Synthesis of Polyacetylene-like Modified Graphene Oxide Aerogel and Its Enhanced Electrical Properties

AI-Enhanced Tools and Strategies for Airborne Disease Prevention in Cultural Heritage Sites

In the wake of the COVID-19 pandemic, the surveillance and safety measures of indoor Cultural Heritage sites have become a paramount concern due to the unique challenges posed by their enclosed environments and high visitor volumes. This communication explores the integration of Artificial Intelligence (AI) in enhancing epidemiological surveillance and health safety protocols in these culturally significant spaces. AI technologies, including machine learning algorithms and Internet of Things (IoT) sensors, have shown promising potential in monitoring air quality, detecting pathogens, and managing crowd dynamics to mitigate the spread of infectious diseases. We review various applications of AI that have been employed to address both direct health risks and indirect impacts such as visitor experience and preservation practices. Additionally, this paper discusses the challenges and limitations of AI deployment, such as ethical considerations, privacy issues, and financial constraints. By harnessing AI, Cultural Heritage sites can not only improve their resilience against future pandemics but also ensure the safety and well-being of visitors and staff, thus preserving these treasured sites for future generations. This exploration into AI's role in post-COVID surveillance at Cultural Heritage sites opens new frontiers in combining technology with traditional conservation and public health efforts, providing a blueprint for enhanced safety and operational efficiency in response to global health challenges.

Bioaerosol Sampling Devices and Pretreatment for Bacterial Characterization: Theoretical Differences and a Field Experience in a Wastewater Treatment Plant

Studies on bioaerosol bacterial biodiversity have relevance in both ecological and health contexts, and molecular methods, such as 16S rRNA gene-based barcoded sequencing, provide efficient tools for the analysis of airborne bacterial communities. Standardized methods for sampling and analysis of bioaerosol DNA are lacking, thus hampering the comparison of results from studies implementing different devices and procedures. Three samplers that use gelatin filtration, swirling aerosol collection, and condensation growth tubes for collecting bioaerosol at an aeration tank of a wastewater treatment plant in Trieste (Italy) were used to determine the bacterial biodiversity. Wastewater samples were collected directly from the untreated sewage to obtain a true representation of the microbiological community present in the plant. Different samplers and collection media provide an indication of the different grades of biodiversity, with condensation growth tubes and DNA/RNA shieldTM capturing the richer bacterial genera. Overall, in terms of relative abundance, the air samples have a lower number of bacterial genera (64 OTUs) than the wastewater ones (75 OTUs). Using the metabarcoding approach to aerosol samples, we provide the first preliminary step toward the understanding of a significant diversity between different air sampling systems, enabling the scientific community to orient research towards the most informative sampling strategy.

The Requirements of Managing Phase I Clinical Trials Risks: The British and Italian Case Studies

Phase I clinical trials represent a critical point in drug development because the investigational medicinal product is being tested in humans for the first time. For this reason, it is essential to evaluate and identify the Maximum Tolerated Dose (MTD) and the safety of the new compound. To mitigate the possible risks associated with drug administration and treatment, the European Competent Authority issued various guidelines to provide provisions and harmonize risk management processes. In the UK and Italy, particular attention should be paid to the Medicines & Healthcare Products Regulatory Agency (MHRA) phase I accreditation scheme and the specific rules set by the Italian Drug Authority through the AIFA Determination no. 809/2015. Both reference documents are based on the concept of quality risk management while conducting phase I clinical studies. Moreover, the AIFA determination outlines specific requirements for those sites that want to conduct non-profit phase I clinical trials. Indeed, the document reports peculiar activities to the "Clinical Trial Quality Team", which is a team that should support the clinical site researchers in designing, starting, performing, and closing non-profit phase I studies. In this paper, we provide a general overview of the main European guidelines concerning the management of risks during phase I trials, focusing on the main peculiarities of the schemes and rules set by the MHRA and AIFA.

Integration of Different Graphene Nanostructures with PDMS to Form Wearable Sensors

This paper presents a substantial review of the fabrication and implementation of graphene-PDMS-based composites for wearable sensing applications. Graphene is a pivotal nanomaterial which is increasingly being used to develop multifunctional sensors due to their enhanced electrical, mechanical, and thermal characteristics. It has been able to generate devices with excellent performances in terms of sensitivity and longevity. Among the polymers, polydimethylsiloxane (PDMS) has been one of the most common ones that has been used in biomedical applications. Certain attributes, such as biocompatibility and the hydrophobic nature of PDMS, have led the researchers to conjugate it in graphene sensors as substrates or a polymer matrix. The use of these graphene/PDMS-based sensors for wearable sensing applications has been highlighted here. Different kinds of electrochemical and strain-sensing applications have been carried out to detect the physiological signals and parameters of the human body. These prototypes have been classified based on the physical nature of graphene used to formulate the sensors. Finally, the current challenges and future perspectives of these graphene/PDMS-based wearable sensors are explained in the final part of the paper.

Ultralight hybrid silica aerogels derived from supramolecular hydrogels self-assembled from insoluble nano building blocks

Supramolecular hydrogels are a type of hydrogel cross-linked by non-chemical bonds and they have been widely applied in the field of smart systems, sensors, tissue engineering, and controlled drug delivery. Most supramolecular hydrogels are formed by soluble molecules, polymers, and metal ions. In this work, supramolecular hydrogels self-assembled between two insoluble nano building blocks (ISNBBs), graphene oxide (GO) and amino-functionalized silica nanoparticles (SiO₂-NH₂), have been discovered and synthesized. The gelation conditions of the two ISNBBs have been investigated. A step further, ultralight hybrid silica aerogels are obtained by supercritical drying of the physical hydrogels. No visible volume shrinkage is observed, due to the fact that the hydrogel networks are formed by rigid ISNBBs. Thus the hybrid aerogels possess ultralow density (down to 7.5 mg cm^-3), high specific surface areas (178.6 m² g^-1), and extremely high porosity (99.6%). The present work shows an alternative strategy to design and synthesize supramolecular hydrogels and aerogels using predetermined building blocks, together with designable morphology and physical properties for the target aerogels.