La stampa 3D in ortopedia: indicazioni e limiti [3D printing products in orthopedics: indications and limits]

Introduzione. Negli ultimi decenni, lo sviluppo delle tecniche e dei materiali ha permesso profondi passi avanti in diversi campi della tecnologia; la medicina, e in particolare l’ortopedia, è tra i settori che ne hanno maggiormente giovato. Sebbene la tecnologia di stampa 3D sia disponibile da diversi decenni, le elevate spese di gestione e i risultati insufficienti ne avevano ridotto l’applicazione solo in campo industriale e meccanico; negli ultimi anni, grazie anche alla riduzione dei prezzi, si è verificata una netta diffusione della stampa 3D anche in campo medico e in particolar modo ortopedico. La stampa tridimensionale permette il passaggio da un modello tridimensionale computerizzato a un manufatto reale, “stampato” da apposite stampanti 3D. Tale processo si basa sulla sovrapposizione progressiva di strati di spessore e materiali variabili, quali polimeri plastici o metalli, secondo uno schema preciso e computerizzato, che viene detto “additivo” per contrapposizione alle tecniche di produzione tradizionali che prevedono la sottrazione di materiale in eccesso da un volume di partenza per la produzione del manufatto definitivo. Materiali e metodi. Sono stati valutati i principali campi di applicazione della stampa 3D in ortopedia, analizzando il processo che porta all’impianto di una protesi custom-made in titanio, stampata con tecnologia 3D. Risultati. Possiamo identificare sette principali usi in ortopedia: uso didattico, planning operatorio, informazione del paziente, produzione di protesi custom-made, produzione di strumenti chirurgici anche dedicati al singolo paziente, template per spaziatori in cemento antibiotato, produzione di ortesi esterne e tutori personalizzati. La corretta interazione tra ortopedico e ingegnere è alla base della riuscita del prodotto custom-made; una volta raggiunto un accordo, saranno necessari circa 30 giorni per avere il prodotto impiantabile. Conclusioni. La tecnologia di stampa 3D è da considerarsi oggi una valida arma nelle mani dell’ortopedico per la risoluzione di casi difficili. I limiti più importanti sono oggi costituiti dal rischio di infezione e dall’osteointegrazione. Altri sviluppi e indicazioni probabilmente si avranno parallelamente all’ulteriore sviluppo tecnologico.Introduction. In recent decades, technical developments have brought an evident progress in several scientific areas; medicine, and in particular orthopedics, is probably one of the sectors which has most benefited from them. In fact, although 3D-printing technology has been available for several years, the high costs and the insufficient results reduced its application only to the industrial and mechanical field; in recent times, thanks to progress of technique and materials, 3D-printing is obtaining more importance in medicine also, and particularly in orthopedics. 3D-printing allows the transition from a computerized three-dimensional model to a real artifact, “printed” by special 3D-printers. This process is based on the gradual superposition of layers of variable materials, such as plastic polymers or metals, according to a precise computerized pattern. Materials and methods. The main orthopedic applications of 3D printing were evaluated, analyzing the process that leads to the production of a custom-made titanium prosthesis, printed with 3D technology. Results. We identified seven main uses in orthopedics: educational use, operative planning, patient education, production of custom-made prosthesis, production of surgical instruments also dedicated to the individual patient, template for spacers in concrete antibiotic, production of external ortheses and braces. The proper interaction between the orthopedic surgeon and the engineer is the basis of the success of the custommade product; once reached an agreement, about 30 days are required to receive the product. Conclusion. 3D printing technology is now considered a valuable weapon for solving difficult cases in the hands of an orthopedists. The most important limits consist of the risk of infection and osteointegration. Other indications will probably be found with the further development of techniques and materials

Host genetics and COVID-19 severity: increasing the accuracy of latest severity scores by Boolean quantum features

The impact of common and rare variants in COVID-19 host genetics has been widely studied. In particular, in Fallerini et al. (Human genetics, 2022, 141, 147–173), common and rare variants were used to define an interpretable machine learning model for predicting COVID-19 severity. First, variants were converted into sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. After that, the Boolean features, selected by these logistic models, were combined into an Integrated PolyGenic Score (IPGS), which offers a very simple description of the contribution of host genetics in COVID-19 severity. IPGS leads to an accuracy of 55%–60% on different cohorts, and, after a logistic regression with both IPGS and age as inputs, it leads to an accuracy of 75%. The goal of this paper is to improve the previous results, using not only the most informative Boolean features with respect to the genetic bases of severity but also the information on host organs involved in the disease. In this study, we generalize the IPGS adding a statistical weight for each organ, through the transformation of Boolean features into “Boolean quantum features,” inspired by quantum mechanics. The organ coefficients were set via the application of the genetic algorithm PyGAD, and, after that, we defined two new integrated polygenic scores ((Formula presented.) and (Formula presented.)). By applying a logistic regression with both IPGS, ((Formula presented.) (or indifferently (Formula presented.)) and age as inputs, we reached an accuracy of 84%–86%, thus improving the results previously shown in Fallerini et al. (Human genetics, 2022, 141, 147–173) by a factor of 10%

Ultra-rare RTEL1 gene variants associate with acute severity of COVID-19 and evolution to pulmonary fibrosis as a specific long COVID disorder

Background: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a novel coronavirus that caused an ongoing pandemic of a pathology termed Coronavirus Disease 19 (COVID-19). Several studies reported that both COVID-19 and RTEL1 variants are associated with shorter telomere length, but a direct association between the two is not generally acknowledged. Here we demonstrate that up to 8.6% of severe COVID-19 patients bear RTEL1 ultra-rare variants, and show how this subgroup can be recognized. Methods: A cohort of 2246 SARS-CoV-2-positive subjects, collected within the GEN-COVID Multicenter study, was used in this work. Whole exome sequencing analysis was performed using the NovaSeq6000 System, and machine learning methods were used for candidate gene selection of severity. A nested study, comparing severely affected patients bearing or not variants in the selected gene, was used for the characterisation of specific clinical features connected to variants in both acute and post-acute phases. Results: Our GEN-COVID cohort revealed a total of 151 patients carrying at least one RTEL1 ultra-rare variant, which was selected as a specific acute severity feature. From a clinical point of view, these patients showed higher liver function indices, as well as increased CRP and inflammatory markers, such as IL-6. Moreover, compared to control subjects, they present autoimmune disorders more frequently. Finally, their decreased diffusion lung capacity for carbon monoxide after six months of COVID-19 suggests that RTEL1 variants can contribute to the development of SARS-CoV-2-elicited lung fibrosis. Conclusion: RTEL1 ultra-rare variants can be considered as a predictive marker of COVID-19 severity, as well as a marker of pathological evolution in pulmonary fibrosis in the post-COVID phase. This notion can be used for a rapid screening in hospitalized infected people, for vaccine prioritization, and appropriate follow-up assessment for subjects at risk. Trial Registration NCT04549831 (www.clinicaltrial.org

An explainable model of host genetic interactions linked to COVID-19 severity

We employed a multifaceted computational strategy to identify the genetic factors contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing (WES) dataset of a cohort of 2000 Italian patients. We coupled a stratified k-fold screening, to rank variants more associated with severity, with the training of multiple supervised classifiers, to predict severity based on screened features. Feature importance analysis from tree-based models allowed us to identify 16 variants with the highest support which, together with age and gender covariates, were found to be most predictive of COVID-19 severity. When tested on a follow-up cohort, our ensemble of models predicted severity with high accuracy (ACC = 81.88%; AUCROC = 96%; MCC = 61.55%). Our model recapitulated a vast literature of emerging molecular mechanisms and genetic factors linked to COVID-19 response and extends previous landmark Genome-Wide Association Studies (GWAS). It revealed a network of interplaying genetic signatures converging on established immune system and inflammatory processes linked to viral infection response. It also identified additional processes cross-talking with immune pathways, such as GPCR signaling, which might offer additional opportunities for therapeutic intervention and patient stratification. Publicly available PheWAS datasets revealed that several variants were significantly associated with phenotypic traits such as “Respiratory or thoracic disease”, supporting their link with COVID-19 severity outcome

A genome-wide association study for survival from a multi-centre European study identified variants associated with COVID-19 risk of death

The clinical manifestations of SARS-CoV-2 infection vary widely among patients, from asymptomatic to life-threatening. Host genetics is one of the factors that contributes to this variability as previously reported by the COVID-19 Host Genetics Initiative (HGI), which identified sixteen loci associated with COVID-19 severity. Herein, we investigated the genetic determinants of COVID-19 mortality, by performing a case-only genome-wide survival analysis, 60 days after infection, of 3904 COVID-19 patients from the GEN-COVID and other European series (EGAS00001005304 study of the COVID-19 HGI). Using imputed genotype data, we carried out a survival analysis using the Cox model adjusted for age, age2, sex, series, time of infection, and the first ten principal components. We observed a genome-wide significant (P-value < 5.0 × 10−8) association of the rs117011822 variant, on chromosome 11, of rs7208524 on chromosome 17, approaching the genome-wide threshold (P-value = 5.19 × 10−8). A total of 113 variants were associated with survival at P-value < 1.0 × 10−5 and most of them regulated the expression of genes involved in immune response (e.g., CD300 and KLR genes), or in lung repair and function (e.g., FGF19 and CDH13). Overall, our results suggest that germline variants may modulate COVID-19 risk of death, possibly through the regulation of gene expression in immune response and lung function pathways

Clinical features and comorbidity pattern of HCV infected migrants compared to native patients in care in Italy: A real-life evaluation of the PITER cohort

Background: Direct-acting antivirals are highly effective for the treatment of hepatitis C virus (HCV) infection, regardless race/ethnicity. We aimed to evaluate demographic, virological and clinical data of HCV-infected migrants vs. natives consecutively enrolled in the PITER cohort. Methods: Migrants were defined by country of birth and nationality that was different from Italy. Mann-Whitney U test, Chi-squared test and multiple logistic regression were used. Results: Of 10,669 enrolled patients, 301 (2.8%) were migrants: median age 47 vs. 62 years, (p < 0.001), females 56.5% vs. 45.3%, (p < 0.001), HBsAg positivity 3.8% vs. 1.4%, (p < 0.05). Genotype 1b was prevalent in both groups, whereas genotype 4 was more prevalent in migrants (p < 0.05). Liver disease severity and sustained virologic response (SVR) were similar. A higher prevalence of comorbidities was reported for natives compared to migrants (p < 0.05). Liver disease progression cofactors (HBsAg, HIV coinfection, alcohol abuse, potential metabolic syndrome) were present in 39.1% and 47.1% (p > 0.05) of migrants and natives who eradicated HCV, respectively. Conclusion: Compared to natives, HCV-infected migrants in care have different demographics, HCV genotypes, viral coinfections and comorbidities and similar disease severity, SVR and cofactors for disease progression after HCV eradication. A periodic clinical assessment after HCV eradication in Italians and migrants with cofactors for disease progression is warranted

Towards methodological adventure in cost overrun research : linking process and product

The continued adoption of singular paradigms in the study of construction phenomena has elicited dialectical debates in scholarly literature. Calls have been made for more adventurous research methods, beyond the positivist versus interpretivist philosophical divide traditionally embraced by the industry. This study analyses the extensive scholarly debates, advancing and advocating philosophical positions to understand construction phenomena, and further narrows down the argument to within the specific domain of cost overrun research. A systematic and chronological literature review of the methodological/philosophical underpinnings of 41 papers was carried out. The papers were selected by following a staged exclusion criterion. The study outcome reveals that similar dialectical debates and methodological conservatism are still evident, with the predominance of mono-paradigm studies in the bulk of the empirical literature. Most of the empirical literature either provides interpretivist theoretical explanations from qualitative data or positivistically analyses quantitative data to provide technical explanations. To this end, mixed paradigm examples are spotlighted, demonstrating the relevance of linking process and product via methodological adventure in cost overrun research. Transcending the paradigmic divide is necessary to develop a more useful and contextually anchored view of practice, essential to mitigate and provide a holistic understanding of what drives cost overruns in public projects

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)