Title: Assessment of silica nanoparticle hydrodynamic diameter in complex media by means of X-Ray Photon Correlation Spectroscopy (XPCS)

Abstract: The constant growth of nanomaterial applications in various fields, including medicine, agriculture, and energy, has created a need for the characterization of nanoparticle properties in challenging environments. In this regard, scattering techniques, both static (e.g. SLS, SAXS) and dynamic ones (e.g. DLS, FCS), are commonly employed to determine size, shape, colloidal stability and interactions of nanoparticles in diverse media. In recent years, synchrotron-based X-ray Photon Correlation Spectroscopy (XPCS) has gained attention as a valuable technique for studying nanoparticle diffusion and deriving their hydrodynamic diameter in complex enviroments, where light-based methods often fail to provide reliable data owing to high scattering and absorption from the media.

This study presents an initial evaluation of the capabilities of the Cateretê beamline at LNLS-Sirius to study nanoparticle diffusion in biologically relevant media by means of XPCS. To this end, silica nanoparticles (SNPs) with sizes ranging from 200 to 700 nm were examined in various media including phosphate buffer saline (PBS), albumin solutions and PBS supplemented with fetal bovine serum (FBS). Additionally, the influence of an antifouling and colloidal stabilizing coating (PEG, Mn=2000) on selected nanoparticle sizes was investigated. Different models were tested to analyze the XPCS derived autocorrelation functions and obtain information on SNP diffusion and hydrodynamic diameters, including single exponential, KKW model, and cumulant analysis. Furthermore, all samples were measured by SAXS and DLS concomitantly and a comprehensive comparison was made focusing on the influence of protein adsorption and colloidal stability/instability on the obtained results from each of the three techniques (XPCS, SAXS and DLS).

Title: The specific, non-specific interaction between dendrimers and HIV gp120 protein
N.P. Cowieson¹, C.F.M Latham², G. Tachedjian², R. Rambo¹

Abstract: Dendrimers are branched polymers that are of interest as anti-microbials or anti-cancer drugs, vectors for drug delivery and other applications in the health sciences. In this study we investigate poly-lysine dendrimers as topical inhibitors of HIV infection. We have used SAXS and other biochemical analyses to study the structure of the dendrimers and their interaction with the HIV gp120 protein that is essential for viral infection.

Previously published molecular modelling results suggested that these dendrimers may collapse making packing interactions within the particle to form a structure with a defined shape and surface that may be capable of making specific interactions in a protein-like manner1. Our SAXS results show that charge repulsion between the head groups cause the dendrimers to adopt a very much larger structure that shrinks and grows in response to changes in salt concentration suggesting a less well-defined structure.

Conversely, measuring particle size by SAXS while titrating the dendrimers onto gp120 show an interaction with a defined stoichiometry that is quite distinct from related unbranched polymers. These results suggest a more specific mode of interaction.

Finally, it does not seem right to model these interactions in a discrete, atomistic way that would be typical for specific interactions or simply in terms of bulk properties as would be typical for non-specific interactions. I will present my preliminary approach at modelling this interesting system.

1) Roberts, Benjamin & Scanlon, Martin & Krippner, Guy & Chalmers, David. (2009). Molecular Dynamics of Poly(L-lysine) Dendrimers with Naphthalene Disulfonate Caps. Macromolecules. 42. 2775-2783. 10.1021/Ma802154e.

Title: Innovative Smart Diagnostics for Early Detection of Pre-Cachexia in Patients with Advanced Cancer

Abstract: The study aims to develop an automated diagnostic tool for pre-cachexia cancer patients using a machine learning algorithm. The algorithm will be trained with infrared spectrum wavenumbers obtained by Attenuated Total Reflection (ATR) – Fourier Transform Infrared (FTIR) spectroscopy in two groups of cancer patients in palliative care, classified as without cachexia and pre-cachexia. The study included 44 advanced cancer patients, of which 29 had no cachexia, and 15 had precachexia. The spectra were measured in the 4000 to 650 cm-1 wavenumber regions using a FTIR spectrometer Agilent Cary 600 Series coupled with MCT detector. The spectrum of air was used as a background before each sample analysis. Sample spectra were taken in triplicate, at a spectral resolution of 4 cm-1, and to each measurement 64 scans were performed. The infrared spectra were analyzed after undergoing pre-processing, which involved positive Rubberband baseline normalization, normalization by minimum and maximum, and second derivative by the Savitzky-Golay filter. The main spectral regions detected in the serum were 945-918 cm-1 and 2875-2869 cm-1. These wavenumbers represent the vibrational modes of PO3 2- symmetric stretching and CH3 symmetric stretching, respectively, which have been previously linked to DNA/RNA ribose and lipids. The feasibility of developing an algorithm for the automated diagnosis of pre-cachexia was examined based on the identified wavenumbers. The Naive Bayes classifier was employed to differentiate between the two study groups, exhibiting an accuracy of 0.77, sensitivity of 0.87, and specificity of 0.72. The changes in biochemical constituents that occur in serum as a result of pre-cachexia are related to the infrared spectrum obtained by ATR-FTIR, featuring a molecular fingerprint. The implementation of this approach in clinical practice may automate the diagnosis of pre-cachexia in advanced cancer patients, monitoring whether changes in therapy or interventions are necessary throughout cancer treatment. To the best of our knowledge, this is the first study to propose a method for the diagnosis of pre-cachexia cancer using a machine learning approach trained with infrared spectrum wavenumbers obtained by ATR-FTIR with blood serum, providing a new avenue for future research in this field.