Precise control of synthetic hydrogel network structure via linear, independent synthesis-swelling relationships

Hydrogel physical properties are tuned by altering synthesis conditions such as initial polymer concentration and polymer–cross-linker stoichiometric ratios. Traditionally, differences in hydrogel synthesis schemes, such as end-linked poly(ethylene glycol) diacrylate hydrogels and cross-linked poly(vinyl alcohol) hydrogels, limit structural comparison between hydrogels. In this study, we use generalized synthesis variables for hydrogels that emphasize how changes in formulation affect the resulting network structure. We identify two independent linear correlations between these synthesis variables and swelling behavior. Analysis through recently updated swollen polymer network models suggests that synthesis-swelling correlations can be used to make a priori predictions of the stiffness and solute diffusivity characteristics of synthetic hydrogels. The same experiments and analyses performed on methacrylamide-modified gelatin hydrogels demonstrate that complex biopolymer structures disrupt the linear synthesis-swelling correlations. These studies provide insight into the control of hydrogel physical properties through structural design and can be used to implement and optimize biomedically relevant hydrogels.

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Psychological networks in clinical populations: investigating the consequences of Berkson's bias

Psychological Medicine ◽

10.1017/s0033291719003209 ◽

2019 ◽

pp. 1-9 ◽

Cited By ~ 10

Author(s):

Jill de Ron ◽

Eiko I. Fried ◽

Sacha Epskamp

Keyword(s):

Network Structure ◽

Binary Data ◽

Ordinal Data ◽

Graphical Model ◽

Rating Scale ◽

Network Models ◽

Simulation Studies ◽

Potential Threat ◽

Sum Score ◽

Research Populations

Abstract Background In clinical research, populations are often selected on the sum-score of diagnostic criteria such as symptoms. Estimating statistical models where a subset of the data is selected based on a function of the analyzed variables introduces Berkson's bias, which presents a potential threat to the validity of findings in the clinical literature. The aim of the present paper is to investigate the effect of Berkson's bias on the performance of the two most commonly used psychological network models: the Gaussian Graphical Model (GGM) for continuous and ordinal data, and the Ising Model for binary data. Methods In two simulation studies, we test how well the two models recover a true network structure when estimation is based on a subset of the data typically seen in clinical studies. The network is based on a dataset of 2807 patients diagnosed with major depression, and nodes in the network are items from the Hamilton Rating Scale for Depression (HRSD). The simulation studies test different scenarios by varying (1) sample size and (2) the cut-off value of the sum-score which governs the selection of participants. Results The results of both studies indicate that higher cut-off values are associated with worse recovery of the network structure. As expected from the Berkson's bias literature, selection reduced recovery rates by inducing negative connections between the items. Conclusion Our findings provide evidence that Berkson's bias is a considerable and underappreciated problem in the clinical network literature. Furthermore, we discuss potential solutions to circumvent Berkson's bias and their pitfalls.

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Modelling community structure and temporal spreading on complex networks

Computational Social Networks ◽

10.1186/s40649-021-00094-z ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Vesa Kuikka

Keyword(s):

Community Structure ◽

Complex Networks ◽

Community Detection ◽

Network Structure ◽

Network Connectivity ◽

Network Models ◽

Building Blocks ◽

Detection Algorithm ◽

Research Area ◽

Detection Methods

AbstractWe present methods for analysing hierarchical and overlapping community structure and spreading phenomena on complex networks. Different models can be developed for describing static connectivity or dynamical processes on a network topology. In this study, classical network connectivity and influence spreading models are used as examples for network models. Analysis of results is based on a probability matrix describing interactions between all pairs of nodes in the network. One popular research area has been detecting communities and their structure in complex networks. The community detection method of this study is based on optimising a quality function calculated from the probability matrix. The same method is proposed for detecting underlying groups of nodes that are building blocks of different sub-communities in the network structure. We present different quantitative measures for comparing and ranking solutions of the community detection algorithm. These measures describe properties of sub-communities: strength of a community, probability of formation and robustness of composition. The main contribution of this study is proposing a common methodology for analysing network structure and dynamics on complex networks. We illustrate the community detection methods with two small network topologies. In the case of network spreading models, time development of spreading in the network can be studied. Two different temporal spreading distributions demonstrate the methods with three real-world social networks of different sizes. The Poisson distribution describes a random response time and the e-mail forwarding distribution describes a process of receiving and forwarding messages.

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Tailoring Properties of Resol Resin-Derived Spherical Carbons for Adsorption of Phenol from Aqueous Solution

Molecules ◽

10.3390/molecules26061736 ◽

2021 ◽

Vol 26 (6) ◽

pp. 1736

Author(s):

Karol Sidor ◽

Tomasz Berniak ◽

Piotr Łątka ◽

Anna Rokicińska ◽

Marek Michalik ◽

...

Keyword(s):

Surface Composition ◽

Micropore Volume ◽

Gaseous Ammonia ◽

Poly Vinyl Alcohol ◽

Clear Correlation ◽

Hno3 Solution ◽

Synthesis Conditions ◽

Adsorption Of Nitrogen ◽

Oxygen Groups ◽

Size Of Particles

The polycondensation of resorcinol and formaldehyde in a water–ethanol mixture using the adapted Stöber method was used to obtain resol resins. An optimization of synthesis conditions and the use of an appropriate stabilizer (e.g., poly(vinyl alcohol)) resulted in spherical grains. The resins were carbonized in the temperature range of 600–1050 °C and then chemically activated in an aqueous HNO3 solution, gaseous ammonia, or by an oxidation–reduction cycle (soaking in a HNO3 solution followed by treatment with NH3). The obtained carbons were characterized by XRD, the low-temperature adsorption of nitrogen, SEM, TGA, and XPS in order to determine degree of graphitization, porosity, shape and size of particles, and surface composition, respectively. Finally, the materials were tested in phenol adsorption. The pseudo-second order model perfectly described the adsorption kinetics. A clear correlation between the micropore volume and the adsorption capacity was found. The content of graphite domains also had a positive effect on the adsorption properties. On the other hand, the presence of heteroatoms, especially oxygen groups, resulted in the clogging of the pores and a decrease in the amount of adsorbed phenol.

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Impact of the Type of Crosslinking Agents on the Properties of Modified Sodium Alginate/Poly(vinyl Alcohol) Hydrogels

Molecules ◽

10.3390/molecules26082381 ◽

2021 ◽

Vol 26 (8) ◽

pp. 2381

Author(s):

Katarzyna Bialik-Wąs ◽

Ewelina Królicka ◽

Dagmara Malina

Keyword(s):

Sodium Alginate ◽

Aqueous Extract ◽

Vinyl Alcohol ◽

Crosslinking Agent ◽

Echinacea Purpurea ◽

Poly Vinyl Alcohol ◽

Spectra Analysis ◽

Natural Origin ◽

Glycol Diacrylate ◽

Soxhlet Apparatus

Here, we report on studies on the influence of different crosslinking methods (ionic and chemical) on the physicochemical (swelling ability and degradation in simulated body fluids), structural (FT-IR spectra analysis) and morphological (SEM analysis) properties of SA/PVA hydrogels containing active substances of natural origin. First, an aqueous extract of Echinacea purpurea was prepared using a Soxhlet apparatus. Next, a series of modified SA/PVA-based hydrogels were obtained through the chemical crosslinking method using poly(ethylene glycol) diacrylate (PEGDA, Mn = 700 g/mol) as a crosslinking agent and, additionally, the ionic reaction in the presence of a 5% w/v calcium chloride solution. The compositions of SA/PVA/E. purpurea-based hydrogels contained a polymer of natural origin—sodium alginate (SA, 1.5% solution)—and a synthetic polymer—poly(vinyl alcohol) (PVA, Mn = 72,000 g/mol, 10% solution)—in the ratio 2:1, and different amounts of the aqueous extract of E. purpurea—5, 10, 15 or 20% (v/v). Additionally, the release behavior of echinacoside from the polymeric matrix was evaluated in phosphate-buffered saline (PBS) at 37 °C. The results indicate that the type of the crosslinking method has a direct impact on the release profile. Consequently, it is possible to design a system that delivers an active substance in a way that depends on the application.

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Vascular-confined multi-passage discoidal nanoconstructs for the low-dose docetaxel inhibition of triple-negative breast cancer growth

Nano Research ◽

10.1007/s12274-021-3507-8 ◽

2021 ◽

Author(s):

Alessia Felici ◽

Daniele Di Mascolo ◽

Miguel Ferreira ◽

Simone Lauciello ◽

Luca Bono ◽

...

Keyword(s):

Breast Cancer ◽

Survival Rate ◽

Triple Negative Breast Cancer ◽

Near Infrared ◽

Triple Negative ◽

Tumor Regression ◽

Polymer Mixture ◽

Poly Vinyl Alcohol ◽

Glycol Diacrylate ◽

Breast Cancer Growth

AbstractTaxane efficacy in triple negative breast cancer (TNBC) is limited by insufficient tumor accumulation and severe off-target effects. Nanomedicines offer a unique opportunity to enhance the anti-cancer potency of this drug. Here, 1,000 nm × 400 nm discoidal polymeric nanoconstructs (DPN) encapsulating docetaxel (DTXL) and the near infrared compound lipid-Cy5 were engineered. DPN were obtained by filling multiple times cylindrical wells in a poly(vinyl alcohol) template with a polymer mixture comprising poly(lactic-co-glycolic acid) (PLGA) and poly(ethylene glycol) diacrylate (PEG-DA) chains together with therapeutic and imaging agents. The resulting “multi-passage” DPN exhibited higher DTXL loading, lipid-Cy5 stability, and stiffness as compared to the conventional “single-passage” approach. Confocal microscopy confirmed that DTXL-DPN were not taken up by MDA-MB-231 cells but would rather sit next to the cell membrane and slowly release DTXL thereof. Empty DPN had no toxicity on TNBC cells, whereas DTXL-DPN presented a cytotoxic potential comparable to free DTXL (IC50 = 2.6 nM ± 1.0 nM vs. 7.0 nM ± 1.09 nM at 72 h). In orthotopic murine models, DPN accumulated in TNBC more efficiently than free-DTXL. With only 2 mg/kg DTXL, intravenously administered every 2 days for a total of 13 treatments, DTXL-DPN induced tumor regression and were associated to an overall 80% survival rate as opposed to a 30% survival rate for free-DTXL, at 120 days. All untreated mice succumbed before 90 days. Collectively, this data demonstrates that vascular confined multi-passage DPN, biomimicking the behavior of circulating platelets, can efficiently deliver chemotherapeutic molecules to malignant tissues and effectively treat orthotopic TNBC at minimal taxane doses.

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Design of Mucoadhesive Strips for Buccal Fast Release of Tramadol

Pharmaceutics ◽

10.3390/pharmaceutics13081187 ◽

2021 ◽

Vol 13 (8) ◽

pp. 1187

Author(s):

Nayla Francine Garcia Pastório ◽

Camila Felix Vecchi ◽

Rafaela Said dos Santos ◽

Marcos Luciano Bruschi

Keyword(s):

Ex Vivo ◽

Polymer Concentration ◽

Peroral Administration ◽

Patient Acceptance ◽

Poly Vinyl Alcohol ◽

Synthetic Analogue ◽

Drug Release Profile ◽

Opioid Agonist ◽

In Vivo Evaluation ◽

Tramadol Hydrochloride

Tramadol hydrochloride is a synthetic analogue of codeine and shows activity on the central nervous system as an opioid agonist and inhibitor of serotonin and norepinephrine reuptake. It has been used for controlling moderate to severe pain. Mucoadhesive fast-dissolving films can present greater drug availability and patient acceptance when compared to the systems of peroral administration. The films were prepared using the solvent casting method with ethylcellulose, polyvinylpyrrolidone and poly(vinyl alcohol). The effect of each polymer concentration was investigated using a 2³ factorial design with repetition at the central point. The formulations were subjected to physicochemical, mechanical, ex vivo mucoadhesive and in vitro drug release profile analysis. These properties were dependent on the polymeric composition (independent factors) of each system. The optimized formulations showed good macroscopic characteristics, improved resistance to bending, rigidity, rapid swelling up to 60 s, improved mechanical and mucoadhesive characteristics, and also fast dissolving and tramadol release. The optimized formulations constitute platforms and strategies to improve the therapy of tramadol with regard to availability at the site of application, considering the necessity of rapid pain relief, and show potential for in vivo evaluation.

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Mutualistic strategies minimize coextinction in plant–disperser networks

Proceedings of The Royal Society B Biological Sciences ◽

10.1098/rspb.2016.2302 ◽

2017 ◽

Vol 284 (1854) ◽

pp. 20162302 ◽

Cited By ~ 15

Author(s):

Evan C. Fricke ◽

Joshua J. Tewksbury ◽

Elizabeth M. Wandrag ◽

Haldre S. Rogers

Keyword(s):

Network Structure ◽

Field Experiments ◽

Empirical Relationship ◽

Network Models ◽

Mutualistic Interactions ◽

Simulated Network ◽

Direct And Indirect Impacts ◽

Indirect Impacts ◽

The Stability ◽

Seed Dispersal Mutualism

The global decline of mutualists such as pollinators and seed dispersers may cause negative direct and indirect impacts on biodiversity. Mutualistic network models used to understand the stability of mutualistic systems indicate that species with low partner diversity are most vulnerable to coextinction following mutualism disruption. However, existing models have not considered how species vary in their dependence on mutualistic interactions for reproduction or survival, overlooking the potential influence of this variation on species' coextinction vulnerability and on network stability. Using global databases and field experiments focused on the seed dispersal mutualism, we found that plants and animals that depend heavily on mutualistic interactions have higher partner diversity. Under simulated network disruption, this empirical relationship strongly reduced coextinction because the species most likely to lose mutualists depend least on their mutualists. The pattern also reduced the importance of network structure for stability; nested network structure had little effect on coextinction after simulations incorporated the empirically derived relationship between partner diversity and mutualistic dependence. Our results highlight a previously unknown source of stability in mutualistic networks and suggest that differences among species in their mutualistic strategy, rather than network structure, primarily accounts for stability in mutualistic communities.

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