Type-specific inflammatory responses of vascular cells activated by interaction with virgin and aged microplastics.

Microplastics (MPs) are recognized as a major environmental problem due to their ubiquitous presence in ecosystems and bioaccumulation in food chains. Not only humans are continuously exposed to these pollutants through ingestion and inhalation, but recent findings suggest they may trigger vascular inflammation and potentially worsen the clinical conditions of cardiovascular patients. Here we combine headspace analysis by needle trap microextraction-gas chromatography-mass spectrometry (HS-NTME-GC-MS) and biological assays to evaluate the effects of polystyrene, high- and low-density polyethylene MPs on phenotype, metabolic activity, and pro-inflammatory status of Vascular Smooth Muscle Cells (VSMCs) the most prominent cells in vascular walls. Virgin and artificially aged MPs (4 weeks at 40 °C and 750 W/m2 simulated solar irradiation) were comparatively tested at 1 mg/mL to simulate a realistic exposure scenario. Our results clearly show the activation of oxidative stress and inflammatory processes when VSMCs were cultured with aged polymers, with significant overexpression of IL-6 and TNF-α. In addition, volatile organic compounds (VOCs), including pentane, acrolein, propanal, and hexanal as the main components, were released by VSMCs into the headspace. Type-specific VOC response profiles were induced on vascular cells from different MPs.

A graphene-based pH sensor on paper for human plasma and seawater.

The relevance of pH assessment in clinical analysis, environmental and industrial control, has raised the demand for the development of portable, low cost and easy-to-use monitoring systems. This paper proposes a pH sensor printed on a paper support passivated with a solid-ink coating. The sensor exploits the pH sensitivity of a reduced graphene oxide functionalized with 3-(4-aminophenil)propionic acid. The sensor responded in the pH range [4], [10] and had a sensitivity of 46 mV/pH. Tests on human plasma and seawater proved this pH sensor to have similar performances than those of a commercial pH-meter with an uncertainty of 0.1 and 0.2 pH unit in plasma and seawater, respectively.

Potential correlation of wound bed score and biomarkers in chronic lower leg wounds: an exploratory study.

OBJECTIVE: The wound bed score is a validated tool to monitor wound healing in chronic wounds, and depends on visual examination by trained personnel. This study describes the feasibility of adding some biochemical and immunohistochemical parameters to increase the objectivity and specificity of the wound bed score Method: Patients with chronic wounds on the lower leg with different durations were enrolled to assess the correlation between the wound bed score and specific wound-related biomarkers, namely MMP-9, MMP-2, NGAL, albumin, integrin α2/ß1, and other histochemical (CD68, PK1, CD32, fractalkine, periostin) and immunocytochemical markers from biopsies and smears taken from wound edges and bed. RESULTS: The study examined samples from 10 patients. Patients with an unfavourable wound bed score had a low expression of periostin and fractalkine in the wound bed tissue. CD68 PK1 showed a low or negative expression in the majority of the samples. Patients negative for CD68 PK1 were also negative for CD32. Principal component analysis revealed that the albumin level and the amount of proteins were associated with a high wound bed score. Two different subsets of patients could be discriminated either by integrin α2/ß1 and albumin percentages or the MMP-9 and MMP-2 activities Conclusion: These preliminary results pave the way towards an improved wound status diagnosis and an advanced quality of wound care and management. These findings need confirming with a large number of patients and at different time points.

Assessment of bioinspired models for pattern recognition in biomimetic systems.

The increasing complexity of the artificial implementations of biological systems, such as the so-called electronic noses (e-noses) and tongues (e-tongues), poses issues in sensory feature extraction and fusion, drift compensation and pattern recognition, especially when high reliability is required. In particular, in order to achieve effective results, the pattern recognition system must be carefully designed. In order to investigate a novel biomimetic approach for the pattern recognition module of such systems, the classification capabilities of an artificial model inspired by the mammalian cortex, a cortical-based artificial neural network (CANN), are compared with several artificial neural networks present in the e-nose and e-tongue literature, a multilayer perceptron (MLP), a Kohonen self-organizing map (KSOM) and a fuzzy Kohonen self-organizing map (FKSOM). Each network was tested with large datasets coming from a conducting polymer-sensor-based e-nose and a composite array-based e-tongue. The comparison of results showed that the CANN model is able to strongly enhance the performances of both systems.