New bioactive hydrogenated linderazulene-derivatives from the gorgonian Echinogorgia complexa

[EN] Chemical analysis of the secondary metabolite pattern of the gorgonian Echinogorgia complexa, collected along South Indian coasts, showed the presence of two new tricyclic guaiane furanosesquiterpenes, iso-echinofuran (3) and 8,9-dihydro-linderazulene (4), co-occurring with the known echinofuran (5) and structurally related to the pigment linderazulene (1). The unprecedented molecules 3 and 4 were characterized by spectral methods, mainly by NMR techniques. Compounds 3¿5 displayed moderate activity in the mitochondrial respiratory chain inhibition assay.Manzo, E.; Ciavatta, ML.; López-Gresa, MP.; Gavagnin, M.; Villani, G.; Naik, CG.; Cimino, G. (2007). New bioactive hydrogenated linderazulene-derivatives from the gorgonian Echinogorgia complexa. Tetrahedron Letters. 48(14):2569-2571. https://doi.org/10.1016/j.tetlet.2007.02.020S25692571481

Fine-Grained Emotion Recognition Using Brain-Heart Interplay Measurements and eXplainable Convolutional Neural Networks

Emotion recognition from electro-physiological signals is an important research topic in multiple scientific domains. While a multimodal input may lead to additional information that increases emotion recognition performance, an optimal processing pipeline for such a vectorial input is yet undefined. Moreover, the algorithm performance often compromises between the ability to generalize over an emotional dimension and the explainability associated with its recognition accuracy. This study proposes a novel explainable artificial intelligence architecture for a 9-level valence recognition from electroencephalographic (EEG) and electrocardiographic (ECG) signals. Synchronous EEG-ECG information are combined to derive vectorial brain-heart interplay features, which are rearranged in a sparse matrix (image) and then classified through an explainable convolutional neural network. The proposed architecture is tested on the publicly available MAHNOB dataset also against the use of vectorial EEG input. Results, also expressed in terms of confusion matrices, outperform the current state of the art, especially in terms of recognition accuracy. In conclusion, we demonstrate the effectiveness of the proposed approach embedding multimodal brain-heart dynamics in an explainable fashion

Improving Emotion Recognition Systems by Exploiting the Spatial Information of EEG Sensors

Electroencephalography (EEG)-based emotion recognition is gaining increasing importance due to its potential applications in various scientific fields, ranging from psychophysiology to neuromarketing. A number of approaches have been proposed that use machine learning (ML) technology to achieve high recognition performance, which relies on engineering features from brain activity dynamics. Since ML performance can be improved by utilizing 2D feature representation that exploits the spatial relationships among the features, here we propose a novel input representation that involves re-arranging EEG features as an image that reflects the top view of the subject’s scalp. This approach enables emotion recognition through image-based ML methods such as pre-trained deep neural networks or "trained-from-scratch" convolutional neural networks. We have employed both of these techniques in our study to demonstrate the effectiveness of our proposed input representation. We also compare the recognition performance of these methods against state-of-the-art tabular data analysis approaches, which do not utilize the spatial relationships between the sensors. We test our proposed approach using two publicly available benchmark datasets for EEG-based emotion recognition tasks, namely DEAP and MAHNOB-HCI. Our results show that the "trained-from-scratch" convolutional neural network outperforms the best approaches in the literature, achieving 97.8% and 98.3% accuracy in valence and arousal classification on MAHNOB-HCI, and 91% and 90.4% on DEAP, respectively

Cytosporin-related compounds from the marine-derived fungus Eutypella scoparia

[EN] Chemical investigation of the culture broth of the fungus Eutypella scoparia ICB-OBX, isolated from the marine pulmonate mollusc Onchidium sp., led to the finding of novel compounds 1 and 2, structurally related to angiotensin II binding inhibitors cytosporins, along with unrelated known nitrogen metabolites (compounds 3¿5). The structure and the relative stereochemistry of the novel metabolites were assigned mainly by a detailed analysis of two-dimensional NMR techniques whereas the absolute stereochemistry was proposed by modified Mosher's method. Compound 2 contains an unusual cyclic carbonate functionality that is rare among natural products.Ciavatta, ML.; López-Gresa, MP.; Gavagnin, M.; Nicoletti, R.; Manzo, E.; Mollo, E.; Guo, Y.... (2008). Cytosporin-related compounds from the marine-derived fungus Eutypella scoparia. Tetrahedron. 64(22):5365-5369. https://doi.org/10.1016/j.tet.2008.03.016S53655369642

Differential Toll like receptor expression in cystic fibrosis patients' airways during rhinovirus infection

Objectives: Since an inappropriate and sustained activation of TLRs may contribute to a chronic inflammatory response resulting in detrimental effects in cystic fibrosis (CF) patients, we sought to examine whether HRV infection might alter the respiratory expression of TLRs according to the microbiological status of CF patients. Methods: Respiratory samples were collected from the respiratory tract of CF patients (n = 294) over a period of 12 months. In addition to the usual microbiological investigation, HRV-RNA detection and typing were performed by RT-PCR and sequencing. HRV viral load and TLRs levels were measured by RT-Real Time PCR. Results: HRV-RNA was detected in 80 out of 515 respiratory samples (15.5%) with a similar rate in all age groups (0–10 years, 11–24 years, ≥ 25 years). Patients infected with different HRV A, B and C species exhibited higher levels of TLR2, TLR4 and TLR8 as compared to HRV negative patients. Moreover, the expression level of TLR2, TLR4 and TLR8 correlated with high level of HRV viral load. HRV positive patients co-colonized by Staphylococcus aureus or Pseudomonas aeruginosa showed also enhanced amounts of TLR2 and TLR2/4-mRNAs expression respectively. In the case of presence of both bacteria, TLR2, TLR4, TLR8 and TLR9 levels are elevated in positive HRV patients. Conclusions: TLRs, especially TLR2 and TLR4, increased in HRV positive CF individuals and varies according to the presence of S. aureus, P. aeruginosa and both bacteria

New caulerpenyne-derived metabolites of an Elysia sacoglossan from the south indian coast

[EN] Chemical analysis of the secondary metabolite pattern of the sacoglossan mollusc Elysia cf. expansa, collected along South Indian coasts, showed the presence of the typical Caulerpa-derived sesquiterpene caulerpenyne (1) and two new minor co-occurring metabolites, the compounds dihydrocaulerpenyne (4) and expansinol (5). The chemical characterization of these molecules, structurally related to 1, is reported.We thank ICB Mass Service and ICB NMR Service Centre (Mrs. D. Melck is kindly acknowledged), Mr. C. Iodice for spectrophotometric measurements and Mr. R. Turco for graphical work. This work was partially supported by a bilateral CNR-CSIR project.Ciavatta, ML.; López-Gresa, MP.; Gavagnin, M.; Manzo, E.; Mollo, E.; D Souza, L.; Cimino, G. (2006). New caulerpenyne-derived metabolites of an Elysia sacoglossan from the south indian coast. Molecules. 11(10):808-816. doi:10.3390/11100808S808816111

SARS-CoV-2 Entry Genes Expression in Relation with Interferon Response in Cystic Fibrosis Patients

The expression rate of SARS-CoV-2 entry genes, angiotensin-converting enzyme 2 (ACE2), the main viral receptor and the proteases, furin and transmembrane serine protease 2 (TMPRSS2) in cystic fibrosis (CF) individuals is poorly known. Hence, we examined their levels in upper respiratory samples of CF patients (n = 46) and healthy controls (n = 45). Moreover, we sought to understand the interplay of type I interferon (IFN-I) with ACE2, furin and TMPRSS2 by evaluating their gene expression with respect to ISG15, a well-known marker of IFN activation, in upper respiratory samples and after ex vivo IFNβ exposure. Lower ACE2 levels and trends toward the reduction of furin and TMPRSS2 were found in CF patients compared with the healthy controls; decreased ACE2 amounts were also detected in CF individuals with pancreatic insufficiency and in those receiving inhaled antibiotics. Moreover, there was a strong positive correlation between ISG15 and ACE2 levels. However, after ex vivo IFNβ stimulation of nasopharyngeal cells, the truncated isoform (dACE2), recently demonstrated as the IFN stimulated one with respect to the full-length isoform (flACE2), slightly augmented in cells from CF patients whereas in those from healthy donors, dACE2 levels showed variable levels of upregulation. An altered expression of SARS-COV-2 entry genes and a poor responsiveness of dACE2 to IFN-I stimulation might be crucial in the diffusion of SARS-CoV-2 infection in CF

Assignment of Absolute Configuration of Bis-[gamma]-pyrone Polypropionates from Marine Pulmonate Molluscs

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The Comprehensive Complication Index (CCI®) is a Novel Cost Assessment Tool for Surgical Procedures

OBJECTIVE The aim of this study was to identify a readily available, reproducible, and internationally applicable cost assessment tool for surgical procedures. SUMMARY OF BACKGROUND DATA Strong economic pressure exists worldwide to slow down the rising of health care costs. Postoperative morbidity significantly impacts on cost in surgical patients. The comprehensive complication index (CCI), reflecting overall postoperative morbidity, may therefore serve as a new marker for cost. METHODS Postoperative complications and total costs from a single tertiary center were prospectively collected (2014 to 2016) up to 3 months after surgery for a variety of abdominal procedures (n = 1388). CCI was used to quantify overall postoperative morbidity. Pearson correlation coefficient (rpears) was calculated for cost and CCI. For cost prediction, a linear regression model based on CCI, age, and type of surgery was developed and validated in an international cohort of patients. RESULTS We found a high correlation between CCI and overall cost (rpears = 0.75) with the strongest correlation for more complex procedures. The prediction model performed very well (R = 0.82); each 10-point increase in CCI corresponded to a 14% increase to the baseline cost. Additional 12% of baseline cost must be added for patients older than 50 years, or 24% for those over 70 years. The validation cohorts showed a good match of predicted and observed cost. CONCLUSION Overall postoperative morbidity correlates highly with cost. The CCI together with the type of surgery and patient age is a novel and reliable predictor of expenses in surgical patients. This finding may enable objective cost comparisons among centers, procedures, or over time obviating the need to look at complex country-specific cost calculations (www.assessurgery.com)