Bombus terrestris terrestris (Linnaeus, 1758) and hybrids with the endemic Bombus xanthopus spotted on Capraia Island (Tuscan Archipelago, Italy): some conservation management implications.

Expansion of wild and managed allochthonous species leads to potential negative consequences for the endemic wildlife, such as resource competition, pathogens spread, hybridization and native species replacements. On Capraia Island, the last sighting of Bombus terrestris terrestris dates back to 1917. All subsequent surveys carried out on the island only reported the presence of B. xanthopus and B. pascuorum melleofacies with B. t. terrestris apparently no longer existing in the area. In 2021 B. t. terrestris was again detected on the island raising two main hypotheses: (i) B. t. terrestris has always been present with a low population density, such as not to be detected in previous investigations, or (ii) its presence is the result of a more recent recolonization. The recolonization event may be promoted by either intentional or unintentional introduction or it may be the result of a natural migration from the mainland or surrounding islands. Hybridization between B. t. terrestris × B. xanthopus on Capraia Island has been also ascertained by the detection of hybrid queens, workers and males. These new finding provides insight on the distribution range of B. t. terrestris in the Tuscan Archipelago and raise concern on the conservation of the endemic B. xanthopus population.

Structured reporting of computed tomography in the polytrauma patient assessment: a Delphi consensus proposal.

OBJECTIVES: To develop a structured reporting (SR) template for whole-body CT examinations of polytrauma patients, based on the consensus of a panel of emergency radiology experts from the Italian Society of Medical and Interventional Radiology. METHODS: A multi-round Delphi method was used to quantify inter-panelist agreement for all SR sections. Internal consistency for each section and quality analysis in terms of average inter-item correlation were evaluated by means of the Cronbach's alpha (Cα) correlation coefficient. RESULTS: The final SR form included 118 items (6 in the "Patient Clinical Data" section, 4 in the "Clinical Evaluation" section, 9 in the "Imaging Protocol" section, and 99 in the "Report" section). The experts' overall mean score and sum of scores were 4.77 (range 1-5) and 257.56 (range 206-270) in the first Delphi round, and 4.96 (range 4-5) and 208.44 (range 200-210) in the second round, respectively. In the second Delphi round, the experts' overall mean score was higher than in the first round, and standard deviation was lower (3.11 in the second round vs 19.71 in the first round), reflecting a higher expert agreement in the second round. Moreover, Cα was higher in the second round than in the first round (0.97 vs 0.87). CONCLUSIONS: Our SR template for whole-body CT examinations of polytrauma patients is based on a strong agreement among panel experts in emergency radiology and could improve communication between radiologists and the trauma team.

Bridging gaps between images and data: a systematic update on imaging biobanks.

BACKGROUND AND OBJECTIVE: The systematic collection of medical images combined with imaging biomarkers and patient non-imaging data is the core concept of imaging biobanks, a key element for fuelling the development of modern precision medicine. Our purpose is to review the existing image repositories fulfilling the criteria for imaging biobanks. METHODS: Pubmed, Scopus and Web of Science were searched for articles published in English from January 2010 to July 2021 using a combination of the terms: "imaging" AND "biobanks" and "imaging" AND "repository". Moreover, the Community Research and Development Information Service (CORDIS) database ( https://cordis.europa.eu/projects ) was searched using the terms: "imaging" AND "biobanks", also including collections, projects, project deliverables, project publications and programmes. RESULTS: Of 9272 articles retrieved, only 54 related to biobanks containing imaging data were finally selected, of which 33 were disease-oriented (61.1%) and 21 population-based (38.9%). Most imaging biobanks were European (26/54, 48.1%), followed by American biobanks (20/54, 37.0%). Among disease-oriented biobanks, the majority were focused on neurodegenerative (9/33, 27.3%) and oncological diseases (9/33, 27.3%). The number of patients enrolled ranged from 240 to 3,370,929, and the imaging modality most frequently involved was MRI (40/54, 74.1%), followed by CT (20/54, 37.0%), PET (13/54, 24.1%), and ultrasound (12/54, 22.2%). Most biobanks (38/54, 70.4%) were accessible under request. CONCLUSIONS: Imaging biobanks can serve as a platform for collecting, sharing and analysing medical images integrated with imaging biomarkers, biological and clinical data. A relatively small proportion of current biobanks also contain images and can thus be classified as imaging biobanks. KEY POINTS: • Imaging biobanks are a powerful tool for large-scale collection and processing of medical images integrated with imaging biomarkers and patient non-imaging data. • Most imaging biobanks retrieved were European, disease-oriented and accessible under user request. • While many biobanks have been developed so far, only a relatively small proportion of them are imaging biobanks.

How temperature rise will influence the toxic impacts of 17 α-ethinylestradiol in Mytilus galloprovincialis?

Pharmaceutical drugs are Contaminants of Emerging Concern (CECs) and are continuously discharged into the environment. As a result of human and veterinary use, these substances are reaching aquatic coastal systems, with limited information regarding the toxic effects of these compounds towards inhabiting organisms. Among CECs are pharmaceuticals like 17 α-ethinylestradiol (EE2), which is a synthetic hormone with high estrogenic potency. EE2 has been increasingly found in different aquatic systems but few studies addressed its potential toxicity to marine wildlife, in particular to bivalves. Therefore, the aim of the present study was to evaluate the influence of temperature (17 °C-control and 21 °C) on the potential effects of EE2 on the mussel Mytilus galloprovincialis. For this purpose, mussels were exposed to different concentrations of EE2 (5.0; 25.0; 125.0 and 625 ng/L), resembling low to highly polluted sites. Mussels exposed to each concentration were maintained under two temperatures, 17 and 21 °C, which represent actual and predicted warming conditions, respectively. After 28 days, oxidative stress status, metabolism related parameters, neurotoxicity and histopathological alterations were measured. The results obtained clearly showed an interactive effect of increased temperature and EE2, with limited antioxidant and biotransformation capacity when both stressors were acting together, leading to higher cellular damage. The combination of both stressors also enhanced mussels' metabolic capacity and neurotoxic effects. Nevertheless, loss of redox balance was confirmed by the strong decrease of the ratio between reduce glutathione (GSH) and oxidized glutathione (GSSG) in contaminated mussels, regardless the temperature. Histopathological indexes in contaminated mussels were significantly different from the control group, indicating impacts in gills and digestive glands of mussels due to EE2, with higher values observed at 21 °C. Overall, this study demonstrates that of EE2 represents a threat to mussels and predicted warming conditions will enhance the impacts, which in a near future might result in impairments at the population and community levels.

A narrative review on current imaging applications of artificial intelligence and radiomics in oncology: focus on the three most common cancers.

The use of artificial intelligence (AI) and radiomics in the healthcare setting to advance disease diagnosis and management and facilitate the creation of new therapeutics is gaining popularity. Given the vast amount of data collected during cancer therapy, there is significant concern in leveraging the algorithms and technologies available with the underlying goal of improving oncologic care. Radiologists will attain better precision and effectiveness with the advent of AI technology, making machine-assisted medical services a valuable and important option for future oncologic medical care. As a result, it is critical to figure out which specific radiology activities are best positioned to gain from AI and radiomics models and methods of oncologic imaging, while also considering the algorithms' capabilities and constraints. Our purpose is to overview the current evidence and future prospects of AI and radiomics algorithms used in oncologic imaging efforts with an emphasis on the three most frequent cancers worldwide, i.e., lung cancer, breast cancer and colorectal cancer. We discuss how AI and radiomics could be used to detect and characterize cancers and assess therapy response.

Extracorporeal membrane oxygenation (ECMO) in COVID-19 patients: a pocket guide for radiologists.

During the coronavirus disease 19 (COVID-19) pandemic, extracorporeal membrane oxygenation (ECMO) has been proposed as a possible therapy for COVID-19 patients with acute respiratory distress syndrome. This pictorial review is intended to provide radiologists with up-to-date information regarding different types of ECMO devices, correct placement of ECMO cannulae, and imaging features of potential complications and disease evolution in COVID-19 patients treated with ECMO, which is essential for a correct interpretation of diagnostic imaging, so as to guide proper patient management.

Clinical implications of microvascular CT scan signs in COVID-19 patients requiring invasive mechanical ventilation.

PURPOSE: COVID-19-related acute respiratory distress syndrome (ARDS) is characterized by the presence of signs of microvascular involvement at the CT scan, such as the vascular tree in bud (TIB) and the vascular enlargement pattern (VEP). Recent evidence suggests that TIB could be associated with an increased duration of invasive mechanical ventilation (IMV) and intensive care unit (ICU) stay. The primary objective of this study was to evaluate whether microvascular involvement signs could have a prognostic significance concerning liberation from IMV. MATERIAL AND METHODS: All the COVID-19 patients requiring IMV admitted to 16 Italian ICUs and having a lung CT scan recorded within 3 days from intubation were enrolled in this secondary analysis. Radiologic, clinical and biochemical data were collected. RESULTS: A total of 139 patients affected by COVID-19 related ARDS were enrolled. After grouping based on TIB or VEP detection, we found no differences in terms of duration of IMV and mortality. Extension of VEP and TIB was significantly correlated with ground-glass opacities (GGOs) and crazy paving pattern extension. A parenchymal extent over 50% of GGO and crazy paving pattern was more frequently observed among non-survivors, while a VEP and TIB extent involving 3 or more lobes was significantly more frequent in non-responders to prone positioning. CONCLUSIONS: The presence of early CT scan signs of microvascular involvement in COVID-19 patients does not appear to be associated with differences in duration of IMV and mortality. However, patients with a high extension of VEP and TIB may have a reduced oxygenation response to prone positioning. TRIAL REGISTRATION: NCT04411459.

Structured reporting of computed tomography in the staging of colon cancer: a Delphi consensus proposal.

BACKGROUND: Structured reporting (SR) in radiology is becoming increasingly necessary and has been recognized recently by major scientific societies. This study aims to build structured CT-based reports in colon cancer during the staging phase in order to improve communication between the radiologist, members of multidisciplinary teams and patients. MATERIALS AND METHODS: A panel of expert radiologists, members of the Italian Society of Medical and Interventional Radiology, was established. A modified Delphi process was used to develop the SR and to assess a level of agreement for all report sections. Cronbach's alpha (Cα) correlation coefficient was used to assess internal consistency for each section and to measure quality analysis according to the average inter-item correlation. RESULTS: The final SR version was built by including n = 18 items in the "Patient Clinical Data" section, n = 7 items in the "Clinical Evaluation" section, n = 9 items in the "Imaging Protocol" section and n = 29 items in the "Report" section. Overall, 63 items were included in the final version of the SR. Both in the first and second round, all sections received a higher than good rating: a mean value of 4.6 and range 3.6-4.9 in the first round; a mean value of 5.0 and range 4.9-5 in the second round. In the first round, Cronbach's alpha (Cα) correlation coefficient was a questionable 0.61. In the first round, the overall mean score of the experts and the sum of scores for the structured report were 4.6 (range 1-5) and 1111 (mean value 74.07, STD 4.85), respectively. In the second round, Cronbach's alpha (Cα) correlation coefficient was an acceptable 0.70. In the second round, the overall mean score of the experts and the sum of score for structured report were 4.9 (range 4-5) and 1108 (mean value 79.14, STD 1.83), respectively. The overall mean score obtained by the experts in the second round was higher than the overall mean score of the first round, with a lower standard deviation value to underline greater agreement among the experts for the structured report reached in this round. CONCLUSIONS: A wide implementation of SR is of critical importance in order to offer referring physicians and patients optimum quality of service and to provide researchers with the best quality data in the context of big data exploitation of available clinical data. Implementation is a complex procedure, requiring mature technology to successfully address the multiple challenges of user-friendliness, organization and interoperability.

Structured reporting of x-ray mammography in the first diagnosis of breast cancer: a Delphi consensus proposal.

BACKGROUND: Radiology is an essential tool in the management of a patient. The aim of this manuscript was to build structured report (SR) Mammography based in Breast Cancer. METHODS: A working team of 16 experts (group A) was composed to create a SR for Mammography Breast Cancer. A further working group of 4 experts (group B), blinded to the activities of the group A, was composed to assess the quality and clinical usefulness of the SR final draft. Modified Delphi process was used to assess level of agreement for all report sections. Cronbach's alpha (Cα) correlation coefficient was used to assess internal consistency and to measure quality analysis according to the average inter-item correlation. RESULTS: The final SR version was built by including n = 2 items in Personal Data, n = 4 items in Setting, n = 2 items in Comparison with previous breast examination, n = 19 items in Anamnesis and clinical context; n = 10 items in Technique; n = 1 item in Radiation dose; n = 5 items Parenchymal pattern; n = 28 items in Description of the finding; n = 12 items in Diagnostic categories and Report and n = 1 item in Conclusions. The overall mean score of the experts and the sum of score for structured report were 4.9 and 807 in the second round. The Cronbach's alpha (Cα) correlation coefficient was 0.82 in the second round. About the quality evaluation, the overall mean score of the experts was 3.3. The Cronbach's alpha (Cα) correlation coefficient was 0.90. CONCLUSIONS: Structured reporting improves the quality, clarity and reproducibility of reports across departments, cities, countries and internationally and will assist patient management and improve breast health care and facilitate research.

Preliminary investigation on enzymatic activity in saliva of Hystrix cristata L., 1758.

Mammal's saliva contains a variety of electrolytes and proteins. They carry out an important role in the digestion process, in the antibacterial and antiviral activity, in lubrication and maintenance of oral general health status. It may also contain several enzymes according to dietary habits and general wellness. Sialochemistry is a valid alternative to the haematochemical analysis for the evaluation of animal health and nutritional status. At present, very little knowledge is available on health status and pathology of crested porcupine (Hystrix cristata) and no data are yet available on salivary enzymes. Between 2018 and 2020, a preliminary investigation of enzymatic activity on saliva samples was carried out from captured porcupines. In crested porcupine saliva, enzymatic activity of trypsin, chymotrypsin, N-Aminopeptidase, amylase, lignin peroxidise, cellulase and chitinase were recorded. Superoxide dismutase, catalase, glutathione S-transferase and alkaline phosphatase activity was also detected. The superoxide dismutase activity resulted higher (3.13 SD 3.58 U/mg proteins) than those of catalase (130.80 SD 110.65 mU/mg proteins) and glutathione S-transferase (20.21 SD 16.62 mM/mg proteins). Alkaline phosphatase activity resulted lower (5.91 SD 6.12 mU/mg proteins) than acidic phosphatase (19.00 SD 16.16 U/mg proteins) with the highest values of saliva alkaline phosphatases recorded in young individuals. These preliminary data bring new knowledge on crested porcupine saliva enzymes and may provide a useful tool for further investigation on the adaptive response of crested porcupine to different environmental condition and diet. Additional investigation concerning a possible alternative use of saliva enzymes as indicator of health and nutritional status of this rodent are desirable.

3D Patient-Specific Virtual Models for Presurgical Planning in Patients with Recto-Sigmoid Endometriosis Nodules: A Pilot Study.

Background and Objective: In recent years, 3D printing has been used to support surgical planning or to guide intraoperative procedures in various surgical specialties. An improvement in surgical planning for recto-sigmoid endometriosis (RSE) excision might reduce the high complication rate related to this challenging surgery. The aim of this study was to build novel presurgical 3D models of RSE nodules from magnetic resonance imaging (MRI) and compare them with intraoperative findings. Materials and Methods: A single-center, observational, prospective, cohort, pilot study was performed by enrolling consecutive symptomatic women scheduled for minimally invasive surgery for RSE between November 2019 and June 2020 at our institution. Preoperative MRI were used for building 3D models of RSE nodules and surrounding pelvic organs. 3D models were examined during multi-disciplinary preoperative planning, focusing especially on three domains: degree of bowel stenosis, nodule's circumferential extension, and bowel angulation induced by the RSE nodule. After surgery, the surgeon was asked to subjectively evaluate the correlation of the 3D model with the intra-operative findings and to express his evaluation as "no correlation", "low correlation", or "high correlation" referring to the three described domains. Results: seven women were enrolled and 3D anatomical virtual models of RSE nodules and surrounding pelvic organs were generated. In all cases, surgeons reported a subjective "high correlation" with the surgical findings. Conclusion: Presurgical 3D models could be a feasible and useful tool to support surgical planning in women with recto-sigmoidal endometriotic involvement, appearing closely related to intraoperative findings.

Quantitative imaging decision support (QIDSTM) tool consistency evaluation and radiomic analysis by means of 594 metrics in lung carcinoma on chest CT scan.

OBJECTIVE: To evaluate the consistency of the quantitative imaging decision support (QIDSTM) tool and radiomic analysis using 594 metrics in lung carcinoma on chest CT scan. MATERIALS AND METHODS: We included, retrospectively, 150 patients with histologically confirmed lung cancer who underwent chemotherapy and baseline and follow-ups CT scans. Using the QIDSTM platform, 3 radiologists segmented each lesion and automatically collected the longest diameter and the density mean value. Inter-observer variability, Bland Altman analysis and Spearman's correlation coefficient were performed. QIDSTM tool consistency was assessed in terms of agreement rate in the treatment response classification. Kruskal Wallis test and the least absolute shrinkage and selection operator (LASSO) method with 10-fold cross validation were used to identify radiomic metrics correlated with lesion size change. RESULTS: Good and significant correlation was obtained between the measurements of largest diameter and of density among the QIDSTM tool and the radiologists measurements. Inter-observer variability values were over 0.85. HealthMyne QIDSTM tool quantitative volumetric delineation was consistent and matched with each radiologist measurement considering the RECIST classification (80-84%) while a lower concordance among QIDSTM and the radiologists CHOI classification was observed (58-63%). Among 594 extracted metrics, significant and robust predictors of RECIST response were energy, histogram entropy and uniformity, Kurtosis, coronal long axis, longest planar diameter, surface, Neighborhood Grey-Level Different Matrix (NGLDM) dependence nonuniformity and low dependence emphasis as Volume, entropy of Log(2.5 mm), wavelet energy, deviation and root man squared. CONCLUSION: In conclusion, we demonstrated that HealthMyne quantitative volumetric delineation was consistent and that several radiomic metrics extracted by QIDSTM were significant and robust predictors of RECIST response.

An international survey on AI in radiology in 1,041 radiologists and radiology residents part 1: fear of replacement, knowledge, and attitude.

OBJECTIVES: Radiologists' perception is likely to influence the adoption of artificial intelligence (AI) into clinical practice. We investigated knowledge and attitude towards AI by radiologists and residents in Europe and beyond. METHODS: Between April and July 2019, a survey on fear of replacement, knowledge, and attitude towards AI was accessible to radiologists and residents. The survey was distributed through several radiological societies, author networks, and social media. Independent predictors of fear of replacement and a positive attitude towards AI were assessed using multivariable logistic regression. RESULTS: The survey was completed by 1,041 respondents from 54 mostly European countries. Most respondents were male (n = 670, 65%), median age was 38 (24-74) years, n = 142 (35%) residents, and n = 471 (45%) worked in an academic center. Basic AI-specific knowledge was associated with fear (adjusted OR 1.56, 95% CI 1.10-2.21, p = 0.01), while intermediate AI-specific knowledge (adjusted OR 0.40, 95% CI 0.20-0.80, p = 0.01) or advanced AI-specific knowledge (adjusted OR 0.43, 95% CI 0.21-0.90, p = 0.03) was inversely associated with fear. A positive attitude towards AI was observed in 48% (n = 501) and was associated with only having heard of AI, intermediate (adjusted OR 11.65, 95% CI 4.25-31.92, p < 0.001), or advanced AI-specific knowledge (adjusted OR 17.65, 95% CI 6.16-50.54, p < 0.001). CONCLUSIONS: Limited AI-specific knowledge levels among radiology residents and radiologists are associated with fear, while intermediate to advanced AI-specific knowledge levels are associated with a positive attitude towards AI. Additional training may therefore improve clinical adoption. KEY POINTS: • Forty-eight percent of radiologists and residents have an open and proactive attitude towards artificial intelligence (AI), while 38% fear of replacement by AI. • Intermediate and advanced AI-specific knowledge levels may enhance adoption of AI in clinical practice, while rudimentary knowledge levels appear to be inhibitive. • AI should be incorporated in radiology training curricula to help facilitate its clinical adoption.

An international survey on AI in radiology in 1041 radiologists and radiology residents part 2: expectations, hurdles to implementation, and education.

OBJECTIVES: Currently, hurdles to implementation of artificial intelligence (AI) in radiology are a much-debated topic but have not been investigated in the community at large. Also, controversy exists if and to what extent AI should be incorporated into radiology residency programs. METHODS: Between April and July 2019, an international survey took place on AI regarding its impact on the profession and training. The survey was accessible for radiologists and residents and distributed through several radiological societies. Relationships of independent variables with opinions, hurdles, and education were assessed using multivariable logistic regression. RESULTS: The survey was completed by 1041 respondents from 54 countries. A majority (n = 855, 82%) expects that AI will cause a change to the radiology field within 10 years. Most frequently, expected roles of AI in clinical practice were second reader (n = 829, 78%) and work-flow optimization (n = 802, 77%). Ethical and legal issues (n = 630, 62%) and lack of knowledge (n = 584, 57%) were mentioned most often as hurdles to implementation. Expert respondents added lack of labelled images and generalizability issues. A majority (n = 819, 79%) indicated that AI should be incorporated in residency programs, while less support for imaging informatics and AI as a subspecialty was found (n = 241, 23%). CONCLUSIONS: Broad community demand exists for incorporation of AI into residency programs. Based on the results of the current study, integration of AI education seems advisable for radiology residents, including issues related to data management, ethics, and legislation. KEY POINTS: • There is broad demand from the radiological community to incorporate AI into residency programs, but there is less support to recognize imaging informatics as a radiological subspecialty. • Ethical and legal issues and lack of knowledge are recognized as major bottlenecks for AI implementation by the radiological community, while the shortage in labeled data and IT-infrastructure issues are less often recognized as hurdles. • Integrating AI education in radiology curricula including technical aspects of data management, risk of bias, and ethical and legal issues may aid successful integration of AI into diagnostic radiology.

How temperature can alter the combined effects of carbon nanotubes and caffeine in the clam Ruditapes decussatus?

Nowadays, multi-walled carbon nanotubes are considered to be emerging contaminants and their impact in ecosystem has drawn special research attention, while other contaminants, such as caffeine, have more coverage in literature. Despite this, the effects of a combination of the two has yet to be evaluated, especially considering predicted temperature rise. In the present study a typical bioindicator species for marine environment, the clam Ruditapes decussatus, and classical tools, such as biomarkers and histopathological indices, were used to shed light on the species' response to these contaminants, under actual and predicted warming scenarios. The results obtained showed that both contaminants have a harmful effect at tissue level, as shown by higher histopathological index, especially in digestive tubules. Temperatures seemed to induce greater biochemical impacts than caffeine (CAF) and -COOH functionalized multi-walled carbon nanotubes (f-MWCNTs) when acting alone, namely in terms of antioxidant defences and energy reserves content, which were exacerbated when both contaminants were acting in combination (MIX treatment). Overall, the present findings highlight the complex response of clams to both pollutants, evidencing the role of temperature on clams' sensitivity, especially to mixture of pollutants.

How Ulva lactuca can influence the impacts induced by the rare earth element Gadolinium in Mytilus galloprovincialis? The role of macroalgae in water safety towards marine wildlife.

Rare earth elements (REEs) are gaining growing attention in environmental and ecotoxicological studies due to their economic relevance, wide range of applications and increasing environmental concentrations. Among REEs, special consideration should be given to Gadolinium (Gd), whose wide exploitation as a magnetic resonance imaging (MRI) contrast agent is enhancing the risk of its occurrence in aquatic environments and impacts on aquatic organisms. A promising approach for water decontamination from REEs is sorption, namely through the use of macroalgae and in particular Ulva lactuca that already proved to be an efficient biosorbent for several chemical elements. Therefore, the present study aimed to evaluate the toxicity of Gd, comparing the biochemical effects induced by this element in the presence or absence of algae. Using the bivalve species Mytilus galloprovincialis, Gd toxicity was evaluated by assessing changes on mussels' metabolic capacity and oxidative status. Results clearly showed the toxicity of Gd but further revealed the capacity of U. lactuca to prevent injuries to M. galloprovincialis, mainly reducing the levels of Gd in water and thus the bioaccumulation and toxicity of this element by the mussels. The results will advance the state of the art not only regarding the effects of REEs but also with regard to the role of algae in accumulation of metals and protection of aquatic organisms, generating new insights on water safety towards aquatic wildlife and highlighting the possibility for resources recovery.

Comparing the first and the second waves of COVID-19 in Italy: differences in epidemiological features and CT findings using a semi-quantitative score.

PURPOSE: CT findings of hospitalized COVID-19 patients were analyzed during both the first and the second waves of the pandemic, in order to detect any significant differences between the two groups. METHODS: In this observational, retrospective, monocentric study, all hospitalized patients who underwent CT for suspected COVID-19 pneumonia from February 27 to March 27, 2020 (first wave) and from October 26 to November 24, 2020 (second wave) were enrolled. Epidemiological data, radiological pattern according to the RSNA consensus statement and visual score extension using a semi-quantitative score were compared. RESULTS: Two hundred and eleven patients (mean age, 64.52 years ± 15.14, 144 males) were evaluated during the first wave while 455 patients (mean age, 68.26 years ± 16.34, 283 males) were studied during the second wave. The same prevalence of patterns was documented in both the first and the second waves (p = 0.916), with non-typical patterns always more frequently observed in elderly patients, especially the "indeterminate" pattern. Compared to those infected during the first wave, the patients of the second wave were older (64.52 vs.68.26, p = 0.005) and presented a slightly higher mean semi-quantitative score (9.0 ± 2.88 vs. 8.4 ± 3.06, p = 0.042). Age and semi-quantitative score showed a positive correlation (r = 0.15, p = 0.001). CONCLUSIONS: There was no difference regarding CT pattern prevalence between the first and the second waves, confirming both the validity of the RSNA consensus and the most frequent radiological COVID-19 features. Non-typical COVID-19 features were more frequently observed in older patients, thus should not be underestimated in the elderly population.

Artificial intelligence: radiologists' expectations and opinions gleaned from a nationwide online survey.

PURPOSE: To report the results of a nationwide online survey on artificial intelligence (AI) among radiologist members of the Italian Society of Medical and Interventional Radiology (SIRM). METHODS AND MATERIALS: All members were invited to the survey as an initiative by the Imaging Informatics Chapter of SIRM. The survey consisted of 13 questions about the participants' demographic information, perceived advantages and issues related to AI implementation in radiological practice, and their overall opinion about AI. RESULTS: In total, 1032 radiologists (equaling 9.5% of active SIRM members for the year 2019) joined the survey. Perceived AI advantages included a lower diagnostic error rate (750/1027, 73.0%) and optimization of radiologists' work (697/1027, 67.9%). The risk of a poorer professional reputation of radiologists compared with non-radiologists (617/1024, 60.3%), and increased costs and workload due to AI system maintenance and data analysis (399/1024, 39.0%) were seen as potential issues. Most radiologists stated that specific policies should regulate the use of AI (933/1032, 90.4%) and were not afraid of losing their job due to it (917/1032, 88.9%). Overall, 77.0% of respondents (794/1032) were favorable to the adoption of AI, whereas 18.0% (186/1032) were uncertain and 5.0% (52/1032) were unfavorable. CONCLUSIONS: Radiologists had a mostly positive attitude toward the implementation of AI in their working practice. They were not concerned that AI will replace them, but rather that it might diminish their professional reputation.

Phenolic Profiles of Red Wine Relate to Vascular Endothelial Benefits Mediated by SIRT1 and SIRT6.

Dietary phenolic compounds possess potent bioactivity against inflammatory pathways of chronic inflammatory conditions, such as type 2 diabetes. Here, the phenolic profile and bioactivity of Italian red wines Gaglioppo, Magliocco, and Nerello Mascalese were characterized. NMR, HPLC/UV-Vis and spectrophotometric characterization showed that Magliocco was the richest wine in monomeric anthocyanins (two-fold), catechins, and low molecular weight phenolics (LMWP). A positive correlation was observed between the polyphenolic content and antioxidant capacity (p < 0.05), with Magliocco displaying the highest antioxidant capacity (p < 0.01). In vitro evidence on the endothelial cell models of insulin resistance and hyperglycemia showed the ability of Magliocco to reduce reactive oxygen species (ROS) (p < 0.01) and cytokine release (p < 0.01) and to upregulate SIRT1 and SIRT6 (p < 0.01). On the whole, the results indicated that the quantitative and qualitative phenolic profiles of red wines influence their in vitro beneficial effects on oxidative and proinflammatory milieu in endothelial cells, showing a positive modulation of SIRT1 and SIRT6, both implied in vascular aging.

Comparison of Three Accelerated Oxidation Tests Applied to Red Wines with Different Chemical Composition.

BACKGROUND: Three accelerated oxidation tests were proposed to simulate red wine oxidation thus providing information useful to correctly manage moderate oxygen exposure of wine during aging in regard to phenolic composition and wine color. Since the results of the tests have never been compared on wines with different initial composition, the aim of this study was to find a suitable method to simulate oxidation of any still red wine. METHODS: Aglianico, Barbera, Gaglioppo, Magliocco, and Nerello wines were treated with (1) three cycles of air saturation, (2) the addition of hydrogen peroxide, and (3) the addition of acetaldehyde. Changes in chromatic characteristics and phenolic composition were determined by spectrophotometric and HPLC methods. RESULTS: Important differences in the behavior of the different wines were detected: the highest formation of polymeric pigments was observed in Barbera and Aglianico wines. In contrast, Gaglioppo and Magliocco wines showed a lower variability before and after the oxidation probably due to the lower anthocyanin/tannin ratio. Among the accelerated oxidation tests applied, no significant differences in color parameters and phenolic composition were detected in samples treated with the addition of H2O2 and the air saturation method. CONCLUSION: The study demonstrated that H2O2 addition is a successful tool to predict the evolution of different phenolic compounds during the air saturation treatment of wines.