Tag Archives: Einstein

Corona-induced transition from molecular to particle motion in biological media

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Light signatures generated by particles in a nanoscopeIn last month’s post [see ‘Nanoparticle motion through heterogeneous hydrogels’ on November 6th, 2024], I described our recent work on tracking nanoparticles through a model of the vitreous humour and mentioned it was the first of two articles published in the Nature journal, Scientific Reports.  In the second article, we explored the use of caustics in an optical microscope [see ‘Seeing the invisible’ on October 29th, 2014] to track nanoparticles in biofluids.  Nanoparticles are below the resolution of an optical microscope because they are substantially smaller than the wavelength of visible light; hence, they are usually tracked using fluorescent markers or tags attached chemically to the nanoparticles.  These tags can influence both the motion of the particles and biological activity so caustics provide a label-free technique that allows particles to be tracked in real-time using a standard optical microscope.  In most of our previous research, we have tracked nanoparticles in transparent fluids such as water, glycerol-water mixtures, or the hydrogels described in last month’s post.  In our latest work, we have tracked small nanoparticles with diameters from 10 to 100 nm in common cell culture media with different concentrations of serum proteins.  These fluids are a ‘soup’ of complex protein molecules that interact with one another and the gold nanoparticles being tracked.  We found that the presence of proteins caused a reduction in the rate of diffusion for both positively- and negatively-charged particles and we concluded that the proteins form a corona around each nanoparticle effectively enlarging its diameter.  For larger nanoparticles, and those positively-charged, the enlargement appears to cause a transition from molecular motion, in which particle diameter is unimportant, to particle motion where larger particles diffuse more slowly.  We first explored this transition from fractional to classical Stokes-Einstein behaviour in simple fluids in 2017 [‘Slow moving nanoparticles‘ on December 13th 2017] and it seems likely to be complicated in these complex fluids.  Hence, understanding protein dynamics as well nanoparticle dynamics will be essential to the development of nanotechnologies applicable in biological environments.  So, we have lots more work to do!

Sources:

Schleyer G, Patterson EA, Curran JM. Label free tracking to quantify nanoparticle diffusion through biological media. Scientific Reports. 2024 Aug 13;14(1):18822.

Coglitore D, Edwardson SP, Macko P, Patterson EA, Whelan MP, Transition from fractional to classical Stokes-Einstein behaviour in simple fluids, Royal Society Open Science, 4:170507, 2017.

Going against the flow

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Decorative photograph of a mountain riverLast week I wrote about research we have been carrying out over the last decade that is being applied to large scale structures in the aerospace industry (see ‘Slowly crossing the valley of death‘ on January 27th, 2021). I also work on very much smaller ‘structures’ that are only tens of nanometers in diameter, or about a billion times smaller than the test samples in last week’s post (see ‘Toxic nanoparticles?‘ on November 13th, 2013). The connection is the use of light to measure shape, deformation and motion; and then utilising the measurements to validate predictions from theoretical or computational models. About three years ago, we published research which demonstrated that the motion of very small particles (less than about 300 nanometres) at low concentrations (less than about a billion per millilitre) in a fluid was dominated by the molecules of the fluid rather than interactions between the particles (see Coglitore et al, 2017 and ‘Slow moving nanoparticles‘ on December 13th, 2017). This data confirmed results from earlier molecular dynamic simulations that contradicted predictions using the Stokes-Einstein equation, which was derived by Einstein in his PhD thesis for a ‘Stokes’ particle undergoing Brownian motion. The Stokes-Einstein equation works well for large particles but the physics of motion changes when the particles are very small and far apart so that Van der Waals forces and electrostatic forces play a dominant role, as we have shown in a more recent paper (see Giorgi et al, 2019).  This becomes relevant when evaluating nanoparticles as potential drug delivery systems or assessing the toxicological impact of nanoparticles.  We have shown recently that instruments based on dynamic scattering of light from nanoparticles are likely to be inaccurate because they are based on fitting measurement data to the Stokes-Einstein equation.  In a paper published last month, we found that asymmetric flow field flow fractionation (or AF4)  in combination with dynamic light scattering when used to detect the size of nanoparticles in suspension, tended to over-estimate the diameter of particles smaller than 60 nanometres at low concentrations by upto a factor of two (see Giorgi et al, 2021).  Someone commented recently that our work in this area was not highly cited but perhaps this is unsurprising when it undermines a current paradigm.  We have certainly learnt to handle rejection letters, to redouble our efforts to demonstrate the rigor in our research and to present conclusions in a manner that appears to build on existing knowledge rather than demolishing it.

Sources:

Coglitore, D., Edwardson, S.P., Macko, P., Patterson, E.A. and Whelan, M., 2017. Transition from fractional to classical Stokes–Einstein behaviour in simple fluids. Royal Society open science, 4(12), p.170507.

Giorgi, F., Coglitore, D., Curran, J.M., Gilliland, D., Macko, P., Whelan, M., Worth, A. and Patterson, E.A., 2019. The influence of inter-particle forces on diffusion at the nanoscale. Scientific reports, 9(1), pp.1-6.

Giorgi, F., Curran, J.M., Gilliland, D., La Spina, R., Whelan, M.P. & Patterson, E.A. 2021, Limitations of nanoparticles size characterization by asymmetric flow field-fractionation coupled with online dynamic light scattering, Chromatographia, doi.org/10/1007/s10337-020-03997-7.

Image is a photograph of a fast flowing mountain river taken in Yellowstone National Park during a roadtrip across the USA in 2006.

Forecasts and chimpanzees throwing darts

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During the coronavirus pandemic, politicians have taken to telling us that their decisions are based on the advice of their experts while the news media have bombarded us with predictions from experts.  Perhaps not unexpectedly, with the benefit of hindsight, many of these decisions and predictions appear to be have been ill-advised or inaccurate which is likely to lead to a loss of trust in both politicians and experts.  However, this is unsurprising and the reliability of experts, particularly those willing to make public pronouncements, is well-known to be dubious.  Professor Philip E. Tetlock of the University of Pennsylvania has assessed the accuracy of forecasts made by purported experts over two decades and found that they were little better than a chimpanzee throwing darts.  However, the more well-known experts seemed to be worse at forecasting [Tetlock & Gardner, 2016].  In other words, we should assign less credibility to those experts whose advice is more frequently sought by politicians or quoted in the media.  Tetlock’s research has found that the best forecasters are better at inductive reasoning, pattern detection, cognitive flexibility and open-mindedness [Mellers et al, 2015]. People with these attributes will tend not to express unambiguous opinions but instead will attempt to balance all factors in reaching a view that embraces many uncertainties.  Politicians and the media believe that we want to hear a simple message unadorned by the complications of describing reality; and, hence they avoid the best forecasters and prefer those that provide the clear but usually inaccurate message.  Perhaps that’s why engineers are rarely interviewed by the media or quoted in the press because they tend to be good at inductive reasoning, pattern detection, cognitive flexibility and are open-minded [see ‘Einstein and public engagement‘ on August 8th, 2018].  Of course, this was well-known to the Chinese philosopher, Lao Tzu who is reported to have said: ‘Those who have knowledge, don’t predict. Those who predict, don’t have knowledge.’

References:

Mellers, B., Stone, E., Atanasov, P., Rohrbaugh, N., Metz, S.E., Ungar, L., Bishop, M.M., Horowitz, M., Merkle, E. and Tetlock, P., 2015. The psychology of intelligence analysis: Drivers of prediction accuracy in world politics. Journal of experimental psychology: applied, 21(1):1-14.

Tetlock, P.E. and Gardner, D., 2016. Superforecasting: The art and science of prediction. London: Penguin Random House.

Salt increases nanoparticle diffusion

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About two and half years ago, I wrote about an article we had published on the motion of nanoparticles [see ‘Slow moving nanoparticles‘ on December 13th, 2017] in which we had shown that, for very small particles at low concentrations, the motion of a particle is independent of its size and does not flow the well-known Stokes-Einstein law.  Our article presented convincing evidence from experiments to support our conclusions but was light on explanation in terms of the mechanics.  At the end of last year, we published a short article in Scientific Reports, in which we demonstrated that the motion of nanoparticles at low concentrations is dependent on the interaction of van der Waals forces and electrostatic forces.  Van der Waals forces are short-range attractive forces between uncharged molecules due to interacting dipole moments, whereas the electrostatic forces are the repulsion of electric charges.  We changed both of these forces by using salt solutions of different concentration and observing the changes in nanoparticle behaviour.  Increasing the molarity increases the diffusion of the particles until the solution is saturated, as shown in the picture for 50 nanometre diameter gold particles (that’s about half the diameter of a coronavirus particle or one thousandth of the diameter of a human hair).  Our findings have implications for understanding the behaviour of nanoparticles dispersed in biological media, which typically contain salt in solution, because the concentration of salt ions in the medium affects nanoparticle diffusion that has been shown to influence cellular uptake and toxicity.

Sources:

Coglitore D, Edwardson SP, Macko P, Patterson EA, Whelan MP, Transition from fractional to classical Stokes-Einstein behaviour in simple fluids, Royal Society Open Science, 4:170507, 2017.

Giorgi F, Coglitore D, Curran JM, Gilliland D, Macko P, Whelan M, Worth A & Patterson EA, The influence of inter-particle forces on diffusion at the nanoscale, Scientific Reports, 9:12689, 2019.