Dynamic links between mechanical forces and metabolism shape the tumor milieu

Cell function relies on the spatiotemporal dynamics of metabolic reactions. In all physiopathological processes of tissues, mechanical forces impact the structure and function of membranes, enzymes, organelles and regulators of metabolic gene programs, thus regulating cell metabolism. In turn, metabolic pathways feedback impacts the physical properties of cell and tissues. Hence, metabolism and tissue mechanics are dynamically intertwined and continuously interact. Cancer is akin to an ecosystem, comprising tumor cells and various subpopulations of stromal cells embedded in an altered extracellular matrix. The progression of cancer, from initiation to advanced stage and metastasis, is driven by genetic mutations and crucially influenced by physical and metabolic alterations in the tumor microenvironment. These alterations also play a pivotal role in cancer cells evasion from immune surveillance and in developing resistance to treatments. Here, we highlight emerging evidence showing that mechano-metabolic circuits in cancer and stromal cells regulate multiple processes crucial for tumor progression and discuss potential approaches to improve therapeutic treatments by interfering with these circuits

Triple peptide vaccination as consolidation treatment in women affected by ovarian and breast cancer: clinical and immunological data of a phase I/II clinical trial

Vaccination with priming and expansion of tumour reacting T cells is an important therapeutic option to be used in combination with novel checkpoint inhibitors to increase the specificity of the T cell infiltrate and the efficacy of the treatment. In this phase I/II study, 14 high-risk disease-free ovarian (OC) and breast cancer (BC) patients after completion of standard therapies were vaccinated with MUC1, ErbB2 and carcinoembryonic antigen (CEA) HLA-A2+-restricted peptides and Montanide. Patients were subjected to 6 doses of vaccine every two weeks and a recall dose after 3 months. ECOG grade 2 toxicity was observed at the injection site. Eight out of 14 patients showed specific CD8+ T cells to at least one antigen. None of 4 patients vaccinated for compassionate use showed a CD8 activation. An OC patient who suffered from a lymph nodal recurrence, showed specific anti-ErbB2 CD8+ T cells in the bulky aortic lymph nodes suggesting homingof the activated T cells. Results confirm that peptide vaccination strategy is feasible, safe and well tolerated. In particular OC patients appear to show a higher response rate compared to BC patients. Vaccination generates a long-lasting immune response, which is strongly enhanced by recall administrations. The clinical outcome of patients enrolled in the trial appears favourable, having registered no deceased patients with a minimum follow-up of 8 years. These promising data, in line with the results of similar studies, the high compliance of patients observed and the favourable toxicity profile, support future trials of peptide vaccination in clinically disease-free patients who have completed standard treatments

Synthetic Data Pretraining for Hyperspectral Image Super-Resolution

Large-scale self-supervised pretraining of deep learning models is known to be critical in several fields, such as language processing, where its has led to significant breakthroughs. Indeed, it is often more impactful than architectural designs. However, the use of self-supervised pretraining lags behind in several domains, such as hyperspectral images, due to data scarcity. This paper addresses the challenge of data scarcity in the development of methods for spatial super-resolution of hyperspectral images (HSI-SR). We show that state-of-the-art HSI-SR methods are severely bottlenecked by the small paired datasets that are publicly available, also leading to unreliable assessment of the architectural merits of the models. We propose to capitalize on the abundance of high resolution (HR) RGB images to develop a self-supervised pretraining approach that significantly improves the quality of HSI-SR models. In particular, we leverage advances in spectral reconstruction methods to create a vast dataset with high spatial resolution and plausible spectra from RGB images, to be used for pretraining HSI-SR methods. Experimental results, conducted across multiple datasets, report large gains for state-of-the-art HSI-SR methods when pretrained according to the proposed procedure, and also highlight the unreliability of ranking methods when training on small datasets

Experience of vaccination against invasive bacterial diseases in Veneto Region (North east Italy)

The goal of this study was to describe and comment the experience of the Veneto Region in the bacterial invasive disease. Vaccina- tion coverage was 93% against pneumococcus and 95% against haemophilus influenzae type B. Regard to meningococcus C the coverage rate was 90.1% In children, 81% at 6 years of age and 78.2% at 15 years . The preliminary data of an active surveillance of invasive bacterial diseases show that the Streptoccoccus pneumoniae was the main agent involved and that its consequences were particularly serious in elderly subjects. With regard to Neisseria meningitidis, we observed a substantial reduction in the number of cases due to serogroup C and a concomitant rise in the percentage of cases due to serogroup B. The suspension of mandatory vaccination should be maintained , the monitoring of vaccination coverage and the active surveillance proved to be a very good assessment tools. The full article is free available on www.jpmh.or

A catalogue of observed geo-effective CME/ICME characteristics

One of the goals of Space Weather studies is to achieve a better understanding of impulsive phenomena, such as Coronal Mass Ejections (CMEs), in order to improve our ability to forecast them and mitigate the risk to our technologically driven society. The essential part of achieving this goal is to assess the performance of forecasting models. To this end, the quality and availability of suitable data are of paramount importance. In this work, we have merged already publicly available data of CMEs from both in-situ and remote instrumentation in order to build a database of CME properties. To evaluate the accuracy of such a database and confirm the relationship between in-situ and remote observations, we have employed the drag-based model (DBM) due to its simplicity and inexpensive cost of computational resources. In this study, we have also explored the parameter space for the drag parameter and solar wind speed using a Monte Carlo approach to evaluate how well the DBM determines the propagation of CMEs for the events in the dataset. The dataset of geoeffective CMEs constructed as a result of this work provides validation of the initial hypothesis about DBM, and solar wind speed and also yields further insight into CME features like arrival time, arrival speed, lift-off time, etc. Using a data-driven approach, this procedure allows us to present a homogeneous, reliable, and robust dataset for the investigation of CME propagation. On the other hand, possible CME events are identified where DBM approximation is not valid due to model limitations and higher uncertainties in the input parameters, those events require more thorough investigation

A Methodology to Account for the Finger Non-Uniformity in Photovoltaic Solar Cell

Abstract In this work we investigate the impact of a non-uniform finger in the front-side metallization on the performance of c-Si solar cells. For this purpose, we propose a methodology based on a mixed-mode simulation approach, which allows evaluating the solar cell properties by performing both numerical device simulations and circuit simulations. The finger roughness profile is modeled by means of Gaussian function. The impact of roughness on the solar cell efficiency is studied as a function of mean finger height, mean finger width and finger resistivity. The proposed methodology has been applied to typical roughness profiles realized with two different metallization techniques, the conventional single screen-printing (SP) and the double screen-printing (DP)

Towards a New System for the Assessment of the Quality in Care Pathways: An Overview of Systematic Reviews

Clinical or care pathways are developed by a multidisciplinary team of healthcare practitioners, based on clinical evidence, and standardized processes. The evaluation of their framework/content quality is unclear. The aim of this study was to describe which tools and domains are able to critically evaluate the quality of clinical/care pathways. An overview of systematic reviews was conducted, according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses, using Medline, Embase, Science Citation Index, PsychInfo, CINAHL, and Cochrane Library, from 2015 to 2020, and with snowballing methods. The quality of the reviews was assessed with Assessment the Methodology of Systematic Review (AMSTAR-2) and categorized with The Leuven Clinical Pathway Compass for the definition of the five domains: processes, service, clinical, team, and financial. We found nine reviews. Three achieved a high level of quality with AMSTAR-2. The areas classified according to The Leuven Clinical Pathway Compass were: 9.7% team multidisciplinary involvement, 13.2% clinical (morbidity/mortality), 44.3% process (continuity-clinical integration, transitional), 5.6% financial (length of stay), and 27.0% service (patient-/family-centered care). Overall, none of the 300 instruments retrieved could be considered a gold standard mainly because they did not cover all the critical pathway domains outlined by Leuven and Health Technology Assessment. This overview shows important insights for the definition of a multiprinciple framework of core domains for assessing the quality of pathways. The core domains should consider general critical aspects common to all pathways, but it is necessary to define specific domains for specific diseases, fast pathways, and adapting the tool to the cultural and organizational characteristics of the health system of each country

Anelastic spectroscopy study of the spin-glass and cluster spin-glass phases of La2−x_{2-x}Srx_{x}CuO4_{4} (0.015<x<0.03)(0.015<x<0.03)

The anelastic spectra of La$_{2-x}$Sr$_{x}$CuO$_{4}$ have been measured at liquid He temperatures slightly below and above the concentration $x_{c}\simeq 0.02$ which is considered to separate the spin-glass phase from the cluster spin-glass (CSG) phase. For $x\le x_{c}$ all the elastic energy loss functions show a step below the temperature $T_{g}(x=0.02)$ of freezing into the CSG state, similarly to what found in samples well within the CSG phase, but with a smaller amplitude. The excess dissipation in the CSG state is attributed to the motion of the domain walls between the clusters of antiferromagnetically correlated spin. These results are in agreement with the recent proposal, based on inelastic neutron scattering, of an electronic phase separation between regions with $x\sim 0$ and $x\sim 0.02$, at least for $x>0.015$Comment: 5 pages, 3 figures, submitted to Phys. Rev.

Face Mask Use in the Community for Reducing the Spread of COVID-19: A Systematic Review

Background: Evidence is needed on the effectiveness of wearing face masks in the community to prevent SARS-CoV-2 transmission. / Methods: Systematic review and meta-analysis to investigate the efficacy and effectiveness of face mask use in a community setting and to predict the effectiveness of wearing a mask. We searched MEDLINE, EMBASE, SCISEARCH, The Cochrane Library, and pre-prints from inception to 22 April 2020 without restriction by language. We rated the certainty of evidence according to Cochrane and GRADE approach. / Findings: Our search identified 35 studies, including three randomized controlled trials (RCTs) (4,017 patients), 10 comparative studies (18,984 patients), 13 predictive models, nine laboratory experimental studies. For reducing infection rates, the estimates of cluster-RCTs were in favor of wearing face masks vs. no mask, but not at statistically significant levels (adjusted OR 0.90, 95% CI 0.78–1.05). Similar findings were reported in observational studies. Mathematical models indicated an important decrease in mortality when the population mask coverage is near-universal, regardless of mask efficacy. In the best-case scenario, when the mask efficacy is at 95%, the R0 can fall to 0.99 from an initial value of 16.90. Levels of mask filtration efficiency were heterogeneous, depending on the materials used (surgical mask: 45–97%). One laboratory study suggested a viral load reduction of 0.25 (95% CI 0.09–0.67) in favor of mask vs. no mask. / Interpretation: The findings of this systematic review and meta-analysis support the use of face masks in a community setting. Robust randomized trials on face mask effectiveness are needed to inform evidence-based policies. / PROSPERO registration: CRD42020184963