80 research outputs found
Assessment of DXA derived bone quality indexes and bone geometry parameters in early breast cancer patients: A single center cross-sectional study
Background: Bone mineral density (BMD) lacks sensitivity in individual fracture risk assessment in early breast cancer (EBC) patients treated with aromatase inhibitors (AIs). New dual-energy X-ray absorptiometry (DXA) based risk factors are needed. Methods: Trabecular bone score (TBS), bone strain index (BSI) and DXA parameters of bone geometry were evaluated in postmenopausal women diagnosed with EBC. The aim was to explore their association with morphometric vertebral fractures (VFs). Subjects were categorized in 3 groups in order to evaluate the impact of AIs and denosumab on bone geometry: AI-naive, AI-treated minus (AIDen-) or plus (AIDen+) denosumab. Results: A total of 610 EBC patients entered the study: 305 were AI-naive, 187 AIDen-, and 118 AIDen+. In the AI-naive group, the presence of VFs was associated with lower total hip BMD and T-score and higher femoral BSI. As regards as bone geometry parameters, AI-naive fractured patients reported a significant increase in femoral narrow neck (NN) endocortical width, femoral NN subperiosteal width, intertrochanteric buckling ratio (BR), intertrochanteric endocortical width, femoral shaft (FS) BR and endocortical width, as compared to non-fractured patients. Intertrochanteric BR and intertrochanteric cortical thickness significantly increased in the presence of VFs in AIDen- patients, not in AIDen+ ones. An increase in cross-sectional area and cross-sectional moment of inertia, both intertrochanteric and at FS, significantly correlated with VFs only in AIDen+. No association with VFs was found for either lumbar BSI or TBS in all groups. Conclusions: Bone geometry parameters are variably associated with VFs in EBC patients, either AI-naive or AI treated in combination with denosumab. These data suggest a tailored choice of fracture risk parameters in the 3 subgroups of EBC patients
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
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
Criteria for the definition of Pituitary Tumor Centers of Excellence (PTCOE): A Pituitary Society Statement
The polymorphism L412F in TLR3 inhibits autophagy and is a marker of severe COVID-19 in males
The polymorphism L412F in TLR3 has been associated with several infectious diseases. However, the mechanism underlying this association is still unexplored. Here, we show that the L412F polymorphism in TLR3 is a marker of severity in COVID-19. This association increases in the sub-cohort of males. Impaired macroautophagy/autophagy and reduced TNF/TNFα production was demonstrated in HEK293 cells transfected with TLR3L412F-encoding plasmid and stimulated with specific agonist poly(I:C). A statistically significant reduced survival at 28 days was shown in L412F COVID-19 patients treated with the autophagy-inhibitor hydroxychloroquine (p = 0.038). An increased frequency of autoimmune disorders such as co-morbidity was found in L412F COVID-19 males with specific class II HLA haplotypes prone to autoantigen presentation. Our analyses indicate that L412F polymorphism makes males at risk of severe COVID-19 and provides a rationale for reinterpreting clinical trials considering autophagy pathways. Abbreviations: AP: autophagosome; AUC: area under the curve; BafA1: bafilomycin A1; COVID-19: coronavirus disease-2019; HCQ: hydroxychloroquine; RAP: rapamycin; ROC: receiver operating characteristic; SARS-CoV-2: severe acute respiratory syndrome coronavirus 2; TLR: toll like receptor; TNF/TNF-α: tumor necrosis factor
A survey of clinical features of allergic rhinitis in adults
Background: Allergic rhinitis (AR) has high prevalence and substantial socio-economic burden.
Material/Methods: The study included 35 Italian Centers recruiting an overall number of 3383 adult patients with rhinitis (48% males, 52% females, mean age 29.1, range 18\u201345 years). For each patient, the attending physician had to fill in a standardized questionnaire, covering, in particular, some issues such as the ARIA classification of allergic rhinitis (AR), the results of skin prick test (SPT), the kind of treatment, the response to treatment, and the satisfaction with treatment.
Results: Out of the 3383 patients with rhinitis, 2788 (82.4%) had AR: 311 (11.5%) had a mild intermittent, 229 (8.8%) a mild persistent, 636 (23.5%) a moderate-severe intermittent, and 1518 (56.1%) a moderate-severe persistent form. The most frequently used drugs were oral antihistamines (77.1%) and topical corticosteroids (60.8%). The response to treatment was judged as excellent in 12.2%, good in 41.3%, fair in 31.2%, poor in 14.5%, and very bad in 0.8% of subjects. The rate of treatment dissatisfaction was significantly higher in patients with moderate-to-severe AR than in patients with mild AR (p<0.0001). Indication to allergen immunotherapy (AIT) was significantly more frequent (p<0.01) in patients with severe AR than with mild AR. .
Conclusions: These fndings confirm the appropriateness of ARIA guidelines in classifying the AR patients and the association of severe symptoms with unsuccessful drug treatment. The optimal targeting of patients to be treated with AIT needs to be reassessed
Modelling of Nox and CO emissions of a small gas turbine unit based on operational data and neural networks
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