7 results
Psychological impact of COVID-19 pandemic on healthcare workers in a highly burdened area of north-east Italy
- A. Lasalvia, C. Bonetto, S. Porru, A. Carta, S. Tardivo, C. Bovo, M. Ruggeri, F. Amaddeo
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- Journal:
- Epidemiology and Psychiatric Sciences / Volume 30 / 2021
- Published online by Cambridge University Press:
- 17 December 2020, e1
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Aims
Healthcare workers exposed to coronavirus 2019 (COVID-19) patients could be psychologically distressed. This study aims to assess the magnitude of psychological distress and associated factors among hospital staff during the COVID-19 pandemic in a large tertiary hospital located in north-east Italy.
MethodsAll healthcare and administrative staff working in the Verona University Hospital (Veneto, Italy) during the COVID-19 pandemic were asked to complete a web-based survey from 21 April to 6 May 2020. Symptoms of post-traumatic distress, anxiety and depression were assessed, respectively, using the Impact of Event Scale (IES-R), the Self-rating Anxiety Scale (SAS) and the Patient Health Questionnaire (PHQ-9). Personal socio-demographic information and job characteristics were also collected, including gender, age, living condition, having pre-existing psychological problems, occupation, length of working experience, hospital unit (ICUs and sub-intensive COVID-19 units vs. non-COVID-19 units). A multivariable logistic regression analysis was performed to identify factors associated with each of the three mental health outcomes.
ResultsA total of 2195 healthcare workers (36.9% of the overall hospital staff) participated in the study. Of the participants, 35.7% were nurses, 24.3% other healthcare staff, 16.4% residents, 13.9% physicians and 9.7% administrative staff. Nine per cent of healthcare staff worked in ICUs, 8% in sub-intensive COVID-19 units and 7.6% in other front-line services, while the remaining staff worked in hospital units not directly engaged with COVID-19 patients. Overall, 63.2% of participants reported COVID-related traumatic experiences at work and 53.8% (95% CI 51.0%–56.6%) showed symptoms of post-traumatic distress; moreover, 50.1% (95% CI 47.9%–52.3%) showed symptoms of clinically relevant anxiety and 26.6% (95% CI 24.7%–28.5%) symptoms of at least moderate depression. Multivariable logistic regressions showed that women, nurses, healthcare workers directly engaged with COVID-19 patients and those with pre-existing psychological problems were at increased risk of psychopathological consequences of the pandemic.
ConclusionsThe psychological impact of the COVID-19 pandemic on healthcare staff working in a highly burdened geographical of north-east Italy is relevant and to some extent greater than that reported in China. The study provides solid grounds to elaborate and implement interventions pertaining to psychology and occupational health.
Comparative evaluation of genomic inbreeding parameters in seven commercial and autochthonous pig breeds
- G. Schiavo, S. Bovo, F. Bertolini, S. Tinarelli, S. Dall’Olio, L. Nanni Costa, M. Gallo, L. Fontanesi
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Single nucleotide polymorphism (SNP) genotyping tools, which can analyse thousands of SNPs covering the whole genome, have opened new opportunities to estimate the inbreeding level of animals directly using genome information. One of the most commonly used genomic inbreeding measures considers the proportion of the autosomal genome covered by runs of homozygosity (ROH), which are defined as continuous and uninterrupted chromosome portions showing homozygosity at all loci. In this study, we analysed the distribution of ROH in three commercial pig breeds (Italian Large White, n = 1968; Italian Duroc, n = 573; and Italian Landrace, n = 46) and four autochthonous breeds (Apulo-Calabrese, n = 90; Casertana, n = 90; Cinta Senese, n = 38; and Nero Siciliano, n = 48) raised in Italy, using SNP data generated from Illumina PorcineSNP60 BeadChip. We calculated ROH-based inbreeding coefficients (FROH) using ROH of different minimum length (1, 2, 4, 8, 16 Mbp) and compared them with several other genomic inbreeding coefficients (including the difference between observed and expected number of homozygous genotypes (FHOM)) and correlated all these genomic-based measures with the pedigree inbreeding coefficient (FPED) calculated for the pigs of some of these breeds. Autochthonous breeds had larger mean size of ROH than all three commercial breeds. FHOM was highly correlated (0.671 to 0.985) with FROH measures in all breeds. Apulo-Calabrese and Casertana had the highest FROH values considering all ROH minimum lengths (ranging from 0.273 to 0.189 and from 0.226 to 0.152, moving from ROH of minimum size of 1 Mbp (FROH1) to 16 Mbp (FROH16)), whereas the lowest FROH values were for Nero Siciliano (from 0.072 to 0.051) and Italian Large White (from 0.117 to 0.042). FROH decreased as the minimum length of ROH increased for all breeds. Italian Duroc had the highest correlations between all FROH measures and FPED (from 0.514 to 0.523) and between FHOM and FPED (0.485). Among all analysed breeds, Cinta Senese had the lowest correlation between FROH and FPED. This might be due to the imperfect measure of FPED, which, mainly in local breeds raised in extensive production systems, cannot consider a higher level of pedigree errors and a potential higher relatedness of the founder population. It appeared that ROH better captured inbreeding information in the analysed breeds and could complement pedigree-based inbreeding coefficients for the management of these genetic resources.
Comparative selection signature analyses identify genomic footprints in Reggiana cattle, the traditional breed of the Parmigiano-Reggiano cheese production system
- F. Bertolini, G. Schiavo, S. Bovo, M. T. Sardina, S. Mastrangelo, S. Dall’Olio, B. Portolano, L. Fontanesi
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Reggiana is an autochthonous cattle breed reared mainly in the province of Reggio Emilia, located in the North of Italy. Reggiana cattle (originally a triple-purpose population largely diffused in the North of Italy) are characterised by a typical solid red coat colour. About 2500 cows of this breed are currently registered to its herd book. Reggiana is now considered a dual-purpose breed even if it is almost completely dedicated to the production of a mono-breed branded Protected Designation of Origin Parmigiano-Reggiano cheese, which is the main driver of the sustainable conservation of this local genetic resource. In this study, we provided the first overview of genomic footprints that characterise Reggiana and define the diversity of this local cattle breed. A total of 168 Reggiana sires (all bulls born over 35 years for which semen was available) and other 3321 sires from 3 cosmopolitan breeds (Brown, Holstein and Simmental) were genotyped with the Illumina BovineSNP50 panel. ADMIXTURE analysis suggested that Reggiana breed might have been influenced, at least in part, by the other three breeds included in this study. Selection signatures in the Reggiana genome were identified using three statistical approaches based on allele frequency differences among populations or on properties of haplotypes segregating in the populations (fixation index (FST); integrated haplotype score; cross-population extended haplotype homozygosity). We identified several regions under peculiar selection in the Reggiana breed, particularly on bovine chromosome (BTA) 6 in the KIT gene region, that is known to be involved in coat colour pattern distribution, and within the region of the LAP3, NCAPG and LCORL genes, that are associated with stature, conformation and carcass traits. Another already known region that includes the PLAG1 gene (BTA14), associated with conformation traits, showed a selection signature in the Reggiana cattle. On BTA18, a signal of selection included the MC1R gene that causes the red coat colour in cattle. Other selection sweeps were in regions, with high density of quantitative trait loci for milk production traits (on BTA20) and in several other large regions that might have contributed to shape and define the Reggiana genome (on BTA17 and BTA29). All these results, overall, indicate that the Reggiana genome might still contain several signs of its multipurpose and non-specialised utilisation, as already described for other local cattle populations, in addition to footprints derived by its ancestral origin and by its adaptation to the specialised Parmigiano-Reggiano cheese production system.
A machine learning approach for the identification of population-informative markers from high-throughput genotyping data: application to several pig breeds
- G. Schiavo, F. Bertolini, G. Galimberti, S. Bovo, S. Dall’Olio, L. Nanni Costa, M. Gallo, L. Fontanesi
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Single nucleotide polymorphisms (SNPs) able to describe population differences can be used for important applications in livestock, including breed assignment of individual animals, authentication of mono-breed products and parentage verification among several other applications. To identify the most discriminating SNPs among thousands of markers in the available commercial SNP chip tools, several methods have been used. Random forest (RF) is a machine learning technique that has been proposed for this purpose. In this study, we used RF to analyse PorcineSNP60 BeadChip array genotyping data obtained from a total of 2737 pigs of 7 Italian pig breeds (3 cosmopolitan-derived breeds: Italian Large White, Italian Duroc and Italian Landrace, and 4 autochthonous breeds: Apulo-Calabrese, Casertana, Cinta Senese and Nero Siciliano) to identify breed informative and reduced SNP panels using the mean decrease in the Gini Index and the Mean Decrease in Accuracy parameters with stability evaluation. Other reduced informative SNP panels were obtained using Delta, Fixation index and principal component analysis statistics, and their performances were compared with those obtained using the RF-defined panels using the RF classification method and its derived Out Of Bag rates and correct prediction proportions. Therefore, the performances of a total of six reduced panels were evaluated. The correct assignment of the animals to its breed was close to 100% for all tested approaches. Porcine chromosome 8 harboured the largest number of selected SNPs across all panels. Many SNPs were included in genomic regions in which previous studies identified signatures of selection or genes (e.g. ESR1, KITL and LCORL) that could contribute to explain, at least in part, phenotypically or economically relevant traits that might differentiate cosmopolitan and autochthonous pig breeds. Random forest used as preselection statistics highlighted informative SNPs that were not the same as those identified by other methods. This might be due to specific features of this machine learning methodology. It will be interesting to explore if the adaptation of RF methods for the identification of selection signature regions could be able to describe population-specific features that are not captured by other approaches.
Genome-wide association studies for seven production traits highlight genomic regions useful to dissect dry-cured ham quality and production traits in Duroc heavy pigs
- F. Bertolini, G. Schiavo, G. Galimberti, S. Bovo, M. D’Andrea, M. Gallo, L. Buttazzoni, M. F. Rothschild, L. Fontanesi
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Protected designation of origin dry-cured hams are obtained from heavy pigs (slaughtered at about 160 kg of live weight). A specific breeding program designed to improve meat quality for this production has included as key traits the level of intermuscular fat between the leg muscles and ham weight loss during the seasoning period together with a balance between fat and lean cuts. In this study we carried out genome-wide association studies for seven traits used in the genetic merit of Italian Duroc heavy pigs, five related to meat and carcass quality traits (visible intermuscular fat, ham weight loss at first salting, backfat thickness, ham weight and lean cuts), and two related to performance and efficiency traits (average daily gain and feed : gain ratio). A total of 573 performance-tested pigs were genotyped with the Illumina PorcineSNP60 BeadChip and genome-wide association analyses were carried out using the Bayes B approach with the 1 Mb window option of GenSel and random residuals for each of the seven traits. Detected windows were supported by independent single nucleotide polymorphism analyses with a linear mixed model (LMM) approach on the same animals for the same traits. A total of 30 windows identifying different quantitative trait loci (QTL) were detected and among those, 27 were confirmed by LMM in one of these traits. Among the confirmed windows, three QTL were reported for visible intermuscular fat, seven for ham weight loss at first salting and five and four for backfat thickness and lean cut, respectively. A total of eight QTL were detected for the other production traits. No overlapping QTL were reported except for one window on porcine chromosome 10 between lean cuts and ham weight that contained the CACNB2 gene that has been already associated with loin marbling score in other Duroc pigs. Several regions contained genes that have been already associated with production traits in other pig breeds, including Duroc lines, related to fat deposition or muscle structure. This work reports, for the first time, genome-wide association study results for several traits in Italian Duroc heavy pigs. These results will be useful to dissect the genetic basis for dry-cured ham production traits that determine the total genetic merit index of Italian Duroc pigs.
Metabolomics evidences plasma and serum biomarkers differentiating two heavy pig breeds
- S. Bovo, G. Mazzoni, G. Galimberti, D. G. Calò, F. Fanelli, M. Mezzullo, G. Schiavo, A. Manisi, P. Trevisi, P. Bosi, S. Dall’Olio, U. Pagotto, L. Fontanesi
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In pigs, many production traits are known to vary among breeds or lines. These traits can be considered end phenotypes or external traits as they are the final results of complex biological interactions and processes whose fine biological mechanisms are still largely unknown. This study was designed to compare plasma and serum metabolomic profiles between animals of two heavy pig breeds (12 Italian Large White and 12 Italian Duroc), testing indirectly the hypothesis that different genetic backgrounds might be the determining factors of differences observed on the level of metabolites in the analyzed biofluids between breeds. We used a targeted metabolomic approach based on mass spectrometric detection of about 180 metabolites and applied a statistical validation pipeline to identify differences in the metabolomic profiles of the two heavy pig breeds. Blood samples were collected after jugulation at the slaughterhouse and prepared for metabolomics analysis that was carried out using the Biocrates AbsoluteIDQ p180 Kit, covering five different biochemical classes: glycerophospholipids, amino acids, biogenic amines, hexoses and acylcarnitines. A statistical pipeline that included the selection of the most relevant metabolites differentiating the two breeds by sparse Partial Least Squares Discriminant Analysis (sPLS-DA) was coupled with a stability test and significance test determined with leave one out and permutation procedures. sPLS-DA plots clearly separated the pigs of the two investigated breeds. A few metabolites (a total of five metabolites considering the two biofluids) involved in key metabolic pathways largely contributed to these differences between breeds. In particular, a higher level of the sphingomyelins SM (OH) C14:1 (both in plasma and serum), SM (OH) C16:1 (in serum) and SM C16:0 (in serum) were observed in Italian Duroc than in Italian Large White pigs and the inverse was for the biogenic amine kynurenine (in plasma). The level of another biogenic amine (acetylornithine) was higher in Italian Large White than in Italian Duroc pigs in both analysed biofluids. These results provided biomarkers that could be important to understand the biological differences between these two heavy pig breeds. In particular, according to the functional role played by sphingomyelins in obesity-induced inflammatory responses, it could be possible to speculate that a higher level of sphingomyelins in Italian Duroc might be related to the higher interrmuscular fat deposition of this breed compared with the Italian Large White. Additional studies will be needed to evaluate the relevance of these biomarkers for practical applications in pig breeding and nutrition.
High frequency hearing loss in the elderly: effect of age and noise exposure in an Italian group
- A Ciorba, A Benatti, C Bianchini, C Aimoni, S Volpato, R Bovo, A Martini
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- Journal:
- The Journal of Laryngology & Otology / Volume 125 / Issue 8 / August 2011
- Published online by Cambridge University Press:
- 10 June 2011, pp. 776-780
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- August 2011
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Objective:
To describe the effect of age and noise on high frequency hearing thresholds in an Italian population aged 70 years and older, in order to investigate the interaction between presbycusis and noise exposure.
Methods:We compared 460 subjects: 367 affected by presbycusis alone (204 women and 163 men) and 93 affected by presbycusis and noise exposure (eight women and 85 men). Pure tone average hearing thresholds, for each ear, were compared between groups, and between sexes and ages within groups.
Results:A slight threshold difference was found between the two groups at 4 kHz. After adjusting for age and gender, this difference was found to be related only to differing patient age. Men's and women's thresholds differed significantly in both groups, especially at high frequencies, at which threshold deterioration was worse in men than women.
Conclusion:The threshold differences between patients with presbycusis with and without noise exposure were limited. Larger studies are needed to assess the relative effects of ageing and noise exposure on hearing thresholds.