Multimodality Imaging in Advanced Heart Failure for Diagnosis, Management and Follow-Up: A Comprehensive Review.

Advanced heart failure (AHF) presents a complex landscape with challenges spanning diagnosis, management, and patient outcomes. In response, the integration of multimodality imaging techniques has emerged as a pivotal approach. This comprehensive review delves into the profound significance of these imaging strategies within AHF scenarios. Multimodality imaging, encompassing echocardiography, cardiac magnetic resonance imaging (CMR), nuclear imaging and cardiac computed tomography (CCT), stands as a cornerstone in the care of patients with both short- and long-term mechanical support devices. These techniques facilitate precise device selection, placement, and vigilant monitoring, ensuring patient safety and optimal device functionality. In the context of orthotopic cardiac transplant (OTC), the role of multimodality imaging remains indispensable. Echocardiography offers invaluable insights into allograft function and potential complications. Advanced methods, like speckle tracking echocardiography (STE), empower the detection of acute cell rejection. Nuclear imaging, CMR and CCT further enhance diagnostic precision, especially concerning allograft rejection and cardiac allograft vasculopathy. This comprehensive imaging approach goes beyond diagnosis, shaping treatment strategies and risk assessment. By harmonizing diverse imaging modalities, clinicians gain a panoramic understanding of each patient's unique condition, facilitating well-informed decisions. The aim is to highlight the novelty and unique aspects of recently published papers in the field. Thus, this review underscores the irreplaceable role of multimodality imaging in elevating patient outcomes, refining treatment precision, and propelling advancements in the evolving landscape of advanced heart failure management.

Coronary artery calcium score: we know where we are but not where we may be.

Cardiac computed tomography angiography (CCTA) has emerged as a cost-effective and time-saving technique for excluding coronary artery disease. One valuable tool obtained by CCTA is the coronary artery calcium (CAC) score. The use of CAC scoring has shown promise in the risk assessment and stratification of cardiovascular disease. CAC scores can be complemented by plaque analysis to assess vulnerable plaque characteristics and further refine risk assessment. This paper aims to provide a comprehensive understanding of the value of the CAC as a prognostic tool and its implications for patient risk assessment, treatment strategies, and outcomes. CAC scoring has demonstrated superior ability in stratifying patients, especially asymptomatic individuals, compared to traditional risk factors and scoring systems. The main evidence suggests that individuals with a CAC score of 0 have a good long-term prognosis, while an elevated CAC score is associated with increased cardiovascular risk. Finally, the clinical power of CAC scoring and the development of new models for risk stratification could be enhanced by machine learning algorithms.

New Non-Invasive Imaging Technologies in Cardiac Transplant Follow-Up: Acquired Evidence and Future Options.

Heart transplantation (HT) is the established treatment for end-stage heart failure, significantly enhancing patients' survival and quality of life. To ensure optimal outcomes, the routine monitoring of HT recipients is paramount. While existing guidelines offer guidance on a blend of invasive and non-invasive imaging techniques, certain aspects such as the timing of echocardiographic assessments and the role of echocardiography or cardiac magnetic resonance (CMR) as alternatives to serial endomyocardial biopsies (EMBs) for rejection monitoring are not specifically outlined in the guidelines. Furthermore, invasive coronary angiography (ICA) is still recommended as the gold-standard procedure, usually performed one year after surgery and every two years thereafter. This review focuses on recent advancements in non-invasive and contrast-saving imaging techniques that have been investigated for HT patients. The aim of the manuscript is to identify imaging modalities that may potentially replace or reduce the need for invasive procedures such as ICA and EMB, considering their respective advantages and disadvantages. We emphasize the transformative potential of non-invasive techniques in elevating patient care. Advanced echocardiography techniques, including strain imaging and tissue Doppler imaging, offer enhanced insights into cardiac function, while CMR, through its multi-parametric mapping techniques, such as T1 and T2 mapping, allows for the non-invasive assessment of inflammation and tissue characterization. Cardiac computed tomography (CCT), particularly with its ability to evaluate coronary artery disease and assess graft vasculopathy, emerges as an integral tool in the follow-up of HT patients. Recent studies have highlighted the potential of nuclear myocardial perfusion imaging, including myocardial blood flow quantification, as a non-invasive method for diagnosing and prognosticating CAV. These advanced imaging approaches hold promise in mitigating the need for invasive procedures like ICA and EMB when evaluating the benefits and limitations of each modality.

The wild taxa utilized as vegetables in Sicily (Italy): a traditional component of the Mediterranean diet.

BACKGROUND: Wild vegetables in the Mediterranean Basin are still often consumed as a part of the diet and, in particular, there is a great tradition regarding their use in Sicily. In this study, an ethnobotanical field investigation was carried out to (a) identify the wild native taxa traditionally gathered and consumed as vegetables in Sicily, comparing the collected ethnobotanical data with those of other countries that have nominated the Mediterranean diet for inclusion in the UNESCO Representative List of the Intangible Cultural Heritage of Humanity and (b) highlight new culinary uses of these plants. METHODS: Interviews were carried out in 187 towns and villages in Sicily between 2005 and 2015. A total of 980 people over the age of 50 were interviewed (mainly farmers, shepherds, and experts on local traditions). Plants recorded were usually collected in collaboration with the informants to confirm the correct identification of the plants. The frequencies of citation were calculated. RESULTS: Two hundred fifty-three taxa (specific and intraspecific) belonging to 39 families, and 128 genera were recorded (26 were cited for the first time). The most represented families were Asteraceae, Brassicaceae, Apiaceae, Amaryllidaceae, Malvaceae, and Polygonaceae. Only 14 taxa were cited by 75% of the people interviewed. The aerial parts of wild plants, including leaves, tender shoots, and basal rosettes, are the main portions collected, while the subterranean parts are used to a lesser extent. For some vegetables, more parts are utilized. Most of the reported vegetables are consumed cooked. In addition to the widely known vegetables (Borago officinalis, Beta spp., Cichorium spp., Brassica spp., Carduus spp., etc.), the so-called ancient vegetables are included (Onopordum illyricum, Centaurea calcitrapa, Nasturtium officinale, Scolymus spp., Smyrnium rotundifolium), and some unique uses were described. Comparing the Sicilian findings to those from other countries, a very high number of vegetable taxa were detected, 72 of which are eaten only in Sicily, while 12 are consumed in all the Mediterranean countries examined. CONCLUSIONS: The research shows a high level of Sicilian knowledge about using wild plants as a traditional food source. Wild vegetables are healthy and authentic ingredients for local and ancient recipes, which are fundamental to the revitalization of quality food strictly connected to traditional agroecosystems.

Laser Ablation Synthesis of Gold Selenides by using a Mass Spectrometer as a Synthesizer: Laser Desorption Ionization Time-of-Flight Mass Spectrometry.

Methods for the rapid construction of new chemical motifs have the potential to accelerate the development of nanoscience. The synthesis of new chemical entities by laser ablation has been systematically demonstrated by using mixtures of gold and selenium. The compounds generated are detected by time-of-flight mass spectrometry and, for selected compounds, the structure is investigated by using density functional theory optimization. In total, 67 new gold selenide clusters have been synthesized, demonstrating an unsuspected richness in gold chemistry. Chemical species generated in the gas phase might inspire new routes for the synthesis of novel compounds in the solid state.

Multivariate Calibration Approach for Quantitative Determination of Cell-Line Cross Contamination by Intact Cell Mass Spectrometry and Artificial Neural Networks.

Cross-contamination of eukaryotic cell lines used in biomedical research represents a highly relevant problem. Analysis of repetitive DNA sequences, such as Short Tandem Repeats (STR), or Simple Sequence Repeats (SSR), is a widely accepted, simple, and commercially available technique to authenticate cell lines. However, it provides only qualitative information that depends on the extent of reference databases for interpretation. In this work, we developed and validated a rapid and routinely applicable method for evaluation of cell culture cross-contamination levels based on mass spectrometric fingerprints of intact mammalian cells coupled with artificial neural networks (ANNs). We used human embryonic stem cells (hESCs) contaminated by either mouse embryonic stem cells (mESCs) or mouse embryonic fibroblasts (MEFs) as a model. We determined the contamination level using a mass spectra database of known calibration mixtures that served as training input for an ANN. The ANN was then capable of correct quantification of the level of contamination of hESCs by mESCs or MEFs. We demonstrate that MS analysis, when linked to proper mathematical instruments, is a tangible tool for unraveling and quantifying heterogeneity in cell cultures. The analysis is applicable in routine scenarios for cell authentication and/or cell phenotyping in general.

Matrix-assisted laser desorption/ionisation quadrupole ion trap time-of-flight mass spectrometry of novel shape-persistent macrocycles.

RATIONALE: Shape-persistent macrocycles (SPMs) represent innovative molecular building blocks for the development of highly organised supramolecular architectures with application in nanotechnology, chemistry, catalysis and optoelectronics. Systematic mass spectrometric characterisation of SPMs and their collision-activated decay is not available to date. METHODS: Characterisation of alkoxy-decorated SPMs was performed by matrix-assisted laser desorption/ionisation quadrupole ion trap time-of-flight mass spectrometry (MALDI-QIT-TOFMS) and collision-induced dissociation (CID). RESULTS: Laser excitation of SPMs leads to the formation of stable cation radicals which show characteristic fragmentation patterns. All the product ions formed were identified. Photoelectrons generated during the MALDI process and full-ring conjugation were found to be fundamental for the formation of molecular cation radicals and their stabilisation, respectively. Formation of supramolecular aggregates of SPMs by π-π stacking was proven. SPMs are suitable motifs for the preparation of novel fullerene-based donor-acceptor systems. CONCLUSIONS: Alkoxy-decorated SPMs represent promising electron-donating building blocks that can be exploited in electronics and optoelectronics for the development of robust and highly efficient laser-activated supramolecular switches.

Generation of new Agm Ten clusters via laser ablation synthesis using Ag-Te nano-composite as precursor. Quadrupole ion trap time-of-flight mass spectrometry.

RATIONALE: Silver tellurides find applications in the development of infrared detection, imaging, magnetics, sensors, memory devices, and optic materials. However, only a limited number of silver tellurides have been described to date. Laser ablation synthesis (LAS) was selected to generate new Ag-Te clusters. METHODS: Isothermal adsorption was used to study the formation of silver nano-particles-tellurium aggregates. Laser desorption ionization quadrupole ion trap time-of-flight mass spectrometry (LDI-QIT-TOFMS) was used for the generation and analysis of Agm Ten clusters. Scanning electron microscopy and energy-dispersive X-ray spectroscopy were used to visualize the structure of materials. The stoichiometry of the generated clusters was determined by computer modeling of isotopic patterns. RESULTS: A simple, one-pot method for the preparation of Ag-Te nano-composite was developed and found suitable for LAS of silver tellurides. The LDI of Ag-Te nano-composite leads to the formation of 11 unary and 52 binary clusters. The stoichiometry of the 34 novel Agm Ten clusters is reported here for the first time. CONCLUSIONS: LAS with TOFMS detection was proven to be a powerful technique for the generation of silver telluride clusters. Knowledge of the stoichiometry of the generated clusters might facilitate the further development of novel high-tech silver tellurium nano-materials.

Generation of Au(p)Ag(q)Te(r) clusters via laser ablation synthesis using Au-Ag-Te nano-composite as precursor: quadrupole ion-trap time-of-flight mass spectrometry.

RATIONALE: Metal tellurides have applications in various fields of science and technology but only a few gold-silver tellurides have been reported. The laser ablation synthesis (LAS) method allows the preparation of nano-materials from solid substrates. Therefore, this method was selected to synthesise some gold-silver tellurides. METHODS: Laser desorption ionisation quadrupole ion trap time-of-flight mass spectrometry (LDI QIT TOF MS) was used for the generation of new Au(p)Ag(q)Te(r) clusters. Scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX) were used to characterise the materials. The stoichiometry of the clusters generated was determined via collision-induced dissociation (CID) and modeling of isotopic patterns. RESULTS: Chemisorption of gold and silver nano-particles on tellurium powder led to the formation of a new kind of Au-Ag-Te nano-composite. The LDI of this nano-composite yielded nine unary (Ag(q), Te(r)), 40 binary (Au(p)Te(r) and Ag(p)Te(r)) and 78 ternary clusters. The stoichiometry of these novel Au(p)Ag(q)Te(r) clusters is reported here for the first time. CONCLUSIONS: The new Au-Ag-Te nano-composite was found to be a more suitable precursor for the generation of clusters than the mixtures of the elements. TOF MS was shown to be a useful technique for following the generation of gold-silver tellurides. Knowledge of the cluster stoichiometry could accelerate the further development of novel high-tech materials such as chalcogenide glasses.

Laser ablation synthesis of new gold carbides. From gold-diamond nano-composite as a precursor to gold-doped diamonds. Time-of-flight mass spectrometric study.

RATIONALE: Gold carbides can be produced via laser ablation synthesis (LAS) from mixtures of nano-gold (NG) and various carbonaceous materials. The nano-composite of nano-gold (NG) and nano-diamond (ND) might represent a promising precursor for the generation of new gold carbides. METHODS: Time-of-flight mass spectrometry (TOF MS), transmission electron microscopy (TEM) and energy-dispersive X-ray spectroscopy (EDX) were used. The stoichiometry of clusters was determined via modelling of the isotopic patterns and MS(n) analysis. RESULTS: A simple procedure for the preparation of ND-NG nano-composite was developed using NG and ND. The formation of AuCn(+) (n = 1-11, 18), Au2Cn(+) (n = 1-16) and Au3Cn(+) (n = 1-10) clusters during LAS of the nano-composite was proved. Structures of gold carbides are proposed and discussed. Diamonds-containing AumCn(+) (m = 1-3, n = 10, 14, 18, 22) clusters might be not carbides but endohedral supramolecular complexes Aum@Cn(+) i.e., 'gold-doped' diamonds. CONCLUSIONS: TOF MS was shown to be a useful technique for following the formation of gold carbides in the gas phase. Clusters and 'gold-doped' diamonds generated might inspire synthesis of new Au-C materials with hardly predictable, unusual properties.

Development and validation of a general approach to predict and quantify the synergism of anti-cancer drugs using experimental design and artificial neural networks.

The combination of two or more drugs using multidrug mixtures is a trend in the treatment of cancer. The goal is to search for a synergistic effect and thereby reduce the required dose and inhibit the development of resistance. An advanced model-free approach for data exploration and analysis, based on artificial neural networks (ANN) and experimental design is proposed to predict and quantify the synergism of drugs. The proposed method non-linearly correlates the concentrations of drugs with the cytotoxicity of the mixture, providing the possibility of choosing the optimal drug combination that gives the maximum synergism. The use of ANN allows for the prediction of the cytotoxicity of each combination of drugs in the chosen concentration interval. The method was validated by preparing and experimentally testing the combinations with the predicted highest synergistic effect. In all cases, the data predicted by the network were experimentally confirmed. The method was applied to several binary mixtures of cisplatin and [Cu(1,10-orthophenanthroline)2(H2O)](ClO4)2, Cu(1,10-orthophenanthroline)(H2O)2(ClO4)2 or [Cu(1,10-orthophenanthroline)2(imidazolidine-2-thione)](ClO4)2. The cytotoxicity of the two drugs, alone and in combination, was determined against human acute T-lymphoblastic leukemia cells (CCRF-CEM). For all systems, a synergistic effect was found for selected combinations.

Laser desorption ionisation quadrupole ion trap time-of-flight mass spectrometry of titanium-carbon thin films.

RATIONALE: Titanium-carbon (Ti-C) ceramic thin films (abbreviated as n-TiC/a-C:H) are very important for industrial applications. However, their chemical structure is still not completely resolved. The aim of this study was to determine the chemical composition of such n-TiC/a-C:H layers prepared by balanced magnetron sputtering under various experimental conditions. METHODS: Mass spectrometric analysis of Ti-C thin films was carried out via laser desorption ionisation (LDI) using a quadrupole ion trap and reflectron time-of-flight analyser. The stoichiometry of clusters formed via laser ablation was determined, and the relative abundances of species for which the isotopic patterns overlaps were estimated using a least-squares program. RESULTS: Ti-C films were found to be composites of (i) pure and hydrogenated TiC, (ii) titanium oxycarbides, and (iii) titanium oxides of various degrees of hydrogenation (all embedded in an amorphous and/or diamond-like carbon matrix). Hydrogenated titanium oxycarbide was the main component of the surface layer, whereas deeper layers were composed primarily of TiC and titanium oxides (also embedded in the carbon matrix). CONCLUSIONS: Mass spectrometry proved useful for elucidating the chemical structure of the hard ceramic-like Ti-C layers produced by magnetron sputtering. The Ti-C layers were found to be complex composites of various chemical entities. Knowledge of the resolved structure could accelerate further development of these kinds of materials.

Artificial neural networks combined with experimental design: a "soft" approach for chemical kinetics.

The possibilities of artificial neural networks (ANNs) "soft" computing to evaluate chemical kinetic data have been studied. In the first stage, a set of "standard" kinetic curves with known parameters (rate constants and/or concentrations of the reactants), which is some kind of "normalized maps", is prepared. The database should be built according to a suitable experimental design (ED). In the second stage, such data set is then used for ANNs "learning". Afterwards, in the second stage, experimental data are evaluated and parameters of "other" kinetic curves are computed without solving anymore the system of differential equations. The combined ED-ANNs approach has been applied to solve several kinetic systems. It was also demonstrated that using ANNs, the optimization of complex chemical systems can be achieved even not knowing or determining the values of the rate constants. Moreover, the solution of differential equations is here not necessary, as well. Using ED the number of experiments can be reduced substantially. Methodology of ED-ANNs applied to multicomponent analysis shows advantages over classical methods while the knowledge of kinetic reactions is not needed. ANNs computation in kinetics is robust as shown evaluating the effect of experimental errors and it is of general applicability.