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0.0 0.5 1.0 1.5 RDA 1 FIG. 4 in Response of bryophytes to disturbances in managed forests. A case study from a Polish forest

0.0 0.5 1.0 1.5 RDA 1 FIG. 4. — Redundancy analysis biplot illustrating the ordination of most frequent bryophyte species colonizing tree trunks in relation to the statistically significant environmental variables for the plots with the presence of tree host species (n=41). Abbreviations as in Fig. 3.

FIG. 6 in Response of bryophytes to disturbances in managed forests. A case study from a Polish forest

FIG. 6. — Redundancy analysis biplot illustrating the ordination of most frequent bryophyte species colonizing dead wood in relation to the statistically significant environmental variables for the plots with the presence of decaying logs (n=80). Abbreviations as in Fig. 3

FIG. 5 in Response of bryophytes to disturbances in managed forests. A case study from a Polish forest

FIG. 5. — Redundancy analysis biplot illustrating the ordination of most frequent bryophyte species colonizing tree bases in relation to the statistically significant environmental variables for the plots with the presence of tree host species (n=96). Abbreviations as in Fig. 3.

FIG. 2 in Response of bryophytes to disturbances in managed forests. A case study from a Polish forest

FIG. 2. — Frequency of occurrence of bryophytes generally and in the four types of substrates considered.

opencc-by-4.0Jun 2024View details →

Collected laboratory data for: Theoretical basis and analyses of temperature responses of water-saturated rocks to rapid changes in confining pressure

<p><span>In this data submission, there are three collected laboratory data sets used in the submitted manuscript: Theoretical basis and analyses of temperature responses of water-saturated rocks to rapid changes in confining pressure. The first data set includes the </span><span>thermophysical properties of the main rock-forming minerals in the crust and water. The second data set includes </span><span>the poroelastic constants for compact and porous rocks. </span><span>The third data set includes <span>the </span>chemical composition (Oxides) and CIPW norm minerals of Karatsu basalt (KBT), and isothermal bulk modulus (<em>K</em><sub>i</sub>) of each mineral.</span></p>

opencc-by-4.0Jun 2024View details →

Accompanying data for the paper "Accounting for the mechanical response of the cell membrane during the uptake of random nanoparticles"

<h2>Contributions</h2> <ul> <li><strong>Iaquinta Sarah</strong> did contribute to the first draft edition, the development of the theoretical background of the algorithms and their implementation</li> <li><strong>Khazaie Sharam</strong> did contribute to the revision and edition of the draft, and to the development of the theoretical background of the algorithms</li> <li><strong>Jacquemin Frédéric</strong> did contribute to the project management and to the revision of the article.</li> <li><strong>Fréour Sylvain</strong> did contribute to the project management and to the revision of the article.</li> </ul> <h2>Funding sources</h2> <p>i-Site NExT : Grant/Award Number: ANR-16-IDEX-0007, Région Pays de la Loire and CNRS (French National Centre for Scientific Research).</p> <h2>Data structure and information</h2> <ul> <li>code - <code>np_uptake source and data directory</code> <ul> <li>workflow - <code>scripts to reproduce figures</code></li> <li>np_uptake - <code>source code producing results and figures</code> <ul> <li>figures - <code>utility module to produce figures</code></li> <li>model - <code>see detailed description below</code></li> <li>metamodel_implementation - <code>see detailed description below</code></li> <li>sensitivity_analysis - <code>see detailed description below</code></li> </ul> </li> </ul> </li> </ul> <h3>Detailed description</h3> <h4>Abstract</h4> <p>In order to improve the efficiency of the delivery of cancer treatments to cancer cells, the cellular uptake of nanoparticles (NPs), used as drug delivery systems, is numerically investigated through a mechanical approach. The objective is to optimize the NP's mechanical and geometrical properties to enhance their entry into cancer cells while avoiding benign ones. In previous studies, these properties are modeled as constant during the process of cellular uptake. However, recent observations of the displacement of the membrane's constituents towards the region in the cell membrane where the uptake of the NPs takes place show that the mechanical properties of the membrane vary during this process. Reason for writing The important contribution of adhesion to the wrapping process is already well documented in literature. It is therefore crucial to model this parameter properly as the conclusions made with a constant adhesion model may not be accurate compared to reality. Methodology Based on the existing knowledge on the reaction of membrane constituents to interaction with NPs, a 3-parameter sigmoidal function, accounting for the delay, amplitude, and speed of the reaction, has been used to model the evolution of adhesion. A variance-based sensitivity analysis has then been performed in order to quantify the influence of these parameters on the outputs of the model. Results It was found that the introduction of a variable adhesion tends to alter the predictions of endocytosis of NPs. The contribution of the amplitude and delay is respectively 0.32 and 0.43 times as important as that of the NP's aspect ratio, which is the prominent parameter. The influence of the slope of the transition is the least important parameter and does not appear to contribute to endocytosis. Implications Hence, models of the cellular uptake of NPs should use a variable, instead of constant, adhesion in order a representative as possible of the behavior of the cell membrane. The predictions are different from those obtained using a model with constant adhesion.</p> <h4>Code</h4> <p>This repository is divided into 4 folders:</p> <ul> <li> <p><em>model</em>: contains the code used to compute the total variation of energy of the interface between a circular NP and a membrane by accounting for the mechanical accommodation of the latter. This folder also contains the routine to determine the final wrapping phase of the system.</p> </li> <li> <p><em>metamodel_implementation</em>: contains a script to check for the representativeness of the dataset used to create a metamodel, a script to create Kriging and PCE metamodels using the Openturns opensource library, and a routine to validate the metamodel that has just been created;</p> </li> <li> <p><em>sensitivity_analysis</em>: contains a script that allows to create samples based on the Kriging metamodels that have been created and exported as .pkl files in the metamodel folder. These samples are then used to the apply sensitivity algorithms. The user can choose among the various sensitivity algorithms provided by Openturns. For PCE metamodels, a routine is implemented to directly get the Sobol indices from the coefficients of the PCE metamodel. The indices can be plotted through plot routines;</p> </li> <li> <p><em>figures</em>: contains a utils script to display the graphs and save them as PNG files with consistency.</p> </li> </ul>

opencc-by-4.0Feb 2024View details →

Figure 5 in Germination responses of the invasive hedge cactus (Cereus uruguoyonus) to environmental factors

Figure 5. Seed survival of two Cereus uruguoyonus accessions under controlled aging at 60% relative humidity and 45 C. Parameter estimates for the negative logistic regression model fit to the data are given in Table 1.

opencc-by-4.0Feb 2024View details →

Figure 2 in Germination responses of the invasive hedge cactus (Cereus uruguoyonus) to environmental factors

Figure 2. Effect of salt stress on the cumulative germination of four seed accessions of Cereus uruguoyonus. Values with the same letter do not differ at a 5% level of significance.

opencc-by-4.0Feb 2024View details →

Figure 3 in Germination responses of the invasive hedge cactus (Cereus uruguoyonus) to environmental factors

Figure 3. Effect of water stress on the cumulative germination of four seed accessions of Cereus uruguoyonus. Values with the same letter do not differ at a 5% level of significance.

Figure 1 in Herbicide response and germination behavior of two goosegrass (Eleusine indica) populations in the Australian environment

Figure 1. Effect of paraquat dose on (A) seedling survival, (B) spike number (percent of nontreated control), and (C) aboveground biomass (percent of nontreated control) of the two Australian populations (Gatton and Ingham) of Eleusine indica. Error bars represent the standard error of the mean.

Figure 5 in Herbicide response and germination behavior of two goosegrass (Eleusine indica) populations in the Australian environment

Figure 5. Effect of osmotic potential on the germination of the two Australian populations (Gatton and Ingham) of Eleusine indica incubated under alternating light/ dark for 28 d at 30/20 C.The lines represent a three-parameter sigmoid model fit to the germination data in response to concentrations of osmotic potentials.

Figure 3 in Herbicide response and germination behavior of two goosegrass (Eleusine indica) populations in the Australian environment

Figure 3. Effect of light/dark regimes on the germination of the two Australian populations (Gatton and Ingham) populations of Eleusine indica. Seeds were incubated for 28 d at alternating day/night temperatures of 30/20 C. Error bars represent the LSD at the 5% level of significance.

Figure 4 in Herbicide response and germination behavior of two goosegrass (Eleusine indica) populations in the Australian environment

Figure 4. Effect of sodium chloride concentration on the germination of the two Australian populations (Gatton and Ingham) of Eleusine indica incubated under alternating light/dark for 28 d at 30/20 C.The lines represent a three-parameter logistic model fit to the germination data in response to sodium chloride concentrations.

Figure 2 in Herbicide response and germination behavior of two goosegrass (Eleusine indica) populations in the Australian environment

Figure 2. Effect of alternating day/night temperatures (15/5 to 35/25 C) on the germination of the two Australian populations (Gatton and Ingham) of Eleusine indica. Error bars represent the LSD at the 5% level of significance.

opencc-by-4.0Jun 2024View details →

Auxiliary data for Moustakis et al. 2024 "Temperature overshoot responses to ambitious forestation in an Earth System Model"

<p>The netcdf file "Moustakis_et_al_2024_Data.nc" contains all the key variables presented in the figures of the manuscript of Moustakis et al. 2024: "Temperature overshoot responses to ambitious forestation in an Earth System Model".</p> <p>Please read the README.txt file for more information on the variables included.</p> <p>For any further queries please refer to the corresponding author, Yiannis Moustakis: <br>yiannis.moustakis@geographie.uni-muenchen.de</p> <p> </p>

Fig. 6 in Seasonal response of benthic foraminifera to anthropogenic pressure in two stations of the Gulf of Trieste (northern Adriatic Sea, Italy): the marine protected area of Miramare versus the Servola water sewage outfall

Fig. 6: Rank-frequency diagram for the Ser(a) and Res(b) stations using the cumulative abundance (as relative frequency) for y-axe and the decreasing rank order for x-axe of each species for each sample. Both axes are on logarithmic scale.

Fig. 4 in Seasonal response of benthic foraminifera to anthropogenic pressure in two stations of the Gulf of Trieste (northern Adriatic Sea, Italy): the marine protected area of Miramare versus the Servola water sewage outfall

Fig. 4: Foraminiferal data for Ser and Res stations using the complete living assemblage of the 0-2 cm level: a) Foraminiferal density (FD) as the number of specimens normalised to 50 cc of sediments and species richness; b) Dominance index; c) bias corrected Shannon (H' bc) and the exponential function Exp(H' ) indexes.

Fig. 3 in Seasonal response of benthic foraminifera to anthropogenic pressure in two stations of the Gulf of Trieste (northern Adriatic Sea, Italy): the marine protected area of Miramare versus the Servola water sewage outfall

Fig. 3: Potentially toxic elements (PTE) concentration in the Ser (a) and Res (b) stations calculated for the 0-1 cm level. PTEs are expressed in micrograms per gram (µg/g).

Fig. 1 in Seasonal response of benthic foraminifera to anthropogenic pressure in two stations of the Gulf of Trieste (northern Adriatic Sea, Italy): the marine protected area of Miramare versus the Servola water sewage outfall

Fig. 1: Study area and location of the Ser (Servola) and Res (Riserva Naturale Marina di Miramare) stations. The Servola pipeline is evidenced in the enlarged square.

Fig. 2 in Seasonal response of benthic foraminifera to anthropogenic pressure in two stations of the Gulf of Trieste (northern Adriatic Sea, Italy): the marine protected area of Miramare versus the Servola water sewage outfall

Fig. 2: Vertical profiles of temperature, salinity, pH, oxygen saturation and chlorophyll a at Ser and Res stations during the seasonal sampling.