via few-layer bismuthene and tetrahedral DNA nanostructured assemblies

In this work we describe a highly sensitive method based on a biocatalyzed electrochemiluminescence approach. The system combines, for the first time, the use of few-layer bismuthene (FLB) as a platform for the oriented immobilization of tetrahedral DNA nanostructures (TDNs) specifically designed and synthetized to detect a specific SARS-CoV-2 gene sequence. In one of its vertices, these TDNs contain a DNA capture probe of the open reading frame 1 ab (ORF1ab) of the virus, available for the biorecognition of the target DNA/RNA. At the other three vertices, there are thiol groups that enable the stable anchoring/binding to the FLB surface. This novel geometry/approach enables not only the binding of the TDNs to surfaces, but also the orientation of the capture probe in a direction normal to the bismuthine surface so that it is readily accessible for binding/recognition of the specific SARS-CoV-2 sequence. The analytical signal is based on the anodic electrochemiluminescence (ECL) intensity of luminol which, in turn, arises as a result of the reaction with H2O2, generated by the enzymatic reaction of glucose oxidation, catalyzed by the biocatalytic label avidin-glucose oxidase conjugate (Av-GOx), which acts as co-reactant in the electrochemiluminescent reaction. The method exhibits a limit of detection (LOD) of 4.31 aM and a wide linear range from 14.4 aM to 1.00 μM, and its applicability was confirmed by detecting SARS-CoV-2 in nasopharyngeal samples from COVID-19 patients without the need of any amplification processPID2020-116728RB-I00, PID2020-116661RB-I00, PID2020-119352RB-I00, PDC2021-120782-C2, PID2022-138908NB-C31, CTQ2015-71955-REDT, S2018/NMT-434

A Simple Mathematical Model Based on the Cancer Stem Cell Hypothesis Suggests Kinetic Commonalities in Solid Tumor Growth

Background: The Cancer Stem Cell (CSC) hypothesis has gained credibility within the cancer research community. According to this hypothesis, a small subpopulation of cells within cancerous tissues exhibits stem-cell-like characteristics and is responsible for the maintenance and proliferation of cancer. Methodologies/Principal Findings: We present a simple compartmental pseudo-chemical mathematical model for tumor growth, based on the CSC hypothesis, and derived using a ‘‘chemical reaction’ ’ approach. We defined three cell subpopulations: CSCs, transit progenitor cells, and differentiated cells. Each event related to cell division, differentiation, or death is then modeled as a chemical reaction. The resulting set of ordinary differential equations was numerically integrated to describe the time evolution of each cell subpopulation and the overall tumor growth. The parameter space was explored to identify combinations of parameter values that produce biologically feasible and consistent scenarios. Conclusions/Significance: Certain kinetic relationships apparently must be satisfied to sustain solid tumor growth and to maintain an approximate constant fraction of CSCs in the tumor lower than 0.01 (as experimentally observed): (a) the rate of symmetrical and asymmetrical CSC renewal must be in the same order of magnitude; (b) the intrinsic rate of renewal and differentiation of progenitor cells must be half an order of magnitude higher than the corresponding intrinsic rates for cancer stem cells; (c) the rates of apoptosis of the CSC, transit amplifying progenitor (P) cells, and terminally differentiate

Geographic patterns of tree dispersal modes in Amazonia and their ecological correlates

Aim: To investigate the geographic patterns and ecological correlates in the geographic distribution of the most common tree dispersal modes in Amazonia (endozoochory, synzoochory, anemochory and hydrochory). We examined if the proportional abundance of these dispersal modes could be explained by the availability of dispersal agents (disperser-availability hypothesis) and/or the availability of resources for constructing zoochorous fruits (resource-availability hypothesis). Time period: Tree-inventory plots established between 1934 and 2019. Major taxa studied: Trees with a diameter at breast height (DBH) ≥ 9.55 cm. Location: Amazonia, here defined as the lowland rain forests of the Amazon River basin and the Guiana Shield. Methods: We assigned dispersal modes to a total of 5433 species and morphospecies within 1877 tree-inventory plots across terra-firme, seasonally flooded, and permanently flooded forests. We investigated geographic patterns in the proportional abundance of dispersal modes. We performed an abundance-weighted mean pairwise distance (MPD) test and fit generalized linear models (GLMs) to explain the geographic distribution of dispersal modes. Results: Anemochory was significantly, positively associated with mean annual wind speed, and hydrochory was significantly higher in flooded forests. Dispersal modes did not consistently show significant associations with the availability of resources for constructing zoochorous fruits. A lower dissimilarity in dispersal modes, resulting from a higher dominance of endozoochory, occurred in terra-firme forests (excluding podzols) compared to flooded forests. Main conclusions: The disperser-availability hypothesis was well supported for abiotic dispersal modes (anemochory and hydrochory). The availability of resources for constructing zoochorous fruits seems an unlikely explanation for the distribution of dispersal modes in Amazonia. The association between frugivores and the proportional abundance of zoochory requires further research, as tree recruitment not only depends on dispersal vectors but also on conditions that favour or limit seedling recruitment across forest types

Linear relationships between model parameters.

<p>Certain linear relationships between CSC self-renewal and differentiation kinetic parameters allow identification of families of feasible solutions: (A) By increasing Φ_2/1 while proportionally decreasing Φ_4/1 a family of feasible model solutions can be found. Similarly, (B) Φ_3/1 and Φ_4/1 are linearly related.</p

Linear relationships between model parameters.

<p>The intrinsic apoptotic rates of CSC and P cells are also linearly related. Proportional increases in Φ_6/1 and Φ_7/1 can reveal a family of feasible model solutions.</p

Analysis of the effect of small perturbations around a particular solution.

<p>(*) ss indicates that the solution reaches a steady state d[CSC/N]/dt = 0 in less than 30 arbitrary time units; (+) indicates that d[CSC/N]/dt>0 after 30 arbitrary time units; (−) indicates that d[CSC/N]/dt<0 after 30 arbitrary time units.</p><p>Rows corresponding to experiments 1 to 14 were built by varying only one Φ_i/j value at a time, while the rest were kept constant with respect to the reference case (Exp. 0). Column 10 indicates whether the CSC/N fraction reaches a steady state; that is, (d[CSC/N]/dt) = 0. If that is the case, the CSC/N fraction is indicated in column 11.</p

Three experimental data sets, corresponding to the different scenarios referred to in the text, were used to validate the model.

<p>A comparison between the experimental data (• black circles) and the model curve-fit (yellow solid line) is provided for each set. The CSC/N fraction (blue line) and P/N fraction (red line) are plotted for each experimental scenario. For each simulation, the vector Φ_i/j = [Φ_2/1, Φ_3/1, Φ_4/1, Φ_5/4, Φ_6/1, Φ_7/1, Φ_8/1] = [1.0, 0.01, 5.35, 0.8, 0.01, 0.1, 1.0] was multiplied by a different scaling factor (17.5×Φ_i/j; 5.0×Φ_i/j; and 7.0×Φ_i/j respectively). (A) A human prostate tumor transplanted into a mouse model <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0026233#pone.0026233-Ellis1" target="_blank">[69]</a>; it is assumed that the original percentage of CSCs was 1%; (B) 2000 CSCs from a breast primary tumor implanted in NOD/SCID mice <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0026233#pone.0026233-Ginestier1" target="_blank">[25]</a>; and (C) 1×10⁵ colon CSCs isolated and implanted in NOD/SCID mice <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0026233#pone.0026233-RicciVitiani1" target="_blank">[13]</a>. For all simulations, the vector Φ_i/j = Φ_i/j = [Φ_2/1, Φ_3/1, Φ_4/1, Φ_5/4, Φ_6/1, Φ_7/1, Φ_8/1] = [1.0, 0.01, 5.35, 0.8, 0.01, 0.1, 1.0] was used.</p

Basic assumptions of the model.

<p>(A) Different cell populations are found in solid tumors. For simplicity, the model considers only three cell compartments or differentiation stages (CSC = Cancer Stem Cells, P = progenitor cells, D = terminally differentiated cells, and M = dead cells). All the possible different stages of differentiation of progenitor cells (P1, P2, etc., have been lumped into the cell subtype P. CSC, P, and D cell subtypes undergo cell death through reactions R6, R7, and R8 respectively. (B) Cellular division events considered in the model: symmetrical self-renewal of cancer stem cells (R1); asymmetrical renewal of cancer stem cells (R2); symmetrical differentiation of cancer stem cells into progenitor cells (R3); symmetrical proliferation of progenitor cells (R4); and symmetrical differentiation of progenitor cells into fully differentiated cells (R5).</p

Feasible solutions for the model.

<p>Within the explored parameter space, once a feasible steady state solution is found, others can be found on the vicinity of a specific vector Φ_i/j. (A) Solution for the vector Φ_i/j = [1.5, 0.005, 5.35, 0.8, 0.01, 0.1,1.0]. (B) Solution for the vector Φ_i/j = [1.5, 0.01, 5.325, 0.8, 0.01, 0.1, 1.0].</p

Model output.

<p>(A) The model estimates the time evolution of each one of the cell subpopulations considered, fully differentiated cells (D; blue line); progenitor cells (P; red line); and cancer stem cells (CSC; green line). (B) by plotting the cell fractions for each cell population (D/N; blue line), (P/N; red line), and (CSC/N; green line), it is possible to search for feasible and biologically consistent solutions (i.e. d[CSC/N]/dt = 0; C/N<0.01). (C) Only a relatively small set of parameter combinations result in solutions that satisfy the constraint d[CSC/N]/dt = 0. The solution defined by the vector Φ_i/j = [1.0, 0.01, 5.35, 0.8, 0.01, 0.1, 1.0] satisfy d[CSC/N]/dt = 0 only if when the specific value of Φ_4/1 = 5.35 was used (green line). Values of Φ_4/1 = <i>k₄</i>/<i>k₁</i>>3.5 (purple and light blue line) cause d[CSC/N]/dt<0; and values of Φ_4/1 = <i>k₄</i>/<i>k₁</i><3.5 (red and dark blue line) cause d[CSC/N]/dt>0.</p