Microbiota and microRNAs in lung diseases: mutual influence and role insights.

Trillions of microbial cells colonize human body both internally and externally. The prevalent amount of these reside in the gastrointestinal tract (gut microbiome). Gut microflora support the transformation of food nutrients. The products of this modification processes both modulate gastro-intestinal immunity, and influence other organs such as lung and brain. Recently, it was reported the role of micro-RNAs (miRNAs) as regulators in different pathways of the innate and/or adaptive immune responses. Latest studies discussed the aptitude of probiotics strains to balance the host immune response at a post-transcriptional level by controlling miRNAs expression. We speculated a model of lung immune regulation driven by the axis microbiota-microRNAs, involving asthma, acute injury, cancer and COPD. Based on this axis, we propose a novel approach based on the modification of microRNAs expression centered not exclusively on antagomiRs but also on microbiota modification in order to further potentiate their therapeutic effects.

Vitamin deficiency as risk factor for SARS-CoV-2 infection: correlation with susceptibility and prognosis.

OBJECTIVE: In 2019, an infection provoked by SARS-CoV-2 virus arose in Wuhan, China. Currently, there is still no definite and efficacious therapy for SARS-CoV-2 infection. Moreover, our understanding of the physiopathology of the infection, and risk elements for severity and mortality, is incomplete. PATIENTS AND METHODS: One largely neglected element that could affect prognosis of SARS-CoV-2 infection is the vitamin status of population. The purpose of this review is to evaluate whether a vitamin insufficiency could provoke an augmented risk of SARS-CoV-2 infection or the appearance of major complications. In particular, we evaluated the presence of studies related to the state and effects of vitamin D, C, B, and A in subjects with SARS-CoV-2 disease. RESULTS: Although, actually, the interest in a possible use for vitamin supplementation in SARS-CoV-2 patients is essentially based on indirect data, we tried to examine the evidence about a favorable effect of vitamin supplementation in the therapy of the infection and its complications. CONCLUSIONS: Supplements with vitamin A, B, C, D, and E could represent an inexpensive and sufficiently safe approach, and a useful therapeutic complement. However, solid clinical research data are expected to support such claim.

Spatio-temporal parameters of ataxia gait dataset obtained with the Kinect.

Ataxic syndromes include several rare, inherited and acquired conditions. One of the main issues is the absence of specific, and sensitive automatic evaluation tools and digital outcome measures to obtain a continuous monitoring of subjects' motor ability. Gait evaluation was performed by Kinect v2 in a cohort of young participant affected by ataxia syndrome. The dataset is composed of the spatio-temporal parameters calculated by the skeleton acquired by the Kinect sensor, by the diagnosis of each participant, and by the total score of the clinical scale SARA. These parameters have been previously validated and corrected as requested by the Bland-Altman test.

Validation of low-cost system for gait assessment in children with ataxia.

BACKGROUND: Ataxic syndromes include several rare, inherited and acquired conditions. One of the main issues is the absence of specific, and sensitive automatic evaluation tools and digital outcome measures to obtain a continuous monitoring of subjects' motor ability. OBJECTIVES: This study aims to test the usability of the Kinect system for assessing ataxia severity, exploring the potentiality of clustering algorithms and validating this system with a standard motion capture system. METHODS: Gait evaluation was performed by standardized gait analysis and by Kinect v2 during the same day in a cohort of young patient (mean age of 13.8±7.2). We analyzed the gait spatio-temporal parameters and we looked at the differences between the two systems through correlation and agreement tests. As well, we tested for possible correlations with the SARA scale as well. Finally, standard classification algorithm and principal components analysis were used to discern disease severity and groups. RESULTS: We found biases and linear relationships between all the parameters. Significant correlations emerged between the SARA and the Speed, the Stride Length and the Step Length. PCA results, highlighting that a machine learning approach combined with Kinect-based evaluation shows great potential to automatically assess disease severity and diagnosis. CONCLUSIONS: The spatio-temporal parameters measured by Kinect cannot be used interchangeably with those parameters acquired with standard motion capture system in clinical practice but can still provide fundamental information. Specifically, these results might bring to the development of a novel system to perform easy and quick evaluation of gait in young patients with ataxia, useful for patients stratification in terms of clinical severity and diagnosis.

Biodegradation ability of two selected microbial autochthonous consortia from a chronically polluted marine coastal area (Priolo Gargallo, Italy).

The aims of this study were: (i) the characterization of the structure of the indigenous microbial community associated with the sediments under study; (ii) the isolation and characterization of microbial consortia able to degrade the aged hydrocarbons contaminating the sediments, and (iii) the assessment of related biodegradation capability of selected consortia. Samples of surface sediments were collected in Priolo Gargallo harbour (Sicily, Italy). The samples were analysed for physical, chemical (GC-FID analysis) and microbiological characteristics (qualitative (16S rDNA clone library) and quantitative (DAPI, CFU and MPN count) analysis). The sediment samples were used for the selection of two microbial consortia (indicated as PSO and PSM) with high biodegradation capacity for crude oil (∼95%) and PAHs (∼63%) respectively. Genetic analysis showed that Alcanivorax and Cycloclasticus were the dominant genera in both the PSO and PSM consortia. Oil-polluted environments naturally develop an elevated biorecovery potential. The presence of a highly specialized microbial flora (adapted to support the contamination) and their stimulation through favourable induced conditions provides a promising recovery strategy. The chance to identify and select indigenous bacteria and/or consortia with a high biodegradation capacity is fundamental for the development and optimization of bioaugmentation strategies especially for those concerning in situ applications.

Disentangling the initiation from the response in joint attention: an eye-tracking study in toddlers with autism spectrum disorders.

Joint attention (JA), whose deficit is an early risk marker for autism spectrum disorder (ASD), has two dimensions: (1) responding to JA and (2) initiating JA. Eye-tracking technology has largely been used to investigate responding JA, but rarely to study initiating JA especially in young children with ASD. The aim of this study was to describe the differences in the visual patterns of toddlers with ASD and those with typical development (TD) during both responding JA and initiating JA tasks. Eye-tracking technology was used to monitor the gaze of 17 children with ASD and 15 age-matched children with TD during the presentation of short video sequences involving one responding JA and two initiating JA tasks (initiating JA-1 and initiating JA-2). Gaze accuracy, transitions and fixations were analyzed. No differences were found in the responding JA task between children with ASD and those with TD, whereas, in the initiating JA tasks, different patterns of fixation and transitions were shown between the groups. These results suggest that children with ASD and those with TD show different visual patterns when they are expected to initiate joint attention but not when they respond to joint attention. We hypothesized that differences in transitions and fixations are linked to ASD impairments in visual disengagement from face, in global scanning of the scene and in the ability to anticipate object's action.

An efficient unsupervised fetal QRS complex detection from abdominal maternal ECG.

Non-invasive fetal heart rate is of great relevance in clinical practice to monitor fetal health state during pregnancy. To date, however, despite significant advances in the field of electrocardiography, the analysis of abdominal fetal ECG is considered a challenging problem for biomedical and signal processing communities. This is mainly due to the low signal-to-noise ratio of fetal ECG and difficulties in cancellation of maternal QRS complexes, motion and electromyographic artefacts. In this paper we present an efficient unsupervised algorithm for fetal QRS complex detection from abdominal multichannel signal recordings combining ICA and maternal ECG cancelling, which outperforms each single method. The signal is first pre-processed to remove impulsive artefacts, baseline wandering and power line interference. The following steps are then applied: maternal ECG extraction through independent component analysis (ICA); maternal QRS detection; maternal ECG cancelling through weighted singular value decomposition; enhancing of fetal ECG through ICA and fetal QRS detection. We participated in the Physionet/Computing in Cardiology Challenge 2013, obtaining the top official scores of the challenge (among 53 teams of participants) of event 1 and event 2 concerning fetal heart rate and fetal interbeat intervals estimation section. The developed algorithms are released as open-source on the Physionet website.

A personal monitoring architecture to detect muscular fatigue in elderly.

Muscle fatigue and exercise intolerance are common and frequent symptoms complained by patients with neuromuscular disease. Muscle fatigue would occur when the intended physical activity can no longer be continued or is perceived as involving excessive effort and discomfort. Except for several rare myopathies with specific metabolic derangements leading to exercise-induced muscle fatigue, most studies fail to identify precise pathogenic mechanism of fatigue in this population of patients. On the other hand, apart from canonical examples of neuromuscular diseases, a number of conditions in which muscle apparatus can be involved is known to occur with high prevalence among certain people categories, such as elderly or people undergoing immobilization. In these cases exercise intolerance and muscle fatigue can be severely incapacitating in common daily activities. An objective and smart, unobtrusive techniques, able to objectively measure fatigue phenomenon, would be useful in monitoring muscle function in both NMD patients and patients with secondary skeletal muscle involvement. In this study, we report a novel, non-invasive assistive architecture for the elderly to assess muscle fatigue by biomedical sensors (surface electromyography) using wireless platform during exercise in an ergonomic platform.

A neuron-astrocyte transistor-like model for neuromorphic dressed neurons.

Experimental evidences on the role of the synaptic glia as an active partner together with the bold synapse in neuronal signaling and dynamics of neural tissue strongly suggest to investigate on a more realistic neuron-glia model for better understanding human brain processing. Among the glial cells, the astrocytes play a crucial role in the tripartite synapsis, i.e. the dressed neuron. A well-known two-way astrocyte-neuron interaction can be found in the literature, completely revising the purely supportive role for the glia. The aim of this study is to provide a computationally efficient model for neuron-glia interaction. The neuron-glia interactions were simulated by implementing the Li-Rinzel model for an astrocyte and the Izhikevich model for a neuron. Assuming the dressed neuron dynamics similar to the nonlinear input-output characteristics of a bipolar junction transistor, we derived our computationally efficient model. This model may represent the fundamental computational unit for the development of real-time artificial neuron-glia networks opening new perspectives in pattern recognition systems and in brain neurophysiology.

Automated extraction and classification of dynamic metrical features of morphological development in dissociated Purkinje neurons.

The morphological development of in vitro single cerebellar Purkinje cells obtained from wild type P1 CD1 mice was assessed through a dedicated non-invasive technique based on image processing algorithms and multivariate analysis. Image processing algorithms were implemented to extract metrical features characterizing cell structure and dendritic arborization from sequential optical micrographs. Quantitative morphological features were analyzed in order to identify relevant metrical characteristics common to Purkinje cells in wild type P1 CD1 mice. Cell arborization was found to be characterized by a high fractal dimension and the directionality and level of complexity were shown to be key features for cell morphology classification, as underlined using a three-way PCA analysis.

Assessment and comparison of neural morphology through metrical feature extraction and analysis in neuron and neuron-glia cultures.

The morphology of dissociated single cerebellar Purkinje cells obtained from wild-type P1 CD1 mice was assessed in the absence and in the presence of glia. A dedicated noninvasive technique based on optical microscopy was developed. Image processing algorithms were implemented to extract metrical features characterizing cell structure and dendritic arborization. The morphological features were analyzed in order to identify quantitative differences in Purkinje cell morphology due to interactions with astrocytes.

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.

Implementation of Fowler's method for end-tidal air sampling.

The design, realization and testing of a CO(2)-triggered breath sampler, capable of a separate collection of dead space and end-tidal air on multiple breaths, is presented. This sampling procedure has advantages in terms of the sample volume, insights regarding the origin of compounds, increased reproducibility and higher concentrations of compounds. The high quality of design and the speed of the components ensure a breath-by-breath estimate of dead volume, as well as the comfort and safety of the subject under test. The system represents a valid tool to contribute to the development of a standardized sampling protocol needed to compare results obtained by the various groups in this field.

A composite sensor array impedentiometric electronic tongue Part I. Characterization.

A study aimed at the characterization of five compounds with different chemical characteristics and gustative perceptions by measuring the variations of the electrical impedance of a composite sensor array is presented. The array was composed of five sensors of three different types based on carbon nanotubes or carbon black dispersed in polymeric matrices and doped polythiophenes. Measurements were carried out by evaluating the electrical impedance of the sensor array at a frequency of 150 Hz, and the data acquisition process was automated; a mechanical arm and a rotating platform controlled by a data acquisition card and a dedicated software allowed the sequential dipping of sensors in the test solutions. Fifty different solutions eliciting the 5 basic tastes (sodium chloride, citric acid, glucose, glutamic acid and sodium dehydrocholate for salty, sour, sweet, umami and bitter, respectively) at 10 concentration levels comprising the human perceptive range were analysed. More than 100 measurements were carried for each sample in a 4-month period to evaluate the system repeatability and robustness. The impedentiometric composite sensor array is shown to be sensitive, selective and stable for use in an electronic tongue.

A composite sensor array impedentiometric electronic tongue Part II. Discrimination of basic tastes.

An impedentiometric electronic tongue based on the combination of a composite sensor array and chemometric techniques aimed at the discrimination of soluble compounds able to elicit different gustative perceptions is presented. A composite array consisting of chemo-sensitive layers based on carbon nanotubes or carbon black dispersed in polymeric matrices and doped polythiophenes was used. The electrical impedance of the sensor array was measured at a frequency of 150 Hz by means of an impedance meter. The experimental set-up was designed in order to allow the automatic selection of a test solution and dipping of the sensor array following a dedicated measurement protocol. Measurements were carried out on 15 different solutions eliciting 5 different tastes (sodium chloride, citric acid, glucose, glutamic acid and sodium dehydrocholate for salty, sour, sweet, umami and bitter, respectively) at 3 concentration levels comprising the human perceptive range. In order to avoid over-fitting, more than 100 repetitions for each sample were carried in a 4-month period. Principal component analysis (PCA) was used to detect and remove outliers. Classification was performed by linear discriminant analysis (LDA). A fairly good degree of discrimination was obtained.