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The application of innovative spatial proteomics techniques, such as those based upon matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) technology, has the potential to impact research in the field of nephropathology. Notwithstanding, the possibility to apply this technology in more routine diagnostic contexts remains limited by the alternative fixatives employed by this ultraspecialized diagnostic field, where most nephropathology laboratories worldwide use bouin-fixed paraffin-embedded (BFPE) samples. Here, the feasibility of performing MALDI-MSI on BFPE renal tissue is explored, evaluating variability within the trypsin-digested proteome as a result of different preanalytical conditions and comparing them with the more standardized formalin-fixed paraffin-embedded (FFPE) counterparts. A large proportion of the features (270, 68.9%) was detected in both BFPE and FFPE renal samples, demonstrating only limited variability in signal intensity (10.22-10.06%). Samples processed with either fixative were able to discriminate the principal parenchyma regions along with diverse renal substructures, such as glomeruli, tubules, and vessels. This was observed when performing an additional "stress test", showing comparable results in both BFPE and FFPE samples when the distribution of several amyloid fingerprint proteins was mapped. These results suggest the utility of BFPE tissue specimens in MSI-based nephropathology research, further widening their application in this field.

Mass spectrometry imaging (MSI) is an emerging technology that is capable of mapping various biomolecules within their native spatial context, and performing spatial multiomics on formalin-fixed paraffin-embedded (FFPE) tissues may further increase the molecular characterization of pathological states. Here we present a novel workflow which enables the sequential MSI of lipids, N- glycans, and tryptic peptides on a single FFPE tissue section and highlight the enhanced molecular characterization that is offered by combining the multiple spatial omics data sets. In murine brain and clear cell renal cell carcinoma (ccRCC) tissue, the three molecular levels provided complementary information and characterized differ- ent histological regions. Moreover, when the spatial omics data was integrated, the different histopathological regions of the ccRCC tissue could be better discriminated with respect to the imaging data set of any single omics class. Taken together, these promising findings demonstrate the capability to more comprehensively map the molecular complexity within pathological tissue.

Introduction: Despite advancements in diagnostic methods, the classification of indeterminate thyroid nodules still poses diagnostic challenges not only in pre-surgical evaluation but even after histological evaluation of surgical specimens. Proteomics, aided by mass spectrometry and integrated with artificial intelligence and machine learning algorithms, shows great promise in identifying diagnostic markers for thyroid lesions. Areas covered: This review provides in-depth exploration of how proteomics has contributed to the understanding of thyroid pathology. It discusses the technical advancements related to immunohistochemistry, genetic and proteomic techniques, such as mass spectrometry, which have greatly improved sensitivity and spatial resolution up to single-cell level. These improvements allowed the identification of specific protein signatures associated with different types of thyroid lesions. Expert commentary: Among all the proteomics approaches, spatial proteomics stands out due to its unique ability to capture the spatial context of proteins in both cytological and tissue thyroid samples. The integration of multi-layers of molecular information combining spatial proteomics, genomics, immunohistochemistry or metabolomics and the implementation of artificial intelligence and machine learning approaches, represent hugely promising steps forward toward the possibility to uncover intricate relationships and interactions among various molecular components, providing a complete picture of the biological landscape whilst fostering thyroid nodule diagnosis.

The aim of this study was to determine alterations of the metabolome in blood plasma in response to concentric-eccentric leg exercise performed at a simulated altitude of 3,500 m. To do so, we recruited 11 well-trained subjects and performed an untargeted metabolomics analysis of plasma samples obtained before, 20 min after as well as on day 8 after five sets of maximal, concentric-eccentric leg exercises that lasted 90 s each. We identified and annotated 115 metabolites through untargeted liquid chromatography-mass spectrometry metabolomics and used them to further calculate 20 sum/ratio of metabolites. A principal component analysis (PCA) revealed differences in-between the overall metabolome at rest and immediately after exercise. Interestingly, some systematic changes of relative metabolite concentrations still persisted on day 8 after exercise. The first two components of the PCA explained 34% of the relative concentrations of all identified metabolites analyzed together. A volcano plot indicates that 35 metabolites and two metabolite ratios were significantly changed directly after exercise, such as metabolites related to carbohydrate and TCA metabolism. Moreover, we observed alterations in the relative concentrations of amino acids (e.g., decreases of valine, leucine and increases in alanine) and purines (e.g., increases in hypoxanthine, xanthine and uric acid). In summary, high intensity concentric-eccentric exercise performed at simulated altitude systematically changed the blood metabolome in trained athletes directly after exercise and some relative metabolite concentrations were still changed on day 8. The importance of that persisting metabolic alterations on exercise performance should be studied further.

What’s brewing? Mapping the distribution of bioactive compounds in green C. arabica coffee beans through MS-driven spatial metabolomics

The association between lipid metabolism and long-term outcomes is relevant for tumor diagnosis and therapy. Archival material such as formalin-fixed and paraffin embedded (FFPE) tissues is a highly valuable resource for this aim as it is linked to long-term clinical follow-up. There-fore, there is a need to develop robust methodologies able to detect lipids in FFPE material and correlate them with clinical outcomes. In this work, lipidic alterations were investigated in patient-derived xenograft of breast cancer by using a matrix-assisted laser desorption ionization mass spec-trometry (MALDI MSI) based workflow that included antigen retrieval as a sample preparation step. We evaluated technical reproducibility, spatial metabolic differentiation within tissue com-partments, and treatment response induced by a glutaminase inhibitor (CB-839). This protocol shows a good inter-day robustness (CV = 26 ± 12%). Several lipids could reliably distinguish necrotic and tumor regions across the technical replicates. Moreover, this protocol identified distinct alterations in the tissue lipidome of xenograft treated with glutaminase inhibitors. In conclusion, lipidic alterations in FFPE tissue of breast cancer xenograft observed in this study are a step-forward to a robust and reproducible MALDI-MSI based workflow for pre-clinical and clinical applications.

Predicting the prognosis of colorectal cancer (CRC) patients remains challenging and a characterisation of the tumour immune environment represents one of the most crucial avenues when attempting to do so. For this reason, molecular approaches which are capable of classifying the immune environments associated with tumour infiltrating lymphocytes (TILs) are being readily investigated. In this proof of concept study, we aim to explore the feasibility of using spatial lipidomics by MALDI-MSI to distinguish CRC tissue based upon their TIL content. Formalin-fixed paraffin-embedded tissue from human thymus and tonsil was first analysed by MALDI-MSI to obtain a curated mass list from a pool of single positive T lymphocytes, whose putative identities were annotated using an LC-MS-based lipidomic approach. A CRC tissue microarray (TMA, n = 30) was then investigated to determine whether these cases could be distinguished based upon their TIL content in the tumour and its microenvironment. MALDI-MSI from the pool of mature T lymphocytes resulted in the generation of a curated mass list containing 18 annotated m/z features. Initially, subsets of T lymphocytes were then distinguished based on their state of maturation and differentiation in the human thymus and tonsil tissue. Then, when applied to a CRC TMA containing differing amounts of T lymphocyte infiltration, those cases with a high TIL content were distinguishable from those with a lower TIL content, especially within the tumour microenvironment, with three lipid signals being shown to have the greatest impact on this separation (p < 0.05). On the whole, this preliminary study represents a promising starting point and suggests that a lipidomics MALDI-MSI approach could be a promising tool for subtyping the diverse immune environments in CRC.

Mass spectrometry imaging (MSI) is an emerging technology that is capable of mapping various biomolecules within their native spatial context, and performing spatial multiomics on formalin-fixed paraffin-embedded (FFPE) tissues may further increase the molecular characterization of pathological states. Here we present a novel workflow which enables the sequential MSI of lipids, N-glycans, and tryptic peptides on a single FFPE tissue section and highlight the enhanced molecular characterization that is offered by combining the multiple spatial omics data sets. In murine brain and clear cell renal cell carcinoma (ccRCC) tissue, the three molecular levels provided complementary information and characterized different histological regions. Moreover, when the spatial omics data was integrated, the different histopathological regions of the ccRCC tissue could be better discriminated with respect to the imaging data set of any single omics class. Taken together, these promising findings demonstrate the capability to more comprehensively map the molecular complexity within pathological tissue.

Con il termine di –omica spaziale si intende l’insieme di diverse tecniche che consentono di rilevare alterazioni significative delle biomolecole all’interno dei loro tessuti d’origine o delle strutture cellulari, permettendo quindi di integrare ed ampliare la comprensione dei cambiamenti biologici che si verificano in tessuti patologici complessi ed eterogenei, come il cancro. Tuttavia, per comprendere appieno la complessità e le dinamiche al di là delle condizioni patologiche, è necessario studiare e integrare diverse analisi molecolari, come quelle di lipidi e glicani, in modo da ottenere un’istantanea molecolare il più completa ed estesa possibile della malattia. Tra le tecniche di -omica spaziale, quella di desorbimento e ionizzazione laser assistiti da matrice (MALDI) abbinata alla spettrometria di massa imaging (MSI), permette lo studio della componente molecolare del tessuto patologico tramite un approccio multiplex, che permette di esaminare diverse centinaia di biomolecole in una singola analisi. Pertanto, l’analisi MALDI-MSI viene utilizzata per studi -omici spaziali di proteine, peptidi e N-glicani su campioni di tessuti clinici fissati in formalina e inclusi in paraffina (FFPE). Per quanto riguarda i lipidi, invece, questo tipo di analisi è sempre stato considerato poco efficace su campioni FFPE a causa della perdita di una grande quantità di contenuto lipidico durante le fasi di lavaggio con solventi organici, mentre i restanti lipidi resistenti ai solventi sono inaccessibili poiché trattenuti nei legami incrociati della formalina. In questi tre anni di dottorato, abbiamo sviluppato nuovi approcci MALDI-MSI per l'analisi spaziale multi-omica su campioni di tessuto clinico FFPE. Le prime tre pubblicazioni riportate in questa tesi si sono concentrate sullo sviluppo di protocolli MALDI-MSI per lipidi in campioni FFPE. In particolare, due di essi descrivono il metodo di preparazione del campione per la rilevazione di ioni di fosfolipidi carichi posi, The field of spatial omics defines the gathering of different techniques that allow the detection of significant alterations of biomolecules in the context of their native tissue or cellular structures. As such, they extend the landscape of biological changes occurring in complex and heterogeneous pathological tissues, such as cancer. However, additional molecular levels, such as lipids and glycans, must be studied to define a more comprehensive molecular snapshot of disease and fully understand the complexity and dynamics beyond pathological condition. Among the spatial-omics techniques, matrix-assisted laser desorption/ionisation (MALDI)-mass spectrometry imaging (MSI) offers a powerful insight into the chemical biology of pathological tissues in a multiplexed approach where several hundreds of biomolecules can be examined within a single experiment. Thus, MALDI-MSI has been readily employed for spatial omics studies of proteins, peptides and N-Glycans on clinical formalin-fixed paraffin-embedded (FFPE) tissue samples. Conversely, MALDI-MSI analysis of lipids has always been considered not feasible on FFPE samples due to the loss of a great amount of lipid content during washing steps with organic solvents, with the remaining solvent-resistant lipids being involved in the formalin cross-links. In this three-year thesis work, novel MALDI-MSI approaches for spatial multi-omics analysis on clinical FFPE tissue samples were developed. The first three publications reported in this thesis focused on the development of protocols for MALDI-MSI of lipids in FFPE samples. In particular, two of them describe a sample preparation method for the detection of positively charged phospholipids ions, mainly phosphatidylcholines (PCs), in clinical clear cell Renal Cell Carcinoma (ccRCC) samples and in a xenograft model of breast cancer. The third publication reports the possibility to use negatively charged phospholipids ions, mainly phosphatidylinositols (PIs), to define lipid sig

Neural tissue has high metabolic requirements. Following spinal cord injury (SCI), the damaged tissue suffers from a severe metabolic impairment, which aggravates axonal degeneration and neuronal loss. Impaired cellular energetic, tricarboxylic acid (TCA) cycle and oxidative phosphorylation metabolism in neuronal cells has been demonstrated to be a major cause of neural tissue death and regeneration failure following SCI. Therefore, rewiring the spinal cord cell metabolism may be an innovative therapeutic strategy for the treatment of SCI. In this study, we evaluated the therapeutic effect of the recovery of oxidative metabolism in a mouse model of severe contusive SCI. Oral administration of TCA cycle intermediates, co-factors, essential amino acids, and branched-chain amino acids was started 3 days post-injury and continued until the end of the experimental procedures. Metabolomic, immunohistological, and biochemical analyses were performed on the injured spinal cord sections. Administration of metabolic precursors enhanced spinal cord oxidative metabolism. In line with this metabolic shift, we observed the activation of the mTORC1 anabolic pathway, the increase in mitochondrial mass, and ROS defense which effectively prevented the injury-induced neural cell apoptosis in treated animals. Consistently, we found more choline acetyltransferase (ChAT)-expressing motor neurons and increased neurofilament-positive corticospinal axons in the spinal cord parenchyma of the treated mice. Interestingly, oral administration of the metabolic precursors increased the number of activated microglia expressing the CD206 marker suggestive of a pro-resolutive, M2-like phenotype. These molecular and histological modifications observed in treated animals ultimately led to a significant, although partial, improvement of the motor functions. Our data demonstrate that rewiring the cellular metabolism can represent an effective strategy to treat SCI.

Introduction: Diabetic nephropathy (DN) and hypertensive nephrosclerosis (HN) represent the most common causes of chronic kidney disease (CKD) and many patients progress to -end-stage renal disease. Patients are treated primarily through the management of cardiovas-cular risk factors and hypertension; however patients with HN have a more favorable outcome. A noninvasive clinical approach to separate these two entities, especially in hypertensive patients who also have diabetes, would allow for targeted treatment and more appropriate resource allocation to those patients at the highest risk of CKD progression. Meth-ods: In this preliminary study, high-spatial-resolution matrix-assisted laser desorption/ion-ization (MALDI) mass spectrometry imaging (MSI) was integrated with high-mass accuracy MALDI-FTICR-MS and nLC-ESI-MS/MS analysis in order to detect tissue proteins within kidney biopsies to discriminate cases of DN (n = 9) from cases of HN (n = 9). Results: Differences in the tryptic peptide profiles of the 2 groups could clearly be detected, with these becoming even more evident in the more severe histological classes, even if this was not evident with routine histology. In particular, 4 putative proteins were detected and had a higher signal intensity within regions of DN tissue with extensive sclerosis or fibrosis. Among these, 2 proteins (PGRMC1 and CO3) had a signal intensity that increased at the latter stages of the disease and may be associated with progression. Discussion/Conclusion: This preliminary study represents a valuable starting point for a future study employing a larger cohort of patients to develop sensitive and specific protein biomarkers that could reliably differentiate between diabetic and hypertensive causes of CKD to allow for improved diagnosis, fewer biopsy procedures, and refined treatment approaches for clinicians.

This study presents the matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) as a unique technology for the in-situ detection of N-glycans and proteins from the same formalin-fixed paraffin-embedded (FFPE) tissue section.

Membranous Nephropathy (MN) is the most frequent cause of nephrotic syndrome in adults and the disease course is characterised by the "rule of third", with one third of patients experiencing complete remission and the remaining experiencing relapses or progression of the disease. Additionally, the therapeutic approach is not standardised, leading to further heterogeneity in terms of response and outcome. In this pilot study, MALDI-MSI analysis was performed on renal biopsies (n = 13) obtained from two homogeneous groups of patients which differentially responded to the immunosuppressive treatments (Ponticelli regimen). A signal at m/z 1303 displayed the greatest discriminatory power when comparing the two groups and was observed to be of higher intensity in the glomeruli of the non-responding patients. The corresponding tryptic peptide was identified as macrophage migration inhibitory factor (MIF). Despite much effort being made in recent years to understand the pathogenesis of MN, a biomarker able to predict the outcome of these patients following therapeutic treatment is still lacking. Here, we highlight a protein (MIF), verified by immunohistochemistry, which can differentiate between these MN patients and could be a valuable starting point for a further study focused on verifying its predictive role in therapy response. This article is protected by copyright. All rights reserved

Protein N-glycosylation is one of the most important post-translational modifications and is involved in many biological processes, with aberrant changes in protein N-glycosylation patterns being closely associated with several diseases, including the progression and spreading of tumours. In light of this, identifying these aberrant protein glycoforms in tumours could be useful for understanding the molecular mechanism of this multifactorial disease, developing specific biomarkers and finding novel therapeutic targets. We investigated the urinary N-glycoproteome of clear cell renal cell carcinoma (ccRCC) patients at different stages (n = 15 at pT1 and n = 15 at pT3), and of non-ccRCC subjects (n = 15), using an N-glyco-FASP-based method. Using label-free nLC-ESI MS/MS, we identified and quantified several N-glycoproteins with altered expression and abnormal changes affecting the occupancy of the glycosylation site in the urine of RCC patients compared to control. In particular, nine of them had a specific trend that was directly related to the stage progression: CD97, COCH and P3IP1 were up-expressed whilst APOB, FINC, CERU, CFAH, HPT and PLTP were down-expressed in ccRCC patients. Overall, these results expand our knowledge related to the role of this post-translational modification in ccRCC and translation of this information into pre-clinical studies could have a significant impact on the discovery of novel biomarkers and therapeutic target in kidney cancer.

Formalin-fixed paraffin-embedded (FFPE) tissue represents the primary source of clinical tissue and is routinely used in MALDI-MSI studies. However, it is not particularly suitable for lipidomics imaging given that many species are depleted during tissue processing. Irrespective, a number of solvent-resistant lipids remain, but their extraction may be hindered by the cross-link between proteins. Therefore, an antigen retrieval step could enable the extraction of a greater number of lipids and may provide information that is complementary to that which can be obtained from other biomolecules, such as proteins. In this short communication, we aim to address the effect of performing antigen retrieval prior to MALDI-MSI of lipids in FFPE tissue. As a result, an increased number of lipid signals could be detected and may have derived from lipid species that are known to be implicated in the lipid-protein cross-linking that is formed as a result of formalin fixation. Human renal cancer tissue was used as a proof of concept to determine whether using these detected lipid signals were also able to highlight the histopathological regions that were present. These preliminary findings may highlight the potential to enhance the clinical relevance of the lipidomic information obtained from FFPE tissue.

Liquid biopsies, as blood and urine, could offer an invaluable, easily accessible source of biomarkers, and evidences for elucidating the pathological processes. Only few studies integrated the proteomes driven by more than one biofluid. Furthermore, it is not clear which biofluid better mirrors the alterations triggered by disease. Venous infiltrating RCC(Renal Cell Carcinoma) could represent an advantageous model for exploring this aspect. Herein, we investigate how blood and urine “proteomically” reflect the changes occurring during RCC infiltration into renal vein(RV) by label-free nLC-ESI-MS/MS. We found 574 and 58 differentially expressed proteins(DEPs) in response to vascular involvement. To the augment of vascular involvement, the abundance of only three proteins in urine(UROM,RALA,CNDP1) and two in plasma(APOA1,K2C1) diminished while increased for twenty-six urinary proteins. 80 proteins were found both in urine and plasma, among which twenty-eight were DEPs. A huge overlap between the two biofluids was highlighted, as expected, being urine the filtrate of blood. However, this consistency decreases when RV-occlusion occurs suggesting alternative protein releases, and a loss of kidney architecture. Moreover, several proteomic and functional signatures were biofluid-specific. In conclusion, the complementarity between the specimens allowed to achieve a deeper level of molecular complexity of the RCC venous infiltration. Significance: Although plasma and urine are strongly interconnected, only few proteomic studies investigated the complementarity of these fluids as bio-sources of information. Moreover, none of them was focused to their analysis and comparison in the context of vascular infiltration of renal cancer. Herein, new insights were gained regarding the impact into urinary and plasma proteome of the changes triggered by the ccRCC invasion into vascular system and renal vein. Furthermore, the integration of the information driven by the two liquid biop

MALDI-MSI represents an ideal tool to explore the spatial distribution of proteins directly in situ, integrating molecular and cytomorphological information, enabling the discovery of potential diagnostic markers in thyroid cytopathology. However, red cells present in the fine needle aspiration biopsy (FNAB) specimens caused ion suppression of other proteins during the MALDI-MSI analysis due to large amount of haemoglobin. Aim of this study was to set up a sample preparation workflow able to manage this haemoglobin interference. Three protocols were compared using ex vivo cytological samples collected from fresh thyroid nodules of 9 patients who underwent thyroidectomy: (A) conventional air-dried smears, (B) cytological smears immediately fixed in ethanol, and (C) ThinPrep liquid-based preparation. Protocols C and A were also evaluated using real FNABs. Results show that protocol C markedly decreased the amount of haemoglobin, with respect to protocols A and B. Protein profiles obtained with protocols A and B were characterised by high inter-patient variability, probably related to the abundance of the haemoglobin, whereas similar spectra were observed for protocol C, where haemoglobin contents were lower. Our findings suggest protocol C as the sample preparation method for MALDI-MSI analysis.

Purpose: MALDI–MS imaging (MALDI–MSI) is an emerging technology that enables the spatial distribution of biomolecules within tissue to be combined with the traditional morphological information familiar to clinicians. Thus, for diagnostic or prognostic purposes, along with predicting response to therapeutic treatment, it is important to properly collect and handle biological specimens in order to avoid degradation or the formation of artifacts in the morphological structure and proteomic profile. Experimental design: In this work, the morphological and proteomic stability of thyroid fine needle aspiration biopsies in PreservCyt (up to 14 days) and CytoLyt (up to 7 days) solutions at 4 °C has been verified, by MALDI–MSI analysis. Moreover, a new measure has been introduced in order to assess the similarity of the obtained MALDI–MSI spectra, by equally taking into account the number of signals (fit and retrofit), and their intensities (Spearman's correlation and spectra overlap). Results: Results show no degradation of the cellular morphology and a good stability of the samples up to 14 days in PreservCyt solution. Conclusions and clinical relevance: Moreover, this protocol can be easily implemented in pathological units, allowing simple sample collection and shipment to be used not only for the proteomic MALDI–MSI analysis of thyroid FNABs but also for other biological liquid based specimens.

The main aim of the study was to assess the feasibility of matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) in the pathological investigation of Medullary Thyroid Carcinoma (MTC). Formalin-fixed paraffin-embedded (FFPE) samples from seven MTC patients were analysed by MALDI-MSI in order to detect proteomic alterations within tumour lesions and to define the molecular profiles of specific findings, such as amyloid deposition and C cell hyperplasia (CCH). nLC-ESI MS/MS was employed for the identification of amyloid components and to select alternative proteomic markers of MTC pathogenesis. Results highlighted the potential of MALDI-MSI to confirm the classic immunohistochemical methods employed for the diagnosis of MTC, with good sensitivity and specificity. Intratumoural amyloid components were also detected and identified, and were characterised by calcitonin, apolipoprotein E, apolipoprotein IV, and vitronectin. The tryptic peptide profiles representative of MTC and CCH were distinctly different, with four alternative markers for MTC being detected; K1C18, and three histones (H2A, H3C, and H4). Finally, a further 115 proteins were identified through the nLC-ESI-MS/MS analysis alone, with moesin, veriscan, and lumican being selected due to their potential involvement in MTC pathogenesis. This approach represents a complimentary strategy that could be employed to detect new proteomic markers of MTC. Statement of significance: Medullary thyroid carcinoma (MTC) is a rare endocrine malignancy that originates from the parafollicular C-cells of the thyroid. The diagnosis is typically established using a combination of fine-needle aspiration biopsy (FNAB) of a suspicious nodule along with the demonstrable elevation of serum biomarkers, such as calcitonin and carcinoembryonic antigen (CEA). Unfortunately, this combination is often associated with a high degree of false-positive results and this can lead to misdiagnosis and avoidable total th

Gastric cancer (GC) is one of the leading causes of cancer-related deaths worldwide and the disease outcome commonly depends upon the tumour stage at the time of diagnosis. However, this cancer can often be asymptomatic during the early stages and remain undetected until the later stages of tumour development, having a significant impact on patient prognosis. However, our comprehension of the mechanisms underlying the development of gastric malignancies is still lacking. For these reasons, the search for new diagnostic and prognostic markers for gastric cancer is an ongoing pursuit. Modern mass spectrometry imaging (MSI) techniques, in particular matrix-assisted laser desorption/ionisation (MALDI), have emerged as a plausible tool in clinical pathology as a whole. More specifically, MALDI-MSI is being increasingly employed in the study of gastric cancer and has already elucidated some important disease checkpoints that may help us to better understand the molecular mechanisms underpinning this aggressive cancer. Here we report the state of the art of MALDI-MSI approaches, ranging from sample preparation to statistical analysis, and provide a complete review of the key findings that have been reported in the literature thus far