Time and temperature abuse of milk in conditions representing a school cafeteria share table does not meaningfully reduce microbial quality

Share tables (ST) are tables or stations in school cafeterias where students can return unopened foods and beverages, providing an opportunity to access these items at no cost. Currently, research suggests that milk is among the most wasted items in breakfast and lunch programs in the United States. Share tables present a simple solution for reducing milk waste, but research is needed to understand the microbial spoilage potential of milk in ST. To this end, uninoculated milk cartons and milk cartons inoculated with 2 to 3 log10(cfu/mL) Pseudomonas poae, a fast-growing psychrotroph, was exposed to ambient temperature during winter (mean temperature = 20.3°C) and summer (23.1°C) for 125 min, repeated over 5 d (the length of a school week). Microbial counts in the inoculated milk cartons increased linearly, exceeding the spoilage threshold of 6.0 log10(cfu/mL) after d 3 and after d 4 in the winter and summer season trials, respectively. In the winter trial, the microbial counts for uninoculated milk cartons never exceeded the lower limit of detection, 2.31 log10(cfu/mL), and in the summer trials, microbial counts never reached the spoilage threshold, indicating that initial contamination is a driving factor of microbial milk spoilage. Regardless of sharing status or seasonality, the greatest changes in counts for inoculated milk cartons occurred during overnight refrigeration, ranging from 0.56 to 1.4 log10(cfu/mL), while during the share table ranged from no observable change up to 0.29 log10(cfu/mL), emphasizing that school nutrition personnel should focus efforts on tightly controlling refrigeration temperatures and returning milk to refrigeration as soon as possible. A previously developed model for school cafeteria share tables was adapted to understand the typical residence time of milk in a simulated cafeteria with an ambient temperature share table for the summer and winter seasons over 1,000 wk. Milk was predicted to have a very short mean residence time (85 min) regardless of sharing status or season, with 99.8% of milk consumed, discarded, or donated within the first 2 d. As a result, only 3 out of 451,410 and 6 out of 451,410 simulated milks spoiled in the winter and summer seasons, respectively. The data generated here can be used to inform science-based decision-making for including milk in share tables, or applied to any system where one might have to accept short-term unrefrigerated storage of milk to meet a waste reduction or food security goal.

Adeno-Associated Virus Type 5 Infection via PDGFRα Is Associated With Interstitial Lung Disease in Systemic Sclerosis and Generates Composite Peptides and Epitopes Recognized by the Agonistic Immunoglobulins Present in Patients With Systemic Sclerosis

OBJECTIVE

The etiopathogenesis of systemic sclerosis (SSc) is unknown. Platelet-derived growth factor receptors (PDGFRs) are overexpressed in patients with SSc. Because PDGFRα is targeted by the adeno-associated virus type 5 (AAV5), we investigated whether AAV5 forms a complex with PDGFRα exposing epitopes that may induce the immune responses to the virus-PDGFRα complex.

METHODS

The binding of monomeric human PDGFRα to the AAV5 capsid was analyzed by in silico molecular docking, surface plasmon resonance (SPR), and genome editing of the PDGFRα locus. AAV5 was detected in SSc lungs by in situ hybridization, immunohistochemistry, confocal microscopy, and molecular analysis of bronchoalveolar lavage (BAL) fluid. Immune responses to AAV5 and PDGFRα were evaluated by SPR using SSc monoclonal anti-PDGFRα antibodies and immunoaffinity-purified anti-PDGFRα antibodies from sera of patients with SSc.

RESULTS

AAV5 was detected in the BAL fluid of 41 of 66 patients with SSc with interstitial lung disease (62.1%) and in 17 of 66 controls (25.75%) (P < 0.001). In SSc lungs, AAV5 localized in type II pneumocytes and in interstitial cells. A molecular complex formed of spatially contiguous epitopes of the AAV5 capsid and of PDGFRα was identified and characterized. In silico molecular docking analysis and binding to the agonistic anti-PDGFRα antibodies identified spatially contiguous epitopes derived from PDGFRα and AAV5 that interacted with SSc agonistic antibodies to PDGFRα. These peptides were also able to bind total IgG isolated from patients with SSc, not from healthy controls.

CONCLUSION

These data link AVV5 with the immune reactivity to endogenous antigens in SSc and provide a novel element in the pathogenesis of SSc.

Intrinsically disordered Prosystemin discloses biologically active repeat motifs

The in-depth studies over the years on the defence barriers by tomato plants have shown that the Systemin peptide controls the response to a wealth of environmental stress agents. This multifaceted stress reaction seems to be related to the intrinsic disorder of its precursor protein, Prosystemin (ProSys). Since latest findings show that ProSys has biological functions besides Systemin sequence, here we wanted to assess if this precursor includes peptide motifs able to trigger stress-related pathways. Candidate peptides were identified in silico and synthesized to test their capacity to trigger defence responses in tomato plants against different biotic stressors. Our results demonstrated that ProSys harbours several repeat motifs which triggered plant immune reactions against pathogens and pest insects. Three of these peptides were detected by mass spectrometry in plants expressing ProSys, demonstrating their effective presence in vivo. These experimental data shed light on unrecognized functions of ProSys, mediated by multiple biologically active sequences which may partly account for the capacity of ProSys to induce defense responses to different stress agents.

Chronic lactate exposure promotes cardiomyocyte cytoskeleton remodelling

We investigated the effect of growing on lactate instead of glucose in human cardiomyocyte assessing their viability, cell cycle activity, oxidative stress and metabolism by a proteomic and metabolomic approach. In previous studies performed on elite players, we found that adaptation to exercise is characterized by a chronic high plasma level of lactate. Lactate is considered not only an energy source but also a signalling molecule and is referred as "lactormone"; heart is one of the major recipients of exogenous lactate. With this in mind, we used a cardiac cell line AC16 to characterize the lactate metabolic profile and investigate the metabolic flexibility of the heart. Interestingly, our data indicated that cardiomyocytes grown on lactate (72 h) show change in several proteins and metabolites linked to cell hypertrophy and cytoskeleton remodelling. The obtained results could help to understand the effect of this metabolite on heart of high-performance athletes.

Long-term outcome of retroperitoneoscopic partial versus total adrenalectomy in patients with Cushing's syndrome

BACKGROUND

We analyze the long-term outcome of surgery for Cushing's syndrome (CS) and the influence of the extent of surgical resection on the duration of postoperative cortisone substitution.

METHODS

One-hundred forty-one patients (129 female, 12 males; mean age: 45.7 ± 12.8 years) operated between January 2000 to June 2020 were included in the analysis. Patients suffered from manifest (124) or subclinical (17) CS due to benign unilateral adrenal neoplasia. All tumors were removed by the posterior retroperitoneoscopic approach. 105 patients had total (TA) and 36 partial (PA) adrenalectomies. All patients were discharged with ongoing corticosteroid supplementation therapy.

RESULTS

Follow-up data could be obtained for 83 patients. Twenty-four (1 male, 23 females; mean age 42.3 years) underwent PA and 59 TA (6 males, 53 females; mean age 44.6 years). Mean follow-up time was 107 ± 68 months (range: 6-243 months). The median duration of postoperative corticosteroid therapy was 9.5 months after PA and 11 months after TA (p = 0.1). Significantly, more patients after total adrenalectomy required corticosteroid therapy for more than 24 months (25% vs. 4%; p = 0.03). Recurrent ipsilateral disease occurred in one case after partial adrenalectomy and was treated by completion adrenalectomy. A case of contralateral recurrence associated with subclinical Cushing's syndrome was observed after total adrenalectomy.

CONCLUSIONS

The risk of local recurrence after partial adrenalectomy in CS is low. Cortical-sparing surgery may shorten corticosteroid supplementation therapy after surgery.

Multi-omic characterisation as a tool to improve knowledge, valorisation and conservation of wild fruit genetic resources: the case of Arbutus unedo L

The valorisation and conservation of plant genetic resources (PGRs) and wild fruit PGRs are critical to ensure the maintenance of genetic and cultural heritage and to promote new perspectives on resource use. New strategies to characterize PGRs are needed, and the omics approach can provide information that is still largely unknown. The Strawberry tree (Arbutus unedo L.) is an underutilized, drought and fire-resistant species distributed in the Mediterranean area and its berries have large ethnobotanical use. Although their phenolic profile and antioxidant capacity are known, they are not well characterised, particularly from a proteomic perspective. The aim of this work is the characterisation of two ecotypes of A. unedo (Campania and Sicily) from a molecular viewpoint to valorise and encourage the preservation of this wild fruit. Samples were collected from two different geographical areas to assess whether different geographical conditions could influence the characteristics of leaves and fruits at the three stages of ripening (green, veraison, red). Proteomic analysis identified 904 proteins, of which 122 showed significance along the ripening. Some of these differentially abundant proteins, such as chalcone synthase, show a marked increase during ripening. The protein functional classes with the highest representation are involved in protein and amino acid metabolism, glycolysis and in secondary metabolism. From a proteomic perspective, there are no differences between the fruits from the two regions compared by the ripening stage. However, the pedoclimatic metabolic imprinting allowed the observation of good diversity in the metabolomic profiles between the two ecotypes, especially for anthocyanins, 4 times more abundant in the Sicilian veraisoned fruit than in the Campania one, and catechins, with double the abundance in the Campania ecotype compared to the Sicilian ecotype in the green phase, but more abundant (3x) in the Sicilian veraisoned fruit. Phenolic compounds show a 20% greater abundance in the Campania green arbutus fruit than in the Sicilian one, values that then equalise as ripening progresses. Multi-omic characterisation enhanced the knowledge on a wild fruit plant species which shows specific adaptations and responses to the environment to be considered when addressing the issue of local agrobiodiversity.

Transcriptional and proteomic analysis of the innate immune response to microbial stimuli in a model invertebrate chordate

Inflammatory response triggered by innate immunity can act to protect against microorganisms that behave as pathogens, with the aim to restore the homeostatic state between host and beneficial microbes. As a filter-feeder organism, the ascidian Ciona robusta is continuously exposed to external microbes that may be harmful under some conditions. In this work, we used transcriptional and proteomic approaches to investigate the inflammatory response induced by stimuli of bacterial (lipopolysaccharide -LPS- and diacylated lipopeptide - Pam2CSK4) and fungal (zymosan) origin, in Ciona juveniles at stage 4 of metamorphosis. We focused on receptors, co-interactors, transcription factors and cytokines belonging to the TLR and Dectin-1 pathways and on immune factors identified by homology approach (i.e. immunoglobulin (Ig) or C-type lectin domain containing molecules). While LPS did not induce a significant response in juvenile ascidians, Pam2CSK4 and zymosan exposure triggered the activation of specific inflammatory mechanisms. In particular, Pam2CSK4-induced inflammation was characterized by modulation of TLR and Dectin-1 pathway molecules, including receptors, transcription factors, and cytokines, while immune response to zymosan primarily involved C-type lectin receptors, co-interactors, Ig-containing molecules, and cytokines. A targeted proteomic analysis enabled to confirm transcriptional data, also highlighting a temporal delay between transcriptional induction and protein level changes. Finally, a protein-protein interaction network of Ciona immune molecules was rendered to provide a wide visualization and analysis platform of innate immunity. The in vivo inflammatory model described here reveals interconnections of innate immune pathways in specific responses to selected microbial stimuli. It also represents the starting point for studying ontogeny and regulation of inflammatory disorders in different physiological conditions.

Inside out Porphyridium cruentum: Beyond the Conventional Biorefinery Concept

Here, an unprecedented biorefinery approach has been designed to recover high-added value bioproducts starting from the culture ofPorphyridium cruentum. This unicellular marine red alga can secrete and accumulate high-value compounds that can find applications in a wide variety of industrial fields. 300 ± 67 mg/L of exopolysaccharides were obtained from cell culture medium; phycoerythrin was efficiently extracted (40% of total extract) and isolated by single chromatography, with a purity grade that allowed the crystal structure determination at 1.60 Å; a twofold increase in β-carotene yield was obtained from the residual biomass; the final residual biomass was found to be enriched in saturated fatty acids. Thus, for the first time, a complete exploitation ofP. cruentumculture was set up.

The antimicrobial peptide Magainin-2 interacts with BamA impairing folding of E. coli membrane proteins

Antimicrobial peptides (AMPs) are a unique and diverse group of molecules endowed with a broad spectrum of antibiotics properties that are being considered as new alternative therapeutic agents. Most of these peptides are membrane-active molecules, killing bacteria by membrane disruption. However, recently an increasing number of AMPs was shown to enter bacterial cells and target intracellular processes fundamental for bacterial life. In this paper we investigated the mechanism of action of Maganin-2 (Mag-2), a well-known antimicrobial peptide isolated from the African clawed frog Xenopus laevis, by functional proteomic approaches. Several proteins belonging to E. coli macromolecular membrane complexes were identified as Mag-2 putative interactors. Among these, we focused our attention on BamA a membrane protein belonging to the BAM complex responsible for the folding and insertion of nascent β-barrel Outer Membrane Proteins (OMPs) in the outer membrane. In silico predictions by molecular modelling, in vitro fluorescence binding and Light Scattering experiments carried out using a recombinant form of BamA confirmed the formation of a stable Mag-2/BamA complex and indicated a high affinity of the peptide for BamA. Functional implications of this interactions were investigated by two alternative and complementary approaches. The amount of outer membrane proteins OmpA and OmpF produced in E. coli following Mag-2 incubation were evaluated by both western blot analysis and quantitative tandem mass spectrometry in Multiple Reaction Monitoring scan mode. In both experiments a gradual decrease in outer membrane proteins production with time was observed as a consequence of Mag-2 treatment. These results suggested BamA as a possible good target for the rational design of new antibiotics since this protein is responsible for a crucial biological event of bacterial life and is absent in humans.

In vivo absorptomics: Identification of bovine milk-derived peptides in human plasma after milk intake

A dedicated two-step purification procedure prior to nanoliquid chromatography-electrospray-tandem mass spectrometry analysis enabled the identification of bovine milk-derived peptides absorbed and circulating in the plasma of three healthy volunteers who received 250 mL of pasteurized milk after a 10-days washout. The appearance and clearance of milk peptides in plasma were monitored at various time points. Overall, 758, 273 and 212 unique peptides derived from 15, 15 and 18 bovine milk proteins, respectively, were identified in the plasma of these volunteers, evidencing a substantial inter-individual variability. Peptides encrypting possible bioactive and/or immunogenic molecules originating from caseins, β-lactoglobulin and minor milk proteins were detected. Peptide representation data revealed the combined action of endoproteases involved in primary hydrolysis during gastroduodenal digestion and exopeptidases that hydrolyse peptides in the small intestine. It remains to be established whether the half-life and concentration ranges of circulating milk-derived peptides may have any impacts on human health.

An Endemic Plant of the Mediterranean Area: Phytochemical Characterization of Strawberry Tree (Arbutus unedo L.) Fruits Extracts at Different Ripening Stages

This work focused on the extraction, quantification, and characterization of bioactive compounds of Arbutus unedo L. fruits, comparing the results obtained from the different ripening states. Extractions were performed by different methods (such as maceration extraction and ultrasonic extraction) and food grade solvents (aqueous and hydroalcoholic solvents) in each of the all ripening states (four states considered, associated with four different colors, i.e., green, yellow, orange, and red). The presence of (poly)phenols was quantified and characterized, and scavenging activity was determined by the Folin–Ciocâlteu reagent and the DPPH method, respectively. The content of bioactive compounds was characterized by LC-MS/MS, such as multiple reaction monitoring (MRM) mass spectrometry. The results showed that ultrasound-assisted extraction (UAE) performed better than maceration extraction; ethanol–water mixture extracts showed a more positive effect than the use of aqueous extracts regarding the content of total phenolic compounds. Overall, the total phenolic compounds in the EtOH:H₂O mixture at a ratio of 7:3 (v:v) were higher than that of the other solvents for both extraction methods. Some bioactive molecules were characterized for the first time in the extracts of A. unedo. The chemical profile of the strawberry tree extracts depended on the degree of fruit ripeness. The results suggest that A. unedo fruits may be of great interest for food and nutraceutical applications.

POS0464 DIFFERENTIAL MOLECULAR PROFILES IN THE SYNOVIAL TISSUE AND SYNOVIAL FLUID OF PATIENTS WITH RHEUMATOID ARTHRITIS AND PSORIATIC ARTHRITIS

Background

The differential diagnosis of Rheumatoid Arthritis (RA) and Psoriatic arthritis (PsA) is often difficult due to the similarity of symptoms and the unavailability of reliable clinical biomarkers. Molecular alterations have been suggested to contribute to the pathophysiological processes in the knee joint, and it is known that chronic inflammation induces significant changes in the synovial tissue (ST) and synovial fluid (SF) lipidome and proteome.

Objectives

We aimed to evaluate whether specific characteristics in the molecular profiles from ST and SF could support the differential diagnosis of these diseases.

Methods

ST frozen samples of patients affected by RA (n=6), PsA (n=12) and control donors (n=10) were compared using Matrix-Assisted Laser Desorption Ionization Mass Spectrometry Imaging (MALDI-MSI) for spatially resolved lipid analysis. To this end, tissue sections were measured on a RapifleX MALDI-TOF/TOF instrument. Next, a targeted approach based on multiple reaction monitoring (MRM-MS) was performed to further validate the lipidomic alterations reported by MALDI-MSI between RA and PsA tissues. In this case, lipids extracted from SF (control donors (n=4), RA (n=21) and PsA (n=27)) were analyzed in a QTRAP 4000 mass spectrometer for the targeted analysis of 84 lipid species. Finally, a quantitative proteomic analysis was carried out on FFPE ST from RA (n=13), PsA (n=13) and controls (n=8) by nLC-MS/MS analysis using a TimsTOF Pro system (Bruker). Statistical analyses were performed using GraphPad Prism, Metaboanalyst and Perseus software.

Results

Lipid profiles in ST from PsA and RA were unequivocally distinguished by MALDI-MSI followed by PCA-DA, and were also different comparing with control tissues. Interestingly, several lipid species, including sphingomyelins, phosphatidylcholines (PC) and phosphatidylethanolamines (PE), presented the greatest separation power to classify RA and PsA tissue samples. ANOVA analysis found 35 lipid species significantly different among the study groups, most of them significantly increased in RA and PsA compared to controls. Particularly, 11 lipids showed higher levels in PsA tissues compared with RA, including several PC and PE. The spatial distribution of these PE species was associated with areas of the sublining layer with increased vascularity and inflammatory cell infiltrates, according to MALDI-MSI images. On the other hand, RA and PsA patients were also correctly classified based on the SF levels of all quantified lipid species according to PCA and clustering analysis. Finally, the proteomic analysis quantified around 2,500 distinct proteins in the ST, including several related with lipid metabolism. Near 300 proteins showed altered abundance in the pathological tissues compared to healthy controls (FDR 0.01%, Figure 1A), being the small subset increased in controls mainly extracellular matrix proteins. The comparison between RA and PsA ST led to the identification of a panel of 36 proteins discriminating the two tissues with high statistical significance (p-value <0.01). In this comparison, all proteins except two appeared increased in RA (Figure 1B). A discriminant analysis shows the usefulness of this protein panel to differentiate the two diseases (Figure 1C).

Figure 1.

Results from the proteomic analysis carried out on synovial tissues. A) Heatmap showing the differential protein profiles between synovial tissues (PsA and RA) and healthy controls (CTL), at FDR 0.01. B) Characteristic protein panel discriminating PsA and RA tissues (p-value < 0.01). C) Discriminant analysis performed using this protein panel.

Conclusion

Our study shows distinct molecular profiles between RA and PsA synovial tissue and synovial fluid, and reports potential clinically useful lipid and protein markers for the differential diagnosis of these diseases.

Disclosure of Interests

None declared.

LC-MS/MS-Based Quantification Method of Polyphenols for Valorization of Ancient Apple Cultivars from Cilento

Safeguarding the biodiversity of plant species is of fundamental importance for their defense against pests and diseases even through the maintenance and dissemination of ancient agricultural traditions rooted within the small rural environments. The investigation area of the current research covered some municipalities belonging to the "Parco Nazionale del Cilento e Vallo di Diano" including the sub-mountainous part of "Comunità Montana del Vallo di Diano (Salerno, Campania)". Fifteen ancient apple varieties were collected from local communities to be analyzed and compared to some commercially available apples. To this aim, a Folin-Ciocâlteu assay was preliminarily used to measure the total polyphenol content in both ancient and commercial apple cultivars. Then, a liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis in the multiple reaction monitoring (MRM) ion mode was then implemented to detect and quantify specific polyphenols and to obtain a molecular comparison of a wide panel of polyphenols. The main finding of the present work pointed out that ancient apple cultivars are richer than commercial ones in anthocyanins, dihydrochalcones, and chlorogenic acid, whose beneficial effects on health are widely known. Thus, the safeguarding of these ancient varieties is greatly encouraged for the richness of polyphenols crucial both for the defense of plants from insects and for remarkable nutraceutical properties, in addition to the need for germplasm conservation as a source of genetic variability.

Oxylipin profile in saliva from patients with cystic fibrosis reveals a balance between pro-resolving and pro-inflammatory molecules

Oxylipins are signaling molecules originated by fatty acids that modulate vascular and bronchial tone, bronchial secretion, cytokine production and immune cell activity. The unbalanced production of pro-inflammatory and pro-resolving (i.e., anti-inflammatory) oxylipins has a relevant role in the pathogenesis of pulmonary inflammation like in cystic fibrosis (CF). We analyzed by LC-MRM/MS 65 oxylipins and 4 fatty acids in resting saliva from 69 patients with CF and 50 healthy subjects (controls). The salivary levels of 48/65 oxylipins were significantly different between CF patients and controls. Among these, EpETE, DHET, 6ketoPGE1 and HDHA were significantly higher in saliva from CF patients than in controls. All these molecules display anti-inflammatory effects, i.e., releasing of bronchial and vascular tone, modulation of cytokine release. While 20-hydroxyPGF2A, PGB2, EpDPE, 9 K-12-ELA, bicyclo-PGE2, oleic acid, LTC4, linoleic acid, 15oxoEDE, 20 hydroxyPGE2 and DHK-PGD2/PGE2 (mostly associated to pro-inflammatory effects) resulted significantly lower in CF patients than in controls. Our data suggest that the salivary oxylipins profile in CF patients is addressed toward a global anti-inflammatory effect. Although these findings need be confirmed on larger populations in prospective studies, they will contribute to better understand the pathogenesis of CF chronic inflammation and to drive targeted therapies based on the modulation of oxylipins synthesis and degradation.

Modulation of Plasma Proteomic Profile by Regular Training in Male and Female Basketball Players: A Preliminary Study

Monitoring fatigue and recovery during training periods contributes to identifying the best training methods to achieve sports performance. To date, little is known about sex-related differences in sports adaptations. The aim of the present study is to identify sex-related sports adaptation proteins in female basketball players and male basketball players using proteomics approach on plasma samples withdrawn from athletes during in-season training period but far from a competition. A cohort of 20 professional basketball players, 10 female (BF) and 10 male (BM), and 20 sedentary male (10 CM) and female (10 CF) as control, of comparable age and BMI, were involved in this study. Protein profiles of plasma samples obtained from BM, BF, CM, and CF were analyzed by two-dimensional electrophoresis (2-DE). Differentially expressed proteins were identified by mass spectrometry. The computational 2-DE gel image analysis pointed out 33 differentially expressed protein spots (ANOVA p-value < 0.05) and differences between male and female basketball players are more evident among the players than controls. The expression profile of 54.5% of the total proteins is affected by sports activity. Furthermore, 14 proteins are differentially expressed in basket female players in comparison with their relative controls while seven are differentially expressed in basket male players in comparison with their controls. In conclusion, we identify in female athletes a reduction in proteins related to transcription regulation, most of these modulate chronic inflammation confirming the anti-inflammatory effect of regular training in female muscle metabolism. In male and female athletes, we found a decrease in Transthyretin involved in muscle homeostasis and regeneration and Dermcidin a stress-induced myokine linked to inflammatory and it will be interesting to fully understand the role of its different isoforms in male and female skeletal muscle contraction.

Relationships between Sex and Adaptation to Physical Exercise in Young Athletes: A Pilot Study

The purpose of this study was to compare the redox, hormonal, metabolic, and lipid profiles of female and male basketball players during the seasonal training period, compared to their relative sedentary controls. 20 basketball players (10 female and 10 male) and 20 sedentary controls (10 female and 10 male) were enrolled in the study. Oxidative stress, adiponectin level, and metabolic profile were determined. Male and female athletes showed an increased antioxidant capacity (27% for males; 21% for females) and lactate level (389% for males; 460% for females) and reduced salivary cortisol (25% for males; 51% for females) compared to the sedentary controls. Moreover, a peculiar metabolite (in particular, amino acids and urea), hormonal, and lipidic profile were highlighted in the two groups of athletes. Female and male adaptations to training have several common traits, such as antioxidant potential enhancement, lactate increase, and activation of detoxifying processes, such as the urea cycle and arachidonic pathways as a response to inflammation. Moreover, we found different lipid and amino acid utilization related to sex. Deeper investigation could help coaches in developing training programs based on the athletes’ sex in order to reduce the drop-out rate of sporting activity by girls and fight the gender stereotypes in sport that also have repercussions in social fields.

Identification of SARS-CoV-2 Proteins from Nasopharyngeal Swabs Probed by Multiple Reaction Monitoring Tandem Mass Spectrometry

Numerous reverse transcription polymerase chain reaction (RT-PCR) tests have emerged over the past year as the gold standard for detecting millions of cases of SARS-CoV-2 reported daily worldwide. However, problems with critical shortages of key reagents such as PCR primers and RNA extraction kits and unpredictable test reliability related to high viral replication cycles have triggered the need for alternative methodologies to PCR to detect specific COVID-19 proteins. Several authors have developed methods based on liquid chromatography with tandem mass spectrometry (LC-MS/MS) to confirm the potential of the technique to detect two major proteins, the spike and the nucleoprotein, of COVID-19. In the present work, an S-Trap mini spin column digestion protocol was used for sample preparation prodromal to LC-MS/MS analysis in multiple reactions monitoring ion mode (MRM) to obtain a comprehensive method capable of detecting different viral proteins. The developed method was applied to n. 81 oro/nasopharyngeal swabs submitted in parallel to quantitative reverse transcription PCR (RT-qPCR) assays to detect RdRP, the S and N genes specific for COVID-19, and the E gene for all Sarbecoviruses, including SARS-CoV-2 (with cycle negativity threshold set to 40). A total of 23 peptides representative of the six specific viral proteins were detected in the monitoring of 128 transitions found to have good ionic currents extracted in clinical samples that reacted differently to the PCR assay. The best instrumental response came from the FLPFQFGR sequence of spike [558-566] peptide used to test the analytical performance of the method that has good sensitivity with a low false-negative rate. Transition monitoring using a targeted MS approach has the great potential to detect the fragmentation reactions of any peptide molecularly defined by a specific amino acid sequence, offering the extensibility of the approach to any viral sequence including derived variants and thus providing insights into the development of new types of clinical diagnostics.

Inflammation protein quantification by multiple reaction monitoring mass spectrometry in lipopolysaccharide-stimulated THP-1 cells

RATIONALE

Inflammation is a cascade of events mediated by a cytokine network triggering the cellular response. In order to monitor the modulation of the crucial inflammatory proteins, e.g., Tumour Necrosis Factor-α (TNF-α), Interferon-γ (INF-γ), Interleukin-8 (IL-8) and Interleukin-10 (IL-10), upon stimulation with endotoxins, differentiated and undifferentiated THP-1 cells were treated with lipopolysaccharides (LPSs) from E. coli, key cell wall components of Gram-negative bacteria.

METHODS

The multiple reaction monitoring mass spectrometry (MRM-MS) method was optimized by using the standard proteins to be quantified, in order to construct external calibration curves and define the analytical parameters. The developed method was used to quantify the above-mentioned inflammatory proteins in THP-1 differentiated cells upon stimulation with LPSs with high accuracy, sensitivity, and robustness.

RESULTS

The analysis of such proteins in MRM mode allowed the kinetics of stimulation along the time up to 24 h to be followed and the MS results were found to be comparable with those obtained by Western-blotting. A significant increase in TNF-α release triggered a cascade mechanism leading to the production of INF-γ and IL-8. IL-10, instead, was found to be constant throughout the process.

CONCLUSIONS

The developed MRM-MS method allowed the quantification of TNF-α, INF-γ, IL-8 and IL-10 along a time-course from 2 to 24 h. Hence, a trace of the kinetics of the inflammatory response in THP-1 cells upon stimulation with E. coli LPSs was obtained. Finally, the extensibility of the developed MRM method to serum samples and other matrices demonstrated the versatility of the approach and the possibility to quantify multiple target proteins in different biological samples by using a few microliters in a single analysis.

Transcatheter aortic valve replacement in severe aortic stenosis and cardiac amyloidosis: a systematic review and meta-analysis

Background

Aortic stenosis (AS) and cardiac amyloidosis (CA) are typical degenerative diseases of the elderly. According to recent studies, up to 16% of patients referred to transcatheter aortic valve replacement (TAVR) have a concomitant diagnosis of CA. Until recently, TAVR in patients with CA and AS has been considered futile, following the results of small observational studies. However, few studies recently suggested a beneficial impact of TAVR in patients with AS and CA as compared with medical therapy alone.

Purpose

To clarify the efficacy and safety profile of TAVR in CA-AS patients.

Methods

We performed a systematic review and meta-analysis of studies evaluating the risk of mortality after TAVR in CA-AS patients as compared with medical therapy. Moreover, we performed a systematic review and descriptive meta-analysis of studies reporting outcomes and complication rates of TAVR in CA-AS patients as compared with patients with AS alone.

Results

We identified 4 observational studies reporting data on mortality in CA-AS patients treated with either TAVR or medical therapy. Mortality was significantly lower in patients undergoing TAVR (OR 0.23, 95% CI 0.07–0.73, I2=0%, NNT=2.6) as compared with medical therapy. A sensitivity analysis with hazard ratio as effect estimate showed consistent results. Then, we identified 4 observational studies reporting data on mortality, re-hospitalizations and periprocedural complications of TAVR in CA-AS patients as compared with patients with AS alone. We found higher rates of mortality, cardiovascular hospitalization and need for permanent pacemaker implantation in CA-AS patients as compared to lone AS patients undergoing TAVR. Conversely, no differences were found in terms of stroke, acute kidney injury and vascular complications.

Conclusions

Our analysis rejects the idea of futility of TAVR in CA-AS patients showing a clear survival benefit of CA-AS patients undergoing TAVR as compared with medical therapy. Moreover, these patients may undergo TAVR with an acceptable procedural risk, that is substantially comparable to lone AS patients, except for a higher incidence of permanent pacemaker implantation.

Funding Acknowledgement

Type of funding sources: None.

Why Consumers Prefer Green Friariello Pepper: Changes in the Protein and Metabolite Profiles Along the Ripening

Fruit ripening is a physiologically complex process altering texture, color, flavor, nutritional value, and aroma. However, some fruits are consumed at an early stage of ripening due to the very peculiar characteristics varying during ripening. An example is a particular ecotype of pepper, the Friariello pepper, among the most important representatives of Campania (Southern Italy) agro-alimentary culture. In this study, for the first time, the physiological variations during Friariello ripening (green, veraison, and fully ripe) were evaluated by hyphenated mass spectrometric techniques in a proteomic and metabolomic approach. We found that Lutein and Thaumatin are particularly abundant in the green Friariello. Friariello at an early stage of ripening, is rich in volatile compounds like butanol, 1 3 5-cycloheptatriene, dimethylheptane, α-pinene, furan-2-penthyl, ethylhexanol, 3-carene, detected by gas chromatography-mass spectrometry (GC-MS) analysis, which give it the peculiar fresh and pleasant taste. The detected features of Friariello may justify its preferential consumption in the early ripening stage and outline new knowledge aimed at preserving specific agro-cultural heritage.

Polyphenol Profiling of Chestnut Pericarp, Integument and Curing Water Extracts to Qualify These Food By-Products as a Source of Antioxidants

Plant polyphenols have beneficial antioxidant effects on human health; practices aimed at preserving their content in foods and/or reusing food by-products are encouraged. The impact of the traditional practice of the water curing procedure of chestnuts, which prevents insect/mould damage during storage, was studied to assess the release of polyphenols from the fruit. Metabolites extracted from pericarp and integument tissues or released in the medium from the water curing process were analyzed by matrix-assisted laser desorption ionization-time of flight-mass spectrometry (MALDI-TOF-MS) and electrospray-quadrupole-time of flight-mass spectrometry (ESI-qTOF-MS). This identified: (i) condensed and hydrolyzable tannins made of (epi)catechin (procyanidins) and acid ellagic units in pericarp tissues; (ii) polyphenols made of gallocatechin and catechin units condensed with gallate (prodelphinidins) in integument counterparts; (iii) metabolites resembling those reported above in the wastewater from the chestnut curing process. Comparative experiments were also performed on aqueous media recovered from fruits treated with processes involving: (i) tap water; (ii) tap water containing an antifungal Lb. pentosus strain; (iii) wastewater from a previous curing treatment. These analyses indicated that the former treatment determines a 6–7-fold higher release of polyphenols in the curing water with respect to the other ones. This event has a negative impact on the luster of treated fruits but qualifies the corresponding wastes as a source of antioxidants. Such a phenomenon does not occur in wastewater from the other curing processes, where the release of polyphenols was reduced, thus preserving the chestnut’s appearance. Polyphenol profiling measurements demonstrated that bacterial presence in water hampered the release of pericarp metabolites. This study provides a rationale to traditional processing practices on fruit appearance and qualifies the corresponding wastes as a source of bioactive compounds for other nutraceutical applications.

Evaluation of the Thermal Inactivation of a Salmonella Serotype Oranienburg Strain During Cocoa Roasting at Conditions Relevant to the Fine Chocolate Industry

Cocoa roasting produces and enhances distinct flavor of chocolate and acts as a critical control point for inactivation of foodborne pathogens in chocolate production. In this study, the inactivation kinetics of Salmonella enterica subsp. enterica serotype Oranienburg strain was assessed on whole cocoa beans using roasting protocols relevant to the fine chocolate industry. Beans were inoculated with 10⁷-10⁸ log₁₀ CFU/bean of Salmonella Oranienburg and roasted at 100-150°C for 2-100 min. A greater than 5 log₁₀ reduction of S. Oranienburg was experimentally achieved after 10-min roasting at 150°C. Data were fitted using log-linear and Weibull models. The log-linear models indicated that the roasting times (D) needed to achieve a decimal reduction of Salmonella at 100, 110, 115, 120, 130, and 140°C were 33.34, 18.57, 12.92, 10.50, 4.20, and 1.90 min, respectively. A Weibull model indicated a decrease in the Salmonella inactivation rate over time (β < 1). Statistical analysis indicated that the Weibull model fitted the data better compared to a log-linear model. These data demonstrate the efficacy of cocoa roasting in inactivation of Salmonella and may be used to guide food safety decision-making.

From untargeted metabolomics to the multiple reaction monitoring-based quantification of polyphenols in chocolates from different geographical areas

Plants, including cocoa bean, are the main source of metabolites with multiple biological functions. Polyphenol extracts are widely used as a nutraceutical supplement for their well-known health-promoting role. In this paper, a preliminary untargeted metabolic screening was carried out by matrix-assisted laser desorption/ionization (MALDI)-time of flight (TOF)/TOF on a pool of chocolate samples made by cocoa beans of different geographical areas. Then, a targeted approach was developed for polyphenol quantification by an optimized Liquid chromatography (LC)-tandem mass spectrometry (MS/MS) method multiple reaction monitoring (MRM) ion mode. Detection limit of polyphenol standard ranged between 1 and 25 pg/μl with variation coefficient lower than 15%. External calibration curves were used for quantification of polyphenols in 18 samples. Fifty polyphenols were detected in a single LC-MRM/MS run and quantified by monitoring almost 90 transitions in a 5-minute run. The polyphenols content of different cocoa beans from several countries was finally compared by principal component analysis (PCA) statistical analysis suggesting that the chocolate made by Ecuador cocoa beans showed the highest level of polyphenols.

Follicular microenvironment: Oxidative stress and adiponectin correlated with steroids hormones in women undergoing in vitro fertilization

Research has been focused on determining the follicular microenviroment produced by the theca and granulosa cells since the molecular characterisation of this body fluid could lead to the understanding of several fertility problems. Oxidative stress may be one of the factors involved in female infertility since it plays a key role in the modulation of oocyte maturation and finally pregnancy. An increase in oxidative stress is correlated with inflammation and intense research was developed to understand the interaction between inflammation and adiponectin, based on the fact that many adipokines are inflammation related proteins linked to reactive oxygen species production. The aim of this study is to investigate the correlation between total adiponectin levels and oxidative stress amount in the serum and follicular fluid (FF) of women who undergone in vitro fertilization. Moreover we verified the expression of adiponectin in granulosa and cumulus cells. To clarify the predictive value of steroid hormones in human assisted reproduction, twelve steroid hormones in FF and serum, were quantified in a single run liquid chromatography/mass spectrometry, by using a multiple reaction monitoring mode and we related the serum and follicular fluids adiponectin levels with the concentration of the investigated steroid hormones.

Enhancing AI-guided STEMI detection algorithms by incorporating higher quality fiduciary EKG elements

Background

As EKG interpretation paradigms to a physician-free milieu, accumulating massive quantities of distilled pre-processed data becomes a must for machine learning techniques. In our pursuit of reducing ischemic times in STEMI management, we have improved our Artificial Intelligence (AI)-guided diagnostic tool by following a three-step approach: 1) Increase accuracy by adding larger clusters of data. 2) Increase the breadth of EKG classifications to provide more precise feedback and further refine the inputs which ultimately reflects in better and more accurate outputs. 3) Improving the algorithms' ability to discern between cardiovascular entities reflected in the EKG records.

Purpose

To bolster our algorithm's accuracy and reliability for electrocardiographic STEMI recognition.

Methods

Dataset: A total of 7,286 12-lead EKG records of 10-seconds length with a sampling frequency of 500 Hz obtained from Latin America Telemedicine Infarct Network from April 2014 to December 2019. This included the following balanced classes: angiographically confirmed STEMI, branch blocks, non-specific ST-T abnormalities, normal, and abnormal (200+ CPT codes, excluding the ones included in other classes). Labels of each record were manually checked by cardiologists to ensure precision (Ground truth). Pre-processing: First and last 250 samples were discarded to avoid a standardization pulse. Order 5 digital low pass filters with a 35 Hz cut-off was applied. For each record, the mean was subtracted to each individual lead. Classification: Determined classes were “STEMI” and “Not-STEMI” (A combination of randomly sampled normal, branch blocks, non-specific ST-T abnormalities and abnormal records – 25% of each subclass). Training & Testing: A 1-D Convolutional Neural Network was trained and tested with a dataset proportion of 90/10, respectively. The last dense layer outputs a probability for each record of being STEMI or Not-STEMI. Additional testing was performed with a subset of the original complete dataset of unconfirmed STEMI. Performance indicators (accuracy, sensitivity, and specificity) were calculated for each model and results were compared with our previous findings from past experiments.

Results

Complete STEMI data: Accuracy: 95.9% Sensitivity: 95.7% Specificity: 96.5%; Confirmed STEMI: Accuracy: 98.1% Sensitivity: 98.1% Specificity: 98.1%; Prior Data obtained in our previous experiments are shown below for comparison.

Conclusion(s)

After the addition of clustered pre-processed data, all performance indicators for STEMI detection increased considerably between both Confirmed STEMI datasets. On the other hand, the Complete STEMI dataset kept a strong and steady set of performance metrics when compared with past results. These findings not only validate the consistency and reliability of our algorithm but also connotes the importance of creating a pristine dataset for this and any other AI-derived medical tools.

Funding Acknowledgement

Type of funding source: None

Waddling beyond door to balloon times and impinging true ischemic times with artificial intelligence-guided single lead EKG for STEMI detection

Background

The present process of STEMI detection is cumbersome as it utilizes outdated equipment and requires a trained technician and an expert cardiologist. We have developed a patient-administered, Artificial Intelligence (AI) guided, Single Lead EKG for early STEMI detection.

Purpose

To answer the question “Is early STEMI detection possible with a Single Lead EKG?”

Methods

We experimented with an AI-guided algorithm for a single-lead EKG for STEMI detection with the following step-wise developments: 1) An AI algorithm that predictably interprets STEMI using a 12-lead EKG; 2) An AI algorithm for STEMI detection using a single-lead EKG; 3) A methodology for identifying the best single lead to detect STEMI; 4) Advanced AI algorithms for STEMI localization with a single-lead EKG. The AI methodology was as follows: Sample: The mammoth Latin American Telemedicine Infarct Network telemedicine database that provides an umbrella of AMI management to 100 million patients in Brazil, Colombia, Mexico, Chile, and Argentina was queried for cardiologist annotated EKG. A total of 8,511 EKG and 90,592 classified heartbeats were selected for the experiments. Preprocessing: segmentation of each ECG into individual heartbeats. Training & Testing: 90% and 10%, respectively, of the total dataset. Classification: 1-D Convolutional Neural Network; classes were construed for each heartbeat. Performance indicators were calculated per lead.

Results

The algorithm was able to provide an accuracy of 91.9%. Lead V2 yielded the best results among individual leads for STEMI detection.

Conclusions

Early experiments provide a framework for augmenting STEMI detection with the use of AI-guided, single lead techniques. Such approaches seem rational as we target the reduction of true STEMI ischemic times.

Funding Acknowledgement

Type of funding source: None

Maximum artificial intelligence and complete reconstruct of population-based AMI care

Background

After creating a behemoth hub and spoke AMI network that encompasses more than 100 million patients in 5 countries, we have begun to incorporate Artificial Intelligence (AI) algorithms into our telemedicine strategy with the goal of creating comprehensive, very early AMI diagnosis and physician-free triage. In doing so, we have replaced door-to-balloon times (d2b) with symptom-to-balloon times (s2b) as an immutable objective.

Purpose

To incorporate AI attributes for very early AMI detection, triage, and management.

Methods

We expanded our effective telemedicine strategy (100 million population; 877,178 telemedicine encounters; 55% overall mortality reduction; $291 million cost savings) with a logistic reset to impact s2b. To do this, we incorporated our Single Lead 1.0 (lead I) and Single Lead 2.0 (lead V2) technology for self-administered AMI detection with our physician-free STEMI diagnosis and triage AI algorithms. Single Lead algorithms and physician-free protocols were generated by utilizing Machine Learning from our mammoth annotated EKG repository.

Results

In addition to three logistic markers of efficiency Time-to-Telemedicine Diagnosis (TTD), Door-In-Door-Out (DIDO) and Transfer Times (TT); we are monitoring s2b. A gradual release of the algorithms and single lead is occurring at the telemedicine spokes. Detailed results will be available at the time of presentation.

Conclusions

Impacting s2b, the Achilles Heel of Primary PCI, may be achieved with the use of patient-administered AMI detection tools. Incorporation of these technologies into AI algorithms will add to telemedicine efficiencies for population-based AMI care.

Funding Acknowledgement

Type of funding source: None

Moving in sync – concordance betweena artificial intelligence and cardiologist on detecting normal electrocardiograms

Background

Merging modern technologies with classic diagnostic tests often results in a sense of insecurity within the medical community, particularly so with potentially life-saving studies such as the electrocardiogram (EKG). In order to provide a greater sense of trust between Artificial Intelligence (AI) and cardiologists, we provide an AI-driven algorithm capable of accurately and reliably characterize an EKG as normal within a highly complex, cardiologist-reviewed EKG database and report the degree of concordance between this machine vs physician scenario.

Purpose

To provide a dependable and accurate AI algorithm that conducts EKG interpretation in a cardiologist-tier manner.

Methods

The International Telemedical System (ITMS) developed and tested an EKG assessing AI algorithm and incorporated it into the workflow of their Telemedicine Integrated Platform, a digital EKG reading program where cardiologists continuously report their findings remotely in real-time. During the month of April 2,019; 35 ITMS cardiologists reported a grand total of 61,441 EKG records, later submitting them to the AI algorithm implemented through the “One Click Report” process. Through this simple 2-step approach, the algorithm provides a suggestion of “Normal” or “Abnormal” to the cardiologist based on the patterns of the fiducial points included in said EKG reports. Confirmation of these suggestions by the cardiologists ensued.

Results

Overall, cardiologists confirmed 23,213 out of 25,013 AI outputs for “Normal” EKGs, demonstrating a concordance of 92.8% for Normal diagnosis.

Conclusion

Through this methodology, we provide an AI technology that can be reliably applied and trusted in EKG digital platforms to identify and suitably label a normal EKG. Further testing will accrue into a multi label algorithm compatible with abnormal cardiovascular entities, potentially precluding the role of the cardiologist for triaging, particularly in the prehospital setting. We anticipate that this approach will become a promising methodology in modern cardiology practice.

Funding Acknowledgement

Type of funding source: None

Innovative techniques to construct powerful artificial intelligence algorithms for st-elevation myocardial infarction

Background

With the sudden advent of Artificial Intelligence (AI), incorporation of these technologies into key aspects of our working environment has become an ever so delicate task, especially so when dealing with time-sensitive and potentially lethal scenarios such as ST-Elevation Myocardial Infarction (STEMI) management. By further expanding into our successful experiences with AI-guided algorithms for STEMI detection, we implemented an innovative ensemble method into our methodology as we seek to improve the algorithm's predictive capabilities.

Purpose

Through the ensemble method, we combined two ML techniques to boost our previous experiments' accuracy and reliability.

Methods

Database: EKG records obtained from Latin America Telemedicine Infarct Network (Mexico, Colombia, Argentina, and Brazil) from April 2014 to December 2019. Dataset: Two separate datasets were used to train and test two sets of AI algorithms. The first comprised of 11,567 records and the second 7,286 records, each composed of 12-lead EKG records of 10-second length with sampling frequency of 500 Hz, including the following balanced classes: unconfirmed & angiographically confirmed STEMI (first model); angiographically confirmed STEMI only (second model); and, for both models, we included branch blocks, non-specific ST-T abnormalities, normal, and abnormal (200+ CPT codes, excluding the ones included in other classes). Label per record was manually checked by cardiologists to ensure precision (Ground truth). Pre-processing: First and last 250 samples were discarded to avoid a standardization pulse. An order 5 digital low pass filter with a 35 Hz cut-off was applied. For each record, the mean was subtracted to each individual lead. Classification: The determined classes were STEMI and Not-STEMI (A combination of randomly sampled normal, branch blocks, non-specific ST-T abnormalities and abnormal records – 25% of each subclass). Training & Testing: The last dense layer outputs a probability for each record of being STEMI or Not-STEMI. These probabilities were calculated for each model (Model 1 trained with Complete STEMI dataset and Model 2 trained with confirmed STEMI only dataset) and aggregated using the mean aggregation to generate the final label for each record. A 1-D Convolutional Neural Network was trained and tested with a dataset proportion of 90%/10%; respectively. Results are reported for both testing datasets (Complete and confirmed STEMI only records).

Results

Complete STEMI Dataset: Accuracy: 96.5% Sensitivity: 96.2% Specificity: 96.9% – Confirmed STEMI only Dataset: Accuracy: 98.5% Sensitivity: 98.3% Specificity: 98.6%'

Conclusion(s)

While Model 1 and Model 2 achieved similar performances with promising results on their own, applying a combination of both through the ensemble model exhibits a clear improvement in performance when applied to both datasets. This provides a blueprint for advanced automated STEMI detection through wearable devices.

Funding Acknowledgement

Type of funding source: None

Artificial intelligence methodology: multi-label classification of abnormal EKG records

Background

Our previous experience with Artificial Intelligence (AI)-conducted EKG characterization displayed outstanding results in fast and reliable identification of Normal EKGs within the International Telemedical System (ITMS)'s massive record repository. By expanding the array of recognizable cardiovascular entities, we upgraded our methodology to accurately discriminate an anomaly amongst a highly complex database of EKG records.

Purpose

To present a feasible AI-guided filter that can accurately discriminate and classify Normal and Abnormal EKG records within a multilabeled cardiologist-annotated EKG database.

Methods

ITMS developed and tested the “One Click”' process, a “Normal/Abnormal” EKG assessing AI algorithm, by incorporating it into their digital EKG reading platform where cardiologists continuously report their findings remotely in real time. To ameliorate the diagnostic range of the algorithm, a separate dataset of 121,641 12-lead EKG records was consolidated from the ITMS database from October 2011 to January 2019. Only de-identified data was used. Preprocessing: The first 2s of each short lead and 9s of the long lead were considered. Limb leads I, II and III; and precordial leads V1, V2, V3, and V5 were used. The mean was removed from each lead. AI models/Classification: Two models were created and tested independently based on the method of EKG acquisition (69,852 records transtelephonic [TTP]; 52,259 mobile transmission [MOB]). Each record is categorized into six disjoint classes based on the most common types of cardiac disorders (Low/null co-occurrence pathologies in these datasets were grouped into analogous groups). Training/Testing: Distribution of both sets per transmission type was performed through a greedy algorithm, which identified multiple diagnoses per EKG record and labeled it separately to the corresponding group, ensuring sufficient samples per class. Detailed class distribution is shown below. An inception convolutional neural network was implemented; “Normal” or “Abnormal” labels were assigned to each EKG record independently and were compared to cardiologists' reports; performance indicators were calculated for each model and group.

Results

MOB model accrued an average accuracy of 86.7%; sensitivity of 90.5%; and specificity of 83.9%. TTP model yielded an average accuracy of 77.2%; sensitivity of 91.1%; and specificity of 69.4% (Lower values were attributed to the “Ventricular Complexes” group, which challenged the algorithm by having a smaller ratio of abnormal exams). Detailed results of each training set are shown below.

Conclusion

Providing an effective and reliable multilabel-capable EKG triaging tool remains a challenging but attainable goal. Continuous systematic enhancement of our AI-driven methodology has led us to satisfactory, yet imperfect results which compel us to further study and improve our efforts to provide a trustworthy cardiologist-friendly triage device.

Funding Acknowledgement

Type of funding source: None

Tautomeric and conformational switching in a new versatile N-rich heterocyclic ligand

A new N-rich triazolo-triazole derivative, 4-methyl-7-(pyrazin-2-yl)-2H-[1,2,4]triazolo[3,2-c][1,2,4]triazole (C8H7N7), bearing a pyrazine residue at 7-position of the triazolo-triazole bicycle, was synthesized, and its acid-base and metal coordination properties were evaluated in solution. The results showed amphoteric behavior and the formation of stable complexes with Cu(ii) and Zn(ii) in pH intervals in which the ligand is neutral or deprotonated. Computational studies were performed in order to evaluate the stability of the different tautomers/conformers of the ligand, and the proton position in the neutral and acidic forms. Single crystal X-ray analysis of the free neutral ligand (2H/s-trans tautomer/conformer), and of its singly protonated (2H-3H/s-trans), doubly protonated (2H-3H-7H/s-trans) and deprotonated forms showed that the influence of the pyrazine ring on the triazolo-triazole system is mainly as electron withdrawing and chelating group, and proton acceptor. Different coordination modes have been evidenced for the neutral and deprotonated ligand. Upon metal coordination, the neutral ligand switches from 2H/s-trans to 3H/s-cis tautomer/conformer forming five-membered chelate rings, while the anionic deprotonated ligand forms six-membered chelate rings in the s-trans conformation. Altogether, five different tautomers/conformers of the ligand were isolated and characterized. In vitro tests confirmed the general antiproliferative activity of triazolo-triazole compounds and the importance of substitution in position 7 for their selectivity.

Relationship between the metabolic and lipid profile in follicular fluid of women undergoing in vitro fertilization

Among the follicular fluid (FF) components promoting the development of the oocyte are included glycoproteins, several fatty acids, and steroid hormones synthesized by the dominant follicle. For this, the analysis of the metabolites present in FF can determine the quality of the oocyte. FF composition is in part determined by local follicular metabolic processes and in part a plasma transudate. Since the causes of impaired fertility may be due to a metabolic imbalance, metabolomics is useful to identify low molecular weight metabolites. Oxidative stress is involved in human infertility and the use of metabolomics can be crucial to identify which other metabolites besides reactive oxygen species are involved in oxidative stress correlated to infertility. To obtain new information on the study of signaling molecules in FF, the knowledge of the lipid content will be important to improve information on the understanding of follicular development. The objective of this study is to identify (a) a metabolic profile and a lipid profile of FF in women undergoing in vitro fertilization and (b) to correlate the previous information obtained regarding adiponectin and oxidative stress with the metabolic and lipid profile obtained in the present study. As result, we found an increase in oxidative stress due to both an increase of androgens and an accumulation of lipids in the follicular environment and we suggest that this might be one of the causes of reduced fertility.

Proteolysis and Process-Induced Modifications in Synbiotic Yogurt Investigated by Peptidomics and Phosphopeptidomics

Probiotic and synbiotic yogurt preparations were manufactured at the semi-industrial pilot scale with Lactobacillus acidophilus and Bifidobacteria strains without inulin or fortified with 1 and 3% (w/w) inulin. The pathway of casein breakdown was determined in probiotic, synbiotic, conventional yogurt, and nonstarted milk base using HPLC-ESI-MS/MS-based peptidomics and phosphopeptidomics; in the latter case, casein phosphorylated peptides (CPPs) were previously enriched by hydroxyapatite chromatography. Compared with traditional yogurt, casein proteolysis increased in probiotic and even more in synbiotic yogurt with 1% inulin. Fortification with 3% inulin greatly modified the proteolytic pattern, indicating a characteristic contribution of probiotics to proteolysis. The enhanced proteolysis in synbiotic yogurt exposed the neo-formed peptides to progressively increase enzymatic or chemical modifications, such as dephosphorylation of CPPs, methionine oxidation, and formation of N-terminal pyroglutamic acids. These modifications might constitute molecular signature descriptors of metabolic processes mediated by complex bacterial communities, with technological, nutritional, and sensorial significance.

Loss of Function of the Gene Encoding the Histone Methyltransferase KMT2D Leads to Deregulation of Mitochondrial Respiration

KMT2D encodes a methyltransferase responsible for histone 3 lysine 4 (H3K4) mono-/di-methylation, an epigenetic mark correlated with active transcription. Here, we tested the hypothesis that KMT2D pathogenic loss-of-function variants, which causes the Kabuki syndrome type 1, could affect the mitochondrial metabolic profile. By using Seahorse technology, we showed a significant reduction of the mitochondrial oxygen consumption rate as well as a reduction of the glycolytic flux in both Kmt2d knockout MEFs and skin fibroblasts of Kabuki patients harboring heterozygous KMT2D pathogenic variants. Mass-spectrometry analysis of intermediate metabolites confirmed alterations in the glycolytic and TCA cycle pathways. The observed metabolic phenotype was accompanied by a significant increase in the production of reactive oxygen species. Measurements of the specific activities of the mitochondrial respiratory chain complexes revealed significant inhibition of CI (NADH dehydrogenase) and CIV (cytochrome c oxidase); this result was further supported by a decrease in the protein content of both complexes. Finally, we unveiled an impaired oxidation of glucose and larger reliance on long-chain fatty acids oxidation. Altogether, our findings clearly indicate a rewiring of the mitochondrial metabolic phenotype in the KMT2D-null or loss-of-function context that might contribute to the development of Kabuki disease, and represents metabolic reprogramming as a potential new therapeutic approach.

Quantification of Polyphenols and Metals in Chinese Tea Infusions by Mass Spectrometry

Chemical compounds within tea (Camellia sinensis) are characterized by an extensive heterogeneity; some of them are crucial for their protective and defensive role in plants, and are closely connected to the benefits that the consumption of tea can provide. This paper is mainly focused on the characterization of polyphenols (secondary metabolites generally involved in defense against ultraviolet radiation and aggression by pathogens) and metals, extracted from nine Chinese tea samples, by integrating different mass spectrometry methodologies, LC-MS/MS in multiple reaction monitoring (MRM) and inductively coupled plasma mass spectrometry (ICP-MS). Our approach allowed to identify and compare forty polyphenols differently distributed in tea infusions at various fermentation levels. The exploration of polyphenols with nutraceutical potential in tea infusions can widely benefit especially tea-oriented populations. The worldwide consumption of tea requires at the same time a careful monitoring of metals released during the infusion of tea leaves. Metal analysis can provide the identification of many healthy minerals such as potassium, sodium, calcium, magnesium, differently affected by the fermentation of leaves. Our results allowed us: (i) to draw up a polyphenols profile of tea leaves subjected to different fermentation processes; (ii) to identify and quantify metals released from tea leaves during infusion. In this way, we obtained a molecular fingerprint useful for both nutraceutical applications and food control/typization, as well as for frauds detection and counterfeiting.

Change in renal function post-nephrectomy for renal cell carcinoma in patients with and without hypertension and/or diabetes

BACKGROUND

The standard of care for surgically resectable disease renal cell carcinoma (RCC) is a nephrectomy. Post-nephrectomy, these patients are at risk for the development of new onset chronic kidney disease or the progression of pre-existing chronic kidney disease. We aimed to report the changes in renal function in patients who had a nephrectomy for RCC.

METHODS

This retrospective, descriptive, cross-sectional study identified 137 patients who had a nephrectomy for RCC from 1 January 2009 to 31 December 2017. The pre-nephrectomy and post-nephrectomy estimated glomerular filtration rate (eGFR) and the histological subtype of RCC on histopathological analysis of the resected specimen were recorded from the National Health Laboratory Services online results platform. All analyses were conducted using SPSS (Version 25) and the significance level was set at p < 0.05.

RESULTS

After a mean follow-up period of 26.5 ± 22 months (median = 19 months), the patients' eGFR dropped by a mean of 4.82 ± 8.67 ml/min/1.73 m2 (95% CI 3.23-6.41) post-nephrectomy. The mean eGFR fall in patients' who had hypertension and/or diabetes (n = 63) was significantly larger compared to patients who had neither of these comorbidities (n = 54; p < .001; mean = 7.30 ± 8.40 ml/min/1.73 m2 (95% CI 5.19-9.42) and 1.93 ± 8.14 ml/min/1.73 m2 (95% CI 0.30-4.15) respectively.

CONCLUSIONS

The decline in renal function in patients with hypertension and/or diabetes mellitus is more pronounced than in patients with neither of these comorbidities. In these high-risk patients, measures must be taken to prevent the development and limit the progression of chronic kidney disease.

Label-free quantitative proteomics of the MCF-7 cellular response to a ferritin–metallodrug complex

Schematic summary of the experimental workflow based on label-free quantitative proteomics.

A multi-scale time-resolved study of photoactivated dynamics in 5-benzyl uracil, a model for DNA/protein interactions

We combine fluorescence up-conversion and time correlated single photon counting experiments to investigate the 5-benzyl uracil excited state dynamics in methanol from 100 fs up to several ns. This molecule has been proposed as a model for DNA/protein interactions. Our results show emission bands at about 310 and 350 nm that exhibit bi-exponential sub-ps decays. Calculations, including solvent effects by a mixed discrete-continuum model, indicate that the Franck Condon region is characterized by significant coupling between the excited states of the benzyl and the uracil moieties, mirrored by the short-lived emission at 310 nm. Two main ground state recovery pathways are identified, both contributing to the 350 nm emission. The first 'photophysical' decay path involves a ππ* excited state localized on the uracil and is connected to the ground electronic state by an easily accessible crossing with S0, accounting for the short lifetime component. Simulations indicate that a possible second pathway is characterized by exciplex formation, with partial benzene → uracil charge transfer character, that may lead instead to photocyclization. The relevance of our results is discussed in view of the photoactivated dynamics of DNA/protein complexes, with implications on their interaction mechanisms.

P6422Physician vs machine: an innovative ST-elevation myocardial infarction pathway through artificial intelligence

Background

The diagnosis of ST-Elevation Myocardial Infarction (STEMI) has traditionally relied on a cardiologist's interpretation of an Electrocardiogram (EKG). This cumbersome process is costly, inefficient and out of date. Artificial Intelligence (AI) -guided algorithms can provide point-of-care, accurate STEMI diagnosis that will facilitate STEMI management.

Purpose

To demonstrate the feasibility of an automated AI-guided EKG analysis for STEMI diagnosis.

Methods

An observational, retrospective, case-control study. Sample: 8,511 EKG cardiologist-annotated records, including 4,255 STEMI cases. Records excluded patient and medical information. The sample was derived from the private International Telemedical Systems (ITMS) database. LUMENGT-AI Algorithm was employed. Preprocessing: detection of QRS complexes by wavelet system, segmentation of each EKG into individual heartbeats (90,592 total beats) with fixed window of 0.4s to the left and 0.9s to the right of main QRS; Classification: A 1-D convolutional neural network was implemented, “STEMI” and “Not-STEMI” classes were considered for each heartbeat, individual probabilities were aggregated to generate the final label for each record. Training & Testing: 90% and 10% of the sample were used, respectively. Experiments: Intel PC i7 8750H processor at 2.21GHz, 16GB RAM, Windows 10 OS with NVidia GTX 1070 GPU, 8GB RAM.

Results

The model achieved an accuracy of 96.5%, with a sensitivity of 96.3%, and a specificity of 96.8%.

Conclusion(s)

1) AI-guided interpretation of the EKG can reliably diagnose STEMI; 2) AI algorithms can be incorporated into ambulance systems for pre-hospital diagnosis, single page activation, emergency department bypass, facilitating more efficient STEMI pathways.

P1524Women are from venus and face barriers for AMI treatment

Background

The Latin American Telemedicine Infarct Network (LATIN), a program for managing population-based AMI care, has utilized an innovative hub-spoke strategy and remote guidance to expand medical access in remote parts of Brazil, Colombia, Mexico, and Argentina. Based on the Global Lumen Organization for Women (GLOW) project, that has previously demonstrated gender inequalities and worse outcomes for women who undergo Primary PCI, our research explored the management of female patients in our network.

Purpose

To demonstrate gender disparities in a telemedicine-guided, population based AMI program.

Methods

Meta-analysis of >750,000 patients within LATIN. Telemedicine was employed as a screening tool to accurately diagnose AMI. According to the duration of chest pain and transfer time, AMI patients were triaged into guidelines-based pathways of thrombolysis, pharmaco-invasive management or Primary PCI. Resource allocation was identical for men and women.

Results

Data from 784,395 screened patients reveals broad gender disparities. The critical results yielded that female patients have a lower prevalence of STEMI diagnosis and treatment regardless of the technique – PCI, pharmaco-invasive or CABG (p<0.01). These findings assume more significance given the fact that more women than men, were screened through the Telemedicine pathway.

Conclusions

LATIN gender data signals the urgency to demand better AMI care for women.

P3352Telemedicine transcends national boundaries in quest of creating a behemoth ami program

Background

The Latin America Telemedicine Infarct Network (LATIN) has exploited the remarkable competence of telemedicine for remote guidance. In doing so, LATIN created a mammoth population-based AMI network that employed experts located several hundred miles away to guide the reperfusion strategies for almost 800,000 screened patients. In this pioneering project, telemedicine was initially utilized to guide AMI management within national confines. We speculated whether LATIN telemedicine navigation could outstrip countrywide borders.

Purpose

To maximally harness the vast possibilities of telemedicine for improving AMI care.

Methods

During its pilot phase, LATIN began as a hub and spoke, AMI system in Colombia where 20 spokes (small community health centers and rural clinics) were configured with 3 hubs that could perform Primary PCI. These sites were linked through web-based connectivity. Expert cardiologists, located 50–250 miles away in Bogota, Colombia, used sophisticated telemedicine platforms for urgent EKG diagnosis and teleconsultation of the entire AMI process. Based upon the duration of chest pain and travel time to the hub, these experts guided patients through guideline-based strategies of thrombolysis, pharmaco invasive management or primary PCI. Efficiency of the telemedicine process was measured with the new metric of time to telemedicine diagnosis (TTD). Cloud computing, GPS navigation, and numerous business intelligent tools were gradually incorporated into LATIN telemedicine. As systems became more scalable, the program was expanded to Brazil, where LATIN flourished. Over the last 18 months, LATIN telemedicine capabilities have been pressed across national boundaries. Presently, all 82 LATIN centers in Mexico are guided by experts located in Bogota, Colombia and the 7 Argentina centers channeled through Santiago, Chile.

Results

784,947 patients were screened for AMI at 350 LATIN centers (Brazil 143, Colombia 118, Mexico 82, Argentina 7). Navigation pathways are depicted in the attached figure. TTD remains extremely low in all four countries, and comparable efficiency and tele-accuracy have been achieved. With expanded geographic reach, 8,448 (1.08%) patients were diagnosed with STEMI and 3,911 (46.3%) urgently reperfused, including 3,049 (78%) with Primary PCI. Time to TTD ranged between 2.8 to 5.8 minutes, with a mean of 3.5 min. Tele-accuracy was 98.5%, D2B 51 min, and in-hospital mortality 5.2%. Various other comparative metrics for the 4 countries are being gathered and will be available at the time of presentation.

Conclusions

LATIN demonstrates the robust ability of telemedicine to transcend national boundaries to guide AMI management. This strategy can be adopted in under-developed countries in Asia and Africa to provide an umbrella of AMI care for the millions of disadvantaged patients.