Unsupervised protein family classification by Density Peak clustering

As the UniProt database approaches the 200 million entries\u2019 mark, the vast majority of proteins it contains lack any experimental validation of their functions. In this context, the identification of homologous relationships between proteins remains the single most widely applicable tool for generating functional and structural hypotheses in silico. Although many databases exist that classify proteins and protein domains into homologous families, large sections of the sequence space remain unassigned. In this thesis we introduce DPCfam, a new unsupervised procedure that uses sequence alignments and Density Peak Clustering to automatically classify homologous protein regions. After a proof-of-principle experiment of the method based on the analysis of two clans from the Pfam protein family database and, we present an all-to-all clustering of the UniRef50 database, containing ~23,000,000 proteins. In both cases we present the DPCfam implementations: in particular present the strategies adopted to write a parallel and optimized implementation of the algorithm, needed to cluster the massive number of sequences in UniRef50. We develop specific measures to assess the quality of DPCfam's clusters, both in terms of boundaries and homology, using the Pfam database as a reference. Our tests indicate that DPCfam automatically-generated clusters are generally evolutionary accurate corresponding to one or more Pfam families and that they cover a significant fraction of known homologs. Moreover, find possible candidates for new family (around 14,000 when clustering UniRef50). Overall, DPCfam shows potential both for assisting manual annotation efforts (domain discovery, detection of classification inconsistencies, improvement of family coverage and boosting of clan membership) and as a stand-alone tool for unsupervised classification of sparsely annotated protein datasets such as those from environmental metagenomics studies (domain discovery, analysis of domain diversity)

Fluctuation properties in random walks on networks and simple integrate and fire models

In questa tesi si è studiato l’insorgere di eventi critici in un semplice modello neurale del tipo Integrate and Fire, basato su processi dinamici stocastici markoviani definiti su una rete. Il segnale neurale elettrico è stato modellato da un flusso di particelle. Si è concentrata l’attenzione sulla fase transiente del sistema, cercando di identificare fenomeni simili alla sincronizzazione neurale, la quale può essere considerata un evento critico. Sono state studiate reti particolarmente semplici, trovando che il modello proposto ha la capacità di produrre effetti "a cascata" nell’attività neurale, dovuti a Self Organized Criticality (auto organizzazione del sistema in stati instabili); questi effetti non vengono invece osservati in Random Walks sulle stesse reti. Si è visto che un piccolo stimolo random è capace di generare nell’attività della rete delle fluttuazioni notevoli, in particolar modo se il sistema si trova in una fase al limite dell’equilibrio. I picchi di attività così rilevati sono stati interpretati come valanghe di segnale neurale, fenomeno riconducibile alla sincronizzazione

The intrinsic dimension of protein sequence evolution

It is well known that, in order to preserve its structure and function, a protein cannot change its sequence at random, but only by mutations occurring preferentially at specific locations. We here investigate quantitatively the amount of variability that is allowed in protein sequence evolution, by computing the intrinsic dimension (ID) of the sequences belonging to a selection of protein families. The ID is a measure of the number of independent directions that evolution can take starting from a given sequence. We find that the ID is practically constant for sequences belonging to the same family, and moreover it is very similar in different families, with values ranging between 6 and 12. These values are significantly smaller than the raw number of amino acids, confirming the importance of correlations between mutations in different sites. However, we demonstrate that correlations are not sufficient to explain the small value of the ID we observe in protein families. Indeed, we show that the ID of a set of protein sequences generated by maximum entropy models, an approach in which correlations are accounted for, is typically significantly larger than the value observed in natural protein families. We further prove that a critical factor to reproduce the natural ID is to take into consideration the phylogeny of sequences

Macedonian Speech Synthesis for Assistive Technology Applications

Speech technology is becoming ever more ubiquitous with the advance of speech enabled devices and services. The use of speech synthesis in Augmentative and Alternative Communication tools, has facilitated inclusion of individuals with speech impediments allowing them to communicate with their surroundings using speech. Although there are numerous speech synthesis systems for the most spoken world languages, there is still a limited offer for smaller languages. We propose and compare three models built using parametric and deep learning techniques for Macedonian trained on a newly recorded corpus. We target low-resource edge deployment for Augmentative and Alternative Communication and assistive technologies, such as communication boards and screen readers. The listening test results show that parametric speech synthesis is as performant compared to the more advanced deep learning models. Since it also requires less resources, and offers full speech rate and pitch control, it is the preferred choice for building a Macedonian TTS system for this application scenario.Comment: 5 pages, 1 figure, EUSIPCO conference 202

Genetic lineage tracing reveals poor angiogenic potential of cardiac endothelial cells.

Abstract Aims Cardiac ischaemia does not elicit an efficient angiogenic response. Indeed, lack of surgical revascularization upon myocardial infarction results in cardiomyocyte death, scarring, and loss of contractile function. Clinical trials aimed at inducing therapeutic revascularization through the delivery of pro-angiogenic molecules after cardiac ischaemia have invariably failed, suggesting that endothelial cells in the heart cannot mount an efficient angiogenic response. To understand why the heart is a poorly angiogenic environment, here we compare the angiogenic response of the cardiac and skeletal muscle using a lineage tracing approach to genetically label sprouting endothelial cells. Methods and results We observed that overexpression of the vascular endothelial growth factor in the skeletal muscle potently stimulated angiogenesis, resulting in the formation of a massive number of new capillaries and arterioles. In contrast, response to the same dose of the same factor in the heart was blunted and consisted in a modest increase in the number of new arterioles. By using Apelin-CreER mice to genetically label sprouting endothelial cells we observed that different pro-angiogenic stimuli activated Apelin expression in both muscle types to a similar extent, however, only in the skeletal muscle, these cells were able to sprout, form elongated vascular tubes activating Notch signalling, and became incorporated into arteries. In the heart, Apelin-positive cells transiently persisted and failed to give rise to new vessels. When we implanted cancer cells in different organs, the abortive angiogenic response in the heart resulted in a reduced expansion of the tumour mass. Conclusion Our genetic lineage tracing indicates that cardiac endothelial cells activate Apelin expression in response to pro-angiogenic stimuli but, different from those of the skeletal muscle, fail to proliferate and form mature and structured vessels. The poor angiogenic potential of the heart is associated with reduced tumour angiogenesis and growth of cancer cells

Antimicrobial potential of resveratrol nanobelt-like particles

The emergence of microbial resistance to commonly used antibiotics has induced search for novel antimicrobial agents. As natural sources have already provided many of the conventional drugs, they can also be a basis for new ones. Resveratrol is a stilbenoid polyphenol, synthesized by plants as a protective compound. Among its’ many biological activities, antimicrobial have often been reported. On the other hand, there are several obstacles for the practical use of this compound, among them solubility and general difficulty of efficient delivery. Nanotechnology has allowed recent progress regarding the use of many natural compounds. However, it usually relies on the use of additional expensive or toxic compounds during the synthesis of nanoparticles. In our research, we used simple, green synthesis to prepare nanoparticles of pure resveratrol, in a nanobelt-like form. Shape, uniform size and absence of carrier substances made these particles convenient for the implementation of resveratrol for different purposes. We tested their potential to inhibit the growth of several bacterial strains, reference and clinical, and one micromycetes strain. For the determination of antibacterial effect, we used microdilution method followed by optical density measurements, resazurin staining and agar plating, to determine effect on growth, as well as minimal inhibitory and minimal bactericidal concentration. In case of microfungal cultures, we used MTT staining for the testing. There were significant differences in the effects, between gram-positive and gram-negative bacteria, and microfungi. While the concentration that led to the inhibition of growth of Staphylococci was 800 μg/ml, the growth of gram-negative bacteria was inhibited only at several times higher concentrations. Aspergillus caespitosus showed significantly higher sensitivity, with MIC/MBC being 200 μg/ml. These results indicated possible use of these particles in further biomaterial design as an additive component with moderate antimicrobial activity

Particle bound pollutants in rivers: Results from suspended sediment sampling in Globaqua River Basins

Transport of hydrophobic pollutants in rivers such as polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs) and heavy metals is often facilitated by suspended sediment particles, which are typically mobilized during high discharge events. Suspended sediments thus represent a means of transport for particle related pollutants within river reaches and may represent a suitable proxy for average pollutant concentrations estimation in a river reach or catchment. In this study, multiple high discharge/turbidity events were sampled at high temporal resolution in the Globaqua River Basins Sava (Slovenia, Serbia), Adige (Italy), and Evrotas (Greece) and analysed for persistent organic pollutants such as PAHs (polycyclic aromatic hydrocarbons) or PCBs (polychlorinated biphenyls) and heavy metals. For comparison, river bed sediment samples were analysed as well. Further, results are compared to previous studies in contrasting catchments in Germany, Iran, Spain, and beyond. Overall results show that loadings of suspended sediments with pollutants are catchment-specific and relatively stable over time at a given location. For PAHs, loadings on suspended particles mainly correlate to urban pressures (potentially diluted by sediment mass fluxes) in the rivers, whereas metal concentrations mainly display a geogenic origin. By cross-comparison with known urban pressure/sediment yield relationships (e.g. for PAHs) or soil background values (for metals) anthropogenic impact – e.g. caused by industrial activities – may be identified. Sampling of suspended sediments gives much more reliable results compared to sediment grab samples which typically show a more heterogeneous contaminant distribution. Based on mean annual suspended sediment concentrations and distribution coefficients of pollutants the fraction of particle facilitated transport versus dissolved fluxes can be calculated

Electrophysiological neuromuscular alterations and severe fatigue predict long-term muscle weakness in survivors of COVID-19 acute respiratory distress syndrome

IntroductionLong-term weakness is common in survivors of COVID-19-associated acute respiratory distress syndrome (CARDS). We longitudinally assessed the predictors of muscle weakness in patients evaluated 6 and 12 months after intensive care unit discharge with in-person visits.MethodsMuscle strength was measured by isometric maximal voluntary contraction (MVC) of the tibialis anterior muscle. Candidate predictors of muscle weakness were follow-up time, sex, age, mechanical ventilation duration, use of steroids in the intensive care unit, the compound muscle action potential of the tibialis anterior muscle (CMAP-TA-S100), a 6-min walk test, severe fatigue, depression and anxiety, post-traumatic stress disorder, cognitive assessment, and body mass index. We also compared the clinical tools currently available for the evaluation of muscle strength (handgrip strength and Medical Research Council sum score) and electrical neuromuscular function (simplified peroneal nerve test [PENT]) with more objective and robust measures of force (MVC) and electrophysiological evaluation of the neuromuscular function of the tibialis anterior muscle (CMAP-TA-S100) for their essential role in ankle control.ResultsMVC improved at 12 months compared with 6 months. CMAP-TA-S100 (P = 0.016) and the presence of severe fatigue (P = 0.036) were independent predictors of MVC. MVC was strongly associated with handgrip strength, whereas CMAP-TA-S100 was strongly associated with PENT.DiscussionElectrical neuromuscular abnormalities and severe fatigue are independently associated with reduced MVC and can be used to predict the risk of long-term muscle weakness in CARDS survivors

Burden of non-communicable diseases among adolescents aged 10–24 years in the EU, 1990–2019: a systematic analysis of the Global Burden of Diseases Study 2019

Background: Disability and mortality burden of non-communicable diseases (NCDs) have risen worldwide; however, the NCD burden among adolescents remains poorly described in the EU. Methods: Estimates were retrieved from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. Causes of NCDs were analysed at three different levels of the GBD 2019 hierarchy, for which mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) were extracted. Estimates, with the 95% uncertainty intervals (UI), were retrieved for EU Member States from 1990 to 2019, three age subgroups (10–14 years, 15–19 years, and 20–24 years), and by sex. Spearman's correlation was conducted between DALY rates for NCDs and the Socio-demographic Index (SDI) of each EU Member State. Findings: In 2019, NCDs accounted for 86·4% (95% uncertainty interval 83·5–88·8) of all YLDs and 38·8% (37·4–39·8) of total deaths in adolescents aged 10–24 years. For NCDs in this age group, neoplasms were the leading causes of both mortality (4·01 [95% uncertainty interval 3·62–4·25] per 100 000 population) and YLLs (281·78 [254·25–298·92] per 100 000 population), whereas mental disorders were the leading cause for YLDs (2039·36 [1432·56–2773·47] per 100 000 population) and DALYs (2040·59 [1433·96–2774·62] per 100 000 population) in all EU Member States, and in all studied age groups. In 2019, among adolescents aged 10–24 years, males had a higher mortality rate per 100 000 population due to NCDs than females (11·66 [11·04–12·28] vs 7·89 [7·53–8·23]), whereas females presented a higher DALY rate per 100 000 population due to NCDs (8003·25 [5812·78–10 701·59] vs 6083·91 [4576·63–7857·92]). From 1990 to 2019, mortality rate due to NCDs in adolescents aged 10–24 years substantially decreased (–40·41% [–43·00 to –37·61), and also the YLL rate considerably decreased (–40·56% [–43·16 to –37·74]), except for mental disorders (which increased by 32·18% [1·67 to 66·49]), whereas the YLD rate increased slightly (1·44% [0·09 to 2·79]). Positive correlations were observed between DALY rates and SDIs for substance use disorders (rs=0·58, p=0·0012) and skin and subcutaneous diseases (rs=0·45, p=0·017), whereas negative correlations were found between DALY rates and SDIs for cardiovascular diseases (rs=–0·46, p=0·015), neoplasms (rs=–0·57, p=0·0015), and sense organ diseases (rs=–0·61, p=0·0005). Interpretation: NCD-related mortality has substantially declined among adolescents in the EU between 1990 and 2019, but the rising trend of YLL attributed to mental disorders and their YLD burden are concerning. Differences by sex, age group, and across EU Member States highlight the importance of preventive interventions and scaling up adolescent-responsive health-care systems, which should prioritise specific needs by sex, age, and location. Funding: Bill & Melinda Gates Foundation