Second campaign of microclimate monitoring in the carcer tullianum: temporal and spatial correlation and gradients evidenced by multivariate analysis

Background

This paper discusses results obtained in the second monitoring campaign of the Carcer Tullianum, a particular hypogeum environment located in the historical centre of Rome (Italy). In the first paper we stressed the need to apply chemometric tools to this kind of studies in order to obtain full and significant information; really information on sampling design, sensors (type, number, position) and instrument validation seems to be not easy to find in literature for researches dealing with monitoring of indoor environments. Also in this case three main parameters (temperature, humidity, illuminance) were monitored in the complex construction by an inexpensive self-assembled system along some horizontal and vertical vectors together with some measurements of oxygen, carbon dioxide and barometric pressure. With respect to the first campaign, we used a higher number of sensors to cover a new excavated zone; for the same reason, as well as to take into account the presence of visitors, a different experimental design was adopted.

Results

Different data treatments were applied to data coming from all the used sensors. A good view of the microclimate was obtained that also resulted coherent with the different position of the three rooms constituting the monitored site (Carcer, Tullianum, Convent). Classical time plots resulted useful to evidence the correlation of the main monitored parameters (T, RH% and illuminance) with macroclimate, as well as their delay in following macroclimate. Box-Whisker and Gain-Loss graphs evidenced at the best the microclimate differences between the three rooms; an almost hypogean microclimate was evidenced for the lower room (Tullianum) where humidity values range between 90 and 100% while lower values, but anyway higher than the external, and spread more widely were measured passing to Convent and Carcer with minimum values around 50% for the last. A scarce or very scarce correlation with macroclimate was evidenced for all the three main measured parameters. Lighting results mainly dependent on artificial light and only in few cases, but unfortunately in the most precious zone, illuminance exceeds values suggested by Normative.

Conclusions

Box-Whisker and Gain-Loss graphs allowed us to have the best view of the microclimate for all the monitored rooms. The influence of lighting by lamps on the other monitored parameters resulted overlapped and clearly topped the solar one. The worst situation was found in the Carcer, where the presence of the main chandelier worsens the state of the frescoed walls, already subjected to wide changes in temperature and humidity. Also the lighthouse located above the Convent provokes lighting exceeding values suggested by Normative while, as expected, LEDs resulted as suitable source of light from a conservation point of view. Susanne Heidi Plattner, Patrizia Fortini and Maria Pia Sammartino contributed equally to this work     

Characterisation of spatial and temporal changes in pH gradients in microfluidic channels using optically trapped fluorescent sensors

This paper demonstrates the use of micron sized beads, modified with fluorescent dyes, as non-invasive sensors to probe the local changes in pH, within a microfluidic channel. To achieve this, amine modified polystyrene spheres (either 3 microm or 6 microm in diameter) were functionalised with the pH sensitive fluorochrome SNARF-1 to produce point sensors. The modified beads were trapped at defined positions close to a pair of integrated planar gold microelectrodes within the channel, using optical tweezers. Both transient and steady-state electrochemical potentials were applied to the microelectrode pair in order to generate changes in the local pH, associated with electrolysis. The functionalised beads indicated the pH changes in the channel, measured as a change in the fluorescence signal, generated by the immobilised pH sensitive dye. Responses were measured with temporal resolutions of between 1 and 200 ms, whilst the spatial resolution of the pH gradients was limited by the size of the beads to 3 microm.     

Spectroscopic and quantitative analysis of spiroorthoester synthesis by two-dimensional correlation and multivariate curve resolution methods of NIR data

The spiroorthoester synthesis includes several competitives reactions. A way of determining the reactions that are taking place and their sequential order, is presented. The reaction between the phenylglycidylether and gamma-butyrolactone to obtain a spiroorthoester has been monitored by near-infrared spectroscopy (NIR). In addition to the formation of the corresponding spiroorthoester, some parallel processes can occur. By means of two-dimensional correlation analysis, only one reaction is postulated, the one corresponding to the spiroorthoester formation. This was confirmed by recording the NMR spectra of the final product. Applying multivariate curve resolution-alternating least squares (MCR-ALS) to the NIR spectra obtained during the reaction, it has been possible to obtain the concentration values of the species involved in the reaction. The recovered spectra were compared with the experimentally recorded spectra for the reagents (phenylglycidylether, gamma-butyrolactone) and the final product (spiroorthoester) and the correlation coefficients were, in all cases, higher than 0.990. The maximum and minimum limits associated with the ALS solutions were calculated, making it possible to limit to a considerable extent the ambiguity that is characteristic of these curve resolution methods.     

Insertion of indigo molecules in the sepiolite structure as evidenced by 1H-29Si heteronuclear correlation spectroscopy

Despite the numerous studies of the famous indigo-based pigment Maya Blue, there are still many questions regarding the elucidation of its structure. Here, two-dimensional (2D) (1)H-(29)Si heteronuclear correlation (HETCOR) spectroscopy with frequency-switched Lee-Goldburg (FSLG) homonuclear decoupling is applied to sepiolite and sepiolite-indigo complexes. Owing to the high resolution in the (1)H dimension of the 2D (1)H-(29)Si HETCOR spectrum obtained by FSLG homonuclear decoupling, the assignment of the (29)Si cross-polarization magic-angle spinning (CPMAS) spectrum of sepiolite is clearly confirmed. Moreover, 2D (1)H-(29)Si FSLG-HETCOR spectroscopy gives the first direct evidence that some indigo molecules are inserted in the sepiolite structure whereas no interaction between indigo and the external side surface (silanol groups) is observed in the (29)Si CPMAS spectra. These results are consistent with the fact that indigo molecules interact with water coordinated to magnesium and suggest that Maya Blue made from sepiolite is not a surface complex.     

Dual-label autoradiographic analysis of human skin fibroblast and myoblast proteins by two-dimensional polyacrylamide gel electrophoresis using immobilised pH gradients in the first dimension

Horizontal two-dimensional polyacrylamide gel electrophoresis with immobilised pH gradients in the first dimension has been applied to the analysis of human skin fibroblast and muscle myoblast total cell proteins. Excellent two-dimensional separations of skin fibroblast proteins were obtained using pH 4-10 immobilised pH gradient gels with a long interelectrode distance (16 cm), but resolution was degraded, particularly of the more acidic proteins, by the use of shorter (10 cm) gels. Improved resolution of acidic and basic proteins was obtained using separate pH 4-7 and pH 7-10 immobilised pH gradient gels respectively in the first dimension. Two-dimensional protein maps of skin fibroblast proteins were visualised both by silver staining and by autoradiography of samples labelled synthetically with [35S]methionine. Horizontal two-dimensional electrophoresis, using pH 4-7 and pH 7-10 immobilised pH gradient gels in the first dimension, was applied to the analysis of protein samples from skin fibroblasts and muscle myoblasts dual-labelled synthetically with [35S]methionine and [75Se]selenomethionine in an attempt to identify sets of proteins specific to each cell type. In addition, two-dimensional maps or protein samples derived from normal individuals and patients with Duchenne muscular dystrophy were compared to search for protein changes associated with the disease state. Although sets of qualitative protein spot differences were observed by visual inspection of the two-dimensional gels, more rigorous qualitative and quantitative analysis of the patterns using a computerised analysis system will be required to obtain the maximum amount of information from these data.     

On the implementation of spatial constraints in multivariate curve resolution alternating least squares for hyperspectral image analysis

Hyperspectral imaging (HSI) is a method for exploring spatial and spectral information associated with the distribution of the different compounds in a chemical or biological sample. Amongst the multivariate image analysis tools utilized to decompose the raw data into a bilinear model, multivariate curve resolution alternating least squares (MCR‐ALS) can be applied to obtain the distribution maps and pure spectra of the components of the sample image. However, a requirement is to have the data in a two‐way matrix. Thus, a preliminary step consists of unfolding the raw HSI data into a single‐pixel direction. Consequently, through this data manipulation, the information regarding pixel neighboring is lost, and spatial information cannot directly be constrained on the component profiles in the current MCR‐ALS algorithm. In this short communication, we propose an adaptation of the MCR‐ALS framework, enabling the potential implementation of any variation of spatial constraint. This can be achieved by adding, at each least‐squares step, refolding/unfolding of the distribution maps for the components. The implementation of segmentation, shape smoothness, and image modeling as spatial constraints is proposed as a proof of concept. Copyright © 2015 John Wiley & Sons, Ltd.     

Immobilized pH gradients as a first dimension in shotgun proteomics and analysis of the accuracy of pI predictability of peptides

In this work, we demonstrate the potential use of immobilized pH gradient isoelectric focusing as a first dimension in shotgun proteomics. The high resolving power and resulting reduction in matrix ionization effects due to analyzing peptides with almost the exact same physiochemical properties, represents a significant improvement in performance over traditional strong cation-exchange first-dimensional analysis associated with the shotgun proteomics approach. For example, using this technology, we were able to identify more than 6000 peptides and > 1200 proteins from the cytosolic fraction of Escherichia coli from approximately 10 microg of material analyzed in the second-dimensional liquid chromatography-tandem mass spectrometry experiment. Sample loads on the order of 1 mg can be resolved to 0.25 isoelectric point (pI) units, which make it possible to analyze organisms with significantly larger genomes/proteomes. Accurate pI prediction can then be employed using currently available algorithms to very effectively filter data for peptide/protein identification, and thus lowering the false-positive rate for cross-correlation-based peptide identification algorithms. By simplifying the protein mixture problem to tryptic peptides, the effect of specific amino acids on pI prediction can be evaluated as a function of their position in the peptide chain.     

Oxidative cleavage of S‐Arylmercaptoacetic acids by pyridinium chlorochromate: Kinetic and correlation analysis

Kinetics of oxidation of 24 S‐Arylmercaptoacetic acids (SAMA) by pyridinium chlorochromate (PCC) have been studied in acidmedium. The product of oxidation is the corresponding thiophenol. The rate data of meta‐ and para‐substituted acids have been correlated well with σ_I, σ_R^o values and the meta‐compounds correlate well with F,R values. The reaction constants are negative and of smaller magnitudes. Further, the ortho‐substituted acids show a good correlation with triparametric equation involving Taft's σ_I and σ_R^o and charton's steric parameter v. There is no considerable steric contribution to the total orthosubstituent effect. Based on these observations, the mechanism involving the formation of protonated arylsulfinylacetic acid intermediate, followed by an intramolecular rearrangement leading to the product thiophenol has been proposed. © 1999 John Wiley & Sons, Inc. Int J Chem Kinet 31: 683–688, 1999     

Slowing-down of positronium: analysis of the age–momentum correlation

The problem of deconvoluting measurements of the slowing-down of positronium by means of the age–momentum correlation technique based on the Doppler broadening of the annihilation-photon line is reduced to the solution of systems of linear equations. The solution gives directly the kinetic energy of positronium as function of the positronium age (=time passed since its formation). A novel time-resolution function consisting of one Gaussian times an arbitrary number of Hermite polynomials is proposed.     

Networkmetrics: multivariate big data analysis in the context of the internet

Multivariate problems are found in all areas of knowledge. In chemistry and related disciplines, the chemometric community was developed in a joint effort to understand and solve problems mainly from a multivariate and exploratory perspective. This perspective is, indeed, of broader applicability, even in areas of knowledge far from chemistry. In this paper, we focus on the Internet: the net of devices that allow an interconnected world where all types of data can be shared and unprecedented communication services can be provided. Problems in the Internet or in general in networking are not very different from chemometric problems. Building on this parallelism, we review four classes of problems in networking: estimation, anomaly detection, optimization, and classification. We present an illustrative set of problems and show how a multivariate perspective may lead to significant improvements from state‐of‐the‐art techniques. In the absence of a better name, we call the approach of treating these problems from that multivariate perspective networkmetrics. Networkmetric problems have their own specificities, mainly, their typical Big Data nature and the presence of unstructured data. We argue that multivariate analysis is, indeed, useful to tackle these specificities. Copyright © 2016 John Wiley & Sons, Ltd.     

Discriminating five Polygonatum medical materials and monitoring their chemical changes associated with traditional process by FT-IR spectroscopy coupled with multivariate analysis

Several Polygonatum species are important medicinal materials as tonic to cure disorders in China. Because of their different medical effects, it is desired to distinguish them at species level. In addition, to ensure and control their medical quality, it is also important to monitor their chemical changes associated with traditional process. Taking the advantages of Fourier transform infrared spectroscopy (FT-IR) and multivariate analysis, we developed a convenient, fast and reliable approach to discriminate and quality control these materials. Despite similar absorption patterns, each species also presented spectral differences, especially on the FT-IR fingerprint range of 1800-600 cm⁻¹. Second derivative method obviously enlarged those differences and then showed more species-specific features. These spectral differences could be used as powerful discriminating points to distinguish them. PCA results showed that each species separated clearly with their biological replicates grouped together, which indicated that the variance between species is greater than within species, therefore, these species could be distinguishable. Using this approach, the five herbal materials were discriminated successfully in their raw, processed and ethanol extracted formats. On the other hand, visual inspecting infrared spectra of samples from 1 to 9 process steps, absorbance near 1737, 1259, 817 and 780 cm^-1 increased gradually but decreased gradually at 927 cm⁻¹. Besides, spectral contour near 1050 cm⁻¹ changed sharply with process treatment. These spectral changes indicated that hydrolyzing polysaccharides into oligo- and mono-saccharides, especially glucose and fructose, are the main chemical changes associated with traditional process. This is consistent with the traditional experience that the processed materials are dark as night and sweet as malt sugar. Meanwhile, our results also indicated that their chemical constituents changed profoundly after process, which might be the chemical basis for raw and processed materials have different medical effects. Based on absorbance at 817 and 780 cm⁻¹ and the color, taste, smell of processed materials followed by energy efficacy, raw materials had to be processed more than 21 h to ensure their quality. This research shows the potential of FT-IR spectroscopy coupled with multivariate analysis to discriminate different herbs and to monitor chemical changes with process and then control their quality. This could be very helpful to ensure the quality, safety, and efficacy of herbs on clinical practices.     

Melting-point purity determinations: Limitations as evidenced by calorimetric studies in the melting region

Typical melting curves, chosen from the results of more than 125 melting-point studies, are presented to illustrate both the reliability and the inherent limitations of the calorimetric method of purity determination. It is shown that this method usually is one of the best means of accurately determining small concentrations of impurity. However, analysis of anomalous melting curves leads to the conclusion that pseudo-equilibrium curves are often obtained as a result of inhomogeneous distribution of impurity in the liquid phase or of non-equilibrium distribution of impurity between the solid and liquid phases. Evidence is given to support the contention that solidsolutions were formed in as many as half of the samples studied and that for this reason, impurity values calculated for perhaps $\text{1}\text{3}$ of the samples are in error by 200% or more. Although these large uncertainties in impurity values usually correspond to less than 0.1 % uncertainty in purity values, modified procedures are proposed to minimize such errors.     

‘Total fluorine’ analysis of seed of Australian Gastrolobium spp. showing temporal, spatial and morphological variation

Alkali-fusion in conjunction with a fluoride selective electrode were used to quantify ‘total fluorine’, being organic fluorine + inorganic fluoride, for the seed of 13 species of Gastrolobium from south-west Western Australia. Intact seed covering spatial and temporal distributions, as well as G. bilobum, G. calycinum and G. parviflorum seed dissected into cotyledons and testa + aril, were analysed. Analysis found significant intra-and inter-species variation, both temporally and spatially, with intact seed concentrations ranging from 1.6 ± 0.3 mg kg⁻¹ in G. spinosum from Mundaring to 1063.9 ± 77.8 mg kg⁻¹ for G. cuneatum from Torbay. Approximately 87% of the ‘total fluorine’ was found to be in the seed cotyledons. Additional analysis detected little inorganic fluoride, indicating the majority of fluorine in the seed is organically bound. Parent compound(s) of the fluorine, seed toxicity and the implications of the results for seed chemical defense are discussed.     

Use of a tree‐structured hierarchical model for estimation of location and uncertainty in multivariate spatial data

Analysis and modeling of spatial data are of considerable interest in many applications. However, the prediction of geographical features from a set of chemical measurements on a set of geographically distinct samples has never been explored. We report a new, tree‐structured hierarchical model for the estimation of geographical location of spatially distributed samples from their chemical measurements. The tree‐structured hierarchical modeling used in this study involves a set of geographic regions stored in a hierarchical tree structure, with each nonterminal node representing a classifier and each terminal node representing a regression model. Once the tree‐structured model is constructed, given a sample with only chemical measurements available, the predicted regional location of the sample is gradually restricted as it is passed through a series of classification steps. The geographic location of the sample can be predicted using a regression model within the terminal subregion. We show that the tree‐structured modeling approach provides reasonable estimates of geographical region and geographic location for surface water samples taken across the entire USA. Further, the location uncertainty, an estimate of a probability that a test sample could be located within a pre‐estimated, joint prediction interval that is much smaller than the terminal subregion, can also be assessed. Copyright © 2014 John Wiley & Sons, Ltd.     

Association of methanol and water in ionic liquids elucidated by infrared spectroscopy using two-dimensional correlation and multivariate curve resolution

Water and methanol associations in ionic liquids (ILs) have been studied by means of FTIR spectroscopy. Spectra at different concentrations of water or methanol in ILs were obtained by means of on-line dilution using a flow injection analysis system. Spectral features in the OH stretching region revealed that most of the water and methanol molecules tended to be isolated from each other and to interact with the anion of the IL via H bonding. By means of two-dimensional correlation spectroscopy, the formation of methanol and water dimers was also detected. Multivariate curve resolution was used to recover pure spectra and concentration profiles of the different species. Methanol dimers form at concentrations higher than 0.8% (w/w) in the three studied ILs, 1-ethyl-3-methylimidazolium tetrafluoroborate (emimBF4), 1-butyl-3-methylimidazolium tetrafluoroborate (bmimBF4), and 1-butyl-3-methylimidazolium hexafluorophosphate (bmimPF6). Self-association of water molecules takes place in emimBF4 and bmimBF4 at a molar ratio similar to that of methanol molecules; however, water dimers cannot be detected in bmimPF6, the most hydrophobic IL studied. No evidence was found that bigger water clusters are formed in these ILs at the studied cosolvent concentrations.     

Accounting for Poisson noise in the multivariate analysis of ToF‐SIMS spectrum images

Recent years have seen the introduction of many surface characterization instruments and other spectral imaging systems that are capable of generating data in truly prodigious quantities. The challenge faced by the analyst, then, is to extract the essential chemical information from this overwhelming volume of spectral data. Multivariate statistical techniques such as principal component analysis (PCA) and other forms of factor analysis promise to be among the most important and powerful tools for accomplishing this task. In order to benefit fully from multivariate methods, the nature of the noise specific to each measurement technique must be taken into account. For spectroscopic techniques that rely upon counting particles (photons, electrons, etc.), the observed noise is typically dominated by ‘counting statistics’ and is Poisson in nature. This implies that the absolute uncertainty in any given data point is not constant, rather, it increases with the number of counts represented by that point. Performing PCA, for instance, directly on the raw data leads to less than satisfactory results in such cases. This paper will present a simple method for weighting the data to account for Poisson noise. Using a simple time‐of‐flight secondary ion mass spectrometry spectrum image as an example, it will be demonstrated that PCA, when applied to the weighted data, leads to results that are more interpretable, provide greater noise rejection and are more robust than standard PCA. The weighting presented here is also shown to be an optimal approach to scaling data as a pretreatment prior to multivariate statistical analysis. Published in 2004 by John Wiley & Sons, Ltd.     

Two-dimensional correlation spectroscopy and multivariate curve resolution for the study of lipid oxidation in edible oils monitored by FTIR and FT-Raman spectroscopy

Accelerate oxidative degradation of six vegetable oils was monitored using FTIR and FT-Raman spectroscopy. Two-dimensional correlation spectroscopy and multivariate curve resolution alternating least squares (MCR-ALS) were applied to the analysis of the data. The use of hetero-spectral two-dimensional correlation of FTIR and FT-Raman data allowed the use of well established band assignments to interpret less clearly assigned spectral features. With a moving window approach it was possible to obtain simplified two-dimensional correlation maps and to detect compounds evolving with different kinetic. Simultaneous analysis of the oxidation experiments of the six different oils monitored by both spectroscopic techniques was performed using MCR-ALS. Although a complete resolution of the data was not possible, the spectral changes occurring during the oxidative degradation of the oils were described with a five-component model. The two fundamentally different chemometric approaches lead to coincident results.     

Isoelectric focusing in immobilized pH gradients: applications in clinical chemistry and forensic analysis

The applications of isoelectric focusing in immobilized pH gradients in clinical chemistry and forensic analysis are reviewed. Strong emphasis is given to the separation of serum proteins, in particular alpha 1-acidic glycoprotein, acid phosphatase, alkaline phosphatase, alpha 1-antitrypsin, apolipoproteins, complement component, factor B, factor XIIIB, group-specific component, lecithin:cholesterol acyltransferase, phosphoglucomutase, prealbumin, protein C and transferrin. The analysis of human parotid salivary proteins is discussed and an assessment is given of the state of the art in thalassaemia screening.