Treponema denticola in Disseminating Endodontic Infections

Treponema denticola is a consensus periodontal pathogen that has recently been associated with endodontic pathology. In this study, the effect of mono-infection of the dental pulp with T. denticola and with polymicrobial “red-complex” organisms (RC) (Porphyromonas gingivalis, Tannerella forsythia, and T. denticola) in inducing disseminating infections in wild-type (WT) and severe-combined-immunodeficiency (SCID) mice was analyzed. After 21 days, a high incidence (5/10) of orofacial abscesses was observed in SCID mice mono-infected with T. denticola, whereas abscesses were rare in SCID mice infected with the red-complex organisms or in wildtype mice. Splenomegaly was present in all groups, but only mono-infected SCID mice had weight loss. T. denticola DNA was detected in the spleen, heart, and brain of mono-infected SCID mice and in the spleen from mono-infected wild-type mice, which also had more periapical bone resorption. The results indicate that T. denticola has high pathogenicity, including dissemination to distant organs, further substantiating its potential importance in oral and linked systemic conditions

An approach based on VR to design industrial human-robot collaborative workstations

This paper presents an integrated approach for the design of human-robot collaborative workstations in industrial shop floors. In particular, the paper presents how to use virtual reality (VR) technologies to support designers in the creation of interactive workstation prototypes and in early validation of design outcomes. VR allows designers to consider and evaluate in advance the overall user experience, adopting a user-centered perspective. The proposed approach relies on two levels: the first allows designers to have an automatic generation and organization of the workstation physical layout in VR, starting from a conceptual description of its functionalities and required tools; the second aims at supporting designers during the design of human-machine interfaces (HMIs) by interaction mapping, HMI prototyping and testing in VR. The proposed approach has been applied on two realistic industrial case studies related to the design of an intensive warehouse and a collaborative assembly workstation for automotive industry, respectively. The two case studies demonstrate how the approach is suited for early prototyping of complex environments and human-machine interactions by taking into account the user experience from the early phases of design

Analysis of the tautomeric equilibrium of two red monoazo dyes by UV–Visible, Raman and SERS spectroscopies

Acid Red 26 and Acid Red 18 are two early synthetic dyes belonging to the monazo dye class. The molecular structure of this class of dyes is characterized by the chromophoric azo group (N[dbnd]N) generally attached to benzene or naphthalene derivatives containing electron withdrawing and/or donating groups as substituents. As both red dyes have an OH group in ortho- position respect to the azo group, they undergo an azo-hydrazone tautomerism. In this work, UV–Vis, Raman and SERS spectroscopic analysis of the red dye solutions were carried out at different pH conditions, in order to evaluate the preponderance of one tautomer over the other as a function of the pH. Different experimental conditions were tested in order to find the best ones for the detection of both dyes. Thus, Raman spectra of the powder and aqueous solutions of AR26 and AR18 were obtained at the natural pH of the solutions, and above and below that value. The SERS analysis of the dye solutions were carried out at various pH values between 2 and 10, and with excitation at 442, 532 and 633 nm. The molecular structure and the theoretical Raman spectra of the two tautomers of both red dyes were calculated by DFT methods. The obtained results were used for the assignment of the Acid Red 26 and Acid Red 18 vibrational modes. Finally, a textile sample dyed with AR18 was analyzed by SERS

Deep eutectic solvents: green solvents for the removal of degraded gelatin on cellulose nitrate cinematographic films

Cellulose nitrate (CN) has been used in the past as support for photographic negatives and cinematographic films. This material is particularly unstable and can undergoes severe degradation due to thermal, photocatalytic and hydrolytic loss of nitro groups from the lateral chain. Thus, to prevent the disappearance of the movies, their scanning and digitalization become a priority. However, CN bases degradation may prevent the scanning of the films. The decrease in pH, for instance, lowers the viscosity of gelatin, which becomes softer. This causes the formation of gelatin residues which stick on the back of the superimposed frames inside the reels creating a deposit. Traditional approaches to clean gelatin residues from the surface of CN bases include the mechanical removal with scalpels and the use of organic solvents (such as isopropyl alcohol). However, these methods are either slow and ineffective or could potentially damage the degraded CN supports. To overcome these drawbacks, we have evaluated the performance of three choline chloride and betaine-based Deep Eutectic Solvent (DES) formulations as alternative for the removal of gelatine residues from CN supports. These solvents are inexpensive (when compared to traditional solvents), easy to prepare, green (non volatile, safe towards the operators and the environment, and potentially recyclable), non flammable and have been previously proposed for the extraction of proteinaceous materials, but their use for the restoration of photographic negatives or cinematographic films has not been reported yet. Selected areas over the frames of a real deteriorated CN cinematographic film were cleaned comparing the DES performances with the ones obtained using isopropyl alcohol as an example of a traditional method. In particular, the tested DES formulations showed superior cleaning power compared to isopropyl alcohol and, at the selected application times, resulted capable to remove the gelatin residues without affecting the CN film supports. Graphical abstract: [Figure not available: see fulltext.]

Light extinction estimates using the IMPROVE algorithm: The relevance of site-specific coefficients

Atmospheric aerosol and gases affect visibility by scattering and absorbing the incoming radiation (Watson, 2002; Pitchford et al, 2007). While the role of gases is relatively well understood, the effect of particulate matter (PM) is more complicated to be assessed since it depends on several factors such as particles size distribution and chemical composition as well as meteorological parameters (e.g. relative humidity \u2013 RH). The U.S. Interagency Monitoring of Protected Visual Environments (IMPROVE) network proposed a method to retrieve atmospheric light extinction coefficient (bext, Mm-1) in national parks from compositional and meteorological data (Malm et al, 1994; Watson, 2002). The result of this approach (often called chemical light extinction) allows the evaluation of visibility indicators such as visual range (VR) via the Koschmieder equation VR=3.912/bext. In this study we tailored the IMPROVE equation using site-specific dry mass extinction efficiencies and hygroscopic growth functions in order to obtain bext estimates which better reflect the typical atmospheric characteristics of the sampling site and period. The revised formulation was tested for the first time in the urban area of Milan, for two weeks during the winter season in 2015. Moreover, it was applied to a large and fully characterized dataset referred to PM1 samples collected in winter 2012. Following the IMPROVE algorithm (Malm et al, 1994; Watson, 2002; Pitchford et al, 2007) the chemical light extinction equation used in this work was: bext = k1 x f1(RH) x [AMSUL] + k2 x f2(RH) x [AMNIT] + k3 x f3(RH) [OM] + k4 x [fine soil] + bap + 0.60 x [coarse mass] + 0.33 x [NO2] (ppb) + Rayleigh scattering, where inputs are the concentrations of the five major PM components (ammonium sulphate - AMSUL, ammonium nitrate AMNIT, organic matter - OM, fine soil, coarse mass) in \u3bcg m-3, NO2 concentration (in ppb), Rayleigh scattering by gases (Mm-1) and aerosol light absorption coefficient (bap, Mm-1) measured with a home-made polar photometer on PTFE filters. Dry mass extinction efficiencies (k1-k4, m2 g-1) for every chemical component of interest were calculated considering size distributions measured in Milan (Vecchi et al, 2012), particles densities and complex refractive indices (Watson, 2002). Furthermore, hygroscopic growth functions fi(RH), defined as the ratios between ambient and dry aerosol scattering coefficients bsp), were also calculated (using hygroscopic growth factors taken from the literature) and were applied to those PM components (AMSUL, AMNIT and OM), whose bsp are enhanced by their water uptake at medium-high RH values. It is worthy to note that in the original IMPROVE algorithm (Malm et al, 1994; Watson, 2002) the hygroscopic growth function f(RH) is calculated referring only to AMSUL ygroscopic properties and it is applied also to AMNIT, whereas OM is considered as non-hygroscopic. Non-negligible discrepancies were found between tailored dry mass extinction efficiencies and the original IMPROVE ones. Furthermore, differences between calculated fi(RH) and IMPROVE hygroscopic growth function were found. The methodology here described was applied to a PM1 dataset thus retrieving the extinction contribution given by the different PM1 components as well as by the major aerosol sources. Both methodological and experimental results will be shown in the presentation. This work shows that \u2013 due to the large variability in size distributions and aerosol composition at sites with different characteristics (e.g. urban, industrial, rural) \u2013 it is advisable to calculate site-specific k1-k4 and fi(RH) coefficients instead of using the original IMPROVE ones, which refer to aerosol properties measured at U.S. national parks

Development of a dual-wavelength thermo-optical transmittance analyser: characterization and first results

Carbonaceous aerosol (CA) plays an important role in many different issues ranging from human health to global climate change. It mainly consists of organic carbon (OC) and elemental carbon (EC) although a minor fraction of carbonate carbon could be also present. Thermal-optical methods (TOT/TOR) are presently the most widespread approach to OC/EC speciation. Despite their popularity, there is still a disagreement among the results, especially for what concerns EC as different thermal protocols can be used. In fact, the pyrolysis occurring during the analysis can heavily affect OC/EC separation, depending on PM composition in addition to the used protocol. The main hypothesis at the basis of the technique relies on the optical properties of EC and OC: while EC is strongly light absorbing, OC is generally transparent in the visible range. However, a fraction of light-absorbing OC exists: the Brown Carbon (BrC) (Andreae and Gelencs\ue9r, 2006). The presence in the sample of BrC can shift the split point since it is slightly absorbing also @ 635nm, the typical laser wavelength used in this technique (Chen et al., 2015). At the Physics Department of the University of Genoa, a Sunset EC/OC analyser unit has been modified in order to monitor the optical transmittance during the thermo-optical analysis at two different wavelengths: 635 nm (the original wavelength of the instrument) and 405 nm (Fig.1). The additional use of the 405 nm transmittance measurement provides valuable information about the composition of the sample as well as on the pyrolytic carbon formation, both able to affect the instrumental \u201csplit point\u201d (i.e. the moment of the analysis in which the laser transmittance is back to its starting value, thus defining EC/OC separation). We present here the new instrument set-up, providing its full characterization with \u201csynthetic\u201d samples (i.e. mixtures of sucrose, graphitic carbon, and pure scattering particles). Moreover, we show also the results obtained analysing at 2-\uf06c - with both NIOSH and EUSAAR_2 protocols - real PM samples collected in very different conditions (i.e. summer-winter) and sites (ranging from urban to rural/mountain). Furthermore, we have recently introduced a new possibility, based on the apportionment of the absorption coefficient (babs) of particle-loaded filters, for correcting the thermo-optical analysis of PM samples (Massab\uf2 et al, 2016), an example in Fig.2. The apportionment is based on the optical analysis performed by the Multi-Wavelength Absorbance Analyser (MWAA), an instrument developed at the Physics Department of the University of Genoa (Massab\uf2 et al., 2015). The apportionment method uses the information gathered at five different wavelengths in a renewed and upgraded version of the approach usually referred to as Aethalometer model (Sandradewi et al., 2008). We present here also the results of the thermo-optical analysis correction (Massab\uf2 et al., 2016) applied to the dual-\uf06c analysis, which lead to a better homogeneity between the results obtained with different thermal protocols

Characteristics of cyclist crashes in Italy using latent class analysis and association rule mining

The factors associated with severity of the bicycle crashes may differ across different bicycle crash patterns. Therefore, it is important to identify distinct bicycle crash patterns with homogeneous attributes. The current study aimed at identifying subgroups of bicycle crashes in Italy and analyzing separately the different bicycle crash types. The present study focused on bicycle crashes that occurred in Italy during the period between 2011 and 2013. We analyzed categorical indicators corresponding to the characteristics of infrastructure (road type, road signage, and location type), road user (i.e., opponent vehicle and cyclist\u2019s maneuver, type of collision, age and gender of the cyclist), vehicle (type of opponent vehicle), and the environmental and time period variables (time of the day, day of the week, season, pavement condition, and weather). To identify homogenous subgroups of bicycle crashes, we used latent class analysis. Using latent class analysis, the bicycle crash data set was segmented into 19 classes, which represents 19 different bicycle crash types. Logistic regression analysis was used to identify the association between class membership and severity of the bicycle crashes. Finally, association rules were conducted for each of the latent classes to uncover the factors associated with an increased likelihood of severity. Association rules highlighted different crash characteristics associated with an increased likelihood of severity for each of the 19 bicycle crash types

Unsafe cycling behaviours and near crashes among Italian cyclists

This study investigates the direct and indirect effect of three types of unsafe behaviours (i.e. errors, generic violations and smartphone-specific violations) on the likelihood of near crashes and actual crashes among Italian cyclists. We considered smartphone-specific violations as a different unsafe behaviour subtype that enhances the probability of committing errors, thus increasing the likelihood of being involved in near crashes. Furthermore, we hypothesized that near crashes will predict actual crashes. Results revealed that errors predicted near crashes, whereas generic and smartphone-specific violations did not. Near crashes mediated the effect of errors on crashes. Moreover, smartphone-specific violations predicted crashes throughout its consecutive effects on errors and near crashes. These findings contribute to deepen our understanding of the relationship between cyclists\u2019 unsafe behaviours, near crashes and actual crashes. To our knowledge, the present study is the first that links errors to near crashes among cyclists