Oncological treatment administration at end of life: a retrospective study.

Background: This work evaluated the proportion of patients who continue therapy until their last month of life or initiate a new therapy in the last 3 months of life (end of life [EOL]). Methods: Data for 486 patients were retrospectively collected. Results: In EOL, 205 (42.3%) received systemic therapy. Better performance status (last month overall response [OR]: 0.39; 95% CI: 0.25-0.60; p < 0.001; last 3 months OR: 0.47; 95% CI: 0.34-0.65; p < 0.001) and lack of activation of palliative care (last month OR: 0.26; 95% CI: 0.13-0.54; p < 0.001; last 3 months OR: 0.18; 95% CI: 0.10-0.32; p < 0.001) were associated with higher probability of EOL therapy. Conclusion: A non-negligible proportion of patients in real-life settings continue to receive systemic treatment in EOL.

The fine line between automation and augmentation in website usability evaluation.

Artificial Intelligence (AI) systems are becoming widespread in all aspects of society, bringing benefits to the whole economy. There is a growing understanding of the potential benefits and risks of this type of technology. While the benefits are more efficient decision processes and industrial productivity, the risks may include a potential progressive disengagement of human beings in crucial aspects of decision-making. In this respect, a new perspective is emerging that aims at reconsidering the centrality of human beings while reaping the benefits of AI systems to augment rather than replace professional skills: Human-Centred AI (HCAI) is a novel framework that posits that high levels of human control do not contradict high levels of computer automation. In this paper, we investigate the two antipodes, automation vs augmentation, in the context of website usability evaluation. Specifically, we have analyzed whether the level of automation provided by a tool for semi-automatic usability evaluation can support evaluators in identifying usability problems. Three different visualizations, each one corresponding to a different level of automation, ranging from a full-automation approach to an augmentation approach, were compared in an experimental study. We found that a fully automated approach could help evaluators detect a significant number of medium and high-severity usability problems, which are the most critical in a software system; however, it also emerged that it was possible to detect more low-severity usability problems using one of the augmented approaches proposed in this paper.

Automated detection of Alzheimer's disease: a multi-modal approach with 3D MRI and amyloid PET.

Recent advances in deep learning and imaging technologies have revolutionized automated medical image analysis, especially in diagnosing Alzheimer's disease through neuroimaging. Despite the availability of various imaging modalities for the same patient, the development of multi-modal models leveraging these modalities remains underexplored. This paper addresses this gap by proposing and evaluating classification models using 2D and 3D MRI images and amyloid PET scans in uni-modal and multi-modal frameworks. Our findings demonstrate that models using volumetric data learn more effective representations than those using only 2D images. Furthermore, integrating multiple modalities enhances model performance over single-modality approaches significantly. We achieved state-of-the-art performance on the OASIS-3 cohort. Additionally, explainability analyses with Grad-CAM indicate that our model focuses on crucial AD-related regions for its predictions, underscoring its potential to aid in understanding the disease's causes.

A Human-AI interaction paradigm and its application to rhinocytology.

This article explores Human-Centered Artificial Intelligence (HCAI) in medical cytology, with a focus on enhancing the interaction with AI. It presents a Human-AI interaction paradigm that emphasizes explainability and user control of AI systems. It is an iterative negotiation process based on three interaction strategies aimed to (i) elaborate the system outcomes through iterative steps (Iterative Exploration), (ii) explain the AI system's behavior or decisions (Clarification), and (iii) allow non-expert users to trigger simple retraining of the AI model (Reconfiguration). This interaction paradigm is exploited in the redesign of an existing AI-based tool for microscopic analysis of the nasal mucosa. The resulting tool is tested with rhinocytologists. The article discusses the analysis of the results of the conducted evaluation and outlines lessons learned that are relevant for AI in medicine.

Percutaneous Retrograde Trans-Gluteal Embolization of Type 2 Endoleak Causing Iliac Aneurysm Enlargement after Endovascular Repair: Case Report and Literature Review.

Late type II endoleaks (T2ELs) arising from the internal iliac artery (IIA) may present during follow-up after endovascular aortic repair (EVAR) of aortoiliac aneurysm and may warrant embolization if enlargement of the aneurysmal sac is demonstrated. When coverage of the IIA ostium has been made due to extensive iliac disease, access options can be challenging. Different treatment options have been reported over recent years, and a careful selection of the best one must be made based on the characteristics of each case. The present study reports a simple and reproducible sheathless percutaneous superior gluteal artery (SGA) access and provides a discussion based on a review of the existing literature on this topic.

Multiscale modelling of chromatin 4D organization in SARS-CoV-2 infected cells.

SARS-CoV-2 can re-structure chromatin organization and alter the epigenomic landscape of the host genome, but the mechanisms that produce such changes remain unclear. Here, we use polymer physics to investigate how the chromatin of the host genome is re-organized upon infection with SARS-CoV-2. We show that re-structuring of A/B compartments can be explained by a re-modulation of intra-compartment homo-typic affinities, which leads to the weakening of A-A interactions and the enhancement of A-B mixing. At the TAD level, re-arrangements are physically described by a reduction in the loop extrusion activity coupled with an alteration of chromatin phase-separation properties, resulting in more intermingling between different TADs and a spread in space of the TADs themselves. In addition, the architecture of loci relevant to the antiviral interferon response, such as DDX58 or IFIT, becomes more variable within the 3D single-molecule population of the infected model, suggesting that viral infection leads to a loss of chromatin structural specificity. Analysing the time trajectories of pairwise gene-enhancer and higher-order contacts reveals that this variability derives from increased fluctuations in the chromatin dynamics of infected cells. This suggests that SARS-CoV-2 alters gene regulation by impacting the stability of the contact network in time.

Concomitant large renal cancer and abdominal aortic aneurysm. An original multidisciplinar approach to solve both pathologies saving residual kidney.

A 65-year-old male patient presented a large mass of the left kidney and a concomitant saccular abdominal aortic aneurysm (AAA) of the infrarenal aorta. Due to the particular vascularization of the right kidney in order to allow an endovascular Aneurysm Repair (EVAR), a hybrid staged repair was planned. Through a median laparotomy, a left radical nephrectomy and an ilio-renal bypass were performed, thus creating the anatomical feasibility for subsequent EVAR. Two days later the AAA was excluded by positioning of an abdominal straight stent graft. This original surgical strategy showed to be effective and reduced invasiveness of traditional approach.

Differential Competitive Growth of Transgenic Subclones of Neuroblastoma Cells Expressing Different Levels of Cathepsin D Co-Cultured in 2D and 3D in Response to EGF: Implications in Tumor Heterogeneity and Metastasis.

Neuroblastoma (NB) is an embryonal tumor arising from the sympathetic central nervous system. The epidermal growth factor (EGF) plays a role in NB growth and metastatic behavior. Recently, we have demonstrated that cathepsin D (CD) contrasts EGF-induced NB cell growth in 2D by downregulating EGFR/MAPK signaling. Aggressive NB is highly metastatic to the bone and the brain. In the metastatic process, adherent cells detach to form clusters of suspended cells that adhere once they reach the metastatic site and form secondary colonies. Whether CD is involved in the survival of metastatic NB clones is not known. Therefore, in this study, we addressed how CD differentially affects cell growth in suspension versus the adherent condition. To mimic tumor heterogeneity, we co-cultured transgenic clones silenced for or overexpressing CD. We compared the growth kinetics of such mixed clones in 2D and 3D models in response to EGF, and we found that the Over CD clone had an advantage for growth in suspension, while the CD knocked-down clone was favored for the adherent growth in 2D. Interestingly, on switching from 3D to 2D culture conditions, the expression of E-cadherin and of N-cadherin increased in the KD-CD and Over CD clones, respectively. The fact that CD plays a dual role in cancer cell growth in 2D and 3D conditions indicates that during clonal evolution, subclones expressing different level of CD may arise, which confers survival and growth advantages depending on the metastatic step. By searching the TCGA database, we found up to 38 miRNAs capable of downregulating CD. Interestingly, these miRNAs are associated with biological processes controlling cell adhesion and cell migration. The present findings support the view that during NB growth on a substrate or when spreading as floating neurospheres, CD expression is epigenetically modulated to confer survival advantage. Thus, epigenetic targeting of CD could represent an additional strategy to prevent NB metastases.

Polymer physics models reveal structural folding features of single-molecule gene chromatin conformations.

Here, we employ polymer physics models of chromatin to investigate the 3D folding of a 2Mb wide genomic region encompassing the human LTN1 gene, a crucial DNA locus involved in key cellular functions. Through extensive Molecular Dynamics simulations, we reconstruct in-silico the ensemble of single-molecule LTN1 3D structures, which we benchmark against recent in-situ Hi-C 2.0 data. The model-derived single molecules are then used to predict structural folding features at the single-cell level, providing testable predictions for super-resolution microscopy experiments.

The Use of Artificial Intelligence in Head and Neck Cancers: A Multidisciplinary Survey.

Artificial intelligence (AI) approaches have been introduced in various disciplines but remain rather unused in head and neck (H&N) cancers. This survey aimed to infer the current applications of and attitudes toward AI in the multidisciplinary care of H&N cancers. From November 2020 to June 2022, a web-based questionnaire examining the relationship between AI usage and professionals' demographics and attitudes was delivered to different professionals involved in H&N cancers through social media and mailing lists. A total of 139 professionals completed the questionnaire. Only 49.7% of the respondents reported having experience with AI. The most frequent AI users were radiologists (66.2%). Significant predictors of AI use were primary specialty (V = 0.455; p < 0.001), academic qualification and age. AI's potential was seen in the improvement of diagnostic accuracy (72%), surgical planning (64.7%), treatment selection (57.6%), risk assessment (50.4%) and the prediction of complications (45.3%). Among participants, 42.7% had significant concerns over AI use, with the most frequent being the 'loss of control' (27.6%) and 'diagnostic errors' (57.0%). This survey reveals limited engagement with AI in multidisciplinary H&N cancer care, highlighting the need for broader implementation and further studies to explore its acceptance and benefits.