University of Bologna
  • Bologna, BO, Italy
Recent publications
Due to growing traffic demand, aging civil infrastructure raises the need for reliable tools to monitor structural health conditions, usable to plan informed maintenance and emergency management. Several structures with historical and monumental importance are instrumented with structural health monitoring (SHM) systems nowadays. However, even the failure of “minor” viaducts could endanger the safety of travelers and goods. Lately, dense wireless sensor networks (WSNs) based on MEMS devices are used to cut costs and simplify the deployment of SHM systems while collecting as much information as possible. However, dense WNSs are affected by data management, synchronization, and battery replacement issues, which make them unappealing for widespread use. This study presents an original damage identification algorithm based on sparse sensor networks. Traveling vehicles are exploited to obtain spatial information and accurately identify the location of structural anomalies. The curvature influence line of the monitored bridge can be calculated by processing the acceleration response measured at a given instrumented location through a low-pass filter. In this procedure, sensors operate individually, not needing energy-consuming synchronization. The proposed identification algorithm is verified on real data collected on a steel truss bridge subject to artificially induced damage.
The analysis of dynamic systems via statistical models built on the measured data is the core idea of the so–called System Identification (SysId), i.e. a methodology which has proven to be one of the most effective tools for spectral analysis and, by extension, for the analysis of vibrating structures. In practical scenarios, where the operational and environmental uncertainties might be responsible for significant, additive noise levels, models more sophisticated than the standard ones are required. This requirement can be efficiently pursued via Errors–In–Variables (EIV) systems, which offer a powerful means to precisely tackling inherent disturbances hidden within real signals. In this work, we overcome the limitations of the classical implementation of output–only EIV models in the time domain by adopting a novel frequency domain approach defined in the Frisch scheme to solve, in a more direct way, the trade–off between frequency resolution and noise level. When applied for vibration diagnostics of a large-scale structure (i.e., a wind turbine blade prototype), the novel EIV–based SysId strategy proved significant accuracy in tracking frequency–related structural changes. Thus, it can be considered as a promising strategy for vibration assessment thanks to its reduced computational complexity and the quality of the retrieved spectral signature.
Aiming at finding natural sources of antidiabetics agents, 15 extracts from Brazilian medicinal plants of the Atlantic Forest and Amazon region were tested against α-glucosidase enzyme. Plants were selected based on the taxonomic relationships with genera including several species with antidiabetic activity. In this screening, the extracts obtained from the flowers of Hyptis monticola and the leaves of Lantana trifolia and Lippia origanoides resulted endowed with promising anti-α-glucosidase activity. The extracts from H. monticola and from L. origanoides collected in two different areas, were characterised by ultra-high performance liquid chromatography coupled to mass spectrometry. Bioassay-guided fractionation led to the identification of several enzyme inhibiting compounds, among them the mechanism of action of naringenin and pinocembrin was investigated. The two L. origanoides extracts showed differences in bioactivity and in the phytochemical profiles. The fractionation of the extract from H. monticola led to a partial loss of the inhibitory effect.
An in-vitro model of human bone marrow mesenchymal stem cells (hBM-MSCs) myogenic commitment by synergic effect of a differentiation media coupled with human primary skeletal myoblasts (hSkMs) co-culture was developed adopting both conventional static co-seeding and perfused culture systems. Static co-seeding provided a notable outcome in terms of gene expression with a significant increase of Desmin (141-fold) and Myosin heavy chain II (MYH2, 32-fold) at day 21, clearly detected also by semi-quantitative immunofluorescence. Under perfusion conditions, myogenic induction ability of hSkMs on hBM-MSCs was exerted by paracrine effect with an excellent gene overexpression and immunofluorescence detection of MYH2 protein; furthermore, due to the dynamic cell culture in separate wells, western blot data were acquired confirming a successful cell commitment at day 14. A significant increase of anti-inflammatory cytokine gene expression, including IL-10 and IL-4 (15-fold and 11-fold, respectively) at day 14, with respect to the pro-inflammatory cytokines IL-12A (7-fold at day 21) and IL-1β (1.4-fold at day 7) was also detected during dynamic culture, confirming the immunomodulatory activity of hBM-MSCs along with commitment events. The present study opens interesting perspectives on the use of dynamic culture based on perfusion as a versatile tool to study myogenic events and paracrine cross-talk compared to the simple co-seeding static culture.
The fast diffusion of the SARS-CoV-2 pandemic have called for an equally rapid evolution of the therapeutic options. The Human recombinant monoclonal antibodies (mAbs) have recently been approved by the Food and Drug Administration (FDA) and by the Italian Medicines Agency (AIFA) in subjects aged ≥12 with SARS-CoV-2 infection and specific risk factors. Currently the indications are specific for the use of two different mAbs combination: Bamlanivimab+Etesevimab (produced by Eli Lilly) and Casirivimab+Imdevimab (produced by Regeneron). These drugs have shown favorable effects in adult patients in the initial phase of infection, whereas to date few data are available on their use in children. AIFA criteria derived from the existing literature which reports an increased risk of severe COVID-19 in children with comorbidities. However, the studies analyzing the determinants for progression to severe disease are mainly monocentric, with limited numbers and reporting mostly generic risk categories. Thus, the Italian Society of Pediatrics invited its affiliated Scientific Societies to produce a Consensus document based on the revision of the criteria proposed by AIFA in light of the most recent literature and experts’ agreement. This Consensus tries to detail which patients actually have the risk to develop severe disease, analyzing the most common comorbidities in children, in order to detail the indications for mAbs administration and to guide the clinicians in identifying eligible patients.
Background Domestication of the rabbit ( Oryctolagus cuniculus ) has led to a multi-purpose species that includes many breeds and lines with a broad phenotypic diversity, mainly for external traits (e.g. coat colours and patterns, fur structure, and morphometric traits) that are valued by fancy rabbit breeders. As a consequence of this human-driven selection, distinct signatures are expected to be present in the rabbit genome, defined as signatures of selection or selective sweeps. Here, we investigated the genome of three Italian commercial meat rabbit breeds (Italian Silver, Italian Spotted and Italian White) and 12 fancy rabbit breeds (Belgian Hare, Burgundy Fawn, Champagne d’Argent, Checkered Giant, Coloured Dwarf, Dwarf Lop, Ermine, Giant Grey, Giant White, Rex, Rhinelander and Thuringian) by using high-density single nucleotide polymorphism data. Signatures of selection were identified based on the fixation index (F ST ) statistic with different approaches, including single-breed and group-based methods, the latter comparing breeds that are grouped based on external traits (different coat colours and body sizes) and types (i.e. meat vs. fancy breeds). Results We identified 309 genomic regions that contained signatures of selection and that included genes that are known to affect coat colour ( ASIP , MC1R and TYR ), coat structure ( LIPH ), and body size ( LCORL / NCAPG , COL11A1 and HOXD ) in rabbits and that characterize the investigated breeds. Their identification proves the suitability of the applied methodologies for capturing recent selection events. Other regions included novel candidate genes that might contribute to the phenotypic variation among the analyzed breeds, including genes for pigmentation-related traits ( EDNRA , EDNRB , MITF and OCA2 ) and body size, with a strong candidate for dwarfism in rabbit ( COL2A1 ). Conclusions We report a genome-wide view of genetic loci that underlie the main phenotypic differences in the analyzed rabbit breeds, which can be useful to understand the shift from the domestication process to the development of breeds in O. cuniculus . These results enhance our knowledge about the major genetic loci involved in rabbit external traits and add novel information to understand the complexity of the genetic architecture underlying body size in mammals.
The accurate simulation of additional interactions at the ATLAS experiment for the analysis of proton–proton collisions delivered by the Large Hadron Collider presents a significant challenge to the computing resources. During the LHC Run 2 (2015–2018), there were up to 70 inelastic interactions per bunch crossing, which need to be accounted for in Monte Carlo (MC) production. In this document, a new method to account for these additional interactions in the simulation chain is described. Instead of sampling the inelastic interactions and adding their energy deposits to a hard-scatter interaction one-by-one, the inelastic interactions are presampled, independent of the hard scatter, and stored as combined events. Consequently, for each hard-scatter interaction, only one such presampled event needs to be added as part of the simulation chain. For the Run 2 simulation chain, with an average of 35 interactions per bunch crossing, this new method provides a substantial reduction in MC production CPU needs of around 20%, while reproducing the properties of the reconstructed quantities relevant for physics analyses with good accuracy.
Policy makers have implemented multiple non-pharmaceutical strategies to mitigate the COVID-19 worldwide crisis. Interventions had the aim of reducing close proximity interactions, which drive the spread of the disease. A deeper knowledge of human physical interactions has revealed necessary, especially in all settings involving children, whose education and gathering activities should be preserved. Despite their relevance, almost no data are available on close proximity contacts among children in schools or other educational settings during the pandemic. Contact data are usually gathered via Bluetooth, which nonetheless offers a low temporal and spatial resolution. Recently, ultra-wideband (UWB) radios emerged as a more accurate alternative that nonetheless exhibits a significantly higher energy consumption, limiting in-field studies. In this paper, we leverage a novel approach, embodied by the Janus system that combines these radios by exploiting their complementary benefits. The very accurate proximity data gathered in-field by Janus, once augmented with several metadata, unlocks unprecedented levels of information, enabling the development of novel multi-level risk analyses. By means of this technology, we have collected real contact data of children and educators in three summer camps during summer 2020 in the province of Trento, Italy. The wide variety of performed daily activities induced multiple individual behaviors, allowing a rich investigation of social environments from the contagion risk perspective. We consider risk based on duration and proximity of contacts and classify interactions according to different risk levels. We can then evaluate the summer camps’ organization, observe the effect of partition in small groups, or social bubbles, and identify the organized activities that mitigate the riskier behaviors. Overall, we offer an insight into the educator-child and child-child social interactions during the pandemic, thus providing a valuable tool for schools, summer camps, and policy makers to (re)structure educational activities safely.
Background Secondary peripheral chondrosarcomas arising in solitary osteochondromas is an unusual complication, reported in small series. In this study, we aimed to present our experience with this rare variant of chondrosarcoma and compare results with already published data in order to determine prognostic factors for overall and disease-free survival. Methods The case study includes retrospective data from patients diagnosed at a single institution from 1943 to 2019. Clinical data were collected reviewing all available medical records from first to last follow-up visits. To exclude the presence of the Multiple Osteochondroma Hereditary Syndrome, few patients, with a suspect of a familial form of the disease, were evaluated for the presence of germline heterozygous variants in EXT1 and EXT2 genes. Results were summarized using descriptive statistics and statistical analysis were performed to reveal associations between variables. Results Two hundred and fourteen secondary peripheral chondrosarcomas that arose exclusively from solitary osteochondromas diagnosed in a multidisciplinary setting at the IRCCS Istituto Ortopedico Rizzoli were retrospectively identified, 66.4% males and 33.6% females with a median age at diagnosis of 38 years. The local recurrence rate was 17.3%, while the metastases one was 5.1%. Besides age, a high histologic grade is the only factor associated with worse 5-year and 10-year overall survival (log-rank p = 0.0005, HR = 3.74; 95% CI 1.69–8.26). Moreover, high histological grade (HR = 3.75; 95% CI = 1.69–8.34; p = 0.001) and surgical debulking (HR = 3.71; 95% CI = 1.57–8.79; p = 0.003) were associated with a significantly worse disease-free survival. Conclusions Our study confirm the low-grade behavior of secondary peripheral chondrosarcomas and demonstrate that the best choice of treatment for those arising in solitary osteochondromas is the wide surgical excision, when possible. Location per se is not a factor that affects prognosis, while the accurate histological grade assessment is correlated with the tumor aggressiveness and a long term follow up is necessary for this rare variant of chondrosarcoma.
The ATLAS experiment at the Large Hadron Collider has a broad physics programme ranging from precision measurements to direct searches for new particles and new interactions, requiring ever larger and ever more accurate datasets of simulated Monte Carlo events. Detector simulation with Geant4 is accurate but requires significant CPU resources. Over the past decade, ATLAS has developed and utilized tools that replace the most CPU-intensive component of the simulation—the calorimeter shower simulation—with faster simulation methods. Here, AtlFast3, the next generation of high-accuracy fast simulation in ATLAS, is introduced. AtlFast3 combines parameterized approaches with machine-learning techniques and is deployed to meet current and future computing challenges, and simulation needs of the ATLAS experiment. With highly accurate performance and significantly improved modelling of substructure within jets, AtlFast3 can simulate large numbers of events for a wide range of physics processes.
Artificial intelligence can enhance our ability to manage natural disasters. However, understanding and addressing its limitations is required to realize its benefits. Here, we argue that interdisciplinary, multistakeholder, and international collaboration is needed for developing standards that facilitate its implementation.
Proximal femoral replacement (PFR) is a well-established treatment for neoplasia of the proximal femur. The use of this surgical technique for non-neoplastic conditions has increased over the years. We carried out a systematic review of the literature to study the indications, complications, and functional results when PFR is used for non-neoplastic conditions. Twenty-seven studies were included in the review with a total of 828 PFRs with a mean follow-up of 50 months (range 1–225 months). The main indications were infection (28%), periprosthetic fracture (27%), aseptic loosening (22%), and fracture (16%). The rate of reoperation was 20.3% overall. The overall revision rate was 15.4%. The main complications were dislocation (10.2%) and infection (7.3%). After 2010, the rates of reoperation (25.5% versus 18.2%), loosening (9.4% versus 3.2%), and dislocation (15.7% versus 7.9%) were lower than before 2010. The 30-day mortality ranged from 0% to 9%. The hip function scores improved post-surgery. In conclusion, the use of PFR in non-neoplastic conditions remains a marginal tool, associated with low direct mortality and high complication rates, but we expect its use to increase in the near future.
Background: In the last years, several efforts have been made to classify colorectal cancer (CRC) into well-defined molecular subgroups, representing the intrinsic inter-patient heterogeneity, known as Consensus Molecular Subtypes (CMSs). Methods: In this work, we performed a meta-analysis of CRC patients stratified into four CMSs. We identified a negative correlation between a high level of anaplastic lymphoma kinase (ALK) expression and relapse-free survival, exclusively in CMS1 subtype. Stemming from this observation, we tested cell lines, patient-derived organoids and mice with potent ALK inhibitors, already approved for clinical use. Results: ALK interception strongly inhibits cell proliferation already at nanomolar doses, specifically in CMS1 cell lines, while no effect was found in CMS2/3/4 groups. Furthermore, in vivo imaging identified a role for ALK in the dynamic formation of 3D tumor spheroids. Consistently, ALK appeares constitutively phosphorylated in CMS1, and it signals mainly through the AKT axis. Mechanistically, we found that CMS1 cells display several copies of ALKAL2 ligand and ALK-mRNAs, suggesting an autocrine loop mediated by ALKAL2 in the activation of ALK pathway, responsible for the invasive phenotype. Consequently, disruption of ALK axis mediates the pro-apoptotic action of CMS1 cell lines, both in 2D and 3D and enhanced cell-cell adhesion and e-cadherin organization. In agreement with all these findings, the ALK signature encompassing 65 genes statistically associated with worse relapse-free survival in CMS1 subtype. Finally, as a proof of concept, the efficacy of ALK inhibition was demonstrated in both patient-derived organoids and in tumor xenografts in vivo. Conclusions: Collectively, these findings suggest that ALK targeting may represent an attractive therapy for CRC, and CMS classification may provide a useful tool to identify patients who could benefit from this treatment. These findings offer rationale and pharmacological strategies for the treatment of CMS1 CRC.
This opinion review explores the microbiology of tellurite, TeO 3 ²⁻ and selenite, SeO 3 ²⁻ oxyanions, two similar Group 16 chalcogen elements, but with slightly different physicochemical properties that lead to intriguing biological differences. Selenium, Se, is a required trace element compared to tellurium, Te, which is not. Here, the challenges around understanding the uptake transport mechanisms of these anions, as reflected in the model organisms used by different groups, are described. This leads to a discussion around how these oxyanions are subsequently reduced to nanomaterials, which mechanistically, has controversies between ideas around the molecule chemistry, chemical reactions involving reduced glutathione and reactive oxygen species (ROS) production along with the bioenergetics at the membrane versus the cytoplasm. Of particular interest is the linkage of glutathione and thioredoxin chemistry from the cytoplasm through the membrane electron transport chain (ETC) system/quinones to the periplasm. Throughout the opinion review we identify open and unanswered questions about the microbial physiology under selenite and tellurite exposure. Thus, demonstrating how far we have come, yet the exciting research directions that are still possible. The review is written in a conversational manner from three long-term researchers in the field, through which to play homage to the late Professor Claudio Vásquez.
Background Neuroblastoma is a deadly childhood cancer, and MYCN -amplified neuroblastoma (MNA-NB) patients have the worst prognoses and are therapy-resistant. While retinoic acid (RA) is beneficial for some neuroblastoma patients, the cause of RA resistance is unknown. Thus, there remains a need for new therapies to treat neuroblastoma. Here we explored the possibility of combining a MYCN -specific antigene oligonucleotide BGA002 and RA as therapeutic approach to restore sensitivity to RA in NB. Methods By molecular and cellular biology techniques, we assessed the combined effect of the two compounds in NB cell lines and in a xenograft mouse model MNA-NB. Results We found that MYCN -specific inhibition by BGA002 in combination with RA (BGA002-RA) act synergistically and overcame resistance in NB cell lines. BGA002-RA also reactivated neuron differentiation (or led to apoptosis) and inhibited invasiveness capacity in MNA-NB. Moreover, we found that neuroblastoma had the highest level of mRNA expression of mTOR pathway genes, and that BGA002 led to mTOR pathway inhibition followed by autophagy reactivation in MNA-NB cells, which was strengthened by BGA002-RA. BGA002-RA in vivo treatment also eliminated tumor vascularization in a MNA-NB mouse model and significantly increased survival. Conclusion Taken together, MYCN modulation mediates the therapeutic efficacy of RA and the development of RA resistance in MNA-NB. Furthermore, by targeting MYCN , a cancer-specific mTOR pathway inhibition occurs only in MNA-NB, thus avoiding the side effects of targeting mTOR in normal cells. These findings warrant clinical testing of BGA002-RA as a strategy for overcoming RA resistance in MNA-NB.
Purpose Placement of dental implants has evolved to be an advantageous treatment option for rehabilitation of the fully or partially edentulous mandible. In case of extensive horizontal bone resorption, the bone volume needs to be augmented prior to or during implant placement in order to obtain dental rehabilitation and maximize implant survival and success. Methods Our aim was to systematically review the available data on lateral augmentation techniques in the horizontally compromised mandible considering all grafting protocols using xenogeneic, synthetic, or allogeneic material. A computerized and manual literature search was performed for clinical studies (published January 1995 to March 2021). Results Eight studies ultimately met the inclusion criteria comprising a total of 276 procedures of xenogeneic, allogeneic, or autogenous bone graft applications in horizontal ridge defects. Particulate materials as well as bone blocks were used as grafts with a mean follow-up of 26.0 months across all included studies. Outcome measures, approaches and materials varied from study to study. A gain of horizontal bone width of the mandible with a mean of 4.8 mm was observed in seven of eight studies. All but one study, reported low bone graft failure rates of 4.4% in average. Conclusions Only limited data are available on the impact of different horizontal augmentation strategies in the mandible. The results show outcomes for xenogeneic as well as autologous bone materials for horizontal ridge augmentation of the lower jaw. The use of allogeneic bone-block grafts in combination with resorbable barrier membranes must be re-evaluated. Randomized controlled clinical trials are largely missing.
BNT162b2 vaccine, developed by BioNTech and Pfizer ha recently approved for use in children aged 5 to 11 years. Recent data show evidence of safety on the administration and serious adverse events have been rarely reported. However, allergic systemic reactions could occur. In some cases, a correct allergic evaluation allows identifying patients at risk of developing an anaphylactic reaction. Risk assessment of allergic reactions to COVID-19 vaccines is useful to limit contraindications to vaccination and help to safely vaccinate people supposed to be at risk of allergic reactions.
Representation learning models for graphs are a successful family of techniques that project nodes into feature spaces that can be exploited by other machine learning algorithms. Since many real-world networks are inherently dynamic, with interactions among nodes changing over time, these techniques can be defined both for static and for time-varying graphs. Here, we show how the skip-gram embedding approach can be generalized to perform implicit tensor factorization on different tensor representations of time-varying graphs. We show that higher-order skip-gram with negative sampling (HOSGNS) is able to disentangle the role of nodes and time, with a small fraction of the number of parameters needed by other approaches. We empirically evaluate our approach using time-resolved face-to-face proximity data, showing that the learned representations outperform state-of-the-art methods when used to solve downstream tasks such as network reconstruction. Good performance on predicting the outcome of dynamical processes such as disease spreading shows the potential of this method to estimate contagion risk, providing early risk awareness based on contact tracing data. Supplementary information: The online version contains supplementary material available at 10.1140/epjds/s13688-022-00344-8.
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33,123 members
Gabriele D'Angelo
  • Department of Computer Science and Engineering DISI
Elvis Mazzoni
  • Department of Psychology PSI
Via Zamboni, 33, I-40136, Bologna, BO, Italy
Head of institution
Prof. Francesco Ubertini