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1.
Annu Int Conf IEEE Eng Med Biol Soc ; 2019: 1563-1566, 2019 Jul.
Article in English | MEDLINE | ID: mdl-31946193

ABSTRACT

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.


Subject(s)
Environmental Monitoring , Graphite , Plasma/chemistry , Seawater/chemistry , Environmental Monitoring/methods , Humans , Hydrogen-Ion Concentration
2.
J Wound Care ; 26(Sup9): S9-S17, 2017 09 01.
Article in English | MEDLINE | ID: mdl-28880755

ABSTRACT

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.


Subject(s)
Leg Ulcer/metabolism , Pyoderma Gangrenosum/metabolism , Aged , Aged, 80 and over , Albumins/metabolism , Antigens, CD/metabolism , Antigens, Differentiation, Myelomonocytic/metabolism , Biomarkers/metabolism , Cell Adhesion Molecules/metabolism , Chemokine CX3CL1/metabolism , Chronic Disease , Female , Humans , Integrin alpha2beta1/metabolism , Leg Ulcer/pathology , Lipocalin-2/metabolism , Macrophages/pathology , Male , Matrix Metalloproteinase 2/metabolism , Matrix Metalloproteinase 9/metabolism , Middle Aged , Principal Component Analysis , Pyoderma Gangrenosum/pathology , Receptors, IgG/metabolism
3.
Bioinspir Biomim ; 3: 016004, 2008 Mar.
Article in English | MEDLINE | ID: mdl-18364563

ABSTRACT

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.


Subject(s)
Artificial Intelligence , Biomimetics/methods , Cerebral Cortex/physiology , Models, Neurological , Nerve Net/physiology , Pattern Recognition, Automated/methods , Pattern Recognition, Physiological/physiology , Animals , Computer Simulation , Humans , Neural Networks, Computer
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