ECHO: A hierarchical combination of classical and multi-agent epistemic planning problems

The continuous interest in Artificial Intelligence (AI) has brought, among other things, the development of several scenarios where multiple artificial entities interact with each other. As for all the other autonomous settings, these multi-agent systems require orchestration. This is, generally, achieved through techniques derived from the vast field of Automated Planning. Notably, arbitration in multi-agent domains is not only tasked with regulating how the agents act, but must also consider the interactions between the agents' information flows and must, therefore, reason on an epistemic level. This brings a substantial overhead that often diminishes the reasoning process's usability in real-world situations. To address this problem, we present ECHO, a hierarchical framework that embeds classical and multi-agent epistemic (epistemic, for brevity) planners in a single architecture. The idea is to combine (i) classical; and(ii) epistemic solvers to model efficiently the agents' interactions with the (i) 'physical world'; and(ii) information flows, respectively. In particular, the presented architecture starts by planning on the 'epistemic level', with a high level of abstraction, focusing only on the information flows. Then it refines the planning process, due to the classical planner, to fully characterize the interactions with the 'physical' world. To further optimize the solving process, we introduced the concept of macros in epistemic planning and enriched the 'classical' part of the domain with goal-networks. Finally, we evaluated our approach in an actual robotic environment showing that our architecture indeed reduces the overall computational time

A Bio-Conjugated Fullerene as a Subcellular-Targeted and Multifaceted Phototheranostic Agent

Fullerenes are candidates for theranostic applications because of their high photodynamic activity and intrinsic multimodal imaging contrast. However, fullerenes suffer from low solubility in aqueous media, poor biocompatibility, cell toxicity, and a tendency to aggregate. C70@lysozyme is introduced herein as a novel bioconjugate that is harmless to a cellular environment, yet is also photoactive and has excellent optical and optoacoustic contrast for tracking cellular uptake and intracellular localization. The formation, water-solubility, photoactivity, and unperturbed structure of C70@lysozyme are confirmed using UV-visible and 2D 1H, 15N NMR spectroscopy. The excellent imaging contrast of C70@lysozyme in optoacoustic and third harmonic generation microscopy is exploited to monitor its uptake in HeLa cells and lysosomal trafficking. Last, the photoactivity of C70@lysozyme and its ability to initiate cell death by means of singlet oxygen (1O2) production upon exposure to low levels of white light irradiation is demonstrated. This study introduces C70@lysozyme and other fullerene-protein conjugates as potential candidates for theranostic applications

The impact of proton LET/RBE modeling and robustness analysis on base-of-skull and pediatric craniopharyngioma proton plans relative to VMAT

Purpose: Pediatric craniopharyngioma, adult base-of-skull sarcoma and chordoma cases are all regarded as priority candidates for proton therapy. In this study, a dosimetric comparison between volumetric modulated arc therapy (VMAT) and intensity modulated proton therapy (IMPT) was first performed. We then investigated the impact of physical and biological uncertainties. We assessed whether IMPT plans remained dosimetrically superior when such uncertainty estimates were considered, especially with regards to sparing organs at risk (OARs). Methodology: We studied 10 cases: four chondrosarcoma, two chordoma and four pediatric craniopharyngioma. VMAT and IMPT plans were created according to modality-specific protocols. For IMPT, we considered (i) variable RBE modeling using the McNamara model for different values of (a/b)x, and (ii) robustness analysis with ±3 mm set-up and 3.5% range uncertainties. Results: When comparing the VMAT and IMPT plans, the dosimetric advantages of IMPT were clear: IMPT led to reduced integral dose and, typically, improved CTV coverage given our OAR constraints. When physical robustness analysis was performed for IMPT, some uncertainty scenarios worsened the CTV coverage but not usually beyond that achieved by VMAT. Certain scenarios caused OAR constraints to be exceeded, particularly for the brainstem and optical chiasm. However, variable RBE modeling predicted even more substantial hotspots, especially for low values of (a/b)x. Variable RBE modeling often prompted dose constraints to be exceeded for critical structures. Conclusion: For base-of-skull and pediatric craniopharyngioma cases, both physical and biological robustness analyses should be considered for IMPT: these analyses can substantially affect the sparing of OARs and comparisons against VMAT. All proton RBE modeling is subject to high levels of uncertainty, but the clinical community should remain cognizant possible RBE effects. Careful clinical and imaging follow-up, plus further research on end-of-range RBE mitigation strategies such as LET optimization, should be prioritized for these cohorts of proton patients

Lenvatinib versus Sorafenib as first-line treatment in hepatocellular carcinoma: A multi-institutional matched case-control study

Background: Advanced Hepatocarcinoma (HCC) is an important health problem worldwide. Recently, the REFLECT trial demonstrated the non-inferiority of Lenvatinib compared to Sorafenib in I line setting, thus leading to the approval of new first-line standard of care, along with Sorafenib. Aims and methods: With aim to evaluate the optimal choice between Sorafenib and Lenvatinib as primary treatment in clinical practice, we performed a multicentric analysis with the propensity score matching on 184 HCC patients. Results: The median overall survival (OS) were 15.2 and 10.5 months for Lenvatinib and Sorafenib arm, respectively. The median progression-free survival (PFS) was 7.0 and 4.5 months for Lenvatinib and Sorafenib arm, respectively. Patients treated with Lenvatinib showed a 36% reduction of death risk (p = 0.0156), a 29% reduction of progression risk (p = 0.0446), a higher response rate (p < 0.00001) and a higher disease control rate (p = 0.002). Sorafenib showed to be correlated with more hand-foot skin reaction and Lenvatinib with more hypertension and fatigue. We highlighted the prognostic role of Barcelona Clinic Liver Cancer (BCLC) stage, Eastern Cooperative Oncology Group Performance Status (ECOG-PS), bilirubin, alkaline phosphatase and eosinophils for Sorafenib. Conversely, albumin, aspartate aminotransferase (AST), alkaline phosphatase and Neutrophil-Lymphocyte Ratio (NLR) resulted prognostic in Lenvatinib arm. Finally, we highlighted the positive predictive role of albumin > Normal Value (NV), ECOG > 0, NLR < 3, absence of Hepatitis C Virus positivity, and presence of portal vein thrombosis in favor of Lenvatinib arm. Eosinophil < 50 and ECOG > 0 negatively predicted the response to Sorafenib. Conclusion: SLenvatinib showed to better perform in a real-word setting compared to Sorafenib. More researches are needed to validate the predictor factors of response to Lenvatinib rather than Sorafenib

Functional Relationship between Protein Disulfide Isomerase Family Members during the Oxidative Folding of Human Secretory Proteins

We systematically depleted PDI family members and show that whereas ERp72 and P5 contributed minimally to oxidative protein folding, PDI and ERp57 were the predominant catalysts. Depletion of PDI or ERp57 alone modestly delayed folding, but depletion of both led to generalized protein misfolding and degradation

Profiles of Small Non-Coding RNAs in Schistosoma japonicum during Development

Schistosomiasis, a debilitating disease, caused by agents of the genus Schistosoma afflicts more than 200 million people worldwide. Schistosomes could serve as an interesting model to explore gene regulation due to its evolutional position, complex life cycle and sexual dimorphism. We previously indicated that sncRNA profile in the parasite S. japonicum was developmentally regulated in hepatic and adult stages. In this study, we systematically investigated mircoRNA (miRNA) and endogenous siRNA (endo-siRNA) profile in this parasite in more detailed developmental stages (cercariae, lung-stage schistosomula, separated adult worms, and liver tissue-trapped eggs) using high-throughput RNA sequencing technology. We observed that the ratio of miRNAs to endo-siRNAs was dynamically changed throughout different developmental stages of the parasite. MiRNAs were expressed dominantly in cercariae, while endo-siRNAs accumulated in adult female worms and hepatic eggs. We demonstrated that miRNAs were mostly derived from intergenic regions whereas siRNAs were mostly derived from transposable elements. We also annotated miRNAs and siRNAs with stage- and gender- biased expression. Our findings would facilitate to understand the gene regulation mechanism of this parasite and discover novel targets for anti-parasite drugs

Epistemic Multiagent Reasoning with Collaborative Robots

Over the last few years, the fields of Artificial Intelligence, Robotics and IoT have gained a lot of attention. This increasing interest has brought, among other things, to the development of autonomous multi-agent systems where robotic entities may interact with each other. As for all the other autonomous settings, also these systems require arbitration. Our work tries to address this problem by presenting a framework that embeds both a classical and a multi-agent epistemic (epistemic, for brevity) planner in a robotic control architecture. The idea is to combine the (i) classical and the (ii) epistemic solvers to model efficiently the interaction with: the (i) physical world and the (ii) information flows, respectively. In particular, the presented architecture starts by planning on the “epistemic level" refining then single-agent world-altering actions thanks to the classical planner. To further optimize the solving process, we also introduce the concept of macros in epistemic planning. Macros, in fact, have been successfully employed in classical planning as they allow for opportune aggregations of actions that may lead to a reduction of plans' length. Finally, the overall framework is exemplified and validated with two Franka Emika manipulators. This allowed us to empirically justify how the combination of the two planning approaches (classical and epistemic), and the introduction of macros, reduce the computational time required by the orchestrating phase