A Damage Detection Approach for Axially Loaded Beam-like Structures Based on Gaussian Mixture Model.

Axially loaded beam-like structures represent a challenging case study for unsupervised learning vibration-based damage detection. Under real environmental and operational conditions, changes in axial load cause changes in the characteristics of the dynamic response that are significantly greater than those due to damage at an early stage. In previous works, the authors proposed the adoption of a multivariate damage feature composed of eigenfrequencies of multiple vibration modes. Successful results were obtained by framing the problem of damage detection as that of unsupervised outlier detection, adopting the well-known Mahalanobis squared distance (MSD) to define an effective damage index. Starting from these promising results, a novel approach based on unsupervised learning data clustering is proposed in this work, which increases the sensitivity to damage and significantly reduces the uncertainty associated with the results, allowing for earlier damage detection. The novel approach, which is based on Gaussian mixture model, is compared with the benchmark one based on the MSD, under the effects of an uncontrolled environment and, most importantly, in the presence of real damage due to corrosion.

Automatic Detection of Real Damage in Operating Tie-Rods.

Many researchers have proposed vibration-based damage-detection approaches for continuous structural health monitoring. Translation to real applications is not always straightforward because the proposed methods have mostly been developed and validated in controlled environments, and they have not proven to be effective in detecting real damage when considering real scenarios in which environmental and operational variations are not controlled. This work was aimed to develop a fully-automated strategy to detect damage in operating tie-rods that only requires one sensor and that can be carried out without knowledge of physical variables, e.g., the axial load. This strategy was created by defining a damage feature based on tie-rod eigenfrequencies and developing a data-cleansing strategy that could significantly improve performance of outlier detection based on the Mahalanobis squared distance in real applications. Additionally, the majority of damage-detection algorithms presented in the literature related to structural health monitoring were validated in controlled environments considering simulated damage conditions. On the contrary, the approach proposed in this paper was shown to allow for the early detection of real damage associated with a corrosion attack under the effects of an intentionally uncontrolled environment.

Circulating SARS-CoV-2 variants in Italy, October 2020-March 2021.

A growing number of emerging SARS-CoV-2 variants is being identified worldwide, potentially impacting the effectiveness of current vaccines. We report the data obtained in several Italian regions involved in the SARS-CoV-2 variant monitoring from the beginning of the epidemic and spanning the period from October 2020 to March 2021.

First identification of porcine parvovirus 3 in a wild boar in Italy by viral metagenomics - Short communication.

Metagenomic analysis revealed the presence of porcine parvovirus 3 (PPV3) in the pool of the internal organs of a wild boar found dead in Southern Italy. Phylogenetic analysis based on the complete coding sequences showed that the newly detected virus is most closely related to those found also in wild boars in Romania during 2010-2011. Even though the death could not be associated with this virus, PPV3 could have contributed to lowering the host's immunological defences.

Evidence of circulation of the novel border disease virus genotype 8 in chamois.

Evidence of association between the novel putative border disease virus genotype 8 (BDV-8) and fatal disease in an Alpine chamois (Rupicapra rupicapra) is reported. Diagnostically, we also demonstrated, as already previously reported, the failure of BDV-specific primers (PDB1 and PDB2) to detect BDV-8.

A new genotype of border disease virus with implications for molecular diagnostics.

Border disease virus (BDV) is a (+) single-stranded RNA pestivirus affecting mainly sheep and goats worldwide. Genetic typing of BDV has led to the identification of at least seven major genotypes. This study reports the detection of a BDV strain from a goat in northwestern Italy during routine investigations. Sequence analysis revealed mutations in the 5'-UTR of the virus with implications for BDV molecular diagnostics. Moreover, subsequent phylogenetic analysis based on the combined 5'-UTR and Npro/partial C genes, showed divergence from known BDV genotypes, revealing the detection of a novel pestivirus group, for which we propose the name BDV genotype 8.

Ranking viruses: measures of positional importance within networks define core viruses for rational polyvalent vaccine development.

MOTIVATION: The extraordinary genetic and antigenic variability of RNA viruses is arguably the greatest challenge to the development of broadly effective vaccines. No single viral variant can induce sufficiently broad immunity, and incorporating all known naturally circulating variants into one multivalent vaccine is not feasible. Furthermore, no objective strategies currently exist to select actual viral variants that should be included or excluded in polyvalent vaccines. RESULTS: To address this problem, we demonstrate a method based on graph theory that quantifies the relative importance of viral variants. We demonstrate our method through application to the envelope glycoprotein gene of a particularly diverse RNA virus of pigs: porcine reproductive and respiratory syndrome virus (PRRSV). Using distance matrices derived from sequence nucleotide difference, amino acid difference and evolutionary distance, we constructed viral networks and used common network statistics to assign each sequence an objective ranking of relative 'importance'. To validate our approach, we use an independent published algorithm to score our top-ranked wild-type variants for coverage of putative T-cell epitopes across the 9383 sequences in our dataset. Top-ranked viruses achieve significantly higher coverage than low-ranked viruses, and top-ranked viruses achieve nearly equal coverage as a synthetic mosaic protein constructed in silico from the same set of 9383 sequences. CONCLUSION: Our approach relies on the network structure of PRRSV but applies to any diverse RNA virus because it identifies subsets of viral variants that are most important to overall viral diversity. We suggest that this method, through the objective quantification of variant importance, provides criteria for choosing viral variants for further characterization, diagnostics, surveillance and ultimately polyvalent vaccine development.

Emulator-based Bayesian inference on non-proportional scintillation models by compton-edge probing.

Scintillator detector response modeling has become an essential tool in various research fields such as particle and nuclear physics, astronomy or geophysics. Yet, due to the system complexity and the requirement for accurate electron response measurements, model inference and calibration remains a challenge. Here, we propose Compton edge probing to perform non-proportional scintillation model (NPSM) inference for inorganic scintillators. We use laboratory-based gamma-ray radiation measurements with a NaI(Tl) scintillator to perform Bayesian inference on a NPSM. Further, we apply machine learning to emulate the detector response obtained by Monte Carlo simulations. We show that the proposed methodology successfully constrains the NPSM and hereby quantifies the intrinsic resolution. Moreover, using the trained emulators, we can predict the spectral Compton edge dynamics as a function of the parameterized scintillation mechanisms. The presented framework offers a simple way to infer NPSMs for any inorganic scintillator without the need for additional electron response measurements.

Fast and reliable real life data on COVID-19 triaging with ID NOW.

In the context of SARS-CoV-2 pandemic, rapid and easy-to-perform diagnostic methods are essential to limit the spread of the virus and for the clinical management of COVID-19 patients. Although real-time polymerase chain reaction remains the "gold standard" to diagnose acute infections, this technique is expensive, requires trained personnel, well-equipped laboratory and is time-consuming. A prospective evaluation of the Abbott ID NOW COVID-19 point-of-care testing that uses isothermal nucleic acid amplification for the qualitative detection of SARS-CoV-2 RdRp gene was run in the Emergency Department during the third wave of COVID-19 pandemic. ID-NOW significantly simplified SARS-CoV-2 identification and COVID-19 patient triaging, being highly valuable in rapidly locating febrile patients in or out of COVID-19 areas, and can be considered as a first-line diagnostic test in the Emergency Room setting.

SARS-CoV-2 microfluidic antigen point-of-care testing in Emergency Room patients during COVID-19 pandemic.

In Emergency Room, Point-of-care antigen testing for SARS-CoV-2 antigen can expedite clinical strategies for patient management. We tested 1,232 consecutive patients during Italian second wave peak using the recent LumiraDx microfluidic assay. This assay showed high concordance (96.9 %), sensitivity and specificity compared to molecular testing, being highly valuable.

Phylogeography and genomic epidemiology of SARS-CoV-2 in Italy and Europe with newly characterized Italian genomes between February-June 2020.

The aims of this study were to characterize new SARS-CoV-2 genomes sampled all over Italy and to reconstruct the origin and the evolutionary dynamics in Italy and Europe between February and June 2020. The cluster analysis showed only small clusters including < 80 Italian isolates, while most of the Italian strains were intermixed in the whole tree. Pure Italian clusters were observed mainly after the lockdown and distancing measures were adopted. Lineage B and B.1 spread between late January and early February 2020, from China to Veneto and Lombardy, respectively. Lineage B.1.1 (20B) most probably evolved within Italy and spread from central to south Italian regions, and to European countries. The lineage B.1.1.1 (20D) developed most probably in other European countries entering Italy only in the second half of March and remained localized in Piedmont until June 2020. In conclusion, within the limitations of phylogeographical reconstruction, the estimated ancestral scenario suggests an important role of China and Italy in the widespread diffusion of the D614G variant in Europe in the early phase of the pandemic and more dispersed exchanges involving several European countries from the second half of March 2020.

Taxon ordering in phylogenetic trees: a workbench test.

BACKGROUND: Phylogenetic trees are an important tool for representing evolutionary relationships among organisms. In a phylogram or chronogram, the ordering of taxa is not considered meaningful, since complete topological information is given by the branching order and length of the branches, which are represented in the root-to-node direction. We apply a novel method based on a (λ + µ)-Evolutionary Algorithm to give meaning to the order of taxa in a phylogeny. This method applies random swaps between two taxa connected to the same node, without changing the topology of the tree. The evaluation of a new tree is based on different distance matrices, representing non-phylogenetic information such as other types of genetic distance, geographic distance, or combinations of these. To test our method we use published trees of Vesicular stomatitis virus, West Nile virus and Rice yellow mottle virus. RESULTS: Best results were obtained when taxa were reordered using geographic information. Information supporting phylogeographic analysis was recovered in the optimized tree, as evidenced by clustering of geographically close samples. Improving the trees using a separate genetic distance matrix altered the ordering of taxa, but not topology, moving the longest branches to the extremities, as would be expected since they are the most divergent lineages. Improved representations of genetic and geographic relationships between samples were also obtained when merged matrices (genetic and geographic information in one matrix) were used. CONCLUSIONS: Our innovative method makes phylogenetic trees easier to interpret, adding meaning to the taxon order and helping to prevent misinterpretations.

Analysis of different medulloblastoma histotypes by two-dimensional gel and MALDI-TOF.

OBJECTIVE: The purpose of this study is to detect different protein profiles in medulloblastoma (MDB) that may be clinically relevant and to check the correspondence of histological classification of MDB with proteomic profiles. MATERIALS AND METHODS: Surgical specimens, snap frozen at the time of neurosurgery, entered the proteomic study. Eight samples from patients (age range, 4 months-26 years) with different MDB histotypes (five classic, one desmoplastic/nodular, one with extensive nodularity, and one anaplastic) were analyzed by two-dimensional gel electrophoresis. One sample for each histotype was further characterized by matrix-assisted laser desorption/ionization time of flight mass spectrometry analysis. RESULTS: Eighty-six unique proteins were identified and compared to histology, with the determination of proteins expressed by single histotypes and of a smaller number of proteins shared by two or three histotypes. The sharp difference of protein expression was found to be in agreement with WHO histological classification, with the identification of type-specific proteins with limited overlapping between histotypes. CONCLUSION: Proteomic analysis confirmed and strengthened the difference between histotypes as biologically relevant. Cluster analysis enhanced the distance of extensive nodularity MDB from other histotypes. Possible innovative approaches to therapy may rely upon a proteomic-based classification of MDB tightly correlated to histology. The utility of snap freezing tumoral samples must be stressed and should become a mandatory task for pathologists.

Draft Genome Sequence of Rhodococcus qingshengii Strain PN_19, Isolated from a Moribund Individual of Pinna nobilis in Sardinia, Italy.

During an epidemiological survey that aimed to discover the causes for the mass mortality of Pinna nobilis, a strain of Rhodococcus was found in a moribund individual. Here, we report its 7,037,134-bp draft genome sequence, which, after the annotation and genome survey, was identified as belonging to Rhodococcus qingshengii PN_19.

On the SARS-CoV-2 "Variolation Hypothesis": No Association Between Viral Load of Index Cases and COVID-19 Severity of Secondary Cases.

Background: Emerging evidence supports the "variolation hypothesis" in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), but the derivative idea that the viral load of index cases may predict disease severity in secondary cases could be unsubstantiated. We assessed whether the prevalence of symptomatic infections, hospitalization, and deaths in household contacts of 2019 novel coronavirus disease (COVID-19) cases differed according to the SARS-CoV-2 PCR cycle threshold (Ct) from nasal-pharyngeal swab at diagnosis of linked index cases. Methods: Cross-sectional study on household contacts of COVID-19 cases randomly sampled from all the infections diagnosed in March at our Microbiology Laboratory (Amedeo di Savoia, Turin). Data were retrospectively collected by phone interviews and from the Piedmont regional platform for COVID-19 emergency. Index cases were classified as high (HVl) and low viral load (LVl) according to two exploratory cut-offs of RdRp gene Ct value. Secondary cases were defined as swab confirmed or symptom based likely when not tested but presenting compatible clinical picture. Results: One hundred thirty-two index cases of whom 87.9% symptomatic and 289 household contacts were included. The latter were male and Caucasian in 44.3 and 95.8% of cases, with a median age of 34 years (19-57). Seventy-four were swab confirmed and other 28 were symptom based likely secondary cases. Considering both, the contacts of HVl and LVl did not differ in the prevalence of symptomatic infections nor COVID-19-related hospitalization and death. No difference in median Ct of index cases between symptomatic and asymptomatic, hospitalized and not hospitalized, or deceased and survived secondary cases was found. Negative findings were confirmed after adjusting for differences in time between COVID-19 onset and swab collection of index cases (median 5 days) and after removing pediatric secondary cases. Conclusions: The amount of SARS-CoV-2 of the source at diagnosis does not predict clinical outcomes of linked secondary cases. Considering the impelling release of assays for SARS-CoV-2 RNA exact quantification, these negative findings should inform clinical and public health strategies on how to interpret and use the data.

COVseq is a cost-effective workflow for mass-scale SARS-CoV-2 genomic surveillance.

While mass-scale vaccination campaigns are ongoing worldwide, genomic surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is critical to monitor the emergence and global spread of viral variants of concern (VOC). Here, we present a streamlined workflow-COVseq-which can be used to generate highly multiplexed sequencing libraries compatible with Illumina platforms from hundreds of SARS-CoV-2 samples in parallel, in a rapid and cost-effective manner. We benchmark COVseq against a standard library preparation method (NEBNext) on 29 SARS-CoV-2 positive samples, reaching 95.4% of concordance between single-nucleotide variants detected by both methods. Application of COVseq to 245 additional SARS-CoV-2 positive samples demonstrates the ability of the method to reliably detect emergent VOC as well as its compatibility with downstream phylogenetic analyses. A cost analysis shows that COVseq could be used to sequence thousands of samples at less than 15 USD per sample, including library preparation and sequencing costs. We conclude that COVseq is a versatile and scalable method that is immediately applicable for SARS-CoV-2 genomic surveillance and easily adaptable to other pathogens such as influenza viruses.

Diagnostic SARS-CoV-2 Cycle Threshold Value Predicts Disease Severity, Survival, and Six-Month Sequelae in COVID-19 Symptomatic Patients.

To date, there is no severe acute respiratory syndrome coronavirus 2-(SARS-CoV-2)-specific prognostic biomarker available. We assessed whether SARS-CoV-2 cycle threshold (Ct) value at diagnosis could predict novel CoronaVirus Disease 2019 (COVID-19) severity, clinical manifestations, and six-month sequelae. Hospitalized and outpatient cases were randomly sampled from the diagnoses of March 2020 and data collected at 6 months by interview and from the regional database for COVID-19 emergency. Patients were stratified according to their RNA-dependent-RNA-polymerase Ct in the nasopharyngeal swab at diagnosis as follows: Group A ≤ 20.0, 20.0 < group B ≤ 28.0, and Group C > 28.0. Disease severity was classified according to a composite scale evaluating hospital admission, worst oxygen support required, and survival. Two hundred patients were included, 27.5% in Groups A and B both, 45.0% in Group C; 90% of patients were symptomatic and 63.7% were hospitalized. The median time from COVID-19 onset to swab collection was five days. Lethality, disease severity, type, and number of signs and symptoms, as well as six-month sequelae distributed inversely among the groups with respect to SARS-CoV-2 Ct. After controlling for confounding, SARS-CoV-2 Ct at diagnosis was still associated with COVID-19-related death (p = 0.023), disease severity (p = 0.023), number of signs and symptoms (p < 0.01), and presence of six-month sequelae (p < 0.01). Early quantification of SARS-CoV-2 may be a useful predictive marker to inform differential strategies of clinical management and resource allocation.

Feline morbillivirus in northwestern Italy: first detection of genotype 1-B.

OBJECTIVES: A novel morbillivirus was recently described in stray and domestic cats in Asia, the USA and Europe. Most cats infected with feline morbillivirus (FeMV) showed lower urinary tract or kidney disease. Although the association of FeMV infection and kidney diseases has been suggested, the virus pathogenicity remains unclear. The present study aimed to investigate the distribution of FeMV infection, as well as the relationship between FeMV infection and kidney diseases in cats from northwestern Italy. METHODS: A total of 153 urine samples (150 individuals and three pools) and 50 kidney samples were collected and included in the study; total RNA was extracted and a reverse transcription quantitative PCR (RT-qPCR) was performed in order to identify FeMV. Kidneys were also submitted to anatomopathological examination. Phylogenetic analysis and isolation attempts were carried out on positive samples. In FeMV-positive cats, urinalysis and blood analysis were performed. RESULTS: FeMV RNA was detected in 7.3% of urine samples and in 8% of kidney samples, both in healthy cats and in cats with clinical signs/post-mortem lesions compatible with kidney disease. At histopathological examination, tubulointerstitial nephritis (TIN) was shown in 3/4 positive kidney samples, but a clear relationship between FeMV and TIN was not observed. Isolation attempts were unsuccessful, although the urine sample of one castrated male cat hosted in a cattery showed a positive signal in RT-qPCR until the fourth cell passage. Phylogenetic analysis revealed that this FeMV strain belonged to genotype 1-B. In the same cattery, a second genotype 1-B variant was detected from a urine pool. Urinalysis showed proteinuria in three cats, while at blood analysis three cats presented altered creatinine levels. CONCLUSIONS AND RELEVANCE: Data reported suggest the presence of a FeMV sub-cluster distinct from the strain previously isolated in Italy, whose role in renal disorders remains uncertain.

Genome Sequence of Oenococcus oeni OE37, an Autochthonous Strain Isolated from an Italian White Wine.

Oenococcus oeni OE37 is an autochthonous strain that was isolated from a Chardonnay wine from Piedmont (Italy) during spontaneous malolactic fermentation. Here, the OE37 genome sequence is presented, and a brief description of the main genes is reported.

Urgent need of rapid tests for SARS CoV-2 antigen detection: Evaluation of the SD-Biosensor antigen test for SARS-CoV-2.

At the time of writing, FIND has listed four CE-marked SARSCoV-2 antigen tests. We evaluated the recently CE-approved rapid POCT SD-Biosensor for SARS-CoV-2 nucleoprotein detection in nasopharyngeal secretions from 330 patients admitted to the Emergency Room for a suspect of COVID-19 and travelers returning home from high risk countries. Sensitivity, specificity, accuracy, negative and predictive values were consistent with the use of the test to mass-screening for SARS-CoV-2 surveillance.