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This study deals with the identification of the factors that affect pyrite oxidation in acid mine drainage conditions. For this scope, weathering experiments have been carried at laboratory scale based on the design of experiments methodology to evaluate the effect of factors such as major ion concentrations, crystal size, and humic acids presence over the amount of elemental sulfur produced due to the involved weathering reactions. In particular, metal and anionic concentrations in solution were quantified by inductively coupled plasma-atomic emission spectroscopy and ion-chromatography techniques, respectively, whereas the amount of elemental sulfur was quantified with a high-performance liquid chromatography with diode-array detection technique after proper extraction procedure. A partial least squares regression was calculated to establish a quantitative relationship between the considered factors and the amount of elemental sulfur. After evaluation of the model, ferric iron, crystal size and the presence of humic acids were identified as the relevant factors for pyrite oxidation under acidic conditions. In addition, the surface of the samples was characterized by Raman imaging spectroscopy and subsequently analyzed by explorative hyperspectral analysis methods to assess the spatial distribution of the elemental sulfur as the main weathering product, resulting in a homogenous distribution.

This study aims the characterization of several tianeptine transformation products in ultrapure water by simulated sunlight irradiation. Tianeptine was completely degraded after 106 h of exposition following pseudo-first-order kinetics (half-life time = 12.0 ± 2.4 h). Furthermore, an ultra-high-performance liquid chromatography coupled with a high-resolution quadrupole time-of-flight-mass spectrometry method was developed and fully validated taking into account different method performance parameters for the quantification of tianeptine in river water up to a concentration of 400 pg L−1. Following a non-targeted approach based on mass data-independent acquisition, eight different transformation products not previously reported in the literature were identified and accordingly elucidated, proposing a photodegradation mechanism based on the accurate tandem mass spectrometry information acquired. Irradiation experiments were replicated for a tianeptine solution prepared in a blank river water sample, resulting in the formation of the same transformation products and similar degradation kinetics. In addition, a toxicity assessment of the photoproducts was performed by in silico method, being generally all TPs of comparable toxicity to the precursor except for TP1, and showing a similar persistence in the environment except for TP2 and TP6, while TP4 was the only TP predicted as mutagenic. The developed method was applied for the analysis of four river water samples.

The objective of this work was to study and develop a new kind of hamburger including meat, fish, and vegetables. After completion of this chapter the reader should be able to know how to develop a new product with statistical analysis, experimental design, and sensory analysis.

In the last decade, kesterite (Cu2ZnSnS4 – CZTS) thin films have been widely studied for photovoltaics (PV), due to their similarity to the well-known and well-performing Cu(In,Ga)Se2 (CIGS). Its high absorption coefficient (> 104 cm-1), its high stability and a tuneable direct band gap of 1.45 - 1.50 eV, promote kesterite as an ideal candidate for non-toxic, cheap, earth-abundant photovoltaic thin-film absorber. Here we present our study on the properties and the possible use of CZTS in the form of nanoparticles (NPs) based on a straightforward hot-injection synthesis in an oxygen-free environment, starting from metal acetates and elemental sulphur in oleylamine. The impact of different injection temperatures on the crystalline size, crystal structure and formation of undesired secondary phases was investigated, along with a procedure to get rid of them. The resulting NPs were fully characterised by Raman spectroscopy, X-ray diffraction, energy-dispersive X-ray spectroscopy, transmission electron microscopy, and scanning electron microscopy. Additionally, the presence and removal of both organic traces and detrimental phases were confirmed by thermogravimetric analysis and FTIR-ATR analysis. Our CZTS NPs were tested as potential inorganic hole transport material (HTM) to achieve costeffectiveness, long-term operational stability and sustainability goals in perovskite solar cells (PSCs), especially if compared to the organic, expensive, not-sustainable but conventionally-used HTMs in PSCs (i.e. PTAA, 2PACz, PEDOT:PSS). The hole mobility and charge transport properties were investigated in plane and out of plane, to ensure the feasibility of the material to act as HTM. The resulting HTM film was used in p-i-n architecture with [CH3NH3]PbI3 and compared to an organic-HTM-containing reference device. Under optimised conditions, the PSCs with CZTS NPs HTM remained stable, with PV performance improving by up to 80% of the initial value over time. Parallelly, the photo

Dangerous emerging water micropollutants like Diclofenac are harming ecosystems all over the planet, and immediate action is needed. The large bandgap photocatalysts conventionally used to degrade them need to be more efficient. Cu2ZnSnS4, a well-known light absorber in photovoltaics with a bandgap of 1.5 eV, can efficiently harvest an abundant portion of the solar spectrum. However, its photocatalytic activity has so far only been reported in relation to the degradation of organic dyes, and it is usually used as a benchmark to assess the activity of a photocatalyst without testing its actual potential on a hazardous water micropollutant conventionally encountered in primary and secondary waters. Here, we report the promising photocatalytic activity of Cu2ZnSnS4 nanoparticles in the degradation of Diclofenac, chosen as a benchmark for dangerous emerging water micropollutants.

Aroma determination in alcoholic beverages has become a hot research topic due to the ongoing effort to obtain quality products, especially in a globalized market. Consumer satisfaction is mainly achieved by balancing several aroma compounds, which are mixtures of numerous volatile molecules enclosed in challenging matrices. Thus, sample preparation strategies for quality control and product development are required. They involve several steps including copious amounts of hazardous solvents or time-consuming procedures. This is bucking the trend of the ever-increasing pressure to reduce the environmental impact of analytical chemistry processes. Hence, the evolution of sample preparation procedures has directed towards miniaturized techniques to decrease or avoid the use of hazardous solvents and integrating sampling, extraction, and enrichment of the targeted analytes in fewer steps. Mass spectrometry coupled to gas or liquid chromatography is particularly well suited to address the complexity of these matrices. This review surveys advancements of green miniaturized techniques coupled to mass spectrometry applied on all categories of odor-active molecules in the most consumed alcoholic beverages: beer, wine, and spirits. The targeted literature consider progresses over the past 20 years.

Orchids are experiencing wide success in ornamental, medicinal, and food fields. The reason for their success is correlated with both their morphology and metabolomics, the latter linked to their taste and biological effects. Despite many orchids having already been the subject of chemotaxonomic works, some of them are still untapped, like the case of Orchis purpurea. O. purpurea is one of the most common species of the genus Orchis, present in hedgerows, verges, and light woodland, where it is one of the few herbaceous plants able to be unpleasant to herbivorous animals. Essential oil from roots, stems, leaves, and flowers were analyzed via GC/MS analyses, revealing the presence of 70 compounds, with a clear prevalence of coumarin. The high concentration of this metabolite may explain the resistance of O. purpurea to herbivores, being associated with appetite-suppressing properties and a bitter taste. Non-volatile fractions were analyzed via UHPLC-MS analysis revealing the presence of hydroxycinnamic acid derivatives, polyphenols, and glycosidic compounds, probably responsible for their color and fragrance. Taken together, the herein presented results shed light on both the defensive strategy and the chemotaxonomy of O. purpurea.

In the original publication [1], there was a mistake in Figure 5 as published. CD3OD was written in place of HDO near the peak at about 4.8 ppm on the 1H NMR spectrum of 4-HBA. The corrected Figure 5 appears below. Figure 6 was published with horizontal orientation instead of vertical one. The graph has also been corrected in the original publication. In Figure S3 of the Supplementary Materials, CD3OD was written in place of HDO near the peak at about 4.8 ppm on the 1H NMR spectrum of catechinic acid (CA). The corrected Figure S3 appears below. There were some language/expression issues in original publication. Excessive information or personal comments not necessary to understand the reported study were included in the original publication. A correction has been made to Abstract (Page 1): The findings seemed not to be reliable because of the existence in the literature of very different findings, because of the high concentration that was attributed to the supposed 4-HBA in the dark mixture, and because of the absence of essential analytical experiments to confirm 4-HBA in AOCA. Particularly, the AOCA chromatograms highlighting a peak attributable to 4-HBA, using commercial 4-HBA as a standard, is missing, as well as investigations concerning the antiviral activity of marketed 4-HBA. A correction has been made to Introduction, Paragraph 4 (Page 2): In a recent study, the main constituent (75%) of AOCA was isolated and named compound 2 [8]. It was identified as the colorless and well-known 4-hydroxy benzoic acid (4-HBA), and it was reported to be responsible for the antiviral activity of AOCA, as 2 had been found to be active on tomato brown rugose fruit virus (ToBRFV). This finding turned out to be very different from what was already widely reported in several specific articles [9–13]. In this regard, the structural identity recently attributed to 2 was validated, since 4-HBA is commonly produced by the thermolytic degradation of some flavonoids [14,15]. However

The chemometric philosophy is based on some well-defined and shared principles: multivariate analysis of the problem, searching for the relevant information of data, model validation to produce predictive models, definition of the model applicability domain for reliable predictions and graphical visualization of the relevant information. The verification of food authenticity is fundamentally a classification problem; indeed, samples are labeled according to their authenticity status, that is, authentic or non-authentic. Chemometric methods are usually applied to data that are collected in a numerical table. Chemometric methods usually require a pre-treatment of the raw data in order to be able to extract useful and non-trivial information and discard obvious (i.e., intrinsic in the single variable) and useless information. Soft independent modeling of class analogy is one of the most popular class modeling approaches. Artificial Neural Networks are currently considered among the most important emerging tools in chemometrics.

In this study, we propose a new approach based on Raman hyperspectral imaging and chemometrics for the analysis of chemically heterogeneous surfaces of weathered minerals. A pyrite sample showing a heterogeneous surface with different alteration products, is used to test the validity of the technique. Principal Component Analysis (PCA) was initially used to evaluate data structure and identify Raman phases and vibrational modes related to minor and major weathering features. Afterwards, Multivariate Curve Resolution-alternating least squares (MCR-ALS) was carried out to identify the specific chemical components of the major weathering phases. Finally, for the analysis of the minor weathering phases, K-means clustering was carried out to identify groups of similar pixels of low percentage of variance in the image. Three major components are found in the analyzed sample, corresponding to pyrite and hematite vibrational modes, as well as features of an amorphous alteration product patina. Four additional spectral signatures revealing the presence of sulfates were found after the analysis of minor components. The proposed method enables a semi-quantitative threshold-based characterization of chemical features and provides a visual representation of the phase distribution on the surface of the sample.

According to the 2021 World Drug Report, around 275 million people use drugs of abuse, and 36 million people suffer from addiction, fostering a thriving market for illicit substances. In Italy, 30,083 people were reported to the Judicial Authority for offenses in violation of the Italian Law D.P.R. 309/1990. These offences are sentenced after a qualitative–quantitative analysis of seized materials. Given the large quantity of seized drugs and the need to perform accurate analytical determinations, Italian forensic laboratories struggle to complete analyses in a short time, delaying the entire reporting process needed to achieve sentencing. For this purpose, an UHPLC-MS/MS-based platform was developed at the University of Milano-Bicocca to support law-enforcement authorities. Software was designed to easily manage street seizure acquisition, documentation registration, and sampling. A sensitive UHPLC-MS/MS method was fully validated for the quantification of the traditional illicit substances (cocaine, heroin, 6-MAM, morphine, amphetamine, methamphetamine, MDMA, ketamine, GHB, GBL, LSD, trans-∆9-THC, and THCA) at the ppb level. The final report is relayed to the Prefecture in 3–4 days, even within 24 h for urgent requests. The platform allows for semi-automatic data handling to minimize erroneous results for an accurate report generation by standardized procedures.

Membrane introduction mass spectrometry (MIMS) is a direct mass spectrometry technique used to monitor online chemical systems or quickly quantify trace levels of different groups of compounds in complex matrices without extensive sample preparation steps and chromatographic separation. MIMS utilizes a thin, semi-permeable, and selective membrane that directly connects the sample and the mass spectrometer. The analytes in the sample are pre-concentrated by the membrane depending on their physicochemical properties and directly transferred, using different acceptor phases (gas, liquid or vacuum) to the mass spectrometer. Condensed phase (CP) MIMS use a liquid as a medium, extending the range to new applications to less-volatile compounds that are challenging or unsuitable to gas-phase MIMS. It directly allows the rapid quantification of selected compounds in complex matrices, the online monitoring of chemical reactions (in real-time), as well as in situ measurements. CP-MIMS has expanded beyond the measurement of several organic compounds because of the use of different types of liquid acceptor phases, geometries, dimensions, and mass spectrometers. This review surveys advancements of CP-MIMS and its applications to several molecules and matrices over the past 15 years.

The reduction of chemical inputs due to fertilizer and pesticide applications is a target shared both by farmers and consumers in order to minimize the side effects for human and environmental health. Among the possible strategies, the use of biostimulants has become increasingly important as demonstrated by the fast growth of their global market and by the increased rate of registration of new products. In this work, we assessed the effects of five bacterial strains (Pseu-domonas fluorescens Pf4, P. putida S1Pf1, P. protegens Pf7, P. migulae 8R6, and Pseudomonas sp. 5Vm1K), which were chosen according to their previously reported plant growth promotion traits and their positive effects on fruit/seed nutrient contents, on a local onion cultivar and on zucchini. The possible variations induced by the inoculation with the bacterial strains on the onion nutritional components were also evaluated. Inoculation resulted in significant growth stimulation and improvement of the mineral concentration of the onion bulb, induced particularly by 5Vm1K and S1Pf1, and in different effects on the flowering of the zucchini plants according to the bacterial strain. The present study provides new information regarding the activity of the five plant growth-promoting bacteria (PGPB) strains on onion and zucchini, two plant species rarely considered by the scientific literature despite their economic relevance.

The Fenton process activated by Zero Valent Iron (ZVI-Fenton) is shown here to effectively remove antibiotics reserved for hospital settings (specifically used to treat antibiotic-resistant infections) from wastewater, thereby helping in the fight against bacterial resistance. Effective degradation of cefazolin, imipenem and vancomycin in real urban wastewater was achieved at pH 5, which is quite near neutrality when compared with classic Fenton that works effectively at pH 3–4. The possibility to operate successfully at pH 5 has several advantages compared to operation at lower pH values: (i) lower reagent costs for pH adjustment; (ii) insignificant impact on wastewater conductivity, because lesser acid is required to acidify and lesser or no base for neutralization; (iii) undetectable release of dissolved Fe, which could otherwise be an issue for wastewater quality. The cost of reagents for the treatment ranges between 0.04 and 0.07 $ m−3, which looks very suitable for practical applications. The structures of the degradation intermediates of the studied antibiotics and their likely abundance suggest that, once the primary compound is eliminated, most of the potential to trigger antibiotic action has been removed. Application of the ZVI-Fenton technique to wastewater treatment could considerably lower the possibility for antibiotics to trigger the development of resistance in bacteria.

Antineoplastic drugs are a wide and heterogeneous group of substances that, as universally known, can cause highly severe toxic effects to whoever is exposed. From an occupational safety point of view, surface contaminations inside preparation and administration units are a growing issue and therefore require the development and implementation of sensible and fast monitoring methods. The unlikelihood of a unique all-embracing chromatography, able to correctly retain and separate each analyte led to the need to create an orthogonal normal phase analysis, which might be able to fill the gaps in the more common reversed-phase ones. An existing hydrophilic interaction method has thus been expanded to 6 other drugs and applied to real samples after an evaluation of its performances. The experimental data were then used to evaluate the possibility of estimating reliable relationships between the chromatographic retention and the chemical-structural features of the drugs under analysis.

Mass spectrometry (MS) is widely used for the identification of chemical compounds by matching the experimentally acquired mass spectrum against a database of reference spectra. However, this approach suffers from a limited coverage of the existing databases causing a failure in the identification of a compound not present in the database. Among the computational approaches for mining metabolite structures based on MS data, one option is to predict molecular fingerprints from the mass spectra by means of chemometric strategies and then use them to screen compound libraries. This can be carried out by calibrating multi-task artificial neural networks from large datasets of mass spectra, used as inputs, and molecular fingerprints as outputs. In this study, we prepared a large LC-MS/MS dataset from an on-line open repository. These data were used to train and evaluate deep-learning-based approaches to predict molecular fingerprints and retrieve the structure of unknown compounds from their LC-MS/MS spectra. Effects of data sparseness and the impact of different strategies of data curing and dimensionality reduction on the output accuracy have been evaluated. Moreover, extensive diagnostics have been carried out to evaluate modelling advantages and drawbacks as a function of the explored chemical space.

The dark brown mixture resulting from the autooxidation of catechinic acid (CA) (AOCA) has been reported to possess antiviral activity against Herpes Simplex Virus 1 and 2 (HSV-1 and HSV-2). Unfortunately, the constituents of AOCA were not separated or identified and the compound(s) responsible for AOCA’s antiviral activity remained unknown until recently. Colorless 4-hydroxy benzoic acid (4-HBA) has been reported as the main constituent (75%) of AOCA, and as being responsible for its antiviral activity. The findings seem not to be reliable because of the existence in the literature of very different findings, the high concentration that was attributed to the supposed 4-HBA in the dark mixture, and the insufficient or inaccurately interpreted analytical experiments reported in the study identifying 4-HBA in AOCA. Of particular concern is the lack of AOCA chromatograms highlighting a peak attributable to 4-HBA, using commercial 4-HBA as a standard, and investigations concerning the antiviral activity of marketed 4-HBA. Therefore, in this study, to verify the exactness of the recent reports, we prepared CA from catechin and AOCA from CA, and the absence of 4-HBA in the mixture was first established by thin-layer chromatography (TLC), and then was confirmed by UHPLC–MS/MS, UV–Vis, and ATR–FTIR analyses. For further confirmation, the ATR–FTIR spectral data were processed by principal components analysis (PCA), which unequivocally established strong structural differences between 4-HBA and AOCA. Finally, while the antiviral effects of AOCA against HSV-2 were confirmed, a commercial sample of 4-HBA was completely inactive.

The study concerns the photodegradation of the antidepressant escitalopram (ESC), the S-enantiomer of the citalopram raceme, both in ultrapure and surface water, considering the contribution of indirect photolysis through the presence of nitrate and bicarbonate. The effect of nitrate and bicarbonate concentrations was investigated by full factorial design, and only the nitrate concentration resulted in having a significant effect on the degradation. The kinetics of ESC photodegradation is the pseudo-first-order (half-life = 62.4 h in ultrapure water and 48.4 h in lake water). The generation of transformation products (TPs) was monitored through a developed and validated HPLC-MS/MS method. Fourteen TPs were identified in ultrapure water (one of them, at m/z 261, for the first time) and other two TPs at m/z 327 (found for the first time in this study) were identified only in presence of a nitrate. Several TPs were the same as those formed during the photodegradation of citalopram. The photodegradation pathway of ESC and its mechanism of degradation in water is proposed. The method was applied successfully to the analyses of surface water samples, in which a few dozen of ng L−1 of ESC was determined together with the presence of TP2, TP5 and TP12. Finally, a preliminary in silico evaluation of the toxicological profile and environmental behavior of TPs by computational models was carried out; two TPs (TP4 and TP10) were identified as of potential concern, as they were predicted mutagenic by Ames test model.

Bitter pit (BP) is one of the most relevant post-harvest disorders for apple industry worldwide, which is often related to calcium (Ca) deficiency at the calyx end of the fruit. Its occurrence takes place along with an imbalance with other minerals, such as potassium (K). Although the K/Ca ratio is considered a valuable indicator of BP, a high variability in the levels of these elements occurs within the fruit, between fruits of the same plant, and between plants and orchards. Prediction systems based on the content of elements in fruit have a high variability because they are determined in samples composed of various fruits. With X-ray fluorescence (XRF) spectrometry, it is possible to characterize non-destructively the signal intensity for several mineral elements at a given position in individual fruit and thus, the complete signal of the mineral composition can be used to perform a predictive model to determine the incidence of bitter pit. Therefore, it was hypothesized that using a multivariate modeling approach, other elements beyond the K and Ca could be found that could improve the current clutter prediction capability. Two studies were carried out: on the first one an experiment was conducted to determine the K/Ca and the whole spectrum using XRF of a balanced sample of affected and non-affected ‘Granny Smith’ apples. On the second study apples of three cultivars (‘Granny Smith’, ‘Brookfield’ and ‘Fuji’), were harvested from two commercial orchards to evaluate the use of XRF to predict BP. With data from the first study a multivariate classification system was trained (balanced database of healthy and BP fruit, consisting in 176 from each group) and then the model was applied on the second study to fruit from two orchards with a history of BP. Results show that when dimensionality reduction was performed on the XRF spectra (1.5 - 8 KeV) of ‘Granny Smith’ apples, comparing fruit with and without BP, along with K and Ca, four other elements (i.e., Cl, Si, P

Orchil is a purple dye extracted from lichens, widely used since the 6th century for dyeing parchments, yarns and textiles, in particular as a substitute for the rare and expensive Tyrian Purple dye; additionally, it was used as a colourant in illuminated manuscripts. The dye was produced since antiquity, through a slow process which could take three weeks or more, by soaking lichens in ammonia in order to promote the transformation of the chemical precursors into a mixture of phenoxazonic compounds, collectively known as orceins. Orchil can be obtained from different lichen species, which are native to specific regions or geographical areas. Since each species can have a typical set of chemical precursors, the final set of orceins could be characteristic of the relative species, even if the macroscopic features of the dye would be similar in terms of hue and spectral responses upon analysis. In this work, a preliminary study is carried out in order to try to identify a diagnostic pattern of three common lichen species (Lasallia pustulata, Ochrolechia tartarea, Roccella tinctoria) by means of HPLC-MS/MS analysis, so as to develop a tool useful to identify the origin of real samples dyed with orchil, among which are featured textiles and purple parchments from ancient manuscripts. Such identification may be exploited in order to assess the relationship between an artwork and the geographical origin of its raw materials.

Neural networks are rapidly gaining popularity in chemical modeling and Quantitative Structure–Activity Relationship (QSAR) thanks to their ability to handle multitask problems. However, outcomes of neural networks depend on the tuning of several hyperparameters, whose small variations can often strongly affect their performance. Hence, optimization is a fundamental step in training neural networks although, in many cases, it can be very expensive from a computational point of view. In this study, we compared four of the most widely used approaches for tuning hyperparameters, namely, grid search, random search, tree-structured Parzen estimator, and genetic algorithms on three multitask QSAR datasets. We mainly focused on parsimonious optimization and thus not only on the performance of neural networks, but also the computational time that was taken into account. Furthermore, since the optimization approaches do not directly provide information about the influence of hyperparameters, we applied experimental design strategies to determine their effects on the neural network performance. We found that genetic algorithms, tree-structured Parzen estimator, and random search require on average 0.08% of the hours required by grid search; in addition, tree-structured Parzen estimator and genetic algorithms provide better results than random search.

Multivariate regression is a fundamental supervised chemometric approach that defines the relationship between a set of independent variables and a quantitative response. It enables the subsequent prediction of the response for future samples, thus avoiding its experimental measurement. Regression approaches have been widely applied for data analysis in different scientific fields. In this paper, we describe the regression toolbox for MATLAB, which is a collection of modules for calculating some well-known regression methods: Ordinary Least Squares (OLS), Partial Least Squares (PLS), Principal Component Regression (PCR), Ridge and local regression based on sample similarities, such as Binned Nearest Neighbours (BNN) and k-Nearest Neighbours (kNN) regression methods. Moreover, the toolbox includes modules to couple regression approaches with supervised variable selection based on All Subset models, Forward Selection, Genetic Algorithms and Reshaped Sequential Replacement. The toolbox is freely available at the Milano Chemometrics and QSAR Research Group website and provides a graphical user interface (GUI), which allows the calculation in a user-friendly graphical environment.

Irinotecan (CPT-11) is a water-soluble anticancer drug widely used to treat several types of cancer. Even if the metabolites of CPT-11 are well-known and investigated, only limited information is available in the literature about the formation of photo-degradation products that can naturally originate from sunlight irradiation when the drug is released in aqueous systems. CTP-11 solutions at 10.0 mg L-1 were irradiated by simulated sunlight. The intensity of the drug decreased by 90% after 7.5 days of irradiation and no significant reduction of absorbance values was observed after 13 days. A sensitive UHPLC-MS/MS method was developed employing a hybrid triple quadrupole/linear ion trap mass spectrometer, that is able to work in data-dependent acquisition mode and to obtain information about the compounds formed during the photoirradiation. Moreover, a selected reaction monitoring method was built using the MS/MS fragmentation pattern of the compounds previously investigated. The method was validated considering LOD, LOQ, linearity, precision, selectivity, recovery and matrix effect. LOD and LOQ values were 0.02 and 0.05 ng mL-1, respectively, whereas MDL and MQL values in real water samples (river water, groundwater, well water, and wastewater) were lower than 0.05 and 0.2 ng mL-1, respectively. Eight photodegradation products were identified, among which five for the first time. Based on the MS and MS/MS fragmentation, the chemical structures of the degradation products were proposed. Hydrolysis experiments were carried out on the same solutions preserved in the dark, but no formation of other species was highlighted. The method was applied to several real samples: CPT-11 was detected and quantified only in a hospital effluent sample at the concentration of 0.41 ± 0.2 ng mL-1 together with the occurrence of PDP3. The outcomes of this study may be useful for updating the pollutant screening in water samples

Oleander is a spontaneous shrub widely occurring in Mediterranean regions. Poisoning is sporadically reported in livestock, mainly due to the ingestion of leaves containing toxic cardiac glycosides (primarily oleandrin). In this study, 50 lactating Fleckvieh cows were affected after being offered a diet containing dry oleander pruning wastes accidentally mixed with fodder. Clinical examination, electrocardiogram, and blood sampling were conducted. Dead animals were necropsied, and heart, liver, kidney, spleen, and intestine were submitted to histological investigation. Oleandrin detection was performed through ultra-high performance liquid chromatography-tandem mass spectrometry in blood, serum, liver, heart, milk, and cheese samples. Severe depression, anorexia, ruminal atony, diarrhea, serous nasal discharge, tachycardia, and irregular heartbeat were the most common clinical signs. The first animal died within 48 h, and a total of 13 cows died in 4 days. Disseminated hyperemia and hemorrhages, multifocal coagulative necrosis of the cardiac muscle fibers, and severe and diffuse enteritis were suggestive of oleander poisoning. The diagnosis was confirmed by the presence of oleandrin in serum, liver, heart, milk, and cheese. Our results confirm the high toxicity of oleander in cattle and report for the first time the transfer into milk and dairy products, suggesting a potential risk for the consumers.

Background: Based on the medical history and laboratory analytical tests, a patient presenting symptoms compatible with Chronic Fatigue Syndrome was suspected of metal intoxication; therefore, a chelating therapy was attempted. In parallel, the profile of elemental excretion in urine was determined. Methods: Chelation therapy by CaNa2EDTA was administered every two weeks and urine samples were routinely collected for 17 months. The samples were mineralized with HNO3 69 % and analyzed by Inductively-Coupled Plasma – Mass Spectrometry. Data were processed by multivariate statistical methods. Results: Most of the toxic elements showed a peak of excretion in 12−24 h after EDTA administration, which returned to basal level by 24−36 h after the treatment. Yet, the excretion of some trace elements persisted in the urine collected 26 h after the treatment. Conclusions: The analysis of excreted metals following the CaNa2EDTA infusion allowed to monitor dynamically the chelation therapy. The chelation therapy was effective in mobilizing and eliminating the principal heavy metals present from the body. However, since such clearance almost vanished 24 h after the treatment, a protocol with more frequent and low-dose administrations is advisable to improve the metal excretion.

The thienopyrimidine TP053 is an antitubercular prodrug active against both replicating and nonreplicating Mycobacterium tuberculosis (M. tuberculosis) cells, which requires activation by the mycothiol-dependent nitroreductase Mrx2. The investigation of the mechanism of action of TP053 revealed that Mrx2 releases nitric oxide from this drug both in the enzyme assays with purified Mrx2 and in mycobacterial cultures, which can explain its activity against nonreplicating bacilli, similar to pretomanid activated by the nitroreductase Ddn. In addition, we identified a highly reactive metabolite, 2-(4-mercapto-6-(methylamino)-2-phenylpyrimidin-5-yl)ethan-1-ol, which can contribute to the antimycobacterial effects on replicating cells as well as on nonreplicating cells. In summary, we explain the mechanism of action of TP053 on both replicating and nonreplicating M. tuberculosis and report a novel activity for Mrx2, which in addition to Ddn, represents another example of nitroreductase releasing nitric oxide from its substrate. These findings are particularly relevant in the context of drugs targeting nonreplicating M. tuberculosis, which is shown to be killed by increased levels of nitric oxide.