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Non-Invasive Brain Stimulation (NIBS) techniques seem to be effective in treating tobacco use disorder. We aimed to analyze what kinds of protocols are used to treat nicotine addiction in term of cessation and/or reduction and to evaluate the long-term effects of NIBS techniques.We searched PubMed, Scopus, and Web of Science for papers published, with combinations of the following search terms: “Non-invasive brain stimulation OR TMS OR transcranial magnetic stimulation OR tDCS OR transcranial direct current stimulation OR transcranial electrical stimulation OR TES AND Nicotine addiction”.We conducted a preliminary search, which revealed papers on the topic. Articles were included in the review according to the following inclusion criteria: English language, publication in peer reviewed journals, articles about studies performed on non-invasive brain stimulations techniques, and RCT studies. Studies involving clinical populations with organic or psychiatric diseases were excluded. We found 280 articles. Of these, at the first screening and conducted by title and abstract, 63 studies were excluded after duplicates were removed (118). After the second screening conducted by full-text examination, 45 articles were excluded. Ten studies met the inclusion criteria and were included in the review.The clinical benefits of NIBS, including the fast onset and minor side effects, showed that this kind of treatment could be helpful in patients with a long history of smoking in terms of cessation and abstinence rates.

Infrared spectroscopy is a standard method in analytical chemistry that transforms the vibration of atoms in a compound into images. In the mid-infrared (MIR) spectral region extending from 4,000-400 cm-1, the chemical, structural, and compositional information of a molecule, regarded as its fingerprint region, in the solid, liquid, and gas phases can be deduced. Fourier transform infrared (FTIR) spectrometers are predominantly used over conventional dispersive instruments because modern computer technology allows real-time, fast Fourier transform algorithms. This study explored the utility of gas-phase Fourier transform infrared spectroscopy for the chemometric differentiation of aromatic rice. The seven cultivars Basmati, Dinorado, Jasmine, Milagrosa, NSICs Rc148, Rc342, and Rc344 were characterized by different infrared patterns. Agglomerative Hierarchical Clustering (AHC) generated clusters that define the rice's similar characteristics. Correspondingly, Principal Component Analysis (PCA) was able to precisely classify the samples into different varieties (?99%). The results demonstrated that chemometric analysis of FTIR spectrograms can be a reliable technique and has a high potential to discriminate aromatic rice samples based on their infrared fingerprints. The study provided a possible inexpensive and nondestructive alternative that has not been explored before to assess the authenticity of rice varieties through an existing analytical platform. [ABSTRACT FROM AUTHOR]

IntroductionPsychiatric comorbidity is frequent in bariatric surgery candidates. This study aimed to classify bariatric surgery patients according to patterns of preoperative measures of the severity of the eating disorder (ED), depression, and personality traits.MethodsIn the present cross-sectional study, 115 adult candidates for bariatric surgery (75 females, 65.22% of sample; mean age 37) were considered for analysis. Patients’ sociodemographic and psychopathological variables were collected. K-Means clustering analysis was adopted to classify bariatric surgery candidates according to their preoperative Eating Disorder Inventory-2 (EDI-2) scores. In addition, we assessed depression and personality traits using the Beck Depression Inventory-2 (BDI-2) and the Minnesota Multiphasic Personality Inventory-2 (MMPI-2).ResultsCluster analysis based on EDI-2 revealed two preoperative patterns: higher severity (n = 39), and low severity (n = 76). The more severe EDI-2 group had higher scores on the BDI-2 and presented higher scores on several MMPI-2 dimensions, particularly those related to anxiety (Psychasthenia, Anxiety, Fears, Obsessiveness), depression (Depression, including both content and clinical MMPI-2 subscales), externalizing symptoms (Anger, Cynicism, Type A Behavior), and social functioning (Social Introversion, Family Problems, Work Interference).DiscussionEating disorders symptoms in candidates for bariatric surgery are closely related to depression and different psychological conditions assessed with MMPI-2. These psychological variables should be evaluated preoperatively and targeted with more specific psychological interventions.

Background/Objectives: The diagnosis of oral potentially malignant disorders (OPMDs) and oral squamous cell carcinoma (OSCC) represent a significant challenge in oral medicine. Optical coherence tomography (OCT) shows promise for evaluating oral tissue microstructure but lacks standardized diagnostic protocols tailored to the structural variability and lesions of oral mucosa. Methods: This cross-sectional observational study aims to evaluate the diagnostic accuracy of targeted biopsy-based and site-coded OCT protocols for common OPMDs and OSCC. Adult patients clinically diagnosed with OPMDs, including oral leukoplakia (OL), oral lichen planus (OLP), and OSCC were enrolled. Clinical and OCT evaluation before and after punch scalpel-site registration preceding diagnostic biopsy on the target site was performed. Blinded observers analyzed the OCT scans for OCT-based diagnoses. Sensitivity, specificity, and diagnostic accuracy for OCT evaluations before and after punch scalpel-site registration were statistically compared with histological findings. Results: A dataset of 2520 OCT scans and 210 selected images from 21 patients was obtained. Sensitivity and specificity post-target site registration were high for OSCC (98.57%, 100.00%), OL (98.57%, 98.57%), and OLP (97.14%, 98.57%). The positive predictive values ranged from 97.14% to 100.00%, while negative predictive values ranged from 98.57% to 99.29%. Inter-observer agreements were strong for OSCC (0.84) and moderate for OL (0.54) and OLP (0.47–0.49). Targeted OCT scans significantly improved diagnostic accuracy for all conditions (p < 0.001). Conclusions: This preliminary study supports using site-targeted OCT scans followed by a site-targeted punch biopsy, enhancing precision in oral diagnostics. This approach is foundational for developing pioneering automated algorithms guiding oral cancer and pre-cancer diagnosis via OCT imaging.

A high-fidelity real-time simulation code based on a lumped, nonlinear representation of gas turbine components is presented. The code is a general-purpose simulation software environment useful for setting up and testing control equipments. The mathematical model and the numerical procedure are specially developed in order to efficiently solve the set of algebraic and ordinary differential equations that describe the dynamic behavior of gas turbine engines. For high-fidelity purposes, the mathematical model takes into account the actual composition of the working gases and the variation of the specific heats with the temperature, including a stage-by-stage model of the air-cooled expansion. The paper presents the model and the adopted solver procedure. The code, developed in Matlab-Simulink using an object-oriented approach, is flexible and can be easily adapted to any kind of plant configuration. Simulation tests of the transients after load rejection have been carried out for a single-shaft heavy-duty gas turbine and a double-shaft aeroderivative industrial engine. Time plots of the main variables that describe the gas turbine dynamic behavior are shown and the results regarding the computational time per time step are discussed. [DOI: 10.1115/1.2132383]

A novel application of pH sensors is in the detection of amplification in nucleic acid-based methods for diagnosis of organisms. The detection is based on the production of hydrogen ions during the amplification process. In this study, a micro-probe potentiometric sensor for pH was fabricated and applied in the reagentless detection of the White Spot Shrimp Virus (WSSV) through the loop-mediated isothermal amplification (LAMP) technique. The pH micro-probe contained a pencil graphite modified with polypyrrole nanotubes through galvanostatic electrodeposition in the presence of methyl orange (MO). Electropolymerization parameters and potentiometric measurements parameters were optimized to obtain maximum sensitivity. The probe was characterized using Field Emission–Scanning Electron Microscopy (FE-SEM) and Fourier Transform-Infrared (FT-IR) Spectroscopy. The sensor showed a sub-Nernstian response (−45.5 mV/pH) at pH range 2–8 and LOD of ${5.19}\times {10}^{-{8}}$ M; with minimum hysteresis ($\Delta $ m = ± 1.27 mV/pH), and low potential drift (±1.00 mV, pH 8). The probe was used to measure the pH of the microliter-volume reaction mixture at the start and at the end of the LAMP assay for WSSV. The probe detected pH change ($\Delta $ pH = −0.675) that occurred during the LAMP assay. This behavior correlated well with the results of fluorescence detection of the LAMP assay kit using SYBR Safe® DNA gel stain. A high diagnostic sensitivity (93.8%) and specificity (100%) was observed. The fabricated potentiometric sensor showed promising result in monitoring positive LAMP reaction through measurement of pH. This provides a method to diagnose shrimp samples with WSSV that is rapid, easy-to-operate, and cost-effective. [ABSTRACT FROM AUTHOR]

The feasibility of the application of One-Step-Ahead Adaptive (OSAA) Control technique to a gas turbine power plant is investigated. The OSAA technique is a control algorithm especially suitable for nonlinear and time-varying systems. This technique uses the least square algorithm to estimate in real-time a linear model of the controlled system and uses the estimated linear model to evaluate the feedback control variables. The proposed technique allows to control the gas turbine power plant in a wide range of electric loads due to its intrinsic adaptive capabilities. Moreover, the OSAA control does not require the knowledge of the dynamic characteristics (e.g., state space systems or transfer functions) in order to design the control system. The OSAA control system has been applied to a single shaft gas turbine power plant, which is numerically simulated. The proposed control technique has been tested both in Single-Input Single Output (SISO) mode and in Multi-Input Multi-Output (MIMO) mode. Starting from a steady-state condition, the power plant has been supposed to undergo a step reduction of the electric load. The results show that the OSAA control technique effectively counteracts the load reduction with limited overshoots in the controlled variables and, introducing an integral correction with a negligible static error. [DOI: 10.1115/1.1470178]

An innovative electronic system for testing the performance of wind turbines is presented. The main goal of the system is to increase the accuracy in the measurements of torque and speed for each steady-state point of the turbine characteristic power curve. Another useful advantage provided by the electronic control is given by the possibility of fine tuning the load in order to obtain a large number of steady state experimental points describing the characteristic curve of the turbine. Moreover, the system is suitable for integration into an automatic data acquisition and control system. In the paper the main characteristics of the electronic system are described and compared with a traditional system. This electronic control system is used for testing a small Vertical Axis Wind Turbine in a wind tunnel. The wind turbine is directly coupled to a direct current electric generator, and a chopper, electronically controlled by means of a Pulse Width Modulator, is used to supply the circuit. The electric generator is used for braking the wind turbine at various speeds during the performance test. The experimental results obtained through the proposed system are presented and discussed. [DOI: 10.1115/1.1404432]

Adverse drug reactions (ADRs) represent a significant threat to patients’ safety in dentistry, necessitating proactive measures for prevention and treatment. However, identifying ADRs of dental and oral interest can be challenging, and underreporting remains a persistent issue globally. This paper illustrates a smart system to help Italian healthcare personnel, including dentists, in identifying and reporting dental and oral ADRs. This educational program is within a larger multi-regional project financed by the Italian Agency of Drugs (AIFA). The proposed system comprises a free online questionnaire on ADRs of dental interest (including specific items about awareness and attitudes), and after the free consultation of an atlas of clinical images of dental and oral ADRs linked with a digital synopsis of drugs potentially related to ADRs. This section of the project was presented in April 2023 at the 30th National Congress of the Italian College of University Professors of Dental Disciplines, and the system appears to hold tremendous potential to improve the knowledge of healthcare professionals on oral and dental ADRs.

The regular monitoring of iodized salt available in the household and marketplace is necessary for the effective implementation of the national program of salt iodization to control iodine deficiency and its associated diseases. This study describes a colorimetric measurement of iodate in table salt using a smartphone equipped with applications for color analysis and direct readout of iodate levels. The method involved the measurement of the blue component of the colored solution under controlled lighting conditions. The parameters for colorimetric reactions were optimized using a univariate approach – including KI concentration, pH, type and volume of acid, and order of addition of reagents. The effect of NaCl and sample size on the B signal was also investigated. Under optimum conditions, a linear response was observed from 10 to 175 mg iodate per kg of salt (r = 0.9959) with a coefficient of variation of 1.9% over this range and a detection limit of 2.7 mg kg–1 salt. The method was applied for real samples, and the results agreed well with the reference method at the 95% confidence level. The simplicity of operation, compactness, and wide availability of smartphones offer a convenient colorimetric platform for the iodate assessment in table salt. [ABSTRACT FROM AUTHOR]

The present paper provides a review of the more important results obtained by the author, sometimes with co-authors, solving inviscid and viscous compressible flows by means of a lambda methodology. In particular, an implicit numerical algorithm, called fast solver, has always been applied. This methodology separately integrates the compatibility conditions, written in terms of generalized Riemann variables, along appropriate bicharacteristic lines. The multi-dimensional flow problem is, thus, reduced to a sequence of simple quasi one-dimensional problems. The merits of this approach are demonstrated by means of the application of the method to the solution of three dimensional (3-D) subsonic and transonic inviscid flows, of two-dimensional (2-D) and 3-D viscous flows and of the 2-D flow around a vertical axis wind turbine. In the transonic case the shock wave is computed by means of a shock fitting technique, which enforces the proper shock jumps by an explicit use of the Rankine-Hugoniot equations; in the wind turbine case the blades are represented in a time-averaged sense by means of an actuator porous cylinder, having the turbine radius. The results are then compared with other numerical results and with experimental results.

An accurate two-dimensional methodology, the COIN Lambda Fast Solver, for the computation of the flow field about a vertical axis wind turbine is presented. Such a technique determines the smooth flow field by integrating the compatibility conditions along the bicharacteristic lines. The time-averaged wind turbine effects are introduced by means of an actuator porous cylinder having the same radius of the wind turbine. A time-averaged flow field is determined. The computed vertical axis wind turbine performances are compared with other numerical results. A qualitative comparison with experimental data is also shown. Such comparisons prove the merits of the proposed methodology.

Oral potentially malignant disorders can be defined as mucosal lesions and conditions with an increased risk of malignant transformation. Oral potentially malignant disorders are a significant health burden, and they are often diagnosed late due to scant attention to routine dental practice and the low number of specialized oral medicine centres. This report summarizes the DoctOral experience, a research initiative, providing a free smartphone-based decision support tool for the general medical/dental practitioner; the tool is based on the clinical appearance of oral lesions. Captured, oral pictures can be immediately examined via interactive decision trees and constructed on the smartphone. Such decision trees are expressed in standard formats, and they are readily accessible for facilitating the completion of a hypothetical diagnostic path. Since October 2017 the DoctOral mobile app has been downloaded by 10K + users, achieving a score of 4.8 out of 5. DoctOral also supports an unfolding joint initiative, called DoctOralAI: this involves selecting reference images, with which to create an open-source model, and perform a Case-Based Reasoning method, both of which are combined with machine learning. The DoctOral mobile app has revolutionized oral pathology by providing dental students and professionals with an interactive platform for recognizing and diagnosing oral lesions.

Abstract Background In Italy, the beginning of 2021 was characterized by the emergence of new variants of SARS-CoV-2 and by the availability of effective vaccines that contributed to the mitigation of non-pharmaceutical interventions and to the avoidance of hospital collapse. Methods We analyzed the COVID-19 propagation in Italy starting from September 2021 with a Susceptible-Exposed-Infected-Recovered (SEIR) model that takes into account SARS-CoV-2 lineages, intervention measures and efficacious vaccines. The model was calibrated with the Bayesian method Conditional Robust Calibration (CRC) using COVID-19 data from September 2020 to May 2021. Here, we apply the Conditional Robustness Analysis (CRA) algorithm to the calibrated model in order to identify model parameters that most affect the epidemic diffusion in the long-term scenario. We focus our attention on vaccination and intervention parameters, which are the key parameters for long-term solutions for epidemic control. Results Our model successfully describes the presence of new variants and the impact of vaccinations and non-pharmaceutical interventions in the Italian scenario. The CRA analysis reveals that vaccine efficacy and waning immunity play a crucial role for pandemic control, together with asymptomatic transmission. Moreover, even though the presence of variants may impair vaccine effectiveness, virus transmission can be kept low with a constant vaccination rate and low restriction levels. Conclusions In the long term, a policy of booster vaccinations together with contact tracing and testing will be key strategies for the containment of SARS-CoV-2 spread.

Abstract Background Acute or chronic irreversible respiratory failure may occur in patients undergoing pneumonectomy. Aim of this study was to determine transcriptome expression changes after experimental pneumonectomy in swine model. Experimental left pneumonectomy was performed in five pigs under general anaesthesia. Both the resected and the remaining lung, after 60 post-operative completely uneventful days, underwent genome-wide bulk RNA-Sequencing (RNA-Seq). Results Histological analysis showed dilation of air spaces and rupture of interalveolar septa. In addition, mild inflammation, no fibrosis, radial stretch of the bronchus, strong enlargement of airspaces and thinning of the blood supply were observed. Bioinformatic analyses of bulk RNA-Seq data identified 553 Differentially Expressed Genes (DEGs) at adjusted P-value below 0.001, between pre- and post-pneumonectomy. The top 10 up-regulated DEGs were Edn1, Areg, Havcr2, Gadd45g, Depp1, Cldn4, Atf3, Myc, Gadd45b, Socs3; the top 10 down-regulated DEGs were Obscn, Cdkn2b, ENSSSCG00000015738, Prrt2, Amer1, Flrt3, Efnb2, Tox3, Znf793, Znf365. Leveraging digital cytometry tools, no difference in cellular abundance was found between the two experimental groups, while the analysis of cell type-specific gene expression patterns highlighted a striking predominance of macrophage-specific genes among the DEGs. DAVID-based gene ontology analysis showed a significant enrichment of “Extrinsic apoptotic signaling pathway” (FDR q = 7.60 × 10− 3) and “Response to insulin” (FDR q = 7.60 × 10− 3) genes, along with an enrichment of genes involved as “Negative regulators of DDX58/IFIH1 signaling” (FDR q = 7.50 × 10− 4) found by querying the REACTOME pathway database. Gene network analyses indicated a general dysregulation of gene inter-connections. Conclusion This translational genomics study highlighted the existence both of individual genes, mostly dysregulated in certain cellular populations (e.g., macrophages), and gene-networks involved in pulmonary reaction after left pneumonectomy. Their involvement in lung homeostasis is largely supported by previous studies, carried out both in humans and in other animal models (under homeostatic or disease-related conditions), that adopted candidate-gene approaches. Overall, the present findings represent a preliminary assessment for future, more focused, studies on compensatory lung adaptation, pulmonary regeneration and functional reload.

Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive neuromodulation technique, and it has been increasingly used as a nonpharmacological intervention for the treatment of various neurological and neuropsychiatric diseases, including depression. In humans, rTMS over the prefrontal cortex is used to induce modulation of the neural circuitry that regulates emotions, cognition, and depressive symptoms. However, the underlying mechanisms are still unknown. In this study, we investigated the effects of a short (5-day) treatment with high-frequency (HF) rTMS (15 Hz) on emotional behavior and prefrontal cortex morphological plasticity in mice. Mice that had undergone HF-rTMS showed an anti-depressant-like activity as evidenced by decreased immobility time in both the Tail Suspension Test and the Forced Swim Test along with increased spine density in both layer II/III and layer V apical and basal dendrites. Furthermore, dendritic complexity assessed by Sholl analysis revealed increased arborization in the apical portions of both layers, but no modifications in the basal dendrites branching. Overall, these results indicate that the antidepressant-like activity of HF-rTMS is paralleled by structural remodeling in the medial prefrontal cortex.

Como consequência da pandemia da COVID-19 foram observadas reduções nas concentrações de dióxido de nitrogênio (NO2) na atmosfera em diversos países, pois esse gás está altamente relacionado à queima de combustíveis fósseis provenientes de meios de transportes. O objetivo deste trabalho é identificar as mudanças no padrão de emissão de NO2 associadas às medidas de restrição de circulação e confinamento durante a pandemia, nas áreas urbanas de Brasília (DF), Anápolis e Goiânia (GO). Coletamos dados de NO2 troposférico, por meio do sensor TROPOMI, do satélite Sentinel-5P, e dados de precipitação por monitoramento de satélite provenientes da rede de Medição de Precipitação Global (GPM). Calculamos as médias dos valores de NO2 e precipitação (mm/h) para cada uma das imagens entre os anos de 2019 e 2021, bem como as médias móveis semanais para cada área urbana. Assim, delimitamos seis períodos de dois meses, e calculamos a razão da média móvel entre os anos 2020/2019 e 2021/2019. No período supracitado observamos queda na densidade da coluna de NO2 em 2020, com aumento posterior, em 2021, no mesmo período e nas três regiões. Em Brasília a queda foi mais expressiva, sendo, em média, -9,35%, seguida de Goiânia com -2,61% e Anápolis com -1,34%. Apesar da queda das emissões em 2020, no ano seguinte ocorreu o aumento de emissão de NO2. A maior alta observada foi em Goiânia, com +30,3%, seguida de Anápolis, +19,30%, e +16,08% em Brasília.

The smartphone camera presents a convenient, portable, and low-cost innovation in colorimetric measurements. In this paper, a smartphone camera was applied for the colorimetric detection of gaseous elemental mercury, an atmospheric pollutant of concern in environment, and workplace monitoring. A cuprous iodide (CuI)/polystyrene composite was used as the recognition element, which exhibited a reddish color in the presence of Hg0. Digital images of the sensing reagent phase were captured by a smartphone camera and were analyzed in red-green-blue color space using ImageJ, an open source image processing program. Parameters for the digital colorimetric sensing including the color values, polymer reagent binder, amount of CuI, exposure time, and Hg0 concentration were investigated and optimized. The linear working range of the sensor was from 61 to 270 μg/m3 Hg0 with a correlation coefficient of 0.978. The limit of detection is 16 μg/m3 Hg0. This method shows the feasibility of applying a smartphone camera for a simple, reliable, and inexpensive colorimetric measurement of Hg0 vapor in a gas mixture such as air. [ABSTRACT FROM AUTHOR]

Fast and efficient alternative methods for wood species identification are needed to combat illegal logging and to control fair trade. One of the possibilities of rapid wood recognition is via chemiresistor gas sensor arrays (“electronic nose”), the application of which is described in the present paper. Carbon nanotube composites (CNTs) of eight insulating polymers were prepared through solution processing and spin casting. The optimum amount of CNTs in the composites was determined by resistance measurement and the CNTs were characterized by scanning electron microscopy. In the case of static headspace analysis, the sensor responses were reproducible and discernible for the wood species. This was demonstrated based on five wood species (Pterocarpus indicus, Acacia auriculiformis, Gmelina arborea, Vitex parviflora and Diospyros philippinensis). Discrimination of the data was achieved through principal component analysis (PCA) and hierarchical cluster analysis (HCA). PCA score plots and groupings in HCA dendrograms rendered possible the discrimination of these wood species. The potential application of the sensor array approach for wood species identification is high. [ABSTRACT FROM AUTHOR]

Solanum glaucophyllum, a toxic plant known for its calcinogenic effects, causes enzootic calcinosis in ruminant and monogastric animals. We describe an outbreak of enzootic calcinosis that occurred in a herd of 110 horses grazing pastureland heavily contaminated with S. glaucophyllum in Buenos Aires province, Argentina. Ten horses developed clinical signs, and 6 horses died. Clinical signs included abnormal gait (stiff-legged action, short strides), stiffness, thoracolumbar kyphosis, reluctance to move, wide stance, chronic weight loss, weakness, recumbency, and difficulty standing. Autopsy of 2 horses revealed severe mineralization of the aorta, pulmonary arteries, heart, and lungs, consistent with enzootic calcinosis. Although horses usually have very selective grazing behavior, under food restriction conditions, they can ingest the toxic plants and can develop the disease. Enzootic calcinosis should be considered as a differential diagnosis in horses grazing S. glaucophyllum–invaded pasturelands with compatible clinical signs and lesions. [ABSTRACT FROM AUTHOR]

BackgroundNeuroimaging studies have shown a complex pattern of brain activation during perception of a pleasant odor and during its olfactory imagery. To date, little is known regarding changes in motor cortex excitability during these tasks. Bergamot essential oil (BEO) is extensively used in perfumes and cosmetics for its pleasantness. Therefore, to further our understanding of the human sense of smell, this study aimed to investigate the effect of perception and imagery of a pleasant odor (BEO) on motor cortex using Transcranial magnetic stimulation (TMS).Materials and MethodsWe examined the primary motor cortex (M1) excitability during perception of a pleasant odor (BEO) or perception of odorless saline (experiment 1). Furthermore, we tested the effect of olfactory imagery (OI) of BEO on corticospinal excitability (experiment 2). The increase in motor evoked potential (MEP) amplitude was correlated with personality dimensions scores, pleasantness, vividness, and general imagery ability.ResultsThe results indicate that the corticospinal excitability changed after both perception and imagery of a pleasant odor (BEO). The correlation analysis shows an association with neuroticism personality trait (experiment 1) and with general olfactory imagery ability (experiment 2).ConclusionBoth perception of a pleasant odor and its olfactory imagery modulate motor cortex excitability. The enhanced brain activation is affected by specific individual characteristics. Overall, our findings provide physiological evidence for a complex interaction between the olfactory and motor systems.

A surface adsorbed reduced graphene oxide (rGO) on nylon-6 was prepared by a facile vacuum-assisted method. Spectroscopic, surface, and thermal characterization of the fabricated film revealed the formation of semi-ordered stacked rGO nanolayers, indicating physical interaction between the rGO and nylon 6 substrate. Electrical conductivity measurement data suggested a percolated system with a conducting network of nanosheets in the composite matrix. A low percolation threshold of 0.48% was observed, which can be attributed to the high conductivity and large surface to volume ratio of rGO. The conductivity of the nanocomposite was affected by the presence of trimethylamine (TMA) vapor, and the variation was dependent on the concentration of TMA in the vapor phase. This behavior proves the potential of the rGO/nylon6 composite as a promising sensing material for TMA. [ABSTRACT FROM PUBLISHER]

A sensor was fabricated by modifying pencil graphite electrodes with molecularly imprinted polypyrrole (MIPpy) synthesized by electropolymerization of pyrrole monomer at constant potential in the presence of chlorogenic acid (CGA). A comparison between the non-imprinted modified pencil graphite electrode and the molecularly imprinted pencil graphite electrode is reported. Several important parameters controlling the performance of the polypyrrole and the method efficiencies were investigated and optimized. Surface morphology of imprinted and non-imprinted sensor was characterized by scanning electron microscope (SEM) and atomic force microscope (AFM). The molecularly imprinted layer exhibited selectivity and sensitivity toward CGA. Under optimized conditions, the calibration curve demonstrated linearity over a concentration range of 1 × 10 −2 mol/L to 1 × 10 −6 mol/L with a correlation coefficient ( R 2 ) of 0.993 and has life span of more than 3 months without any considerable change in the measured response. The sensor exhibited a sensitivity of −54.7 mV per decade. As an application, this potentiometric sensor has been successfully applied to the determination of CGA content in four different coffee samples and compared with HPLC results. [ABSTRACT FROM AUTHOR]

Abstract Background In cancer research, robustness of a complex biochemical network is one of the most relevant properties to investigate for the development of novel targeted therapies. In cancer systems biology, biological networks are typically modeled through Ordinary Differential Equation (ODE) models. Hence, robustness analysis consists in quantifying how much the temporal behavior of a specific node is influenced by the perturbation of model parameters. The Conditional Robustness Algorithm (CRA) is a valuable methodology to perform robustness analysis on a selected output variable, representative of the proliferation activity of cancer disease. Results Here we introduce our new freely downloadable software, the CRA Toolbox. The CRA Toolbox is an Object-Oriented MATLAB package which implements the features of CRA for ODE models. It offers the users the ability to import a mathematical model in Systems Biology Markup Language (SBML), to perturb the model parameter space and to choose the reference node for the robustness analysis. The CRA Toolbox allows the users to visualize and save all the generated results through a user-friendly Graphical User Interface (GUI). The CRA Toolbox has a modular and flexible architecture since it is designed according to some engineering design patterns. This tool has been successfully applied in three nonlinear ODE models: the Prostate-specific Pten −/− mouse model, the Pulse Generator Network and the EGFR-IGF1R pathway. Conclusions The CRA Toolbox for MATLAB is an open-source tool implementing the CRA to perform conditional robustness analysis. With its unique set of functions, the CRA Toolbox is a remarkable software for the topological study of biological networks. The source and example code and the corresponding documentation are freely available at the web site: http://gitlab.ict4life.com/SysBiOThe/CRA-Matlab.

Computational modeling is a common tool to quantitatively describe biological processes. However, most model parameters are usually unknown because they cannot be directly measured. Therefore, a key issue in Systems Biology is model calibration, i.e., estimate parameters from experimental data. Existing methodologies for parameter estimation are divided in two classes: frequentist and Bayesian methods. The first ones optimize a cost function while the second ones estimate the parameter posterior distribution through different sampling techniques. Here, we present an innovative Bayesian method, called Conditional Robust Calibration (CRC), for nonlinear model calibration and robustness analysis using omics data. CRC is an iterative algorithm based on the sampling of a proposal distribution and on the definition of multiple objective functions, one for each observable. CRC estimates the probability density function of parameters conditioned to the experimental measures and it performs a robustness analysis, quantifying how much each parameter influences the observables behavior. We apply CRC to three Ordinary Differential Equations (ODE) models to test its performances compared to the other state of the art approaches, namely Profile Likelihood (PL), Approximate Bayesian Computation Sequential Monte Carlo (ABC-SMC), and Delayed Rejection Adaptive Metropolis (DRAM). Compared with these methods, CRC finds a robust solution with a reduced computational cost. CRC is developed as a set of Matlab functions (version R2018), whose fundamental source code is freely available at https://github.com/fortunatobianconi/CRC.

Background: Cancer patients undergoing chemotherapy often experience chemotherapy-induced peripheral neuropathy (CIPN), which reportedly causes gait disturbances that may increase their risk for falls. The purpose of this study was to investigate whether CIPN is associated with spatial-temporal gait adaptations and fall risk in post-treatment adult cancer survivors. Method: This study enrolled 16 subjects between 50 and 70 years of age, including 8 subjects with CIPN and 8 subjects with age and morphologically-matched controls. Gait velocity, step length, step time, base of support, swing time, single support time, and double support time as measured by GAITRite. Fall risk was assessed utilizing the Timed Up and Go (TUG) test. Results: Overall, gait velocity (110.75 cm/s, SD = 26.79, p = 0.006) was significantly slower, and step length (53.92 cm, SD = 23.55, p = 0.005) was significantly shorter in those subjects with CIPN. Additionally, CIPN participants had a significantly higher TUG Score (12.33 s, SD = 6.25, p = 0.001) compared to the controls (6.62 s, SD = 1.10). Conclusion: Our investigation suggested that gait speed and step length are key indicators for fall risk. Compared to controls, cancer patients with CIPN may display slower gait velocities, shorter step length, and are at an increased fall risk as indicated by TUG scores. The presence of CIPN appears to increase fall risk, which may easily be assessed in a clinical setting using the TUG test.