Clinical management ranges from surveillance or curettage to wide resection for atypical to higher-grade cartilaginous tumours, respectively. Our aim was to investigate the performance of computed ...tomography (CT) radiomics-based machine learning for classification of atypical cartilaginous tumours and higher-grade chondrosarcomas of long bones.
One-hundred-twenty patients with histology-proven lesions were retrospectively included. The training cohort consisted of 84 CT scans from centre 1 (n=55 G1 or atypical cartilaginous tumours; n=29 G2-G4 chondrosarcomas). The external test cohort consisted of the CT component of 36 positron emission tomography-CT scans from centre 2 (n=16 G1 or atypical cartilaginous tumours; n=20 G2-G4 chondrosarcomas). Bidimensional segmentation was performed on preoperative CT. Radiomic features were extracted. After dimensionality reduction and class balancing in centre 1, the performance of a machine-learning classifier (LogitBoost) was assessed on the training cohort using 10-fold cross-validation and on the external test cohort. In centre 2, its performance was compared with preoperative biopsy and an experienced radiologist using McNemar's test.
The classifier had 81% (AUC=0.89) and 75% (AUC=0.78) accuracy in identifying the lesions in the training and external test cohorts, respectively. Specifically, its accuracy in classifying atypical cartilaginous tumours and higher-grade chondrosarcomas was 84% and 78% in the training cohort, and 81% and 70% in the external test cohort, respectively. Preoperative biopsy had 64% (AUC=0.66) accuracy (p=0.29). The radiologist had 81% accuracy (p=0.75).
Machine learning showed good accuracy in classifying atypical and higher-grade cartilaginous tumours of long bones based on preoperative CT radiomic features.
ESSR Young Researchers Grant.
Italy was the first European country to face the SARS-CoV-2 virus (COVID-19) pandemic in 2020. The country quickly implemented strategies to contain contagions and re-organize medical resources. We ...evaluated the COVID-19 effects on the activity of a tertiary-level orthopedic emergency department (ED) during the first and second pandemic waves. We retrospectively collected and compared clinical radiological data of ED admissions during four periods: period A, first pandemic wave; period B, second pandemic wave; period C, three months before the COVID-19 outbreak; period D, same timeframe of the first wave but in 2019. During period A, we found a reduction in ED admissions (-68.2% and -59.9% compared with periods D and C) and a decrease in white codes (non-urgent) (-7.5%) compared with pre-pandemic periods, with a slight increase for all other codes: +6.3% green (urgent, not critical), +0.8% yellow (moderately critical) and +0.3% red (highly urgent, risk of death). We observed an increased rate of fracture diagnosis in period A: +14.9% and +13.3% compared with periods D and C. Our study shows that the COVID-19 pandemic caused a drastic change in the ED patient flow and clinical radiological activity, with a marked reduction in admissions and an increased rate of more severe triage codes and diagnosed fractures.
Growing evidence suggests that artificial intelligence tools could help radiologists in differentiating COVID-19 pneumonia from other types of viral (non-COVID-19) pneumonia. To test this hypothesis, ...an R-AI classifier capable of discriminating between COVID-19 and non-COVID-19 pneumonia was developed using CT chest scans of 1031 patients with positive swab for SARS-CoV-2 (
= 647) and other respiratory viruses (
= 384). The model was trained with 811 CT scans, while 220 CT scans (
= 151 COVID-19;
= 69 non-COVID-19) were used for independent validation. Four readers were enrolled to blindly evaluate the validation dataset using the CO-RADS score. A pandemic-like high suspicion scenario (CO-RADS 3 considered as COVID-19) and a low suspicion scenario (CO-RADS 3 considered as non-COVID-19) were simulated. Inter-reader agreement and performance metrics were calculated for human readers and R-AI classifier. The readers showed good agreement in assigning CO-RADS score (Gwet's AC2 = 0.71,
< 0.001). Considering human performance, accuracy = 78% and accuracy = 74% were obtained in the high and low suspicion scenarios, respectively, while the AI classifier achieved accuracy = 79% in distinguishing COVID-19 from non-COVID-19 pneumonia on the independent validation dataset. The R-AI classifier performance was equivalent or superior to human readers in all comparisons. Therefore, a R-AI classifier may support human readers in the difficult task of distinguishing COVID-19 from other types of viral pneumonia on CT imaging.
•Maiorca malt possesses the technological parameters required for brewing cereals.•Maiorca malt has adequate enzymatic activity resulting in better extraction values.•Brewing with 100 % Maiorca malt ...offers a novel approach in the brewing sector.
This study explores the potential of Maiorca wheat malt as an alternative ingredient in beer production, investigating its impact on the brewing process and beer quality at different recipe contents (50 %, 75 %, 100 %). The study encompasses a comprehensive analysis of key malt parameters, revealing Maiorca malt’s positive influence on maltose, glucose, filterability, extract, free amino nitrogen, and fermentability. Notably, the malt exhibited heightened levels of α-amylase and β-amylase enzymes compared to conventional commercial malt. Furthermore, the analysis of aroma compounds and subsequent sensory evaluations unveiled a significant correlation between the proportion of Maiorca malt in the formulation and intensified estery, fruity, malty, honey, complemented by a reduction in attributes such as aromatic compounds, phenolic, yeasty, sulfury, oxidized, and solvent-like odors. This research underscores the favorable contribution of Maiorca wheat malt to enhancing both the brewing process and final beer quality, highlighting its potential as an innovative ingredient in brewing practices.
The natural isoflavone phytoestrogen genistein has been shown to stimulate osteoblastic bone formation, inhibit osteoclastic bone resorption, and prevent bone loss in ovariectomized rats. However, no ...controlled clinical trial has been performed so far to evaluate the effects of the phytoestrogen on bone loss in postmenopausal women. We performed a randomized double‐blind placebo‐controlled study to evaluate and compare with hormone‐replacement therapy (HRT) the effect of the phytoestrogen genistein on bone metabolism and bone mineral density (BMD) in postmenopausal women. Participants were 90 healthy ambulatory women who were 47–57 years of age, with a BMD at the femoral neck of <0.795 g/cm2. After a 4‐week stabilization on a standard fat‐reduced diet, participants of the study were randomly assigned to receive continuous HRT for 1 year (n = 30; 1 mg of 17β‐estradiol E2 combined with 0.5 mg of norethisterone acetate), the phytoestrogen genistein (n = 30; 54 mg/day), or placebo (n = 30). Urinary excretion of pyridinoline (PYR) and deoxypyridinoline (DPYR) was not significantly modified by placebo administration either at 6 months or at 12 months. Genistein treatment significantly reduced the excretion of pyridinium cross‐links at 6 months (PYR = −54 ± 10%; DPYR = −55 ± 13%; p < 0.001) and 12 months (PYR = −42 ± 12%; DPYR = −44 ± 16%; p < 0.001). A similar and not statistically different decrease in excretion of pyridinium cross‐links was also observed in the postmenopausal women randomized to receive HRT. Placebo administration did not change the serum levels of the bone‐specific ALP (B‐ALP) and osteocalcin (bone Gla protein BGP). In contrast, administration of genistein markedly increased serum B‐ALP and BGP either at 6 months (B‐ALP = 23 ± 4%; BGP = 29 ± 11%; p < 0.005) or at 12 months (B‐ALP = 25 ± 7%; BGP = 37 ± 16%; p < 0.05). Postmenopausal women treated with HRT had, in contrast, decreased serum B‐ALP and BGP levels either at 6 months (B‐ALP = −17 ± 6%; BGP = −20 ± 9%; p < 0.001) or 12 months (B‐ALP = −20 ± 5%; BGP = −22 ± 10%; p < 0.001). Furthermore, at the end of the experimental period, genistein and HRT significantly increased BMD in the femur (femoral neck: genistein = 3.6 ± 3%, HRT = 2.4 ± 2%, placebo = −0.65 ± 0.1%, and p < 0.001) and lumbar spine (genistein = 3 ± 2%, HRT = 3.8 ± 2.7%, placebo = −1.6 ± 0.3%, and p < 0.001). This study confirms the genistein‐positive effects on bone loss already observed in the experimental models of osteoporosis and indicates that the phytoestrogen reduces bone resorption and increases bone formation in postmenopausal women.
Background
If Parkinson’s Disease (PD) may represent a risk factor for Coronavirus disease 2019 (COVID-19) is debated and there are few data on the direct and indirect effects of this pandemic in PD ...patients.
Objective
In the current study we evaluated the prevalence, mortality and case-fatality of COVID-19 in a PD cohort, also exploring possible risk factors. We also aimed to investigate the effect of lockdown on motor/non-motor symptoms in PD patients as well as their acceptability/accessibility to telemedicine.
Method
A case-controlled survey about COVID-19 and other clinical features in PD patients living in Tuscany was conducted. In non-COVID-19 PD patients motor/non-motor symptoms subjective worsening during the lockdown as well as feasibility of telemedicine were explored.
Results
Out of 740 PD patients interviewed, 7 (0.9%) were affected by COVID-19, with 0.13% mortality and 14% case-fatality. COVID-19 PD patients presented a higher presence of hypertension (
p
< 0.001) and diabetes (
p
= 0.049) compared to non-COVID-19. In non-COVID-19 PD population (
n
= 733) about 70% did not experience a subjective worsening of motor symptoms or mood, anxiety or insomnia. In our population 75.2% of patients was favorable to use technology to perform scheduled visits, however facilities for telemedicine were available only for 51.2% of cases.
Conclusion
A higher prevalence of COVID-19 respect to prevalence in Tuscany and Italy was found in the PD population. Hypertension and diabetes, as for general population, were identified as risk factors for COVID-19 in PD. PD patients did not experience a subjective worsening of symptoms during lockdown period and they were also favorable to telemedicine, albeit we reported a reduced availability to perform it.
Osteoporosis represents an important cause of morbidity in adult thalassemic patients, and its pathogenesis has not, as yet, been completely clarified. In our study, we observed that thalassemic ...patients showed a significantly lower OPG/RANKL ratio than normal subjects. These data are extremely important for the possible therapeutic use of RANKL antagonists such as OPG in thalassemia‐induced osteoporosis.
Introduction: Osteoporosis represents an important cause of morbidity in adult thalassemic patients who display increased fracture risk. The etiology of this bone disease is multifactorial, but it is thought that the main role is played by hypogonadism. The mechanisms by which the skeletal effects of sex steroids are mediated are still not fully understood. Recently, two new cytokines, osteoprotegerin (OPG) and RANKL, have been implicated in the pathogenesis of postmenopausal osteoporosis and other metabolic bone diseases. Thus, the aim of this study was to characterize the possible role of the OPG/RANKL system in thalassemia‐related bone loss.
Materials and Methods: We measured, in 30 thalassemic patients and in 20 healthy control subjects, serum OPG and RANKL levels, and determined their correlations with bone turnover markers, BMD, sex steroid levels, erythropoietin, and hemoglobin.
Results: Thalassemic patients had an unbalanced bone turnover with an increased resorption phase (shown by high levels of pyridinium cross‐links) and a decreased neoformation phase (shown by the slightly low levels of osteocalcin). Moreover, they displayed lower BMD values than controls both at the lumbar and femoral level. As far as the OPG/RANKL system is concerned, thalassemic patients showed no differences in plasma levels of OPG compared with controls, and significantly higher plasma levels of RANKL, with a consequent significantly lower OPG/RANKL ratio.
Conclusions: Our data suggest that, in thalassemic patients, an altered modulation of the OPG/RANKL system, resulting in increased expression of RANKL by stromal or osteoblastic cells, could contribute to the enhanced osteoclastic bone resorption and bone loss characteristic of these patients.
Composites obtained by bio-derived polymers are promising materials for the realization of green sensors. Bio-derived composites consisting of a sheet of bacterial cellulose, covered on both faces by ...two layers of conducting polymers and infused by ionic liquids have been demonstrated to have generating properties when used as deformation sensor. In the paper, the frequency analysis of the composite is investigated in order to experimentally determine the dependence of the transduction property on the frequency of the applied mechanical deformation. A model has been proposed to fit experimental data.
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