scholarly journals Hydrocolloids between soft matter and taste: Culinary polymer physics

2012 ◽  
Vol 1 (1) ◽  
pp. 46-53 ◽  
Author(s):  
Thomas A. Vilgis
Keyword(s):  
Soft Matter ◽  
Polymer Physics

scholarly journals On the design of precision nanomedicines

2019 ◽  
Author(s):  
Xiaohe Tian ◽  
Stefano Agioletti-Uberti ◽  
Giuseppe Battaglia
Keyword(s):  
Soft Matter ◽  
Polymer Physics ◽  
Analytical Models ◽  
Polymerization Degree ◽  
Threshold Density ◽  
Tight Control ◽  
System A ◽  
Multiple Receptors ◽  
Unique Cell ◽  
Sweet Spots

<div> <div> <p>Tight control on the selectivity of nanoparticles' interaction with biological systems is paramount for the development of targeted therapies. However, the large number of synthetically tunable parameters makes it difficult to identify optimal design ``sweet spots'' without rational guiding principles. Here we address this problem combining super-selectivity theory (SST) with analytical models from soft matter and polymer physics into a unified theoretical framework. Starting from an archetypal system, a polymersome functionalized with targeting ligands, we use our model to identify the most selective combination of parameters in terms of particle size, brush polymerization degree and grafting density, as well as tether length, binding affinity and ligands number. We further show how to combine multivalent interactions into multiplexed systems which act holistically as a function of the density of more than one receptor type, so as to achieve binding only when multiple receptors are expressed above a threshold density. We show that theory can be used to effectively fit experimental data and, hence confirming its suitability. We thus propose the design of “bar-coding" targeting approach that can be tailor-made to unique cell populations enabling personalized therapies. </p> </div> </div>

scholarly journals On the design of precision nanomedicines

2019 ◽  
Author(s):  
Xiaohe Tian ◽  
Stefano Agioletti-Uberti ◽  
Giuseppe Battaglia
Keyword(s):  
Soft Matter ◽  
Polymer Physics ◽  
Analytical Models ◽  
Polymerization Degree ◽  
Threshold Density ◽  
Tight Control ◽  
System A ◽  
Multiple Receptors ◽  
Unique Cell ◽  
Sweet Spots

<div> <div> <p>Tight control on the selectivity of nanoparticles' interaction with biological systems is paramount for the development of targeted therapies. However, the large number of synthetically tunable parameters makes it difficult to identify optimal design ``sweet spots'' without rational guiding principles. Here we address this problem combining super-selectivity theory (SST) with analytical models from soft matter and polymer physics into a unified theoretical framework. Starting from an archetypal system, a polymersome functionalized with targeting ligands, we use our model to identify the most selective combination of parameters in terms of particle size, brush polymerization degree and grafting density, as well as tether length, binding affinity and ligands number. We further show how to combine multivalent interactions into multiplexed systems which act holistically as a function of the density of more than one receptor type, so as to achieve binding only when multiple receptors are expressed above a threshold density. We show that theory can be used to effectively fit experimental data and, hence confirming its suitability. We thus propose the design of “bar-coding" targeting approach that can be tailor-made to unique cell populations enabling personalized therapies. </p> </div> </div>

Design principles for precision targeting

2017 ◽  
Author(s):  
Giuseppe Battaglia ◽  
Stefano Angioletti-Umberti
Keyword(s):  
Soft Matter ◽  
Polymer Physics ◽  
Analytical Models ◽  
Threshold Density ◽  
Tight Control ◽  
System A ◽  
Multiple Receptors ◽  
Unique Cell ◽  
Polymer Stabilized ◽  
Sweet Spots

<div> <div> <div> <p>Tight control on the selectivity of nanoparticles’ interaction with biological systems is paramount for the development of targeted therapies. However, the large number of synthetically tuneable parameters makes it difficult to identify optimal design “sweet spots” without rational guiding principles. Here we address this problem combining super-selectivity theory (SST) with analytical models from soft matter and polymer physics into a unified theoretical framework. Starting from an archetypal system, a polymer-stabilized nanoparticle function- alised with targeting ligands, we use our model to identify the most selective combination of parameters in terms of particle size, brush polymerization degree and grafting density, as well as tether length, binding affinity and ligands number. We further show how to combine mul- tivalent interactions into multiplexed systems which act holistically as a function of the den- sity of more than one receptor type, so as to achieve binding only when multiple receptors are expressed above a threshold density. We thus propose the design of ”bar-coding” targeting approach that can be tailor-made to unique cell populations enabling personalized therapies. </p> </div> </div> </div>

Design principles for precision targeting

2018 ◽  
Author(s):  
Giuseppe Battaglia ◽  
Stefano Agioletti-Uberti
Keyword(s):  
Particle Size ◽  
Soft Matter ◽  
Polymer Physics ◽  
Analytical Models ◽  
Polymerization Degree ◽  
Tight Control ◽  
System A ◽  
Grafting Density ◽  
Polymer Stabilized ◽  
Sweet Spots

<div> <div> <div> <p>Tight control on the selectivity of nanoparticles’ interaction with biological systems is paramount for the development of targeted therapies. However, the large number of synthetically tuneable parameters makes it difficult to identify optimal design “sweet spots” without rational guiding principles. Here we address this problem combining super-selectivity theory (SST) with analytical models from soft matter and polymer physics into a unified theoretical framework. Starting from an archetypal system, a polymer-stabilized nanoparticle function- alised with targeting ligands, we use our model to identify the most selective combination of parameters in terms of particle size, brush polymerization degree and grafting density, as well as tether length, binding affinity and ligands number. </p> </div> </div> </div>

scholarly journals On the design of precision nanomedicines

2019 ◽  
Author(s):  
Xiaohe Tian ◽  
Stefano Agioletti-Uberti ◽  
Giuseppe Battaglia
Keyword(s):  
Soft Matter ◽  
Polymer Physics ◽  
Analytical Models ◽  
Polymerization Degree ◽  
Threshold Density ◽  
Tight Control ◽  
System A ◽  
Multiple Receptors ◽  
Unique Cell ◽  
Sweet Spots

<div> <div> <p>Tight control on the selectivity of nanoparticles' interaction with biological systems is paramount for the development of targeted therapies. However, the large number of synthetically tunable parameters makes it difficult to identify optimal design ``sweet spots'' without rational guiding principles. Here we address this problem combining super-selectivity theory (SST) with analytical models from soft matter and polymer physics into a unified theoretical framework. Starting from an archetypal system, a polymersome functionalized with targeting ligands, we use our model to identify the most selective combination of parameters in terms of particle size, brush polymerization degree and grafting density, as well as tether length, binding affinity and ligands number. We further show how to combine multivalent interactions into multiplexed systems which act holistically as a function of the density of more than one receptor type, so as to achieve binding only when multiple receptors are expressed above a threshold density. We show that theory can be used to effectively fit experimental data and, hence confirming its suitability. We thus propose the design of “bar-coding" targeting approach that can be tailor-made to unique cell populations enabling personalized therapies. </p> </div> </div>

Polymer Physics

2009 ◽  
Author(s):  
Fumihiko Tanaka
Keyword(s):  
Polymer Physics

Allosteric regulation of GPCR Rhodopsin by soft matter

2020 ◽  
Author(s):  
Nipuna Weerasinghe ◽  
Steven Fried ◽  
Anna Eitel ◽  
Andrey Struts ◽  
Suchithranga Perera ◽  
...  
Keyword(s):  
Soft Matter ◽  
Allosteric Regulation

Natural Killer Cell Inspired AIE Nanoterminator for Blood-Brain-Barrier Crossing via Tight-Junction Modulation and NIR-II Gliomas Theranostics

2020 ◽  
Author(s):  
Guanjun Deng ◽  
Xinghua Peng ◽  
Zhihong Sun ◽  
Wei Zheng ◽  
Jia Yu ◽  
...  
Keyword(s):  
Natural Killer Cell ◽  
Natural Killer ◽  
Intracellular Signaling ◽  
Soft Matter ◽  
Tumor Imaging ◽  
Nk Cell ◽  
Killer Cell ◽  
Light Illumination ◽  
Blood Brain ◽  
Intracellular Signaling Cascade

Nature has always inspired robotic designs and concepts. It is conceivable that biomimic nanorobots will soon play a prominent role in medicine. In this paper, we developed a natural killer cell-mimic AIE nanoterminator (NK@AIEdots) by coating natural kill cell membrane on the AIE-active polymeric endoskeleton, PBPTV, a highly bright NIR-II AIE-active conjugated polymer. Owning to the AIE and soft-matter characteristics of PBPTV, as-prepared nanoterminator maintained the superior NIR-II brightness (quantum yield ~8%) and good biocompatibility. Besides, they could serve as tight junctions (TJs) modulator to trigger an intracellular signaling cascade, causing TJs disruption and actin cytoskeleton reorganization to form intercellular “green channel” to help themselves crossing Blood-Brain Barriers (BBB) silently. Furthermore, they could initiatively accumulate to glioblastoma cells in the complex brain matrix for high-contrast and through-skull tumor imaging. The tumor growth was also greatly inhibited by these nanoterminator under the NIR light illumination. As far as we known, The QY of PBPTV is the highest among the existing NIR-II luminescent conjugated polymers. Besides, the NK-cell biomimetic nanorobots will open new avenue for BBB-crossing delivery.

Sensitive Mechanocontrolled Luminescence in Cross-Linked Polymer Films

2019 ◽  
Author(s):  
Ayumu Karimata ◽  
Pradnya Patil ◽  
Eugene Khaskin ◽  
Sébastien Lapointe ◽  
robert fayzullin ◽  
...  
Keyword(s):  
Mechanical Stress ◽  
Polymer Films ◽  
Soft Matter ◽  
Small Strain ◽  
Visual Methods ◽  
Photoluminescence Intensity ◽  
Stimuli Responsive ◽  
Responsive Materials ◽  
Highly Sensitive ◽  
Mechanical Stretching

Direct translation of mechanical force into changes in chemical behavior on a molecular level has important implication not only for the fundamental understanding of mechanochemical processes, but also for the development of new stimuli-responsive materials. In particular, detection of mechanical stress in polymers via non-destructive methods is important in order to prevent material failure and to study the mechanical properties of soft matter. Herein, we report that highly sensitive changes in photoluminescence intensity can be observed in response to the mechanical stretching of cross-linked polymer films when using stable, (pyridinophane)Cu-based dynamic mechanophores. Upon stretching, the luminescence intensity increases in a fast and reversible manner even at small strain (< 50%) and applied stress (< 0.1 MPa) values. Such sensitivity is unprecedented when compared to previously reported systems based on organic mechanophores. The system also allows for the detection of weak mechanical stress by spectroscopic measurements or by direct visual methods.<br>

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