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The research explores the relationship between the spreading of digital technologies and the maritime labour market. The field of investigation focused on the transport sector in the European and Italian contexts. Firstly, the reasons and main features of the maritime employment crisis are discussed, with particular regard to crew shortage, lack of generational turnover and mismatch. Secondly, the current transition from on-board work to shore-based work is highlighted. The aim of the study is twofold. Primarily, the author intends to illustrate the implications of the spreading of new navigation technologies on the maritime labour market and to investigate the possible developments of the sea-to-land transition. Moreover, the intent is to encourage reflection on how to address the current and future issues that the maritime labour market is facing. The analysis and proposals are divided between the current/short-term situation and the future/long-term issues (that will require completely new actions).

Purpose: To investigate the potential role of radiomics-based machine learning in differentiating small renal oncocytoma (RO) from clear cells carcinoma (ccRCC) on contrast-enhanced CT (CECT). Material and methods: Fifty-two patients with small renal masses who underwent CECT before surgery between January 2016 and December 2020 were retrospectively included in the study. At pathology examination 39 ccRCC and 13 RO were identified. All lesions were manually delineated unenhanced (B), arterial (A) and venous (V) phases. Radiomics features were extracted using three different fixed bin widths (bw) of 25 HU, 10 HU, and 5 HU from each phase (B, A, V), and with different combinations (B+A, B+V, B+A+V, A+V), leading to 21 different datasets. Montecarlo Cross Validation technique was used to quantify the estimator performance. The final model built using the hyperparameter selected with Optuna was trained again on the training set and the final performance evaluation was made on the test set. Results: The A+V bw 10 achieved the greater median (IQR) balanced accuracy considering all the models of 0.70 (0.64–0.75), while A bw 10 considering only the monophasic ones. The A bw 10 model achieved a median (IQR) sensitivity of 0.60 (0.40–0.60), specificity of 0.80 (0.73–0.87), AUC-ROC of 0.77 (0.66–0.84), accuracy of 0.75 (0.70–0.80), and a Phi Coefficient of 0.38 (0.20–0.47). None of the nine models with the lowest mean balanced accuracy values implemented features from A. Conclusion: The A bw 10 model was identified as the most efficient mono-phasic model in differentiating small RO from ccRCC.

In a prior study we demonstrated that the presence of face masks impairs the human capability of accurately inferring emotions conveyed through facial expressions, at all ages. The degree of impairment posed by face covering was notably more pronounced in children aged between three and five years old. In the current study, we conducted the same test as a follow-up after one year from the onset of the COVID-19 pandemic, when the requirement of wearing face masks was holding in almost all circumstances of everyday life when social interactions occur. The results indicate a noteworthy improvement in recognizing facial expressions with face masks among children aged three to five, compared to the pre-pandemic settings. These findings hold a significant importance, suggesting that toddlers effectively mitigated the social challenges associated with masks use: they overcame initial environmental limitations, improving their capability to interpret facial expressions even in the absence of visual cues from the lower part of the face.

Este artículo aplica el algoritmo Latent Dirichlet Allocation, LDA, como una técnica de aprendizaje de máquina y minería de texto para descubrir temas en OER en el contexto de la educación en ingeniería. El algoritmo LDA permite extraer temas, en este estudio los temas que se extraen de OER pueden ser considerados como metadatos adicionales que enriquecerán la descripción y clasificación de los mismos. Además, se define una metodología para la identificación automática de temas en los recursos educativos abiertos. En esta investigación, se utiliza un dataset de 80 OER extraído del repositorio Skills Commons. El valor más alto de coherencia es 0.42, cuando el número de temas en el modelo LDA es 9. Estos nueve temas están relacionados con Educación en Tecnologías de la Información.

Purpose: Metastatic melanoma lymph nodes (MMLns) might be challenging to detect on MR-WBI, as both MMLns and normal lymph nodes (NLns) can show restricted water diffusion. Our purpose is to assess the potential contribution of the DIXON sequence in differentiating MMLns from NLns. Material and methods: We followed a cohort of 107 patients with stage IIIb/c and IV skin melanoma for 32 months using MR-WBI with DIXON, STIR, and DWI/ADC sequences. We compared signal intensity (SI) values of MMLns and NLns in the four series of the DIXON sequence (in/out-of-phase, fat_only, and water_only series). The fat fraction (SIfat_only/SIin) and the long:short axis ratio of MMLns were calculated. The fat fraction was also calculated in the fatty hila of NLns. Results: All MMLns (8 from 7 patients) showed SIout>SIin with a mean fat fraction of 10%. In 40 normal fatty hila (25 patients), the proportion of SIout>SIin was 100% and mean fat fraction was 89% (pSIin pattern was identified in 41/113 cases from 19/40 patients. The median long:short axis ratio in MMLns was 1.13 (range 1.03–1.25). Conclusion: The combination of three features of MMLns (SIout>SIin, low-fat fraction and rounded shape) might hold promise in differentiating NLns from MMLns in patients with skin melanoma. Further research is warranted due to the small number of MMLns in our cohort.

Abstract Pharmacometric models were used to investigate the utility of biomarkers in predicting the efficacy (Crohn's Disease Activity Index [CDAI]) of brazikumab and provide a data‐driven framework for precision therapy for Crohn's disease (CD). In a phase IIa trial in patients with moderate to severe CD, treatment with brazikumab, an anti‐interleukin 23 monoclonal antibody, was associated with clinical improvement. Brazikumab treatment effect was determined to be dependent on the baseline IL‐22 (BIL22) or baseline C‐reactive protein (BCRP; predictive biomarkers), and placebo effect was found to be correlated with the baseline CDAI (a prognostic biomarker). A maximal total inhibition on CDAI input function of 50.6% and 42.4% was predicted for patients with extremely high BIL22 or BCRP, compared to a maximal total inhibition of 20.9% and 17.8% for patients with extremely low BIL22 or BCRP, respectively, which were mainly due to the placebo effect. We demonstrated that model‐derived baseline biomarker levels that achieve 50% of maximum unbound systemic concentration of 22.8 pg/mL and 8.03 mg/L for BIL22 and BCRP as the cutoffs to select subpopulations can effectively identify high‐response subgroup patients with improved separation of responders when compared to using the median values as the cutoff. This work exemplifies the utility of pharmacometrics to quantify biomarker‐driven responses in biologic therapies and distinguish between predictive and prognostic biomarkers, complementing clinical efforts of identifying subpopulations with higher likelihood of response to brazikumab.

Immunology is a knowledge area of paramount importance in life sciences and health care professional education with diverse applications, as well as for a general public understanding of issues related to vaccination. However, many concepts are complex and difficult to understand based only on conventional classes or static images. The use of tools, such as educational software, may enhance the learning of dynamic molecular phenomena that occur in our bodies. Virtual Immunology is a software that aims to facilitate the learning of certain complex immunology concepts. Herein, we present the "Antigen-antibody interactions" module that was used and evaluated by 127 students and 3 teachers from medical schools from 2 universities, 1 public and 1 private, both in the state of Rio de Janeiro, Brazil. The pretest/posttest research design was used to assess student learning in a randomized sample. To evaluate user perceptions concerning software quality, 14 statements were analyzed using a Likert scale. Results indicate suitable evaluations from both students and teachers concerning the "Antigen-antibody module" as an auxiliary tool in immunology teaching. The software was well rated as an educational resource since it allows dynamically viewing immunological phenomena. In addition, its ease of use and immunological process visualization were the best-evaluated parameters by the students, who recommended this software module as an auxiliary learning tool. The use of the evaluated software may motivate students and aid in the understanding of immunology-related concepts, becoming a complementary tool that may enhance the teaching-learning process.

Background: The new immunotherapies have not only changed the oncological therapeutic approach but have also made it necessary to develop new imaging methods for assessing the response to treatment. Delta radiomics consists of the analysis of radiomic features variation between different medical images, usually before and after therapy. Purpose: This review aims to evaluate the role of delta radiomics in the immunotherapy response assessment. Methods: A systematic search was performed in PubMed, Scopus, and Web Of Science using “delta radiomics AND immunotherapy” as search terms. The included articles' methodological quality was measured using the Radiomics Quality Score (RQS) tool. Results: Thirteen articles were finally included in the systematic review. Overall, the RQS of the included studies ranged from 4 to 17, with a mean RQS total of 11,15 ± 4,18 with a corresponding percentage of 30.98 ± 11.61 %. Eleven articles out of 13 performed imaging at multiple time points. All the included articles performed feature reduction. No study carried out prospective validation, decision curve analysis, or cost-effectiveness analysis. Conclusions: Delta radiomics has been demonstrated useful in evaluating the response in oncologic patients undergoing immunotherapy. The overall quality was found law, due to the lack of prospective design and external validation. Thus, further efforts are needed to bring delta radiomics a step closer to clinical implementation.

Abstract NAVIGATOR is an Italian regional project boosting precision medicine in oncology with the aim of making it more predictive, preventive, and personalised by advancing translational research based on quantitative imaging and integrative omics analyses. The project’s goal is to develop an open imaging biobank for the collection and preservation of a large amount of standardised imaging multimodal datasets, including computed tomography, magnetic resonance imaging, and positron emission tomography data, together with the corresponding patient-related and omics-related relevant information extracted from regional healthcare services using an adapted privacy-preserving model. The project is based on an open-source imaging biobank and an open-science oriented virtual research environment (VRE). Available integrative omics and multi-imaging data of three use cases (prostate cancer, rectal cancer, and gastric cancer) will be collected. All data confined in NAVIGATOR (i.e., standard and novel imaging biomarkers, non-imaging data, health agency data) will be used to create a digital patient model, to support the reliable prediction of the disease phenotype and risk stratification. The VRE that relies on a well-established infrastructure, called D4Science.org, will further provide a multiset infrastructure for processing the integrative omics data, extracting specific radiomic signatures, and for identification and testing of novel imaging biomarkers through big data analytics and artificial intelligence.

Our radiology department conducted an assessment of 300 neonatal radiographs in the neonatal intensive care unit over almost two years. The purpose was to evaluate the correct positioning of intravascular venous catheters. Our case series revealed that out of a total of 95 cases with misplaced devices, 59 were umbilical venous catheters and 36 were peripherally inserted central catheters. However, all of the central venous catheters were found to be properly positioned. Misplacements of neonatal intravascular devices were found to occur more frequently than expected. The scientific literature contains several articles highlighting the potential complications associated with misplaced devices. Our goal is to highlight the potential misplacements and associated complications that radiologists may encounter while reviewing conventional radiology imaging. Based on our experience, which primarily involved placing UVCs and PICCs, we discovered that conventional radiology is the most effective method for assessing proper device placement with the lowest possible radiation exposure. Given the high number of neonatal vascular device placement procedures, it is essential for radiologists to maintain a high level of vigilance and stay updated on the latest developments in this field.

Ribociclib plus an aromatase inhibitor and ovarian function suppression is the preferred first-line option for pre-/perimenopausal women with hormone receptor-positive/human epidermal growth factor receptor-2-negative advanced or metastatic breast cancer. We opened an italian managed access program (MAP) that permitted access to ribociclib to selected patients and allowed to collect informative results on the clinical impact of the therapy. The MAP (April 2018–May 2020) included 64 premenopausal patients, with characteristics similar to those of the MONALEESA-7 trial. Of 57 patients with a known response, 48 (84.2%) achieved a clinical benefit (i.e., complete response, N = 7 (12.3%); partial response, N = 17 (29.8%); stable disease, N = 24 (42.1%)), while 9 (15.8%) experienced tumor progression. Some patients (N = 15–23.4%) needed ribociclib dose reduction because of adverse events. Thereafter, the treatment was well tolerated, and no new safety signals emerged. Our study is the first reported Italian real-world evidence of ribociclib effectiveness in premenopausal HR+/HER2− advanced breast cancer patients. Response and clinical benefit rates were particularly encouraging compared with those of the ribociclib group of MONALEESA-7. Our work confirms that ribociclib in combination with endocrine therapy is highly effective in the treatment of premenopausal HR+/HER2− advanced breast cancer patients with an expected safety profile.