Pandemic COVID-19 caused by SARS-CoV-2: genetic structure, vaccination, and therapeutic approaches.

We give a summary of SARS-genetic CoV-2's structure and evolution, as well as current attempts to develop efficient vaccine and treatment methods for SARS-CoV-2 infection, in this article. Most therapeutic strategies are based on repurposing of existing therapeutic agents used against various virus infections and focused mainly on inhibition of the virus replication cycle, enhancement of innate immunity, and alleviation of CRS caused by COVID-19. Currently, more than 100 clinical trials on COVID-19 aim to provide robust evidence on the efficacy of the currently available anti-SARS-CoV-2 antiviral substances, such as the nucleotide analogue remdesivir, the antimalarial drug chloroquine, and drugs directed against docking of SARS-CoV-2 to the membrane-associated angiotensin-converting enzyme 2 (ACE2) such as transmembrane protease serine 2 (TMPRSS2). The current vaccination campaign is ongoing worldwide using different types of vaccines such as Pfizer-BioNTech and Moderna, Johnson & Johnson, Oxford-AstraZeneca, Novavax, and others with efficacy ranging from 72-95%. In March 2021 Germany limited the use of the Oxford-AstraZeneca COVID-19 vaccine to people 60 years of age and older due to concerns that it may be causing blood clots. Further study and more data are needed to confirm the safety of different available vaccines.

A Real-World Multicentre Retrospective Study of Paclitaxel-Bevacizumab and Maintenance Therapy as First-Line for HER2-Negative Metastatic Breast Cancer.

Bevacizumab in combination with taxanes in HER2-negative metastatic breast cancer (MBC) patients has shown improved progression-free survival (PFS), despite the lack of clear overall survival (OS) benefit. We performed a retrospective analysis to evaluate the impact of paclitaxel-bevacizumab and of maintenance therapy with bevacizumab (BM) and endocrine therapy (ET) in the real-world practice. We identified 314 HER2-negative MBC patients treated in 12 cancer centers. Overall, the median PFS and OS were 14 and 40 months, respectively. Among the 254 patients potentially eligible for BM, 183 received BM after paclitaxel discontinuation until progression/toxicity. PFS and OS were improved in patients who had received BM in comparison with those potentially eligible but who did not receive BM (P< 0.0001 and P = 0.001, respectively). Results were confirmed when adjusting for propensity score. Among the 216 hormone-receptor positive patients eligible for BM, a more favorable PFS and OS were observed when maintenance ET was administered (P < 0.0001). Multivariate analysis showed that PS, BM, number of disease sites and maintenance ET were related to PFS, while response and maintenance ET were related to OS. In hormone-receptor positive patients, BM produced a significant PFS and a trend towards OS benefit only in absence of maintenance ET (P = 0.0007 and P = 0.06, respectively). In the triple-negative subgroup, we observed a trend towards a better OS for patients who received BM (P = 0.06), without differences in PFS (P = 0.21). Our results confirmed the efficacy of first-line paclitaxel-bevacizumab in real-world practice; both BM and maintenance ET significantly improved PFS and OS compared to no maintenance therapies. J. Cell. Physiol. 232: 1571-1578, 2017. © 2016 Wiley Periodicals, Inc.

Robotic monitoring of dunes: a dataset from the EU habitats 2110 and 2120 in Sardinia (Italy).

This data descriptor presents a novel dataset collected using the quadrupedal robot ANYmal C in the Mediterranean coastal dune environment of the European Union (EU) habitats 2110 and 2120 in Sardinia, Italy. The dataset mainly consists of photos, videos, and point clouds of the coastal dunes, providing valuable information on the structure and composition of this habitat. The data was collected by a team of robotic engineers and plant scientists as result of a joint effort towards robotic habitat monitoring. The dataset is publicly available through Zenodo and can be used by researchers working in both the fields of robotics and habitat ecology and conservation. The availability of this dataset has the potential to inform future research and conservation efforts in the EU habitats 2110 and 2120, and it highlights the importance of interdisciplinary collaboration in the field of habitat monitoring. This paper serves as a comprehensive description of the dataset and the methods used to collect it, making it a valuable resource for the scientific community.

Pre-emptive skin toxicity treatment for anti-EGFR drugs: evaluation of efficacy of skin moisturizers and lymecycline. A phase II study.

BACKGROUND: Anti-epidermal growth factor receptor (EGFR) target therapies like erlotinib for metastatic lung cancer and cetuximab or panitumumab for metastatic colorectal cancer (mCRC) cause skin reaction that seems to be related to treatment efficacy. Skin toxicity evaluation protocol with panitumumab study has shown that preemptive treatment reduces the incidence of ≥Grade 2 (G2) skin toxicity in mCRC treated with panitumumab. Aim of this study is to evaluate if preemptive skin toxicity treatment with different drugs has good efficacy in patients receiving anti-EGFR therapies, such as cetuximab, panitumumab, and erlotinib, for mCRC and metastatic lung cancer. METHODS: Treatment included skin moisturizers with sunscreen and lymecycline 300 mg/daily. Primary objective is to reduce the incidence of ≥G2 skin toxicity during the first 3 months of therapy. Toxicities are reported with confidence interval at 95%. Quality of life was assessed with Dermatology Life Quality Index every 2 weeks and evaluated with repeated measure ANOVA. RESULTS: Fifty-one patients with mCRC (60.8%) and metastatic lung cancer (39.2%) were enrolled. Anticancer drugs were erlotinib/cetuximab/panitumumab 20:30:1. At 3-month evaluation, 27.4% patients had =G2 skin toxicity. Skin toxicity was not related with age (p = 0.67), sex (p = 0.65), previous chemotherapy regimens (p = 0.41), and current anti-EGFR treatment (p = 0.22). No gastrointestinal or hematological toxicities related to lymecycline were observed. Only six patients required further drugs. Quality of life analysis did not show a significant difference from the beginning and the end of treatment. CONCLUSIONS: Data show efficacy of preemptive treatment with a well-tolerated profile. A reduction of severe skin toxicities is shown with an increase of grade 1 toxicities, not leading to anti-EGFR dose reduction and with better quality of life for patients.

Robotic monitoring of grasslands: a dataset from the EU Natura2000 habitat 6210* in the central Apennines (Italy).

Despite the remarkable growth of the global market for robotics, robotic monitoring of habitats is still an understudied topic. This is true, among others, for the species-rich EU Annex I habitat "6210 - Semi-natural grasslands and scrubland facies on calcareous substrates". This habitat is typically surveyed by human operators. In this work, we present a dataset concerning relevés performed through the quadrupedal robot ANYmal C. The dataset contains information from three plots, which include the robot state, videos, and images acquired to assess the habitat conservation status. Additionally, a collection of videos and pictures about two typical and one early warning species of habitat 6210 is also presented. This database is publicly available in the provided Zenodo repository and will aid researchers in several fields. Robot state information can be used by engineers to validate their algorithms, while data gathered by the robot can be used to design new methodologies and new metrics to assess the habitat conservation status or train/test classifiers (e.g. neural networks) for plant classification.

Robotic monitoring of Alpine screes: a dataset from the EU Natura2000 habitat 8110 in the Italian Alps.

The surveying of European Union (EU) Annex I habitat "8110 - Siliceous scree of the montane to snow levels (Androsacetalia alpinae and Galeopsietalia ladani)" is generally executed by humans. However, robots could increase human monitoring capabilities. To this end, we collected information on this habitat employing the quadrupedal robot ANYmal C. These data include videos of eight different typical or early warning species. Additionally, data on four relevés are provided. These consist, for instance, of the robot state, and videos and pictures collected to evaluate the habitat conservation status. The aim of this dataset is to help researchers in a variety of fields. For instance, information on plant species collected by the robot can be utilized to develop new procedures and new metrics to assess the habitat conservation status or to train neural networks for plant classification. On the other hand, engineers can use robot state information to validate their algorithms. This database is publicly available in the provided Zenodo repository.

Robotic monitoring of forests: a dataset from the EU habitat 9210* in the Tuscan Apennines (central Italy).

Effective monitoring of habitats is crucial for their preservation. As the impact of anthropic activities on natural habitats increases, accurate and up-to-date information on the state of ecosystems has become imperative. This paper presents a new dataset collected from the forests located in the Tuscan Apennines (Italy) using the ANYmal robot. The dataset provides information regarding the structure and composition of the EU priority habitat 9210*. The dataset, which is publicly available through a Zenodo repository, includes photos, videos, and point clouds of the environment. This dataset is a valuable resource for the scientific community working in the field of forest ecology and conservation and has the potential to inform future research and conservation efforts on habitat 9210*. The collaboration between robotic engineers and plant scientists provides a unique perspective on the forest ecosystem and underscores the potential for interdisciplinary work in this field. This dataset constitutes an important contribution to the ongoing effort to monitor and conserve habitats globally, particularly in light of the challenges posed by global changes.

Legged locomotion over irregular terrains: state of the art of human and robot performance.

Legged robotic technologies have moved out of the lab to operate in real environments, characterized by a wide variety of unpredictable irregularities and disturbances, all this in close proximity with humans. Demonstrating the ability of current robots to move robustly and reliably in these conditions is becoming essential to prove their safe operation. Here, we report an in-depth literature review aimed at verifying the existence of common or agreed protocols and metrics to test the performance of legged system in realistic environments. We primarily focused on three types of robotic technologies, i.e., hexapods, quadrupeds and bipeds. We also included a comprehensive overview on human locomotion studies, being it often considered the gold standard for performance, and one of the most important sources of bioinspiration for legged machines. We discovered that very few papers have rigorously studied robotic locomotion under irregular terrain conditions. On the contrary, numerous studies have addressed this problem on human gait, being nonetheless of highly heterogeneous nature in terms of experimental design. This lack of agreed methodology makes it challenging for the community to properly assess, compare and predict the performance of existing legged systems in real environments. On the one hand, this work provides a library of methods, metrics and experimental protocols, with a critical analysis on the limitations of the current approaches and future promising directions. On the other hand, it demonstrates the existence of an important lack of benchmarks in the literature, and the possibility of bridging different disciplines, e.g., the human and robotic, towards the definition of standardized procedures that will boost not only the scientific development of better bioinspired solutions, but also their market uptake.

Control Architecture for Human-Like Motion With Applications to Articulated Soft Robots.

Human beings can achieve a high level of motor performance that is still unmatched in robotic systems. These capabilities can be ascribed to two main enabling factors: (i) the physical proprieties of human musculoskeletal system, and (ii) the effectiveness of the control operated by the central nervous system. Regarding point (i), the introduction of compliant elements in the robotic structure can be regarded as an attempt to bridge the gap between the animal body and the robot one. Soft articulated robots aim at replicating the musculoskeletal characteristics of vertebrates. Yet, substantial advancements are still needed under a control point of view, to fully exploit the new possibilities provided by soft robotic bodies. This paper introduces a control framework that ensures natural movements in articulated soft robots, implementing specific functionalities of the human central nervous system, i.e., learning by repetition, after-effect on known and unknown trajectories, anticipatory behavior, its reactive re-planning, and state covariation in precise task execution. The control architecture we propose has a hierarchical structure composed of two levels. The low level deals with dynamic inversion and focuses on trajectory tracking problems. The high level manages the degree of freedom redundancy, and it allows to control the system through a reduced set of variables. The building blocks of this novel control architecture are well-rooted in the control theory, which can furnish an established vocabulary to describe the functional mechanisms underlying the motor control system. The proposed control architecture is validated through simulations and experiments on a bio-mimetic articulated soft robot.