Scalable production of chitosan sub-micron particles by membrane ionotropic gelation process.

Ionotropic gelation (IG) is a highly attractive method for the synthesis of natural water-soluble polymeric nanoparticles (NPs) and sub-micron particles (sMP) due to its relatively simple procedure and the absence of organic solvents. The method involves the electrostatic interaction between two ionic species of opposite charge. Although it is well studied at the laboratory scale, the difficulty to achieve size control in conventional bench-top process is actually a critical aspect of the technology. The aim of this work is to study the membrane dispersion technology in combination with IG as a suitable scalable method for the production of chitosan sub-micron particles (CS-sMPs). The two phases, one containing chitosan (CS) and the other containing sodium tripolyphosphate (TPP), were put in contact using a tubular hydrophobic glass membrane with a pore diameter of 1 µm. TPP (dispersed phase) was permeated through the membrane pores into the lumen side along which the CS solution (the continuous phase) flowed in batch recirculation or continuous single-pass operation mode. The influence of chemical variables (i.e. pH, concentration and mass ratio of polyelectrolyte species, emulsifier) and fluid-dynamic parameters (i.e. polyelectrolyte solution flow rate and their relative mass ratio) was studied to precisely tune the size of CS-Ps.

Infodemic Signal Detection During the COVID-19 Pandemic: Development of a Methodology for Identifying Potential Information Voids in Online Conversations.

BACKGROUND: The COVID-19 pandemic has been accompanied by an infodemic: excess information, including false or misleading information, in digital and physical environments during an acute public health event. This infodemic is leading to confusion and risk-taking behaviors that can be harmful to health, as well as to mistrust in health authorities and public health responses. The World Health Organization (WHO) is working to develop tools to provide an evidence-based response to the infodemic, enabling prioritization of health response activities. OBJECTIVE: In this work, we aimed to develop a practical, structured approach to identify narratives in public online conversations on social media platforms where concerns or confusion exist or where narratives are gaining traction, thus providing actionable data to help the WHO prioritize its response efforts to address the COVID-19 infodemic. METHODS: We developed a taxonomy to filter global public conversations in English and French related to COVID-19 on social media into 5 categories with 35 subcategories. The taxonomy and its implementation were validated for retrieval precision and recall, and they were reviewed and adapted as language about the pandemic in online conversations changed over time. The aggregated data for each subcategory were analyzed on a weekly basis by volume, velocity, and presence of questions to detect signals of information voids with potential for confusion or where mis- or disinformation may thrive. A human analyst reviewed and identified potential information voids and sources of confusion, and quantitative data were used to provide insights on emerging narratives, influencers, and public reactions to COVID-19-related topics. RESULTS: A COVID-19 public health social listening taxonomy was developed, validated, and applied to filter relevant content for more focused analysis. A weekly analysis of public online conversations since March 23, 2020, enabled quantification of shifting interests in public health-related topics concerning the pandemic, and the analysis demonstrated recurring voids of verified health information. This approach therefore focuses on the detection of infodemic signals to generate actionable insights to rapidly inform decision-making for a more targeted and adaptive response, including risk communication. CONCLUSIONS: This approach has been successfully applied to identify and analyze infodemic signals, particularly information voids, to inform the COVID-19 pandemic response. More broadly, the results have demonstrated the importance of ongoing monitoring and analysis of public online conversations, as information voids frequently recur and narratives shift over time. The approach is being piloted in individual countries and WHO regions to generate localized insights and actions; meanwhile, a pilot of an artificial intelligence-based social listening platform is using this taxonomy to aggregate and compare online conversations across 20 countries. Beyond the COVID-19 pandemic, the taxonomy and methodology may be adapted for fast deployment in future public health events, and they could form the basis of a routine social listening program for health preparedness and response planning.

WHO Digital Intelligence Analysis for Tracking Narratives and Information Voids in the COVID-19 Infodemic.

The COVID-19 pandemic is the first to unfold in the highly digitalized society of the 21st century and is therefore the first pandemic to benefit from and be threatened by a thriving real-time digital information ecosystem. For this reason, the response to the infodemic required development of a public health social listening taxonomy, a structure that can simplify the chaotic information ecosystem to enable an adaptable monitoring infrastructure that detects signals of fertile ground for misinformation and guides trusted sources of verified information to fill in information voids in a timely manner. A weekly analysis of public online conversations since 23 March 2020 has enabled the quantification of running shifts of public interest in public health-related topics concerning the pandemic and has demonstrated the frequent resumption of information voids relevant for public health interventions and risk communication in an emergency response setting.

The Importance of Interactions at the Molecular Level: A Spectroscopic Study of a New Composite Sorber Material.

The functional properties of a new composite material having water vapor getter properties have been investigated by a large arsenal of characterization techniques. The composite system is originated by combining two constituents having very different chemical natures, a magnesium perchlorate (Mg(ClO4)2) salt and a polymeric acrylic matrix. In particular, Fourier transform infrared (FT-IR) and Raman spectroscopy have been fundamental to understand the type of interactions between the salt and the matrix in different hydration conditions. It was found that in the anhydrous composite system the dispersed Mg(ClO4)2 salt retains its molecular structure, because Mg2+ cations are still surrounded by their [ClO4]- counter-anions; at the same time, the salt and the polymeric matrix chemically interact each other at the molecular level. These interactions gradually vanish in the presence of water, and disappear in the fully hydrated composite system, where the Mg2+ cations are completely solvated by the water molecules.

Self-assembled ordered structures in thin films of HAT5 discotic liquid crystal.

Thin films of the discotic liquid crystal hexapentyloxytriphenylene (HAT5), prepared from solution via casting or spin-coating, were investigated by atomic force microscopy and polarizing optical microscopy, revealing large-scale ordered structures substantially different from those typically observed in standard samples of the same material. Thin and very long fibrils of planar-aligned liquid crystal were found, possibly formed as a result of an intermediate lyotropic nematic state arising during the solvent evaporation process. Moreover, in sufficiently thin films the crystallization seems to be suppressed, extending the uniform order of the liquid crystal phase down to room temperature. This should be compared to the bulk situation, where the same material crystallizes into a polymorphic structure at 68 °C.